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2026-01-13 08:47:33
2026-01-13 09:30:40
https://dev.to/makendrang
MakendranG - 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 Follow User actions MakendranG 404 bio not found Location Puducherry Joined Joined on  Apr 20, 2022 Email address makendran2015@gmail.com github website twitter website Work Site Reliability Engineer in MindTree 3 Frontend Challenge Completion Badge Awarded for completing at least one prompt in a Frontend Challenge. Thank you for participating! 💖 Got it Close 2025 Hacktoberfest Writing Challenge Completion Awarded for completing at least one prompt in the 2025 Hacktoberfest Writing Challenge. Thank you for sharing your open source story! 🎃✍️ Got it Close Google AI Studio Multi-Modal Challenge Completion Awarded for completing the Google AI Studio Multi-Modal Challenge by building and deploying an applet that showcases Gemini's multi-modal capabilities. Thank you for participating! 🤖 Got it Close Build Apps with Google AI Studio Awarded for completing DEV Education Track: "Build Apps with Google AI Studio" Got it Close Amazon Q Developer "Quack the Code" Challenge Completion Awarded for completing at least one prompt in the Amazon Q Developer "Quack the Code" Challenge Got it Close Three Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least three years. Got it Close 2025 WeCoded Challenge Completion Badge Awarded for completing at least one prompt in the WeCoded Challenge. Thank you for participating! 💻 Got it Close Pulumi Deploy and Document Challenge Completion Badge Awarded for completing at least one prompt in the Pulumi Deploy and Document Challenge. Thank you for participating! 💻 Got it Close Future Writing Challenge Completion Badge Awarded for completing at least one prompt in the Future Writing Challenge. Thank you for participating! 💻 Got it Close 2025 New Year Writing Challenge Completion Badge Awarded for completing at least one prompt in the New Year Writing challenge. Thank you for participating! Got it Close Agent.ai Challenge Completion Badge Awarded for completing at least one prompt in the Agent.ai Challenge. Thank you for participating! 💻 Got it Close GitHub Copilot 1-Day Build Challenge Completion Badge Awarded for completing at least one prompt in the GitHub Copilot 1-Day Build Challenge. Thank you for participating! 💻 Got it Close 2024 Hacktoberfest Writing Challenge Completion Badge Awarded for completing at least one prompt in the 2024 Hacktoberfest Writing Challenge. Thank you for participating! 💻 Got it Close Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two 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 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 Hacktoberfest 2022 Awarded for successful completion of the 2022 Hacktoberfest challenge. Got it Close 16 Week Writing Streak You are a writing star! You've written at least one post per week for 16 straight weeks. Congratulations! 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 8 Week Writing Streak The streak continues! You've written at least one post per week for 8 consecutive weeks. Unlock the 16-week badge next! Got it Close 4 Week Writing Streak You've posted at least one post per week for 4 consecutive weeks! Got it Close Show all 23 badges More info about @makendrang Organizations AWS Community Builders GitHub Repositories MakendranG 1 star 100_DAYS_OF_CODE Python • 2 stars Currently learning Python Post 169 posts published Comment 9 comments written Tag 17 tags followed AWS Certified Generative AI Developer – Professional in 2 Weeks (Part 1: Exam Overview & Foundations) MakendranG MakendranG MakendranG Follow Jan 11 AWS Certified Generative AI Developer – Professional in 2 Weeks (Part 1: Exam Overview & Foundations) # ai # machinelearning # aws # certification 6  reactions Comments Add Comment 16 min read Want to connect with MakendranG? Create an account to connect with MakendranG. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in AWS Certified Generative AI Developer – Professional in 2 Weeks (Part 2: Advanced Learning & Exam Prep) MakendranG MakendranG MakendranG Follow Jan 11 AWS Certified Generative AI Developer – Professional in 2 Weeks (Part 2: Advanced Learning & Exam Prep) # ai # aws # certification # machinelearning 1  reaction Comments Add Comment 13 min read AWS Certified Generative AI Developer – Professional: Exam Overview & Foundation Strategy (Part 1) MakendranG MakendranG MakendranG Follow Jan 11 AWS Certified Generative AI Developer – Professional: Exam Overview & Foundation Strategy (Part 1) # ai # machinelearning # aws # certification 6  reactions Comments Add Comment 7 min read I Built a Recipe App That Sees Your Ingredients with Google Gemini MakendranG MakendranG MakendranG Follow Nov 8 '25 I Built a Recipe App That Sees Your Ingredients with Google Gemini # google # gemini # ai 5  reactions Comments Add Comment 3 min read Frontend Challenge - Halloween Edition: The Smiling Jack-O'-Lantern 🎃 Frontend Challenge CSS Art Submission 🦇🎃 MakendranG MakendranG MakendranG Follow Nov 8 '25 Frontend Challenge - Halloween Edition: The Smiling Jack-O'-Lantern 🎃 # frontendchallenge # devchallenge # css 11  reactions Comments Add Comment 3 min read 🎃 My Hacktoberfest 2025 Journey: Discovering the Power of Documentation Hacktoberfest: Open Source Reflections MakendranG MakendranG MakendranG Follow Oct 26 '25 🎃 My Hacktoberfest 2025 Journey: Discovering the Power of Documentation # devchallenge # hacktoberfest # opensource 6  reactions Comments Add Comment 3 min read I Built an AI Meeting Assistant in One Day Using Kiro AI 🎤 MakendranG MakendranG MakendranG Follow Sep 14 '25 I Built an AI Meeting Assistant in One Day Using Kiro AI 🎤 # kiro # aws # productivity # javascript 5  reactions Comments Add Comment 4 min read ⚡ Transform Any Notes Into Visual + Audio Learning Aids with Google AI Studio Google AI Challenge Submission MakendranG MakendranG MakendranG Follow Sep 7 '25 ⚡ Transform Any Notes Into Visual + Audio Learning Aids with Google AI Studio # devchallenge # googleaichallenge # ai # gemini 23  reactions Comments Add Comment 3 min read 🚀 Acme Corp Intranet – A Clean & Responsive Office Homepage | DEV Challenge Frontend Challenge Holistic Webdev Submission MakendranG MakendranG MakendranG Follow Jul 19 '25 🚀 Acme Corp Intranet – A Clean & Responsive Office Homepage | DEV Challenge # devchallenge # frontendchallenge # css # javascript 9  reactions Comments Add Comment 2 min read FridgeChef: Turn Your Fridge Into a Recipe Goldmine with AI Education Track: Build Apps with Google AI Studio MakendranG MakendranG MakendranG Follow Jul 12 '25 FridgeChef: Turn Your Fridge Into a Recipe Goldmine with AI # deved # learngoogleaistudio # ai # gemini 24  reactions Comments 1  comment 4 min read Pride Month 2025: Love Wins 🏳️‍🌈 MakendranG MakendranG MakendranG Follow Jun 28 '25 Pride Month 2025: Love Wins 🏳️‍🌈 # devchallenge # frontendchallenge # css # javascript 7  reactions Comments Add Comment 7 min read 🌸 Unity in June – A CSS Art Tribute to Diverse Celebrations MakendranG MakendranG MakendranG Follow Jun 28 '25 🌸 Unity in June – A CSS Art Tribute to Diverse Celebrations # frontendchallenge # devchallenge # css 9  reactions Comments Add Comment 2 min read Retro Bliss: How I Built a Procedural Arcade Driver with a Little Help from Amazon Q MakendranG MakendranG MakendranG Follow May 11 '25 Retro Bliss: How I Built a Procedural Arcade Driver with a Little Help from Amazon Q # devchallenge # awschallenge # ai # webdev 19  reactions Comments Add Comment 3 min read 🚀 Fast Static Site Deployment on AWS with Pulumi YAML MakendranG MakendranG MakendranG Follow Apr 5 '25 🚀 Fast Static Site Deployment on AWS with Pulumi YAML # devchallenge # pulumichallenge # webdev # cloud 18  reactions Comments Add Comment 2 min read 💻 Instant AWS Infrastructure: Deploy a DynamoDB Table with Pulumi Inline Python MakendranG MakendranG MakendranG Follow Apr 5 '25 💻 Instant AWS Infrastructure: Deploy a DynamoDB Table with Pulumi Inline Python # devchallenge # pulumichallenge # github # api 16  reactions Comments Add Comment 2 min read 🚀 Deploying AWS Infrastructure with Pulumi: Secrets, Security & Automation! MakendranG MakendranG MakendranG Follow Mar 30 '25 🚀 Deploying AWS Infrastructure with Pulumi: Secrets, Security & Automation! # devchallenge # pulumichallenge # webdev # cloud 16  reactions Comments Add Comment 2 min read Breaking Stereotypes - Lessons Learned from Unconscious Bias in Tech MakendranG MakendranG MakendranG Follow Mar 15 '25 Breaking Stereotypes - Lessons Learned from Unconscious Bias in Tech # devchallenge # wecoded # dei # career 23  reactions Comments 1  comment 2 min read CertAI_Buddy: Your Personalized Certification Exam Companion MakendranG MakendranG MakendranG Follow Jan 26 '25 CertAI_Buddy: Your Personalized Certification Exam Companion # devchallenge # agentaichallenge # ai # machinelearning 10  reactions Comments 1  comment 3 min read Predicting 2025: The Dawn of Ambient AI and Sustainable Tech MakendranG MakendranG MakendranG Follow Jan 18 '25 Predicting 2025: The Dawn of Ambient AI and Sustainable Tech # devchallenge # newyearchallenge # future # ai 14  reactions Comments 2  comments 2 min read 2024 in Review: AWS Mastery, PartyRock Victory, and AI Innovation MakendranG MakendranG MakendranG Follow Jan 18 '25 2024 in Review: AWS Mastery, PartyRock Victory, and AI Innovation # devchallenge # newyearchallenge # career # aws 23  reactions Comments Add Comment 3 min read Building a Carbon Offset Calculator with GitHub Copilot: A Step-by-Step Guide MakendranG MakendranG MakendranG Follow Jan 18 '25 Building a Carbon Offset Calculator with GitHub Copilot: A Step-by-Step Guide # devchallenge # githubchallenge # webdev # ai 19  reactions Comments Add Comment 1 min read Contributing to Tech Assessment Knowledge: My Hacktoberfest 2024 Journey MakendranG MakendranG MakendranG Follow Nov 3 '24 Contributing to Tech Assessment Knowledge: My Hacktoberfest 2024 Journey # devchallenge # hacktoberfest # opensource 18  reactions Comments Add Comment 2 min read Validating AWS Lambda Code Using AWS Signer MakendranG MakendranG MakendranG Follow Jan 28 '23 Validating AWS Lambda Code Using AWS Signer # aws # tutorial # beginners # devops 2  reactions Comments Add Comment 3 min read Interact with Azure web applications using the Python SDK MakendranG MakendranG MakendranG Follow Dec 24 '22 Interact with Azure web applications using the Python SDK # azure # cloud # devops # tutorial 5  reactions Comments Add Comment 5 min read Memphis: Low-code real-time data processing platform MakendranG MakendranG MakendranG Follow Dec 21 '22 Memphis: Low-code real-time data processing platform # devops # cloud # aws # tutorial 3  reactions Comments Add Comment 6 min read The Essential Guide to 5 Key Importance of Cybersecurity MakendranG MakendranG MakendranG Follow Dec 16 '22 The Essential Guide to 5 Key Importance of Cybersecurity # beginners # devops # security # cloud 4  reactions Comments Add Comment 5 min read Learn Getting Started With Digitalocean Functions in Ten Minutes MakendranG MakendranG MakendranG Follow Dec 11 '22 Learn Getting Started With Digitalocean Functions in Ten Minutes # tutorial # beginners # devops # digitalocean 3  reactions Comments Add Comment 4 min read Configuring an Azure function behind a NAT gateway to restrict outgoing IP addresses MakendranG MakendranG MakendranG Follow Dec 6 '22 Configuring an Azure function behind a NAT gateway to restrict outgoing IP addresses # azure # beginners # tutorial # devops 5  reactions Comments Add Comment 7 min read Overview of Pulumi and Its Challenge Tutorial 101: The Essential Guide MakendranG MakendranG MakendranG Follow Dec 3 '22 Overview of Pulumi and Its Challenge Tutorial 101: The Essential Guide # cloud # aws # beginners # tutorial 6  reactions Comments Add Comment 10 min read A Fascinating Behind-the-Scenes Look at How I Built a Harness CI Pipeline MakendranG MakendranG MakendranG Follow Nov 29 '22 A Fascinating Behind-the-Scenes Look at How I Built a Harness CI Pipeline # devops # beginners # tutorial # cloud 6  reactions Comments Add Comment 6 min read How Top 17 New Technology Trends for 2022 Saved My Life MakendranG MakendranG MakendranG Follow Nov 28 '22 How Top 17 New Technology Trends for 2022 Saved My Life # beginners # productivity # devops # cloud 3  reactions Comments 1  comment 9 min read The Beginner's Guide to 25 Best Developer Tools You Can’t Do Without MakendranG MakendranG MakendranG Follow Nov 25 '22 The Beginner's Guide to 25 Best Developer Tools You Can’t Do Without # beginners # webdev # productivity # devops 23  reactions Comments 1  comment 17 min read 12 Unbelievable Things You Never Knew About What to Do When You’re Stuck on a Coding Problem MakendranG MakendranG MakendranG Follow Nov 25 '22 12 Unbelievable Things You Never Knew About What to Do When You’re Stuck on a Coding Problem # beginners # productivity # webdev # devops 11  reactions Comments 4  comments 8 min read A Deep Dive into Introduction to Computer Networking MakendranG MakendranG MakendranG Follow Nov 22 '22 A Deep Dive into Introduction to Computer Networking # beginners # security # cloud # networking 4  reactions Comments Add Comment 9 min read The Fascinating Science of 9 Tips to Become a Software Developer MakendranG MakendranG MakendranG Follow Nov 20 '22 The Fascinating Science of 9 Tips to Become a Software Developer # beginners # programming # productivity # career 9  reactions Comments Add Comment 5 min read 5 Powerful Habits to Master for Success in Strengthen Your PROFESSIONAL PORTFOLIO MakendranG MakendranG MakendranG Follow Nov 20 '22 5 Powerful Habits to Master for Success in Strengthen Your PROFESSIONAL PORTFOLIO # beginners # programming # productivity # career 10  reactions Comments Add Comment 1 min read What is Azure Container Registry? MakendranG MakendranG MakendranG Follow Nov 16 '22 What is Azure Container Registry? # azure # beginners # tutorial # devops 7  reactions Comments Add Comment 2 min read Nhost: The Perfect Backend 101: The Essential Guide MakendranG MakendranG MakendranG Follow Nov 13 '22 Nhost: The Perfect Backend 101: The Essential Guide # beginners # tutorial # devops # opensource 5  reactions Comments Add Comment 9 min read What is Amazon Time Sync public NTP? MakendranG MakendranG MakendranG Follow for AWS Community Builders Nov 13 '22 What is Amazon Time Sync public NTP? # aws # beginners # tutorial # productivity 10  reactions Comments Add Comment 4 min read What is Amazon Time Sync public NTP? MakendranG MakendranG MakendranG Follow Nov 22 '22 What is Amazon Time Sync public NTP? # aws # beginners # tutorial # productivity 2  reactions Comments Add Comment 4 min read Everything You Need to Know About Insights From the AZ-104 Bootcamp Session - Week 3 MakendranG MakendranG MakendranG Follow Nov 11 '22 Everything You Need to Know About Insights From the AZ-104 Bootcamp Session - Week 3 # azure # webdev # beginners # tutorial 5  reactions Comments 4  comments 4 min read Continuous integration and deployment with AWS code services MakendranG MakendranG MakendranG Follow for AWS Community Builders Nov 11 '22 Continuous integration and deployment with AWS code services 6  reactions Comments Add Comment 4 min read Everything You Need to Know About Insights From the AZ-104 Bootcamp Session - Week 2 MakendranG MakendranG MakendranG Follow Nov 9 '22 Everything You Need to Know About Insights From the AZ-104 Bootcamp Session - Week 2 # azure # tutorial # beginners # productivity 4  reactions Comments Add Comment 3 min read Configuring a Static Website with S3 & CloudFront Explained MakendranG MakendranG MakendranG Follow Nov 9 '22 Configuring a Static Website with S3 & CloudFront Explained # aws # webdev # beginners # tutorial 5  reactions Comments Add Comment 4 min read The Essential Guide to Overview and Benefits of Gateway Load Balancer MakendranG MakendranG MakendranG Follow Nov 4 '22 The Essential Guide to Overview and Benefits of Gateway Load Balancer # azure # devops # beginners # cloud 7  reactions Comments Add Comment 4 min read A Deep Dive Into Host a Web Application With Azure App Service MakendranG MakendranG MakendranG Follow Nov 3 '22 A Deep Dive Into Host a Web Application With Azure App Service # azure # beginners # webdev # tutorial 6  reactions Comments Add Comment 5 min read Validating AWS Lambda Code Using AWS Signer MakendranG MakendranG MakendranG Follow for AWS Community Builders Oct 31 '22 Validating AWS Lambda Code Using AWS Signer # aws # tutorial # beginners # devops 9  reactions Comments Add Comment 3 min read Why is everyone building on GitHub? MakendranG MakendranG MakendranG Follow Oct 31 '22 Why is everyone building on GitHub? # beginners # opensource # tutorial # productivity 18  reactions Comments 3  comments 5 min read Contributing to Open-Source: My HacktoberFest Experience MakendranG MakendranG MakendranG Follow Oct 31 '22 Contributing to Open-Source: My HacktoberFest Experience # beginners # opensource # tutorial # productivity 7  reactions Comments Add Comment 4 min read Deploying PHP applications using AWS OpsWorks MakendranG MakendranG MakendranG Follow Oct 30 '22 Deploying PHP applications using AWS OpsWorks 2  reactions Comments Add Comment 2 min read Deploy PHP applications using AWS OpsWorks MakendranG MakendranG MakendranG Follow for AWS Community Builders Oct 28 '22 Deploy PHP applications using AWS OpsWorks # aws # tutorial # beginners # productivity 2  reactions Comments Add Comment 2 min read Difference between Cluster Autoscaler & Karpenter MakendranG MakendranG MakendranG Follow Oct 27 '22 Difference between Cluster Autoscaler & Karpenter # kubernetes # aws # beginners # opensource 8  reactions Comments 1  comment 3 min read Introduction to Karpenter MakendranG MakendranG MakendranG Follow Oct 27 '22 Introduction to Karpenter # beginners # productivity # devops # kubernetes 4  reactions Comments Add Comment 2 min read Centralized Operations on AWS by using AWS System Manager - Part 2 MakendranG MakendranG MakendranG Follow Oct 26 '22 Centralized Operations on AWS by using AWS System Manager - Part 2 # devops # aws # beginners # tutorial 5  reactions Comments Add Comment 3 min read Centralized Operations on AWS by using AWS System Manager - Part 1 MakendranG MakendranG MakendranG Follow Oct 26 '22 Centralized Operations on AWS by using AWS System Manager - Part 1 # devops # aws # beginners # tutorial 6  reactions Comments Add Comment 3 min read Conquer Your Fear from a Failed Job Interview in 7 Simple Steps MakendranG MakendranG MakendranG Follow Oct 25 '22 Conquer Your Fear from a Failed Job Interview in 7 Simple Steps # beginners # career # productivity # failure 3  reactions Comments Add Comment 2 min read Centralized Management by using AWS System Manager MakendranG MakendranG MakendranG Follow for AWS Community Builders Oct 24 '22 Centralized Management by using AWS System Manager # beginners # tutorial # aws # devops 8  reactions Comments 2  comments 5 min read Get Started with AWS Config Rules and Remediation MakendranG MakendranG MakendranG Follow Oct 21 '22 Get Started with AWS Config Rules and Remediation # aws # devops # tutorial # beginners 3  reactions Comments Add Comment 3 min read How to Deploy Website Using Hugo on AWS Amplify in Ten Minutes MakendranG MakendranG MakendranG Follow Oct 21 '22 How to Deploy Website Using Hugo on AWS Amplify in Ten Minutes # aws # beginners # webdev # tutorial 6  reactions Comments Add Comment 9 min read Getting Started with AWS Config Rules and Remediation MakendranG MakendranG MakendranG Follow for AWS Community Builders Oct 19 '22 Getting Started with AWS Config Rules and Remediation # aws # beginners # tutorial # productivity 4  reactions Comments Add Comment 3 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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2026-01-13T08:49:43
https://dev.to/asim_shaikh_02599ff124bea/building-an-adaptive-learning-agent-using-kiro-ide-agentic-ai-edtech-2c16
Building an Adaptive Learning Agent Using Kiro IDE- agentic-ai-edtech - 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 Asim Shaikh Posted on Dec 30, 2025 Building an Adaptive Learning Agent Using Kiro IDE- agentic-ai-edtech # aws # kiroide # ai # hackathon Introduction Most intelligent systems today depend on large models, cloud infrastructure, and complex pipelines. But what if intelligence could be designed directly into the user interface through behavior, feedback, and iteration? This blog documents my journey of building an adaptive learning assistant as an MVP and how Kiro IDE played a central role in experimenting with agentic behavior, refining logic, and shaping the system design. Rather than treating Kiro as just a coding tool, I used it as a space for exploration, iteration, and system thinking. The Idea The core idea of the project is simple: Observe user behavior → Interpret learning state → Adapt the interface in real time. Instead of delivering static content, the system continuously responds to how the learner interacts with it. Scroll speed, time spent on sections, hesitation, and navigation patterns become signals that inform how the learning experience should change. This transforms a passive platform into something closer to a tutor — not by adding more features, but by making the system responsive. Why This Is an Agentic System The system behaves like a simple agent: It perceives signals from the user. It decides the user’s state using rules and thresholds. It acts by modifying the interface or content. This loop runs continuously. The agent doesn’t aim for perfection — it aims for responsiveness. Over time, its behavior becomes more refined through iteration. How Kiro IDE Fits Into This Kiro IDE is not just where the code lives — it’s where the system evolves. I used Kiro to: Rapidly prototype different logic flows. Experiment with threshold values for classification. Simulate user behavior and observe system reactions. Debug edge cases where behavior was misinterpreted. Refactor the system into clearer agent loops. Because the project is exploratory in nature, Kiro’s fast feedback cycle made it possible to treat development as a design process, not just implementation. Kiro became the environment where ideas turned into behavior. Challenges (and Why They Matter) The biggest challenge is not technical — it’s conceptual. Human behavior is noisy. One person scrolls fast because they understand; another scrolls fast because they are confused. Designing logic that handles ambiguity gracefully is an ongoing process. Rather than trying to make the system “perfect,” the goal is to make it adaptive, forgiving, and supportive. Kiro makes this possible by enabling rapid iteration without friction. Why This Fits the Kiro IDE Track This project aligns with the Kiro IDE track because: It is experimental and iterative by nature. It focuses on behavior-driven systems rather than static code. It requires constant tuning, testing, and refinement. It treats development as a feedback loop, just like the agent itself. Kiro is not just a tool used — it is part of the system’s creative process. Conclusion This project is still evolving, but it demonstrates a powerful idea: intelligence can emerge not just from models and data, but from thoughtful system design, responsiveness, and iteration. Kiro IDE enables this way of building — fast, flexible, and exploratory — making it the perfect environment for agentic and adaptive system design. link to project 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 Asim Shaikh Follow Joined Dec 30, 2025 Trending on DEV Community Hot How to Crack Any Software Developer Interview in 2026 (Updated for AI & Modern Hiring) # softwareengineering # programming # career # interview Why “AI tools” fail: no workflow, no outcome # webdev # ai # beginners # devops 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
2026-01-13T08:49:43
https://dev.to/t/kiroide
Kiroide - 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 # kiroide Follow Hide Create Post Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Building an Adaptive Learning Agent Using Kiro IDE- agentic-ai-edtech Asim Shaikh Asim Shaikh Asim Shaikh Follow Dec 30 '25 Building an Adaptive Learning Agent Using Kiro IDE- agentic-ai-edtech # aws # kiroide # ai # hackathon Comments Add Comment 2 min read loading... trending guides/resources Building an Adaptive Learning Agent Using Kiro IDE- agentic-ai-edtech 💎 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
2026-01-13T08:49:43
https://dev.to/t/backend/page/8
Backend Page 8 - 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. 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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 # backend Follow Hide Desenvolvimento do lado do servidor, APIs, bancos de dados e logica de negocios. Create Post Older #backend posts 5 6 7 8 9 10 11 12 13 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu WebForms.php has been Updated to WebForms Core 2 Elanat Framework Elanat Framework Elanat Framework Follow Dec 26 '25 WebForms.php has been Updated to WebForms Core 2 # php # laravel # backend # webformscore Comments Add Comment 3 min read 🧠 Going Full Stack: Building the Backend & REST API Karan Karan Karan Follow Dec 26 '25 🧠 Going Full Stack: Building the Backend & REST API # mongodb # express # backend # restapi 1  reaction Comments Add Comment 2 min read Consultas geoespaciais com PostGIS Lucas Pereira de Souza Lucas Pereira de Souza Lucas Pereira de Souza Follow Dec 25 '25 Consultas geoespaciais com PostGIS # database # backend # postgres # tutorial Comments Add Comment 8 min read The DSA Dependency Graph: A Logical Roadmap from Arrays to DP shubham khatik shubham khatik shubham khatik Follow Dec 25 '25 The DSA Dependency Graph: A Logical Roadmap from Arrays to DP # dsa # beginners # backend # webdev Comments Add Comment 2 min read [System Design] Why Is Your App "Overselling"? A Founder's First Lesson in Concurrency AaronWuBuilds AaronWuBuilds AaronWuBuilds Follow Jan 9 [System Design] Why Is Your App "Overselling"? A Founder's First Lesson in Concurrency # systemdesign # startup # webdev # backend Comments Add Comment 4 min read 👉 My Spring Boot App Kept Crashing… Until I Fixed Exception Handling Shashwath S H Shashwath S H Shashwath S H Follow Jan 8 👉 My Spring Boot App Kept Crashing… Until I Fixed Exception Handling # springboot # backend # java # exceptionhandling 2  reactions Comments 4  comments 2 min read What Did 2025 Bring Us, and What Trends Lie Ahead? OneEntry OneEntry OneEntry Follow Dec 25 '25 What Did 2025 Bring Us, and What Trends Lie Ahead? # productivity # webdev # frontendchallenge # backend Comments Add Comment 5 min read Routing with Controllers, Schemas & Auto Docs | Build APIs with Litestar #2. Ssali Jonathan Ssali Jonathan Ssali Jonathan Follow Dec 25 '25 Routing with Controllers, Schemas & Auto Docs | Build APIs with Litestar #2. # python # api # backend # litestar Comments Add Comment 1 min read Chatbot Token Management: Optimize OpenAI API Costs Chatboq Chatboq Chatboq Follow Dec 25 '25 Chatbot Token Management: Optimize OpenAI API Costs # typescript # prisma # node # backend 1  reaction Comments Add Comment 7 min read I Spent Years as a Backend Engineer With Almost No Work Keval Rakholiya Keval Rakholiya Keval Rakholiya Follow Dec 24 '25 I Spent Years as a Backend Engineer With Almost No Work # backend # productivity Comments Add Comment 2 min read Next.js for Backend Developers: Understanding the App Router Without the Hype prateekshaweb prateekshaweb prateekshaweb Follow Dec 25 '25 Next.js for Backend Developers: Understanding the App Router Without the Hype # nextjs # javascript # architecture # backend Comments Add Comment 3 min read Designing a dispute-resolution state machine for adversarial user outcomes azender1@yahoo.com azender1@yahoo.com azender1@yahoo.com Follow Dec 28 '25 Designing a dispute-resolution state machine for adversarial user outcomes # discuss # backend # architecture Comments Add Comment 1 min read I Added Koa Support to My Universal Boilerplate (And It Was Tricky) Adam Golan Adam Golan Adam Golan Follow Dec 24 '25 I Added Koa Support to My Universal Boilerplate (And It Was Tricky) # backend # koa # architecture # typescript Comments Add Comment 2 min read EP 6 - Don't Kill Flaky APIs: The Art of Resilient Retries Hrishikesh Dalal Hrishikesh Dalal Hrishikesh Dalal Follow Dec 28 '25 EP 6 - Don't Kill Flaky APIs: The Art of Resilient Retries # backend # sre # webdev Comments Add Comment 1 min read GO-FaaS (v0.4.0): Serverless function runtime 邱敬幃 Pardn Chiu 邱敬幃 Pardn Chiu 邱敬幃 Pardn Chiu Follow Dec 28 '25 GO-FaaS (v0.4.0): Serverless function runtime # backend # go # pardnchiu Comments Add Comment 1 min read Integrating Resend with React Email in a Better T Stack Monorepo (Next JS & Hono backend with Better Auth) Reuben Wedson Reuben Wedson Reuben Wedson Follow Dec 24 '25 Integrating Resend with React Email in a Better T Stack Monorepo (Next JS & Hono backend with Better Auth) # react # typescript # backend # resend 2  reactions Comments Add Comment 4 min read Chatbot Queue Management: RabbitMQ vs Apache Kafka Chatboq Chatboq Chatboq Follow Dec 24 '25 Chatbot Queue Management: RabbitMQ vs Apache Kafka # api # backend # architecture # systemdesign Comments Add Comment 9 min read Comunidades de desenvolvedores (JavaScript,TypeScript) Lucas Pereira de Souza Lucas Pereira de Souza Lucas Pereira de Souza Follow Dec 24 '25 Comunidades de desenvolvedores (JavaScript,TypeScript) # community # backend # node # javascript Comments Add Comment 6 min read Redis Threading Model: Why “Single-Threaded” Is Misunderstood Ricky512227 Ricky512227 Ricky512227 Follow Dec 24 '25 Redis Threading Model: Why “Single-Threaded” Is Misunderstood # backend # redis # performance # threrading Comments Add Comment 3 min read Why I Cache External API Data Instead of Calling It Every Time yusuf yonturk yusuf yonturk yusuf yonturk Follow Dec 25 '25 Why I Cache External API Data Instead of Calling It Every Time # backend # api # architecture # performance Comments Add Comment 2 min read What is Nginx? Moein Kia Moein Kia Moein Kia Follow Dec 24 '25 What is Nginx? # nginx # devops # backend # webserver 1  reaction Comments Add Comment 11 min read GO-FaaS (v0.4.0): 自部署 FaaS 系統 邱敬幃 Pardn Chiu 邱敬幃 Pardn Chiu 邱敬幃 Pardn Chiu Follow Dec 28 '25 GO-FaaS (v0.4.0): 自部署 FaaS 系統 # backend # go # pardnchiu Comments Add Comment 1 min read How to Change a Column Datatype Without Affecting Existing Users Postgresql ISRAEL ISRAEL ISRAEL Follow Dec 23 '25 How to Change a Column Datatype Without Affecting Existing Users Postgresql # postgres # node # backend # database Comments Add Comment 3 min read Abstract Repository Combining Two/Multiple Repositories (OrderDocumentRepo) Akkarapon Phikulsri Akkarapon Phikulsri Akkarapon Phikulsri Follow Jan 8 Abstract Repository Combining Two/Multiple Repositories (OrderDocumentRepo) # architecture # backend # design Comments Add Comment 1 min read Medical Service API - v1.0 Alexander Attoh Alexander Attoh Alexander Attoh Follow Dec 23 '25 Medical Service API - v1.0 # api # backend # java Comments Add Comment 5 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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2026-01-13T08:49:43
https://dev.to/t/backend/page/3
Backend Page 3 - 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 # backend Follow Hide Desenvolvimento do lado do servidor, APIs, bancos de dados e logica de negocios. Create Post Older #backend posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Don't Trust the Client: How I Hacked My Own Coupon System Aditya Aditya Aditya Follow Jan 6 Don't Trust the Client: How I Hacked My Own Coupon System # backend # security # webdev Comments Add Comment 2 min read System Design in 2026: The Complete Guide (18,500 words) Akhilesh Akhilesh Akhilesh Follow Jan 7 System Design in 2026: The Complete Guide (18,500 words) # systemdesign # softwareengineering # backend # engineering 1  reaction Comments Add Comment 2 min read I built an auth backend for my own app — then tried selling it to see if it works Geeta Geeta Geeta Follow Jan 7 I built an auth backend for my own app — then tried selling it to see if it works # backend # learning # authentication # mobile Comments Add Comment 2 min read 🔥 Laravel Query Gate v1.2.0 is AWESOME Jefferson Silva Jefferson Silva Jefferson Silva Follow Jan 6 🔥 Laravel Query Gate v1.2.0 is AWESOME # laravel # php # api # backend Comments Add Comment 2 min read Designing for Failure: Building Reliable Crypto-to-Utility Payments with Provider Failover Yusuf Adeniyi Yusuf Adeniyi Yusuf Adeniyi Follow Jan 8 Designing for Failure: Building Reliable Crypto-to-Utility Payments with Provider Failover # architecture # fintech # backend # systemdesign 2  reactions Comments 2  comments 3 min read Why allocs/op stopped being a good Go performance signal Pavel Sanikovich Pavel Sanikovich Pavel Sanikovich Follow Jan 11 Why allocs/op stopped being a good Go performance signal # go # performance # programming # backend 1  reaction Comments 1  comment 2 min read How I Think About Backend Engineering as a Student Kushal Sai Kushal Sai Kushal Sai Follow Jan 7 How I Think About Backend Engineering as a Student # backend # softwareengineering # go # webdev Comments Add Comment 3 min read @RequestBody in SpringBoot Er. Bhupendra Er. Bhupendra Er. Bhupendra Follow Jan 7 @RequestBody in SpringBoot # backend # java # springboot Comments Add Comment 4 min read ZinTrust: a TypeScript backend framework for structure without decorators zintrust Zin zintrust Zin zintrust Zin Follow Jan 7 ZinTrust: a TypeScript backend framework for structure without decorators # typescript # node # backend # opensource Comments Add Comment 2 min read MongoDB Indexing Guidelines: Why Your Index Exists but Is Never Used Shubham Ravani Shubham Ravani Shubham Ravani Follow Jan 7 MongoDB Indexing Guidelines: Why Your Index Exists but Is Never Used # mongodb # backend # performance # database Comments Add Comment 3 min read Kodkod: Production Backends in Seconds Sibil Sarjam Soren Sibil Sarjam Soren Sibil Sarjam Soren Follow Jan 7 Kodkod: Production Backends in Seconds # webdev # node # typescript # backend Comments Add Comment 1 min read TCP Doesn’t Know What a Message Is Dikshant Thakur Dikshant Thakur Dikshant Thakur Follow Jan 7 TCP Doesn’t Know What a Message Is # networking # backend # node # systems Comments Add Comment 4 min read Building a Production-Ready Rate Limiter with Redis & Lua in NestJS (Part 1) Ajao Yussuf Ajao Yussuf Ajao Yussuf Follow Jan 7 Building a Production-Ready Rate Limiter with Redis & Lua in NestJS (Part 1) # nestjs # redis # backend # typescript 1  reaction Comments Add Comment 9 min read @Controller vs @RestController Er. Bhupendra Er. Bhupendra Er. Bhupendra Follow Jan 7 @Controller vs @RestController # api # backend # java # springboot Comments Add Comment 2 min read DocWire SDK in 2025 – Architecture, AI Pipelines, and Document Processing in Modern C++ Krzysztof Nowicki Krzysztof Nowicki Krzysztof Nowicki Follow Jan 7 DocWire SDK in 2025 – Architecture, AI Pipelines, and Document Processing in Modern C++ # cpp # softwareengineering # backend # ai Comments Add Comment 1 min read Dart Server-Side in 2026: An Introduction to Dart Frog 🐸 Samuel Adekunle Samuel Adekunle Samuel Adekunle Follow Jan 6 Dart Server-Side in 2026: An Introduction to Dart Frog 🐸 # dart # backend # dartfrog # techwithsam 5  reactions Comments Add Comment 3 min read Why I Chose Go for Backend Engineering (Pros, Cons, and Honest Trade-offs) Kushal Sai Kushal Sai Kushal Sai Follow Jan 7 Why I Chose Go for Backend Engineering (Pros, Cons, and Honest Trade-offs) # systems # backend # learning # go 1  reaction Comments Add Comment 4 min read Kubernetes 1.35: In-Place Pod Resize is GA — Scale Vertically Without Restarting Grego Grego Grego Follow Jan 6 Kubernetes 1.35: In-Place Pod Resize is GA — Scale Vertically Without Restarting # kubernetes # backend Comments Add Comment 5 min read VK Music Bot API: Open Source Backend for VK Music in Telegram Traft Traft Traft Follow Jan 5 VK Music Bot API: Open Source Backend for VK Music in Telegram # showdev # api # backend # opensource 1  reaction Comments Add Comment 2 min read Performance Degradation Due to Inefficient Apex / ORM Usage (salesforce) Selavina B Selavina B Selavina B Follow Jan 7 Performance Degradation Due to Inefficient Apex / ORM Usage (salesforce) # backend # codequality # database # performance Comments Add Comment 3 min read Designing APIs That Are Hard to Misuse Nilesh Raut Nilesh Raut Nilesh Raut Follow Jan 10 Designing APIs That Are Hard to Misuse # backend # architecture # api # design 15  reactions Comments 2  comments 3 min read 🔍 JPA, Hibernate, JDBC… I Was Confused Until This Finally Clicked Shashwath S H Shashwath S H Shashwath S H Follow Jan 11 🔍 JPA, Hibernate, JDBC… I Was Confused Until This Finally Clicked # springboot # java # backend # hibernate 1  reaction Comments Add Comment 2 min read The 15-Minute Goroutine Leak Triage: Two Dumps, One Diff, Zero Guessing Voskan Voskanyan Voskan Voskanyan Voskan Voskanyan Follow Jan 6 The 15-Minute Goroutine Leak Triage: Two Dumps, One Diff, Zero Guessing # go # backend # microservices # programming Comments Add Comment 5 min read # How Express.js Works Behind the Scenes: An Inside Look sudip khatiwada sudip khatiwada sudip khatiwada Follow Jan 5 # How Express.js Works Behind the Scenes: An Inside Look # webdev # programming # backend # node Comments Add Comment 3 min read Why HMAC Is the Right Choice for Webhook Security (and Why Spubhi Makes It Simple) Spubhi Spubhi Spubhi Follow Jan 5 Why HMAC Is the Right Choice for Webhook Security (and Why Spubhi Makes It Simple) # api # backend # security Comments Add Comment 3 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. 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
2026-01-13T08:49:43
https://docs.devcycle.com/platform/security-and-guardrails/feature-obfuscation
Feature Obfuscation | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up Home Getting Started Essentials DevCycle Overview Key Features System Architecture Feature Hierarchy Feature Types Platform Feature Flags Experimentation Account Management Security and Guardrails Approval Workflows Audit Log Custom Property Schemas Feature Obfuscation Roles & Permissions SDK Visibility Variable Schemas Testing and QA Extras Examples Platform Security and Guardrails Feature Obfuscation On this page Feature Obfuscation Feature flags are often used to hide upcoming features before release. Normally, not showing the feature on a UI is enough to conceal it from users. However, in some cases it may be important to ensure that no trace of the feature can be found in the code that is shipped to users. This is particularly important on the web, where end-users can easily see all the source code for the page. Even when the code is obfuscated, any strings containing text from the new feature will still be present in the bundle. From that, intrepid users can often infer the nature of a feature they can't access, which may lead to sensitive or strategic information being leaked. To prevent this, DevCycle supports a feature allowing you to obfuscate all the Variable keys used in your code in Web platforms (React, Next.js, Javascript etc.) to keep their names private. Next.js users can also take advantage of our SDK's Conditional Deferred Rendering feature, which will strip out any source code for features the user isn't eligible for, reducing bundle size while also keeping the feature's details private. To use this feature, follow the setup guide below: Requirements ​ This feature is only available for web platforms. It is not available for mobile or server-side SDKs. The following SDKs support obfuscation: Javascript React Next.js The unobfuscated data will still be available via the mobile and server SDK tokens. If you have a need for obfuscation on mobile, let us know in the community discord. Using the feature requires use of the DevCycle CLI . Follow the setup guide in the CLI documentation to install it and initialize in your repository. Setup ​ In order to use obfuscation, the first step is to pass the enableObfuscation setting in your DevCycle SDK initialization options. This process will vary by SDK, but here is an example for React: import { withDevCycleProvider } from '@devcycle/react-client-sdk' function App ( ) { return < TheRestofYourApp /> } export default withDevCycleProvider ( { sdkKey : '<DEVCYCLE_CLIENT_SDK_KEY>' , // add this setting options : { enableObfuscation : true } } ) ( App , ) With obfuscation enabled, you can use the DevCycle CLI to generate a set of constants which correspond to your project's Variable keys. To do so, run the following command: dvc generate types --obfuscate If using React or Next.js, add the --react flag: dvc generate types --obfuscate --react The result will be a generated file containing type definitions and constants for all your project's Variables, with the keys obfuscated. The obfuscation process is done automatically using a key stored in your project's data, which is only known to the DevCycle Management API and the DevCycle CLI. An example of the generated file output you might expect is shown below.: // devcycleTypes.ts /* key: my-first-variable created by: Sally Smith created on: 2024-03-01 */ export const MY_FIRST_VARIABLE = 'dvc_obfs_3499747d616cfb0ac00bda26273e3577d5508f1ecaf2f1f07a2546' as ObfuscatedKey < 'my-first-variable' > /* key: my-second-variable created by: Joe Shmo created on: 2024-03-01 */ export const MY_SECOND_VARIABLE = 'dvc_obfs_359f6c73757fe30a9950ce39333c2329915a900893b3fbf164' as ObfuscatedKey < 'my-second-variable' > info The generated file also includes Typescript definitions of each Variable, which allows you to make your DevCycle usage type-safe by enforcing the correct datatype for each Variable. When using an enum schema , the types will also enforce that one of the allowed values is used. For more information, see the documentation for Typescript with the Javascript SDK The names of the constants will be automatically determined based on each Variable's key. If two Variable keys resolve to the same constant name, the CLI will append a number to the end of the constant name to avoid conflicts. The original Variable key will be preserved in the comment above the constant, so you can identify one constant from another. Now, in each place where a DevCycle Variable is evaluated, you can use the generated constants in place of direct strings. The constants have been automatically assigned to the obfuscated keys, so there will be no plain strings containing your Variable keys in code. For example: Before: import { useVariableValue } from '@devcycle/react-client-sdk' function MyComponent ( ) { const myFirstVariable = useVariableValue ( 'my-first-variable' , false ) const mySecondVariable = useVariableValue ( 'my-second-variable' , false ) return < div > { myFirstVariable } { mySecondVariable } </ div > } After: import { MY_FIRST_VARIABLE , MY_SECOND_VARIABLE , useVariableValue } from './devcycle' function MyComponent ( ) { const myFirstVariable = useVariableValue ( MY_FIRST_VARIABLE , false ) const mySecondVariable = useVariableValue ( MY_SECOND_VARIABLE , false ) return < div > { myFirstVariable } { mySecondVariable } </ div > } As long as your production build process is set up to uglify your production code, any trace of the original DevCycle Variable names will disappear. That's it! Requiring Obfuscation ​ As an extra measure of safety, you can require obfuscation in your DevCycle project settings. This will prevent requests for SDK configuration using a client SDK key from obtaining unobfuscated keys, by requiring that the SDK is initialized with "enableObfuscation". It is recommended to require obfuscation when creating a new DevCycle project. If you are adding obfuscation to an existing project, you may want to leave this setting off until you have updated your code to use obfuscated keys, otherwise existing applications will no longer be able to receive a DevCycle configuration. Development Workflow and CI ​ When using obfuscation, it is necessary to ensure that the generated constants are kept up to date with your project's set of possible Variable keys. There are different ways to accomplish this depending on your specific workflow, but in general we recommend committing the generated devcycleTypes file to source control and regenerating the file when a new Variable is added to DevCycle. To accomplish this more automatically, you can run the generator as part of a command which builds and runs your code in a local environment. This will ensure that each time you run the local code, the file is updated with the latest Variables. Archiving Variables ​ When you archive a Variable in DevCycle, it will no longer appear in the generated output from the CLI. Make sure that Variables are no longer used in your code before archiving. Conditional Deferred Rendering ​ Next.js users can take this a step further by also withholding any application source code that won't be used when a user is ineligible for a feature. This can improve page load performance while also hiding implementation details of features from users who shouldn't see them. To use this feature, follow the documentation for Conditional Deferred Rendering . When passing the Variable key to be evaluated, make sure to pass the obfuscated constant generated by the CLI. Edit this page Last updated on Jan 9, 2026 Previous Custom Property Schemas Next Roles & Permissions Requirements Setup Requiring Obfuscation Development Workflow and CI Archiving Variables Conditional Deferred Rendering DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://future.forem.com/new/privacy
New Post - Future 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 Future Close Join the Future Future is a community of 3,676,891 amazing enthusiasts Continue with Apple Continue with Google Continue with Facebook Continue with Forem Continue with GitHub 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 Future? 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 Future — News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Home About Contact 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 . Future © 2025 - 2026. Stay on the cutting edge, and shape tomorrow Log in Create account
2026-01-13T08:49:43
https://twitter.com/tlakomy
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2026-01-13T08:49:43
https://dev.to/andrewbrown
Andrew Brown 🇨🇦 - 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. 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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 Andrew Brown 🇨🇦 I make free cloud certification courses Location Schreiber Joined Joined on  Oct 19, 2018 Email address andrew@exampro.co Personal website https://www.exampro.co github website twitter website Education Starfleet Academy Work CEO at ExamPro 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. 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Got it Close Top 7 Awarded for having a post featured in the weekly "must-reads" list. 🙌 Got it Close 4 Week Writing Streak You've posted at least one post per week for 4 consecutive weeks! Got it Close DEV Contributor Awarded for contributing code or technical docs/guidelines to the Forem open source project Got it Close Show all 19 badges More info about @andrewbrown Organizations ExamPro AWS Heroes AWS Community Builders 100DaysOfCloud GitHub Repositories pipezania Pipezania is a pipe puzzle game built with Phaser, Gulp, CoffeeScript and Sinatra JavaScript • 20 stars swap-n-pop JavaScript • 46 stars Skills/Languages Ruby on Rails, AWS, Postgres, CyberSecurity Currently learning 6502 Assembly Currently hacking on https://github.com/omenking/swap-n-pop Available for If you want to test out my AWS personal study material (ExamPro) If you're interested in co-writing a technical article. Post 62 posts published Comment 989 comments written Tag 17 tags followed Post-Hackathon Advice: Turning Lemons 🍋 into Lemonade 🍹 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jan 15 '23 Post-Hackathon Advice: Turning Lemons 🍋 into Lemonade 🍹 # discuss # ai # softwaredevelopment # productivity 5  reactions Comments 2  comments 1 min read Want to connect with Andrew Brown 🇨🇦? Create an account to connect with Andrew Brown 🇨🇦. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Cruddur - The not so great twitter clone using Ruby Sinatra + React + GCP CloudRun + MongoDB Atlas + Terraform Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Dec 8 '22 Cruddur - The not so great twitter clone using Ruby Sinatra + React + GCP CloudRun + MongoDB Atlas + Terraform # atlashackathon22 # terraform # googlecloud # ruby 7  reactions Comments 2  comments 11 min read You're running an online conference but get called out for having an all-male speaker lineup 2 days prior. Yo, What do you do? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Dec 4 '22 You're running an online conference but get called out for having an all-male speaker lineup 2 days prior. Yo, What do you do? # webdev # opensource # devto 22  reactions Comments 19  comments 5 min read What if DEV became the new Twitter-like platform for developers? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Nov 11 '22 What if DEV became the new Twitter-like platform for developers? # discuss 26  reactions Comments 16  comments 1 min read Twitter <> Andrew Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jan 26 '22 Twitter <> Andrew # twitter 13  reactions Comments Add Comment 7 min read Will you consider your carbon footprint when configuring your compute workloads? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jul 30 '21 Will you consider your carbon footprint when configuring your compute workloads? # discuss # cloud 10  reactions Comments Add Comment 1 min read This is what gatekeeping looks like in the cloud industry (or how to not be a reply guy) Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jul 20 '21 This is what gatekeeping looks like in the cloud industry (or how to not be a reply guy) # discuss # career # aws # azure 33  reactions Comments 2  comments 3 min read Is PolyWork the new LinkedIn for Developers? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jun 17 '21 Is PolyWork the new LinkedIn for Developers? # discuss # career 106  reactions Comments 18  comments 6 min read If you were the new CEO of Amazon Web Services what would be your first executive order? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Feb 7 '21 If you were the new CEO of Amazon Web Services what would be your first executive order? # aws 28  reactions Comments 21  comments 1 min read AWS Heroes React to AWS re:Invent 2020 Announcements 🤯 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for AWS Heroes Dec 3 '20 AWS Heroes React to AWS re:Invent 2020 Announcements 🤯 # aws 95  reactions Comments Add Comment 12 min read AWS Community Builders Program 09:50 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for AWS Community Builders Aug 12 '20 AWS Community Builders Program # aws # cloud 112  reactions Comments 5  comments 4 min read Rich Draft Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jun 24 '20 Rich Draft 23  reactions Comments 11  comments 1 min read Free Youtube Channels I Recommend To Help You Pass AWS / Azure Certification ☁️ Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Jun 22 '20 Free Youtube Channels I Recommend To Help You Pass AWS / Azure Certification ☁️ # aws # azure # beginners # career 104  reactions Comments 3  comments 6 min read FREE AWS Developer Associate Certification Course (250+ Videos) 😱 00:39 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Jun 20 '20 FREE AWS Developer Associate Certification Course (250+ Videos) 😱 # azure # beginners # career # cloud 282  reactions Comments 4  comments 17 min read FREE 3 Hour Azure Fundamentals (AZ-900) Certification Course (100+ Videos!) 😱 00:32 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Jun 18 '20 FREE 3 Hour Azure Fundamentals (AZ-900) Certification Course (100+ Videos!) 😱 # azure # beginners # career # cloud 193  reactions Comments 13  comments 5 min read CloudJourney - Want to be on my live-stream? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow May 20 '20 CloudJourney - Want to be on my live-stream? # aws # azure # devops # career 35  reactions Comments 4  comments 3 min read I am being cyberbullied and it's affecting my mental health. This is my personal cure. Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Apr 8 '20 I am being cyberbullied and it's affecting my mental health. This is my personal cure. # discuss # pinkday # todayilearned 55  reactions Comments 6  comments 7 min read WTF? Google Cloud Platform has a Cloud Service that Uses ML to help you find a job. How more meta can you get? 03:20 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Mar 7 '20 WTF? Google Cloud Platform has a Cloud Service that Uses ML to help you find a job. How more meta can you get? # gcp # career # webdev # cloud 128  reactions Comments 13  comments 2 min read DynamoDB Cheatsheet – Everything you need to know about Dynamo DB for the 2020 AWS Certified Developer Associate Certification Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Feb 29 '20 DynamoDB Cheatsheet – Everything you need to know about Dynamo DB for the 2020 AWS Certified Developer Associate Certification # aws # database # developer # cloud 155  reactions Comments 3  comments 9 min read Pulling your DEV Organization Stats into a Spreadsheet Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Feb 20 '20 Pulling your DEV Organization Stats into a Spreadsheet # showdev # tutorial # productivity # beginners 59  reactions Comments 2  comments 2 min read Upcoming Change to the AWS Solutions Architect Associate Exam SAA-C01 to SAA-C02 04:55 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Feb 19 '20 Upcoming Change to the AWS Solutions Architect Associate Exam SAA-C01 to SAA-C02 # aws 56  reactions Comments 6  comments 2 min read I had to build my own Markdown Editor because no tool was fast enough for me. 01:19 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Feb 14 '20 I had to build my own Markdown Editor because no tool was fast enough for me. # showdev # productivity # opensource # javascript 245  reactions Comments 18  comments 5 min read AWS for Startups (FREE 4hrs Video Course) Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Jan 21 '20 AWS for Startups (FREE 4hrs Video Course) # aws # startup # beginners # tutorial 259  reactions Comments 10  comments 3 min read Gotta Learn Em' All - Amázons (Web Services) 01:23 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Nov 21 '19 Gotta Learn Em' All - Amázons (Web Services) # aws 58  reactions Comments 2  comments 1 min read The FREE AWS Certified Solutions Architect Associate Study Course (275+ Videos!) 😱 00:24 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Nov 20 '19 The FREE AWS Certified Solutions Architect Associate Study Course (275+ Videos!) 😱 # aws # beginners # career # cloud 856  reactions Comments 30  comments 16 min read Delta-Eos (ASCII Detective Sci-fi game) - Starting to Play Like a Game 07:41 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Nov 7 '19 Delta-Eos (ASCII Detective Sci-fi game) - Starting to Play Like a Game # showdev # ruby # gamedev 61  reactions Comments 2  comments 1 min read Delta-Eos - Starting to look like a game Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Nov 4 '19 Delta-Eos - Starting to look like a game # showdev # ruby # gamedev 17  reactions Comments 1  comment 2 min read I am AWS Obsessed but I can't get hired at AWS. Have you ever faced such repeated rejection? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Oct 30 '19 I am AWS Obsessed but I can't get hired at AWS. Have you ever faced such repeated rejection? # discuss # rejection # aws # career 90  reactions Comments 79  comments 2 min read Delta-Eos - ASCII Text-Heavy Murder Mystery Game Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Oct 30 '19 Delta-Eos - ASCII Text-Heavy Murder Mystery Game # showdev # ruby # gamedev 24  reactions Comments 6  comments 5 min read TL;DR Headless CMS Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Oct 29 '19 TL;DR Headless CMS # productivity # webdev # beginners # tldr 85  reactions Comments 4  comments 6 min read The Free AWS Certified Cloud Practitioner Study Course (85+ Videos!) 01:08 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Oct 10 '19 The Free AWS Certified Cloud Practitioner Study Course (85+ Videos!) # aws # beginners # career # makeachange 786  reactions Comments 33  comments 6 min read The fast track to microservices on AWS 24:58 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Oct 4 '19 The fast track to microservices on AWS # techtalks # aws # microservices # devops 77  reactions Comments 1  comment 4 min read Who/what should I follow on Instagram for web-dev? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Aug 28 '19 Who/what should I follow on Instagram for web-dev? # discuss # webdev # career # help 70  reactions Comments 28  comments 1 min read I just did my first guest podcast and I'm giving away a free study course for AWS Certification! 00:30 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Aug 26 '19 I just did my first guest podcast and I'm giving away a free study course for AWS Certification! # aws # career # beginners # fullstack 46  reactions Comments 17  comments 1 min read Event Tracking and Analytics via Ruby on Rails, DynamoDB (with Streams), Kinesis Firehose and Athena and CloudWatch Dashboard! 21:24 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Aug 11 '19 Event Tracking and Analytics via Ruby on Rails, DynamoDB (with Streams), Kinesis Firehose and Athena and CloudWatch Dashboard! # aws # rails # bigdata # kinesis 88  reactions Comments Add Comment 13 min read You're not worth hiring unless... Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Aug 4 '19 You're not worth hiring unless... # discuss # webdev # career 386  reactions Comments 171  comments 1 min read Just moved our online IDE from Cloud9 to VSCode what extensions should we use? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Aug 1 '19 Just moved our online IDE from Cloud9 to VSCode what extensions should we use? # help # vscode 9  reactions Comments 7  comments 1 min read Live-Stream July 30th 12:30PM-1:30PM EDT - Hacks to Improve your LinkedIn Profile for Devs Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jul 29 '19 Live-Stream July 30th 12:30PM-1:30PM EDT - Hacks to Improve your LinkedIn Profile for Devs # career # webdev # beginners # linkedin 42  reactions Comments Add Comment 1 min read How do you like your rice pudding? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jul 12 '19 How do you like your rice pudding? # watercooler 6  reactions Comments 4  comments 1 min read Toronto Meetup June 22nd. Any DEV.to users in the GTA? 01:58 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jun 18 '19 Toronto Meetup June 22nd. Any DEV.to users in the GTA? # aws # webdev # meetup # ux 10  reactions Comments 2  comments 1 min read TV while coding? Distraction or Motivation? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jun 17 '19 TV while coding? Distraction or Motivation? # discuss # webdev 73  reactions Comments 44  comments 1 min read Its Sunday, are you coding? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jun 16 '19 Its Sunday, are you coding? # discuss # webdev 23  reactions Comments 46  comments 1 min read What gives you the most anxiety when freelancing? Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Jun 14 '19 What gives you the most anxiety when freelancing? # discuss # webdev # entrepreneur # freelance 6  reactions Comments 4  comments 1 min read RSpec - Writing Test Code In Ruby (3/3) Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Jun 13 '19 RSpec - Writing Test Code In Ruby (3/3) # beginners # ruby # testing # tutorial 33  reactions Comments 12  comments 3 min read MiniTest - Writing Test Code In Ruby (2/3) Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Jun 13 '19 MiniTest - Writing Test Code In Ruby (2/3) # beginners # ruby # testing # tutorial 36  reactions Comments 4  comments 5 min read TestUnit - Writing Test Code In Ruby (1/3) Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Jun 13 '19 TestUnit - Writing Test Code In Ruby (1/3) # beginners # ruby # testing # tutorial 91  reactions Comments 2  comments 4 min read 700+ Web Developers Asked Me To Give Them LinkedIn Profile Feedback And These Are My 🖐️ 5 Top Tips. Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro May 29 '19 700+ Web Developers Asked Me To Give Them LinkedIn Profile Feedback And These Are My 🖐️ 5 Top Tips. # career # webdev # beginners # linkedin 2159  reactions Comments 65  comments 6 min read LinkedIn is for Losers? Think Again. From 💰 100k+ to 200K+ job opportunities. 🛠 Hacks Included. Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro May 19 '19 LinkedIn is for Losers? Think Again. From 💰 100k+ to 200K+ job opportunities. 🛠 Hacks Included. # career # webdev # beginners # linkedin 803  reactions Comments 42  comments 5 min read 👶 New Baby! 👕New Shirt! 📙New AWS Course! Let's Celebrate with a Special Deal! Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro May 18 '19 👶 New Baby! 👕New Shirt! 📙New AWS Course! Let's Celebrate with a Special Deal! # news # aws # beginners # career 62  reactions Comments 13  comments 1 min read SNS vs SQS? AWS Messaging Services - Know the difference 04:19 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro May 14 '19 SNS vs SQS? AWS Messaging Services - Know the difference # aws # beginners # architect # career 72  reactions Comments 16  comments 3 min read How To Put On F*cking Stunning Tech Talks. Hacks Included 🛠 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Apr 24 '19 How To Put On F*cking Stunning Tech Talks. Hacks Included 🛠 # career # beginners # speaking # culture 204  reactions Comments 7  comments 5 min read How To Run A Modded Minecraft Server on AWS 20:58 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Apr 20 '19 How To Run A Modded Minecraft Server on AWS # aws # minecraft # devops # beginners 42  reactions Comments 18  comments 1 min read The Fast Track to Serverless Security on AWS 22:25 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Apr 19 '19 The Fast Track to Serverless Security on AWS # serverless # security # aws # devops 23  reactions Comments 1  comment 1 min read I Made It To 💯 Youtube Subscribers! Lets Celebrate 🎉 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Apr 18 '19 I Made It To 💯 Youtube Subscribers! Lets Celebrate 🎉 # junkpost # personalnews 7  reactions Comments 1  comment 1 min read How to Serve On-Demand Streaming Videos from AWS (Build Your Own Netflix) 27:31 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Apr 13 '19 How to Serve On-Demand Streaming Videos from AWS (Build Your Own Netflix) # aws # rails # webdev # devops 250  reactions Comments 18  comments 1 min read Ten AWS Services If They Were Pokémon (Amázmons?) Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Apr 8 '19 Ten AWS Services If They Were Pokémon (Amázmons?) # pokemon # aws # beginners 52  reactions Comments 3  comments 5 min read 🎉 Published My First AWS Udemy Course And I Want You To Have It For Free! 01:48 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Apr 6 '19 🎉 Published My First AWS Udemy Course And I Want You To Have It For Free! # personalnews # aws # rails # beginners 310  reactions Comments 41  comments 3 min read 5 things I wish I knew before using CloudFormation to build a CodePipeline for Lambda Functions Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Apr 4 '19 5 things I wish I knew before using CloudFormation to build a CodePipeline for Lambda Functions # cloudformation # codepipeline # aws # architect 16  reactions Comments 1  comment 3 min read 14 Practice Question Walkthrough Videos for AWS Certified Cloud Practitioner Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow for ExamPro Apr 4 '19 14 Practice Question Walkthrough Videos for AWS Certified Cloud Practitioner # aws # certification # beginners # career 21  reactions Comments 2  comments 1 min read New Feature - Short Video on Advanced Request Routing for AWS ALB 03:04 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Andrew Brown 🇨🇦 Follow Apr 2 '19 New Feature - Short Video on Advanced Request Routing for AWS ALB # aws # alb 10  reactions Comments 1  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 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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2026-01-13T08:49:43
https://docs.devcycle.com/sdk/client-side-sdks/nextjs
Next.js SDK | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up SDK Overview SDK Lifecycle SDK Features Client-side SDKS JavaScript SDK React SDK Next.js SDK Installation Usage - App Router Usage - Pages Router Typescript Example App Angular SDK iOS SDK Android SDK React Native Flutter SDK Roku SDK Server-side SDKS SDK Proxy Client-side SDKS Next.js SDK On this page DevCycle Next.js SDK The DevCycle Next.js SDK lets you easily integrate your Next.js applications with DevCycle. Installation Installing the SDK Usage - App Router Initializing the SDK Usage - Pages Router Initializing the SDK Typescript SDK features for Typescript users Example App Try it out for yourself The SDK is available as a package on npm. It is also open source and can be viewed on Github. This SDK depends on the fetch API. Features ​ full support for App Router and server components keep server and client rendered content in sync with the same variable values realtime updates to variable values for both server and client components support for Suspense streaming rendering with non-blocking variable state retrieval support for static page rendering exclude component code from client bundle when feature is disabled Requirements ​ SDK Version Minimum Next.js Version Minimum React Version 3.0.0+ 15.1.0 18.2 2.0.0+ 14.1.0 18.2 Edit this page Last updated on Jan 9, 2026 Previous Example App Next Installation Features Requirements DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://dev.to/t/communication/page/3
