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https://dev.to/devteam/congrats-to-the-google-ai-multimodal-challenge-winners-385f | Congrats to the Google AI Multimodal Challenge Winners! - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Jess Lee for The DEV Team Posted on Oct 2, 2025 Congrats to the Google AI Multimodal Challenge Winners! # devchallenge # googleaichallenge # ai # gemini The wait is over! We are excited to announce the winners of the Google AI Studio Multimodal Challenge . From home designing applications to personalized interview experiences to custom games, everyone who participated demonstrated remarkable ingenuity in their submissions. We were impressed by the technical sophistication, creativity, and real-world problem-solving on display that highlighted the transformative power of multimodal AI. The competition for this challenge was fierce! Whether or not you're declared a winner, we hope you enjoyed working on your submission and are proud of what you accomplished. And most importantly, we hope you keep on building! Without further ado, our winners. Congratulations To… Sunbeam @james_hoang_c601f7e9561c2 created Sunbeam, an AI-powered visual assistant that serves as a lifeline for the 1.3 billion visually impaired people worldwide. 🌞 👁️ Sunbeam: AI-Powered Visual Assistant for the Visually Impaired James Hoang ・ Sep 14 #devchallenge #googleaichallenge #ai #gemini This voice-first web application transforms smartphones into intelligent eyes, enabling users to navigate environments through natural conversation with AI. VisionGen @nadinev built VisionGen, a "Video-to-Video" generation tool that automates prompt generation using a sophisticated a-la-carte JSON prompting system designed to "get it right the first time." VisionGen Nadine ・ Sep 13 #devchallenge #googleaichallenge #ai #gemini VisionGen revolutionizes how we create consistent, narrative-driven videos! Winner #3 @simimwanza created Reverse Engineering Reality, a tool that transforms curiosity into an interactive learning experience. Reverse Engineering Reality with Google AI Mwanza Simi ・ Sep 14 #devchallenge #googleaichallenge #ai #gemini Upload a photo of any everyday object and receive a detailed, imaginative set of instructions for assembling or disassembling it. Our three winners will each receive $1,000 USD, a DEV++ Membership , and an exclusive DEV badge. All participants with valid submissions will receive a completion badge on their DEV profile! Google AI ❤️ We want to give a huge shoutout to the team at Google AI for partnering with us! They are at the forefront of multimodal AI and it was amazing to see the community push the boundaries of what's possible when combining vision, audio, and text understanding. @vivjair and team were wonderful to work with, and we can't wait for the next one! What's next? Stay tuned for more exciting challenges! Keep an eye on our challenges page and follow our challenge tags to be the first to know about new opportunities to build, create, and win. # googleaichallenge Follow This is the official tag for submissions and announcements related to Google AI Studio Challenges. # devchallenge Follow This is the official tag for submissions and announcements related to DEV Challenges. We hope you had fun, felt challenged, and maybe added a thing or two to your professional profile. See you next time! Interested in being a volunteer judge for future challenges? Learn more here ! Top comments (28) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand Peter Kim Frank The DEV Team Peter Kim Frank The DEV Team Peter Kim Frank Follow Doing a bit of everything at DEV / Forem Email peter@dev.to Education Wesleyan University Pronouns He/Him Work Co-Founder Joined Jan 3, 2017 • Oct 2 '25 Dropdown menu Copy link Hide Congrats @james_hoang_c601f7e9561c2 , @nadinev , and @simimwanza -- terrific submissions! Like comment: Like comment: 9 likes Like Comment button Reply Collapse Expand Nadine Nadine Nadine Follow 💫 About Me: I operate with a results-driven, self-directed methodology. My approach prioritizes rapid, on-the-fly acquisition of necessary skills to meet project goals. Education BA, BSc, AWS Certified, GitHub 300 Work Contractor Joined May 31, 2025 • Oct 2 '25 Dropdown menu Copy link Hide Thank you so much 😃 ! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Mwanza Simi Mwanza Simi Mwanza Simi Follow Cloud Fairy Joined Jan 22, 2025 • Oct 2 '25 Dropdown menu Copy link Hide Thank you Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand James Hoang James Hoang James Hoang Follow Good morning 😎 Joined Jul 10, 2025 • Oct 2 '25 Dropdown menu Copy link Hide Thank you 😊 😊 Like comment: Like comment: Like Comment button Reply Collapse Expand Varshith V Hegde Varshith V Hegde Varshith V Hegde Follow A simple programmer fond of learning Email varshithvh@gmail.com Location Mangalore Education Mangalore Institute of Technology and Engineering Work Software Engineer@KPIT Joined Jun 30, 2022 • Oct 2 '25 Dropdown menu Copy link Hide Congrats!! To All Winners🔥🥳 Like comment: Like comment: 6 likes Like Comment button Reply Collapse Expand James Hoang James Hoang James Hoang Follow Good morning 😎 Joined Jul 10, 2025 • Oct 2 '25 Dropdown menu Copy link Hide Thank you so much. I think I'm the happiest person on earth today 🥳 🥳 🥳. Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Ben Halpern The DEV Team Ben Halpern The DEV Team Ben Halpern Follow A Canadian software developer who thinks he’s funny. Email ben@forem.com Location NY Education Mount Allison University Pronouns He/him Work Co-founder at Forem Joined Dec 27, 2015 • Oct 2 '25 Dropdown menu Copy link Hide Congrats! Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Vivian Jair Vivian Jair Vivian Jair Follow Hey there, I'm Vivian. I lead the Google AI x DEV partnership initiative. Location San Francisco Education University of Pennsylvania, Wharton School Work Product Marketing Manager Joined May 30, 2025 • Oct 2 '25 Dropdown menu Copy link Hide Huge congrats to all the winners, and thank you to everyone who participated! Such a joy to see all the creative applications built with AI Studio & Cloud Run! Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Frederik 👨💻➡️🌐 Creemers Frederik 👨💻➡️🌐 Creemers Frederik 👨💻➡️🌐 Creemers Follow I'm never sure what to put in a bio. If there's anything you want to know, don't be afraid to ask! Email frederikcreemers@gmail.com Location Maastricht, the Netherlands Education Knowledge Engineering & Data Science at Maastricht University Pronouns he/him Work Developer at TalkJS Joined Mar 22, 2017 • Oct 2 '25 Dropdown menu Copy link Hide Congrats! Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Drashya Kuruwa Drashya Kuruwa Drashya Kuruwa Follow Creative Technologist, Immersive Web (Three.js/p5.js), Generative AI & Storytelling, building interactive, human-centered experiences. Joined Sep 14, 2025 • Oct 2 '25 Dropdown menu Copy link Hide Congratulations to the all the winners.. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Veronika Kashtanova Veronika Kashtanova Veronika Kashtanova Follow Software Engineer | AI Agent Developer | ⚡ Building intelligent systems & multi-agent solutions. Passionate about open-source & problem-solving with Python/Java/JS. Award-winning hackathon participant Location Ukraine Education Master's Degree with Distinction Work Software Engineer | AI Agent Developer Joined Jun 3, 2025 • Oct 3 '25 Dropdown menu Copy link Hide 🎉 Congrats to the winners! Amazing projects, and big thanks to the organizers for the inspiration! Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow AWS Community Builder Bridging critical thinking and innovation, from philosophy to DevOps. Email programmerpravesh@gmail.com Location India Education Hindu College, Delhi University, India Pronouns he/him Work Freelance DevOps Engineer At Fiverr Joined Jul 19, 2024 • Oct 2 '25 Dropdown menu Copy link Hide Congratulations @nadinev , great work buddy :) Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Nadine Nadine Nadine Follow 💫 About Me: I operate with a results-driven, self-directed methodology. My approach prioritizes rapid, on-the-fly acquisition of necessary skills to meet project goals. Education BA, BSc, AWS Certified, GitHub 300 Work Contractor Joined May 31, 2025 • Oct 2 '25 Dropdown menu Copy link Hide Thanks buddy! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand kimdidit kimdidit kimdidit Follow High. I am Kim. Location Nairobi, Kenya Joined Jun 4, 2025 • Oct 3 '25 Dropdown menu Copy link Hide Congratulations to @james_hoang_c601f7e9561c2 @nadinev and @simimwanza Like comment: Like comment: 4 likes Like Comment button Reply View full discussion (28 comments) Some comments may only be visible to logged-in visitors. Sign in to view all comments. Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse The DEV Team Follow The hardworking team behind DEV ❤️ Want to contribute to open source and help make the DEV community stronger? The code that powers DEV is called Forem and is freely available on GitHub. You're welcome to jump in! Contribute to Forem More from The DEV Team Congrats to the AI Agents Intensive Course Writing Challenge Winners! # googleaichallenge # devchallenge # ai # agents Join the Algolia Agent Studio Challenge: $3,000 in Prizes! # algoliachallenge # devchallenge # agents # webdev Congrats to the Xano AI-Powered Backend Challenge Winners! # xanochallenge # backend # api # ai 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://www.fine.dev/blog/remote-first-tech-startup#1-establish-a-strong-communication-foundation | How to Build a Remote-First Tech Team as a Startup CTO: Tools and Tactics Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back How to Build a Remote-First Tech Team as a Startup CTO: Tools and Tactics Building a successful remote-first tech team requires the right tools and tactics. Some startups thrive off of remote workers around the world - others are sunk by inefficiency and communication failures. In this post, we'll explore essential steps and technologies to help you build a high-performing remote-first team. Table of Contents Establish a Strong Communication Foundation Use the Right Collaboration Tools Create an Inclusive Team Culture Hire for Remote-Friendly Qualities Focus on Employee Well-Being Measure Team Performance Effectively Prioritize Security and Data Protection Choose a Collaborative AI Platform Stay on Top of Code Reviews 1. Establish a Strong Communication Foundation Communication is the lifeline of any remote-first tech team. Ensuring that everyone stays connected and informed requires a blend of asynchronous and real-time communication tools. As a startup CTO, consider investing in: Slack or Microsoft Teams for real-time messaging and updates. Zoom or Google Meet for video calls, meetings, and check-ins. Loom for recording walkthroughs and sharing asynchronous video updates. The key to building a cohesive team is setting clear expectations about how and when different tools should be used. Creating guidelines for communication not only helps streamline workflow but also reduces burnout by ensuring team members can disconnect after work hours. 2. Use the Right Collaboration Tools Your tech stack is crucial to enabling effective collaboration among remote engineers. Select tools that encourage transparency and make collaboration as seamless as possible. Here are some must-have tools for remote-first tech teams: GitHub or GitLab for version control and managing code collaboratively. Jira or Linear for tracking tasks and sprint planning. Confluence or Notion for documenting processes, creating shared knowledge bases, and improving accessibility to resources. A well-documented codebase and clearly defined processes empower developers to operate independently, minimizing bottlenecks and improving productivity. 3. Create an Inclusive Team Culture Fostering an inclusive and collaborative culture is essential to the success of a remote-first team. This starts with ensuring all voices are heard, regardless of geographic location. Here are a few tactics that can help: Regular Virtual Meetups : Schedule weekly check-ins or team-building events where team members can share updates, ask questions, and bond. Async Standups : Consider using tools like Geekbot to automate daily standups, enabling each member to share their progress and blockers asynchronously. Recognition and Feedback : Use platforms like 15Five to gather feedback and recognize individual contributions. It helps foster a positive work environment where team members feel valued. 4. Hire for Remote-Friendly Qualities Hiring for a remote-first tech team requires different criteria compared to an on-site environment. It’s crucial to look for qualities such as excellent written communication, self-motivation, and the ability to work autonomously. During the interview process, assess candidates for their comfort level with remote work by asking questions about their previous remote experiences, how they manage their time, and how they communicate asynchronously. Tools like HireVue can assist in conducting initial screenings through video interviews, allowing you to see how well candidates adapt to remote-first communication. Remember, some people thrive on the office atmosphere and are less efficient working from home, surrounded by distractions ranging from laundry to kids. Ask for an honest self-assessment: where do you perform better? When working from home, what does your day look like? 5. Focus on Employee Well-Being Employee well-being is fundamental for retaining top talent in a remote-first setup. As a startup CTO, your team's health should be a priority. Encourage employees to establish work-life balance, take breaks, and avoid overworking. Here are some ways to promote well-being: Flexible Work Hours : Give your team flexibility to work when they are most productive, keeping in mind that different time zones require adjustments. Wellness Programs : Platforms like Headspace or Calm can offer resources to help employees reduce stress and improve their mental health. No-Meeting Days : Designate a day of the week for no meetings to help everyone focus on deep work without interruptions. Context switching is a huge productivity killer. 6. Measure Team Performance Effectively Measuring performance in a remote-first environment can be tricky. Instead of relying on metrics like hours worked, focus on output-based performance indicators. Use tools like GitPrime to understand productivity metrics without micro-managing. Set clear, outcome-based goals for each team member and evaluate success based on these targets. Regular one-on-ones are also key for providing guidance, discussing blockers, and keeping each team member aligned with the broader business goals. 7. Prioritize Security and Data Protection Security is a non-negotiable aspect of building a remote-first tech team. Your remote employees will be accessing company resources from various locations, which presents unique challenges in terms of data protection. VPN and Endpoint Protection : Make sure that your team uses a secure VPN and endpoint protection software when accessing company servers. Password Managers : Tools like 1Password or LastPass can help keep team credentials secure. Multi-Factor Authentication : Enforce MFA to ensure that access to sensitive data is protected. Establishing best practices for security and ensuring that everyone understands the importance of cybersecurity is critical to preventing data breaches and protecting your business. 8. Choose a Collaborative AI Platform Selecting the right AI platform is essential for boosting productivity and collaboration among your remote team. Fine is designed specifically for teams, offering seamless integration with tools like Linear and GitHub, making it ideal for remote work. Unlike IDE-based AI assistants that are more suited for solo developers, Fine provides an all-in-one AI coding agent that enhances teamwork and accelerates startup growth. 9. Stay on Top of Code Reviews When working remotely, it can be easy for developers to finish writing code and leave it sitting, waiting for review for days or even weeks. Code reviews are essential for maintaining quality and ensuring knowledge sharing across the team. Use tools like Linear and GitHub to keep track of open tickets and close them efficiently. Setting up automated reminders for reviewers can help ensure that reviews are completed promptly, keeping the team moving forward and avoiding bottlenecks. Conclusion Building a remote-first tech team as a startup CTO is no easy feat, but with the right tools and strategies, it can lead to a more diverse and efficient development team. By focusing on communication, collaboration, culture, and security, you can create an environment where your remote team can thrive and innovate. The success of a remote-first team lies not just in the tools you use, but in how you nurture your team culture and make everyone feel connected despite the distance. Start small, iterate, and adapt as you learn more about your team’s needs—that’s how you’ll build a resilient and agile remote-first team ready for anything. Are you looking to streamline your development processes with collaborative AI coding? Discover how Fine can help your remote team collaborate better to ship software and boost productivity. Sign up today and see what AI-driven development can do for you! Start building today Try out the smoothest way to build, launch and manage an app Try for Free -> © Fine.dev - All rights reserved. Product Overview AI Workflows Pricing & Plans Changelog Blog Docs Company Press Terms & Conditions Privacy policy | 2026-01-13T08:49:36 |
https://dev.to/scale_youtube/devoxx-inspiring-the-next-generations-58ck | Devoxx: Inspiring the Next Generations - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Scale YouTube Posted on Nov 2, 2025 Devoxx: Inspiring the Next Generations # career Inspiring the Next Generations At Devoxx Belgium 2025, Frank Delporte sat down with Cassandra Chin, author of Raising Young Coders , who shared tips on teaching kids programming (plus a 20% discount code “APAUT” for her Springer book). He also chatted with Daniel De Luca, founder of Devoxx4Kids, about the hands-on workshops and fun activities that spark tech curiosity in children of all ages. Watch on YouTube Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Scale YouTube Follow Joined Aug 2, 2025 More from Scale YouTube NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
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https://www.storyblok.com/ | Storyblok — Headless CMS with Visual Editor | Storyblok 🍪 Cookie Notice We use cookies to learn how you interact with our content, and show you relevant content and ads based on your browsing history. You can adjust your settings below. Here's our policy . Only necessary Accept all Cookie settings Skip to main content Storyblok named a Leader in IDC MarketScape 2025 for AI-Enabled Headless CMS - Download it here ! 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Scale with Intelligence. A headless CMS made for humans. Built for the AI-driven content era. Create a demo site in just 5 minutes. Try for Free | #1 Enterprise Headless CMS Trusted by leading brands across the globe The proof is in the pudding, and our customers keep coming back for more. 50% increase in content operations speed 486,000+ total pages created 2 months to build 16 global sites 50% reduction in development time Key Product Announcements from JoyConf. Watch the Keynote. Discover how Storyblok is evolving for the AI Content Era - with new tools for automation, vector data, and connected workflows across your entire stack. Your browser does not support the video tag. Loading... Load and start video Storyblok Strata See Everything. Solve Anything. Strata is Storyblok’s vector data layer , enabling RAG workflows, AI-native search, and personalisation-at-scale by transforming your content into a semantic layer. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Machine Learning Follow Hide A branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Create Post submission guidelines Articles and discussions should be directly related to the machine learning. Questions are encouraged! (See the #help tag) Older #machinelearning posts 72 73 74 75 76 77 78 79 80 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Quantum Leaps in Concept Understanding: Building AI That Truly 'Gets It' Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 Quantum Leaps in Concept Understanding: Building AI That Truly 'Gets It' # quantumcomputing # machinelearning # ai # python 4 reactions Comments Add Comment 2 min read Don't Be Ashamed to Use AI, Even Iron Man Did Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Oct 13 '25 Don't Be Ashamed to Use AI, Even Iron Man Did # discuss # ai # machinelearning # career 12 reactions Comments 6 comments 19 min read Tensor Logic: The Elegant Foundation for Next-Gen AI by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 15 '25 Tensor Logic: The Elegant Foundation for Next-Gen AI by Arvind Sundararajan # ai # machinelearning # datascience # tensors 1 reaction Comments Add Comment 2 min read Smarter Tuning: LLMs Automate Hyperparameter Magic Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 Smarter Tuning: LLMs Automate Hyperparameter Magic # machinelearning # ai # python # optimization 5 reactions Comments Add Comment 2 min read Quantum Composition: Teaching AI to Think Like Us Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 Quantum Composition: Teaching AI to Think Like Us # quantumcomputing # machinelearning # ai # python 5 reactions Comments Add Comment 2 min read LLMs: Transforming AI with Large Language Models Youssef Taha Youssef Taha Youssef Taha Follow Sep 12 '25 LLMs: Transforming AI with Large Language Models # ai # llms # machinelearning # nlp Comments Add Comment 1 min read Poisoned Prompts: How Malicious Documentation Can Hijack Your AI Code Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 Poisoned Prompts: How Malicious Documentation Can Hijack Your AI Code # ai # security # machinelearning # llm Comments Add Comment 2 min read Unlock Robot Speed: Decoupling 'Seeing' and 'Doing' Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 Unlock Robot Speed: Decoupling 'Seeing' and 'Doing' # ai # robotics # machinelearning # python 1 reaction Comments Add Comment 2 min read Understanding Neural Networks: From Neurons to LLMs siva1b3 siva1b3 siva1b3 Follow Sep 16 '25 Understanding Neural Networks: From Neurons to LLMs # deeplearning # ai # machinelearning # llm Comments Add Comment 2 min read The story of how machines went from mimicking humans to creating ideas of their own. Sailee Das Sailee Das Sailee Das Follow Sep 12 '25 The story of how machines went from mimicking humans to creating ideas of their own. # machinelearning # datascience # chatgpt # ai Comments Add Comment 4 min read Unlock LLM Potential at the Edge: Secure, Efficient Inference Without the Cloud Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 Unlock LLM Potential at the Edge: Secure, Efficient Inference Without the Cloud # ai # machinelearning # privacy # security 5 reactions Comments Add Comment 2 min read Altruistic AI: When Helping Others Helps You Win by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 15 '25 Altruistic AI: When Helping Others Helps You Win by Arvind Sundararajan # ai # machinelearning # reinforcementlearning # marl 2 reactions Comments Add Comment 2 min read Taming the Twist: Mastering Rotation Actions in Robotic Reinforcement Learning Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 15 '25 Taming the Twist: Mastering Rotation Actions in Robotic Reinforcement Learning # machinelearning # python # ai # robotics Comments Add Comment 2 min read Bridging Worlds: AI's Breakthrough in Nepali Sign Language Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Bridging Worlds: AI's Breakthrough in Nepali Sign Language # a11y # machinelearning # python # opensource 4 reactions Comments Add Comment 2 min read Decoding the LLM Cipher: Unlocking AI Behavior Through Geometric Insights Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 15 '25 Decoding the LLM Cipher: Unlocking AI Behavior Through Geometric Insights # ai # machinelearning # llm # datascience Comments Add Comment 2 min read I Built a Mental Wellness AI with Python + Streamlit (Complete Tutorial) Akshat Raj Akshat Raj Akshat Raj Follow Oct 14 '25 I Built a Mental Wellness AI with Python + Streamlit (Complete Tutorial) # python # ai # machinelearning # opensource 1 reaction Comments Add Comment 2 min read Tensor Harmony: Unifying AI Through Equation Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 15 '25 Tensor Harmony: Unifying AI Through Equation # ai # machinelearning # datascience # programming 1 reaction Comments Add Comment 2 min read Unleashing AI Speed: Decoupling Perception for Blazing-Fast Robots by Arvind Sundararajan Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 Unleashing AI Speed: Decoupling Perception for Blazing-Fast Robots by Arvind Sundararajan # ai # robotics # machinelearning # embodiedai 5 reactions Comments Add Comment 2 min read Mastering Hyperparameter Tuning in Machine Learning Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Oct 15 '25 Mastering Hyperparameter Tuning in Machine Learning # python # tutorial # machinelearning # performance 3 reactions Comments Add Comment 2 min read **Episodic vs Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Follow Oct 15 '25 **Episodic vs # ai # machinelearning # technology # programming 3 reactions Comments Add Comment 1 min read Private Graphs, Public Insights: Feature Propagation with a Twist by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Private Graphs, Public Insights: Feature Propagation with a Twist by Arvind Sundararajan # machinelearning # privacy # graphneuralnetworks # ai 1 reaction Comments Add Comment 2 min read 🧠Introducing OrKa Cloud API marcosomma marcosomma marcosomma Follow Oct 14 '25 🧠Introducing OrKa Cloud API # ai # opensource # machinelearning # mlops 9 reactions Comments Add Comment 12 min read Lifespan Thinking: How to Build IoT that Learns Forever Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 Lifespan Thinking: How to Build IoT that Learns Forever # iot # machinelearning # embedded # sustainability 1 reaction Comments Add Comment 2 min read Breaking Barriers: AI Empowers Nepali Sign Language Recognition by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Breaking Barriers: AI Empowers Nepali Sign Language Recognition by Arvind Sundararajan # a11y # machinelearning # python # opensource 1 reaction Comments Add Comment 2 min read AI's Spatial Blind Spot: Why Brain-Inspired Navigation is the Next Frontier by Arvind Sundararajan Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 AI's Spatial Blind Spot: Why Brain-Inspired Navigation is the Next Frontier by Arvind Sundararajan # 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https://www.algolia.com/fr/products/ | Plateforme et produits : API de recherche, API de recommandations et autres fonctionnalités. | Algolia Niket --> Deutsch English français News DevCon2025 | October 1-2 Learn more Algolia Partners Support Login Logout Algolia mark white Algolia logo white Products Search Show users what they're looking for with AI-driven resuts. Search Show users what they're looking for with AI-driven resuts. Recommendations Use behavioral cues to drive higher engagement. Recommendations Use behavioral cues to drive higher engagement. Personalization Show each user what they need across their journey. Personalization Show each user what they need across their journey. Analytics All your insights in one dashboard. Analytics All your insights in one dashboard. Browse Move customers down the funnel with curated category pages. Browse Move customers down the funnel with curated category pages. Agent Studio Create, test, and deploy AI agents, fast. 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We got you covered! Brand guidelines Download logo pack Nos solutions Une recherche par IA qui montre aux utilisateurs ce dont ils ont besoin Améliorez le parcours de vos utilisateurs grâce à des solutions de recherche, de navigation et de recommandations. Demandez une démo Commencez gratuitement Make every interaction smarter with AI retrieval Every modern AI experience depends on one core capability: finding the right information at the right moment. That process is retrieval. Retrieval is how search engines, LLMs, and AI agents locate the data they need to answer questions, generate content, or take action. When retrieval is strong, these experiences behave intelligently; when it isn’t, they guess. Les trois caractéristiques uniques d’Algolia Facilité d’utilisation Implémentez un scénario de test en quelques minutes grâce à nos API. Donnez à vos équipes commerciales la visibilité et le contrôle nécessaires pour optimiser le classement, et des automatisations pour leur faire gagner du temps. Vitesse Vos recherches apparaissent à mesure que vous tapez, grâce à la recherche basée sur l’IA la plus rapide que nous connaissons. Des résultats plus rapides entraînent des revenus plus élevés. Échelle Faites confiance au plus grand moteur de recherche hébergé au monde, avec 1,7 billion de recherches par an. Algolia est également hautement conforme et stable (avec une disponibilité allant jusqu’à 99,999 %). Build retrieval-powered solutions today AI retrieval powers the next generation of agentic, generative, and search experiences that adapt to intent, not syntax. Search AI Construisez des expériences de recherche puissantes pour votre application ou site grâce à une IA qui comprend, classe et s’adapte en temps réel. Combinez résultats traditionnels, génératifs et agentiques pour offrir une expérience optimale et engageante. Recherche hybride : la recherche vectorielle sémantique rencontre la précision des mots-clés pour des résultats rapides et intuitifs, alignés avec l’intention utilisateur. En savoir plus Classement IA : combinez machine learning et contrôle humain pour améliorer en continu la pertinence des résultats. En savoir plus Catégorisation des requêtes : transformez des requêtes non structurées en données exploitables pour un merchandising et une analyse plus intelligents. En savoir plus Personnalisation avancée : proposez des expériences adaptées au comportement, aux préférences et au contexte de chaque utilisateur, dès la mise en place. En savoir plus En savoir plus sur la recherche par IA Agentic Studio Agent Studio est la manière la plus rapide de construire et de déployer des agents RAG. C’est un framework destiné aux développeurs qui simplifie la création d’agents IA augmentés par la recherche, prêts pour la production. Agents de marque : créez et testez des agents capables d’interagir avec vos visiteurs — ou développez des agents automatisés pour vos équipes internes. Opérations agentiques : améliorez les résultats de recherche grâce à des assistants intelligents qui configurent les opérations pour optimiser vos résultats business. Agentic search commerce : vendez vos produits via des sites tiers pilotés par des agents (ex. Perplexity, ChatGPT, etc.) grâce au serveur MCP d’Algolia. En savoir plus sur l'Agentic Studio La pertinence à grande échelle La plateforme IA d’Algolia fusionne recherche, langage et logique pour offrir une pertinence à grande échelle. Elle combine des algorithmes de recherche avancés, des grands modèles de langage (LLMs) et la génération augmentée par recherche (RAG) afin de fournir des expériences utilisateur hautement personnalisées, performantes et en temps réel. Expériences IA génératives : une boîte à outils pour développeurs permettant de créer des guides riches en contenu — alimentés par des LLMs et adaptés à votre audience. En savoir plus Guides : générez automatiquement des guides informatifs à partir de votre catalogue produit. Mise en place facile – sans création manuelle de contenu. En savoir plus Ask AI : ajoutez un assistant IA à vos documents, votre site web ou votre centre de support pour fournir des réponses précises et conversationnelles — directement depuis votre barre de recherche. En savoir plus Learn more about Generative Experiences Connectez vos agents IA avec Algolia MCP Le Model Context Protocol (MCP) d’Algolia fournit l’infrastructure nécessaire pour contrôler et orchestrer le commerce piloté par agents. Il est essentiel pour coordonner les différents systèmes nécessaires à une transaction agentique complète. Que vous construisiez des recommandations produits, des assistants de recherche ou des tableaux de bord analytiques, MCP permet d’en faire plus, plus vite, et à grande échelle. En savoir plus Outils pour les utilisateurs business Merchandising Studio Créez de meilleures expériences client basées sur les données, sans avoir à coder. Les équipes commerciales utilisent le Merchandising Studio d’Algolia pour contrôler et mener des campagnes à travers AI Search, AI Browse et AI Recommendations. En savoir plus Analytics Obtenez des informations sur les taux de clics, les performances par position et la saisonnalité. Suivez les termes de recherche qui génèrent votre chiffre d’affaires, corrigez les résultats nuls et améliorez les performances de vos catégories. Le tout sur un tableau de bord intuitif. En savoir plus Un coup de pouce pour les développeurs Composants d’interface utilisateur Lancez-vous rapidement grâce à nos bibliothèques de composants d’interface utilisateur pour les interfaces de n’importe quelle résolution et n’importe quel framework JS. Nous vous proposons des fonctions de recherche instantanée, d’autocomplétion, de tri et de pagination et bien d’autres encore. Découvrez nos composants d’interface utilisateur Intégrations Connectez-vous directement à votre stack technologique ou à votre framework. Démarrez rapidement grâce à des intégrations avec des plateformes d’e-commerce telles que Shopify et Salesforce Commerce Cloud. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Machine Learning Follow Hide A branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Create Post submission guidelines Articles and discussions should be directly related to the machine learning. Questions are encouraged! (See the #help tag) Older #machinelearning posts 76 77 78 79 80 81 82 83 84 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Harmonious Motion: Streamlining Robot Movement with Convergent Flow Fields by Arvind Sundararajan Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Harmonious Motion: Streamlining Robot Movement with Convergent Flow Fields by Arvind Sundararajan # robotics # ai # motionplanning # machinelearning 1 reaction Comments Add Comment 2 min read Harmonious Motion: Untangling Robot Paths with Flow Field Dynamics Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Harmonious Motion: Untangling Robot Paths with Flow Field Dynamics # robotics # ai # motionplanning # machinelearning 1 reaction Comments Add Comment 2 min read AI for Everyone: Secure Language Models Without the Hardware Hype Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 AI for Everyone: Secure Language Models Without the Hardware Hype # security # ai # privacy # machinelearning 1 reaction Comments Add Comment 2 min read Robots That 'Get' the Real World: Context-Aware AI Planning Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Robots That 'Get' the Real World: Context-Aware AI Planning # ai # robotics # machinelearning # python 1 reaction Comments Add Comment 2 min read Unlock AI Intuition: Mapping the World Like a Human Brain Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Unlock AI Intuition: Mapping the World Like a Human Brain # ai # neuroscience # robotics # machinelearning 1 reaction Comments Add Comment 2 min read AI Heartbeat: Decoding Cardiac Motion with Implicit Neural Magic by Arvind Sundararajan Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 AI Heartbeat: Decoding Cardiac Motion with Implicit Neural Magic by Arvind Sundararajan # ai # machinelearning # healthcare # python 1 reaction Comments Add Comment 2 min read Unlocking Speed: Ditching Strict Symmetry in Neural Nets by Arvind Sundararajan Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 Unlocking Speed: Ditching Strict Symmetry in Neural Nets by Arvind Sundararajan # machinelearning # deeplearning # ai # neuralnetworks 1 reaction Comments Add Comment 2 min read Seeing the Invisible: AI Reveals Hidden Heart Strain, Predicts Cardiac Events Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Seeing the Invisible: AI Reveals Hidden Heart Strain, Predicts Cardiac Events # machinelearning # ai # medicalimaging # python 1 reaction Comments Add Comment 2 min read AI is Failing Nigerian Languages: 7 Critical Loopholes Developers Must Fix Christian Ohwofasa Christian Ohwofasa Christian Ohwofasa Follow Sep 12 '25 AI is Failing Nigerian Languages: 7 Critical Loopholes Developers Must Fix # discuss # ai # machinelearning Comments Add Comment 5 min read Graph Neural Networks: A Reality Check on Verifying Readout by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 12 '25 Graph Neural Networks: A Reality Check on Verifying Readout by Arvind Sundararajan # machinelearning # graphneuralnetworks # ai # datascience 3 reactions Comments Add Comment 2 min read 🌩️ Smart Cloud Computing: How AI and ML Are Transforming Cloud Cost Optimization ADITI ADITI ADITI Follow Oct 12 '25 🌩️ Smart Cloud Computing: How AI and ML Are Transforming Cloud Cost Optimization # cloudcomputing # cost # ai # machinelearning 3 reactions Comments Add Comment 3 min read From ML Beginner to Production Engineer: How I’m Leveling Up My AI Projects marcusmayo marcusmayo marcusmayo Follow Oct 12 '25 From ML Beginner to Production Engineer: How I’m Leveling Up My AI Projects # machinelearning # mlops # ai # buildinpublic Comments Add Comment 1 min read Lost in Translation: Unmasking Cultural Blind Spots in AI Video Analysis Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 12 '25 Lost in Translation: Unmasking Cultural Blind Spots in AI Video Analysis # ai # machinelearning # computervision # ethics Comments Add Comment 2 min read Lost in Translation: When Video AI Doesn't Get the Joke (Or the Culture) Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 12 '25 Lost in Translation: When Video AI Doesn't Get the Joke (Or the Culture) # machinelearning # ai # computervision # ethics Comments Add Comment 2 min read Unlocking 3D Worlds: How Differentiable Rendering Bridges AI and Graphics Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 13 '25 Unlocking 3D Worlds: How Differentiable Rendering Bridges AI and Graphics # machinelearning # computergraphics # ai # python Comments Add Comment 2 min read Quantum Autonomy: Algorithms That Design Themselves by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 12 '25 Quantum Autonomy: Algorithms That Design Themselves by Arvind Sundararajan # 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https://www.fine.dev/blog/bolt-vs-v0#comparative-analysis | Comparing Bolt.new and v0 by Vercel: Which AI-Powered Development Tool Suits Your Startup? Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Comparing Bolt.new and v0 by Vercel: Which AI-Powered Development Tool Suits Your Startup? Every second counts. Choose the wrong AI-powered development platform, and you risk burnout. We'll compare two key tools—Bolt.new and v0 by Vercel—then introduce Fine , the alternative that might be just what you need. Table of Contents Introduction: Setting the Stage Overview of Bolt.new and v0 by Vercel Comparative Analysis The Hidden Gaps Enter Fine: The Startup’s Secret Weapon Call to Action: Try Fine Today Conclusion Bibliography Overview of Bolt.new and v0 by Vercel Bolt.new What It Is: Bolt.new is an AI-powered full-stack development platform that operates directly within your browser. Designed to streamline the development process, Bolt.new leverages artificial intelligence to facilitate rapid app creation without the traditional overhead. Key Features: Generates and Runs Multi-Page Apps: Create complex, multi-page applications effortlessly. Uses Natural Language Prompts: Interact with the platform using simple natural language commands, making development more intuitive. One-Click Deployment: Deploy your applications with a single click, reducing the time from development to production. Strengths: Bolt.new excels in rapid prototyping and easy scaling. Its AI-driven approach enables developers, especially those just starting out, to quickly iterate on ideas and scale applications as user demands grow, all within a user-friendly interface. v0 by Vercel What It Is: v0 by Vercel is an AI-driven UI generator tailored specifically for React and Tailwind CSS. It focuses on enhancing the front-end development experience, making it easier to create visually appealing and responsive user interfaces. Key Features: Generates React Components from Natural Language: Describe the UI you want, and v0 will generate the corresponding React components. Seamless Next.js and Tailwind Integration: Built to work flawlessly with Next.js and Tailwind CSS, ensuring your projects maintain consistency and scalability. AI SDK 3.0 for Real-Time UI Rendering: Leverage the latest AI SDK to render UIs in real-time, facilitating immediate feedback and adjustments. Strengths: v0 is particularly beneficial for those deploying their front-end via Vercel. Comparative Analysis Development Speed: Which Tool Gets Your MVP Out Faster? When time is of the essence, development speed is paramount. Bolt.new shines with its AI-driven full-stack capabilities, enabling rapid prototyping and swift transitions from development to deployment. Its one-click deployment feature ensures that your Minimum Viable Product (MVP) can reach the market quickly without the usual delays. On the other hand, v0 by Vercel is optimized for front-end development. While it accelerates UI creation with its natural language-driven component generation, it may require additional tools or platforms to handle back-end functionalities, potentially elongating the overall development timeline for a full-stack MVP. Winner: Bolt.new offers a more comprehensive solution for getting an MVP out faster, especially if your project demands both front-end and back-end capabilities from the outset. Tech Stack Integration: Flexibility in Choosing Libraries and Frameworks Bolt.new provides a unified environment that may limit flexibility in choosing specific libraries and frameworks outside its ecosystem. While it supports multi-page app generation and scaling, integrating additional tools might require workarounds or may not be as seamless. v0 by Vercel excels in tech stack integration, especially for projects centered around React and Tailwind CSS. Its seamless integration with Next.js allows developers to leverage a robust and popular framework, ensuring compatibility with a wide range of libraries and tools within the React ecosystem. Winner: v0 by Vercel offers greater flexibility for projects that rely heavily on specific front-end frameworks and libraries, making it a better choice for tech stacks centered around React and Tailwind. Ease of Use: How Intuitive Are They for Non-Expert Developers? Both platforms prioritize user-friendly interfaces, but their approaches differ. Bolt.new uses natural language prompts for development, making it highly accessible for non-expert developers or those new to full-stack development. Its comprehensive toolset reduces the learning curve, allowing users to focus on building rather than configuring. v0 by Vercel also employs natural language prompts for generating UI components, which simplifies front-end development. However, its focus is more specialized, which might require users to have a basic understanding of React and Tailwind to fully leverage its capabilities. Winner: Bolt.new edges out slightly as the more intuitive option for non-expert developers seeking a full-stack solution without needing deep technical knowledge. Collaboration: Support for Team-Based Projects and Feedback Loops Effective collaboration is essential for startup teams. Bolt.new offers collaborative features that support team-based projects, allowing multiple developers to work simultaneously and integrate feedback seamlessly. Its AI-driven environment facilitates real-time collaboration, making it easier to manage team workflows. v0 by Vercel also supports collaboration, particularly in the context of front-end development. Its integration with design tools and real-time UI rendering fosters a collaborative design and development process. However, its focus on the front end might require additional collaboration tools for back-end or full-stack projects. Winner: Both platforms offer solid collaboration features, but Bolt.new provides a more holistic approach for full-stack team projects, making it more suitable for comprehensive team collaboration. Deployment Options: Bolt.new’s One-Click Deploy vs. Vercel’s Platform-Specific Integrations Bolt.new simplifies deployment with its one-click deploy feature, allowing developers to push their applications to production effortlessly. This streamlined process is ideal for startups needing quick deployments without extensive configuration. v0 by Vercel, part of the Vercel ecosystem, offers platform-specific integrations that provide optimized deployment for front-end applications. While it excels in deploying React and Tailwind projects, the process might require more steps compared to Bolt.new’s all-in-one deployment approach. Winner: Bolt.new provides a quicker and more straightforward deployment process, which is advantageous for startups looking to minimize deployment complexities. Cost & Accessibility: Free Tiers vs. Paid Plans and Limitations Both Bolt.new and v0 by Vercel offer free tiers, allowing startups to explore their features without immediate financial commitment. However, their paid plans vary in terms of features and scalability. Bolt.new’s free tier includes essential features for small projects, but scaling might require upgrading to paid plans that offer enhanced capabilities like advanced AI features and higher deployment limits. v0 by Vercel integrates into Vercel’s pricing model, which provides scalable plans based on usage. The free tier is generous for front-end projects, but extensive usage or the need for advanced integrations will necessitate moving to a paid plan. Winner: Both platforms offer competitive pricing structures, but Bolt.new may present a more cost-effective solution for full-stack needs, whereas v0 by Vercel is ideal for startups heavily focused on front-end development. The Hidden Gaps While both Bolt.new and v0 by Vercel offer impressive features, they have their shortcomings that startups should consider. Where Bolt.new Falls Short: Limited Integrations with Issue Trackers: Bolt.new lacks extensive integrations with popular issue trackers like GitHub or Linear , which are essential for managing development workflows and tracking bugs. Where v0 by Vercel Falls Short: Limited Back-End and Full-Stack Support: v0 is primarily focused on front-end UI generation , offering limited support for back-end and full-stack solutions, which can hinder comprehensive application development. Common Gaps: Minimal Collaborative Automation: Both platforms provide basic collaboration features but lack advanced collaborative automation beyond individual development, making it challenging to manage larger, more complex team projects efficiently. Enter Fine: The Startup’s Secret Weapon While Bolt.new and v0 by Vercel each have their strengths, Fine emerges as the ultimate solution that bridges their gaps and offers a more comprehensive development environment tailored for startups. How Fine Bridges the Gaps: Comprehensive AI Agent Support: Fine supports both front-end and back-end development, providing AI agents that handle the entire stack. This eliminates the need to juggle multiple tools and ensures a cohesive development process. Live Previews: Build, run, and test your applications directly in the browser with Fine’s live previews. This feature allows developers to see changes in real-time, facilitating immediate feedback and quicker iterations. Workflow Automation: Fine automates repetitive tasks, reducing development cycle times and allowing developers to focus on what truly matters—building innovative solutions. Automation features streamline workflows, enhancing productivity and efficiency. Team Collaboration: With shared workspaces, Fine offers streamlined project management for teams. Multiple developers can work together seamlessly, with integrated feedback loops and collaborative tools that enhance teamwork and communication. Specific Benefits for Startups: Faster MVP Launches with Fewer Bugs: Fine’s comprehensive toolset and AI-driven capabilities enable startups to develop and launch their MVPs quickly while maintaining high code quality, reducing the likelihood of bugs and errors. Enhanced Code Consistency and Quality: The platform enforces consistent coding standards and best practices, ensuring that the codebase remains maintainable and scalable as the startup grows. Integration with GitHub and Linear for End-to-End Workflow: Fine seamlessly integrates with popular tools like GitHub and Linear, providing an end-to-end workflow that encompasses version control, issue tracking, and project management. This integration ensures that all aspects of development are interconnected and easily manageable. Call to Action: Try Fine Today Whether you're intrigued by Bolt.new's all-in-one full-stack environment or v0 by Vercel’s sleek UI generation, Fine offers the perfect blend of both worlds—and then some. By addressing the limitations of both platforms and providing a more holistic development environment, Fine stands out as the optimal choice for startups aiming to save time, reduce complexity, and scale efficiently. Ready to elevate your development process? Try Fine today with our free trial or enjoy our easy sign-up process to get started on building your next big idea without the hassle. Conclusion Choosing the right development tool is a critical decision for startups striving to build robust, scalable applications efficiently. Bolt.new offers a powerful full-stack solution with rapid deployment capabilities, while v0 by Vercel excels in front-end UI generation and seamless integration with React and Tailwind. However, both platforms have their limitations, particularly in areas like comprehensive integrations and collaborative automation. Fine emerges as the ultimate solution for startup developers, bridging the gaps left by Bolt.new and v0 by Vercel. With its comprehensive AI agent support, live previews, workflow automation, and robust team collaboration features, Fine empowers startups to launch faster, maintain high code quality, and scale seamlessly. Your startup’s success story starts with the right tools. Choose Fine and set your development process on the path to efficiency, innovation, and growth . Full Table of Contents Introduction: Setting the Stage Overview of Bolt.new and v0 by Vercel Bolt.new v0 by Vercel Comparative Analysis Development Speed: Which Tool Gets Your MVP Out Faster? Tech Stack Integration: Flexibility in Choosing Libraries and Frameworks Ease of Use: How Intuitive Are They for Non-Expert Developers? Collaboration: Support for Team-Based Projects and Feedback Loops Deployment Options: Bolt.new’s One-Click Deploy vs. Vercel’s Platform-Specific Integrations Cost & Accessibility: Free Tiers vs. Paid Plans and Limitations The Hidden Gaps Where Bolt.new Falls Short Where v0 by Vercel Falls Short Common Gaps Enter Fine: The Startup’s Secret Weapon How Fine Bridges the Gaps Specific Benefits for Startups Call to Action: Try Fine Today Conclusion Bibliography Bibliography 10Web. (n.d.). v0 by Vercel Review: Features, Pros, and Cons. Retrieved from https://10web.io/ai-tools/v0-by-vercel/ AI Product Reviews. (2024). Bolt.new: Features, Pricing, and Alternatives. Retrieved from https://ai-product-reviews.com/boltnew AI Review. (2023). v0 by Vercel: Price, Pros & Cons, Alternatives, App Reviews. Retrieved from https://ai-review.com/developer-tools/v0-by-vercel/ Aideloje, P. (2024). Vercel v0 and the future of AI-powered UI generation. Retrieved from https://blog.logrocket.com/vercel-v0-ai-powered-ui-generation/ Ånand, M. (2024). Should You Try v0, Webcrumbs or Both?. Retrieved from https://hackernoon.com/should-you-try-v0-webcrumbs-or-both Bolt. (2024). Documentation for Bolt.new. Retrieved from https://docs.bolt.new Bolt. (2024). GitHub Repository: Bolt.new. Retrieved from https://github.com/coleam00/bolt.new-any-llm Bolt. (2024). Introducing Bolt.new: AI-Powered Full-Stack Development in Your Browser. Retrieved from https://bolt.new Gelfenbuim, L. (2023). Vercel v0 First Impressions. Retrieved from https://lev.engineer/blog/vercel-v0-first-impressions Harris, L. (2024). Bolt.new vs. Vercel v0: Which AI Tool is Better for Web Development?. Retrieved from https://ai-tool-comparison.com/bolt-vs-v0 Johnson, R. (2024). How Bolt.new Simplifies Full-Stack Development for AI Enthusiasts. Retrieved from https://codejournal.io/boltnew-ai NoCodeDevs. (2024). Bolt.new Tutorial for Beginners (The Cursor AI and v0 Killer). Retrieved from https://www.nocodedevs.com/videos/bolt-new-tutorial Parkhomchuk, V. (2024). Vercel v0 AI Review: How To Use, Features And Alternatives. Retrieved from https://www.banani.co/blog/vercel-v0-ai-review Patel, D. (2024). Bolt.new Review: The Future of Full-Stack AI Development?. Retrieved from https://dev.to/patel/best-ai-tools/boltnew Rajab, A. (2024). What is Vercel's AI tool, V0.dev and how do you use it?. Retrieved from https://dev.to/opensauced/what-is-vercels-ai-tool-v0dev-and-how-do-you-use-it-3nge Rivera, J. (2024). Bolt.new Tutorial: Building a Full-Stack App Without Local Setup. Retrieved from https://tutorialcenter.com/boltnew StackShare. (n.d.). Bolt.new - Reviews, Pros & Cons | Companies using Bolt.new. Retrieved from https://stackshare.io/bolt-new StackShare. (n.d.). v0 by Vercel - Reviews, Pros & Cons | Companies using v0 by Vercel. Retrieved from https://stackshare.io/v0-vercel Vercel. (2024). AI SDK 3.0: Now Supporting Generative UI. Retrieved from https://vercel.com/blog/ai-sdk-3-generative-ui Vercel. (2024). Announcing v0: Generative UI by Vercel. Retrieved from https://vercel.com/blog/announcing-v0-generative-ui Vercel. (2024). v0 FAQ. Retrieved from https://v0.dev/faq Vercel. (2024). v0 Subscription Plans. Retrieved from https://v0.dev/subscription Wavel. (n.d.). v0 Review - Features, Pricing and Alternatives. Retrieved from https://wavel.io/ai-tools/v0-2/ YouTube. (2024). Bolt.new | Vercel v0 Killer? Retrieved from https://www.youtube.com/watch?v=R-frcOq6Kdc Zeniteq. (2024). Vercel's V0 Can Build Web Frontend In Seconds Using AI. Retrieved from https://www.zeniteq.com/blog/vercels-v0-can-build-web-frontend-in-seconds-using-ai Start building today Try out the smoothest way to build, launch and manage an app Try for Free -> © Fine.dev - All rights reserved. Product Overview AI Workflows Pricing & Plans Changelog Blog Docs Company Press Terms & Conditions Privacy policy | 2026-01-13T08:49:36 |
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https://v0.dev/faq | FAQs | v0 Docs Vercel Slash Docs API Search... ⌘K Ask AI Ask AI Getting Started What is v0? Agentic Features Vercel Integration Quickstart FAQs Prompt Text Prompting Screenshots and Files Figma Iterate Code editing Design mode Design systems Images and videos Versions Integrate AI models Databases External APIs GitHub MCP Integrations Ship Deployments Custom domain Sharing Templates Manage Account Community Enterprise Instructions Projects Pricing Teams Security Embed Cline Cursor OpenAI Codex Zed Guides Full-stack apps Prototyping PRD design Compare On this page FAQs Common questions about what v0 is, how it works, and how to build with it. About v0 What is v0? v0 is an AI-powered development platform that turns ideas into production-ready, full-stack web apps. Through a conversational chat interface, it generates sophisticated UIs and backend logic from natural language, taking you from prompt to production in minutes. v0 empowers anyone to build functional web applications faster without writing code manually. It supports popular frontend frameworks and UI libraries, with best-in-class expertise in Next.js, React, Tailwind CSS, shadcn/ui, and the AI SDK. The code generated is ready to deploy on Vercel's globally scalable infrastructure. How does v0 work? v0 supports the full development lifecycle from idea to production. Check out the Quickstart guide to start building on v0. Prompt : Describe what you want, upload screenshots or mockups, or import Figma designs. v0 transforms any input into working code. Iterate : Add features, adjust visuals in Design Mode, edit code, or apply your design system for consistent branding. Integrate : Connect databases, AI models, external APIs, and GitHub to build full data-driven applications. Ship : Publish with one click on Vercel, add domains, and share with your team. Manage : Collaborate in shared workspaces with permissions, security controls, and usage insights. Embed : Use v0 in your existing development environment through integrations with Cline, Cursor, and Zed, or the v0 Model API. Who can use v0? Anyone with an idea. v0 removes technical barriers and enables a new class of creators who build and collaborate without writing code. Founders ship MVPs quickly and iterate with speed. Product managers prototype without waiting on design queues. Designers test real interactions early. Engineers skip boilerplate code and develop faster. Sales engineers produce custom demos instantly. Marketers launch pages independently. Do I need coding knowledge? No coding experience is required. Describe what you want using natural language and v0 will handle the technical implementation. Do I need to write prompts in English? No. You can write prompts in your preferred language and v0 will translate them into code. Why should I choose v0? v0's deep integration with the Vercel ecosystem powers the complete workflow from prompt to production. vs. General LLMs: v0 generates interactive UIs and deployable full-stack apps, not isolated code snippets. vs. AI-Augmented IDEs: v0 provides a collaborative, conversational environment where PMs, designers, engineers, and other professionals can build together across the full product development cycle. vs. Code Generation Products: v0 delivers best-in-class Next.js expertise backed by Vercel's enterprise infrastructure and security, unlike standalone tools without proven production infrastructure. vs. AI-Powered Design Tools: v0 generates production-ready code with backend logic and deployment, not prototype only designs. Building with v0 What can I build with v0? You can build anything, from simple components to full-stack applications. For example: Landing pages Dashboards E-commerce sites Data visualization tools Internal tools Mobile-responsive apps Explore what our community is building Can v0 build full-stack or complex applications? Yes. v0 handles everything from simple components to full-stack apps with authentication, databases, and external API integrations. Can I use my own designs? Yes. Upload screenshots, mockups, or Figma designs. v0 converts them into working applications with pixel-perfect accuracy. Learn more about Figma What happened to the model switcher / GPT-5? We received feedback that users were confused by which model to choose for different scenarios. v0 now intelligently decides what model(s) to use for your query. Can v0 integrate with existing projects? Yes. You can export v0-generated components into your existing codebases. Can I use v0 offline? No. v0 requires an internet connection to process prompts and generate code. Is my code secure? Yes. v0 follows secure coding best practices, and deployed apps benefit from Vercel's enterprise-grade infrastructure. How much does v0 cost? v0 offers 5 plans: Free : No cost. For people looking to explore. Premium : $20/month. For higher limits and power users. Team : $30/user/month. For fast moving teams and collaboration. Business : $100/user/month. For privacy conscious teams. Enterprise : For large companies that require additional security. See the pricing page for more information. Editing and Collaborating Can I edit the generated code? Yes. Export the code to work locally or edit directly in v0. The bi-directional Git integration allows seamless syncing between local development and v0. Can teams collaborate in v0? Yes. Team plans enable multiple users to work on projects together. Share projects, iterate on designs, and deploy from a shared workspace. Deploying and infrastructure How do I deploy my application? Click the Share button in v0 and navigate to the Publish tab. Your application goes live on Vercel's platform , no set up or configuration needed. What is Vercel's relationship with v0? Vercel created v0 and provides the underlying infrastructure. The deep integration enables one-click deployment to enterprise grade infrastructure, with SOC 2 Type 2 compliance, strong security, and global scalability. v0's code is optimized for the Vercel platform, ensuring a smooth path from idea to production. Learn more about Vercel Do I need a new v0 account if I already have a Vercel account? No. Your Vercel account will give you access to v0. Just go to v0.app and log in! Training data What data was v0 trained on? Vercel uses a combination of public and private data sets to provide v0. v0 was trained on a large corpus of data from various sources, including third parties listed in Vercel's AI Policy . The data sets primarily cover areas related to web development, particularly with React, Next.js, and modern web technologies. Will my generations be used for training? v0 may use user-generated prompts and/or content as inputs to models and learning systems from third-party providers to improve our products. Using this data gives v0 the ability to provide more accurate and relevant recommendations to our users. Content of v0 Enterprise customers is not used for training. Further, customer data or code of customers using Vercel's platform services is not used to train, improve, or fine tune the models used by v0. Can I access my data? The ability to download your usage data is not currently supported. Is v0 trained on customer data from Vercel's platform services, like the DX Platform? No data related to your usage of Vercel's platform, Vercel CLI, or Vercel's deployment services is or will be used to train v0. Please refer to Vercel's AI Policy for more information. Can I see a history of all my chats? Yes, you can view your chat history at v0.app/chat/history Can we request deletion of data? Yes, please contact us to request deletion of v0 outputs. Please note that if any or your inputs and outputs were used to train existing v0 models, those models will not be updated. If you prefer for all of your content to not be used for training, please contact us to upgrade to a v0 Enterprise plan. To request deletion of your personal data under data protection regulations, please see Vercel's Privacy Notice . Can I use output from v0 for commercial uses? Vercel doesn't own the code generated based on your queries and prompts. However, output that you receive may be the same or similar to other users' output or third party's IP, be incomplete or contain bugs, or be inappropriate for your use. You are responsible for evaluating any content you generate through v0 and making your own determination about its suitability for commercial or other purposes. Is v0 compliant? Vercel has a SOC 2 Type 2 attestation for Security, Confidentiality, and Availability. v0 is included in the scope of Vercel's SOC 2 report. More information is available at security.vercel.com . What if I need help? If you run into issues or have further questions, you can: Browse the documentation (you are here). Join the discussion in the community forum . Contact support at vercel.com/help . On this page About v0 What is v0? How does v0 work? Who can use v0? Do I need coding knowledge? Do I need to write prompts in English? Why should I choose v0? Building with v0 What can I build with v0? Can v0 build full-stack or complex applications? Can I use my own designs? What happened to the model switcher / GPT-5? Can v0 integrate with existing projects? Can I use v0 offline? Is my code secure? How much does v0 cost? Editing and Collaborating Can I edit the generated code? Can teams collaborate in v0? Deploying and infrastructure How do I deploy my application? What is Vercel's relationship with v0? Do I need a new v0 account if I already have a Vercel account? Training data What data was v0 trained on? Will my generations be used for training? Can I access my data? Is v0 trained on customer data from Vercel's platform services, like the DX Platform? Can I see a history of all my chats? Can we request deletion of data? Can I use output from v0 for commercial uses? Is v0 compliant? What if I need help? Scroll to top Give feedback Copy page Ask AI about this page Open in chat Product Home Enterprise Pricing v0 for Students Company Terms AI Policy Privacy Cookies Resources FAQs Docs Ambassadors Vercel Community Vercel Social Twitter LinkedIn | 2026-01-13T08:49:36 |
https://dev.to/new?prefill=---%0Atitle%3A%20%0Apublished%3A%20%0Atags%3A%20devchallenge%2C%20brightdatachallenge%2C%20ai%2C%20webdata%0A---%0A%0A*This%20is%20a%20submission%20for%20the%20%5BBright%20Data%20AI%20Web%20Access%20Hackathon%5D(https%3A%2F%2Fdev.to%2Fchallenges%2Fbrightdata-2025-05-07)*%0A%0A%23%23%20What%20I%20Built%0A%3C!--%20Provide%20an%20overview%20of%20your%20AI%20agent%20or%20system%20and%20what%20problem%20it%20solves.%20--%3E%0A%0A%23%23%20Demo%0A%3C!--%20Share%20a%20link%20to%20your%20project%20repository%20and%20include%20screenshots%20or%20videos%20showing%20your%20solution%20in%20action.%20--%3E%0A%0A%23%23%20How%20I%20Used%20Bright%20Data%27s%20Infrastructure%0A%3C!--%20Explain%20how%20you%20leveraged%20Bright%20Data%27s%20tools%20for%20web%20data%20access%20and%20how%20it%20enhanced%20your%20AI%20solution.%20--%3E%0A%0A%23%23%20Performance%20Improvements%0A%3C!--%20Describe%20how%20real-time%20web%20data%20access%20improved%20your%20AI%20system%27s%20performance%20compared%20to%20traditional%20approaches.%20--%3E%0A%0A%3C!--%20Don%27t%20forget%20to%20add%20a%20cover%20image%20(if%20you%20want).%20--%3E%0A%0A%3C!--%20Team%20Submissions%3A%20Please%20pick%20one%20member%20to%20publish%20the%20submission%20and%20credit%20teammates%20by%20listing%20their%20DEV%20usernames%20directly%20in%20the%20body%20of%20the%20post.%20--%3E%0A%0A%3C!--%20And%20if%20you%20enjoyed%20working%20with%20Bright%20Data%2C%20please%20consider%20giving%20their%20repo%20some%20love%3A%20https%3A%2F%2Fgithub.com%2Fluminati-io%2Fbrightdata-mcp%20%F0%9F%8C%9F%20--%3E%0A%0A%3C!--%20Thanks%20for%20participating!%20--%3E | New Post - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Join the DEV Community DEV Community is a community of 3,676,891 amazing developers Continue with Apple Continue with Facebook Continue with Forem Continue with GitHub Continue with Google Continue with Twitter (X) OR Email Password Remember me Forgot password? By signing in, you are agreeing to our privacy policy , terms of use and code of conduct . New to DEV Community? Create account . 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://dev.to/georgekobaidze/will-developers-survive-ai-takeover-part-2-dont-be-ashamed-to-use-ai-even-iron-man-did-3l7a | Don't Be Ashamed to Use AI, Even Iron Man Did - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Giorgi Kobaidze Posted on Oct 13, 2025 • Edited on Nov 7, 2025 Don't Be Ashamed to Use AI, Even Iron Man Did # ai # machinelearning # career # discuss Will Developers Survive AI Takeover? (4 Part Series) 1 Will Developers Survive AI Takeover? Equalizer vs Amplifier 2 Don't Be Ashamed to Use AI, Even Iron Man Did 3 What Happens If You Stay Old School in the AI Era? 4 The Popstar Developer Table of Contents No Hero Fights Without a Suit It's Always Been This Way, History Repeats Itself 1980s: The Command-Line Cowboys 1990s: The IDE Boom 2000s: Framework Fever 2010s: Stack Overflow and NPM Nation Every Hero Needs a Sidekick - a Human Being But Finding a Good One Is Hard Driving Each Other to Success - Explained with NASCAR The Experience That Finally Converted Me But Not Everyone Has a Project Partner — That's Where AI Can Step In and Fill the Gap (Well, Kinda) Let's See How Iron Man Does It AI Can Absolutely Be Your Sidekick Where AI Falls Short Summary No Hero Fights Without a Suit It was a Friday evening. I was sitting at my desk, exhausted from the week, scrolling through X (formerly Twitter), something I rarely do. But I was too tired to engage in anything more intellectually demanding than mindless social media scrolling (yeah, you can tell I was pretty messed up). Then I came across a post from a verified account that said something like, "Real developers don't use AI!" You know the type, those deliberately controversial posts designed to grab your attention and engage in the comments. It was so aggressive and polarizing that it actually caught my eye, even though my attention tank was completely empty. Even me, who's cautious about overusing AI tools, think it's completely wrong to discourage someone from using them just because "real developers don't use AI." What else? Real superheroes don't use armor, right? The truth is, AI isn't replacing developers, it's upgrading them. It's the new suit, not the new hero. It's Always Been This Way, History Repeats Itself Every generation of developers has had its own "shortcut" - helper tools that made their lives as easy as possible for that time. Let's look at a few examples from each generation, starting with the 1980s: 🕹 1980s: The Command-Line Cowboys Back then, you were the debugger, IDE, and stack overflow all in one. Developers started using text editors like Emacs and Vim, and when makefiles came around, it was basically witchcraft. Automated builds? Unheard of. Then came C compilers that actually optimized your code instead of making you do the math yourself. That was their "AI moment." 💾 1990s: The IDE Boom Enter Visual Basic, Delphi, and Borland C++ Builder, drag-and-drop GUIs were born. But soon, everyone realized they could make entire Windows apps without touching the Windows API. The shortcut? Integrated Development Environments that made coding feel like assembling LEGO. By the way, I still can't believe I actually wrote code in Borland C++. I'm a 90s kid (a.k.a. a 30-year-old man now), but for some reason, my very first line of code was written in Borland C++, back in 2006. Looking back, it was so raw and unsophisticated, but at the time, it felt like pure magic. It was the single coolest thing I'd ever done in my life, and nothing even came close. It was one of the most popular editors of its time. Now I work with tools like VS Code and JetBrains IDEs, they're not even in the same galaxy when it comes to features and capabilities. Let me explain what I mean by telling a quick story (completely made up): A Trip to the '50s 1955 – Bell Labs Basement, New Jersey, USA (11:45 PM) The air smells like warm dust. Fans hum, relays click and a printer roars in the corner. Though you're so used to those sounds, you don't even recognize them anymore. You're at your desk, cluttered with punch cards, coffee stains, dust, and a growing pile of frustration and the only one in the room who regrets ever trying - well, actually you're also the only one in the room anyways, it's almost midnight. It's not your 2nd, 3rd, or 5th day it's the 8th day (weekend included) you've had to work this late, wrestling with a problem no one else can help you solve. Even coffee has stopped doing the trick. "Alright, FORTRAN test number thirty-two" You mutter, sliding a fresh deck into the card reader. "This has gotta do the trick." The machine starts clanking relentlessly, swallowing the cards one by one, just like you swallowed the last bite of that pizza 10 hours ago... yeah, you're actually starving, but all you need to do right now is to make that thing work and go home. You're staring at the blinker, hoping to work this time. Minutes later... You snatch the output as soon as it stops, scanning for the holy grail: ‘NORMAL TERMINATION.’ Instead, you see: COMPILER DIAGNOSTIC: ILLEGAL CHARACTER IN COLUMN 7. "Column 7? Again?" You flip through this printout, finger tracing down the line numbers. "Statement 60... hmm... that's the loop for summation. I checked that last night." You go back to the keypunch machine, feed a blank card and re-type the line 60 with surgical precision. Only to result in the same diagnostic. "What? I swear to god, this thing is broken or something. Alright, I'm done, I'll continue tomorrow. I'm going home!" As you start unlocking your Ford Mainline on an empty street, someone approaches, carrying a large bag. Stranger: "Hey, my name's John. I'm actually from the future. I know you don't believe me… how could you, right?" You: "Well, buddy, I'm just trying to get home, okay? I don't need any problems right now, I've got plenty already. Have a good night!" Stranger: "No, seriously. Let me show you." [He opens the bag and places something on the hood of your Mainline.] You: "Whoa… what's that bright thing? A typewriter? And put it away, don't scratch my car, I just bought it!" Stranger: "Relax. It's plastic and light. It's called a laptop." You: "What the hell is a "lab top"?" Stranger: "It's from the 2000s. Don't worry, it's a computer, well, not the kind you know. Much more advanced." You: "How's that tiny plastic brick more advanced than my..." Stranger: "OK, here, I've got your problem written and compiled in this editor called Borland C++." [He continues to show the whole thing.] You lean against the car, completely blown away, unable to believe what you just witnessed. You: "So you're telling me... you don't even need punch cards, card readers, or keypunch machines? And it can process logic in milliseconds? And that "Boar Land C Plus Plus" actually tells you what you've done wrong? Man, the future looks awesome... I wish I'd been born then!". Stranger: "Well, it's better, sure... but careful what you wish for, my friend. We've got the same scale of bugs and errors too. Some old-timers even wish times had never changed..." Now, you could tell a similar story set at any point in the history of software engineering, it would feel just as remarkable. 🌐 2000s: Framework Fever This was when developers said, "Why write everything yourself when there's a framework for that?" We got .NET, Java EE, Rails, PHP frameworks, and Spring - a generation that replaced manual wiring with configuration magic. It was also the era of Dreamweaver, where "web developers" could build a website without writing a single line of HTML. (And yes, they still called themselves developers.) 📚 2010s: Stack Overflow and NPM Nation Have We Become Assemblers Instead of Creators? Developers learned a powerful new spell: Ctrl+C , Ctrl+V . Stack Overflow became the universal brain, NPM and NuGet turned "reinventing the wheel" into "installing it with one command," and GitHub made collaboration instant. You didn't need to know how everything worked, just what to search for. Engineering became more about assembling ready-made components than creating them first and then putting them together. A Short Story from My Early Days (True Story This Time) I remember back in my bachelor's days, when I started looking for my first software engineering job. One of my friends who was already working told me, "Man, there are code snippets all over the internet, I barely have to write anything myself. I just copy and paste what I need, and it works." I remember feeling so frustrated when I heard that. Was that what software engineering had become? Copying and pasting snippets from the internet? So I'm gonna be a copy-paster, and that's it? I really hoped he was just overly exaggerating things. Fortunately, I was right for the most part. When I started working, I actually had to write quite a lot of code manually, and boy, did I enjoy that process. I still remember one particular feature (one of the first ones I had to implement), it involved generating documents with specific formatting, styles, colors, content, images, signature fields - everything, all based on user input. That was quite a task. I'd been working on it the entire week, and by Friday, I still hadn't finished. But I was so deep in the flow state that I didn't want to break it. I literally came to the office on Saturday and Sunday, sat there all alone from 9 AM till 11 PM (yes, over 12 hours straight - each day), and finally wrapped it up. I can't even begin to describe how rewarding it felt, going back home that Sunday midnight, exhausted, but proud. That was the moment I realized that finishing projects is hard, and often not fun. But, good lord, when you finally do, it's incredibly rewarding. What I'm trying to tell you, especially if you're a rookie software engineer or someone aspiring to become one, is this: don't listen to people who try to sound smart by saying "AI does all the work now." That's simply not true. Whether this job stays interesting for you depends entirely on how you approach it. If you strongly believe and expect you'll just sit at a desk, type a few prompts, and have AI magically do everything for you without needing to think deeply or understand what's happening then, honestly, this job might not be for you. Well... unless this article changes your mind. I sure hope it does. Every Hero Needs a Sidekick - a Human Being But Finding a Good One Is Hard I know some of you have probably rolled your eyes, thinking you can do it all alone, right? I thought the same way about 7-8 years ago. To be honest, I still do a lot of grinding and learning on my own (I'm an introvert). But a few years back, I realized that working with someone else can actually make you a better software engineer. Seeing the industry from another person's perspective can be incredibly valuable and it might even save your career. Of course, this person (or people) should be at least as motivated to learn as you are, or at the very least, be open to becoming just as motivated and maybe even more so with your help. I've worked with plenty of software engineers, but I can only name a handful who were at that level - the kind where I could think, "Alright, they're special. I can learn so much from them!" You know how it goes: you work with them for a few months or years, and then either one of you changes jobs, or life changes, and the connection fades. It's hard to find people willing to collaborate on projects outside of work hours on something you care about just as much as they do. And don't let friendship fool you: just because someone's your friend doesn't mean they'll make a good project partner. Those are two very different things. But if you're lucky enough to find someone who's both a friend and an exceptional collaborator... well, congratulations. You just hit the jackpot. Driving Each Other to Success - Explained with NASCAR You're probably wondering what NASCAR has to do with this article. Well, we just talked about how important other people are for moving your career forward. I like to explain teamwork using a NASCAR analogy. First, let's define a few important terms: Aerodynamics - aerodynamics is all about how air flows around a car to reduce drag and increase speed. Draft - in NASCAR, drafting is when a car follows closely behind another to reduce air resistance and gain speed. Bumping - bumping is when one car nudges another to help it move ahead, often strategically. If you've ever watched a NASCAR race, you might notice one thing that happens all the time - one thing that makes NASCAR so much more exciting than other racing categories: the leader almost never dominates the race, not even for a short stretch, let alone the entire event. That's because the leader has no car in front of them (well, unless they're lapping another car, which doesn't really count, since they'll eventually pass it). Without a car ahead, they don't get the benefit of drafting, which makes them slower than the cars in the pack behind. As a result, the race winner is often decided on the last lap and it could be someone who was running 5th, or even further back, just one lap before the finish. And all of this happens because of how aerodynamics work. If a car is running alone, with no one in front or around it, it's going to be slower. Two cars can run faster togetger than one, here's how (time for a brief physics/aerodynamics lesson): The car in front cuts through the air, creating a draft for the car behind. The rear car gains much more speed than the front one, catches up, and gives it a gentle bump, helping the front car go even faster. Then the front car slices even more air, and the rear car bumps again, their speed increases drastically. By working together like this, they can go much faster than they ever could alone. Sometimes they even swap positions and roles, taking turns benefiting from drafting and pushing each other forward. This is a brilliant analogy of how you can work with someone and make yourself 10 times (or even more) better than you were before. That can work extremely effectively. Don't be a car that cuts air and doesn't get any push, you deserve to be pushed to success and you also deserve to understand how good it feels when your effort makes someone else successful . The Experience That Finally Converted Me Up until a few weeks ago, I was one of those people who were a little skeptical about AI. Sure, I had been slowly changing my mind, leaning more in its favor, but it wasn't until a recent experience that it really clicked for me. That moment made me realize I should've started using AI tools extensively in my workflow, ignoring them doesn't make you a better developer, it only holds you back. Simple as that. So, I was helping someone with a website, not even a friend, we're not even in the same time zone, nor country... not even the same continent. We discussed the requirements, features, and all the usual stuff. Then I started the planning process, just like I always do, thinking about where to begin. After about an hour (maybe even less), while I was still sketching ideas on paper with a pen, she came back with an initial website design. The core layout was already done and it even had some pretty fancy features. The conversation went something like this (I hope I'm remembering the conversation accurately, I don't want to misquote) Me: "Wow, that's gorgeous. How did you manage it so fast? Have you been working on it like for a week or smth?" Her: "I know, right? It's beautiful! I just generated it using copilot." Me: "I have no words... And that image right there, the one you're using as a component, where did you get that?" Her: "Oh that's also generated by copilot." Me: "What? Is it THAT good in generating images? I mean even the text is flawlessly generated." Her: "I have an idea to make that dynamic." Me: "OK, I'll look into that. It's going to be a lot of CSS and JS hustle." Her: "Hmmm... it's actually easy peasy... (proceeds to explain why)." I've always considered myself an extremely doer type of person. But that moment made me realize there are levels to that game. I saw there was room for me to improve as a doer. In NASCAR terms, I was giving this person a draft (helping with the project). Then she came through with even more speed - being a doer in her own right - and pushed me forward. Now, I'm an even stronger doer than I was before, which lets me help her even more. Gosh, how I love explaining everything in racing terms. I'm not really a markup person, and I know she doesn't have extensive experience in HTML and CSS either. I mean, we both have some experience, but we're no magicians who can whip up impossible stuff on CodePen. Yet, using AI, we actually managed to create something incredibly cool, something that even a master markupper would struggle to get right in a reasonable time period. Me? I'd probably take about 3 months or something. It was at that moment I realized that talking to people and working together can still bring a lot of value. Just the thought that I might never have to write HTML and CSS manually again brought me so much joy, I can’t even describe it. I've spent hours, even days, wrestling with silly CSS rules: dragging components around, counting pixels to make things responsive, tweaking margins and padding... oh god, don't even get me started on effects, colors, and all the rest of it. I never found joy in that. I love puzzles, logic, and problem-solving - not dragging components around. I can't get that lost time back, but I'm genuinely happy those days are gone. And you know that meme about back-end developers creating markup? That meme is outdated, retired, and officially DONE. It's not happening anymore. So finally, I can say just like I mentioned in one of my articles: I'm all in on AI! (But still... stay away from vibe coding, please!) But Not Everyone Has a Project Partner - That's Where AI Can Step In and Fill the Gap (Well, Kinda) Let's See How Iron Man Does It OK, let's talk about Iron Man. Sure, he has some people around him, but really, he's still a pretty lonely guy, right? He spends most of his time working on his projects. Why does that sound so relatable? Anyway, even though he's mostly alone, he has an AI friend - J.A.R.V.I.S. J.A.R.V.I.S. is the one Tony Stark spends the most time talking to. And it's not just talking, he uses J.A.R.V.I.S. extensively, for practically every task. Commands: "J.A.R.V.I.S., subject at my 12 o'clock is not a target, disengage!" "J.A.R.V.I.S., do me a favor and blow Mark 42." Dialogues: Tony Stark: "J.A.R.V.I.S., where's my flight power?!" J.A.R.V.I.S.: "Working on it, sir. This is a prototype." Tony Stark: "Ever been to Tennessee, J.A.R.V.I.S.?" J.A.R.V.I.S.: "Creating a flight plan for Tennessee." Jarvis to Tony: "As always, sir, a great pleasure watching you work." Sounds familiar, right? Have you ever used Copilot, Claude Code, or something similar? The interaction vibe (I hesitate to even use the word "vibe" anymore after vibe coding ruined it for me) is pretty much the same. So here's my question: if even Tony Stark - genius inventor, engineer, scientist, businessman, and THE SUPERHERO AVENGER - relies on AI to work efficiently, why would you deny it? Maybe that's the way we are supposed to build software? Maybe we've been grinding to reach this level? Think about this. For the record, I'm well-aware he's a fictional character, but the analogy still stands. Tony Stark doesn't have to do everything by himself, that would be counter-productive and take forever. He doesn't even build his own suit anymore, the robot does it. His role is deciding which features to add, and there's nothing wrong with that. At the same time, he's perfectly capable of doing the manual work. Remember the first Iron Man movie, when he was held captive? He built the very first Iron Man suit - "Mark 1" - crude, clunky, but still brilliant. It wasn't nowhere near as advanced as the later versions, of course. Here's the comparison between the "Mark 1" - built with skills and pieces of junk, without AI and the "Mark 85" - built with all the right tools and AI. Why was the difference that significant? Because back then, he had his skills and limited tools. Later, he used the same skills and every tool available: robots, AI, simulations and that's what made him unstoppable. He didn't say, "Real engineers don't use AI." You have to delegate boring and repetitive work to AI, but when the time comes, you should be able to get involved manually. Then you might ask: if I delegate all that work to AI, how can I improve my skills? Good question, I'll try to explain from my own experience: if you mindfully code with AI, you're going to learn even more than from the tutorial hell. I'll expand on this topic in one of the upcoming parts of this series. AI Can Absolutely Be Your Sidekick AI can definitely be your project partner. Have you ever tried pair programming? It's the same concept - just without the human factor. Sometimes, that's even better. When you code with another person, you're relying on their knowledge or approach, which can occasionally be biased or incorrect. That's especially risky if you're not experienced enough to catch mistakes and correct them. With AI, this problem rarely occurs. Of course, it's still not perfect, but it's only going to get better. Take Claude Code as an example. One thing I absolutely love about it is that when you install it on your local machine, the very first thing it shows you is something like this: AND, once again, I ABSOLUTELY LOVE THAT! Kudos to Anthropic for this. They don't just promote themselves or claim their product is perfect - they make it clear that you need to lead the process, you need to be the main pilot in your Boeing 777. Claude should be your second pilot, and it's always your responsibility to check and verify the quality and correctness of the code (or anything else) it generates. That small but crucial element makes me think they're legit. It's a solid reason to use their product, which, to be honest, is absolutely fantastic. At first glance, it might seem like anti-promotion, but to me, it's actually a pretty strong selling point. AI for Experienced Software Engineers AI tools are extremely powerful weapons in the hands of an experienced software engineer. It's like giving a baseball bat to an MMA champion, dangerous, right? An experienced programmer is more likely to use AI wisely and mindfully: they verify the code and truly understand what the AI is generating. But some experienced developers get too comfortable. They don't ask AI questions to understand lesser-known concepts, which is a mistake. You should always take AI's suggestions with a grain of salt. No matter how experienced you are, there will always be concepts you don't fully grasp. Use the vast amount of resources AI provides to your advantage. Make AI justify all the decisions it makes. Don't trust it blindly and don't trust yourself blindly either. AI for Junior Software Engineers Even if you're a rookie, you can still use AI tools to your advantage. But you need to be mindful, don't fall into the trap of leaning too heavily on AI and skipping the learning process. Don't use AI just to generate code for you, no matter how urgent the task is. Everyone at your company should understand that you're a beginner and need time to build knowledge and get familiar with the basics. Use AI as your mentor: sit down, chat with it, and ask even the simplest questions. Let me show you an example: Prompt: > Can you explain the different types of browser caching and how each level works? Response: Browser caching operates at several distinct levels, each with different characteristics: 1. Memory Cache (L1) - Fastest but most volatile - Stored in RAM during the current browser session - Cleared when tab/browser closes - Typical for: Images, fonts, scripts actively used on the current page - Size limit: ~10-50MB depending on available memory 2. Disk Cache (L2) - Persistent across browser sessions - Stored on disk in the browser's cache directory - Survives browser restarts but can be cleared by user or browser policies - Typical for: Any cacheable HTTP resources - Size limit: Usually 50MB-1GB (browser dependent) 3. Service Worker Cache (Application Cache) - Most persistent and developer-controlled - Programmatically managed via JavaScript - Survives cache clearing in many cases (user must explicitly clear "site data") - Typical for: PWA assets, offline-first applications - Size limit: Varies by browser (Chrome ~6% of free disk space) 4. HTTP Cache (Browser Cache) Controlled by HTTP headers: - Cache-Control: max-age, no-cache, no-store, public, private - ETag: Validates if resource changed (conditional request) - Last-Modified: Timestamp-based validation - Expires: Legacy expiration date Cache Priority Order When a resource is requested: 1. Check Memory Cache → instant return if found 2. Check Service Worker → programmable response 3. Check Disk Cache → fast return if valid 4. Network request → fetch from server, then cache based on headers Enter fullscreen mode Exit fullscreen mode See? Now you can ask even more detailed questions at any level. For the most part, you can even replace boring and time-consuming video tutorials with AI. You can build projects and learn with AI tools. That said, there are still amazing video tutorials you don't want to miss, especially ones about career development, managing your engineering path, and improving your skills properly. Sure, you can get answers to these questions from AI as well, but they'll usually be general. In real life, things often work in very peculiar and specific ways, so some guidance from experienced humans is still invaluable. Video tutorials are still valuable at some level, as they show you a process of project creation from start to finish, which is a critical skill for a developer. I'd say it's more mental than technical. Always be a finisher when it comes to projects. Where AI Falls Short I'd say the biggest limitation of AI, at least for now, is that it doesn't have emotions. It can't form genuine friendships with you, and that can make a real difference. When you have an emotional connection with someone, the work you do together can turn into a shared mission - your number one goal. You know that someone who truly cares about the project relies on you, and you can't let them down. You share the struggles, the breakthroughs, and the joy of celebrating small victories together. This kind of moments engrave the experience and knowledge in your brain 10 times better. AI can't give you that feeling. It doesn't care about the outcome, its only purpose is to assist you, not to emotionally support you. Let me show you an example: Prompt: > Hey Claude, you're awesome!!! Answer: Thanks! Is there anything you'd like help with on the project, or any other technical questions I can answer? Enter fullscreen mode Exit fullscreen mode If your friend responded to your enthusiasm like that, you'd probably think something's wrong, it just sounds so dry and lifeless, right? A real human would say something like: "Hey! Where did that come from? Thanks!" or "Oh my god, thank you! You're amazing too!" - something with actual emotion behind it. And honestly, even if AI replied that way, it still wouldn't feel the same as hearing it from a real person. So, if what you're looking for is emotional connection, AI might not be the best companion or partner but it can still be an incredible ally when it comes to solving problems. Summary Don't hurt your potential by being hostile toward AI. Use it mindfully, and it will benefit you - it'll make your life and work so much better. You can use AI as your peer programmer, your rubber duck (on steroids), your teacher, or even your mentor. I've seen people call AI many things: some call it danger, others call it awesome, I call it J.A.R.V.I.S. Shall we code, J.A.R.V.I.S.? Will Developers Survive AI Takeover? (4 Part Series) 1 Will Developers Survive AI Takeover? Equalizer vs Amplifier 2 Don't Be Ashamed to Use AI, Even Iron Man Did 3 What Happens If You Stay Old School in the AI Era? 4 The Popstar Developer Top comments (6) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand MUHAMMAD USMAN AWAN MUHAMMAD USMAN AWAN MUHAMMAD USMAN AWAN Follow Hi, I am a skilled Full Stack web developer with skills HTML, CSS, JavaScript, TypeScript, ReactJs, NextJs, Bootstrap, Tailwind CSS, NodeJs, ExpressJs, mongoDb, Docker, Vercel and JestJs. Email usmanaugust28@gmail.com Location Abbottabad, Pakistan Education National University of Science and Technology, Islamabad Work Layout Manager / Core Front-end Engineer at GrowthRune. Joined Sep 23, 2024 • Oct 18 '25 Dropdown menu Copy link Hide Nice bro, that line "Even Iron man used Jarvis", like 🔥🔥🔥🔥🔥 Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow I write code like I brew my coffee: strong, clean, and with care. ☕ Mostly working with .NET, but I’m tech-agnostic. I’m a problem solver by nature. Location Tbilisi, Georgia Education San Diego State University Work Principal Software Engineer at Flutter Entertainment Joined Jan 29, 2018 • Oct 18 '25 Dropdown menu Copy link Hide Thank you! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Khurram Shehzad Khurram Shehzad Khurram Shehzad Follow My name is Khurram Shehzad. I am a dynamic and results-driven Project Manager at 247Gulftrivia, leading diverse teams to deliver innovative and high-impact digital projects. Location Dubai, United Arab Emirates Education University Of Dubai Work 247GulfTrivia.org Joined Oct 13, 2025 • Oct 18 '25 Dropdown menu Copy link Hide Interesting! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow I write code like I brew my coffee: strong, clean, and with care. ☕ Mostly working with .NET, but I’m tech-agnostic. I’m a problem solver by nature. Location Tbilisi, Georgia Education San Diego State University Work Principal Software Engineer at Flutter Entertainment Joined Jan 29, 2018 • Oct 18 '25 Dropdown menu Copy link Hide Thanks! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Jerrykerry Jerrykerry Jerrykerry Follow Sharing real testing and results about streaming apps & APK optimization at https://inatbixindir.tr. Joined Oct 13, 2025 • Oct 18 '25 Dropdown menu Copy link Hide Great job! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow I write code like I brew my coffee: strong, clean, and with care. ☕ Mostly working with .NET, but I’m tech-agnostic. I’m a problem solver by nature. Location Tbilisi, Georgia Education San Diego State University Work Principal Software Engineer at Flutter Entertainment Joined Jan 29, 2018 • Oct 18 '25 Dropdown menu Copy link Hide Thanks! Like comment: Like comment: 1 like Like Comment button Reply Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Giorgi Kobaidze Follow I write code like I brew my coffee: strong, clean, and with care. ☕ Mostly working with .NET, but I’m tech-agnostic. I’m a problem solver by nature. Location Tbilisi, Georgia Education San Diego State University Work Principal Software Engineer at Flutter Entertainment Joined Jan 29, 2018 More from Giorgi Kobaidze The Popstar Developer # ai # machinelearning # career # discuss What Happens If You Stay Old School in the AI Era? # ai # machinelearning # discuss # career Will Developers Survive AI Takeover? Equalizer vs Amplifier # ai # machinelearning # discuss # career 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://dev.to/momen_hq/momen-vs-bubble-key-differences-and-pricing-explained-4mo9 | Momen vs Bubble: Key differences and pricing explained - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Alex for Momen Posted on Oct 17, 2024 Momen vs Bubble: Key differences and pricing explained # webdev # powerfuldevs # productivity # devops Which no-code platform is right for your next project? Our latest livestream covers the key differences between Momen and Bubble, focusing on pricing, performance, and flexibility. Quick Highlights: 01:29 Topic Overview 03:24 Momen’s Functionalities 18:51 Momen vs Bubble: Front-end Reuse, Logs, and Ecosystem 24:27 Momen vs Bubble: Pricing 32:58 Momen vs Bubble: Performance 40:30 Momen vs Bubble: Flexibility and more Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Momen Follow Momen is a full-stack no-code web app builder. There is no limit to what you can build with Momen. Start to build today More from Momen How to Build a Custom AI Trip Planner: Connecting Lovable (Frontend) to Momen (Backend) # nocode # ai # powerfuldevs # aitrip Building Your Own AI Resume Screener: A Step-by-Step No-Code Guide # ai # powerfuldevs # productivity # pdf How to Build the Navigation Bar and User Authentication Using Momen # auth # nocode # powerfuldevs 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
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https://dev.to/arvindsundararajan/quantum-leaps-in-concept-understanding-building-ai-that-truly-gets-it-54da | Quantum Leaps in Concept Understanding: Building AI That Truly 'Gets It' - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Arvind Sundara Rajan Posted on Sep 12, 2025 Quantum Leaps in Concept Understanding: Building AI That Truly 'Gets It' # machinelearning # quantumcomputing # ai # python Quantum Leaps in Concept Understanding: Building AI That Truly 'Gets It' Imagine AI that understands complex ideas, not just memorizes data. Current AI often struggles with combining concepts, requiring massive retraining for even simple variations. What if we could imbue AI with a more human-like ability to generalize and understand compositional meaning, all while making it efficient and accessible? The core idea? Harness the power of quantum circuits to learn and represent compositional relationships. Instead of classical tensors, we're leveraging the inherent properties of quantum systems to encode and process information, allowing our AI to grasp nuances that traditional methods miss. Think of it like this: a classical computer sees 'red car' as two separate words. A quantum system sees the intertwined relationship – a vehicle characterized by its redness. This approach uses parameterized quantum circuits, trained to map visual information and associated textual descriptions. Encoding the images into a quantum state and then manipulating this state with the parameterized circuit lets us find patterns and associations more efficiently than brute-force classical approaches. The circuit learns the relationships between image features and the words that describe them, leading to better generalization. Benefits for Developers: Improved Generalization: Build models that understand the 'spirit' of a concept, not just the specific examples they were trained on. Faster Training: Quantum circuits can potentially learn these relationships faster, reducing training time and resource consumption. Enhanced Robustness: More resilient to variations and noise in the input data. Composable Concepts: Effortlessly combine learned concepts to understand new, complex ideas. Novel Applications: Unlock new possibilities in fields like medical imaging analysis or advanced robotics, where understanding complex relationships is crucial. Insight: One of the biggest challenges is efficient data encoding. Finding the right quantum representation for your data is key to unlocking the full potential of this approach. Practical Tip: Start with simpler, low-dimensional data sets to experiment with different encoding techniques before tackling complex, real-world scenarios. This is a stepping stone towards AI that truly understands the world around it. The ability to generalize compositional concepts opens up exciting new possibilities for more robust, adaptable, and efficient AI systems. As quantum computing technology matures, these techniques will become increasingly accessible, empowering developers to build the next generation of intelligent machines. Related Keywords: Quantum Machine Learning, Variational Quantum Circuits, Generalization, Concept Learning, Quantum Algorithms, Parameterized Quantum Circuits, Quantum Neural Networks, Data Encoding, Feature Mapping, Quantum Optimization, Hybrid Algorithms, Quantum Advantage, NISQ Era, Quantum Software, Quantum Simulation, Quantum Data, Quantum Artificial Intelligence, Cloud Computing, Machine Learning, Artificial Intelligence, Python, Tensorflow Quantum, PennyLane Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Arvind Sundara Rajan Follow Arvind Sundara Rajan is a Generative AI Strategist and Senior Director @ LTIMindtree. He is reffered to as arvind sundararajan,arvind rajan, arvind s rajan, aravind sundararajan, sundarajan arvind Location Warsaw Education College Pronouns He/Him Work Senior Director & Gen AI Strategist at LTIMindtree Joined Aug 31, 2025 More from Arvind Sundara Rajan Unveiling Brain Dynamics: A New Era in EEG Analysis # machinelearning # neuroscience # python # datascience Code Your Way to Perfect 3D: Introducing Gradient-Powered Geometry by Arvind Sundararajan # machinelearning # graphics # 3d # ai AI Unveils the Secrets of Chemical Reactions: A Leap for Innovation by Arvind Sundararajan # machinelearning # chemistry # python # opensource 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://ai-review.com/developer-tools/v0-by-vercel/ | ⋙ v0 by Vercel: Price, Pros & Cons, Alternatives, App Reviews Skip to content Search for: Ai review Artificial intelligence tools & services Home » Developer tools v0 by Vercel Developer tools Reading 3 min Published by December 17, 2023 Modified by October 8, 2025 As a software developer, I’m always on the lookout for tools that simplify the process of creating user interfaces. Recently, I had the opportunity to explore Vercel’s v0 UI generator, and I was pleasantly surprised by its functionality and features. In this article, I’ll provide a detailed user report, describe its functionality, and showcase some of its standout features with examples of use. User Report: Vercel’s v0 UI generator is currently in beta, and it offers a streamlined approach to creating UI elements using simple text prompts. It allows users to quickly generate various components and sections for web applications. During my experience, I found the user interface to be intuitive and easy to navigate. The inclusion of consent settings for tracking technologies ensures user privacy, giving control to opt-in or opt-out. Functionality: The functionality of v0 is impressive. It can generate a wide range of UI elements, including product categories, hero sections, contact forms, e-commerce dashboards, and more. It even supports multi-language prompts, making it accessible to users worldwide. One of its standout features is the ability to generate a minimalist blog post template. This template can be customized and integrated seamlessly into any blog or content website, offering a clean and aesthetically pleasing design. Example of Use: Imagine you want to create a personal portfolio website with a minimalistic landing page, just like I did. With v0, you can simply input your name and a brief description of yourself as a software developer. The tool will generate a beautifully designed landing page with sections showcasing your projects and GitHub repositories. The result is a clean, one-page portfolio that’s easy to scroll through, eliminating the need for a traditional menu. Another notable feature is the ability to generate a contact form. In my case, I used this to create a contact form with fields for first name, last name, email, and a message. The form is neatly displayed within a card, and a submit button makes it easy for visitors to get in touch. In conclusion, Vercel’s v0 UI generator is a powerful tool for simplifying UI creation. Its versatility, ease of use, and the ability to generate a wide range of components make it a valuable asset for developers. Whether you’re building a personal website, an e-commerce platform, or any other web application, v0 can help you quickly generate the UI elements you need, saving you time and effort. Give it a try and experience the convenience of generating UI with simple text prompts. Rate article Add a comment Cancel reply Name * Email * Comment Save my name, email, and website in this browser for the next time I comment. You may also like Runable Runable.com stands out as a versatile AI agent platform 15 0 JDoodle JDoodle revolutionizes app development by letting anyone 2 0 Firebase Studio Firebase Studio is Google’s new cloud-based development 2 0 YouWare YouWare is an AI-powered coding platform designed to 0 0 Blocks Blocks is an innovative AI-powered platform that lets 0 0 Monity Monity is an AI-powered website monitoring platform 0 0 Kimi Kimi is an advanced AI assistant developed by Moonshot 0 0 TweakCN TweakCN is a powerful visual theme editor created specifically 0 0 © 2022-2026 Ai tools reviews | Privacy policy | Terms and conditions | About us This website uses cookies to improve user experience. 🤖 By continuing to use the site, you consent to the use of cookies. OK | 2026-01-13T08:49:36 |
https://www.heroku.com/github-students/ | GitHub Student Developer Pack Offer | Heroku Search overlay panel for performing site-wide searches Search For: Close Boost Performance & Scale with Postgres Advanced. Join Pilot Now! Search Open Search Popup Account menu Dashboard Databases Dataclips Elements Documentation Support Login Sign Up Products Products Discover Heroku’s AI PaaS (Platform as a Service), designed for effortless app deployment and scaling. Explore our cloud application platform features, reliable managed data services, and a robust ecosystem to power your modern applications. Heroku Platform Deploy, manage, and scale apps on Heroku, an AI PaaS based on a managed container system. Heroku AI Build intelligent applications with managed inference and agents, MCP, and more. Heroku Data Services Simplify your data management with Heroku’s fully managed cloud databases and data services. 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Latest News from the Heroku Blog Heroku AI: Accelerating AI Development With New Models, Performance Improvements, and Messages API News Last Updated: December 18, 2025 Anush DSouza This month marks significant expansion for Heroku Managed Inference and Agents , directly accelerating our AI PaaS framework. We’re announcing a substantial addition to our model catalog , providing access to leading proprietary AI models such as Claude Opus 4.5,… Heroku for GitHub Students A special offer for students enrolled in the GitHub Student Developer Pack. Learn on Heroku + GitHub Heroku is a cloud-based, AI platform as a service (AI PaaS) for building, running, and managing apps. Students use Heroku to learn and grow their skills by taking advantage of the platform’s fully managed runtime environment coupled with a wide range of tools and integrated services. Heroku makes app deployment fast and easy. The platform’s GitHub integration allows you to connect your Heroku app to your GitHub repo and deploy on every push to GitHub. We invite you to explore the Heroku developer experience throughout your studies and beyond. Heroku offers a range of low-cost services to help you experiment, learn, and prototype new ideas. For GitHub Students, we are going a step further and adding even more resources to your GitHub Student Developer Pack . Get the student offer Special offer for registered GitHub Students All Heroku applications run in a collection of lightweight Linux containers called dynos . If you are registered with the GitHub Student Developer Pack , you are eligible to receive platform credits worth $13 per month for 24 months (for a total value of $312). You’ll be able to spend those credits on any Heroku product, including Heroku Dynos, Heroku Postgres, and Heroku Key-Value Store, except for third-party Heroku Add-ons. For example, the $13 in monthly platform credits is enough to cover one month of the Eco Dynos plan ($5 for 1000 dyno hours/month), one Mini Heroku Postgres database ($5/month), and one Mini Heroku Key-Value Store database ($3/month). Learn more about the GitHub Student Developer Pack on our Code[ish] podcast . Heroku offer FAQ Q: How do I qualify for the Heroku offer in the GitHub Student Developer Pack? A: If you qualify for the GitHub Student Developer Pack and are 18 years of age or older, then you are eligible to apply for the Heroku offer. See the GitHub Program FAQ for more information. Q: How can I apply for the Heroku offer in the GitHub Student Developer Pack? A: You can apply for the program in three easy steps: Enroll in the GitHub Student Developer Pack (if you’ve not already done so) and click on the Heroku offer. Sign up for a Heroku account , or if you already have one, log in to your account . Apply for the Heroku for GitHub Students offer. Q: Do I need a credit card to redeem the offer? A: Yes, you will need a valid credit or debit card on file to redeem this offer. In addition, the credit card will be charged for resources consumed in excess of the $13 per month credit. You can add a new card by going to the Billing tab under Account Settings. For step-by-step details, watch the short video tutorial. Q: I’ve applied for the Heroku offer in the GitHub Student Developer Pack. When will I hear back? A: Wait times can vary depending on the volume of requests we receive. However, as long as you applied well in advance of the end of the month, we will do our best to ensure that you receive your credit allocation in a timely manner. Q: How can I check if I received my credits? A: You can go to the Billing tab under Account Settings to see if you’ve received $312 in platform credits to be used over the 24 month program period. It would be listed in the Billing Information section of this tab. Q: How many platform credits will I receive? A: Once your application is approved, you will receive one allocation of platform credits worth $312, which will burn down at a rate of $13 per month over 24 months. Q: When will I receive the platform credits? A: Once your application is approved, your platform credits will be applied immediately. However, they will be set to begin on the first day of the current month. For example, if your application is approved on the 23rd of October, the $13 in credits will begin on the 1st of October and will expire at the end of October (i.e., the 31st). To make full use of your platform credit allocation, we recommend that you apply for the program at the beginning of the month. Q: What can I spend my platform credits on? A: You can spend your credits on any Heroku product, including Heroku Dynos, Heroku Postgres, and Heroku Key-Value Store. Credits do not apply to paid third-party add-ons. For more information on how to provision or change your platform resources, watch the short video tutorial. Q: If I don’t spend $13 worth of platform credits by the end of the month, will they roll over? A: No. Any unused credits will expire and do not roll over month to month. Q: What will happen at the end of the 24-month program period? A: Any unused platform credits at the end of the program period will expire. You will need to either spin down your resources or be charged for them. Q: At the end of the program period, can I reapply to the program and get another 24 months worth of credits? A: No. Previous participants of our current Heroku for GitHub Students program (which began October 2022) cannot reapply for the program. Q: I was a part of the old Heroku for GitHub Students program (which ran from 2018-2020). Can I apply to this new version of the program? A: Yes. This new Heroku for GitHub Students offering is open to all current students, regardless of whether they participated previously. However, keep in mind that students may only participate in the new program for one 24-month period. Q: Can I apply my credits to a Heroku Teams account? A: Unfortunately, this offer cannot be applied to a Team account. For more information, see the Dev Center article: Collaborating with Other Developers on Your App . Q: I applied for the Heroku offer with a different or incorrect email address. Can I switch the request to a different account? A: No. Due to the large volume of requests we receive, we aren’t able to transfer your platform credits to a different account once you’ve applied. Q: Where do I find help with deploying my app on Heroku? A: Heroku maintains a wealth of documentation in our Dev Center. We recommend that you start with one of our step-by-step Getting Started on Heroku guides — simply choose your favorite language and follow the steps to get set up on Heroku. Q: How can I keep up with what’s new at Heroku? A: Stay in touch with us via RSS and the Heroku Blog . Q: How do I contact Heroku with questions about the GitHub Student Developer Pack? A: For questions specific to this program, feel free to contact us at: heroku-students@salesforce.com . Q: Have more questions? A: Check out this Knowledge Base article for more information. Heroku makes deployment easy Stay up to date with Heroku Read the Heroku Blog for the latest updates, product releases, technical discussions, and more. 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https://dev.to/scale_youtube/devoxx-inspiring-the-next-generations-35g6 | Devoxx: Inspiring the Next Generations - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Scale YouTube Posted on Nov 5, 2025 Devoxx: Inspiring the Next Generations # career At Devoxx Belgium 2025, Frank Delporte sat down with Cassandra Chin to dig into her new book Raising Young Coders, sharing tips on teaching programming to kids and even snagging a 20% discount with code APAUT on Springer’s site. Earlier at 06:56, he chatted with Daniel De Luca, the founder of Devoxx4Kids, about the creative, hands-on activities they run to spark tech curiosity in children of all ages. Watch on YouTube Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Scale YouTube Follow Joined Aug 2, 2025 More from Scale YouTube NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://www.fine.dev/blog/remote-first-tech-startup#9-stay-on-top-of-code-reviews | How to Build a Remote-First Tech Team as a Startup CTO: Tools and Tactics Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back How to Build a Remote-First Tech Team as a Startup CTO: Tools and Tactics Building a successful remote-first tech team requires the right tools and tactics. Some startups thrive off of remote workers around the world - others are sunk by inefficiency and communication failures. In this post, we'll explore essential steps and technologies to help you build a high-performing remote-first team. Table of Contents Establish a Strong Communication Foundation Use the Right Collaboration Tools Create an Inclusive Team Culture Hire for Remote-Friendly Qualities Focus on Employee Well-Being Measure Team Performance Effectively Prioritize Security and Data Protection Choose a Collaborative AI Platform Stay on Top of Code Reviews 1. Establish a Strong Communication Foundation Communication is the lifeline of any remote-first tech team. Ensuring that everyone stays connected and informed requires a blend of asynchronous and real-time communication tools. As a startup CTO, consider investing in: Slack or Microsoft Teams for real-time messaging and updates. Zoom or Google Meet for video calls, meetings, and check-ins. Loom for recording walkthroughs and sharing asynchronous video updates. The key to building a cohesive team is setting clear expectations about how and when different tools should be used. Creating guidelines for communication not only helps streamline workflow but also reduces burnout by ensuring team members can disconnect after work hours. 2. Use the Right Collaboration Tools Your tech stack is crucial to enabling effective collaboration among remote engineers. Select tools that encourage transparency and make collaboration as seamless as possible. Here are some must-have tools for remote-first tech teams: GitHub or GitLab for version control and managing code collaboratively. Jira or Linear for tracking tasks and sprint planning. Confluence or Notion for documenting processes, creating shared knowledge bases, and improving accessibility to resources. A well-documented codebase and clearly defined processes empower developers to operate independently, minimizing bottlenecks and improving productivity. 3. Create an Inclusive Team Culture Fostering an inclusive and collaborative culture is essential to the success of a remote-first team. This starts with ensuring all voices are heard, regardless of geographic location. Here are a few tactics that can help: Regular Virtual Meetups : Schedule weekly check-ins or team-building events where team members can share updates, ask questions, and bond. Async Standups : Consider using tools like Geekbot to automate daily standups, enabling each member to share their progress and blockers asynchronously. Recognition and Feedback : Use platforms like 15Five to gather feedback and recognize individual contributions. It helps foster a positive work environment where team members feel valued. 4. Hire for Remote-Friendly Qualities Hiring for a remote-first tech team requires different criteria compared to an on-site environment. It’s crucial to look for qualities such as excellent written communication, self-motivation, and the ability to work autonomously. During the interview process, assess candidates for their comfort level with remote work by asking questions about their previous remote experiences, how they manage their time, and how they communicate asynchronously. Tools like HireVue can assist in conducting initial screenings through video interviews, allowing you to see how well candidates adapt to remote-first communication. Remember, some people thrive on the office atmosphere and are less efficient working from home, surrounded by distractions ranging from laundry to kids. Ask for an honest self-assessment: where do you perform better? When working from home, what does your day look like? 5. Focus on Employee Well-Being Employee well-being is fundamental for retaining top talent in a remote-first setup. As a startup CTO, your team's health should be a priority. Encourage employees to establish work-life balance, take breaks, and avoid overworking. Here are some ways to promote well-being: Flexible Work Hours : Give your team flexibility to work when they are most productive, keeping in mind that different time zones require adjustments. Wellness Programs : Platforms like Headspace or Calm can offer resources to help employees reduce stress and improve their mental health. No-Meeting Days : Designate a day of the week for no meetings to help everyone focus on deep work without interruptions. Context switching is a huge productivity killer. 6. Measure Team Performance Effectively Measuring performance in a remote-first environment can be tricky. Instead of relying on metrics like hours worked, focus on output-based performance indicators. Use tools like GitPrime to understand productivity metrics without micro-managing. Set clear, outcome-based goals for each team member and evaluate success based on these targets. Regular one-on-ones are also key for providing guidance, discussing blockers, and keeping each team member aligned with the broader business goals. 7. Prioritize Security and Data Protection Security is a non-negotiable aspect of building a remote-first tech team. Your remote employees will be accessing company resources from various locations, which presents unique challenges in terms of data protection. VPN and Endpoint Protection : Make sure that your team uses a secure VPN and endpoint protection software when accessing company servers. Password Managers : Tools like 1Password or LastPass can help keep team credentials secure. Multi-Factor Authentication : Enforce MFA to ensure that access to sensitive data is protected. Establishing best practices for security and ensuring that everyone understands the importance of cybersecurity is critical to preventing data breaches and protecting your business. 8. Choose a Collaborative AI Platform Selecting the right AI platform is essential for boosting productivity and collaboration among your remote team. Fine is designed specifically for teams, offering seamless integration with tools like Linear and GitHub, making it ideal for remote work. Unlike IDE-based AI assistants that are more suited for solo developers, Fine provides an all-in-one AI coding agent that enhances teamwork and accelerates startup growth. 9. Stay on Top of Code Reviews When working remotely, it can be easy for developers to finish writing code and leave it sitting, waiting for review for days or even weeks. Code reviews are essential for maintaining quality and ensuring knowledge sharing across the team. Use tools like Linear and GitHub to keep track of open tickets and close them efficiently. Setting up automated reminders for reviewers can help ensure that reviews are completed promptly, keeping the team moving forward and avoiding bottlenecks. Conclusion Building a remote-first tech team as a startup CTO is no easy feat, but with the right tools and strategies, it can lead to a more diverse and efficient development team. By focusing on communication, collaboration, culture, and security, you can create an environment where your remote team can thrive and innovate. The success of a remote-first team lies not just in the tools you use, but in how you nurture your team culture and make everyone feel connected despite the distance. Start small, iterate, and adapt as you learn more about your team’s needs—that’s how you’ll build a resilient and agile remote-first team ready for anything. Are you looking to streamline your development processes with collaborative AI coding? Discover how Fine can help your remote team collaborate better to ship software and boost productivity. Sign up today and see what AI-driven development can do for you! Start building today Try out the smoothest way to build, launch and manage an app Try for Free -> © Fine.dev - All rights reserved. Product Overview AI Workflows Pricing & Plans Changelog Blog Docs Company Press Terms & Conditions Privacy policy | 2026-01-13T08:49:36 |
https://dev.to/github/what-were-your-favourite-github-universe-moments-heres-mine-25fi | What were your favourite GitHub Universe moments? Here's mine - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Michelle Duke for GitHub Posted on Nov 8, 2021 • Edited on Feb 23, 2022 What were your favourite GitHub Universe moments? Here's mine # event # github # devops GitHub Universe (2 Part Series) 1 This is the Way • GitHub Universe 2020 is here 2 What were your favourite GitHub Universe moments? Here's mine GitHub Universe is now finished. What were your favourite moments? If you missed our post on all things Universe, check it out. What you missed at GitHub Universe, the latest feature announcements Michelle Duke for GitHub ・ Oct 29 '21 #github #product #devops #opensource If you haven't already, read all the cool announcements we made, and let us know your favourites. We had our APAC Watch parties and we loved all the things we saw. Here's my top announcements, as well as a few other awesome moments from GitHub Universe. Codespaces I love the fact anyone can open Codespaces on their computer, laptop, iPad, phone, even a Tesla, and deploy fixes. I can do this anytime, anywhere in the world (as long as I have an internet connection). All my dependencies are added, and I can still use my VS Code settings. This has been a game changer for our team who works all over the world. Copilot GitHub Copilot has been an incredible asset in my coding journey. Copilot makes suggestions to my code on what I should include next, and even helps me write whole functions. It's super useful when starting out, or, if you're like me, and still learning along the way. New GitHub Issues We've been using the new GitHub Issues for a while and they have been amazing. It's been great using the new project boards and tables, and being able to convert tasks to Issues. We've been tracking project ideas and building lists of things we might like to do in future. Once we're ready to put a list item into action, we convert it into an Issue and we're off planning. It's definitely a game changer for project planning! GitHub Discussions Discussions are a loved feature among the community. Maintainers use them to connect to their contributors, and many others use Discussions to collect ideas. The new features added to Discussions such as labels and announcements is something we've been using on a number of our repos. I can't wait until polls are implemented! Papercuts There's never a GitHub Universe without announcing several changes to help make all our lives easier. The new table of contents to help navigate markdown files makes my life a whole lot better. I'm always looking at READMEs, and being able to navigate them easily is so useful. Being able to copy large pieces of code is perfect when looking through tutorials. And navigating the GitHub web got a whole lot easier with the Command Palette. I'll be pressing CTRL+K (yes I use Windows) all the time now! Other Goodies from Universe It wouldn't be a GitHub Universe without a few other goodies. Whilst these aren't major feature announcements, these are all amazing things happening in the developer community and relevant to developers. Here's my favourites. DevOps This What is DevOps video by Emily Freeman is epic! There's a lot of Easter eggs in this one, plus quirky analogies. This video (shown on Day 2 of Universe) certainly gave us a lot of laughs. It Depends One of our GitHub Stars, Cassidy Williams , did an awesome video for Universe. She went back in time and spoke to her younger self. The catch, "it depends". Sadly (or luckily), most things in life 'depend' on something else. This funny and loveable interaction had us all laughing, and resonating! Fun fact, this one was filmed in one of the meeting rooms at GitHub. Yes, this is an actual room which exists... for meetings! DJs and coding At our last two Universe events, we've been lucky enough to have live performances from some DJ-coding extraordinaires. This year was no different. We had some amazing music produced for all our entertainment. Check out one of these awesome sets by DJ Dave. GitHub Universe You'll find plenty more videos, cuts, and the full Universe live streams on our GitHub YouTube channel . There are more being added, so make sure you like and subscribe so you don't miss out. What was your favourite Universe moment or feature announcement? GitHub Universe (2 Part Series) 1 This is the Way • GitHub Universe 2020 is here 2 What were your favourite GitHub Universe moments? 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Report Abuse Brian Douglas for GitHub Posted on Feb 25, 2021 • Edited on Mar 1, 2021 Repository Automation with GitHub Actions # github # githubactions # devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions My favorite thing to do with GitHub Actions by far is automating tedious tasks using webhooks. GitHub Actions is built on a few developer primitives for users to quickly ship integrations for their repos. Two of those primitives include their API and webhooks. Automating PR reviews. In a previous post, I shared how you can use the actions/github-script to automate events directly in your workflow YAML. 02:05 Automate your PR reviews with GitHub Action scripting in JavaScript Brian Douglas for GitHub ・ Feb 14 '21 #github #devops #githubactions #javascript Automating the creation of issues My team is made of many folks from around the world. To manage our team's weekly stand-ups, we use GitHub Actions to automate our issue's creation. on : schedule : - cron : 01 13 * * 0 name : Top 5 jobs : createAnIssue : name : Create an issue runs-on : ubuntu-latest steps : - uses : actions/checkout@v2 - name : Create an issue uses : bdougie/create-an-issue@e43b083ea71e22e77a81ffb4a55dacb2addb71ed env : GITHUB_TOKEN : ${{ secrets.GITHUB_TOKEN }} with : args : .github/ISSUE_TEMPLATE/TOP5.md Enter fullscreen mode Exit fullscreen mode Using this workflow makes our team syncs more impactful, with the same agenda being automated the generated issues. I encourage you to give it a try while your team is working remotely. JasonEtco / create-an-issue A GitHub Action for creating a new issue from a template file. Create an Issue Action A GitHub Action that creates a new issue using a template file. Usage This GitHub Action creates a new issue based on an issue template file. Here's an example workflow that creates a new issue any time you push a commit: # .github/workflows/issue-on-push.yml on : [push] name : Create an issue on push permissions : contents : read issues : write jobs : stuff : runs-on : ubuntu-latest steps : - uses : actions/checkout@v3 - uses : JasonEtco/create-an-issue@v2 env : GITHUB_TOKEN : ${{ secrets.GITHUB_TOKEN }} Enter fullscreen mode Exit fullscreen mode This reads from the .github/ISSUE_TEMPLATE.md file. This file should have front matter to help construct the new issue: --- title : Someone just pushed assignees : JasonEtco, matchai labels : bug, enhancement --- Someone just pushed, oh no! Here's who did it: {{ payload.sender.login }}. Enter fullscreen mode Exit fullscreen mode You'll notice that the above example has some {{ mustache }} variables. Your issue templates have… View on GitHub In addition to the above workflow, I have an action that closes the issue on a Friday, and another that pins the issue to the repo. There are countless ways to improve your developer workflow through actions. Let me know if you have examples in the comments. Always happy to learn. This is part of my 28 days of Actions series. To get notified of more GitHub Action tips, follow the GitHub organization right here on Dev. Learn how to build action with Node.js 01:23 Caching dependencies to speed up workflows in GitHub Actions Brian Douglas for GitHub ・ Feb 25 '21 #github #devops #node ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse GitHub Follow Let's build from here_ Celebrate 20 years of Git at Git Merge 2025 . Join developers from around the world this September in San Francisco. Get your ticket More from GitHub Speed Up Your CI/CD: ARM 64 Runners for GitHub Actions # programming # githubactions # cicd # devops Showcase your open source project at SCALE 🐧 Pasadena, CA · March 6-9, 2025 # github # linux # opensource Release Radar · September 2024: Major updates from the open source community # github # community # opensource # hacktoberfest 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://dev.to/scale_youtube/devoxx-inspiring-the-next-generations-3fl2 | Devoxx: Inspiring the Next Generations - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Scale YouTube Posted on Nov 5, 2025 Devoxx: Inspiring the Next Generations # career Inspiring the Next Generations At Devoxx Belgium 2025, Frank Delporte sits down with Cassandra Chin—developer and author of Raising Young Coders —to chat about fun ways to teach programming, her book (20% off with code APAUT on Springer) and how to get the next generation hooked on tech. Connect with her on LinkedIn: https://www.linkedin.com/in/cassandra-chin-developer/ He then catches up with Daniel De Luca, founder of Devoxx4Kids, who shares hands-on activities and creative ideas to spark curiosity in kids of all ages. Learn more on his LinkedIn: https://www.linkedin.com/in/danieldeluca/ Watch on YouTube Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Scale YouTube Follow Joined Aug 2, 2025 More from Scale YouTube NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
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https://go.opensource.org/microsoft | Microsoft Open Source skip to content Return to homepage Get involved Projects Ecosystem Our program Blog Jobs Open. Collaborative. Flexible. Open Source enables Microsoft products and services to bring choice, technology and community to our customers. Get involved Explore projects Pause animations and stop showing new graphics Pause Projects Some of the most popular developer tools, frameworks and experiences in the world are built around open communities. Here are a few featured Microsoft projects of note: Windows Terminal The new Windows Terminal and the original Windows console host, all in the same place! Open Education Analytics (OEA) Open Education Analytics collaborates with education systems across the world to develop modern data intelligence capabilities. Accessibility Insights Accessibility Insights is a suite of open source tools that help developers find and fix accessibility issues in Web, Windows and Android applications. Explore Microsoft projects Microsoft's communities Get involved We are building value together and welcome everyone to participate. Together, in the open, it's an exciting time to use technology to build hacks, apps, and services. Happening now Find a "good first issue" Featured projects Learn from our enterprise-scale approach Our program & tools We have worked to develop a strong open source program over the past decade, making it easy for every team at Microsoft to choose to use, contribute to, and release open source software. Many of our tools and approaches are available for you to learn from, too. Our program Our tools The ecosystem we support Innovate faster and more securely with open source on Azure Build on a highly secure cloud platform designed to protect your data and business assets, including proactive, comprehensive compliance coverage. Gain the flexibility to move your app anywhere. Operate seamlessly and elastically, on-premises, in hybrid or multicloud environments, or at the edge. Learn more about open source on Azure Community Resources We welcome you to our open communities. Please check out our Code of Conduct and one-time Contributor License Agreement to help us all participate with care. Microsoft's Open Source Code of Conduct Microsoft Contributor License Agreement Third-Party Source Disclosures Microsoft's Open Source Program Microsoft Open Source Open At Microsoft Open At Microsoft microsoft/opensource.microsoft.com Powered by Open Source and Microsoft Azure Employee sign-in Jobs Blog Code of Conduct California Consumer Privacy Act (CCPA) Opt-Out Icon Your Privacy Choices Privacy & Cookies Manage Cookies Terms Trademarks © 2026 Microsoft | 2026-01-13T08:49:36 |
https://www.linkedin.com/company/github | GitHub | LinkedIn Skip to main content LinkedIn Top Content People Learning Jobs Games Sign in Join for free GitHub Software Development San Francisco, CA 5,698,171 followers The home of software development See jobs Follow Discover all 6,024 employees Report this company Overview Jobs Life About us As the global home for all developers, GitHub is the complete AI-powered developer platform to build, scale, and deliver secure software. Over 100 million people, including developers from 90 of the Fortune 100 companies, use GitHub to build amazing things together across 330+ million repositories. With all the collaborative features of GitHub, it has never been easier for individuals and teams to write faster, better code. Website https://github.com External link for GitHub Industry Software Development Company size 501-1,000 employees Headquarters San Francisco, CA Type Privately Held Founded 2008 Products No more previous content GitHub GitHub Actions GitHub Advanced Security, Static Application Security Testing (SAST) Software GitHub Advanced Security Static Application Security Testing (SAST) Software GitHub Codespaces GitHub Copilot GitHub Enterprise GitHub Issues, Project Management Software GitHub Issues Project Management Software No more next content Locations Primary 88 Colin P Kelly Jr St San Francisco, CA 94107, US Get directions Employees at GitHub Edd Wilder-James Bradley Dunn Philip T. Clay Nelson See all employees Updates GitHub 5,698,171 followers 5h Report this post Join us for Open Source Friday featuring Daniel Roe, leader of the Nuxt core team! Discover the latest from the Nuxt project, get insights on frontend, web performance, and open source, plus live demos of Copilot and Agent Mode. Open Source Friday with Nuxt www.linkedin.com 52 2 Comments Like Comment Share GitHub 5,698,171 followers 13h Report this post Imagine if 94% of your compilation errors just … vanished. Your skin would clear. The laundry would be folded. ✨ A new study shows that’s exactly the percentage of LLM errors that are just type-check failures. Cassidy Williams explains why AI is settling the "typed vs. untyped" debate. ⬇️ https://lnkd.in/dw64HmUp Why AI is pushing developers toward typed languages https://github.blog 114 16 Comments Like Comment Share GitHub 5,698,171 followers 1d Report this post Built with Python. Powered by F1 data. 🐍 🏁 Tom Shaw 🤖 created F1 Race Replay, an impressive open source app that lets you visualize and replay full Grand Prix events. 😱 Watch our latest project spotlight. ✨ …more 271 12 Comments Like Comment Share GitHub 5,698,171 followers 2d Report this post We asked for WAVES. You delivered 700+ games, all free to play, with source code you can actually poke at. Meet the top 10 entries from Game Off 2025 🌊👇 https://lnkd.in/g3xtb6as …more 197 9 Comments Like Comment Share GitHub 5,698,171 followers 3d Report this post It's 2026. Where's your Spec Kit? 🧰 Instead of coding first and writing docs later, spec-driven development flips the script. Start with a spec, a clear contract for how your code should behave. This makes it easier for your AI agents to generate, test, and validate high-quality code. 🤖 Get started with this new open source toolkit. ⬇️ https://lnkd.in/gkcVQ5s6 Spec-driven development with AI: Get started with a new open source toolkit https://github.blog 188 9 Comments Like Comment Share GitHub 5,698,171 followers 3d Report this post Grab your favorite beverage and join us for a laid-back, community-powered yap-session about where we want open source to go this year. No slides, no demos...just unfiltered hopes, hot takes, and wild ideas for 2026. Bring your wishlist: better docs, greener CI, maintainer burnout fixes, AI that actually helps, or something we haven’t even imagined yet. Open Source Friday Special - Vision Board 2026 www.linkedin.com 416 315 Comments Like Comment Share GitHub 5,698,171 followers 1mo Edited Report this post What happens when you measure the right things? Join Jeff Keyes , Field CTO at Allstacks, as we explore how the Intelligence Engine and deep research agents help optimize engineering investments. We break down why most AI adoption falls short, tackle watermelon projects, and discuss how to measure what actually matters: alignment and ROI. Learn how to speak the language of business and eliminate bottlenecks across your development pipeline. Transforming Engineering Leadership with AI and Metrics www.linkedin.com 381 163 Comments Like Comment Share GitHub 5,698,171 followers 4d Report this post Engineers at GitHub spent a year testing Copilot coding agent to find the best workflow. Now they have an easy-to-remember acronym: WRAP. W – Write effective issues R – Refine your instructions A – Atomic tasks P – Pair with the coding agent Here's how to WRAP up your backlog. ⬇️ https://lnkd.in/d-hRfmHe WRAP up your backlog with GitHub Copilot coding agent https://github.blog 370 13 Comments Like Comment Share GitHub 5,698,171 followers 6d Report this post Join us for Rubber Duck Thursdays! A lighthearted and informal stream where we live code on some projects. We'll revisit the countdown projects that we made at the end of 2025 and explore how they've evolved into an extensible app. We'll also learn how we've set it up on GitHub to provide inspiration for your own projects! Rubber Duck Thursdays - It's time to build! www.linkedin.com 397 252 Comments Like Comment Share GitHub 5,698,171 followers 5d Report this post Don't wait for the next malware campaign to audit your security. 👀 We’ve outlined practical steps to lock down your supply chain now: ✅ Switch to phishing-resistant MFA (Passkeys/WebAuthn) ✅ Rotate and scope your tokens ✅ Review third-party access A little security cleanup today can save you from a massive headache tomorrow. 😅 https://lnkd.in/eYrsSZMs Strengthening supply chain security: Preparing for the next malware campaign https://github.blog 95 9 Comments Like Comment Share Join now to see what you are missing Find people you know at GitHub Browse recommended jobs for you View all updates, news, and articles Join now Affiliated pages Microsoft Software Development Redmond, Washington GitHub Brasil Software Development GitHub LATAM Software Development GitHub Education Software Development GitHub Enterprise Software Development GitHub Security Lab Software Development Student Developer Pack Show more affiliated pages Show fewer affiliated pages Similar pages Microsoft Software Development Redmond, Washington Google Software Development Mountain View, CA OpenAI Research Services San Francisco, CA GitLab IT Services and IT Consulting San Francisco, California Amazon Software Development Seattle, WA GeeksforGeeks Education NOIDA, G. 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https://dev.to/aaron_rose_0787cc8b4775a0 | Aaron Rose - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Aaron Rose Software engineer and technology writer at tech-reader.blog Location Dallas, TX Joined Joined on Aug 24, 2024 Personal website https://www.tech-reader.blog 8 Week Community Wellness Streak Consistency pays off! Be an active part of our community by posting at least 2 comments per week for 8 straight weeks. Earn the 16 Week Badge next. 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Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close More info about @aaron_rose_0787cc8b4775a0 Skills/Languages Python, Node.js, SQL, AWS, GCP, Azure, Oracle Cloud, LocalStack, Docker, Kubernetes, Linux, DevOps pipelines, IaC (Terraform, CloudFormation), CI/CD, serverless, Raspberry Pi, database administration Currently learning Advanced multi-cloud architecture patterns across AWS, GCP, Azure, and Oracle Cloud. Exploring infrastructure automation with Python and diving deep into LocalStack for local cloud development. Currently hacking on Multi-cloud infrastructure automation with Python, building DevOps pipelines that span multiple cloud providers, and maintaining a homelab that's equal parts Ubuntu servers and Raspberry Pi clusters. Available for * Cloud infrastructure discussions * Cloud tooling * Serverless patterns * Database design * Creative edge computing solutions * Everything Ubuntu * Everything Raspberry Pi Post 176 posts published Comment 79 comments written Tag 12 tags followed The Secret Life of JavaScript: Identity Aaron Rose Aaron Rose Aaron Rose Follow Jan 13 The Secret Life of JavaScript: Identity # javascript # coding # programming # software 1 reaction Comments Add Comment 3 min read Want to connect with Aaron Rose? Create an account to connect with Aaron Rose. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in The Secret Life of Go: Interfaces Aaron Rose Aaron Rose Aaron Rose Follow Jan 12 The Secret Life of Go: Interfaces # go # coding # programming # software 9 reactions Comments Add Comment 5 min read The Secret Life of Go: Testing Aaron Rose Aaron Rose Aaron Rose Follow Jan 10 The Secret Life of Go: Testing # go # coding # programming # softwaredevelopment 14 reactions Comments 3 comments 6 min read The Secret Life of Python: The Matryoshka Trap Aaron Rose Aaron Rose Aaron Rose Follow Jan 9 The Secret Life of Python: The Matryoshka Trap # python # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 4 min read The Secret Life of Python: The Dangerous Reflection Aaron Rose Aaron Rose Aaron Rose Follow Jan 8 The Secret Life of Python: The Dangerous Reflection # python # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: Illusions Aaron Rose Aaron Rose Aaron Rose Follow Jan 6 The Secret Life of JavaScript: Illusions # javascript # coding # programming # softwaredevelopment 9 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: Memories Aaron Rose Aaron Rose Aaron Rose Follow Jan 5 The Secret Life of JavaScript: Memories # javascript # coding # programming # softwaredevelopment 20 reactions Comments 3 comments 3 min read Happy New Year! 🎉 Aaron Rose Aaron Rose Aaron Rose Follow Jan 1 Happy New Year! 🎉 # python # 2026 # coding # strongcoffee 44 reactions Comments 20 comments 1 min read The Secret Life of JavaScript: Inheritance Aaron Rose Aaron Rose Aaron Rose Follow Dec 30 '25 The Secret Life of JavaScript: Inheritance # javascript # coding # programming # softwaredevelopment 15 reactions Comments 3 comments 3 min read The Secret Life of Go: Error Handling Aaron Rose Aaron Rose Aaron Rose Follow Dec 29 '25 The Secret Life of Go: Error Handling # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 6 min read The Secret Life of Go: Packages and Structure Aaron Rose Aaron Rose Aaron Rose Follow Dec 28 '25 The Secret Life of Go: Packages and Structure # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 5 min read Python by Structure: Precise Error Scoping with Try/Except/Else Aaron Rose Aaron Rose Aaron Rose Follow Dec 27 '25 Python by Structure: Precise Error Scoping with Try/Except/Else # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 2 min read Python by Structure: Decorators and the "Logic Envelope" Aaron Rose Aaron Rose Aaron Rose Follow Dec 27 '25 Python by Structure: Decorators and the "Logic Envelope" # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 2 min read Python by Structure: List Comprehensions and the "Single Action" Aaron Rose Aaron Rose Aaron Rose Follow Dec 24 '25 Python by Structure: List Comprehensions and the "Single Action" # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 3 min read Python by Structure: How the 'with' Statement Automates Resource Management Aaron Rose Aaron Rose Aaron Rose Follow Dec 24 '25 Python by Structure: How the 'with' Statement Automates Resource Management # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 3 min read The Secret Life of Python: The Truth About Nothing Aaron Rose Aaron Rose Aaron Rose Follow Dec 23 '25 The Secret Life of Python: The Truth About Nothing # python # coding # programming # software 6 reactions Comments 1 comment 4 min read The Secret Life of JavaScript: Asynchrony Aaron Rose Aaron Rose Aaron Rose Follow Dec 21 '25 The Secret Life of JavaScript: Asynchrony # javascript # coding # programming # software 9 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: The Power of Function Composition Aaron Rose Aaron Rose Aaron Rose Follow Dec 20 '25 The Secret Life of JavaScript: The Power of Function Composition # javascript # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 5 min read The Secret Life of Go: Atomic Operations Aaron Rose Aaron Rose Aaron Rose Follow Dec 19 '25 The Secret Life of Go: Atomic Operations # go # coding # programming # softwaredevelopment 8 reactions Comments 1 comment 6 min read The Secret Life of Python: The Infinite Copy Aaron Rose Aaron Rose Aaron Rose Follow Dec 18 '25 The Secret Life of Python: The Infinite Copy # python # coding # programming # software 15 reactions Comments 6 comments 4 min read The Secret Life of Python: The Statue in the Memory Aaron Rose Aaron Rose Aaron Rose Follow Dec 17 '25 The Secret Life of Python: The Statue in the Memory # python # coding # programming # softwaredevelopment 11 reactions Comments 2 comments 4 min read The Secret Life of Python: The Myth of the Box Aaron Rose Aaron Rose Aaron Rose Follow Dec 16 '25 The Secret Life of Python: The Myth of the Box # python # coding # programming # softwaredevelopment 11 reactions Comments 1 comment 4 min read The Secret Life of JavaScript: Currying vs. Partial Application Aaron Rose Aaron Rose Aaron Rose Follow Dec 15 '25 The Secret Life of JavaScript: Currying vs. Partial Application # javascript # coding # programming # softwaredevelopment 13 reactions Comments 2 comments 5 min read Python by Structure: List Comprehensions and Their Hidden Complexity Aaron Rose Aaron Rose Aaron Rose Follow Dec 14 '25 Python by Structure: List Comprehensions and Their Hidden Complexity # python # coding # programming # software 6 reactions Comments Add Comment 7 min read The Secret Life of JavaScript: Understanding Closures Aaron Rose Aaron Rose Aaron Rose Follow Dec 12 '25 The Secret Life of JavaScript: Understanding Closures # javascript # coding # programming # softwaredevelopment 38 reactions Comments 5 comments 10 min read The Secret Life of JavaScript: Understanding Prototypes Aaron Rose Aaron Rose Aaron Rose Follow Dec 11 '25 The Secret Life of JavaScript: Understanding Prototypes # javascript # coding # programming # softwaredevelopment 29 reactions Comments 7 comments 11 min read The Secret Life of Python: The Import System Aaron Rose Aaron Rose Aaron Rose Follow Dec 10 '25 The Secret Life of Python: The Import System # python # coding # programming # software 7 reactions Comments 3 comments 19 min read The Secret Life of Go: Mutexes and Synchronization Aaron Rose Aaron Rose Aaron Rose Follow Dec 9 '25 The Secret Life of Go: Mutexes and Synchronization # go # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 10 min read The Secret Life of JavaScript: Understanding 'this' Aaron Rose Aaron Rose Aaron Rose Follow Dec 8 '25 The Secret Life of JavaScript: Understanding 'this' # javascript # coding # programming # software 12 reactions Comments 5 comments 11 min read The Secret Life of JavaScript: Let, Const, and Why Variables Are Complicated Aaron Rose Aaron Rose Aaron Rose Follow Dec 8 '25 The Secret Life of JavaScript: Let, Const, and Why Variables Are Complicated # javascript # coding # programming # software 43 reactions Comments 15 comments 9 min read Python by Structure: Context Managers and the 'with' Statement Aaron Rose Aaron Rose Aaron Rose Follow Dec 7 '25 Python by Structure: Context Managers and the 'with' Statement # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 6 min read The Secret Life of Python: Metaclasses - Classes That Make Classes Aaron Rose Aaron Rose Aaron Rose Follow Dec 6 '25 The Secret Life of Python: Metaclasses - Classes That Make Classes # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 17 min read The Secret Life of Go: Goroutines and Channels Aaron Rose Aaron Rose Aaron Rose Follow Dec 5 '25 The Secret Life of Go: Goroutines and Channels # go # coding # programming # software 6 reactions Comments 1 comment 9 min read Python by Structure: Return Value Transformations with Decorators Aaron Rose Aaron Rose Aaron Rose Follow Dec 4 '25 Python by Structure: Return Value Transformations with Decorators # python # coding # programming # softwaredevelopment 3 reactions Comments 3 comments 4 min read The Secret Life of Python: super() and the Method Resolution Order Aaron Rose Aaron Rose Aaron Rose Follow Dec 3 '25 The Secret Life of Python: super() and the Method Resolution Order # python # coding # programming # software 21 reactions Comments 4 comments 18 min read The Secret Life of Go: Interfaces Aaron Rose Aaron Rose Aaron Rose Follow Dec 2 '25 The Secret Life of Go: Interfaces # go # coding # programming # softwaredevelopment 7 reactions Comments Add Comment 8 min read Python by Structure: Property Decorators and Managed Attributes Aaron Rose Aaron Rose Aaron Rose Follow Dec 1 '25 Python by Structure: Property Decorators and Managed Attributes # python # coding # programming # software 4 reactions Comments 1 comment 5 min read The Secret Life of Go: Structs Aaron Rose Aaron Rose Aaron Rose Follow Dec 1 '25 The Secret Life of Go: Structs # go # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 8 min read The Secret Life of Go: Maps Aaron Rose Aaron Rose Aaron Rose Follow Nov 29 '25 The Secret Life of Go: Maps # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 7 min read The Secret Life of Go: Arrays and Slices Aaron Rose Aaron Rose Aaron Rose Follow Nov 28 '25 The Secret Life of Go: Arrays and Slices # go # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 8 min read Python by Structure: How Decorators Transform Classes Aaron Rose Aaron Rose Aaron Rose Follow Nov 27 '25 Python by Structure: How Decorators Transform Classes # python # coding # programming # softwaredevelopment 3 reactions Comments 1 comment 5 min read The Secret Life of Python: Attribute Lookup Secrets Aaron Rose Aaron Rose Aaron Rose Follow Nov 27 '25 The Secret Life of Python: Attribute Lookup Secrets # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 16 min read The Secret Life of Go: Functions Aaron Rose Aaron Rose Aaron Rose Follow Nov 25 '25 The Secret Life of Go: Functions # go # coding # programming # softwaredevelopment 6 reactions Comments 1 comment 8 min read The Secret Life of Go: Variables & Types Aaron Rose Aaron Rose Aaron Rose Follow Nov 25 '25 The Secret Life of Go: Variables & Types # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 10 min read The Secret Life of Go Aaron Rose Aaron Rose Aaron Rose Follow Nov 22 '25 The Secret Life of Go # go # coding # programming # softwaredevelopment 13 reactions Comments 4 comments 10 min read Python by Structure - Class-Based Decorators That Remember Aaron Rose Aaron Rose Aaron Rose Follow Nov 21 '25 Python by Structure - Class-Based Decorators That Remember # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 3 min read The Secret Life of Python: Bytecode Secrets - What Python Really Runs Aaron Rose Aaron Rose Aaron Rose Follow Nov 20 '25 The Secret Life of Python: Bytecode Secrets - What Python Really Runs # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 26 min read Python by Structure: Decorator Chains and Execution Order Aaron Rose Aaron Rose Aaron Rose Follow Nov 20 '25 Python by Structure: Decorator Chains and Execution Order # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 5 min read The Secret Life of Python: MRO Secrets - The Diamond Problem Solved Aaron Rose Aaron Rose Aaron Rose Follow Nov 19 '25 The Secret Life of Python: MRO Secrets - The Diamond Problem Solved # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 24 min read Python by Structure: Match Statements and Pattern Guards Aaron Rose Aaron Rose Aaron Rose Follow Nov 19 '25 Python by Structure: Match Statements and Pattern Guards # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 6 min read The Secret Life of Python: GIL Secrets - Python's Threading Mystery Aaron Rose Aaron Rose Aaron Rose Follow Nov 18 '25 The Secret Life of Python: GIL Secrets - Python's Threading Mystery # python # coding # programming # softwaredevelopment 5 reactions Comments 2 comments 21 min read Python by Structure: The Walrus Operator - Assignment Where You Need It Aaron Rose Aaron Rose Aaron Rose Follow Nov 18 '25 Python by Structure: The Walrus Operator - Assignment Where You Need It # python # coding # programming # softwaredevelopment 10 reactions Comments Add Comment 4 min read Python by Structure: Context Managers and the With Statement Aaron Rose Aaron Rose Aaron Rose Follow Nov 16 '25 Python by Structure: Context Managers and the With Statement # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 4 min read Python by Structure: Generator Delegation with Yield From Aaron Rose Aaron Rose Aaron Rose Follow Nov 16 '25 Python by Structure: Generator Delegation with Yield From # python # coding # programming # softwaredevelopment Comments Add Comment 4 min read The Secret Life of Python: Metaclass Secrets - Classes That Create Classes Aaron Rose Aaron Rose Aaron Rose Follow Nov 15 '25 The Secret Life of Python: Metaclass Secrets - Classes That Create Classes # python # coding # programming # software Comments Add Comment 13 min read Python by Structure: The For/Else Block You Didn't Know Existed Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 Python by Structure: The For/Else Block You Didn't Know Existed # python # coding # programming # softwaredevelopment 5 reactions Comments 5 comments 3 min read Python by Structure: The Try/Else Block You're Not Using Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 Python by Structure: The Try/Else Block You're Not Using # python # coding # programming # software 6 reactions Comments Add Comment 3 min read The Secret Life of Python: Descriptor Secrets - How Properties Really Work Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 The Secret Life of Python: Descriptor Secrets - How Properties Really Work # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 16 min read The Secret Life of Python: Context Manager Secrets - The Magic of `with` Aaron Rose Aaron Rose Aaron Rose Follow Nov 13 '25 The Secret Life of Python: Context Manager Secrets - The Magic of `with` # python # coding # programming # software 4 reactions Comments Add Comment 14 min read The Secret Life of Python: Decorator Secrets - Functions That Wrap Functions Aaron Rose Aaron Rose Aaron Rose Follow Nov 12 '25 The Secret Life of Python: Decorator Secrets - Functions That Wrap Functions # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 14 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.algolia.com/fr/products/?utm_cta=aioverview | Plateforme et produits : API de recherche, API de recommandations et autres fonctionnalités. | Algolia Niket --> Deutsch English français News DevCon2025 | October 1-2 Learn more Algolia Partners Support Login Logout Algolia mark white Algolia logo white Products Search Show users what they're looking for with AI-driven resuts. Search Show users what they're looking for with AI-driven resuts. Recommendations Use behavioral cues to drive higher engagement. Recommendations Use behavioral cues to drive higher engagement. Personalization Show each user what they need across their journey. Personalization Show each user what they need across their journey. Analytics All your insights in one dashboard. Analytics All your insights in one dashboard. Browse Move customers down the funnel with curated category pages. Browse Move customers down the funnel with curated category pages. Agent Studio Create, test, and deploy AI agents, fast. 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We got you covered! Brand guidelines Download logo pack Nos solutions Une recherche par IA qui montre aux utilisateurs ce dont ils ont besoin Améliorez le parcours de vos utilisateurs grâce à des solutions de recherche, de navigation et de recommandations. Demandez une démo Commencez gratuitement Make every interaction smarter with AI retrieval Every modern AI experience depends on one core capability: finding the right information at the right moment. That process is retrieval. Retrieval is how search engines, LLMs, and AI agents locate the data they need to answer questions, generate content, or take action. When retrieval is strong, these experiences behave intelligently; when it isn’t, they guess. Les trois caractéristiques uniques d’Algolia Facilité d’utilisation Implémentez un scénario de test en quelques minutes grâce à nos API. 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Mario Rodriguez · @mariorod October 29, 2024 | Updated November 5, 2024 | 13 minutes Share: Welcome to your flow state. This year marks our tenth GitHub Universe—and one theme has remained constant: our focus on developers and the developer experience. Over 10 years, that developer experience has evolved from inventing the pull request to building the world’s most widely adopted AI coding tool, GitHub Copilot. Today, our platform serves more than 100 million developers, and through the power of this interconnected community combined with generative AI, we are enabling every developer to build, release, scale, and secure software rapidly. We have a lot to cover. As developers, we’re not known for being patient. So, let’s jump in. Introducing new, powerful AI-native experiences The best model for the task: the power of developer choice We are bringing developer choice to GitHub Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview and o1-mini. These new models will be rolling out—first in Copilot Chat, with OpenAI o1-preview and o1-mini available now, Claude 3.5 Sonnet rolling out progressively over the next week, and Google’s Gemini 1.5 Pro in the coming weeks. From Copilot Workspace to multi-file editing to code review, security autofix, and the CLI, we will bring multi-model choice across many of GitHub Copilot’s surface areas and functions soon. Whether it’s in VS Code or on GitHub.com, individual developers can now decide which models work best for them, while organizations and enterprises have full control over which models they enable for their team. Try multi-model Copilot today ! AI-native = GitHub Copilot Workspace + Code Review + Copilot Autofix With Copilot Workspace in pull requests, you can rapidly refine, validate, and land Copilot-generated code suggestions coming from Copilot code review, Copilot Autofix, and third-party Copilot Extensions. Get your pull requests “ready to merge” faster than ever. Learn about GitHub Copilot Workspace and Copilot Code Reviews > Bring your ideas to life with GitHub Spark It starts with an idea. It always does. When we’re kids, we have thousands of them. Many of them are silly. Some of them are crazy. Today, we are giving you a new product to try all of them. We call it GitHub Spark—it’s powered by natural language, and it sets the stage for our vision to help 1 billion people become developers. This is about fun and personal software, not about enterprise productivity apps. With live history, previews, and the ability to edit code directly, GitHub Spark allows you to create micro apps that take that crazy small, fun idea and bring it to life. Go and play… Learn about the GitHub Spark technical preview > Increasing your productivity with the Copilot-powered developer platform Momentum is our oxygen. And that is why we are announcing a wide range of improvements to accelerate how you build, release, scale, and secure software. Get ready to unlock your creativity. Multi-file editing in GitHub Copilot on VS Code Edit multiple lines and files with Copilot in VS Code, applying edits directly as you iterate on your codebase with natural language. Complex changes? Tab, tab, and apply. Learn about GitHub Copilot multi-file editing in VS Code > GitHub Copilot code reviews Get Copilot-powered feedback on your code as soon as you create a pull request. That means no more waiting for hours to start the feedback loop. Configure rules for your team, and keep quality high with the help of your trusted AI-pair programmer. We’ll support C#, Java, JavaScript, Python, TypeScript, Ruby, Go, and Markdown at launch. Learn about GitHub Copilot code reviews > Raising the quality of your Copilot-powered experiences These updates enhance your development workflow with new features like multi-model choice, improved code completion, implicit agent selection in GitHub Copilot Chat, better support for C++ and .NET, and expanded availability in Xcode and Windows Terminal. READ MORE ⤵️ Multi-model choice and access to OpenAI’s o1 model in GitHub Copilot . Toggle between different AI models during conversations, seamlessly switching from explaining APIs or generating boilerplate code to designing complex algorithms or analyzing logic bugs. Copilot users now have access to the o1-preview and o1-mini models in Copilot Chat and GitHub Models. Custom instructions . Specify custom instructions to personalize Copilot Chat responses in VS Code and Visual Studio, based on your preferred tools, organizational knowledge, and coding conventions. Improvements to code completion and chat quality. Enjoy enhanced contextual performance along with a preview of a new debugging experience initiated through Copilot Chat. Selection of agents in Copilot Chat . Copilot Chat in VS Code can automatically invoke internal and external agents—such as @workspace, @github, and other installed Copilot extensions—to provide more relevant responses. Better language support for C++ and .NET. Improved C++ completion quality in VS Code and Visual Studio with more relevant context. Plus, Copilot Chat now has increased performance in project-specific properties for C++ and .NET in Visual Studio. GitHub Copilot for Xcode . GitHub Copilot code completion is now available in Xcode, enabling macOS and iOS developers to leverage its capabilities. GitHub Copilot in Windows Terminal . Interact with GitHub Copilot directly from the Windows Terminal through a chat-based interface. Enhancing how you work in your IDE We’re introducing several updates to GitHub Copilot to boost productivity across various IDEs, including new @github skills, error explanations, and improved code assistance. READ MORE ⤵️ Improved skills and search in Copilot Chat. Search across GitHub for commits, issues, pull requests, repositories, and releases directly from Copilot Chat in VS Code. Explain and fix C++ and C# errors in Visual Studio. Use GitHub Copilot to understand and resolve C++ and C# errors within Visual Studio. Quick info on C++ and C# in Visual Studio. Instantly learn about C++ and C# symbols by hovering to invoke Copilot in the Quick Info dialog. Improved code referencing. Easily see if a code suggestion matches public code, including file locations and licensing information. Bing integration in Copilot Chat . Search with Bing directly from Copilot Chat in VS Code and Visual Studio for Individual and Business users. .NET test debugging. Debug .NET code tests seamlessly within Visual Studio. Copilot upgrade assistant for Java We are excited about this one. This new preview uses an agentic workflow designed to autonomously handle upgrading your Java application’s runtime and optional dependencies like Spring Boot and JUnit. If you have gone through projects like this before, you know they’re time consuming and expensive. With this assistant, Copilot analyzes your project, proposes an upgrade plan, transforms your code, and fixes issues through a dynamic build-and-fix loop. The assistant also puts you in the pilot’s seat to address errors and make fixes. Learn more about the upgrade assistant for Java technical preview > Simplifying your workflows with GitHub Copilot Extensions Whether you’re an individual developer looking to streamline your workflow or an organization aiming to integrate proprietary tools, GitHub Copilot Extensions now offers a platform to make that happen and to share your creations on the GitHub Marketplace. READ MORE ⤵️ GitHub Copilot Extensions . Extend GitHub Copilot with ready-to-use extensions, build your own, and get access to third-party applications and internal systems for a more personalized experience. Copilot Extensions in GitHub Mobile . You can now access extensions in Copilot Chat while on the go, right from your phone. GitHub Copilot for Azure . Deploy and manage Azure services, find and deploy application templates, and diagnose and troubleshoot application issues. Making it easy to build generative AI applications with GitHub Models GitHub Models makes it simple to use, compare, experiment, and build with AI models from OpenAI, Cohere, Microsoft, Mistral, and more. Starting today, developers and AI engineers can access new capabilities on GitHub Models, including side-by-side model comparison, support for multi-modal models, the ability to save and share prompts and parameters, and new cookbooks and SDK support in GitHub Codespaces. GitHub ❤️ AI engineers There’s no more waitlist, so try GitHub Models out right away. GitHub Models CLI extension View the full catalog of GitHub Models and run inference against them—even use models in shell scripts and one-liner demos—straight from your terminal. Learn more about GitHub Models > ⭐️ Explore what’s new with GitHub Copilot ⭐️ A more secure developer experience where found means fixed Security should never be a bottleneck for developers. That’s why we’re making it part of the development process with GitHub Copilot Autofix. Our goal is simple: when a vulnerability is found, it gets fixed—fast. Copilot Autofix for open source Improve the security of your open source projects with Copilot Autofix, dramatically reducing the time to fix vulnerabilities. And, as always, it is free for our open source community. Learn about Copilot Autofix for open source > Triage a thousand alerts at a time with security campaigns Create security campaigns to remediate vulnerabilities at an unprecedented scale, triaging up to thousands of alerts at a time—filtered by type, severity, repository, and team—with suggested fixes and explanations powered by Copilot Autofix. Find out about security campaigns with Copilot Autofix > More secure code from the IDE to production We know developers are often on the front lines of security. That’s why we want to make it easier for you to write more secure code from start to finish with Copilot Autofix, our Copilot-powered vulnerability remediation tool, now reaching further into your workflows and code. READ MORE ⤵️ Improved CodeQL coverage. Address security debt and historical CodeQL alerts with Copilot-generated fixes that cover more than 90% of alert types in JavaScript, Typescript, Java, Python, Ruby, C#, C/C++, and Go. Copilot secret scanning . Copilot secret scanning, which detects generic passwords using AI, offers greater precision for unstructured credentials that can cause security breaches if exposed. Over 350,000 repositories have already enabled this password detection. New partner integrations . Integrate Copilot Autofix natively with supported partner code scanning tools of your choice, starting with ESLint, JFrog SAST, and Black Duck’s Polaris™ platform (powered by Coverity®). Copilot Autofix for Dependabot . Get natural language explanations and pull request code suggestions to update between major versions of dependencies seamlessly. ⭐️ Explore what’s new with GitHub Advanced Security ⭐️ Enterprise-grade experiences that put you in control From powerful new GitHub Actions runners to enhanced project management tools (and a whole lot more), we’re investing in increasing your iteration velocity while keeping you compliant at every step. Now in the European Union: Data residency for GitHub Enterprise Cloud With data residency for GitHub Enterprise Cloud in the European Union, you can store your code and repository data with enhanced management, and unique namespaces. Learn about data residency in GitHub Enterprise Cloud > 👋 from GitHub Issues We continue to advance planning and tracking capabilities with sub issues, issue types, advanced search, and increased project item limits. Explore the new GitHub Issues > Improved controls for governance and compliance We know maintaining governance and compliance is critical for you—and definitely for your administrators. That’s why we’re introducing new features to give admins more control over user management, repository policies, and security workflows. This is governance at scale. And happy admins mean happy devs. READ MORE ⤵️ Bring your own identity provider to Enterprise Managed Users (EMUs). Use the SSO and SCIM providers of your choice, separate from one another, for a more flexible approach to user life cycle management. Prevent commits that include specific changes with push rulesets . Limit updates to sensitive files like actions workflows and help enforce code hygiene by keeping unwanted objects out of your repositories with push rulesets. Enterprise repository policies. Manage repository lifecycles with granular governance of repository configurations across your enterprise and its organizations. Enterprise custom repository properties. Create and manage custom repository properties across your organizations, and promote existing organization properties to the enterprise. Immutable GitHub Actions . Secure your supply chain with semantically versioned, immutable actions stored in GitHub Packages. Create custom organization roles. Use repository-level permissions and roles at the organizational-level across all repositories in an organization. GitHub Apps for your organization . Create enterprise-owned, internal-visibility GitHub Apps for installation across your organizations. PATs and fine-grained PATs lifetime requirements policy . Set maximum lifetime requirements for Personal Access Tokens (PATs) that access enterprise resources. The new GitHub Enterprise Trust Center . Find information on key topics for your enterprise like privacy, security, and data protection all in one place. More compute resources and better insights for your workflows No matter what you’re doing, compute power matters—and so do performance and API insights. That’s why we’re introducing new Arm64-powered runners and improving performance tracking across your workflows and CI/CD pipelines on GitHub Actions and API activity on GitHub. READ MORE ⤵️ Arm64 GitHub-hosted runners . Build, test, and deploy on Arm64 GitHub-hosted runners on GitHub Free plans to unify your CI/CD workflow and optimize compute costs. This feature will be released broadly in early 2025. Performance metrics for GitHub Actions . Monitor and optimize your GitHub Actions workflows and job performance to eliminate inefficiencies. API insights . Investigate and resolve API rate-limiting of your GitHub integrations via an in-product dashboard with insights to help monitor API activity. ⭐️ Explore what’s new with GitHub Enterprise ⭐️ Your multi-model, AI-native developer experience starts today Thank you for building with GitHub. If there’s one takeaway we want you to leave with, it’s that software development has never been more exciting. Today we’re giving you choices with AI models from OpenAI, Anthropic, and Google—so you can pick the right tool for the task. This choice is also powering AI-native developer experiences designed to enable new ways of thinking and coding. With GitHub Copilot Workspace and GitHub Spark, natural language is taking center stage and powering a future where we merge the developer canvas with powerful agents that simplify your workflows and unlock your creativity at scale. This is the innovation we need to foster the next 1 billion developers, and help them continue to accelerate human progress. To GitHub Universe, happy birthday. 