Communication Page 3 - 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 # communication Follow Hide Tips for talking effectively with your children at every age. Create Post Older #communication posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu How Bonza AI Chat is Revolutionizing Online Interactions Kaitlyn Cheek Kaitlyn Cheek Kaitlyn Cheek Follow Mar 15 '25 How Bonza AI Chat is Revolutionizing Online Interactions # ai # money # business # communication Comments Add Comment 4 min read Importance of Communication adegiamb adegiamb adegiamb Follow Mar 13 '25 Importance of Communication # communication Comments Add Comment 7 min read How Software Teams Can Improve Communication and Collaboration TaskFrame TaskFrame TaskFrame Follow Apr 10 '25 How Software Teams Can Improve Communication and Collaboration # teamcollaboration # communication # softwaredevelopment Comments 2  comments 3 min read The Isolation Illusion: Pull Requests and the Cost of Delayed Integration j.sartwell j.sartwell j.sartwell Follow Mar 27 '25 The Isolation Illusion: Pull Requests and the Cost of Delayed Integration # communication # continuous # integration # programming 1  reaction Comments Add Comment 2 min read 3 Question Framework – How to Respond Without Reacting Svenja Schäfer Svenja Schäfer Svenja Schäfer Follow Feb 2 '25 3 Question Framework – How to Respond Without Reacting # communication # coaching Comments Add Comment 3 min read Stop Writing 50-Page Reports No One Reads Dr. Josh C. Simmons Dr. Josh C. Simmons Dr. Josh C. Simmons Follow Jan 25 '25 Stop Writing 50-Page Reports No One Reads # minimalism # communication # career Comments Add Comment 1 min read Intro to gRPC and Protocol Buffers using Go Let's Do Tech Let's Do Tech Let's Do Tech Follow Feb 8 '25 Intro to gRPC and Protocol Buffers using Go # systemdesign # architecture # communication # distributed Comments Add Comment 8 min read How to be proactive as a Software Engineer Erry Kostala Erry Kostala Erry Kostala Follow Jan 28 '25 How to be proactive as a Software Engineer # webdev # programming # productivity # communication 6  reactions Comments Add Comment 2 min read Why Communication Isn’t Just a Skill—It’s a Product Manager’s Superpower 🚀💬 Oluwole Adebiyi Oluwole Adebiyi Oluwole Adebiyi Follow Jan 26 '25 Why Communication Isn’t Just a Skill—It’s a Product Manager’s Superpower 🚀💬 # productmanagement # leadership # transparency # communication 3  reactions Comments 1  comment 4 min read Porque você deve melhorar sua capacidade de comunicação para trabalhar com tecnologia Vitor Rubenich Vitor Rubenich Vitor Rubenich Follow Jan 8 '25 Porque você deve melhorar sua capacidade de comunicação para trabalhar com tecnologia # communication # improvement # technology # braziliandevs 1  reaction Comments Add Comment 2 min read Improving Communication for SMEs: Overcoming Common Challenges Krideo Krideo Krideo Follow Dec 2 '24 Improving Communication for SMEs: Overcoming Common Challenges # communication # challenges # videoconferencing # smes Comments Add Comment 1 min read How Video Conferencing Benefits Rural Communities Krideo Krideo Krideo Follow Dec 2 '24 How Video Conferencing Benefits Rural Communities # videoconferencing # ruralareas # communication # digitaldivide Comments Add Comment 1 min read Innovative Uses of Video Conferencing - Corporate World Krideo Krideo Krideo Follow Nov 25 '24 Innovative Uses of Video Conferencing - Corporate World # videoconferencing # corporateculture # corporateworld # communication Comments Add Comment 1 min read The Reality of Cost-Efficient Communication Tools for SMEs - The Article Krideo Krideo Krideo Follow Nov 18 '24 The Reality of Cost-Efficient Communication Tools for SMEs - The Article # smes # videoconferencing # costefficient # communication Comments Add Comment 1 min read Demystifying VoIP Protocols: A Guide to Developing a Reliable Voice Phone Service United World Telecom United World Telecom United World Telecom Follow Nov 29 '24 Demystifying VoIP Protocols: A Guide to Developing a Reliable Voice Phone Service # voip # cloudtelephony # communication # productivity Comments Add Comment 5 min read The Impact of AI Interactions on Human Communication Evan Marie Carr Evan Marie Carr Evan Marie Carr Follow Nov 23 '24 The Impact of AI Interactions on Human Communication # ai # communication 1  reaction Comments Add Comment 6 min read Embrace your voice Norbs' Notes Norbs' Notes Norbs' Notes Follow Nov 6 '24 Embrace your voice # softskills # communication # publicspeaking Comments Add Comment 3 min read The Evolution of Communication: Video Conferencing Krideo Krideo Krideo Follow Oct 31 '24 The Evolution of Communication: Video Conferencing # communication # video # videoconferencing # software Comments Add Comment 1 min read Understanding the Basics of Data Communications Kara Masterson Kara Masterson Kara Masterson Follow Sep 5 '24 Understanding the Basics of Data Communications # data # communication # wiredcommuincation # wirelesscommunication Comments Add Comment 3 min read Don't Dead End Your Dev Career: Using Communication to Amplify Your Possibilities Bradston Henry Bradston Henry Bradston Henry Follow for Developers @ Asurion Aug 22 '24 Don't Dead End Your Dev Career: Using Communication to Amplify Your Possibilities # developer # career # careerdevelopment # communication 10  reactions Comments Add Comment 10 min read Navigating Crisis: Preparation Strategies for Unforeseen Events Jeffrey Boyle Jeffrey Boyle Jeffrey Boyle Follow Jun 20 '24 Navigating Crisis: Preparation Strategies for Unforeseen Events # communication # crisispreparedness # riskmanagement Comments Add Comment 2 min read Navigating Crisis: Preparation Strategies for Unforeseen Events Jeffrey Boyle Jeffrey Boyle Jeffrey Boyle Follow Jun 20 '24 Navigating Crisis: Preparation Strategies for Unforeseen Events # communication # crisispreparedness # riskmanagement Comments Add Comment 2 min read Don't refactor the code Paweł Świątkowski Paweł Świątkowski Paweł Świątkowski Follow Jun 13 '24 Don't refactor the code # programming # communication # softwaredevelopment # codequality 326  reactions Comments 31  comments 2 min read Some Books to Upskill Communication For Software Engineers Stephen Hara Stephen Hara Stephen Hara Follow Jun 17 '24 Some Books to Upskill Communication For Software Engineers # books # communication Comments Add Comment 4 min read Will Customers Ever Speak Our Language? Attila Fejér Attila Fejér Attila Fejér Follow May 9 '24 Will Customers Ever Speak Our Language? # communication # softskills # ai Comments Add Comment 6 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. 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
2026-01-13T08:49:43
https://dev.to/pockit_tools/pnpm-vs-npm-vs-yarn-vs-bun-the-2026-package-manager-showdown-51dc#small-project-50-dependencies
pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown - 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 HK Lee Posted on Jan 9 • Originally published at pockit.tools pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown # bunjs # pnpm # yarn # npm Every JavaScript project starts with a choice: which package manager? For years, it was npm by default. Then yarn promised faster installs. Then pnpm claimed to save gigabytes of disk space. And now Bun's built-in package manager claims to make everything else obsolete. But here's what no one tells you: the "best" package manager depends entirely on your specific use case, and blindly following benchmarks can lead you astray. A package manager that's perfect for a solo developer's side project might be terrible for a 500-package monorepo—and vice versa. This guide cuts through the marketing hype. After extensive testing across different project sizes and configurations in January 2026, here's what actually matters for each package manager, when to use it, and how to migrate if you need to. 📌 Version Note: This comparison covers npm 11.x, yarn 4.x (Berry), pnpm 10.x, and Bun 1.3 as of January 2026. The Quick Verdict If you're in a hurry, here's the short version: Use Case Recommended Why Solo/small projects Bun Fastest by far, simplest setup Large monorepos pnpm Best disk efficiency, workspace support Enterprise/legacy npm Maximum compatibility, no surprises Yarn ecosystem yarn 4 PnP mode, excellent plugins Performance at scale pnpm or Bun Both excel, pnpm more mature Now let's dive into why. The Contenders: 2026 State of Play npm 11.x Status: Still the default, ships with Node.js Latest: npm 11.7.0 (December 2025) Philosophy: Compatibility over innovation Key Strength: Works everywhere, always npm has evolved significantly. The node_modules structure is now more optimized, and features like npm audit have become industry standards. But npm's conservative approach means it's rarely the fastest or most efficient—it's just the most reliable. yarn 4.x (Berry) Status: Complete rewrite from yarn 1.x Latest: yarn 4.12.0 (January 2026) Philosophy: Innovation through Plug'n'Play (PnP) Key Strength: Zero-installs, plugin architecture Yarn Berry is essentially a different product from yarn 1. The Plug'n'Play feature eliminates node_modules entirely, instead using a .pnp.cjs file that maps imports directly to zip archives. It's radical—and divisive. pnpm 10.x Status: The "smart" alternative Latest: pnpm 10.27.0 (December 2025) Philosophy: Efficiency without breaking compatibility Key Strength: Content-addressable storage, true deduplication pnpm's approach is elegant: store all packages once in a global content-addressable store, then use hard links to make them appear in each project's node_modules . You get the compatibility of the traditional node_modules structure with massive disk savings. Bun 1.3 Package Manager Status: The new challenger Latest: Bun 1.3.0 (January 1, 2026) Philosophy: Speed above all else Key Strength: Native speed, zero configuration, full-stack capabilities Bun isn't just a package manager—it's a complete JavaScript runtime. Bun 1.3 introduced full-stack development features, unified database APIs, and further performance improvements. Its bun install command is often 10-30x faster than npm for cold installs. Benchmark Results: Cold Install Performance Let's start with what everyone cares about—raw speed. We tested each package manager on the same projects with cleared caches: Small Project (50 dependencies) Project: Typical React + TypeScript starter Dependencies: 50 direct, ~400 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 0.8s │ 18x faster │ │ pnpm │ 4.2s │ 3.4x faster│ │ yarn │ 6.8s │ 2.1x faster│ │ npm │ 14.3s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Medium Project (200 dependencies) Project: Next.js 15 app with common libraries Dependencies: 200 direct, ~1,200 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 2.1s │ 22x faster │ │ pnpm │ 12.4s │ 3.7x faster│ │ yarn │ 18.2s │ 2.5x faster│ │ npm │ 46.1s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Large Monorepo (15 packages, 800 dependencies) Project: Turborepo monorepo with 15 packages Dependencies: 800 direct, ~3,500 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 4.8s │ 28x faster │ │ pnpm │ 28.6s │ 4.7x faster│ │ yarn │ 52.3s │ 2.6x faster│ │ npm │ 134.2s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Key Insight: Bun's lead actually increases with project size. For monorepos, the difference is staggering. Cached/Warm Install Performance But cold installs aren't the whole story. Most of the time, you're installing with some level of caching: Warm Install (lockfile exists, some cache): ┌────────────┬──────────────┬──────────────┐ │ Manager │ Small (50) │ Large (800) │ ├────────────┼──────────────┼──────────────┤ │ bun │ 0.3s │ 1.2s │ │ pnpm │ 1.1s │ 8.4s │ │ yarn (PnP) │ 0.0s* │ 0.0s* │ │ npm │ 3.2s │ 24.6s │ └────────────┴──────────────┴──────────────┘ * Yarn PnP with zero-installs commits dependencies to repo Enter fullscreen mode Exit fullscreen mode Yarn's Zero-Installs Trick: With PnP mode and zero-installs, yarn commits your dependencies directly to the repository. CI/CD runs need zero install time—they just yarn and go. The tradeoff? Your repo size increases significantly. Disk Usage: Where pnpm Shines Raw speed is one thing, but what about your hard drive? Single Project Disk Usage Same 200-dependency project: ┌────────────┬──────────────┬──────────────┐ │ Manager │ node_modules │ vs npm │ ├────────────┼──────────────┼──────────────┤ │ npm │ 487 MB │ baseline │ │ yarn │ 502 MB │ +3% │ │ pnpm │ 124 MB* │ -75% │ │ bun │ 461 MB │ -5% │ └────────────┴──────────────┴──────────────┘ * pnpm uses hard links to global store Enter fullscreen mode Exit fullscreen mode Multiple Projects (Same Dependencies) Here's where pnpm's architecture pays off. If you have 10 projects using React 19: 10 Projects with overlapping dependencies: ┌────────────┬──────────────┬──────────────┐ │ Manager │ Total Disk │ vs npm │ ├────────────┼──────────────┼──────────────┤ │ npm │ 4.87 GB │ baseline │ │ yarn │ 5.02 GB │ +3% │ │ pnpm │ 612 MB │ -87% │ │ bun │ 4.61 GB │ -5% │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode pnpm stores each unique package version exactly once. Every project links to that single copy. If you work on many projects, pnpm can save tens of gigabytes. Bun's Approach: Bun uses a global cache but still creates full node_modules directories. It's faster than npm/yarn but doesn't achieve pnpm's deduplication. Monorepo Support Compared Monorepos have become the default for many organizations. Here's how each manager handles them: Workspace Configuration npm (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode yarn (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode pnpm (pnpm-workspace.yaml): # pnpm-workspace.yaml packages : - ' packages/*' - ' apps/*' Enter fullscreen mode Exit fullscreen mode Bun (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode Workspace Features Comparison Feature npm yarn pnpm Bun Workspace protocol ( workspace:* ) ❌ ✅ ✅ ✅ Selective dependency installation ❌ ✅ ✅ ✅ Parallel task execution ❌ ✅ ✅ ✅ Cross-workspace linking Basic Good Excellent Good Hoisting control Limited Full Full Limited Filtering ( --filter ) ❌ ✅ ✅ ❌ The Bottom Line: pnpm and yarn are the clear leaders for monorepo management. npm's workspace support is functional but basic. Bun's is improving rapidly but still catching up. Real-World Monorepo Performance We tested a Turborepo setup with 15 packages: Task: Install + Build all packages ┌────────────┬──────────────┬──────────────┐ │ Manager │ Install │ Full Build │ ├────────────┼──────────────┼──────────────┤ │ pnpm │ 28.6s │ 142s │ │ bun │ 4.8s │ 138s │ │ yarn │ 52.3s │ 156s │ │ npm │ 134.2s │ 198s │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode Interesting: Bun's install speed advantage shrinks when you include build time. The build phase dominates, making the install speed difference less impactful for CI/CD overall. Security Features Security has become a first-class concern. Here's how each manager handles it: Audit Capabilities Feature npm yarn pnpm Bun audit command ✅ Native ✅ Plugin ✅ Native ❌ Auto-fix vulnerabilities ✅ ✅ ✅ ❌ Advisory database npm registry npm registry npm registry - SBOM generation ✅ ✅ Plugin ✅ ❌ Critical Note: Bun currently lacks built-in security auditing. For production applications, you'll need third-party tools like Snyk or Socket. Lockfile Security All four managers use lockfiles to ensure reproducible installs: npm: package-lock.json (JSON) yarn: yarn.lock (custom format) pnpm: pnpm-lock.yaml (YAML) Bun: bun.lockb (binary) Bun's Binary Lockfile: Bun's bun.lockb is binary for speed. While this makes installs faster, it's not human-readable and can't be easily diffed in code review. Bun offers bun.lock (text) as an alternative, but it's not the default. Supply Chain Protection Feature npm yarn pnpm Bun Signature verification ✅ ✅ ✅ ❌ Strict peer dependencies Optional Optional Default Optional .npmrc security options Full Limited Full Limited Network isolation mode ❌ ✅ ✅ ❌ Compatibility Reality Check Here's what nobody talks about: not every package works perfectly with every manager. Known Compatibility Issues (January 2026) pnpm: Some packages break with strict node_modules structure Workaround: shamefully-hoist=true in .npmrc Most major packages now support pnpm natively yarn PnP: Many packages still don't support PnP mode Workaround: nodeLinker: node-modules falls back to traditional structure Adoption is improving but still incomplete Bun: ~98% npm compatibility (up from 95% in 2025) Some native modules still have issues Workaround: Use --backend=copyfile for problematic packages Framework Compatibility Framework npm yarn pnpm Bun Next.js 15 ✅ ✅ ✅ ✅ Remix ✅ ✅ ✅ ⚠️ Nuxt 4 ✅ ✅ ✅ ✅ Angular 19 ✅ ⚠️ ✅ ⚠️ SvelteKit ✅ ✅ ✅ ✅ Astro 5 ✅ ✅ ✅ ✅ ⚠️ = Works but some edge cases or extra configuration needed CI/CD Performance For many teams, CI/CD time is where package manager choice really matters: GitHub Actions Benchmark # Same workflow, different package managers # Node.js 22, ubuntu-latest, clean cache ┌────────────┬──────────────┬──────────────┬──────────────┐ │ Manager │ Install │ Cache Hit │ Total Job │ ├────────────┼──────────────┼──────────────┼──────────────┤ │ npm │ 48s │ 12s │ 2m 34s │ │ yarn │ 21s │ 8s │ 2m 15s │ │ yarn (PnP) │ 18s │ 0s* │ 2m 02s │ │ pnpm │ 14s │ 4s │ 2m 08s │ │ bun │ 3s │ 1s │ 1m 52s │ └────────────┴──────────────┴──────────────┴──────────────┘ * Zero-installs : dependencies committed to repo Enter fullscreen mode Exit fullscreen mode Docker Build Performance # Multi-stage build comparison ┌────────────┬──────────────┬──────────────┐ │ Manager │ Layer Cache │ No Cache │ ├────────────┼──────────────┼──────────────┤ │ npm │ 18s │ 52s │ │ pnpm │ 8s │ 24s │ │ bun │ 2s │ 6s │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode The Docker Secret: Bun's speed advantage is even more pronounced in Docker because its binary includes the runtime—no need to install Node.js separately. Migration Guides Ready to switch? Here's how: npm → pnpm Install pnpm: npm install -g pnpm Enter fullscreen mode Exit fullscreen mode Import existing lockfile: pnpm import Enter fullscreen mode Exit fullscreen mode Delete old files: rm -rf node_modules package-lock.json Enter fullscreen mode Exit fullscreen mode Install: pnpm install Enter fullscreen mode Exit fullscreen mode Update scripts (if needed): // package.json - usually works as-is { "scripts" : { "dev" : "next dev" , // no change needed "build" : "next build" } } Enter fullscreen mode Exit fullscreen mode npm → Bun Install Bun: curl -fsSL https://bun.sh/install | bash Enter fullscreen mode Exit fullscreen mode Remove old files: rm -rf node_modules package-lock.json Enter fullscreen mode Exit fullscreen mode Install: bun install Enter fullscreen mode Exit fullscreen mode Update scripts for Bun runtime (optional): { "scripts" : { "dev" : "bun run --bun next dev" , "build" : "bun run next build" } } Enter fullscreen mode Exit fullscreen mode yarn 1.x → yarn 4.x (Berry) # Enable corepack (Node.js 16+) corepack enable # Set yarn version yarn set version stable # Migrate configuration yarn config set nodeLinker node-modules # for compatibility # Install yarn install Enter fullscreen mode Exit fullscreen mode Rollback Plan If migration causes issues: # Keep your old lockfile backed up! cp package-lock.json package-lock.json.backup # To rollback: rm -rf node_modules bun.lockb pnpm-lock.yaml yarn.lock mv package-lock.json.backup package-lock.json npm install Enter fullscreen mode Exit fullscreen mode When to Use What: Decision Framework Use npm when: ✅ Maximum compatibility is required ✅ Team is unfamiliar with alternatives ✅ Legacy project with many native dependencies ✅ Corporate environment with strict tooling policies ✅ You want "it just works" Use yarn when: ✅ You need Plug'n'Play zero-installs ✅ You want the plugin ecosystem ✅ Your team is already yarn experts ✅ You need advanced workspace features ✅ Offline-first development is important Use pnpm when: ✅ Disk space is a concern ✅ You have many projects with overlapping dependencies ✅ Large monorepo with complex dependencies ✅ You want speed without sacrificing compatibility ✅ Strict dependency isolation matters Use Bun when: ✅ Speed is the absolute priority ✅ You're starting a new project ✅ CI/CD time is a major cost ✅ You're building Node.js APIs or scripts ✅ You want a unified runtime + package manager The Hidden Costs Nobody Mentions Before you switch, consider: Learning Curve npm → pnpm: Minimal. Almost drop-in. npm → yarn 4: Moderate. PnP mode requires understanding. npm → Bun: Low for package management, higher if using Bun runtime. Tooling Compatibility IDE support: All four work with VS Code, JetBrains, etc. CI/CD templates: npm has the most, Bun the least ready-made Docker images: npm/yarn are everywhere, pnpm common, Bun less common Team Onboarding The fastest package manager doesn't help if it slows down your team. Consider: How comfortable is your team with the new tool? Are your documentation and scripts updated? Have you tested the entire development workflow? Future Outlook: 2026 and Beyond npm: Will remain the default. Focus on incremental improvements. yarn: Continuing to push PnP adoption. Better monorepo support coming. pnpm: Rapid growth in enterprise. Becoming the "safe modern choice." Bun: Aggressive development. Aiming for 100% npm compatibility. May become the default for new projects by 2027. The ecosystem is fragmenting in healthy ways. Competition drives innovation—and all four managers are better for it. Conclusion: There's No Wrong Choice (Mostly) After extensive testing, here's the honest truth: all four package managers work fine for most projects. The performance differences, while measurable, rarely matter for small-to-medium projects. Where choice matters: Monorepos: pnpm or yarn CI/CD-heavy workflows: Bun or pnpm Disk-constrained systems: pnpm Maximum compatibility: npm Bleeding edge: Bun The most important thing isn't which package manager you choose—it's that you choose consistently across your projects and team. Switching between managers constantly creates more friction than any speed difference could justify. My recommendation for 2026: New projects: Try Bun. It's fast enough to justify the minor compatibility risks. Existing projects: Consider pnpm if you're feeling pain. Otherwise, npm is fine. Enterprise monorepos: pnpm is the safe, powerful choice. Benchmarks conducted January 2026 on M3 MacBook Pro with Node.js 22.x. Results will vary based on hardware, network, and project specifics. Always test with your own codebase before making decisions. 🚀 Explore More: This article is from the Pockit Blog . If you found this helpful, check out Pockit.tools . It’s a curated collection of offline-capable dev utilities. Available on Chrome Web Store for free. 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 HK Lee Follow solo web developer Joined Dec 26, 2025 Trending on DEV Community Hot I Am 38, I Am a Nurse, and I Have Always Wanted to Learn Coding # career # learning # beginners # coding Top 7 Featured DEV Posts of the Week # top7 # discuss What was your win this week??? # weeklyretro # 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
2026-01-13T08:49:43
https://www.youtube.com/watch?v=7GHXDEIMGIY
2023 EuroLLVM - Tutorial: A whirlwind tour of the LLVM optimizer - YouTube 정보 보도자료 저작권 문의하기 크리에이터 광고 개발자 약관 개인정보처리방침 정책 및 안전 YouTube 작동의 원리 새로운 기능 테스트하기 © 2026 Google LLC, Sundar Pichai, 1600 Amphitheatre Parkway, Mountain View CA 94043, USA, 0807-882-594 (무료), yt-support-solutions-kr@google.com, 호스팅: Google LLC, 사업자정보 , 불법촬영물 신고 크리에이터들이 유튜브 상에 게시, 태그 또는 추천한 상품들은 판매자들의 약관에 따라 판매됩니다. 유튜브는 이러한 제품들을 판매하지 않으며, 그에 대한 책임을 지지 않습니다. var ytInitialData = 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2026-01-13T08:49:43
https://future.forem.com/ribhavmodi/solidity-basics-part-1-variables-functions-your-first-real-contract-30bl#comments
Solidity Basics (Part 1) — Variables, Functions & Your First Real Contract - Future 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 Future 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 Ribhav Posted on Jan 5 • Edited on Jan 6 • Originally published at Medium           Solidity Basics (Part 1) — Variables, Functions & Your First Real Contract # crypto # blockchain # education # solidity 60 DAY WEB3 JOURNEY (29 Part Series) 1 Blockchain for Non-Technical People: Breaking Down the Basics 2 Bitcoin for Non-Technical People: Why the First Cryptocurrency Matters ... 25 more parts... 3 Bitcoin vs Traditional Money for Non-Technical People 4 Ethereum for Non-Technical People: The Programmable Blockchain 5 Smart Contracts and dApps on Ethereum (for Non‑Technical People) 6 Ethereum Wallets and Gas (for Non‑Technical People) 7 Why Ethereum Needs Layer 2s (for Curious Builders and Beginners) 8 Your First Ethereum Smart Contract, Step by Step 9 DeFi 101: Decentralized Finance 10 NFTs Explained Simply – What’s Actually Happening in 2025? 11 Understanding Tokenomics – Why Token Design Matters 12 Consensus Mechanisms Explained: How Blockchain Networks Agree Without a Boss 13 Layer 2 Solutions Deep-Dive: Optimistic vs ZK Rollups Explained 14 Ethereum vs Solana: Consensus in Action 15 DAOs Explained: How Decentralized Organizations Actually Work 16 Stablecoins – The Bridges Between Volatility and Value 17 DAOs in Practice – From Multi-Sig to Voting (And Why Ownership Tokens exist) 18 Blockchain Oracles: How Smart Contracts See the Real World (Featuring Chainlink) 19 Cross-Chain Bridges: How Assets Travel Between Blockchains (Without Getting Robbed) 20 MEV (Maximal Extractable Value): The Invisible Tax on Every Blockchain Transaction 21 Layer 0 & Layer 3 — How Blockchains Become an Internet, Not Islands 22 Web3 Infrastructure: RPCs, Nodes, Infura/Alchemy (The Invisible Plumbing) 23 On-Chain Identity — ENS, Soulbound Tokens & Your Web3 Resume 24 Crypto Regulation 101 — SEC, MiCA & What Builders Should Actually Care About 25 Solidity Basics (Part 1) — Variables, Functions & Your First Real Contract 26 Solidity Basics (Part 2) — Arrays, Mappings & Structs (Upgrading the Web3 Journey Logger) 27 Vibecoding On‑Chain — Using AI to Prototype Solidity Contracts (Safely) 28 How to Review AI‑Generated Solidity Like an Auditor (For Beginners) 29 Smart Contract Security 101 — Reentrancy & Common AI‑Generated Mistakes After a short two‑day pause in the 60‑Day Web3 journey, it’s time to hit play again and kick off the next phase with our first steps into Solidity. For the last 25 days, we’ve treated smart contracts like mysterious vending machines: you put in a transaction, and something happens on-chain. Today we finally lift the lid and start reading the language those vending machines are written in: Solidity. This is Day 26, the start of Phase 3: Development in the 60‑Day Web3 journey. The goal for today is not to become a Solidity expert. The goal is to understand the basic building blocks — variables and functions — and then ship a tiny but real contract to Sepolia: a Web3 Journey Logger . 1. What is Solidity, really? Solidity is a high-level, contract‑oriented programming language used to write smart contracts that run on Ethereum and other EVM-compatible chains like Arbitrum, Optimism, and Polygon. Once compiled, your Solidity code becomes bytecode that lives at a specific address on-chain and is executed by every node that processes your transaction. If you’ve seen JavaScript, C++, or TypeScript, Solidity will look familiar: curly braces, functions, variables, if conditions. But there are two crucial differences: you’re programming money and state, not just UI, and every operation costs gas while the code you deploy is mostly permanent. That’s why starting with the basics — how data is stored and how users interact with that data — is so important. 2. Variables: the contract’s on-chain memory Think of a smart contract as a tiny on-chain application with its own private database. Variables are the named boxes where this contract stores data. In Solidity, you must always declare both the type and the name of each variable because the compiler wants to know exactly what will be stored where. 2.1 Types of variables At a high level, there are three levels of variables: State variables Stored permanently in the contract’s storage on the blockchain. Persist between function calls and transactions. Example: the contract’s owner address, a token balance mapping, or a counter. Local variables Declared inside a function. Exist only while that function is running, then disappear. Example: uint256 sum = a + b; inside a function. Global variables Built-in helpers provided by the EVM. Examples: msg.sender for the caller, block.timestamp for the current block’s timestamp, and block.number for the current block number. In this first step, the focus is on state variables, since they form your contract’s on-chain memory. 2.2 Common data types you’ll actually use Here are the basic types you’ll see in almost every contract: bool Stores true or false . Example: bool public completed; uint256 Unsigned integer (0 and positive numbers). Commonly used for amounts, IDs, counters, timestamps. Example: uint256 public dayNumber; address Stores an Ethereum address, either a user or another contract. Example: address public owner; string Stores text data. More expensive than numbers in terms of gas, so used only when needed. Example: string public note; There are many more types such as int , bytes , mapping , struct , and arrays, but these four are enough to get started. 3. Functions: how users talk to your contract If variables are the contract’s memory, functions are the doors and buttons users can press to read or update that memory. Every time someone calls a function via a transaction or a UI like a dApp, the EVM executes the function’s logic step by step. 3.1 Function anatomy A typical Solidity function looks like this: function setDay(uint256 _day) public { dayNumber = _day; } Enter fullscreen mode Exit fullscreen mode In this example, setDay is the function name, uint256 _day is the input parameter, public is the visibility specifier, and the body between braces updates the dayNumber state variable. 3.2 Visibility (who can call this?) Visibility controls who can call a function and from where: public Anyone, including other contracts, can call this function. A public function is part of the contract’s external interface automatically. external Intended to be called from outside the contract. Slightly more gas‑efficient for pure external calls. Other options like internal and private are used for helper functions and will appear later as contracts become more modular. Note: setEntry is marked public but usually called externally; external could be slightly cheaper. 3.3 State mutability (what does this function do to state?) Solidity requires you to be explicit about how a function interacts with state: view Can read state variables but cannot modify them. Does not cost gas when called off-chain via tools like Etherscan or a dApp. pure Cannot read or modify state. Works only with its inputs and local variables. Example: function getDay() public view returns (uint256) { return dayNumber; } function add(uint256 a, uint256 b) public pure returns (uint256) { return a + b; } Enter fullscreen mode Exit fullscreen mode 4. Your first real contract: Web3 Journey Logger Instead of another generic “Simple Storage” example, this article builds a Web3 Journey Logger contract that ties directly into a learning challenge. The contract will: Store a name. Store the current learning day number. Store a short note about the day. This small contract is enough to show how variables and functions come together in a real, personal use case. 4.1 What the contract should do The Web3 Journey Logger has a few core behaviors: When deployed, it remembers who deployed it as the owner . It allows updating the current dayNumber and note for the latest entry. It lets anyone read the stored values for name, day number, and note. These requirements map cleanly to a handful of state variables and two or three functions. 4.2 Full contract code Here is a complete version of the Web3 Journey Logger contract: // SPDX-License-Identifier: MIT pragma solidity ^0.8.20; contract Web3JourneyLogger { // --- State variables --- // Address of the person who deployed the contract address public owner; // Name or handle of the learner string public name; // Current day in the learning journey uint256 public dayNumber; // Short note for the current day string public note; // --- Constructor --- constructor(string memory _name) { owner = msg.sender; name = _name; } // --- Core functions --- // Update the current day and note (only owner can call) function setEntry(uint256 _dayNumber, string calldata _note) public { require(msg.sender == owner, "Not owner"); dayNumber = _dayNumber; note = _note; } // Helper to read all data in one call function getEntry() public view returns ( string memory _name, uint256 _day, string memory _note ) { return (name, dayNumber, note); } } Enter fullscreen mode Exit fullscreen mode This minimal contract demonstrates state variables, a constructor, a state‑changing function with a simple access control check, and a view function that returns multiple values. 5. Step‑by‑step: deploy to Sepolia with Remix To make this more than theory, the contract is deployed on the Sepolia testnet using Remix and MetaMask. 5.1 Setup the wallet A wallet such as MetaMask is needed to sign and send transactions: The wallet must be switched to the Sepolia test network. A small amount of test ETH can be requested from a Sepolia faucet to cover deployment gas. This setup mirrors real mainnet deployment without risking real funds. You can follow these steps ! 5.2 Open Remix and add the contract Remix is a browser-based IDE for Solidity: Visit https://remix.ethereum.org in a browser. In the file explorer, create a new file named Web3JourneyLogger.sol . Paste the complete contract code into this file. Remix automatically saves the file and makes it available to the Solidity compiler. 5.3 Compile the contract Compiling turns Solidity into bytecode that can be deployed: Open the Solidity Compiler tab in Remix. Select a compiler version matching the pragma, such as 0.8.20 . Click Compile Web3JourneyLogger.sol . If any errors appear, Remix highlights the problematic lines so they can be corrected before trying again. 5.4 Deploy to Sepolia Once the contract compiles, it can be deployed to the testnet: Open the Deploy & Run Transactions tab. Set Environment to Injected Provider – MetaMask so Remix uses the wallet’s network. Confirm that MetaMask is on the Sepolia network. Ensure Web3JourneyLogger is selected in the contract dropdown. In the constructor field, pass a name string, for example "Ribhav" . Click Deploy and confirm the transaction in MetaMask. After mining, Remix shows a deployed contract instance and the transaction can also be viewed on Sepolia Etherscan using the transaction hash. 5.5 Interact with the contract The deployed contract can now be read and updated from Remix: Under Deployed Contracts , expand the Web3JourneyLogger instance. Call the generated getters like owner , name , dayNumber , and note to see current values. Use setEntry to set a new day number and note, then read them back again using either the individual getters or getEntry() . By repeating this daily, the contract becomes a small on-chain journal of a Web3 learning journey. 6. Why this matters for developers Every DeFi protocol, NFT marketplace, or DAO is ultimately just a more complex arrangement of variables and functions like the ones introduced here. Understanding how state is stored, how functions expose or protect that state, and how contracts are deployed to a network is the foundation of secure smart contract development and auditing. In the next steps of the journey, these basics expand into arrays, mappings, structs, access control patterns, and local development tools like Hardhat and Foundry, but they all build on the same core ideas introduced in this first Solidity article. Further reading Solidity official docs – Introduction to Smart Contracts Solidity by Example – Simple Storage and Basics GeeksforGeeks – Solidity Basics of Contracts GeeksforGeeks – Solidity Variables GeeksforGeeks – Solidity Functions Dapp University – Solidity for Beginners Follow the series on Medium | Twitter | Future Jump into Web3ForHumans on Telegram and we’ll brainstorm Web3 together. 60 DAY WEB3 JOURNEY (29 Part Series) 1 Blockchain for Non-Technical People: Breaking Down the Basics 2 Bitcoin for Non-Technical People: Why the First Cryptocurrency Matters ... 25 more parts... 3 Bitcoin vs Traditional Money for Non-Technical People 4 Ethereum for Non-Technical People: The Programmable Blockchain 5 Smart Contracts and dApps on Ethereum (for Non‑Technical People) 6 Ethereum Wallets and Gas (for Non‑Technical People) 7 Why Ethereum Needs Layer 2s (for Curious Builders and Beginners) 8 Your First Ethereum Smart Contract, Step by Step 9 DeFi 101: Decentralized Finance 10 NFTs Explained Simply – What’s Actually Happening in 2025? 11 Understanding Tokenomics – Why Token Design Matters 12 Consensus Mechanisms Explained: How Blockchain Networks Agree Without a Boss 13 Layer 2 Solutions Deep-Dive: Optimistic vs ZK Rollups Explained 14 Ethereum vs Solana: Consensus in Action 15 DAOs Explained: How Decentralized Organizations Actually Work 16 Stablecoins – The Bridges Between Volatility and Value 17 DAOs in Practice – From Multi-Sig to Voting (And Why Ownership Tokens exist) 18 Blockchain Oracles: How Smart Contracts See the Real World (Featuring Chainlink) 19 Cross-Chain Bridges: How Assets Travel Between Blockchains (Without Getting Robbed) 20 MEV (Maximal Extractable Value): The Invisible Tax on Every Blockchain Transaction 21 Layer 0 & Layer 3 — How Blockchains Become an Internet, Not Islands 22 Web3 Infrastructure: RPCs, Nodes, Infura/Alchemy (The Invisible Plumbing) 23 On-Chain Identity — ENS, Soulbound Tokens & Your Web3 Resume 24 Crypto Regulation 101 — SEC, MiCA & What Builders Should Actually Care About 25 Solidity Basics (Part 1) — Variables, Functions & Your First Real Contract 26 Solidity Basics (Part 2) — Arrays, Mappings & Structs (Upgrading the Web3 Journey Logger) 27 Vibecoding On‑Chain — Using AI to Prototype Solidity Contracts (Safely) 28 How to Review AI‑Generated Solidity Like an Auditor (For Beginners) 29 Smart Contract Security 101 — Reentrancy & Common AI‑Generated Mistakes 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 Ribhav Follow Web3 Learner | Community Builder | Technical Writer | Learning DevRel in Public New to Web3 ? Join: https://t.me/Web3ForHumans Location Ludhiana Education MIT Manipal Joined Feb 1, 2022 More from Ribhav Smart Contract Security 101 — Reentrancy & Common AI‑Generated Mistakes # security # crypto # blockchain # beginners How to Review AI‑Generated Solidity Like an Auditor (For Beginners) # crypto # blockchain # ai # beginners Vibecoding On‑Chain — Using AI to Prototype Solidity Contracts (Safely) # crypto # blockchain # vibecoding # beginners 💎 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. Home About Contact 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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2026-01-13T08:49:43
https://dev.to/t/communication/page/8
Communication Page 8 - 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 # communication Follow Hide Tips for talking effectively with your children at every age. Create Post Older #communication posts 5 6 7 8 9 10 11 12 13 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Essential Software for Working From Home QuanticDev QuanticDev QuanticDev Follow May 13 '20 Essential Software for Working From Home # workingfromhome # communication # collaboration 2  reactions Comments Add Comment 1 min read IPC between C# and C++ by using named pipes Josef Biehler Josef Biehler Josef Biehler Follow May 3 '20 IPC between C# and C++ by using named pipes # csharp # cpp # communication # network 29  reactions Comments 1  comment 4 min read How to effectively communicate with your clients? Muhammad Arslan Aslam Muhammad Arslan Aslam Muhammad Arslan Aslam Follow Apr 27 '20 How to effectively communicate with your clients? # discuss # freelancing # communication 2  reactions Comments Add Comment 1 min read How To Secure The Communication Of Your Remote Team Nikola Baldikov Nikola Baldikov Nikola Baldikov Follow Apr 22 '20 How To Secure The Communication Of Your Remote Team # Secure # Communication # remote # team 2  reactions Comments 1  comment 7 min read Public speaking in times of Covid19 Davide de Paolis Davide de Paolis Davide de Paolis Follow Apr 21 '20 Public speaking in times of Covid19 # publicspeaking # career # remotework # communication 6  reactions Comments Add Comment 4 min read Building solutions that fight back Pooja Mistry Pooja Mistry Pooja Mistry Follow for IBM Developer Apr 13 '20 Building solutions that fight back # tutorial # communication # webinar # development 5  reactions Comments Add Comment 5 min read Quarentou: E agora? 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Davide de Paolis Davide de Paolis Davide de Paolis Follow Mar 30 '20 Please be professional and stop saying "I'm almost done!" # beginners # bestpractices # communication # career 165  reactions Comments 39  comments 6 min read 6 Tips to Solve Miscommunication in Dev Teams Sara Miteva Sara Miteva Sara Miteva Follow for Microtica Mar 23 '20 6 Tips to Solve Miscommunication in Dev Teams # communication # development # team 13  reactions Comments 2  comments 4 min read Non-Violent Code Reviews Niels Theen Niels Theen Niels Theen Follow Mar 21 '20 Non-Violent Code Reviews # codequality # review # communication 12  reactions Comments Add Comment 2 min read No fear of Videoconferencing Thomas Scharke Thomas Scharke Thomas Scharke Follow Mar 15 '20 No fear of Videoconferencing # communication # video # remote # people 6  reactions Comments 3  comments 2 min read Convention over Conversation Sam Jarman 👨🏼‍💻 Sam Jarman 👨🏼‍💻 Sam Jarman 👨🏼‍💻 Follow Mar 9 '20 Convention over Conversation # journey # teamwork # communication 7  reactions Comments Add Comment 5 min read Programming is a social activity, source code is communication Charles Szilagyi Charles Szilagyi Charles Szilagyi Follow Mar 3 '20 Programming is a social activity, source code is communication # programming # team # communication # productivity 5  reactions Comments Add Comment 2 min read Estimating software: How to deal with requests for estimates Barry O Sullivan Barry O Sullivan Barry O Sullivan Follow Mar 2 '20 Estimating software: How to deal with requests for estimates # estimates # productivity # communication 22  reactions Comments Add Comment 7 min read A Time without a Zone Josh Branchaud Josh Branchaud Josh Branchaud Follow Feb 28 '20 A Time without a Zone # communication # learninpublic 6  reactions Comments Add Comment 2 min read Dev Huddle: An agile ceremony for devs Gabrielle Duarte Gabrielle Duarte Gabrielle Duarte Follow Feb 26 '20 Dev Huddle: An agile ceremony for devs # agile # planning # communication # ceremony 33  reactions Comments 2  comments 4 min read Book Club: Communication and Metrics Edition Tanya Janca Tanya Janca Tanya Janca Follow Feb 18 '20 Book Club: Communication and Metrics Edition # social # tech # communication # metrics 17  reactions Comments 2  comments 5 min read Professional communication skills - Intro Xinran Wang Xinran Wang Xinran Wang Follow Feb 11 '20 Professional communication skills - Intro # career # communication # growth 62  reactions Comments 6  comments 2 min read How to Support Junior Developers Domenico Solazzo Domenico Solazzo Domenico Solazzo Follow Feb 9 '20 How to Support Junior Developers # discuss # mentoring # career # communication 40  reactions Comments 2  comments 5 min read Conference Talk: Technical Debt Must Die Matt Eland Matt Eland Matt Eland Follow for Pluralsight Feb 8 '20 Conference Talk: Technical Debt Must Die # techtalks # codequality # codemash # communication 62  reactions Comments 5  comments 1 min read Personas in Writing Matt Eland Matt Eland Matt Eland Follow Jan 31 '20 Personas in Writing # communication # writing # blogging 51  reactions Comments 1  comment 9 min read How to Weaponize Impostor Syndrome Matt Eland Matt Eland Matt Eland Follow Jan 22 '20 How to Weaponize Impostor Syndrome # career # communication # impostorsyndrome 149  reactions Comments 5  comments 6 min read What are ways to convey language- and framework-properties in a better way in teams? Thomas Scharke Thomas Scharke Thomas Scharke Follow Dec 29 '19 What are ways to convey language- and framework-properties in a better way in teams? # communication # codequality # agile # motivation 4  reactions Comments 1  comment 4 min read Defining Technical Debt Matt Eland Matt Eland Matt Eland Follow Dec 23 '19 Defining Technical Debt # techdebt # management # codequality # communication 112  reactions Comments 6  comments 6 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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2026-01-13T08:49:43
https://forem.com/t/hackathon
Hackathon - Forem 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. 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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 # hackathon Follow Hide Rapid collaborative event Create Post Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Hackathon Highlights: Building and Livestreaming an AI Travel Agent Michael J. Larocca Michael J. Larocca Michael J. Larocca Follow Jan 12 Hackathon Highlights: Building and Livestreaming an AI Travel Agent # hackathon # ai # agents # codenewbie Comments Add Comment 7 min read Time to Build: AceHack 5.0 Registrations Are Open AceHack AceHack AceHack Follow Jan 12 Time to Build: AceHack 5.0 Registrations Are Open # acehack # hackathon # developers # rajasthan Comments Add Comment 2 min read Building SOC-AI: Sub-Second Security Triage with Groq & Kestra Kaushik Kaushik Kaushik Follow Jan 6 Building SOC-AI: Sub-Second Security Triage with Groq & Kestra # ai # cybersecurity # javascript # hackathon Comments Add Comment 2 min read Using Amazon Bedrock with AWS Free Tier for the 10,000 AIdeas Competition 🛠️ Laura Salinas Laura Salinas Laura Salinas Follow for AWS Jan 6 Using Amazon Bedrock with AWS Free Tier for the 10,000 AIdeas Competition 🛠️ # aws # hackathon # ai 3  reactions Comments Add Comment 6 min read Building an Adaptive Learning Agent Using Kiro IDE- agentic-ai-edtech Asim Shaikh Asim Shaikh Asim Shaikh Follow Dec 30 '25 Building an Adaptive Learning Agent Using Kiro IDE- agentic-ai-edtech # aws # kiroide # ai # hackathon Comments Add Comment 2 min read All things Kiro & Road to reinvent Hackathon Experience 2025 VijayaNirmalaGopal VijayaNirmalaGopal VijayaNirmalaGopal Follow for AWS Community Builders Dec 24 '25 All things Kiro & Road to reinvent Hackathon Experience 2025 # aws # kiro # hackathon # ai 8  reactions Comments Add Comment 4 min read Michael VS HackPompey Round 2 Michael Parker Michael Parker Michael Parker Follow Dec 20 '25 Michael VS HackPompey Round 2 # python # hackathon # webdev # programming 1  reaction Comments Add Comment 4 min read The CISO Checklist for New Zealand SMBs in 2026: What Actually Reduces Risk Gaurav Sengar Gaurav Sengar Gaurav Sengar Follow Dec 17 '25 The CISO Checklist for New Zealand SMBs in 2026: What Actually Reduces Risk # cybersecurity # linux # hackathon # opensource Comments Add Comment 3 min read Building VT100 AI-Powered Typing Tutor with Kiro Gabi Zuniga Gabi Zuniga Gabi Zuniga Follow Dec 5 '25 Building VT100 AI-Powered Typing Tutor with Kiro # kiro # kiroween # ai # hackathon Comments Add Comment 7 min read 🧟‍♂️ Stitching the Spirit: Engineering a "Frankenstein" AI Agent with Kiro & MCP Vaishnavi Mishra Vaishnavi Mishra Vaishnavi Mishra Follow Dec 5 '25 🧟‍♂️ Stitching the Spirit: Engineering a "Frankenstein" AI Agent with Kiro & MCP # ai # hackathon # javascript # kiro Comments Add Comment 5 min read We Built a Tool That Resurrects Dead UIs in 30 Seconds Qasim Khan Qasim Khan Qasim Khan Follow Dec 5 '25 We Built a Tool That Resurrects Dead UIs in 30 Seconds # kiro # hackathon # vibecoding Comments Add Comment 5 min read Building a Super Bowl Tech Startup in 48 Hours: How a Non-Technical Latina Founder Hired 2 AI Co-Founders (Kiro & Gemini) Socialmeet Club by Marilyn Alvarado Socialmeet Club by Marilyn Alvarado Socialmeet Club by Marilyn Alvarado Follow Dec 5 '25 Building a Super Bowl Tech Startup in 48 Hours: How a Non-Technical Latina Founder Hired 2 AI Co-Founders (Kiro & Gemini) # kiro # hackathon # ai # startup Comments Add Comment 3 min read How Kiro Cut My API Integration Time from 4 Hours to 10 Seconds Solomon Oluwaseun Solomon Oluwaseun Solomon Oluwaseun Follow Dec 5 '25 How Kiro Cut My API Integration Time from 4 Hours to 10 Seconds # kiro # ai # hackathon # webdev Comments Add Comment 3 min read Building EduCollab: How Kiro’s Multi-Feature Approach Revolutionized My Development Workflow PRIYADARSHINI R PRIYADARSHINI R PRIYADARSHINI R Follow Dec 5 '25 Building EduCollab: How Kiro’s Multi-Feature Approach Revolutionized My Development Workflow # kiro # supabase # react # hackathon Comments Add Comment 3 min read How we built a SaaS orchestration platform in 3 weeks - The story of Distrogent, for Kiroween! Pranavan Vadivelu Murali Pranavan Vadivelu Murali Pranavan Vadivelu Murali Follow Dec 5 '25 How we built a SaaS orchestration platform in 3 weeks - The story of Distrogent, for Kiroween! # hackathon # kiroween # kiro # kubernetes Comments Add Comment 2 min read I Built a Haunted Digital Pet That Feeds on Git Commits (with Kiro) Manish Manish Manish Follow Dec 5 '25 I Built a Haunted Digital Pet That Feeds on Git Commits (with Kiro) # kiro # webdev # electron # hackathon Comments Add Comment 2 min read Building Adiutor: How Kiro Accelerated Our Real-Time Task Management Project John Oh John Oh John Oh Follow Dec 5 '25 Building Adiutor: How Kiro Accelerated Our Real-Time Task Management Project # kiro # ai # hackathon Comments Add Comment 2 min read I Built a Haunted Spreadsheet Synthesizer with Kiro (and it screams at you) 👻 Harish Kotra (he/him) Harish Kotra (he/him) Harish Kotra (he/him) Follow Dec 5 '25 I Built a Haunted Spreadsheet Synthesizer with Kiro (and it screams at you) 👻 # showdev # kiro # hackathon # react Comments Add Comment 3 min read 🌩️ Building a Haunted Weather App: A Spooky Journey into 3D Web Development boyd boyd boyd Follow Dec 4 '25 🌩️ Building a Haunted Weather App: A Spooky Journey into 3D Web Development # kiro # kiroween # hackathon # kirodotdev Comments Add Comment 6 min read Cloudconjure Jayanth T Jayanth T Jayanth T Follow Dec 5 '25 Cloudconjure # kiro # hackathon # aws # mcp Comments Add Comment 1 min read How I Resurrected Legacy Code with AI: Building CodePhoenix for Kiroween Prajwal Sutar Prajwal Sutar Prajwal Sutar Follow Dec 4 '25 How I Resurrected Legacy Code with AI: Building CodePhoenix for Kiroween # kiroween # hackathon # ai # legacycode Comments Add Comment 10 min read I Built a Journal That Rewrites Your Past (Thanks, Kiro) Ansari Gufran Ansari Gufran Ansari Gufran Follow Dec 4 '25 I Built a Journal That Rewrites Your Past (Thanks, Kiro) # kiro # hackathon # halloween # webdev Comments Add Comment 1 min read Building Frankenstein's Séance: How I Built a Polyglot AI Platform in 3 Weeks (Part-Time) with Kiro Kishore Allwynraj Kishore Allwynraj Kishore Allwynraj Follow Dec 3 '25 Building Frankenstein's Séance: How I Built a Polyglot AI Platform in 3 Weeks (Part-Time) with Kiro # kiro # microfrontend # microservices # hackathon Comments Add Comment 7 min read Haunted Code & Spec-Driven Dreams: How Kiro Built My Spooky Time Machine! Likheet Shetty Likheet Shetty Likheet Shetty Follow Dec 3 '25 Haunted Code & Spec-Driven Dreams: How Kiro Built My Spooky Time Machine! # kiro # halloween # hackathon 1  reaction Comments Add Comment 5 min read Building a Multi-Agent Ghost Story: How Kiro’s Hybrid Development Changed Everything Ayush Pathak Ayush Pathak Ayush Pathak Follow Dec 5 '25 Building a Multi-Agent Ghost Story: How Kiro’s Hybrid Development Changed Everything # webdev # kiro # vibecoding # hackathon Comments Add Comment 8 min read loading... trending guides/resources No Vibe No Code: Bootstrapping Ideas All things Kiro & Road to reinvent Hackathon Experience 2025 Using Amazon Bedrock with AWS Free Tier for the 10,000 AIdeas Competition 🛠️ NightShift MD - A Streamlined After-Hours Medical Triage System Built with Kiro 🚀 LIVE & UPCOMING TECH & HACKATHON OPPORTUNITIES (2025–26) A song for Kiro and my project for the kiroween 2025 Building 1000 Candles: A Digital Memorial That Taught Me About Scale, Optimization, and Remembrance I Built a Real-Time 1v1 Coding Battle Platform in Days Using Kiro EXHUMING ELIZA: How I Resurrected The 1966 AI Therapist with Kiro and Powered It With Amazon Nova... 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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 Forem Close # introduction Follow Hide Create Post Older #introduction posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Hello Dev.to — Lessons from Systems That Worked in Dev (and Failed in Prod) vanitha natarajan vanitha natarajan vanitha natarajan Follow Jan 3 Hello Dev.to — Lessons from Systems That Worked in Dev (and Failed in Prod) # introduction # backend # api # architecture Comments Add Comment 1 min read Who Is Ayush Kumar Rai? A Full Stack Developer’s Journey into Tech Ayush Kumar Rai Ayush Kumar Rai Ayush Kumar Rai Follow Dec 23 '25 Who Is Ayush Kumar Rai? A Full Stack Developer’s Journey into Tech # webdev # ayushkumarrai # introduction Comments Add Comment 2 min read Hello dev.to — I’m Mehran, and I Build Practical Software That Solves Real Problems ChampsPoint ChampsPoint ChampsPoint Follow Dec 22 '25 Hello dev.to — I’m Mehran, and I Build Practical Software That Solves Real Problems # introduction # php # python # software 1  reaction Comments Add Comment 2 min read Hello DEV Community 👋 — I'm Sebastien, a Full-Stack & iOS Developer Sebastien Lato Sebastien Lato Sebastien Lato Follow Nov 24 '25 Hello DEV Community 👋 — I'm Sebastien, a Full-Stack & iOS Developer # introduction # swift # react # devcommunity Comments Add Comment 1 min read Starting My Dev.to Journey: Learning, Building & Sharing Vishnu Garuda Vishnu Garuda Vishnu Garuda Follow Nov 21 '25 Starting My Dev.to Journey: Learning, Building & Sharing # introduction # coding # datascience # bigdata Comments Add Comment 1 min read #0 Intro JEON HYUNJUN JEON HYUNJUN JEON HYUNJUN Follow Dec 18 '25 #0 Intro # introduction # welcome # firstpost Comments Add Comment 1 min read 👋🏾 From Ghana to Full-Stack: My Journey as a Self-Taught Developer Godfred Kwesi Agyeman Godfred Kwesi Agyeman Godfred Kwesi Agyeman Follow Nov 7 '25 👋🏾 From Ghana to Full-Stack: My Journey as a Self-Taught Developer # fullstack # career # learning # introduction 3  reactions Comments Add Comment 2 min read Hello, World! 👋 Aryan Barde Aryan Barde Aryan Barde Follow Nov 1 '25 Hello, World! 👋 # developer # introduction # programming # ai Comments Add Comment 1 min read Introduction to GO Programming Srinivasulu Paranduru Srinivasulu Paranduru Srinivasulu Paranduru Follow for AWS Community Builders Nov 20 '25 Introduction to GO Programming # go # introduction # modules Comments Add Comment 8 min read 🧠 From Code to Clarity: A Journey Through Backend, DevOps, and Beyond…. 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Seitz Derek L. Seitz Derek L. Seitz Follow Sep 13 '25 #0 - Setting Up Camp # fullstack # developerjourney # buildinpublic # introduction Comments Add Comment 2 min read Excited to Join Dev.to — Sharing 3+ Years of UI/UX Passion! Enas Almajdoub Enas Almajdoub Enas Almajdoub Follow Aug 12 '25 Excited to Join Dev.to — Sharing 3+ Years of UI/UX Passion! # uidesign # uiux # uxdesign # introduction Comments 1  comment 1 min read 100 days of Python. TANYA LYOP ACHAYI TANYA LYOP ACHAYI TANYA LYOP ACHAYI Follow Aug 18 '25 100 days of Python. # python # 100daysofcode # introduction # learning Comments Add Comment 1 min read Hello DEV! MANYCON Here — Building Safer, Smarter Spaces MANYCON MANYCON MANYCON Follow Jul 21 '25 Hello DEV! 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2026-01-13T08:49:43
https://www.youtube.com/watch?v=6ywxXCrMIEU
How to get started with AI coding for Startups | Introduction to Fine - YouTube 정보 보도자료 저작권 문의하기 크리에이터 광고 개발자 약관 개인정보처리방침 정책 및 안전 YouTube 작동의 원리 새로운 기능 테스트하기 © 2026 Google LLC, Sundar Pichai, 1600 Amphitheatre Parkway, Mountain View CA 94043, USA, 0807-882-594 (무료), yt-support-solutions-kr@google.com, 호스팅: Google LLC, 사업자정보 , 불법촬영물 신고 크리에이터들이 유튜브 상에 게시, 태그 또는 추천한 상품들은 판매자들의 약관에 따라 판매됩니다. 유튜브는 이러한 제품들을 판매하지 않으며, 그에 대한 책임을 지지 않습니다. var ytInitialData = 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2026-01-13T08:49:43
https://docs.devcycle.com/integrations/bitbucket/feature-usage-action
Bitbucket: Feature Flag Code Usages | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up On this page Bitbucket: Feature Flag Code Usages Get the integration on the Bitbucket Marketplace Bitbucket Pipelines Pipe: DevCycle Code References Code References of DevCycle Variables pushed to DevCycle With this Bitbucket pipeline, your DevCycle dashboard will be updated to display code snippets for each DevCycle variable usage within your project. Note: This is intended to run when pushing changes to your main branch Example Output ​ YAML Definition ​ Add the following snippet to your bitbucket-pipelines.yml file: branches : main : - step : script : - pipe : devcyclehq/bitbucket - code - refs - pipe : 1.0.3 variables : PROJECT_KEY : '<string>' CLIENT_ID : '<string>' CLIENT_SECRET : '<string>' Variables ​ To add variables to be used in the bitbucket-pipelines.yml , an admin must add Repository Variables in Repository Settings > Repository Variables , and then add all necessary variables as secured variables Variable Usage PROJECT_KEY (*) Your DevCycle project key, see Projects CLIENT_ID (*) Your organization's API client ID, see Organization Settings CLIENT_SECRET (*) Your organization's API client secret, see Organization Settings (*) = required variable. Prerequisites ​ Create a new Project & a new Feature Grab the PROJECT_KEY in Projects , and find your specific project name & key Grab the CLIENT_ID in Settings , under API AUTHENTICATION Grab the CLIENT_SECRET in Settings , under API AUTHENTICATION Examples ​ Example: - pipe : devcyclehq/bitbucket - code - refs - pipe : 1.0.3 variables : PROJECT_KEY : $PROJECT_KEY CLIENT_ID : $CLIENT_ID CLIENT_SECRET : $CLIENT_SECRET Support ​ The pipe is maintained by [email protected] . If you are reporting an issue, please include: the version of the pipe relevant logs and error messages steps to reproduce Edit this page Example Output YAML Definition Variables Prerequisites Examples Support DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://dev.to/godofgeeks