🎉 And to our global developer community, we ❤️ you, and we’ll see you all again next year. Let’s build from here—together. Want the most recent updates? Stay informed about the latest in software development by subscribing to the GitHub Changelog. Explore the Changelog > Tags: GitHub Advanced Security GitHub Copilot GitHub Enterprise GitHub Universe Written by Mario Rodriguez @mariorod Mario Rodriguez leads the GitHub Product team as Chief Product Officer. His core identity is being a learner and his passion is creating developer tools—so much so that he has spent the last 20 years living that mission in leadership roles across Microsoft and GitHub. Mario most recently oversaw GitHub’s AI strategy and the GitHub Copilot product line, launching and growing Copilot across thousands of organizations and millions of users. Mario spends time outside of GitHub with his wife and two daughters. He also co-chairs and founded a charter school in an effort to progress education in rural regions of the United States. GitHub Advanced Security GitHub Copilot GitHub Enterprise GitHub Universe Table of Contents Introducing new, powerful AI-native experiences Increasing your productivity with the Copilot-powered developer platform A more secure developer experience where found means fixed Enterprise-grade experiences that put you in control Your multi-model, AI-native developer experience starts today More on GitHub Advanced Security GitHub found 39M secret leaks in 2024. Here's what we're doing to help Every minute, GitHub blocks several secrets with push protection—but secret leaks still remain one of the most common causes of security incidents. Learn how GitHub is making it easier to protect yourself from exposed secrets, including today’s launches of standalone Secret Protection, org-wide scanning, and better access for teams of all sizes. Erin Havens Finding leaked passwords with AI: How we built Copilot secret scanning Passwords are notoriously difficult to detect with conventional programming approaches. AI can help us find passwords better because it understands context. This blog post will explore the technical challenges we faced with building the feature and the novel and creative ways we solved them. Ashwin Mohan & Courtney Claessens Related posts News & insights The future of AI-powered software optimization (and how it can help your team) We envision the future of AI-enabled tooling to look like near-effortless engineering for sustainability. We call it Continuous Efficiency. Paull Young News & insights Let’s talk about GitHub Actions A look at how we rebuilt GitHub Actions’ core architecture and shipped long-requested upgrades to improve performance, workflow flexibility, reliability, and everyday developer experience. Ben De St Paer-Gotch Company news GitHub Availability Report: November 2025 In November, we experienced three incidents that resulted in degraded performance across GitHub services. Jakub Oleksy Explore more from GitHub Docs Everything you need to master GitHub, all in one place. Go to Docs GitHub Build what’s next on GitHub, the place for anyone from anywhere to build anything. Start building Customer stories Meet the companies and engineering teams that build with GitHub. Learn more GitHub Universe 2024 Get tickets to the 10th anniversary of our global developer event on AI, DevEx, and security. Get tickets We do newsletters, too Discover tips, technical guides, and best practices in our biweekly newsletter just for devs. Your email address * Your email address Subscribe Yes please, I’d like GitHub and affiliates to use my information for personalized communications, targeted advertising and campaign effectiveness. See the GitHub Privacy Statement for more details. 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https://ai.google.dev/gemini-api/docs/pricing#:~:text=Free%20Tier%20Paid%20Tier%2C%20per,then%20%2435%20%2F%201%2C000%20requests | Gemini Developer API pricing | Gemini API | Google AI for Developers Skip to main content / English Deutsch Español – América Latina Français Indonesia Italiano Polski Português – Brasil Shqip Tiếng Việt Türkçe Русский עברית العربيّة فارسی हिंदी বাংলা ภาษาไทย 中文 – 简体 中文 – 繁體 日本語 한국어 Get API key Cookbook Community Sign in Docs API reference Gemini API Docs API reference Get API key Cookbook Community Get started Overview Quickstart API keys Libraries Interactions API Models Gemini Gemini 3 Nano Banana image generation Veo video generation Lyria music generation Imagen image generation Embeddings Robotics Pricing Rate limits Core capabilities Text Image Image generation 🍌 Image understanding Video Documents Speech and audio Speech generation Audio understanding Thinking and thought signatures Thinking Thought signatures Structured outputs Function calling Long context Tools and agents Overview Deep Research Google Search Google Maps Code execution URL context Computer Use File Search Live API Get started Capabilities Tool use Session management Ephemeral tokens Guides Batch API File input Input methods Files API Context caching OpenAI compatibility Media resolution Token counting Prompt engineering Logs and datasets Get started with logs Data logging and sharing Safety Safety settings Safety guidance Open-Source frameworks LangChain & LangGraph CrewAI LlamaIndex Vercel AI SDK Resources Migrate to Gen AI SDK Release notes Deprecations API troubleshooting Billing info Partner and library integrations Google AI Studio Quickstart Vibe code in Build mode Try out LearnLM Troubleshooting Access for Workspace users Google Cloud Platform VertexAI Gemini API OAuth authentication Policies Terms of service Available regions Additional usage polices Home Gemini API Docs Gemini Developer API pricing We have updated our Terms of Service . Start building free of charge with generous limits, then scale up with pay-as-you-go pricing for your production ready applications. Free For developers and small projects getting started with the Gemini API. check_circle Limited access to certain models check_circle Free input & output tokens check_circle Google AI Studio access check_circle Content used to improve our products * Get started for Free Paid For production applications that require higher volumes and advanced features. check_circle Higher rate limits for production deployments check_circle Access to Context caching check_circle Batch API (50% cost reduction) check_circle Access to Google's most advanced models check_circle Content not used to improve our products * Upgrade to Paid Enterprise For large-scale deployments with custom needs for security, support, and compliance, powered by Vertex AI . check_circle All features in Paid, plus optional access to: check_circle Dedicated support channels check_circle Advanced security & compliance check_circle Provisioned throughput check_circle Volume-based discounts (based on usage) check_circle ML ops, model garden and more Contact Sales Gemini 3 Pro Preview gemini-3-pro-preview Try it in Google AI Studio The best model in the world for multimodal understanding, and our most powerful agentic and vibe-coding model yet. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $2.00, prompts $4.00, prompts > 200k tokens Output price (including thinking tokens) Not available $12.00, prompts $18.00, prompts > 200k Context caching price Not available $0.20, prompts $0.40, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 5,000 prompts per month (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00, prompts $2.00, prompts > 200k tokens Output price (including thinking tokens) Not available $6.00, prompts $9.00, prompts > 200k Context caching price Not available $0.20, prompts $0.40, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 1,500 RPD (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No * A customer-submitted request to Gemini may result in one or more queries to Google Search. You will be charged for each individual search query performed. ** Gemini 3 billing for Grounding with Google Search will start January 5, 2026. Gemini 3 Flash Preview gemini-3-flash-preview Try it in Google AI Studio Our most intelligent model built for speed, combining frontier intelligence with superior search and grounding. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $3.00 Context caching price Free of charge $0.05 (text / image / video) $0.10 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 5,000 prompts per month (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.25 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.50 Context caching price Not available Same as Standard, Batch pricing not yet implemented $0.05 (text / image / video) $0.10 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 1,500 RPD (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No * A customer-submitted request to Gemini may result in one or more queries to Google Search. You will be charged for each individual search query performed. ** Gemini 3 billing for Grounding with Google Search will start January 5, 2026. Gemini 3 Pro Image Preview 🍌 gemini-3-pro-image-preview Try it in Google AI Studio Our native image generation model, optimized for speed, flexibility, and contextual understanding. Text input and output is priced the same as Gemini 3 Pro . Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $2.00 (text/image), equivalent to $0.0011 per image * Output price Not available $12.00 (text and thinking) $120.00 (images) equivalent to $0.134 per 1K/2K image ** and $0.24 per 4K image ** Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00 (text), $0.0006 (image) * Output price Not available $6.00 (text and thinking) $0.067 per 1K/2K image ** $0.12 per 4K image ** Used to improve our products Yes No * Image input is set at 560 tokens or $0.0011 per image. ** Image output is priced at $120 per 1,000,000 tokens. Output images from 1024x1024px (1K) and up to 2048x2048px (2K) consume 1120 tokens and are equivalent to $0.134 per image. Output images up to 4096x4096px (4K) consume 2000 tokens and are equivalent to $0.24 per image. Gemini 2.5 Pro gemini-2.5-pro Try it in Google AI Studio Our state-of-the-art multipurpose model, which excels at coding and complex reasoning tasks. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $1.25, prompts $2.50, prompts > 200k tokens Output price (including thinking tokens) Free of charge $10.00, prompts $15.00, prompts > 200k Context caching price Not available $0.125, prompts $0.25, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available 10,000 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.625, prompts $1.25, prompts > 200k tokens Output price (including thinking tokens) Not available $5.00, prompts $7.50, prompts > 200k Context caching price Not available $0.125, prompts $0.25, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash gemini-2.5-flash Try it in Google AI Studio Our first hybrid reasoning model which supports a 1M token context window and has thinking budgets. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.25 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash Preview gemini-2.5-flash-preview-09-2025 Try it in Google AI Studio The latest model based on the 2.5 Flash model. 2.5 Flash Preview is best for large scale processing, low-latency, high volume tasks that require thinking, and agentic use cases. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.25 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Gemini 2.5 Flash-Lite gemini-2.5-flash-lite Try it in Google AI Studio Our smallest and most cost effective model, built for at scale usage. Standard Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Free of charge $0.10 (text / image / video) $0.30 (audio) Output price (including thinking tokens) Free of charge $0.40 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash RPD) 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Not available $0.05 (text / image / video) $0.15 (audio) Output price (including thinking tokens) Not available $0.20 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash-Lite Preview gemini-2.5-flash-lite-preview-09-2025 Try it in Google AI Studio The latest model based on Gemini 2.5 Flash lite optimized for cost-efficiency, high throughput and high quality. Standard Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Free of charge $0.10 (text / image / video) $0.30 (audio) Output price (including thinking tokens) Free of charge $0.40 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash RPD) 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Not available $0.05 (text / image / video) $0.15 (audio) Output price (including thinking tokens) Not available $0.20 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Gemini 2.5 Flash Native Audio (Live API) gemini-2.5-flash-native-audio-preview-12-2025 Try it in Google AI Studio Our Live API native audio models optimized for higher quality audio outputs with better pacing, voice naturalness, verbosity, and mood. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text) $3.00 (audio / video) Output price (including thinking tokens) Free of charge $2.00 (text) $12.00 (audio) Used to improve our products Yes No Gemini 2.5 Flash Image 🍌 gemini-2.5-flash-image Try it in Google AI Studio Our native image generation model, optimized for speed, flexibility, and contextual understanding. Text input and output is priced the same as 2.5 Flash . Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.30 (text / image) Output price Not available $0.039 per image* Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image) Output price Not available $0.0195 per image* Used to improve our products Yes No [*] Image output is priced at $30 per 1,000,000 tokens. Output images up to 1024x1024px consume 1290 tokens and are equivalent to $0.039 per image. Gemini 2.5 Flash Preview TTS gemini-2.5-flash-preview-tts Try it in Google AI Studio Our 2.5 Flash text-to-speech audio model optimized for price-performant, low-latency, controllable speech generation. Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text) Output price Free of charge $10.00 (audio) Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.25 (text) Output price Not available $5.00 (audio) Used to improve our products Yes No Gemini 2.5 Pro Preview TTS gemini-2.5-pro-preview-tts Try it in Google AI Studio Our 2.5 Pro text-to-speech audio model optimized for powerful, low-latency speech generation for more natural outputs and easier to steer prompts. Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00 (text) Output price Not available $20.00 (audio) Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.50 (text) Output price Not available $10.00 (audio) Used to improve our products Yes No Gemini 2.0 Flash gemini-2.0-flash Try it in Google AI Studio Our most balanced multimodal model with great performance across all tasks, with a 1 million token context window, and built for the era of Agents. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.10 (text / image / video) $0.70 (audio) Output price Free of charge $0.40 Context caching price Free of charge $0.025 / 1,000,000 tokens (text/image/video) $0.175 / 1,000,000 tokens (audio) Context caching (storage) Not available $1.00 / 1,000,000 tokens per hour Image generation pricing Free of charge $0.039 per image* Tuning price Not available Not available Grounding with Google Search Free of charge, up to 500 RPD 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.05 (text / image / video) $0.35 (audio) Output price Not available $0.20 Context caching price Not available $0.025 / 1,000,000 tokens (text/image/video) $0.175 / 1,000,000 tokens (audio) Context caching (storage) Not available $1.00 / 1,000,000 tokens per hour Image generation pricing Not available $0.0195 per image* Tuning price Not available Not available Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No [*] Image output is priced at $30 per 1,000,000 tokens. Output images up to 1024x1024px consume 1290 tokens and are equivalent to $0.039 per image. Gemini 2.0 Flash-Lite gemini-2.0-flash-lite Try it in Google AI Studio Our smallest and most cost effective model, built for at scale usage. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.075 Output price Free of charge $0.30 Context caching price Not available Not available Context caching (storage) Not available Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.0375 Output price Not available $0.15 Context caching price Not available Not available Context caching (storage) Not available Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Imagen 4 imagen-4.0-generate-001 , imagen-4.0-ultra-generate-001 , imagen-4.0-fast-generate-001 Try it in Google AI Studio Our latest image generation model, with significantly better text rendering and better overall image quality. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per Image in USD Imagen 4 Fast image price Not available $0.02 Imagen 4 Standard image price Not available $0.04 Imagen 4 Ultra image price Not available $0.06 Used to improve our products Yes No Imagen 3 imagen-3.0-generate-002 Try it in Google AI Studio Our state-of-the-art image generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per Image in USD Image price Not available $0.03 Used to improve our products Yes No Veo 3.1 veo-3.1-generate-preview , veo-3.1-fast-generate-preview Try Veo 3.1 Our latest video generation model, available to developers on the paid tier of the Gemini API. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per second in USD Veo 3.1 Standard video with audio price (default) Not available $0.40 Veo 3.1 Fast video with audio price (default) Not available $0.15 Used to improve our products Yes No Note: In some cases, an audio processing issue may prevent a video from being generated. You will only be charged if your video is successfully generated. Veo 3 veo-3.0-generate-001 , veo-3.0-fast-generate-001 Try Veo 3 Our stable video generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per second in USD Veo 3 Standard video with audio price (default) Not available $0.40 Veo 3 Fast video with audio price (default) Not available $0.15 Used to improve our products Yes No Note: In some cases, an audio processing issue may prevent a video from being generated. You will only be charged if your video is successfully generated. Veo 2 veo-2.0-generate-001 Try the API Our state-of-the-art video generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per second in USD Video price Not available $0.35 Used to improve our products Yes No Gemini Embedding gemini-embedding-001 Try the API Our newest embeddings model, more stable and with higher rate limits than previous versions, available to developers on the free and paid tiers of the Gemini API. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.15 Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.075 Used to improve our products Yes No Gemini Robotics-ER 1.5 Preview gemini-robotics-er-1.5-preview Try it in Google AI Studio Gemini Robotics-ER, short for Gemini Robotics-Embodied Reasoning, is a thinking model that enhances robots' abilities to understand and interact with the physical world. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available Not available Output price (including thinking tokens) Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Gemini 2.5 Computer Use Preview gemini-2.5-computer-use-preview-10-2025 Our Computer Use model optimized for building browser control agents that automate tasks. Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.25, prompts $2.50, prompts > 200k token Output price Not available $10.00, prompts $15.00, prompts > 200k Used to improve our products Yes No Gemma 3 Our lightweight, state-of the art, open model built from the same technology that powers our Gemini models. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge Not available Output price Free of charge Not available Context caching price Free of charge Not available Context caching (storage) Free of charge Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Gemma 3n Our open model built for efficient performance on everyday devices like mobile phones, laptops, and tablets. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge Not available Output price Free of charge Not available Context caching price Free of charge Not available Context caching (storage) Free of charge Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Pricing for tools Tools are priced at their own rates, applied to the model using them. Check the Models page for which tools are available to each model. Free Tier Paid Tier, per 1M tokens in USD Google Search 500 RPD free (limit shared for Flash and Flash-Lite). Not available for Pro. 1,500 RPD free (limit shared for Flash and Flash-Lite). Then $35 / 1,000 grounded prompts See the Gemini 3 Pro Preview pricing section for Gemini 3 specific Search pricing. Google Maps 500 RPD Not available for Pro. 1,500 RPD free (limit shared for Flash and Flash-Lite) 10,000 RPD free for Pro. Then $25 / 1,000 grounded prompts Code execution Free of charge Free of charge URL context Free of charge Charged as input tokens per model pricing. Computer use Not available See Gemini 2.5 Computer Use Preview pricing table. File search Free of charge Charged for embeddings at $0.15 / 1M tokens. Retrieved document tokens charged as regular tokens per model pricing. [*] Google AI Studio usage is free of charge in all available regions . See Billing FAQs for details. [**] Prices may differ from the prices listed here and the prices offered on Vertex AI. For Vertex prices, see the Vertex AI pricing page . [***] If you are using dynamic retrieval to optimize costs, only requests that contain at least one grounding support URL from the web in their response are charged for Grounding with Google Search. Costs for Gemini always apply. Rate limits are subject to change. Pricing for agents Agent usage costs are calculated based on the underlying token consumption and usage of the tools. Model Tools Gemini Deep Research Agent All model inference is charged at standard Gemini 3 Pro list rates, including input, output, and intermediate input / reasoning tokens generated during agentic loops. Tool usage fees apply per existing pricing structure, maintaining standard distinctions for Search Grounding (retrieved tokens excluded) versus Url_context / File Search (retrieved tokens included in all other tools). Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates. Last updated 2025-12-18 UTC. [[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-12-18 UTC."],[],[]] Terms Privacy Manage cookies English Deutsch Español – América Latina Français Indonesia Italiano Polski Português – Brasil Shqip Tiếng Việt Türkçe Русский עברית العربيّة فارسی हिंदी বাংলা ภาษาไทย 中文 – 简体 中文 – 繁體 日本語 한국어 | 2026-01-13T08:49:36 |
https://ai.google.dev/gemini-api/docs/pricing#:~:text=Context%20caching%20price%20Coming%20soon%21,products%20Yes%20%20%2079 | Gemini Developer API pricing | Gemini API | Google AI for Developers Skip to main content / English Deutsch Español – América Latina Français Indonesia Italiano Polski Português – Brasil Shqip Tiếng Việt Türkçe Русский עברית العربيّة فارسی हिंदी বাংলা ภาษาไทย 中文 – 简体 中文 – 繁體 日本語 한국어 Get API key Cookbook Community Sign in Docs API reference Gemini API Docs API reference Get API key Cookbook Community Get started Overview Quickstart API keys Libraries Interactions API Models Gemini Gemini 3 Nano Banana image generation Veo video generation Lyria music generation Imagen image generation Embeddings Robotics Pricing Rate limits Core capabilities Text Image Image generation 🍌 Image understanding Video Documents Speech and audio Speech generation Audio understanding Thinking and thought signatures Thinking Thought signatures Structured outputs Function calling Long context Tools and agents Overview Deep Research Google Search Google Maps Code execution URL context Computer Use File Search Live API Get started Capabilities Tool use Session management Ephemeral tokens Guides Batch API File input Input methods Files API Context caching OpenAI compatibility Media resolution Token counting Prompt engineering Logs and datasets Get started with logs Data logging and sharing Safety Safety settings Safety guidance Open-Source frameworks LangChain & LangGraph CrewAI LlamaIndex Vercel AI SDK Resources Migrate to Gen AI SDK Release notes Deprecations API troubleshooting Billing info Partner and library integrations Google AI Studio Quickstart Vibe code in Build mode Try out LearnLM Troubleshooting Access for Workspace users Google Cloud Platform VertexAI Gemini API OAuth authentication Policies Terms of service Available regions Additional usage polices Home Gemini API Docs Gemini Developer API pricing We have updated our Terms of Service . Start building free of charge with generous limits, then scale up with pay-as-you-go pricing for your production ready applications. Free For developers and small projects getting started with the Gemini API. check_circle Limited access to certain models check_circle Free input & output tokens check_circle Google AI Studio access check_circle Content used to improve our products * Get started for Free Paid For production applications that require higher volumes and advanced features. check_circle Higher rate limits for production deployments check_circle Access to Context caching check_circle Batch API (50% cost reduction) check_circle Access to Google's most advanced models check_circle Content not used to improve our products * Upgrade to Paid Enterprise For large-scale deployments with custom needs for security, support, and compliance, powered by Vertex AI . check_circle All features in Paid, plus optional access to: check_circle Dedicated support channels check_circle Advanced security & compliance check_circle Provisioned throughput check_circle Volume-based discounts (based on usage) check_circle ML ops, model garden and more Contact Sales Gemini 3 Pro Preview gemini-3-pro-preview Try it in Google AI Studio The best model in the world for multimodal understanding, and our most powerful agentic and vibe-coding model yet. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $2.00, prompts $4.00, prompts > 200k tokens Output price (including thinking tokens) Not available $12.00, prompts $18.00, prompts > 200k Context caching price Not available $0.20, prompts $0.40, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 5,000 prompts per month (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00, prompts $2.00, prompts > 200k tokens Output price (including thinking tokens) Not available $6.00, prompts $9.00, prompts > 200k Context caching price Not available $0.20, prompts $0.40, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 1,500 RPD (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No * A customer-submitted request to Gemini may result in one or more queries to Google Search. You will be charged for each individual search query performed. ** Gemini 3 billing for Grounding with Google Search will start January 5, 2026. Gemini 3 Flash Preview gemini-3-flash-preview Try it in Google AI Studio Our most intelligent model built for speed, combining frontier intelligence with superior search and grounding. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $3.00 Context caching price Free of charge $0.05 (text / image / video) $0.10 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 5,000 prompts per month (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.25 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.50 Context caching price Not available Same as Standard, Batch pricing not yet implemented $0.05 (text / image / video) $0.10 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 1,500 RPD (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No * A customer-submitted request to Gemini may result in one or more queries to Google Search. You will be charged for each individual search query performed. ** Gemini 3 billing for Grounding with Google Search will start January 5, 2026. Gemini 3 Pro Image Preview 🍌 gemini-3-pro-image-preview Try it in Google AI Studio Our native image generation model, optimized for speed, flexibility, and contextual understanding. Text input and output is priced the same as Gemini 3 Pro . Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $2.00 (text/image), equivalent to $0.0011 per image * Output price Not available $12.00 (text and thinking) $120.00 (images) equivalent to $0.134 per 1K/2K image ** and $0.24 per 4K image ** Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00 (text), $0.0006 (image) * Output price Not available $6.00 (text and thinking) $0.067 per 1K/2K image ** $0.12 per 4K image ** Used to improve our products Yes No * Image input is set at 560 tokens or $0.0011 per image. ** Image output is priced at $120 per 1,000,000 tokens. Output images from 1024x1024px (1K) and up to 2048x2048px (2K) consume 1120 tokens and are equivalent to $0.134 per image. Output images up to 4096x4096px (4K) consume 2000 tokens and are equivalent to $0.24 per image. Gemini 2.5 Pro gemini-2.5-pro Try it in Google AI Studio Our state-of-the-art multipurpose model, which excels at coding and complex reasoning tasks. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $1.25, prompts $2.50, prompts > 200k tokens Output price (including thinking tokens) Free of charge $10.00, prompts $15.00, prompts > 200k Context caching price Not available $0.125, prompts $0.25, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available 10,000 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.625, prompts $1.25, prompts > 200k tokens Output price (including thinking tokens) Not available $5.00, prompts $7.50, prompts > 200k Context caching price Not available $0.125, prompts $0.25, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash gemini-2.5-flash Try it in Google AI Studio Our first hybrid reasoning model which supports a 1M token context window and has thinking budgets. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.25 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash Preview gemini-2.5-flash-preview-09-2025 Try it in Google AI Studio The latest model based on the 2.5 Flash model. 2.5 Flash Preview is best for large scale processing, low-latency, high volume tasks that require thinking, and agentic use cases. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.25 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Gemini 2.5 Flash-Lite gemini-2.5-flash-lite Try it in Google AI Studio Our smallest and most cost effective model, built for at scale usage. Standard Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Free of charge $0.10 (text / image / video) $0.30 (audio) Output price (including thinking tokens) Free of charge $0.40 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash RPD) 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Not available $0.05 (text / image / video) $0.15 (audio) Output price (including thinking tokens) Not available $0.20 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash-Lite Preview gemini-2.5-flash-lite-preview-09-2025 Try it in Google AI Studio The latest model based on Gemini 2.5 Flash lite optimized for cost-efficiency, high throughput and high quality. Standard Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Free of charge $0.10 (text / image / video) $0.30 (audio) Output price (including thinking tokens) Free of charge $0.40 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash RPD) 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Not available $0.05 (text / image / video) $0.15 (audio) Output price (including thinking tokens) Not available $0.20 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Gemini 2.5 Flash Native Audio (Live API) gemini-2.5-flash-native-audio-preview-12-2025 Try it in Google AI Studio Our Live API native audio models optimized for higher quality audio outputs with better pacing, voice naturalness, verbosity, and mood. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text) $3.00 (audio / video) Output price (including thinking tokens) Free of charge $2.00 (text) $12.00 (audio) Used to improve our products Yes No Gemini 2.5 Flash Image 🍌 gemini-2.5-flash-image Try it in Google AI Studio Our native image generation model, optimized for speed, flexibility, and contextual understanding. Text input and output is priced the same as 2.5 Flash . Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.30 (text / image) Output price Not available $0.039 per image* Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image) Output price Not available $0.0195 per image* Used to improve our products Yes No [*] Image output is priced at $30 per 1,000,000 tokens. Output images up to 1024x1024px consume 1290 tokens and are equivalent to $0.039 per image. Gemini 2.5 Flash Preview TTS gemini-2.5-flash-preview-tts Try it in Google AI Studio Our 2.5 Flash text-to-speech audio model optimized for price-performant, low-latency, controllable speech generation. Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text) Output price Free of charge $10.00 (audio) Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.25 (text) Output price Not available $5.00 (audio) Used to improve our products Yes No Gemini 2.5 Pro Preview TTS gemini-2.5-pro-preview-tts Try it in Google AI Studio Our 2.5 Pro text-to-speech audio model optimized for powerful, low-latency speech generation for more natural outputs and easier to steer prompts. Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00 (text) Output price Not available $20.00 (audio) Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.50 (text) Output price Not available $10.00 (audio) Used to improve our products Yes No Gemini 2.0 Flash gemini-2.0-flash Try it in Google AI Studio Our most balanced multimodal model with great performance across all tasks, with a 1 million token context window, and built for the era of Agents. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.10 (text / image / video) $0.70 (audio) Output price Free of charge $0.40 Context caching price Free of charge $0.025 / 1,000,000 tokens (text/image/video) $0.175 / 1,000,000 tokens (audio) Context caching (storage) Not available $1.00 / 1,000,000 tokens per hour Image generation pricing Free of charge $0.039 per image* Tuning price Not available Not available Grounding with Google Search Free of charge, up to 500 RPD 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.05 (text / image / video) $0.35 (audio) Output price Not available $0.20 Context caching price Not available $0.025 / 1,000,000 tokens (text/image/video) $0.175 / 1,000,000 tokens (audio) Context caching (storage) Not available $1.00 / 1,000,000 tokens per hour Image generation pricing Not available $0.0195 per image* Tuning price Not available Not available Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No [*] Image output is priced at $30 per 1,000,000 tokens. Output images up to 1024x1024px consume 1290 tokens and are equivalent to $0.039 per image. Gemini 2.0 Flash-Lite gemini-2.0-flash-lite Try it in Google AI Studio Our smallest and most cost effective model, built for at scale usage. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.075 Output price Free of charge $0.30 Context caching price Not available Not available Context caching (storage) Not available Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.0375 Output price Not available $0.15 Context caching price Not available Not available Context caching (storage) Not available Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Imagen 4 imagen-4.0-generate-001 , imagen-4.0-ultra-generate-001 , imagen-4.0-fast-generate-001 Try it in Google AI Studio Our latest image generation model, with significantly better text rendering and better overall image quality. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per Image in USD Imagen 4 Fast image price Not available $0.02 Imagen 4 Standard image price Not available $0.04 Imagen 4 Ultra image price Not available $0.06 Used to improve our products Yes No Imagen 3 imagen-3.0-generate-002 Try it in Google AI Studio Our state-of-the-art image generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per Image in USD Image price Not available $0.03 Used to improve our products Yes No Veo 3.1 veo-3.1-generate-preview , veo-3.1-fast-generate-preview Try Veo 3.1 Our latest video generation model, available to developers on the paid tier of the Gemini API. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per second in USD Veo 3.1 Standard video with audio price (default) Not available $0.40 Veo 3.1 Fast video with audio price (default) Not available $0.15 Used to improve our products Yes No Note: In some cases, an audio processing issue may prevent a video from being generated. You will only be charged if your video is successfully generated. Veo 3 veo-3.0-generate-001 , veo-3.0-fast-generate-001 Try Veo 3 Our stable video generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per second in USD Veo 3 Standard video with audio price (default) Not available $0.40 Veo 3 Fast video with audio price (default) Not available $0.15 Used to improve our products Yes No Note: In some cases, an audio processing issue may prevent a video from being generated. You will only be charged if your video is successfully generated. Veo 2 veo-2.0-generate-001 Try the API Our state-of-the-art video generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per second in USD Video price Not available $0.35 Used to improve our products Yes No Gemini Embedding gemini-embedding-001 Try the API Our newest embeddings model, more stable and with higher rate limits than previous versions, available to developers on the free and paid tiers of the Gemini API. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.15 Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.075 Used to improve our products Yes No Gemini Robotics-ER 1.5 Preview gemini-robotics-er-1.5-preview Try it in Google AI Studio Gemini Robotics-ER, short for Gemini Robotics-Embodied Reasoning, is a thinking model that enhances robots' abilities to understand and interact with the physical world. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available Not available Output price (including thinking tokens) Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Gemini 2.5 Computer Use Preview gemini-2.5-computer-use-preview-10-2025 Our Computer Use model optimized for building browser control agents that automate tasks. Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.25, prompts $2.50, prompts > 200k token Output price Not available $10.00, prompts $15.00, prompts > 200k Used to improve our products Yes No Gemma 3 Our lightweight, state-of the art, open model built from the same technology that powers our Gemini models. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge Not available Output price Free of charge Not available Context caching price Free of charge Not available Context caching (storage) Free of charge Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Gemma 3n Our open model built for efficient performance on everyday devices like mobile phones, laptops, and tablets. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge Not available Output price Free of charge Not available Context caching price Free of charge Not available Context caching (storage) Free of charge Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Pricing for tools Tools are priced at their own rates, applied to the model using them. Check the Models page for which tools are available to each model. Free Tier Paid Tier, per 1M tokens in USD Google Search 500 RPD free (limit shared for Flash and Flash-Lite). Not available for Pro. 1,500 RPD free (limit shared for Flash and Flash-Lite). Then $35 / 1,000 grounded prompts See the Gemini 3 Pro Preview pricing section for Gemini 3 specific Search pricing. Google Maps 500 RPD Not available for Pro. 1,500 RPD free (limit shared for Flash and Flash-Lite) 10,000 RPD free for Pro. Then $25 / 1,000 grounded prompts Code execution Free of charge Free of charge URL context Free of charge Charged as input tokens per model pricing. Computer use Not available See Gemini 2.5 Computer Use Preview pricing table. File search Free of charge Charged for embeddings at $0.15 / 1M tokens. Retrieved document tokens charged as regular tokens per model pricing. [*] Google AI Studio usage is free of charge in all available regions . See Billing FAQs for details. [**] Prices may differ from the prices listed here and the prices offered on Vertex AI. For Vertex prices, see the Vertex AI pricing page . [***] If you are using dynamic retrieval to optimize costs, only requests that contain at least one grounding support URL from the web in their response are charged for Grounding with Google Search. Costs for Gemini always apply. Rate limits are subject to change. Pricing for agents Agent usage costs are calculated based on the underlying token consumption and usage of the tools. Model Tools Gemini Deep Research Agent All model inference is charged at standard Gemini 3 Pro list rates, including input, output, and intermediate input / reasoning tokens generated during agentic loops. Tool usage fees apply per existing pricing structure, maintaining standard distinctions for Search Grounding (retrieved tokens excluded) versus Url_context / File Search (retrieved tokens included in all other tools). Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates. Last updated 2025-12-18 UTC. [[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-12-18 UTC."],[],[]] Terms Privacy Manage cookies English Deutsch Español – América Latina Français Indonesia Italiano Polski Português – Brasil Shqip Tiếng Việt Türkçe Русский עברית العربيّة فارسی हिंदी বাংলা ภาษาไทย 中文 – 简体 中文 – 繁體 日本語 한국어 | 2026-01-13T08:49:36 |
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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Machine Learning Follow Hide A branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Create Post submission guidelines Articles and discussions should be directly related to the machine learning. Questions are encouraged! (See the #help tag) Older #machinelearning posts 73 74 75 76 77 78 79 80 81 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Private Graphs, Public Insights: Feature Propagation with a Twist by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Private Graphs, Public Insights: Feature Propagation with a Twist by Arvind Sundararajan # machinelearning # privacy # graphneuralnetworks # ai 1 reaction Comments Add Comment 2 min read 🧠Introducing OrKa Cloud API marcosomma marcosomma marcosomma Follow Oct 14 '25 🧠Introducing OrKa Cloud API # ai # opensource # machinelearning # mlops 9 reactions Comments Add Comment 12 min read Lifespan Thinking: How to Build IoT that Learns Forever Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 Lifespan Thinking: How to Build IoT that Learns Forever # iot # machinelearning # embedded # sustainability 1 reaction Comments Add Comment 2 min read Breaking Barriers: AI Empowers Nepali Sign Language Recognition by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Breaking Barriers: AI Empowers Nepali Sign Language Recognition by Arvind Sundararajan # a11y # machinelearning # python # opensource 1 reaction Comments Add Comment 2 min read AI's Spatial Blind Spot: Why Brain-Inspired Navigation is the Next Frontier by Arvind Sundararajan Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 AI's Spatial Blind Spot: Why Brain-Inspired Navigation is the Next Frontier by Arvind Sundararajan # ai # neuroscience # machinelearning # spatialcomputing 1 reaction Comments Add Comment 2 min read Unlock Nanoscale Secrets: Deep Equilibrium Force Fields Accelerate Simulations Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 Unlock Nanoscale Secrets: Deep Equilibrium Force Fields Accelerate Simulations # machinelearning # science # python # simulation 5 reactions Comments Add Comment 2 min read Beliefs that are true for regular software but false when applied to AI Aman Shekhar Aman Shekhar Aman Shekhar Follow Oct 15 '25 Beliefs that are true for regular software but false when applied to AI # ai # machinelearning # techtrends Comments Add Comment 4 min read AI vs Climate Change: How Data Science Is Becoming Earth’s Secret Weapon HARIHARA SUDHAN SIVAKKUMAR HARIHARA SUDHAN SIVAKKUMAR HARIHARA SUDHAN SIVAKKUMAR Follow Oct 15 '25 AI vs Climate Change: How Data Science Is Becoming Earth’s Secret Weapon # datascience # ai # python # machinelearning 3 reactions Comments Add Comment 3 min read Unlock Hidden Insights: Privacy-Preserving Graph Learning on Sparse Data by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Unlock Hidden Insights: Privacy-Preserving Graph Learning on Sparse Data by Arvind Sundararajan # machinelearning # privacy # graphneuralnetworks # datascience 1 reaction Comments Add Comment 2 min read ML Serving as a Microservice Ekemini Thompson Ekemini Thompson Ekemini Thompson Follow Sep 11 '25 ML Serving as a Microservice # ekeminithompson # machinelearning # xai # ai Comments Add Comment 3 min read Face Detection in Python Using OpenCV HAAR CASCADE Method Debajyati Dey Debajyati Dey Debajyati Dey Follow Oct 12 '25 Face Detection in Python Using OpenCV HAAR CASCADE Method # python # tutorial # machinelearning # programming 20 reactions Comments 7 comments 4 min read **Unraveling the Mysteries of AI Blindspots: The Unseen Gaps Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Follow Oct 14 '25 **Unraveling the Mysteries of AI Blindspots: The Unseen Gaps # ai # machinelearning # technology # programming 1 reaction Comments Add Comment 1 min read **Reimagining AI: Beyond Fine-Tuning with Augmentation** Th Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Follow Oct 14 '25 **Reimagining AI: Beyond Fine-Tuning with Augmentation** Th # ai # machinelearning # technology # programming 1 reaction Comments Add Comment 1 min read Unlocking 12-Lead ECG Precision from a Smartwatch: The Power of AI Reconstruction Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Unlocking 12-Lead ECG Precision from a Smartwatch: The Power of AI Reconstruction # machinelearning # python # healthtech # datascience 1 reaction Comments Add Comment 2 min read Unlocking Robotic Dexterity: Navigating the Twists and Turns of Rotational Actions by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Unlocking Robotic Dexterity: Navigating the Twists and Turns of Rotational Actions by Arvind Sundararajan # machinelearning # deeplearning # reinforcementlearning # robotics 2 reactions Comments Add Comment 2 min read Building a Self-Learning Recommender System (Without Needing Netflix Data!) mahmoudabbasi mahmoudabbasi mahmoudabbasi Follow Sep 24 '25 Building a Self-Learning Recommender System (Without Needing Netflix Data!) # machinelearning # python # recommendersystem # datascience 1 reaction Comments Add Comment 2 min read Unlock Deeper Heart Insights: Reconstructing a Full ECG From Your Smartwatch Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Unlock Deeper Heart Insights: Reconstructing a Full ECG From Your Smartwatch # machinelearning # datascience # ai # healthcare Comments Add Comment 2 min read Democratizing AI: Hyperparameter Harmony Through LLM Whispering Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 12 '25 Democratizing AI: Hyperparameter Harmony Through LLM Whispering # machinelearning # ai # python # datascience 5 reactions Comments Add Comment 2 min read LLMs: Decoding the Geometry of Alignment Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 LLMs: Decoding the Geometry of Alignment # ai # machinelearning # llm # deeplearning Comments Add Comment 2 min read MLZC25-22. Regularización en Regresión Logística: Ajuste Fino del Parámetro C para Mejor Generalización Jesus Oviedo Riquelme Jesus Oviedo Riquelme Jesus Oviedo Riquelme Follow Oct 13 '25 MLZC25-22. Regularización en Regresión Logística: Ajuste Fino del Parámetro C para Mejor Generalización # spanish # python # machinelearning # tutorial 1 reaction Comments Add Comment 9 min read MLZC25-18. Análisis Exploratorio de Datos: Correlaciones y Distribuciones en Clasificación Jesus Oviedo Riquelme Jesus Oviedo Riquelme Jesus Oviedo Riquelme Follow Oct 13 '25 MLZC25-18. Análisis Exploratorio de Datos: Correlaciones y Distribuciones en Clasificación # datascience # spanish # machinelearning # tutorial Comments Add Comment 8 min read Unlocking AI's Potential: Secure Language Models for Sensitive Data Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 11 '25 Unlocking AI's Potential: Secure Language Models for Sensitive Data # ai # machinelearning # privacy # encryption 5 reactions Comments Add Comment 2 min read MLZC25-20. Regresión Logística y One-Hot Encoding: Entrenando Nuestro Primer Modelo de Clasificación Jesus Oviedo Riquelme Jesus Oviedo Riquelme Jesus Oviedo Riquelme Follow Oct 13 '25 MLZC25-20. Regresión Logística y One-Hot Encoding: Entrenando Nuestro Primer Modelo de Clasificación # spanish # python # machinelearning # tutorial Comments Add Comment 8 min read Machine Learning vs. Deep Learning: Choosing the Right Tool for the Job Libin Babu Libin Babu Libin Babu Follow Sep 11 '25 Machine Learning vs. Deep Learning: Choosing the Right Tool for the Job # machinelearning # beginners # ai # deeplearning Comments Add Comment 2 min read Unlocking the Secrets of Network Evolution: A New Approach to Predicting the Future Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 14 '25 Unlocking the Secrets of Network Evolution: A New Approach to Predicting the Future # machinelearning # python # datascience # ai 1 reaction Comments Add Comment 2 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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Got it Close Post 117 posts published Comment 0 comments written Tag 0 tags followed vivo Vision mixed reality headset shown off, testers praise its comfortable design AR/VR News AR/VR News AR/VR News Follow Aug 12 '25 vivo Vision mixed reality headset shown off, testers praise its comfortable design # arvr # wearables # iot # edgecomputing Comments Add Comment 1 min read Snap Spectacles 5 - Optical Analysis of the AR HMD AR/VR News AR/VR News AR/VR News Follow Aug 12 '25 Snap Spectacles 5 - Optical Analysis of the AR HMD # arvr # wearables # manufacturing # nanotech Comments Add Comment 1 min read Meta's prototype headsets show off the future of mixed reality AR/VR News AR/VR News AR/VR News Follow Aug 12 '25 Meta's prototype headsets show off the future of mixed reality # arvr # wearables # science # manufacturing Comments Add Comment 1 min read Meta's prototype headsets show off the future of mixed reality AR/VR News AR/VR News AR/VR News Follow Aug 8 '25 Meta's prototype headsets show off the future of mixed reality # arvr # wearables # science # manufacturing Comments Add Comment 1 min read 'Autofocus' specs promise sharp vision, near or far AR/VR News AR/VR News AR/VR News Follow Aug 7 '25 'Autofocus' specs promise sharp vision, near or far # wearables # healthtech # science # nanotech Comments Add Comment 1 min read Exclusive: Even Realities waveguide supplier Greatar secures another hundred-million-yuan-level financing AR/VR News AR/VR News AR/VR News Follow Aug 5 '25 Exclusive: Even Realities waveguide supplier Greatar secures another hundred-million-yuan-level financing # arvr # manufacturing # wearables # nanotech Comments Add Comment 1 min read New Nanodevice can enable Holographic XR Headsets: “we can do everything – holography, beam steering, 3D displays – anything” AR/VR News AR/VR News AR/VR News Follow Aug 5 '25 New Nanodevice can enable Holographic XR Headsets: “we can do everything – holography, beam steering, 3D displays – anything” # education # science # healthtech # energy Comments Add Comment 1 min read Brilliant Labs launches Halo: AI smartglasses that last all day AR/VR News AR/VR News AR/VR News Follow Aug 5 '25 Brilliant Labs launches Halo: AI smartglasses that last all day # ai # arvr # wearables # edgecomputing 3 reactions Comments Add Comment 1 min read Karl Guttag: Google XR Glasses Using Google's Raxium MicroLEDs While Waveguide Lab Sold to Vuzix AR/VR News AR/VR News AR/VR News Follow Jul 29 '25 Karl Guttag: Google XR Glasses Using Google's Raxium MicroLEDs While Waveguide Lab Sold to Vuzix # arvr # wearables # nanotech # manufacturing Comments 1 comment 1 min read Gixel comes out of stealth with a new type of AR optical engine AR/VR News AR/VR News AR/VR News Follow Jul 28 '25 Gixel comes out of stealth with a new type of AR optical engine # arvr # wearables # manufacturing # science Comments Add Comment 1 min read ALIBABA will announce its first AI Glasses this week: There's a version with display, and a version without AR/VR News AR/VR News AR/VR News Follow Jul 28 '25 ALIBABA will announce its first AI Glasses this week: There's a version with display, and a version without # ai # wearables # arvr # edgecomputing Comments Add Comment 1 min read Karl Guttag: Google XR Glasses Using Google's Raxium MicroLEDs While Waveguide Lab Sold to Vuzix AR/VR News AR/VR News AR/VR News Follow Jul 28 '25 Karl Guttag: Google XR Glasses Using Google's Raxium MicroLEDs While Waveguide Lab Sold to Vuzix # arvr # wearables # nanotech # manufacturing Comments Add Comment 1 min read Brilliant Labs to Launch Next-gen Smart Glasses on July 31st AR/VR News AR/VR News AR/VR News Follow Jul 28 '25 Brilliant Labs to Launch Next-gen Smart Glasses on July 31st # ai # arvr # wearables # iot Comments Add Comment 1 min read CREAL raised 8.9 M USD. Here is my interview with the founder AR/VR News AR/VR News AR/VR News Follow Jul 22 '25 CREAL raised 8.9 M USD. Here is my interview with the founder # ai # arvr # wearables # iot Comments Add Comment 1 min read Xiaomi AI Glasses hands-on: a promising first-gen product AR/VR News AR/VR News AR/VR News Follow Jul 22 '25 Xiaomi AI Glasses hands-on: a promising first-gen product # ai # arvr # wearables # smarthomes Comments Add Comment 1 min read Could smart goggles bridge the gap between Vision Pro and Apple Glasses? AR/VR News AR/VR News AR/VR News Follow Jul 17 '25 Could smart goggles bridge the gap between Vision Pro and Apple Glasses? # arvr # wearables # iot # edgecomputing Comments Add Comment 1 min read New lightweight headset from PICO? AR/VR News AR/VR News AR/VR News Follow Jul 17 '25 New lightweight headset from PICO? # arvr # wearables # ai # edgecomputing Comments Add Comment 1 min read Beyond Military, Meta is Eyeing an XR Expansion into the Medical Field AR/VR News AR/VR News AR/VR News Follow Jul 15 '25 Beyond Military, Meta is Eyeing an XR Expansion into the Medical Field # arvr # healthtech # wearables # employment Comments Add Comment 1 min read Don't Get Comfortable: Why Today's Mixed Reality is a Bridge, Not a Destination AR/VR News AR/VR News AR/VR News Follow Jul 14 '25 Don't Get Comfortable: Why Today's Mixed Reality is a Bridge, Not a Destination # productivity # education # security # privacy Comments Add Comment 1 min read New Meta lab is dedicated to advancing audio technologies for future AR and AI glasses AR/VR News AR/VR News AR/VR News Follow Jul 14 '25 New Meta lab is dedicated to advancing audio technologies for future AR and AI glasses # science # arvr # iot # smarthomes Comments Add Comment 1 min read Leaked Meta Hypernova firmware reveals Photos App zoom and pan instructions AR/VR News AR/VR News AR/VR News Follow Jul 8 '25 Leaked Meta Hypernova firmware reveals Photos App zoom and pan instructions # privacy # security # productivity # education Comments Add Comment 1 min read Apple accuses ex-engineer of stealing Vision Pro secrets AR/VR News AR/VR News AR/VR News Follow Jul 7 '25 Apple accuses ex-engineer of stealing Vision Pro secrets # arvr # security # wearables # employment Comments Add Comment 1 min read Oculus co-founder Nate Mitchell joins AI glasses startup Sesame AR/VR News AR/VR News AR/VR News Follow Jul 2 '25 Oculus co-founder Nate Mitchell joins AI glasses startup Sesame # ai # arvr # wearables # iot Comments Add Comment 1 min read Mentra raises $8M for its open-source smartglasses OS — Should we do another AMA with them here ?!? AR/VR News AR/VR News AR/VR News Follow Jul 2 '25 Mentra raises $8M for its open-source smartglasses OS — Should we do another AMA with them here ?!? # ai # wearables # arvr # iot Comments Add Comment 1 min read Exclusive: I tested Viture's next-gen AR glasses, and my eyes couldn't believe what they saw AR/VR News AR/VR News AR/VR News Follow Jun 26 '25 Exclusive: I tested Viture's next-gen AR glasses, and my eyes couldn't believe what they saw # arvr Comments Add Comment 1 min read Hands-on with Lumus waveguides AR/VR News AR/VR News AR/VR News Follow Jun 26 '25 Hands-on with Lumus waveguides # arvr Comments Add Comment 1 min read Exclusive: I tested Viture's next-gen AR glasses, and my eyes couldn't believe what they saw AR/VR News AR/VR News AR/VR News Follow Jun 26 '25 Exclusive: I tested Viture's next-gen AR glasses, and my eyes couldn't believe what they saw # arvr Comments Add Comment 1 min read HTC plans to deepen collaboration with Alphabet and further strengthen its role in the global XR ecosystem AR/VR News AR/VR News AR/VR News Follow Jun 25 '25 HTC plans to deepen collaboration with Alphabet and further strengthen its role in the global XR ecosystem # arvr Comments Add Comment 1 min read A look into Google's Android XR strategy and its big gaming push AR/VR News AR/VR News AR/VR News Follow Jun 25 '25 A look into Google's Android XR strategy and its big gaming push # arvr Comments Add Comment 1 min read Exclusive: I tested Viture's next-gen AR glasses, and my eyes couldn't believe what they saw AR/VR News AR/VR News AR/VR News Follow Jun 25 '25 Exclusive: I tested Viture's next-gen AR glasses, and my eyes couldn't believe what they saw # arvr Comments Add Comment 1 min read Hands-on: Prophesee enables eye tracking with very low power consumption AR/VR News AR/VR News AR/VR News Follow Jun 22 '25 Hands-on: Prophesee enables eye tracking with very low power consumption # arvr Comments Add Comment 1 min read Vuzix receives an additional $5 million investment from Quanta Computer AR/VR News AR/VR News AR/VR News Follow Jun 20 '25 Vuzix receives an additional $5 million investment from Quanta Computer # arvr Comments Add Comment 1 min read XREAL Project Aura: AR Glasses with up to 70 FoV - New X1S chip in the glasses and a Snapdragon in the puck AR/VR News AR/VR News AR/VR News Follow Jun 16 '25 XREAL Project Aura: AR Glasses with up to 70 FoV - New X1S chip in the glasses and a Snapdragon in the puck # arvr Comments Add Comment 1 min read Samsung's Mixed Reality HMD ‘Project Moohan' will launch in July AR/VR News AR/VR News AR/VR News Follow Jun 16 '25 Samsung's Mixed Reality HMD ‘Project Moohan' will launch in July # arvr Comments Add Comment 1 min read Apple's Liquid Glass design is paving the way for AR glasses AR/VR News AR/VR News AR/VR News Follow Jun 16 '25 Apple's Liquid Glass design is paving the way for AR glasses # arvr Comments Add Comment 1 min read XREAL Project Aura: AR Glasses with up to 70 FoV - New X1S chip in the glasses and a Snapdragon in the puck AR/VR News AR/VR News AR/VR News Follow Jun 16 '25 XREAL Project Aura: AR Glasses with up to 70 FoV - New X1S chip in the glasses and a Snapdragon in the puck # arvr Comments Add Comment 1 min read Samsung's Mixed Reality HMD ‘Project Moohan' will launch in July AR/VR News AR/VR News AR/VR News Follow Jun 16 '25 Samsung's Mixed Reality HMD ‘Project Moohan' will launch in July # arvr Comments Add Comment 1 min read Google to release development tools for Android XR glasses later this year AR/VR News AR/VR News AR/VR News Follow Jun 13 '25 Google to release development tools for Android XR glasses later this year # arvr Comments Add Comment 1 min read XREAL Project Aura: AR Glasses with up to 70 FoV - New X1S chip in the glasses and a Snapdragon in the puck AR/VR News AR/VR News AR/VR News Follow Jun 13 '25 XREAL Project Aura: AR Glasses with up to 70 FoV - New X1S chip in the glasses and a Snapdragon in the puck # arvr Comments Add Comment 1 min read Samsung's Mixed Reality HMD ‘Project Moohan' will launch in July AR/VR News AR/VR News AR/VR News Follow Jun 13 '25 Samsung's Mixed Reality HMD ‘Project Moohan' will launch in July # arvr Comments Add Comment 1 min read XREAL Project Aura: AR Glasses with up to 70 FoV - New X1S chip in the glasses and a Snapdragon in the puck AR/VR News AR/VR News AR/VR News Follow Jun 11 '25 XREAL Project Aura: AR Glasses with up to 70 FoV - New X1S chip in the glasses and a Snapdragon in the puck # arvr Comments Add Comment 1 min read Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset AR/VR News AR/VR News AR/VR News Follow Jun 11 '25 Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset # arvr Comments Add Comment 1 min read Here are three ways Apple's rumored AI smart glasses could beat Meta Ray-Ban AR/VR News AR/VR News AR/VR News Follow Jun 10 '25 Here are three ways Apple's rumored AI smart glasses could beat Meta Ray-Ban # arvr Comments Add Comment 1 min read Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset AR/VR News AR/VR News AR/VR News Follow Jun 10 '25 Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset # arvr Comments Add Comment 1 min read Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset AR/VR News AR/VR News AR/VR News Follow Jun 9 '25 Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset # arvr Comments Add Comment 1 min read Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset AR/VR News AR/VR News AR/VR News Follow Jun 6 '25 Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset # arvr Comments Add Comment 1 min read Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset AR/VR News AR/VR News AR/VR News Follow Jun 5 '25 Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset # arvr Comments Add Comment 1 min read Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset AR/VR News AR/VR News AR/VR News Follow Jun 5 '25 Meta's reportedly shopping for exclusive Disney and A24 content on its upcoming ultralight XR headset # arvr Comments Add Comment 1 min read Google CEO: Next year millions of people will try AI smartglasses - We'll have products in the hands of developers this year AR/VR News AR/VR News AR/VR News Follow Jun 4 '25 Google CEO: Next year millions of people will try AI smartglasses - We'll have products in the hands of developers this year # arvr Comments Add Comment 1 min read Google CEO: Next year millions of people will try AI smartglasses - We'll have products in the hands of developers this year AR/VR News AR/VR News AR/VR News Follow Jun 2 '25 Google CEO: Next year millions of people will try AI smartglasses - We'll have products in the hands of developers this year # arvr Comments Add Comment 1 min read Samsung Research: Single-layer waveguide display uses achromatic metagratings for more compact augmented reality eyewear AR/VR News AR/VR News AR/VR News Follow Jun 2 '25 Samsung Research: Single-layer waveguide display uses achromatic metagratings for more compact augmented reality eyewear # arvr Comments Add Comment 1 min read Exclusive: Viture is teasing next-gen XR glasses — here's what we know about them AR/VR News AR/VR News AR/VR News Follow Jun 2 '25 Exclusive: Viture is teasing next-gen XR glasses — here's what we know about them # arvr Comments Add Comment 1 min read Is it more weird to wear earbuds in social situations than wearing Smartglasses ? AR/VR News AR/VR News AR/VR News Follow Jun 2 '25 Is it more weird to wear earbuds in social situations than wearing Smartglasses ? # arvr Comments Add Comment 1 min read MIXED is shutting down, one of the two best XR news websites AR/VR News AR/VR News AR/VR News Follow Jun 2 '25 MIXED is shutting down, one of the two best XR news websites # arvr Comments Add Comment 1 min read Google CEO: Next year millions of people will try AI smartglasses - We'll have products in the hands of developers this year AR/VR News AR/VR News AR/VR News Follow Jun 2 '25 Google CEO: Next year millions of people will try AI smartglasses - We'll have products in the hands of developers this year # arvr Comments Add Comment 1 min read DreamPark raises $1.1M to transform real-world spaces into mixed reality theme parks AR/VR News AR/VR News AR/VR News Follow May 30 '25 DreamPark raises $1.1M to transform real-world spaces into mixed reality theme parks # arvr Comments Add Comment 1 min read Anduril and Meta Team Up to Transform XR for the American Military AR/VR News AR/VR News AR/VR News Follow May 30 '25 Anduril and Meta Team Up to Transform XR for the American Military # arvr Comments Add Comment 1 min read Google CEO: Next year millions of people will try AI smartglasses - We'll have products in the hands of developers this year AR/VR News AR/VR News AR/VR News Follow May 30 '25 Google CEO: Next year millions of people will try AI smartglasses - We'll have products in the hands of developers this year # arvr Comments Add Comment 1 min read You may laugh when you hear what OpenAI's top secret AI gadget allegedly looks like AR/VR News AR/VR News AR/VR News Follow May 29 '25 You may laugh when you hear what OpenAI's top secret AI gadget allegedly looks like # arvr Comments Add Comment 1 min read Meta is working on plans to open retail stores to boost sales of smartglasses and other devices, internal comms show AR/VR News AR/VR News AR/VR News Follow May 29 '25 Meta is working on plans to open retail stores to boost sales of smartglasses and other devices, internal comms show # arvr Comments Add Comment 1 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Future — News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. 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Report Abuse Brian Douglas for GitHub Posted on Feb 21, 2021 • Edited on Mar 1, 2021 Sending PR notifications through SMS and GitHub Actions # github # twilio # githubactions # devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions GitHub Actions thrive thanks to its ecosystem of community actions. In that community, you will find several open-sourced actions from solo developers looking to improve their workflows, but amongst those actions, you will find a number of your popular developer tools with actions in the marketplace. GitHub Marketplace is a new way to discover and purchase tools that extend your workflow. Learn how you can publish your Action to Marketplace . twilio-labs / actions-sms Send an SMS through GitHub Actions Twilio SMS GitHub Action Send an SMS from GitHub Actions. Prerequisites A Twilio Account. Sign up for free A Twilio Auth Token A Registered Phone Number Usage Set up your credentials as secrets in your repository settings using TWILIO_ACCOUNT_SID , TWILIO_AUTH_TOKEN , TO_PHONE_NUMBER , FROM_PHONE_NUMBER Add the following to your workflow name : Twilio Send on : workflow_dispatch : # allows you to manually trigger the workflow schedule : # runs on a cron, nightly - cron : 0 0 * * * env : TWILIO_ACCOUNT_SID : ${{ secrets.TWILIO_ACCOUNT_SID }} TWILIO_AUTH_TOKEN : ${{ secrets.TWILIO_AUTH_TOKEN }} TWILIO_API_SECRET : ${{ secrets.TWILIO_API_SECRET }} permissions : contents : read jobs : send : runs-on : ubuntu-latest steps : - name : ' Sending SMS Notification ' uses : twilio-labs/actions-sms@v1 with : FROM_PHONE_NUMBER : ${{ secrets.FROM_PHONE_NUMBER }} TO_PHONE_NUMBER : ${{ secrets.TO_PHONE_NUMBER }} message : ' Hello from Twilio ' Enter fullscreen mode Exit fullscreen mode Inputs FROM_PHONE_NUMBER Required Phone number in… View on GitHub To begin, you will need a GitHub Actions workflow YAML. I copied mine directly from the twilio-labs/actions-sms . The Twilio team maintains the action from an open-source repo, so if you have questions or looking for other features, definitely reach out to them there. name : PR text MSG on : [ pull_request ] jobs : text : runs-on : ubuntu-latest steps : - name : ' Sending SMS Notification' uses : twilio-labs/actions-sms@v1 with : fromPhoneNumber : ' +1(267)8282212' toPhoneNumber : ${{ secrets.PAGER_NUMBER }} message : ' Hello from Twilio' env : TWILIO_ACCOUNT_SID : ${{ secrets.TWILIO_ACCOUNT_SID }} TWILIO_API_KEY : ${{ secrets.TWILIO_API_KEY }} TWILIO_API_SECRET : ${{ secrets.TWILIO_API_SECRET }} Enter fullscreen mode Exit fullscreen mode Something to keep in mind is that you will need a Twilio trial account and create a Programmable Messaging service to generate your secret key and SID. If you are also curious about how to set up secrets in a GitHub rep, check out my previous article on The Secrets of An Authenticated GitHub Action Workflow . You will want to put the PAGER_NUMBER in a secret too. Finally, set sending phone numbers to the one generated in Twilio. Also, to trigger the action I have it set to pull_request, but for testing, purposes you can also set it as workflow_dispatch . And that is it. Enjoy your new text messages. This is part of my 28 days of Actions series. To get notified of more GitHub Action tips, follow the GitHub organization right here on Dev. Learn how to build action with Node.js 01:33 Conditional Workflows and Failures in GitHub Actions Brian Douglas for GitHub ・ Feb 19 '21 #github #devops #githubactions ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. 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Geschwindigkeit So schnell wie tippen: die schnellste Enterprise-KI-Suche, die wir kennen. Schnellere Ergebnisse bedeuten höhere Umsätze. Skalierbarkeit Profitieren Sie von der weltweit größten gehosteten Suchmaschine mit 1,7 Billionen Suchanfragen pro Jahr. Algolia bietet zudem höchste Compliance und Stabilität – mit bis zu 99,999 % Verfügbarkeit. Build retrieval-powered solutions today AI retrieval powers the next generation of agentic, generative, and search experiences that adapt to intent, not syntax. Search AI Bauen Sie leistungsstarke Sucherlebnisse für Ihre App oder Website mit einer KI, die versteht, rankt und sich in Echtzeit anpasst. Kombinieren Sie traditionelle Suchergebnisse mit agentischen und generativen Ergebnissen für ein optimales, begeisterndes Nutzererlebnis. Hybride Suche : Semantische Vektorsuche trifft auf Keyword-Präzision für schnelle, intuitive Ergebnisse, die die Nutzerintention exakt widerspiegeln. Mehr erfahren. KI-Ranking : Kombinieren Sie maschinelles Lernen mit menschlicher Steuerung, um die Relevanz der Ergebnisse kontinuierlich zu verbessern. Mehr erfahren. Abfrage-Kategorisierung : Wandeln Sie unstrukturierte Anfragen in strukturierte Daten um – für intelligenteres Merchandising und Analysen. Mehr erfahren. Erweiterte Personalisierung : Bieten Sie Erlebnisse, die das Verhalten, die Präferenzen und den Kontext jedes Nutzers widerspiegeln – sofort einsatzbereit. Mehr erfahren. Mehr erfahren über Search AI Agentic Studio Agent Studio ist der schnellste Weg, um RAG-Agenten zu entwickeln und bereitzustellen. Es ist ein Framework für Entwickler, das die Erstellung produktionsreifer, retrieval-augmentierter KI-Agenten vereinfacht. Marken-Agenten : Erstellen und testen Sie Agenten, die mit Ihren Besuchern chatten — oder automatisierte Agenten für Ihr internes Team. Agentische Operationen : Verbessern Sie Suchergebnisse mithilfe intelligenter Helfer, die Geschäftsprozesse optimieren. Agentic Search Commerce : Verkaufen Sie Ihre Produkte über agentengetriebene Drittanbieterplattformen (z. B. Perplexity, ChatGPT) mit Unterstützung des Algolia MCP-Servers. Mehr erfahren über Agent Studio Relevanz in großem Maßstab Algolias KI-Plattform vereint Suche, Sprache und Logik, um Relevanz in großem Maßstab zu liefern. Sie kombiniert fortschrittliche Suchalgorithmen, Large Language Models (LLMs) und Retrieval-Augmented Generation (RAG), um hochgradig personalisierte, leistungsstarke Nutzererlebnisse mit Echtzeit-Relevanz zu ermöglichen. Generative KI-Erlebnisse : Ein Entwickler-Toolkit zur Erstellung inhaltsreicher Anleitungen — unterstützt von LLMs, abgestimmt auf Ihr Publikum. Mehr erfahren. Guides : Erstellen Sie automatisch informative Anleitungen aus Ihrem Produktkatalog. Einfaches Setup – keine manuelle Inhaltserstellung erforderlich. Mehr erfahren. Ask AI : Fügen Sie Ihrer Dokumentation, Website oder Support-Seite einen KI-Assistenten hinzu, der präzise, konversationelle Antworten direkt aus Ihrer Suchleiste liefert. Mehr erfahren. Learn more about Generative Experiences Verbinden Sie KI-Agenten mit Algolia MCP Der Model Context Protocol (MCP) -Server von Algolia liefert die Grundlage, um agentischen Handel zu steuern und zu orchestrieren. Er ist entscheidend, um die verschiedenen Systeme zu koordinieren, die für eine vollständige agentische Transaktion benötigt werden. Ob Produktempfehlungen, Suchassistenten oder Analyse-Dashboards – MCP ermöglicht mehr Leistung, schneller und in großem Maßstab. Mehr erfahren Tools für Business-Teams Merchandising Studio Gestalten Sie bessere Kundenerlebnisse – ganz ohne Code. Mit dem Algolia Merchandising Studio können Business-Teams Kampagnen über AI Search, AI Browse und AI Recommendations steuern und optimieren. Mehr erfahren Analytics Erhalten Sie Einblicke in Klickverhalten, Performance nach Position und Saisonalität. Verfolgen Sie die Suchbegriffe, die Umsatz bringen, beheben Sie Nulltreffer und verbessern Sie die Kategorieleistung – alles über ein intuitives Dashboard. Mehr erfahren Unterstützung für Entwickler UI Components Starten Sie schnell mit unseren UI Component Libraries für Interfaces in jeder Auflösung und jedem JS-Framework. Von Instant Search über Autocomplete bis zu Sortierung und Pagination – wir haben alles, was Sie brauchen. Unsere UI Components entdecken Integrationen Integrieren Sie Algolia direkt in Ihren Tech-Stack oder Ihr Framework. Starten Sie sofort mit Anbindungen an alle führenden E-Commerce-Plattformen und steigern Sie Ihre Umsätze, indem Ihre Kunden in Sekunden die richtigen Produkte finden. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Bright Data Web Scraping Challenge Follow Hide This is the official tag for submissions and announcements related to the Bright Data Web Scraping Challenge. Create Post about #brightdatachallenge The newest Bright Data Challenge is happening now! Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Why Having More Data Still Slows Decisions Gyan Solutions Gyan Solutions Gyan Solutions Follow Jan 5 Why Having More Data Still Slows Decisions # operations # devops # systemdesign # brightdatachallenge Comments Add Comment 6 min read Pushing Python to 20,000 Requests Sent/Second Tibabalase Oludemi Tibabalase Oludemi Tibabalase Oludemi Follow Nov 3 '25 Pushing Python to 20,000 Requests Sent/Second # python # brightdatachallenge # botting # programming 4 reactions Comments Add Comment 4 min read Bright Data vs Browse AI: Choosing the Right Web Scraping Stack Without Regret Ali Farhat Ali Farhat Ali Farhat Follow Nov 2 '25 Bright Data vs Browse AI: Choosing the Right Web Scraping Stack Without Regret # brightdatachallenge # browseai # ai # programming 10 reactions Comments 1 comment 9 min read Automating Data Pipelines with Bright Data, n8n, and Airtable n8n and Bright Challenge: Unstoppable Workflow Ali Farhat Ali Farhat Ali Farhat Follow Sep 26 '25 Automating Data Pipelines with Bright Data, n8n, and Airtable # brightdatachallenge # n8nbrightdatachallenge # n8n # airtable 16 reactions Comments 4 comments 5 min read Automating Data Center Design with BIM APIs and Python Scripts Reetie Lubana Reetie Lubana Reetie Lubana Follow Sep 12 '25 Automating Data Center Design with BIM APIs and Python Scripts # python # architecture # api # brightdatachallenge 1 reaction Comments Add Comment 3 min read LinkLens — Your Daily LinkedIn Digest Slim junior Slim junior Slim junior Follow Sep 1 '25 LinkLens — Your Daily LinkedIn Digest # devchallenge # brightdatachallenge # ai # webdata 17 reactions Comments Add Comment 2 min read Building Intelligent Agents with ScrapeGraph: The Complete Guide Mohammad Ehsan Ansari Mohammad Ehsan Ansari Mohammad Ehsan Ansari Follow Jun 24 '25 Building Intelligent Agents with ScrapeGraph: The Complete Guide # ai # brightdatachallenge # webdev # programming Comments Add Comment 5 min read # saveearth4lilith Courtney Brown Courtney Brown Courtney Brown Follow May 22 '25 # saveearth4lilith # devchallenge # brightdatachallenge # ai # webdata Comments Add Comment 1 min read AI CreaI QQriri99 QQriri99 QQriri99 Follow May 21 '25 AI CreaI # devchallenge # brightdatachallenge # ai # webdata Comments 1 comment 3 min read Congratulations to the winner of the Bright Data Real-Time AI Agents Challenge! dev.to staff dev.to staff dev.to staff Follow for The DEV Team Jun 10 '25 Congratulations to the winner of the Bright Data Real-Time AI Agents Challenge! # devchallenge # brightdatachallenge # webdev # ai 42 reactions Comments 8 comments 2 min read OpinionFlow – Real-Time Review Intelligence with Bright Data, Gemini 2.0 & Pinecone Shivansh Singh Shivansh Singh Shivansh Singh Follow May 26 '25 OpinionFlow – Real-Time Review Intelligence with Bright Data, Gemini 2.0 & Pinecone # devchallenge # brightdatachallenge # ai # webdata 353 reactions Comments 77 comments 2 min read Fluencr - Find Instagram Influencer For your brand Shweta Kale Shweta Kale Shweta Kale Follow May 26 '25 Fluencr - Find Instagram Influencer For your brand # devchallenge # brightdatachallenge # ai # webdata 24 reactions Comments 14 comments 2 min read Smart Shopper AI – Real-Time Product Intelligence Powered by Bright Data MCP proxy. 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Follow for AWS Community Builders May 26 '25 Financial Signals Dashboard: AI-Powered Real-time Stock Analysis with Bright Data MCP Server & Strands Agents SDK # devchallenge # brightdatachallenge # ai # webdata 26 reactions Comments 1 comment 7 min read 🧠 NewsPulse AI – Real-Time News Analysis with LLMs & Web Scraping via Bright Data Suman Kumar Suman Kumar Suman Kumar Follow May 25 '25 🧠 NewsPulse AI – Real-Time News Analysis with LLMs & Web Scraping via Bright Data # devchallenge # brightdatachallenge # ai # webdata 34 reactions Comments 13 comments 7 min read DecipherIt: Building a NotebookLM-Inspired AI Research Assistant powered by Bright Data Amit Wani Amit Wani Amit Wani Follow May 25 '25 DecipherIt: Building a NotebookLM-Inspired AI Research Assistant powered by Bright Data # devchallenge # brightdatachallenge # ai # webdata 19 reactions Comments Add Comment 8 min read ✨ Submission: Trend-Aware Content Generator John Eric John Eric John Eric Follow May 26 '25 ✨ Submission: Trend-Aware Content Generator # devchallenge # brightdatachallenge # ai # webdata 12 reactions Comments Add Comment 3 min read Rival Guru : Know realtime facts about your competitors. Shivam Shivam Shivam Follow May 26 '25 Rival Guru : Know realtime facts about your competitors. # devchallenge # brightdatachallenge # ai # webdata 11 reactions Comments Add Comment 2 min read Realtime Opportunity Engine - AI Powere Marvin Rivera Marvin Rivera Marvin Rivera Follow May 26 '25 Realtime Opportunity Engine - AI Powere # devchallenge # brightdatachallenge # ai # webdata 12 reactions Comments 1 comment 3 min read Smart Stock Analyzer: Real-Time Investment Insights Using AI and Bright Data Devesh Kumar Devesh Kumar Devesh Kumar Follow May 25 '25 Smart Stock Analyzer: Real-Time Investment Insights Using AI and Bright Data # devchallenge # brightdatachallenge # ai # webdata 28 reactions Comments 1 comment 3 min read 🥷 NewsNinja M. Hassan Mahmood M. Hassan Mahmood M. Hassan Mahmood Follow May 25 '25 🥷 NewsNinja # devchallenge # brightdatachallenge # ai # webdata 11 reactions Comments Add Comment 2 min read ✨ Challenge Feed: Real-Time Programming Challenges in One Place James Moro James Moro James Moro Follow May 21 '25 ✨ Challenge Feed: Real-Time Programming Challenges in One Place # devchallenge # brightdatachallenge # ai # webdata 49 reactions Comments 13 comments 2 min read AI News Sentiment Analyzer Veríssimo Cassange Veríssimo Cassange Veríssimo Cassange Follow May 26 '25 AI News Sentiment Analyzer # devchallenge # brightdatachallenge # ai # webdata 7 reactions Comments Add Comment 4 min read Realyze : Realtime RealTime real estate property finder Emmanuel Taiwo Emmanuel Taiwo Emmanuel Taiwo Follow May 26 '25 Realyze : Realtime RealTime real estate property finder # brightdatachallenge # webdev # programming 20 reactions Comments 9 comments 2 min read hermitAI v0.3: LLM + RAG + MCP = Real-time Personalized AI Twin Kai Chew Kai Chew Kai Chew Follow May 25 '25 hermitAI v0.3: LLM + RAG + MCP = Real-time Personalized AI Twin # devchallenge # brightdatachallenge # ai # webdata 26 reactions Comments 11 comments 5 min read loading... trending guides/resources Bright Data vs Browse AI: Choosing the Right Web Scraping Stack Without Regret Pushing Python to 20,000 Requests Sent/Second Why Having More Data Still Slows Decisions 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Machine Learning Follow Hide A branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Create Post submission guidelines Articles and discussions should be directly related to the machine learning. Questions are encouraged! (See the #help tag) Older #machinelearning posts 74 75 76 77 78 79 80 81 82 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu AI in Crypto Trading: From Rule-Based Bots to Adaptive Systems TradeLink TradeLink TradeLink Follow Oct 14 '25 AI in Crypto Trading: From Rule-Based Bots to Adaptive Systems # ai # cryptocurrency # machinelearning Comments Add Comment 3 min read AI-Powered Beamforming: Boosting 5G/6G Performance with Smart Signal Shaping Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 13 '25 AI-Powered Beamforming: Boosting 5G/6G Performance with Smart Signal Shaping # machinelearning # wireless # ai # networks 3 reactions Comments Add Comment 2 min read The Quiet AI Revolution in Your Doctor's Office Deep Data Insight Deep Data Insight Deep Data Insight Follow Oct 14 '25 The Quiet AI Revolution in Your Doctor's Office # ai # machinelearning Comments Add Comment 3 min read We just open-sourced XAI’s Macrohard, an autonomous computer-using agent Prateek YJ Prateek YJ Prateek YJ Follow Oct 13 '25 We just open-sourced XAI’s Macrohard, an autonomous computer-using agent # automation # ai # machinelearning # opensource 2 reactions Comments Add Comment 2 min read Red Planet Unveiled: AI Paints a New Martian Reality by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 18 '25 Red Planet Unveiled: AI Paints a New Martian Reality by Arvind Sundararajan # ai # vr # space # machinelearning Comments 1 comment 2 min read ML Zoomcamp Week 3 Shukurat Bello Shukurat Bello Shukurat Bello Follow Oct 14 '25 ML Zoomcamp Week 3 # machinelearning # classification # python # learning Comments Add Comment 1 min read I'm not Sure, but Here's a Guess Ted Hagos Ted Hagos Ted Hagos Follow Oct 6 '25 I'm not Sure, but Here's a Guess # discuss # ai # machinelearning 13 reactions Comments 5 comments 1 min read Mall Customer Segmentation using ML — A Step-by-Step Tutorial Naman Naman Naman Follow Oct 13 '25 Mall Customer Segmentation using ML — A Step-by-Step Tutorial # datascience # tutorial # python # machinelearning 5 reactions Comments Add Comment 3 min read AI-Powered Micro-Robots: Revolutionizing Precision Medicine Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 13 '25 AI-Powered Micro-Robots: Revolutionizing Precision Medicine # robotics # ai # healthcare # machinelearning Comments Add Comment 2 min read **AI Bias Alert: A Wake-Up Call for Fair Hiring Practices** Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Follow Oct 13 '25 **AI Bias Alert: A Wake-Up Call for Fair Hiring Practices** # ai # machinelearning # technology # programming 2 reactions Comments Add Comment 1 min read Audio Deepfakes: Exposing the Echo Chamber in AI Security Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Audio Deepfakes: Exposing the Echo Chamber in AI Security # ai # security # machinelearning # deeplearning 1 reaction Comments Add Comment 2 min read Beyond Pattern Matching: Teaching AI to Think Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 13 '25 Beyond Pattern Matching: Teaching AI to Think # ai # machinelearning # neuralnetworks # symbolicai Comments Add Comment 2 min read **The Hidden Dangers of Oversimplification in AI Sports Coac Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Follow Oct 13 '25 **The Hidden Dangers of Oversimplification in AI Sports Coac # ai # machinelearning # technology # programming 1 reaction Comments Add Comment 1 min read **Unlocking Faster Learning in Complex Environments: The Pow Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Follow Oct 13 '25 **Unlocking Faster Learning in Complex Environments: The Pow # ai # machinelearning # technology # programming 1 reaction Comments Add Comment 1 min read Speak Freely: Private Language Models on a Shoestring Budget by Arvind Sundararajan Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 13 '25 Speak Freely: Private Language Models on a Shoestring Budget by Arvind Sundararajan # machinelearning # privacy # ai # python Comments Add Comment 2 min read Predictive Motion: Charting the Course for Autonomous Robots with Flow Fields Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Predictive Motion: Charting the Course for Autonomous Robots with Flow Fields # ai # robotics # machinelearning # motionplanning 1 reaction Comments Add Comment 2 min read Unlocking AI Storytelling: The Power of Collaborative Text Generation Arvind SundaraRajan Arvind SundaraRajan Arvind SundaraRajan Follow Oct 13 '25 Unlocking AI Storytelling: The Power of Collaborative Text Generation # ai # nlp # machinelearning # generativeai Comments Add Comment 2 min read Illuminating the Unseen: AI-Powered Clarity in Low-Light Imaging Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Illuminating the Unseen: AI-Powered Clarity in Low-Light Imaging # computervision # machinelearning # python # imaging 1 reaction Comments Add Comment 2 min read AI's 'Aha!' Moment: Cracking Generalization in Reinforcement Learning Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 AI's 'Aha!' Moment: Cracking Generalization in Reinforcement Learning # machinelearning # python # ai # reinforcementlearning 1 reaction Comments Add Comment 2 min read The Audio Illusion: How Easily AI Deepfakes Deceive Our Ears Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 The Audio Illusion: How Easily AI Deepfakes Deceive Our Ears # ai # machinelearning # security # audio 1 reaction Comments Add Comment 2 min read Democratizing AI: Structured Deep RL for Everyone Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Democratizing AI: Structured Deep RL for Everyone # ai # machinelearning # reinforcementlearning # python 1 reaction Comments Add Comment 2 min read **Unlocking the Power of Reinforcement Learning: AI's Trial Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Follow Oct 13 '25 **Unlocking the Power of Reinforcement Learning: AI's Trial # ai # machinelearning # technology # programming 2 reactions Comments Add Comment 1 min read **The Future of Human-AI Convergence: Unlocking Unparalleled Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Dr. Carlos Ruiz Viquez Follow Oct 13 '25 **The Future of Human-AI Convergence: Unlocking Unparalleled # ai # machinelearning # technology # programming 1 reaction Comments Add Comment 1 min read Quantum Compositionality: A New Dawn for AI Understanding Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Quantum Compositionality: A New Dawn for AI Understanding # quantumcomputing # machinelearning # ai # python 1 reaction Comments Add Comment 2 min read Predictive Motion: Guiding Robots with Learned Flow Fields by Arvind Sundararajan Arvind Sundara Rajan Arvind Sundara Rajan Arvind Sundara Rajan Follow Sep 14 '25 Predictive Motion: Guiding Robots with Learned Flow Fields by Arvind Sundararajan # robotics # ai # motionplanning # machinelearning 1 reaction Comments Add Comment 2 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://dev.to/georgekobaidze | Giorgi Kobaidze - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Giorgi Kobaidze I write code like I brew my coffee: strong, clean, and with care. ☕ Mostly working with .NET, but I’m tech-agnostic. I’m a problem solver by nature. Location Tbilisi, Georgia Joined Joined on Jan 29, 2018 Personal website https://www.linkedin.com/in/giorgikobaidze/ github website twitter website Education San Diego State University Work Principal Software Engineer at Flutter Entertainment C# Awarded to the top C# author each week Got it Close 2 Top 7 Awarded for having a post featured in the weekly "must-reads" list. 