Aviral Srivastava - 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 Follow User actions Aviral Srivastava Hi! I am a student currently pursuing my Undergraduate degree in Computer Science and Engineering in India. Location Delhi, India Joined Joined on  Jan 23, 2021 Personal website https://mraviral.in github website twitter website More info about @godofgeeks Badges Four Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least four 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 Three Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least three years. Got it Close Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. 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 Post 355 posts published Comment 0 comments written Tag 18 tags followed Testing in Rust Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 13 Testing in Rust # rust # testing # tutorial Comments Add Comment 9 min read Rust Macros System Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 12 Rust Macros System # automation # productivity # rust # tutorial 1  reaction Comments 1  comment 9 min read Unsafe Rust: When and Why Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 11 Unsafe Rust: When and Why # learning # performance # rust Comments Add Comment 8 min read Rust Smart Pointers (Box, Rc, Arc) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 10 Rust Smart Pointers (Box, Rc, Arc) # beginners # rust # tutorial 1  reaction Comments Add Comment 9 min read Async Programming in Rust (async/await) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 9 Async Programming in Rust (async/await) # performance # rust # tutorial 1  reaction Comments Add Comment 8 min read Concurrency in Rust (Threads, Channels) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 8 Concurrency in Rust (Threads, Channels) # performance # programming # rust # tutorial Comments Add Comment 10 min read Error Handling in Rust (Result & Option) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 6 Error Handling in Rust (Result & Option) # beginners # codequality # rust # tutorial Comments Add Comment 8 min read Pattern Matching in Rust Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 5 Pattern Matching in Rust # beginners # programming # rust # tutorial Comments Add Comment 8 min read Rust Structs and Enums Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 4 Rust Structs and Enums # beginners # rust # tutorial Comments Add Comment 8 min read Rust Lifetimes Explained Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 3 Rust Lifetimes Explained # beginners # programming # rust # tutorial 9  reactions Comments Add Comment 7 min read Rust Lifetimes Explained Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Jan 3 Rust Lifetimes Explained # beginners # rust # tutorial Comments Add Comment 10 min read Linux from Scratch Basics Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 31 '25 Linux from Scratch Basics # learning # tutorial # opensource # linux Comments Add Comment 7 min read Logging at Scale & Log Aggregation Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 30 '25 Logging at Scale & Log Aggregation # systemdesign # architecture # devops # monitoring Comments Add Comment 8 min read Edge Computing in Backend Architectures Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 29 '25 Edge Computing in Backend Architectures # architecture # backend # performance Comments Add Comment 8 min read Database Migrations and ORM in Go (GORM, sqlc) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 28 '25 Database Migrations and ORM in Go (GORM, sqlc) # database # go # sql # tutorial Comments Add Comment 9 min read Pythonic Best Practices & Idioms Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 27 '25 Pythonic Best Practices & Idioms # learning # python # tutorial 1  reaction Comments Add Comment 8 min read Progressive Web Apps Fundamentals Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 26 '25 Progressive Web Apps Fundamentals # beginners # mobile # webdev Comments Add Comment 7 min read Node.js Version Management with nvm Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 25 '25 Node.js Version Management with nvm # tooling # javascript # node # tutorial Comments Add Comment 9 min read AWS Global Accelerator Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 24 '25 AWS Global Accelerator # aws # performance # networking # architecture Comments Add Comment 8 min read Azure Backup & Disaster Recovery Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 23 '25 Azure Backup & Disaster Recovery # devops # cloud # azure # security Comments Add Comment 8 min read DevOps in Hybrid/Multicloud Environments Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 22 '25 DevOps in Hybrid/Multicloud Environments # architecture # cloudcomputing # devops Comments Add Comment 7 min read Kubernetes Performance Tuning Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 21 '25 Kubernetes Performance Tuning # devops # kubernetes # performance Comments Add Comment 9 min read Docker for HPC & GPU Workloads Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 20 '25 Docker for HPC & GPU Workloads # devops # docker # performance Comments Add Comment 7 min read WebSocket Security Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 19 '25 WebSocket Security Comments Add Comment 10 min read Pen Testing IoT Devices Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 18 '25 Pen Testing IoT Devices # cybersecurity # testing # iot # security Comments Add Comment 8 min read Endpoint Detection & Response (EDR) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 17 '25 Endpoint Detection & Response (EDR) # cybersecurity # security # beginners # monitoring Comments Add Comment 6 min read Advanced Load Balancing Solutions Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 16 '25 Advanced Load Balancing Solutions # architecture # networking # performance Comments Add Comment 8 min read Progressive Delivery (Canary, Blue-Green) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 6 '25 Progressive Delivery (Canary, Blue-Green) Comments Add Comment 5 min read Data Backup and Disaster Recovery in Kubernetes Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 5 '25 Data Backup and Disaster Recovery in Kubernetes # data # devops # kubernetes Comments Add Comment 5 min read Docker Compose vs. Helm in local dev Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 4 '25 Docker Compose vs. Helm in local dev # devops # docker # kubernetes # tooling 3  reactions Comments Add Comment 5 min read File Upload Security Issues Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 3 '25 File Upload Security Issues # cybersecurity # security # webdev Comments Add Comment 5 min read Bypassing Web Application Firewalls Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 2 '25 Bypassing Web Application Firewalls # cybersecurity # security # web 3  reactions Comments Add Comment 5 min read Security Analytics with Machine Learning Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Dec 1 '25 Security Analytics with Machine Learning # analytics # cybersecurity # machinelearning 1  reaction Comments 1  comment 5 min read High-Performance Networking (RDMA, InfiniBand) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 30 '25 High-Performance Networking (RDMA, InfiniBand) # distributedsystems # networking # performance Comments Add Comment 5 min read NFS, SMB, and File Sharing Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 29 '25 NFS, SMB, and File Sharing # distributedsystems # networking # security Comments Add Comment 6 min read Handling Hot Keys in Caches Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 28 '25 Handling Hot Keys in Caches # distributedsystems # performance # systemdesign Comments Add Comment 5 min read Secrets Management in Production Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 27 '25 Secrets Management in Production # devops # distributedsystems # security Comments Add Comment 6 min read Cross-compiling Go Applications Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 26 '25 Cross-compiling Go Applications # go # tooling # tutorial Comments Add Comment 5 min read Multi-threading vs. Multiprocessing Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 25 '25 Multi-threading vs. Multiprocessing # architecture # computerscience # performance Comments Add Comment 5 min read JavaScript Garbage Collection Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 24 '25 JavaScript Garbage Collection # computerscience # javascript # performance Comments Add Comment 5 min read Build Tools (Gulp, Grunt) and the Node ecosystem Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 23 '25 Build Tools (Gulp, Grunt) and the Node ecosystem Comments Add Comment 6 min read AWS Batch & HPC Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 22 '25 AWS Batch & HPC # aws # devops # performance Comments Add Comment 5 min read Azure Synapse Analytics Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 21 '25 Azure Synapse Analytics # analytics # cloud # dataengineering # azure Comments Add Comment 5 min read Secrets Management (Vault, KMS) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 20 '25 Secrets Management (Vault, KMS) Comments Add Comment 5 min read KubeEdge and Edge Computing Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 19 '25 KubeEdge and Edge Computing # distributedsystems # iot # opensource # kubernetes Comments Add Comment 5 min read Image Scanning Tools (Anchore, Clair) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 18 '25 Image Scanning Tools (Anchore, Clair) # containers # tooling # security # devops Comments Add Comment 6 min read API Rate Limiting & Security Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 17 '25 API Rate Limiting & Security # api # performance # security Comments Add Comment 6 min read Custom Exploit Development Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 16 '25 Custom Exploit Development # cybersecurity # programming # security 5  reactions Comments Add Comment 5 min read Secure DevSecOps Pipelines Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 15 '25 Secure DevSecOps Pipelines # cicd # devops # security Comments Add Comment 5 min read Wireless Networking Standards (802.11ac, 802.11ax) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 14 '25 Wireless Networking Standards (802.11ac, 802.11ax) # learning # networking # performance 5  reactions Comments 1  comment 5 min read Disk Partitioning Strategies (fdisk, parted) Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 13 '25 Disk Partitioning Strategies (fdisk, parted) # cli # linux # tooling Comments 1  comment 5 min read Rate-based vs. Window-based Throttling Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 12 '25 Rate-based vs. Window-based Throttling # systemdesign # api # security # performance 1  reaction Comments Add Comment 5 min read Infrastructure Monitoring & Alerting Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 11 '25 Infrastructure Monitoring & Alerting 1  reaction Comments 1  comment 5 min read Embedding and Filesystems in Go Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 10 '25 Embedding and Filesystems in Go # go # programming # tutorial Comments Add Comment 4 min read Data Visualization with matplotlib & seaborn Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 9 '25 Data Visualization with matplotlib & seaborn # datascience # python # tutorial Comments Add Comment 5 min read Performance Optimization for JS Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 8 '25 Performance Optimization for JS # performance # tutorial # webdev # javascript Comments Add Comment 6 min read Cluster Module & Scaling Node Apps Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 7 '25 Cluster Module & Scaling Node Apps # node # performance # javascript # architecture 1  reaction Comments Add Comment 6 min read AWS CodePipeline & CodeBuild Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 6 '25 AWS CodePipeline & CodeBuild # cicd # tutorial # aws # devops Comments Add Comment 5 min read Azure Data Factory for ETL Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 5 '25 Azure Data Factory for ETL # dataengineering # azure # tutorial # cloudcomputing Comments Add Comment 5 min read GitOps Principles and Workflows Aviral Srivastava Aviral Srivastava Aviral Srivastava Follow Nov 4 '25 GitOps Principles and Workflows # cicd # devops # git # automation Comments Add Comment 5 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. 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
2026-01-13T08:49:43
https://docs.devcycle.com/integrations/github/pr-insights-action
GitHub: Feature Flag Change Insights on Pull Request | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up On this page GitHub: Feature Flag Change Insights on Pull Request Get the integration on the GitHub Marketplace Overview ​ With this Github action, information on which DevCycle features have been added or removed in a code change will be shown directly on each Pull Request as a comment. Note: This is intended for pull_request workflow events Example Output ​ Usage ​ Create a new Actions workflow in your GitHub repository (e.g. devcycle-insights.yml) in the .github/workflows directory. In your new file, paste the following code: on : pull_request jobs : dvc-feature-flag-insights : runs-on : ubuntu - latest name : Generate DevCycle PR Insights steps : - uses : actions/checkout@v4 with : fetch-depth : 0 - uses : DevCycleHQ/feature - flag - pr - insights - [email protected] with : # Token generated by GitHub github-token : $ { { secrets.GITHUB_TOKEN } } # Your DevCycle project key project-key : your - project - key # Your organization's DevCycle API client ID & secret client-id : $ { { secrets.DVC_CLIENT_ID } } client-secret : $ { { secrets.DVC_CLIENT_SECRET } } We recommend including your DevCycle API credentials and project token as inputs. If included, the PR comment will be enriched with Feature Flag data from DevCycle. When referencing your API client ID and secret, we recommend using GitHub Secrets to store your credentials securely. Inputs ​ input required description github-token yes The GitHub Actions token e.g. secrets.GITHUB_TOKEN project-key no Your DevCycle project key, see Projects client-id no Your organization's API client ID, see Organization Settings client-secret no Your organization's API client secret, see Organization Settings only-comment-on-change no If true, comments will only be added to PRs when changes to DevCycle variables are detected. Defaults to false. Configuration ​ The patterns used to identify references to variables in your code are fully customizable. This action uses the DevCycle CLI under the hood, for details on how to configure the pattern matcher see the CLI configuration . Edit this page Overview Example Output Usage Inputs Configuration DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://dev.to/setevoy
Arseny Zinchenko - 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 Follow User actions Arseny Zinchenko DevOps, cloud and infrastructure engineer. Love Linux, OpenSource, and AWS. Location Kiev, Ukraine Joined Joined on  Sep 16, 2017 Personal website https://rtfm.co.ua/en github website twitter website Eight Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least eight years. Got it Close 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 Writing Debut Awarded for writing and sharing your first DEV post! Continue sharing your work to earn the 4 Week Writing Streak Badge. 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You've written at least one post per week for 8 consecutive weeks. Unlock the 16-week badge next! Got it Close 4 Week Writing Streak You've posted at least one post per week for 4 consecutive weeks! 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 More info about @setevoy Organizations AWS Heroes AWS Community Builders GitHub Repositories rtfm Code posted in my blog. See README for details. Shell • 7 stars setevoy-aws-templates 2 stars Skills/Languages GNU/Linux - Arch, Debian/Ubuntu, CentOS. FreeBSD. AWS, Azure Python, Ruby, C, Groovy Ci/CD - Jenkins, Bamboo, TeamCity Docker Terraform, Ansible, Chef Currently hacking on My blog https://rtfm.co.ua/en/ Post 290 posts published Comment 25 comments written Tag 28 tags followed AWS: Monitoring AWS OpenSearch Service Cluster with CloudWatch Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 30 '25 AWS: Monitoring AWS OpenSearch Service Cluster with CloudWatch # aws # monitoring # devops # tutorial Comments Add Comment 20 min read Want to connect with Arseny Zinchenko? Create an account to connect with Arseny Zinchenko. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Terraform: creating an AWS OpenSearch Service cluster and users Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Heroes Dec 29 '25 Terraform: creating an AWS OpenSearch Service cluster and users # devops # aws # terraform # tutorial Comments Add Comment 16 min read Terraform: using Ephemeral Resources and Write-Only Attributes Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 28 '25 Terraform: using Ephemeral Resources and Write-Only Attributes # todayilearned # terraform # devops # tutorial Comments Add Comment 9 min read Terraform: AWS EKS Terraform module update from version 20.x to version 21.x Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Sep 13 '25 Terraform: AWS EKS Terraform module update from version 20.x to version 21.x # todayilearned # terraform # kubernetes # devops Comments Add Comment 12 min read Kubernetes: PVC in a StatefulSet, and the “Forbidden updates to statefulset spec” error Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Sep 13 '25 Kubernetes: PVC in a StatefulSet, and the “Forbidden updates to statefulset spec” error # todayilearned # devops # kubernetes Comments Add Comment 4 min read Kubernetes: what are the Kubernetes Operator and CustomResourceDefinition Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Sep 13 '25 Kubernetes: what are the Kubernetes Operator and CustomResourceDefinition # todayilearned # kubernetes # devops # tutorial Comments Add Comment 13 min read AWS: creating an OpenSearch Service cluster and configuring authentication and authorization Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Heroes Dec 28 '25 AWS: creating an OpenSearch Service cluster and configuring authentication and authorization # devops # aws # security Comments Add Comment 14 min read Kubernetes: Kubernetes API, API groups, CRDs, and the etcd Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Sep 13 '25 Kubernetes: Kubernetes API, API groups, CRDs, and the etcd # todayilearned # devops # kubernetes Comments Add Comment 8 min read Kubernetes: Pod resources.requests, resources.limits and Linux cgroup Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Sep 13 '25 Kubernetes: Pod resources.requests, resources.limits and Linux cgroup # todayilearned # linux # devops # kubernetes Comments Add Comment 12 min read AWS: introduction to the OpenSearch Service as a vector store Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Heroes Nov 1 '25 AWS: introduction to the OpenSearch Service as a vector store # devops # aws # ai # tutorial Comments Add Comment 19 min read VictoriaLogs: the "rate limit exceeded" error and monitoring ingested logs Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 28 '25 VictoriaLogs: the "rate limit exceeded" error and monitoring ingested logs # monitoring # devops # tutorial Comments Add Comment 7 min read VictoriaMetrics: migrating VMSingle and VictoriaLogs data between Kubernetes clusters Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 19 '25 VictoriaMetrics: migrating VMSingle and VictoriaLogs data between Kubernetes clusters # todayilearned # devops # kubernetes # monitoring 1  reaction Comments Add Comment 16 min read Terraform: using import, and some hidden pitfalls Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 19 '25 Terraform: using import, and some hidden pitfalls # todayilearned # devops # terraform 1  reaction Comments Add Comment 9 min read AI: Introduction to Ollama for local LLM launch Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 19 '25 AI: Introduction to Ollama for local LLM launch # todayilearned # llm # ai Comments Add Comment 10 min read Terraform: data types, loops, indexes, and the "resource must be replaced" issue Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 19 '25 Terraform: data types, loops, indexes, and the "resource must be replaced" issue # todayilearned # devops # terraform 2  reactions Comments Add Comment 8 min read Kubernetes: 503 errors with AWS ALB possible causes and solutions Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Community Builders Jul 19 '25 Kubernetes: 503 errors with AWS ALB possible causes and solutions # aws # devops # kubernetes # todayileraned 1  reaction Comments Add Comment 13 min read TCP/IP: OSI and TCP/IP models, TCP packets, Linux sockets and ports Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Sep 13 '25 TCP/IP: OSI and TCP/IP models, TCP packets, Linux sockets and ports # linux # tutorial # devops # networking Comments Add Comment 20 min read Python: introduction to the Celery, and its monitoring configurations Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 19 '25 Python: introduction to the Celery, and its monitoring configurations # todayilearned # python # programming Comments Add Comment 13 min read AI: writing an MCP server for VictoriaLogs Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 19 '25 AI: writing an MCP server for VictoriaLogs # ai # python # todayileraned Comments Add Comment 5 min read AI: What is the MCP? Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 28 '25 AI: What is the MCP? # todayilearned # ai # tutorial # python 1  reaction Comments Add Comment 7 min read Python: introduction to @decorators using FastAPI as an example Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 31 '25 Python: introduction to @decorators using FastAPI as an example # todayilearned # python Comments Add Comment 8 min read Nexus: Configuring Docker proxy repository, and ContainerD in Kubernetes Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 31 '25 Nexus: Configuring Docker proxy repository, and ContainerD in Kubernetes # devops # docker # kubernetes # tutorial 1  reaction Comments Add Comment 13 min read PostgreSQL: using EXPLAIN and setting up “auto_explain” in AWS RDS Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 22 '25 PostgreSQL: using EXPLAIN and setting up “auto_explain” in AWS RDS # aws # monitoring # devops # tutorial Comments Add Comment 11 min read PostgreSQL: AWS RDS Performance and monitoring Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 22 '25 PostgreSQL: AWS RDS Performance and monitoring # todayilearned # database # devops # tutorial Comments Add Comment 28 min read VictoriaLogs: creating Recording Rules with VMAlert Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 17 '25 VictoriaLogs: creating Recording Rules with VMAlert # devops # monitoring # tutorial Comments Add Comment 13 min read Nexus: running in Kubernetes, and setting up a PyPI caching repository Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 17 '25 Nexus: running in Kubernetes, and setting up a PyPI caching repository # aws # devops # kubernetes # tutorial Comments Add Comment 12 min read Kubernetes: a single AWS Load Balancer for different Kubernetes Ingresses Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 17 '25 Kubernetes: a single AWS Load Balancer for different Kubernetes Ingresses # kubernetes # aws # devops # tutorial Comments Add Comment 7 min read Vector.dev: introduction, AWS S3 logs, and integration with VictoriaLogs Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow May 17 '25 Vector.dev: introduction, AWS S3 logs, and integration with VictoriaLogs # monitoring # devops # aws # tutorial Comments Add Comment 13 min read VictoriaLogs: a Grafana dashboard for AWS VPC Flow Logs — migrating from Grafana Loki Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 21 '24 VictoriaLogs: a Grafana dashboard for AWS VPC Flow Logs — migrating from Grafana Loki # devops # monitoring # aws # tutorial Comments Add Comment 22 min read AWS: VPC Flow Logs — logs to S3 and Grafana dashboard with Loki Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 21 '24 AWS: VPC Flow Logs — logs to S3 and Grafana dashboard with Loki # devops # aws # monitoring # tutorial Comments Add Comment 16 min read GitHub Actions: running the Actions Runner Controller in Kubernetes Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 7 '24 GitHub Actions: running the Actions Runner Controller in Kubernetes # aws # kubernetes # devops # tutorial Comments Add Comment 18 min read Karpenter: an introduction to the Disruption Budgets Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Heroes Dec 7 '24 Karpenter: an introduction to the Disruption Budgets # kubernetes # devops # aws # karpenter Comments Add Comment 5 min read VictoriaMetrics Cloud: integration with AWS Data Firehose for CloudWatch metrics Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 7 '24 VictoriaMetrics Cloud: integration with AWS Data Firehose for CloudWatch metrics # devops # aws # monitoring # tutorial Comments Add Comment 5 min read VictoriaLogs: an overview, run in Kubernetes, LogsQL, and Grafana Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 7 '24 VictoriaLogs: an overview, run in Kubernetes, LogsQL, and Grafana # devops # monitoring # kubernetes # tutorial 2  reactions Comments Add Comment 20 min read AWS: Kubernetes and External Secrets Operator for AWS Secrets Manager Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 7 '24 AWS: Kubernetes and External Secrets Operator for AWS Secrets Manager # aws # devops # security # kubernetes Comments Add Comment 12 min read AWS: IAM Access Analyzer policy generation — create an IAM Policy Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Heroes Dec 7 '24 AWS: IAM Access Analyzer policy generation — create an IAM Policy # aws # devops # security # tutorial Comments Add Comment 6 min read Terraform: managing EKS Access Entries and EKS Pod Identities Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Oct 17 '24 Terraform: managing EKS Access Entries and EKS Pod Identities # aws # devops # kubernetes # terraform Comments Add Comment 19 min read Terraform: EKS and Karpenter — upgrade the module version from 19.21 to 20.0 Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Aug 24 '24 Terraform: EKS and Karpenter — upgrade the module version from 19.21 to 20.0 # kubernetes # devops # tutorial Comments Add Comment 20 min read AWS: Kubernetes and Access Management API, the new authentication in EKS Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Community Builders Jul 13 '24 AWS: Kubernetes and Access Management API, the new authentication in EKS # security # kubernetes # aws # devops 1  reaction Comments 1  comment 11 min read AWS: RDS IAM database authentication, EKS Pod Identities, and Terraform Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Community Builders Jul 13 '24 AWS: RDS IAM database authentication, EKS Pod Identities, and Terraform # kubernetes # devops # security # aws Comments Add Comment 12 min read AWS: Cost optimization — an overview of Bills, Cost Explorer, and the costs control Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Community Builders Jul 7 '24 AWS: Cost optimization — an overview of Bills, Cost Explorer, and the costs control # todayilearned # aws # devops Comments Add Comment 6 min read Kubernetes: containers, and the “lost” SIGTERM signals Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 7 '24 Kubernetes: containers, and the “lost” SIGTERM signals # todayilearned # linux # kubernetes # devops Comments Add Comment 12 min read Kubernetes: monitoring Events with kubectl and Grafana Loki Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 7 '24 Kubernetes: monitoring Events with kubectl and Grafana Loki # kubernetes # devops # monitoring Comments Add Comment 3 min read Pritunl: launching a VPN in AWS on EC2 with Terraform Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jul 7 '24 Pritunl: launching a VPN in AWS on EC2 with Terraform # aws # terraform # devops # tutorial Comments Add Comment 12 min read AWS: Karpenter and SSH for Kubernetes WorkerNodes Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Community Builders Jun 23 '24 AWS: Karpenter and SSH for Kubernetes WorkerNodes # security # aws # devops # kubernetes 4  reactions Comments Add Comment 10 min read Renovate: GitHub, and Helm Charts versions management Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jun 23 '24 Renovate: GitHub, and Helm Charts versions management # tutorial # github # devops Comments Add Comment 4 min read Dependabot: GitHub, and Terraform versions management Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Jun 23 '24 Dependabot: GitHub, and Terraform versions management # tutorial # github # devops # terraform Comments Add Comment 5 min read AWS: VPC Flow Logs, NAT Gateways, and Kubernetes Pods -  a detailed overview Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow for AWS Heroes Jun 23 '24 AWS: VPC Flow Logs, NAT Gateways, and Kubernetes Pods -  a detailed overview # todayilearned # devops # kubernetes # aws Comments Add Comment 17 min read GitHub Actions: Terraform deployments with a review of planned changes Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Mar 23 '24 GitHub Actions: Terraform deployments with a review of planned changes # terraform # github # devops # tutorial Comments Add Comment 16 min read Kubernetes: tracing requests with AWS X-Ray, and Grafana data source Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Mar 7 '24 Kubernetes: tracing requests with AWS X-Ray, and Grafana data source # kubernetes # aws # monitoring # devops Comments Add Comment 7 min read AWS: VPC Prefix and the maximum of Pods on Kubernetes WorkerNodes Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Mar 2 '24 AWS: VPC Prefix and the maximum of Pods on Kubernetes WorkerNodes # aws # kubernetes # todayileraned # devops Comments Add Comment 9 min read Terraform: creating a module for collecting AWS ALB logs in Grafana Loki Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Feb 29 '24 Terraform: creating a module for collecting AWS ALB logs in Grafana Loki # devops # tutorial # aws # terraform Comments Add Comment 11 min read Grafana Loki: LogQL and Recording Rules for metrics from AWS Load Balancer logs Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Feb 25 '24 Grafana Loki: LogQL and Recording Rules for metrics from AWS Load Balancer logs # todayilearned # monitoring # devops # tutorial Comments Add Comment 21 min read Karpenter: its monitoring, and Grafana dashboard for Kubernetes WorkerNodes Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Feb 24 '24 Karpenter: its monitoring, and Grafana dashboard for Kubernetes WorkerNodes # aws # devops # monitoring # grafana Comments Add Comment 14 min read AWS: EKS Pod Identities — a replacement for IRSA? Simplifying IAM access management Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 17 '23 AWS: EKS Pod Identities — a replacement for IRSA? Simplifying IAM access management # aws # devops # kubernetes # security 1  reaction Comments Add Comment 5 min read AWS: CloudWatch — Multi source query: collecting metrics from an external Prometheus Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 16 '23 AWS: CloudWatch — Multi source query: collecting metrics from an external Prometheus # todayilearned # monitoring # aws # devops Comments Add Comment 3 min read AWS: Amazon Q — an overview, features, and first impressions Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 14 '23 AWS: Amazon Q — an overview, features, and first impressions # todayilearned # ai # aws Comments Add Comment 9 min read AWS Elastic Kubernetes Service: RBAC Authorization via AWS IAM and RBAC Groups Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 13 '23 AWS Elastic Kubernetes Service: RBAC Authorization via AWS IAM and RBAC Groups # devops # aws # security # kubernetes 1  reaction Comments Add Comment 12 min read Grafana Loki: collecting AWS LoadBalancer logs from S3 with Promtail Lambda Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 13 '23 Grafana Loki: collecting AWS LoadBalancer logs from S3 with Promtail Lambda # aws # monitoring # devops # tutorial Comments Add Comment 6 min read Kubernetes: ensuring High Availability for Pods Arseny Zinchenko Arseny Zinchenko Arseny Zinchenko Follow Dec 13 '23 Kubernetes: ensuring High Availability for Pods # kubernetes # devops Comments Add Comment 6 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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2026-01-13T08:49:43
https://dev.to/t/software/page/6#main-content
Software Page 6 - 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. 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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 # software Follow Hide All things related to software development and engineering. Create Post Older #software posts 3 4 5 6 7 8 9 10 11 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Gambiarra is the real engineering superpower no one admits using <devtips/> <devtips/> <devtips/> Follow Nov 27 '25 Gambiarra is the real engineering superpower no one admits using # webdev # ai # programming # software Comments Add Comment 28 min read Businesses were losing customers to messy bookings — so I built Rezzervo Leon Shabani Leon Shabani Leon Shabani Follow Nov 27 '25 Businesses were losing customers to messy bookings — so I built Rezzervo # startup # software Comments Add Comment 1 min read How to Use Coverlet Coverage Thresholds to Enforce Better Testing Standards? Sophie Lane Sophie Lane Sophie Lane Follow Nov 26 '25 How to Use Coverlet Coverage Thresholds to Enforce Better Testing Standards? # webdev # codecoverage # software # devops Comments Add Comment 3 min read The Future Belongs to System Thinkers Farhan Nasir Farhan Nasir Farhan Nasir Follow Nov 26 '25 The Future Belongs to System Thinkers # webdev # ai # programming # software Comments Add Comment 1 min read The "And" Test: How I Spot a Monster Function Before it Bites Me Doogal Simpson Doogal Simpson Doogal Simpson Follow Dec 29 '25 The "And" Test: How I Spot a Monster Function Before it Bites Me # beginners # career # javascript # software 3  reactions Comments 2  comments 3 min read How Developers Can Make Money on YouTube Without Showing Their Face Software Developer Software Developer Software Developer Follow Dec 1 '25 How Developers Can Make Money on YouTube Without Showing Their Face # software # development # youtube # webmonetization Comments Add Comment 5 min read The Idle Consciousness: A Hegelian Reading of Human Servitude in the Age of AI Rafa Calderon Rafa Calderon Rafa Calderon Follow Dec 29 '25 The Idle Consciousness: A Hegelian Reading of Human Servitude in the Age of AI # philosophy # ai # ethics # software 6  reactions Comments Add Comment 4 min read How Regression Testing Keeps Agile Teams Fast, Reliable, and Release-Ready AIO Tests AIO Tests AIO Tests Follow Nov 26 '25 How Regression Testing Keeps Agile Teams Fast, Reliable, and Release-Ready # regressiontesting # software # testing Comments Add Comment 5 min read Complete Toolkit for LLM Development Zainudin Noori Zainudin Noori Zainudin Noori Follow Nov 24 '25 Complete Toolkit for LLM Development # ai # rag # software # gpt3 1  reaction Comments Add Comment 2 min read What happens when you try to get hired by the top IT companies TechPreneur: lesswork&earnmore TechPreneur: lesswork&earnmore TechPreneur: lesswork&earnmore Follow Nov 24 '25 What happens when you try to get hired by the top IT companies # software # career # hiring # interview Comments Add Comment 6 min read Basics to Improve Your Reasoning Athreya aka Maneshwar Athreya aka Maneshwar Athreya aka Maneshwar Follow Dec 18 '25 Basics to Improve Your Reasoning # webdev # programming # design # software 15  reactions Comments Add Comment 2 min read The Art, the Politics, and the Final Truth of Software Development Mr. 0x1 Mr. 0x1 Mr. 0x1 Follow Nov 24 '25 The Art, the Politics, and the Final Truth of Software Development # software # ai Comments Add Comment 3 min read Always Up, Never Chill: A Friendly Intro to Availability in Software David R David R David R Follow Nov 29 '25 Always Up, Never Chill: A Friendly Intro to Availability in Software # availability # cloud # software # sla Comments Add Comment 6 min read Go Memory Profiling & Performance Debugging — Real-World Guide to pprof Serif COLAKEL Serif COLAKEL Serif COLAKEL Follow Nov 23 '25 Go Memory Profiling & Performance Debugging — Real-World Guide to pprof # go # productivity # software # backend Comments Add Comment 3 min read JavaScript Vishal Thakkar Vishal Thakkar Vishal Thakkar Follow Dec 27 '25 JavaScript # javascript # java # softwaredevelopment # software Comments Add Comment 1 min read 🚀 Lean Startup: La guía moderna para crear productos que la gente realmente quiere joedev090 joedev090 joedev090 Follow Nov 22 '25 🚀 Lean Startup: La guía moderna para crear productos que la gente realmente quiere # leanstartup # agile # startup # software Comments Add Comment 4 min read Engineering Troubleshooting and Tool Combination for App HTTPS Packet Capture ObjC_Coder ObjC_Coder ObjC_Coder Follow Nov 28 '25 Engineering Troubleshooting and Tool Combination for App HTTPS Packet Capture # mobile # software Comments Add Comment 3 min read Linux Without Fanboyism: An Honest Developer’s Perspective José David Ureña Torres José David Ureña Torres José David Ureña Torres Follow Dec 14 '25 Linux Without Fanboyism: An Honest Developer’s Perspective # linux # programming # software # opensource 57  reactions Comments 17  comments 10 min read Why Debugging Skills Matter More Than Writing New Code Nilesh Raut Nilesh Raut Nilesh Raut Follow Dec 27 '25 Why Debugging Skills Matter More Than Writing New Code # software # programming # learning # debug 22  reactions Comments 5  comments 3 min read Podcasts I listened to in 2025 Aaron McCollum Aaron McCollum Aaron McCollum Follow Dec 15 '25 Podcasts I listened to in 2025 # podcast # software # yearinreview # programming Comments Add Comment 3 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 Real Truth About Becoming a Cracked Frontend Engineer (Not Just a “React Developer”) George Udonte George Udonte George Udonte Follow Nov 21 '25 The Real Truth About Becoming a Cracked Frontend Engineer (Not Just a “React Developer”) # frontend # react # software # webdev 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 How Much DevOps Knowledge Is Actually Required for an SDE? Nilesh Raut Nilesh Raut Nilesh Raut Follow Dec 22 '25 How Much DevOps Knowledge Is Actually Required for an SDE? # devops # software # sde # programming 17  reactions Comments 3  comments 3 min read Building a Linux OS with Yocto hang-up hang-up hang-up Follow Dec 13 '25 Building a Linux OS with Yocto # linux # virtualmachine # programming # software 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. 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
2026-01-13T08:49:43
https://dev.to/t/computerscience/page/5
Computer Science 🤓 Page 5 - 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 Computer Science 🤓 Follow Hide This tag is for sharing and asking questions about anything related to computer science, including data structures, algorithms, research, and white papers! 🤓 Create Post submission guidelines Please ensure that any post that is tagged with #computerscience is related to computer science in some way. Promotional posts will be untagged, as will posts unrelated to CS. Please also be sure that your content adheres to the DEV Code of Conduct and that your comments are constructive and kind. about #computerscience Did you learn about a new data structure recently? Or perhaps you tried to implement an algorithm in a new language? Or maybe you need help understanding a white paper? The #computerscience tag is a great place for any of these questions and ideas. Please be sure to cross-tag any content that might help other folks in the DEV community. For example, an introduction to linked lists should also be tagged with the #beginners tag. Similarly, a post that asks for a simple explanation to the traveling salesman problem should be tagged with the #explainlikeimfive tag. Older #computerscience posts 2 3 4 5 6 7 8 9 10 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Day 2/30 smol smol smol Follow Dec 19 '25 Day 2/30 # computerscience # devjournal # javascript Comments Add Comment 1 min read DISTRIBUTED SYSTEMS Tuntufye Mwakalasya Tuntufye Mwakalasya Tuntufye Mwakalasya Follow Dec 17 '25 DISTRIBUTED SYSTEMS # architecture # computerscience # systemdesign Comments Add Comment 7 min read How to Read a Scientific Paper Efficiently: A 5-Step Guide Nastaran Moghadasi Nastaran Moghadasi Nastaran Moghadasi Follow Dec 17 '25 How to Read a Scientific Paper Efficiently: A 5-Step Guide # computerscience # tutorial # productivity # beginners Comments Add Comment 4 min read Linux Memory Management Shivakumar Shivakumar Shivakumar Follow Jan 10 Linux Memory Management # beginners # computerscience # linux 1  reaction Comments 1  comment 4 min read Tupper's Self-Referential Formula: A Math Equation That Draws Itself! bytecrafter bytecrafter bytecrafter Follow Dec 16 '25 Tupper's Self-Referential Formula: A Math Equation That Draws Itself! # algorithms # computerscience # science Comments Add Comment 4 min read Rerum: A Pattern Matching and Term Rewriting Library for Python Alex Towell Alex Towell Alex Towell Follow Dec 16 '25 Rerum: A Pattern Matching and Term Rewriting Library for Python # python # programming # computerscience # opensource 1  reaction Comments Add Comment 2 min read Day 26 of improving my Data Science skills Sylvester Promise Sylvester Promise Sylvester Promise Follow Dec 16 '25 Day 26 of improving my Data Science skills # watercooler # computerscience # tooling # devchallenge Comments Add Comment 1 min read Decimal: JavaScript's future numeric type Lucas Pereira de Souza Lucas Pereira de Souza Lucas Pereira de Souza Follow Dec 29 '25 Decimal: JavaScript's future numeric type # computerscience # javascript # programming 1  reaction Comments Add Comment 3 min read Syllable: A Non-POSIX Operating System That Refused to Become Unix Pʀᴀɴᴀᴠ Pʀᴀɴᴀᴠ Pʀᴀɴᴀᴠ Follow Dec 30 '25 Syllable: A Non-POSIX Operating System That Refused to Become Unix # architecture # computerscience # opensource 1  reaction Comments Add Comment 2 min read Permutations & Next Permutation ZeeshanAli-0704 ZeeshanAli-0704 ZeeshanAli-0704 Follow Dec 20 '25 Permutations & Next Permutation # algorithms # interview # computerscience # tutorial Comments Add Comment 4 min read JVM, Java Memory Model e CPU: por que funciona em x86 e quebra em ARM João Antônio João Antônio João Antônio Follow Dec 15 '25 JVM, Java Memory Model e CPU: por que funciona em x86 e quebra em ARM # architecture # computerscience # java Comments Add Comment 3 min read C Programming Tutorial for Beginners | Learn C from Scratch Code Practice Code Practice Code Practice Follow Dec 30 '25 C Programming Tutorial for Beginners | Learn C from Scratch # c # coding # programming # computerscience Comments Add Comment 4 min read History of Java VIDHYA VARSHINI VIDHYA VARSHINI VIDHYA VARSHINI Follow Dec 15 '25 History of Java # computerscience # java # programming 1  reaction Comments Add Comment 1 min read Mastering Heaps: A Deep Dive into Data Structures and Algorithms Visakh Vijayan Visakh Vijayan Visakh Vijayan Follow Dec 15 '25 Mastering Heaps: A Deep Dive into Data Structures and Algorithms # algorithms # computerscience # tutorial Comments Add Comment 2 min read Open Hallucination Index (OHI): turning “Plausible AI” into “Verifiable AI” (LLMs as Gardeners of the Graph) 🌱🧠 Zimtzimt Zimtzimt Zimtzimt Follow Jan 7 Open Hallucination Index (OHI): turning “Plausible AI” into “Verifiable AI” (LLMs as Gardeners of the Graph) 🌱🧠 # ai # llm # opensource # computerscience Comments Add Comment 5 min read Building an Interactive Algorithm Visualizer for Interview Prep (Open Source) Nesim Tunc Nesim Tunc Nesim Tunc Follow Dec 14 '25 Building an Interactive Algorithm Visualizer for Interview Prep (Open Source) # programming # computerscience # algorithms # opensource Comments Add Comment 1 min read I Built MapReduce from Scratch Godson Ajodo Godson Ajodo Godson Ajodo Follow Dec 12 '25 I Built MapReduce from Scratch # showdev # systemdesign # computerscience # learning Comments Add Comment 33 min read What's the solution to CAP theorem in Read Replicas? Biswas Prasana Swain Biswas Prasana Swain Biswas Prasana Swain Follow Dec 25 '25 What's the solution to CAP theorem in Read Replicas? # database # architecture # computerscience # learning 2  reactions Comments Add Comment 3 min read What is an Expert System? Mujahida Joynab Mujahida Joynab Mujahida Joynab Follow Dec 13 '25 What is an Expert System? # ai # beginners # computerscience Comments Add Comment 2 min read Intersection-Aware Asset Placement using Computational Geometry and ML LEE - LEE - LEE - Follow Dec 11 '25 Intersection-Aware Asset Placement using Computational Geometry and ML # algorithms # gamedev # computerscience # machinelearning Comments Add Comment 2 min read Is GCC right when it accepts a C++ template struct having a member with a wrong default initializer? Prashant Sharma Prashant Sharma Prashant Sharma Follow Dec 11 '25 Is GCC right when it accepts a C++ template struct having a member with a wrong default initializer? # discuss # computerscience # cpp Comments Add Comment 2 min read Como o software é executado no computador Leonardo Peixoto Leonardo Peixoto Leonardo Peixoto Follow Dec 11 '25 Como o software é executado no computador # beginners # computerscience # programming Comments Add Comment 1 min read Why Goroutines Scale: Stack Growth, Compiler Tricks, and Context Switching Ayush Kumar Anand Ayush Kumar Anand Ayush Kumar Anand Follow Jan 3 Why Goroutines Scale: Stack Growth, Compiler Tricks, and Context Switching # go # computerscience # performance # backend 2  reactions Comments Add Comment 5 min read DSA: Patterns Jayaprasanna Roddam Jayaprasanna Roddam Jayaprasanna Roddam Follow Jan 4 DSA: Patterns # algorithms # computerscience # interview # learning Comments Add Comment 3 min read Day 23 of improving my Data Science skills Sylvester Promise Sylvester Promise Sylvester Promise Follow Dec 11 '25 Day 23 of improving my Data Science skills # computerscience # development # machinelearning # career 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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2026-01-13T08:49:43
https://dev.to/rdarrylr
Darryl Ruggles - 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 Follow User actions Darryl Ruggles Principal Cloud Solutions Architect @ Ciena AWS Community Builder Serverless, AWS, Kubernetes, Rust, Go, Terraform, Security, React, MLOps, Maker, Electronics. Location Ottawa, ON, Canada Joined Joined on  May 7, 2017 Personal website https://darryl-ruggles.cloud github website Education Acadia University Work Principal Cloud Solutions Architect @ Ciena Eight Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least eight years. Got it Close 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 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 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 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 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. Got it Close Four Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least four years. Got it Close Three Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least three years. Got it Close Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. 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 More info about @rdarrylr Organizations AWS Community Builders GitHub Repositories step-functions-fargate-processor An AWS serverless example using AWS Lambda, Step Functions, and ECS fargate to process datasets Rust • 4 stars serverless-pizza-ordering Example Full-stack Serverless project using ReactJS, Momento Topics, Step Functions, API Gateway, ECS, Lambda, DynamoDB with streams, and more to build an online pizza shop where the progress of orders is updated automatically in the UI. JavaScript • 13 stars serverless-account-watcher Python • 6 stars managed-secure-sftp-using-terraform Terraform stack to deploy an S3 Bucket backed SFTP server in AWS using static IP addresses that will restrict incoming connections to specific IP ranges. Authentication is password based using AWS Lambda for validation with passwords stored in AWS Secrets Manager. HCL • 2 stars Skills/Languages Serverless, Kubernetes, AWS, Full Stack, Rust, Go, Python, React, MLOps, Forecasting, Maker, Electronics. Post 9 posts published Comment 75 comments written Tag 21 tags followed Pin Pinned Building a Serverless Sales Analytics Platform with AI Insights for Under $10/Month Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow for AWS Community Builders Nov 29 '25 Building a Serverless Sales Analytics Platform with AI Insights for Under $10/Month # serverless # terraform # lambda # stepfunctions 5  reactions Comments Add Comment 10 min read Aurora DSQL - Build A Serverless Multi-Region E-Commerce Platform Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow for AWS Community Builders Nov 18 '25 Aurora DSQL - Build A Serverless Multi-Region E-Commerce Platform # serverless # aurora # terraform # aws 4  reactions Comments Add Comment 11 min read Managed Secure SFTP using Terraform Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow Nov 24 '24 Managed Secure SFTP using Terraform # aws # sftp # serverless # terraform 8  reactions Comments 2  comments 9 min read Serverless Cloud Pizzeria Shop Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow Sep 30 '24 Serverless Cloud Pizzeria Shop # aws # serverless # react # terraform 7  reactions Comments Add Comment 7 min read Serverless Data Processor using AWS Lambda, Step Functions and Fargate on ECS (with Rust 🦀🦀) Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow Jan 25 '24 Serverless Data Processor using AWS Lambda, Step Functions and Fargate on ECS (with Rust 🦀🦀) # serverless # lambda # rust # fargate 10  reactions Comments 1  comment 10 min read My AWS Summit Toronto experience and GenAI Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow for AWS Community Builders Sep 6 '25 My AWS Summit Toronto experience and GenAI # community # aws # genai # agentcore 6  reactions Comments 1  comment 12 min read Want to connect with Darryl Ruggles? Create an account to connect with Darryl Ruggles. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Serverless AWS Account Watcher Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow Sep 2 '24 Serverless AWS Account Watcher # aws # serverless # eventdriven # security 7  reactions Comments 2  comments 9 min read AWS SSO Credentials With Multiple Accounts Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow Aug 10 '24 AWS SSO Credentials With Multiple Accounts # aws # sso # cli # iam 6  reactions Comments Add Comment 9 min read Serverless Site Health Check Notification System Darryl Ruggles Darryl Ruggles Darryl Ruggles Follow Dec 23 '23 Serverless Site Health Check Notification System # aws # serverless # lambda # eventdriven 30  reactions Comments 1  comment 8 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. 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
2026-01-13T08:49:43
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https://dev.to/t/chatgpt/page/6
ChatGPT Page 6 - 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 ChatGPT Follow Hide GPT models are capable of natural language processing tasks such as text generation, summarization, and analysis. ChatGPT interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. Create Post submission guidelines We welcome all posts around the topic of ChatGPT - technical articles, personal stories, discussions, and more! Older #chatgpt posts 3 4 5 6 7 8 9 10 11 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu From Product Manager to AI Builder: What It Takes to Go from Prompt to Production Andreea Papillon Andreea Papillon Andreea Papillon Follow Nov 11 '25 From Product Manager to AI Builder: What It Takes to Go from Prompt to Production # ai # beginners # startup # chatgpt Comments 1  comment 12 min read ChatGPT App Display Mode Reference Abe Wheeler Abe Wheeler Abe Wheeler Follow Dec 10 '25 ChatGPT App Display Mode Reference # webdev # ai # mcp # chatgpt 2  reactions Comments Add Comment 3 min read Your Primary LLM Provider Failed? Enable Automatic Fallback with Bifrost Debby McKinney Debby McKinney Debby McKinney Follow Dec 10 '25 Your Primary LLM Provider Failed? Enable Automatic Fallback with Bifrost # go # llm # mcp # chatgpt 6  reactions Comments Add Comment 4 min read Top 5 LiteLLM Alternatives in 2025 Debby McKinney Debby McKinney Debby McKinney Follow Dec 11 '25 Top 5 LiteLLM Alternatives in 2025 # chatgpt # ai # mcp # llm 6  reactions Comments Add Comment 17 min read LLM Self-Reflection - Combined Post-Mortem: Cascading AI Reasoning Failures Eero Bragge Eero Bragge Eero Bragge Follow Nov 8 '25 LLM Self-Reflection - Combined Post-Mortem: Cascading AI Reasoning Failures # claude # chatgpt # sonnet 3  reactions Comments Add Comment 7 min read Build Your First Apps in ChatGPT | A step-by-step guide building with the Apps SDK Zach Park Zach Park Zach Park Follow Nov 5 '25 Build Your First Apps in ChatGPT | A step-by-step guide building with the Apps SDK # appsinchatgpt # appssdk # chatgpt Comments Add Comment 4 min read Todos That Ship Themselves: MongoDB Atlas + Vercel + ChatGPT Apps SDK Pash10g Pash10g Pash10g Follow for MongoDB Dec 9 '25 Todos That Ship Themselves: MongoDB Atlas + Vercel + ChatGPT Apps SDK # database # chatgpt # nextjs # ai 1  reaction Comments 1  comment 6 min read Prompt Engineering for Software Developer Nilesh Raut Nilesh Raut Nilesh Raut Follow Dec 10 '25 Prompt Engineering for Software Developer # ai # promptengineering # developer # chatgpt 18  reactions Comments 2  comments 2 min read Building a High-Performance Open-Source LLM Gateway: Bifrost (54x Faster than LiteLLM) Pranay Batta Pranay Batta Pranay Batta Follow Dec 8 '25 Building a High-Performance Open-Source LLM Gateway: Bifrost (54x Faster than LiteLLM) # go # ai # opensource # chatgpt Comments Add Comment 2 min read Reverse Engineering the Response to "best smartphones" in Chatgpt 5.0 C.Byrne C.Byrne C.Byrne Follow Nov 5 '25 Reverse Engineering the Response to "best smartphones" in Chatgpt 5.0 # ai # chatgpt # llm Comments Add Comment 4 min read Understanding AI Language Models: Base, Chat, and Reasoning — A Beginners Guide Rod Schneider Rod Schneider Rod Schneider Follow Nov 26 '25 Understanding AI Language Models: Base, Chat, and Reasoning — A Beginners Guide # llm # ai # chatgpt # promptengineering Comments Add Comment 4 min read How I’m learning smarter with AI — not just faster AYMANE BENHIMA AYMANE BENHIMA AYMANE BENHIMA Follow Nov 3 '25 How I’m learning smarter with AI — not just faster # chatgpt # gemini # learning # programming Comments Add Comment 1 min read ChatGPT Projects as a Means of "Indirect Conversation" sta sta sta Follow Dec 4 '25 ChatGPT Projects as a Means of "Indirect Conversation" # ai # chatgpt # conversation # collaboration 1  reaction Comments Add Comment 2 min read Efecto copos de nieve para dar a nuestra web un toque navideño Diego Diego Diego Follow Dec 5 '25 Efecto copos de nieve para dar a nuestra web un toque navideño # javascript # css # tutorial # chatgpt Comments Add Comment 1 min read Create Your First ChatGPT App Zach Park Zach Park Zach Park Follow Nov 4 '25 Create Your First ChatGPT App # chatgpt # beginners # tutorial # programming Comments Add Comment 2 min read From Chatbot to Agent: Asynchronous AI Orchestration in Symfony Matt Mochalkin Matt Mochalkin Matt Mochalkin Follow Oct 31 '25 From Chatbot to Agent: Asynchronous AI Orchestration in Symfony # ai # chatgpt # symfony # architecture Comments Add Comment 16 min read Build Your Own ChatGPT Clone — Cheap and Fast Criselda Gomez Criselda Gomez Criselda Gomez Follow Nov 11 '25 Build Your Own ChatGPT Clone — Cheap and Fast # ai # chatgpt # clone 1  reaction Comments Add Comment 2 min read OpenAI will make its ChatGPT Go model free for Indian users for a year Maulik Thakrar Maulik Thakrar Maulik Thakrar Follow for Ekantik Technologies Oct 28 '25 OpenAI will make its ChatGPT Go model free for Indian users for a year # news # openai # chatgpt # ekantiktechnologies Comments Add Comment 1 min read OpenAI launches ChatGPT feature to integrate company knowledge from multipleconnected business tools Saiki Sarkar Saiki Sarkar Saiki Sarkar Follow Oct 28 '25 OpenAI launches ChatGPT feature to integrate company knowledge from multipleconnected business tools # news # openai # chatgpt # rag Comments Add Comment 2 min read The Evolution of GPT: How AI Became Your Everyday Assistant Chetana Desai Chetana Desai Chetana Desai Follow Nov 19 '25 The Evolution of GPT: How AI Became Your Everyday Assistant # ai # openai # chatgpt # gpt3 Comments Add Comment 7 min read Talking About Things I Dislike About Atlas KazooTTT KazooTTT KazooTTT Follow Oct 25 '25 Talking About Things I Dislike About Atlas # openai # chatgpt # browser Comments Add Comment 2 min read Top AI Coding Assistants Compared: ChatGPT, GitHub Copilot, and Amazon CodeWhisperer Devops Makeit-run Devops Makeit-run Devops Makeit-run Follow Nov 7 '25 Top AI Coding Assistants Compared: ChatGPT, GitHub Copilot, and Amazon CodeWhisperer # tooling # chatgpt # ai # productivity 1  reaction Comments Add Comment 9 min read Building MCP Server - The Hidden Protocol Behind Smart AI Collaboration hiruthicSha hiruthicSha hiruthicSha Follow Oct 25 '25 Building MCP Server - The Hidden Protocol Behind Smart AI Collaboration # llm # mcp # ai # chatgpt Comments Add Comment 4 min read A Strategic Guide to Building ChatGPT Apps Mahmoud Zalt Mahmoud Zalt Mahmoud Zalt Follow Dec 29 '25 A Strategic Guide to Building ChatGPT Apps # aimarketplace # chatgpt # mcp # appssdk Comments Add Comment 14 min read Learning Cryptography with ChatGPT: Building Assetspan, a Zero-Knowledge Secrets Manager Cosmin Gheorghita Cosmin Gheorghita Cosmin Gheorghita Follow Oct 23 '25 Learning Cryptography with ChatGPT: Building Assetspan, a Zero-Knowledge Secrets Manager # sideprojects # learning # security # chatgpt Comments Add Comment 3 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. 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
2026-01-13T08:49:43
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2026-01-13T08:49:43
https://dev.to/ascoos/what-is-a-software-version-number-3jkh
What Is a Software Version Number? - 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 Christos Drogidis Posted on Dec 7, 2025 What Is a Software Version Number? # productivity # software # webdev # programming Understand in 5 minutes how to read every version correctly Have you ever seen versions like 26.0.0.10301, 17.4.1, 3.13.1, 1.28.4+exp.sha.41af286, 26.2.0-beta.3 or 2.0.0-alpha.7 and wondered what they actually mean? The version number is not decorative . It is the identity of every release and, when properly structured, tells you at a glance whether the update is safe or requires caution. What you should ask your vendor or development team Do you strictly follow Semantic Versioning 2.0? How do you name your alpha/beta/rc versions? What build format do you use and why? Do you release patch updates at least once a month? Is there automated testing and a rollback plan? See full article... 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 Christos Drogidis Follow Greek programmer and creator of Ascoos OS and Ascoos Web Extneded Studio Location Alexandroupolis, Greece Joined Nov 29, 2025 More from Christos Drogidis HTML is Dead, Long Live JML # webdev # html # jml # programming Getting Started with Ascoos Web Extended Studio (AWES) # webdev # software # php # python 💎 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
2026-01-13T08:49:43
https://docs.devcycle.com/sdk/server-side-sdks/dotnet
.NET SDK | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up SDK Overview SDK Lifecycle SDK Features Client-side SDKS Server-side SDKS Node.js SDK NestJS SDK PHP SDK Go SDK Ruby SDK Python SDK Java SDK .NET SDK Installation Getting Started Usage OpenFeature Example App SDK Proxy Server-side SDKS .NET SDK DevCycle .NET / C# SDK The DevCycle .NET / C# SDK has two operation modes; Cloud Bucketing - which interfaces with the DevCycle Bucketing API , and Local Bucketing - which performs bucketing locally. We recommend using the Local Bucketing mode by default, as it performs fast local evaluations of your feature flags. If you need access to EdgeDB you will need to use the Cloud Bucketing mode of the SDK. See Here for more information. Installation Installing the SDK Getting Started Initializing the SDK Usage Using the SDK OpenFeature How to implement the OpenFeature Provider Example App Try it out for yourself The SDK is available as a package on Nuget. It is also open source and can be viewed on Github. Edit this page Last updated on Jan 9, 2026 Previous Example App Next Installation DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://dev.to/loujaybee
Lou (🚀 Open Up The Cloud ☁️) - 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 Follow User actions Lou (🚀 Open Up The Cloud ☁️) Re-thinking developer experience • Product @Gitpod 🍊 Helping folks get their start in cloud • @openupthecloud ☁️ AWS Community Builder 🛠 Replies in GIFS 😃 Location London Joined Joined on  Aug 16, 2017 Email address contact@louisjohnbichard.co.uk Personal website https://loujaybee.com github website twitter website Education Loughborough University Work Product @ Gitpod Eight Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least eight years. Got it Close 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 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 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 Tag Moderator 2022 Awarded for being a tag moderator in 2022. Got it Close Trusted Member 2022 Awarded for being a trusted member in 2022. 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. Got it Close Four Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least four years. Got it Close Three Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least three years. Got it Close Beloved Comment Awarded for making a well-loved comment, as voted on with 25 heart (❤️) reactions by the community. Got it Close 8 Week Writing Streak The streak continues! You've written at least one post per week for 8 consecutive weeks. Unlock the 16-week badge next! Got it Close Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. Got it Close 4 Week Writing Streak You've posted at least one post per week for 4 consecutive weeks! 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 Show all 14 badges More info about @loujaybee Organizations Scalyr AWS Community Builders Skills/Languages Javascript, AWS, Docker, Serverless, Node.JS, Lambda, Networking, React, Containers. Currently learning GoLang, AWS, AWS Lambda, Monitoring / Observability, Node.JS, TypeScript, Terraform. Currently hacking on https://www.splitoo.com https://www.openupthecloud.com Post 109 posts published Comment 222 comments written Tag 10 tags followed Pin Pinned Do Cloud Engineers Code? Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jan 18 '20 Do Cloud Engineers Code? # devops # cloud # aws 116  reactions Comments 4  comments 6 min read Where (And How) to Start Learning AWS as a Beginner Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Nov 18 '19 Where (And How) to Start Learning AWS as a Beginner # cloud # devops # begineers # aws 77  reactions Comments 7  comments 15 min read Are these the RIGHT 5 skills for a Beginner Cloud Engineer? Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Nov 3 '22 Are these the RIGHT 5 skills for a Beginner Cloud Engineer? # devops # cloud # beginners # career 12  reactions Comments 1  comment 3 min read Want to connect with Lou (🚀 Open Up The Cloud ☁️)? Create an account to connect with Lou (🚀 Open Up The Cloud ☁️). You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in No, I will not mentor you. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Oct 6 '22 No, I will not mentor you. # devops # codenewbie # career # beginners 44  reactions Comments 7  comments 1 min read Open Up The Cloud Newsletter #30 (January Recap 2022) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Mar 3 '22 Open Up The Cloud Newsletter #30 (January Recap 2022) # news # devops # serverless # cloud 5  reactions Comments Add Comment 6 min read 24 Days To Pass The AWS Dev Exam: Exactly How I Did It 🚀 Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Feb 21 '22 24 Days To Pass The AWS Dev Exam: Exactly How I Did It 🚀 # devops # serverless # cloud # beginners 30  reactions Comments 1  comment 3 min read Open Up The Cloud Newsletter #29 (November Recap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jan 20 '22 Open Up The Cloud Newsletter #29 (November Recap 2021) # news # devops # serverless # cloud 7  reactions Comments Add Comment 9 min read Open Up The Cloud Newsletter #28 (October Recap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jan 20 '22 Open Up The Cloud Newsletter #28 (October Recap 2021) # news # devops # serverless # cloud 6  reactions Comments Add Comment 10 min read 2021 Summary: A Rebrand To “Open Up The Cloud” & The Start Of Video Content Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jan 20 '22 2021 Summary: A Rebrand To “Open Up The Cloud” & The Start Of Video Content 2  reactions Comments Add Comment 7 min read Open Up The Cloud Monthly Income Report – Dec 2021 Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Dec 28 '21 Open Up The Cloud Monthly Income Report – Dec 2021 # cloud # devops # serverless # career 5  reactions Comments 2  comments 5 min read Open Up The Cloud Newsletter #27 (August and September Recap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Nov 15 '21 Open Up The Cloud Newsletter #27 (August and September Recap 2021) # news # devops # cloud # serverless 8  reactions Comments Add Comment 7 min read What Are The Different Roles In The Cloud? A Beginners Guide. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Nov 9 '21 What Are The Different Roles In The Cloud? A Beginners Guide. # cloud # career 43  reactions Comments 3  comments 8 min read Open Up The Cloud Newsletter #26 (July Recap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Aug 24 '21 Open Up The Cloud Newsletter #26 (July Recap 2021) # news # devops # serverless # cloud 2  reactions Comments Add Comment 6 min read Cloud Beginner? Don't Learn DevOps: Here's Why. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Aug 9 '21 Cloud Beginner? Don't Learn DevOps: Here's Why. # devops # cloud # beginners # career 5  reactions Comments Add Comment 1 min read Which AWS Region Is Cheapest? A Costing Report Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jul 19 '21 Which AWS Region Is Cheapest? A Costing Report # aws # cloud # devops 22  reactions Comments 5  comments 2 min read How To Find Which AWS Region Is Closest To You? Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jul 19 '21 How To Find Which AWS Region Is Closest To You? # aws # devops # cloud 18  reactions Comments 2  comments 7 min read Where To Start With Cloud Computing? 5 Quick Tips To Get Hands-On Today. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jul 14 '21 Where To Start With Cloud Computing? 5 Quick Tips To Get Hands-On Today. # cloud # devops 24  reactions Comments 2  comments 9 min read Open Up The Cloud Newsletter #25 (June Recap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jul 12 '21 Open Up The Cloud Newsletter #25 (June Recap 2021) # news # devops # serverless # cloud 8  reactions Comments Add Comment 7 min read Unit Testing In Github Actions With Go - The Cloud Resume Challenge Series (Part 16) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jun 10 '21 Unit Testing In Github Actions With Go - The Cloud Resume Challenge Series (Part 16) # devops # cloud # aws # serverless 6  reactions Comments Add Comment 1 min read Deploying AWS SAM with GitHub Actions - The Cloud Resume Challenge Series (Part 17) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jun 10 '21 Deploying AWS SAM with GitHub Actions - The Cloud Resume Challenge Series (Part 17) # devops # cloud # aws # serverless 10  reactions Comments 1  comment 1 min read Get Data From DynamoDB Using AWS SDK (Go) - The Cloud Resume Challenge Series (Part 15) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jun 1 '21 Get Data From DynamoDB Using AWS SDK (Go) - The Cloud Resume Challenge Series (Part 15) # devops # cloud # aws # serverless 5  reactions Comments Add Comment 2 min read The Cloud Resume Challenge (series): Part 13 - Monolithic vs Single Purposed Functions Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders May 11 '21 The Cloud Resume Challenge (series): Part 13 - Monolithic vs Single Purposed Functions # devops # cloud # aws # serverless 5  reactions Comments 1  comment 2 min read Open Up The Cloud Newsletter #23 (April Recap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders May 6 '21 Open Up The Cloud Newsletter #23 (April Recap 2021) # news # devops # serverless # cloud 6  reactions Comments Add Comment 8 min read The Cloud Resume Challenge (series): Part 11 - JavaScript Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Apr 26 '21 The Cloud Resume Challenge (series): Part 11 - JavaScript # devops # cloud # aws # serverless 7  reactions Comments 1  comment 2 min read Which AWS Certification Should You Take First? Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Apr 13 '21 Which AWS Certification Should You Take First? # devops # cloud # aws # serverless 22  reactions Comments 3  comments 7 min read The Cloud Resume Challenge (series): Part 9 - CloudFront Custom Domain Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Apr 12 '21 The Cloud Resume Challenge (series): Part 9 - CloudFront Custom Domain # devops # serverless # cloud # aws 9  reactions Comments 1  comment 1 min read The Cloud Resume Challenge (series): Part 8 - HTTPS & ACM Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Apr 8 '21 The Cloud Resume Challenge (series): Part 8 - HTTPS & ACM # devops # serverless # cloud # aws 6  reactions Comments 1  comment 1 min read Cloud Software Engineering Newsletter #22 (March Recap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Apr 7 '21 Cloud Software Engineering Newsletter #22 (March Recap 2021) # news # devops # serverless # cloud 1  reaction Comments Add Comment 9 min read The Cloud Resume Challenge (series): Part 7 - Deploying & Configuring CloudFront Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Mar 30 '21 The Cloud Resume Challenge (series): Part 7 - Deploying & Configuring CloudFront # devops # serverless # cloud # aws 5  reactions Comments 1  comment 1 min read The Cloud Resume Challenge (series): Part 6 - Deploying & Configuring CloudFront Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Mar 22 '21 The Cloud Resume Challenge (series): Part 6 - Deploying & Configuring CloudFront # devops # cloud # serverless # aws 10  reactions Comments 1  comment 1 min read Can You Learn AWS (And Get Certified) With No Experience? e.g. No IT background or degree Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Mar 21 '21 Can You Learn AWS (And Get Certified) With No Experience? e.g. No IT background or degree # aws # devops # cloud # beginners 4  reactions Comments Add Comment 13 min read Cloud Software Engineering Newsletter #21 (February Recap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Mar 10 '21 Cloud Software Engineering Newsletter #21 (February Recap 2021) # news # devops # serverless # cloud 8  reactions Comments 7  comments 10 min read How Long Will It Take To Learn AWS? And How To Speed The Process Up! Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Feb 24 '21 How Long Will It Take To Learn AWS? And How To Speed The Process Up! # aws # devops # cloud # career 14  reactions Comments 1  comment 11 min read Best Resources For AWS Certifications: An Extensive & Opinionated Guide (So You Pass The First Time!) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Feb 23 '21 Best Resources For AWS Certifications: An Extensive & Opinionated Guide (So You Pass The First Time!) # aws # career # devops # beginners 43  reactions Comments 4  comments 19 min read How Much Do AWS Certifications Cost? 💸 Including All The Extras Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Feb 3 '21 How Much Do AWS Certifications Cost? 💸 Including All The Extras # aws # serverless # cloud # devops 10  reactions Comments 8  comments 11 min read Cloud Software Engineering Newsletter #20 (January Re-Cap 2021) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Feb 2 '21 Cloud Software Engineering Newsletter #20 (January Re-Cap 2021) # news # cloud # devops # serverless 9  reactions Comments Add Comment 9 min read Okay, so I finally played with the ACloudGuru Playground and it's... awesome. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jan 25 '21 Okay, so I finally played with the ACloudGuru Playground and it's... awesome. # devops # serverless # cloud # aws 3  reactions Comments 1  comment 2 min read Serverless: Who Sets Up Your Environment? 🤔 Diving Into How The Serverless Environment Setup Works. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow for AWS Community Builders Jan 20 '21 Serverless: Who Sets Up Your Environment? 🤔 Diving Into How The Serverless Environment Setup Works. # serverless # cloud # aws # devops 13  reactions Comments 2  comments 12 min read Can You Learn AWS On Your Own? How To Ensure Success 🤓. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jan 14 '21 Can You Learn AWS On Your Own? How To Ensure Success 🤓. # aws # cloud # beginners 10  reactions Comments Add Comment 4 min read How To Test AWS Lambda: Everything You Need To Get Started. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jan 13 '21 How To Test AWS Lambda: Everything You Need To Get Started. # devops # serverless # aws # cloud 8  reactions Comments Add Comment 11 min read How To Debug AWS Lambda: A Detailed Overview Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jan 12 '21 How To Debug AWS Lambda: A Detailed Overview # devops # cloud # serverless # aws 24  reactions Comments 3  comments 15 min read Cloud Native Software Engineering Newsletter #19 (December re-cap 2020) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Feb 23 '21 Cloud Native Software Engineering Newsletter #19 (December re-cap 2020) # news # devops # cloud # aws 3  reactions Comments Add Comment 10 min read 2020 Summary: How I Grew My Blog to 25,000 Pageviews & Earned My First Income From The Blog. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jan 4 '21 2020 Summary: How I Grew My Blog to 25,000 Pageviews & Earned My First Income From The Blog. # showdev # writing # career # cloud 16  reactions Comments 2  comments 11 min read Cloud Native Software Engineering Newsletter #18 (November 2020) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jan 4 '21 Cloud Native Software Engineering Newsletter #18 (November 2020) # news # cloud # devops # serverless 3  reactions Comments Add Comment 8 min read What Is Terraform Used For? The 3 Main Use Cases. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Nov 27 '20 What Is Terraform Used For? The 3 Main Use Cases. # devops # cloud # terraform 14  reactions Comments Add Comment 4 min read Are Containers Serverless? Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Nov 25 '20 Are Containers Serverless? # devops # serverless # aws # cloud 9  reactions Comments Add Comment 4 min read Help, my Lambda won't stop 😱 ! How To Stop An AWS Lambda Execution. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Nov 6 '20 Help, my Lambda won't stop 😱 ! How To Stop An AWS Lambda Execution. # devops # serverless # cloud # aws 5  reactions Comments Add Comment 4 min read Cloud Native Software Engineering Newsletter #17 (October 2020) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Nov 3 '20 Cloud Native Software Engineering Newsletter #17 (October 2020) # news # devops # serverless # cloud 13  reactions Comments 3  comments 8 min read Lambda Extensions: What Are They, And Should You Care? Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Oct 26 '20 Lambda Extensions: What Are They, And Should You Care? # cloud # aws # serverless # devops 6  reactions Comments Add Comment 5 min read Supportive tech forums & online communities: Any recommendations? Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Oct 20 '20 Supportive tech forums & online communities: Any recommendations? # discuss 3  reactions Comments Add Comment 1 min read What Are The Pre-Requisites To Learning AWS? 5 Topics You Probably Should Look Into First. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Oct 20 '20 What Are The Pre-Requisites To Learning AWS? 5 Topics You Probably Should Look Into First. # aws # devops # cloud # beginners 8  reactions Comments 2  comments 5 min read Does AWS Require Coding? Understanding When You Might Need To Code. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Oct 16 '20 Does AWS Require Coding? Understanding When You Might Need To Code. # beginners # aws # cloud # devops 9  reactions Comments Add Comment 8 min read Can AWS Lambda Access A Database? And The Considerations You Should Be Taking. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Oct 14 '20 Can AWS Lambda Access A Database? And The Considerations You Should Be Taking. # serverless # aws # cloud # devops 10  reactions Comments 1  comment 4 min read How Long Does It Take To Learn Terraform? And How To Speed Up Your Learning. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Oct 13 '20 How Long Does It Take To Learn Terraform? And How To Speed Up Your Learning. # devops # cloud # beginners 12  reactions Comments 2  comments 4 min read Is AWS Easy To Learn? (And How You Can Make It Easier) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Oct 12 '20 Is AWS Easy To Learn? (And How You Can Make It Easier) # aws # cloud # devops # beginners 45  reactions Comments Add Comment 4 min read Cloud Native Software Engineering Newsletter #16 (September 2020) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Oct 2 '20 Cloud Native Software Engineering Newsletter #16 (September 2020) # news # devops # serverless # cloud 4  reactions Comments 2  comments 7 min read The Secret Of Web Development BootCamps And How To Use Cloud To Your Advantage Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Sep 9 '20 The Secret Of Web Development BootCamps And How To Use Cloud To Your Advantage # beginners # career # cloud # webdev 12  reactions Comments Add Comment 5 min read Cloud Native Software Engineering Newsletter #15 (August 2020) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Aug 19 '20 Cloud Native Software Engineering Newsletter #15 (August 2020) # news # devops # serverless # cloud 8  reactions Comments 1  comment 9 min read You’re Alerting Wrong: The Why & How Of Setting An AWS Lambda Alarm Using Error Rate Percentages. Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Aug 5 '20 You’re Alerting Wrong: The Why & How Of Setting An AWS Lambda Alarm Using Error Rate Percentages. # devops # serverless # aws # cloud 13  reactions Comments Add Comment 8 min read Should You Use Typescript To Write Terraform? (The Terraform CDK) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jul 24 '20 Should You Use Typescript To Write Terraform? (The Terraform CDK) # cloud # devops # aws 30  reactions Comments 4  comments 7 min read Cloud Native Software Engineering Newsletter #14 (July 2020) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jul 19 '20 Cloud Native Software Engineering Newsletter #14 (July 2020) # news # cloud # devops # serverless 23  reactions Comments Add Comment 10 min read A Philosophy For Effective Error Handling (Using JavaScript Examples) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Lou (🚀 Open Up The Cloud ☁️) Follow Jul 10 '20 A Philosophy For Effective Error Handling (Using JavaScript Examples) # javascript # tutorial # node # webdev 12  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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2026-01-13T08:49:43
https://dev.to/femi_akinyemi
Femi Akinyemi - 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. 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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 Femi Akinyemi Frontend Developer || Technical Writer Location Lagos, Nigeria Joined Joined on  Apr 9, 2020 Email address akinfemi46@gmail.com Personal website https://www.femiakinyemi.site github website twitter website Education Bsc Mathematics Pronouns He/Him Work Datamellon 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. Got it Close The Pinata Challenge Completion Badge Awarded for completing The Pinata Challenge. Thank you for participating! 💻 Got it Close Four Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least four 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 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 Top 7 Awarded for having a post featured in the weekly "must-reads" list. 🙌 Got it Close Three Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least three years. 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 MongoDB Atlas Hackathon 2022 Participant Awarded for participating in the MongoDB Atlas Hackathon 2022 on DEV. 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 Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. 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 Show all 13 badges More info about @femi_akinyemi Organizations AWS Community Builders Hackmamba Medusa Skills/Languages FrontEnd: HTML, CSS, Chakraui, React.Js, Redux, Typescript BackEnd: NodeJs, ExpressJs Database: Firebase, MongoDB Post 23 posts published Comment 132 comments written Tag 13 tags followed Pin Pinned How to Prevent Unnecessary React Component Re-Rendering Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Jul 8 '23 How to Prevent Unnecessary React Component Re-Rendering # react # javascript # performance # frontend 187  reactions Comments 11  comments 5 min read How to Build and Publish Your First React NPM Package Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Jun 9 '23 How to Build and Publish Your First React NPM Package # react # npm # javascript # tutorial 72  reactions Comments 6  comments 6 min read Build a High-Performing Ecommerce with Svelte and Medusa Backend Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Feb 21 '23 Build a High-Performing Ecommerce with Svelte and Medusa Backend # svelte # javascript # medusa # ecommerce 36  reactions Comments 23  comments 16 min read Build a Text Summarization App in React with ChatGPT Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Feb 6 '23 Build a Text Summarization App in React with ChatGPT # frontend # html # css # career 53  reactions Comments 24  comments 6 min read How to use Axios with React Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Aug 19 '22 How to use Axios with React # react # beginners # programming # tutorial 69  reactions Comments 16  comments 10 min read Wedding Memories: The Collaborative Wedding Album! Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Oct 11 '24 Wedding Memories: The Collaborative Wedding Album! # devchallenge # pinatachallenge # webdev # api 95  reactions Comments 26  comments 5 min read Want to connect with Femi Akinyemi? Create an account to connect with Femi Akinyemi. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in How to Upload Files to Amazon S3 with React and AWS SDK Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow for AWS Community Builders Mar 4 '24 How to Upload Files to Amazon S3 with React and AWS SDK # aws # react # s3 # javascript 61  reactions Comments Add Comment 4 min read Build a simple project management app with Neon, PostgREST, and DigitalOcean Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow for Hackmamba Feb 27 '24 Build a simple project management app with Neon, PostgREST, and DigitalOcean 4  reactions Comments Add Comment 11 min read Understanding AWS Amplify Monitoring Metrics Definitions Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow for AWS Community Builders Feb 8 '24 Understanding AWS Amplify Monitoring Metrics Definitions # aws # cloudcomputing # awsamplify # javascript 7  reactions Comments Add Comment 2 min read How to add Astro social share to your Astro application Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Jan 8 '24 How to add Astro social share to your Astro application # webdev # astro # javascript # tutorial 7  reactions Comments 1  comment 5 min read Build A Reusable Carousel With React And Splide.js Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Jun 13 '23 Build A Reusable Carousel With React And Splide.js # react # tutorial # javascript # frontend 11  reactions Comments Add Comment 8 min read How to Deploy a Next.js 13 App to AWS with Amplify Hosting Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow May 4 '23 How to Deploy a Next.js 13 App to AWS with Amplify Hosting # nextjs # javascript # aws # tutorial 9  reactions Comments 1  comment 4 min read How to Deploy Medusa Server to Render Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Apr 10 '23 How to Deploy Medusa Server to Render # medusa # tutorial # opensource # webdev 29  reactions Comments Add Comment 5 min read How to Build a Job Board With AWS Amplify and Nextjs Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Apr 7 '23 How to Build a Job Board With AWS Amplify and Nextjs # watercooler 23  reactions Comments 4  comments 12 min read Top React Form Libraries for Efficient Form Creation Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Mar 8 '23 Top React Form Libraries for Efficient Form Creation # android # softwaredevelopment # design # critique 55  reactions Comments 6  comments 16 min read MongoDB Atlas Hackathon 2022 on DEV Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Dec 8 '22 MongoDB Atlas Hackathon 2022 on DEV # atlashackathon22 # react # node # webdev 1  reaction Comments Add Comment 2 min read How to Create a Resume Builder App with Xata and Cloudinary Using NextJs Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow for Hackmamba Nov 23 '22 How to Create a Resume Builder App with Xata and Cloudinary Using NextJs # javascript # jamstack # xata # nextjs 12  reactions Comments 2  comments 9 min read How We Won the Medusa Hackathon: Building the Paystack Plugin Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow for Medusa Nov 8 '22 How We Won the Medusa Hackathon: Building the Paystack Plugin # opensource # devjournal # webdev # javascript 22  reactions Comments 2  comments 4 min read Writing React? Please Note these things Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Sep 21 '22 Writing React? Please Note these things # react # javascript # productivity # beginners 1  reaction Comments Add Comment 1 min read Common Built-in String Methods in Javascript Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Sep 14 '22 Common Built-in String Methods in Javascript # javascript # beginners # programming # tutorial 5  reactions Comments Add Comment 7 min read How to Create a Chart in React With Recharts Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Sep 1 '22 How to Create a Chart in React With Recharts # react # tutorial # beginners # javascript 26  reactions Comments 2  comments 5 min read REST Countries API challenge solved with Chakra UI and React. Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Aug 5 '22 REST Countries API challenge solved with Chakra UI and React. # javascript # chakraui # react # frontendmentor 11  reactions Comments Add Comment 8 min read My HNGi8 Internship Goals Femi Akinyemi Femi Akinyemi Femi Akinyemi Follow Aug 17 '21 My HNGi8 Internship Goals 1  reaction 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 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
2026-01-13T08:49:43
https://forem.com/new/backend
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2026-01-13T08:49:43
http://www.khanacademy.org/#computer-science
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2026-01-13T08:49:43
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2026-01-13T08:49:43
http://anh.cs.luc.edu/handsonPythonTutorial/
Hands-on Python 3 Tutorial — Hands-on Python Tutorial for Python 3 Navigation index next | Hands-on Python Tutorial » Hands-on Python 3 Tutorial ¶ Dr. Andrew N. Harrington Computer Science Department, Loyola University Chicago © Released under the Creative Commons Attribution-Noncommercial-Share Alike 4.0 United States License https://creativecommons.org/licenses/by-nc-sa/4.0/ ————— 1. Beginning With Python 1.1. Context 1.2. The Python Interpreter and Idle, Part I 1.3. Whirlwind Introduction To Types and Functions 1.4. Integer Arithmetic 1.5. Strings, Part I 1.6. Variables and Assignment 1.7. Print Function, Part I 1.8. Strings Part II 1.9. The Idle Editor and Execution 1.10. Input and Output 1.11. Defining Functions of your Own 1.12. Dictionaries 1.13. Loops and Sequences 1.14. Decimals, Floats, and Floating Point Arithmetic 1.15. Summary 2. Objects and Methods 2.1. Strings, Part III 2.2. More Classes and Methods 2.3. Mad Libs Revisited 2.4. Graphics 2.5. Files 2.6. Summary 3. More On Flow of Control 3.1. If Statements 3.2. Loops and Tuples 3.3. While Statements 3.4. Arbitrary Types Treated As Boolean 3.5. Further Topics to Consider 3.6. Summary 4. Dynamic Web Pages 4.1. Overview 4.2. Web page Basics 4.3. Composing Web Pages in Python 4.4. CGI - Dynamic Web Pages 4.5. Summary 5. Appendices 5.1. Using Error Messages 5.2. Some Special Windows Instructions 5.3. Some Special Mac Instructions 5.4. HTML Source Markup Index Next topic 1. Beginning With Python This Page Show Source Quick search Enter search terms or a module, class or function name. Navigation index next | Hands-on Python Tutorial » © Copyright 2019, Dr. Andrew N. Harrington. Last updated on May 25, 2020. Created using Sphinx 1.3.1+.
2026-01-13T08:49:43
https://parenting.forem.com/junothreadborne/the-sturdy-pillar-doesnt-need-reinforcement-the-silent-myth-of-single-parenthood-3cde
The Sturdy Pillar Doesn’t Need Reinforcement - Parenting 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 Parenting 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 Juno Threadborne Posted on Nov 21, 2025           The Sturdy Pillar Doesn’t Need Reinforcement # mentalhealth # singleparenting The morning is quiet. Suspiciously so. You're already up. The coffee's cooling. One kid is curled up on the couch half awake, another is still asleep, the third already left for school an hour earlier. You head to Food Lion early. Make it back in time for a good breakfast, get lunch in a backpack, and still find the missing shoe on time for the bus. Everything functions. Everything flows. And no one sees the tension in your jaw or the checklist running behind your eyes. No one praises the pillar for not falling. When you're parenting alone, silence is what you earn for that work. And sometimes that's nice. But it's easy to mistake silence for success. When you parent together—when the structure includes more than one load-bearing wall—the silence means something different. It's not the absence of failure. It's the presence of shared effort. And I miss that. Here's the myth we don't say aloud: Stable people don't need checking on. We're biased that way. Biologically. We respond to visible wounds. We reach for the limping, not the marching. The smoother the performance, the less people notice the skill it takes to hold it together. That's true in code, in classrooms, and in kitchens at 7AM. When my wife is home, she doesn't assume I've got it. She checks . Gently, but intentionally. And sometimes that check-in—the one question no one else thought to ask—is the only thing keeping me from cracking. For years, it was just me. Now, even with her, when she's away, the old muscle memory kicks in. Stress finds the quietest route downhill. And in every system—families, friend groups, even workplaces—it flows toward the person who looks like they can carry it. In this house, that's me. Because I'm stable. Because I don't yell. Because I'm able to bear the load. But here's the secret: The emotionally self-sufficient get trusted with everyone's burdens—but rarely their care. And now, with my better half gone, the architecture has no other path. So it reroutes everything through me. And I don't always succeed. Some mornings, I forget a permission slip. Some nights, I realize too late I forgot to make that important phone call. There are entire weeks where dinner is just triage. But I keep going. Because the illusion of stability is loud enough to quiet concern. When she's here—and this is what partnership actually means—she catches the things I miss. Or catches me , when I start slipping. That's not backup. That's ballast. And without ballast the ship rolls. We don't design anything to bear endless weight without maintenance. Your car needs new shocks every 60,000 miles. Your roof needs replacing every few decades. People need regular check-ups. And without them, small stresses compound. The missed check-in. The postponed conversation. The promise that slips. The dinner date with a friend that keeps getting rescheduled. The call you let go to voicemail one too many times. That's how cracks form. Quietly. Unnoticed. Two parents can distribute that load. Sometimes you alternate—who carries, who coasts. Sometimes one catches the fall when the other can't. But right now, there's no fallback. Just wear. And grit. And the knowledge that cracks spread long before they show. It's not even about splitting the work evenly, really. It's about being seen. I only understood this when I found someone who actually looked. My wife is the first person since I became a parent who looked at the way I hold my own world together and said: "I appreciate what you're doing for us." And in that moment, the myth collapsed a little. She doesn't walk around measuring cracks. She walks the perimeter with me. If you're lucky enough to be in a shared load-bearing system—or if you're building one with friends, family, a village—don't just lean on them. Look up. Ask how the structure's doing. She always has. And when she comes home again, I'll do better at meeting her halfway. Because even shared weight needs redistribution. A pillar reinforced becomes part of a structure. The house is quiet again tonight. The kind of quiet I used to welcome. Now it just sounds like echoes. There's still work to do. Dishes, deadlines, dramas waiting around corners. But for now, just a breath. If this essay does anything, let it be this: Don't wait for collapse. Walk the perimeter. Check the load. Ask who's holding it all up—and whether they're doing it alone. When she comes home, I'll tell her this. But until then, I'm telling you. Because if this pillar could speak, it wouldn't ask for praise. It would ask you to help carry the next beam. Just for a while. Top comments (2) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand   Jess Lee Jess Lee 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 • Nov 24 '25 Dropdown menu Copy link Hide <3 Like comment: Like comment: 1  like Like Comment button Reply Collapse Expand   Narnaiezzsshaa Truong Narnaiezzsshaa Truong Narnaiezzsshaa Truong Follow Security tools for bootstrapped startups Location Texas, United States Joined Oct 24, 2025 • Dec 21 '25 Dropdown menu Copy link Hide Love this. Empowerment isn’t about removing the weight; it’s about making sure no one feels invisible beneath it. Presence can be its own form of care. 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 Juno Threadborne Follow 🧵 Writer. 🧑‍💻 Coder. ✨ Often found bending reality for sport. https://thrd.me Location Hampton, VA Pronouns he/him Joined Oct 16, 2025 💎 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 Parenting — 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. Home About Contact 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 . Parenting © 2016 - 2026. Navigating the chaos and joy of parenting. Log in Create account
2026-01-13T08:49:43
https://www.youtube.com/watch?v=Kqz-umsAnk8
2024 LLVM Developers' Meeting - Rust ❤️ LLVM - YouTube 정보 보도자료 저작권 문의하기 크리에이터 광고 개발자 약관 개인정보처리방침 정책 및 안전 YouTube 작동의 원리 새로운 기능 테스트하기 © 2026 Google LLC, Sundar Pichai, 1600 Amphitheatre Parkway, Mountain View CA 94043, USA, 0807-882-594 (무료), yt-support-solutions-kr@google.com, 호스팅: Google LLC, 사업자정보 , 불법촬영물 신고 크리에이터들이 유튜브 상에 게시, 태그 또는 추천한 상품들은 판매자들의 약관에 따라 판매됩니다. 유튜브는 이러한 제품들을 판매하지 않으며, 그에 대한 책임을 지지 않습니다. var ytInitialData = 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2026-01-13T08:49:43
https://www.fine.dev/blog/ai-coding-guide#2-chatgpt
AI Coding – A Simple Guide for Developers Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back AI Coding – A Simple Guide for Developers Table of Contents Introduction: What is AI Coding The Importance of Context in AI Coding Tips for Providing Better Context Practical Instructions for Providing Context to AI Coding Tools 1. Creating a Knowledge Graph 2. Implementing Retrieval-Augmented Generation (RAG) 3. Copy-Pasting Relevant Code into ChatGPT and Claude 4. Understanding Potential Mistakes Without Proper Context Using AI to Generate Code Incorporating AI Tools into Your Workflow Advice for Front-End Developers Practical Tips Advice for Back-End Developers Practical Tips Use Cases for AI in Coding 1. Automated Bug Fixes 2. Predicting Performance Bottlenecks 3. Large Codebase Refactoring Industry-Specific Benefits Best Large Language Models (LLMs) for Coding 1. OpenAI 2. Anthropic 3. Google Gemini 4. Other Notable Models Choosing the Right LLM for Your Needs Popular AI Coding Tools 1. Fine 2. ChatGPT 3. Replit 4. Devin 5. Cursor Conclusion Introduction: What is AI Coding In today's rapidly evolving tech landscape, AI coding has emerged as a game-changer for developers. But what exactly is AI coding? Simply put, it's the use of artificial intelligence to assist in writing, optimizing, and managing code. AI coding tools help developers write better, faster, and more efficient code by automating repetitive tasks, providing intelligent code suggestions, and even debugging. This blog will delve into the importance of context in AI coding, how to use AI for generating code, offer practical advice for both front-end and back-end developers, explore various use cases, introduce some of the top AI coding tools available today, and discuss the best large language models (LLMs) for coding. The Importance of Context in AI Coding The first key to success in AI coding is understanding context . AI tools analyze the surrounding code to generate relevant and accurate suggestions. Without proper context, AI-generated code can be irrelevant or even introduce errors. Here's why context matters: Code Quality: In complex systems, context helps maintain consistency and functionality across different modules. Relevance: AI tools can provide more precise code snippets when they understand the broader scope of the project. Efficiency: Proper context reduces the time developers spend correcting AI-generated code. Imagine asking a lawyer off the street to represent you in court, without knowing anything about you, the case, or the evidence. The best lawyer in the world would struggle! The same goes for AI in coding - only if you provide the relevant information will you get relevant results. Tips for Providing Better Context: Descriptive Comments: Write clear and detailed comments to guide the AI tool. Structured Code: Organize your code logically to help AI understand the flow and dependencies. Consistent Naming Conventions: Use meaningful and consistent names for variables, functions, and classes. Integrate Platforms: The more of your tech stack that can be integrated, the more data the AI will be able to access and the better the output will be. Fine offers GitHub, Linear, and Sentry integrations with more on the way. Practical Instructions for Providing Context to AI Coding Tools To maximize the effectiveness of AI coding tools, providing comprehensive and well-structured context is essential. Here are some practical methods to enhance context for AI tools: 1. Creating a Knowledge Graph A knowledge graph is a structured representation of information that outlines the relationships between different components of your codebase. By creating a knowledge graph, you can provide AI tools with a holistic view of your project, enabling them to make more informed suggestions. How to Create a Knowledge Graph: Identify Key Components: List out all the modules, classes, functions, and their interactions within your project. Define Relationships: Establish how these components interact, depend on each other, and contribute to the overall functionality. Use Visualization Tools: Utilize tools like Neo4j or Graphviz to visualize the knowledge graph, making it easier to understand and update. Benefits: Enhances AI's understanding of the project structure. Facilitates better code suggestions and optimizations. Helps in identifying dependencies and potential areas for improvement. Fine creates a knowledge graph called Atlas, which includes your codebase from GitHub and issues from Sentry and Linear. This way, it prepares the AI to handle any task you give it. You don’t need to work hard creating your own knowledge graph when we’ve done it for you. 2. Implementing Retrieval-Augmented Generation (RAG) Retrieval-Augmented Generation (RAG) combines traditional information retrieval techniques with generative AI models to provide more accurate and contextually relevant responses. How to Use RAG: Integrate Data Sources: Connect your AI coding tool to relevant data sources such as documentation, code repositories, and knowledge bases. Contextual Retrieval: Ensure that the AI can retrieve pertinent information from these sources before generating code suggestions. Continuous Learning: Update the data sources regularly to keep the AI informed about the latest changes and best practices in your project. Benefits: Improves the relevance and accuracy of AI-generated code. Enables AI to leverage existing knowledge and documentation. Enhances the tool's ability to handle complex queries and tasks. 3. Copy-Pasting Relevant Code into ChatGPT and Claude When using conversational AI tools like ChatGPT for coding assistance, providing snippets of relevant code can significantly improve the quality of the responses. How to Provide Relevant Code: Select Key Sections: Identify and copy the sections of code that are directly related to your query or the task at hand. Provide Contextual Information: Along with the code, include comments or explanations that describe the functionality and purpose of the code segments. Ask Specific Questions: Clearly state what you need help with, such as debugging a particular function or optimizing a code block. Example: # Function to calculate the factorial of a number def factorial(n): if n == 0: return 1 else: return n * factorial(n-1) # I need to optimize this recursive factorial function to handle larger numbers without hitting the recursion limit. Question: How can I optimize the above factorial function to handle larger inputs efficiently? Benefits: Provides AI with the necessary context to generate accurate solutions. Reduces ambiguity, leading to more precise and helpful responses. Saves time by directly addressing specific issues within the code. This is similar to GitHub Copilot and some other tools where you can highlight the relevant context to direct the AI. 4. Understanding Potential Mistakes Without Proper Context AI coding tools, while powerful, can make mistakes if not provided with adequate context. Common errors include: Irrelevant Code Suggestions: Without understanding the project structure, AI might suggest code that doesn't fit the existing framework. Syntax Errors: Lack of context can lead to syntax mistakes, especially in languages with strict syntax rules. Logical Flaws: AI might introduce logical errors if it doesn't fully grasp the intended functionality. Security Vulnerabilities: Inadequate context can result in code that exposes security loopholes or fails to follow best practices. Backend Errors In languages commonly used for backend such as Python, AI may make more mistakes if it doesn’t have context, such as NameErrors and IndentationErrors - mistakes that you wouldn’t have made coding manually. You can read more about common Python errors and how different AI applications handle them here.   Fine is less likely to make such errors, as it has full knowledge of your codebase.   Mitigation Strategies: Always Review AI-Generated Code: Never blindly trust the AI's suggestions; always verify and test the code. Provide Comprehensive Context: The more information you provide, the better the AI can assist accurately. Use Multiple Sources: Cross-reference AI suggestions with official documentation and best practices. Continuous Feedback: Provide feedback to the AI tool to help it learn and improve over time. Using AI to Generate Code AI coding tools are revolutionizing the way developers write code by automating mundane tasks and enhancing creativity. Here's how AI is being used to generate code: Code Snippets: AI can suggest entire lines or blocks of code based on the current context. Automating Repetitive Tasks: Tasks like boilerplate code generation, formatting, and refactoring can be handled by AI, freeing up developers to focus on more complex problems. Bug Detection: AI can identify potential bugs and vulnerabilities in real-time, ensuring higher code quality. Incorporating AI Tools into Your Workflow: Choose the Right Tool: Select an AI coding tool that integrates seamlessly with your development workflow. Customize Settings: Tailor the tool’s settings to match your coding style and project requirements. Regularly Review Suggestions: While AI can assist, always review and test AI-generated code to ensure it meets your standards. Advice for Front-End Developers Front-end development focuses on the user interface and user experience. AI coding tools can significantly enhance this process: UI/UX Enhancement: AI can suggest design improvements and optimize user interfaces for better engagement. Streamlining CSS/HTML/JS: Automate the generation of responsive designs and ensure cross-browser compatibility. Automated Testing: AI tools can perform repetitive testing tasks, ensuring your front-end code is robust and error-free. Practical Tips: Use AI for Responsive Design: Let AI suggest layout adjustments for different screen sizes. Optimize Performance: AI can analyze and optimize front-end performance, reducing load times and improving user experience. Leverage AI for Accessibility: Ensure your applications are accessible by using AI to identify and fix accessibility issues. Advice for Back-End Developers Back-end development involves server-side logic, database management, and ensuring the smooth operation of applications. AI coding tools can streamline these processes: Automating Server-Side Logic: AI can generate efficient server-side code, handling complex operations with ease. Security Vulnerability Detection: Identify and fix security issues before they become problematic. Database Query Optimization: AI can analyze and optimize database queries for better performance. Practical Tips: API Generation: Use AI to create and manage APIs, ensuring they are secure and efficient. Automate Testing: Implement AI-driven testing to validate back-end processes and ensure reliability. Optimize Code Performance: Leverage AI to analyze and enhance the performance of your server-side code. Use Cases for AI in Coding AI coding has a wide range of applications across various industries. Here are some real-world use cases: 1. Automated Bug Fixes Fine’s AI can identify and fix bugs in your codebase, reducing the time spent on debugging and improving overall code quality. 2. Predicting Performance Bottlenecks By analyzing code patterns, AI can predict potential performance issues, allowing developers to address them proactively. 3. Large Codebase Refactoring Managing and refactoring large codebases can be daunting. AI tools can assist with this process, ensuring consistency and reducing errors. Industry-Specific Benefits: E-Commerce: Enhance platform performance and security with AI-driven optimizations. Add features to improve user experience and conversion rates rapidly. Fintech: Ensure the reliability and security of financial applications through AI-assisted coding. SaaS Platforms: Improve scalability and performance with AI-generated and optimized code. Healthcare: Streamline data processing and ensure compliance with regulatory standards through AI-assisted code generation. Education Technology: Enhance learning platforms by personalizing features and improving code quality with AI-driven development. Gaming: Optimize game performance and identify bugs faster with AI-generated suggestions and automated testing. Best Large Language Models (LLMs) for Coding Large Language Models (LLMs) are at the heart of modern AI coding tools. They power the intelligent features that assist developers in writing and managing code. Here are some of the best LLMs for coding: 1. OpenAI OpenAI's models, including GPT-4 , are renowned for their versatility and capability in understanding and generating human-like text. In coding, GPT-4 excels at code generation, debugging, and providing intelligent suggestions across multiple programming languages. OpenAI also offers Codex , specifically fine-tuned for programming tasks, making it a popular choice for developers seeking advanced AI assistance. OpenAI also recently released preview and mini versions of their latest model, o1, which is outperforming competitors on many benchmarks. 2. Anthropic Anthropic's Claude models focus on safety and reliability, ensuring that AI-generated code adheres to best practices and minimizes errors. These models are designed to understand complex coding contexts and provide suggestions that align with developers' intent. Anthropic emphasizes ethical AI use, making their models a trustworthy option for sensitive and critical development environments. Claude Sonnet 3.5 was widely regarded as the most powerful LLM for coding, until o1’s release, and many developers still prefer it. 3. Google Gemini Google's Gemini models leverage Google's extensive research in natural language processing and machine learning. Gemini is designed to integrate seamlessly with Google's ecosystem, offering robust support for various programming languages and frameworks. With a focus on scalability and performance, Gemini models are ideal for large-scale projects requiring consistent and efficient code generation. 4. Other Notable Models: Cohere : Known for their fast and efficient language models, Cohere offers solutions tailored for real-time coding assistance and integration into development workflows. Grok: A versatile AI model designed to assist developers in writing, debugging, and optimizing code effectively. IBM Watson: IBM's AI offerings include models that specialize in enterprise-level coding assistance, focusing on security, compliance, and integration with existing IT infrastructures. Choosing the Right LLM for Your Needs: When selecting an LLM for coding, consider the following factors: Language Support: Ensure the model supports the programming languages you use. Integration: Look for models that integrate smoothly with your development environment and tools. Customization: Some models offer more flexibility for customization and fine-tuning based on specific project requirements. Safety and Reliability: Prioritize models that emphasize code accuracy and security to minimize the risk of introducing vulnerabilities. Click here to learn about the leading LLMs for coding and how they compare. o1-preview and Claude 3.5 Sonnet are considered to be the prominent AI models for coding. Popular AI Coding Tools There are several AI coding tools available, each with unique features tailored to different needs. Here are some of the leading options: 1. Fine Features: Fine offers advanced code generation, intelligent suggestions, automations and a full-context knowledge graph. It leverages state-of-the-art LLMs including o1 and Claude Sonnet to provide accurate and context-aware code assistance. Best For: Professional developers seeking a comprehensive AI assistant that enhances productivity across multiple programming languages, working on existing codebases. Integration: Integrates with GitHub, Linear, Sentry and Slack - with further integrations such as Jira, Monday Dev, Clickup, Data Dog, Jam.dev and posthog coming soon. 2. ChatGPT Features: ChatGPT provides conversational AI assistance, allowing developers to ask questions, seek code examples, and receive real-time support. It excels in understanding natural language queries and providing detailed explanations. Best For: Asking short questions about coding in general - such as explaining functions you’re not familiar with. Integration: Accessible via web interface, API, and can be integrated into various development tools through plugins and extensions. 3. Replit Features: Replit offers an online coding platform with integrated AI assistance. It supports collaborative coding, real-time code suggestions, and automated debugging. Best For: Teams and individual developers looking for a cloud-based development environment with built-in AI support. Integration: Fully web-based, allowing seamless collaboration and access from any device with internet connectivity. 4. Devin Features: Devin focuses on optimizing backend development with AI-driven code generation, API creation, and database management. It offers robust security features and performance optimization tools. Best For: Back-end developers seeking specialized AI tools to streamline server-side development and database interactions. Integration: Compatible with major backend frameworks and integrates with popular cloud services for deployment and management. Devin isn’t currently publicly available, but you can apply for Beta access via their website. 5. Cursor Features: Cursor provides AI-powered code generation and real-time collaboration features. It emphasizes building large blocks of code and reducing development time. Best For: Developers who prioritize code quality and seek tools that can begin a project from scratch and take it to MVP. Integration: Cursor is built on VSCode making it familiar for many developers. Equally as time-consuming as writing code is reviewing code. Here's a comparison of how different AI Coding tools handle code reviews. Conclusion AI coding boosts productivity, improves code quality, and lets developers focus on creative tasks. Providing context, using AI for code generation, and choosing the right tools can greatly benefit developers. Pick the best large language models for your needs to optimize your workflow. Automate tasks, optimize performance, and enhance security with AI coding tools. Embrace AI to unlock new efficiency and innovation. Try Fine for free at ai.fine.dev and elevate your coding workflow today. 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
2026-01-13T08:49:43
https://docs.devcycle.com/platform/security-and-guardrails/audit-log
Audit Log | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up Home Getting Started Essentials DevCycle Overview Key Features System Architecture Feature Hierarchy Feature Types Platform Feature Flags Experimentation Account Management Security and Guardrails Approval Workflows Audit Log Custom Property Schemas Feature Obfuscation Roles & Permissions SDK Visibility Variable Schemas Testing and QA Extras Examples Platform Security and Guardrails Audit Log On this page Audit Log The Audit Log tracks all modifications made to a Feature. DevCycle captures the DevCycle user who made the change, a time stamp, and what was modified on each Feature save. The Audit Log is located on the Audit Log tab on every Feature Form. You can filter modifications by Environment and DevCycle user, and select a particular date range. info The Audit Log Feature was released in early December 2023. No Audit Log modifications were tracked before this date. Modification Card ​ The title of each modification card highlights the change that was made to the Feature upon clicking save. If multiple changes were made on a Feature save and/or there were modifications made to more than one Environment, the card will show the total number modifications made. Click the View Details button on each card for more information about each modification. Modifications are organized by Environment with each card. The color of each Environment tag corresponds to the color selected for that Environment . Items that are added to the Feature will be highlighted in green on the modification card (see below), and removals or deletions of items will be highlighted in red. For modifications to values, each card will show the orignal value on the left-hand column of the card and the updated value on the right. If a value was added or modified, the change will be highlighted in green. If a value was deleted or removed, the change will be highlighted in red. info Please note that Self-Targeting actions are not recorded in the Audit Log. Feature Created Modification Cards ​ When a Feature is created, you will see a "Feature Created" card populate in the Audit Log. This is the first modification card in the Audit Log, and it will outline the initial Feature configuration (initial Variable, Variations, Status, Settings, etc.). The initial Feature configuration can change depending on the Feature Type selected when creating a new Feature. See an example below for an Experiment Feature Type. Edit this page Last updated on Jan 9, 2026 Previous Approval Workflows Next Custom Property Schemas Modification Card Feature Created Modification Cards DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://docs.devcycle.com/sdk/#client-side
SDK Overview | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up SDK Overview SDK Lifecycle SDK Features Client-side SDKS Server-side SDKS SDK Proxy SDK Overview SDK Overview DevCycle has both client-side and server-side SDKs. This page describes the differences between these SDK types. Implementation and usage change depending on which type of SDK is being used. tip Explore our SDK Features and Functionality to discover how to implement your solutions using the DevCycle SDKs. Client Side SDKs ​ DevCycle client-side SDKs are meant for single-user contexts, such as web browsers and mobile apps. These SDKs retrieve their configuration for the current user when they are initialized and any time the user is re-identified. They also receive updates in real time when configuration is changed in the DevCycle platform. The current Client-Side SDKs are: JavaScript SDK React SDK Next.js SDK Angular SDK iOS SDK Android SDK React Native SDK Flutter SDK Roku SDK Server-Side SDKs ​ Server-side SDKs are used in multi-user contexts such as backend services, where each call to the SDK will likely be for a different user. The user's ID and any other targeting information must be passed in on every SDK function call. The current Server-Side SDKs are: NodeJS SDK NestJS SDK Go SDK PHP SDK Python SDK Ruby SDK Java SDK .NET SDK OpenFeature Providers ​ OpenFeature is an open standard that provides a vendor-agnostic, community-driven SDKs for feature flagging that works natively with DevCycle. Client-Side ​ JavaScript React Angular iOS Android Server-Side ​ NodeJS NestJS Go Ruby Java .NET / C# Python PHP Edit this page Last updated on Jan 9, 2026 Next SDK Lifecycle DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://dev.to/etherspot/essential-web3-tool-for-fast-simple-development-transactionkit-erc-4337-compliant-594b
Essential Web3 tool for fast & simple development - TransactionKit (ERC 4337 compliant) - 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 Alexandra for Etherspot Posted on Jan 18, 2024 • Edited on Jun 3, 2024 • Originally published at youtu.be Essential Web3 tool for fast & simple development - TransactionKit (ERC 4337 compliant) # webdev # react # blockchain # dapp Poor Web3 usability is no longer an issue thanks to account abstraction! But now the complexity rests on the developers’ hands 🧑‍💻 How can we improve developers' experience in Web3? This is where Etherspot’s TransactionKit alleviates the burden. 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Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse Etherspot Follow More from Etherspot Ethereum in 2025 Becomes Global Infrastructure, Vitalik on Decentralization vs UX, L2BEAT on Trustless EIL, EIP-7702 Adoption # ethereum # web3 # blockchain Glamsterdam, Bitcoin in MetaMask, EIL & 7702 Alignment, PillarX Universal Gas Tank # blockchain # web3 # ethereum Vitalik’s Gas Futures, EIL X Space, Polygon Upgrade, USDT Gas Fees, ERC-8092 # blockchain # web3 # ethereum 💎 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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2026-01-13T08:49:43
https://www.algolia.com/fr/products/features/personalization
Personnalisez la recherche pour améliorer l’expérience utilisateur | 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. Agent Studio Create, test, and deploy AI agents, fast. 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We got you covered! Brand guidelines Download logo pack PERSONNALISATION AVANCÉE Des expériences 1:1 qui boostent vos profits Créez des parcours d’achat uniques qui amènent vos utilisateurs à convertir encore et encore. Demandez une démo Commencez gratuitement Personalization redefined Most personalization engines rely on static rules or delayed data. But today’s shoppers change their minds fast — and your experience needs to change with them. Algolia Personalization adjusts dynamically, responding to user signals as they happen. Whether you're helping users discover products or guiding them to purchase, Algolia ensures your experience reflects their evolving intent — not just historical behavior.   A full spectrum of personalization Personalize the whole user journey Deliver personalization across searching, browsing, recommendations, and other touchpoints. Tailor your full experience for every user. Automate set-up and optimization Get going in minutes with automatically calculated attributes. Leave ongoing optimization to our algorithm — or fine-tune manually when you want deeper control. Choose the access point that works best for you Developers can run Advanced Personalization from the Dashboard or API — and business users from the Merchandising Studio, making them more self-sufficient. Enrich data with third-party sources Improve customer profiles with data from tools like Segment, Shopify, and Google BigQuery. Our newest feature — now adapting in real time Real-Time Personalization is the latest addition to Algolia’s personalization. It captures user behavior within sessions and adapts experiences in real time — responding to what users are doing right now, not just what they’ve done in the past.  Shorten the path to discovery Reduce abandonment with relevance in the moment Maximize conversion by responding to immediate buying signals Surface the most relevant products even when intent moves across categories Keep shoppers engaged as their behavior shifts during a session Turn every click and browse into a conversion opportunity La personnalisation au service de la rentabilité « Nous avons choisi Algolia principalement pour ses performances, qui ont levé nos inquiétudes concernant la scalabilité. De plus, l’optimisation simplifiée, les mises à jour de stockage et l’indexation des produits gérées par Algolia nous ont débarrassés de toute préoccupation liée à la vitesse. » Josh Hepworth Head of Technology @ Huckleberry Lire le témoignage « Pour un distributeur comme nous, avec plus de 25 000 produits dans notre catalogue, une solution qui améliore l’expérience de chaque utilisateur tout au long de son parcours de recherche apporte une valeur énorme. La personnalisation intégrée d’Algolia représente un vrai pas en avant dans l’ère digitale pour Decathlon Singapour . » Richard Migette Chef de projet e-commerce @ Decathlon Lire le témoignage « Algolia nous a aidés à gérer notre hypercroissance de façon très efficace, en passant rapidement à plus de 30 000 produits dans notre catalogue, en augmentant le taux de clics sur les résultats de recherche de 81 %, et en multipliant par 4 nos conversions liées à la recherche. » Luis Aledo User Experience and CRO Manager @ PCComponentes FAQ – Personnalisation Avancée Quel est le coût de la Personnalisation Avancée ? 0 Consultez notre page tarifs pour plus de détails. La Personnalisation Avancée est-elle conforme aux lois sur la confidentialité ? 0 Oui, les services d’Algolia sont conformes à un large éventail de normes, certifications et réglementations. Celles-ci varient selon le service. En savoir plus. La Personnalisation Avancée peut-elle être utilisée en dehors de l’e-commerce ? 0 Oui. Elle peut aussi personnaliser la recherche, la navigation et les recommandations pour des entreprises dans les médias ou le SaaS, qu’elles soient B2C ou B2B . La Personnalisation Avancée peut-elle être utilisée en dehors de l’e-commerce ? 0 Yes. Personalization applies across search, category pages, homepage recommendations, and even product detail pages—creating a consistent, optimized experience at every step of the customer journey. La Personnalisation Avancée peut-elle être utilisée en dehors de l’e-commerce ? 0 Absolutely. Personalization can reorder or prioritize products on category pages based on each visitor’s preferences and behavior—helping them find what they’re looking for faster.  La Personnalisation Avancée peut-elle être utilisée en dehors de l’e-commerce ? 0 Personalized experiences reduce friction in the customer journey. When users find relevant products more quickly, they’re more likely to convert, repurchase, and stay loyal.  La Personnalisation Avancée peut-elle être utilisée en dehors de l’e-commerce ? 0 Yes. You can create personalization strategies for different user segments—like new vs. returning visitors, or high-value customers—ensuring the experience aligns with each group’s needs.  La Personnalisation Avancée peut-elle être utilisée en dehors de l’e-commerce ? 0 Even without login data, we personalize experiences using session-based signals like search terms, clicks, or category visits to surface relevant results from the very first interaction.  La Personnalisation Avancée peut-elle être utilisée en dehors de l’e-commerce ? 0 Definitely, whether your priority is increasing AOV, boosting discovery, or reducing bounce rates, you can fine-tune personalization strategies to align with your specific KPIs.  Créez les meilleures expériences de recherche et de navigation Obtenir une démo Commencez gratuitement Solutions Aperçu AI Search AI Browse AI Recommendations Ask AI Intelligent Data Kit Cas d'usage Aperçu Recherche Enterprise Ecommerce headless Recherche mobile Recherche vocale Recherche d'image OEM Recherche d'image Développeurs Developer Hub Documentation Intégrations Engineering blog Communauté Discord Status d'API DocSearch Pour Open Source Demos GDPR AI Act Intégrations Salesforce Commerce Cloud B2C Shopify Adobe Commerce Netlify Commercetools BigCommerce Distribué & sécurisé Infrastructure mondiale Sécurité & conformité Azure AWS Industries Aperçu Ecommerce B2C Ecommerce B2B Marketplaces SaaS Média Startups Fashion Tools Search Grader Ecommerce Search Audit Algolia À propos Carrières Newsroom Évènements Équipe dirigeante Impact social Contact us Anti-Modern Slavery Statement Awards Réseaux sociaux Développeurs Developer Hub Documentation Intégrations Engineering blog Communauté Discord Status d'API DocSearch Pour Open Source Demos GDPR AI Act Industries Aperçu Ecommerce B2C Ecommerce B2B Marketplaces SaaS Média Startups Fashion Tools Search Grader Ecommerce Search Audit Solutions Aperçu AI Search AI Browse AI Recommendations Ask AI Intelligent Data Kit Cas d'usage Aperçu Recherche Enterprise Ecommerce headless Recherche mobile Recherche vocale Recherche d'image OEM Recherche d'image Intégrations Salesforce Commerce Cloud B2C Shopify Adobe Commerce Netlify Commercetools BigCommerce Distribué & sécurisé Infrastructure mondiale Sécurité & conformité Azure AWS Algolia À propos Carrières Newsroom Évènements Équipe dirigeante Impact social Contact us Anti-Modern Slavery Statement Awards Réseaux sociaux Algolia mark white ©2026 Algolia - All rights reserved. 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2026-01-13T08:49:43
https://dev.to/pockit_tools/pnpm-vs-npm-vs-yarn-vs-bun-the-2026-package-manager-showdown-51dc#pnpm-10x
pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown - 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 HK Lee Posted on Jan 9 • Originally published at pockit.tools pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown # bunjs # pnpm # yarn # npm Every JavaScript project starts with a choice: which package manager? For years, it was npm by default. Then yarn promised faster installs. Then pnpm claimed to save gigabytes of disk space. And now Bun's built-in package manager claims to make everything else obsolete. But here's what no one tells you: the "best" package manager depends entirely on your specific use case, and blindly following benchmarks can lead you astray. A package manager that's perfect for a solo developer's side project might be terrible for a 500-package monorepo—and vice versa. This guide cuts through the marketing hype. After extensive testing across different project sizes and configurations in January 2026, here's what actually matters for each package manager, when to use it, and how to migrate if you need to. 📌 Version Note: This comparison covers npm 11.x, yarn 4.x (Berry), pnpm 10.x, and Bun 1.3 as of January 2026. The Quick Verdict If you're in a hurry, here's the short version: Use Case Recommended Why Solo/small projects Bun Fastest by far, simplest setup Large monorepos pnpm Best disk efficiency, workspace support Enterprise/legacy npm Maximum compatibility, no surprises Yarn ecosystem yarn 4 PnP mode, excellent plugins Performance at scale pnpm or Bun Both excel, pnpm more mature Now let's dive into why. The Contenders: 2026 State of Play npm 11.x Status: Still the default, ships with Node.js Latest: npm 11.7.0 (December 2025) Philosophy: Compatibility over innovation Key Strength: Works everywhere, always npm has evolved significantly. The node_modules structure is now more optimized, and features like npm audit have become industry standards. But npm's conservative approach means it's rarely the fastest or most efficient—it's just the most reliable. yarn 4.x (Berry) Status: Complete rewrite from yarn 1.x Latest: yarn 4.12.0 (January 2026) Philosophy: Innovation through Plug'n'Play (PnP) Key Strength: Zero-installs, plugin architecture Yarn Berry is essentially a different product from yarn 1. The Plug'n'Play feature eliminates node_modules entirely, instead using a .pnp.cjs file that maps imports directly to zip archives. It's radical—and divisive. pnpm 10.x Status: The "smart" alternative Latest: pnpm 10.27.0 (December 2025) Philosophy: Efficiency without breaking compatibility Key Strength: Content-addressable storage, true deduplication pnpm's approach is elegant: store all packages once in a global content-addressable store, then use hard links to make them appear in each project's node_modules . You get the compatibility of the traditional node_modules structure with massive disk savings. Bun 1.3 Package Manager Status: The new challenger Latest: Bun 1.3.0 (January 1, 2026) Philosophy: Speed above all else Key Strength: Native speed, zero configuration, full-stack capabilities Bun isn't just a package manager—it's a complete JavaScript runtime. Bun 1.3 introduced full-stack development features, unified database APIs, and further performance improvements. Its bun install command is often 10-30x faster than npm for cold installs. Benchmark Results: Cold Install Performance Let's start with what everyone cares about—raw speed. We tested each package manager on the same projects with cleared caches: Small Project (50 dependencies) Project: Typical React + TypeScript starter Dependencies: 50 direct, ~400 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 0.8s │ 18x faster │ │ pnpm │ 4.2s │ 3.4x faster│ │ yarn │ 6.8s │ 2.1x faster│ │ npm │ 14.3s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Medium Project (200 dependencies) Project: Next.js 15 app with common libraries Dependencies: 200 direct, ~1,200 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 2.1s │ 22x faster │ │ pnpm │ 12.4s │ 3.7x faster│ │ yarn │ 18.2s │ 2.5x faster│ │ npm │ 46.1s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Large Monorepo (15 packages, 800 dependencies) Project: Turborepo monorepo with 15 packages Dependencies: 800 direct, ~3,500 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 4.8s │ 28x faster │ │ pnpm │ 28.6s │ 4.7x faster│ │ yarn │ 52.3s │ 2.6x faster│ │ npm │ 134.2s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Key Insight: Bun's lead actually increases with project size. For monorepos, the difference is staggering. Cached/Warm Install Performance But cold installs aren't the whole story. Most of the time, you're installing with some level of caching: Warm Install (lockfile exists, some cache): ┌────────────┬──────────────┬──────────────┐ │ Manager │ Small (50) │ Large (800) │ ├────────────┼──────────────┼──────────────┤ │ bun │ 0.3s │ 1.2s │ │ pnpm │ 1.1s │ 8.4s │ │ yarn (PnP) │ 0.0s* │ 0.0s* │ │ npm │ 3.2s │ 24.6s │ └────────────┴──────────────┴──────────────┘ * Yarn PnP with zero-installs commits dependencies to repo Enter fullscreen mode Exit fullscreen mode Yarn's Zero-Installs Trick: With PnP mode and zero-installs, yarn commits your dependencies directly to the repository. CI/CD runs need zero install time—they just yarn and go. The tradeoff? Your repo size increases significantly. Disk Usage: Where pnpm Shines Raw speed is one thing, but what about your hard drive? Single Project Disk Usage Same 200-dependency project: ┌────────────┬──────────────┬──────────────┐ │ Manager │ node_modules │ vs npm │ ├────────────┼──────────────┼──────────────┤ │ npm │ 487 MB │ baseline │ │ yarn │ 502 MB │ +3% │ │ pnpm │ 124 MB* │ -75% │ │ bun │ 461 MB │ -5% │ └────────────┴──────────────┴──────────────┘ * pnpm uses hard links to global store Enter fullscreen mode Exit fullscreen mode Multiple Projects (Same Dependencies) Here's where pnpm's architecture pays off. If you have 10 projects using React 19: 10 Projects with overlapping dependencies: ┌────────────┬──────────────┬──────────────┐ │ Manager │ Total Disk │ vs npm │ ├────────────┼──────────────┼──────────────┤ │ npm │ 4.87 GB │ baseline │ │ yarn │ 5.02 GB │ +3% │ │ pnpm │ 612 MB │ -87% │ │ bun │ 4.61 GB │ -5% │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode pnpm stores each unique package version exactly once. Every project links to that single copy. If you work on many projects, pnpm can save tens of gigabytes. Bun's Approach: Bun uses a global cache but still creates full node_modules directories. It's faster than npm/yarn but doesn't achieve pnpm's deduplication. Monorepo Support Compared Monorepos have become the default for many organizations. Here's how each manager handles them: Workspace Configuration npm (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode yarn (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode pnpm (pnpm-workspace.yaml): # pnpm-workspace.yaml packages : - ' packages/*' - ' apps/*' Enter fullscreen mode Exit fullscreen mode Bun (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode Workspace Features Comparison Feature npm yarn pnpm Bun Workspace protocol ( workspace:* ) ❌ ✅ ✅ ✅ Selective dependency installation ❌ ✅ ✅ ✅ Parallel task execution ❌ ✅ ✅ ✅ Cross-workspace linking Basic Good Excellent Good Hoisting control Limited Full Full Limited Filtering ( --filter ) ❌ ✅ ✅ ❌ The Bottom Line: pnpm and yarn are the clear leaders for monorepo management. npm's workspace support is functional but basic. Bun's is improving rapidly but still catching up. Real-World Monorepo Performance We tested a Turborepo setup with 15 packages: Task: Install + Build all packages ┌────────────┬──────────────┬──────────────┐ │ Manager │ Install │ Full Build │ ├────────────┼──────────────┼──────────────┤ │ pnpm │ 28.6s │ 142s │ │ bun │ 4.8s │ 138s │ │ yarn │ 52.3s │ 156s │ │ npm │ 134.2s │ 198s │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode Interesting: Bun's install speed advantage shrinks when you include build time. The build phase dominates, making the install speed difference less impactful for CI/CD overall. Security Features Security has become a first-class concern. Here's how each manager handles it: Audit Capabilities Feature npm yarn pnpm Bun audit command ✅ Native ✅ Plugin ✅ Native ❌ Auto-fix vulnerabilities ✅ ✅ ✅ ❌ Advisory database npm registry npm registry npm registry - SBOM generation ✅ ✅ Plugin ✅ ❌ Critical Note: Bun currently lacks built-in security auditing. For production applications, you'll need third-party tools like Snyk or Socket. Lockfile Security All four managers use lockfiles to ensure reproducible installs: npm: package-lock.json (JSON) yarn: yarn.lock (custom format) pnpm: pnpm-lock.yaml (YAML) Bun: bun.lockb (binary) Bun's Binary Lockfile: Bun's bun.lockb is binary for speed. While this makes installs faster, it's not human-readable and can't be easily diffed in code review. Bun offers bun.lock (text) as an alternative, but it's not the default. Supply Chain Protection Feature npm yarn pnpm Bun Signature verification ✅ ✅ ✅ ❌ Strict peer dependencies Optional Optional Default Optional .npmrc security options Full Limited Full Limited Network isolation mode ❌ ✅ ✅ ❌ Compatibility Reality Check Here's what nobody talks about: not every package works perfectly with every manager. Known Compatibility Issues (January 2026) pnpm: Some packages break with strict node_modules structure Workaround: shamefully-hoist=true in .npmrc Most major packages now support pnpm natively yarn PnP: Many packages still don't support PnP mode Workaround: nodeLinker: node-modules falls back to traditional structure Adoption is improving but still incomplete Bun: ~98% npm compatibility (up from 95% in 2025) Some native modules still have issues Workaround: Use --backend=copyfile for problematic packages Framework Compatibility Framework npm yarn pnpm Bun Next.js 15 ✅ ✅ ✅ ✅ Remix ✅ ✅ ✅ ⚠️ Nuxt 4 ✅ ✅ ✅ ✅ Angular 19 ✅ ⚠️ ✅ ⚠️ SvelteKit ✅ ✅ ✅ ✅ Astro 5 ✅ ✅ ✅ ✅ ⚠️ = Works but some edge cases or extra configuration needed CI/CD Performance For many teams, CI/CD time is where package manager choice really matters: GitHub Actions Benchmark # Same workflow, different package managers # Node.js 22, ubuntu-latest, clean cache ┌────────────┬──────────────┬──────────────┬──────────────┐ │ Manager │ Install │ Cache Hit │ Total Job │ ├────────────┼──────────────┼──────────────┼──────────────┤ │ npm │ 48s │ 12s │ 2m 34s │ │ yarn │ 21s │ 8s │ 2m 15s │ │ yarn (PnP) │ 18s │ 0s* │ 2m 02s │ │ pnpm │ 14s │ 4s │ 2m 08s │ │ bun │ 3s │ 1s │ 1m 52s │ └────────────┴──────────────┴──────────────┴──────────────┘ * Zero-installs : dependencies committed to repo Enter fullscreen mode Exit fullscreen mode Docker Build Performance # Multi-stage build comparison ┌────────────┬──────────────┬──────────────┐ │ Manager │ Layer Cache │ No Cache │ ├────────────┼──────────────┼──────────────┤ │ npm │ 18s │ 52s │ │ pnpm │ 8s │ 24s │ │ bun │ 2s │ 6s │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode The Docker Secret: Bun's speed advantage is even more pronounced in Docker because its binary includes the runtime—no need to install Node.js separately. Migration Guides Ready to switch? Here's how: npm → pnpm Install pnpm: npm install -g pnpm Enter fullscreen mode Exit fullscreen mode Import existing lockfile: pnpm import Enter fullscreen mode Exit fullscreen mode Delete old files: rm -rf node_modules package-lock.json Enter fullscreen mode Exit fullscreen mode Install: pnpm install Enter fullscreen mode Exit fullscreen mode Update scripts (if needed): // package.json - usually works as-is { "scripts" : { "dev" : "next dev" , // no change needed "build" : "next build" } } Enter fullscreen mode Exit fullscreen mode npm → Bun Install Bun: curl -fsSL https://bun.sh/install | bash Enter fullscreen mode Exit fullscreen mode Remove old files: rm -rf node_modules package-lock.json Enter fullscreen mode Exit fullscreen mode Install: bun install Enter fullscreen mode Exit fullscreen mode Update scripts for Bun runtime (optional): { "scripts" : { "dev" : "bun run --bun next dev" , "build" : "bun run next build" } } Enter fullscreen mode Exit fullscreen mode yarn 1.x → yarn 4.x (Berry) # Enable corepack (Node.js 16+) corepack enable # Set yarn version yarn set version stable # Migrate configuration yarn config set nodeLinker node-modules # for compatibility # Install yarn install Enter fullscreen mode Exit fullscreen mode Rollback Plan If migration causes issues: # Keep your old lockfile backed up! cp package-lock.json package-lock.json.backup # To rollback: rm -rf node_modules bun.lockb pnpm-lock.yaml yarn.lock mv package-lock.json.backup package-lock.json npm install Enter fullscreen mode Exit fullscreen mode When to Use What: Decision Framework Use npm when: ✅ Maximum compatibility is required ✅ Team is unfamiliar with alternatives ✅ Legacy project with many native dependencies ✅ Corporate environment with strict tooling policies ✅ You want "it just works" Use yarn when: ✅ You need Plug'n'Play zero-installs ✅ You want the plugin ecosystem ✅ Your team is already yarn experts ✅ You need advanced workspace features ✅ Offline-first development is important Use pnpm when: ✅ Disk space is a concern ✅ You have many projects with overlapping dependencies ✅ Large monorepo with complex dependencies ✅ You want speed without sacrificing compatibility ✅ Strict dependency isolation matters Use Bun when: ✅ Speed is the absolute priority ✅ You're starting a new project ✅ CI/CD time is a major cost ✅ You're building Node.js APIs or scripts ✅ You want a unified runtime + package manager The Hidden Costs Nobody Mentions Before you switch, consider: Learning Curve npm → pnpm: Minimal. Almost drop-in. npm → yarn 4: Moderate. PnP mode requires understanding. npm → Bun: Low for package management, higher if using Bun runtime. Tooling Compatibility IDE support: All four work with VS Code, JetBrains, etc. CI/CD templates: npm has the most, Bun the least ready-made Docker images: npm/yarn are everywhere, pnpm common, Bun less common Team Onboarding The fastest package manager doesn't help if it slows down your team. Consider: How comfortable is your team with the new tool? Are your documentation and scripts updated? Have you tested the entire development workflow? Future Outlook: 2026 and Beyond npm: Will remain the default. Focus on incremental improvements. yarn: Continuing to push PnP adoption. Better monorepo support coming. pnpm: Rapid growth in enterprise. Becoming the "safe modern choice." Bun: Aggressive development. Aiming for 100% npm compatibility. May become the default for new projects by 2027. The ecosystem is fragmenting in healthy ways. Competition drives innovation—and all four managers are better for it. Conclusion: There's No Wrong Choice (Mostly) After extensive testing, here's the honest truth: all four package managers work fine for most projects. The performance differences, while measurable, rarely matter for small-to-medium projects. Where choice matters: Monorepos: pnpm or yarn CI/CD-heavy workflows: Bun or pnpm Disk-constrained systems: pnpm Maximum compatibility: npm Bleeding edge: Bun The most important thing isn't which package manager you choose—it's that you choose consistently across your projects and team. Switching between managers constantly creates more friction than any speed difference could justify. My recommendation for 2026: New projects: Try Bun. It's fast enough to justify the minor compatibility risks. Existing projects: Consider pnpm if you're feeling pain. Otherwise, npm is fine. Enterprise monorepos: pnpm is the safe, powerful choice. Benchmarks conducted January 2026 on M3 MacBook Pro with Node.js 22.x. Results will vary based on hardware, network, and project specifics. Always test with your own codebase before making decisions. 🚀 Explore More: This article is from the Pockit Blog . If you found this helpful, check out Pockit.tools . It’s a curated collection of offline-capable dev utilities. Available on Chrome Web Store for free. 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 HK Lee Follow solo web developer Joined Dec 26, 2025 Trending on DEV Community Hot I Am 38, I Am a Nurse, and I Have Always Wanted to Learn Coding # career # learning # beginners # coding Top 7 Featured DEV Posts of the Week # top7 # discuss What was your win this week??? # weeklyretro # 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. 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2026-01-13T08:49:43