🙌 Got it Close 4 Week Community Wellness Streak Keep contributing to discussions by posting at least 2 comments per week for 4 straight weeks. Unlock the 8 Week Badge next. 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Say Hey! if you want to create, learn, or chat about tech together! 👋 Post 19 posts published Comment 97 comments written Tag 18 tags followed Pin Pinned .NET 10: The Performance Beast That's Redefining Modern Application Development Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Dec 14 '25 .NET 10: The Performance Beast That's Redefining Modern Application Development # microsoft # dotnet # csharp # programming 13 reactions Comments 2 comments 37 min read I'm All In on AI, But We Need to Talk About Vibe Coding Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Jun 24 '25 I'm All In on AI, But We Need to Talk About Vibe Coding # ai # vibecoding # machinelearning # coding 126 reactions Comments 64 comments 16 min read The Popstar Developer Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Nov 5 '25 The Popstar Developer # discuss # ai # machinelearning # career 2 reactions Comments 1 comment 7 min read Want to connect with Giorgi Kobaidze? Create an account to connect with Giorgi Kobaidze. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in What Happens If You Stay Old School in the AI Era? Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Nov 1 '25 What Happens If You Stay Old School in the AI Era? # discuss # ai # machinelearning # career 4 reactions Comments 4 comments 12 min read How a Simple Race Condition Bug Can Take Down Even the Biggest Systems Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Oct 28 '25 How a Simple Race Condition Bug Can Take Down Even the Biggest Systems # systems # cloud # failure # design 1 reaction Comments Add Comment 14 min read Don't Be Ashamed to Use AI, Even Iron Man Did Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Oct 13 '25 Don't Be Ashamed to Use AI, Even Iron Man Did # discuss # ai # machinelearning # career 12 reactions Comments 6 comments 19 min read Will Developers Survive AI Takeover? Equalizer vs Amplifier Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Oct 8 '25 Will Developers Survive AI Takeover? Equalizer vs Amplifier # discuss # ai # machinelearning # career 16 reactions Comments 6 comments 9 min read Template Your Own Clean, Precise Boilerplate Code: No AI, No Wallet Drain. Part 3 – Enough Theory, Now We Code Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Sep 20 '25 Template Your Own Clean, Precise Boilerplate Code: No AI, No Wallet Drain. Part 3 – Enough Theory, Now We Code # microsoft # dotnet # productivity # csharp 15 reactions Comments 3 comments 24 min read Template Your Own Clean, Precise Boilerplate Code: No AI, No Wallet Drain. Part 2 – Exploring Every Hidden Trail Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Sep 9 '25 Template Your Own Clean, Precise Boilerplate Code: No AI, No Wallet Drain. Part 2 – Exploring Every Hidden Trail # microsoft # dotnet # productivity # csharp 2 reactions Comments Add Comment 11 min read Template Your Own Precise Boilerplate Code: No AI, No Wallet Drain. Part 1 – Microsoft’s Implementation Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Sep 1 '25 Template Your Own Precise Boilerplate Code: No AI, No Wallet Drain. Part 1 – Microsoft’s Implementation # microsoft # dotnet # productivity # csharp 5 reactions Comments 3 comments 11 min read Behind the Mic: AI and the Vibe Coding Podcast Retrospective Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Aug 4 '25 Behind the Mic: AI and the Vibe Coding Podcast Retrospective # ai # vibecoding # coding # podcast 6 reactions Comments 2 comments 7 min read 20 Rules for Becoming THAT Manager (From a Principal Engineer’s Perspective) Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Jul 19 '25 20 Rules for Becoming THAT Manager (From a Principal Engineer’s Perspective) # management # softskills # leadership # career 19 reactions Comments 15 comments 8 min read 4th of July Special: Land of the Free, Home of Technology Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Jul 4 '25 4th of July Special: Land of the Free, Home of Technology # history # innovation # usa # science 2 reactions Comments Add Comment 13 min read The Hidden Major Flaws in ‘Work Smart, Not Hard’ That Make People Mediocre Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Jun 3 '25 The Hidden Major Flaws in ‘Work Smart, Not Hard’ That Make People Mediocre # discuss # career # careeradvice # workculture 1 reaction Comments 2 comments 9 min read Why I Believe 'dotnet run app.cs' Is a Huge Leap Forward Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow May 27 '25 Why I Believe 'dotnet run app.cs' Is a Huge Leap Forward # dotnet # cli # softwareengineering # csharp 1 reaction Comments 5 comments 4 min read Kickstarting a .NET Solution from Scratch with the CLI Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow May 15 '25 Kickstarting a .NET Solution from Scratch with the CLI # dotnet # cli # softwareengineering # terminal 15 reactions Comments Add Comment 6 min read Foundational Project Structure for .NET Projects Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow May 4 '25 Foundational Project Structure for .NET Projects # dotnet # architecture # techtips # templating 2 reactions Comments Add Comment 3 min read Go-ing Beyond TypeScript: Microsoft Picks Go—How Will This Change the Landscape? Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Mar 31 '25 Go-ing Beyond TypeScript: Microsoft Picks Go—How Will This Change the Landscape? # microsoft # typescript # go # csharp 1 reaction Comments Add Comment 12 min read Understanding Your Audience as a Software Engineer Giorgi Kobaidze Giorgi Kobaidze Giorgi Kobaidze Follow Mar 25 '25 Understanding Your Audience as a Software Engineer # discuss # softwareengineering # programming # productivity 4 reactions Comments Add Comment 7 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.productplan.com/glossary/moscow-prioritization/ | What is MoSCoW Prioritization? | Overview of the MoSCoW Method Solutions Strategy Prioritization Roadmaps Launch AI/ML Discovery Integrations Service Excellence Implementation Training and Support Pricing Resources Learning Center Support Center Templates Release Notes Glossary Webinars Blog Security API Docs Status Certification Newsletter Company Contact Us Careers Customer Stories Strategic Alliances Events Newsroom Sign In Get Started MoSCoW Prioritization What is MoSCoW Prioritization? MoSCoW prioritization, also known as the MoSCoW method or MoSCoW analysis, is a popular prioritization technique for managing requirements. The acronym MoSCoW represents four categories of initiatives: must-have, should-have, could-have, and won’t-have, or will not have right now. Some companies also use the “W” in MoSCoW to mean “wish.” What is the History of the MoSCoW Method? Software development expert Dai Clegg created the MoSCoW method while working at Oracle. He designed the framework to help his team prioritize tasks during development work on product releases. You can find a detailed account of using MoSCoW prioritization in the Dynamic System Development Method (DSDM) handbook . But because MoSCoW can prioritize tasks within any time-boxed project, teams have adapted the method for a broad range of uses. How Does MoSCoW Prioritization Work? Before running a MoSCoW analysis, a few things need to happen. First, key stakeholders and the product team need to get aligned on objectives and prioritization factors. Then, all participants must agree on which initiatives to prioritize. At this point, your team should also discuss how they will settle any disagreements in prioritization. If you can establish how to resolve disputes before they come up, you can help prevent those disagreements from holding up progress. Finally, you’ll also want to reach a consensus on what percentage of resources you’d like to allocate to each category. With the groundwork complete, you may begin determining which category is most appropriate for each initiative. But, first, let’s further break down each category in the MoSCoW method. Start prioritizing your initiatives → MoSCoW Prioritization Categories 1. Must-have initiatives As the name suggests, this category consists of initiatives that are “musts” for your team. They represent non-negotiable needs for the project, product, or release in question. For example, if you’re releasing a healthcare application, a must-have initiative may be security functionalities that help maintain compliance. The “must-have” category requires the team to complete a mandatory task. If you’re unsure about whether something belongs in this category, ask yourself the following. If the product won’t work without an initiative, or the release becomes useless without it, the initiative is most likely a “must-have.” 2. Should-have initiatives Should-have initiatives are just a step below must-haves. They are essential to the product, project, or release, but they are not vital. If left out, the product or project still functions. However, the initiatives may add significant value. “Should-have” initiatives are different from “must-have” initiatives in that they can get scheduled for a future release without impacting the current one. For example, performance improvements, minor bug fixes, or new functionality may be “should-have” initiatives. Without them, the product still works. 3. Could-have initiatives Another way of describing “could-have” initiatives is nice-to-haves. “Could-have” initiatives are not necessary to the core function of the product. However, compared with “should-have” initiatives, they have a much smaller impact on the outcome if left out. So, initiatives placed in the “could-have” category are often the first to be deprioritized if a project in the “should-have” or “must-have” category ends up larger than expected. 4. Will not have (this time) One benefit of the MoSCoW method is that it places several initiatives in the “will-not-have” category. The category can manage expectations about what the team will not include in a specific release (or another timeframe you’re prioritizing). Placing initiatives in the “will-not-have” category is one way to help prevent scope creep . If initiatives are in this category, the team knows they are not a priority for this specific time frame. Some initiatives in the “will-not-have” group will be prioritized in the future, while others are not likely to happen. Some teams decide to differentiate between those by creating a subcategory within this group. How Can Development Teams Use MoSCoW? Although Dai Clegg developed the approach to help prioritize tasks around his team’s limited time, the MoSCoW method also works when a development team faces limitations other than time. For example: Prioritize based on budgetary constraints. What if a development team’s limiting factor is not a deadline but a tight budget imposed by the company? Working with the product managers, the team can use MoSCoW first to decide on the initiatives that represent must-haves and the should-haves. Then, using the development department’s budget as the guide, the team can figure out which items they can complete. Prioritize based on the team’s skillsets. A cross-functional product team might also find itself constrained by the experience and expertise of its developers. If the product roadmap calls for functionality the team does not have the skills to build, this limiting factor will play into scoring those items in their MoSCoW analysis. Prioritize based on competing needs at the company. Cross-functional teams can also find themselves constrained by other company priorities. The team wants to make progress on a new product release, but the executive staff has created tight deadlines for further releases in the same timeframe. In this case, the team can use MoSCoW to determine which aspects of their desired release represent must-haves and temporarily backlog everything else. What Are the Drawbacks of MoSCoW Prioritization? Although many product and development teams have prioritized MoSCoW, the approach has potential pitfalls. Here are a few examples. 1. An inconsistent scoring process can lead to tasks placed in the wrong categories. One common criticism against MoSCoW is that it does not include an objective methodology for ranking initiatives against each other. Your team will need to bring this methodology to your analysis. The MoSCoW approach works only to ensure that your team applies a consistent scoring system for all initiatives. Pro tip: One proven method is weighted scoring, where your team measures each initiative on your backlog against a standard set of cost and benefit criteria. You can use the weighted scoring approach in ProductPlan’s roadmap app . 2. Not including all relevant stakeholders can lead to items placed in the wrong categories. To know which of your team’s initiatives represent must-haves for your product and which are merely should-haves, you will need as much context as possible. For example, you might need someone from your sales team to let you know how important (or unimportant) prospective buyers view a proposed new feature. One pitfall of the MoSCoW method is that you could make poor decisions about where to slot each initiative unless your team receives input from all relevant stakeholders. 3. Team bias for (or against) initiatives can undermine MoSCoW’s effectiveness. Because MoSCoW does not include an objective scoring method, your team members can fall victim to their own opinions about certain initiatives. One risk of using MoSCoW prioritization is that a team can mistakenly think MoSCoW itself represents an objective way of measuring the items on their list. They discuss an initiative, agree that it is a “should have,” and move on to the next. But your team will also need an objective and consistent framework for ranking all initiatives. That is the only way to minimize your team’s biases in favor of items or against them. When Do You Use the MoSCoW Method for Prioritization? MoSCoW prioritization is effective for teams that want to include representatives from the whole organization in their process. You can capture a broader perspective by involving participants from various functional departments. Another reason you may want to use MoSCoW prioritization is it allows your team to determine how much effort goes into each category. Therefore, you can ensure you’re delivering a good variety of initiatives in each release. What Are Best Practices for Using MoSCoW Prioritization? If you’re considering giving MoSCoW prioritization a try, here are a few steps to keep in mind. Incorporating these into your process will help your team gain more value from the MoSCoW method. 1. Choose an objective ranking or scoring system. Remember, MoSCoW helps your team group items into the appropriate buckets—from must-have items down to your longer-term wish list. But MoSCoW itself doesn’t help you determine which item belongs in which category. You will need a separate ranking methodology. You can choose from many, such as: Weighted scoring Value vs. complexity Kano model Buy-a-feature Opportunity scoring For help finding the best scoring methodology for your team, check out ProductPlan’s article: 7 strategies to choose the best features for your product . 2. Seek input from all key stakeholders. To make sure you’re placing each initiative into the right bucket—must-have, should-have, could-have, or won’t-have—your team needs context. At the beginning of your MoSCoW method, your team should consider which stakeholders can provide valuable context and insights. Sales? Customer success? The executive staff? Product managers in another area of your business? Include them in your initiative scoring process if you think they can help you see opportunities or threats your team might miss. 3. Share your MoSCoW process across your organization. MoSCoW gives your team a tangible way to show your organization prioritizing initiatives for your products or projects. The method can help you build company-wide consensus for your work, or at least help you show stakeholders why you made the decisions you did. Communicating your team’s prioritization strategy also helps you set expectations across the business. When they see your methodology for choosing one initiative over another, stakeholders in other departments will understand that your team has thought through and weighed all decisions you’ve made. If any stakeholders have an issue with one of your decisions, they will understand that they can’t simply complain—they’ll need to present you with evidence to alter your course of action. Related Terms 2×2 prioritization matrix / Eisenhower matrix / DACI decision-making framework / ICE scoring model / RICE scoring model Back to Glossary Talk to an Expert Schedule a few minutes with us to share more about your product roadmapping goals and we'll tailor a demo to show you how easy it is to build strategic roadmaps, align behind customer needs, prioritize, and measure success. 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Report Abuse Brian Douglas for GitHub Posted on Mar 1, 2021 Setup Continuous Delivery with GitHub Actions # github # githubactions # devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions GitHub Actions gets a lot of continuous integration, but what about continuous delivery? In this post, I will share the building blocks for managing the continuous delivery of your project. With this foundation, you can have continuous integration, staging reviews, and production deployments in the same YAML. Using the visualization graph Every workflow run generates a real-time graph that illustrates the run progress. You can use this graph to monitor and debug workflows. The graph displays each job in the workflow. An icon to the left of the job name indicates the status of the job. Lines between jobs indicate dependencies. Dependent jobs By default, the jobs in your workflow all run in parallel at the same time. So if you have a job that must only run after another job has been completed, you can use the needs keyword to create this dependency. If one of the jobs fails, all dependent jobs are skipped; however, if you need the jobs to continue, you can define this using the if conditional statement. In this example, the setup, build, and test jobs run in series, with build and test being dependent on the successful completion of the job that precedes them: jobs : setup : runs-on : ubuntu-latest steps : - run : ./setup_server.sh build : needs : setup runs-on : ubuntu-latest steps : - run : ./build_server.sh test : needs : build runs-on : ubuntu-latest steps : - run : ./test_server.sh Enter fullscreen mode Exit fullscreen mode Environments You can configure environments with protection rules and secrets. When a workflow job references an environment, the job won't start until all of the environment's protection rules pass. A job also cannot access secrets that are defined in an environment until all the environment protection rules pass. Learn more about environments. Build and Deploy Use deployment branches to restrict which branches can deploy to the environment. Below are the options for deployment branches for an environment: All branches: All branches in the repository can deploy to the environment. Protected branches: Only branches with branch protection rules enabled can deploy to the environment. If no branch protection rules are defined for any branch in the repository, then all branches can deploy. For more information about branch protection rules, see "About protected branches." Selected branches: Only branches that match your specified name patterns can deploy to the environment. You can have certain events run for specific branches. You adjust the YAML to include branch names to only run CI checks on branches you needed them. Below is an example with placeholder text for the environment and commands. Please leverage this to get you started, but be sure to replace the text with your build and deploy steps. # This is a basic workflow to help you get started with Actions name : CI/CD # Controls when the action will run. on : # Allows you to run this workflow manually from the Actions tab [ workflow_dispatch , pull_request , push ] # A workflow run is made up of one or more jobs that can run sequentially or in parallel jobs : build : runs-on : ubuntu-latest steps : - uses : actions/checkout@v2 - name : Run a one-line script run : echo Hello, world! - name : Run a multi-line script run : | echo Add other actions to build, echo test, and deploy your project. deploy-staging : needs : [ build ] if : github.ref == 'refs/heads/main' runs-on : ubuntu-latest environment : name : staging url : http://staging.int.foo.com steps : - uses : actions/checkout@v2 - name : Run a one-line script run : echo Hello, world! - name : Run a multi-line script run : | echo Add other actions to build, echo test, and deploy your project. test-site : needs : [ deploy-staging ] runs-on : ubuntu-latest name : Test on ${{ matrix.browser }} strategy : matrix : browser : [ ' edge' , ' chrome' , ' mozilla' ] steps : - name : Run a one-line script run : echo Hello, world! - name : Run a multi-line script run : | echo Add other actions to build, echo test, and deploy your project. deploy-production : needs : [ test-site ] if : github.ref == 'refs/heads/main' runs-on : ubuntu-latest environment : name : production url : http://www.foo.com steps : - uses : actions/checkout@v2 - name : Run a one-line script run : echo Hello, world! - name : Run a multi-line script run : | echo Add other actions to build, echo test, and deploy your project. deploy-review : needs : [ build ] if : github.event_name == 'pull_request' runs-on : ubuntu-latest environment : name : review url : http://review-23.lab.foo.com steps : - uses : actions/checkout@v2 - name : Run a one-line script run : echo Hello, world! - name : Run a multi-line script run : | echo Add other actions to build, echo test, and deploy your project. Enter fullscreen mode Exit fullscreen mode This is part of my 28 days of Actions series. To get notified of more GitHub Action tips, follow the GitHub organization right here on Dev. Learn how to build action with Node.js 01:53 Sync Forks to Upstream Using GitHub Actions Brian Douglas for GitHub ・ Feb 28 '21 #github #devops #githubactions ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. 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Report Abuse Brian Douglas for GitHub Posted on Feb 23, 2021 • Edited on Mar 16, 2021 Bring your own (self-hosted) environment for GitHub Action Workflows # github # devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions You can self-host your runners with customized environments in your GitHub Actions workflows. These runners are available thanks to the fact that GitHub open-sourced their runners on GitHub of course. actions / runner The Runner for GitHub Actions 🚀 GitHub Actions Runner The runner is the application that runs a job from a GitHub Actions workflow. It is used by GitHub Actions in the hosted virtual environments , or you can self-host the runner in your own environment. Get Started For more information about installing and using self-hosted runners, see Adding self-hosted runners and Using self-hosted runners in a workflow Runner releases: Pre-reqs | Download Pre-reqs | Download Pre-reqs | Download Note Thank you for your interest in this GitHub repo, however, right now we are not taking contributions. We continue to focus our resources on strategic areas that help our customers be successful while making developers' lives easier. While GitHub Actions remains a key part of this vision, we are allocating resources towards other areas of Actions and are not taking contributions to this repository at this time. The GitHub public roadmap is the best place to follow… View on GitHub Self-hosted runners offer more control of hardware, operating system, and software tools than GitHub-hosted runners provide. With self-hosted runners, you can choose to create a custom hardware configuration with more processing power or memory to run larger jobs, install software available on your local network, and choose an operating system not offered by GitHub-hosted runners. Self-hosted runners can be physical, virtual, in a container, on-premises, or in a cloud. You can add self-hosted runners at various levels in the management hierarchy: Repository-level runners are dedicated to a single repository. Organization-level runners can process jobs for multiple repositories in an organization. Enterprise-level runners can be assigned to multiple organizations in an enterprise account. 3 Steps to add your own runner 1: Head over to GitHub repo's settings and scroll down to the to add a runner. 2: Here you will find instructions that can be copy and pasted into a virtual or on-premise environment. I will be using a 2018 Macbook Pro (touchbar) and show how to install self-hosted runners to leverage in a workflow in the demo. 3: Finally, replace the runs-on: self-hosted to your action workflow. Some things to consider There are some limits on GitHub Actions usage when using self-hosted runners. These limits are subject to change. Workflow run time - Each workflow run is limited to 72 hours. If a workflow run reaches this limit, the workflow run is canceled. Job queue time - Each job for self-hosted runners can be queued for a maximum of 24 hours. If a self-hosted runner does not start executing the job within this limit, the job is terminated and fails to complete. API requests - You can execute up to 1000 API requests in an hour across all actions within a repository. If exceeded, additional API calls will fail, which might cause jobs to fail. Job matrix - A job matrix can generate a maximum of 256 jobs per workflow run. This limit also applies to self-hosted runners. To learn more about self-hosted runners, check out the GitHub Documentation This is part of my 28 days of Actions series. To get notified of more GitHub Action tips, follow the GitHub organization right here on Dev. Learn how to build action with Node.js 01:58 Sending PR notifications through SMS and GitHub Actions Brian Douglas for GitHub ・ Feb 21 '21 #github #twilio #githubactions #devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. 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Latest News from the Heroku Blog Heroku AI: Accelerating AI Development With New Models, Performance Improvements, and Messages API News Last Updated: December 18, 2025 Anush DSouza This month marks significant expansion for Heroku Managed Inference and Agents , directly accelerating our AI PaaS framework. We’re announcing a substantial addition to our model catalog , providing access to leading proprietary AI models such as Claude Opus 4.5,… Heroku AI: The AI PaaS for Modern Apps Build intelligent applications with managed inference and agents Get Started Now A streamlined platform for building AI-powered apps Heroku is your gateway to building, deploying, and scaling AI-powered applications without the operational complexity. As an AI PaaS, Heroku gives developers the infrastructure, tools, and managed services needed to bring AI apps to life faster. We go beyond the basics by unifying model inference, agents, and seamless interoperability with tools like MCP—all within the trusted Heroku developer experience, with our hallmark simplicity. Heroku brings together the core building blocks needed for AI development: Easy integration of AI models Support for agentic workflows Interoperability between AI and Heroku’s dynamic infrastructure Extensibility through tools like MCP With familiar features like Pipelines and Review Apps, Heroku helps teams iterate quickly and scale AI apps with confidence—backed by the ease, flexibility, and reliability Heroku is known for. Heroku Managed Inference and Agents Build intelligent apps with Heroku Managed Inference and Agents. Access top AI models using a production-ready API, with just a few CLI commands. Heroku Managed Inference and Agents supports a curated set of popular frameworks and models, optimized for performance and cost-efficiency—so you can focus on building, not managing infrastructure. Explore Heroku Managed Inference and Agents MCP (Model Context Protocol) on Heroku Heroku’s MCP Toolkits provide a unified gateway to deploy and manage multiple MCP servers on Heroku. This gives agentic systems like Claude Desktop, Cursor and Heroku Managed Inference and Agents a consistent interface to call APIs and interact with resources, whether they’re running on Heroku or elsewhere. This approach streamlines tool integration, reduces operational overhead, and ensures secure, scalable access to both internal and external services. Explore MCP on Heroku pgvector for Heroku Postgres Enhance your AI applications with vector similarity search using the pgvector extension on Heroku Postgres. Store embeddings, run semantic queries, and power use cases like RAG (retrieval augmented generation) and recommendations—all within your trusted database. Explore pgvector for Heroku Postgres How it works Heroku, a comprehensive AI PaaS, integrates powerful components to bring intelligent capabilities to your application seamlessly. Heroku Managed Inference and Agents provides a comprehensive ecosystem for connecting AI to your application: inference models from top AI providers, embedding generation, vector storage with pgvector for Heroku Postgres and agentic tool calling with MCP – all within Heroku’s trusted infrastructure. Your apps, made smarter Heroku AI is designed for building cloud-native and AI-powered applications and services, accelerating delivery of agentic workflows at scale. Secure, scalable infrastructure Heroku AI runs on Heroku’s proven platform infrastructure, trusted by developers to deploy and scale applications reliably and securely. Whether you’re running a single agent or scaling to thousands, you benefit from Heroku’s mature runtime, built-in security features, and seamless operational experience—all while having access to leading AI models from the world’s top AI providers. Integrated with Heroku developer experience Heroku AI extends the trusted Heroku developer experience to AI use cases. Reduce IT complexity with an integrated platform experience that includes infrastructure, runtime, application, managed inference, agents, AI-native workflows, and developer services. Confidently build and ship AI-powered apps across environments, at scale. Open standards, interoperable tools Heroku AI gives you access to leading AI models, optimized for a range of agentic workflows. It’s built for flexibility—supporting a variety of models, libraries, and development tools—so you can integrate seamlessly with your team’s existing frameworks and build intelligent, responsive applications faster. Get Started Now Heroku AI is ideal for Product teams adding AI-driven features Simplify AI integration. Heroku’s managed platform handles the complexities of inference and agents, freeing up product teams to concentrate on core features. Engineers looking for access to powerful foundation models Get to production faster. Heroku AI services enable you to easily leverage a variety of AI models tailored to your application needs, removing infrastructure hurdles so you can integrate AI into your applications with speed and confidence. Startups iterating fast leveraging managed infrastructure Unleash your AI innovation. Heroku AI services lets you quickly deploy and iterate on intelligent features without infrastructure bottlenecks slowing you down. Enterprises integrating AI into cloud-native architectures Achieve enterprise-grade AI scalability. Built on a next-generation AI PaaS, Heroku AI ensures reliable performance for your critical AI-powered applications at any scale. I was able to get access to using Heroku Managed Inference and Agents and ‘boom’ I’ve got a model running immediately that I can attach to my app and instantly start interacting with and it uses the OpenAI APIs. So all the existing SDKs just work. It saves me so much time and headache. So I can now go and actually run some of these experiments that are critical for some of our new products. Freedom Dumlao Chief Technology Officer, Vestmark Resources Heroku Managed Inference and Agents docs Heroku Managed Inference and Agents Add-on API docs Heroku Managed Inference and Agents Add-on CLI Commands Heroku Managed Inference and Agents Add-on Quick Start Guides Heroku Managed Inference and Agents Available Models docs Heroku Platform MCP Server docs Working with MCP on Heroku pgvector on Heroku Postgres docs Ready to start building with Heroku AI? 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https://www.algolia.com/fr/products/features/analytics/ | Optimisez l’expérience utilisateur avec de puissantes analyses de recherche | Algolia Niket --> Deutsch English français News DevCon2025 | October 1-2 Learn more Algolia Partners Support Login Logout Algolia mark white Algolia logo white Products Search Show users what they're looking for with AI-driven resuts. Search Show users what they're looking for with AI-driven resuts. Recommendations Use behavioral cues to drive higher engagement. Recommendations Use behavioral cues to drive higher engagement. Personalization Show each user what they need across their journey. Personalization Show each user what they need across their journey. Analytics All your insights in one dashboard. Analytics All your insights in one dashboard. Browse Move customers down the funnel with curated category pages. Browse Move customers down the funnel with curated category pages. Agent Studio Create, test, and deploy AI agents, fast. 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https://dev.to/devteam/join-the-google-ai-studio-multimodal-challenge-3000-in-prizes-58g | Join the Google AI Studio Multimodal Challenge: $3,000 in Prizes! - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Jess Lee for The DEV Team Posted on Sep 3, 2025 • Edited on Sep 4, 2025 Join the Google AI Studio Multimodal Challenge: $3,000 in Prizes! # devchallenge # googleaichallenge # ai # gemini We're excited to announce our first challenge with Google AI ! Running through September 14 , the Google AI Studio Multimodal Challenge invites you to build and deploy innovative applets that showcase the incredible power of Gemini's multimodal capabilities. There's one prompt for this challenge but three chances to win! We hope you give it a try. Our Prompt Your mission is to build and deploy an applet on Google AI Studio that shows off the power of Gemini in multimodal content understanding and/or generation. Your applet must meet these requirements: Built on Google AI Studio Deployed using Cloud Run Utilize at least one of the below multimodal functionality: Gemini 2.5 Pro / Flash-supported image, video, or audio understanding Gemini 2.5 Flash Image (free tier available for Sept 6-7) Live API (free tier supports 3 concurrent sessions) Imagen (requires paid tier) Veo (requires paid tier) Think interactive storytelling experiences, tools that process audio and visual content, platforms that understand and generate content across multiple media types. If you can think it, you can build it! Important Notes: Use of paid APIs are purely optional and won't enhance your chance of winning. If you used Gemini 2.5 Flash Image during the free trial period and it is no longer available for your app during the judging period, be sure to include a video so we can see your project in action. "Build Apps with Google AI Studio" DEV Education Track submissions do not count towards this challenge, you must build and deploy a new, original applet. How To Participate To participate, create your Google AI Studio account and publish a post using the submission template below. Your applet should demonstrate creative and practical applications of Gemini's multimodal capabilities. Think beyond basic demos - how can multimodal AI solve real problems or create delightful experiences? Google AI Studio Challenge Submission Template Be sure to review our judging criteria, rules, guidelines, and FAQ page before submitting so you understand our participation guidelines and official contest rules. Please note: additional eligibility requirements are listed below. Prizes We'll select three winners for this challenge. Each winner will receive: $1,000 USD DEV++ Membership Exclusive DEV Badge All Participants with a valid submission will receive a completion badge on their DEV profile. Getting Started with Google AI Studio 🛠️ New to Google AI Studio? You can get to know Google AI Studio by tackling the "Build Apps with Google AI Studio" DEV Education Track: Announcing the First DEV Education Track: "Build Apps with Google AI Studio" Jess Lee for The DEV Team ・ Jul 2 #learngoogleaistudio #ai #deved #gemini DEV Tutorial From prompt to deployed app in less than 2 minutes Paige Bailey for Google AI ・ Jul 2 #webdev #programming #ai #gemini Eligibility Requirements This specific challenge includes the following restrictions: Territories and regions excluded: Afghanistan, Belarus, Central African Republic, Cuba, Equatorial Guinea, Iran, Iraq, Kosovo, Libya, Myanmar (Burma), North Korea, Russia, South Sudan, Sudan, Syria, Tanzania, Venezuela, Yemen, Crimea, the so-called Donetsk People's Republic (DNR), the so-called Luhansk People's Republic (LNR). Additional participant exclusions for this challenge: Government institution employees, Google employees Open only to 18+ These challenge-specific restrictions are in addition to all eligibility requirements and exclusions detailed in our General Contest Official Rules and Google AI Studio Multimodal v25.09.03 Contest Rules . Important Dates September 3: Google AI Studio Multimodal Challenge begins! September 14: Submissions due at 11:59 PM PDT October 2: Winners Announced We can't wait to see the innovative applets you build with Google AI Studio! Questions about the challenge? Ask them below. Good luck and happy coding! Top comments (44) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand Ben Halpern The DEV Team Ben Halpern The DEV Team Ben Halpern Follow A Canadian software developer who thinks he’s funny. Email ben@forem.com Location NY Education Mount Allison University Pronouns He/him Work Co-founder at Forem Joined Dec 27, 2015 • Sep 3 '25 Dropdown menu Copy link Hide This is going to be epic Like comment: Like comment: 10 likes Like Comment button Reply Collapse Expand Noah Brinker The DEV Team Noah Brinker The DEV Team Noah Brinker Follow Marketing @ DEV Joined Apr 4, 2022 • Sep 3 '25 Dropdown menu Copy link Hide Can't wait to see these Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Moinul Moin Moinul Moin Moinul Moin Follow love to build things - Next.js - AI, SaaS, Open Source. If you are building anything with AI, I can help. Email moinulmoin101@gmail.com Location Earth Pronouns he/him Work Founder & Engineer @ Ideaplexa Joined Apr 19, 2020 • Sep 4 '25 Dropdown menu Copy link Hide Thats cool Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Jim Hill The DEV Team Jim Hill The DEV Team Jim Hill Follow Musician and burgeoning game developer :) Joined Aug 2, 2024 • Sep 3 '25 Dropdown menu Copy link Hide This looks awesome Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Dela Dela Dela Follow Joined Oct 31, 2024 • Sep 4 '25 Dropdown menu Copy link Hide Interesting challenge, but I have a question: If I recall correctly, doesn't deploying an applet to Cloud Run require a billing account, which in turn incurs billing for the participant per run? Is the deployment part mandatory? Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Jess Lee The DEV Team Jess Lee The DEV Team Jess Lee Follow Building DEV and Forem with everyone here. Interested in the future. Email jess@forem.com Location USA / TAIWAN Pronouns she/they Work Co-Founder & COO at Forem Joined Jul 29, 2016 • Sep 4 '25 Dropdown menu Copy link Hide Hey @delaaja , great call out. Deployment is required, and Cloud Run actually has a substantial free tier, which should cover anything incurred from our judging usage. Please see this page here to see what's covered, so you can be aware while testing (pre-submission): https://cloud.google.com/run?e=48754805&hl=en#pricing Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Divya Divya Divya Follow A curious lifelong learner, currently a full-time Masters student persuing Computer Science stream. Enthusiastic about development. Joined Jul 9, 2022 • Sep 8 '25 • Edited on Sep 8 • Edited Dropdown menu Copy link Hide Hello mam @jess Can I create the app in Gemini itself, then zip the code, and work on it locally using Gemini CLI? I'll be deploying the app, but not using Cloud Run, but probably Netlify/Vercel. Would it be eligible, or will it make it ineligible for the challenge? Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Naresh Naresh Naresh Follow Joined Sep 9, 2025 • Oct 2 '25 Dropdown menu Copy link Hide But for the api it will charge more Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Sebastian Van Rooyen Sebastian Van Rooyen Sebastian Van Rooyen Follow Joined Mar 13, 2024 • Sep 4 '25 Dropdown menu Copy link Hide Exactly! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Prema Ananda Prema Ananda Prema Ananda Follow Full-stack developer: AI applications, rapid MVPs, database expert (MongoDB, Redis, PostgreSQL). Multi-agent systems specialist. Fixed-price development. Days, not months! Email djoty108@gmail.com Location Ukraine Joined May 24, 2025 • Sep 7 '25 Dropdown menu Copy link Hide Question about contest rules: Hi! I have a question about the development workflow for this challenge. My situation: I created a new, original applet in Google AI Studio specifically for this contest Downloaded the generated code to continue development locally Now I'm enhancing it further using Gemini CLI for additional features and improvements Is this approach compliant with the contest rules? The applet was created from scratch for the challenge, but I'm now developing it further outside of the AI Studio interface using Google's own development tools. Thanks for clarification! Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Olga Braginskaya Olga Braginskaya Olga Braginskaya Follow Oh That Data Girl Anti-Bullshit Enthusiast. Data engineer with a systems mindset, mildly owned by cats. Writing what I wish someone had written earlier. Pronouns she/her Work Senior Data Engineer Joined Mar 22, 2023 • Sep 6 '25 Dropdown menu Copy link Hide To be honest, I don't really understand the point of the challenge. The models that can actually generate something useful are all paid. Fine, I added billing. Now I’ve built a game, and it generates images during gameplay. The limit for the first tier is 70 requests per day. I have 4 images per run, so basically I used up all my requests just this morning and now I can’t even record a video of the game. I’ll have to wait until tomorrow. The third model, imagen-3.0-generate-001, isn’t even available via API, it says it’s not supported. And to move to Tier 2, I apparently need to spend $300 somehow. So overall, it’s not really clear what the organizers were expecting. I'll wait for tomorrow to record my demo videos but overall so far experience is not what I expected for the goal " Think interactive storytelling experiences, tools that process audio and visual content, platforms that understand and generate content across multiple media types ." Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Olga Braginskaya Olga Braginskaya Olga Braginskaya Follow Oh That Data Girl Anti-Bullshit Enthusiast. Data engineer with a systems mindset, mildly owned by cats. Writing what I wish someone had written earlier. Pronouns she/her Work Senior Data Engineer Joined Mar 22, 2023 • Sep 6 '25 Dropdown menu Copy link Hide ok, I found that gemini-2.5-flash-image-preview also can generate images - but Google AI Studio doesn't know how to use this model so in the end I fixed the code by myself. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand sana sana sana Follow Coding enthusiast | MERN | THREE.js | python | photogrammetry | Drones Joined Jan 8, 2025 • Sep 3 '25 Dropdown menu Copy link Hide This looks fun!!! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Shan F Shan F Shan F Follow I am a Computer Science Professional exploring Generative AI Solutions. Location Sri Lanka Pronouns She / Her Work Freelance Consultant Joined Apr 9, 2025 • Sep 14 '25 Dropdown menu Copy link Hide Thanks for hosting the challenge. Here is what I have come up with Google AI Studio's Multimodal powered Disaster Recovery Assistant Tool 🤖 RapidRelief Disaster Recovery Assistant AI 2025: 5X Faster Damage Assessment & Rescue Guide ⚠️🛟 Shan F ・ Sep 14 #devchallenge #googleaichallenge #ai #gemini Checkout and Looking forward to have your constructive feedback Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Sajjad Rahman Sajjad Rahman Sajjad Rahman Follow I am Learning MLOps ( TFX ) . Also an Open Sources Lover. Love to learn together. Location Sylhet, Bangladesh Education B.Sc (Honours) Pronouns he/him Joined Aug 8, 2022 • Sep 7 '25 Dropdown menu Copy link Hide instead of deploy on cloud , can we share the drive link ? Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Divya Divya Divya Follow A curious lifelong learner, currently a full-time Masters student persuing Computer Science stream. Enthusiastic about development. Joined Jul 9, 2022 • Sep 8 '25 Dropdown menu Copy link Hide dev.to/jess/comment/311pa Seems like we need to deploy it. Like comment: Like comment: 1 like Like Comment button Reply View full discussion (44 comments) Some comments may only be visible to logged-in visitors. Sign in to view all comments. Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse The DEV Team Follow The hardworking team behind DEV ❤️ Want to contribute to open source and help make the DEV community stronger? The code that powers DEV is called Forem and is freely available on GitHub. You're welcome to jump in! 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https://www.anthropic.com/news/model-context-protocol#:~:text=to%20scale | Skip to main content Skip to footer Research Economic Futures Commitments Learn News Try Claude Announcements Introducing the Model Context Protocol Nov 25, 2024 Today, we're open-sourcing the Model Context Protocol (MCP), a new standard for connecting AI assistants to the systems where data lives, including content repositories, business tools, and development environments. Its aim is to help frontier models produce better, more relevant responses. As AI assistants gain mainstream adoption, the industry has invested heavily in model capabilities, achieving rapid advances in reasoning and quality. Yet even the most sophisticated models are constrained by their isolation from data—trapped behind information silos and legacy systems. Every new data source requires its own custom implementation, making truly connected systems difficult to scale. MCP addresses this challenge. It provides a universal, open standard for connecting AI systems with data sources, replacing fragmented integrations with a single protocol. The result is a simpler, more reliable way to give AI systems access to the data they need. Model Context Protocol The Model Context Protocol is an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools. The architecture is straightforward: developers can either expose their data through MCP servers or build AI applications (MCP clients) that connect to these servers. Today, we're introducing three major components of the Model Context Protocol for developers: The Model Context Protocol specification and SDKs Local MCP server support in the Claude Desktop apps An open-source repository of MCP servers Claude 3.5 Sonnet is adept at quickly building MCP server implementations, making it easy for organizations and individuals to rapidly connect their most important datasets with a range of AI-powered tools. To help developers start exploring, we’re sharing pre-built MCP servers for popular enterprise systems like Google Drive, Slack, GitHub, Git, Postgres, and Puppeteer. Early adopters like Block and Apollo have integrated MCP into their systems, while development tools companies including Zed, Replit, Codeium, and Sourcegraph are working with MCP to enhance their platforms—enabling AI agents to better retrieve relevant information to further understand the context around a coding task and produce more nuanced and functional code with fewer attempts. "At Block, open source is more than a development model—it’s the foundation of our work and a commitment to creating technology that drives meaningful change and serves as a public good for all,” said Dhanji R. Prasanna, Chief Technology Officer at Block. “Open technologies like the Model Context Protocol are the bridges that connect AI to real-world applications, ensuring innovation is accessible, transparent, and rooted in collaboration. We are excited to partner on a protocol and use it to build agentic systems, which remove the burden of the mechanical so people can focus on the creative.” Instead of maintaining separate connectors for each data source, developers can now build against a standard protocol. As the ecosystem matures, AI systems will maintain context as they move between different tools and datasets, replacing today's fragmented integrations with a more sustainable architecture. Getting started Developers can start building and testing MCP connectors today. All Claude.ai plans support connecting MCP servers to the Claude Desktop app. Claude for Work customers can begin testing MCP servers locally, connecting Claude to internal systems and datasets. We'll soon provide developer toolkits for deploying remote production MCP servers that can serve your entire Claude for Work organization. To start building: Install pre-built MCP servers through the Claude Desktop app Follow our quickstart guide to build your first MCP server Contribute to our open-source repositories of connectors and implementations An open community We’re committed to building MCP as a collaborative, open-source project and ecosystem, and we’re eager to hear your feedback. Whether you’re an AI tool developer, an enterprise looking to leverage existing data, or an early adopter exploring the frontier, we invite you to build the future of context-aware AI together. Related content Advancing Claude in healthcare and the life sciences Claude for Healthcare introduces HIPAA-ready infrastructure for providers and payers, while expanded Life Sciences capabilities add connectors to Medidata and ClinicalTrials.gov for clinical trial operations and regulatory work. Read more Sharing our compliance framework for California's Transparency in Frontier AI Act Read more Working with the US Department of Energy to unlock the next era of scientific discovery Read more Products Claude Claude Code Claude in Chrome Claude in Excel Claude in Slack Skills Max plan Team plan Enterprise plan Download app Pricing Log in to Claude Models Opus Sonnet Haiku Solutions AI agents Code modernization Coding Customer support Education Financial services Government Healthcare Life sciences Nonprofits Claude Developer Platform Overview Developer docs Pricing Regional Compliance Amazon Bedrock Google Cloud’s Vertex AI Console login Learn Blog Claude partner network Connectors Courses Customer stories Engineering at Anthropic Events Powered by Claude Service partners Startups program Tutorials Use cases Company Anthropic Careers Economic Futures Research News Responsible Scaling Policy Security and compliance Transparency Help and security Availability Status Support center Terms and policies Privacy policy Consumer health data privacy policy Responsible disclosure policy Terms of service: Commercial Terms of service: Consumer Usage policy © 2025 Anthropic PBC Introducing the Model Context Protocol \ Anthropic | 2026-01-13T08:49:36 |
https://slack.com | Slack | AI Work Platform & Productivity Tools Skip to main content Features COLLABORATION Channels Organize teams and work Slack Connect Work with external partners Messaging Chat with your team Huddles Meet with audio and video Clips Record and share updates CRM Salesforce in Slack Bring Salesforce into the flow of work PROJECT MANAGEMENT Templates Start any task, fast Canvas Create rich, flexible docs Lists Organize, track and manage projects File Sharing Bring files to the flow of work PLATFORM Agentic Platform Customize, extend, and unify your tech stack in Slack Apps & Integrations Connect your tools with Slack Workflow Builder Automate everyday tasks INTELLIGENCE AI in Slack Save time and work smarter with powerfully simple AI Agentforce Empower your whole team with AI-powered agents in Slack Enterprise Search Find anything, all from a single search bar ADMIN & SECURITY Security Protect data, ensure compliance Enterprise Key Management Monitor and revoke access Slack Atlas Discover rich profiles and org charts Watch demo Download Slack Slack Marketplace Find new agents and apps that fit your team’s needs. Browse marketplace What is Slack? Slack vs. Email Accessibility Solutions BY DEPARTMENT Engineering IT Customer Service Sales Project Management Marketing Human Resources Security BY INDUSTRY Manufacturing, Auto & Energy Technology Media Small Business Financial Services Retail Education Health & Life Sciences Watch demo Download Slack See all solutions TEMPLATE GALLERY Start work faster with pre-made templates for every task. See all templates Task Management Scale Engagement Trust Enterprise Resources Resources Library What’s New Product Tour Events Developers Partners Customer Stories Community Slack Certified Blog Slack Marketplace Watch demo Download Slack FEATURED Tips and tricks on getting started with Slack Get started Help Center Customer Support Pricing Search Sign in Request a demo Get started Get started Back Features COLLABORATION Channels Organize teams and work Slack Connect Work with external partners Messaging Chat with your team Huddles Meet with audio and video Clips Record and share updates CRM Salesforce in Slack Bring Salesforce into the flow of work PROJECT MANAGEMENT Templates Start any task, fast Canvas Create rich, flexible docs Lists Organize, track and manage projects File Sharing Bring files to the flow of work PLATFORM Agentic Platform Customize, extend, and unify your tech stack in Slack Apps & Integrations Connect your tools with Slack Workflow Builder Automate everyday tasks INTELLIGENCE AI in Slack Save time and work smarter with powerfully simple AI Agentforce Empower your whole team with AI-powered agents in Slack Enterprise Search Find anything, all from a single search bar ADMIN & SECURITY Security Protect data, ensure compliance Enterprise Key Management Monitor and revoke access Slack Atlas Discover rich profiles and org charts Watch demo Download Slack Slack Marketplace Find new agents and apps that fit your team’s needs. Browse marketplace What is Slack? Slack vs. Email Accessibility Solutions BY DEPARTMENT Engineering IT Customer Service Sales Project Management Marketing Human Resources Security BY INDUSTRY Manufacturing, Auto & Energy Technology Media Small Business Financial Services Retail Education Health & Life Sciences Watch demo Download Slack See all solutions TEMPLATE GALLERY Start work faster with pre-made templates for every task. See all templates Task Management Scale Engagement Trust Enterprise Resources Resources Library What’s New Product Tour Events Developers Partners Customer Stories Community Slack Certified Blog Slack Marketplace Watch demo Download Slack FEATURED Tips and tricks on getting started with Slack Get started Help Center Customer Support Pricing Sign in Request a demo Download Slack Close Navigation Close Navigation Slack is your team's collective brain. Move faster and work smarter, with people, apps, and AI at your side. Get started Find your plan Trusted by top teams Plan launches Run projects Chat with clients Ask an agent Automate tasks Plan launches Run projects Chat with clients Ask an agent Automate tasks Reimagine what’s possible with AI and agents. AI in Slack doesn’t make you think, it helps you do. It summarizes and searches based on actual conversations, and with it, makes every app and agent more helpful and contextually aware than ever. Organize your day with Slackbot Summarize a conversation you missed Get fast answers with Claude Turn on AI note-taking in huddles Review code with Github Copilot Lookup customer data in Agentforce Organize your day with Slackbot Summarize a conversation you missed Get fast answers with Claude Turn on AI note-taking in huddles Review code with Github Copilot Lookup customer data in Agentforce Knowledge People Process Platform Knowledge Give everyone instant context. Get access to every file, decision, and conversation, so you can build on past work instead of recreating it. One search to rule them all. AI-powered search puts your company’s entire memory at your fingertips. Learn about AI-powered search Bring CRM data to the conversation. Customer insights now live alongside conversations, so deals keep moving forward. Learn about Salesforce in Slack Give your team a team of agents. There’s an AI agent for every team (and every task) in Slack. See all available AI agents 97 min average time users can save weekly with AI in Slack 1 People Let your people connect like people. Slack’s conversational UI makes collaborating more approachable, whether you're working with a colleague or an agent. It all starts with a channel. Channels are flexible, transparent spaces for working with your team, AI assistants, and agents. Learn about channels When talking is easier than typing… …hop on a huddle, our built-in video tool. With AI in Slack, your meeting notes take themselves. Learn about huddles Bring conversations out of the inbox. Slack Connect lets you chat with clients and vendors in real-time, right from Slack. Email could never. Learn about Slack connect “Slack has been essential to our growth, our speed, and our ability to stay aligned as we scale” Kate Jenson, Head of Americas, Anthropic Process Manage all your work from one place. Automate daily stand-ups, project updates, and approvals so your team can focus on growth instead of guesswork. Anyone can automate in Slack. By click or by code, Slack makes it easy for anyone to build time-saving automations of their own. Learn about workflows Manage projects and tasks. Track. Approve. Mark as complete. All without leaving the conversation. Learn about lists A simpler way to get started. Project manager's block? Beginning a brief? There’s a template for that. See all templates 35% increase in time saved due to automations for Slack users 2 Platform Secure. Scaleable. Silo-free. Our flexible, open platform is purpose-built for bringing the best agents and AI to every business, and can be tailored to fit however your teams work best. From Atlassian to Zoom. Google Drive. ChatGPT. Vercel. Box. Asana. Workday. You name it, it works in Slack. See all integrations Customize Slack to fit your needs. Our platform is flexible so you can build solutions specific to your business. Learn about dev tools Work without worry. If it’s shared in Slack, it’s safe. Our security program protects your data at every layer. Learn about security “Work starts in conversation. That’s why we see Slack as the natural place to build our agents.” Guillermo Rauch, CEO, Vercel The most innovative companies run their business in Slack. How OpenAI Connects with Customers and Expands ChatGPT with Slack Slack helps Box bring agents to every employee Caraway Brings All The Right Ingredients Together In Slack Slack helps Rivian do business in the fast lane How OpenAI Connects with Customers and Expands ChatGPT with Slack Slack helps Box bring agents to every employee Caraway Brings All The Right Ingredients Together In Slack Slack helps Rivian do business in the fast lane Get Started Find Your Plan We’re in the business of growing businesses. 90 % of users say Slack helps them stay more connected 4 43 The average number of apps used by teams in Slack 3 87 % of users say Slack helps them collaborate more efficiently 4 Millions of people love to work in Slack. 700M Messages sent daily 3 4M Slack Connect users working directly with external teams each week 3 3M Daily Workflows 3 1.7M Apps actively used each week 3 Don’t just take our word for it. Slack is a leader in over 314 G2 market reports. 5 Your Slack deep dive starts here. Link may open in new tab Event Ready for the future of AI in Slack? Watch on-demand Link may open in new tab Webinar Unlock Agentic Productivity for Every Employee Watch Now Link may open in new tab Blog Agentforce 2.0: Agentforce Arrives in Slack Read Now Link may open in new tab Guide 10 Ways to Replace Ineffective Meetings with Slack Read more Link may open in new tab Event Ready for the future of AI in Slack? Watch on-demand Link may open in new tab Webinar Unlock Agentic Productivity for Every Employee Watch Now Link may open in new tab Blog Agentforce 2.0: Agentforce Arrives in Slack Read Now Link may open in new tab Guide 10 Ways to Replace Ineffective Meetings with Slack Read more 1 Based on an internal analysis during the pilot of AI in Slack features (channel recaps, thread summaries, and AI search answers). 2 FY24 Customer Success Metrics. Base: Total n = 247-1,696, Slack internal data. 3 FY25 Slack internal data, product usage analysis. 4 FY25 Slack Customer Tracking Survey. Internal survey of weekly active Slack users in the US, UK, CA, and AU. Total n = 2,410. 5 G2 Winter 2026 market reports for work management, workflow management, project collaboration software, enterprise search, knowledge base, employee Q&A, audio conferencing, business instant messaging, unified workspaces and more. See all you can accomplish in Slack. Get started Request a demo esc Change Region Selecting a different region will change the language and content of slack.com. Americas Latinoamérica (español) Brasil (português) United States (English) Europe Deutschland (Deutsch) España (español) France (français) Italia (italiano) United Kingdom (English) Asia Pacific 简体中文 繁體中文 India (English) 日本 (日本語) 대한민국 (한국어) Change Region Product Product Watch Demo Pricing Paid vs. Free Accessibility Featured Releases Changelog Status Why Slack? Why Slack? Slack vs. Email Slack vs. Teams Enterprise Small Business Productivity Task Management Scale Trust Features Features Channels Slack Connect Workflow Builder Messaging Huddles Canvas Lists Clips Apps & Integrations File Sharing Slack AI Agentforce Enterprise Search Security Enterprise Key Management Slack Atlas See all features Solutions Solutions Engineering IT Customer Service Sales Project Management Marketing Security Manufacturing, Auto & Energy Technology Media Financial Services Retail Public Sector Education Health & Life Sciences See all solutions Resources Resources Help Center What’s New Resources Library Slack Blog Community Customer Stories Events Developers Partners Partner Offers Slack Marketplace Slack Certified Company Company About Us News Media Kit Brand Center Careers Swag Store Engineering Blog Design Blog Contact Us Download Slack Privacy Terms Cookie Preferences Your Privacy Choices ©2026 Slack Technologies, LLC, a Salesforce company. All rights reserved. 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https://dev.to/leon0824 | Leon - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Leon 404 bio not found Joined Joined on Aug 12, 2018 Personal website https://leonh.space/ github website twitter website Seven Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least seven years. Got it Close Six Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least six years. Got it Close Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close Five Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least five years. 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centos # nginx 3 reactions Comments Add Comment 1 min read Odoo 安裝 Leon Leon Leon Follow May 1 '22 Odoo 安裝 # odoo 12 reactions Comments Add Comment 1 min read 自學的 SoloLearn Leon Leon Leon Follow Apr 22 '22 自學的 SoloLearn # sololearn 3 reactions Comments Add Comment 1 min read 給 PHP 開發者的 Docker 文件（六） Leon Leon Leon Follow Apr 21 '22 給 PHP 開發者的 Docker 文件（六） 5 reactions Comments Add Comment 1 min read 給 PHP 開發者的 Docker 文件（五） Leon Leon Leon Follow Feb 18 '22 給 PHP 開發者的 Docker 文件（五） # php # docker 7 reactions Comments Add Comment 1 min read 給 PHP 開發者的 Docker 文件（四） Leon Leon Leon Follow Feb 17 '22 給 PHP 開發者的 Docker 文件（四） # php # docker 5 reactions Comments 1 comment 2 min read 給 PHP 開發者的 Docker 文件（三） Leon Leon Leon Follow Feb 13 '22 給 PHP 開發者的 Docker 文件（三） 4 reactions Comments Add Comment 1 min read 給 PHP 開發者的 Docker 文件（二） Leon Leon Leon Follow Jan 19 '22 給 PHP 開發者的 Docker 文件（二） # docker # php Comments Add Comment 1 min read 給 PHP 開發者的 Docker 文件（一） Leon Leon Leon Follow Jan 18 '22 給 PHP 開發者的 Docker 文件（一） # 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aws # ebs Comments Add Comment 1 min read 以 Authlib 實現 OAuth 1 的 Twitter 登入 Leon Leon Leon Follow Nov 25 '21 以 Authlib 實現 OAuth 1 的 Twitter 登入 # oauth # twitter # authlib # python 2 reactions Comments Add Comment 5 min read 升級裝有 Plesk 的 Ubuntu 16.04 Leon Leon Leon Follow Nov 24 '21 升級裝有 Plesk 的 Ubuntu 16.04 # ubuntu # plesk 1 reaction Comments Add Comment 2 min read Python Log 從小白到入門 Leon Leon Leon Follow Nov 23 '21 Python Log 從小白到入門 # python # logging 7 reactions Comments Add Comment 3 min read 如何在 Jupyter Notebook 跑 Python 異步程式 Leon Leon Leon Follow Nov 22 '21 如何在 Jupyter Notebook 跑 Python 異步程式 # python # jupyter # async 1 reaction Comments Add Comment 1 min read 你的資料庫支援時間資料型別嗎？ Leon Leon Leon Follow Nov 18 '21 你的資料庫支援時間資料型別嗎？ # database # json # nosql 3 reactions Comments Add Comment 2 min read Orator ORM 的 Seeding 機制 Leon Leon Leon Follow Nov 15 '21 Orator ORM 的 Seeding 機制 # python # orm # orator 1 reaction Comments Add Comment 2 min read 初探 Orator ORM Leon Leon Leon Follow Nov 14 '21 初探 Orator ORM # python # orm # orator 4 reactions Comments Add Comment 5 min read 初探 Strapi Headless CMS Leon Leon Leon Follow Nov 14 '21 初探 Strapi Headless CMS # strapi # cms # headless 6 reactions Comments Add Comment 2 min read 建置 Python 3 開發環境 Leon Leon Leon Follow Nov 13 '21 建置 Python 3 開發環境 # python 2 reactions Comments Add Comment 5 min read MailPoet 為 WordPress 量身設計的發信服務 Leon Leon Leon Follow Nov 12 '21 MailPoet 為 WordPress 量身設計的發信服務 # wordpress # mailpoet 3 reactions Comments Add Comment 1 min read Plesk / Cloudflare / Lightsail 混合架構的安全規劃 Leon Leon Leon Follow Nov 11 '21 Plesk / Cloudflare / Lightsail 混合架構的安全規劃 # plesk # cloudflare # lightsail # firewall 2 reactions Comments Add Comment 2 min read 為什麼你的個資會外洩？談社交工程 Leon Leon Leon Follow Nov 10 '21 為什麼你的個資會外洩？談社交工程 # 社交工程 # 詐騙 3 reactions Comments Add Comment 1 min read 靜態網站產生器 Zola Leon Leon Leon Follow Nov 8 '21 靜態網站產生器 Zola # zola # ssg 5 reactions Comments Add Comment 3 min read Google Search Console 的「已檢索」、「已找到」是什麼意思？ Leon Leon Leon Follow Nov 7 '21 Google Search Console 的「已檢索」、「已找到」是什麼意思？ # google # seo 2 reactions Comments Add Comment 1 min read Rapid Environment Editor 設定 Windows 環境變數的工具 Leon Leon Leon Follow Nov 6 '21 Rapid Environment Editor 設定 Windows 環境變數的工具 # windows 2 reactions Comments Add Comment 1 min read Rules Engine 規則引擎 Leon Leon Leon Follow Nov 5 '21 Rules Engine 規則引擎 # rulesengine # rete 2 reactions Comments Add Comment 1 min read KeePass 密碼管理器 Leon Leon Leon Follow Nov 4 '21 KeePass 密碼管理器 # keepass # password 2 reactions Comments Add Comment 1 min read 如何理解 Jira 的 Story Leon Leon Leon Follow Nov 3 '21 如何理解 Jira 的 Story # jira 1 reaction Comments Add Comment 1 min read Cockpit 高大上的 Linux Web 管理介面 Leon Leon Leon Follow Nov 2 '21 Cockpit 高大上的 Linux Web 管理介面 # cockpit # linux 4 reactions Comments Add Comment 1 min read 自己的 VPN 自己建，用 ZeroTier 建構自己的虛擬內網 Leon Leon Leon Follow Oct 31 '21 自己的 VPN 自己建，用 ZeroTier 建構自己的虛擬內網 # zerotier # vpn 4 reactions Comments Add Comment 1 min read 用 Spectron 對 Electron App 做測試 Leon Leon Leon Follow Oct 30 '21 用 Spectron 對 Electron App 做測試 # 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Report Abuse Brian Douglas for GitHub Posted on Feb 28, 2021 • Edited on Mar 1, 2021 Sync Forks to Upstream Using GitHub Actions # github # githubactions # devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions Most challenging and severely under-documented in open source is how to keep your fork updated with the upstream. There are a lot of unwritten rules in open source and inconsistencies between how projects approach contributions—your best chance for understanding that per project is the CONTRIBUTING.md. When I started contributing to open source, I always deleted my forks when my contribution merged; This can be tedious and overwhelming if you are working with many repositories. Below is the workflow I leverage to keep bdougie/open-sauced-goals repo synced with the upstream. // https://github.com/open-sauced/goals-template/blob/main/.github/workflows/sync-2-upstream.yml name : Sync to Upstream on : schedule : - cron : ' 12 7 * * 1,4' # scheduled at 07:12 every Monday and Thursday workflow_dispatch : jobs : sync_with_upstream : runs-on : ubuntu-latest name : Sync HEAD with upstream latest steps : # Step 1: run a standard checkout action, provided by github - name : Checkout HEAD uses : actions/checkout@v2 with : ref : main # Step 2: run this sync action - specify the upstream repo, upstream branch to sync with, and target sync branch - name : Pull upstream changes id : sync uses : bdougie/Fork-Sync-With-Upstream-action@fork with : upstream_repository : open-sauced/goals-template upstream_branch : main target_branch : main # optional github_token : ${{ secrets.GITHUB_TOKEN }} # optional, for accessing repos that require authentication Enter fullscreen mode Exit fullscreen mode To make my action work, I forked an existing GitHub Action to add specific changes I needed. Consider checking out the original. aormsby / Fork-Sync-With-Upstream-action An action to automatically update your fork with new commits from the upstream repo Also, consider checking opensource.guides for more information on how to contribute to open source. This is part of my 28 days of Actions series. To get notified of more GitHub Action tips, follow the GitHub organization right here on Dev. Learn how to build action with Node.js 01:43 Repository Automation with GitHub Actions Brian Douglas for GitHub ・ Feb 25 '21 #github #githubactions #devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions Top comments (1) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand Brian Douglas Brian Douglas Brian Douglas Follow Brian writes code Location Oakland, CA Pronouns he/him Work Head of DX Joined May 27, 2017 • Mar 1 '21 Dropdown menu Copy link Hide GitHub Actions now provides timestamps by default with "shift + T" in the logs. Like comment: Like comment: 1 like Like Comment button Reply Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse GitHub Follow Let's build from here_ Celebrate 20 years of Git at Git Merge 2025 . Join developers from around the world this September in San Francisco. Get your ticket More from GitHub Speed Up Your CI/CD: ARM 64 Runners for GitHub Actions # programming # githubactions # cicd # devops Showcase your open source project at SCALE 🐧 Pasadena, CA · March 6-9, 2025 # github # linux # opensource Release Radar · September 2024: Major updates from the open source community # github # community # opensource # hacktoberfest 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.anthropic.com/claude/sonnet#:~:text=Claude%203,a%20variety%20of%20use%20cases | Skip to main content Skip to footer Research Economic Futures Commitments Learn News Try Claude Claude Sonnet 4.5 Hybrid reasoning model with superior intelligence for agents, and 200K context window Try Claude Get API access Announcements New Claude Sonnet 4.5 Sep 29, 2025 Sonnet 4.5 is the best model in the world for agents, coding, and computer use. It’s also our most accurate and detailed model for long-running tasks, with enhanced domain knowledge in coding, finance, and cybersecurity. Read more Claude Sonnet 4 May 22, 2025 Sonnet 4 improves on Sonnet 3.7 across a variety of areas, especially coding. It offers frontier performance that’s practical for most AI use cases, including user-facing AI assistants and high-volume tasks. Read more Claude Sonnet 3.7 and Claude Code Feb 24, 2025 Sonnet 3.7 is the first hybrid reasoning model and our most intelligent model to date. It’s state-of-the art for coding and delivers significant improvements in content generation, data analysis, and planning. Read more Availability and pricing Anyone can chat with Claude using Sonnet 4.5 on Claude.ai, available on web, iOS, and Android. For developers interested in building agents, Sonnet 4.5 is available on the Claude Developer Platform natively, and in Amazon Bedrock, Google Cloud's Vertex AI, and Microsoft Foundry. Pricing for Sonnet 4.5 starts at $3 per million input tokens and $15 per million output tokens, with up to 90% cost savings with prompt caching and 50% cost savings with batch processing . To learn more, check out our pricing page. To get started, simply use claude-sonnet-4-5 via the Claude API . Use cases Sonnet 4.5 is a powerful, versatile model—built for daily use, scaled production, and complex tasks. Sonnet 4.5 can produce near-instant responses or extended, step-by-step thinking that is made visible to the user. API users also have fine-grained control over how long the model thinks. Popular use cases include: Long-running agents Sonnet 4.5 offers superior instruction following, tool selection, error correction, and advanced reasoning for customer-facing agents and complex AI workflows. Code generation Sonnet 4.5 is a powerful choice for agentic coding, and can complete tasks across the entire software development lifecycle, from initial planning to bug fixes, maintenance to large refactors. It offers strong performance in both planning and solving for complex coding tasks, making it an ideal choice to power end-to-end software development processes. Sonnet 4.5 supports up to 64K output tokens, which is particularly valuable for rich code generation and planning. Browser and computer use Sonnet 4.5 excels in computer use capabilities, reliably handling any browser-based task from competitive analysis to procurement workflows to customer onboarding. Sonnet 3.5 was the first frontier AI model to be able to use computers in this way. Sonnet 4.5 uses computers even more accurately and reliably, and we expect the capability to improve over time. Cybersecurity Teams using Sonnet 4.5 with Claude Code can deploy agents that autonomously patch vulnerabilities before exploitation, shifting from reactive detection to proactive defense. Financial analysis Sonnet 4.5 handles everything from entry-level financial analysis to advanced predictive analysis. For example, it can continuously monitor global regulatory changes and preemptively adapt compliance systems, evolving beyond manual audit preparation to intelligent risk management. Business tasks Sonnet 4.5 excels at producing and editing office files like slides, documents, and spreadsheets. Research Sonnet 4.5 can search through external and internal data sources to synthesize comprehensive insights across complex information landscapes. Content generation and analysis Sonnet 4.5 excels at writing and can understand nuance and tone to generate more compelling content and analyze content on a deeper level. Benchmarks Sonnet 4.5 is our powerful and versatile model for everyday use, combining strong reasoning with efficient performance. It excels at powering agents for financial analysis, cybersecurity, and research—coordinating multiple agents and processing high volumes of data with the reliability these domains demand. Trust & Safety We ’ ve conducted extensive testing and evaluation of Sonnet 4.5, working with external experts to ensure it meets our standards for safety, security, and reliability. In the model card for this release, we discuss new safety results in several categories. Hear from our customers We're seeing state-of-the-art coding performance from Claude Sonnet 4.5, with significant improvements on longer horizon tasks. It reinforces why many developers using Cursor choose Claude for solving their most complex problems. Michael Truell Co-founder and CEO , Cursor Claude Sonnet 4.5 amplifies GitHub Copilot's core strengths. Our initial evals show significant improvements in multi-step reasoning and code comprehension—enabling Copilot's agentic experiences to handle complex, codebase-spanning tasks better. We expect these gains to deliver meaningful value to developers moving from idea to implementation with confidence. Mario Rodriguez Chief Product Officer , Github Claude Sonnet 4.5 reduced average vulnerability intake time for our Hai security agents by 44% while improving accuracy by 25%, helping us reduce risk for businesses with confidence. Nidhi Aggarwal Chief Product Officer , HackerOne For Devin, Claude Sonnet 4.5 increased planning performance by 18% and end-to-end eval scores by 12%—the biggest jump we've seen since the release of Claude Sonnet 3.6. It excels at testing its own code, enabling Devin to run longer, handle harder tasks, and deliver production-ready code more consistently. Scott Wu Co-founder & CEO , Cognition Claude Sonnet 4.5 is state of the art on the most complex litigation tasks. For example, analyzing full briefing cycles and conducting research to synthesize excellent first drafts of an opinion for judges, or interrogating entire litigation records to create detailed summary judgment analysis. Pablo Arredondo Vice President, CoCounsel , Thomson Reuters Claude Sonnet 4.5's edit capabilities are exceptional — we went from 9% error rate on Sonnet 4 to 0% on our internal code editing benchmark. Higher tool success at lower cost is a major leap for agentic coding. Claude Sonnet 4.5 balances creativity and control perfectly, thoroughly completing tasks without over-engineering. Michele Catasta President , Replit For complex financial analysis—risk, structured products, portfolio screening—Claude Sonnet 4.5 with thinking delivers investment-grade insights that require less human review. When depth matters more than speed, it's a meaningful step forward for institutional finance. Stian Kirkeberg Head of AI and Machine Learning , Norges Bank Investment Management Claude Sonnet 4.5 delivers measurable improvements for Next.js tasks. It is particularly good at building and linting Next.js code, showing up to a 17% improvement over its predecessor. We're excited to integrate it into v0 and AI Gateway at launch, giving developers instant access to these advances. Guillermo Rauch CEO , Vercel Sonnet 4.5 is state-of-the-art for real-world, agentic enterprise workflows. We've seen a leap in reasoning capabilities within Snowflake Intelligence—enabling customers to extract deeper, more actionable insights from their data. Baris Gultekin VP of AI , Snowflake Claude Sonnet 4.5 resets our expectations—it handles 30+ hours of autonomous coding, freeing our engineers to tackle months of complex architectural work in dramatically less time while maintaining coherence across massive codebases. Sean Ward CEO & Co-Founder , iGent Claude Sonnet 4.5 delivers clear wins over Sonnet 4: sharper instruction-following, stronger planning, smarter parallelization. Tasks require fewer iterations, which is critical for our most demanding agentic workflows. Ankit Shankar AIP Product Lead , Palantir Claude Sonnet 4.5 shows strong promise for red teaming, generating creative attack scenarios that accelerate how we study attacker tradecraft. These insights strengthen our defenses across endpoints, identity, cloud, data, SaaS, and AI workloads. Sven Krasser Sr. Vice President for Data Science and Chief Scientist , Crowdstrike Claude Sonnet 4.5 is excellent at software development tasks, learning our codebase patterns to deliver precise implementations. It handles everything from debugging to architecture with deep contextual understanding, transforming our development velocity. Eric Wendelin Tech Lead, GenAI for Developer Productivity , Netflix 01 / 13 See Claude in action Coding What should I look for when reviewing a Pull Request for a Python web app? Ask Claude Writing Create a 3-month editorial calendar template for a weekly newsletter Ask Claude Students What's an effective study schedule template for final exams? Ask Claude Frequently asked questions When should I use Claude Sonnet 4.5? We offer different models across the spectrum of speed, price, and performance. Sonnet 4.5 delivers superior intelligence with optimal efficiency for high-volume use cases. We recommend Sonnet 4.5 for most AI applications where you need a balance of advanced capabilities and practical throughput—such as customer-facing agents, production coding workflows, content generation at scale, and real-time research tasks. How much does it cost to use Claude Sonnet 4.5 Pricing depends on how you want to use Sonnet 4.5. To learn more, check out our pricing page . When should I use extended thinking? Sonnet 4.5 is both a standard model and a hybrid reasoning model in one: you can pick when you want the model to answer normally and when you want it to use extended thinking. Extended thinking mode is best when performance and accuracy matter more than latency. It significantly improves response quality for complex reasoning tasks, extended agentic work, multi-step coding projects, and deep research. Thinking summaries help you understand key aspects of the model's reasoning process. Products Claude Claude Code Claude in Chrome Claude in Excel Claude in Slack Skills Max plan Team plan Enterprise plan Download app Pricing Log in to Claude Models Opus Sonnet Haiku Solutions AI agents Code modernization Coding Customer support Education Financial services Government Healthcare Life sciences Nonprofits Claude Developer Platform Overview Developer docs Pricing Regional Compliance Amazon Bedrock Google Cloud’s Vertex AI Console login Learn Blog Claude partner network Connectors Courses Customer stories Engineering at Anthropic Events Powered by Claude Service partners Startups program Tutorials Use cases Company Anthropic Careers Economic Futures Research News Responsible Scaling Policy Security and compliance Transparency Help and security Availability Status Support center Terms and policies Privacy policy Consumer health data privacy policy Responsible disclosure policy Terms of service: Commercial Terms of service: Consumer Usage policy © 2025 Anthropic PBC Claude Sonnet 4.5 \ Anthropic | 2026-01-13T08:49:36 |
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Right menu Mastering End to End testing for Reliable Modern Software Alok Kumar Alok Kumar Alok Kumar Follow Nov 5 '25 Mastering End to End testing for Reliable Modern Software # software # testing # webdev # programming Comments 1 comment 5 min read The Four Types of Software Maintenance Theekshana Udara Theekshana Udara Theekshana Udara Follow Nov 19 '25 The Four Types of Software Maintenance # software # softwaredevelopment # softwareengineering Comments Add Comment 1 min read The Secret Life of Python: Generator Secrets - Functions That Remember Aaron Rose Aaron Rose Aaron Rose Follow Nov 10 '25 The Secret Life of Python: Generator Secrets - Functions That Remember # python # coding # programming # software 2 reactions Comments Add Comment 17 min read The Reality of "Autonomous" Multi-Agent Development Aviad Rozenhek Aviad Rozenhek Aviad Rozenhek Follow Nov 6 '25 The Reality of "Autonomous" Multi-Agent Development # ai # agents # software # vibecoding Comments Add Comment 8 min read Rust chronicles #1 - the beginning Malek Malek Malek Follow Dec 8 '25 Rust chronicles #1 - the beginning # rust # beginners # programming # software Comments Add Comment 4 min read Why LED Lighting Is More of a Software Problem Than We Think emmma emmma emmma Follow Dec 8 '25 Why LED Lighting Is More of a Software Problem Than We Think # led # software Comments 1 comment 2 min read Delivering Greenfield Projects: Getting the Foundations Right Audacia Audacia Audacia Follow Nov 3 '25 Delivering Greenfield Projects: Getting the Foundations Right # greenfield # software # cloud # devops Comments Add Comment 8 min read Don't get scammed on an interview. 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https://infisical.com/blog/vibe-coding-security-playbook#:~:text=According%20to%20a%20recent%20report,higher%20rate%20of%20secret%20exposure | A Vibe Coding Security Playbook: Keeping AI-Generated Code Safe Infisical Stars Docs Careers Blog Pricing Get a Demo Sign Up ← Back Blog post • 10 min read A Vibe Coding Security Playbook: Keeping AI-Generated Code Safe Published on Wednesday, April 2, 2025 What's Vibe Coding? Vibe coding is a new term coined by Andrej Karpathy to describe a new approach to software development that leverages AI tools to handle most of the coding work. In a tweet that went viral, he explained: There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists . It's possible because the LLMs (e.g. Cursor Composer w Sonnet) are getting too good. Also I just talk to Composer with SuperWhisper so I barely even touch the keyboard. [...] I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works. Vibe coding involves heavy reliance on AI tools to generate, refine, and debug code, allowing developers to rapidly iterate and deploy applications with minimal manual coding effort. This practice is rapidly gaining popularity and has since been featured in the New York Times , Ars Technica , the Guardian and countless online discussions. It's particularly appealing to people who don't speak code yet want to create their own app, for fun or even for profit. Yet, over-reliance on AI-generated code can lead to security vulnerabilities, inefficiencies, and errors if not carefully reviewed by developers. The OWASP Top 10: A Security Foundation for Vibe Coders Before diving into specific vulnerabilities, let's establish why security matters for vibe coders. The OWASP Top 10 represents the most critical web application security risks and provides an excellent framework for understanding potential issues in AI-generated code. AI code generators have specific limitations that make them prone to introducing these security issues: Limitation Description Security Impact Pattern Reproduction AIs replicate code patterns from training data without understanding security implications May reproduce vulnerable code that's common in public repositories Context Blindness AI lacks awareness of the broader application security context Generates code that might be secure in isolation but creates vulnerabilities when integrated Training on Legacy Code Large portions of training data contain outdated security practices Propagates deprecated patterns that don't meet modern security standards Incomplete Implementation AI focuses on functional requirements rather than security requirements Omits crucial validation, error handling, and security checks Major Security Risks in AI-Generated Code Let's examine the most critical security vulnerabilities you're likely to encounter when using AI coding assistants, with practical examples and solutions for each. 1. Data Security Vulnerabilities Hardcoded Credentials and Exposed Secrets AI code assistants frequently suggest hardcoding credentials directly in source code. Consider this example: import { Pool } from 'pg' ; // Create a connection pool to PostgreSQL const pool = new Pool ( { user : 'postgres' , host : 'localhost' , database : 'myapp' , password : 'admin123' , // Hardcoded password! port : 5432 , } ) ; This approach creates serious vulnerabilities because: Credentials are visible to anyone with access to the codebase Secrets can persist in git history indefinitely Rotating credentials requires code changes Different environments require hardcoded credential variations According to a recent report by GitGuardian, nearly 24 million secrets were inadvertently exposed on GitHub just last year, with repositories using AI coding tools showing a 40% higher rate of secret exposure. Read: What is Secret Sprawl and How to Solve It? Some concerns have even been raised recently about AI coding assistants with read access to the entire codebase leaking sensitive credentials stored in .env files to remote servers, or overriding the .gitignore file, leading to a risk of committing sensitive .env files to git. Secure alternative: Use environment variables or a dedicated secrets management solution. Here's a simple environment variable approach: import { Pool } from 'pg' ; // Create a connection pool using environment variables const pool = new Pool ( { user : process . env . DB_USER , host : process . env . DB_HOST , database : process . env . DB_NAME , password : process . env . DB_PASSWORD , port : parseInt ( process . env . DB_PORT || '5432' ) , } ) ; For more robust solutions, consider dedicated secrets managers like Infisical, AWS Secrets Manager, or HashiCorp Vault, which offer: Separation of code and credentials Granular access control Automated secret rotation Audit logging capabilities Environment-specific configuration 2. Input Validation Vulnerabilities SQL Injection AI-generated code often prioritizes functionality over security, leading to unsafe database queries: // VULNERABLE CODE import { Pool } from 'pg' ; export async function getUserData ( username : string ) : Promise < any > { const pool = new Pool ( ) ; const query = ` SELECT * FROM users WHERE username = ' ${ username } ' ` ; const result = await pool . query ( query ) ; return result . rows [ 0 ] ; } This code directly concatenates user input into a SQL query without proper sanitization or parameterization. An attacker could input a value like admin' OR '1'='1 to bypass authentication or execute arbitrary SQL commands. Secure alternative: // SECURE CODE import { Pool } from 'pg' ; export async function getUserData ( username : string ) : Promise < any > { const pool = new Pool ( ) ; // Use parameterized queries to prevent SQL injection const query = 'SELECT * FROM users WHERE username = $1' ; const result = await pool . query ( query , [ username ] ) ; return result . rows [ 0 ] ; } Cross-Site Scripting (XSS) AI assistants often miss proper output encoding, creating XSS vulnerabilities: // VULNERABLE CODE import express from 'express' ; const app = express ( ) ; app . get ( '/search' , ( req , res ) => { const searchTerm = req . query . term as string ; res . send ( ` <h1>Search results for: ${ searchTerm } </h1> ` ) ; } ) ; This code inserts user input directly into HTML without sanitization, allowing attackers to inject malicious scripts that execute in users' browsers. Secure alternative: // SECURE CODE import express from 'express' ; import escapeHtml from 'escape-html' ; const app = express ( ) ; app . get ( '/search' , ( req , res ) => { const searchTerm = escapeHtml ( req . query . term as string ) ; res . send ( ` <h1>Search results for: ${ searchTerm } </h1> ` ) ; } ) ; 3. Authentication and Authorization Flaws AI assistants often generate code that handles user authentication but lacks critical security protections: // VULNERABLE CODE function loginUser ( username , password ) { const user = findUserByUsername ( username ) ; if ( user && user . password === password ) { return generateToken ( user . id ) ; } return null ; } This implementation has multiple security issues: Passwords are compared in plaintext rather than being hashed No protection against brute force attacks No account lockout mechanism No logging of failed login attempts Secure alternative: // SECURE CODE import bcrypt from 'bcrypt' ; async function loginUser ( username , password , ip ) { // Rate limiting check if ( isRateLimited ( ip ) ) { logFailedAttempt ( ip , username , 'rate_limited' ) ; throw new Error ( 'Too many attempts. Try again later.' ) ; } const user = await findUserByUsername ( username ) ; // Always perform hash comparison even if user isn't found to prevent timing attacks const passwordValid = user ? await bcrypt . compare ( password , user . passwordHash ) : false ; if ( ! user || ! passwordValid ) { logFailedAttempt ( ip , username , 'invalid_credentials' ) ; throw new Error ( 'Invalid username or password' ) ; } return generateToken ( user . id ) ; } Security Review Guide for Vibe Coders When reviewing AI-generated code, be vigilant for these common warning signs: Security Red Flags Sensitive Information Exposure Hardcoded credentials, API keys, or tokens Database connection strings with embedded passwords Debug or error messages revealing internal details Unsafe Data Handling Unparameterized queries (SQL, NoSQL, LDAP) Direct insertion of user input into HTML, JavaScript, or command strings Missing input validation or reliance only on client-side validation Weak Security Controls Insufficient error handling that leaks sensitive information Missing or weak authentication mechanisms Absence of authorization checks on sensitive functions Outdated cryptographic methods (MD5, SHA1, DES) Configuration Issues Development features enabled in production code Overly permissive CORS settings Unnecessary services or features enabled by default Best Practices for Secure Vibe Coding Implement these practical guidelines to maximize the benefits of AI code assistants while minimizing security risks: Prompt Engineering for Security The way you phrase your prompts significantly affects the security of generated code: Instead of: Write me a login function Try: Write a secure login function using bcrypt for password hashing, with rate limiting and protection against timing attacks, following OWASP best practices Multi-Stage Security Reviews When working with AI-generated code, adopt this review workflow: Initial Generation : Get your working code solution Security Verification : Follow up with prompts like: "What security vulnerabilities might exist in this code?" "How can we improve error handling to prevent information leakage?" "Are there any edge cases that could lead to security issues?" Challenge Testing : Test with problematic inputs: "How would this code handle a user input of: admin'; DROP TABLE users; --" "What happens if a file upload contains malicious content?" Automate Security Checks Integrate security tools into your development workflow: Security Layer Tools to Consider Code Analysis SonarQube, ESLint Security Plugin, Semgrep Dependency Scanning OWASP Dependency-Check, Snyk, GitHub Dependabot Secret Detection GitLeaks, TruffleHog, detect-secrets Runtime Protection RASP tools, WAF configuration Educate Yourself on Core Security Concepts Even with minimal coding experience, understanding these fundamental security principles will help you evaluate AI-generated code: Defense in Depth : Multiple layers of protection are better than a single strong defense Principle of Least Privilege : Give components access only to what they absolutely need Input Validation : Never trust external input without proper validation Secure by Default : Start with the most secure configuration and only open what's necessary Conclusion: Responsible Vibe Coding Vibe coding is an exciting development that makes software creation accessible to more people than ever before. However, with this power comes responsibility, particularly around security. Treat AI assistants as collaborators whose work requires careful review rather than infallible experts whose code can be blindly trusted. By applying the security principles outlined in this playbook, you can confidently vibe code while keeping your applications secure. Remember: The most secure code is code that you understand. Take time to have your AI assistant explain its security choices and learn from them as you go. Next, check our guide on how to manage secrets in your MCP servers to learn how to keep your secrets safe and secure. Thomas Segura Thomas is a tech writer at Infisical, passionate about open-source software and cloud security. 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https://slack.com/ | AI Work Management & Productivity Tools | Slack Skip to main content Features COLLABORATION Channels Organize teams and work Slack Connect Work with external partners Messaging Chat with your team Huddles Meet with audio and video Clips Record and share updates CRM Salesforce in Slack Bring Salesforce into the flow of work PROJECT MANAGEMENT Templates Start any task, fast Canvas Create rich, flexible docs Lists Organize, track and manage projects File Sharing Bring files to the flow of work PLATFORM Agentic Platform Customize, extend, and unify your tech stack in Slack Apps & Integrations Connect your tools with Slack Workflow Builder Automate everyday tasks INTELLIGENCE AI in Slack Save time and work smarter with powerfully simple AI Agentforce Empower your whole team with AI-powered agents in Slack Enterprise Search Find anything, all from a single search bar ADMIN & SECURITY Security Protect data, ensure compliance Enterprise Key Management Monitor and revoke access Slack Atlas Discover rich profiles and org charts Watch demo Download Slack Slack Marketplace Find new agents and apps that fit your team’s needs. Browse marketplace What is Slack? Slack vs. Email Accessibility Solutions BY DEPARTMENT Engineering IT Customer Service Sales Project Management Marketing Human Resources Security BY INDUSTRY Manufacturing, Auto & Energy Technology Media Small Business Financial Services Retail Education Health & Life Sciences Watch demo Download Slack See all solutions TEMPLATE GALLERY Start work faster with pre-made templates for every task. See all templates Task Management Scale Engagement Trust Enterprise Resources Resources Library What’s New Product Tour Events Developers Partners Customer Stories Community Slack Certified Blog Slack Marketplace Watch demo Download Slack FEATURED Tips and tricks on getting started with Slack Get started Help Center Customer Support Pricing Search Sign in Request a demo Get started Get started Back Features COLLABORATION Channels Organize teams and work Slack Connect Work with external partners Messaging Chat with your team Huddles Meet with audio and video Clips Record and share updates CRM Salesforce in Slack Bring Salesforce into the flow of work PROJECT MANAGEMENT Templates Start any task, fast Canvas Create rich, flexible docs Lists Organize, track and manage projects File Sharing Bring files to the flow of work PLATFORM Agentic Platform Customize, extend, and unify your tech stack in Slack Apps & Integrations Connect your tools with Slack Workflow Builder Automate everyday tasks INTELLIGENCE AI in Slack Save time and work smarter with powerfully simple AI Agentforce Empower your whole team with AI-powered agents in Slack Enterprise Search Find anything, all from a single search bar ADMIN & SECURITY Security Protect data, ensure compliance Enterprise Key Management Monitor and revoke access Slack Atlas Discover rich profiles and org charts Watch demo Download Slack Slack Marketplace Find new agents and apps that fit your team’s needs. Browse marketplace What is Slack? Slack vs. Email Accessibility Solutions BY DEPARTMENT Engineering IT Customer Service Sales Project Management Marketing Human Resources Security BY INDUSTRY Manufacturing, Auto & Energy Technology Media Small Business Financial Services Retail Education Health & Life Sciences Watch demo Download Slack See all solutions TEMPLATE GALLERY Start work faster with pre-made templates for every task. See all templates Task Management Scale Engagement Trust Enterprise Resources Resources Library What’s New Product Tour Events Developers Partners Customer Stories Community Slack Certified Blog Slack Marketplace Watch demo Download Slack FEATURED Tips and tricks on getting started with Slack Get started Help Center Customer Support Pricing Sign in Request a demo Download Slack Close Navigation Close Navigation Share it. Discuss it. Get it done. Side-by-side with AI agents. Get started Find your plan Bring your people, apps, and AI agents together. Collaboration Knowledge integrations AI Agents Collaboration Work with your colleagues and AI agents. Slack is built for bringing people and information together. Type things out. Talk things out. Invite external organizations into the conversation. And get work done with AI agents. 80% of the Fortune 100 use Slack Connect to work with partners and customers 1 Knowledge Access your team’s collective brain. Need to remember why a decision was made six months ago? Or who approved those contract terms? Just ask your question in Slack to find any past conversation, file, or project update. 47% increase in productivity for teams using Slack 2 Integrations Tap into the tools you already use. Over 2,600 apps are ready to connect in Slack so you can turn multi-step tasks like customer feedback requests and IT ticket requests into automated actions inside Slack. 35% increase in time saved due to automation for Slack users 3 AI Start faster with AI thats already a part of the team. Summarize threads you missed while on vacation, zero in on action items from every meeting, and get contextual help on your next strategy doc. 97 min average time users can save weekly with AI in Slack 4 Agents Pick the perfect AI agent for the job. Use Agentforce, Claude, Google Agent Space, and Vercel v0 to collaboratively create copy, code, and strategy right inside your Slack channels. Learn more The most innovative companies run their business in Slack. How OpenAI Connects with Customers and Expands ChatGPT with Slack Slack helps Box bring agents to every employee Caraway Brings All The Right Ingredients Together In Slack Slack helps Rivian do business in the fast lane How OpenAI Connects with Customers and Expands ChatGPT with Slack Slack helps Box bring agents to every employee Caraway Brings All The Right Ingredients Together In Slack Slack helps Rivian do business in the fast lane Get Started Find Your Plan We’re in the business of growing businesses. 90 % of users say Slack helps them stay more connected 5 43 The average number of apps used by teams in Slack 3 87 % of users say Slack helps them collaborate more efficiently 5 Millions of people love to work in Slack. 700M Messages sent daily 1 4M Slack Connect users working directly with external teams each week 1 3M Daily Workflows 1 1.7M Apps actively used each week 1 Don’t just take our word for it. Slack is a leader in over 314 G2 market reports 6 Your Slack deep dive starts here. Link may open in new tab Event Join us at Dreamforce, the world’s largest, most trusted technology event. Read more Link may open in new tab Webinar Unlock Agentic Productivity for Every Employee Watch Now Link may open in new tab Blog Agentforce 2.0: Agentforce Arrives in Slack Read Now Link may open in new tab Guide 10 Ways to Replace Ineffective Meetings with Slack Read more Link may open in new tab Event Join us at Dreamforce, the world’s largest, most trusted technology event. Read more Link may open in new tab Webinar Unlock Agentic Productivity for Every Employee Watch Now Link may open in new tab Blog Agentforce 2.0: Agentforce Arrives in Slack Read Now Link may open in new tab Guide 10 Ways to Replace Ineffective Meetings with Slack Read more 1 FY25 Slack internal data, product usage analysis. 2 FY23 Slack Customer Tracking Survey. Internal survey of weekly active Slack users in the US, UK, CA, and AU. Total n = 1,456. 3 FY24 Customer Success Metrics. Base: Total n = 247-1,696, Slack internal data. 4 Based on an internal analysis during the pilot of AI in Slack features (channel recaps, thread summaries, and AI search answers). 5 FY25 Slack Customer Tracking Survey. Internal survey of weekly active Slack users in the US, UK, CA, and AU. Total n = 2,410. 6 G2 Winter 2026 market reports for work management, workflow management, project collaboration software, enterprise search, knowledge base, employee Q&A, audio conferencing, business instant messaging, unified workspaces and more. See all you can accomplish in Slack. Get started Request a demo esc Change Region Selecting a different region will change the language and content of slack.com. 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Slack vs. Email Slack vs. Teams Enterprise Small Business Productivity Task Management Scale Trust Features Features Channels Slack Connect Workflow Builder Messaging Huddles Canvas Lists Clips Apps & Integrations File Sharing Slack AI Agentforce Enterprise Search Security Enterprise Key Management Slack Atlas See all features Solutions Solutions Engineering IT Customer Service Sales Project Management Marketing Security Manufacturing, Auto & Energy Technology Media Financial Services Retail Public Sector Education Health & Life Sciences See all solutions Resources Resources Help Center What’s New Resources Library Slack Blog Community Customer Stories Events Developers Partners Partner Offers Slack Marketplace Slack Certified Company Company About Us News Media Kit Brand Center Careers Swag Store Engineering Blog Design Blog Contact Us Download Slack Privacy Terms Cookie Preferences Your Privacy Choices ©2026 Slack Technologies, LLC, a Salesforce company. All rights reserved. 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https://infisical.com/blog/vibe-coding-security-playbook#:~:text=Safe%20infisical,generated | A Vibe Coding Security Playbook: Keeping AI-Generated Code Safe Infisical Stars Docs Careers Blog Pricing Get a Demo Sign Up ← Back Blog post • 10 min read A Vibe Coding Security Playbook: Keeping AI-Generated Code Safe Published on Wednesday, April 2, 2025 What's Vibe Coding? Vibe coding is a new term coined by Andrej Karpathy to describe a new approach to software development that leverages AI tools to handle most of the coding work. In a tweet that went viral, he explained: There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists . It's possible because the LLMs (e.g. Cursor Composer w Sonnet) are getting too good. Also I just talk to Composer with SuperWhisper so I barely even touch the keyboard. [...] I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works. Vibe coding involves heavy reliance on AI tools to generate, refine, and debug code, allowing developers to rapidly iterate and deploy applications with minimal manual coding effort. This practice is rapidly gaining popularity and has since been featured in the New York Times , Ars Technica , the Guardian and countless online discussions. It's particularly appealing to people who don't speak code yet want to create their own app, for fun or even for profit. Yet, over-reliance on AI-generated code can lead to security vulnerabilities, inefficiencies, and errors if not carefully reviewed by developers. The OWASP Top 10: A Security Foundation for Vibe Coders Before diving into specific vulnerabilities, let's establish why security matters for vibe coders. The OWASP Top 10 represents the most critical web application security risks and provides an excellent framework for understanding potential issues in AI-generated code. AI code generators have specific limitations that make them prone to introducing these security issues: Limitation Description Security Impact Pattern Reproduction AIs replicate code patterns from training data without understanding security implications May reproduce vulnerable code that's common in public repositories Context Blindness AI lacks awareness of the broader application security context Generates code that might be secure in isolation but creates vulnerabilities when integrated Training on Legacy Code Large portions of training data contain outdated security practices Propagates deprecated patterns that don't meet modern security standards Incomplete Implementation AI focuses on functional requirements rather than security requirements Omits crucial validation, error handling, and security checks Major Security Risks in AI-Generated Code Let's examine the most critical security vulnerabilities you're likely to encounter when using AI coding assistants, with practical examples and solutions for each. 1. Data Security Vulnerabilities Hardcoded Credentials and Exposed Secrets AI code assistants frequently suggest hardcoding credentials directly in source code. Consider this example: import { Pool } from 'pg' ; // Create a connection pool to PostgreSQL const pool = new Pool ( { user : 'postgres' , host : 'localhost' , database : 'myapp' , password : 'admin123' , // Hardcoded password! port : 5432 , } ) ; This approach creates serious vulnerabilities because: Credentials are visible to anyone with access to the codebase Secrets can persist in git history indefinitely Rotating credentials requires code changes Different environments require hardcoded credential variations According to a recent report by GitGuardian, nearly 24 million secrets were inadvertently exposed on GitHub just last year, with repositories using AI coding tools showing a 40% higher rate of secret exposure. Read: What is Secret Sprawl and How to Solve It? Some concerns have even been raised recently about AI coding assistants with read access to the entire codebase leaking sensitive credentials stored in .env files to remote servers, or overriding the .gitignore file, leading to a risk of committing sensitive .env files to git. Secure alternative: Use environment variables or a dedicated secrets management solution. Here's a simple environment variable approach: import { Pool } from 'pg' ; // Create a connection pool using environment variables const pool = new Pool ( { user : process . env . DB_USER , host : process . env . DB_HOST , database : process . env . DB_NAME , password : process . env . DB_PASSWORD , port : parseInt ( process . env . DB_PORT || '5432' ) , } ) ; For more robust solutions, consider dedicated secrets managers like Infisical, AWS Secrets Manager, or HashiCorp Vault, which offer: Separation of code and credentials Granular access control Automated secret rotation Audit logging capabilities Environment-specific configuration 2. Input Validation Vulnerabilities SQL Injection AI-generated code often prioritizes functionality over security, leading to unsafe database queries: // VULNERABLE CODE import { Pool } from 'pg' ; export async function getUserData ( username : string ) : Promise < any > { const pool = new Pool ( ) ; const query = ` SELECT * FROM users WHERE username = ' ${ username } ' ` ; const result = await pool . query ( query ) ; return result . rows [ 0 ] ; } This code directly concatenates user input into a SQL query without proper sanitization or parameterization. An attacker could input a value like admin' OR '1'='1 to bypass authentication or execute arbitrary SQL commands. Secure alternative: // SECURE CODE import { Pool } from 'pg' ; export async function getUserData ( username : string ) : Promise < any > { const pool = new Pool ( ) ; // Use parameterized queries to prevent SQL injection const query = 'SELECT * FROM users WHERE username = $1' ; const result = await pool . query ( query , [ username ] ) ; return result . rows [ 0 ] ; } Cross-Site Scripting (XSS) AI assistants often miss proper output encoding, creating XSS vulnerabilities: // VULNERABLE CODE import express from 'express' ; const app = express ( ) ; app . get ( '/search' , ( req , res ) => { const searchTerm = req . query . term as string ; res . send ( ` <h1>Search results for: ${ searchTerm } </h1> ` ) ; } ) ; This code inserts user input directly into HTML without sanitization, allowing attackers to inject malicious scripts that execute in users' browsers. Secure alternative: // SECURE CODE import express from 'express' ; import escapeHtml from 'escape-html' ; const app = express ( ) ; app . get ( '/search' , ( req , res ) => { const searchTerm = escapeHtml ( req . query . term as string ) ; res . send ( ` <h1>Search results for: ${ searchTerm } </h1> ` ) ; } ) ; 3. Authentication and Authorization Flaws AI assistants often generate code that handles user authentication but lacks critical security protections: // VULNERABLE CODE function loginUser ( username , password ) { const user = findUserByUsername ( username ) ; if ( user && user . password === password ) { return generateToken ( user . id ) ; } return null ; } This implementation has multiple security issues: Passwords are compared in plaintext rather than being hashed No protection against brute force attacks No account lockout mechanism No logging of failed login attempts Secure alternative: // SECURE CODE import bcrypt from 'bcrypt' ; async function loginUser ( username , password , ip ) { // Rate limiting check if ( isRateLimited ( ip ) ) { logFailedAttempt ( ip , username , 'rate_limited' ) ; throw new Error ( 'Too many attempts. Try again later.' ) ; } const user = await findUserByUsername ( username ) ; // Always perform hash comparison even if user isn't found to prevent timing attacks const passwordValid = user ? await bcrypt . compare ( password , user . passwordHash ) : false ; if ( ! user || ! passwordValid ) { logFailedAttempt ( ip , username , 'invalid_credentials' ) ; throw new Error ( 'Invalid username or password' ) ; } return generateToken ( user . id ) ; } Security Review Guide for Vibe Coders When reviewing AI-generated code, be vigilant for these common warning signs: Security Red Flags Sensitive Information Exposure Hardcoded credentials, API keys, or tokens Database connection strings with embedded passwords Debug or error messages revealing internal details Unsafe Data Handling Unparameterized queries (SQL, NoSQL, LDAP) Direct insertion of user input into HTML, JavaScript, or command strings Missing input validation or reliance only on client-side validation Weak Security Controls Insufficient error handling that leaks sensitive information Missing or weak authentication mechanisms Absence of authorization checks on sensitive functions Outdated cryptographic methods (MD5, SHA1, DES) Configuration Issues Development features enabled in production code Overly permissive CORS settings Unnecessary services or features enabled by default Best Practices for Secure Vibe Coding Implement these practical guidelines to maximize the benefits of AI code assistants while minimizing security risks: Prompt Engineering for Security The way you phrase your prompts significantly affects the security of generated code: Instead of: Write me a login function Try: Write a secure login function using bcrypt for password hashing, with rate limiting and protection against timing attacks, following OWASP best practices Multi-Stage Security Reviews When working with AI-generated code, adopt this review workflow: Initial Generation : Get your working code solution Security Verification : Follow up with prompts like: "What security vulnerabilities might exist in this code?" "How can we improve error handling to prevent information leakage?" "Are there any edge cases that could lead to security issues?" Challenge Testing : Test with problematic inputs: "How would this code handle a user input of: admin'; DROP TABLE users; --" "What happens if a file upload contains malicious content?" Automate Security Checks Integrate security tools into your development workflow: Security Layer Tools to Consider Code Analysis SonarQube, ESLint Security Plugin, Semgrep Dependency Scanning OWASP Dependency-Check, Snyk, GitHub Dependabot Secret Detection GitLeaks, TruffleHog, detect-secrets Runtime Protection RASP tools, WAF configuration Educate Yourself on Core Security Concepts Even with minimal coding experience, understanding these fundamental security principles will help you evaluate AI-generated code: Defense in Depth : Multiple layers of protection are better than a single strong defense Principle of Least Privilege : Give components access only to what they absolutely need Input Validation : Never trust external input without proper validation Secure by Default : Start with the most secure configuration and only open what's necessary Conclusion: Responsible Vibe Coding Vibe coding is an exciting development that makes software creation accessible to more people than ever before. However, with this power comes responsibility, particularly around security. Treat AI assistants as collaborators whose work requires careful review rather than infallible experts whose code can be blindly trusted. By applying the security principles outlined in this playbook, you can confidently vibe code while keeping your applications secure. Remember: The most secure code is code that you understand. Take time to have your AI assistant explain its security choices and learn from them as you go. Next, check our guide on how to manage secrets in your MCP servers to learn how to keep your secrets safe and secure. Thomas Segura Thomas is a tech writer at Infisical, passionate about open-source software and cloud security. He enjoys simplifying complex topics and helping developers build secure applications. twitter github linkedin security ai-coding vibe-coding devsecops owasp Previous Article SSH Certificates: A Complete Guide Next Article Infisical Gateway: Securely Connect Infisical to Anything, Anywhere Starting with Infisical is simple, fast, and free. Get Started Get a demo PRODUCT Secret Management Secret Scanning Share Secret Pricing Security USE CASES Infisical Agent Kubernetes Dynamic Secrets Terraform Ansible Jenkins Docker AWS ECS GitLab GitHub SDKs DEVELOPERS Documentation Changelog API Reference Status Feedback & Requests Community Slack How to contribute RESOURCES Blog Infisical vs Vault Careers Hiring Forum Open Source Friends Customers Company Handbook Trust Center LEGAL Terms of Service Privacy Policy Subprocessors Service Level Agreement CONTACT Team Email Sales Support Copyright © 2026 Infisical Inc. | 2026-01-13T08:49:36 |
https://infisical.com/blog/vibe-coding-security-playbook#:~:text=Secure%20alternative%3A%20Use%20environment%20variables,a%20simple%20environment%20variable%20approach | A Vibe Coding Security Playbook: Keeping AI-Generated Code Safe Infisical Stars Docs Careers Blog Pricing Get a Demo Sign Up ← Back Blog post • 10 min read A Vibe Coding Security Playbook: Keeping AI-Generated Code Safe Published on Wednesday, April 2, 2025 What's Vibe Coding? Vibe coding is a new term coined by Andrej Karpathy to describe a new approach to software development that leverages AI tools to handle most of the coding work. In a tweet that went viral, he explained: There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists . It's possible because the LLMs (e.g. Cursor Composer w Sonnet) are getting too good. Also I just talk to Composer with SuperWhisper so I barely even touch the keyboard. [...] I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works. Vibe coding involves heavy reliance on AI tools to generate, refine, and debug code, allowing developers to rapidly iterate and deploy applications with minimal manual coding effort. This practice is rapidly gaining popularity and has since been featured in the New York Times , Ars Technica , the Guardian and countless online discussions. It's particularly appealing to people who don't speak code yet want to create their own app, for fun or even for profit. Yet, over-reliance on AI-generated code can lead to security vulnerabilities, inefficiencies, and errors if not carefully reviewed by developers. The OWASP Top 10: A Security Foundation for Vibe Coders Before diving into specific vulnerabilities, let's establish why security matters for vibe coders. The OWASP Top 10 represents the most critical web application security risks and provides an excellent framework for understanding potential issues in AI-generated code. AI code generators have specific limitations that make them prone to introducing these security issues: Limitation Description Security Impact Pattern Reproduction AIs replicate code patterns from training data without understanding security implications May reproduce vulnerable code that's common in public repositories Context Blindness AI lacks awareness of the broader application security context Generates code that might be secure in isolation but creates vulnerabilities when integrated Training on Legacy Code Large portions of training data contain outdated security practices Propagates deprecated patterns that don't meet modern security standards Incomplete Implementation AI focuses on functional requirements rather than security requirements Omits crucial validation, error handling, and security checks Major Security Risks in AI-Generated Code Let's examine the most critical security vulnerabilities you're likely to encounter when using AI coding assistants, with practical examples and solutions for each. 1. Data Security Vulnerabilities Hardcoded Credentials and Exposed Secrets AI code assistants frequently suggest hardcoding credentials directly in source code. Consider this example: import { Pool } from 'pg' ; // Create a connection pool to PostgreSQL const pool = new Pool ( { user : 'postgres' , host : 'localhost' , database : 'myapp' , password : 'admin123' , // Hardcoded password! port : 5432 , } ) ; This approach creates serious vulnerabilities because: Credentials are visible to anyone with access to the codebase Secrets can persist in git history indefinitely Rotating credentials requires code changes Different environments require hardcoded credential variations According to a recent report by GitGuardian, nearly 24 million secrets were inadvertently exposed on GitHub just last year, with repositories using AI coding tools showing a 40% higher rate of secret exposure. Read: What is Secret Sprawl and How to Solve It? Some concerns have even been raised recently about AI coding assistants with read access to the entire codebase leaking sensitive credentials stored in .env files to remote servers, or overriding the .gitignore file, leading to a risk of committing sensitive .env files to git. Secure alternative: Use environment variables or a dedicated secrets management solution. Here's a simple environment variable approach: import { Pool } from 'pg' ; // Create a connection pool using environment variables const pool = new Pool ( { user : process . env . DB_USER , host : process . env . DB_HOST , database : process . env . DB_NAME , password : process . env . DB_PASSWORD , port : parseInt ( process . env . DB_PORT || '5432' ) , } ) ; For more robust solutions, consider dedicated secrets managers like Infisical, AWS Secrets Manager, or HashiCorp Vault, which offer: Separation of code and credentials Granular access control Automated secret rotation Audit logging capabilities Environment-specific configuration 2. Input Validation Vulnerabilities SQL Injection AI-generated code often prioritizes functionality over security, leading to unsafe database queries: // VULNERABLE CODE import { Pool } from 'pg' ; export async function getUserData ( username : string ) : Promise < any > { const pool = new Pool ( ) ; const query = ` SELECT * FROM users WHERE username = ' ${ username } ' ` ; const result = await pool . query ( query ) ; return result . rows [ 0 ] ; } This code directly concatenates user input into a SQL query without proper sanitization or parameterization. An attacker could input a value like admin' OR '1'='1 to bypass authentication or execute arbitrary SQL commands. Secure alternative: // SECURE CODE import { Pool } from 'pg' ; export async function getUserData ( username : string ) : Promise < any > { const pool = new Pool ( ) ; // Use parameterized queries to prevent SQL injection const query = 'SELECT * FROM users WHERE username = $1' ; const result = await pool . query ( query , [ username ] ) ; return result . rows [ 0 ] ; } Cross-Site Scripting (XSS) AI assistants often miss proper output encoding, creating XSS vulnerabilities: // VULNERABLE CODE import express from 'express' ; const app = express ( ) ; app . get ( '/search' , ( req , res ) => { const searchTerm = req . query . term as string ; res . send ( ` <h1>Search results for: ${ searchTerm } </h1> ` ) ; } ) ; This code inserts user input directly into HTML without sanitization, allowing attackers to inject malicious scripts that execute in users' browsers. Secure alternative: // SECURE CODE import express from 'express' ; import escapeHtml from 'escape-html' ; const app = express ( ) ; app . get ( '/search' , ( req , res ) => { const searchTerm = escapeHtml ( req . query . term as string ) ; res . send ( ` <h1>Search results for: ${ searchTerm } </h1> ` ) ; } ) ; 3. Authentication and Authorization Flaws AI assistants often generate code that handles user authentication but lacks critical security protections: // VULNERABLE CODE function loginUser ( username , password ) { const user = findUserByUsername ( username ) ; if ( user && user . password === password ) { return generateToken ( user . id ) ; } return null ; } This implementation has multiple security issues: Passwords are compared in plaintext rather than being hashed No protection against brute force attacks No account lockout mechanism No logging of failed login attempts Secure alternative: // SECURE CODE import bcrypt from 'bcrypt' ; async function loginUser ( username , password , ip ) { // Rate limiting check if ( isRateLimited ( ip ) ) { logFailedAttempt ( ip , username , 'rate_limited' ) ; throw new Error ( 'Too many attempts. Try again later.' ) ; } const user = await findUserByUsername ( username ) ; // Always perform hash comparison even if user isn't found to prevent timing attacks const passwordValid = user ? await bcrypt . compare ( password , user . passwordHash ) : false ; if ( ! user || ! passwordValid ) { logFailedAttempt ( ip , username , 'invalid_credentials' ) ; throw new Error ( 'Invalid username or password' ) ; } return generateToken ( user . id ) ; } Security Review Guide for Vibe Coders When reviewing AI-generated code, be vigilant for these common warning signs: Security Red Flags Sensitive Information Exposure Hardcoded credentials, API keys, or tokens Database connection strings with embedded passwords Debug or error messages revealing internal details Unsafe Data Handling Unparameterized queries (SQL, NoSQL, LDAP) Direct insertion of user input into HTML, JavaScript, or command strings Missing input validation or reliance only on client-side validation Weak Security Controls Insufficient error handling that leaks sensitive information Missing or weak authentication mechanisms Absence of authorization checks on sensitive functions Outdated cryptographic methods (MD5, SHA1, DES) Configuration Issues Development features enabled in production code Overly permissive CORS settings Unnecessary services or features enabled by default Best Practices for Secure Vibe Coding Implement these practical guidelines to maximize the benefits of AI code assistants while minimizing security risks: Prompt Engineering for Security The way you phrase your prompts significantly affects the security of generated code: Instead of: Write me a login function Try: Write a secure login function using bcrypt for password hashing, with rate limiting and protection against timing attacks, following OWASP best practices Multi-Stage Security Reviews When working with AI-generated code, adopt this review workflow: Initial Generation : Get your working code solution Security Verification : Follow up with prompts like: "What security vulnerabilities might exist in this code?" "How can we improve error handling to prevent information leakage?" "Are there any edge cases that could lead to security issues?" Challenge Testing : Test with problematic inputs: "How would this code handle a user input of: admin'; DROP TABLE users; --" "What happens if a file upload contains malicious content?" Automate Security Checks Integrate security tools into your development workflow: Security Layer Tools to Consider Code Analysis SonarQube, ESLint Security Plugin, Semgrep Dependency Scanning OWASP Dependency-Check, Snyk, GitHub Dependabot Secret Detection GitLeaks, TruffleHog, detect-secrets Runtime Protection RASP tools, WAF configuration Educate Yourself on Core Security Concepts Even with minimal coding experience, understanding these fundamental security principles will help you evaluate AI-generated code: Defense in Depth : Multiple layers of protection are better than a single strong defense Principle of Least Privilege : Give components access only to what they absolutely need Input Validation : Never trust external input without proper validation Secure by Default : Start with the most secure configuration and only open what's necessary Conclusion: Responsible Vibe Coding Vibe coding is an exciting development that makes software creation accessible to more people than ever before. However, with this power comes responsibility, particularly around security. Treat AI assistants as collaborators whose work requires careful review rather than infallible experts whose code can be blindly trusted. By applying the security principles outlined in this playbook, you can confidently vibe code while keeping your applications secure. Remember: The most secure code is code that you understand. Take time to have your AI assistant explain its security choices and learn from them as you go. Next, check our guide on how to manage secrets in your MCP servers to learn how to keep your secrets safe and secure. Thomas Segura Thomas is a tech writer at Infisical, passionate about open-source software and cloud security. He enjoys simplifying complex topics and helping developers build secure applications. twitter github linkedin security ai-coding vibe-coding devsecops owasp Previous Article SSH Certificates: A Complete Guide Next Article Infisical Gateway: Securely Connect Infisical to Anything, Anywhere Starting with Infisical is simple, fast, and free. Get Started Get a demo PRODUCT Secret Management Secret Scanning Share Secret Pricing Security USE CASES Infisical Agent Kubernetes Dynamic Secrets Terraform Ansible Jenkins Docker AWS ECS GitLab GitHub SDKs DEVELOPERS Documentation Changelog API Reference Status Feedback & Requests Community Slack How to contribute RESOURCES Blog Infisical vs Vault Careers Hiring Forum Open Source Friends Customers Company Handbook Trust Center LEGAL Terms of Service Privacy Policy Subprocessors Service Level Agreement CONTACT Team Email Sales Support Copyright © 2026 Infisical Inc. | 2026-01-13T08:49:36 |
https://dev.to/devteam/join-the-bright-data-real-time-ai-agents-challenge-3000-in-prizes-cog | Join the Bright Data Real-Time AI Agents Challenge: $3,000 in prizes! - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse dev.to staff for The DEV Team Posted on May 7, 2025 • Edited on Jun 10, 2025 Join the Bright Data Real-Time AI Agents Challenge: $3,000 in prizes! # devchallenge # brightdatachallenge # ai # webdev We're excited to announce our newest challenge with Bright Data ! Running through May 18 May 25 , the Bright Data Real-Time AI Agents Challenge invites you to build intelligent AI agents and systems that can autonomously interact with the web, retrieve live data, and make decisions based on the most current information available. Whether you're an AI engineer, data scientist, or vibe coder, this hackathon is the perfect opportunity to build something awesome. One talented developer will take home $3,000, an exclusive DEV badge, and a DEV++ membership ! All participants will receive a completion badge. We hope you give it a try! Our Prompt Your mandate is to leverage Bright Data and build an AI agent or system powered by real-time web data . The most powerful submissions will utilize Bright Data's MCP server to enable all four key actions: Discover: Find relevant content across the open web Access: Navigate even the most complex or protected websites Extract: Pull structured, real-time data at scale Interact: Engage with dynamic, JavaScript-rendered pages as a human would The MCP server is specifically designed to empower AI agents to perform these actions seamlessly, and we encourage you to incorporate all four capabilities in your project. The most important aspect? Your solution should showcase how access to reliable web data improves AI performance in solving real-world problems. How To Participate In order to participate, you will need to create a Bright Data account through this link and publish a post using the submission template below. Your project should integrate Bright Data’s infrastructure for real-time data usage and demonstrate how AI systems perform better when they have reliable, current information from across the web. All projects must be deployed and functional. If your app requires logging in, please provide testing credentials in your submission and/or instructions on how to best test your application for judges. Bright Data Hackathon Submission Template Bright Data Credits Participants will receive $250 in credits upon signing up through our dedicated sign up link . If you're not seeing the credits in your account, try adding devto as a promo code. If additional credits are required, participants can email noah@brightdata.com with the subject line “DEV Challenge - Credit Required,” including the email they used to sign up and details about their use case. Important Note: Use of Data Provided by Bright Data If you receive data from Bright Data as part of this challenge, it is solely for use in your project submission. This data is not intended for reuse, resale, or redistribution at any point. Data provided for the competition will be accessed through an account created by Bright Data and credited using a dev.to promotion code. The promotion code will provide the necessary credits to complete your project as part of the challenge. Misuse of the data or credits may result in disqualification from the competition and/or revocation of access. Please review our judging criteria, rules, guidelines, and FAQ page before submitting so you understand our participation guidelines and official contests rules such as eligibility requirements. Recommended Tech Stack 🛠️ Use the latest open-source AI tools to build your project. Here’s a modern stack to get you started (but feel free to get creative!): Frontend: Next.js, Vercel, Streamlit Embeddings & RAG Libraries: Nomic, Cognita, LLMWare, JinaAI Backend & Model Access: LangChain, Netflix Metaflow, Hugging Face, FastAPI, Ollama Data & Retrieval: Postgres, Milvus, Weaviate, PGVector, FAISS Large Language Models: LLaMA 3.3, Mistral, Gemma 2, Qwen, Phi You can get to know the Bright Data platform by utilizing their docs and tutorials: Developer Docs Bright Data Blog Bright Data Use Cases Project Ideas 💡 Real-time news or sentiment trackers Market or price monitoring bots LLMs with live data pieplines Multi-agent research assistants Crawlers for data extraction from forums like reddit Or anything else you can imagine! Important Dates May 7: Bright Data AI Web Access Hackathon begins! May 18 May 25 : Submissions due at 11:59 PM PDT May 29 June 5: Winners Announced We can't wait to meet the agents you build! Questions about the challenge? Ask them below. Good luck and happy coding! Top comments (46) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand Ben Halpern The DEV Team Ben Halpern The DEV Team Ben Halpern Follow A Canadian software developer who thinks he’s funny. Email ben@forem.com Location NY Education Mount Allison University Pronouns He/him Work Co-founder at Forem Joined Dec 27, 2015 • May 7 '25 Dropdown menu Copy link Hide Good luck! I've been playing around with Bright Data and am impressed (Inspired by the last Bright Data challenge) Like comment: Like comment: 12 likes Like Comment button Reply Collapse Expand Anshu Mandal Anshu Mandal Anshu Mandal Follow Location India Joined Aug 30, 2024 • May 7 '25 • Edited on May 8 • Edited Dropdown menu Copy link Hide Wishing if prize pool was split into three like all challenges but thanks again for this opportunity I'll try my best 🐱 Also I wanted to ask when will you announce winners of Alibaba challenge? Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Collins Dada Collins Dada Collins Dada Follow Passionate Coder and Cyber Security Enthusiast Email dada4ash@gmail.com Location Abuja, Nigeria Pronouns Optimus/Prime Joined Mar 22, 2025 • May 11 '25 Dropdown menu Copy link Hide i wished the same. and are we getting participation badges? Like comment: Like comment: 3 likes Like Thread Thread Jess Lee The DEV Team Jess Lee The DEV Team Jess Lee Follow Building DEV and Forem with everyone here. Interested in the future. Email jess@forem.com Location USA / TAIWAN Pronouns she/they Work Co-Founder & COO at Forem Joined Jul 29, 2016 • May 12 '25 Dropdown menu Copy link Hide @contractorx yup! all participants with valid submissions will receive a completion badge. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Jess Lee The DEV Team Jess Lee The DEV Team Jess Lee Follow Building DEV and Forem with everyone here. Interested in the future. Email jess@forem.com Location USA / TAIWAN Pronouns she/they Work Co-Founder & COO at Forem Joined Jul 29, 2016 • May 8 '25 Dropdown menu Copy link Hide Good luck! Here are the Alibaba Winners: Congrats to the Alibaba Cloud Web Game Challenge Winners! dev.to staff for The DEV Team ・ May 8 #devchallenge #alibabachallenge #webdev #cloud Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand sahra 💫 sahra 💫 sahra 💫 Follow software engineer 👩💻, technical writer, i posts contents relating to Linux, C programming language, software tools, JavaScript, React e.t.c. 🟢Volunteer Mod and Challenge Judge here on DEV🟢 Location Lagos, Nigeria Joined Jul 23, 2022 • May 9 '25 Dropdown menu Copy link Hide @jess @brightdata I currently have a bright data account (created from the last Bright data challenge), and I no longer have any free credits. Is there a way I can get the $250 credits without having to create a new account? Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Wassim Soltani Wassim Soltani Wassim Soltani Follow I love exploring new stuff ✨ Location Tunisia Education Lots of it Pronouns He/Him Work Software Engineer & Founder of Blueblood Joined May 4, 2025 • May 10 '25 Dropdown menu Copy link Hide Try reaching out to noah@brightdata.com with the subject line "DEV Challenge - Credit Required". Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Jess Lee The DEV Team Jess Lee The DEV Team Jess Lee Follow Building DEV and Forem with everyone here. Interested in the future. Email jess@forem.com Location USA / TAIWAN Pronouns she/they Work Co-Founder & COO at Forem Joined Jul 29, 2016 • May 12 '25 Dropdown menu Copy link Hide @sarahokolo does using the code devto at checkout resolve your issue? Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand davinceleecode davinceleecode davinceleecode Follow Software dev with experience in Windows, .NET, web dev, APIs, .NET Core, Razor Pages, and ReactJS. I love exploring new tech and building modern solutions. Email vincent.lee.c.flores@davinceleecode.tech Location Void Education College-educated with a strong self-taught background in software development. Pronouns He/Him Work Software Developer Joined Mar 8, 2025 • May 8 '25 Dropdown menu Copy link Hide Another keyboard is about to get broken again...🔥🔥🔥 Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand P.H Isidor P.H Isidor P.H Isidor Follow Joined May 2, 2025 • May 14 '25 Dropdown menu Copy link Hide Thank God! This was extended. I actually am just starting today. I needed that time, but was willing to push through. Good luck to everyone.👍 Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Wassim Soltani Wassim Soltani Wassim Soltani Follow I love exploring new stuff ✨ Location Tunisia Education Lots of it Pronouns He/Him Work Software Engineer & Founder of Blueblood Joined May 4, 2025 • May 14 '25 Dropdown menu Copy link Hide Same here, but I'm curious about what prompted the push.. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Jess Lee The DEV Team Jess Lee The DEV Team Jess Lee Follow Building DEV and Forem with everyone here. Interested in the future. Email jess@forem.com Location USA / TAIWAN Pronouns she/they Work Co-Founder & COO at Forem Joined Jul 29, 2016 • May 7 '25 Dropdown menu Copy link Hide Good luck everyone! Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Shweta Kale Shweta Kale Shweta Kale Follow Software Developer Location India Work Fable - https://www.sharefable.com Joined May 28, 2020 • May 26 '25 • Edited on May 26 • Edited Dropdown menu Copy link Hide I've seen a few projects using https://api.brightdata.com instead of @brightdata/mcp . I think @brightdata/mcp uses the API under the hood, but they are different, right? For this hackathon, were we required to use @brightdata/mcp ? Can someone confirm if I'm correct or wrong? @noah_kalson_8115056be2f03 Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Noah Kalson Noah Kalson Noah Kalson Follow Joined May 19, 2025 • May 26 '25 Dropdown menu Copy link Hide That is correct, the goal of the hachathon is to use the MCP. The APIs sit under the MCP so they will be used regardless. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Shweta Kale Shweta Kale Shweta Kale Follow Software Developer Location India Work Fable - https://www.sharefable.com Joined May 28, 2020 • May 26 '25 Dropdown menu Copy link Hide Thank you!! That clears up my confusion😊 Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Olga Braginskaya Olga Braginskaya Olga Braginskaya Follow Oh That Data Girl Anti-Bullshit Enthusiast. Data engineer with a systems mindset, mildly owned by cats. Writing what I wish someone had written earlier. Pronouns she/her Work Senior Data Engineer Joined Mar 22, 2023 • May 9 '25 Dropdown menu Copy link Hide So I used a link to sign up and didn't get 250$ credits, only 2$. I don't know how to proceed from here. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Jess Lee The DEV Team Jess Lee The DEV Team Jess Lee Follow Building DEV and Forem with everyone here. Interested in the future. Email jess@forem.com Location USA / TAIWAN Pronouns she/they Work Co-Founder & COO at Forem Joined Jul 29, 2016 • May 9 '25 Dropdown menu Copy link Hide Oh no! We'll reach out to their team and get back to you ASAP. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Olga Braginskaya Olga Braginskaya Olga Braginskaya Follow Oh That Data Girl Anti-Bullshit Enthusiast. Data engineer with a systems mindset, mildly owned by cats. Writing what I wish someone had written earlier. Pronouns she/her Work Senior Data Engineer Joined Mar 22, 2023 • May 9 '25 Dropdown menu Copy link Hide I wrote to noah@brightdata.com and got the code which solved the problem. Thanks! Like comment: Like comment: 2 likes Like Thread Thread Jess Lee The DEV Team Jess Lee The DEV Team Jess Lee Follow Building DEV and Forem with everyone here. Interested in the future. Email jess@forem.com Location USA / TAIWAN Pronouns she/they Work Co-Founder & COO at Forem Joined Jul 29, 2016 • May 9 '25 Dropdown menu Copy link Hide Oh good! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Wassim Soltani Wassim Soltani Wassim Soltani Follow I love exploring new stuff ✨ Location Tunisia Education Lots of it Pronouns He/Him Work Software Engineer & Founder of Blueblood Joined May 4, 2025 • May 10 '25 Dropdown menu Copy link Hide Same issue happened to me, about to reach out via email. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Wassim Soltani Wassim Soltani Wassim Soltani Follow I love exploring new stuff ✨ Location Tunisia Education Lots of it Pronouns He/Him Work Software Engineer & Founder of Blueblood Joined May 4, 2025 • May 10 '25 Dropdown menu Copy link Hide If anyone has a similar issue, you can apply the promo code "devto" manually in the billing screen to get the full credits. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Raziel Rodrigues Raziel Rodrigues Raziel Rodrigues Follow Useful technical articles and thoughts about everything Email raziel.rodrigues@outlook.pt Location Brazilian living in Portugal Joined Jun 15, 2023 • May 16 '25 Dropdown menu Copy link Hide I am almost finishing my project be aware with my submission my friends AQUI É BRASIL! Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Nevo David Nevo David Nevo David Follow Founder of Postiz, an open-source social media scheduling tool. Running Gitroom, the best place to learn how to grow open-source tools. Education Didn't finish high school :( Pronouns Nev/Nevo Work OSS Chief @ Gitroom Joined Feb 23, 2022 • May 7 '25 Dropdown menu Copy link Hide Man, $3k for a smart agent? Alright, might roll up my sleeves and take a crack at this. Deadlines make me move faster anyway. Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand ANIRUDDHA ADAK ANIRUDDHA ADAK ANIRUDDHA ADAK Follow AI Agent Engineer focused on creating self-directed AI systems that learn, adapt, and execute multi-step tasks without human intervention. Email aniruddhaadak80@gmail.com Joined Nov 11, 2024 • May 7 '25 Dropdown menu Copy link Hide That is we all need 🔥🔥🔥 Like comment: Like comment: 3 likes Like Comment button Reply View full discussion (46 comments) Some comments may only be visible to logged-in visitors. Sign in to view all comments. Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse The DEV Team Follow The hardworking team behind DEV ❤️ Want to contribute to open source and help make the DEV community stronger? 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Contribute to Forem More from The DEV Team Congrats to the AI Agents Intensive Course Writing Challenge Winners! # googleaichallenge # devchallenge # ai # agents Join the Algolia Agent Studio Challenge: $3,000 in Prizes! # algoliachallenge # devchallenge # agents # webdev Congrats to the Xano AI-Powered Backend Challenge Winners! # xanochallenge # backend # api # ai 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://ai.google.dev/gemini-api/docs/pricing#:~:text=Free%20Tier%20Paid%20Tier%2C%20per,price%20Not%20available%20Coming%20soon | Gemini Developer API pricing | Gemini API | Google AI for Developers Skip to main content / English Deutsch Español – América Latina Français Indonesia Italiano Polski Português – Brasil Shqip Tiếng Việt Türkçe Русский עברית العربيّة فارسی हिंदी বাংলা ภาษาไทย 中文 – 简体 中文 – 繁體 日本語 한국어 Get API key Cookbook Community Sign in Docs API reference Gemini API Docs API reference Get API key Cookbook Community Get started Overview Quickstart API keys Libraries Interactions API Models Gemini Gemini 3 Nano Banana image generation Veo video generation Lyria music generation Imagen image generation Embeddings Robotics Pricing Rate limits Core capabilities Text Image Image generation 🍌 Image understanding Video Documents Speech and audio Speech generation Audio understanding Thinking and thought signatures Thinking Thought signatures Structured outputs Function calling Long context Tools and agents Overview Deep Research Google Search Google Maps Code execution URL context Computer Use File Search Live API Get started Capabilities Tool use Session management Ephemeral tokens Guides Batch API File input Input methods Files API Context caching OpenAI compatibility Media resolution Token counting Prompt engineering Logs and datasets Get started with logs Data logging and sharing Safety Safety settings Safety guidance Open-Source frameworks LangChain & LangGraph CrewAI LlamaIndex Vercel AI SDK Resources Migrate to Gen AI SDK Release notes Deprecations API troubleshooting Billing info Partner and library integrations Google AI Studio Quickstart Vibe code in Build mode Try out LearnLM Troubleshooting Access for Workspace users Google Cloud Platform VertexAI Gemini API OAuth authentication Policies Terms of service Available regions Additional usage polices Home Gemini API Docs Gemini Developer API pricing We have updated our Terms of Service . Start building free of charge with generous limits, then scale up with pay-as-you-go pricing for your production ready applications. Free For developers and small projects getting started with the Gemini API. check_circle Limited access to certain models check_circle Free input & output tokens check_circle Google AI Studio access check_circle Content used to improve our products * Get started for Free Paid For production applications that require higher volumes and advanced features. check_circle Higher rate limits for production deployments check_circle Access to Context caching check_circle Batch API (50% cost reduction) check_circle Access to Google's most advanced models check_circle Content not used to improve our products * Upgrade to Paid Enterprise For large-scale deployments with custom needs for security, support, and compliance, powered by Vertex AI . check_circle All features in Paid, plus optional access to: check_circle Dedicated support channels check_circle Advanced security & compliance check_circle Provisioned throughput check_circle Volume-based discounts (based on usage) check_circle ML ops, model garden and more Contact Sales Gemini 3 Pro Preview gemini-3-pro-preview Try it in Google AI Studio The best model in the world for multimodal understanding, and our most powerful agentic and vibe-coding model yet. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $2.00, prompts $4.00, prompts > 200k tokens Output price (including thinking tokens) Not available $12.00, prompts $18.00, prompts > 200k Context caching price Not available $0.20, prompts $0.40, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 5,000 prompts per month (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00, prompts $2.00, prompts > 200k tokens Output price (including thinking tokens) Not available $6.00, prompts $9.00, prompts > 200k Context caching price Not available $0.20, prompts $0.40, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 1,500 RPD (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No * A customer-submitted request to Gemini may result in one or more queries to Google Search. You will be charged for each individual search query performed. ** Gemini 3 billing for Grounding with Google Search will start January 5, 2026. Gemini 3 Flash Preview gemini-3-flash-preview Try it in Google AI Studio Our most intelligent model built for speed, combining frontier intelligence with superior search and grounding. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $3.00 Context caching price Free of charge $0.05 (text / image / video) $0.10 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 5,000 prompts per month (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.25 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.50 Context caching price Not available Same as Standard, Batch pricing not yet implemented $0.05 (text / image / video) $0.10 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search * Not available 1,500 RPD (free), then (Coming soon ** ) $14 / 1,000 search queries Grounding with Google Maps Not available Not available Used to improve our products Yes No * A customer-submitted request to Gemini may result in one or more queries to Google Search. You will be charged for each individual search query performed. ** Gemini 3 billing for Grounding with Google Search will start January 5, 2026. Gemini 3 Pro Image Preview 🍌 gemini-3-pro-image-preview Try it in Google AI Studio Our native image generation model, optimized for speed, flexibility, and contextual understanding. Text input and output is priced the same as Gemini 3 Pro . Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $2.00 (text/image), equivalent to $0.0011 per image * Output price Not available $12.00 (text and thinking) $120.00 (images) equivalent to $0.134 per 1K/2K image ** and $0.24 per 4K image ** Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00 (text), $0.0006 (image) * Output price Not available $6.00 (text and thinking) $0.067 per 1K/2K image ** $0.12 per 4K image ** Used to improve our products Yes No * Image input is set at 560 tokens or $0.0011 per image. ** Image output is priced at $120 per 1,000,000 tokens. Output images from 1024x1024px (1K) and up to 2048x2048px (2K) consume 1120 tokens and are equivalent to $0.134 per image. Output images up to 4096x4096px (4K) consume 2000 tokens and are equivalent to $0.24 per image. Gemini 2.5 Pro gemini-2.5-pro Try it in Google AI Studio Our state-of-the-art multipurpose model, which excels at coding and complex reasoning tasks. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $1.25, prompts $2.50, prompts > 200k tokens Output price (including thinking tokens) Free of charge $10.00, prompts $15.00, prompts > 200k Context caching price Not available $0.125, prompts $0.25, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available 10,000 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.625, prompts $1.25, prompts > 200k tokens Output price (including thinking tokens) Not available $5.00, prompts $7.50, prompts > 200k Context caching price Not available $0.125, prompts $0.25, prompts > 200k $4.50 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash gemini-2.5-flash Try it in Google AI Studio Our first hybrid reasoning model which supports a 1M token context window and has thinking budgets. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.25 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash Preview gemini-2.5-flash-preview-09-2025 Try it in Google AI Studio The latest model based on the 2.5 Flash model. 2.5 Flash Preview is best for large scale processing, low-latency, high volume tasks that require thinking, and agentic use cases. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image / video) $0.50 (audio) Output price (including thinking tokens) Not available $1.25 Context caching price Not available $0.03 (text / image / video) $0.1 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Gemini 2.5 Flash-Lite gemini-2.5-flash-lite Try it in Google AI Studio Our smallest and most cost effective model, built for at scale usage. Standard Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Free of charge $0.10 (text / image / video) $0.30 (audio) Output price (including thinking tokens) Free of charge $0.40 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash RPD) 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Not available $0.05 (text / image / video) $0.15 (audio) Output price (including thinking tokens) Not available $0.20 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No Gemini 2.5 Flash-Lite Preview gemini-2.5-flash-lite-preview-09-2025 Try it in Google AI Studio The latest model based on Gemini 2.5 Flash lite optimized for cost-efficiency, high throughput and high quality. Standard Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Free of charge $0.10 (text / image / video) $0.30 (audio) Output price (including thinking tokens) Free of charge $0.40 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash RPD) 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price (text, image, video) Not available $0.05 (text / image / video) $0.15 (audio) Output price (including thinking tokens) Not available $0.20 Context caching price Not available $0.01 (text / image / video) $0.03 (audio) $1.00 / 1,000,000 tokens per hour (storage price) Grounding with Google Search Not available 1,500 RPD (free, limit shared with Flash RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Gemini 2.5 Flash Native Audio (Live API) gemini-2.5-flash-native-audio-preview-12-2025 Try it in Google AI Studio Our Live API native audio models optimized for higher quality audio outputs with better pacing, voice naturalness, verbosity, and mood. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text) $3.00 (audio / video) Output price (including thinking tokens) Free of charge $2.00 (text) $12.00 (audio) Used to improve our products Yes No Gemini 2.5 Flash Image 🍌 gemini-2.5-flash-image Try it in Google AI Studio Our native image generation model, optimized for speed, flexibility, and contextual understanding. Text input and output is priced the same as 2.5 Flash . Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.30 (text / image) Output price Not available $0.039 per image* Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.15 (text / image) Output price Not available $0.0195 per image* Used to improve our products Yes No [*] Image output is priced at $30 per 1,000,000 tokens. Output images up to 1024x1024px consume 1290 tokens and are equivalent to $0.039 per image. Gemini 2.5 Flash Preview TTS gemini-2.5-flash-preview-tts Try it in Google AI Studio Our 2.5 Flash text-to-speech audio model optimized for price-performant, low-latency, controllable speech generation. Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.50 (text) Output price Free of charge $10.00 (audio) Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.25 (text) Output price Not available $5.00 (audio) Used to improve our products Yes No Gemini 2.5 Pro Preview TTS gemini-2.5-pro-preview-tts Try it in Google AI Studio Our 2.5 Pro text-to-speech audio model optimized for powerful, low-latency speech generation for more natural outputs and easier to steer prompts. Preview models may change before becoming stable and have more restrictive rate limits. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.00 (text) Output price Not available $20.00 (audio) Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.50 (text) Output price Not available $10.00 (audio) Used to improve our products Yes No Gemini 2.0 Flash gemini-2.0-flash Try it in Google AI Studio Our most balanced multimodal model with great performance across all tasks, with a 1 million token context window, and built for the era of Agents. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.10 (text / image / video) $0.70 (audio) Output price Free of charge $0.40 Context caching price Free of charge $0.025 / 1,000,000 tokens (text/image/video) $0.175 / 1,000,000 tokens (audio) Context caching (storage) Not available $1.00 / 1,000,000 tokens per hour Image generation pricing Free of charge $0.039 per image* Tuning price Not available Not available Grounding with Google Search Free of charge, up to 500 RPD 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps 500 RPD 1,500 RPD (free), then $25 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.05 (text / image / video) $0.35 (audio) Output price Not available $0.20 Context caching price Not available $0.025 / 1,000,000 tokens (text/image/video) $0.175 / 1,000,000 tokens (audio) Context caching (storage) Not available $1.00 / 1,000,000 tokens per hour Image generation pricing Not available $0.0195 per image* Tuning price Not available Not available Grounding with Google Search Not available 1,500 RPD (free), then $35 / 1,000 grounded prompts Grounding with Google Maps Not available Not available Used to improve our products Yes No [*] Image output is priced at $30 per 1,000,000 tokens. Output images up to 1024x1024px consume 1290 tokens and are equivalent to $0.039 per image. Gemini 2.0 Flash-Lite gemini-2.0-flash-lite Try it in Google AI Studio Our smallest and most cost effective model, built for at scale usage. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.075 Output price Free of charge $0.30 Context caching price Not available Not available Context caching (storage) Not available Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.0375 Output price Not available $0.15 Context caching price Not available Not available Context caching (storage) Not available Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Imagen 4 imagen-4.0-generate-001 , imagen-4.0-ultra-generate-001 , imagen-4.0-fast-generate-001 Try it in Google AI Studio Our latest image generation model, with significantly better text rendering and better overall image quality. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per Image in USD Imagen 4 Fast image price Not available $0.02 Imagen 4 Standard image price Not available $0.04 Imagen 4 Ultra image price Not available $0.06 Used to improve our products Yes No Imagen 3 imagen-3.0-generate-002 Try it in Google AI Studio Our state-of-the-art image generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per Image in USD Image price Not available $0.03 Used to improve our products Yes No Veo 3.1 veo-3.1-generate-preview , veo-3.1-fast-generate-preview Try Veo 3.1 Our latest video generation model, available to developers on the paid tier of the Gemini API. Preview models may change before becoming stable and have more restrictive rate limits. Free Tier Paid Tier, per second in USD Veo 3.1 Standard video with audio price (default) Not available $0.40 Veo 3.1 Fast video with audio price (default) Not available $0.15 Used to improve our products Yes No Note: In some cases, an audio processing issue may prevent a video from being generated. You will only be charged if your video is successfully generated. Veo 3 veo-3.0-generate-001 , veo-3.0-fast-generate-001 Try Veo 3 Our stable video generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per second in USD Veo 3 Standard video with audio price (default) Not available $0.40 Veo 3 Fast video with audio price (default) Not available $0.15 Used to improve our products Yes No Note: In some cases, an audio processing issue may prevent a video from being generated. You will only be charged if your video is successfully generated. Veo 2 veo-2.0-generate-001 Try the API Our state-of-the-art video generation model, available to developers on the paid tier of the Gemini API. Free Tier Paid Tier, per second in USD Video price Not available $0.35 Used to improve our products Yes No Gemini Embedding gemini-embedding-001 Try the API Our newest embeddings model, more stable and with higher rate limits than previous versions, available to developers on the free and paid tiers of the Gemini API. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.15 Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available $0.075 Used to improve our products Yes No Gemini Robotics-ER 1.5 Preview gemini-robotics-er-1.5-preview Try it in Google AI Studio Gemini Robotics-ER, short for Gemini Robotics-Embodied Reasoning, is a thinking model that enhances robots' abilities to understand and interact with the physical world. Standard Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge $0.30 (text / image / video) $1.00 (audio) Output price (including thinking tokens) Free of charge $2.50 Grounding with Google Search Free of charge, up to 500 RPD (limit shared with Flash-Lite RPD) 1,500 RPD (free, limit shared with Flash-Lite RPD), then $35 / 1,000 grounded prompts Used to improve our products Yes No Batch Free Tier Paid Tier, per 1M tokens in USD Input price Not available Not available Output price (including thinking tokens) Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Gemini 2.5 Computer Use Preview gemini-2.5-computer-use-preview-10-2025 Our Computer Use model optimized for building browser control agents that automate tasks. Free Tier Paid Tier, per 1M tokens in USD Input price Not available $1.25, prompts $2.50, prompts > 200k token Output price Not available $10.00, prompts $15.00, prompts > 200k Used to improve our products Yes No Gemma 3 Our lightweight, state-of the art, open model built from the same technology that powers our Gemini models. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge Not available Output price Free of charge Not available Context caching price Free of charge Not available Context caching (storage) Free of charge Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Gemma 3n Our open model built for efficient performance on everyday devices like mobile phones, laptops, and tablets. Free Tier Paid Tier, per 1M tokens in USD Input price Free of charge Not available Output price Free of charge Not available Context caching price Free of charge Not available Context caching (storage) Free of charge Not available Tuning price Not available Not available Grounding with Google Search Not available Not available Used to improve our products Yes No Pricing for tools Tools are priced at their own rates, applied to the model using them. Check the Models page for which tools are available to each model. Free Tier Paid Tier, per 1M tokens in USD Google Search 500 RPD free (limit shared for Flash and Flash-Lite). Not available for Pro. 1,500 RPD free (limit shared for Flash and Flash-Lite). Then $35 / 1,000 grounded prompts See the Gemini 3 Pro Preview pricing section for Gemini 3 specific Search pricing. Google Maps 500 RPD Not available for Pro. 1,500 RPD free (limit shared for Flash and Flash-Lite) 10,000 RPD free for Pro. Then $25 / 1,000 grounded prompts Code execution Free of charge Free of charge URL context Free of charge Charged as input tokens per model pricing. Computer use Not available See Gemini 2.5 Computer Use Preview pricing table. File search Free of charge Charged for embeddings at $0.15 / 1M tokens. Retrieved document tokens charged as regular tokens per model pricing. [*] Google AI Studio usage is free of charge in all available regions . See Billing FAQs for details. [**] Prices may differ from the prices listed here and the prices offered on Vertex AI. For Vertex prices, see the Vertex AI pricing page . [***] If you are using dynamic retrieval to optimize costs, only requests that contain at least one grounding support URL from the web in their response are charged for Grounding with Google Search. Costs for Gemini always apply. Rate limits are subject to change. Pricing for agents Agent usage costs are calculated based on the underlying token consumption and usage of the tools. Model Tools Gemini Deep Research Agent All model inference is charged at standard Gemini 3 Pro list rates, including input, output, and intermediate input / reasoning tokens generated during agentic loops. Tool usage fees apply per existing pricing structure, maintaining standard distinctions for Search Grounding (retrieved tokens excluded) versus Url_context / File Search (retrieved tokens included in all other tools). Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates. Last updated 2025-12-18 UTC. [[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-12-18 UTC."],[],[]] Terms Privacy Manage cookies English Deutsch Español – América Latina Français Indonesia Italiano Polski Português – Brasil Shqip Tiếng Việt Türkçe Русский עברית العربيّة فارسی हिंदी বাংলা ภาษาไทย 中文 – 简体 中文 – 繁體 日本語 한국어 | 2026-01-13T08:49:36 |