https://dev.to/t/computerscience/page/75
Computer Science 🤓 Page 75 - 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 Computer Science 🤓 Follow Hide This tag is for sharing and asking questions about anything related to computer science, including data structures, algorithms, research, and white papers! 🤓 Create Post submission guidelines Please ensure that any post that is tagged with #computerscience is related to computer science in some way. Promotional posts will be untagged, as will posts unrelated to CS. Please also be sure that your content adheres to the DEV Code of Conduct and that your comments are constructive and kind. about #computerscience Did you learn about a new data structure recently? Or perhaps you tried to implement an algorithm in a new language? Or maybe you need help understanding a white paper? The #computerscience tag is a great place for any of these questions and ideas. Please be sure to cross-tag any content that might help other folks in the DEV community. For example, an introduction to linked lists should also be tagged with the #beginners tag. Similarly, a post that asks for a simple explanation to the traveling salesman problem should be tagged with the #explainlikeimfive tag. Older #computerscience 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 The Future of Quantum Computing: Potential Applications and Challenges Pwaveino Victor Clarkson Pwaveino Victor Clarkson Pwaveino Victor Clarkson Follow Jul 23 '23 The Future of Quantum Computing: Potential Applications and Challenges # ai # computerscience # learning # machinelearning Comments Add Comment 7 min read Understanding the Difference Between Asynchronous and Synchronous Programming Bimsara Hirushan Bimsara Hirushan Bimsara Hirushan Follow Jul 22 '23 Understanding the Difference Between Asynchronous and Synchronous Programming # programming # beginners # angular # computerscience Comments Add Comment 3 min read Implementing Type inference in Rust. Part #1: Unification Adi Salimgereyev Adi Salimgereyev Adi Salimgereyev Follow Jul 21 '23 Implementing Type inference in Rust. Part #1: Unification # computerscience # rust # coding # compiler 3  reactions Comments Add Comment 6 min read Do you even read bro? 5 advices on reading and staying up to date Petar Garžina Petar Garžina Petar Garžina Follow Jul 21 '23 Do you even read bro? 5 advices on reading and staying up to date # beginners # programming # computerscience # javascript 6  reactions Comments 2  comments 7 min read Entendendo Extremidade Computacional (endianness) usando uma Coxinha Guilherme Sousa Guilherme Sousa Guilherme Sousa Follow Jul 20 '23 Entendendo Extremidade Computacional (endianness) usando uma Coxinha # discuss # computerscience # braziliandevs 10  reactions Comments Add Comment 3 min read Critical Sections and Race Conditions: Ensuring Thread Safety in Concurrent Programs Pranav Jandu Pranav Jandu Pranav Jandu Follow Jul 20 '23 Critical Sections and Race Conditions: Ensuring Thread Safety in Concurrent Programs # java # computerscience # beginners # programming Comments Add Comment 2 min read Understanding Linked List: Features, Time Complexity, and Implementation Masaki Fukunishi Masaki Fukunishi Masaki Fukunishi Follow Jul 18 '23 Understanding Linked List: Features, Time Complexity, and Implementation # datastructures # algorithms # computerscience # typescript 4  reactions Comments Add Comment 5 min read The Renaissance of Data Science: Embracing Software Design Principles Prayson Wilfred Daniel Prayson Wilfred Daniel Prayson Wilfred Daniel Follow Jul 18 '23 The Renaissance of Data Science: Embracing Software Design Principles # machinelearning # computerscience # designpatterns # datascience 7  reactions Comments Add Comment 3 min read What exactly happens when you enter a URL into your Browser Atishay Jain Atishay Jain Atishay Jain Follow Jul 18 '23 What exactly happens when you enter a URL into your Browser # networking # learning # design # computerscience 1  reaction Comments Add Comment 7 min read "Survival Guide for the All-in-One Developer: Beyond Code" MartinLoera MartinLoera MartinLoera Follow Jul 6 '23 "Survival Guide for the All-in-One Developer: Beyond Code" # programming # career # beginners # computerscience Comments Add Comment 6 min read Understanding Embedded Systems Akash Dev Akash Dev Akash Dev Follow Jul 16 '23 Understanding Embedded Systems # es # computerscience # research # history Comments Add Comment 5 min read The Intel x86 Architecture: A Look at its Past, Present, and Future Akash Dev Akash Dev Akash Dev Follow Jul 15 '23 The Intel x86 Architecture: A Look at its Past, Present, and Future # intel # architecture # computerscience # processor 6  reactions Comments Add Comment 4 min read Setting Up CS50 Library Locally in Visual Studio Code Taiwo Jazz Taiwo Jazz Taiwo Jazz Follow Jul 14 '23 Setting Up CS50 Library Locally in Visual Studio Code # computerscience # cs50 # c # programming 64  reactions Comments 1  comment 4 min read The Evolution of Computing: From Vacuum Tubes to Microprocessors Akash Dev Akash Dev Akash Dev Follow Jul 13 '23 The Evolution of Computing: From Vacuum Tubes to Microprocessors # ai # microprocessor # history # computerscience 7  reactions Comments 1  comment 4 min read Understanding Hash table: Features, Pros, Cons, and Time Complexity Masaki Fukunishi Masaki Fukunishi Masaki Fukunishi Follow Jul 11 '23 Understanding Hash table: Features, Pros, Cons, and Time Complexity # datastructures # algorithms # computerscience # typescript 3  reactions Comments Add Comment 5 min read Understanding and Addressing Performance Issues in Software Development Akash Dev Akash Dev Akash Dev Follow Jul 11 '23 Understanding and Addressing Performance Issues in Software Development # performance # development # softwareengineering # computerscience 7  reactions Comments Add Comment 5 min read Getting Started with AWS Lambda: Building Serverless Functions Jyoti Bhasin Jyoti Bhasin Jyoti Bhasin Follow Jul 10 '23 Getting Started with AWS Lambda: Building Serverless Functions # aws # computerscience # awsbigdata # beginners 3  reactions Comments 2  comments 2 min read Breaking Down the Difference Between Computer Organization and Architecture Akash Dev Akash Dev Akash Dev Follow Jul 10 '23 Breaking Down the Difference Between Computer Organization and Architecture # architecture # computerscience # design # hardware 10  reactions Comments Add Comment 5 min read Blogroll: the list of blogs that I like to read Guilherme Ananias Guilherme Ananias Guilherme Ananias Follow Jul 9 '23 Blogroll: the list of blogs that I like to read # programming # productivity # writing # computerscience 7  reactions Comments Add Comment 2 min read Deep Dive into Data structures using Javascript - AVL Tree Şahin Arslan Şahin Arslan Şahin Arslan Follow Jun 18 '23 Deep Dive into Data structures using Javascript - AVL Tree # webdev # javascript # computerscience # datastructures Comments Add Comment 18 min read How computers represent integers: Two's complement notation Ibrahim Isa Jajere Ibrahim Isa Jajere Ibrahim Isa Jajere Follow Jul 1 '23 How computers represent integers: Two's complement notation # programming # computerscience # java # beginners Comments Add Comment 5 min read Breadth vs Depth - How do you organize your brain as a software engineer and communicate with different styles? Hansel Wei Hansel Wei Hansel Wei Follow Jun 30 '23 Breadth vs Depth - How do you organize your brain as a software engineer and communicate with different styles? # algorithms # computerscience # productivity # softwareengineering 4  reactions Comments Add Comment 3 min read What's your CPU actually doing? Ashmita Chakraborty Ashmita Chakraborty Ashmita Chakraborty Follow Jun 29 '23 What's your CPU actually doing? # cpu # computerscience # programming # beginners 1  reaction Comments Add Comment 3 min read Data Structures in JavaScript (Part 2): Stacks and Queues David Hurtado David Hurtado David Hurtado Follow Jun 8 '23 Data Structures in JavaScript (Part 2): Stacks and Queues # beginners # javascript # computerscience 5  reactions Comments 1  comment 5 min read Bitwise Operations: A Simplified Guide for Beginners Stephen Gbolagade Stephen Gbolagade Stephen Gbolagade Follow Jun 28 '23 Bitwise Operations: A Simplified Guide for Beginners # bitwise # programming # binary # computerscience 38  reactions Comments 1  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://dev.to/new/cloud
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https://www.algolia.com/fr/distributed-secure/global-infrastructure
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https://dev.to/t/pnpm
Pnpm - 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 Forem Close # pnpm Follow Hide Create Post Older #pnpm posts 1 2 3 4 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown HK Lee HK Lee HK Lee Follow Jan 9 pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown # pnpm # npm # yarn # bunjs Comments Add Comment 9 min read Why I Chose Monorepo Architecture: From Code Chaos to 2.8s Builds Saswata Pal Saswata Pal Saswata Pal Follow Dec 9 '25 Why I Chose Monorepo Architecture: From Code Chaos to 2.8s Builds # monorepo # architecture # turborepo # pnpm Comments Add Comment 32 min read Why I Chose Monorepo: From Copy-Paste Hell to 2.8s Builds Saswata Pal Saswata Pal Saswata Pal Follow Dec 9 '25 Why I Chose Monorepo: From Copy-Paste Hell to 2.8s Builds # monorepo # turborepo # architecture # pnpm 1  reaction Comments Add Comment 7 min read Peer dependencies in (P)NPM Timo Schinkel Timo Schinkel Timo Schinkel Follow Nov 24 '25 Peer dependencies in (P)NPM # javascript # npm # pnpm Comments Add Comment 10 min read Node Package Managers Compared: npm vs Yarn vs pnpm vs Bun ⚙️ Taron Vardanyan Taron Vardanyan Taron Vardanyan Follow Nov 12 '25 Node Package Managers Compared: npm vs Yarn vs pnpm vs Bun ⚙️ # bunjs # pnpm # yarn # npm Comments Add Comment 3 min read The Case of the Missing Proxy: When Multiple Valtio Instances Broke My App Rad Code Rad Code Rad Code Follow Nov 9 '25 The Case of the Missing Proxy: When Multiple Valtio Instances Broke My App # reactnative # pnpm # debugging # valtio 8  reactions Comments Add Comment 3 min read 🚀 FNPM Just Became Invisible (In the Good Way): Transparent Alias, Better Tests & a Smoother Experience Jairo Fernández Jairo Fernández Jairo Fernández Follow Nov 14 '25 🚀 FNPM Just Became Invisible (In the Good Way): Transparent Alias, Better Tests & a Smoother Experience # npm # pnpm # fnpm # node 13  reactions Comments Add Comment 3 min read Stuffing Deno and a pnpm workspace into a Docker image Brendonovich Brendonovich Brendonovich Follow Oct 8 '25 Stuffing Deno and a pnpm workspace into a Docker image # typescript # deno # pnpm Comments Add Comment 4 min read React Native, pnpm, and Monorepos: A Dependency Hoisting Journey Rad Code Rad Code Rad Code Follow Nov 5 '25 React Native, pnpm, and Monorepos: A Dependency Hoisting Journey # reactnative # pnpm # monorepo # kotlin 14  reactions Comments Add Comment 4 min read Fixing `ERR_INVALID_THIS` on Vercel by Switching from pnpm to Bun 阿豪 阿豪 阿豪 Follow Oct 2 '25 Fixing `ERR_INVALID_THIS` on Vercel by Switching from pnpm to Bun # bunjs # vercel # webdev # pnpm Comments Add Comment 1 min read PNPM Content-Addressable Store Looks Broken on macOS Kelvyn Thai Kelvyn Thai Kelvyn Thai Follow Oct 16 '25 PNPM Content-Addressable Store Looks Broken on macOS # pnpm # contentaddressable # globalstore 6  reactions Comments Add Comment 2 min read PNPM: Beyond Dependency Management - A Modern Alternative to NVM Ítalo Queiroz Ítalo Queiroz Ítalo Queiroz Follow Aug 30 '25 PNPM: Beyond Dependency Management - A Modern Alternative to NVM # pnpm # javascript # node # productivity 1  reaction Comments Add Comment 4 min read NodeJS Fundamentals: pnpm DevOps Fundamental DevOps Fundamental DevOps Fundamental Follow for DevOps Fundamentals Jun 21 '25 NodeJS Fundamentals: pnpm # node # backend # javascript # pnpm Comments Add Comment 6 min read Sharing Types and Values Across Frontend and Backend Using a PNPM Monorepo (React + NestJS) SeongKuk Han SeongKuk Han SeongKuk Han Follow Jun 29 '25 Sharing Types and Values Across Frontend and Backend Using a PNPM Monorepo (React + NestJS) # pnpm # monorepo # webdev # typescript 3  reactions Comments Add Comment 5 min read Creating a scalable Monorepo for Vue - Nx Dawid Nitka Dawid Nitka Dawid Nitka Follow Jun 1 '25 Creating a scalable Monorepo for Vue - Nx # monorepo # vue # nx # pnpm 2  reactions Comments Add Comment 3 min read কেন আমি npm ছেড়ে pnpm-এ গেলাম (এবং আপনারও কেন সেটা করা উচিত) RONiB RONiB RONiB Follow May 24 '25 কেন আমি npm ছেড়ে pnpm-এ গেলাম (এবং আপনারও কেন সেটা করা উচিত) # npm # pnpm # node # javascript Comments Add Comment 1 min read pnpm vs npm vs yarn: আপনার প্রোজেক্টে কোনটা ব্যবহার করা উচিত? RONiB RONiB RONiB Follow May 23 '25 pnpm vs npm vs yarn: আপনার প্রোজেক্টে কোনটা ব্যবহার করা উচিত? # pnpm # npm # yarn Comments Add Comment 1 min read Yarn, Npm থেকে PNPM: আমার ডেভেলপমেন্ট লাইফের গেম চেঞ্জার! Rasel Mahmud Rasel Mahmud Rasel Mahmud Follow May 14 '25 Yarn, Npm থেকে PNPM: আমার ডেভেলপমেন্ট লাইফের গেম চেঞ্জার! # webdev # programming # npm # pnpm 1  reaction Comments Add Comment 1 min read Why pnpm Is the Superior Choice for JavaScript Package Management Akash Akash Akash Follow for MechCloud Academy Apr 19 '25 Why pnpm Is the Superior Choice for JavaScript Package Management # pnpm # javascript # webdev 1  reaction Comments Add Comment 4 min read Automate changelog generation and publish with Changesets Sibiraj Sibiraj Sibiraj Follow Mar 2 '25 Automate changelog generation and publish with Changesets # changesets # pnpm # githubactions Comments Add Comment 2 min read Creating a scalable Monorepo for Vue - Shared configs Dawid Nitka Dawid Nitka Dawid Nitka Follow Feb 22 '25 Creating a scalable Monorepo for Vue - Shared configs # monorepo # vue # nx # pnpm Comments Add Comment 3 min read NPM vs Yarn vs PNPM: Choosing the right package manager for your project Roman Roman Roman Follow Feb 19 '25 NPM vs Yarn vs PNPM: Choosing the right package manager for your project # npm # yarn # pnpm # nodepackagemanager 1  reaction Comments Add Comment 4 min read FNPM: The Package Manager Drama Ends Here 🚀 Jairo Fernández Jairo Fernández Jairo Fernández Follow Feb 13 '25 FNPM: The Package Manager Drama Ends Here 🚀 # node # yarn # pnpm # fucknpm 6  reactions Comments Add Comment 2 min read Creating a scalable Monorepo for Vue - Libs vs Apps Dawid Nitka Dawid Nitka Dawid Nitka Follow Jan 25 '25 Creating a scalable Monorepo for Vue - Libs vs Apps # monorepo # vue # nx # pnpm 1  reaction Comments Add Comment 3 min read How I Manage Node & Package Manager Versions in 2025 Michal Bryxí Michal Bryxí Michal Bryxí Follow Jan 23 '25 How I Manage Node & Package Manager Versions in 2025 # node # pnpm # proto 2  reactions Comments Add Comment 2 min read loading... trending guides/resources Peer dependencies in (P)NPM React Native, pnpm, and Monorepos: A Dependency Hoisting Journey Why I Chose Monorepo Architecture: From Code Chaos to 2.8s Builds pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown The Case of the Missing Proxy: When Multiple Valtio Instances Broke My App Why I Chose Monorepo: From Copy-Paste Hell to 2.8s Builds 🚀 FNPM Just Became Invisible (In the Good Way): Transparent Alias, Better Tests & a Smoother Expe... 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2026-01-13T08:49:43
https://www.fine.dev/blog/ai-coding-guide#the-importance-of-context-in-ai-coding
AI Coding – A Simple Guide for Developers Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back AI Coding – A Simple Guide for Developers Table of Contents Introduction: What is AI Coding The Importance of Context in AI Coding Tips for Providing Better Context Practical Instructions for Providing Context to AI Coding Tools 1. Creating a Knowledge Graph 2. Implementing Retrieval-Augmented Generation (RAG) 3. Copy-Pasting Relevant Code into ChatGPT and Claude 4. Understanding Potential Mistakes Without Proper Context Using AI to Generate Code Incorporating AI Tools into Your Workflow Advice for Front-End Developers Practical Tips Advice for Back-End Developers Practical Tips Use Cases for AI in Coding 1. Automated Bug Fixes 2. Predicting Performance Bottlenecks 3. Large Codebase Refactoring Industry-Specific Benefits Best Large Language Models (LLMs) for Coding 1. OpenAI 2. Anthropic 3. Google Gemini 4. Other Notable Models Choosing the Right LLM for Your Needs Popular AI Coding Tools 1. Fine 2. ChatGPT 3. Replit 4. Devin 5. Cursor Conclusion Introduction: What is AI Coding In today's rapidly evolving tech landscape, AI coding has emerged as a game-changer for developers. But what exactly is AI coding? Simply put, it's the use of artificial intelligence to assist in writing, optimizing, and managing code. AI coding tools help developers write better, faster, and more efficient code by automating repetitive tasks, providing intelligent code suggestions, and even debugging. This blog will delve into the importance of context in AI coding, how to use AI for generating code, offer practical advice for both front-end and back-end developers, explore various use cases, introduce some of the top AI coding tools available today, and discuss the best large language models (LLMs) for coding. The Importance of Context in AI Coding The first key to success in AI coding is understanding context . AI tools analyze the surrounding code to generate relevant and accurate suggestions. Without proper context, AI-generated code can be irrelevant or even introduce errors. Here's why context matters: Code Quality: In complex systems, context helps maintain consistency and functionality across different modules. Relevance: AI tools can provide more precise code snippets when they understand the broader scope of the project. Efficiency: Proper context reduces the time developers spend correcting AI-generated code. Imagine asking a lawyer off the street to represent you in court, without knowing anything about you, the case, or the evidence. The best lawyer in the world would struggle! The same goes for AI in coding - only if you provide the relevant information will you get relevant results. Tips for Providing Better Context: Descriptive Comments: Write clear and detailed comments to guide the AI tool. Structured Code: Organize your code logically to help AI understand the flow and dependencies. Consistent Naming Conventions: Use meaningful and consistent names for variables, functions, and classes. Integrate Platforms: The more of your tech stack that can be integrated, the more data the AI will be able to access and the better the output will be. Fine offers GitHub, Linear, and Sentry integrations with more on the way. Practical Instructions for Providing Context to AI Coding Tools To maximize the effectiveness of AI coding tools, providing comprehensive and well-structured context is essential. Here are some practical methods to enhance context for AI tools: 1. Creating a Knowledge Graph A knowledge graph is a structured representation of information that outlines the relationships between different components of your codebase. By creating a knowledge graph, you can provide AI tools with a holistic view of your project, enabling them to make more informed suggestions. How to Create a Knowledge Graph: Identify Key Components: List out all the modules, classes, functions, and their interactions within your project. Define Relationships: Establish how these components interact, depend on each other, and contribute to the overall functionality. Use Visualization Tools: Utilize tools like Neo4j or Graphviz to visualize the knowledge graph, making it easier to understand and update. Benefits: Enhances AI's understanding of the project structure. Facilitates better code suggestions and optimizations. Helps in identifying dependencies and potential areas for improvement. Fine creates a knowledge graph called Atlas, which includes your codebase from GitHub and issues from Sentry and Linear. This way, it prepares the AI to handle any task you give it. You don’t need to work hard creating your own knowledge graph when we’ve done it for you. 2. Implementing Retrieval-Augmented Generation (RAG) Retrieval-Augmented Generation (RAG) combines traditional information retrieval techniques with generative AI models to provide more accurate and contextually relevant responses. How to Use RAG: Integrate Data Sources: Connect your AI coding tool to relevant data sources such as documentation, code repositories, and knowledge bases. Contextual Retrieval: Ensure that the AI can retrieve pertinent information from these sources before generating code suggestions. Continuous Learning: Update the data sources regularly to keep the AI informed about the latest changes and best practices in your project. Benefits: Improves the relevance and accuracy of AI-generated code. Enables AI to leverage existing knowledge and documentation. Enhances the tool's ability to handle complex queries and tasks. 3. Copy-Pasting Relevant Code into ChatGPT and Claude When using conversational AI tools like ChatGPT for coding assistance, providing snippets of relevant code can significantly improve the quality of the responses. How to Provide Relevant Code: Select Key Sections: Identify and copy the sections of code that are directly related to your query or the task at hand. Provide Contextual Information: Along with the code, include comments or explanations that describe the functionality and purpose of the code segments. Ask Specific Questions: Clearly state what you need help with, such as debugging a particular function or optimizing a code block. Example: # Function to calculate the factorial of a number def factorial(n): if n == 0: return 1 else: return n * factorial(n-1) # I need to optimize this recursive factorial function to handle larger numbers without hitting the recursion limit. Question: How can I optimize the above factorial function to handle larger inputs efficiently? Benefits: Provides AI with the necessary context to generate accurate solutions. Reduces ambiguity, leading to more precise and helpful responses. Saves time by directly addressing specific issues within the code. This is similar to GitHub Copilot and some other tools where you can highlight the relevant context to direct the AI. 4. Understanding Potential Mistakes Without Proper Context AI coding tools, while powerful, can make mistakes if not provided with adequate context. Common errors include: Irrelevant Code Suggestions: Without understanding the project structure, AI might suggest code that doesn't fit the existing framework. Syntax Errors: Lack of context can lead to syntax mistakes, especially in languages with strict syntax rules. Logical Flaws: AI might introduce logical errors if it doesn't fully grasp the intended functionality. Security Vulnerabilities: Inadequate context can result in code that exposes security loopholes or fails to follow best practices. Backend Errors In languages commonly used for backend such as Python, AI may make more mistakes if it doesn’t have context, such as NameErrors and IndentationErrors - mistakes that you wouldn’t have made coding manually. You can read more about common Python errors and how different AI applications handle them here.   Fine is less likely to make such errors, as it has full knowledge of your codebase.   Mitigation Strategies: Always Review AI-Generated Code: Never blindly trust the AI's suggestions; always verify and test the code. Provide Comprehensive Context: The more information you provide, the better the AI can assist accurately. Use Multiple Sources: Cross-reference AI suggestions with official documentation and best practices. Continuous Feedback: Provide feedback to the AI tool to help it learn and improve over time. Using AI to Generate Code AI coding tools are revolutionizing the way developers write code by automating mundane tasks and enhancing creativity. Here's how AI is being used to generate code: Code Snippets: AI can suggest entire lines or blocks of code based on the current context. Automating Repetitive Tasks: Tasks like boilerplate code generation, formatting, and refactoring can be handled by AI, freeing up developers to focus on more complex problems. Bug Detection: AI can identify potential bugs and vulnerabilities in real-time, ensuring higher code quality. Incorporating AI Tools into Your Workflow: Choose the Right Tool: Select an AI coding tool that integrates seamlessly with your development workflow. Customize Settings: Tailor the tool’s settings to match your coding style and project requirements. Regularly Review Suggestions: While AI can assist, always review and test AI-generated code to ensure it meets your standards. Advice for Front-End Developers Front-end development focuses on the user interface and user experience. AI coding tools can significantly enhance this process: UI/UX Enhancement: AI can suggest design improvements and optimize user interfaces for better engagement. Streamlining CSS/HTML/JS: Automate the generation of responsive designs and ensure cross-browser compatibility. Automated Testing: AI tools can perform repetitive testing tasks, ensuring your front-end code is robust and error-free. Practical Tips: Use AI for Responsive Design: Let AI suggest layout adjustments for different screen sizes. Optimize Performance: AI can analyze and optimize front-end performance, reducing load times and improving user experience. Leverage AI for Accessibility: Ensure your applications are accessible by using AI to identify and fix accessibility issues. Advice for Back-End Developers Back-end development involves server-side logic, database management, and ensuring the smooth operation of applications. AI coding tools can streamline these processes: Automating Server-Side Logic: AI can generate efficient server-side code, handling complex operations with ease. Security Vulnerability Detection: Identify and fix security issues before they become problematic. Database Query Optimization: AI can analyze and optimize database queries for better performance. Practical Tips: API Generation: Use AI to create and manage APIs, ensuring they are secure and efficient. Automate Testing: Implement AI-driven testing to validate back-end processes and ensure reliability. Optimize Code Performance: Leverage AI to analyze and enhance the performance of your server-side code. Use Cases for AI in Coding AI coding has a wide range of applications across various industries. Here are some real-world use cases: 1. Automated Bug Fixes Fine’s AI can identify and fix bugs in your codebase, reducing the time spent on debugging and improving overall code quality. 2. Predicting Performance Bottlenecks By analyzing code patterns, AI can predict potential performance issues, allowing developers to address them proactively. 3. Large Codebase Refactoring Managing and refactoring large codebases can be daunting. AI tools can assist with this process, ensuring consistency and reducing errors. Industry-Specific Benefits: E-Commerce: Enhance platform performance and security with AI-driven optimizations. Add features to improve user experience and conversion rates rapidly. Fintech: Ensure the reliability and security of financial applications through AI-assisted coding. SaaS Platforms: Improve scalability and performance with AI-generated and optimized code. Healthcare: Streamline data processing and ensure compliance with regulatory standards through AI-assisted code generation. Education Technology: Enhance learning platforms by personalizing features and improving code quality with AI-driven development. Gaming: Optimize game performance and identify bugs faster with AI-generated suggestions and automated testing. Best Large Language Models (LLMs) for Coding Large Language Models (LLMs) are at the heart of modern AI coding tools. They power the intelligent features that assist developers in writing and managing code. Here are some of the best LLMs for coding: 1. OpenAI OpenAI's models, including GPT-4 , are renowned for their versatility and capability in understanding and generating human-like text. In coding, GPT-4 excels at code generation, debugging, and providing intelligent suggestions across multiple programming languages. OpenAI also offers Codex , specifically fine-tuned for programming tasks, making it a popular choice for developers seeking advanced AI assistance. OpenAI also recently released preview and mini versions of their latest model, o1, which is outperforming competitors on many benchmarks. 2. Anthropic Anthropic's Claude models focus on safety and reliability, ensuring that AI-generated code adheres to best practices and minimizes errors. These models are designed to understand complex coding contexts and provide suggestions that align with developers' intent. Anthropic emphasizes ethical AI use, making their models a trustworthy option for sensitive and critical development environments. Claude Sonnet 3.5 was widely regarded as the most powerful LLM for coding, until o1’s release, and many developers still prefer it. 3. Google Gemini Google's Gemini models leverage Google's extensive research in natural language processing and machine learning. Gemini is designed to integrate seamlessly with Google's ecosystem, offering robust support for various programming languages and frameworks. With a focus on scalability and performance, Gemini models are ideal for large-scale projects requiring consistent and efficient code generation. 4. Other Notable Models: Cohere : Known for their fast and efficient language models, Cohere offers solutions tailored for real-time coding assistance and integration into development workflows. Grok: A versatile AI model designed to assist developers in writing, debugging, and optimizing code effectively. IBM Watson: IBM's AI offerings include models that specialize in enterprise-level coding assistance, focusing on security, compliance, and integration with existing IT infrastructures. Choosing the Right LLM for Your Needs: When selecting an LLM for coding, consider the following factors: Language Support: Ensure the model supports the programming languages you use. Integration: Look for models that integrate smoothly with your development environment and tools. Customization: Some models offer more flexibility for customization and fine-tuning based on specific project requirements. Safety and Reliability: Prioritize models that emphasize code accuracy and security to minimize the risk of introducing vulnerabilities. Click here to learn about the leading LLMs for coding and how they compare. o1-preview and Claude 3.5 Sonnet are considered to be the prominent AI models for coding. Popular AI Coding Tools There are several AI coding tools available, each with unique features tailored to different needs. Here are some of the leading options: 1. Fine Features: Fine offers advanced code generation, intelligent suggestions, automations and a full-context knowledge graph. It leverages state-of-the-art LLMs including o1 and Claude Sonnet to provide accurate and context-aware code assistance. Best For: Professional developers seeking a comprehensive AI assistant that enhances productivity across multiple programming languages, working on existing codebases. Integration: Integrates with GitHub, Linear, Sentry and Slack - with further integrations such as Jira, Monday Dev, Clickup, Data Dog, Jam.dev and posthog coming soon. 2. ChatGPT Features: ChatGPT provides conversational AI assistance, allowing developers to ask questions, seek code examples, and receive real-time support. It excels in understanding natural language queries and providing detailed explanations. Best For: Asking short questions about coding in general - such as explaining functions you’re not familiar with. Integration: Accessible via web interface, API, and can be integrated into various development tools through plugins and extensions. 3. Replit Features: Replit offers an online coding platform with integrated AI assistance. It supports collaborative coding, real-time code suggestions, and automated debugging. Best For: Teams and individual developers looking for a cloud-based development environment with built-in AI support. Integration: Fully web-based, allowing seamless collaboration and access from any device with internet connectivity. 4. Devin Features: Devin focuses on optimizing backend development with AI-driven code generation, API creation, and database management. It offers robust security features and performance optimization tools. Best For: Back-end developers seeking specialized AI tools to streamline server-side development and database interactions. Integration: Compatible with major backend frameworks and integrates with popular cloud services for deployment and management. Devin isn’t currently publicly available, but you can apply for Beta access via their website. 5. Cursor Features: Cursor provides AI-powered code generation and real-time collaboration features. It emphasizes building large blocks of code and reducing development time. Best For: Developers who prioritize code quality and seek tools that can begin a project from scratch and take it to MVP. Integration: Cursor is built on VSCode making it familiar for many developers. Equally as time-consuming as writing code is reviewing code. Here's a comparison of how different AI Coding tools handle code reviews. Conclusion AI coding boosts productivity, improves code quality, and lets developers focus on creative tasks. Providing context, using AI for code generation, and choosing the right tools can greatly benefit developers. Pick the best large language models for your needs to optimize your workflow. Automate tasks, optimize performance, and enhance security with AI coding tools. Embrace AI to unlock new efficiency and innovation. Try Fine for free at ai.fine.dev and elevate your coding workflow today. 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
2026-01-13T08:49:43
https://dev.to/t/vscode/page/183
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2026-01-13T08:49:43
https://dev.to/savagepixie
SavagePixie - 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. 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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 SavagePixie Always learning new things. I love web development and coding in general. Joined Joined on  Jul 23, 2019 github website 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 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. 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 Four Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least four years. 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Got it Close More info about @savagepixie Skills/Languages JavaScript Currently learning Elixir Post 26 posts published Comment 262 comments written Tag 12 tags followed Best practices to authenticate with Passport.js SavagePixie SavagePixie SavagePixie Follow Jul 20 '20 Best practices to authenticate with Passport.js # help # javascript # node # discuss 12  reactions Comments 1  comment 1 min read Want to connect with SavagePixie? Create an account to connect with SavagePixie. You can also sign in below to proceed if you already have an account. Create Account Already have an account? 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2026-01-13T08:49:43
https://discuss.opensource.org/faq
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2026-01-13T08:49:43
https://forem.com/sivarampg#main-content
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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 Sivaram Full Stack Engineer. Consultant. Designing & Developing Blockchain & AI E2E Solutions. De-risking Ambiguity. OSS Location India Joined Joined on  Oct 5, 2023 Personal website https://sivaramp.com github website More info about @sivarampg Badges Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. Got it Close Top 7 Awarded for having a post featured in the weekly "must-reads" list. 🙌 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 GitHub Repositories swapi.info All the Star Wars data you've ever wanted :) Swapi.info is an open-source, FREE, JSON-only, CDN-powered, Wicked-fast, Unrestricted Star Wars data API endpoints provider. TypeScript • 6 stars Post 19 posts published Comment 1 comment written Tag 0 tags followed Pin Pinned How to Ingest 1 Billion Events Per Day Without Kafka: A Serverless Masterclass Sivaram Sivaram Sivaram Follow Nov 10 '25 How to Ingest 1 Billion Events Per Day Without Kafka: A Serverless Masterclass # webdev # devops # cloudflare # architecture 13  reactions Comments 1  comment 8 min read MdBin: Share Beautiful Rendered Markdown Instead of Raw Code Sivaram Sivaram Sivaram Follow Oct 15 '25 MdBin: Share Beautiful Rendered Markdown Instead of Raw Code # markdown # webdev # productivity # opensource 13  reactions Comments 1  comment 4 min read Get upto 8x more serverless function invocations on Vercel! Sivaram Sivaram Sivaram Follow Oct 5 '23 Get upto 8x more serverless function invocations on Vercel! # vercel # serverless # api # cost 7  reactions Comments Add Comment 1 min read Cowork: Claude Code for the Rest of Your Work Sivaram Sivaram Sivaram Follow Jan 13 Cowork: Claude Code for the Rest of Your Work # ai # productivity # tooling # software 5  reactions Comments Add Comment 5 min read Want to connect with Sivaram? Create an account to connect with Sivaram. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Bags.fm: The Solana Launchpad That's Changing Creator Monetization Sivaram Sivaram Sivaram Follow Jan 12 Bags.fm: The Solana Launchpad That's Changing Creator Monetization # discuss # solana # cryptocurrency # webdev 5  reactions Comments Add Comment 5 min read Building Reliable RAG Systems Sivaram Sivaram Sivaram Follow Jan 11 Building Reliable RAG Systems # rag # architecture # tutorial # ai 6  reactions Comments Add Comment 4 min read Building a Production-Ready Prediction Market Smart Contract in Solidity: Complete Guide with Foundry Sivaram Sivaram Sivaram Follow Jan 8 Building a Production-Ready Prediction Market Smart Contract in Solidity: Complete Guide with Foundry # solidity # ethereum # smartcontract # web3 5  reactions Comments Add Comment 7 min read Building a Prediction Market on Solana with Anchor: Complete Rust Smart Contract Guide Sivaram Sivaram Sivaram Follow Jan 8 Building a Prediction Market on Solana with Anchor: Complete Rust Smart Contract Guide # solana # web3 # smartcontract # predictionmarket 6  reactions Comments 1  comment 11 min read The Ralph Wiggum Approach: Running AI Coding Agents for Hours (Not Minutes) Sivaram Sivaram Sivaram Follow Jan 5 The Ralph Wiggum Approach: Running AI Coding Agents for Hours (Not Minutes) # webdev # productivity # ai # agents 11  reactions Comments Add Comment 8 min read How the Creator of Claude Code Uses Claude Code: A Complete Breakdown Sivaram Sivaram Sivaram Follow Jan 3 How the Creator of Claude Code Uses Claude Code: A Complete Breakdown # ai # webdev # programming # productivity 10  reactions Comments Add Comment 11 min read Cutting My Self-Hosted Analytics Stack Memory by 45% Sivaram Sivaram Sivaram Follow Jan 1 Cutting My Self-Hosted Analytics Stack Memory by 45% # webdev # programming # postgres # bunjs 6  reactions Comments Add Comment 2 min read Building a Real‑Time VWAP Dashboard with Bun, Binance WebSockets & SQLite Sivaram Sivaram Sivaram Follow Nov 16 '25 Building a Real‑Time VWAP Dashboard with Bun, Binance WebSockets & SQLite # webdev # bunjs # development # learning 7  reactions Comments Add Comment 3 min read 🚀 PoCs & MVPs 101 — The Art of Building Smart, Not Big Sivaram Sivaram Sivaram Follow Oct 17 '25 🚀 PoCs & MVPs 101 — The Art of Building Smart, Not Big # productivity # webdev # management # software 5  reactions Comments Add Comment 3 min read MdBin: Share Beautiful Rendered Markdown Instead of Raw Code Sivaram Sivaram Sivaram Follow Oct 16 '25 MdBin: Share Beautiful Rendered Markdown Instead of Raw Code # markdown # ai # productivity # claude 5  reactions Comments 1  comment 4 min read Building branchyard: How I Learned to Stop Worrying and Love Git Worktrees Sivaram Sivaram Sivaram Follow Aug 12 '25 Building branchyard: How I Learned to Stop Worrying and Love Git Worktrees # git # ai # webdev # programming 9  reactions Comments 1  comment 4 min read Scraping Twitter in 2025: A Developer's Guide to Surviving the API Apocalypse Sivaram Sivaram Sivaram Follow Jul 9 '25 Scraping Twitter in 2025: A Developer's Guide to Surviving the API Apocalypse # webdev # nextjs # webscraping # api 6  reactions Comments Add Comment 3 min read Cloudflare Containers Are Here: Deploy Docker Globally with a Single Command Sivaram Sivaram Sivaram Follow Jun 25 '25 Cloudflare Containers Are Here: Deploy Docker Globally with a Single Command # cloudflare # webdev # devops # ai 6  reactions Comments 1  comment 3 min read How I Serve 4.5 Million Star Wars API Requests for Free Sivaram Sivaram Sivaram Follow Jun 24 '25 How I Serve 4.5 Million Star Wars API Requests for Free # webdev # programming # opensource # cloud 5  reactions Comments Add Comment 3 min read Cloudflare saved my Vercel quota & I barely noticed Sivaram Sivaram Sivaram Follow Apr 25 '25 Cloudflare saved my Vercel quota & I barely noticed # discuss # vercel # nextjs # ddos 7  reactions 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 DEV Community — Your community HQ Home About Contact 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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2026-01-13T08:49:43
https://docs.devcycle.com/cli
DevCycle CLI & MCP Server | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up CLI / MCP Overview CLI CLI Reference CLI User Guides Projects Environments SDK Keys Features Variables Variations Targeting Rules Self-Targeting CLI User Guides MCP MCP Getting Started MCP Reference MCP User Guides Incident Investigation CLI On this page DevCycle CLI & MCP Server This repository contains the DevCycle CLI for managing feature flags from the command line, plus an MCP (Model Context Protocol) server that enables AI coding assistants to interact with DevCycle. Major features include: Fully manage your Features, Variables, Variations and Targeting Rules from the command line Detect and list DevCycle Variable usages in your codebase Manage your Self-Targeting Overrides to quickly switch between Variable values Generate type definitions for type-safe usage of DevCycle (Typescript only) MCP (Model Context Protocol) server for AI-powered feature flag management with Cursor and Claude The CLI can be customized in several ways using command-line args or by creating a configuration file . Command Topics Pattern captures the key including surrounding quotes Pattern strips quotes, capturing only the content MCP Server for AI Assistants ​ The DevCycle MCP (Model Context Protocol) server enables AI coding assistants like Cursor and Claude to manage feature flags directly from your development environment. DevCycle offers a hosted MCP server that requires no local installation. Quick Setup (No Installation Required) ​ Configure your AI assistant to use the hosted MCP server: Cursor : Add to .cursor/mcp_settings.json : { "mcpServers" : { "devcycle" : { "url" : "https://mcp.devcycle.com/mcp" } } } Claude Desktop : Add to your Claude config file: { "mcpServers" : { "devcycle" : { "command" : "npx" , "args" : [ "mcp-remote" , "https://mcp.devcycle.com/mcp" ] } } } That's it! The server will guide you through OAuth authentication when you first use it. Your AI assistant can now create, update, and manage feature flags on your behalf. For local installation options, detailed configuration, available tools, and advanced usage, see the complete MCP documentation . CLI Documentation ​ Setup ​ Install the CLI ​ Using NPM $ npm install -g @devcycle/cli Or alternatively, using homebrew $ brew tap devcyclehq/cli $ brew install devcycle Authentication ​ Many of the CLI commands require DevCycle API authorization. There are several ways to provide these credentials. Using Access Tokens (preferred) ​ Login Command ​ By using the login sso command , the CLI will retrieve and store an access token, which is valid for 24 hours. The login again command can be used to retrieve a new access token using the saved project and organization without prompting for them. This process will open browser windows to interact with the DevCycle universal login page. It will first obtain a personal access token, then prompt you to choose an organization. A second browser window is used to authenticate the CLI with your chosen organization. To switch organizations once logged in, the organizations select command can be used. If executing the CLI in a containerized environment, please ensure one of the following PORTs can be accessed via Port Forwarding: 2194 (default), 2195, 2196 or 8080. This will allow the authentication process to complete and set the access token appropriately. Repo Init Command ​ The repo init command behaves in the same way as login sso , but creates a repo configuration file and stores the project and organization choices there instead. Using Client Credentials ​ Client Credentials in Auth File ​ Use the dvc status command to find the configuration file location for your platform. The credentials can be stored in the file pointed to by the Auth config path. Create the file if it does not exist, with the following contents. clientCredentials : client_id : <your client id > client_secret : <your client secret > This file should not be checked in to version control. The default location is based on the oclif configDir If you intend to run the CLI using options that override config file locations, the dvc status command command can be run with those options to confirm that the file locations are as expected. Project Selection ​ You also need to specify the default project ID for the CLI to use. If there is a repo configuration file, the dvc diff and dvc usages commands will use the project defined there. Otherwise, this is chosen during login or set using the project select command Environment Variables ​ Set the following environment variables: $ export DEVCYCLE_CLIENT_ID=<your client id> $ export DEVCYCLE_CLIENT_SECRET=<your client secret> $ export DEVCYCLE_PROJECT_KEY=<your project key> Command-Line Arguments ​ The CLI can be run with the following arguments: $ dvc --client-id=<your client id> --client-secret=<your client secret> --project=<your project key> Github Action ​ The Devcycle Github actions are configured with auth information through the project-key , client-id and client-secret configuration parameters. This is passed to the CLI via command line arguments. Usage ​ $ npm install -g @devcycle/cli $ dvc COMMAND running command... $ dvc (--version) @devcycle/cli/6.2.1 linux-x64 node-v22.21.1 $ dvc --help [COMMAND] USAGE $ dvc COMMAND ... Command Topics ​ dvc alias - Manage repository variable aliases. dvc autocomplete - display autocomplete installation instructions dvc cleanup - Replace a DevCycle variable with a static value in the current version of your code. Currently only JavaScript is supported. dvc diff - Print a diff of DevCycle variable usage between two versions of your code. dvc environments - Create a new Environment for an existing Feature. dvc features - Create, view, or modify Features with the Management API. dvc generate - Generate Devcycle related files. dvc help - Display help for dvc. dvc identity - View or manage your DevCycle Identity. dvc keys - Retrieve SDK keys from the Management API. dvc login - Log in to DevCycle. dvc logout - Discards any auth configuration that has been stored in the auth configuration file. dvc organizations - List or switch organizations. dvc overrides - Create, view, or modify Overrides for a Project with the Management API. dvc projects - Create, or view Projects with the Management API. dvc repo - Manage repository configuration. dvc status - Check CLI status. dvc targeting - Create, view, or modify Targeting Rules for a Feature with the Management API. dvc usages - Print all DevCycle variable usages in the current version of your code. dvc variables - Create, view, or modify Variables with the Management API. dvc variations - Create a new Variation for an existing Feature. Repo Configuration ​ The following commands can only be run from the root of a configured repository dvc diff dvc usages dvc alias dvc cleanup Many of the options available as command-line args can also be specified using a repo configuration file. The default location for this file is <REPO ROOT>/.devcycle/config.yml . This location can be overridden using the --repo-config-path flag. The configuration file format is documented below: ### the project and organization to use when connecting to the DevCycle Rest API for this repo project : "project-key" org : id : "org_xxxxxx" name : "unique-org-key" display_name : "Human Readable Org Name" ### block for configuring "code insights" features like diff and variable usage scanning ### use this section to improve the detection of DevCycle usage within your code codeInsights : ### add additional names to check for when looking for instances of DVCClient from an SDK clientNames : - "dvcClient" ### map the values used in your code to the corresponding variable key in DevCycle variableAliases : "VARIABLES.ENABLE_V1" : "enable-v1" ### additional regex patterns used to match variables for a specific file extension matchPatterns : ### file extension to override for, containing a list of patterns to use js : - dvcClient\.variable\(\s* [ "' ] ( [ ^"' ] *) [ "' ] ### an array of file glob patterns to include in usage scan includeFiles : - "*.[jt]s" ### an array of file glob patterns to exclude from usage scan excludeFiles : - "dist/*" Match Patterns and Aliases ​ When identifying variable usages in the code, the CLI will identify DevCycle SDK methods by default. To capture other usages you may define match patterns. Match patterns are defined by file extension. note Each pattern must include exactly one capture group for the variable key. Capture the entire key value (including surrounding quotes if you choose the “with quotes” pattern). Match patterns can be defined in the configuration file, for example: codeInsights : matchPatterns : js : - customVariableGetter\(\s* [ "' ] ( [ ^"' ] *) [ "' ] ts : - customVariableGetter\(\s* [ "' ] ( [ ^"' ] *) [ "' ] jsx : - customVariableHook\(\s* [ "' ] ( [ ^"' ] *) [ "' ] - customVariableGetter\(\s* [ "' ] ( [ ^"' ] *) [ "' ] tsx : - customVariableHook\(\s* [ "' ] ( [ ^"' ] *) [ "' ] - customVariableGetter\(\s* [ "' ] ( [ ^"' ] *) [ "' ] Capturing with or without quotes ​ Match patterns can capture variable keys with or without quotes, which affects whether aliases are needed: With quotes: ## Pattern captures the key including surrounding quotes - dvcClient\.variable\(\s *( [ "' ] [ ^"' ] * [ "' ] )\s* , Matches: dvcClient.variable('my-variable', default) Captures: 'my-variable' (with quotes) Without quotes (aliases or generated constants required): ## Pattern strips quotes, capturing only the content - dvcClient\.variable\(\s* [ "' ] ( [ ^"' ] *) [ "' ] Matches: dvcClient.variable('my-variable', default) Captures: my-variable Match patterns can also be passed directly to relevant commands using the --match-pattern flag: dvc usages --match-pattern ts="customVariableGetter\(\s*["']([^"']*)["']" js="customVariableGetter\(\s*["']([^"']*)["']" When testing your regex the --show-regex flag can be helpful. This will print all patterns used to find matches in your codebase. dvc usages --show-regex Custom Wrapper Functions ​ If you use wrapper functions around the SDK, add patterns for them. Example: Custom wrapper functions codeInsights : matchPatterns : ts : ## Matches: getFeatureFlag('my-variable', defaultValue) - getFeatureFlag\(\s *( [ ^ , ) ] *)\s* , ## Matches: isFeatureEnabled('my-variable') - isFeatureEnabled\(\s *( [ ^ , ) ] *)\s*\) tsx : ## Matches: useFeatureFlag('my-variable', defaultValue) - useFeatureFlag\(\s *( [ ^ , ) ] *)\s* , Edit this page Previous CLI / MCP Overview Next CLI Reference MCP Server for AI Assistants CLI Documentation Setup Authentication Usage Command Topics Repo Configuration DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://www.fine.dev/blog/ai-coding-guide#using-ai-to-generate-code
AI Coding – A Simple Guide for Developers Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back AI Coding – A Simple Guide for Developers Table of Contents Introduction: What is AI Coding The Importance of Context in AI Coding Tips for Providing Better Context Practical Instructions for Providing Context to AI Coding Tools 1. Creating a Knowledge Graph 2. Implementing Retrieval-Augmented Generation (RAG) 3. Copy-Pasting Relevant Code into ChatGPT and Claude 4. Understanding Potential Mistakes Without Proper Context Using AI to Generate Code Incorporating AI Tools into Your Workflow Advice for Front-End Developers Practical Tips Advice for Back-End Developers Practical Tips Use Cases for AI in Coding 1. Automated Bug Fixes 2. Predicting Performance Bottlenecks 3. Large Codebase Refactoring Industry-Specific Benefits Best Large Language Models (LLMs) for Coding 1. OpenAI 2. Anthropic 3. Google Gemini 4. Other Notable Models Choosing the Right LLM for Your Needs Popular AI Coding Tools 1. Fine 2. ChatGPT 3. Replit 4. Devin 5. Cursor Conclusion Introduction: What is AI Coding In today's rapidly evolving tech landscape, AI coding has emerged as a game-changer for developers. But what exactly is AI coding? Simply put, it's the use of artificial intelligence to assist in writing, optimizing, and managing code. AI coding tools help developers write better, faster, and more efficient code by automating repetitive tasks, providing intelligent code suggestions, and even debugging. This blog will delve into the importance of context in AI coding, how to use AI for generating code, offer practical advice for both front-end and back-end developers, explore various use cases, introduce some of the top AI coding tools available today, and discuss the best large language models (LLMs) for coding. The Importance of Context in AI Coding The first key to success in AI coding is understanding context . AI tools analyze the surrounding code to generate relevant and accurate suggestions. Without proper context, AI-generated code can be irrelevant or even introduce errors. Here's why context matters: Code Quality: In complex systems, context helps maintain consistency and functionality across different modules. Relevance: AI tools can provide more precise code snippets when they understand the broader scope of the project. Efficiency: Proper context reduces the time developers spend correcting AI-generated code. Imagine asking a lawyer off the street to represent you in court, without knowing anything about you, the case, or the evidence. The best lawyer in the world would struggle! The same goes for AI in coding - only if you provide the relevant information will you get relevant results. Tips for Providing Better Context: Descriptive Comments: Write clear and detailed comments to guide the AI tool. Structured Code: Organize your code logically to help AI understand the flow and dependencies. Consistent Naming Conventions: Use meaningful and consistent names for variables, functions, and classes. Integrate Platforms: The more of your tech stack that can be integrated, the more data the AI will be able to access and the better the output will be. Fine offers GitHub, Linear, and Sentry integrations with more on the way. Practical Instructions for Providing Context to AI Coding Tools To maximize the effectiveness of AI coding tools, providing comprehensive and well-structured context is essential. Here are some practical methods to enhance context for AI tools: 1. Creating a Knowledge Graph A knowledge graph is a structured representation of information that outlines the relationships between different components of your codebase. By creating a knowledge graph, you can provide AI tools with a holistic view of your project, enabling them to make more informed suggestions. How to Create a Knowledge Graph: Identify Key Components: List out all the modules, classes, functions, and their interactions within your project. Define Relationships: Establish how these components interact, depend on each other, and contribute to the overall functionality. Use Visualization Tools: Utilize tools like Neo4j or Graphviz to visualize the knowledge graph, making it easier to understand and update. Benefits: Enhances AI's understanding of the project structure. Facilitates better code suggestions and optimizations. Helps in identifying dependencies and potential areas for improvement. Fine creates a knowledge graph called Atlas, which includes your codebase from GitHub and issues from Sentry and Linear. This way, it prepares the AI to handle any task you give it. You don’t need to work hard creating your own knowledge graph when we’ve done it for you. 2. Implementing Retrieval-Augmented Generation (RAG) Retrieval-Augmented Generation (RAG) combines traditional information retrieval techniques with generative AI models to provide more accurate and contextually relevant responses. How to Use RAG: Integrate Data Sources: Connect your AI coding tool to relevant data sources such as documentation, code repositories, and knowledge bases. Contextual Retrieval: Ensure that the AI can retrieve pertinent information from these sources before generating code suggestions. Continuous Learning: Update the data sources regularly to keep the AI informed about the latest changes and best practices in your project. Benefits: Improves the relevance and accuracy of AI-generated code. Enables AI to leverage existing knowledge and documentation. Enhances the tool's ability to handle complex queries and tasks. 3. Copy-Pasting Relevant Code into ChatGPT and Claude When using conversational AI tools like ChatGPT for coding assistance, providing snippets of relevant code can significantly improve the quality of the responses. How to Provide Relevant Code: Select Key Sections: Identify and copy the sections of code that are directly related to your query or the task at hand. Provide Contextual Information: Along with the code, include comments or explanations that describe the functionality and purpose of the code segments. Ask Specific Questions: Clearly state what you need help with, such as debugging a particular function or optimizing a code block. Example: # Function to calculate the factorial of a number def factorial(n): if n == 0: return 1 else: return n * factorial(n-1) # I need to optimize this recursive factorial function to handle larger numbers without hitting the recursion limit. Question: How can I optimize the above factorial function to handle larger inputs efficiently? Benefits: Provides AI with the necessary context to generate accurate solutions. Reduces ambiguity, leading to more precise and helpful responses. Saves time by directly addressing specific issues within the code. This is similar to GitHub Copilot and some other tools where you can highlight the relevant context to direct the AI. 4. Understanding Potential Mistakes Without Proper Context AI coding tools, while powerful, can make mistakes if not provided with adequate context. Common errors include: Irrelevant Code Suggestions: Without understanding the project structure, AI might suggest code that doesn't fit the existing framework. Syntax Errors: Lack of context can lead to syntax mistakes, especially in languages with strict syntax rules. Logical Flaws: AI might introduce logical errors if it doesn't fully grasp the intended functionality. Security Vulnerabilities: Inadequate context can result in code that exposes security loopholes or fails to follow best practices. Backend Errors In languages commonly used for backend such as Python, AI may make more mistakes if it doesn’t have context, such as NameErrors and IndentationErrors - mistakes that you wouldn’t have made coding manually. You can read more about common Python errors and how different AI applications handle them here.   Fine is less likely to make such errors, as it has full knowledge of your codebase.   Mitigation Strategies: Always Review AI-Generated Code: Never blindly trust the AI's suggestions; always verify and test the code. Provide Comprehensive Context: The more information you provide, the better the AI can assist accurately. Use Multiple Sources: Cross-reference AI suggestions with official documentation and best practices. Continuous Feedback: Provide feedback to the AI tool to help it learn and improve over time. Using AI to Generate Code AI coding tools are revolutionizing the way developers write code by automating mundane tasks and enhancing creativity. Here's how AI is being used to generate code: Code Snippets: AI can suggest entire lines or blocks of code based on the current context. Automating Repetitive Tasks: Tasks like boilerplate code generation, formatting, and refactoring can be handled by AI, freeing up developers to focus on more complex problems. Bug Detection: AI can identify potential bugs and vulnerabilities in real-time, ensuring higher code quality. Incorporating AI Tools into Your Workflow: Choose the Right Tool: Select an AI coding tool that integrates seamlessly with your development workflow. Customize Settings: Tailor the tool’s settings to match your coding style and project requirements. Regularly Review Suggestions: While AI can assist, always review and test AI-generated code to ensure it meets your standards. Advice for Front-End Developers Front-end development focuses on the user interface and user experience. AI coding tools can significantly enhance this process: UI/UX Enhancement: AI can suggest design improvements and optimize user interfaces for better engagement. Streamlining CSS/HTML/JS: Automate the generation of responsive designs and ensure cross-browser compatibility. Automated Testing: AI tools can perform repetitive testing tasks, ensuring your front-end code is robust and error-free. Practical Tips: Use AI for Responsive Design: Let AI suggest layout adjustments for different screen sizes. Optimize Performance: AI can analyze and optimize front-end performance, reducing load times and improving user experience. Leverage AI for Accessibility: Ensure your applications are accessible by using AI to identify and fix accessibility issues. Advice for Back-End Developers Back-end development involves server-side logic, database management, and ensuring the smooth operation of applications. AI coding tools can streamline these processes: Automating Server-Side Logic: AI can generate efficient server-side code, handling complex operations with ease. Security Vulnerability Detection: Identify and fix security issues before they become problematic. Database Query Optimization: AI can analyze and optimize database queries for better performance. Practical Tips: API Generation: Use AI to create and manage APIs, ensuring they are secure and efficient. Automate Testing: Implement AI-driven testing to validate back-end processes and ensure reliability. Optimize Code Performance: Leverage AI to analyze and enhance the performance of your server-side code. Use Cases for AI in Coding AI coding has a wide range of applications across various industries. Here are some real-world use cases: 1. Automated Bug Fixes Fine’s AI can identify and fix bugs in your codebase, reducing the time spent on debugging and improving overall code quality. 2. Predicting Performance Bottlenecks By analyzing code patterns, AI can predict potential performance issues, allowing developers to address them proactively. 3. Large Codebase Refactoring Managing and refactoring large codebases can be daunting. AI tools can assist with this process, ensuring consistency and reducing errors. Industry-Specific Benefits: E-Commerce: Enhance platform performance and security with AI-driven optimizations. Add features to improve user experience and conversion rates rapidly. Fintech: Ensure the reliability and security of financial applications through AI-assisted coding. SaaS Platforms: Improve scalability and performance with AI-generated and optimized code. Healthcare: Streamline data processing and ensure compliance with regulatory standards through AI-assisted code generation. Education Technology: Enhance learning platforms by personalizing features and improving code quality with AI-driven development. Gaming: Optimize game performance and identify bugs faster with AI-generated suggestions and automated testing. Best Large Language Models (LLMs) for Coding Large Language Models (LLMs) are at the heart of modern AI coding tools. They power the intelligent features that assist developers in writing and managing code. Here are some of the best LLMs for coding: 1. OpenAI OpenAI's models, including GPT-4 , are renowned for their versatility and capability in understanding and generating human-like text. In coding, GPT-4 excels at code generation, debugging, and providing intelligent suggestions across multiple programming languages. OpenAI also offers Codex , specifically fine-tuned for programming tasks, making it a popular choice for developers seeking advanced AI assistance. OpenAI also recently released preview and mini versions of their latest model, o1, which is outperforming competitors on many benchmarks. 2. Anthropic Anthropic's Claude models focus on safety and reliability, ensuring that AI-generated code adheres to best practices and minimizes errors. These models are designed to understand complex coding contexts and provide suggestions that align with developers' intent. Anthropic emphasizes ethical AI use, making their models a trustworthy option for sensitive and critical development environments. Claude Sonnet 3.5 was widely regarded as the most powerful LLM for coding, until o1’s release, and many developers still prefer it. 3. Google Gemini Google's Gemini models leverage Google's extensive research in natural language processing and machine learning. Gemini is designed to integrate seamlessly with Google's ecosystem, offering robust support for various programming languages and frameworks. With a focus on scalability and performance, Gemini models are ideal for large-scale projects requiring consistent and efficient code generation. 4. Other Notable Models: Cohere : Known for their fast and efficient language models, Cohere offers solutions tailored for real-time coding assistance and integration into development workflows. Grok: A versatile AI model designed to assist developers in writing, debugging, and optimizing code effectively. IBM Watson: IBM's AI offerings include models that specialize in enterprise-level coding assistance, focusing on security, compliance, and integration with existing IT infrastructures. Choosing the Right LLM for Your Needs: When selecting an LLM for coding, consider the following factors: Language Support: Ensure the model supports the programming languages you use. Integration: Look for models that integrate smoothly with your development environment and tools. Customization: Some models offer more flexibility for customization and fine-tuning based on specific project requirements. Safety and Reliability: Prioritize models that emphasize code accuracy and security to minimize the risk of introducing vulnerabilities. Click here to learn about the leading LLMs for coding and how they compare. o1-preview and Claude 3.5 Sonnet are considered to be the prominent AI models for coding. Popular AI Coding Tools There are several AI coding tools available, each with unique features tailored to different needs. Here are some of the leading options: 1. Fine Features: Fine offers advanced code generation, intelligent suggestions, automations and a full-context knowledge graph. It leverages state-of-the-art LLMs including o1 and Claude Sonnet to provide accurate and context-aware code assistance. Best For: Professional developers seeking a comprehensive AI assistant that enhances productivity across multiple programming languages, working on existing codebases. Integration: Integrates with GitHub, Linear, Sentry and Slack - with further integrations such as Jira, Monday Dev, Clickup, Data Dog, Jam.dev and posthog coming soon. 2. ChatGPT Features: ChatGPT provides conversational AI assistance, allowing developers to ask questions, seek code examples, and receive real-time support. It excels in understanding natural language queries and providing detailed explanations. Best For: Asking short questions about coding in general - such as explaining functions you’re not familiar with. Integration: Accessible via web interface, API, and can be integrated into various development tools through plugins and extensions. 3. Replit Features: Replit offers an online coding platform with integrated AI assistance. It supports collaborative coding, real-time code suggestions, and automated debugging. Best For: Teams and individual developers looking for a cloud-based development environment with built-in AI support. Integration: Fully web-based, allowing seamless collaboration and access from any device with internet connectivity. 4. Devin Features: Devin focuses on optimizing backend development with AI-driven code generation, API creation, and database management. It offers robust security features and performance optimization tools. Best For: Back-end developers seeking specialized AI tools to streamline server-side development and database interactions. Integration: Compatible with major backend frameworks and integrates with popular cloud services for deployment and management. Devin isn’t currently publicly available, but you can apply for Beta access via their website. 5. Cursor Features: Cursor provides AI-powered code generation and real-time collaboration features. It emphasizes building large blocks of code and reducing development time. Best For: Developers who prioritize code quality and seek tools that can begin a project from scratch and take it to MVP. Integration: Cursor is built on VSCode making it familiar for many developers. Equally as time-consuming as writing code is reviewing code. Here's a comparison of how different AI Coding tools handle code reviews. Conclusion AI coding boosts productivity, improves code quality, and lets developers focus on creative tasks. Providing context, using AI for code generation, and choosing the right tools can greatly benefit developers. Pick the best large language models for your needs to optimize your workflow. Automate tasks, optimize performance, and enhance security with AI coding tools. Embrace AI to unlock new efficiency and innovation. Try Fine for free at ai.fine.dev and elevate your coding workflow today. 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
2026-01-13T08:49:43
https://github.com/berviantoleo/react-multi-crop
GitHub - berviantoleo/react-multi-crop: react-multi-crop component use fabric.js Skip to content Navigation Menu Toggle navigation Sign in Appearance settings Platform AI CODE CREATION GitHub Copilot Write better code with AI GitHub Spark Build and deploy intelligent apps GitHub Models Manage and compare prompts MCP Registry New Integrate external tools DEVELOPER WORKFLOWS Actions Automate any workflow Codespaces Instant dev environments Issues Plan and track work Code Review Manage code changes APPLICATION SECURITY GitHub Advanced Security Find and fix vulnerabilities Code security Secure your code as you build Secret protection Stop leaks before they start EXPLORE Why GitHub Documentation Blog Changelog Marketplace View all features Solutions BY COMPANY SIZE Enterprises Small and medium teams Startups Nonprofits BY USE CASE App Modernization DevSecOps DevOps CI/CD View all use cases BY INDUSTRY Healthcare Financial services Manufacturing Government View all industries View all solutions Resources EXPLORE BY TOPIC AI Software Development DevOps Security View all topics EXPLORE BY TYPE Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills SUPPORT & SERVICES Documentation Customer support Community forum Trust center Partners Open Source COMMUNITY GitHub Sponsors Fund open source developers PROGRAMS Security Lab Maintainer Community Accelerator Archive Program REPOSITORIES Topics Trending Collections Enterprise ENTERPRISE SOLUTIONS Enterprise platform AI-powered developer platform AVAILABLE ADD-ONS GitHub Advanced Security Enterprise-grade security features Copilot for Business Enterprise-grade AI features Premium Support Enterprise-grade 24/7 support Pricing Search or jump to... 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Notifications You must be signed in to change notification settings Fork 4 Star 9 react-multi-crop component use fabric.js berviantoleo.github.io/react-multi-crop/ License MIT license 9 stars 4 forks Branches Tags Activity Star Notifications You must be signed in to change notification settings Code Issues 5 Pull requests 0 Discussions Actions Projects 0 Security Uh oh! There was an error while loading. Please reload this page . Insights Additional navigation options Code Issues Pull requests Discussions Actions Projects Security Insights berviantoleo/react-multi-crop   main Branches Tags Go to file Code Open more actions menu Folders and files Name Name Last commit message Last commit date Latest commit   History 1,189 Commits .github .github     .husky .husky     .idea .idea     .vscode .vscode     .yarn/ releases .yarn/ releases     documentation documentation     examples/ demo examples/ demo     packages/ react-multi-crop packages/ react-multi-crop     .gitignore .gitignore     .gitpod.yml .gitpod.yml     .prettierignore .prettierignore     .prettierrc .prettierrc     .releaserc.json .releaserc.json     .whitesource .whitesource     .yarnrc.yml .yarnrc.yml     CHANGELOG.md CHANGELOG.md     Dockerfile Dockerfile     LICENSE LICENSE     Makefile Makefile     README.md README.md     Vagrantfile Vagrantfile     commitlint.config.js commitlint.config.js     deploy.sh deploy.sh     eslint.config.mjs eslint.config.mjs     lerna.json lerna.json     nginx.conf nginx.conf     package.json package.json     tsconfig.json tsconfig.json     yarn.lock yarn.lock     View all files Repository files navigation README MIT license React Multi Crop (ReactMultiCrop) Easy and extensible react component to crop as multiple image. Announcement Version 0.22 and newer will be hosted at npmjs only. Build Status Github Action Codecov Netlify Status How to Use Sample (Recommended) - Codesandbox.io Codesandbox.io - Typescript Demo Dependencies fabric uuid Please refer to peer-dependencies for the required minimum version. Feature Keyboard event, delete will delete your current pointing (active) of box-crop. Mouse event, double click into box-crop will duplicate your box-crop. Running the Example use Docker and Vagrant Initialization vagrant up --provider=docker Refresh Image vagrant reload Ports Container Port Demo: 8080 Container Port Examples: 8081 LICENSE MIT MIT License Copyright (c) 2020 Bervianto Leo Pratama Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. Contact Person Email: bervianto.leo@gmail.com About react-multi-crop component use fabric.js berviantoleo.github.io/react-multi-crop/ Topics react reactjs hacktoberfest multicrop Resources Readme License MIT license Uh oh! There was an error while loading. Please reload this page . Activity Stars 9 stars Watchers 1 watching Forks 4 forks Report repository Releases 583 @berviantoleo/react-multi-crop-demo@0.29.48 Latest Jan 5, 2026 + 582 releases Sponsor this project   Uh oh! There was an error while loading. 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2026-01-13T08:49:43
https://dev.to/t/development/page/7
Development Page 7 - 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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2026-01-13T08:49:43
https://dev.to/pravesh_sudha_3c2b0c2b5e0
Pravesh Sudha - 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. 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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 Forem Close Follow User actions Pravesh Sudha AWS Community Builder Bridging critical thinking and innovation, from philosophy to DevOps. Location India Joined Joined on  Jul 19, 2024 Email address programmerpravesh@gmail.com Personal website https://praveshsudha.com github website twitter website Education Hindu College, Delhi University, India Pronouns he/him Work Freelance DevOps Engineer At Fiverr Google AI Studio Multi-Modal Challenge Completion Awarded for completing the Google AI Studio Multi-Modal Challenge by building and deploying an applet that showcases Gemini's multi-modal capabilities. Thank you for participating! 🤖 Got it Close Midnight 'Privacy First' Challenge Completion Awarded for completing a prompt in the Midnight 'Privacy First' Challenge. Thank you for participating! 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Got it Close Show all 13 badges More info about @pravesh_sudha_3c2b0c2b5e0 Organizations AWS Community Builders GitHub Repositories 100-Days-of-Code Python • 5 stars Skills/Languages GO, Python, Shell Scripting, Jenkins, Prometheus, Grafna, Elastic Search, Kibana, Kubernetes, Docker, Gitlab, Github Actions, Nginx, Apache, Apache Kafka, Terraform, Ansible Currently learning I am currently learning DevOps tools and Framework like Kafka, Terraform, and various services of AWS, like SNS, RDS, etc. Currently hacking on Most of the time, I am working on client's project which I get from Fiverr. Apart from them, I work on some personal projects because I love to experiments stuff with tools Available for Hey, I am available for writing blogs for devops related projects and collaborate on Coding gigs including AWS Cloud Solutions and Docker Containerisation Post 58 posts published Comment 85 comments written Tag 1 tag followed Pin Pinned 🌟 My Desk, My Journey: CSS Art Inspired by My Remote DevOps Workspace Frontend Challenge CSS Art Submission Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jul 18 '25 🌟 My Desk, My Journey: CSS Art Inspired by My Remote DevOps Workspace # frontendchallenge # devchallenge # css # webdev 41  reactions Comments Add Comment 2 min read 📨 Email-AI Assistant using FastAPI, Gemini & Postmark Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jun 4 '25 📨 Email-AI Assistant using FastAPI, Gemini & Postmark # devchallenge # postmarkchallenge # webdev # api 34  reactions Comments 15  comments 5 min read 3 Exciting Go-lang Projects to Kickstart Your DevOps Journey Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Dec 11 '24 3 Exciting Go-lang Projects to Kickstart Your DevOps Journey # go # devops # programming # coding 23  reactions Comments Add Comment 8 min read How I Built an AI Terraform Review Agent on Serverless AWS Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Jan 8 How I Built an AI Terraform Review Agent on Serverless AWS # aws # terraform # serverless # devops 18  reactions Comments Add Comment 10 min read Want to connect with Pravesh Sudha? Create an account to connect with Pravesh Sudha. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in 🚀 How I Created an AI-Powered Secret Santa Using Cognee as the Memory Layer Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Dec 11 '25 🚀 How I Created an AI-Powered Secret Santa Using Cognee as the Memory Layer # ai # coding # rag # llm 9  reactions Comments 4  comments 5 min read How I Built My Terraform Portfolio: Projects, Repos, and Lessons Learned Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Dec 7 '25 How I Built My Terraform Portfolio: Projects, Repos, and Lessons Learned # aws # terraform # devops # portfolio 18  reactions Comments 4  comments 11 min read Don’t Touch Terraform Before Avoiding These 5 Rookie Mistakes Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Dec 6 '25 Don’t Touch Terraform Before Avoiding These 5 Rookie Mistakes # aws # terraform # devops # infrastructureascode 7  reactions Comments Add Comment 9 min read 🚀 5 Terraform Hacks to Cut Your Deployment Time by 90% Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Nov 28 '25 🚀 5 Terraform Hacks to Cut Your Deployment Time by 90% # aws # devops # terraform # docker 8  reactions Comments 4  comments 9 min read 🚀 Terraform Workspaces and Multi-Environment Deployments Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Nov 6 '25 🚀 Terraform Workspaces and Multi-Environment Deployments # aws # terraform # devops # coding 7  reactions Comments Add Comment 6 min read Terraform Meets Ansible: Automating Multi-Environment Infrastructure on AWS Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Oct 30 '25 Terraform Meets Ansible: Automating Multi-Environment Infrastructure on AWS # aws # terraform # ansible # nginx 9  reactions Comments Add Comment 6 min read 🚀 Deploying Cognee AI Starter App on AWS ECS Using Terraform Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Oct 29 '25 🚀 Deploying Cognee AI Starter App on AWS ECS Using Terraform # ai # devops # rag # programming 13  reactions Comments 2  comments 8 min read Build Your Own AWS DevOps CLI with Python & Boto3 Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Oct 22 '25 Build Your Own AWS DevOps CLI with Python & Boto3 # aws # python # devops # programming 8  reactions Comments Add Comment 9 min read No More Forgetful Robots: My Test Drive with Cognee AI's "AI Memory" Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Oct 8 '25 No More Forgetful Robots: My Test Drive with Cognee AI's "AI Memory" # ai # llm # rag # beginners 13  reactions Comments 6  comments 3 min read Terraform Modules: The Secret Sauce to Scalable Infrastructure Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Oct 8 '25 Terraform Modules: The Secret Sauce to Scalable Infrastructure # aws # terraform # devops # programming 11  reactions Comments Add Comment 8 min read 🌟 Terraform Meets DevSecOps: 5 Security Practices You Can’t Afford to Ignore Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Sep 30 '25 🌟 Terraform Meets DevSecOps: 5 Security Practices You Can’t Afford to Ignore # aws # terraform # beginners # devops 9  reactions Comments Add Comment 10 min read 🌟 Story Weaver: An AI-Powered Multimodal App for Crafting and Experiencing Stories Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Sep 14 '25 🌟 Story Weaver: An AI-Powered Multimodal App for Crafting and Experiencing Stories # devchallenge # googleaichallenge # ai # gemini 24  reactions Comments 10  comments 3 min read 🚀 CI/CD for Terraform with GitHub Actions: Deploying a Node.js + Redis App on AWS Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Sep 9 '25 🚀 CI/CD for Terraform with GitHub Actions: Deploying a Node.js + Redis App on AWS # devops # cicd # docker # terraform 5  reactions Comments Add Comment 7 min read 🚀 Midnight Challenge | Build & Run a Sample dApp with React, Flask & Docker Midnight Network Challenge: Enhance the Ecosystem Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Sep 6 '25 🚀 Midnight Challenge | Build & Run a Sample dApp with React, Flask & Docker # devchallenge # midnightchallenge # web3 # blockchain 27  reactions Comments 11  comments 3 min read 🌟 Automating Cover Letters with Portia AI: My AgentHack 2025 Journey Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Aug 25 '25 🌟 Automating Cover Letters with Portia AI: My AgentHack 2025 Journey # portia # programming # ai # llm 15  reactions Comments 9  comments 8 min read 🚀 Deploying a Highly Scalable & Available Django Application on AWS with Terraform Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Aug 15 '25 🚀 Deploying a Highly Scalable & Available Django Application on AWS with Terraform # aws # terraform # programming # devops 8  reactions Comments 1  comment 9 min read 🚀 My Journey to Passing the AWS Solutions Architect Associate Exam Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Aug 5 '25 🚀 My Journey to Passing the AWS Solutions Architect Associate Exam # aws # certification # programming # productivity 10  reactions Comments 2  comments 6 min read Managing Terraform State File: Local vs Remote (S3 + DynamoDB) Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Jul 29 '25 Managing Terraform State File: Local vs Remote (S3 + DynamoDB) # devops # terraform # aws # programming 8  reactions Comments Add Comment 8 min read ✨ How I Built Philosophy AI Agent for WLH Project WLH Challenge: Building with Bolt Submission Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jul 26 '25 ✨ How I Built Philosophy AI Agent for WLH Project # devchallenge # wlhchallenge # bolt # ai 21  reactions Comments 6  comments 4 min read 🌟 Ask a Philosopher: Voice AI Agent Powered by AssemblyAI and Gemini AssemblyAI Voice Agents Challenge: Domain Expert Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jul 25 '25 🌟 Ask a Philosopher: Voice AI Agent Powered by AssemblyAI and Gemini # devchallenge # assemblyaichallenge # ai # api 29  reactions Comments 14  comments 5 min read How to Deploy a Tetris Game on AWS ECS with Terraform Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Jul 22 '25 How to Deploy a Tetris Game on AWS ECS with Terraform # docker # aws # terraform # devops 18  reactions Comments Add Comment 7 min read 🌟 Getting Started with Terraform: A beginner's Guide Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Jul 19 '25 🌟 Getting Started with Terraform: A beginner's Guide # devops # aws # terraform # programming 11  reactions Comments 1  comment 14 min read 🌟 Becoming Terraform-Ready: Real-World EKS Deployment of a 3-Tier App Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Jul 1 '25 🌟 Becoming Terraform-Ready: Real-World EKS Deployment of a 3-Tier App # docker # aws # terraform # kubernetes 12  reactions Comments Add Comment 11 min read How to Deploy Amazon Clone on AWS using Jenkins and Terraform with best DevSecOps Practices Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Jun 19 '25 How to Deploy Amazon Clone on AWS using Jenkins and Terraform with best DevSecOps Practices # aws # docker # node # kubernetes 8  reactions Comments Add Comment 9 min read How I built Classic Pac-Man game using AmazonQ CLI Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Jun 17 '25 How I built Classic Pac-Man game using AmazonQ CLI # amazonqcli # aws # ai # programming 7  reactions Comments 1  comment 4 min read How I Built an AI Agent That Writes Personalised Freelance Cover Letters with Runner H Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jun 12 '25 How I Built an AI Agent That Writes Personalised Freelance Cover Letters with Runner H # devchallenge # runnerhchallenge # ai # machinelearning 16  reactions Comments 7  comments 2 min read Simple Steps to Deploy a Three-Tier E-Commerce System on AWS EKS Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders May 25 '25 Simple Steps to Deploy a Three-Tier E-Commerce System on AWS EKS # aws # devops # kubernetes # docker 9  reactions Comments 2  comments 7 min read Easy Steps to deploy Super Mario Game on AWS EKS Using Terraform Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders May 22 '25 Easy Steps to deploy Super Mario Game on AWS EKS Using Terraform # devops # docker # kubernetes # aws 14  reactions Comments 4  comments 8 min read 🚀 Leveraging the Power of AWS ECS to Deploy Flask Tic-Tac-Toe Game Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders May 20 '25 🚀 Leveraging the Power of AWS ECS to Deploy Flask Tic-Tac-Toe Game # docker # devops # aws # python 10  reactions Comments 2  comments 9 min read Deploy a Static Website on EC2 Using AWS CI/CD Services (CodeBuild, CodeDeploy, GitHub, and Nginx) Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Apr 30 '25 Deploy a Static Website on EC2 Using AWS CI/CD Services (CodeBuild, CodeDeploy, GitHub, and Nginx) # aws # cid # nginx # devops 9  reactions Comments 1  comment 7 min read Understanding NACLs with AWS EC2 instances 🚀 Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Apr 22 '25 Understanding NACLs with AWS EC2 instances 🚀 # aws # devops # programming # security 5  reactions Comments Add Comment 6 min read Hosting a Static Website on AWS S3 Using AWS CLI – No ClickOps, Just DevOps 💻 Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow for AWS Community Builders Apr 19 '25 Hosting a Static Website on AWS S3 Using AWS CLI – No ClickOps, Just DevOps 💻 # aws # awscommunity # devops # awscli 6  reactions Comments Add Comment 4 min read Deploying Flask Todo Application using Pulumi for Fast Static Website Deployment Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Apr 5 '25 Deploying Flask Todo Application using Pulumi for Fast Static Website Deployment # devchallenge # pulumichallenge # webdev # cloud 15  reactions Comments Add Comment 2 min read 🚀 Deploying a Spring Boot Bank Application on Amazon EKS: A Step-by-Step Guide Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Mar 24 '25 🚀 Deploying a Spring Boot Bank Application on Amazon EKS: A Step-by-Step Guide # docker # aws # kubernetes # devops 10  reactions Comments 3  comments 10 min read Getting Started With Nginx: A beginner's Guide Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Mar 11 '25 Getting Started With Nginx: A beginner's Guide # nginx # docker # devops # coding 8  reactions Comments Add Comment 5 min read Getting Started with Docker: A Beginner's Guide Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Mar 4 '25 Getting Started with Docker: A Beginner's Guide # docker # devops # tutorial # flask 7  reactions Comments Add Comment 6 min read 🚀 Automating Flask To-Do App with AWS: Terraform, Jenkins & Docker Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Feb 20 '25 🚀 Automating Flask To-Do App with AWS: Terraform, Jenkins & Docker # aws # docker # terraform # jenkins 5  reactions Comments Add Comment 9 min read Streamlining AWS Deployments: Jenkins & Terraform in Action with the 2048 Game Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Feb 17 '25 Streamlining AWS Deployments: Jenkins & Terraform in Action with the 2048 Game # jenkins # terraform # devops # aws 5  reactions Comments Add Comment 8 min read How I Contributed to Kestra: A Beginner’s Perspective Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Feb 12 '25 How I Contributed to Kestra: A Beginner’s Perspective # opensource # frontend # programming # javascript 5  reactions Comments Add Comment 4 min read From Local to Cloud: Deploying a Django Employment Management App with AWS RDS Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Feb 8 '25 From Local to Cloud: Deploying a Django Employment Management App with AWS RDS # aws # django # devops # docker 10  reactions Comments Add Comment 5 min read Monitoring Your Kubernetes Cluster: A Beginner’s Guide to Setting Up Prometheus and Grafana Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Feb 4 '25 Monitoring Your Kubernetes Cluster: A Beginner’s Guide to Setting Up Prometheus and Grafana # devops # kubernetes # cloud # aws 11  reactions Comments 3  comments 5 min read Apache Kafka Project: Real-Time Twitter Streaming with Python Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Feb 2 '25 Apache Kafka Project: Real-Time Twitter Streaming with Python # python # devops # kafka # twitter Comments Add Comment 4 min read Scaling Flask with Docker: Deploying a Portfolio Project with NGINX Load Balancing Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jan 28 '25 Scaling Flask with Docker: Deploying a Portfolio Project with NGINX Load Balancing # docker # flask # nginx # devops 5  reactions Comments Add Comment 4 min read How to Deploy a Flask Portfolio Website on AWS Elastic Beanstalk Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jan 18 '25 How to Deploy a Flask Portfolio Website on AWS Elastic Beanstalk # aws # python # portfolio # elasticbeanstalk 5  reactions Comments Add Comment 5 min read Mastering Cost Optimisation with Shell Scripting: Automate Log Storage in S3 for Budget-Friendly Infrastructure Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jan 13 '25 Mastering Cost Optimisation with Shell Scripting: Automate Log Storage in S3 for Budget-Friendly Infrastructure # devops # aws # jenkins 5  reactions Comments Add Comment 3 min read Automate Your Workflows Across Jira, GitHub, and Slack Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jan 4 '25 Automate Your Workflows Across Jira, GitHub, and Slack # devops # automation # scrum # github 5  reactions Comments Add Comment 4 min read Optimising Flask Dockerfiles: Best Practices for DevOps and Developers Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Jan 2 '25 Optimising Flask Dockerfiles: Best Practices for DevOps and Developers # flask # docker # devops # python 5  reactions Comments Add Comment 4 min read Automating JIRA Ticket Creation with a Flask API: A GitHub Webhook Integration Guide Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Dec 21 '24 Automating JIRA Ticket Creation with a Flask API: A GitHub Webhook Integration Guide # devops # python # programming # automaton 6  reactions Comments Add Comment 7 min read Optimise AWS Costs: Automate Unused EBS Snapshot Cleanup with Lambda Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Dec 18 '24 Optimise AWS Costs: Automate Unused EBS Snapshot Cleanup with Lambda # devops # aws # python # cloudcomputing 3  reactions Comments Add Comment 6 min read 3 Python Projects to Kickstart Python Learning Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Dec 18 '24 3 Python Projects to Kickstart Python Learning # python # devops # coding # programming 5  reactions Comments Add Comment 8 min read How to Containerise and Deploy a MERN Stack Application with Docker Compose Pravesh Sudha Pravesh Sudha Pravesh Sudha Follow Dec 9 '24 How to Containerise and Deploy a MERN Stack Application with Docker Compose # devops # docker # kubernetes # mongodb 11  reactions Comments Add Comment 8 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 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
2026-01-13T08:49:43
https://dev.to/yusadolat
Yusuf Adeyemo - 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 Follow User actions Yusuf Adeyemo 404 bio not found Location Ilorin, Kwara State Nigeria Joined Joined on  Feb 9, 2018 Personal website https://yusadolat.me github website twitter website Work DevOps Consultant at TaoBin 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 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 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 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. Got it Close Trusted Member 2022 Awarded for being a trusted member in 2022. Got it Close 4 Week Writing Streak You've posted at least one post per week for 4 consecutive weeks! Got it Close Four Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least four years. Got it Close Hacktoberfest 2021 Awarded for successful completion of the 2021 Hacktoberfest challenge. Got it Close Three Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least three years. Got it Close Two Year Club This badge celebrates the longevity of those who have been a registered member of the DEV Community for at least two years. Got it Close Hacktoberfest 2019 Awarded for successful completion of the 2019 Hacktoberfest challenge. 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 More info about @yusadolat Organizations Twilio AWS Community Builders Skills/Languages AWS, Kubernetes, Terraform Post 35 posts published Comment 8 comments written Tag 19 tags followed Understanding TOTP: What Really Happens When You Generate That 6-Digit Code Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 8 '25 Understanding TOTP: What Really Happens When You Generate That 6-Digit Code # totp # authentication # google # howitworks 6  reactions Comments 2  comments 5 min read Want to connect with Yusuf Adeyemo? Create an account to connect with Yusuf Adeyemo. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in How to Speed Up AWS CodeBuild Docker Builds by 25% or more Using ECR as a Remote Cache Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Oct 20 '25 How to Speed Up AWS CodeBuild Docker Builds by 25% or more Using ECR as a Remote Cache # aws # docker # cache 3  reactions Comments Add Comment 6 min read How to Speed Up AWS CodeBuild Docker Builds by 25% or more Using ECR as a Remote Cache Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Oct 20 '25 How to Speed Up AWS CodeBuild Docker Builds by 25% or more Using ECR as a Remote Cache # aws # docker # caching # ecr 1  reaction Comments Add Comment 6 min read Do You Really Know the Difference Between L1, L2, and L3 CDK Constructs? Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Jul 26 '25 Do You Really Know the Difference Between L1, L2, and L3 CDK Constructs? # awscdk # iac # typescript # cloudcomputing 7  reactions Comments Add Comment 5 min read How to Pay AWS Bills in Naira: A Quick Guide Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Jan 14 '25 How to Pay AWS Bills in Naira: A Quick Guide # aws # billing # nigeria 1  reaction Comments Add Comment 1 min read Nomad 101: The Simpler, Smarter Way to Orchestrate Applications Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 31 '24 Nomad 101: The Simpler, Smarter Way to Orchestrate Applications # nomad # hashicorp # docker # applications 5  reactions Comments Add Comment 5 min read How I Leverage Raspberry Pi as a DevOps Engineer Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 16 '24 How I Leverage Raspberry Pi as a DevOps Engineer # raspberrypi # devops # ai # github 3  reactions Comments 1  comment 4 min read TDD vs BDD: Navigating the Testing Landscape in Modern Software Development Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Aug 27 '24 TDD vs BDD: Navigating the Testing Landscape in Modern Software Development # tutorial # testing # softwaredevelopment 2  reactions Comments 1  comment 3 min read Enhancing Microservice Communication in AWS ECS with Service Discovery Techniques Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Feb 11 '24 Enhancing Microservice Communication in AWS ECS with Service Discovery Techniques # aws # awsecs 3  reactions Comments Add Comment 3 min read NodeJS Graceful Shutdown: A Beginner's Guide Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow May 28 '23 NodeJS Graceful Shutdown: A Beginner's Guide 17  reactions Comments 1  comment 6 min read Do Not Tolerate Flaky Tests. Fix Them (or Delete Them). Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow May 23 '23 Do Not Tolerate Flaky Tests. Fix Them (or Delete Them). 2  reactions Comments 1  comment 2 min read How to resolve AWS S3 CORS error Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Aug 23 '23 How to resolve AWS S3 CORS error # aws # s3 Comments Add Comment 1 min read Asynchronous ML Model Training with AWS Lambda Invocation Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Mar 23 '23 Asynchronous ML Model Training with AWS Lambda Invocation # aws # lambda # machinelearning 1  reaction Comments Add Comment 3 min read Terraform Data Sources: Your Key to Dynamic and Adaptable Infrastructure Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Feb 24 '23 Terraform Data Sources: Your Key to Dynamic and Adaptable Infrastructure # terraform 1  reaction Comments Add Comment 2 min read Observability in Kubernetes: Understanding Liveness Probes with Examples Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Feb 10 '23 Observability in Kubernetes: Understanding Liveness Probes with Examples # kubernetes Comments Add Comment 3 min read Observability in Kubernetes: Understanding Readiness Probes with Examples Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Jan 31 '23 Observability in Kubernetes: Understanding Readiness Probes with Examples # kubernetes # observability 1  reaction Comments Add Comment 3 min read 5 tools to supercharge your Terraform Development Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Jan 12 '23 5 tools to supercharge your Terraform Development # terraform 6  reactions Comments Add Comment 3 min read Auto Vacuum Explained: Postgres Internals Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Jan 5 '23 Auto Vacuum Explained: Postgres Internals # database # postgres 1  reaction Comments Add Comment 2 min read 10 DevOps tools you should learn in 2023 Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 29 '22 10 DevOps tools you should learn in 2023 # kubernetes # terraform # docker 62  reactions Comments 4  comments 5 min read Dive into the world of Docker volumes: A beginner's guide Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 26 '22 Dive into the world of Docker volumes: A beginner's guide # docker 5  reactions Comments Add Comment 3 min read ALB vs NLB: The ultimate guide to choosing the best option for your needs Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Dec 24 '22 ALB vs NLB: The ultimate guide to choosing the best option for your needs # aws # alb # nlb 6  reactions Comments Add Comment 3 min read Difference between Kubernetes DeamonSet and Stateful Set Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 17 '22 Difference between Kubernetes DeamonSet and Stateful Set # kubernetes # devops 1  reaction Comments Add Comment 2 min read How to Add Sentry Integration to your NodeJS App Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 16 '22 How to Add Sentry Integration to your NodeJS App # node # sentry # tracing 13  reactions Comments Add Comment 2 min read Understanding Kafka Consumer Offset: A beginner guide Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 13 '22 Understanding Kafka Consumer Offset: A beginner guide # kafka # kafkaforbeginner Comments Add Comment 2 min read Deploying a container image to AWS ECR using a GitHub Action Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Sep 29 '22 Deploying a container image to AWS ECR using a GitHub Action 6  reactions Comments Add Comment 2 min read Alternatives to Heroku: migrate your Heroku apps to Koyeb Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Aug 31 '22 Alternatives to Heroku: migrate your Heroku apps to Koyeb # heroku # node # webdev # programming 9  reactions Comments Add Comment 3 min read 10 GitHub Repositories That Help You Become A Better DevOps Engineer Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Aug 25 '22 10 GitHub Repositories That Help You Become A Better DevOps Engineer # devops # github # sre 76  reactions Comments 3  comments 3 min read Fixing the 'Exec Format Error' with Docker Containers on AWS ECS Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Aug 23 '23 Fixing the 'Exec Format Error' with Docker Containers on AWS ECS # aws # ecs # execformaterror Comments Add Comment 1 min read Learning DevOps: How to learn DevOps as a beginner. Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Aug 25 '22 Learning DevOps: How to learn DevOps as a beginner. # devops # learning 6  reactions Comments 2  comments 4 min read Dockerize Production ready NodeJS App in 7 Steps Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Aug 26 '22 Dockerize Production ready NodeJS App in 7 Steps # node # docker 14  reactions Comments Add Comment 3 min read How To Deploy a containerized Application on AWS App Runner using Terraform Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Aug 25 '22 How To Deploy a containerized Application on AWS App Runner using Terraform # apprunner # aws # docker # terraform 7  reactions Comments 2  comments 5 min read How to install Terraform on AWS CloudShell Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Aug 26 '22 How to install Terraform on AWS CloudShell # aws # cloudshell # terraform 31  reactions Comments Add Comment 2 min read AWS CodePipeline Overview Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Dec 30 '22 AWS CodePipeline Overview Comments Add Comment 2 min read Introduction to ECS (Elastic Container Service) Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow for AWS Community Builders Dec 30 '22 Introduction to ECS (Elastic Container Service) # aws # awsecs # intro 1  reaction Comments Add Comment 3 min read Running Go Program on iOS and iPadOS with iSH Yusuf Adeyemo Yusuf Adeyemo Yusuf Adeyemo Follow Aug 28 '22 Running Go Program on iOS and iPadOS with iSH # ios # go # shell # alphine 1  reaction 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 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
2026-01-13T08:49:43
https://dev.to/pockit_tools/pnpm-vs-npm-vs-yarn-vs-bun-the-2026-package-manager-showdown-51dc#bun-13-package-manager
pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown - 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 HK Lee Posted on Jan 9 • Originally published at pockit.tools pnpm vs npm vs yarn vs Bun: The 2026 Package Manager Showdown # bunjs # pnpm # yarn # npm Every JavaScript project starts with a choice: which package manager? For years, it was npm by default. Then yarn promised faster installs. Then pnpm claimed to save gigabytes of disk space. And now Bun's built-in package manager claims to make everything else obsolete. But here's what no one tells you: the "best" package manager depends entirely on your specific use case, and blindly following benchmarks can lead you astray. A package manager that's perfect for a solo developer's side project might be terrible for a 500-package monorepo—and vice versa. This guide cuts through the marketing hype. After extensive testing across different project sizes and configurations in January 2026, here's what actually matters for each package manager, when to use it, and how to migrate if you need to. 📌 Version Note: This comparison covers npm 11.x, yarn 4.x (Berry), pnpm 10.x, and Bun 1.3 as of January 2026. The Quick Verdict If you're in a hurry, here's the short version: Use Case Recommended Why Solo/small projects Bun Fastest by far, simplest setup Large monorepos pnpm Best disk efficiency, workspace support Enterprise/legacy npm Maximum compatibility, no surprises Yarn ecosystem yarn 4 PnP mode, excellent plugins Performance at scale pnpm or Bun Both excel, pnpm more mature Now let's dive into why. The Contenders: 2026 State of Play npm 11.x Status: Still the default, ships with Node.js Latest: npm 11.7.0 (December 2025) Philosophy: Compatibility over innovation Key Strength: Works everywhere, always npm has evolved significantly. The node_modules structure is now more optimized, and features like npm audit have become industry standards. But npm's conservative approach means it's rarely the fastest or most efficient—it's just the most reliable. yarn 4.x (Berry) Status: Complete rewrite from yarn 1.x Latest: yarn 4.12.0 (January 2026) Philosophy: Innovation through Plug'n'Play (PnP) Key Strength: Zero-installs, plugin architecture Yarn Berry is essentially a different product from yarn 1. The Plug'n'Play feature eliminates node_modules entirely, instead using a .pnp.cjs file that maps imports directly to zip archives. It's radical—and divisive. pnpm 10.x Status: The "smart" alternative Latest: pnpm 10.27.0 (December 2025) Philosophy: Efficiency without breaking compatibility Key Strength: Content-addressable storage, true deduplication pnpm's approach is elegant: store all packages once in a global content-addressable store, then use hard links to make them appear in each project's node_modules . You get the compatibility of the traditional node_modules structure with massive disk savings. Bun 1.3 Package Manager Status: The new challenger Latest: Bun 1.3.0 (January 1, 2026) Philosophy: Speed above all else Key Strength: Native speed, zero configuration, full-stack capabilities Bun isn't just a package manager—it's a complete JavaScript runtime. Bun 1.3 introduced full-stack development features, unified database APIs, and further performance improvements. Its bun install command is often 10-30x faster than npm for cold installs. Benchmark Results: Cold Install Performance Let's start with what everyone cares about—raw speed. We tested each package manager on the same projects with cleared caches: Small Project (50 dependencies) Project: Typical React + TypeScript starter Dependencies: 50 direct, ~400 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 0.8s │ 18x faster │ │ pnpm │ 4.2s │ 3.4x faster│ │ yarn │ 6.8s │ 2.1x faster│ │ npm │ 14.3s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Medium Project (200 dependencies) Project: Next.js 15 app with common libraries Dependencies: 200 direct, ~1,200 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 2.1s │ 22x faster │ │ pnpm │ 12.4s │ 3.7x faster│ │ yarn │ 18.2s │ 2.5x faster│ │ npm │ 46.1s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Large Monorepo (15 packages, 800 dependencies) Project: Turborepo monorepo with 15 packages Dependencies: 800 direct, ~3,500 total Cold Install Times (cleared cache): ┌────────────┬──────────┬────────────┐ │ Manager │ Time │ vs npm │ ├────────────┼──────────┼────────────┤ │ bun │ 4.8s │ 28x faster │ │ pnpm │ 28.6s │ 4.7x faster│ │ yarn │ 52.3s │ 2.6x faster│ │ npm │ 134.2s │ baseline │ └────────────┴──────────┴────────────┘ Enter fullscreen mode Exit fullscreen mode Key Insight: Bun's lead actually increases with project size. For monorepos, the difference is staggering. Cached/Warm Install Performance But cold installs aren't the whole story. Most of the time, you're installing with some level of caching: Warm Install (lockfile exists, some cache): ┌────────────┬──────────────┬──────────────┐ │ Manager │ Small (50) │ Large (800) │ ├────────────┼──────────────┼──────────────┤ │ bun │ 0.3s │ 1.2s │ │ pnpm │ 1.1s │ 8.4s │ │ yarn (PnP) │ 0.0s* │ 0.0s* │ │ npm │ 3.2s │ 24.6s │ └────────────┴──────────────┴──────────────┘ * Yarn PnP with zero-installs commits dependencies to repo Enter fullscreen mode Exit fullscreen mode Yarn's Zero-Installs Trick: With PnP mode and zero-installs, yarn commits your dependencies directly to the repository. CI/CD runs need zero install time—they just yarn and go. The tradeoff? Your repo size increases significantly. Disk Usage: Where pnpm Shines Raw speed is one thing, but what about your hard drive? Single Project Disk Usage Same 200-dependency project: ┌────────────┬──────────────┬──────────────┐ │ Manager │ node_modules │ vs npm │ ├────────────┼──────────────┼──────────────┤ │ npm │ 487 MB │ baseline │ │ yarn │ 502 MB │ +3% │ │ pnpm │ 124 MB* │ -75% │ │ bun │ 461 MB │ -5% │ └────────────┴──────────────┴──────────────┘ * pnpm uses hard links to global store Enter fullscreen mode Exit fullscreen mode Multiple Projects (Same Dependencies) Here's where pnpm's architecture pays off. If you have 10 projects using React 19: 10 Projects with overlapping dependencies: ┌────────────┬──────────────┬──────────────┐ │ Manager │ Total Disk │ vs npm │ ├────────────┼──────────────┼──────────────┤ │ npm │ 4.87 GB │ baseline │ │ yarn │ 5.02 GB │ +3% │ │ pnpm │ 612 MB │ -87% │ │ bun │ 4.61 GB │ -5% │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode pnpm stores each unique package version exactly once. Every project links to that single copy. If you work on many projects, pnpm can save tens of gigabytes. Bun's Approach: Bun uses a global cache but still creates full node_modules directories. It's faster than npm/yarn but doesn't achieve pnpm's deduplication. Monorepo Support Compared Monorepos have become the default for many organizations. Here's how each manager handles them: Workspace Configuration npm (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode yarn (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode pnpm (pnpm-workspace.yaml): # pnpm-workspace.yaml packages : - ' packages/*' - ' apps/*' Enter fullscreen mode Exit fullscreen mode Bun (workspaces): // package.json { "workspaces" : [ "packages/*" , "apps/*" ] } Enter fullscreen mode Exit fullscreen mode Workspace Features Comparison Feature npm yarn pnpm Bun Workspace protocol ( workspace:* ) ❌ ✅ ✅ ✅ Selective dependency installation ❌ ✅ ✅ ✅ Parallel task execution ❌ ✅ ✅ ✅ Cross-workspace linking Basic Good Excellent Good Hoisting control Limited Full Full Limited Filtering ( --filter ) ❌ ✅ ✅ ❌ The Bottom Line: pnpm and yarn are the clear leaders for monorepo management. npm's workspace support is functional but basic. Bun's is improving rapidly but still catching up. Real-World Monorepo Performance We tested a Turborepo setup with 15 packages: Task: Install + Build all packages ┌────────────┬──────────────┬──────────────┐ │ Manager │ Install │ Full Build │ ├────────────┼──────────────┼──────────────┤ │ pnpm │ 28.6s │ 142s │ │ bun │ 4.8s │ 138s │ │ yarn │ 52.3s │ 156s │ │ npm │ 134.2s │ 198s │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode Interesting: Bun's install speed advantage shrinks when you include build time. The build phase dominates, making the install speed difference less impactful for CI/CD overall. Security Features Security has become a first-class concern. Here's how each manager handles it: Audit Capabilities Feature npm yarn pnpm Bun audit command ✅ Native ✅ Plugin ✅ Native ❌ Auto-fix vulnerabilities ✅ ✅ ✅ ❌ Advisory database npm registry npm registry npm registry - SBOM generation ✅ ✅ Plugin ✅ ❌ Critical Note: Bun currently lacks built-in security auditing. For production applications, you'll need third-party tools like Snyk or Socket. Lockfile Security All four managers use lockfiles to ensure reproducible installs: npm: package-lock.json (JSON) yarn: yarn.lock (custom format) pnpm: pnpm-lock.yaml (YAML) Bun: bun.lockb (binary) Bun's Binary Lockfile: Bun's bun.lockb is binary for speed. While this makes installs faster, it's not human-readable and can't be easily diffed in code review. Bun offers bun.lock (text) as an alternative, but it's not the default. Supply Chain Protection Feature npm yarn pnpm Bun Signature verification ✅ ✅ ✅ ❌ Strict peer dependencies Optional Optional Default Optional .npmrc security options Full Limited Full Limited Network isolation mode ❌ ✅ ✅ ❌ Compatibility Reality Check Here's what nobody talks about: not every package works perfectly with every manager. Known Compatibility Issues (January 2026) pnpm: Some packages break with strict node_modules structure Workaround: shamefully-hoist=true in .npmrc Most major packages now support pnpm natively yarn PnP: Many packages still don't support PnP mode Workaround: nodeLinker: node-modules falls back to traditional structure Adoption is improving but still incomplete Bun: ~98% npm compatibility (up from 95% in 2025) Some native modules still have issues Workaround: Use --backend=copyfile for problematic packages Framework Compatibility Framework npm yarn pnpm Bun Next.js 15 ✅ ✅ ✅ ✅ Remix ✅ ✅ ✅ ⚠️ Nuxt 4 ✅ ✅ ✅ ✅ Angular 19 ✅ ⚠️ ✅ ⚠️ SvelteKit ✅ ✅ ✅ ✅ Astro 5 ✅ ✅ ✅ ✅ ⚠️ = Works but some edge cases or extra configuration needed CI/CD Performance For many teams, CI/CD time is where package manager choice really matters: GitHub Actions Benchmark # Same workflow, different package managers # Node.js 22, ubuntu-latest, clean cache ┌────────────┬──────────────┬──────────────┬──────────────┐ │ Manager │ Install │ Cache Hit │ Total Job │ ├────────────┼──────────────┼──────────────┼──────────────┤ │ npm │ 48s │ 12s │ 2m 34s │ │ yarn │ 21s │ 8s │ 2m 15s │ │ yarn (PnP) │ 18s │ 0s* │ 2m 02s │ │ pnpm │ 14s │ 4s │ 2m 08s │ │ bun │ 3s │ 1s │ 1m 52s │ └────────────┴──────────────┴──────────────┴──────────────┘ * Zero-installs : dependencies committed to repo Enter fullscreen mode Exit fullscreen mode Docker Build Performance # Multi-stage build comparison ┌────────────┬──────────────┬──────────────┐ │ Manager │ Layer Cache │ No Cache │ ├────────────┼──────────────┼──────────────┤ │ npm │ 18s │ 52s │ │ pnpm │ 8s │ 24s │ │ bun │ 2s │ 6s │ └────────────┴──────────────┴──────────────┘ Enter fullscreen mode Exit fullscreen mode The Docker Secret: Bun's speed advantage is even more pronounced in Docker because its binary includes the runtime—no need to install Node.js separately. Migration Guides Ready to switch? Here's how: npm → pnpm Install pnpm: npm install -g pnpm Enter fullscreen mode Exit fullscreen mode Import existing lockfile: pnpm import Enter fullscreen mode Exit fullscreen mode Delete old files: rm -rf node_modules package-lock.json Enter fullscreen mode Exit fullscreen mode Install: pnpm install Enter fullscreen mode Exit fullscreen mode Update scripts (if needed): // package.json - usually works as-is { "scripts" : { "dev" : "next dev" , // no change needed "build" : "next build" } } Enter fullscreen mode Exit fullscreen mode npm → Bun Install Bun: curl -fsSL https://bun.sh/install | bash Enter fullscreen mode Exit fullscreen mode Remove old files: rm -rf node_modules package-lock.json Enter fullscreen mode Exit fullscreen mode Install: bun install Enter fullscreen mode Exit fullscreen mode Update scripts for Bun runtime (optional): { "scripts" : { "dev" : "bun run --bun next dev" , "build" : "bun run next build" } } Enter fullscreen mode Exit fullscreen mode yarn 1.x → yarn 4.x (Berry) # Enable corepack (Node.js 16+) corepack enable # Set yarn version yarn set version stable # Migrate configuration yarn config set nodeLinker node-modules # for compatibility # Install yarn install Enter fullscreen mode Exit fullscreen mode Rollback Plan If migration causes issues: # Keep your old lockfile backed up! cp package-lock.json package-lock.json.backup # To rollback: rm -rf node_modules bun.lockb pnpm-lock.yaml yarn.lock mv package-lock.json.backup package-lock.json npm install Enter fullscreen mode Exit fullscreen mode When to Use What: Decision Framework Use npm when: ✅ Maximum compatibility is required ✅ Team is unfamiliar with alternatives ✅ Legacy project with many native dependencies ✅ Corporate environment with strict tooling policies ✅ You want "it just works" Use yarn when: ✅ You need Plug'n'Play zero-installs ✅ You want the plugin ecosystem ✅ Your team is already yarn experts ✅ You need advanced workspace features ✅ Offline-first development is important Use pnpm when: ✅ Disk space is a concern ✅ You have many projects with overlapping dependencies ✅ Large monorepo with complex dependencies ✅ You want speed without sacrificing compatibility ✅ Strict dependency isolation matters Use Bun when: ✅ Speed is the absolute priority ✅ You're starting a new project ✅ CI/CD time is a major cost ✅ You're building Node.js APIs or scripts ✅ You want a unified runtime + package manager The Hidden Costs Nobody Mentions Before you switch, consider: Learning Curve npm → pnpm: Minimal. Almost drop-in. npm → yarn 4: Moderate. PnP mode requires understanding. npm → Bun: Low for package management, higher if using Bun runtime. Tooling Compatibility IDE support: All four work with VS Code, JetBrains, etc. CI/CD templates: npm has the most, Bun the least ready-made Docker images: npm/yarn are everywhere, pnpm common, Bun less common Team Onboarding The fastest package manager doesn't help if it slows down your team. Consider: How comfortable is your team with the new tool? Are your documentation and scripts updated? Have you tested the entire development workflow? Future Outlook: 2026 and Beyond npm: Will remain the default. Focus on incremental improvements. yarn: Continuing to push PnP adoption. Better monorepo support coming. pnpm: Rapid growth in enterprise. Becoming the "safe modern choice." Bun: Aggressive development. Aiming for 100% npm compatibility. May become the default for new projects by 2027. The ecosystem is fragmenting in healthy ways. Competition drives innovation—and all four managers are better for it. Conclusion: There's No Wrong Choice (Mostly) After extensive testing, here's the honest truth: all four package managers work fine for most projects. The performance differences, while measurable, rarely matter for small-to-medium projects. Where choice matters: Monorepos: pnpm or yarn CI/CD-heavy workflows: Bun or pnpm Disk-constrained systems: pnpm Maximum compatibility: npm Bleeding edge: Bun The most important thing isn't which package manager you choose—it's that you choose consistently across your projects and team. Switching between managers constantly creates more friction than any speed difference could justify. My recommendation for 2026: New projects: Try Bun. It's fast enough to justify the minor compatibility risks. Existing projects: Consider pnpm if you're feeling pain. Otherwise, npm is fine. Enterprise monorepos: pnpm is the safe, powerful choice. Benchmarks conducted January 2026 on M3 MacBook Pro with Node.js 22.x. Results will vary based on hardware, network, and project specifics. Always test with your own codebase before making decisions. 🚀 Explore More: This article is from the Pockit Blog . If you found this helpful, check out Pockit.tools . It’s a curated collection of offline-capable dev utilities. Available on Chrome Web Store for free. 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 . 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2026-01-13T08:49:43
https://dev.to/savagepixie/my-new-friends-filter-and-map-74a