https://dev.to/scale_youtube/devoxx-inspiring-the-next-generations-35eg | Devoxx: Inspiring the Next Generations - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Scale YouTube Posted on Nov 2, 2025 Devoxx: Inspiring the Next Generations # career Inspiring the Next Generations At Devoxx Belgium 2025, Frank Delporte grabs the camera and mic to chat with Cassandra Chin (14:00), author of Raising Young Coders . She shares fun tips for teaching programming to kids and even hands out a 20% discount code (APAUT) for her Springer book. Later, at 06:56, Delporte catches up with Daniel De Luca, founder of Devoxx4Kids, who walks us through his hands-on workshops designed to spark curiosity and a lasting love of tech in children of all ages. Watch on YouTube Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Scale YouTube Follow Joined Aug 2, 2025 More from Scale YouTube NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career NDC Conferences: Optimize Your Internal OS and Minimize Compatibility Issues at Work - Alice Meredith # career 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://dev.to/dheerajaggarwal/api-testing-compare-expected-vs-actual-json-api-response-c69 | API Testing - Compare Expected vs Actual JSON API Response - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Dheeraj Aggarwal Posted on Feb 18, 2021 • Edited on Feb 22, 2021 API Testing - Compare Expected vs Actual JSON API Response # testing # api # qa # vrestng See, how you may quickly compare expected and actual JSON API response in vREST NG. In our future sessions, we will see more advanced approaches to validate your complex API responses like a piece of cake. So stay tuned to our video series. Youtube Link: https://youtu.be/ugSXeDv0-vE Youtube Playlist: https://youtube.com/playlist?list=PLmua155_WrDzt1AbB6iV5Lsw_Z7QrzZZ0 vREST NG is an enterprise-ready application for Automated API Testing. You can download and install the vREST NG application directly on Windows, OSX, and Linux via our website. Important Links: vREST NG Website Contact Email Community Chat Book a Live Demo Please do like and share if you found this video helpful and let the voice heard by the testing community. Also, let us know your feedback by commenting on this post. Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Dheeraj Aggarwal Follow Creator of vREST NG, API Automation Expert with 10+ years of experience. Passionate about Yoga and Kalaripayattu. Location India Education M.S. from BITS Pilani Work Engineering Manager at Optimizory Technologies Pvt. Ltd. Joined Dec 30, 2019 More from Dheeraj Aggarwal API Testing - Executing API Tests on the command line # testing # tutorial # apitesting # vrest API Testing - Setting up API Tests for different environments like Dev, Prod,... # testing # tutorial # apitesting # vrest API Testing - How to manage API Test suites in vREST NG Application? # testing # tutorial # apitesting # vrest 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://www.xda-developers.com/open-source-not-same-source-available/ | Why transparency alone doesn't make software truly open: a deep dive Menu Sign in Sign in now Close News PC Hardware Submenu CPU GPU Storage Monitors Keyboards & Mice Software Submenu Productivity Self-Hosting Home Lab Other Software Operating Systems Submenu Windows Linux macOS Devices Submenu Single-Board Computers Laptops Gaming Handheld Prebuilt PC Home Submenu Networking Smart Home Gaming Submenu Game Reviews Sign in Newsletter Array Copyright © 2026 www.xda-developers.com --> Menu Follow Followed Like Threads More Action Summary Generate a summary of this story Sign in Sign in now ESP32 Windows 11 NotebookLM Gaming Forums Close Why transparency alone doesn't make software truly open: a deep dive By Jeff Butts Published Oct 20, 2025 Jeff's been involved in the IT industry since before the Internet and spent more than 20 years working in technical support, system administration, network administration, and consulting roles. He holds an undergraduate degree in English, a Master's degree in English with a focus on professional writing and editing, and another Master's degree in Computing & Information Systems. After teaching university English and computer science for a few years, Jeff launched his writing career . He's written for Macworld , Tom's Hardware , groovyPost , The Mac Observer , and more before beginning here at XDA. Sign in to your XDA account Add Us On Summary Generate a summary of this story follow Follow followed Followed Like Like Thread Log in Here is a fact-based summary of the story contents: Try something different: Show me the facts Explain it like I’m 5 Give me a lighthearted recap Transparency is one of the most appealing parts of modern software development . When a company says its product is “open” or that the source code is available, many people assume that means open-source. It’s an easy mistake to make, since all three terms imply that the code is visible. The problem is that visibility alone doesn’t equal freedom, and that’s where the distinction truly lies. Transparency is valuable, but freedom is essential. The line between open-source and source-available software has blurred over time. Marketing teams often use both terms interchangeably, even though the philosophy and licensing behind them are very different. It’s not just a technical argument or a matter of wording. This difference has real-world implications for users, developers, and the entire open-source community . Why the difference between 'open source' and 'source available' matters Freedom, not just visibility, defines open-source Open-source software is more than a chance to peek at the code. It’s a legal and ethical framework that gives users the right to use, modify, and redistribute software freely. Licenses like the GNU General Public License (GPL) or MIT codify those freedoms so that anyone can build on existing work. This is what makes open-source robust and resilient, even decades after a project’s launch. There are many open-source licenses approved by the Open Source Initiative (OSI) , but these are the most common. Others include: License SPDX Short Identifier More information Apache License, v2.0 Apache-2.0 https://www.apache.org/licenses/LICENSE-2.0 The 3-Clause BSD License BSD-3-Clause https://opensource.org/license/BSD-3-Clause GNU Lesser General Public License v3.0 LGPL-3.0-only https://www.gnu.org/licenses/lgpl-3.0.en.html Mozilla Public License 2.0 MPL-2.0 https://www.mozilla.org/en-US/MPL/2.0/ Apple Public Source License 2.0 APSL-2.0 https://opensource.apple.com/apsl/ Source-available software doesn’t offer that same flexibility. The source code might be viewable, but the license restricts what you can do with it. Some developers adopt this approach to protect their business interests while still appearing transparent. Users can learn from the code, but often can’t modify or redistribute it, which limits community innovation and long-term sustainability. The distinction matters because it affects control. With open-source, users have agency to fix bugs, add features, or fork a project if needed. With source-available code, development depends entirely on the original author’s choices. That dependency runs counter to the collaborative ideals that make open-source ecosystems thrive. How companies blur the lines Marketing buzz versus community principles The term “open” has become a marketing magnet. Companies use it to create the impression of transparency and community involvement. Yet when you read the fine print, the license often restricts commercial use or forbids derivative works. Those limitations mean the software no longer qualifies as open-source under the Open Source Initiative’s definition. Sometimes, this confusion comes from good intentions rather than manipulation. A developer might release code under a restrictive license simply to prevent misuse while still wanting to share knowledge. However, those restrictions still matter. The result is software that looks open at first glance but is closed in practice, which misleads users about their actual rights. This blending of language erodes trust over time. Users come to expect openness and flexibility, only to find barriers when they try to contribute or self-host. Each misuse of the “open” label makes it harder to distinguish genuine community-driven projects from those using openness as a sales pitch. Clarity in licensing keeps that trust intact. Real-world examples of 'source available' When visibility replaces genuine openness Several high-profile projects have recently reignited the discussion about what “open” really means. One of the most talked-about examples is Meta’s Llama large language model . While Meta released the code and model weights for research, its license prohibits commercial use. That restriction alone means Lllama isn’t open-source, despite widespread references to it as such in media and marketing. Another example is Elastic, the company behind Elasticsearch. After years of operating under an open-source license, Elastic switched to a source-available model that forbids certain types of redistribution. The company made this change to protect against cloud providers offering Elasticsearch as a hosted service without contributing back. The move sparked intense debate about whether “open” projects can remain sustainable without being fully free. Ultimately, Elasticsearch returned to the open-source world, adding the GNU Affero General Public License (AGPL) to the available licensing options for the software. Redis, once a flagship of open-source databases, followed a similar path. Its license now limits commercial use to protect the company’s interests. While understandable from a business standpoint, these changes illustrate how quickly open projects can become restricted when corporate priorities shift. For users and developers, the result is the same: less freedom and more confusion about what “open” really means. In the end, just like Elasticsearch, Redis adopted the AGPL, bringing the software fully back in line with open-source licensing. How to tell the difference Licenses reveal what “open” really means Credit: Source: EvanLovely/Wikimedia Commons CC BY 2.0 If you want to know whether something is truly open-source, the license tells the story. OSI-approved licenses such as GPLv3, MIT, or Apache 2.0 allow unrestricted use, modification, and redistribution . Any license that adds caveats, like prohibiting commercial use, disqualifies it from being open-source. It may still be source-available, but it doesn’t carry the same freedoms. You can also tell a lot by observing community behavior. True open-source projects encourage collaboration through pull requests, issue tracking, and forking. Source-available projects often limit contributions and reserve decision-making power for the original creator. This structural difference reveals the project’s true nature more clearly than a marketing tagline ever could. Understanding those distinctions helps users make better choices. Supporting true open-source projects means supporting collective progress and longevity. By contrast, supporting source-available software often benefits a single organization. Both models have value, but one fosters independence while the other maintains control. Why this distinction protects the community Freedom is what keeps open-source alive Every time a company markets restricted code as open-source, it weakens the term’s meaning. The open-source movement depends on shared ownership and accountability. Diluting that label with projects that limit user rights damages the credibility of genuine open initiatives. Over time, this can lead to fewer contributors, less innovation, and more proprietary fragmentation. XDA Report: Subscribe and never miss what matters Stay ahead in the world of Windows, software, PC components, and more with XDA Subscribe By subscribing, you agree to receive newsletter and marketing emails, and accept Valnet’s Terms of Use and Privacy Policy . You can unsubscribe anytime. Real open-source projects succeed because no single entity owns them. Anyone can pick up abandoned code and breathe new life into it. That level of resilience is what has allowed software like Linux, VLC, and Blender to outlive their original creators. Source-available models don’t offer that guarantee, and once the controlling company loses interest, the project often fades away. Protecting the meaning of “open-source” is about more than technical purity. It ensures that the freedoms promised to users remain intact for future generations of developers. Upholding those principles keeps the software world diverse, adaptable, and community-driven. What developers and users should take away Both models have legitimate places in the software landscape. Developers may choose source-available licenses to protect business interests or intellectual property. That’s a valid decision as long as it’s presented honestly. Calling restricted software “open-source” is what crosses the line and confuses users who expect freedom, not just visibility. Restrictions still matter, no matter how good the intentions. Users, in turn, can safeguard their own interests by checking licenses carefully. When you support open-source projects, you’re contributing to a shared pool of innovation that benefits everyone. When you use source-available software, you’re trusting a single entity to keep the project alive. Knowing which you’re choosing makes all the difference. Understanding that open-source and source-available software aren’t the same helps preserve what makes the open-source movement special. Transparency is valuable, but freedom is essential. By supporting projects that uphold true open-source principles, users and developers ensure a future where collaboration remains at the heart of progress. 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https://dev.to/lambdatest/introduction-to-gitlab-interface-gitlab-tutorial-for-beginners-part-ii-4pil | Introduction To GitLab Interface | GitLab Tutorial For Beginners | Part II - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse LambdaTest Team for LambdaTest Posted on Apr 19, 2022 Introduction To GitLab Interface | GitLab Tutorial For Beginners | Part II # devops # beginners # tutorial # git GitLab CI Tutorial Series Videos. (7 Part Series) 1 Introduction to GitLab CI | What is GitLab CI | GitLab Tutorial For Beginners | Part I 2 Introduction To GitLab Interface | GitLab Tutorial For Beginners | Part II ... 3 more parts... 3 What Is GitLab Workflow | GitLab Flow | GitLab Tutorial For Beginners | Part III 4 How To Use GitLab Flow In GitLab Project | GitLab Tutorial For Beginners | Part IV 5 What Is GitLab Pipeline? | How To Create GitLab Pipeline | GitLab Tutorial For Beginners | Part V 6 How To Migrate From Jenkins Pipeline To GitLab CI | GitLab Tutorial For Beginners | Part VI 7 What is GitLab Registry? | GitLab Pipeline | GitLab Tutorial For Beginners | Part VII GitLab offers a feature-based system with a centralized, integrated platform for web developers. In addition, GitLab features help in project management, issue tracking, and free private repository hosting to simplify planning and managing your projects. Start FREE Testing ! Integrate GitLab with LambdaTest: https://bit.ly/3ti02GM In this part of GitLab Tutorial for Beginners, Moss(@tech_with_moss), a DevOps engineer, introduces you to GitLab account authentication and group dashboard interface. Furthermore, you will be getting familiar with GitLab user interface features which enables you to automatically build, test, and deploy your software. Its features like built-in continuous integration and continuous delivery make it seamless to go from a code change to a running pipeline. You will also learn about the GitLab project dashboard to help you create a new project, ‘new issue’ within the project, and explore the ‘package & registry’ section. This video will help answer the following questions 🎫 -: 🔹What is GitLab UI? 🔹How do you access GitLab UI? 🔹How do you use GitLab? 🔹What can you do with GitLab? GitLab CI Tutorial Series Videos. 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Submit Preview Dismiss Collapse Expand Chandre Van Der Westhuizen Chandre Van Der Westhuizen Chandre Van Der Westhuizen Follow Community Maintainer @ MindsDB Joined Jan 18, 2022 • Oct 17 '22 Dropdown menu Copy link Hide Hey I really loved this video Mirza! If your team is looking to explore Hacktoberfest feel free to check out MindsDB . One of the categories is creating videos and posting them on Youtube. The top 3 authors can win a prize, the top prize is $1000 and you stand to win a a high-end Razer Blade 15 Laptop . If you want more details feel free to contact me on Slack. Like comment: Like comment: 1 like Like Comment button Reply Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . 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https://www.notion.so | The AI workspace that works for you. | Notion Notion Features Notion AI Build, write, automate Agents Handles manual tasks Enterprise Search Find answers instantly AI Meeting Notes Perfectly written by AI Docs Simple & powerful Knowledge Base Centralize your knowledge Projects Manage any project Sites Publish anything, fast Get started Explore AI use cases See what Notion AI can do Browse marketplace Templates for everything View integrations Connect your apps with Notion Download web clipper Save from the web into Notion Try the Notion desktop app for a faster experience Download app Mail Calendar AI Enterprise Pricing Explore Teams Eng & Product Design Marketing IT Team size Startups SMBs Enterprise Education Learn Help center Notion Academy Customer stories Blog Community Partner programs Build API Templates Security Consultants Request a demo Log in Get Notion free One workspace. Zero busywork. Notion is where your teams and AI agents capture knowledge, find answers, and automate projects. Now a team of 7 feels like 70. Get Notion free Request a demo Play Trusted by top teams Introducing Notion 3.0 Notion Agent New You assign the tasks. Your Notion Agent does the work. → Hand off your busywork What used to take days in minutes. Tell it your goal and watch it work. Collaborates with your team It's like having a built-in power user that works alongside your team. Knows everything you know Searches all your pages, messages, files, and the web to surface exactly what you need. Personalized to you Your Agent learns how you work. You control everything from how it behaves to how it looks. Custom Agents Coming soon Automate repetitive tasks. → Enterprise Search One search for everything. → AI Meeting Notes Perfect notes, every time. → Flexible workflows Manage any project, big or small. → Your AI everything app. More productivity. Fewer tools. Bring all your tools and teams under one roof. Calculate savings below. See pricing plans → AI Search $35/user AI Chatbot $20/user AI Meeting Notes $18/user AI Writing Assistant $20/user AI Email App $30/user AI Research $40/user Calendar Scheduling $15/user Team Wiki $10/user Project Management Tool $24/user Basic CRM $20/user Site Builder $20/user Forms $15/user Team size Monthly savings $0 Annual savings $0 Trusted by teams that ship. There’s power in a single platform where you can do all your work. Notion is that single place. Read the full story → View the video Streamlined workflows to reduce timelines by 3x. → “With Notion, every person at Ramp has an AI agent.” → “Notion understands that you can solve a lot of problems with one tool.” → “Notion has been the most powerful and impactful way to streamline our workflow.” → “Using the most AI‑native tools like Notion is an important competitive advantage for us.” → One hub for work and AI keeps everyone informed and work flowing. → Close dialog Play Uh-oh! It looks like your ad blocker is preventing the video from playing. Please watch it on YouTube Read the full story → Over 100M users worldwide #1 knowledge base 3 years running (G2) #1 AI enterprise search (G2) #1 rated AI writing (G2) 62% of Fortune 100 Over 50% of YC companies 1.4M+ community members Over 100M users worldwide #1 knowledge base 3 years running (G2) #1 AI enterprise search (G2) #1 rated AI writing (G2) 62% of Fortune 100 Over 50% of YC companies 1.4M+ community members Over 100M users worldwide #1 knowledge base 3 years running (G2) #1 AI enterprise search (G2) #1 rated AI writing (G2) 62% of Fortune 100 Over 50% of YC companies 1.4M+ community members Let Notion AI handle the busywork. Pick a use case to see how Notion does the work for you. Explore more → Go from brainstorm to roadmap → Turn meetings into social posts → Organize your workspace → Onboard a new hire → Revise a landing page → Plan an offsite → Track favorite restaurants → Transform notes into tasks → Try for free. Get started on Notion Your AI workspace with built-in agents. Download for Mac Notion Mail The AI inbox that thinks like you. Download Notion Calendar Time, scheduling, tasks—all together. Download Notion is always at home right in your browser . English (US) Cookie settings © 2026 Notion Labs, Inc. Company About us Careers Security Status Terms & privacy Your privacy rights Download iOS & Android Mac & Windows Calendar Web Clipper Resources Help center Pricing Blog Community Integrations Templates Partner programs Notion for Enterprise Small business Personal Explore more → | 2026-01-13T08:49:36 |
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https://www.fine.dev/blog/about-devcontainers#troubleshooting-common-issues-with-dev-containers | Everything you need to know about Dev Containers Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Everything you need to know about Dev Containers Table of Contents What Are Dev Containers? Key Components of Dev Containers Why Use Dev Containers? Consistency Across Environments Simplified Setup Isolation Portability Enhanced Productivity How to Get Started with Dev Containers 1. Install Necessary Tools 2. Create Configuration Files 3. Launch the Dev Container Best Practices for Using Dev Containers 1. Keep Configuration Files Under Version Control 2. Optimize Dockerfile for Performance 3. Define Clear Extension Requirements 4. Manage Secrets Securely Common Use Cases for Dev Containers 1. Multi-language Projects 2. Open Source Contributions 3. Continuous Integration/Continuous Deployment (CI/CD) 4. Experimentation and Prototyping Troubleshooting Common Issues with Dev Containers 1. Container Fails to Build 2. Extensions Not Installing 3. Port Forwarding Not Working 4. Performance Issues 5. Volume Mounting Problems 6. Dependency Conflicts 7. Container Not Starting 8. SSH/Authentication Problems Conclusion What Are Dev Containers? A dev container (short for development container ) is an isolated, reproducible environment tailored for software development. Leveraging containerization technologies like Docker, dev containers encapsulate all the necessary tools, libraries, dependencies, and configurations required for a project. This ensures that your development environment remains consistent, regardless of the underlying host system. Key Components of Dev Containers Container Image : A lightweight, standalone package that includes everything needed to run the application—code, runtime, system tools, libraries, and settings. Dockerfile : A script containing a series of instructions to build the container image. It specifies the base image and outlines steps to install dependencies and configure the environment. devcontainer.json : A configuration file used by development tools (like Visual Studio Code) to customize the container setup. It defines settings such as extensions, port mappings, and environment variables. Why Use Dev Containers? Adopting dev containers offers numerous advantages, especially for developers new to the concept: 1. Consistency Across Environments Dev containers ensure that every team member works in the same environment, eliminating the notorious "it works on my machine" problem. This consistency reduces bugs and streamlines collaboration. 2. Simplified Setup Onboarding new developers becomes a breeze. Instead of manually installing dependencies and configuring environments, newcomers can get started quickly by simply using the predefined dev container configuration. 3. Isolation Dev containers keep project dependencies isolated from the host system. This prevents conflicts between different projects and maintains a clean local environment. 4. Portability Containers are platform-agnostic. Whether you're on Windows, macOS, or Linux, dev containers behave the same way, making it easy to switch between different development setups or collaborate with others. 5. Enhanced Productivity Integration with popular IDEs, like Visual Studio Code, allows developers to work seamlessly inside containers. Features such as debugging, version control, and extensions work as if you were working on a local machine. How to Get Started with Dev Containers Setting up a dev container is straightforward, especially with tools like Visual Studio Code (VS Code) and Docker. Here's a step-by-step guide to help you get started: 1. Install Necessary Tools Docker : Install Docker from docker.com . Docker is essential for creating and managing containers. Visual Studio Code : Download and install VS Code from code.visualstudio.com . Dev Containers Extension : In VS Code, navigate to the Extensions marketplace and install the Dev Containers extension . 2. Create Configuration Files Within your project directory, create a .devcontainer folder. This folder will house the necessary configuration files: Dockerfile : Defines the base image and instructions to set up the container environment. # Use an official Node.js runtime as the base image FROM node:14 # Set the working directory inside the container WORKDIR /usr/src/app # Copy package.json and package-lock.json COPY package*.json ./ # Install project dependencies RUN npm install # Copy the rest of the application code COPY . . # Expose port 3000 EXPOSE 3000 # Define the command to run the application CMD ["npm", "start"] 3. Launch the Dev Container Open your project in VS Code. Press Ctrl+Shift+P (Windows/Linux) or Cmd+Shift+P (macOS) to open the Command Palette. Type Remote-Containers: Open Folder in Container and select it. VS Code will build the container based on your configuration files. This process might take a few minutes, especially the first time. Once built, your project will open inside the container, ready for development. Best Practices for Using Dev Containers To maximize the benefits of dev containers, consider the following best practices: 1. Keep Configuration Files Under Version Control Include your .devcontainer folder in your version control system (e.g., Git). This ensures that all team members use the same environment setup. 2. Optimize Dockerfile for Performance Leverage Caching : Order your Dockerfile instructions to take advantage of Docker's layer caching. For instance, copy package.json and run npm install before copying the rest of the code. This minimizes rebuild times when only code changes. Use Lightweight Base Images : Choose base images that are lightweight to reduce build times and resource usage. 3. Define Clear Extension Requirements Specify only the necessary VS Code extensions in devcontainer.json . This keeps the container lean and ensures faster startup times. 4. Manage Secrets Securely Avoid hardcoding sensitive information in configuration files. Use environment variables or secret management tools to handle credentials securely. Common Use Cases for Dev Containers Dev containers are versatile and can be beneficial in various scenarios: 1. Multi-language Projects Projects that use multiple programming languages or frameworks can define a dev container that includes all necessary tools and dependencies, streamlining the development process. Dev containers are versatile and can be beneficial in various scenarios: 1. Multi-language Projects Projects that use multiple programming languages or frameworks can define a dev container that includes all necessary tools and dependencies, streamlining the development process. 2. Open Source Contributions Open source projects often attract contributors from diverse backgrounds. Providing a dev container setup allows contributors to get started quickly without worrying about environment configurations. 3. Continuous Integration/Continuous Deployment (CI/CD) Ensuring that the development environment matches the production environment reduces deployment issues. Dev containers can be integrated into CI/CD pipelines to maintain consistency. 4. Experimentation and Prototyping Developers can experiment with new technologies or configurations within isolated containers without affecting their primary development setup. Troubleshooting Common Issues with Dev Containers While dev containers simplify the development workflow, you might encounter some common issues during setup and usage. Below are typical problems developers face with dev containers and straightforward solutions to resolve them. 1. Container Fails to Build Issue: During the build process, the container fails to build, often due to errors in the Dockerfile or missing dependencies. Solution: Check the Dockerfile for syntax errors and ensure all necessary dependencies are correctly specified. Review the build logs to identify the exact step causing the failure and adjust the configurations accordingly. Updating Docker to the latest version can also resolve compatibility issues. 2. Extensions Not Installing Issue: VS Code extensions specified in devcontainer.json are not being installed inside the container. Solution: Verify that the extension identifiers in devcontainer.json are correct and compatible with the container's environment. Ensure that the postCreateCommand is properly configured to install extensions. Restarting VS Code and rebuilding the container can also help apply the changes. 3. Port Forwarding Not Working Issue: Ports exposed in the container are not accessible from the host machine, hindering the ability to test web applications or APIs. Solution: Ensure that the ports are correctly specified in the forwardPorts section of devcontainer.json . Check for any firewall or network settings on the host that might be blocking the ports. Additionally, confirm that the application inside the container is listening on the correct network interface (e.g., 0.0.0.0 ). 4. Performance Issues Issue: Developers experience slow performance or lag when working inside the dev container, affecting productivity. Solution: Optimize the Dockerfile by minimizing the number of layers and using lightweight base images to reduce build times. Allocate sufficient resources (CPU, memory) to Docker through its settings. Avoid unnecessary processes running inside the container to enhance responsiveness. 5. Volume Mounting Problems Issue: Source code or other volumes are not mounting correctly into the container, preventing access to the latest code changes. Solution: Check the mounts configuration in devcontainer.json to ensure paths are correctly specified. Verify that Docker has the necessary permissions to access the directories being mounted. Restarting the container can also help apply any recent changes to the mounting configurations. 6. Dependency Conflicts Issue: Conflicts arise between dependencies required by the project and those installed in the container, leading to build or runtime errors. Solution: Use a clean and specific base image that matches the project's requirements to minimize conflicts. Explicitly define dependency versions in configuration files like package.json or requirements.txt . Consider using virtual environments or dependency managers to isolate and manage dependencies effectively. 7. Container Not Starting Issue: The dev container fails to start, leaving the development environment inaccessible. Solution: Inspect the Docker daemon to ensure it is running correctly and that there are no issues with Docker itself. Review the devcontainer.json and Dockerfile for any misconfigurations or missing commands that could prevent the container from initializing. Rebuilding the container from scratch can often resolve startup issues. 8. SSH/Authentication Problems Issue: Authentication failures occur when trying to access services or repositories from within the dev container. Solution: Ensure that SSH keys and authentication tokens are correctly mounted or copied into the container. Verify that environment variables related to authentication are properly set in devcontainer.json . Using SSH agent forwarding can also help manage secure access without exposing sensitive credentials inside the container. Conclusion Dev containers represent a significant advancement in modern software development, offering consistency, portability, and efficiency. By encapsulating your development environment, you ensure that your projects are reproducible and free from environmental discrepancies. Whether you're working solo or as part of a team, integrating dev containers into your workflow can streamline development processes, reduce setup times, and enhance overall productivity. If you haven't explored dev containers yet, now is the perfect time to dive in. With tools like Docker and Visual Studio Code making setup seamless, embracing dev containers can elevate your development experience to new heights. Start experimenting today and discover the myriad benefits that dev containers have to offer. Start building today Try out the smoothest way to build, launch and manage an app Try for Free -> © Fine.dev - All rights reserved. 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https://infisical.com/blog/vibe-coding-security-playbook#:~:text=AI,leading%20to%20unsafe%20database%20queries | A Vibe Coding Security Playbook: Keeping AI-Generated Code Safe Infisical Stars Docs Careers Blog Pricing Get a Demo Sign Up ← Back Blog post • 10 min read A Vibe Coding Security Playbook: Keeping AI-Generated Code Safe Published on Wednesday, April 2, 2025 What's Vibe Coding? Vibe coding is a new term coined by Andrej Karpathy to describe a new approach to software development that leverages AI tools to handle most of the coding work. In a tweet that went viral, he explained: There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists . It's possible because the LLMs (e.g. Cursor Composer w Sonnet) are getting too good. Also I just talk to Composer with SuperWhisper so I barely even touch the keyboard. [...] I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works. Vibe coding involves heavy reliance on AI tools to generate, refine, and debug code, allowing developers to rapidly iterate and deploy applications with minimal manual coding effort. This practice is rapidly gaining popularity and has since been featured in the New York Times , Ars Technica , the Guardian and countless online discussions. It's particularly appealing to people who don't speak code yet want to create their own app, for fun or even for profit. Yet, over-reliance on AI-generated code can lead to security vulnerabilities, inefficiencies, and errors if not carefully reviewed by developers. The OWASP Top 10: A Security Foundation for Vibe Coders Before diving into specific vulnerabilities, let's establish why security matters for vibe coders. The OWASP Top 10 represents the most critical web application security risks and provides an excellent framework for understanding potential issues in AI-generated code. AI code generators have specific limitations that make them prone to introducing these security issues: Limitation Description Security Impact Pattern Reproduction AIs replicate code patterns from training data without understanding security implications May reproduce vulnerable code that's common in public repositories Context Blindness AI lacks awareness of the broader application security context Generates code that might be secure in isolation but creates vulnerabilities when integrated Training on Legacy Code Large portions of training data contain outdated security practices Propagates deprecated patterns that don't meet modern security standards Incomplete Implementation AI focuses on functional requirements rather than security requirements Omits crucial validation, error handling, and security checks Major Security Risks in AI-Generated Code Let's examine the most critical security vulnerabilities you're likely to encounter when using AI coding assistants, with practical examples and solutions for each. 1. Data Security Vulnerabilities Hardcoded Credentials and Exposed Secrets AI code assistants frequently suggest hardcoding credentials directly in source code. Consider this example: import { Pool } from 'pg' ; // Create a connection pool to PostgreSQL const pool = new Pool ( { user : 'postgres' , host : 'localhost' , database : 'myapp' , password : 'admin123' , // Hardcoded password! port : 5432 , } ) ; This approach creates serious vulnerabilities because: Credentials are visible to anyone with access to the codebase Secrets can persist in git history indefinitely Rotating credentials requires code changes Different environments require hardcoded credential variations According to a recent report by GitGuardian, nearly 24 million secrets were inadvertently exposed on GitHub just last year, with repositories using AI coding tools showing a 40% higher rate of secret exposure. Read: What is Secret Sprawl and How to Solve It? Some concerns have even been raised recently about AI coding assistants with read access to the entire codebase leaking sensitive credentials stored in .env files to remote servers, or overriding the .gitignore file, leading to a risk of committing sensitive .env files to git. Secure alternative: Use environment variables or a dedicated secrets management solution. Here's a simple environment variable approach: import { Pool } from 'pg' ; // Create a connection pool using environment variables const pool = new Pool ( { user : process . env . DB_USER , host : process . env . DB_HOST , database : process . env . DB_NAME , password : process . env . DB_PASSWORD , port : parseInt ( process . env . DB_PORT || '5432' ) , } ) ; For more robust solutions, consider dedicated secrets managers like Infisical, AWS Secrets Manager, or HashiCorp Vault, which offer: Separation of code and credentials Granular access control Automated secret rotation Audit logging capabilities Environment-specific configuration 2. Input Validation Vulnerabilities SQL Injection AI-generated code often prioritizes functionality over security, leading to unsafe database queries: // VULNERABLE CODE import { Pool } from 'pg' ; export async function getUserData ( username : string ) : Promise < any > { const pool = new Pool ( ) ; const query = ` SELECT * FROM users WHERE username = ' ${ username } ' ` ; const result = await pool . query ( query ) ; return result . rows [ 0 ] ; } This code directly concatenates user input into a SQL query without proper sanitization or parameterization. An attacker could input a value like admin' OR '1'='1 to bypass authentication or execute arbitrary SQL commands. Secure alternative: // SECURE CODE import { Pool } from 'pg' ; export async function getUserData ( username : string ) : Promise < any > { const pool = new Pool ( ) ; // Use parameterized queries to prevent SQL injection const query = 'SELECT * FROM users WHERE username = $1' ; const result = await pool . query ( query , [ username ] ) ; return result . rows [ 0 ] ; } Cross-Site Scripting (XSS) AI assistants often miss proper output encoding, creating XSS vulnerabilities: // VULNERABLE CODE import express from 'express' ; const app = express ( ) ; app . get ( '/search' , ( req , res ) => { const searchTerm = req . query . term as string ; res . send ( ` <h1>Search results for: ${ searchTerm } </h1> ` ) ; } ) ; This code inserts user input directly into HTML without sanitization, allowing attackers to inject malicious scripts that execute in users' browsers. Secure alternative: // SECURE CODE import express from 'express' ; import escapeHtml from 'escape-html' ; const app = express ( ) ; app . get ( '/search' , ( req , res ) => { const searchTerm = escapeHtml ( req . query . term as string ) ; res . send ( ` <h1>Search results for: ${ searchTerm } </h1> ` ) ; } ) ; 3. Authentication and Authorization Flaws AI assistants often generate code that handles user authentication but lacks critical security protections: // VULNERABLE CODE function loginUser ( username , password ) { const user = findUserByUsername ( username ) ; if ( user && user . password === password ) { return generateToken ( user . id ) ; } return null ; } This implementation has multiple security issues: Passwords are compared in plaintext rather than being hashed No protection against brute force attacks No account lockout mechanism No logging of failed login attempts Secure alternative: // SECURE CODE import bcrypt from 'bcrypt' ; async function loginUser ( username , password , ip ) { // Rate limiting check if ( isRateLimited ( ip ) ) { logFailedAttempt ( ip , username , 'rate_limited' ) ; throw new Error ( 'Too many attempts. Try again later.' ) ; } const user = await findUserByUsername ( username ) ; // Always perform hash comparison even if user isn't found to prevent timing attacks const passwordValid = user ? await bcrypt . compare ( password , user . passwordHash ) : false ; if ( ! user || ! passwordValid ) { logFailedAttempt ( ip , username , 'invalid_credentials' ) ; throw new Error ( 'Invalid username or password' ) ; } return generateToken ( user . id ) ; } Security Review Guide for Vibe Coders When reviewing AI-generated code, be vigilant for these common warning signs: Security Red Flags Sensitive Information Exposure Hardcoded credentials, API keys, or tokens Database connection strings with embedded passwords Debug or error messages revealing internal details Unsafe Data Handling Unparameterized queries (SQL, NoSQL, LDAP) Direct insertion of user input into HTML, JavaScript, or command strings Missing input validation or reliance only on client-side validation Weak Security Controls Insufficient error handling that leaks sensitive information Missing or weak authentication mechanisms Absence of authorization checks on sensitive functions Outdated cryptographic methods (MD5, SHA1, DES) Configuration Issues Development features enabled in production code Overly permissive CORS settings Unnecessary services or features enabled by default Best Practices for Secure Vibe Coding Implement these practical guidelines to maximize the benefits of AI code assistants while minimizing security risks: Prompt Engineering for Security The way you phrase your prompts significantly affects the security of generated code: Instead of: Write me a login function Try: Write a secure login function using bcrypt for password hashing, with rate limiting and protection against timing attacks, following OWASP best practices Multi-Stage Security Reviews When working with AI-generated code, adopt this review workflow: Initial Generation : Get your working code solution Security Verification : Follow up with prompts like: "What security vulnerabilities might exist in this code?" "How can we improve error handling to prevent information leakage?" "Are there any edge cases that could lead to security issues?" Challenge Testing : Test with problematic inputs: "How would this code handle a user input of: admin'; DROP TABLE users; --" "What happens if a file upload contains malicious content?" Automate Security Checks Integrate security tools into your development workflow: Security Layer Tools to Consider Code Analysis SonarQube, ESLint Security Plugin, Semgrep Dependency Scanning OWASP Dependency-Check, Snyk, GitHub Dependabot Secret Detection GitLeaks, TruffleHog, detect-secrets Runtime Protection RASP tools, WAF configuration Educate Yourself on Core Security Concepts Even with minimal coding experience, understanding these fundamental security principles will help you evaluate AI-generated code: Defense in Depth : Multiple layers of protection are better than a single strong defense Principle of Least Privilege : Give components access only to what they absolutely need Input Validation : Never trust external input without proper validation Secure by Default : Start with the most secure configuration and only open what's necessary Conclusion: Responsible Vibe Coding Vibe coding is an exciting development that makes software creation accessible to more people than ever before. However, with this power comes responsibility, particularly around security. Treat AI assistants as collaborators whose work requires careful review rather than infallible experts whose code can be blindly trusted. By applying the security principles outlined in this playbook, you can confidently vibe code while keeping your applications secure. Remember: The most secure code is code that you understand. Take time to have your AI assistant explain its security choices and learn from them as you go. Next, check our guide on how to manage secrets in your MCP servers to learn how to keep your secrets safe and secure. Thomas Segura Thomas is a tech writer at Infisical, passionate about open-source software and cloud security. He enjoys simplifying complex topics and helping developers build secure applications. twitter github linkedin security ai-coding vibe-coding devsecops owasp Previous Article SSH Certificates: A Complete Guide Next Article Infisical Gateway: Securely Connect Infisical to Anything, Anywhere Starting with Infisical is simple, fast, and free. Get Started Get a demo PRODUCT Secret Management Secret Scanning Share Secret Pricing Security USE CASES Infisical Agent Kubernetes Dynamic Secrets Terraform Ansible Jenkins Docker AWS ECS GitLab GitHub SDKs DEVELOPERS Documentation Changelog API Reference Status Feedback & Requests Community Slack How to contribute RESOURCES Blog Infisical vs Vault Careers Hiring Forum Open Source Friends Customers Company Handbook Trust Center LEGAL Terms of Service Privacy Policy Subprocessors Service Level Agreement CONTACT Team Email Sales Support Copyright © 2026 Infisical Inc. | 2026-01-13T08:49:36 |
https://cursor.com/ | Cursor Skip to content Cursor Features Enterprise Pricing Resources ↓ Changelog Blog Docs ↗ Community Learn ↗ Workshops Forum ↗ Careers Features Enterprise Pricing Resources → Sign in Download Built to make you extraordinarily productive, Cursor is the best way to code with AI. Download for macOS ⤓ Try mobile agent → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: the IDE with AI-powered coding assistance, the CLI with command-line assistance. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools train_model.py run_experiment.py config.yaml import torch import torch . nn as nn from torch . utils . data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms . Compose ([ transforms . ToTensor ()]) train = datasets . MNIST ( root = "data" , train = True , download = True , transform = transform ) test = datasets . MNIST ( root = "data" , train = False , download = True , transform = transform ) return DataLoader ( train , batch_size = batch_size , shuffle = True ), DataLoader ( test , batch_size = batch_size ) class MLP ( nn . Module ): def __init__ ( self , hidden = 128 ): super (). __init__ () self . net = nn . Sequential ( nn . Flatten (), nn . Linear ( 28 * 28 , hidden ), nn . ReLU (), nn . Linear ( hidden , 10 ), ) def forward ( self , x ): return self . net ( x ) def train_model ( epochs = 1 , lr = 1e-3 , device = None): device = device or ( "cuda" if torch . cuda . is_available () else "cpu" ) model = MLP (). to ( device ) opt = torch . optim . Adam ( model . parameters (), lr = lr ) loss_fn = nn . CrossEntropyLoss () train_loader , _ = get_dataloaders () + # Seed for reproducibility + torch . manual_seed ( 42 ) + if device == "cuda" : + torch . cuda . manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch . cuda . amp . GradScaler ( enabled =( device == "cuda" )) + scheduler = torch . optim . lr_scheduler . CosineAnnealingLR ( opt , T_max = epochs ) model . train () for epoch in range ( epochs ) : total , correct = 0 , 0 for x , y in tqdm ( train_loader , desc = f "epoch { epoch + 1 } " ) : x , y = x . to ( device ), y . to ( device ) opt . zero_grad ( set_to_none = True ) logits = model ( x ) loss = loss_fn ( logits , y ) loss . backward () opt . step () scaler . scale ( loss ). backward () scaler . unscale_ ( opt ) + torch . nn . utils . clip_grad_norm_ ( model . parameters (), max_norm = 1.0 ) scaler . step ( opt ) scaler . update () + preds = logits . argmax ( dim = 1 ) + total += y . size ( 0 ) + correct += ( preds == y ). sum (). item () + acc = correct / max ( 1 , total ) scheduler . step () + print ( f "epoch { epoch + 1 } : acc= { acc :.3f } " ) return model `, import torch import torch.nn as nn from torch.utils.data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms. Compose ([transforms. ToTensor ()]) train = datasets. MNIST (root= " data " , train= True , download= True , transform=transform) test = datasets. MNIST (root= " data " , train= False , download= True , transform=transform) return DataLoader (train, batch_size=batch_size, shuffle= True ), DataLoader (test, batch_size=batch_size) class MLP (nn.Module): def __init__ ( self , hidden = 128 ): super (). __init__ () self .net = nn. Sequential ( nn. Flatten (), nn. Linear ( 28 * 28 , hidden), nn. ReLU (), nn. Linear (hidden, 10 ), ) def forward ( self , x ): return self . net (x) def train_model ( epochs = 1 , lr = 1e-3 , device = None ): device = device or ( " cuda " if torch.cuda. is_available () else " cpu " ) model = MLP (). to (device) opt = torch.optim. Adam (model. parameters (), lr=lr) loss_fn = nn. CrossEntropyLoss () train_loader, _ = get_dataloaders () + # Seed for reproducibility + torch. manual_seed ( 42 ) + if device == " cuda " : + torch.cuda. manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch.cuda.amp. GradScaler (enabled=(device == " cuda " )) + scheduler = torch.optim.lr_scheduler. CosineAnnealingLR (opt, T_max=epochs) model. train () for epoch in range (epochs): total, correct = 0 , 0 for x, y in tqdm (train_loader, desc= f "epoch { epoch+ 1 } " ): x, y = x. to (device), y. to (device) opt. zero_grad (set_to_none= True ) logits = model (x) loss = loss_fn (logits, y) loss. backward () opt. step () scaler. scale (loss). backward () scaler. unscale_ (opt) + torch.nn.utils. clip_grad_norm_ (model. parameters (), max_norm= 1.0 ) scaler. step (opt) scaler. update () + preds = logits. argmax (dim= 1 ) + total += y. size ( 0 ) + correct += (preds == y). sum (). item () + acc = correct / max ( 1 , total) scheduler. step () + print ( f "epoch { epoch+ 1 } : acc= { acc :.3f } " ) return model ` , PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. Agent GPT-5 agent Get CLI Cursor Agent ~/Repos/ml-research-notebook PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. → GPT-5.2 / for commands · @ for files Trusted every day by millions of professional developers. Agent turns ideas into code A human-AI programmer, orders of magnitude more effective than any developer alone. Learn about Agent → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools Analyze Tab vs Agent Usage Patterns Help me understand how teams split their focus between the tab view and the agents panel across our workspaces. Agent GPT-5 Magically accurate autocomplete Our custom Tab model predicts your next action with striking speed and precision. Learn about Tab → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor Dashboard.tsx SupportChat.tsx "use client" ; import React , { useState } from "react" ; import Navigation from "./Navigation" ; import SupportChat from "./SupportChat" ; export default function Dashboard () { return ( < div className = "flex h-[600px] border rounded-lg overflow-hidden" > < div className = "w-64 border-r" > </ div > < div className = "w-80 border-l" > < SupportChat /> </ div > </ div > ); } " use client " ; import React, { useState } from " react " ; import Navigation from " ./Navigation " ; import SupportChat from " ./SupportChat " ; export default function Dashboard() { return ( < div className = " flex h-[600px] border rounded-lg overflow-hidden " > < div className = " w-64 border-r " > </ div > < div className = " w-80 border-l " > < SupportChat /> </ div > </ div > ); } Everywhere software gets built Cursor is in GitHub reviewing your PRs, a teammate in Slack, and anywhere else you work. Learn about Cursor's ecosystem → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: Slack integration for team communication, GitHub integration for code review and debugging. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Slack Get Cursor for Slack #ask-cursor 8 members dylan small thing but would be really good to have anchor links on the website for releases 4 replies dylan wanna be able to go to cursor.com/changelog#1.0 to see 1.0 changelog eric checks out @cursor can you take a stab? Cursor APP I implemented direct linking for changelog entries and updated Node.js version constraints across the project to improve compatibility and maintainability. View PR Open in Cursor Open in Web dylan Nice @eric can you take a look? GitHub Pull Request Get BugBot Review cursor bot reviewed 1m ago src/vs/workbench/composer/browser/components/ComposerUnifiedDropdown.tsx 3292 - {selectedMode().keybinding} 3293 + {composerOpenModeToggleKeybinding} cursor bot 1m ago Bug: Function Returns Object Instead of String (Logic bug) The composerOpenModeToggleKeybinding is a function that needs to be called to get its value. Using it directly causes the keybinding display condition to always be truthy. Fix in Cursor Fix in Web The new way to build software. It was night and day from one batch to another, adoption went from single digits to over 80%. It just spread like wildfire, all the best builders were using Cursor. Diana Hu General Partner , Y Combinator The most useful AI tool that I currently pay for, hands down, is Cursor. It's fast, autocompletes when and where you need it to, handles brackets properly, sensible keyboard shortcuts, bring-your-own-model... everything is well put together. shadcn Creator of shadcn/ui The best LLM applications have an autonomy slider: you control how much independence to give the AI. In Cursor, you can do Tab completion, Cmd+K for targeted edits, or you can let it rip with the full autonomy agentic version. Andrej Karpathy CEO , Eureka Labs Cursor quickly grew from hundreds to thousands of extremely enthusiastic Stripe employees. We spend more on R&D and software creation than any other undertaking, and there's significant economic outcomes when making that process more efficient and productive. Patrick Collison Co‑Founder & CEO , Stripe It's official. I hate vibe coding. I love Cursor tab coding. It's wild. ThePrimeagen @ThePrimeagen It's definitely becoming more fun to be a programmer. It's less about digging through pages and more about what you want to happen. We are at the 1% of what's possible, and it's in interactive experiences like Cursor where models like GPT-5 shine brightest. Greg Brockman President , OpenAI Stay on the frontier Access the best models Choose between every cutting-edge model from OpenAI, Anthropic, Gemini, and xAI. Explore models ↗ Auto Suggested Composer 1 GPT-5 High Fast Claude Sonnet 4.5 ✓ Claude Opus 4.5 Gemini 3 Pro Grok Code Complete codebase understanding Cursor learns how your codebase works, no matter the scale or complexity. Learn about codebase indexing ↗ Where are these menu label colors defined? Develop enduring software Trusted by over half of the Fortune 500 to accelerate development, securely and at scale. Explore enterprise → Changelog CLI Jan 8, 2026 New CLI Features and Improved CLI Performance 2.3 Dec 22, 2025 Layout Customization and Stability Improvements Dec 18, 2025 Enterprise Insights, Billing Groups, Service Accounts, and Improved Security Controls 2.2 Dec 10, 2025 Debug Mode, Plan Mode Improvements, Multi-Agent Judging, and Pinned Chats See what's new in Cursor → Cursor is an applied team focused on building the future of coding. Join us → Recent highlights Introducing Cursor 2.0 and Composer A new interface and our first coding model, both purpose-built for working with agents. Product · Oct 29, 2025 Improving Cursor Tab with online RL Our new Tab model makes 21% fewer suggestions while having 28% higher accept rate. Research · Sep 12, 2025 1.5x faster MoE training with custom MXFP8 kernels Achieving a 3.5x MoE layer speedup with a complete rebuild for Blackwell GPUs. Research · Aug 29, 2025 View more posts → Try Cursor now. Download for macOS ⤓ Try mobile agent → Product Features Enterprise Web Agents Bugbot CLI Pricing Resources Download Changelog Docs ↗ Learn ↗ Forum ↗ Status ↗ Company Careers Blog Community Workshops Students Brand Legal Terms of Service Privacy Policy Data Use Security Connect X ↗ LinkedIn ↗ YouTube ↗ © 2026 Cursor 🛡 SOC 2 Certified 🌐 English ↓ English ✓ 简体中文 日本語 繁體中文 Skip to content Cursor Features Enterprise Pricing Resources ↓ Changelog Blog Docs ↗ Community Learn ↗ Workshops Forum ↗ Careers Features Enterprise Pricing Resources → Sign in Download Built to make you extraordinarily productive, Cursor is the best way to code with AI. Download for macOS ⤓ Try mobile agent → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: the IDE with AI-powered coding assistance, the CLI with command-line assistance. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools train_model.py run_experiment.py config.yaml import torch import torch . nn as nn from torch . utils . data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms . Compose ([ transforms . ToTensor ()]) train = datasets . MNIST ( root = "data" , train = True , download = True , transform = transform ) test = datasets . MNIST ( root = "data" , train = False , download = True , transform = transform ) return DataLoader ( train , batch_size = batch_size , shuffle = True ), DataLoader ( test , batch_size = batch_size ) class MLP ( nn . Module ): def __init__ ( self , hidden = 128 ): super (). __init__ () self . net = nn . Sequential ( nn . Flatten (), nn . Linear ( 28 * 28 , hidden ), nn . ReLU (), nn . Linear ( hidden , 10 ), ) def forward ( self , x ): return self . net ( x ) def train_model ( epochs = 1 , lr = 1e-3 , device = None): device = device or ( "cuda" if torch . cuda . is_available () else "cpu" ) model = MLP (). to ( device ) opt = torch . optim . Adam ( model . parameters (), lr = lr ) loss_fn = nn . CrossEntropyLoss () train_loader , _ = get_dataloaders () + # Seed for reproducibility + torch . manual_seed ( 42 ) + if device == "cuda" : + torch . cuda . manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch . cuda . amp . GradScaler ( enabled =( device == "cuda" )) + scheduler = torch . optim . lr_scheduler . CosineAnnealingLR ( opt , T_max = epochs ) model . train () for epoch in range ( epochs ) : total , correct = 0 , 0 for x , y in tqdm ( train_loader , desc = f "epoch { epoch + 1 } " ) : x , y = x . to ( device ), y . to ( device ) opt . zero_grad ( set_to_none = True ) logits = model ( x ) loss = loss_fn ( logits , y ) loss . backward () opt . step () scaler . scale ( loss ). backward () scaler . unscale_ ( opt ) + torch . nn . utils . clip_grad_norm_ ( model . parameters (), max_norm = 1.0 ) scaler . step ( opt ) scaler . update () + preds = logits . argmax ( dim = 1 ) + total += y . size ( 0 ) + correct += ( preds == y ). sum (). item () + acc = correct / max ( 1 , total ) scheduler . step () + print ( f "epoch { epoch + 1 } : acc= { acc :.3f } " ) return model `, import torch import torch.nn as nn from torch.utils.data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms. Compose ([transforms. ToTensor ()]) train = datasets. MNIST (root= " data " , train= True , download= True , transform=transform) test = datasets. MNIST (root= " data " , train= False , download= True , transform=transform) return DataLoader (train, batch_size=batch_size, shuffle= True ), DataLoader (test, batch_size=batch_size) class MLP (nn.Module): def __init__ ( self , hidden = 128 ): super (). __init__ () self .net = nn. Sequential ( nn. Flatten (), nn. Linear ( 28 * 28 , hidden), nn. ReLU (), nn. Linear (hidden, 10 ), ) def forward ( self , x ): return self . net (x) def train_model ( epochs = 1 , lr = 1e-3 , device = None ): device = device or ( " cuda " if torch.cuda. is_available () else " cpu " ) model = MLP (). to (device) opt = torch.optim. Adam (model. parameters (), lr=lr) loss_fn = nn. CrossEntropyLoss () train_loader, _ = get_dataloaders () + # Seed for reproducibility + torch. manual_seed ( 42 ) + if device == " cuda " : + torch.cuda. manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch.cuda.amp. GradScaler (enabled=(device == " cuda " )) + scheduler = torch.optim.lr_scheduler. CosineAnnealingLR (opt, T_max=epochs) model. train () for epoch in range (epochs): total, correct = 0 , 0 for x, y in tqdm (train_loader, desc= f "epoch { epoch+ 1 } " ): x, y = x. to (device), y. to (device) opt. zero_grad (set_to_none= True ) logits = model (x) loss = loss_fn (logits, y) loss. backward () opt. step () scaler. scale (loss). backward () scaler. unscale_ (opt) + torch.nn.utils. clip_grad_norm_ (model. parameters (), max_norm= 1.0 ) scaler. step (opt) scaler. update () + preds = logits. argmax (dim= 1 ) + total += y. size ( 0 ) + correct += (preds == y). sum (). item () + acc = correct / max ( 1 , total) scheduler. step () + print ( f "epoch { epoch+ 1 } : acc= { acc :.3f } " ) return model ` , PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. Agent GPT-5 agent Get CLI Cursor Agent ~/Repos/ml-research-notebook PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. → GPT-5.2 / for commands · @ for files Trusted every day by millions of professional developers. Agent turns ideas into code A human-AI programmer, orders of magnitude more effective than any developer alone. Learn about Agent → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools Analyze Tab vs Agent Usage Patterns Help me understand how teams split their focus between the tab view and the agents panel across our workspaces. Agent GPT-5 Magically accurate autocomplete Our custom Tab model predicts your next action with striking speed and precision. Learn about Tab → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor Dashboard.tsx SupportChat.tsx "use client" ; import React , { useState } from "react" ; import Navigation from "./Navigation" ; import SupportChat from "./SupportChat" ; export default function Dashboard () { return ( < div className = "flex h-[600px] border rounded-lg overflow-hidden" > < div className = "w-64 border-r" > </ div > < div className = "w-80 border-l" > < SupportChat /> </ div > </ div > ); } " use client " ; import React, { useState } from " react " ; import Navigation from " ./Navigation " ; import SupportChat from " ./SupportChat " ; export default function Dashboard() { return ( < div className = " flex h-[600px] border rounded-lg overflow-hidden " > < div className = " w-64 border-r " > </ div > < div className = " w-80 border-l " > < SupportChat /> </ div > </ div > ); } Everywhere software gets built Cursor is in GitHub reviewing your PRs, a teammate in Slack, and anywhere else you work. Learn about Cursor's ecosystem → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: Slack integration for team communication, GitHub integration for code review and debugging. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Slack Get Cursor for Slack #ask-cursor 8 members dylan small thing but would be really good to have anchor links on the website for releases 4 replies dylan wanna be able to go to cursor.com/changelog#1.0 to see 1.0 changelog eric checks out @cursor can you take a stab? Cursor APP I implemented direct linking for changelog entries and updated Node.js version constraints across the project to improve compatibility and maintainability. View PR Open in Cursor Open in Web dylan Nice @eric can you take a look? GitHub Pull Request Get BugBot Review cursor bot reviewed 1m ago src/vs/workbench/composer/browser/components/ComposerUnifiedDropdown.tsx 3292 - {selectedMode().keybinding} 3293 + {composerOpenModeToggleKeybinding} cursor bot 1m ago Bug: Function Returns Object Instead of String (Logic bug) The composerOpenModeToggleKeybinding is a function that needs to be called to get its value. Using it directly causes the keybinding display condition to always be truthy. Fix in Cursor Fix in Web The new way to build software. It was night and day from one batch to another, adoption went from single digits to over 80%. It just spread like wildfire, all the best builders were using Cursor. Diana Hu General Partner , Y Combinator The most useful AI tool that I currently pay for, hands down, is Cursor. It's fast, autocompletes when and where you need it to, handles brackets properly, sensible keyboard shortcuts, bring-your-own-model... everything is well put together. shadcn Creator of shadcn/ui The best LLM applications have an autonomy slider: you control how much independence to give the AI. In Cursor, you can do Tab completion, Cmd+K for targeted edits, or you can let it rip with the full autonomy agentic version. Andrej Karpathy CEO , Eureka Labs Cursor quickly grew from hundreds to thousands of extremely enthusiastic Stripe employees. We spend more on R&D and software creation than any other undertaking, and there's significant economic outcomes when making that process more efficient and productive. Patrick Collison Co‑Founder & CEO , Stripe It's official. I hate vibe coding. I love Cursor tab coding. It's wild. ThePrimeagen @ThePrimeagen It's definitely becoming more fun to be a programmer. It's less about digging through pages and more about what you want to happen. We are at the 1% of what's possible, and it's in interactive experiences like Cursor where models like GPT-5 shine brightest. Greg Brockman President , OpenAI Stay on the frontier Access the best models Choose between every cutting-edge model from OpenAI, Anthropic, Gemini, and xAI. Explore models ↗ Auto Suggested Composer 1 GPT-5 High Fast Claude Sonnet 4.5 ✓ Claude Opus 4.5 Gemini 3 Pro Grok Code Complete codebase understanding Cursor learns how your codebase works, no matter the scale or complexity. Learn about codebase indexing ↗ Where are these menu label colors defined? Develop enduring software Trusted by over half of the Fortune 500 to accelerate development, securely and at scale. Explore enterprise → Changelog CLI Jan 8, 2026 New CLI Features and Improved CLI Performance 2.3 Dec 22, 2025 Layout Customization and Stability Improvements Dec 18, 2025 Enterprise Insights, Billing Groups, Service Accounts, and Improved Security Controls 2.2 Dec 10, 2025 Debug Mode, Plan Mode Improvements, Multi-Agent Judging, and Pinned Chats See what's new in Cursor → Cursor is an applied team focused on building the future of coding. Join us → Recent highlights Introducing Cursor 2.0 and Composer A new interface and our first coding model, both purpose-built for working with agents. Product · Oct 29, 2025 Improving Cursor Tab with online RL Our new Tab model makes 21% fewer suggestions while having 28% higher accept rate. Research · Sep 12, 2025 1.5x faster MoE training with custom MXFP8 kernels Achieving a 3.5x MoE layer speedup with a complete rebuild for Blackwell GPUs. Research · Aug 29, 2025 View more posts → Try Cursor now. Download for macOS ⤓ Try mobile agent → Product Features Enterprise Web Agents Bugbot CLI Pricing Resources Download Changelog Docs ↗ Learn ↗ Forum ↗ Status ↗ Company Careers Blog Community Workshops Students Brand Legal Terms of Service Privacy Policy Data Use Security Connect X ↗ LinkedIn ↗ YouTube ↗ © 2026 Cursor 🛡 SOC 2 Certified 🌐 English ↓ English ✓ 简体中文 日本語 繁體中文 | 2026-01-13T08:49:36 |
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https://dev.to/new?prefill=---%0Atitle%3A%20%0Apublished%3A%20%0Atags%3A%20devchallenge%2C%20frontendchallenge%2C%20webdev%2C%20javascript%0A---%0A%0A_This%20is%20a%20submission%20for%20%5BFrontend%20Challenge%20-%20Halloween%20Edition%2C%20Perfect%20Landing%5D(https%3A%2F%2Fdev.to%2Fchallenges%2Ffrontend-2025-10-15)_%0A%0A%23%23%20What%20I%20Built%0A%0A%3C!--%20Tell%20us%20about%20your%20landing%20page%20and%20the%20Halloween%20theme%20you%20chose.%20--%3E%0A%0A%23%23%20Demo%0A%3C!--%20Show%20us%20your%20project!%20You%20can%20embed%20your%20project%20using%3A%20--%3E%20%3C!--%20Google%20Cloud%20Run%3A%20%60%7B%25%20embed%20cloud_run_link%20%25%7D%60%20--%3E%20%3C!--%20CodePen%3A%20%60%7B%25%20codepen%20https%3A%2F%2F...%20%25%7D%60%20--%3E%20%3C!--%20Or%20share%20an%20image%20of%20your%20project%20with%20a%20direct%20link%20to%20the%20live%20demo.%20--%3E%0A%0A%23%23%20Journey%0A%3C!--%20Tell%20us%20about%20your%20process%2C%20what%20you%20learned%2C%20anything%20you%20are%20particularly%20proud%20of%2C%20what%20you%20hope%20to%20do%20next%2C%20etc.%20--%3E%0A%0A%3C!--%20Team%20Submissions%3A%20Please%20pick%20one%20member%20to%20publish%20the%20submission%20and%20credit%20teammates%20by%20listing%20their%20DEV%20usernames%20directly%20in%20the%20body%20of%20the%20post.%20--%3E%0A%0A%3C!--%20We%20encourage%20you%20to%20consider%20adding%20a%20license%20for%20your%20code.%20--%3E%0A%0A%3C!--%20Don | New Post - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. DUMB DEV Community Follow Memes and software development shitposting Design Community Follow Web design, graphic design and everything in-between Security Forem Follow Your central hub for all things security. From ethical hacking and CTFs to GRC and career development, for beginners and pros alike Golf Forem Follow A community of golfers and golfing enthusiasts Crypto Forem Follow A collaborative community for all things Crypto—from Bitcoin to protocol development and DeFi to NFTs and market analysis. Parenting Follow A place for parents to the share the joys, challenges, and wisdom that come from raising kids. We're here for them and for each other. Forem Core Follow Discussing the core forem open source software project — features, bugs, performance, self-hosting. Maker Forem Follow A community for makers, hobbyists, and professionals to discuss Arduino, Raspberry Pi, 3D printing, and much more. HMPL.js Forem Follow For developers using HMPL.js to build fast, lightweight web apps. A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Join the DEV Community DEV Community is a community of 3,676,891 amazing developers Continue with Apple Continue with Facebook Continue with Forem Continue with GitHub Continue with Google Continue with Twitter (X) OR Email Password Remember me Forgot password? By signing in, you are agreeing to our privacy policy , terms of use and code of conduct . New to DEV Community? Create account . 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://www.fsf.org/working-together/moving | Moving to free software — Free Software Foundation — Working together for free software ​ Push freedom ahead! The free software community has always thwarted the toughest challenges facing freedom in technology. This winter season, we want to thank the many individuals and projects that have helped us get where we are today: a world where a growing number of users are able to do their computing in full freedom. Our work isn't over. We have so much more to do. Help us reach our stretch New Year's membership goal of 100 new associate members by January 16, 2026, and keep the FSF strong and independent. Join | Read more Join Renew Donate Skip to content , sitemap or skip to search . Personal tools Log in Help! Members forum About Campaigns Licensing Membership Resources Community ♥Donate♥ Shop Search You are here: Home › Working together for free software › Moving to free software Info Moving to free software by Matt Lee Contributions — Published on Jun 24, 2010 12:10 PM Making the first step toward using free software is easier than you'd think, even for the most inexperienced of computer users. Here are some guides for some simple first steps you can make, as well as long-term solutions you may wish to consider. If you use... Microsoft Windows macOS Learn more Try a free operating system! Meet the Free Software Community Look who's using free software Document Actions Share on social networks Syndicate: News Events Blogs Jobs GNU 1PC9aZC4hNX2rmmrt7uHTfYAS3hRbph4UN Sign up Enter your email address to receive our monthly newsletter, the Free Software Supporter News Eko K. A. Owen joins the FSF board as the union staff pick Dec 29, 2025 Free Software Foundation receives historic private donations Dec 24, 2025 Free Software Awards winners announced: Andy Wingo, Alx Sa, Govdirectory Dec 09, 2025 More news… Recent blogs Turning freedom values into freedom practice with the FSF tech team December GNU Spotlight with Amin Bandali featuring sixteen new GNU releases: GnuPG, a2ps, and more! Celebrate the new year: join the free software community! A message from FSF president Ian Kelling Recent blogs - More… Upcoming Events Free Software Directory meeting on IRC: Friday, January 16, starting at 12:00 EST (17:00 UTC) Jan 16, 2026 12:00 PM - 03:00 PM — #fsf on libera.chat Previous events… Upcoming events… The FSF is a charity with a worldwide mission to advance software freedom — learn about our history and work. Copyright © 2004-2026 Free Software Foundation , Inc. Privacy Policy . This work is licensed under a Creative Commons Attribution-No Derivative Works 3.0 license (or later version) — Why this license? Skip sitemap or skip to licensing items About Staff and Board Contact Us Press Information Jobs Volunteering and Internships History Privacy Policy JavaScript Licenses Hardware Database Free Software Directory Free Software Resources Copyright Infringement Notification Skip to general items Campaigns Freedom Ladder Fight to Repair Free JavaScript High Priority Free Software Projects Secure Boot vs Restricted Boot Surveillance Upgrade from Windows Working Together for Free Software GNU Operating System Defective by Design End Software Patents OpenDocument Free BIOS Connect with free software users Skip to philosophical items Licensing Education Licenses GNU GPL GNU AGPL GNU LGPL GNU FDL Licensing FAQ Compliance How to use GNU licenses for your own software Latest News Upcoming Events FSF Blogs Skip list Donate to the FSF Join the FSF Patrons Associate Members My Account Working Together for Free Software Fund Philosophy The Free Software Definition Copyleft: Pragmatic Idealism Free Software and Free Manuals Selling Free Software Motives for Writing Free Software The Right To Read Why Open Source Misses the Point of Free Software Complete Sitemap fsf.org is powered by: Plone Zope Python CiviCRM HTML5 Arabic Belarussian Bulgarian Catalan Chinese Cornish Czech Danish English French German Greek Hebrew Hindi Italian Japanese Korean Norwegian Polish Portuguese Portuguese (Brazil) Romanian Russian Slovak Spanish Swedish Turkish Urdu Welsh Send your feedback on our translations and new translations of pages to campaigns@fsf.org . | 2026-01-13T08:49:36 |
https://www.fsf.org/share?u=https://www.fsf.org/working-together/working-together-for-free-software&t=Working together for free software | — Free Software Foundation — Working together for free software ​ Push freedom ahead! The free software community has always thwarted the toughest challenges facing freedom in technology. This winter season, we want to thank the many individuals and projects that have helped us get where we are today: a world where a growing number of users are able to do their computing in full freedom. Our work isn't over. We have so much more to do. Help us reach our stretch New Year's membership goal of 100 new associate members by January 16, 2026, and keep the FSF strong and independent. Join | Read more Join Renew Donate Skip to content , sitemap or skip to search . Personal tools Log in Help! Members forum About Campaigns Licensing Membership Resources Community ♥Donate♥ Shop Search You are here: Home › share Info Help us raise awareness of free software within your social networks We recommend these sites because they follow ethical guidelines and respect their users. Sign up for an account on any instance of: Mastodon , and follow the FSF . PeerTube , and follow the FSF . GNU social You can also help us create awareness by sharing on: Hacker News Other popular sites for sharing news are a problem for technology users -- they are set up to lock users to their services and deny them basic privacy and autonomy, though on any such site, you may find free software supporters congregating in unofficial groups. It's important that we let people everywhere know about the importance of free software, so if you have an account on these sites, please help spread the word. Share on Facebook — What's wrong with Facebook? Share on X Share on Reddit Please don't let sharing important news about free software lead to further use of these sites. 1PC9aZC4hNX2rmmrt7uHTfYAS3hRbph4UN Sign up Enter your email address to receive our monthly newsletter, the Free Software Supporter News Eko K. A. Owen joins the FSF board as the union staff pick Dec 29, 2025 Free Software Foundation receives historic private donations Dec 24, 2025 Free Software Awards winners announced: Andy Wingo, Alx Sa, Govdirectory Dec 09, 2025 More news… Recent blogs Turning freedom values into freedom practice with the FSF tech team December GNU Spotlight with Amin Bandali featuring sixteen new GNU releases: GnuPG, a2ps, and more! Celebrate the new year: join the free software community! A message from FSF president Ian Kelling Recent blogs - More… Upcoming Events Free Software Directory meeting on IRC: Friday, January 16, starting at 12:00 EST (17:00 UTC) Jan 16, 2026 12:00 PM - 03:00 PM — #fsf on libera.chat Previous events… Upcoming events… The FSF is a charity with a worldwide mission to advance software freedom — learn about our history and work. Copyright © 2004-2026 Free Software Foundation , Inc. Privacy Policy . This work is licensed under a Creative Commons Attribution-No Derivative Works 3.0 license (or later version) — Why this license? Skip sitemap or skip to licensing items About Staff and Board Contact Us Press Information Jobs Volunteering and Internships History Privacy Policy JavaScript Licenses Hardware Database Free Software Directory Free Software Resources Copyright Infringement Notification Skip to general items Campaigns Freedom Ladder Fight to Repair Free JavaScript High Priority Free Software Projects Secure Boot vs Restricted Boot Surveillance Upgrade from Windows Working Together for Free Software GNU Operating System Defective by Design End Software Patents OpenDocument Free BIOS Connect with free software users Skip to philosophical items Licensing Education Licenses GNU GPL GNU AGPL GNU LGPL GNU FDL Licensing FAQ Compliance How to use GNU licenses for your own software Latest News Upcoming Events FSF Blogs Skip list Donate to the FSF Join the FSF Patrons Associate Members My Account Working Together for Free Software Fund Philosophy The Free Software Definition Copyleft: Pragmatic Idealism Free Software and Free Manuals Selling Free Software Motives for Writing Free Software The Right To Read Why Open Source Misses the Point of Free Software Complete Sitemap fsf.org is powered by: Plone Zope Python CiviCRM HTML5 Arabic Belarussian Bulgarian Catalan Chinese Cornish Czech Danish English French German Greek Hebrew Hindi Italian Japanese Korean Norwegian Polish Portuguese Portuguese (Brazil) Romanian Russian Slovak Spanish Swedish Turkish Urdu Welsh Send your feedback on our translations and new translations of pages to campaigns@fsf.org . | 2026-01-13T08:49:36 |