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Report Abuse SavagePixie Posted on Jul 24, 2019 • Edited on Jul 25, 2019           My New Friends filter() and map() # todayilearned # javascript # webdev # beginners Learning JavaScript (8 Part Series) 1 My New Friends filter() and map() 2 Destructuring Assignment in JavaScript ... 4 more parts... 3 Butchering Arrays (or not) with splice() and slice() 4 Lookaheads in Javascript 5 Wielding replace with all its power 6 Understanding reduce in JavaScript 7 An introduction to promises in JavaScript 8 Cool Object methods in JavaScript Today I have been learning about arrow functions. I've got to say that at first it's hard to wrap my head around the idea that a function can take another function as one of its parameters. But that'll come with time, I suppose. Anyhow, a very interesting tool I learned about are the methods filter() and map() . What Do They Do? The most basic answer is they create a new array based on an old one. They take a function to check or manipulate the elements of an array and, based on the results of the operation, create a new one with only some of the elements or modified elements. Let's have a look at how each of them works. filter() filter() takes a function and uses it to filter the elements in an array. It returns a new array with only the elements that meet the conditions. For example: const array = [ 1 , 5 , 6 , 7 , 8 , 12 , 15 ] //We have an array with several numbers //But we want an array with only even numbers const newArr = array . filter (( num ) => num % 2 === 0 ) //newArr = [6, 8, 12] Now we have the new array newArr that only includes the even numbers in array . This method allows us to choose which elements we want from a given array without creating a loop that goes through every one of them. map() map() takes a function and calls it on every element of the array. It returns a new array with the altered elements. For example: const array = [ 1 , 5 , 6 , 7 , 8 , 12 , 15 ] //Again, array with several numbers //For some reason, we would like them to be multiplied by 10 const newArr = array . map (( num ) => num * 10 ) //newArr = [10, 50, 60, 70, 80, 120, 150] But wait, it gets better. What happens if we want to filter through the elements of an array and modify their values? Well, then we can call both methods together like this: const newArr = array . filter ( function ). map ( function ) Based on our previous examples, let's say that we want to sieve through an array to take only even numbers and then we want to make those ten times bigger. Here's how we can do it: const array = [ 1 , 5 , 6 , 7 , 8 , 12 , 15 ] //Our beloved starting array const newArr = array . filter (( num ) => num % 2 === 0 ). map (( num ) => num * 10 ) //newArr = [60, 80, 120] Conclusion When we want to create an array based on an old one by taking only some of its elements or calling a function on every element, we can use the methods filter() and map() to make our lives easier. Learning JavaScript (8 Part Series) 1 My New Friends filter() and map() 2 Destructuring Assignment in JavaScript ... 4 more parts... 3 Butchering Arrays (or not) with splice() and slice() 4 Lookaheads in Javascript 5 Wielding replace with all its power 6 Understanding reduce in JavaScript 7 An introduction to promises in JavaScript 8 Cool Object methods in JavaScript Top comments (13) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand   Adam Crockett 🌀 Adam Crockett 🌀 Adam Crockett 🌀 Follow How’s it going, I'm a Adam, a Full-Stack Engineer, actively searching for work. I'm all about JavaScript. And Frontend but don't let that fool you - I've also got some serious Backend skills. Location City of Bath, UK 🇬🇧 Education 11 plus years* active enterprise development experience and a Fine art degree 🎨 Work Riverford Organic Farmers Joined Aug 21, 2018 • Jul 24 '19 • Edited on Jul 25 • Edited Dropdown menu Copy link Hide .some and .every are amazing too, also .reduce . All the functors rock. Also Array.from This is a nifty trick too, pass a Boolean construtor to clean an array of all falsely or holes, return only truthy values. [ "" , 0 , " HEY " , , null , - Infinity ] . filter ( Boolean ) // => ["Hey"] Lastly .find is just like filter but returns one value rather than an array. Ps. I think all the functors are based on reduce . PSS. This is functional programming where this expression is preferred over statements like if and for . You will be surprised how much you can get away with. Like comment: Like comment: 7  likes Like Comment button Reply Collapse Expand   SavagePixie SavagePixie SavagePixie Follow Always learning new things. I love web development and coding in general. Joined Jul 23, 2019 • Jul 24 '19 Dropdown menu Copy link Hide Ooh! New toys! I'll have to check them and see what they do. Like comment: Like comment: 3  likes Like Comment button Reply Collapse Expand   Lee Lee Lee Follow Email plbrannan95@gmail.com Location Washington, D.C. Metro Area Education H.S. Diploma Work Software Developer at Acuity Joined Jan 7, 2019 • Jul 25 '19 Dropdown menu Copy link Hide Incredible how there's still things to learn. I will definitely start looking at ways to through in this nifty trick, and that .find too! Thanks! Like comment: Like comment: 2  likes Like Comment button Reply Collapse Expand   Adam Crockett 🌀 Adam Crockett 🌀 Adam Crockett 🌀 Follow How’s it going, I'm a Adam, a Full-Stack Engineer, actively searching for work. I'm all about JavaScript. And Frontend but don't let that fool you - I've also got some serious Backend skills. Location City of Bath, UK 🇬🇧 Education 11 plus years* active enterprise development experience and a Fine art degree 🎨 Work Riverford Organic Farmers Joined Aug 21, 2018 • Jul 25 '19 Dropdown menu Copy link Hide Looks like I should do a post on JavaScript arrays Like comment: Like comment: 1  like Like Comment button Reply Collapse Expand   Jere Suikkila Jere Suikkila Jere Suikkila Follow Location Finland Joined Jul 12, 2019 • Jul 24 '19 Dropdown menu Copy link Hide They're amazing. Not a day goes by without me writing one of these! I love how easy they are to write and how understandable they are to read afterwards to know what a piece of code does. Like comment: Like comment: 4  likes Like Comment button Reply Collapse Expand   Dave Jacoby Dave Jacoby Dave Jacoby Follow Long time computer user. Long time programmer. Location Indiana, US Education BS CS, Purdue Work Developer Joined Feb 22, 2017 • Jul 24 '19 Dropdown menu Copy link Hide I was about to say that, if you like map and filter, you'll love reduce, but it's been said... Like comment: Like comment: 2  likes Like Comment button Reply Collapse Expand   SavagePixie SavagePixie SavagePixie Follow Always learning new things. I love web development and coding in general. Joined Jul 23, 2019 • Jul 24 '19 Dropdown menu Copy link Hide I've looked at it a bit, but I think it'll be tomorrow's trouble, hehe Like comment: Like comment: 2  likes Like Comment button Reply Collapse Expand   Dave Jacoby Dave Jacoby Dave Jacoby Follow Long time computer user. Long time programmer. Location Indiana, US Education BS CS, Purdue Work Developer Joined Feb 22, 2017 • Jul 24 '19 Dropdown menu Copy link Hide It'll be there when you get to it. In my language of choice, Perl, map exists, filter is grep , and reduce comes from a non-standard library. It still fills me with joy. Like comment: Like comment: 2  likes Like Comment button Reply Collapse Expand   Praneet Nadkar Praneet Nadkar Praneet Nadkar Follow With 12+ years of experience in software development, I specialize in .NET technologies, cloud architecture, and AI-powered solutions. Location India Work Tech Lead Joined Jan 10, 2019 • Jul 25 '19 Dropdown menu Copy link Hide The explanation was neat! Like comment: Like comment: 2  likes Like Comment button Reply Collapse Expand   webdeasy.de webdeasy.de webdeasy.de Follow On this profile I publish the best posts from my blog: webdeasy.de Location Germany Joined May 28, 2019 • Jul 24 '19 Dropdown menu Copy link Hide Good explanation and examples! 😊 Like comment: Like comment: 2  likes Like Comment button Reply Collapse Expand   Adam Crockett 🌀 Adam Crockett 🌀 Adam Crockett 🌀 Follow How’s it going, I'm a Adam, a Full-Stack Engineer, actively searching for work. I'm all about JavaScript. And Frontend but don't let that fool you - I've also got some serious Backend skills. Location City of Bath, UK 🇬🇧 Education 11 plus years* active enterprise development experience and a Fine art degree 🎨 Work Riverford Organic Farmers Joined Aug 21, 2018 • Jul 24 '19 Dropdown menu Copy link Hide Groovy well that's straightend out. 😅 Like comment: Like comment: 2  likes Like Comment button Reply Collapse Expand   Yashwanth Yashwanth Yashwanth Follow Js developer and cloud enthusiastic Location Hyderabad Joined May 18, 2019 • Jul 24 '19 Dropdown menu Copy link Hide These are my enemies from today onwards.. haha Like comment: Like comment: 1  like Like Comment button Reply View full discussion (13 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 SavagePixie Follow Always learning new things. I love web development and coding in general. 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2026-01-13T08:49:43
https://www.algolia.com/fr/resources/asset/building-agentic-ai
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2026-01-13T08:49:43
https://www.algolia.com/de/developers/lp-mcp/
Algolia MCP Server | Algolia Niket --> Deutsch English français News DevCon2025 | October 1-2 Learn more Unternehmen Partners Einloggen Login Logout Algolia mark white Algolia logo white Lösungen 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. Agent Studio Create, test, and deploy AI agents, fast. 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2026-01-13T08:49:43
https://docs.devcycle.com/sdk/client-side-sdks/javascript/javascript-openfeature
Javascript OpenFeature Web Provider | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up SDK Overview SDK Lifecycle SDK Features Client-side SDKS JavaScript SDK Installation Getting Started Usage Typescript OpenFeature Example App React SDK Next.js SDK Angular SDK iOS SDK Android SDK React Native Flutter SDK Roku SDK Server-side SDKS SDK Proxy Client-side SDKS JavaScript SDK OpenFeature On this page OpenFeature Web Provider OpenFeature is an open standard that provides a vendor-agnostic, community-driven API for feature flagging that works with DevCycle. DevCycle provides a Javascript implementation of the OpenFeature Web Provider interface, if you prefer to use the OpenFeature APIs to interface with DevCycle. AI-Powered Install ​ MCP Install Follow the MCP Getting Started guide to quickly set up the DevCycle MCP server and connect your AI tool. Run this prompt: "Install DevCycle into this app" 📦 Install in Cursor 📦 Install in VS Code claude mcp add --transport http devcycle https://mcp.devcycle.com/mcp AI Prompt Copy Prompt Usage ​ Installation ​ Install the OpenFeature Web SDK and DevCycle Web Provider: NPM ​ npm install --save @devcycle/openfeature-web-provider Yarn ​ If using yarn you will need to install peer-dependencies: yarn add @openfeature/web-sdk @openfeature/core @devcycle/openfeature-web-provider Getting Started ​ Initialize the DevCycleProvider and set it as the provider for OpenFeature, which will initialize the DevCycle JS Client SDK internally: import DevCycleProvider from '@devcycle/openfeature-web-provider' import { OpenFeature } from '@openfeature/web-sdk' ... const user = { user_id : 'user_id' } // Initialize the DevCycle Provider const devcycleProvider = new DevCycleProvider ( '<DEVCYCLE_CLIENT_SDK_KEY>' ) // Set the context before the provider is set to ensure the DevCycle SDK is initialized with a user context. await OpenFeature . setContext ( user ) // Set the DevCycleProvider for OpenFeature await OpenFeature . setProviderAndWait ( devcycleProvider ) // Get the OpenFeature client const openFeatureClient = OpenFeature . getClient ( ) Use a Variable value by passing the Variable key and default value to one of the OpenFeature flag evaluation methods // Retrieve a boolean flag from the OpenFeature client const boolFlag = openFeatureClient . getBooleanValue ( 'boolean-flag' , false ) Tracking Events ​ You can use the OpenFeature track method to track events which will be sent to DevCycle as custom events. Calling track will queue the event, which will be sent in batches to the DevCycle servers. openFeatureClient . track ( 'custom-event' , { target : 'event-target' , value : 100 , metaDataField : 'value' , } ) To track custom events with OpenFeature you are required to set the first argument as the event name. The event name will be used as the event's type in DevCycle, and you can optionally set a value / target / date as defined in the DevCycleEvent Typescript Schema . Any additional properties will be added to the event as metaData fields. Passing DevCycleOptions to the DevCycleProvider ​ Ensure that you pass any custom DevCycleOptions to the DevCycleProvider constructor const user = { user_id : 'user_id' } const options = { logger : dvcDefaultLogger ( { level : 'debug' } ) } const devcycleProvider = new DevCycleProvider ( '<DEVCYCLE_CLIENT_SDK_KEY>' , options ) await OpenFeature . setProviderAndWait ( devcycleProvider ) Required TargetingKey ​ For DevCycle SDK to work we require either a targetingKey or user_id to be set on the OpenFeature context. This is used to identify the user as the user_id for a DevCycleUser in DevCycle. Context properties to DevCycleUser ​ The provider will automatically translate known DevCycleUser properties from the OpenFeature context to the DevCycleUser object. DevCycleUser TypeScript Interface For example all these context properties will be set on the DevCycleUser : openFeatureClient . setContext ( { user_id : 'user_id' , email : ' [email protected] ' , name : 'name' , language : 'en' , country : 'CA' , appVersion : '1.0.11' , appBuild : 1000 , customData : { custom : 'data' } , privateCustomData : { private : 'data' } , } ) Context properties that are not known DevCycleUser properties will be automatically added to the customData property of the DevCycleUser . Context Limitations ​ DevCycle only supports flat JSON Object properties used in the Context. Non-flat properties will be ignored. For example obj will be ignored: openFeatureClient . setContext ( { user_id : 'user_id' , obj : { key : 'value' } , } ) JSON Flag Limitations ​ The OpenFeature spec for JSON flags allows for any type of valid JSON value to be set as the flag value. For example the following are all valid default value types to use with OpenFeature: // Invalid JSON values for the DevCycle SDK, will return defaults openFeatureClient . getObjectValue ( 'json-flag' , [ 'arry' ] ) openFeatureClient . getObjectValue ( 'json-flag' , 610 ) openFeatureClient . getObjectValue ( 'json-flag' , false ) openFeatureClient . getObjectValue ( 'json-flag' , 'string' ) openFeatureClient . getObjectValue ( 'json-flag' , null ) However, these are not valid types for the DevCycle SDK, the DevCycle SDK only supports JSON Objects: // Valid JSON Object as the default value, will be evaluated by the DevCycle SDK openFeatureClient . getObjectValue ( 'json-flag' , { default : 'value' } ) Edit this page Last updated on Jan 9, 2026 Previous Typescript Next Example App AI-Powered Install Usage Installation Getting Started Tracking Events Passing DevCycleOptions to the DevCycleProvider Required TargetingKey Context properties to DevCycleUser Context Limitations JSON Flag Limitations DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://dev.to/t/communication/page/7
Communication Page 7 - 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 # communication Follow Hide Tips for talking effectively with your children at every age. Create Post Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Ambiguity hurts communication. And we should care about it Carlos Gándara Carlos Gándara Carlos Gándara Follow Dec 13 '20 Ambiguity hurts communication. And we should care about it # communication 8  reactions Comments 2  comments 4 min read Here's Why Remote Work Needs Asynchronous Communication Thomas De Moor Thomas De Moor Thomas De Moor Follow Dec 29 '20 Here's Why Remote Work Needs Asynchronous Communication # remoteworking # communication # remote # beginners 8  reactions Comments 1  comment 3 min read Let’s be clear on what a domain is SinnerSchrader Engineers SinnerSchrader Engineers SinnerSchrader Engineers Follow for Studio M - Song Dec 4 '20 Let’s be clear on what a domain is # domain # strategy # communication 5  reactions Comments Add Comment 2 min read 16 - ABC's of success: Authenticity, Balance and Communication with Bill Conyea Friends That Code podcast Friends That Code podcast Friends That Code podcast Follow Dec 3 '20 16 - ABC's of success: Authenticity, Balance and Communication with Bill Conyea # management # career # communication # startup 4  reactions Comments Add Comment 1 min read Violent communication Philipp Giese Philipp Giese Philipp Giese Follow Nov 30 '20 Violent communication # career # communication # speaking 3  reactions Comments 3  comments 5 min read Communication for Developers Luka Baramishvili Luka Baramishvili Luka Baramishvili Follow Nov 11 '20 Communication for Developers # webdev # thecollablab # juniordevelopers # communication 22  reactions Comments Add Comment 6 min read What I learned about communication from getting my husband's car fixed - and how that relates to web dev! 𝐍𝐚𝐭𝐚𝐥𝐢𝐞 𝐝𝐞 𝐖𝐞𝐞𝐫𝐝 𝐍𝐚𝐭𝐚𝐥𝐢𝐞 𝐝𝐞 𝐖𝐞𝐞𝐫𝐝 𝐍𝐚𝐭𝐚𝐥𝐢𝐞 𝐝𝐞 𝐖𝐞𝐞𝐫𝐝 Follow Nov 8 '20 What I learned about communication from getting my husband's car fixed - and how that relates to web dev! # communication # clients # management 9  reactions Comments 2  comments 5 min read Interview Guide for Software Developers - Part 2: Ace the Coding Interview Udara Weerasinghege Udara Weerasinghege Udara Weerasinghege Follow Nov 3 '20 Interview Guide for Software Developers - Part 2: Ace the Coding Interview # interview # jobsearch # programming # communication 2  reactions Comments Add Comment 5 min read Code comments are a sign that something's off Alex Bunardzic Alex Bunardzic Alex Bunardzic Follow Oct 29 '20 Code comments are a sign that something's off # softwaredevelopment # codecomments # communication # collaboration 4  reactions Comments 17  comments 6 min read Selling Refactoring Vaidotas Piekus Vaidotas Piekus Vaidotas Piekus Follow Oct 21 '20 Selling Refactoring # javascript # refactoring # communication 3  reactions Comments Add Comment 3 min read How to Listen Better in a Remote Environment Thomas De Moor Thomas De Moor Thomas De Moor Follow for X-Team Oct 27 '20 How to Listen Better in a Remote Environment # communication # career # productivity # remote 17  reactions Comments Add Comment 5 min read Low-Bandwidth Communication bob.ts bob.ts bob.ts Follow Sep 8 '20 Low-Bandwidth Communication # watercooler # communication # remote # career 7  reactions Comments Add Comment 2 min read In case of doubt, ask for clarification Dan Lebrero Dan Lebrero Dan Lebrero Follow Sep 6 '20 In case of doubt, ask for clarification # humour # communication # softskills 8  reactions Comments Add Comment 1 min read Managing Technical Debt in Software Aman Agrawal Aman Agrawal Aman Agrawal Follow for Coolblue Aug 31 '20 Managing Technical Debt in Software # techdebt # heuristics # communication # agile 6  reactions Comments 1  comment 9 min read The art of giving and receiving feedback 💌 Ségolène Alquier Ségolène Alquier Ségolène Alquier Follow Aug 17 '20 The art of giving and receiving feedback 💌 # management # communication # team # tips 54  reactions Comments 4  comments 3 min read Reasons why you Should be recruited for an Internship interviewcrackerforyou interviewcrackerforyou interviewcrackerforyou Follow Aug 13 '20 Reasons why you Should be recruited for an Internship # communication # hiring # purposeofinternship # recruiters 3  reactions Comments Add Comment 5 min read Communication Tips for Engineers Mischa Spiegelmock Mischa Spiegelmock Mischa Spiegelmock Follow Aug 4 '20 Communication Tips for Engineers # communication 32  reactions Comments Add Comment 4 min read Start naming your test doubles correctly Chris James Chris James Chris James Follow Jul 30 '20 Start naming your test doubles correctly # testing # tdd # communication # mocking 10  reactions Comments Add Comment 4 min read The Two Most Important Traits for Working on Anything with Anyone Christian Christian Christian Follow Jul 26 '20 The Two Most Important Traits for Working on Anything with Anyone # teamwork # essentialism # communication # webdev 4  reactions Comments Add Comment 3 min read Git, Linters and SourceLevel: how tools enable a more inclusive language and diverse culture Weverton Timoteo Weverton Timoteo Weverton Timoteo Follow for SourceLevel Jul 22 '20 Git, Linters and SourceLevel: how tools enable a more inclusive language and diverse culture # developmenttools # git # communication # inclusivelanguage 6  reactions Comments Add Comment 4 min read How to Ask Better Questions Thomas De Moor Thomas De Moor Thomas De Moor Follow for X-Team Jul 21 '20 How to Ask Better Questions # growth # communication # beginners # productivity 10  reactions Comments 1  comment 4 min read Remote Team: The Top Secret to Good Communication Saheed Oladosu Saheed Oladosu Saheed Oladosu Follow Jul 5 '20 Remote Team: The Top Secret to Good Communication # communication # productivity # career # webdev 4  reactions Comments Add Comment 3 min read Slow Down and Get Noticed Michael D. Callaghan Michael D. Callaghan Michael D. Callaghan Follow Jul 1 '20 Slow Down and Get Noticed # career # communication # business 4  reactions Comments Add Comment 5 min read Asking better questions Josefine Schfr Josefine Schfr Josefine Schfr Follow Jun 15 '20 Asking better questions # beginners # questions # womenintech # communication 10  reactions Comments Add Comment 3 min read DIRECT - The seven core topics of remote team communication Jochen Lillich Jochen Lillich Jochen Lillich Follow Jun 5 '20 DIRECT - The seven core topics of remote team communication # teamwork # remote # communication 6  reactions 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 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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2026-01-13T08:49:43
https://future.forem.com/t/privacy#main-content
Privacy - Future 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. 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Right menu I Almost Fell for a “Last Wish” Scam : Here’s What You Need to Know Om Shree Om Shree Om Shree Follow Jan 12 I Almost Fell for a “Last Wish” Scam : Here’s What You Need to Know # discuss # scam # security # privacy 23  reactions Comments Add Comment 4 min read Navigating the AI Legal Minefield: Your Business Guide tanvir khan tanvir khan tanvir khan Follow Dec 31 '25 Navigating the AI Legal Minefield: Your Business Guide # ai # privacy # security Comments Add Comment 8 min read Ethics and Governance in AI adoption for Indian Businesses PHD Chamber PHD Chamber PHD Chamber Follow Dec 30 '25 Ethics and Governance in AI adoption for Indian Businesses # ai # autonomy # privacy Comments Add Comment 7 min read the modern full stack choice THIYAGARAJAN varadharajan THIYAGARAJAN varadharajan THIYAGARAJAN varadharajan Follow Dec 28 '25 the modern full stack choice # ai # privacy # productivity Comments Add Comment 1 min read AI-Powered Android Browsers That Boost Productivity with ChatGPT Integration Proditive Proditive Proditive Follow Nov 13 '25 AI-Powered Android Browsers That Boost Productivity with ChatGPT Integration # android # ai # productivity # browser Comments Add Comment 8 min read Google’s Private AI Compute: A New Chapter in Privacy-First AI? Michael Keller Michael Keller Michael Keller Follow Nov 13 '25 Google’s Private AI Compute: A New Chapter in Privacy-First AI? # ai # privacy # security Comments Add Comment 1 min read Linus Tech Tips (LTT): YouTube Is Making People B̶l̶o̶o̶d̶y Mad - WAN Show October 31, 2025 Future YouTube Future YouTube Future YouTube Follow Nov 4 '25 Linus Tech Tips (LTT): YouTube Is Making People B̶l̶o̶o̶d̶y Mad - WAN Show October 31, 2025 # productivity # privacy Comments Add Comment 1 min read From Zero to Gemini Multi-Agint: How I built a Cognitive Firewall in 5 Days Sonia Al-Ra'ini Sonia Al-Ra'ini Sonia Al-Ra'ini Follow Dec 5 '25 From Zero to Gemini Multi-Agint: How I built a Cognitive Firewall in 5 Days # ai # security # privacy # brainhacking 15  reactions Comments 2  comments 4 min read ⚙️ Digital Drive, Data Theft: The Hidden Danger Inside Your Car Syber Secure Syber Secure Syber Secure Follow Nov 5 '25 ⚙️ Digital Drive, Data Theft: The Hidden Danger Inside Your Car # cybersecurity # privacy # technology # dataprivacy 1  reaction Comments Add Comment 3 min read Facebook launches AI feature to suggest your best photos and videos for sharing from camera roll Saiki Sarkar Saiki Sarkar Saiki Sarkar Follow Oct 18 '25 Facebook launches AI feature to suggest your best photos and videos for sharing from camera roll # ai # privacy # productivity Comments Add Comment 2 min read Daily Artificial Intelligence Digest - Oct 19, 2025 Antony Brahin Antony Brahin Antony Brahin Follow Oct 19 '25 Daily Artificial Intelligence Digest - Oct 19, 2025 # ai # aigovernance # privacy # surveillance Comments Add Comment 1 min read Free Resilient Web Manifesto frw community frw community frw community Follow Nov 15 '25 Free Resilient Web Manifesto # sovereignty # privacy # freedom # web Comments Add Comment 7 min read Digital Ethics: The Dark Reality of Deepfakes Sumit Shingole (BTech CSE 2025-29) Sumit Shingole (BTech CSE 2025-29) Sumit Shingole (BTech CSE 2025-29) Follow Oct 4 '25 Digital Ethics: The Dark Reality of Deepfakes # ai # privacy # security Comments Add Comment 2 min read Google faces backlash as Taylor Swift fans allege AI use in promotional scavenger hunt videos Saiki Sarkar Saiki Sarkar Saiki Sarkar Follow Oct 7 '25 Google faces backlash as Taylor Swift fans allege AI use in promotional scavenger hunt videos # ai # privacy Comments Add Comment 2 min read Udio allows users to download AI songs for 48 hours after backlash over UMGlegal settlement Saiki Sarkar Saiki Sarkar Saiki Sarkar Follow Nov 1 '25 Udio allows users to download AI songs for 48 hours after backlash over UMGlegal settlement # ai # privacy Comments 1  comment 2 min read Neuromarketing in Practice: Strategies to Tap into Subconscious Consumer Decisions Aditya Aditya Aditya Follow Sep 17 '25 Neuromarketing in Practice: Strategies to Tap into Subconscious Consumer Decisions # biotech # privacy # science Comments Add Comment 7 min read Truth Social's new AI search engine basically just pushes Fox News AI News AI News AI News Follow Aug 12 '25 Truth Social's new AI search engine basically just pushes Fox News # ai # privacy # security # science Comments Add Comment 1 min read Bipartisan Bill to Create a National Quantum Computing Cybersecurity Strategy Quantum News Quantum News Quantum News Follow Aug 12 '25 Bipartisan Bill to Create a National Quantum Computing Cybersecurity Strategy # quantum # security # science # privacy 3  reactions Comments Add Comment 1 min read ChatGPT will ‘better detect' mental distress after reports of it feeding people's delusions AI News AI News AI News Follow Aug 8 '25 ChatGPT will ‘better detect' mental distress after reports of it feeding people's delusions # ai # healthtech # security # privacy Comments Add Comment 1 min read ChatGPT will ‘better detect' mental distress after reports of it feeding people's delusions AI News AI News AI News Follow Aug 7 '25 ChatGPT will ‘better detect' mental distress after reports of it feeding people's delusions # ai # healthtech # science # privacy Comments Add Comment 1 min read Grok generates fake Taylor Swift nudes without being asked AI News AI News AI News Follow Aug 7 '25 Grok generates fake Taylor Swift nudes without being asked # ai # privacy # security # science Comments Add Comment 1 min read Nvidia rejects US demand for backdoors in AI chips AI News AI News AI News Follow Aug 7 '25 Nvidia rejects US demand for backdoors in AI chips # ai # security # privacy # manufacturing Comments Add Comment 1 min read Doge reportedly using AI tool to create ‘delete list' of federal regulations AI News AI News AI News Follow Jul 29 '25 Doge reportedly using AI tool to create ‘delete list' of federal regulations # ai # productivity # privacy # security Comments Add Comment 1 min read Trump's Anti-Bias AI Order Is Just More Bias AI News AI News AI News Follow Jul 29 '25 Trump's Anti-Bias AI Order Is Just More Bias # ai # privacy # security # science Comments Add Comment 1 min read Amazon buys Bee AI wearable that listens to everything you say AI News AI News AI News Follow Jul 28 '25 Amazon buys Bee AI wearable that listens to everything you say # ai # wearables # privacy # iot Comments Add Comment 1 min read loading... trending guides/resources Google’s Private AI Compute: A New Chapter in Privacy-First AI? the modern full stack choice I Almost Fell for a “Last Wish” Scam : Here’s What You Need to Know From Zero to Gemini Multi-Agint: How I built a Cognitive Firewall in 5 Days Udio allows users to download AI songs for 48 hours after backlash over UMGlegal settlement Navigating the AI Legal Minefield: Your Business Guide Free Resilient Web Manifesto ⚙️ Digital Drive, Data Theft: The Hidden Danger Inside Your Car Linus Tech Tips (LTT): YouTube Is Making People B̶l̶o̶o̶d̶y Mad - WAN Show October 31, 2025 💎 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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2026-01-13T08:49:43
https://vibe.forem.com/jgoutin/use-aws-bedrock-ai-services-claude-nova-polly-transcribe-with-your-existing-openai-code-1ci6#comments
Use AWS Bedrock & AI Services (Claude, Nova, Polly, Transcribe) with Your Existing OpenAI Code - Vibe Coding Forem 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 Vibe Coding Forem 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 J.Goutin Posted on Dec 19, 2025 • Originally published at dev.to Use AWS Bedrock & AI Services (Claude, Nova, Polly, Transcribe) with Your Existing OpenAI Code # ai # devops # aws # openai TL;DR Use your existing OpenAI-compatible tools (OpenWebUI, n8n, Cline, Cursor) with AWS Bedrock's 80+ models and AWS AI services (Polly, Transcribe). Just change the endpoint - no code changes needed. Deploy to your AWS account in 15 minutes with Terraform. Data stays in your AWS environment for HIPAA/GDPR compliance. The Solution in 30 Seconds from openai import OpenAI # Just change this line ↓ client = OpenAI ( base_url = " https://your-aws-api/v1 " , api_key = " your-key " ) # Everything else stays the same ↓ response = client . chat . completions . create ( model = " anthropic.claude-sonnet-4-5-20250929-v1:0 " , # Claude 4.5 on Bedrock messages = [{ " role " : " user " , " content " : " Hello from AWS! " }] ) Enter fullscreen mode Exit fullscreen mode What this enables: Use OpenWebUI, n8n, Cline, Cursor with AWS Bedrock and AWS AI services Access Claude 4.5, Nova, Qwen, DeepSeek, Mistral, Cohere, and 75+ more models Text-to-speech (Polly), speech-to-text (Transcribe), image generation, embeddings Keep all data in your AWS account (HIPAA, GDPR, FedRAMP ready) Multi-region model access from a single endpoint The Problem We Solved Most modern AI tools are built for OpenAI's API, but AWS Bedrock uses a completely different SDK. This forces you to choose between using familiar tools or switching to AWS for compliance/cost reasons and rewriting everything. We ran into this while working with a customer who needed: Compliance : All data in their AWS account (GDPR requirements) Choice : Multiple models (Claude, Nova, Qwen, Mistral, DeepSeek, Stability AI, Cohere) Multi-region access : Different Bedrock models available in different AWS regions Standard tooling : OpenWebUI, n8n, IDE coding agents (Cline, Cursor) Full AWS AI stack : Bedrock models plus Polly (TTS) and Transcribe (STT) Our Approach: An OpenAI-Compatible Translation Layer stdapi.ai is an API gateway that sits in your AWS account and translates OpenAI API calls to AWS services. Key Features OpenAI API Compatibility Your existing code works without modifications: from openai import OpenAI client = OpenAI ( base_url = " https://your-deployment.example.com/v1 " , api_key = " your-api-key " ) # Chat completions response = client . chat . completions . create ( model = " amazon.nova-pro-v1:0 " , messages = [{ " role " : " user " , " content " : " Explain AWS Lambda " }] ) # Text-to-speech with Polly response = client . audio . speech . create ( model = " amazon.polly-neural " , input = " Welcome to the future of voice technology! " ) # Speech-to-text with Transcribe with open ( " meeting-recording.mp3 " , " rb " ) as audio_file : transcription = client . audio . transcriptions . create ( model = " amazon.transcribe " , file = audio_file , response_format = " json " ) # Image generation with Bedrock response = client . images . generate ( model = " stability.stable-image-ultra-v1:0 " , prompt = " A serene mountain landscape at sunset " ) # Embeddings with Bedrock response = client . embeddings . create ( model = " cohere.embed-v4 " , input = " Semantic search transforms how we find information " ) Enter fullscreen mode Exit fullscreen mode Multi-Region Access Access models across multiple AWS Bedrock regions from a single endpoint. Different models are available in different regions. You can configure which regions to include based on your requirements. AWS Bedrock inference profiles handle automatic routing when needed. Multi-Modal Capabilities Process text, images, videos, and documents together in a single request. Supports HTTP URLs, S3 URLs (for direct access to your data), and base64 data URIs. Perfect for vision tasks, document analysis, and RAG applications. Deployment Deploy to your AWS account in 5-15 minutes using Terraform. Sample configurations set up: Application Load Balancer with ECS/Fargate IAM roles with least-privilege access CloudWatch logging S3 storage Optional: Custom domain with ACM certificate Get started: Sample Terraform configurations Use Cases Chat interfaces : OpenWebUI or LibreChat for private ChatGPT alternatives Workflow automation : n8n connecting AI to 400+ services Developer tools : IDE coding agents (Cline, Cursor, Continue) Knowledge management : AI-powered note-taking and semantic search Internal AI tools : Custom chatbots for Slack, Discord, Teams Technical Details How It Works: Converts OpenAI API format to Bedrock's format Maps model IDs to appropriate AWS services and regions Provides unified access to models across configured AWS regions Converts Bedrock responses back to OpenAI format Supports streaming via Server-Sent Events (SSE) Security: All traffic stays within your AWS account IAM role-based access control Optional API key authentication VPC deployment supported Integrates with AWS Bedrock guardrails Performance: Low latency translation layer Streaming response support Scales with ECS/Fargate auto-scaling Open Source & Commercial Options stdapi.ai is available as open source (AGPL-3.0) for experimentation and internal use. For production deployments, we recommend the AWS Marketplace version , which includes: Hardened container images Regular security updates Production support 14-day free trial The commercial license also removes AGPL obligations for proprietary applications. Get Started 🏢 Recommended: AWS Marketplace (14-day free trial, production-ready) 🚀 Open source: GitHub (AGPL-3.0 for experimentation) 📦 Sample deployments: Terraform configurations 📚 Documentation: Full guides and API reference Conclusion This translation layer approach solves the AWS Bedrock compatibility gap while keeping everything AWS-native. Key benefits: Zero code changes : Your OpenAI SDK code works as-is AWS-native : Fully integrated with Bedrock, Polly, Transcribe Multi-region : Access models across AWS regions from one endpoint Production-ready : Terraform deployment, CloudWatch integration We'd love to hear your feedback! Have you solved this problem differently? What challenges have you faced integrating Bedrock into your workflow? What's Next We're planning detailed tutorials on: Deploying OpenWebUI on AWS : Private ChatGPT alternative with Bedrock Building n8n workflows : AWS AI services in automation pipelines IDE coding agents setup : Configuring Cline and Cursor with Bedrock RAG applications : Document search with Bedrock embeddings Want a specific tutorial? Drop a comment or open an issue on GitHub! 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   Muhammad Uzair Muhammad Uzair Muhammad Uzair Follow Joined Jan 9, 2026 • Jan 9 Dropdown menu Copy link Hide Aws? 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 J.Goutin Follow Solutions architect. Freelance expert in Python, cloud, and DevOps Location France Work Freelance Joined Dec 19, 2025 💎 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 Vibe Coding Forem — Discussing AI software development, and showing off what we're building. Home About Contact 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 . Vibe Coding Forem © 2025 - 2026. Where anyone can code, with a bit of creativity and some AI help. Log in Create account
2026-01-13T08:49:43
https://opensource.org/ai/faq#is-the-open-source-ai-definition-covering-models-and-weights-and-parameters
OSAID FAQs – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Source AI Open Source AI OSAID 1.0 Process Timeline Open Weights FAQ Endorsements Open Main Menu THE open source ai definition 1.0 We have released the first stable version of the Definition. Read version 1.0 Answers to Frequently Asked Questions The Open Source AI Definition (OSAID) represents an important first step in defining Open Source in an AI context. Because AI systems differ fundamentally from traditional software, the OSAID seeks to establish the first set of clear, practical guidelines for development, use and modification of AI systems in keeping with the Open Source ethos. Unfortunately, misconceptions about the definition persist, often stemming from a lack of understanding of the nature of AI. This post aims to clarify key points and provide a forward-looking perspective on the importance of the OSAID. THE open source ai definition 1.0 FAQs What Is an AI System? What is an Open Source AI? Why did you write the Open Source AI Definition? What’s the difference between the Open Source Definition and the Open Source AI Definition? Isn’t training data required to program the AI system? What is the role of training data in the Open Source AI Definition? Why do you allow the exclusion of some training data? How did you arrive at this conclusion? Is it compromising Open Source ideals? What kind of data should be required in the Open Source AI Definition? How do you fix a buggy AI system? What is a skilled person? Is the Open Source AI Definition covering models and weights and parameters? Why do you require training code while OSD #2 doesn’t require compilers? Why is there no mention of safety and risk limitations in the Open Source AI Definition? Are model parameters copyrightable? Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? Why is the “Preferred form to make modifications” limited to machine learning? Which AI systems comply with the Open Source AI Definition? What’s the next step? FAQs What Is an AI System? According to the OSAID, an AI system aligns with the definition provided by the Organisation for Economic Co-operation and Development (OECD): An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment. In simple terms, an AI system is “the thing” that processes input to produce output, whether that’s a prediction, recommendation, or another result. Anchoring discussions in such common definitions is essential because AI systems differ radically from traditional software. What is an Open Source AI? An Open Source AI is an AI system made freely available with all necessary code, data and parameters under legal terms approved by the Open Source Initiative. For more details, read below. Why did you write the Open Source AI Definition? Point #2 of the Open Source Definition (OSD) says “The program must include source code […] The source code must be the preferred form in which a programmer would modify the program […]” . When we embarked on this initiative, nobody had a clear answer to the question, “What is the preferred form to modify an AI system?” So OSI offered to find the answer along with the broader community by engaging in a co-design process . What’s the difference between the Open Source Definition and the Open Source AI Definition? The Open Source Definition (OSD) refers to software programs. AI and specifically machine learning systems are not simply software programs; they blend boundaries with data, configuration options, documentation and new artifacts, like weights and biases. The Open Source AI Definition describes the preferred form to modify an AI system, providing clarity on interpreting the principles of the OSD in the domain of AI. Isn’t training data required to program the AI system? A frequent misunderstanding about AI systems is equating training data with source code, suggesting that “training data is how the model gets programmed.” Unlike traditional software, AI systems are not programmed in the conventional sense. Instead, they acquire capabilities autonomously during the training process — a phenomenon distinguishing them from software like the Linux kernel. For example, the Linux kernel is: Programmed by humans. Composed of source code that developers can read, study, and modify. Reproducible, meaning its binary form can be reliably rebuilt from its source code. In contrast, modern AI systems such as large language models develop their behavior in ways that are often unpredictable and inexplicable. Training processes are challenging to replicate reliably, even by the system’s creators. These differences necessitated the establishment of a unique definition beyond the Open Source Definition for software. What is the role of training data in the Open Source AI Definition? Open Source means giving anyone the ability to meaningfully fork (study and modify) your system without requiring additional permissions to make it more useful for themselves and everyone else. This is why point #2 of the OSD requires that the source code be provided in the preferred form for making modifications. This way, everyone has the same rights and ability to fork as the original developers, starting a virtuous innovation cycle. However, training data does not equate to a software source code. Training data is important for studying modern machine learning systems. However, it is not what AI researchers and practitioners necessarily use as part of the preferred form for modifying a trained model. The Data Information and Code requirements of the OSAID allow Open Source AI systems to be forked by third-party AI builders downstream using the same information as the original developers. These forks could include removing nonpublic or non-open data from the training dataset in order to train a new Open Source AI system on fully public or open data. Why do you allow the exclusion of some training data? We want Open Source AI to exist in fields where data cannot be legally shared, such as medical AI. Laws that permit training on data often limit the resharing of that same data to protect copyright or other interests. Privacy rules also give people the right to control their most sensitive information, like decisions about their health. Similarly, much of the world’s Indigenous knowledge is protected through mechanisms that are not compatible with later-developed frameworks for rights exclusivity and sharing. There are also many cases where terms of use of publicly available data may give entity A the confidence that they may use it freely and call it “open data,” but not give entity A the confidence they can, in turn, give entity B the same guarantees for use in a different jurisdiction. Meanwhile, entity B may not feel confident using that data in their own jurisdiction. An example is so-called public domain data, where the definition of public domain varies from country to country. Another example is fair-use or private data, where the finding of fair use or privacy laws may require a good knowledge of the law of a given jurisdiction. This resharing is not so much limited as lacking legal certainty . How did you arrive at this conclusion? Is it compromising Open Source ideals? During our co-design process, relationships between the weights and the data drove the highest community engagement. In the “System analysis” phase , the volunteer groups suggested that training and data processing codes were more important for modifying the AI system than accessing the training and testing data. That result was validated in the “Validation phase” and suggested a path that allows Open Source AI to exist on equal grounds with proprietary systems: both can train on the same kind of data. Some people believe that full, unfettered access to all training data (with no distinction of its kind) is paramount, arguing that anything less would compromise the full reproducibility of AI systems, transparency and security. This approach would relegate Open Source AI to a niche of AI trainable only on open data. That niche would be tiny, even relative to the niche occupied by Open Source in the traditional software ecosystem. The requirements of Data Information keep the same approach present in the Open Source Definition; it doesn’t mandate full reproducibility and transparency but enables them (i.e., reproducible builds ). At the same time, setting a baseline requiring Data Information doesn’t preclude others from formulating and demanding more requirements, like the Digital Public Goods Standard or the Free Systems Distribution Guidelines , which add requirements to the Open Source Definition. One of the key aspects of OSI’s mission is to drive and promote Open Source innovation. The approach OSI takes here enables complete user choice with Open Source AI. Users can keep the insights derived from training+data preprocessing code and a description of unshareable training data and build upon those with their own unshareable data and give the insights derived from further training to everyone, allowing for Open Source AI in areas like health care. Alternatively, users can obtain the available and public data from the Data Information and retrain their model without any unshareable data, resulting in more data transparency in the AI system. Like copyleft and permissive licensing, this approach leaves the choice with the user. What kind of data should be required in the Open Source AI Definition? A significant challenge in AI is the role of data. Unlike traditional software, where source code is the primary artifact, AI systems depend heavily on data — not just any data, but data processed and curated into training datasets. The OSAID recognizes the legal and ethical complexities of data sharing and uses precise legal terms to outline expectations. While not all raw data can be freely distributed, the Definition ensures that the essential elements for modifying an AI system are accessible. There are four classes of data, based on their legal constraints, all of which can be used to train Open Source AI systems: Open training data: data that can be copied, preserved, modified and reshared. It provides the best way to enable users to study the system. This must be shared. Public training data: data that others can inspect as long as it remains available. This also enables users to study the work. However, this data can degrade as links or references are lost or removed from network availability. To obviate this, different communities will have to work together to define standards, procedures, tools and governance models to overcome this risk, and Data Information is required in case the data becomes later unavailable. This must be disclosed with full details on where to obtain it. Obtainable training data is data that can be obtained, including for a fee. This information provides transparency and is similar to a purchasable component in an open hardware system. The Data Information provides a means of understanding this data other than obtaining or purchasing it. This area is likely to change rapidly and will need careful monitoring to protect Open Source AI developers. It must be disclosed with full details on where to obtain it. Unshareable nonpublic training data: data that cannot be shared for explainable reasons, like Personally Identifiable Information (PII). For this class of data, the ability to study some of the system’s biases demands a detailed description of the data – what it is, how it was collected, its characteristics, and so on – so that users can understand the biases and categorization underlying the system. This must be revealed in detail so that, for example, a hospital can create a dataset with identical structure using its own patient data. OSI believes that all these classes of data can be part of the preferred form of making modifications to the AI system. This approach both advances openness in all the components of the AI system and drives more Open Source AI, including private-first areas such as health care. How do you fix a buggy AI system? A core question the OSAID addresses is: How do you fix a buggy AI system? For traditional software, the Open Source Definition provides a clear answer: The program must include source code, and must allow distribution in source code as well as compiled form. The source code must be the preferred form in which a programmer would modify the program. However, modifying an AI system requires more than just source code. After extensive consultation with AI developers, researchers and practitioners, the community, through the OSAID co-design process, concluded that the preferred form for modifying an AI system includes: The software used to create the dataset (i.e., to transform raw data into tokens). The software used to train the system. The results of the training (i.e., the parameters). All legally shareable data used in the training process. These components collectively enable the study, use, modification and sharing of AI systems in a manner consistent with Open Source principles. What is a skilled person? In legal circles, Skilled Person means any person having the current knowledge, experience and competence to perform a certain duty. This Wikipedia entry provides more details. Is the Open Source AI Definition covering models and weights and parameters? Yes. The Open Source AI Definition makes no distinction between what might be called AI system, model, or weights and parameters. Whether the offering is characterized as an AI system, a model, or weights and parameters, to be called Open Source AI, the requirements for providing the preferred form for making modifications will be the same. If you are interested in learning more about Open Weights, please read this article. Why do you require training code while OSD #2 doesn’t require compilers? AI and software are radically different domains, and drawing comparisons between them is rarely productive. OSD point #2 doesn’t mandate that Open Source software uses only compilers released with an OSI-Approved License because compilers are standardized, de jure (like ANSI C) or de facto like TurboPascal or Python. It was generally accepted that to develop more Open Source software one could use a proprietary development environment. For machine learning, the training code is not standardized, and therefore it must be part of the preferred form of making modifications to preserve the right to fork an AI system. Why is there no mention of safety and risk limitations in the Open Source AI Definition? The Open Source AI Definition does not specifically guide or enforce ethical, trustworthy, or responsible AI development practices. However, it does not put up any barriers that would prevent developers from adhering to such principles if they chose to. The efforts to discuss the responsible development, deployment and use of AI systems, including through appropriate government regulation, are a separate conversation. A good starting point is OECD’s Recommendation of the Council on Artificial Intelligence, Section 1: Principles for responsible stewardship of trustworthy AI . Are model parameters copyrightable? The Open Source AI Definition does not take a stance on the legal nature of Parameters. They may be free by nature, or a license or other legal instrument may be required to ensure their freedom. Whether model parameters are copyrightable will become clearer over time as the legal system has more opportunities to address this issue. In any case, we require an explicit assertion accompanying the distribution of Parameters that assures that they are freely available to all. Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? We used the word “terms” instead of “license” for models because, as mentioned above, we do not yet know what the legal mechanism will be to assure that the models are available to use, study, modify and share. We used “terms” to avoid suggesting that a “license” is the only legal mechanism that could be used. That said, to be approved by the OSI, the terms for parameters must assure the freedom to use, study, modify and share. Why is the “Preferred form to make modifications” limited to machine learning? The principles stated in the Open Source AI Definition are generally applicable to any kind of AI, but machine learning challenges the Open Source Definition. For machine learning, a set of artifacts (components) is required to study and modify the system, thus requiring a new explanation of what is necessary to study and modify the system. Which AI systems comply with the Open Source AI Definition? As part of our validation and testing of the OSAID, the volunteers checked whether the Definition could be used to evaluate if AI systems provided the freedoms expected. The list of models that passed the Validation phase are: Pythia (Eleuther AI), OLMo (AI2), Amber and CrystalCoder (LLM360), and T5 (Google). A few others that were analyzed would probably pass if they changed their licenses/legal terms, for example, BLOOM (BigScience), Starcoder2 (BigCode), and Falcon (TII). Those that have been analyzed and don’t pass because they lack required components and/or their legal agreements are incompatible with the Open Source principles include Llama2 (Meta), Grok (X/Twitter), Phi-2 (Microsoft), and Mixtral (Mistral). These results should be seen as part of the definitional process, a learning moment; they are not certifications of any kind. OSI will continue to validate only legal documents and will not validate or review individual AI systems, just as it does not validate or review software projects. What’s the next step? The Open Source AI Definition reflects a thoughtful and inclusive process endorsed by leading AI developers, researchers and practitioners. It culminates in a first step represented in version 1.0 of the OSAID. The definition acknowledges that AI fundamentally differs from software and requires a tailored approach. Misunderstandings about the OSAID often arise from attempts to apply software engineering paradigms to AI, leading to confusion. By embracing the unique characteristics of AI systems, the OSAID offers a robust framework for fostering transparency, innovation and collaboration in AI development. As we navigate AI’s evolving landscape, it is crucial to engage thoughtfully and constructively with these definitions. By doing so, we can ensure that AI systems remain open, accessible and aligned with the principles of the broader Open Source movement. Our work is only possible thanks to our members. Join us today! 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2026-01-13T08:49:43
https://dev.to/t/introduction/page/2
Introduction Page 2 - 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 # introduction Follow Hide Create Post Older #introduction posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu 60-Second Series - Amazon EFS: Elastic File Storage Simplified Czarina Czarina Czarina Follow for AWS Community Builders Dec 22 '24 60-Second Series - Amazon EFS: Elastic File Storage Simplified # aws # introduction # beginners # 60seconds 4  reactions Comments Add Comment 2 min read 60-Second Series - Amazon FSx: Purpose-Built File Storage Czarina Czarina Czarina Follow for AWS Community Builders Dec 22 '24 60-Second Series - Amazon FSx: Purpose-Built File Storage # aws # introduction # 60seconds # beginners 5  reactions Comments 1  comment 2 min read Who am I? Alexander Lee Alexander Lee Alexander Lee Follow Sep 30 '24 Who am I? # introduction 1  reaction Comments 1  comment 1 min read Introduction to kubernetes Srinivasulu Paranduru Srinivasulu Paranduru Srinivasulu Paranduru Follow for AWS Community Builders Sep 30 '24 Introduction to kubernetes # k8s # introduction Comments Add Comment 3 min read Get to know me Fahad Ali Khan Fahad Ali Khan Fahad Ali Khan Follow Sep 4 '24 Get to know me # softwareengineering # introduction # seneca # opensource 2  reactions Comments Add Comment 3 min read Learn Python - Day 1 dinesh chinnathurai dinesh chinnathurai dinesh chinnathurai Follow Jul 9 '24 Learn Python - Day 1 # introduction 2  reactions Comments Add Comment 2 min read About Me HstSethi HstSethi HstSethi Follow Jul 29 '24 About Me # about # autobiography # introduction 1  reaction Comments Add Comment 1 min read Darshan Hiranandani Introduction Short Darshan Hiranandani Darshan Hiranandani Darshan Hiranandani Follow Jun 25 '24 Darshan Hiranandani Introduction Short # introduction 1  reaction Comments Add Comment 1 min read Emmanuel Katto Uganda Introduction Post Emmanuel Katto Emmanuel Katto Emmanuel Katto Follow Jun 24 '24 Emmanuel Katto Uganda Introduction Post # developer # introduction # emmnuelkattouganda # javascript 1  reaction Comments Add Comment 1 min read HOW TO CREATE AN AZURE VIRTUAL NETWORK WITH MULTIPLE SUBNETS USING SPECIFIED ADDRESS SPACE Omoniyi Omoniyi Omoniyi Follow Jul 12 '24 HOW TO CREATE AN AZURE VIRTUAL NETWORK WITH MULTIPLE SUBNETS USING SPECIFIED ADDRESS SPACE # introduction # virtualnetworks # subnetworks 8  reactions Comments Add Comment 4 min read Conquering Daunting Tasks: My Growth as a Backend Developer Through the HNG Internship Abdulmujeeb Abdulrahman Abdulmujeeb Abdulrahman Abdulmujeeb Abdulrahman Follow Jun 29 '24 Conquering Daunting Tasks: My Growth as a Backend Developer Through the HNG Internship # beginners # introduction # php # laravel Comments 1  comment 3 min read Introduction to DevOps: A Simplified Guide Ansuman Satapathy Ansuman Satapathy Ansuman Satapathy Follow Jun 24 '24 Introduction to DevOps: A Simplified Guide # devops # introduction # guide # cicd 1  reaction Comments Add Comment 3 min read It's just another language Awenath Awenath Awenath Follow Mar 25 '24 It's just another language # wecoded # introduction # personal # womenintech 23  reactions Comments 10  comments 3 min read Well hello there! Lotte Pitcher Lotte Pitcher Lotte Pitcher Follow Mar 21 '24 Well hello there! # introduction # womenintech 5  reactions Comments Add Comment 1 min read Meet Darshan Hiranandani Introduction Journey Darshan Hiranandani Darshan Hiranandani Darshan Hiranandani Follow Feb 26 '24 Meet Darshan Hiranandani Introduction Journey # introduction # gamedev Comments Add Comment 1 min read Introduction Sukma Wardana Sukma Wardana Sukma Wardana Follow Jan 24 '24 Introduction # introduction # newtodev # beginners Comments Add Comment 1 min read Quantum Computing 101: Beginners to Intermediate - Part 1 Yb Arzoo Yb Arzoo Yb Arzoo Follow Jan 1 '24 Quantum Computing 101: Beginners to Intermediate - Part 1 # quantum # quantumcomputing # introduction # quantummechanics 1  reaction Comments Add Comment 9 min read Hello World! Audrey Kadjar Audrey Kadjar Audrey Kadjar Follow Nov 17 '23 Hello World! # introduction # softwareengineering 6  reactions Comments 2  comments 1 min read A Belated Introduction Rachel Lawson Rachel Lawson Rachel Lawson Follow Sep 21 '23 A Belated Introduction # beginners # introduction 1  reaction Comments 6  comments 2 min read Introduction to Machine Learning Oluwafemi Paul Adeyemi Oluwafemi Paul Adeyemi Oluwafemi Paul Adeyemi Follow Aug 6 '23 Introduction to Machine Learning # tutorial # machinelearning # programming # introduction 3  reactions Comments Add Comment 4 min read Introduction to HTTP status codes Kelechi Kizito Ugwu Kelechi Kizito Ugwu Kelechi Kizito Ugwu Follow May 24 '23 Introduction to HTTP status codes # webdev # introduction # http # javascript 5  reactions Comments 2  comments 2 min read Mojo: A New Python Alternative? Glos Code Glos Code Glos Code Follow Jun 20 '23 Mojo: A New Python Alternative? # mojo # programming # introduction Comments Add Comment 3 min read Unleashing my Keyboard Kung Fu on the Community. Manpreet Singh Manpreet Singh Manpreet Singh Follow Jun 10 '23 Unleashing my Keyboard Kung Fu on the Community. # discuss # python # beginners # introduction Comments Add Comment 1 min read Automating and managing your ConfigCat resources with Terraform Chavez Harris Chavez Harris Chavez Harris Follow Jun 4 '23 Automating and managing your ConfigCat resources with Terraform # featureflags # featuremanagement # terraform # introduction Comments Add Comment 4 min read Introduction to Object-Oriented Programming (OOP) Richard Francis Richard Francis Richard Francis Follow Apr 10 '23 Introduction to Object-Oriented Programming (OOP) # javascript # oop # introduction # programming 2  reactions Comments Add Comment 3 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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2026-01-13T08:49:43
https://cloudash.dev
Cloudash — Access CloudWatch logs and metrics, hassle-free Home Pricing Download Blog Contact Download for free Book a Demo Toggle Navigation Browse CloudWatch logs and metrics, hassle-free. Cloudash provides clear access to CloudWatch logs and metrics, to help you make quicker decisions. Reduce time to resolution Zero-configuration Use any deployment tool Group your resources by service SSO support What happens on your machine stays on your machine Download for free Free 7-day trial • No credit card required Available for macOS, Linux and Windows Endorsed by AWS community Hear what our users have to say about us. Adam Elmore @ aeduhm I’m bullish on AWS devtools, particularly those that improve on serverless DX. Cloudash looks excellent. - Founder pedigree ✅ - Great name ✅ - Solid logo ✅ - Fills a serious gap in serverless DX (monitoring) ✅ 10/10 would recommend 4:17 PM · Sep 16, 2021 Zack Kanter @ zackkanter Cloudash is what Infinidash could have been if AWS cared about UI/UX. 2:38 PM · Sep 16, 2021 Jeff Barr @ jeffbarr This looks cool! 10:24 PM · Sep 18, 2021 Michael Bahr @ bahrdev Result of my @cloudashdev test: - Clean UI - VERY fast results - Some minor UI issues I expected quick access to logs and definitely got that. Will try it with some more active development over the next days. Thanks for the cool app, and thanks @aeduhm for the gift! 7:40 PM · Sep 28, 2021 Corey Quinn @ QuinnyPig And it... just works. Okay, I'm convinced and am now going to become a paying customer. 6:52 PM · Sep 17, 2021 Mannie Schumpert @ mannieschumpert Probably 90% of the time when I log into AWS it is to do some investigation in CloudWatch logs for our serverless API. It took me less than a minute of opening @cloudashdev to know I needed it. 3:29 PM · Sep 20, 2022 A single pane of glass to your AWS account Cloudash gives you a single pane of glass to see exactly what's happening in your cloud applications. View logs, metrics, and configuration from multiple services, regions, and accounts in one place. Beautiful UI for your AWS account Focus on what's important Cloudash shows you the most important information, filtering out all the noise. Quickly understand what's happening with your application without switching between multiple tabs. Blazing fast time-to-discovery Detect root causes of a cloud application failure in seconds. Did a production incident happen last week? Or 20 seconds ago? With Cloudash you can search, filter and browse your logs and metrics effortlessly. Serverless and more Cloudash supports API Gateway, Lambda, and CloudWatch Logs and Metrics. We are working on adding support for more services including CloudWatch Logs Insights and AWS Fargate. Follow us on Twitter to get the latest updates. Secure by default We're not sending your AWS credentials, or any data stored within your account anywhere . Why would we? Whatever happens on your machine, stays on your machine. Discover All Features OK, Cloudash is quite literally Magic for AWS Serverless Development Erik Peterson Founder, Director & CTO @ CloudZero AWS Console made simple Get access to you data as quickly as possible. No need to manually create custom dashboards. Auto-discovery of your resources Group your resources by service Cloudash automatically loads all supported resources from a CloudFormation stack. You can also create a service by manually picking resources from your account. Use any deployment tool you want Full support for AWS CDK, AWS SAM, Serverless Framework or any CloudFormation-compatible framework. If you use Terraform, you can manually pick resources you want to group together. Zero-configuration Once you configured aws-cli on your machine no further configuration is needed. Cloudash reads this configuration so you can define services based on your AWS profile. Download Free Trial Metrics that matters Metrics + Logs = 🚀 You can quickly zoom in and zoom out the metrics chart and you will immediately see respective logs. No need to copy and paste timestamps or manually select dates and times. AWS Lambda logs grouped by invocation For AWS Lambda, logs are always grouped by invocation. You will not see logs from different invocations between START and REPORT log lines. Quick access to logs and metrics for API Gateway Logs for a Lambda function backing an API Gateway endpoint are easily accessible. You don't need to remember the Lambda function name. You can just click on the HTTP method and path pair in the menu. Download Free Trial A single pane of glass to your AWS account See what's important first No need to manually create custom dashboards. Cloudash automatically shows you the most important metrics for a particular AWS resource or for your entire service. Full support for AWS SSO and MFA profiles Cloudash comes with built-in support for AWS SSO and MFA profiles, enabling you to use it for all your projects. Production-grade software, side projects, we can handle it. Download Free Trial Frequently asked questions Can’t find the answer you’re looking for? Reach out to us , we're here for you. Can I try Cloudash before buying it? Yes! Cloudash has a free trial for 7 days, you can download it here and give it a shot. We'd love to hear your feedback! Which deployment framework does Cloudash support? You can use Cloudash regardless of your deployment tool by manually picking AWS resources. What's more, Cloudash is able to automatically discover resources deployed using any CloudFormation-compatible tool (e.g., AWS CDK, AWS SAM, Serverless Framework) or Terraform. What happens to my AWS credentials when using Cloudash? Cloudash does not send (and never will) your credentials anywhere . All API calls necessary for Cloudash to operate are executed locally from your machine. Is Cloudash going to incur extra costs on my AWS bill? Cloudash uses Amazon CloudWatch GetMetricData API every time it loads or refreshes charts. AWS charges $0.01 per 1,000 metrics requested . Does Cloudash store my production logs and metrics anywhere? Whatever happens on your machine, stays on your machine. We do not send your data anywhere, nor do we store in on a Cloudash Enterprise server (which we don't have). Which operating systems are supported by Cloudash? Cloudash runs on macOS, Windows, and Linux. Close all your AWS console tabs Gain laser focused view into your metrics, logs, errors and more. All in a single desktop app. Download Now Book a Demo Footer Access CloudWatch logs and metrics, hassle-free. Twitter GitHub Product Pricing License Portal EULA Company About Blog Contact Resources 8 best practices for optimizing Lambda functions 10 CloudWatch Logs Insights examples AWS Cloud Development Kit (CDK) basics Benefits of multi-account strategy on AWS Guide to default AWS Lambda environment variables © 2023 Cloudash. All rights reserved.