https://dev.to/aaron_rose_0787cc8b4775a0 | Aaron Rose - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Aaron Rose Software engineer and technology writer at tech-reader.blog Location Dallas, TX Joined Joined on Aug 24, 2024 Personal website https://www.tech-reader.blog 8 Week Community Wellness Streak Consistency pays off! Be an active part of our community by posting at least 2 comments per week for 8 straight weeks. Earn the 16 Week Badge next. Got it Close JavaScript Awarded to the top JavaScript author each week Got it Close Top 7 Awarded for having a post featured in the weekly "must-reads" list. 🙌 Got it Close Go Awarded to the top Go author each week Got it Close Python Awarded to the top Python author each week Got it Close 4 Week Community Wellness Streak Keep contributing to discussions by posting at least 2 comments per week for 4 straight weeks. Unlock the 8 Week Badge next. Got it Close 2 Week Community Wellness Streak Keep the community conversation going! Post at least 2 comments for 2 straight weeks and unlock the 4 Week Badge. Got it Close 1 Week Community Wellness Streak For actively engaging with the community by posting at least 2 comments in a single week. Got it Close One Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least one year. Got it Close Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close More info about @aaron_rose_0787cc8b4775a0 Skills/Languages Python, Node.js, SQL, AWS, GCP, Azure, Oracle Cloud, LocalStack, Docker, Kubernetes, Linux, DevOps pipelines, IaC (Terraform, CloudFormation), CI/CD, serverless, Raspberry Pi, database administration Currently learning Advanced multi-cloud architecture patterns across AWS, GCP, Azure, and Oracle Cloud. Exploring infrastructure automation with Python and diving deep into LocalStack for local cloud development. Currently hacking on Multi-cloud infrastructure automation with Python, building DevOps pipelines that span multiple cloud providers, and maintaining a homelab that's equal parts Ubuntu servers and Raspberry Pi clusters. Available for * Cloud infrastructure discussions * Cloud tooling * Serverless patterns * Database design * Creative edge computing solutions * Everything Ubuntu * Everything Raspberry Pi Post 176 posts published Comment 79 comments written Tag 12 tags followed The Secret Life of JavaScript: Identity Aaron Rose Aaron Rose Aaron Rose Follow Jan 13 The Secret Life of JavaScript: Identity # javascript # coding # programming # software 1 reaction Comments Add Comment 3 min read Want to connect with Aaron Rose? Create an account to connect with Aaron Rose. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in The Secret Life of Go: Interfaces Aaron Rose Aaron Rose Aaron Rose Follow Jan 12 The Secret Life of Go: Interfaces # go # coding # programming # software 9 reactions Comments Add Comment 5 min read The Secret Life of Go: Testing Aaron Rose Aaron Rose Aaron Rose Follow Jan 10 The Secret Life of Go: Testing # go # coding # programming # softwaredevelopment 14 reactions Comments 3 comments 6 min read The Secret Life of Python: The Matryoshka Trap Aaron Rose Aaron Rose Aaron Rose Follow Jan 9 The Secret Life of Python: The Matryoshka Trap # python # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 4 min read The Secret Life of Python: The Dangerous Reflection Aaron Rose Aaron Rose Aaron Rose Follow Jan 8 The Secret Life of Python: The Dangerous Reflection # python # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: Illusions Aaron Rose Aaron Rose Aaron Rose Follow Jan 6 The Secret Life of JavaScript: Illusions # javascript # coding # programming # softwaredevelopment 9 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: Memories Aaron Rose Aaron Rose Aaron Rose Follow Jan 5 The Secret Life of JavaScript: Memories # javascript # coding # programming # softwaredevelopment 20 reactions Comments 3 comments 3 min read Happy New Year! 🎉 Aaron Rose Aaron Rose Aaron Rose Follow Jan 1 Happy New Year! 🎉 # python # 2026 # coding # strongcoffee 44 reactions Comments 20 comments 1 min read The Secret Life of JavaScript: Inheritance Aaron Rose Aaron Rose Aaron Rose Follow Dec 30 '25 The Secret Life of JavaScript: Inheritance # javascript # coding # programming # softwaredevelopment 15 reactions Comments 3 comments 3 min read The Secret Life of Go: Error Handling Aaron Rose Aaron Rose Aaron Rose Follow Dec 29 '25 The Secret Life of Go: Error Handling # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 6 min read The Secret Life of Go: Packages and Structure Aaron Rose Aaron Rose Aaron Rose Follow Dec 28 '25 The Secret Life of Go: Packages and Structure # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 5 min read Python by Structure: Precise Error Scoping with Try/Except/Else Aaron Rose Aaron Rose Aaron Rose Follow Dec 27 '25 Python by Structure: Precise Error Scoping with Try/Except/Else # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 2 min read Python by Structure: Decorators and the "Logic Envelope" Aaron Rose Aaron Rose Aaron Rose Follow Dec 27 '25 Python by Structure: Decorators and the "Logic Envelope" # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 2 min read Python by Structure: List Comprehensions and the "Single Action" Aaron Rose Aaron Rose Aaron Rose Follow Dec 24 '25 Python by Structure: List Comprehensions and the "Single Action" # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 3 min read Python by Structure: How the 'with' Statement Automates Resource Management Aaron Rose Aaron Rose Aaron Rose Follow Dec 24 '25 Python by Structure: How the 'with' Statement Automates Resource Management # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 3 min read The Secret Life of Python: The Truth About Nothing Aaron Rose Aaron Rose Aaron Rose Follow Dec 23 '25 The Secret Life of Python: The Truth About Nothing # python # coding # programming # software 6 reactions Comments 1 comment 4 min read The Secret Life of JavaScript: Asynchrony Aaron Rose Aaron Rose Aaron Rose Follow Dec 21 '25 The Secret Life of JavaScript: Asynchrony # javascript # coding # programming # software 9 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: The Power of Function Composition Aaron Rose Aaron Rose Aaron Rose Follow Dec 20 '25 The Secret Life of JavaScript: The Power of Function Composition # javascript # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 5 min read The Secret Life of Go: Atomic Operations Aaron Rose Aaron Rose Aaron Rose Follow Dec 19 '25 The Secret Life of Go: Atomic Operations # go # coding # programming # softwaredevelopment 8 reactions Comments 1 comment 6 min read The Secret Life of Python: The Infinite Copy Aaron Rose Aaron Rose Aaron Rose Follow Dec 18 '25 The Secret Life of Python: The Infinite Copy # python # coding # programming # software 15 reactions Comments 6 comments 4 min read The Secret Life of Python: The Statue in the Memory Aaron Rose Aaron Rose Aaron Rose Follow Dec 17 '25 The Secret Life of Python: The Statue in the Memory # python # coding # programming # softwaredevelopment 11 reactions Comments 2 comments 4 min read The Secret Life of Python: The Myth of the Box Aaron Rose Aaron Rose Aaron Rose Follow Dec 16 '25 The Secret Life of Python: The Myth of the Box # python # coding # programming # softwaredevelopment 11 reactions Comments 1 comment 4 min read The Secret Life of JavaScript: Currying vs. Partial Application Aaron Rose Aaron Rose Aaron Rose Follow Dec 15 '25 The Secret Life of JavaScript: Currying vs. Partial Application # javascript # coding # programming # softwaredevelopment 13 reactions Comments 2 comments 5 min read Python by Structure: List Comprehensions and Their Hidden Complexity Aaron Rose Aaron Rose Aaron Rose Follow Dec 14 '25 Python by Structure: List Comprehensions and Their Hidden Complexity # python # coding # programming # software 6 reactions Comments Add Comment 7 min read The Secret Life of JavaScript: Understanding Closures Aaron Rose Aaron Rose Aaron Rose Follow Dec 12 '25 The Secret Life of JavaScript: Understanding Closures # javascript # coding # programming # softwaredevelopment 38 reactions Comments 5 comments 10 min read The Secret Life of JavaScript: Understanding Prototypes Aaron Rose Aaron Rose Aaron Rose Follow Dec 11 '25 The Secret Life of JavaScript: Understanding Prototypes # javascript # coding # programming # softwaredevelopment 29 reactions Comments 7 comments 11 min read The Secret Life of Python: The Import System Aaron Rose Aaron Rose Aaron Rose Follow Dec 10 '25 The Secret Life of Python: The Import System # python # coding # programming # software 7 reactions Comments 3 comments 19 min read The Secret Life of Go: Mutexes and Synchronization Aaron Rose Aaron Rose Aaron Rose Follow Dec 9 '25 The Secret Life of Go: Mutexes and Synchronization # go # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 10 min read The Secret Life of JavaScript: Understanding 'this' Aaron Rose Aaron Rose Aaron Rose Follow Dec 8 '25 The Secret Life of JavaScript: Understanding 'this' # javascript # coding # programming # software 12 reactions Comments 5 comments 11 min read The Secret Life of JavaScript: Let, Const, and Why Variables Are Complicated Aaron Rose Aaron Rose Aaron Rose Follow Dec 8 '25 The Secret Life of JavaScript: Let, Const, and Why Variables Are Complicated # javascript # coding # programming # software 43 reactions Comments 15 comments 9 min read Python by Structure: Context Managers and the 'with' Statement Aaron Rose Aaron Rose Aaron Rose Follow Dec 7 '25 Python by Structure: Context Managers and the 'with' Statement # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 6 min read The Secret Life of Python: Metaclasses - Classes That Make Classes Aaron Rose Aaron Rose Aaron Rose Follow Dec 6 '25 The Secret Life of Python: Metaclasses - Classes That Make Classes # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 17 min read The Secret Life of Go: Goroutines and Channels Aaron Rose Aaron Rose Aaron Rose Follow Dec 5 '25 The Secret Life of Go: Goroutines and Channels # go # coding # programming # software 6 reactions Comments 1 comment 9 min read Python by Structure: Return Value Transformations with Decorators Aaron Rose Aaron Rose Aaron Rose Follow Dec 4 '25 Python by Structure: Return Value Transformations with Decorators # python # coding # programming # softwaredevelopment 3 reactions Comments 3 comments 4 min read The Secret Life of Python: super() and the Method Resolution Order Aaron Rose Aaron Rose Aaron Rose Follow Dec 3 '25 The Secret Life of Python: super() and the Method Resolution Order # python # coding # programming # software 21 reactions Comments 4 comments 18 min read The Secret Life of Go: Interfaces Aaron Rose Aaron Rose Aaron Rose Follow Dec 2 '25 The Secret Life of Go: Interfaces # go # coding # programming # softwaredevelopment 7 reactions Comments Add Comment 8 min read Python by Structure: Property Decorators and Managed Attributes Aaron Rose Aaron Rose Aaron Rose Follow Dec 1 '25 Python by Structure: Property Decorators and Managed Attributes # python # coding # programming # software 4 reactions Comments 1 comment 5 min read The Secret Life of Go: Structs Aaron Rose Aaron Rose Aaron Rose Follow Dec 1 '25 The Secret Life of Go: Structs # go # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 8 min read The Secret Life of Go: Maps Aaron Rose Aaron Rose Aaron Rose Follow Nov 29 '25 The Secret Life of Go: Maps # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 7 min read The Secret Life of Go: Arrays and Slices Aaron Rose Aaron Rose Aaron Rose Follow Nov 28 '25 The Secret Life of Go: Arrays and Slices # go # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 8 min read Python by Structure: How Decorators Transform Classes Aaron Rose Aaron Rose Aaron Rose Follow Nov 27 '25 Python by Structure: How Decorators Transform Classes # python # coding # programming # softwaredevelopment 3 reactions Comments 1 comment 5 min read The Secret Life of Python: Attribute Lookup Secrets Aaron Rose Aaron Rose Aaron Rose Follow Nov 27 '25 The Secret Life of Python: Attribute Lookup Secrets # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 16 min read The Secret Life of Go: Functions Aaron Rose Aaron Rose Aaron Rose Follow Nov 25 '25 The Secret Life of Go: Functions # go # coding # programming # softwaredevelopment 6 reactions Comments 1 comment 8 min read The Secret Life of Go: Variables & Types Aaron Rose Aaron Rose Aaron Rose Follow Nov 25 '25 The Secret Life of Go: Variables & Types # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 10 min read The Secret Life of Go Aaron Rose Aaron Rose Aaron Rose Follow Nov 22 '25 The Secret Life of Go # go # coding # programming # softwaredevelopment 13 reactions Comments 4 comments 10 min read Python by Structure - Class-Based Decorators That Remember Aaron Rose Aaron Rose Aaron Rose Follow Nov 21 '25 Python by Structure - Class-Based Decorators That Remember # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 3 min read The Secret Life of Python: Bytecode Secrets - What Python Really Runs Aaron Rose Aaron Rose Aaron Rose Follow Nov 20 '25 The Secret Life of Python: Bytecode Secrets - What Python Really Runs # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 26 min read Python by Structure: Decorator Chains and Execution Order Aaron Rose Aaron Rose Aaron Rose Follow Nov 20 '25 Python by Structure: Decorator Chains and Execution Order # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 5 min read The Secret Life of Python: MRO Secrets - The Diamond Problem Solved Aaron Rose Aaron Rose Aaron Rose Follow Nov 19 '25 The Secret Life of Python: MRO Secrets - The Diamond Problem Solved # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 24 min read Python by Structure: Match Statements and Pattern Guards Aaron Rose Aaron Rose Aaron Rose Follow Nov 19 '25 Python by Structure: Match Statements and Pattern Guards # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 6 min read The Secret Life of Python: GIL Secrets - Python's Threading Mystery Aaron Rose Aaron Rose Aaron Rose Follow Nov 18 '25 The Secret Life of Python: GIL Secrets - Python's Threading Mystery # python # coding # programming # softwaredevelopment 5 reactions Comments 2 comments 21 min read Python by Structure: The Walrus Operator - Assignment Where You Need It Aaron Rose Aaron Rose Aaron Rose Follow Nov 18 '25 Python by Structure: The Walrus Operator - Assignment Where You Need It # python # coding # programming # softwaredevelopment 10 reactions Comments Add Comment 4 min read Python by Structure: Context Managers and the With Statement Aaron Rose Aaron Rose Aaron Rose Follow Nov 16 '25 Python by Structure: Context Managers and the With Statement # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 4 min read Python by Structure: Generator Delegation with Yield From Aaron Rose Aaron Rose Aaron Rose Follow Nov 16 '25 Python by Structure: Generator Delegation with Yield From # python # coding # programming # softwaredevelopment Comments Add Comment 4 min read The Secret Life of Python: Metaclass Secrets - Classes That Create Classes Aaron Rose Aaron Rose Aaron Rose Follow Nov 15 '25 The Secret Life of Python: Metaclass Secrets - Classes That Create Classes # python # coding # programming # software Comments Add Comment 13 min read Python by Structure: The For/Else Block You Didn't Know Existed Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 Python by Structure: The For/Else Block You Didn't Know Existed # python # coding # programming # softwaredevelopment 5 reactions Comments 5 comments 3 min read Python by Structure: The Try/Else Block You're Not Using Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 Python by Structure: The Try/Else Block You're Not Using # python # coding # programming # software 6 reactions Comments Add Comment 3 min read The Secret Life of Python: Descriptor Secrets - How Properties Really Work Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 The Secret Life of Python: Descriptor Secrets - How Properties Really Work # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 16 min read The Secret Life of Python: Context Manager Secrets - The Magic of `with` Aaron Rose Aaron Rose Aaron Rose Follow Nov 13 '25 The Secret Life of Python: Context Manager Secrets - The Magic of `with` # python # coding # programming # software 4 reactions Comments Add Comment 14 min read The Secret Life of Python: Decorator Secrets - Functions That Wrap Functions Aaron Rose Aaron Rose Aaron Rose Follow Nov 12 '25 The Secret Life of Python: Decorator Secrets - Functions That Wrap Functions # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 14 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://dev.to/aaron_rose_0787cc8b4775a0 | Aaron Rose - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Aaron Rose Software engineer and technology writer at tech-reader.blog Location Dallas, TX Joined Joined on Aug 24, 2024 Personal website https://www.tech-reader.blog 8 Week Community Wellness Streak Consistency pays off! Be an active part of our community by posting at least 2 comments per week for 8 straight weeks. Earn the 16 Week Badge next. Got it Close JavaScript Awarded to the top JavaScript author each week Got it Close Top 7 Awarded for having a post featured in the weekly "must-reads" list. 🙌 Got it Close Go Awarded to the top Go author each week Got it Close Python Awarded to the top Python author each week Got it Close 4 Week Community Wellness Streak Keep contributing to discussions by posting at least 2 comments per week for 4 straight weeks. Unlock the 8 Week Badge next. Got it Close 2 Week Community Wellness Streak Keep the community conversation going! Post at least 2 comments for 2 straight weeks and unlock the 4 Week Badge. Got it Close 1 Week Community Wellness Streak For actively engaging with the community by posting at least 2 comments in a single week. Got it Close One Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least one year. Got it Close Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close More info about @aaron_rose_0787cc8b4775a0 Skills/Languages Python, Node.js, SQL, AWS, GCP, Azure, Oracle Cloud, LocalStack, Docker, Kubernetes, Linux, DevOps pipelines, IaC (Terraform, CloudFormation), CI/CD, serverless, Raspberry Pi, database administration Currently learning Advanced multi-cloud architecture patterns across AWS, GCP, Azure, and Oracle Cloud. Exploring infrastructure automation with Python and diving deep into LocalStack for local cloud development. Currently hacking on Multi-cloud infrastructure automation with Python, building DevOps pipelines that span multiple cloud providers, and maintaining a homelab that's equal parts Ubuntu servers and Raspberry Pi clusters. Available for * Cloud infrastructure discussions * Cloud tooling * Serverless patterns * Database design * Creative edge computing solutions * Everything Ubuntu * Everything Raspberry Pi Post 176 posts published Comment 79 comments written Tag 12 tags followed The Secret Life of JavaScript: Identity Aaron Rose Aaron Rose Aaron Rose Follow Jan 13 The Secret Life of JavaScript: Identity # javascript # coding # programming # software 1 reaction Comments Add Comment 3 min read Want to connect with Aaron Rose? Create an account to connect with Aaron Rose. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in The Secret Life of Go: Interfaces Aaron Rose Aaron Rose Aaron Rose Follow Jan 12 The Secret Life of Go: Interfaces # go # coding # programming # software 9 reactions Comments Add Comment 5 min read The Secret Life of Go: Testing Aaron Rose Aaron Rose Aaron Rose Follow Jan 10 The Secret Life of Go: Testing # go # coding # programming # softwaredevelopment 14 reactions Comments 3 comments 6 min read The Secret Life of Python: The Matryoshka Trap Aaron Rose Aaron Rose Aaron Rose Follow Jan 9 The Secret Life of Python: The Matryoshka Trap # python # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 4 min read The Secret Life of Python: The Dangerous Reflection Aaron Rose Aaron Rose Aaron Rose Follow Jan 8 The Secret Life of Python: The Dangerous Reflection # python # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: Illusions Aaron Rose Aaron Rose Aaron Rose Follow Jan 6 The Secret Life of JavaScript: Illusions # javascript # coding # programming # softwaredevelopment 9 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: Memories Aaron Rose Aaron Rose Aaron Rose Follow Jan 5 The Secret Life of JavaScript: Memories # javascript # coding # programming # softwaredevelopment 20 reactions Comments 3 comments 3 min read Happy New Year! 🎉 Aaron Rose Aaron Rose Aaron Rose Follow Jan 1 Happy New Year! 🎉 # python # 2026 # coding # strongcoffee 44 reactions Comments 20 comments 1 min read The Secret Life of JavaScript: Inheritance Aaron Rose Aaron Rose Aaron Rose Follow Dec 30 '25 The Secret Life of JavaScript: Inheritance # javascript # coding # programming # softwaredevelopment 15 reactions Comments 3 comments 3 min read The Secret Life of Go: Error Handling Aaron Rose Aaron Rose Aaron Rose Follow Dec 29 '25 The Secret Life of Go: Error Handling # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 6 min read The Secret Life of Go: Packages and Structure Aaron Rose Aaron Rose Aaron Rose Follow Dec 28 '25 The Secret Life of Go: Packages and Structure # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 5 min read Python by Structure: Precise Error Scoping with Try/Except/Else Aaron Rose Aaron Rose Aaron Rose Follow Dec 27 '25 Python by Structure: Precise Error Scoping with Try/Except/Else # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 2 min read Python by Structure: Decorators and the "Logic Envelope" Aaron Rose Aaron Rose Aaron Rose Follow Dec 27 '25 Python by Structure: Decorators and the "Logic Envelope" # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 2 min read Python by Structure: List Comprehensions and the "Single Action" Aaron Rose Aaron Rose Aaron Rose Follow Dec 24 '25 Python by Structure: List Comprehensions and the "Single Action" # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 3 min read Python by Structure: How the 'with' Statement Automates Resource Management Aaron Rose Aaron Rose Aaron Rose Follow Dec 24 '25 Python by Structure: How the 'with' Statement Automates Resource Management # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 3 min read The Secret Life of Python: The Truth About Nothing Aaron Rose Aaron Rose Aaron Rose Follow Dec 23 '25 The Secret Life of Python: The Truth About Nothing # python # coding # programming # software 6 reactions Comments 1 comment 4 min read The Secret Life of JavaScript: Asynchrony Aaron Rose Aaron Rose Aaron Rose Follow Dec 21 '25 The Secret Life of JavaScript: Asynchrony # javascript # coding # programming # software 9 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: The Power of Function Composition Aaron Rose Aaron Rose Aaron Rose Follow Dec 20 '25 The Secret Life of JavaScript: The Power of Function Composition # javascript # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 5 min read The Secret Life of Go: Atomic Operations Aaron Rose Aaron Rose Aaron Rose Follow Dec 19 '25 The Secret Life of Go: Atomic Operations # go # coding # programming # softwaredevelopment 8 reactions Comments 1 comment 6 min read The Secret Life of Python: The Infinite Copy Aaron Rose Aaron Rose Aaron Rose Follow Dec 18 '25 The Secret Life of Python: The Infinite Copy # python # coding # programming # software 15 reactions Comments 6 comments 4 min read The Secret Life of Python: The Statue in the Memory Aaron Rose Aaron Rose Aaron Rose Follow Dec 17 '25 The Secret Life of Python: The Statue in the Memory # python # coding # programming # softwaredevelopment 11 reactions Comments 2 comments 4 min read The Secret Life of Python: The Myth of the Box Aaron Rose Aaron Rose Aaron Rose Follow Dec 16 '25 The Secret Life of Python: The Myth of the Box # python # coding # programming # softwaredevelopment 11 reactions Comments 1 comment 4 min read The Secret Life of JavaScript: Currying vs. Partial Application Aaron Rose Aaron Rose Aaron Rose Follow Dec 15 '25 The Secret Life of JavaScript: Currying vs. Partial Application # javascript # coding # programming # softwaredevelopment 13 reactions Comments 2 comments 5 min read Python by Structure: List Comprehensions and Their Hidden Complexity Aaron Rose Aaron Rose Aaron Rose Follow Dec 14 '25 Python by Structure: List Comprehensions and Their Hidden Complexity # python # coding # programming # software 6 reactions Comments Add Comment 7 min read The Secret Life of JavaScript: Understanding Closures Aaron Rose Aaron Rose Aaron Rose Follow Dec 12 '25 The Secret Life of JavaScript: Understanding Closures # javascript # coding # programming # softwaredevelopment 38 reactions Comments 5 comments 10 min read The Secret Life of JavaScript: Understanding Prototypes Aaron Rose Aaron Rose Aaron Rose Follow Dec 11 '25 The Secret Life of JavaScript: Understanding Prototypes # javascript # coding # programming # softwaredevelopment 29 reactions Comments 7 comments 11 min read The Secret Life of Python: The Import System Aaron Rose Aaron Rose Aaron Rose Follow Dec 10 '25 The Secret Life of Python: The Import System # python # coding # programming # software 7 reactions Comments 3 comments 19 min read The Secret Life of Go: Mutexes and Synchronization Aaron Rose Aaron Rose Aaron Rose Follow Dec 9 '25 The Secret Life of Go: Mutexes and Synchronization # go # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 10 min read The Secret Life of JavaScript: Understanding 'this' Aaron Rose Aaron Rose Aaron Rose Follow Dec 8 '25 The Secret Life of JavaScript: Understanding 'this' # javascript # coding # programming # software 12 reactions Comments 5 comments 11 min read The Secret Life of JavaScript: Let, Const, and Why Variables Are Complicated Aaron Rose Aaron Rose Aaron Rose Follow Dec 8 '25 The Secret Life of JavaScript: Let, Const, and Why Variables Are Complicated # javascript # coding # programming # software 43 reactions Comments 15 comments 9 min read Python by Structure: Context Managers and the 'with' Statement Aaron Rose Aaron Rose Aaron Rose Follow Dec 7 '25 Python by Structure: Context Managers and the 'with' Statement # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 6 min read The Secret Life of Python: Metaclasses - Classes That Make Classes Aaron Rose Aaron Rose Aaron Rose Follow Dec 6 '25 The Secret Life of Python: Metaclasses - Classes That Make Classes # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 17 min read The Secret Life of Go: Goroutines and Channels Aaron Rose Aaron Rose Aaron Rose Follow Dec 5 '25 The Secret Life of Go: Goroutines and Channels # go # coding # programming # software 6 reactions Comments 1 comment 9 min read Python by Structure: Return Value Transformations with Decorators Aaron Rose Aaron Rose Aaron Rose Follow Dec 4 '25 Python by Structure: Return Value Transformations with Decorators # python # coding # programming # softwaredevelopment 3 reactions Comments 3 comments 4 min read The Secret Life of Python: super() and the Method Resolution Order Aaron Rose Aaron Rose Aaron Rose Follow Dec 3 '25 The Secret Life of Python: super() and the Method Resolution Order # python # coding # programming # software 21 reactions Comments 4 comments 18 min read The Secret Life of Go: Interfaces Aaron Rose Aaron Rose Aaron Rose Follow Dec 2 '25 The Secret Life of Go: Interfaces # go # coding # programming # softwaredevelopment 7 reactions Comments Add Comment 8 min read Python by Structure: Property Decorators and Managed Attributes Aaron Rose Aaron Rose Aaron Rose Follow Dec 1 '25 Python by Structure: Property Decorators and Managed Attributes # python # coding # programming # software 4 reactions Comments 1 comment 5 min read The Secret Life of Go: Structs Aaron Rose Aaron Rose Aaron Rose Follow Dec 1 '25 The Secret Life of Go: Structs # go # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 8 min read The Secret Life of Go: Maps Aaron Rose Aaron Rose Aaron Rose Follow Nov 29 '25 The Secret Life of Go: Maps # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 7 min read The Secret Life of Go: Arrays and Slices Aaron Rose Aaron Rose Aaron Rose Follow Nov 28 '25 The Secret Life of Go: Arrays and Slices # go # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 8 min read Python by Structure: How Decorators Transform Classes Aaron Rose Aaron Rose Aaron Rose Follow Nov 27 '25 Python by Structure: How Decorators Transform Classes # python # coding # programming # softwaredevelopment 3 reactions Comments 1 comment 5 min read The Secret Life of Python: Attribute Lookup Secrets Aaron Rose Aaron Rose Aaron Rose Follow Nov 27 '25 The Secret Life of Python: Attribute Lookup Secrets # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 16 min read The Secret Life of Go: Functions Aaron Rose Aaron Rose Aaron Rose Follow Nov 25 '25 The Secret Life of Go: Functions # go # coding # programming # softwaredevelopment 6 reactions Comments 1 comment 8 min read The Secret Life of Go: Variables & Types Aaron Rose Aaron Rose Aaron Rose Follow Nov 25 '25 The Secret Life of Go: Variables & Types # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 10 min read The Secret Life of Go Aaron Rose Aaron Rose Aaron Rose Follow Nov 22 '25 The Secret Life of Go # go # coding # programming # softwaredevelopment 13 reactions Comments 4 comments 10 min read Python by Structure - Class-Based Decorators That Remember Aaron Rose Aaron Rose Aaron Rose Follow Nov 21 '25 Python by Structure - Class-Based Decorators That Remember # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 3 min read The Secret Life of Python: Bytecode Secrets - What Python Really Runs Aaron Rose Aaron Rose Aaron Rose Follow Nov 20 '25 The Secret Life of Python: Bytecode Secrets - What Python Really Runs # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 26 min read Python by Structure: Decorator Chains and Execution Order Aaron Rose Aaron Rose Aaron Rose Follow Nov 20 '25 Python by Structure: Decorator Chains and Execution Order # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 5 min read The Secret Life of Python: MRO Secrets - The Diamond Problem Solved Aaron Rose Aaron Rose Aaron Rose Follow Nov 19 '25 The Secret Life of Python: MRO Secrets - The Diamond Problem Solved # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 24 min read Python by Structure: Match Statements and Pattern Guards Aaron Rose Aaron Rose Aaron Rose Follow Nov 19 '25 Python by Structure: Match Statements and Pattern Guards # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 6 min read The Secret Life of Python: GIL Secrets - Python's Threading Mystery Aaron Rose Aaron Rose Aaron Rose Follow Nov 18 '25 The Secret Life of Python: GIL Secrets - Python's Threading Mystery # python # coding # programming # softwaredevelopment 5 reactions Comments 2 comments 21 min read Python by Structure: The Walrus Operator - Assignment Where You Need It Aaron Rose Aaron Rose Aaron Rose Follow Nov 18 '25 Python by Structure: The Walrus Operator - Assignment Where You Need It # python # coding # programming # softwaredevelopment 10 reactions Comments Add Comment 4 min read Python by Structure: Context Managers and the With Statement Aaron Rose Aaron Rose Aaron Rose Follow Nov 16 '25 Python by Structure: Context Managers and the With Statement # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 4 min read Python by Structure: Generator Delegation with Yield From Aaron Rose Aaron Rose Aaron Rose Follow Nov 16 '25 Python by Structure: Generator Delegation with Yield From # python # coding # programming # softwaredevelopment Comments Add Comment 4 min read The Secret Life of Python: Metaclass Secrets - Classes That Create Classes Aaron Rose Aaron Rose Aaron Rose Follow Nov 15 '25 The Secret Life of Python: Metaclass Secrets - Classes That Create Classes # python # coding # programming # software Comments Add Comment 13 min read Python by Structure: The For/Else Block You Didn't Know Existed Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 Python by Structure: The For/Else Block You Didn't Know Existed # python # coding # programming # softwaredevelopment 5 reactions Comments 5 comments 3 min read Python by Structure: The Try/Else Block You're Not Using Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 Python by Structure: The Try/Else Block You're Not Using # python # coding # programming # software 6 reactions Comments Add Comment 3 min read The Secret Life of Python: Descriptor Secrets - How Properties Really Work Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 The Secret Life of Python: Descriptor Secrets - How Properties Really Work # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 16 min read The Secret Life of Python: Context Manager Secrets - The Magic of `with` Aaron Rose Aaron Rose Aaron Rose Follow Nov 13 '25 The Secret Life of Python: Context Manager Secrets - The Magic of `with` # python # coding # programming # software 4 reactions Comments Add Comment 14 min read The Secret Life of Python: Decorator Secrets - Functions That Wrap Functions Aaron Rose Aaron Rose Aaron Rose Follow Nov 12 '25 The Secret Life of Python: Decorator Secrets - Functions That Wrap Functions # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 14 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://coderabbit.ai/blog/how-we-built-our-ai-code-review-tool-for-ides | How we built our AI code review tool for IDEs Features Enterprise Customers Pricing Blog Resources Docs Trust Center Contact Us FAQ Log In Get a free trial Products Pull Request Reviews IDE Reviews CLI Reviews Navigation About Us Features FAQ System Status Careers DPA Startup Program Vulnerability Disclosure Resources Blog Docs Changelog Case Studies Trust Center Brand Guidelines Contact Support Sales Pricing Partnerships Subscribe By signing up you agree to our Terms of Use and Privacy Policy Select language English 日本語 Terms of Service Privacy Policy CodeRabbit Inc © 2026 Products Pull Request Reviews IDE Reviews CLI Reviews Navigation About Us Features FAQ System Status Careers DPA Startup Program Vulnerability Disclosure Resources Blog Docs Changelog Case Studies Trust Center Brand Guidelines Contact Support Sales Pricing Partnerships Subscribe By signing up you agree to our Terms of Use and Privacy Policy How we built our AI code review agent for IDEs by Amitosh Swain English Featured May 14, 2025 9 min read May 14, 2025 9 min read Transforming CodeRabbit’s typical code review pipeline Balancing quality and speed How we engineered it Review processing and delivery Context preparation Prompt and model optimization Choosing non-streaming LLM responses over streaming responses UI changes Working with users’ preferred AI coding agents What’s next on the roadmap? Near term Longer-term Back to blog Share Cut code review time & bugs by 50% Most installed AI app on GitHub and GitLab Free 14-day trial Get Started Catch the latest, right in your inbox. Subscribe Add us your feed. Catch the latest, right in your inbox. Subscribe Add us your feed. Keep reading Why users shouldn’t choose their own LLM models: Choice is not always good Giving users a dropdown of LLMs to choose from often seems like the right product choice. After all, users might have a favorite model or they might want to try the latest release the moment it drops. One problem: unless they’re an ML engineer runnin... An (actually useful) framework for evaluating AI code review tools Benchmarks have always promised objectivity. Reduce a complex system to a score, compare competitors on equal footing, and let the numbers speak for themselves. But, in practice, benchmarks rarely measure “quality” in the abstract. They measure whate... CodeRabbit's AI Code Reviews now support NVIDIA Nemotron TL;DR: Blend of frontier & open models is more cost efficient and reviews faster. NVIDIA Nemotron is supported for CodeRabbit self-hosted customers. We are delighted to share that CodeRabbit now supports the NVIDIA Nemotron family of open models amon... Get Started in 2 clicks. No credit card needed Your browser does not support the video. Install in VS Code Your browser does not support the video. | 2026-01-13T08:49:36 |
https://dev.to/irohomolola/002-12244transitioning-into-devops-2318 | Transitioning into DevOps - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Iroh Omolola Posted on Jul 12, 2024 Transitioning into DevOps # webdev # devops # beginners # techtalks DevOps is a set of practices that combines software development (Dev) and IT operations (Ops). The goal is to shorten the system development life cycle and provide continuous delivery with high software quality. This requires a cultural shift, emphasizing collaboration between development and operations teams. Top comments (4) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand Antoine Price Antoine Price Antoine Price Follow I enjoy programming for the life of me Joined Jul 19, 2022 • Jul 14 '24 Dropdown menu Copy link Hide love it Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Mansolo Dc 👨💻 Mansolo Dc 👨💻 Mansolo Dc 👨💻 Follow web developer ui/ux designer Work web developer Joined Apr 28, 2023 • Jul 15 '24 Dropdown menu Copy link Hide great Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Stefanie Melvin Stefanie Melvin Stefanie Melvin Follow Joined Jul 12, 2024 • Jul 12 '24 Dropdown menu Copy link Hide How do you get the dev Account Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Iroh Omolola Iroh Omolola Iroh Omolola Follow Iroh Nkechi Omolola is a dynamic Software Engineer specializing in React.js/Next.js. With a keen eye for detail and a passion for crafting elegant, user-friendly solutions. Email irohomolola@gmail.com Location Lagos, Nigeria Education University of Benin Pronouns She/her Work Software Engineer Joined Jul 11, 2023 • Jul 12 '24 Dropdown menu Copy link Hide Registered on dev acct Like comment: Like comment: 1 like Like Comment button Reply Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Iroh Omolola Follow Iroh Nkechi Omolola is a dynamic Software Engineer specializing in React.js/Next.js. With a keen eye for detail and a passion for crafting elegant, user-friendly solutions. Location Lagos, Nigeria Education University of Benin Pronouns She/her Work Software Engineer Joined Jul 11, 2023 Trending on DEV Community Hot Devs AI adoption starts with one KPI, not 10 use cases # webdev # ai # beginners # startup I Didn’t “Become” a Senior Developer. I Accumulated Damage. # programming # ai # career # discuss AI should not be in Code Editors # programming # ai # productivity # discuss 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://aws.amazon.com/codeguru/ | Optimize Code Performance – Amazon CodeGuru Profiler – Amazon Web Services Skip to main content Filter: All English Contact us AWS Marketplace Support My account Search Filter: All Sign in to console Create account Amazon CodeGuru Profiler Overview Features Pricing FAQs Customers More Machine Learning › AWS CodeGuru › AWS CodeGuru Profiler 90 days free of CodeGuru Profiler with the AWS Free Tier Amazon CodeGuru Profiler Optimize application performance and reduce operational costs Get started with CodeGuru Profiler Benefits Feature Find your most expensive lines of code to help reduce operational costs by up to 50%. Learn more Feature Discover anomalies in code and troubleshoot performance issues with continuous monitoring. Learn more Feature Analyze application runtime data to improve perfromance, latency, and throughput Learn more How it works Amazon CodeGuru Profiler is a developer tool that identifies an application’s most expensive lines of code and provides machine learning (ML)–based insights and recommendations for improving code quality. Explore Amazon CodeGuru CodeGuru Profiler continuously monitors your applications in production. When it identifies opportunities to optimize application performance, it shows you what's causing the issue, how to resolve it, and where in the code it’s impacting your application. CodeGuru Profiler also estimates the cost of continuing to run inefficient code. Play Use cases Learn More Improve runtime code quality Evaluate applications’ runtime data to optimize CPU and memory usage, and troubleshoot performance issues to lower latency and throughput. Learn more Learn More Visualize your application heap Consolidate views of the heap and identify what objects are using up memory so you can optimize applications in production. Learn more Learn More Improve performance with flame graphs Understand which code paths consume the most resources, verify applications are performing as expected, and uncover areas for further optimization. Learn more How to get started Explore Amazon CodeGuru Reviewer Read the CodeGuru Reviewer documentation Explore Amazon CodeGuru Profiler Explore resources Start building in the console Sign in Create an AWS account Learn What Is AWS? What Is Cloud Computing? What Is Agentic AI? Cloud Computing Concepts Hub AWS Cloud Security What's New Blogs Press Releases Resources Getting Started Training AWS Trust Center AWS Solutions Library Architecture Center Product and Technical FAQs Analyst Reports AWS Partners Developers Builder Center SDKs & Tools .NET on AWS Python on AWS Java on AWS PHP on AWS JavaScript on AWS Help Contact Us File a Support Ticket AWS re:Post Knowledge Center AWS Support Overview Get Expert Help AWS Accessibility Legal English Back to top Amazon is an Equal Opportunity Employer: Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age. x facebook linkedin instagram twitch youtube podcasts email Privacy Site terms Cookie Preferences © 2026, Amazon Web Services, Inc. or its affiliates. All rights reserved. | 2026-01-13T08:49:36 |
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https://www.anthropic.com/claude/sonnet#:~:text= | Skip to main content Skip to footer Research Economic Futures Commitments Learn News Try Claude Claude Sonnet 4.5 Hybrid reasoning model with superior intelligence for agents, and 200K context window Try Claude Get API access Announcements New Claude Sonnet 4.5 Sep 29, 2025 Sonnet 4.5 is the best model in the world for agents, coding, and computer use. It’s also our most accurate and detailed model for long-running tasks, with enhanced domain knowledge in coding, finance, and cybersecurity. Read more Claude Sonnet 4 May 22, 2025 Sonnet 4 improves on Sonnet 3.7 across a variety of areas, especially coding. It offers frontier performance that’s practical for most AI use cases, including user-facing AI assistants and high-volume tasks. Read more Claude Sonnet 3.7 and Claude Code Feb 24, 2025 Sonnet 3.7 is the first hybrid reasoning model and our most intelligent model to date. It’s state-of-the art for coding and delivers significant improvements in content generation, data analysis, and planning. Read more Availability and pricing Anyone can chat with Claude using Sonnet 4.5 on Claude.ai, available on web, iOS, and Android. For developers interested in building agents, Sonnet 4.5 is available on the Claude Developer Platform natively, and in Amazon Bedrock, Google Cloud's Vertex AI, and Microsoft Foundry. Pricing for Sonnet 4.5 starts at $3 per million input tokens and $15 per million output tokens, with up to 90% cost savings with prompt caching and 50% cost savings with batch processing . To learn more, check out our pricing page. To get started, simply use claude-sonnet-4-5 via the Claude API . Use cases Sonnet 4.5 is a powerful, versatile model—built for daily use, scaled production, and complex tasks. Sonnet 4.5 can produce near-instant responses or extended, step-by-step thinking that is made visible to the user. API users also have fine-grained control over how long the model thinks. Popular use cases include: Long-running agents Sonnet 4.5 offers superior instruction following, tool selection, error correction, and advanced reasoning for customer-facing agents and complex AI workflows. Code generation Sonnet 4.5 is a powerful choice for agentic coding, and can complete tasks across the entire software development lifecycle, from initial planning to bug fixes, maintenance to large refactors. It offers strong performance in both planning and solving for complex coding tasks, making it an ideal choice to power end-to-end software development processes. Sonnet 4.5 supports up to 64K output tokens, which is particularly valuable for rich code generation and planning. Browser and computer use Sonnet 4.5 excels in computer use capabilities, reliably handling any browser-based task from competitive analysis to procurement workflows to customer onboarding. Sonnet 3.5 was the first frontier AI model to be able to use computers in this way. Sonnet 4.5 uses computers even more accurately and reliably, and we expect the capability to improve over time. Cybersecurity Teams using Sonnet 4.5 with Claude Code can deploy agents that autonomously patch vulnerabilities before exploitation, shifting from reactive detection to proactive defense. Financial analysis Sonnet 4.5 handles everything from entry-level financial analysis to advanced predictive analysis. For example, it can continuously monitor global regulatory changes and preemptively adapt compliance systems, evolving beyond manual audit preparation to intelligent risk management. Business tasks Sonnet 4.5 excels at producing and editing office files like slides, documents, and spreadsheets. Research Sonnet 4.5 can search through external and internal data sources to synthesize comprehensive insights across complex information landscapes. Content generation and analysis Sonnet 4.5 excels at writing and can understand nuance and tone to generate more compelling content and analyze content on a deeper level. Benchmarks Sonnet 4.5 is our powerful and versatile model for everyday use, combining strong reasoning with efficient performance. It excels at powering agents for financial analysis, cybersecurity, and research—coordinating multiple agents and processing high volumes of data with the reliability these domains demand. Trust & Safety We ’ ve conducted extensive testing and evaluation of Sonnet 4.5, working with external experts to ensure it meets our standards for safety, security, and reliability. In the model card for this release, we discuss new safety results in several categories. Hear from our customers We're seeing state-of-the-art coding performance from Claude Sonnet 4.5, with significant improvements on longer horizon tasks. It reinforces why many developers using Cursor choose Claude for solving their most complex problems. Michael Truell Co-founder and CEO , Cursor Claude Sonnet 4.5 amplifies GitHub Copilot's core strengths. Our initial evals show significant improvements in multi-step reasoning and code comprehension—enabling Copilot's agentic experiences to handle complex, codebase-spanning tasks better. We expect these gains to deliver meaningful value to developers moving from idea to implementation with confidence. Mario Rodriguez Chief Product Officer , Github Claude Sonnet 4.5 reduced average vulnerability intake time for our Hai security agents by 44% while improving accuracy by 25%, helping us reduce risk for businesses with confidence. Nidhi Aggarwal Chief Product Officer , HackerOne For Devin, Claude Sonnet 4.5 increased planning performance by 18% and end-to-end eval scores by 12%—the biggest jump we've seen since the release of Claude Sonnet 3.6. It excels at testing its own code, enabling Devin to run longer, handle harder tasks, and deliver production-ready code more consistently. Scott Wu Co-founder & CEO , Cognition Claude Sonnet 4.5 is state of the art on the most complex litigation tasks. For example, analyzing full briefing cycles and conducting research to synthesize excellent first drafts of an opinion for judges, or interrogating entire litigation records to create detailed summary judgment analysis. Pablo Arredondo Vice President, CoCounsel , Thomson Reuters Claude Sonnet 4.5's edit capabilities are exceptional — we went from 9% error rate on Sonnet 4 to 0% on our internal code editing benchmark. Higher tool success at lower cost is a major leap for agentic coding. Claude Sonnet 4.5 balances creativity and control perfectly, thoroughly completing tasks without over-engineering. Michele Catasta President , Replit For complex financial analysis—risk, structured products, portfolio screening—Claude Sonnet 4.5 with thinking delivers investment-grade insights that require less human review. When depth matters more than speed, it's a meaningful step forward for institutional finance. Stian Kirkeberg Head of AI and Machine Learning , Norges Bank Investment Management Claude Sonnet 4.5 delivers measurable improvements for Next.js tasks. It is particularly good at building and linting Next.js code, showing up to a 17% improvement over its predecessor. We're excited to integrate it into v0 and AI Gateway at launch, giving developers instant access to these advances. Guillermo Rauch CEO , Vercel Sonnet 4.5 is state-of-the-art for real-world, agentic enterprise workflows. We've seen a leap in reasoning capabilities within Snowflake Intelligence—enabling customers to extract deeper, more actionable insights from their data. Baris Gultekin VP of AI , Snowflake Claude Sonnet 4.5 resets our expectations—it handles 30+ hours of autonomous coding, freeing our engineers to tackle months of complex architectural work in dramatically less time while maintaining coherence across massive codebases. Sean Ward CEO & Co-Founder , iGent Claude Sonnet 4.5 delivers clear wins over Sonnet 4: sharper instruction-following, stronger planning, smarter parallelization. Tasks require fewer iterations, which is critical for our most demanding agentic workflows. Ankit Shankar AIP Product Lead , Palantir Claude Sonnet 4.5 shows strong promise for red teaming, generating creative attack scenarios that accelerate how we study attacker tradecraft. These insights strengthen our defenses across endpoints, identity, cloud, data, SaaS, and AI workloads. Sven Krasser Sr. Vice President for Data Science and Chief Scientist , Crowdstrike Claude Sonnet 4.5 is excellent at software development tasks, learning our codebase patterns to deliver precise implementations. It handles everything from debugging to architecture with deep contextual understanding, transforming our development velocity. Eric Wendelin Tech Lead, GenAI for Developer Productivity , Netflix 01 / 13 See Claude in action Coding What should I look for when reviewing a Pull Request for a Python web app? Ask Claude Writing Create a 3-month editorial calendar template for a weekly newsletter Ask Claude Students What's an effective study schedule template for final exams? Ask Claude Frequently asked questions When should I use Claude Sonnet 4.5? We offer different models across the spectrum of speed, price, and performance. Sonnet 4.5 delivers superior intelligence with optimal efficiency for high-volume use cases. We recommend Sonnet 4.5 for most AI applications where you need a balance of advanced capabilities and practical throughput—such as customer-facing agents, production coding workflows, content generation at scale, and real-time research tasks. How much does it cost to use Claude Sonnet 4.5 Pricing depends on how you want to use Sonnet 4.5. To learn more, check out our pricing page . When should I use extended thinking? Sonnet 4.5 is both a standard model and a hybrid reasoning model in one: you can pick when you want the model to answer normally and when you want it to use extended thinking. Extended thinking mode is best when performance and accuracy matter more than latency. It significantly improves response quality for complex reasoning tasks, extended agentic work, multi-step coding projects, and deep research. Thinking summaries help you understand key aspects of the model's reasoning process. Products Claude Claude Code Claude in Chrome Claude in Excel Claude in Slack Skills Max plan Team plan Enterprise plan Download app Pricing Log in to Claude Models Opus Sonnet Haiku Solutions AI agents Code modernization Coding Customer support Education Financial services Government Healthcare Life sciences Nonprofits Claude Developer Platform Overview Developer docs Pricing Regional Compliance Amazon Bedrock Google Cloud’s Vertex AI Console login Learn Blog Claude partner network Connectors Courses Customer stories Engineering at Anthropic Events Powered by Claude Service partners Startups program Tutorials Use cases Company Anthropic Careers Economic Futures Research News Responsible Scaling Policy Security and compliance Transparency Help and security Availability Status Support center Terms and policies Privacy policy Consumer health data privacy policy Responsible disclosure policy Terms of service: Commercial Terms of service: Consumer Usage policy © 2025 Anthropic PBC Claude Sonnet 4.5 \ Anthropic | 2026-01-13T08:49:36 |
https://go.opensource.org/openlogic | Enterprise Open Source Support and Services | OpenLogic Skip to main content Secondary Navigation { if (value) { $nextTick(() => { const input = document.querySelector('#search-modal-content input[type=text]'); if (input) input.focus(); }); } })" class="fixed inset-0 bg-p4-primary bg-opacity-90 flex items-center justify-center z-50"> Sitewide Search ✖ Partners Downloads Customer Portal Company About Leadership Culture Careers Open Source Policy AI Approach Events Trust Center Press Contact Us Mega Menu Open menu ☰ Close menu ✖ Solutions ActiveMQ AngularJS Bootstrap Databases Enterprise Linux Hadoop Java Kafka Middleware Spring Tomcat All Supported Technologies Products Technical Support Long Term Support Open Source Service Bundles Hardened Linux Images Customers Services Services Consulting Services Implementations & Upgrades Migration Services Technical Account Management Training Apache Camel Apache ActiveMQ Apache Kafka DevOps and CI/CD Kubernetes Bootcamp Monitoring and Observability MySQL and PostgreSQL 1 Day MySQL and PostgreSQL 2.5 Day NGINX Resources eBooks & Papers Webinars Videos Blog All Resources Talk to an Expert Partners Downloads Customer Portal Company About Leadership Culture Careers Open Source Policy AI Approach Events Trust Center Press Contact Us 0) { leftValue = -rightOverflow; } // Calculate left overflow const leftOverflow = rect.left; if (leftOverflow Solutions Show submenu for Solutions ActiveMQ AngularJS Bootstrap Databases Enterprise Linux Hadoop Java Kafka Middleware Spring Tomcat All Supported Technologies 0) { leftValue = -rightOverflow; } // Calculate left overflow const leftOverflow = rect.left; if (leftOverflow Products Show submenu for Products Featured Product Kafka Service Bundle With the Kafka Service Bundle, you can do more with Kafka for less. Get the benefits of fully supported and managed open source Kafka for a fraction of the cost of commercial alternatives. See What's Included > Technical Support Long Term Support Open Source Service Bundles Hardened Linux Images Customers 0) { leftValue = -rightOverflow; } // Calculate left overflow const leftOverflow = rect.left; if (leftOverflow Services Show submenu for Services Services Consulting Services Implementations & Upgrades Migration Services Technical Account Management Training Apache Camel Apache ActiveMQ Apache Kafka DevOps and CI/CD Kubernetes Bootcamp Monitoring and Observability MySQL and PostgreSQL 1 Day MySQL and PostgreSQL 2.5 Day NGINX 0) { leftValue = -rightOverflow; } // Calculate left overflow const leftOverflow = rect.left; if (leftOverflow Resources Show submenu for Resources eBooks & Papers Webinars Videos Blog All Resources Taking an Open Source Approach to Big Data Management Find out how to lower costs by migrating off proprietary platforms to an open source Big Data stack. Read Now Talk to an Expert Unbeatable Expertise and Support for Your Open Source Stack Companies that depend on open source software for their mission-critical IT infrastructure rely on OpenLogic to keep their tech stacks secure, performant, and compliant. Talk to an Open Source Expert Take Your Open Source Strategy to the Next Level Scale Your Business Securely and Cost-Effectively Cost savings from open source can disappear quickly if you don’t have the personnel to keep it up to date. OpenLogic can set you up for success so you can do more with your OSS — right now and as you grow. Escape Lock-In From Proprietary Solutions Why restrict innovation with out-of-the-box commercial platforms? With OpenLogic, you can deploy anywhere and customize your infrastructure with OSS that delivers the same — or better — functionality. Get Full Stack Expertise From One Vendor If skill gaps are holding your team back, let our Enterprise Architects take that complexity off your plate. OpenLogic supports hundreds of OSS packages, so you don’t have to juggle multiple support contracts. = maxSlide ? 'bg-p4-teal opacity-30 pointer-events-none' : 'bg-p4-teal rounded-full hover:bg-p4-cyan'" class="ml-4 rounded-full transition p-2" aria-label="Next" > Image Consolidate Support for Your Stack and Save No more finger-pointing. With SLAs for hundreds of open source technologies, OpenLogic is the one vendor that can support all the OSS in your infrastructure — your single point of contact for trusted guidance and fast resolution. See What We Support Trusted by the Global 500 and Beyond Open Source Solutions Designed to Meet Enterprise Needs From end-to-end support to comprehensive service bundles, you'll benefit from our full stack expertise and unbiased guidance every step of the way. SVG 24/7 Expert Technical Support, Backed by SLAs Avoid escalations and connect directly with an Enterprise Architect when you need fast resolution. Support Details SVG Long-Term Support for CentOS, AngularJS, Kafka and More Extend your migration runway and stay compliant with security patches for EOL software while you plan next steps. LTS Solutions SVG Professional Services From Migrations to Data Management Whether you’re modernizing a legacy system, looking for Linux migration support, or need admin-as-a-service, our experts can help. Talk to an Expert 0"> ★ Best-in-Class Support Delivers Best-in-Class Results Explore customer success stories to see how we have been helping companies innovate with open source for more than two decades. Catalina Modernizes Their Hadoop Big Data Infrastructure Read Case Study Credit Card Processing Company Avoids Kafka Exploit Read Case Study SaaS Provider Improves System Stability and Scale with Open Source Support Read Case Study When Open Source Is the Strategy, OpenLogic Is the Force Multiplier. Partner with OpenLogic to unleash the power of OSS backed by enterprise-grade support. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Add reaction Like Unicorn Exploding Head Raised Hands Fire Jump to Comments Save Boost More... Copy link Copy link Copied to Clipboard Share to X Share to LinkedIn Share to Facebook Share to Mastodon Share Post via... Report Abuse Alok Kumar Posted on Nov 5, 2025 Mastering End to End testing for Reliable Modern Software # testing # webdev # programming # software In today’s world of interconnected systems, software applications are more complex than ever. These applications involve a mix of frontend , backend , databases , and often third-party integrations . While unit and integration tests focus on specific components, end‑to‑end (E2E) testing ensures that the entire application works as expected across all layers. It is the final line of defense before deployment, offering full validation of the system’s end-to-end flow. In this post, we’ll explore what end‑to‑end testing entails, why it’s essential for modern software delivery, and how to implement it effectively in your development pipeline. Why End to End Testing Is Crucial for Modern Software In today's fast-paced software development landscape, where applications are increasingly distributed and complex, ensuring that every part of the system functions as expected can be overwhelming. Microservices, REST APIs, databases, third-party integrations, and front-end elements must work together in a seamless flow to ensure a positive user experience. However, it’s all too common for bugs to emerge when services interact in production environments, even if unit and integration tests pass for individual components. This is where end-to-end testing becomes invaluable. End-to-End Testing validates the flow of data through the entire system, ensuring that from the moment a user interacts with the app, everything works smoothly in real-world conditions. It simulates how users interact with the system — from logging in and performing actions to data processing and notifications. Without it, you risk missing critical failures that could go unnoticed in isolated tests. What Does End to End Testing Cover? End-to-end tests are comprehensive. They don’t just check individual components in isolation; they ensure that entire workflows, including multiple interacting components, perform as expected. Some key areas that E2E testing typically covers include: Frontend Testing : Verifies the user interface (UI), form submission, button clicks, and data rendering. Backend Testing : Ensures that business logic, APIs, and servers are functioning correctly and communicating with the UI and database. Database Integration : Verifies that data is being read and written correctly from the database, ensuring no data integrity issues. Third-party Service Testing : Ensures that integrations with external services (e.g., payment gateways, social media logins) are working as expected. Cross-platform Testing : Tests how the application performs on different platforms and devices (e.g., mobile, desktop). E2E testing is critical for full system validation , ensuring that all pieces of the application — from front to back — work together without breaking. Key Benefits of End-to-End Testing While unit and integration tests check individual components, end-to-end tests ensure that everything works together as a cohesive whole. Here’s why this is important: Complete System Coverage : E2E tests check entire user journeys, from frontend interactions to backend processes, providing a more holistic approach to testing. Improved User Experience : Since E2E tests simulate actual user behavior, they ensure that the app meets user expectations, reducing the chances of frustrating bugs or failures after deployment. Better Detection of Complex Bugs : Some issues only appear when multiple services interact, such as timing issues, network failures, or data synchronization problems. E2E tests catch these issues before they reach production. Increased Deployment Confidence : E2E testing integrates into continuous integration/continuous deployment (CI/CD) pipelines, ensuring every code change goes through comprehensive validation before deployment. This leads to more frequent and reliable releases. The Challenges of End-to-End Testing Although E2E testing brings tremendous value, it’s not without its challenges. Some common hurdles include: Flaky Tests : Since E2E tests cover multiple services, they can be prone to flakiness due to network issues, timing problems, or external dependencies. Slow Execution : E2E tests typically take longer to run than unit or integration tests, especially when they involve UI automation or real data. Complex Test Environments : Setting up realistic test environments that mirror production is often time-consuming and requires significant resources. Test Maintenance : As applications evolve and features change, maintaining E2E tests can become difficult, especially when there are frequent UI or API changes. Despite these challenges, advancements in test automation tools are helping teams overcome them. How to Implement Effective End-to-End Testing To build a reliable and efficient end-to-end testing suite, follow these best practices: Prioritize Critical User Journeys : Focus on testing the most important workflows — for example, user login, payment processing, and checkout. Start with the paths that users interact with the most. Use Test Automation Frameworks : Leverage popular test automation frameworks like Cypress , Selenium , or Playwright for front-end testing. These tools allow you to simulate real user interactions and validate UI behavior automatically. Mock External Services : While testing in production environments is ideal, it’s often impractical. Instead, use mocking or stubbing to simulate interactions with external systems like payment gateways or third-party APIs. Run Tests in Parallel : To mitigate the long execution time of E2E tests, consider running them in parallel across different environments or test machines. This speeds up feedback cycles and makes testing more efficient. Integrate E2E Tests into CI/CD : Automate the execution of E2E tests as part of your CI/CD pipeline. Every code push or pull request should trigger an automated suite of tests, ensuring that no changes break existing workflows. Monitor Test Results : Actively monitor the results of your E2E tests and track flaky tests. Refine tests that fail intermittently and make necessary adjustments to improve reliability. Using AI to Enhance End-to-End Testing AI and machine learning are transforming how we approach E2E testing. With Keploy , for example, AI-powered traffic recording allows teams to automatically generate tests based on real user interactions. By capturing actual traffic and responses, Keploy can create reusable and maintainable test cases without manual input. Furthermore, AI tools can adapt to changes in the application, automatically updating test cases to accommodate UI updates or API modifications. These advancements allow teams to test more thoroughly and with greater confidence — making the process smarter and more efficient . For more on automated test generation , visit Keploy . Conclusion: The Future of Software Testing As software architectures become more complex, end-to-end testing will continue to be an essential part of the development process. By validating entire user journeys, E2E testing ensures that all parts of the system work together seamlessly, helping you deliver a flawless user experience. With modern testing tools like Keploy and the rise of AI-driven test automation, the future of E2E testing is not only automated but intelligent. By embracing smarter testing practices, teams can push code with confidence, accelerate release cycles, and continuously improve software quality. Top comments (1) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand EchoSparrow EchoSparrow EchoSparrow Follow Joined Oct 31, 2025 • Nov 5 '25 Dropdown menu Copy link Hide Really informative post! End-to-end testing often gets overlooked, but it’s key to catching real-world issues before release. I like how you highlighted AI-driven tools like Keploy they make managing and maintaining tests so much easier. Like comment: Like comment: 1 like Like Comment button Reply Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Alok Kumar Follow Joined Oct 14, 2025 More from Alok Kumar Integration Testing: Definition, How-To, Examples # testing # programming # cicd # keploy What is Grey Box Testing? (Techniques & Example) # testing # keploy # greybox # sdlc AI for Coding: Transforming Software Development in 2025 # aicode # programming # coding # keploy 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV Forem — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. Made with love and Ruby on Rails . Forem © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:49:36 |
https://cursor.com | Cursor Skip to content Cursor Features Enterprise Pricing Resources ↓ Changelog Blog Docs ↗ Community Learn ↗ Workshops Forum ↗ Careers Features Enterprise Pricing Resources → Sign in Download Built to make you extraordinarily productive, Cursor is the best way to code with AI. Download for macOS ⤓ Try mobile agent → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: the IDE with AI-powered coding assistance, the CLI with command-line assistance. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools train_model.py run_experiment.py config.yaml import torch import torch . nn as nn from torch . utils . data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms . Compose ([ transforms . ToTensor ()]) train = datasets . MNIST ( root = "data" , train = True , download = True , transform = transform ) test = datasets . MNIST ( root = "data" , train = False , download = True , transform = transform ) return DataLoader ( train , batch_size = batch_size , shuffle = True ), DataLoader ( test , batch_size = batch_size ) class MLP ( nn . Module ): def __init__ ( self , hidden = 128 ): super (). __init__ () self . net = nn . Sequential ( nn . Flatten (), nn . Linear ( 28 * 28 , hidden ), nn . ReLU (), nn . Linear ( hidden , 10 ), ) def forward ( self , x ): return self . net ( x ) def train_model ( epochs = 1 , lr = 1e-3 , device = None): device = device or ( "cuda" if torch . cuda . is_available () else "cpu" ) model = MLP (). to ( device ) opt = torch . optim . Adam ( model . parameters (), lr = lr ) loss_fn = nn . CrossEntropyLoss () train_loader , _ = get_dataloaders () + # Seed for reproducibility + torch . manual_seed ( 42 ) + if device == "cuda" : + torch . cuda . manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch . cuda . amp . GradScaler ( enabled =( device == "cuda" )) + scheduler = torch . optim . lr_scheduler . CosineAnnealingLR ( opt , T_max = epochs ) model . train () for epoch in range ( epochs ) : total , correct = 0 , 0 for x , y in tqdm ( train_loader , desc = f "epoch { epoch + 1 } " ) : x , y = x . to ( device ), y . to ( device ) opt . zero_grad ( set_to_none = True ) logits = model ( x ) loss = loss_fn ( logits , y ) loss . backward () opt . step () scaler . scale ( loss ). backward () scaler . unscale_ ( opt ) + torch . nn . utils . clip_grad_norm_ ( model . parameters (), max_norm = 1.0 ) scaler . step ( opt ) scaler . update () + preds = logits . argmax ( dim = 1 ) + total += y . size ( 0 ) + correct += ( preds == y ). sum (). item () + acc = correct / max ( 1 , total ) scheduler . step () + print ( f "epoch { epoch + 1 } : acc= { acc :.3f } " ) return model `, import torch import torch.nn as nn from torch.utils.data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms. Compose ([transforms. ToTensor ()]) train = datasets. MNIST (root= " data " , train= True , download= True , transform=transform) test = datasets. MNIST (root= " data " , train= False , download= True , transform=transform) return DataLoader (train, batch_size=batch_size, shuffle= True ), DataLoader (test, batch_size=batch_size) class MLP (nn.Module): def __init__ ( self , hidden = 128 ): super (). __init__ () self .net = nn. Sequential ( nn. Flatten (), nn. Linear ( 28 * 28 , hidden), nn. ReLU (), nn. Linear (hidden, 10 ), ) def forward ( self , x ): return self . net (x) def train_model ( epochs = 1 , lr = 1e-3 , device = None ): device = device or ( " cuda " if torch.cuda. is_available () else " cpu " ) model = MLP (). to (device) opt = torch.optim. Adam (model. parameters (), lr=lr) loss_fn = nn. CrossEntropyLoss () train_loader, _ = get_dataloaders () + # Seed for reproducibility + torch. manual_seed ( 42 ) + if device == " cuda " : + torch.cuda. manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch.cuda.amp. GradScaler (enabled=(device == " cuda " )) + scheduler = torch.optim.lr_scheduler. CosineAnnealingLR (opt, T_max=epochs) model. train () for epoch in range (epochs): total, correct = 0 , 0 for x, y in tqdm (train_loader, desc= f "epoch { epoch+ 1 } " ): x, y = x. to (device), y. to (device) opt. zero_grad (set_to_none= True ) logits = model (x) loss = loss_fn (logits, y) loss. backward () opt. step () scaler. scale (loss). backward () scaler. unscale_ (opt) + torch.nn.utils. clip_grad_norm_ (model. parameters (), max_norm= 1.0 ) scaler. step (opt) scaler. update () + preds = logits. argmax (dim= 1 ) + total += y. size ( 0 ) + correct += (preds == y). sum (). item () + acc = correct / max ( 1 , total) scheduler. step () + print ( f "epoch { epoch+ 1 } : acc= { acc :.3f } " ) return model ` , PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. Agent GPT-5 agent Get CLI Cursor Agent ~/Repos/ml-research-notebook PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. → GPT-5.2 / for commands · @ for files Trusted every day by millions of professional developers. Agent turns ideas into code A human-AI programmer, orders of magnitude more effective than any developer alone. Learn about Agent → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools Analyze Tab vs Agent Usage Patterns Help me understand how teams split their focus between the tab view and the agents panel across our workspaces. Agent GPT-5 Magically accurate autocomplete Our custom Tab model predicts your next action with striking speed and precision. Learn about Tab → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor Dashboard.tsx SupportChat.tsx "use client" ; import React , { useState } from "react" ; import Navigation from "./Navigation" ; import SupportChat from "./SupportChat" ; export default function Dashboard () { return ( < div className = "flex h-[600px] border rounded-lg overflow-hidden" > < div className = "w-64 border-r" > </ div > < div className = "w-80 border-l" > < SupportChat /> </ div > </ div > ); } " use client " ; import React, { useState } from " react " ; import Navigation from " ./Navigation " ; import SupportChat from " ./SupportChat " ; export default function Dashboard() { return ( < div className = " flex h-[600px] border rounded-lg overflow-hidden " > < div className = " w-64 border-r " > </ div > < div className = " w-80 border-l " > < SupportChat /> </ div > </ div > ); } Everywhere software gets built Cursor is in GitHub reviewing your PRs, a teammate in Slack, and anywhere else you work. Learn about Cursor's ecosystem → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: Slack integration for team communication, GitHub integration for code review and debugging. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Slack Get Cursor for Slack #ask-cursor 8 members dylan small thing but would be really good to have anchor links on the website for releases 4 replies dylan wanna be able to go to cursor.com/changelog#1.0 to see 1.0 changelog eric checks out @cursor can you take a stab? Cursor APP I implemented direct linking for changelog entries and updated Node.js version constraints across the project to improve compatibility and maintainability. View PR Open in Cursor Open in Web dylan Nice @eric can you take a look? GitHub Pull Request Get BugBot Review cursor bot reviewed 1m ago src/vs/workbench/composer/browser/components/ComposerUnifiedDropdown.tsx 3292 - {selectedMode().keybinding} 3293 + {composerOpenModeToggleKeybinding} cursor bot 1m ago Bug: Function Returns Object Instead of String (Logic bug) The composerOpenModeToggleKeybinding is a function that needs to be called to get its value. Using it directly causes the keybinding display condition to always be truthy. Fix in Cursor Fix in Web The new way to build software. It was night and day from one batch to another, adoption went from single digits to over 80%. It just spread like wildfire, all the best builders were using Cursor. Diana Hu General Partner , Y Combinator The most useful AI tool that I currently pay for, hands down, is Cursor. It's fast, autocompletes when and where you need it to, handles brackets properly, sensible keyboard shortcuts, bring-your-own-model... everything is well put together. shadcn Creator of shadcn/ui The best LLM applications have an autonomy slider: you control how much independence to give the AI. In Cursor, you can do Tab completion, Cmd+K for targeted edits, or you can let it rip with the full autonomy agentic version. Andrej Karpathy CEO , Eureka Labs Cursor quickly grew from hundreds to thousands of extremely enthusiastic Stripe employees. We spend more on R&D and software creation than any other undertaking, and there's significant economic outcomes when making that process more efficient and productive. Patrick Collison Co‑Founder & CEO , Stripe It's official. I hate vibe coding. I love Cursor tab coding. It's wild. ThePrimeagen @ThePrimeagen It's definitely becoming more fun to be a programmer. It's less about digging through pages and more about what you want to happen. We are at the 1% of what's possible, and it's in interactive experiences like Cursor where models like GPT-5 shine brightest. Greg Brockman President , OpenAI Stay on the frontier Access the best models Choose between every cutting-edge model from OpenAI, Anthropic, Gemini, and xAI. Explore models ↗ Auto Suggested Composer 1 GPT-5 High Fast Claude Sonnet 4.5 ✓ Claude Opus 4.5 Gemini 3 Pro Grok Code Complete codebase understanding Cursor learns how your codebase works, no matter the scale or complexity. Learn about codebase indexing ↗ Where are these menu label colors defined? Develop enduring software Trusted by over half of the Fortune 500 to accelerate development, securely and at scale. Explore enterprise → Changelog CLI Jan 8, 2026 New CLI Features and Improved CLI Performance 2.3 Dec 22, 2025 Layout Customization and Stability Improvements Dec 18, 2025 Enterprise Insights, Billing Groups, Service Accounts, and Improved Security Controls 2.2 Dec 10, 2025 Debug Mode, Plan Mode Improvements, Multi-Agent Judging, and Pinned Chats See what's new in Cursor → Cursor is an applied team focused on building the future of coding. Join us → Recent highlights Introducing Cursor 2.0 and Composer A new interface and our first coding model, both purpose-built for working with agents. Product · Oct 29, 2025 Improving Cursor Tab with online RL Our new Tab model makes 21% fewer suggestions while having 28% higher accept rate. Research · Sep 12, 2025 1.5x faster MoE training with custom MXFP8 kernels Achieving a 3.5x MoE layer speedup with a complete rebuild for Blackwell GPUs. Research · Aug 29, 2025 View more posts → Try Cursor now. Download for macOS ⤓ Try mobile agent → Product Features Enterprise Web Agents Bugbot CLI Pricing Resources Download Changelog Docs ↗ Learn ↗ Forum ↗ Status ↗ Company Careers Blog Community Workshops Students Brand Legal Terms of Service Privacy Policy Data Use Security Connect X ↗ LinkedIn ↗ YouTube ↗ © 2026 Cursor 🛡 SOC 2 Certified 🌐 English ↓ English ✓ 简体中文 日本語 繁體中文 Skip to content Cursor Features Enterprise Pricing Resources ↓ Changelog Blog Docs ↗ Community Learn ↗ Workshops Forum ↗ Careers Features Enterprise Pricing Resources → Sign in Download Built to make you extraordinarily productive, Cursor is the best way to code with AI. Download for macOS ⤓ Try mobile agent → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: the IDE with AI-powered coding assistance, the CLI with command-line assistance. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools train_model.py run_experiment.py config.yaml import torch import torch . nn as nn from torch . utils . data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms . Compose ([ transforms . ToTensor ()]) train = datasets . MNIST ( root = "data" , train = True , download = True , transform = transform ) test = datasets . MNIST ( root = "data" , train = False , download = True , transform = transform ) return DataLoader ( train , batch_size = batch_size , shuffle = True ), DataLoader ( test , batch_size = batch_size ) class MLP ( nn . Module ): def __init__ ( self , hidden = 128 ): super (). __init__ () self . net = nn . Sequential ( nn . Flatten (), nn . Linear ( 28 * 28 , hidden ), nn . ReLU (), nn . Linear ( hidden , 10 ), ) def forward ( self , x ): return self . net ( x ) def train_model ( epochs = 1 , lr = 1e-3 , device = None): device = device or ( "cuda" if torch . cuda . is_available () else "cpu" ) model = MLP (). to ( device ) opt = torch . optim . Adam ( model . parameters (), lr = lr ) loss_fn = nn . CrossEntropyLoss () train_loader , _ = get_dataloaders () + # Seed for reproducibility + torch . manual_seed ( 42 ) + if device == "cuda" : + torch . cuda . manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch . cuda . amp . GradScaler ( enabled =( device == "cuda" )) + scheduler = torch . optim . lr_scheduler . CosineAnnealingLR ( opt , T_max = epochs ) model . train () for epoch in range ( epochs ) : total , correct = 0 , 0 for x , y in tqdm ( train_loader , desc = f "epoch { epoch + 1 } " ) : x , y = x . to ( device ), y . to ( device ) opt . zero_grad ( set_to_none = True ) logits = model ( x ) loss = loss_fn ( logits , y ) loss . backward () opt . step () scaler . scale ( loss ). backward () scaler . unscale_ ( opt ) + torch . nn . utils . clip_grad_norm_ ( model . parameters (), max_norm = 1.0 ) scaler . step ( opt ) scaler . update () + preds = logits . argmax ( dim = 1 ) + total += y . size ( 0 ) + correct += ( preds == y ). sum (). item () + acc = correct / max ( 1 , total ) scheduler . step () + print ( f "epoch { epoch + 1 } : acc= { acc :.3f } " ) return model `, import torch import torch.nn as nn from torch.utils.data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms. Compose ([transforms. ToTensor ()]) train = datasets. MNIST (root= " data " , train= True , download= True , transform=transform) test = datasets. MNIST (root= " data " , train= False , download= True , transform=transform) return DataLoader (train, batch_size=batch_size, shuffle= True ), DataLoader (test, batch_size=batch_size) class MLP (nn.Module): def __init__ ( self , hidden = 128 ): super (). __init__ () self .net = nn. Sequential ( nn. Flatten (), nn. Linear ( 28 * 28 , hidden), nn. ReLU (), nn. Linear (hidden, 10 ), ) def forward ( self , x ): return self . net (x) def train_model ( epochs = 1 , lr = 1e-3 , device = None ): device = device or ( " cuda " if torch.cuda. is_available () else " cpu " ) model = MLP (). to (device) opt = torch.optim. Adam (model. parameters (), lr=lr) loss_fn = nn. CrossEntropyLoss () train_loader, _ = get_dataloaders () + # Seed for reproducibility + torch. manual_seed ( 42 ) + if device == " cuda " : + torch.cuda. manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch.cuda.amp. GradScaler (enabled=(device == " cuda " )) + scheduler = torch.optim.lr_scheduler. CosineAnnealingLR (opt, T_max=epochs) model. train () for epoch in range (epochs): total, correct = 0 , 0 for x, y in tqdm (train_loader, desc= f "epoch { epoch+ 1 } " ): x, y = x. to (device), y. to (device) opt. zero_grad (set_to_none= True ) logits = model (x) loss = loss_fn (logits, y) loss. backward () opt. step () scaler. scale (loss). backward () scaler. unscale_ (opt) + torch.nn.utils. clip_grad_norm_ (model. parameters (), max_norm= 1.0 ) scaler. step (opt) scaler. update () + preds = logits. argmax (dim= 1 ) + total += y. size ( 0 ) + correct += (preds == y). sum (). item () + acc = correct / max ( 1 , total) scheduler. step () + print ( f "epoch { epoch+ 1 } : acc= { acc :.3f } " ) return model ` , PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. Agent GPT-5 agent Get CLI Cursor Agent ~/Repos/ml-research-notebook PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. → GPT-5.2 / for commands · @ for files Trusted every day by millions of professional developers. Agent turns ideas into code A human-AI programmer, orders of magnitude more effective than any developer alone. Learn about Agent → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools Analyze Tab vs Agent Usage Patterns Help me understand how teams split their focus between the tab view and the agents panel across our workspaces. Agent GPT-5 Magically accurate autocomplete Our custom Tab model predicts your next action with striking speed and precision. Learn about Tab → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor Dashboard.tsx SupportChat.tsx "use client" ; import React , { useState } from "react" ; import Navigation from "./Navigation" ; import SupportChat from "./SupportChat" ; export default function Dashboard () { return ( < div className = "flex h-[600px] border rounded-lg overflow-hidden" > < div className = "w-64 border-r" > </ div > < div className = "w-80 border-l" > < SupportChat /> </ div > </ div > ); } " use client " ; import React, { useState } from " react " ; import Navigation from " ./Navigation " ; import SupportChat from " ./SupportChat " ; export default function Dashboard() { return ( < div className = " flex h-[600px] border rounded-lg overflow-hidden " > < div className = " w-64 border-r " > </ div > < div className = " w-80 border-l " > < SupportChat /> </ div > </ div > ); } Everywhere software gets built Cursor is in GitHub reviewing your PRs, a teammate in Slack, and anywhere else you work. Learn about Cursor's ecosystem → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: Slack integration for team communication, GitHub integration for code review and debugging. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Slack Get Cursor for Slack #ask-cursor 8 members dylan small thing but would be really good to have anchor links on the website for releases 4 replies dylan wanna be able to go to cursor.com/changelog#1.0 to see 1.0 changelog eric checks out @cursor can you take a stab? Cursor APP I implemented direct linking for changelog entries and updated Node.js version constraints across the project to improve compatibility and maintainability. View PR Open in Cursor Open in Web dylan Nice @eric can you take a look? GitHub Pull Request Get BugBot Review cursor bot reviewed 1m ago src/vs/workbench/composer/browser/components/ComposerUnifiedDropdown.tsx 3292 - {selectedMode().keybinding} 3293 + {composerOpenModeToggleKeybinding} cursor bot 1m ago Bug: Function Returns Object Instead of String (Logic bug) The composerOpenModeToggleKeybinding is a function that needs to be called to get its value. Using it directly causes the keybinding display condition to always be truthy. Fix in Cursor Fix in Web The new way to build software. It was night and day from one batch to another, adoption went from single digits to over 80%. It just spread like wildfire, all the best builders were using Cursor. Diana Hu General Partner , Y Combinator The most useful AI tool that I currently pay for, hands down, is Cursor. It's fast, autocompletes when and where you need it to, handles brackets properly, sensible keyboard shortcuts, bring-your-own-model... everything is well put together. shadcn Creator of shadcn/ui The best LLM applications have an autonomy slider: you control how much independence to give the AI. In Cursor, you can do Tab completion, Cmd+K for targeted edits, or you can let it rip with the full autonomy agentic version. Andrej Karpathy CEO , Eureka Labs Cursor quickly grew from hundreds to thousands of extremely enthusiastic Stripe employees. We spend more on R&D and software creation than any other undertaking, and there's significant economic outcomes when making that process more efficient and productive. Patrick Collison Co‑Founder & CEO , Stripe It's official. I hate vibe coding. I love Cursor tab coding. It's wild. ThePrimeagen @ThePrimeagen It's definitely becoming more fun to be a programmer. It's less about digging through pages and more about what you want to happen. We are at the 1% of what's possible, and it's in interactive experiences like Cursor where models like GPT-5 shine brightest. Greg Brockman President , OpenAI Stay on the frontier Access the best models Choose between every cutting-edge model from OpenAI, Anthropic, Gemini, and xAI. Explore models ↗ Auto Suggested Composer 1 GPT-5 High Fast Claude Sonnet 4.5 ✓ Claude Opus 4.5 Gemini 3 Pro Grok Code Complete codebase understanding Cursor learns how your codebase works, no matter the scale or complexity. Learn about codebase indexing ↗ Where are these menu label colors defined? Develop enduring software Trusted by over half of the Fortune 500 to accelerate development, securely and at scale. Explore enterprise → Changelog CLI Jan 8, 2026 New CLI Features and Improved CLI Performance 2.3 Dec 22, 2025 Layout Customization and Stability Improvements Dec 18, 2025 Enterprise Insights, Billing Groups, Service Accounts, and Improved Security Controls 2.2 Dec 10, 2025 Debug Mode, Plan Mode Improvements, Multi-Agent Judging, and Pinned Chats See what's new in Cursor → Cursor is an applied team focused on building the future of coding. Join us → Recent highlights Introducing Cursor 2.0 and Composer A new interface and our first coding model, both purpose-built for working with agents. Product · Oct 29, 2025 Improving Cursor Tab with online RL Our new Tab model makes 21% fewer suggestions while having 28% higher accept rate. Research · Sep 12, 2025 1.5x faster MoE training with custom MXFP8 kernels Achieving a 3.5x MoE layer speedup with a complete rebuild for Blackwell GPUs. Research · Aug 29, 2025 View more posts → Try Cursor now. Download for macOS ⤓ Try mobile agent → Product Features Enterprise Web Agents Bugbot CLI Pricing Resources Download Changelog Docs ↗ Learn ↗ Forum ↗ Status ↗ Company Careers Blog Community Workshops Students Brand Legal Terms of Service Privacy Policy Data Use Security Connect X ↗ LinkedIn ↗ YouTube ↗ © 2026 Cursor 🛡 SOC 2 Certified 🌐 English ↓ English ✓ 简体中文 日本語 繁體中文 | 2026-01-13T08:49:36 |
https://devcenter.heroku.com/articles/heroku-inference-working-with-mcp | Working With MCP on Heroku | Heroku Dev Center Skip Navigation Show nav Dev Center Get Started Documentation Changelog Search Dev Center Get Started Node.js Ruby on Rails Ruby Python Java PHP Go Scala Clojure .NET Documentation Changelog More Additional Resources Home Elements Products Pricing Careers Help Status Events Podcasts Compliance Center Heroku Blog Heroku Blog Find out what's new with Heroku on our blog. 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Heroku offers native support for MCP servers through the Managed Inference and Agents add-on , which automatically handles tool registration, execution, and orchestration. With the add-on, you can use the Managed Inference and Agents API to view registered MCP tools and run registered MCP tools automatically . The add-on also enables you to build an MCP toolkit. An MCP toolkit is a collection of Heroku-hosted MCP servers that are accessible to your model through a unified URL. Toolkits provide a secure, centralized way to manage and run AI tools. To use the Managed Inference and Agents API and create an MCP toolkit, deploy and then register your custom MCP servers with an add-on chat model on Heroku. Deploy and Register Custom MCP Servers Only deploy MCP Servers that you trust. Registering third-party MCP Servers can result in vulnerability to malicious actors. Deploy a Custom MCP Server to Heroku To deploy an MCP server to Heroku, create a Procfile that defines your MCP process and add any required files for your language of choice (e.g., requirements.txt for Python, Gemfile for Ruby). For examples, see our open source MCP templates . When you deploy a standard MCP server to Heroku, you can use frameworks like LangChain with our /v1/chat/completions endpoint to make tool calls directly to your server. However, this approach requires you to: Build and maintain a control loop to handle tool calls from the model, execute them, and return structured responses Manage several different MCP servers and tool sets Have multi-tenant long-running SSE or streamable HTTP MCP servers, which can be less secure and costly Instead, you can use Heroku’s Managed Inference and Agents add-on . The add-on automatically handles tool registration, execution, and orchestration. It also grants you access to the Managed Inference and Agents API and enables you to build an MCP toolkit. To use Managed Inference and Agents add-on features, register your deployed custom MCP servers with Heroku. Register a Custom MCP Server with Heroku You must register deployed MCP servers with Heroku to access servers and enable automatic custom tool execution through the Managed Inference and Agents API . Registration also builds out your MCP toolkit, which gives your model access to all of your Heroku-hosted MCP servers registered with that model resource through a single URL. There are two steps to register your deployed MCP app with Heroku: Add a line to your MCP app’s Procfile . Attach your MCP app to the add-on model you want to access your server. Heroku provides open-source MCP example repos you can modify and deploy to Heroku: Purpose Repository Ruby Code Execution mcp-code-exec-ruby Python Code Execution mcp-code-exec-python Go Code Execution mcp-code-exec-go Node Code Execution mcp-code-exec-node Document Parsing (HTML & PDF –> Markdown) mcp-doc-reader These examples are standard MCP apps. They include required files (e.g. Procfile) and have an additional line in the Procfile to declare the MCP server. To deploy an example repo as is, click the Deploy to Heroku button in the README . These tools are also available natively as heroku_tools and don’t require MCP deployment. Deployment offers additional benefits, including no upper limit on ttl_seconds for dyno runtime . You can fork the example repos to help you develop and deploy your own custom tools. Currently, MCP servers running in Private Spaces cannot be registered or used by /v1/agents/heroku . Add an MCP Line to a Procfile To register, add a line to your MCP app’s Procfile that declares the MCP server. Procfile STDIO server names must: Start with "mcp" Be unique across all apps registered with your model resource For example, Procfiles that declare MCP servers, see Heroku’s open-source MCP repos (e.g. Python Procfile ). Attach an MCP Server to an Add-on Attaching an MCP Server gives it full access to the Heroku Managed Inference and Agents add-on. Only attach MCP Servers that you trust, because a malicious MCP Server could access all tools and data available to the add-on. Attach your deployed MCP app to a Heroku Managed Inference and Agents chat model to grant the model access to your MCP server’s tools. To attach a new model resource to an MCP app , run: heroku ai:models:create MODEL_NAME -a $APP_NAME --as INFERENCE To attach an existing model resource to an MCP app , run: heroku addons:attach MODEL_RESOURCE -a $APP_NAME --as INFERENCE If you have an app you’re already running inference requests from, you can attach the MCP server to your app’s inference add-on to grant it access to MCP tools. After attaching, your MCP server is automatically registered, tools synced, and requests made to /v1/agents/heroku with your model can execute your tools automatically in secure, isolated, one-off dynos. List Registered MCP Servers To access the Managed Inference and Agents API, retrieve your model resource’s INFERENCE_KEY and INFERENCE_URL : export INFERENCE_KEY=$(heroku config:get INFERENCE_KEY -a $APP_NAME) export INFERENCE_URL=$(heroku config:get INFERENCE_URL -a $APP_NAME) List all MCP servers registered to your model with the /v1/mcp/servers endpoint: curl "$INFERENCE_URL/v1/mcp/servers" \ -H "Authorization: Bearer $INFERENCE_KEY" \ -H "Content-Type: application/json" | jq . The endpoint returns metadata about each server, including its process type, namespace, and all registered tools with their schemas and annotations. To learn more about the response format, see the /v1/mcp/servers API reference . Execute Tools Automatically with /v1/agents/heroku After you register an MCP server , you can include its tools in the tools parameter when you call the /v1/agents/heroku endpoint. For each tool you want your model to have access to, include a Tool Object with "type": "mcp" and the tool’s name. The tool only executes if the model chooses to call it during generation. Example /v1/agents/heroku Request with mcp Tool curl "$INFERENCE_URL/v1/agents/heroku" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $INFERENCE_KEY" \ -H "X-Forwarded-Proto: https" \ -d @- <<EOF { "model": "claude-4-sonnet", "messages": [ { "role": "user", "content": "Use the code exec tool to take the sha256 of the following string: 'Heroku Rocks'." } ], "tools": [ { "type": "mcp", "name": "code_exec_python" } ] } EOF You don’t need to include tool parameters, schemas, or descriptions in a /v1/agents/heroku request, because after registration metadata is included automatically. To learn more, see the /v1/agents/heroku docs. Example /v1/agents/heroku mcp Tool Call Response event:message data:{"id":"chatcmpl-184410e4ae2b7bb5180ae","object":"chat.completion","created":1748541138,"model":"claude-4-sonnet","system_fingerprint":"heroku-inf-1sefyj8","choices":[{"index":0,"message":{"role":"assistant","content":"I'll use the Python code execution tool to calculate the SHA256 hash of the string 'Heroku Rocks'.","refusal":null,"tool_calls":[{"id":"tooluse_GDSgVgflTByFOnL_ZbCrhQ","type":"function","function":{"name":"mcp-python/code_exec_python","arguments":"{\"code\":\"import hashlib\\n\\n# String to hash\\ntext = 'Heroku Rocks'\\n\\n# Calculate SHA256 hash\\nsha256_hash = hashlib.sha256(text.encode('utf-8')).hexdigest()\\n\\nprint(f\\\"String: {text}\\\")\\nprint(f\\\"SHA256: {sha256_hash}\\\")\"}"}}]},"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":629,"completion_tokens":163,"total_tokens":792}} event:message data:{"id":"chatcmpl-184410e4ae2b7bb5180ae","object":"tool.completion","created":1748541141,"system_fingerprint":"heroku-inf-1sefyj8","choices":[{"index":0,"message":{"role":"tool","content":"Tool 'mcp-python/code_exec_python' returned result: {\"content\":[{\"type\":\"text\",\"text\":\"{\\n \\\"returncode\\\": 0,\\n \\\"stdout\\\": \\\"String: Heroku Rocks\\\\nSHA256: 7ebc92bcf8f51f0b623a18f0a357639410a409340043c7a670bb180acd138e6b\\\",\\n \\\"stderr\\\": \\\"\\\"\\n}\"}],\"isError\":false}","refusal":null,"tool_call_id":"tooluse_GDSgVgflTByFOnL_ZbCrhQ","name":"mcp-python/code_exec_python"},"finish_reason":""}],"usage":{}} event:message data:{"id":"chatcmpl-184410e4ae2b7bb5180ae","object":"chat.completion","created":1748541146,"model":"claude-4-sonnet","system_fingerprint":"heroku-inf-1sefyj8","choices":[{"index":0,"message":{"role":"assistant","content":"The SHA256 hash of the string 'Heroku Rocks' is:\n\n**7ebc92bcf8f51f0b623a18f0a357639410a409340043c7a670bb180acd138e6b**","refusal":null},"finish_reason":"stop"}],"usage":{"prompt_tokens":947,"completion_tokens":62,"total_tokens":1009}} event:done data:[DONE] Manage MCP Servers You can view and manage your registered MCP tools with the CLI or in the Heroku dashboard . Run this CLI command : heroku addons:open INFERENCE -a $APP_NAME Alternatively, in your dashboard : Click your app to open it. Select the Resources tab. Select the Managed Inference and Agents add-on under Add-on Services . Use Registered Tools With External Clients External AI applications like Cursor provide the ability to integrate with MCP servers via configuration files. To integrate an external AI application with your deployed and registered Heroku mcp tools: Run this CLI command to open your add-on in the Heroku dashboard : heroku addons:open INFERENCE -a $APP_NAME Copy the Toolkit URL ( $INFERENCE_URL/mcp/sse ) and Toolkit Token ( $INFERENCE_KEY ). Add the Toolkit URL and Toolkit Token to your client’s configuration file. For example, in Cursor , your .cursor/mcp.json might look like this: { "mcpServers": { "myCustomTools": { "command": "npx", "args": [ "mcp-remote", "<YOUR-TOOLKIT-URL>", "--header", "Authorization:${AUTH_HEADER}" ], "env": { "AUTH_HEADER": "Bearer <YOUR-TOOLKIT-TOKEN>" } } } } Test Registered Tools with MCP Inspector You can test deployed MCP servers with MCP Inspector : Run this command: npx @modelcontextprotocol/inspector Open the locally hosted UI (typically http://127.0.0.1:6274 ). Select SSE under Transport Type in the left pane. Under URL , add $INFERENCE_URL/mcp/sse (e.g. https://us.inference.heroku.com/mcp/sse ). Select Authentication and add your model add-on’s $INFERENCE_KEY as the Bearer Token . Click Connect . You can now list your tools and make example requests in MCP Inspector. The MCP Inspector interface uses SSE, but underlying tool call executions are run in secure, isolated, one-off dynos (STDIO mode). 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Aaron Rose Software engineer and technology writer at tech-reader.blog Location Dallas, TX Joined Joined on Aug 24, 2024 Personal website https://www.tech-reader.blog 8 Week Community Wellness Streak Consistency pays off! Be an active part of our community by posting at least 2 comments per week for 8 straight weeks. Earn the 16 Week Badge next. 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Continue sharing your work to earn the 4 Week Writing Streak Badge. Got it Close More info about @aaron_rose_0787cc8b4775a0 Skills/Languages Python, Node.js, SQL, AWS, GCP, Azure, Oracle Cloud, LocalStack, Docker, Kubernetes, Linux, DevOps pipelines, IaC (Terraform, CloudFormation), CI/CD, serverless, Raspberry Pi, database administration Currently learning Advanced multi-cloud architecture patterns across AWS, GCP, Azure, and Oracle Cloud. Exploring infrastructure automation with Python and diving deep into LocalStack for local cloud development. Currently hacking on Multi-cloud infrastructure automation with Python, building DevOps pipelines that span multiple cloud providers, and maintaining a homelab that's equal parts Ubuntu servers and Raspberry Pi clusters. Available for * Cloud infrastructure discussions * Cloud tooling * Serverless patterns * Database design * Creative edge computing solutions * Everything Ubuntu * Everything Raspberry Pi Post 176 posts published Comment 79 comments written Tag 12 tags followed The Secret Life of JavaScript: Identity Aaron Rose Aaron Rose Aaron Rose Follow Jan 13 The Secret Life of JavaScript: Identity # javascript # coding # programming # software 1 reaction Comments Add Comment 3 min read Want to connect with Aaron Rose? Create an account to connect with Aaron Rose. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in The Secret Life of Go: Interfaces Aaron Rose Aaron Rose Aaron Rose Follow Jan 12 The Secret Life of Go: Interfaces # go # coding # programming # software 9 reactions Comments Add Comment 5 min read The Secret Life of Go: Testing Aaron Rose Aaron Rose Aaron Rose Follow Jan 10 The Secret Life of Go: Testing # go # coding # programming # softwaredevelopment 14 reactions Comments 3 comments 6 min read The Secret Life of Python: The Matryoshka Trap Aaron Rose Aaron Rose Aaron Rose Follow Jan 9 The Secret Life of Python: The Matryoshka Trap # python # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 4 min read The Secret Life of Python: The Dangerous Reflection Aaron Rose Aaron Rose Aaron Rose Follow Jan 8 The Secret Life of Python: The Dangerous Reflection # python # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: Illusions Aaron Rose Aaron Rose Aaron Rose Follow Jan 6 The Secret Life of JavaScript: Illusions # javascript # coding # programming # softwaredevelopment 9 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: Memories Aaron Rose Aaron Rose Aaron Rose Follow Jan 5 The Secret Life of JavaScript: Memories # javascript # coding # programming # softwaredevelopment 20 reactions Comments 3 comments 3 min read Happy New Year! 🎉 Aaron Rose Aaron Rose Aaron Rose Follow Jan 1 Happy New Year! 🎉 # python # 2026 # coding # strongcoffee 44 reactions Comments 20 comments 1 min read The Secret Life of JavaScript: Inheritance Aaron Rose Aaron Rose Aaron Rose Follow Dec 30 '25 The Secret Life of JavaScript: Inheritance # javascript # coding # programming # softwaredevelopment 15 reactions Comments 3 comments 3 min read The Secret Life of Go: Error Handling Aaron Rose Aaron Rose Aaron Rose Follow Dec 29 '25 The Secret Life of Go: Error Handling # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 6 min read The Secret Life of Go: Packages and Structure Aaron Rose Aaron Rose Aaron Rose Follow Dec 28 '25 The Secret Life of Go: Packages and Structure # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 5 min read Python by Structure: Precise Error Scoping with Try/Except/Else Aaron Rose Aaron Rose Aaron Rose Follow Dec 27 '25 Python by Structure: Precise Error Scoping with Try/Except/Else # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 2 min read Python by Structure: Decorators and the "Logic Envelope" Aaron Rose Aaron Rose Aaron Rose Follow Dec 27 '25 Python by Structure: Decorators and the "Logic Envelope" # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 2 min read Python by Structure: List Comprehensions and the "Single Action" Aaron Rose Aaron Rose Aaron Rose Follow Dec 24 '25 Python by Structure: List Comprehensions and the "Single Action" # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 3 min read Python by Structure: How the 'with' Statement Automates Resource Management Aaron Rose Aaron Rose Aaron Rose Follow Dec 24 '25 Python by Structure: How the 'with' Statement Automates Resource Management # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 3 min read The Secret Life of Python: The Truth About Nothing Aaron Rose Aaron Rose Aaron Rose Follow Dec 23 '25 The Secret Life of Python: The Truth About Nothing # python # coding # programming # software 6 reactions Comments 1 comment 4 min read The Secret Life of JavaScript: Asynchrony Aaron Rose Aaron Rose Aaron Rose Follow Dec 21 '25 The Secret Life of JavaScript: Asynchrony # javascript # coding # programming # software 9 reactions Comments Add Comment 3 min read The Secret Life of JavaScript: The Power of Function Composition Aaron Rose Aaron Rose Aaron Rose Follow Dec 20 '25 The Secret Life of JavaScript: The Power of Function Composition # javascript # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 5 min read The Secret Life of Go: Atomic Operations Aaron Rose Aaron Rose Aaron Rose Follow Dec 19 '25 The Secret Life of Go: Atomic Operations # go # coding # programming # softwaredevelopment 8 reactions Comments 1 comment 6 min read The Secret Life of Python: The Infinite Copy Aaron Rose Aaron Rose Aaron Rose Follow Dec 18 '25 The Secret Life of Python: The Infinite Copy # python # coding # programming # software 15 reactions Comments 6 comments 4 min read The Secret Life of Python: The Statue in the Memory Aaron Rose Aaron Rose Aaron Rose Follow Dec 17 '25 The Secret Life of Python: The Statue in the Memory # python # coding # programming # softwaredevelopment 11 reactions Comments 2 comments 4 min read The Secret Life of Python: The Myth of the Box Aaron Rose Aaron Rose Aaron Rose Follow Dec 16 '25 The Secret Life of Python: The Myth of the Box # python # coding # programming # softwaredevelopment 11 reactions Comments 1 comment 4 min read The Secret Life of JavaScript: Currying vs. Partial Application Aaron Rose Aaron Rose Aaron Rose Follow Dec 15 '25 The Secret Life of JavaScript: Currying vs. Partial Application # javascript # coding # programming # softwaredevelopment 13 reactions Comments 2 comments 5 min read Python by Structure: List Comprehensions and Their Hidden Complexity Aaron Rose Aaron Rose Aaron Rose Follow Dec 14 '25 Python by Structure: List Comprehensions and Their Hidden Complexity # python # coding # programming # software 6 reactions Comments Add Comment 7 min read The Secret Life of JavaScript: Understanding Closures Aaron Rose Aaron Rose Aaron Rose Follow Dec 12 '25 The Secret Life of JavaScript: Understanding Closures # javascript # coding # programming # softwaredevelopment 38 reactions Comments 5 comments 10 min read The Secret Life of JavaScript: Understanding Prototypes Aaron Rose Aaron Rose Aaron Rose Follow Dec 11 '25 The Secret Life of JavaScript: Understanding Prototypes # javascript # coding # programming # softwaredevelopment 29 reactions Comments 7 comments 11 min read The Secret Life of Python: The Import System Aaron Rose Aaron Rose Aaron Rose Follow Dec 10 '25 The Secret Life of Python: The Import System # python # coding # programming # software 7 reactions Comments 3 comments 19 min read The Secret Life of Go: Mutexes and Synchronization Aaron Rose Aaron Rose Aaron Rose Follow Dec 9 '25 The Secret Life of Go: Mutexes and Synchronization # go # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 10 min read The Secret Life of JavaScript: Understanding 'this' Aaron Rose Aaron Rose Aaron Rose Follow Dec 8 '25 The Secret Life of JavaScript: Understanding 'this' # javascript # coding # programming # software 12 reactions Comments 5 comments 11 min read The Secret Life of JavaScript: Let, Const, and Why Variables Are Complicated Aaron Rose Aaron Rose Aaron Rose Follow Dec 8 '25 The Secret Life of JavaScript: Let, Const, and Why Variables Are Complicated # javascript # coding # programming # software 43 reactions Comments 15 comments 9 min read Python by Structure: Context Managers and the 'with' Statement Aaron Rose Aaron Rose Aaron Rose Follow Dec 7 '25 Python by Structure: Context Managers and the 'with' Statement # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 6 min read The Secret Life of Python: Metaclasses - Classes That Make Classes Aaron Rose Aaron Rose Aaron Rose Follow Dec 6 '25 The Secret Life of Python: Metaclasses - Classes That Make Classes # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 17 min read The Secret Life of Go: Goroutines and Channels Aaron Rose Aaron Rose Aaron Rose Follow Dec 5 '25 The Secret Life of Go: Goroutines and Channels # go # coding # programming # software 6 reactions Comments 1 comment 9 min read Python by Structure: Return Value Transformations with Decorators Aaron Rose Aaron Rose Aaron Rose Follow Dec 4 '25 Python by Structure: Return Value Transformations with Decorators # python # coding # programming # softwaredevelopment 3 reactions Comments 3 comments 4 min read The Secret Life of Python: super() and the Method Resolution Order Aaron Rose Aaron Rose Aaron Rose Follow Dec 3 '25 The Secret Life of Python: super() and the Method Resolution Order # python # coding # programming # software 21 reactions Comments 4 comments 18 min read The Secret Life of Go: Interfaces Aaron Rose Aaron Rose Aaron Rose Follow Dec 2 '25 The Secret Life of Go: Interfaces # go # coding # programming # softwaredevelopment 7 reactions Comments Add Comment 8 min read Python by Structure: Property Decorators and Managed Attributes Aaron Rose Aaron Rose Aaron Rose Follow Dec 1 '25 Python by Structure: Property Decorators and Managed Attributes # python # coding # programming # software 4 reactions Comments 1 comment 5 min read The Secret Life of Go: Structs Aaron Rose Aaron Rose Aaron Rose Follow Dec 1 '25 The Secret Life of Go: Structs # go # coding # programming # softwaredevelopment 8 reactions Comments Add Comment 8 min read The Secret Life of Go: Maps Aaron Rose Aaron Rose Aaron Rose Follow Nov 29 '25 The Secret Life of Go: Maps # go # coding # programming # softwaredevelopment 6 reactions Comments Add Comment 7 min read The Secret Life of Go: Arrays and Slices Aaron Rose Aaron Rose Aaron Rose Follow Nov 28 '25 The Secret Life of Go: Arrays and Slices # go # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 8 min read Python by Structure: How Decorators Transform Classes Aaron Rose Aaron Rose Aaron Rose Follow Nov 27 '25 Python by Structure: How Decorators Transform Classes # python # coding # programming # softwaredevelopment 3 reactions Comments 1 comment 5 min read The Secret Life of Python: Attribute Lookup Secrets Aaron Rose Aaron Rose Aaron Rose Follow Nov 27 '25 The Secret Life of Python: Attribute Lookup Secrets # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 16 min read The Secret Life of Go: Functions Aaron Rose Aaron Rose Aaron Rose Follow Nov 25 '25 The Secret Life of Go: Functions # go # coding # programming # softwaredevelopment 6 reactions Comments 1 comment 8 min read The Secret Life of Go: Variables & Types Aaron Rose Aaron Rose Aaron Rose Follow Nov 25 '25 The Secret Life of Go: Variables & Types # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 10 min read The Secret Life of Go Aaron Rose Aaron Rose Aaron Rose Follow Nov 22 '25 The Secret Life of Go # go # coding # programming # softwaredevelopment 13 reactions Comments 4 comments 10 min read Python by Structure - Class-Based Decorators That Remember Aaron Rose Aaron Rose Aaron Rose Follow Nov 21 '25 Python by Structure - Class-Based Decorators That Remember # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 3 min read The Secret Life of Python: Bytecode Secrets - What Python Really Runs Aaron Rose Aaron Rose Aaron Rose Follow Nov 20 '25 The Secret Life of Python: Bytecode Secrets - What Python Really Runs # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 26 min read Python by Structure: Decorator Chains and Execution Order Aaron Rose Aaron Rose Aaron Rose Follow Nov 20 '25 Python by Structure: Decorator Chains and Execution Order # python # coding # programming # softwaredevelopment 5 reactions Comments Add Comment 5 min read The Secret Life of Python: MRO Secrets - The Diamond Problem Solved Aaron Rose Aaron Rose Aaron Rose Follow Nov 19 '25 The Secret Life of Python: MRO Secrets - The Diamond Problem Solved # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 24 min read Python by Structure: Match Statements and Pattern Guards Aaron Rose Aaron Rose Aaron Rose Follow Nov 19 '25 Python by Structure: Match Statements and Pattern Guards # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 6 min read The Secret Life of Python: GIL Secrets - Python's Threading Mystery Aaron Rose Aaron Rose Aaron Rose Follow Nov 18 '25 The Secret Life of Python: GIL Secrets - Python's Threading Mystery # python # coding # programming # softwaredevelopment 5 reactions Comments 2 comments 21 min read Python by Structure: The Walrus Operator - Assignment Where You Need It Aaron Rose Aaron Rose Aaron Rose Follow Nov 18 '25 Python by Structure: The Walrus Operator - Assignment Where You Need It # python # coding # programming # softwaredevelopment 10 reactions Comments Add Comment 4 min read Python by Structure: Context Managers and the With Statement Aaron Rose Aaron Rose Aaron Rose Follow Nov 16 '25 Python by Structure: Context Managers and the With Statement # python # coding # programming # softwaredevelopment 4 reactions Comments Add Comment 4 min read Python by Structure: Generator Delegation with Yield From Aaron Rose Aaron Rose Aaron Rose Follow Nov 16 '25 Python by Structure: Generator Delegation with Yield From # python # coding # programming # softwaredevelopment Comments Add Comment 4 min read The Secret Life of Python: Metaclass Secrets - Classes That Create Classes Aaron Rose Aaron Rose Aaron Rose Follow Nov 15 '25 The Secret Life of Python: Metaclass Secrets - Classes That Create Classes # python # coding # programming # software Comments Add Comment 13 min read Python by Structure: The For/Else Block You Didn't Know Existed Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 Python by Structure: The For/Else Block You Didn't Know Existed # python # coding # programming # softwaredevelopment 5 reactions Comments 5 comments 3 min read Python by Structure: The Try/Else Block You're Not Using Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 Python by Structure: The Try/Else Block You're Not Using # python # coding # programming # software 6 reactions Comments Add Comment 3 min read The Secret Life of Python: Descriptor Secrets - How Properties Really Work Aaron Rose Aaron Rose Aaron Rose Follow Nov 14 '25 The Secret Life of Python: Descriptor Secrets - How Properties Really Work # python # coding # programming # softwaredevelopment 2 reactions Comments Add Comment 16 min read The Secret Life of Python: Context Manager Secrets - The Magic of `with` Aaron Rose Aaron Rose Aaron Rose Follow Nov 13 '25 The Secret Life of Python: Context Manager Secrets - The Magic of `with` # python # coding # programming # software 4 reactions Comments Add Comment 14 min read The Secret Life of Python: Decorator Secrets - Functions That Wrap Functions Aaron Rose Aaron Rose Aaron Rose Follow Nov 12 '25 The Secret Life of Python: Decorator Secrets - Functions That Wrap Functions # python # coding # programming # softwaredevelopment 3 reactions Comments Add Comment 14 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.fsf.org/working-together/next-steps | What are the next steps? — Free Software Foundation — Working together for free software ​ Push freedom ahead! The free software community has always thwarted the toughest challenges facing freedom in technology. This winter season, we want to thank the many individuals and projects that have helped us get where we are today: a world where a growing number of users are able to do their computing in full freedom. Our work isn't over. We have so much more to do. Help us reach our stretch New Year's membership goal of 100 new associate members by January 16, 2026, and keep the FSF strong and independent. Join | Read more Join Renew Donate Skip to content , sitemap or skip to search . Personal tools Log in Help! Members forum About Campaigns Licensing Membership Resources Community ♥Donate♥ Shop Search You are here: Home › Working together for free software › Next steps Info What are the next steps? by Matt Lee Contributions — Published on Jun 24, 2010 01:04 PM Here we have some next steps and forward-looking ideas for future free software advocates. Free software for Windows — a comprehensive guide to free software on Windows Free software for Mac OS X — a comprehensive guide to free software on macOS and Mac OS X Free software for Android — a comprehensive guide to free software on the Android platform Building a free software smartphone For more on how to take small steps toward freedom, check out the FSF's Freedom Ladder campaign. Document Actions Share on social networks Syndicate: News Events Blogs Jobs GNU 1PC9aZC4hNX2rmmrt7uHTfYAS3hRbph4UN Sign up Enter your email address to receive our monthly newsletter, the Free Software Supporter News Eko K. A. Owen joins the FSF board as the union staff pick Dec 29, 2025 Free Software Foundation receives historic private donations Dec 24, 2025 Free Software Awards winners announced: Andy Wingo, Alx Sa, Govdirectory Dec 09, 2025 More news… Recent blogs Turning freedom values into freedom practice with the FSF tech team December GNU Spotlight with Amin Bandali featuring sixteen new GNU releases: GnuPG, a2ps, and more! Celebrate the new year: join the free software community! A message from FSF president Ian Kelling Recent blogs - More… Upcoming Events Free Software Directory meeting on IRC: Friday, January 16, starting at 12:00 EST (17:00 UTC) Jan 16, 2026 12:00 PM - 03:00 PM — #fsf on libera.chat Previous events… Upcoming events… The FSF is a charity with a worldwide mission to advance software freedom — learn about our history and work. Copyright © 2004-2026 Free Software Foundation , Inc. Privacy Policy . This work is licensed under a Creative Commons Attribution-No Derivative Works 3.0 license (or later version) — Why this license? Skip sitemap or skip to licensing items About Staff and Board Contact Us Press Information Jobs Volunteering and Internships History Privacy Policy JavaScript Licenses Hardware Database Free Software Directory Free Software Resources Copyright Infringement Notification Skip to general items Campaigns Freedom Ladder Fight to Repair Free JavaScript High Priority Free Software Projects Secure Boot vs Restricted Boot Surveillance Upgrade from Windows Working Together for Free Software GNU Operating System Defective by Design End Software Patents OpenDocument Free BIOS Connect with free software users Skip to philosophical items Licensing Education Licenses GNU GPL GNU AGPL GNU LGPL GNU FDL Licensing FAQ Compliance How to use GNU licenses for your own software Latest News Upcoming Events FSF Blogs Skip list Donate to the FSF Join the FSF Patrons Associate Members My Account Working Together for Free Software Fund Philosophy The Free Software Definition Copyleft: Pragmatic Idealism Free Software and Free Manuals Selling Free Software Motives for Writing Free Software The Right To Read Why Open Source Misses the Point of Free Software Complete Sitemap fsf.org is powered by: Plone Zope Python CiviCRM HTML5 Arabic Belarussian Bulgarian Catalan Chinese Cornish Czech Danish English French German Greek Hebrew Hindi Italian Japanese Korean Norwegian Polish Portuguese Portuguese (Brazil) Romanian Russian Slovak Spanish Swedish Turkish Urdu Welsh Send your feedback on our translations and new translations of pages to campaigns@fsf.org . | 2026-01-13T08:49:36 |
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Report Abuse Brian Douglas for GitHub Posted on Feb 23, 2021 • Edited on Mar 1, 2021 Environment Scoped Secrets for GitHub Action Workflows # github # devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions Secrets are encrypted environment variables that you create in an organization, repository, or environment. These secrets are also available to use in GitHub Actions workflows. GitHub uses the open-source libsodium encryption library to ensure that secrets are encrypted before reaching GitHub and remaining encrypted until you use them in a workflow. jedisct1 / libsodium A modern, portable, easy to use crypto library. Organization-level Secrets For secrets stored at the organization-level, you can use access policies to control which repositories can use organization secrets. Organization-level secrets let you share secrets between multiple repositories, which reduces the need for creating duplicating secrets. Updating an organization secret in one location also ensures that the change takes effect in all repository workflows that use that secret. Repository Environment Secrets For secrets stored at the environment level, you can enable required reviewers to control access to the secrets. A workflow job cannot access environment secrets until the required approvers approve. In my examples, I have a DATABASE_URL secret specifically for my staging environment. If you want to see, this live in an action. Check out this GitHub Universe talk from Chris Patterson (GitHub Action PM). This is part of my 28 days of Actions series. To get notified of more GitHub Action tips, follow the GitHub organization right here on Dev. Learn how to build action with Node.js 01:43 Bring your own (self-hosted) environment for GitHub Action Workflows Brian Douglas for GitHub ・ Feb 23 '21 #github #devops ["28-github-actions"] (25 Part Series) 1 Automating my Storybook deployment with GitHub Actions 2 GitHub Actions: Manual triggers with workflow_dispatch ... 21 more parts... 3 How to Run GitHub Actions on Forks 4 Running GitHub Actions CI/CD triggers on specific branches 5 Generate semantic-release notes with GitHub Actions 6 Compress Images for the Web with GitHub Actions 7 Keeping GitHub Action workflows secure 8 Skip pull request and push GitHub Action workflows with [skip ci] 9 Running complex matrix builds using variable substitution in GitHub Actions 10 The Secrets of An Authenticated GitHub Action Workflow 11 Debug your GitHub Actions via SSH by using tmate 12 Run your GitHub Actions like a makefile 13 Automate your PR reviews with GitHub Action scripting in JavaScript 14 Generate your own GitHub Action with the actions-toolkit CLI 15 Build your own GitHub Action with a Docker Container 16 Publish your GitHub Action to Marketplace 17 Build your own GitHub Action WITHOUT a Docker Container 18 Conditional Workflows and Failures in GitHub Actions 19 Sending PR notifications through SMS and GitHub Actions 20 Bring your own (self-hosted) environment for GitHub Action Workflows 21 Environment Scoped Secrets for GitHub Action Workflows 22 Caching dependencies to speed up workflows in GitHub Actions 23 Repository Automation with GitHub Actions 24 Sync Forks to Upstream Using GitHub Actions 25 Setup Continuous Delivery with GitHub Actions Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. 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https://devcenter.heroku.com/articles/heroku-inference | Managed Inference and Agents Add-on | Heroku Dev Center Skip Navigation Show nav Dev Center Get Started Documentation Changelog Search Dev Center Get Started Node.js Ruby on Rails Ruby Python Java PHP Go Scala Clojure .NET Documentation Changelog More Additional Resources Home Elements Products Pricing Careers Help Status Events Podcasts Compliance Center Heroku Blog Heroku Blog Find out what's new with Heroku on our blog. 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Due to the nature of generative AI, the output that it generates may be unpredictable, and may include inaccurate or harmful responses. Customer assumes all responsibility for such output, including ensuring its accuracy, safety, and compliance with applicable laws and third-party acceptable use policies. For more information, please see the Heroku Notices and License Information Documentation . The Heroku Managed Inference and Agents add-on offers an easy way to access various large foundational AI models, including supported language (chat), embedding, and diffusion (image) models. To use these models, attach one or more model resources from the Heroku Managed Inference and Agents add-on to your Heroku app. The add-on adds config variables to your app, allowing you to call the provisioned models. You can call models with the Heroku AI CLI plug-in or via direct curl requests . All available models are hosted on Amazon Bedrock . Heroku provides an API similar to OpenAI’s to access the models. Check out the Python, Ruby, and JavaScript (Node.js) quick start guides . Tools This add-on can also enable your large language models (LLMs) to run tools on Heroku automatically, with built-in support for retries and error correction. It supports both custom tools you create and built-in tools, like code execution, provided by Heroku. When enabled, your app’s LLM calls a tool that triggers Heroku’s control loop to provision, execute, and deprovision dynos in the background, with action traces included in the model’s output. See Heroku Tools and Working With MCP to learn more. Benefits Heroku owns and maintains the add-on. Your data is never sent outside of secure AWS accounts. Inference prompts and completions are only logged temporarily via Heroku Logplex , which you control. Security Heroku is committed to providing a secure and reliable platform. The Managed Inference and Agents add-on is protected by extensive security measures designed to safeguard our underlying infrastructure and services. However, there are unique security challenges inherent to LLMs. The Nature of LLM Vulnerabilities LLMs are designed to interpret and respond dynamically to natural language. This core capability makes them uniquely susceptible to attacks where malicious instructions are embedded in the input. Prompt injection and chained attacks are two notable vulnerabilities. Prompt Injection Prompt injection is when an attacker exploits an LLM by introducing text that overrides the model’s built-in system instructions and security policies. LLM providers write security policies in natural language, and attackers can use this knowledge to bypass them. Chained Attacks Chained attacks are when an initial prompt injection combines with other model capabilities or external connections to achieve a larger, often unauthorized, action. A model’s ability to connect to and operate tools creates potential pathways for compromise if it generates malicious output. Treat LLM Output as Untrusted Input Due to the fundamental characteristics of LLMs, technology providers can’t entirely eliminate the risk of vulnerabilities. Achieving full protection requires a multi-layered strategy that extends beyond a managed platform service. We recommend all customers adopt a security-first approach when integrating LLM output into app logic, user interfaces, or any system connected to sensitive data or functions. Treat LLM output as untrusted input. Available Models For a complete list of available models in us and eu regions, see Managed Inference and Agents API Model Cards . Install the CLI Plugin Heroku provides an AI CLI plugin to interact with your model resources. Install the Heroku CLI if you haven’t installed it yet. Then, install the Heroku AI plugin: heroku plugins:install @heroku/plugin-ai See Heroku AI CLI Plugin Command Reference for details of all plugin commands. Provision Access to an AI Model Resource To use a model, you must first create and attach a model resource $MODEL_ID to your app $APP_NAME . If you don’t have an app, you can create one with heroku create <your-new-app-name> . To view the available models, you can run heroku ai:models:list . After deciding which model you want to use, run: heroku ai:models:create -a $APP_NAME $MODEL_ID By default, apps in the us region can only provision us models , and apps in the eu region can only provision eu models . Similarly, private space apps in the oregon , virginia , or montreal regions by default can only provision us models ; apps in the remaining private space regions can only provision eu models . To override this, use the --region flag and use addons:create instead of ai:models:create to create your model resource: heroku addons:create heroku-inference:$MODEL_ID -a $APP_NAME -- --region=us/eu You can attach multiple model resources to a single app. By default, the first model resource you attach to an app has an alias of INFERENCE . Subsequent attachments have randomized alias names, so we recommend you specify an alias with the --as flag. Specifically, we recommend using --as values of EMBEDDING and DIFFUSION for our embedding and diffusion models: heroku ai:models:create -a $APP_NAME cohere-embed-multilingual --as EMBEDDING heroku ai:models:create -a $APP_NAME stable-image-ultra --as DIFFUSION We recommend using an alias of INFERENCE for the chat models, an alias of EMBEDDING for the embedding model ( cohere-embed-multilingual ), and DIFFUSION for the image model ( stable-image-ultra ) that we offer. Our example code follows this pattern, so for easy copy and pasting of commands, we recommend you also use these aliases. If you attach more than one model resource of the same type to a single app, you must specify your own alias and replace any example code you’re using with the resulting config vars. Model Resource Config Vars After attaching a model resource to your app, your app has three new config variables. You can view these variables by calling heroku config -a $APP_NAME . If your app’s model resource has an alias of INFERENCE , which is the default, your three new config variables are: INFERENCE_KEY INFERENCE_MODEL_ID INFERENCE_URL To save these config variables as environment variables in your current environment, you can run: export INFERENCE_KEY=$(heroku config:get INFERENCE_KEY -a $APP_NAME) export INFERENCE_MODEL_ID=$(heroku config:get INFERENCE_MODEL_ID -a $APP_NAME) export INFERENCE_URL=$(heroku config:get INFERENCE_URL -a $APP_NAME) Or you can view and export your config vars all at once with: eval $(heroku config -a $APP_NAME --shell | grep '^INFERENCE_' | tee /dev/tty | sed 's/^/export /') In subsequent commands, you can specify your app’s <MODEL_RESOURCE> by either the --as alias, which is "INFERENCE" by default. Or you can specify it by the model resource slug, for example, inference-production-curved-41276 . Run heroku ai:models:info -a $APP_NAME to view the slug and alias of an attached model resource. Language-Specific Examples We have language-specific quick start guides in Python, Ruby, and JavaScript for each of our endpoints. Call an AI Model Resource Via API / curl Requests A typical model call looks like this: curl $INFERENCE_URL/v1/chat/completions \ -H "Authorization: Bearer $INFERENCE_KEY" \ -d '{ "model": '"\"$INFERENCE_MODEL_ID\""', <other model keyword-arguments, varies model to model> }' Though the full endpoint URL varies depending on the model you’re using. For example: Chat models use the /v1/chat/completions endpoint. Embedding model cohere-embed-multilingual uses the /v1/embeddings endpoint. Diffusion model stable-image-ultra uses the /v1/images/generations endpoint. See our model cards for details on each model. We recommend using streaming for all inferencing requests to prevent timeouts when requests exceed 29 seconds. Important Caveat: When using streaming with tool calling, the add-on streams complete responses after each tool call, rather than incremental updates. If any individual tool call takes 55 seconds or longer, a timeout will occur. Via Heroku AI Plugin A typical model call looks like this: heroku ai:models:call <MODEL_RESOURCE> -a $APP_NAME --prompt 'What is 1+2?' See our model cards for details on each model. Rate Limit Headers Token and request rate limits are per minute and calculated with a sliding window. Review these headers for information on the current state of your inference add-on’s rate limits: Header Description Example x-ratelimit-limit-requests limit on requests per minute 200 x-ratelimit-limit-tokens limit on tokens per minute 800000 x-ratelimit-remaining-requests remaining number of requests permitted before reaching rate limit 198 x-ratelimit-remaining-tokens remaining number of tokens permitted before reaching rate limit 799892 x-ratelimit-reset-requests time until more request capacity becomes available* 51s x-ratelimit-reset-tokens time until more token capacity becomes available* 51s * These headers are calculated with a one-minute sliding window. As entries expire, additional capacity releases gradually rather than all at once. The returned time value indicates when the oldest entry expires in the sliding window. Prompt Caching Prompt caching optimizes the Heroku Managed Inference and Agents add-on to deliver faster responses for common workflows, document processing, and code-generation tools. Heroku automatically enables prompt caching for system prompts and tool definitions. You can disable prompt caching for any request. When agentic apps make calls to models, a portion of the request content remains static. Prompt caching enables Heroku to not reprocess this static content for every call and instead use its already processed result from a secure cache. How prompt caching works: First request: A request with a new, substantial prompt is processed and Heroku securely caches the results. Similar requests: For subsequent requests with the same initial prompt or tools, Heroku reuses the cached components to provide a faster response. Caching only occurs when content meets the minimum token threshold, improving performance where it adds the most value. The secure cache automatically expires after five minutes of inactivity. Each cache is built on Heroku’s secure infrastructure and protects your data with cryptographic hashing and automatic expiration. Heroku only uses prompt caching for system prompts and tool definitions, and not for user messages or conversation history. Heroku doesn’t charge for cache writes or pass on the difference for cache hits. Disable Prompt Caching You can disable prompt caching for a request by adding an HTTP header: X-Heroku-Prompt-Caching: false Monitoring and Logging Display stats and the current state of your model resources via the ai plugin: heroku ai:models:info <MODEL_RESOURCE> -a $APP_NAME # model resource can be the resource ID or alias. Tracking Usage To view usage data for an AI model resource, run: heroku usage:addons -a example-app -t example-team Heroku returns the metered data, for example: === Usage for example-team Add-on Meter Quantity ───────────────────────── ────── ──────── inference-amorphous-42410 input 8 inference-amorphous-42410 output 12 Metered data displays the number of tokens processed (input) and generated (output) by an AI model resource in the current billing period. For pricing details, see the Heroku Managed Inference and Agents add-on . Deprovisioning an AI Model Resource If you only ever use heroku ai:models:create commands to create and attach model resources, you can use heroku ai:models:destroy to destroy that resource. However, in some cases users attach a single model resource to multiple apps via heroku ai:models:attach . To destroy a model resource connected to multiple apps, you must first detach the resource from all but one app with heroku ai:models:detach . Then, run heroku ai:models:destroy or run the destroy command with the --force flag. Destroy an AI Model Resource This action destroys all associated data and you can’t undo it! To destroy an AI model resource, run: heroku ai:models:destroy <MODEL_RESOURCE> --app $APP_NAME When destroying a model resource, you can specify the model resource’s alias or the resource ID. Detach an AI Model Resource If you chose to create and then attach model resources to certain apps, you can detach an AI model resource from a specific app with: heroku ai:models:detach <MODEL_RESOURCE> --app $APP_NAME When detaching a model resource, you can specify the model resource’s alias or the resource ID. This add-on bills by usage. A detached AI model resource never bills you, nor will an attached AI model resource that you’re not actively using. Feedback Log in to submit feedback. 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https://devin.ai | Devin | The AI Software Engineer Home Enterprise Pricing Customers Financial Services --> View more About us Careers Blog Contact us Docs About us Careers Blog Contact Docs Login Get started Home Enterprise Pricing Customers About us Careers Blog Docs Contact Get started Login How Nubank refactors millions of lines of code to improve engineering efficiency with Devin 8x engineering time efficiency gain 20x cost savings Overview One of Nubank’s most critical, company-wide projects for 2023-2024 was a migration of their core ETL — an 8 year old, multi-million lines of code monolith — to sub-modules. To handle such a large refactor, their only option was a multi-year effort that distributed repetitive refactoring work across over one thousand of their engineers. With Devin, however, this changed: engineers were able to delegate Devin to handle their migrations and achieve a 12x efficiency improvement in terms of engineering hours saved, and over 20x cost savings. Among others, Data, Collections, and Risk business units verified and completed their migrations in weeks instead of months or years. The Problem Nubank was born into the tradition of centralized ETL FinServ architectures. To date, the monolith architecture had worked well for Nubank — it enabled the developer autonomy and flexibility that carried them through their hypergrowth phases. After 8 years, however, Nubank’s sheer volume of customer growth, as well as geographic and product expansion beyond their original credit card business, led to an entangled, behemoth ETL with countless cross-dependencies and no clear path to continuing to scale. For Nubankers, business critical data transformations started taking increasingly long to run, with chains of dependencies as deep as 70 and insufficient formal agreements on who was responsible for maintaining what. As the company continued to grow, it became clear that the ETL would be a primary bottleneck to scale. Nubank concluded that there was an urgent need to split up their monolithic ETL repository, amassing over 6 million lines of code, into smaller, more flexible sub-modules. Nubank’s code migration was filled with the monotonous, repetitive work that engineers dread. Moving each data class implementation from one architecture to another while tracing imports correctly, performing multiple delicate refactoring steps, and accounting for any number of edge cases was highly tedious, even to do just once or twice. At Nubank’s scale, however, the total migration scope involved more than 1,000 engineers moving ~100,000 data class implementations over an expected timeline of 18 months. In a world where engineering resources are scarce, such large-scale migrations and modernizations become massively expensive, time-consuming projects that distract from any engineering team’s core mission: building better products for customers. Unfortunately, this is the reality for many of the world’s largest organizations. The Decision: an army of Devins to tackle subtasks in parallel At project outset in 2023, Nubank had no choice but to rely on their engineers to perform code changes manually. Migrating one data class was a highly discretionary task, with multiple variations, edge cases, and ad hoc decision-making — far too complex to be scriptable, but high-volume enough to be a significant manual effort. Within weeks of Devin’s launch, Nubank identified a clear opportunity to accelerate their refactor at a fraction of the engineering hours. Migration or large refactoring tasks are often fantastic projects for Devin: after investing a small, fixed cost to teach Devin how to approach sub-tasks, Devin can go and complete the migration autonomously. A human is kept in the loop just to manage the project and approve Devin’s changes. The Solution: Custom ETL Migration Devin A task of this magnitude, with the vast number of variations that it had, was a ripe opportunity for fine-tuning. The Nubank team helped to collect examples of previous migrations their engineers had done manually, some of which were fed to Devin for fine-tuning. The rest were used to create a benchmark evaluation set. Against this evaluation set, we observed a doubling of Devin’s task completion scores after fine-tuning, as well as a 4x improvement in task speed. Roughly 40 minutes per sub-task dropped to 10, which made the whole migration start to look much cheaper and less time-consuming, allowing the company to devote more energy to new business and new value creation instead. Devin contributed to its own speed improvements by building itself classical tools and scripts it would later use on the most common, mechanical components of the migration. For instance, detecting the country extension of a data class (either ‘br’, ‘co’, or ‘mx’) based on its file path was a few-step process for each sub-task. Devin’s script automatically turned this into a single step executable — improvements from which added up immensely across all tens of thousands of sub-tasks. There is also a compounding advantage on Devin’s learning. In the first weeks, it was common to see outstanding errors to fix, or small things Devin wasn’t sure how to solve. But as Devin saw more examples and gained familiarity with the task, it started to avoid rabbit holes more often and find faster solutions to previously-seen errors and edge cases. Much like a human engineer, we observed obvious speed and reliability improvements with every day Devin worked on the migration. Results: Delivering an 8-12x faster migration, lifting a burden from every engineer, and slashing migration costs by 20x. “Devin provided an easy way to reduce the number of engineering hours for the migration, in a way that was more stable and less prone to human error. Rather than engineers having to work across several files and complete an entire migration task 100%, they could just review Devin’s changes, make minor adjustments, then merge their PR” Jose Carlos Castro, Senior Product Manager 8-12x efficiency gains This is calculated by comparing the typical engineering hours required to complete a data class migration task against the total engineering hours spent prompting and reviewing Devin’s work on the same task. Over 20x cost savings on scope of the migration delegated to Devin This is calculated by comparing the cost of running Devin versus the hourly cost of an engineer completing that task. The significant savings are heavily driven by speed of task execution and cost effectiveness of Devin relative to human engineering time – it does not even consider the value captured by completing the entire project months ahead of schedule! Fewer dreaded migration tasks for Nubank engineers Devin, the AI software engineer Start building Crush your backlog with your personal AI engineering team. 1 Ticket Integrate Slack, Teams, Linear, and Jira 2 Plan Quickly review Devin's proposal 3 Test Devin tests changes by itself 4 PR Review changes natively slack Linear Ticket Integrate Slack, Teams, Linear, and Jira Plan Quickly review Devin's proposal Test Devin tests changes by itself PR Review changes natively Devin has authored millions of lines of code for top teams. See what our customers built. Use cases From implementing new features to fixing thousands of lint errors, Devin can clear your backlog, modernize your codebase, and help you build more. Code Migration + Refactors Language migrations Version upgrades Codebase restructuring Data Engineering + Analysis Data warehouse migrations ETL development Data cleaning and preprocessing Bugs + Backlog Work Ticket resolution CI/CD First-draft PR creation for backlog tasks Code Migration + Refactors Language migrations Version upgrades Codebase restructuring Data Engineering + Analysis Data warehouse migrations ETL development Data cleaning and preprocessing Bugs + Backlog Work Ticket resolution CI/CD First-draft PR creation for backlog tasks Application development Frontend bugs and edge cases Unit and E2E testing Building SaaS integrations Bug & issue triage Automated on-call response Ticket resolution CI/CD autotriage And many others Technical debt Performance optimization Scraping New repo onboarding Maintaining documentation Learn & work together Devin is built for collaboration and can learn to fit into your unique workflow. Use when When working in the backend repo Approved new knowledge: When working in the backend repo Rejected new knowledge: When working in the backend repo Devin learns your codebase & picks up tribal knowledge Code on the go Write code using natural language instructions with Devin on mobile. Collaborate Use Devin's editor, shell and browser Take over and run commands, edit code, or use the browser for Devin at any time. Able to work with hundreds of tools Devin connects to your favorite MCP servers, from Asana to Zapier Build together with Confluence Build together with Airtable Build together with Segment Build together with Asana Build together with Notion Build together with Stripe Build together with AWS Build together with GitHub Build together with Datadog Build together with Linear Build together with Databricks Build together with Slack Build together with Google Drive Build together with Sentry Build together with gg gg PostgreSQL Build together with Azure Build together with Snowflake Build together with MongoDB GitHub Devin can independently create PRs, respond to PR comments, review PRs, etc. Linear Assign Devin tickets directly in Linear, or add the Devin tag. Slack and Teams Assign Devin tasks by tagging @Devin in Slack or Teams. Devin keeps you updated on progress in replies. Linear Tag @Devin directly in Linear tickets or add the Devin tag to delegate tasks to Devin. gg gg GitHub Devin can independently create PRs, respond to PR comments, review PRs, etc. Linear Tag @Devin directly in Linear tickets or add the Devin tag to delegate tasks to Devin. Slack and Teams Assign Devin tasks by tagging @Devin in Slack or Teams. Devin keeps you updated on progress in replies. Industry leaders choose to Build with Devin Hear from our customers Build more with Devin Get started Need Devin for your enterprise? Get started with Devin Enterprise Devin Enterprise provides additional capabilities, security and control for your organization. Learn about Devin Enterprise Contact us Privacy policy Terms of service Linkedin X (Twitter) | 2026-01-13T08:49:36 |
https://www.cursor.com/ | Cursor Skip to content Cursor Features Enterprise Pricing Resources ↓ Changelog Blog Docs ↗ Community Learn ↗ Workshops Forum ↗ Careers Features Enterprise Pricing Resources → Sign in Download Built to make you extraordinarily productive, Cursor is the best way to code with AI. Download for macOS ⤓ Try mobile agent → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: the IDE with AI-powered coding assistance, the CLI with command-line assistance. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools train_model.py run_experiment.py config.yaml import torch import torch . nn as nn from torch . utils . data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms . Compose ([ transforms . ToTensor ()]) train = datasets . MNIST ( root = "data" , train = True , download = True , transform = transform ) test = datasets . MNIST ( root = "data" , train = False , download = True , transform = transform ) return DataLoader ( train , batch_size = batch_size , shuffle = True ), DataLoader ( test , batch_size = batch_size ) class MLP ( nn . Module ): def __init__ ( self , hidden = 128 ): super (). __init__ () self . net = nn . Sequential ( nn . Flatten (), nn . Linear ( 28 * 28 , hidden ), nn . ReLU (), nn . Linear ( hidden , 10 ), ) def forward ( self , x ): return self . net ( x ) def train_model ( epochs = 1 , lr = 1e-3 , device = None): device = device or ( "cuda" if torch . cuda . is_available () else "cpu" ) model = MLP (). to ( device ) opt = torch . optim . Adam ( model . parameters (), lr = lr ) loss_fn = nn . CrossEntropyLoss () train_loader , _ = get_dataloaders () + # Seed for reproducibility + torch . manual_seed ( 42 ) + if device == "cuda" : + torch . cuda . manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch . cuda . amp . GradScaler ( enabled =( device == "cuda" )) + scheduler = torch . optim . lr_scheduler . CosineAnnealingLR ( opt , T_max = epochs ) model . train () for epoch in range ( epochs ) : total , correct = 0 , 0 for x , y in tqdm ( train_loader , desc = f "epoch { epoch + 1 } " ) : x , y = x . to ( device ), y . to ( device ) opt . zero_grad ( set_to_none = True ) logits = model ( x ) loss = loss_fn ( logits , y ) loss . backward () opt . step () scaler . scale ( loss ). backward () scaler . unscale_ ( opt ) + torch . nn . utils . clip_grad_norm_ ( model . parameters (), max_norm = 1.0 ) scaler . step ( opt ) scaler . update () + preds = logits . argmax ( dim = 1 ) + total += y . size ( 0 ) + correct += ( preds == y ). sum (). item () + acc = correct / max ( 1 , total ) scheduler . step () + print ( f "epoch { epoch + 1 } : acc= { acc :.3f } " ) return model `, import torch import torch.nn as nn from torch.utils.data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms. Compose ([transforms. ToTensor ()]) train = datasets. MNIST (root= " data " , train= True , download= True , transform=transform) test = datasets. MNIST (root= " data " , train= False , download= True , transform=transform) return DataLoader (train, batch_size=batch_size, shuffle= True ), DataLoader (test, batch_size=batch_size) class MLP (nn.Module): def __init__ ( self , hidden = 128 ): super (). __init__ () self .net = nn. Sequential ( nn. Flatten (), nn. Linear ( 28 * 28 , hidden), nn. ReLU (), nn. Linear (hidden, 10 ), ) def forward ( self , x ): return self . net (x) def train_model ( epochs = 1 , lr = 1e-3 , device = None ): device = device or ( " cuda " if torch.cuda. is_available () else " cpu " ) model = MLP (). to (device) opt = torch.optim. Adam (model. parameters (), lr=lr) loss_fn = nn. CrossEntropyLoss () train_loader, _ = get_dataloaders () + # Seed for reproducibility + torch. manual_seed ( 42 ) + if device == " cuda " : + torch.cuda. manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch.cuda.amp. GradScaler (enabled=(device == " cuda " )) + scheduler = torch.optim.lr_scheduler. CosineAnnealingLR (opt, T_max=epochs) model. train () for epoch in range (epochs): total, correct = 0 , 0 for x, y in tqdm (train_loader, desc= f "epoch { epoch+ 1 } " ): x, y = x. to (device), y. to (device) opt. zero_grad (set_to_none= True ) logits = model (x) loss = loss_fn (logits, y) loss. backward () opt. step () scaler. scale (loss). backward () scaler. unscale_ (opt) + torch.nn.utils. clip_grad_norm_ (model. parameters (), max_norm= 1.0 ) scaler. step (opt) scaler. update () + preds = logits. argmax (dim= 1 ) + total += y. size ( 0 ) + correct += (preds == y). sum (). item () + acc = correct / max ( 1 , total) scheduler. step () + print ( f "epoch { epoch+ 1 } : acc= { acc :.3f } " ) return model ` , PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. Agent GPT-5 agent Get CLI Cursor Agent ~/Repos/ml-research-notebook PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. → GPT-5.2 / for commands · @ for files Trusted every day by millions of professional developers. Agent turns ideas into code A human-AI programmer, orders of magnitude more effective than any developer alone. Learn about Agent → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools Analyze Tab vs Agent Usage Patterns Help me understand how teams split their focus between the tab view and the agents panel across our workspaces. Agent GPT-5 Magically accurate autocomplete Our custom Tab model predicts your next action with striking speed and precision. Learn about Tab → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor Dashboard.tsx SupportChat.tsx "use client" ; import React , { useState } from "react" ; import Navigation from "./Navigation" ; import SupportChat from "./SupportChat" ; export default function Dashboard () { return ( < div className = "flex h-[600px] border rounded-lg overflow-hidden" > < div className = "w-64 border-r" > </ div > < div className = "w-80 border-l" > < SupportChat /> </ div > </ div > ); } " use client " ; import React, { useState } from " react " ; import Navigation from " ./Navigation " ; import SupportChat from " ./SupportChat " ; export default function Dashboard() { return ( < div className = " flex h-[600px] border rounded-lg overflow-hidden " > < div className = " w-64 border-r " > </ div > < div className = " w-80 border-l " > < SupportChat /> </ div > </ div > ); } Everywhere software gets built Cursor is in GitHub reviewing your PRs, a teammate in Slack, and anywhere else you work. Learn about Cursor's ecosystem → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: Slack integration for team communication, GitHub integration for code review and debugging. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Slack Get Cursor for Slack #ask-cursor 8 members dylan small thing but would be really good to have anchor links on the website for releases 4 replies dylan wanna be able to go to cursor.com/changelog#1.0 to see 1.0 changelog eric checks out @cursor can you take a stab? Cursor APP I implemented direct linking for changelog entries and updated Node.js version constraints across the project to improve compatibility and maintainability. View PR Open in Cursor Open in Web dylan Nice @eric can you take a look? GitHub Pull Request Get BugBot Review cursor bot reviewed 1m ago src/vs/workbench/composer/browser/components/ComposerUnifiedDropdown.tsx 3292 - {selectedMode().keybinding} 3293 + {composerOpenModeToggleKeybinding} cursor bot 1m ago Bug: Function Returns Object Instead of String (Logic bug) The composerOpenModeToggleKeybinding is a function that needs to be called to get its value. Using it directly causes the keybinding display condition to always be truthy. Fix in Cursor Fix in Web The new way to build software. It was night and day from one batch to another, adoption went from single digits to over 80%. It just spread like wildfire, all the best builders were using Cursor. Diana Hu General Partner , Y Combinator The most useful AI tool that I currently pay for, hands down, is Cursor. It's fast, autocompletes when and where you need it to, handles brackets properly, sensible keyboard shortcuts, bring-your-own-model... everything is well put together. shadcn Creator of shadcn/ui The best LLM applications have an autonomy slider: you control how much independence to give the AI. In Cursor, you can do Tab completion, Cmd+K for targeted edits, or you can let it rip with the full autonomy agentic version. Andrej Karpathy CEO , Eureka Labs Cursor quickly grew from hundreds to thousands of extremely enthusiastic Stripe employees. We spend more on R&D and software creation than any other undertaking, and there's significant economic outcomes when making that process more efficient and productive. Patrick Collison Co‑Founder & CEO , Stripe It's official. I hate vibe coding. I love Cursor tab coding. It's wild. ThePrimeagen @ThePrimeagen It's definitely becoming more fun to be a programmer. It's less about digging through pages and more about what you want to happen. We are at the 1% of what's possible, and it's in interactive experiences like Cursor where models like GPT-5 shine brightest. Greg Brockman President , OpenAI Stay on the frontier Access the best models Choose between every cutting-edge model from OpenAI, Anthropic, Gemini, and xAI. Explore models ↗ Auto Suggested Composer 1 GPT-5 High Fast Claude Sonnet 4.5 ✓ Claude Opus 4.5 Gemini 3 Pro Grok Code Complete codebase understanding Cursor learns how your codebase works, no matter the scale or complexity. Learn about codebase indexing ↗ Where are these menu label colors defined? Develop enduring software Trusted by over half of the Fortune 500 to accelerate development, securely and at scale. Explore enterprise → Changelog CLI Jan 8, 2026 New CLI Features and Improved CLI Performance 2.3 Dec 22, 2025 Layout Customization and Stability Improvements Dec 18, 2025 Enterprise Insights, Billing Groups, Service Accounts, and Improved Security Controls 2.2 Dec 10, 2025 Debug Mode, Plan Mode Improvements, Multi-Agent Judging, and Pinned Chats See what's new in Cursor → Cursor is an applied team focused on building the future of coding. Join us → Recent highlights Introducing Cursor 2.0 and Composer A new interface and our first coding model, both purpose-built for working with agents. Product · Oct 29, 2025 Improving Cursor Tab with online RL Our new Tab model makes 21% fewer suggestions while having 28% higher accept rate. Research · Sep 12, 2025 1.5x faster MoE training with custom MXFP8 kernels Achieving a 3.5x MoE layer speedup with a complete rebuild for Blackwell GPUs. Research · Aug 29, 2025 View more posts → Try Cursor now. Download for macOS ⤓ Try mobile agent → Product Features Enterprise Web Agents Bugbot CLI Pricing Resources Download Changelog Docs ↗ Learn ↗ Forum ↗ Status ↗ Company Careers Blog Community Workshops Students Brand Legal Terms of Service Privacy Policy Data Use Security Connect X ↗ LinkedIn ↗ YouTube ↗ © 2026 Cursor 🛡 SOC 2 Certified 🌐 English ↓ English ✓ 简体中文 日本語 繁體中文 Skip to content Cursor Features Enterprise Pricing Resources ↓ Changelog Blog Docs ↗ Community Learn ↗ Workshops Forum ↗ Careers Features Enterprise Pricing Resources → Sign in Download Built to make you extraordinarily productive, Cursor is the best way to code with AI. Download for macOS ⤓ Try mobile agent → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: the IDE with AI-powered coding assistance, the CLI with command-line assistance. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools train_model.py run_experiment.py config.yaml import torch import torch . nn as nn from torch . utils . data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms . Compose ([ transforms . ToTensor ()]) train = datasets . MNIST ( root = "data" , train = True , download = True , transform = transform ) test = datasets . MNIST ( root = "data" , train = False , download = True , transform = transform ) return DataLoader ( train , batch_size = batch_size , shuffle = True ), DataLoader ( test , batch_size = batch_size ) class MLP ( nn . Module ): def __init__ ( self , hidden = 128 ): super (). __init__ () self . net = nn . Sequential ( nn . Flatten (), nn . Linear ( 28 * 28 , hidden ), nn . ReLU (), nn . Linear ( hidden , 10 ), ) def forward ( self , x ): return self . net ( x ) def train_model ( epochs = 1 , lr = 1e-3 , device = None): device = device or ( "cuda" if torch . cuda . is_available () else "cpu" ) model = MLP (). to ( device ) opt = torch . optim . Adam ( model . parameters (), lr = lr ) loss_fn = nn . CrossEntropyLoss () train_loader , _ = get_dataloaders () + # Seed for reproducibility + torch . manual_seed ( 42 ) + if device == "cuda" : + torch . cuda . manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch . cuda . amp . GradScaler ( enabled =( device == "cuda" )) + scheduler = torch . optim . lr_scheduler . CosineAnnealingLR ( opt , T_max = epochs ) model . train () for epoch in range ( epochs ) : total , correct = 0 , 0 for x , y in tqdm ( train_loader , desc = f "epoch { epoch + 1 } " ) : x , y = x . to ( device ), y . to ( device ) opt . zero_grad ( set_to_none = True ) logits = model ( x ) loss = loss_fn ( logits , y ) loss . backward () opt . step () scaler . scale ( loss ). backward () scaler . unscale_ ( opt ) + torch . nn . utils . clip_grad_norm_ ( model . parameters (), max_norm = 1.0 ) scaler . step ( opt ) scaler . update () + preds = logits . argmax ( dim = 1 ) + total += y . size ( 0 ) + correct += ( preds == y ). sum (). item () + acc = correct / max ( 1 , total ) scheduler . step () + print ( f "epoch { epoch + 1 } : acc= { acc :.3f } " ) return model `, import torch import torch.nn as nn from torch.utils.data import DataLoader from torchvision import datasets def get_dataloaders ( batch_size = 64 ): transform = transforms. Compose ([transforms. ToTensor ()]) train = datasets. MNIST (root= " data " , train= True , download= True , transform=transform) test = datasets. MNIST (root= " data " , train= False , download= True , transform=transform) return DataLoader (train, batch_size=batch_size, shuffle= True ), DataLoader (test, batch_size=batch_size) class MLP (nn.Module): def __init__ ( self , hidden = 128 ): super (). __init__ () self .net = nn. Sequential ( nn. Flatten (), nn. Linear ( 28 * 28 , hidden), nn. ReLU (), nn. Linear (hidden, 10 ), ) def forward ( self , x ): return self . net (x) def train_model ( epochs = 1 , lr = 1e-3 , device = None ): device = device or ( " cuda " if torch.cuda. is_available () else " cpu " ) model = MLP (). to (device) opt = torch.optim. Adam (model. parameters (), lr=lr) loss_fn = nn. CrossEntropyLoss () train_loader, _ = get_dataloaders () + # Seed for reproducibility + torch. manual_seed ( 42 ) + if device == " cuda " : + torch.cuda. manual_seed_all ( 42 ) + # AMP + Scheduler + scaler = torch.cuda.amp. GradScaler (enabled=(device == " cuda " )) + scheduler = torch.optim.lr_scheduler. CosineAnnealingLR (opt, T_max=epochs) model. train () for epoch in range (epochs): total, correct = 0 , 0 for x, y in tqdm (train_loader, desc= f "epoch { epoch+ 1 } " ): x, y = x. to (device), y. to (device) opt. zero_grad (set_to_none= True ) logits = model (x) loss = loss_fn (logits, y) loss. backward () opt. step () scaler. scale (loss). backward () scaler. unscale_ (opt) + torch.nn.utils. clip_grad_norm_ (model. parameters (), max_norm= 1.0 ) scaler. step (opt) scaler. update () + preds = logits. argmax (dim= 1 ) + total += y. size ( 0 ) + correct += (preds == y). sum (). item () + acc = correct / max ( 1 , total) scheduler. step () + print ( f "epoch { epoch+ 1 } : acc= { acc :.3f } " ) return model ` , PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. Agent GPT-5 agent Get CLI Cursor Agent ~/Repos/ml-research-notebook PyTorch MNIST Experiments Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings. → GPT-5.2 / for commands · @ for files Trusted every day by millions of professional developers. Agent turns ideas into code A human-AI programmer, orders of magnitude more effective than any developer alone. Learn about Agent → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor In Progress 4 Enterprise Order Management System Generating Analyze Tab vs Agent Usage Patterns Generating PyTorch MNIST Experiments Generating Fix PR Comments Fetching Issue Generating Ready for Review 2 Set up Cursor Rules for Dashboard + 37 - 0 · Set up Cursor Rules for Dashboard Bioinformatics Tools + 135 - 21 · Bioinformatics Tools Analyze Tab vs Agent Usage Patterns Help me understand how teams split their focus between the tab view and the agents panel across our workspaces. Agent GPT-5 Magically accurate autocomplete Our custom Tab model predicts your next action with striking speed and precision. Learn about Tab → This element contains an interactive demo for sighted users. It's a demonstration of Cursor's IDE showing AI-powered coding assistance features. The interface is displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Cursor Get Cursor Dashboard.tsx SupportChat.tsx "use client" ; import React , { useState } from "react" ; import Navigation from "./Navigation" ; import SupportChat from "./SupportChat" ; export default function Dashboard () { return ( < div className = "flex h-[600px] border rounded-lg overflow-hidden" > < div className = "w-64 border-r" > </ div > < div className = "w-80 border-l" > < SupportChat /> </ div > </ div > ); } " use client " ; import React, { useState } from " react " ; import Navigation from " ./Navigation " ; import SupportChat from " ./SupportChat " ; export default function Dashboard() { return ( < div className = " flex h-[600px] border rounded-lg overflow-hidden " > < div className = " w-64 border-r " > </ div > < div className = " w-80 border-l " > < SupportChat /> </ div > </ div > ); } Everywhere software gets built Cursor is in GitHub reviewing your PRs, a teammate in Slack, and anywhere else you work. Learn about Cursor's ecosystem → This element contains an interactive demo for sighted users showing multiple Cursor interfaces: Slack integration for team communication, GitHub integration for code review and debugging. The interfaces are displayed over a scenic painted landscape wallpaper, giving the demo an artistic backdrop. Slack Get Cursor for Slack #ask-cursor 8 members dylan small thing but would be really good to have anchor links on the website for releases 4 replies dylan wanna be able to go to cursor.com/changelog#1.0 to see 1.0 changelog eric checks out @cursor can you take a stab? Cursor APP I implemented direct linking for changelog entries and updated Node.js version constraints across the project to improve compatibility and maintainability. View PR Open in Cursor Open in Web dylan Nice @eric can you take a look? GitHub Pull Request Get BugBot Review cursor bot reviewed 1m ago src/vs/workbench/composer/browser/components/ComposerUnifiedDropdown.tsx 3292 - {selectedMode().keybinding} 3293 + {composerOpenModeToggleKeybinding} cursor bot 1m ago Bug: Function Returns Object Instead of String (Logic bug) The composerOpenModeToggleKeybinding is a function that needs to be called to get its value. Using it directly causes the keybinding display condition to always be truthy. Fix in Cursor Fix in Web The new way to build software. It was night and day from one batch to another, adoption went from single digits to over 80%. It just spread like wildfire, all the best builders were using Cursor. Diana Hu General Partner , Y Combinator The most useful AI tool that I currently pay for, hands down, is Cursor. It's fast, autocompletes when and where you need it to, handles brackets properly, sensible keyboard shortcuts, bring-your-own-model... everything is well put together. shadcn Creator of shadcn/ui The best LLM applications have an autonomy slider: you control how much independence to give the AI. In Cursor, you can do Tab completion, Cmd+K for targeted edits, or you can let it rip with the full autonomy agentic version. Andrej Karpathy CEO , Eureka Labs Cursor quickly grew from hundreds to thousands of extremely enthusiastic Stripe employees. We spend more on R&D and software creation than any other undertaking, and there's significant economic outcomes when making that process more efficient and productive. Patrick Collison Co‑Founder & CEO , Stripe It's official. I hate vibe coding. I love Cursor tab coding. It's wild. ThePrimeagen @ThePrimeagen It's definitely becoming more fun to be a programmer. It's less about digging through pages and more about what you want to happen. We are at the 1% of what's possible, and it's in interactive experiences like Cursor where models like GPT-5 shine brightest. Greg Brockman President , OpenAI Stay on the frontier Access the best models Choose between every cutting-edge model from OpenAI, Anthropic, Gemini, and xAI. Explore models ↗ Auto Suggested Composer 1 GPT-5 High Fast Claude Sonnet 4.5 ✓ Claude Opus 4.5 Gemini 3 Pro Grok Code Complete codebase understanding Cursor learns how your codebase works, no matter the scale or complexity. Learn about codebase indexing ↗ Where are these menu label colors defined? Develop enduring software Trusted by over half of the Fortune 500 to accelerate development, securely and at scale. Explore enterprise → Changelog CLI Jan 8, 2026 New CLI Features and Improved CLI Performance 2.3 Dec 22, 2025 Layout Customization and Stability Improvements Dec 18, 2025 Enterprise Insights, Billing Groups, Service Accounts, and Improved Security Controls 2.2 Dec 10, 2025 Debug Mode, Plan Mode Improvements, Multi-Agent Judging, and Pinned Chats See what's new in Cursor → Cursor is an applied team focused on building the future of coding. Join us → Recent highlights Introducing Cursor 2.0 and Composer A new interface and our first coding model, both purpose-built for working with agents. Product · Oct 29, 2025 Improving Cursor Tab with online RL Our new Tab model makes 21% fewer suggestions while having 28% higher accept rate. Research · Sep 12, 2025 1.5x faster MoE training with custom MXFP8 kernels Achieving a 3.5x MoE layer speedup with a complete rebuild for Blackwell GPUs. Research · Aug 29, 2025 View more posts → Try Cursor now. 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https://www.fine.dev/blog/integrate-ai-technical-guide#10-leveraging-litellm-for-seamless-ai-integration | How to Integrate AI into Your Startup: A Technical Guide for CTOs Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back How to Integrate AI into Your Startup: A Technical Guide for CTOs Table of Contents Define the Use Case for AI Choose Your AI Model Wisely Access and Integrate APIs Consider Latency and Cost for AI Integration Model Customization and Fine-Tuning for AI Infrastructure Considerations for AI Deployment Testing and Monitoring AI Systems Performance Optimization for AI Integration Ensure a Smooth User Experience with AI Leveraging LiteLLM for Seamless AI Integration Potential Challenges and Solutions in AI Integration Conclusion Integrating artificial intelligence into a startup's offerings is a transformative endeavor that enhances user experience and drives innovation. For CTOs aspiring to embed AI-powered features into their products, this guide provides a comprehensive overview of the technical aspects involved in integrating advanced language models such as OpenAI's GPT-4, Anthropic's Claude, and other leading large language models (LLMs). This document will help you navigate the complexities of incorporating AI, ensuring a successful and technically sound transition. 1. Define the Use Case for AI Before embarking on AI integration, it is essential to precisely define the problem that AI will address for your users. Will AI enhance customer support, summarize complex data, or add conversational capabilities? The specific use case will dictate the appropriate AI architecture and integration strategy. For instance, automating customer support might require real-time natural language understanding and response generation, whereas document analysis could involve batch processing and data summarization. Establishing these requirements upfront helps identify the optimal LLM, the necessary tuning, and the appropriate integration model. While anyone can create a chatbot using Retrieval-Augmented Generation (RAG), the distinction lies in how effectively your AI solution addresses genuine user challenges. A sophisticated AI-driven solution, like Fine’s approach, surpasses basic RAG implementations through advanced model fine-tuning, context-aware management, and a comprehensive integration workflow. This ensures that the AI-generated solutions are accurate, pertinent, and aligned with user needs, thereby delivering actionable insights that enhance user productivity and reduce friction. 2. Choose Your AI Model Wisely Selecting an appropriate large language model (LLM) is paramount for the successful integration of AI capabilities. Different LLMs exhibit distinct strengths: OpenAI's GPT-4 is renowned for its versatility, capable of executing complex tasks such as coding assistance, creative content generation, and language translation. This flexibility makes GPT-4 suitable for a wide range of applications. Anthropic's Claude emphasizes safety and controllability, making it a preferred choice for scenarios demanding rigorous risk mitigation, such as minimizing toxic or biased outputs. Cohere, Mistral, and Llama provide specialized models that excel in domains like multilingual support and cost-effective deployment. The selection of an AI model should align with your application's priorities—whether those are accuracy, safety, efficiency, or a combination of these factors. Real-time applications may benefit from models optimized for responsiveness, whereas batch processing tasks might prioritize throughput efficiency. 3. Access and Integrate APIs Most prominent LLMs offer APIs that facilitate straightforward integration, which is crucial for effective AI deployment. Below is a detailed guide on how to integrate these models, including practical code examples. Set up API Access : Obtain API keys from your preferred LLM provider. Providers like OpenAI and Anthropic offer detailed documentation to guide you through the setup of API access and configuration of usage limits. Python Example : import openai openai.api_key = 'YOUR_OPENAI_API_KEY' response = openai.Completion.create( engine="text-davinci-003", prompt="How do I integrate AI into my startup?", max_tokens=150 ) print(response.choices[0].text) Node.js Example : const { Configuration, OpenAIApi } = require("openai"); const configuration = new Configuration({ apiKey: "YOUR_OPENAI_API_KEY", }); const openai = new OpenAIApi(configuration); async function getResponse() { const response = await openai.createCompletion({ model: "text-davinci-003", prompt: "How do I integrate AI into my startup?", max_tokens: 150, }); console.log(response.data.choices[0].text); } getResponse(); Backend Integration : Employ server-side languages like Python, Node.js, or Go to make API requests. Build a middleware layer that manages API requests, processes responses, and handles errors effectively. This middleware should ensure robustness in the face of API downtime and rate limitations. Python Middleware Example : from flask import Flask, request, jsonify import openai app = Flask(__name__) openai.api_key = 'YOUR_OPENAI_API_KEY' @app.route('/ask', methods=['POST']) def ask(): prompt = request.json.get("prompt") try: response = openai.Completion.create( engine="text-davinci-003", prompt=prompt, max_tokens=150 ) return jsonify(response.choices[0].text) except Exception as e: return jsonify({"error": str(e)}), 500 if __name__ == '__main__': app.run(debug=True) Node.js Middleware Example : const express = require('express'); const { Configuration, OpenAIApi } = require("openai"); const app = express(); const configuration = new Configuration({ apiKey: "YOUR_OPENAI_API_KEY", }); const openai = new OpenAIApi(configuration); app.use(express.json()); app.post('/ask', async (req, res) => { const prompt = req.body.prompt; try { const response = await openai.createCompletion({ model: "text-davinci-003", prompt: prompt, max_tokens: 150, }); res.json(response.data.choices[0].text); } catch (error) { res.status(500).json({ error: error.message }); } }); app.listen(3000, () => { console.log('Server is running on port 3000'); }); Optimize API Requests : To manage costs and improve response times, limit the data sent to the LLM by focusing on critical information. For complex queries, implement pre-processing (e.g., data summarization) and post-processing to enhance usability while minimizing the data payload. Python Example for Pre-processing : def preprocess_data(data): # Simplify data before sending to LLM return data[:500] # Example: trimming data to the first 500 characters prompt = preprocess_data(user_input) response = openai.Completion.create( engine="text-davinci-003", prompt=prompt, max_tokens=150 ) 4. Consider Latency and Cost for AI Integration The costs associated with API usage can escalate rapidly as your application scales. To mitigate these costs while maintaining optimal AI performance, consider the following strategies: Cache Responses : Implement caching for frequently requested responses to minimize redundant API calls. Optimize Context Windows : Large context windows can be beneficial for understanding but come with increased costs. Focus on sending only necessary context to reduce expenses. Utilize Hybrid Models : Combine smaller, open-source models (e.g., Llama 2) for low-stakes interactions with high-accuracy models (e.g., GPT-4) for critical tasks. This hybrid approach helps manage costs while retaining key AI functionalities. 5. Model Customization and Fine-Tuning for AI Pre-trained LLMs are powerful but may require customization to meet specific domain needs effectively. Prompt Engineering : Carefully crafted prompts can often yield the desired output without necessitating model fine-tuning. Experiment with different prompt formats, including few-shot prompting, to guide the model effectively. Fine-Tuning : In cases where deeper domain expertise is necessary, consider fine-tuning the model. OpenAI, among others, offers fine-tuning options. Ensure that you use well-curated datasets to avoid introducing biases during this process. 6. Infrastructure Considerations for AI Deployment AI integration requires robust infrastructure modifications beyond simple API access: Scalability : LLMs can be resource-intensive. Design server infrastructure capable of handling increased traffic and added latency, particularly during peak demand. Data Privacy : Data passing through third-party AI models presents privacy risks. Anonymize user data and implement compliance measures in alignment with relevant data policies and regulations. Edge Deployment : For applications requiring minimal latency, such as IoT, consider deploying lightweight models on edge devices while leveraging cloud-based LLMs for more demanding processing. 7. Testing and Monitoring AI Systems AI systems are dynamic and behave differently from traditional software systems. Rigorous Testing : Test the AI model against edge cases and simulate diverse scenarios to identify potential failure modes. Human-in-the-loop : In high-stakes environments, incorporate mechanisms for human oversight to ensure AI outputs meet quality standards. User feedback should be continuously leveraged to refine model behavior. Continuous Monitoring : Track key metrics such as response latency, error rates, and user satisfaction to ensure ongoing performance optimization. 8. Performance Optimization for AI Integration Effective AI integration demands careful performance tuning to ensure scalability and responsiveness. Asynchronous Processing : Use asynchronous calls to avoid blocking application threads while waiting for LLM responses. This approach allows concurrent task handling, improving overall efficiency. Python Example (Asynchronous) : import openai import asyncio async def get_response(prompt): response = await openai.Completion.acreate( engine="text-davinci-003", prompt=prompt, max_tokens=150 ) return response.choices[0].text loop = asyncio.get_event_loop() prompt = "How can asynchronous processing improve AI performance?" response_text = loop.run_until_complete(get_response(prompt)) print(response_text) Load Balancing : Use load balancers to distribute incoming API requests across multiple servers, preventing any single server from becoming overwhelmed, particularly during periods of high demand. Node.js Example with Load Balancer : Use Nginx as a load balancer to manage and distribute traffic. upstream openai_backend { server server1.example.com; server server2.example.com; } server { listen 80; location /ask { proxy_pass http://openai_backend; } } Containerization with Docker : Docker containers help maintain consistent deployment environments, ensuring easy scaling. Use Kubernetes for orchestrating multiple containers, thereby achieving high availability. Dockerfile Example : # Use an official Python runtime as a parent image FROM python:3.9-slim # Set the working directory in the container WORKDIR /app # Copy the current directory contents into the container at /app COPY . /app # Install any needed packages specified in requirements.txt RUN pip install --no-cache-dir -r requirements.txt # Make port 80 available to the world outside this container EXPOSE 80 # Define environment variable ENV NAME World # Run app.py when the container launches CMD ["python", "app.py"] Kubernetes Deployment Example : apiVersion: apps/v1 kind: Deployment metadata: name: openai-app-deployment spec: replicas: 3 selector: matchLabels: app: openai-app template: metadata: labels: app: openai-app spec: containers: - name: openai-app image: openai-app-image:latest ports: - containerPort: 80 9. Ensure a Smooth User Experience with AI Finally, it’s critical to think about how users will interact with the AI feature. Transparency : Let users know when they’re interacting with an AI model and what its limitations are. This transparency builds trust. Fail Gracefully : In case of a failed API call or confusing AI response, have a fallback ready—such as a templated response or escalation to human support. This ensures the AI adds value rather than creating frustration. 10. Leveraging LiteLLM for Seamless AI Integration For startups looking to efficiently integrate and manage multiple LLMs, LiteLLM offers a powerful framework that simplifies the AI integration process. Here’s how LiteLLM can help: Unified API Access : LiteLLM provides a consistent interface to interact with over 100 LLMs, including those from OpenAI, Anthropic, Hugging Face, and Azure. This simplifies switching between different AI models without altering your codebase, allowing you to be flexible and agile in your AI strategy. Proxy Server (LLM Gateway) : LiteLLM’s proxy server acts as a gateway for centralized AI management. It allows teams to monitor usage, implement guardrails, and customize logging and caching across projects, providing a comprehensive control layer that ensures both security and consistency. Python SDK : The LiteLLM Python SDK helps developers integrate AI functionalities directly into their applications with ease. It standardizes input and output formats, supports retry and fallback mechanisms, and ensures seamless integration with multiple LLM providers. Cost Tracking and Budgeting : LiteLLM enables startups to monitor and manage AI expenditures by tracking usage and setting budgets per project. This feature helps maintain cost efficiency, especially as your AI applications scale. Observability and Logging : With support for tools like Langfuse, Helicone, and PromptLayer, LiteLLM ensures you have comprehensive observability over your AI interactions. This makes debugging easier and helps you track performance metrics to continuously refine your AI integration. Streaming and Asynchronous Support : LiteLLM supports streaming responses and asynchronous operations, which is crucial for real-time AI applications that require high responsiveness. By leveraging LiteLLM, you can simplify the integration of AI capabilities, enhance scalability, and maintain cost-efficiency, making it an excellent choice for startups aiming to incorporate multiple LLMs into their tech stack. 11. Potential Challenges and Solutions in AI Integration Integrating AI into your startup comes with challenges. Here are some common pitfalls and strategies for overcoming them: Common AI Pitfalls Data Privacy Concerns : User data may be exposed during LLM interactions, creating privacy risks. Solution : Implement data anonymization techniques to strip out personally identifiable information (PII) before sending it to third-party AI models. Use encryption for data in transit and consider local processing where possible to limit exposure. Model Bias : AI LLMs can exhibit biases based on the data they were trained on, which may result in unintended consequences in your application. Solution : Conduct regular audits of model outputs to identify biases. Fine-tune AI models using curated datasets that reflect your users' diversity and values. Introduce human-in-the-loop systems to flag and correct problematic outputs. Scalability Issues : As your startup scales, increased API requests can lead to performance bottlenecks. Solution : Implement load balancing and use a combination of asynchronous processing and containerized deployments (e.g., Docker and Kubernetes) to ensure your infrastructure can scale efficiently with growing demand. Risk Management in AI Integration Model Failures : AI models can fail unpredictably, providing incorrect or incomplete responses. Solution : Use fallback strategies—if the AI model fails, implement default responses or escalate to human support. This ensures continuity in service and maintains user satisfaction. Maintaining Uptime : Relying on external LLM APIs can lead to outages that affect your product. Solution : Use redundant AI APIs from multiple providers. Incorporate a caching layer to serve responses for common queries even if the API is down. Compliance with Data Protection Regulations : Handling user data comes with legal responsibilities, including compliance with regulations like GDPR or CCPA. Solution : Work with legal experts to understand the specific data handling requirements in your region. Implement user consent mechanisms, anonymize data, and maintain a data retention policy that aligns with regulatory guidelines. Conclusion Integrating AI into your startup is an exciting journey that requires careful planning and technical rigor. Choosing the right AI model, setting up an efficient infrastructure, mitigating potential challenges, and ensuring high-quality user experience are key to success. With the power of OpenAI, Anthropic, LiteLLM, and other LLMs at your fingertips, you can create smarter, more engaging AI features that will set your startup apart. Fine is an AI coding tool that can help your startup win in the packed race to release new, AI-powered technology. Ship faster, resolve bugs and improve user satisfaction by adopting Fine as your AI coding agent. Start building today Try out the smoothest way to build, launch and manage an app Try for Free -> © Fine.dev - All rights reserved. Product Overview AI Workflows Pricing & Plans Changelog Blog Docs Company Press Terms & Conditions Privacy policy | 2026-01-13T08:49:36 |
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