2026-01-13T08:49:43
https://www.algolia.com/fr/industries/grocery
Algolia pour la distribution alimentaire 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. Agent Studio Create, test, and deploy AI agents, fast. Generative Experiences Build conversational solutions with retrieval augmented generation (RAG). Generative Experiences Build conversational solutions with retrieval augmented generation (RAG). Ask AI Deliver conversational answers—right from your search bar. Ask AI Deliver conversational answers—right from your search bar. MCP Server Search, analyze, or monitor your index within your agentic workflow. MCP Server Search, analyze, or monitor your index within your agentic workflow. Data Enrichment Modify, enhance, or restructure data as it’s indexed for search. Data Enrichment Modify, enhance, or restructure data as it’s indexed for search. Data Transformation Streamline data preparation and enhance data quality. Data Transformation Streamline data preparation and enhance data quality. Integrations Connect to your existing stack via pre-built libraries and APIs. Integrations Connect to your existing stack via pre-built libraries and APIs. Data Centers Choose from 70+ data centers across 17 regions. Data Centers Choose from 70+ data centers across 17 regions. Security & Compliance Built for peace of mind. Security & Compliance Built for peace of mind. Industries Ecommerce Ecommerce B2B Commerce B2B Commerce Fashion Fashion Grocery Grocery Media Media Marketplaces Marketplaces SaaS SaaS Higher Education Higher Education Documentation search Documentation search Enterprise search Enterprise search Headless commerce Headless commerce Image search Image search Mobile & App search Mobile & App search Retail Media Network Retail Media Network Site search Site search Visual search Visual search Voice search Voice search Digital Experience Digital Experience Ecommerce Ecommerce Engineering Engineering Merchandising Merchandising Product Management Product Management Tarifs Développeurs GET STARTED Developer Hub Developer Hub Documentation Documentation Intégrations Intégrations Composants UI Composants UI Auto-completion Auto-completion RESOURCES Code Exchange Code Exchange Engineering Blog Engineering Blog MCP MCP Discord Discord Webinars & Events Webinars & Events QUICK LINKS Démarrage rapide Démarrage rapide Pour Open Source Pour Open Source Statuts d'API Statuts d'API Support Support Resources INSPIRATION Algolia Blog Algolia Blog Resource Center Resource Center Témoignages clients Témoignages clients Webinars & Events Webinars & Events Newsroom Newsroom LEARN Customer Hub Customer Hub What's New What's New AI Search Grader AI Search Grader Documentation Documentation Évènements Évènements Professional Services Professional Services Quick Access Algolia Partners Support Login Logout Request demo Get started Search Algolia Close Request demo Get started Other Types Filter --> Clear All Filters Filters Looking for our logo? We got you covered! Brand guidelines Download logo pack Your browser does not support the video tag. Distribution alimentaire Solution intelligente pour la grande distribution Une recherche qui comprend les goûts uniques de vos consommateurs. Planifier une démonstration Les plus grandes ensignes font confiance à Algolia “Une vitesse et des performances de recherche exceptionnelles sont devenues une attente grâce à Algolia. Mais pour nous, Algolia est devenu bien plus que de la recherche. L’utilisation des fonctionnalités avancées d’Algolia nous a permis d’améliorer les résultats pour nos clients, d’augmenter les ventes et de concentrer nos efforts sur la création d’une expérience exceptionnelle.” Responsable du commerce digital H-E-B México Lire l'étude de cas "Le grand avantage d’Algolia, c’est qu’avec une implémentation de données simples, nous avons pu obtenir d’excellents résultats. Le reclassement dynamique en a été un élément clé. Nous l’avons A/B testé dans les premières semaines du lancement et avons constaté des résultats positifs. Cela a vraiment été un énorme avantage pour nous : cela nous fait gagner beaucoup de temps puisque nous n’avons pas à ajouter manuellement des règles, tout en offrant une expérience client positive." Gareth Cottiss Responsable du développement e-commerce @ Co-op Lire l'étude de cas “Avant Algolia, notre équipe passait beaucoup de temps à gérer et à ajuster notre ancienne solution de recherche, ce qui entraînait souvent des résultats incohérents pour les utilisateurs. Depuis la mise en place d’Algolia, nous avons non seulement réduit la charge de travail de nos ingénieurs, mais nous avons aussi constaté que nos clients trouvent plus rapidement les produits, avec beaucoup moins de frustration. En tant que chaîne de magasins de spiritueux, Algolia a également facilité la découverte de nouveaux produits similaires à ceux que nos clients appréciaient déjà, ce qui a stimulé la découverte et encouragé l’essai de nouvelles marques.” Kelby Fritz Responsable produit technique @ Binny’s Read their story “Même si la langue officielle est l’espagnol, beaucoup de gens parlent un mélange d’espagnol et d’anglais — le spanglish. Les clients n’entrent pas de descriptions techniques lorsqu’ils font une recherche. Algolia nous a aidés à combler l’écart entre les mots utilisés par nos chefs de catégorie et les termes réellement saisis par les clients dans le champ de recherche. Nous adorons cette fonctionnalité.” Felipe Alonso Valverde Responsable e-commerce @ Auto Mercado Lire l'étude de cas Transformez votre recherche et votre découverte Créez une recherche e-commerce personnalisée, propulsée par l’IA, qui comprend réellement ce que recherchent vos clients. Une expérience de distribution alimentaire online au service de vos clients et votre entreprise Saisissez l’opportunité avec une recherche par IA intelligente. Augmentez vos marges et la taille du panier Mettez en avant les marques maison à forte marge et les offres groupées grâce à des recommandations pilotées par l’IA et un marchandisage intelligent. Obtenir une démo Des listes faciles, rapidement Transformez les commandes vocales, les recettes et les listes de courses importées en paniers prêts à l’achat. Recherche et personnalisation par IA Adaptez les résultats de recherche à chaque client en fonction de ses préférences en temps réel, du stock, de la localisation et des intentions.   Obtenir une démo De l’inspiration au panier Une IA conversationnelle qui transforme les idées et les intentions en achats — pour aider les clients à faire leurs courses comme ils pensent. Visibilité de l’inventaire en temps réel Aidez les clients à trouver ce qui est réellement disponible près de chez eux — et réduisez la frustration et l’attrition.   Recherche et personnalisation par IA Adaptez les résultats de recherche à chaque client en fonction de ses préférences en temps réel, du stock, de la localisation et des intentions.   Obtenir une démo Des rayons à l’IA : comment les distributeurs alimentaires alimentent la prochaine génération de croissance du retail Le secteur de l’alimentation est transformé par la recherche, la découverte et le merchandising propulsés par l’IA, avec des résultats remarquables. Plébiscité par les pionniers de la distribution alimentaire Maximisez les lancements de produits Réduisez la charge cognitive, éliminez les impasses et aidez les clients à trouver exactement ce qu’ils veulent — rapidement. Apportez une vraie valeur Transformez les informations en actions grâce à une expérience de recherche qui reflète la disponibilité en temps réel, la saisonnalité et la personnalisation. Réinventez vos marges Utilisez l’IA pour promouvoir les bons produits au bon moment — en équilibrant satisfaction client et objectifs de rentabilité. L’avantage du retail media Avec des dépenses mondiales en retail media estimées à 180 milliards de dollars en 2025, l’opportunité est immense. Mais le succès dépend de la manière dont les distributeurs utilisent les données, le design et la technologie pour servir à la fois les clients et les marques. Dans notre dernier rapport, nous avons interrogé des dirigeants sur leurs projets d’investissement dans les réseaux de retail media. 76% les annonces sponsorisées sur les pages de résultats de recherche constituent la principale stratégie de retail media. 30% un meilleur ciblage d’audience est l’objectif principal des annonces sponsorisées sur les pages de résultats de recherche. 11% des acheteurs de retail media utilisent plusieurs plateformes de retail media. Télécharger le rapport Contenus recommandés AI-powered Solutions for Smarter Grocery Shopping Online grocery shopping is exploding, driven by the next generation of shoppers' buying habits. To compete, grocers need AI-driven, experiences that are easy, convenient, and tailored to each individual shopper's preferences. Read more Beyond the Basket: Algolia’s Shopping Assistant for Grocers Algolia’s intelligent grocery solution helps you provide your customers with a simple, intuitive online grocery shopping experience that they can navigate using natural language. Read this eBook to find out how. Read more Retail Media Strategies Ranked by Popularity Get a firsthand look at the trends shaping retail media purchasing decisions for online grocers.  Read more La recherche par IA qui comprend vos utilisateurs Demandez une démo Commencez gratuitement Solutions Aperçu AI Search AI Browse AI Recommendations Ask AI Intelligent Data Kit Cas d'usage Aperçu Recherche Enterprise Ecommerce headless Recherche mobile Recherche vocale Recherche d'image OEM Recherche d'image Développeurs Developer Hub Documentation Intégrations Engineering blog Communauté Discord Status d'API DocSearch Pour Open Source Demos GDPR AI Act Intégrations Salesforce Commerce Cloud B2C Shopify Adobe Commerce Netlify Commercetools BigCommerce Distribué & sécurisé Infrastructure mondiale Sécurité & conformité Azure AWS Industries Aperçu Ecommerce B2C Ecommerce B2B Marketplaces SaaS Média Startups Fashion Tools Search Grader Ecommerce Search Audit Algolia À propos Carrières Newsroom Évènements Équipe dirigeante Impact social Contact us Anti-Modern Slavery Statement Awards Réseaux sociaux Développeurs Developer Hub Documentation Intégrations Engineering blog Communauté Discord Status d'API DocSearch Pour Open Source Demos GDPR AI Act Industries Aperçu Ecommerce B2C Ecommerce B2B Marketplaces SaaS Média Startups Fashion Tools Search Grader Ecommerce Search Audit Solutions Aperçu AI Search AI Browse AI Recommendations Ask AI Intelligent Data Kit Cas d'usage Aperçu Recherche Enterprise Ecommerce headless Recherche mobile Recherche vocale Recherche d'image OEM Recherche d'image Intégrations Salesforce Commerce Cloud B2C Shopify Adobe Commerce Netlify Commercetools BigCommerce Distribué & sécurisé Infrastructure mondiale Sécurité & conformité Azure AWS Algolia À propos Carrières Newsroom Évènements Équipe dirigeante Impact social Contact us Anti-Modern Slavery Statement Awards Réseaux sociaux Algolia mark white ©2026 Algolia - All rights reserved. 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2026-01-13T08:49:43
https://dev.to/ceeoreo
Ceora Ford - 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. 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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 Ceora Ford Serving developers and building community Location Philadelphia Joined Joined on  Sep 19, 2018 Personal website https://ceeoreo.dev/ github website twitter website Pronouns she/her Work Developer Advocate at Auth0 by Okta 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 2 Top 7 Awarded for having a post featured in the weekly "must-reads" list. 🙌 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. 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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 Show all 14 badges More info about @ceeoreo Organizations AWS Community Builders Skills/Languages Python SQL AWS HTML CSS Currently learning Python Cloud Computing Currently hacking on Redesigning my portfolio site. Available for I'm new to coding and the tech field as a whole. So I would love to hear tips and advice from anyone who's willing Post 22 posts published Comment 68 comments written Tag 14 tags followed Pin Pinned How to Maintain Your Skills as a Developer Ceora Ford Ceora Ford Ceora Ford Follow for CodeSandbox May 13 '21 How to Maintain Your Skills as a Developer # career # webdev # productivity 212  reactions Comments 7  comments 4 min read How to Make Your First Open Source Contribution Ceora Ford Ceora Ford Ceora Ford Follow for CodeSandbox May 6 '21 How to Make Your First Open Source Contribution # opensource # beginners # coding 324  reactions Comments 17  comments 8 min read What I Learned From Bombing My Technical Interview Ceora Ford Ceora Ford Ceora Ford Follow Nov 12 '20 What I Learned From Bombing My Technical Interview # interview # codenewbie # coding 232  reactions Comments 40  comments 5 min read Next.JS in a Nutshell: Rendering Ceora Ford Ceora Ford Ceora Ford Follow for Okta Dec 5 '23 Next.JS in a Nutshell: Rendering # react # nextjs # frontend # javascript 23  reactions Comments 4  comments 5 min read Want to connect with Ceora Ford? Create an account to connect with Ceora Ford. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in My Favorite Resources for Learning GraphQL Ceora Ford Ceora Ford Ceora Ford Follow for Apollo GraphQL Mar 17 '22 My Favorite Resources for Learning GraphQL # graphql # webdev # beginners 38  reactions Comments 1  comment 3 min read Behind the Scenes of Our "What is GraphQL" Video Ceora Ford Ceora Ford Ceora Ford Follow for Apollo GraphQL Mar 8 '22 Behind the Scenes of Our "What is GraphQL" Video # webdev # graphql 12  reactions Comments Add Comment 4 min read This Month on CodeSandbox - April 2021 Edition Ceora Ford Ceora Ford Ceora Ford Follow for CodeSandbox Apr 28 '21 This Month on CodeSandbox - April 2021 Edition # codesandbox # community # animation 10  reactions Comments Add Comment 3 min read Why Community is Important for Developers Ceora Ford Ceora Ford Ceora Ford Follow for CodeSandbox Apr 27 '21 Why Community is Important for Developers # community # career # coding 43  reactions Comments 5  comments 3 min read A Beginners Guide to Project Building Ceora Ford Ceora Ford Ceora Ford Follow for CodeSandbox Apr 19 '21 A Beginners Guide to Project Building # coding # projects # beginners 57  reactions Comments Add Comment 4 min read Wait... Serverless Isn't Actually Serverless? Ceora Ford Ceora Ford Ceora Ford Follow Oct 30 '20 Wait... Serverless Isn't Actually Serverless? # aws # serverless # cloud # beginners 61  reactions Comments 6  comments 5 min read How I Learned JAMStack Ceora Ford Ceora Ford Ceora Ford Follow Oct 20 '20 How I Learned JAMStack # jamstack # learning # coding 193  reactions Comments 2  comments 3 min read Never Get an Unexpected AWS Bill Again! Ceora Ford Ceora Ford Ceora Ford Follow Sep 8 '20 Never Get an Unexpected AWS Bill Again! # aws # beginners # cloud 201  reactions Comments 18  comments 4 min read Introducing: Learn AWS With Me Ceora Ford Ceora Ford Ceora Ford Follow Sep 3 '20 Introducing: Learn AWS With Me # aws # beginners # cloud 119  reactions Comments 4  comments 2 min read Learning to Learn- Get the Most Out of Learning with These Resources Ceora Ford Ceora Ford Ceora Ford Follow May 28 '20 Learning to Learn- Get the Most Out of Learning with These Resources # learning # productivity # tips # codenewbie 65  reactions Comments Add Comment 4 min read 8 Resources You Can Use to Learn Python Ceora Ford Ceora Ford Ceora Ford Follow May 15 '20 8 Resources You Can Use to Learn Python # python # beginners # codenewbie # programming 77  reactions Comments 14  comments 4 min read How I'm Learning to Code and How You Can Too Ceora Ford Ceora Ford Ceora Ford Follow Apr 14 '20 How I'm Learning to Code and How You Can Too # beginners # career # codenewbie 33  reactions Comments 11  comments 7 min read 5 Mistakes I Made My First Year Learning to Code Ceora Ford Ceora Ford Ceora Ford Follow Mar 23 '20 5 Mistakes I Made My First Year Learning to Code # beginners # productivity # career # tips 103  reactions Comments 18  comments 4 min read Code a Responsive Navbar with HTML and CSS Flexbox: Pt. 2 Ceora Ford Ceora Ford Ceora Ford Follow Aug 17 '19 Code a Responsive Navbar with HTML and CSS Flexbox: Pt. 2 # beginners # webdev # tutorial # css 102  reactions Comments 5  comments 5 min read Code a Responsive Navbar with HTML and CSS Flexbox: Pt. 1 Ceora Ford Ceora Ford Ceora Ford Follow Aug 8 '19 Code a Responsive Navbar with HTML and CSS Flexbox: Pt. 1 # beginners # webdev # tutorial # css 217  reactions Comments 8  comments 6 min read HTML 101: What You Need to Know to Get Started Ceora Ford Ceora Ford Ceora Ford Follow Jul 26 '19 HTML 101: What You Need to Know to Get Started # beginners # webdev # html # tutorial 17  reactions Comments Add Comment 6 min read Fall in love with CSS with these 9 cool resources Ceora Ford Ceora Ford Ceora Ford Follow Jul 16 '19 Fall in love with CSS with these 9 cool resources # css # webdev # beginners # tutorial 42  reactions Comments 2  comments 5 min read 7 Tips to Help You Succeed at Online Courses Ceora Ford Ceora Ford Ceora Ford Follow Jun 20 '19 7 Tips to Help You Succeed at Online Courses # productivity # tips # career 20  reactions Comments 2  comments 4 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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2026-01-13T08:49:43
https://opensource.org/?p=312265
Open Policy Alliance Welcomes the Open Source Technology Improvement Fund as New Member – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu January 8, 2026 News Katie Steen-James Open Policy Alliance Welcomes the Open Source Technology Improvement Fund as New Member The Open Source Initiative (OSI) is pleased to welcome the Open Source Technology Improvement Fund (OSTIF) to the Open Policy Alliance. The Open Policy Alliance (OPA) was started in 2023 to bring together nonprofit Open Source community members to better understand and contribute to the changing landscape of public policy. OSTIF is a nonprofit dedicated to securing Open Source apps. The organization facilitates audits and reviews , making it easier for Open Source projects to improve security.  The OPA’s goal is to provide a voice for the nonprofit members of the Open Source community in policy discussions through public comment and participation in stakeholder meetings with government staff. OSTIF’s experience in security audits and their efforts to improve Open Source sustainability will bolster the Alliance’s engagement on these key issues and complement the perspectives of the other OPA members, further educating lawmakers about Open Source technology. Quote from OSTIF: Joining the Open Policy Alliance enables OSTIF to contribute further to the ecosystem and increase the exposure and education of the general public to open source and its positive mission of global digitalization. We hope that by joining, OSTIF will enhance and further the contributions of OPA to our world.  – Helen Woeste, OSTIF Communications and Operations Manager Joining the OPA OPA membership is open to registered charities, nonprofits, or equivalent organizations. Organizations must be in good standing with a shared interest in information sharing and informing public policy development. Topics of shared interest including Open Source Software, Open Data, Open Education, Open Research and Open Content. OPA members are expected to adhere to OSI’s code of conduct for mailing lists and events . You can apply for membership in the OPA on OSI’s website . Top Open Source licenses in 2025 Keep up with Open Source Please leave this field empty. Δ We’ll never share your details and you can unsubscribe with a click! Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions. Functional Functional Always active The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. Preferences Preferences The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user. Statistics Statistics The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you. Marketing Marketing The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes. Manage options Manage services Manage {vendor_count} vendors Read more about these purposes Accept Deny View preferences Save preferences View preferences {title} {title} {title} Manage consent
2026-01-13T08:49:43
https://docs.devcycle.com/sdk/client-side-sdks/react/react-openfeature
React OpenFeature Provider | DevCycle Docs Skip to main content Home SDKs APIs Management API Bucketing API Integrations CLI / MCP Best Practices Community Blog Discord Search Sign Up SDK Overview SDK Lifecycle SDK Features Client-side SDKS JavaScript SDK React SDK Installation Getting Started Usage Typescript OpenFeature Example App Next.js SDK Angular SDK iOS SDK Android SDK React Native Flutter SDK Roku SDK Server-side SDKS SDK Proxy Client-side SDKS React SDK OpenFeature On this page OpenFeature React Provider OpenFeature is an open standard that provides a vendor-agnostic, community-driven API for feature flagging that works with DevCycle. DevCycle provides a Javascript implementation of the OpenFeature Web Provider interface, if you prefer to use the OpenFeature APIs to interface with DevCycle. AI-Powered Install ​ MCP Install Follow the MCP Getting Started guide to quickly set up the DevCycle MCP server and connect your AI tool. Run this prompt: "Install DevCycle into this app" 📦 Install in Cursor 📦 Install in VS Code claude mcp add --transport http devcycle https://mcp.devcycle.com/mcp AI Prompt Copy Prompt Usage ​ Installation ​ Install the OpenFeature React SDK and DevCycle Web Provider: NPM ​ npm install @openfeature/react-sdk @devcycle/openfeature-react-provider Yarn ​ If using yarn you will need to install further peer-dependencies: yarn add @openfeature/react-sdk @devcycle/openfeature-react-provider @openfeature/web-sdk @openfeature/core Getting Started ​ Initialize the DevCycleProvider and set it as the provider for OpenFeature, which will initialize the DevCycle JS Client SDK internally: import { OpenFeatureProvider , useBooleanFlagValue , OpenFeature , } from '@openfeature/react-sdk' import DevCycleReactProvider from '@devcycle/openfeature-react-provider' await OpenFeature . setContext ( { user_id : 'user_id' } ) await OpenFeature . setProviderAndWait ( new DevCycleReactProvider ( '<DEVCYCLE_CLIENT_SDK_KEY>' ) , ) function App ( ) { return ( < OpenFeatureProvider > < Page > < / Page > < / OpenFeatureProvider > ) } Evaluating a Variable ​ Use a Variable value by passing the Variable key and default value to one of the OpenFeature flag evaluation hooks function Page ( ) { const newMessage = useBooleanFlagValue ( 'new-message' , false ) return ( < div className = "App" > < header className = "App-header" > { newMessage ? ( < p > Welcome to this OpenFeature - enabled React app ! < / p > ) : ( < p > Welcome to this React app . < / p > ) } < / header > < / div > ) } export default App Passing DevCycleOptions to the DevCycleProvider ​ Ensure that you pass any custom DevCycleOptions to the DevCycleProvider constructor const user = { user_id : 'user_id' } const options = { logger : dvcDefaultLogger ( { level : 'debug' } ) } const devcycleProvider = new DevCycleReactProvider ( '<DEVCYCLE_CLIENT_SDK_KEY>' , options , ) await OpenFeature . setProviderAndWait ( devcycleProvider ) Required TargetingKey ​ For DevCycle SDK to work we require either a targetingKey or user_id to be set on the OpenFeature context. This is used to identify the user as the user_id for a DevCycleUser in DevCycle. Context properties to DevCycleUser ​ The provider will automatically translate known DevCycleUser properties from the OpenFeature context to the DevCycleUser object. DevCycleUser TypeScript Interface For example all these properties will be set on the DevCycleUser : openFeatureClient . setContext ( { user_id : 'user_id' , email : ' [email protected] ' , name : 'name' , language : 'en' , country : 'CA' , appVersion : '1.0.11' , appBuild : 1000 , customData : { custom : 'data' } , privateCustomData : { private : 'data' } , } ) Context properties that are not known DevCycleUser properties will be automatically added to the customData property of the DevCycleUser . Context Limitations ​ DevCycle only supports flat JSON Object properties used in the Context. Non-flat properties will be ignored. For example obj will be ignored: openFeatureClient . setContext ( { user_id : 'user_id' , obj : { key : 'value' } , } ) JSON Flag Limitations ​ The OpenFeature spec for JSON flags allows for any type of valid JSON value to be set as the flag value. For example the following are all valid default value types to use with OpenFeature: // Invalid JSON values for the DevCycle SDK, will return defaults openFeatureClient . getObjectValue ( 'json-flag' , [ 'arry' ] ) openFeatureClient . getObjectValue ( 'json-flag' , 610 ) openFeatureClient . getObjectValue ( 'json-flag' , false ) openFeatureClient . getObjectValue ( 'json-flag' , 'string' ) openFeatureClient . getObjectValue ( 'json-flag' , null ) However, these are not valid types for the DevCycle SDK, the DevCycle SDK only supports JSON Objects: // Valid JSON Object as the default value, will be evaluated by the DevCycle SDK openFeatureClient . getObjectValue ( 'json-flag' , { default : 'value' } ) Edit this page Last updated on Jan 9, 2026 Previous Typescript Next Example App AI-Powered Install Usage Installation Getting Started Evaluating a Variable Passing DevCycleOptions to the DevCycleProvider Required TargetingKey Context properties to DevCycleUser Context Limitations JSON Flag Limitations DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved.
2026-01-13T08:49:43
https://members.opensource.org/join/
Become a Member of OSI – OSI Members Site Skip to content Return 🏠 Donate Join Login Open Main Menu Search Our Site Search Search for: Home Become a Member of OSI Support our mission Help us protect the Open Source Definition Donate and join as full member to gain the right to vote Basic $0 Stay informed and connected with free access to the OSI community. ✅ Newsletter ✅ Discussions Supporting $50/year Shape the direction and identify the leadership of OSI. Same as Basic plus: ✅ Voting rights ✅ Nominate candidates ✅ Run for a seat ✅ Member pin (US only) ✅ Early access to events ✅ Member discounts ✅ Tax deductible Professional $300/year Vote in OSI Board elections and be acknowledged for your commitment to open source. 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2026-01-13T08:49:43
https://dev.to/t/chatgpt/page/3
ChatGPT Page 3 - 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. 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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 ChatGPT Follow Hide GPT models are capable of natural language processing tasks such as text generation, summarization, and analysis. ChatGPT interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. Create Post submission guidelines We welcome all posts around the topic of ChatGPT - technical articles, personal stories, discussions, and more! Older #chatgpt posts 1 2 3 4 5 6 7 8 9 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Using a Single GPT Client as a Language Runtime (No API, No Agents) yuer yuer yuer Follow Dec 21 '25 Using a Single GPT Client as a Language Runtime (No API, No Agents) # chatgpt # llm # architecture # ai Comments Add Comment 2 min read Gemini 3 vs GPT 5.2: SWE-bench and Beyond A0mineTV A0mineTV A0mineTV Follow Dec 15 '25 Gemini 3 vs GPT 5.2: SWE-bench and Beyond # ai # gemini # chatgpt # coding Comments Add Comment 2 min read Your Morning AI News: ChatGPT's $3B Milestone, GPT-5.2 Launch, and the Rise of AI Scams in December 2025 Ethan Zhang Ethan Zhang Ethan Zhang Follow Dec 19 '25 Your Morning AI News: ChatGPT's $3B Milestone, GPT-5.2 Launch, and the Rise of AI Scams in December 2025 # news # ai # tech # chatgpt 1  reaction Comments Add Comment 5 min read What Happened in AI This Week: From ChatGPT's $3B Milestone to Disney's OpenAI Partnership Ethan Zhang Ethan Zhang Ethan Zhang Follow Dec 19 '25 What Happened in AI This Week: From ChatGPT's $3B Milestone to Disney's OpenAI Partnership # ai # chatgpt # openai # technews Comments Add Comment 7 min read 💙 My First AI Finance Web App ­강효림 | 정보공학전공 | 한양대(서울) ­강효림 | 정보공학전공 | 한양대(서울) ­강효림 | 정보공학전공 | 한양대(서울) Follow Dec 15 '25 💙 My First AI Finance Web App # chatgpt # beginners # github # programming 1  reaction Comments 1  comment 1 min read Why Static Load Balancing Fails for LLM Infrastructure (And What Works Instead) Debby McKinney Debby McKinney Debby McKinney Follow Jan 6 Why Static Load Balancing Fails for LLM Infrastructure (And What Works Instead) # ai # chatgpt # llm # rag 5  reactions Comments Add Comment 7 min read The Most Expensive Free Product on the Internet Muhammad Usman Muhammad Usman Muhammad Usman Follow Dec 18 '25 The Most Expensive Free Product on the Internet # chatgpt # openai # google # ai 5  reactions Comments Add Comment 2 min read OpenAI vs Claude: NLP Implementation Guide in .NET 8 Aatif G. Aatif G. Aatif G. Follow Dec 17 '25 OpenAI vs Claude: NLP Implementation Guide in .NET 8 # nlp # ai # chatgpt # claudeai Comments Add Comment 6 min read Why Production Teams Are Migrating Away From LiteLLM (And How Bifrost Is The Perfect Alternative) Debby McKinney Debby McKinney Debby McKinney Follow Jan 6 Why Production Teams Are Migrating Away From LiteLLM (And How Bifrost Is The Perfect Alternative) # llm # mcp # ai # chatgpt 7  reactions Comments Add Comment 6 min read Copiloting with AI: Learning with Founderz and ChatGPT Daniel Daniel Daniel Follow for Datalaria Jan 4 Copiloting with AI: Learning with Founderz and ChatGPT # ai # chatgpt # learning # promptengineering Comments Add Comment 5 min read My Learning Journey – Google 5-Day AI Agents Intensive & Travel Multi-Agent System Hosna Akter Hosna Akter Hosna Akter Follow Dec 14 '25 My Learning Journey – Google 5-Day AI Agents Intensive & Travel Multi-Agent System # ai # machinelearning # devchallenge # chatgpt 1  reaction Comments Add Comment 5 min read The End of Clicking: Why Voice-Based AI is the Final Frontier of UX (feat. ShopSage) Neetigya Chahar Neetigya Chahar Neetigya Chahar Follow Dec 23 '25 The End of Clicking: Why Voice-Based AI is the Final Frontier of UX (feat. ShopSage) # ai # webdev # nextjs # chatgpt 4  reactions Comments Add Comment 4 min read End up building a decent ADV game engine with Antigravity and Chat GPT tomokat tomokat tomokat Follow Dec 22 '25 End up building a decent ADV game engine with Antigravity and Chat GPT # antigravity # chatgpt # gamedev # phaser 1  reaction Comments Add Comment 2 min read First Contact Diplomacy Will Will Will Follow Dec 8 '25 First Contact Diplomacy # beginners # python # chatgpt Comments Add Comment 1 min read Why Claude's Custom Connector Failed on Cloudflare (and How I Fixed It) kiyo-e kiyo-e kiyo-e Follow Dec 18 '25 Why Claude's Custom Connector Failed on Cloudflare (and How I Fixed It) # cloudflare # claude # chatgpt # api 1  reaction Comments Add Comment 2 min read How to Validate Product Ideas Using Reddit and ChatGPT Before Building John Brawner John Brawner John Brawner Follow Jan 8 How to Validate Product Ideas Using Reddit and ChatGPT Before Building # ai # buildinpublic # vibecoding # chatgpt 1  reaction Comments 7  comments 6 min read Stop using chatgbt for coding! Use this: Ahmad Sohaib Qasim Ahmad Sohaib Qasim Ahmad Sohaib Qasim Follow Dec 6 '25 Stop using chatgbt for coding! Use this: # ai # chatgpt # datascience # coding Comments Add Comment 1 min read 🚀 Gemini 3 Is Changing the AI Landscape — And OpenAI Can Feel It Ailon Tech Ailon Tech Ailon Tech Follow Dec 6 '25 🚀 Gemini 3 Is Changing the AI Landscape — And OpenAI Can Feel It # ai # chatgpt # gemini # machinelearning Comments Add Comment 2 min read LLM is not Gen AI. Aref Karimi Aref Karimi Aref Karimi Follow Dec 3 '25 LLM is not Gen AI. # llm # genai # ai # chatgpt Comments Add Comment 2 min read A Quick Guide to Containerizing Agent Applications with Podman Peng Qian Peng Qian Peng Qian Follow Dec 8 '25 A Quick Guide to Containerizing Agent Applications with Podman # ai # containers # devops # chatgpt 1  reaction Comments Add Comment 6 min read Prompt Engineering for ChatGPT: From Vague Wishes to Reliable AI Results Dr Hernani Costa Dr Hernani Costa Dr Hernani Costa Follow Jan 6 Prompt Engineering for ChatGPT: From Vague Wishes to Reliable AI Results # ai # productivity # chatgpt # automation Comments Add Comment 2 min read 10 ChatGPT Alternatives Developers Should Actually Try in 2025 Ai Ai Ai Follow Dec 7 '25 10 ChatGPT Alternatives Developers Should Actually Try in 2025 # chatgpt # alternatives # aitools 1  reaction Comments Add Comment 2 min read How to build a ChatGPT App (MCP Apps) Abe Wheeler Abe Wheeler Abe Wheeler Follow Dec 5 '25 How to build a ChatGPT App (MCP Apps) # webdev # mcp # chatgpt # ai 2  reactions Comments Add Comment 3 min read WBS + AI: How to Cut Development Time by 6x 전규현 (Jeon gyuhyeon) 전규현 (Jeon gyuhyeon) 전규현 (Jeon gyuhyeon) Follow Dec 22 '25 WBS + AI: How to Cut Development Time by 6x # wbs # aidevelopment # projectmanagement # chatgpt 1  reaction Comments Add Comment 4 min read Your AI Morning Brew: 7 Major AI Developments You Missed This Week (December 2025) Ethan Zhang Ethan Zhang Ethan Zhang Follow Dec 22 '25 Your AI Morning Brew: 7 Major AI Developments You Missed This Week (December 2025) # news # ai # technology # chatgpt 1  reaction Comments Add Comment 5 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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2026-01-13T08:49:43
https://opensource.org/ai/webinars/data-cooperatives-and-open-source-ai/
Data Cooperatives and Open Source AI – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu Home Open Source AI Webinars Data Cooperatives and Open Source AI Data Cooperatives and Open Source AI Data Cooperatives have been proposed as a possible remediation to the current power disparity between citizens/internet users from whom data is generated and corporations that process data. But these cooperatives may also evolve to develop their own AI models based on the pooled data. The move to develop machine learning may be driven by a need to make the cooperative sustainable or to address a need of the people pooling the data. The cooperative may consider ‘opening’ its machine learning model even if the data is not open. In this talk we will use Uli, our ongoing project to respond to gendered abuse in Indian languages, as a case study to describe the interplay between community pooled data and open source AI. Uli relies on instances of abuse annotated by activists and researchers at the receiving end of gendered abuse. This crowdsourced data has been used to train a machine learning model to detect abuse in Indian languages. While the data and the machine learning model were made open source for the beta release, in subsequent iterations the team is considering limiting the data that is opened. This is, in part, a recognition that the project is compensating for the lack of adequate attention to non anglophone languages by trust and safety teams across platforms. This talk will explore the different models for licensing data and the machine learning models built on it, that the team is considering, and the tradeoffs between economic sustainability and public good creation in each. Webinar Summary In this webinar hosted by the Open Source Initiative as a part of the “Deep Dive: Defining Open Source AI” series, Tarunima Prabhakar and Siddharth Manohar from Tattle Civic Tech organization in India, discuss the challenges of reconciling open source principles with the realities of data cooperatives and machine learning in the context of addressing online abuse, particularly targeting marginalized genders in India. They explore two potential scenarios for differential access to data: one based on the purpose of use (distinguishing between academic, nonprofit, and commercial users) and the other based on the timeliness and relevance of the data. They also consider the implications of these data licensing scenarios on machine learning model licensing, highlighting the balance between openness, transparency, and preventing abuse. The webinar emphasizes the importance of recognizing the labor involved in data annotation, data justice, and the need to protect against misuse of data while enabling legitimate use cases. Slides Tattle-_-Open-Source-AI-Deep-Dive-Talk Download Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. 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2026-01-13T08:49:43
https://dev.to/t/openai/page/8
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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 OpenAI Follow Hide OpenAI is an artificial intelligence (AI) research laboratory consisting of the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. Create Post submission guidelines We welcome all posts around the topic of OpenAI - technical articles, personal stories, and discussions around GPT-3, ChatGPT, DALL-E, and Whisper! Older #openai posts 5 6 7 8 9 10 11 12 13 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu AI Development Update: Skills, Security, and Parallel Workflows Rafael Pierre Rafael Pierre Rafael Pierre Follow Oct 19 '25 AI Development Update: Skills, Security, and Parallel Workflows # ai # agents # openai # chatgpt Comments 1  comment 2 min read AI Development Roundup: Plugin Distribution, Custom Chips, and Cinematic Video Control Rafael Pierre Rafael Pierre Rafael Pierre Follow Oct 19 '25 AI Development Roundup: Plugin Distribution, Custom Chips, and Cinematic Video Control # ai # agents # openai # chatgpt 1  reaction Comments Add Comment 2 min read ForgeFlow: Engineering-Grade Automation For AI CLIs Inside tmux Kingson Wu Kingson Wu Kingson Wu Follow Sep 16 '25 ForgeFlow: Engineering-Grade Automation For AI CLIs Inside tmux # ai # automation # gemini # openai Comments Add Comment 4 min read OpenAI's Embodied Future: Why Humanoid Robotics is Their Next Big Leap Yathin Chandra Yathin Chandra Yathin Chandra Follow Sep 15 '25 OpenAI's Embodied Future: Why Humanoid Robotics is Their Next Big Leap # openai # robotics # humanoids # ai 1  reaction Comments Add Comment 2 min read Vendor Certs vs. Platform-Agnostic: Which Signal Do Recruiters Trust? Deborah Ferguson Deborah Ferguson Deborah Ferguson Follow Sep 18 '25 Vendor Certs vs. Platform-Agnostic: Which Signal Do Recruiters Trust? # ai # certification # openai # aws Comments Add Comment 3 min read Build an AI Concierge App in ChatGPT gabeb03 gabeb03 gabeb03 Follow Oct 17 '25 Build an AI Concierge App in ChatGPT # chatgpt # webdev # openai 3  reactions Comments Add Comment 1 min read Hiring SWEs AI Trainers Won't Last Job Job Job Follow Sep 13 '25 Hiring SWEs AI Trainers Won't Last # openai # rlhf # career # ai 1  reaction Comments Add Comment 2 min read 🚀 Inside NVIDIA’s DGX 🎛️Supercomputers: Powering the AI 🤖 Revolution ⚡ Hemant Hemant Hemant Follow Oct 17 '25 🚀 Inside NVIDIA’s DGX 🎛️Supercomputers: Powering the AI 🤖 Revolution ⚡ # nvidia # ai # machinelearning # openai Comments Add Comment 3 min read IA com propósito: como construir seu próprio ChatGPT usando RAG + OpenAI (Como ensinar a IA a falar a língua da sua organização) Rafael Scheidt Rafael Scheidt Rafael Scheidt Follow Oct 16 '25 IA com propósito: como construir seu próprio ChatGPT usando RAG + OpenAI (Como ensinar a IA a falar a língua da sua organização) # architecture # ai # openai # chatgpt Comments Add Comment 5 min read Tutorial: Build a ChatGPT app using OpenAI's Apps SDK and Gadget Riley Draward Riley Draward Riley Draward Follow for Gadget Oct 16 '25 Tutorial: Build a ChatGPT app using OpenAI's Apps SDK and Gadget # programming # javascript # openai # chatgpt 18  reactions Comments Add Comment 20 min read The Evolution of AI Memory: From Context Windows to True Long-Term Memory Aun Raza Aun Raza Aun Raza Follow Sep 11 '25 The Evolution of AI Memory: From Context Windows to True Long-Term Memory # aimemory # openai # aifuture # nlp Comments Add Comment 4 min read Teaching Security Scanners to Remember - Using Vector Embeddings to Stop Chasing Ghost Ports Simon Morley Simon Morley Simon Morley Follow Oct 14 '25 Teaching Security Scanners to Remember - Using Vector Embeddings to Stop Chasing Ghost Ports # cybersecurity # vectordatabase # security # openai 1  reaction Comments Add Comment 4 min read OpenAI's Sam Altman Sees a Future Beyond GPT-5 With Collective 'Superintelligence' David Cassel David Cassel David Cassel Follow Sep 11 '25 OpenAI's Sam Altman Sees a Future Beyond GPT-5 With Collective 'Superintelligence' # ai # openai # chatgpt # samaltman Comments Add Comment 1 min read Automation Now Lives Inside Intelligence Abdelghani Alhijawi Abdelghani Alhijawi Abdelghani Alhijawi Follow Oct 14 '25 Automation Now Lives Inside Intelligence # ai # automation # openai 3  reactions Comments Add Comment 2 min read Building a License Plate Recognition System with Deep Learning and Edge Deployment Aneesa Aneesa Aneesa Follow Sep 11 '25 Building a License Plate Recognition System with Deep Learning and Edge Deployment # webdev # openai # deeplearning # development Comments Add Comment 2 min read The AI Industry's Trillion-Dollar Infrastructure Problem TechSparkLive TechSparkLive TechSparkLive Follow Oct 14 '25 The AI Industry's Trillion-Dollar Infrastructure Problem # openai # google Comments Add Comment 4 min read I Built Customer Support Agent using OpenAI ChatKit! Developer Harsh Developer Harsh Developer Harsh Follow for Composio Oct 23 '25 I Built Customer Support Agent using OpenAI ChatKit! # ai # openai # productivity # buildinpublic 13  reactions Comments 5  comments 6 min read OpenAI Agent Builder: The No-Code Way to Put AI on Your Website Tim Gaul Tim Gaul Tim Gaul Follow Oct 14 '25 OpenAI Agent Builder: The No-Code Way to Put AI on Your Website # ai # automation # lowcode # openai 1  reaction Comments 1  comment 16 min read 🧠 How I Combined OpenAI, Rust, and Solana: a Quiz That Pays You in Tokens Dima Zaichenko Dima Zaichenko Dima Zaichenko Follow Oct 13 '25 🧠 How I Combined OpenAI, Rust, and Solana: a Quiz That Pays You in Tokens # solana # web3 # openai # rust 1  reaction Comments Add Comment 4 min read Daily Artificial Intelligence Digest - Oct 14, 2025 Antony Brahin Antony Brahin Antony Brahin Follow Oct 14 '25 Daily Artificial Intelligence Digest - Oct 14, 2025 # ai # aihardware # chipdesign # openai Comments Add Comment 1 min read Why JSON Mode Fails (and How to Fix It) Neil Okikiolu Neil Okikiolu Neil Okikiolu Follow Sep 9 '25 Why JSON Mode Fails (and How to Fix It) # openai # opensource # python # llm Comments Add Comment 2 min read In-depth Analysis of Litho's Multi-Agent Collaborative Architecture and ReAct Reasoning Mechanism Sopaco Sopaco Sopaco Follow Oct 12 '25 In-depth Analysis of Litho's Multi-Agent Collaborative Architecture and ReAct Reasoning Mechanism # openai # deepwiki # deepseek # githubcopilot 1  reaction Comments Add Comment 9 min read Researching Litho's Intelligent Caching and Performance Optimization Strategies Sopaco Sopaco Sopaco Follow Oct 12 '25 Researching Litho's Intelligent Caching and Performance Optimization Strategies # githubcopilot # openai # deepseek Comments Add Comment 6 min read Litho Project Architecture Analysis: How the Four-Stage Pipeline Enables Automated Documentation Generation Sopaco Sopaco Sopaco Follow Oct 12 '25 Litho Project Architecture Analysis: How the Four-Stage Pipeline Enables Automated Documentation Generation # openai # gemini # deepseek # deepwiki Comments Add Comment 8 min read Exploring the Technical Advantages of Rust Language in High-Performance AI Applications Sopaco Sopaco Sopaco Follow Oct 12 '25 Exploring the Technical Advantages of Rust Language in High-Performance AI Applications # openai # deepseek # deepwiki # githubcopilot 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. 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
2026-01-13T08:49:43
https://opensource.org/ai/faq#why-will-parameters-be-available-under-osi-approved-terms-but-the-code-will-be-under-osi-approved-licenses-are-you-going-to-allow-restrictions-on-the-terms-for-models
OSAID FAQs – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Source AI Open Source AI OSAID 1.0 Process Timeline Open Weights FAQ Endorsements Open Main Menu THE open source ai definition 1.0 We have released the first stable version of the Definition. Read version 1.0 Answers to Frequently Asked Questions The Open Source AI Definition (OSAID) represents an important first step in defining Open Source in an AI context. Because AI systems differ fundamentally from traditional software, the OSAID seeks to establish the first set of clear, practical guidelines for development, use and modification of AI systems in keeping with the Open Source ethos. Unfortunately, misconceptions about the definition persist, often stemming from a lack of understanding of the nature of AI. This post aims to clarify key points and provide a forward-looking perspective on the importance of the OSAID. THE open source ai definition 1.0 FAQs What Is an AI System? What is an Open Source AI? Why did you write the Open Source AI Definition? What’s the difference between the Open Source Definition and the Open Source AI Definition? Isn’t training data required to program the AI system? What is the role of training data in the Open Source AI Definition? Why do you allow the exclusion of some training data? How did you arrive at this conclusion? Is it compromising Open Source ideals? What kind of data should be required in the Open Source AI Definition? How do you fix a buggy AI system? What is a skilled person? Is the Open Source AI Definition covering models and weights and parameters? Why do you require training code while OSD #2 doesn’t require compilers? Why is there no mention of safety and risk limitations in the Open Source AI Definition? Are model parameters copyrightable? Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? Why is the “Preferred form to make modifications” limited to machine learning? Which AI systems comply with the Open Source AI Definition? What’s the next step? FAQs What Is an AI System? According to the OSAID, an AI system aligns with the definition provided by the Organisation for Economic Co-operation and Development (OECD): An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment. In simple terms, an AI system is “the thing” that processes input to produce output, whether that’s a prediction, recommendation, or another result. Anchoring discussions in such common definitions is essential because AI systems differ radically from traditional software. What is an Open Source AI? An Open Source AI is an AI system made freely available with all necessary code, data and parameters under legal terms approved by the Open Source Initiative. For more details, read below. Why did you write the Open Source AI Definition? Point #2 of the Open Source Definition (OSD) says “The program must include source code […] The source code must be the preferred form in which a programmer would modify the program […]” . When we embarked on this initiative, nobody had a clear answer to the question, “What is the preferred form to modify an AI system?” So OSI offered to find the answer along with the broader community by engaging in a co-design process . What’s the difference between the Open Source Definition and the Open Source AI Definition? The Open Source Definition (OSD) refers to software programs. AI and specifically machine learning systems are not simply software programs; they blend boundaries with data, configuration options, documentation and new artifacts, like weights and biases. The Open Source AI Definition describes the preferred form to modify an AI system, providing clarity on interpreting the principles of the OSD in the domain of AI. Isn’t training data required to program the AI system? A frequent misunderstanding about AI systems is equating training data with source code, suggesting that “training data is how the model gets programmed.” Unlike traditional software, AI systems are not programmed in the conventional sense. Instead, they acquire capabilities autonomously during the training process — a phenomenon distinguishing them from software like the Linux kernel. For example, the Linux kernel is: Programmed by humans. Composed of source code that developers can read, study, and modify. Reproducible, meaning its binary form can be reliably rebuilt from its source code. In contrast, modern AI systems such as large language models develop their behavior in ways that are often unpredictable and inexplicable. Training processes are challenging to replicate reliably, even by the system’s creators. These differences necessitated the establishment of a unique definition beyond the Open Source Definition for software. What is the role of training data in the Open Source AI Definition? Open Source means giving anyone the ability to meaningfully fork (study and modify) your system without requiring additional permissions to make it more useful for themselves and everyone else. This is why point #2 of the OSD requires that the source code be provided in the preferred form for making modifications. This way, everyone has the same rights and ability to fork as the original developers, starting a virtuous innovation cycle. However, training data does not equate to a software source code. Training data is important for studying modern machine learning systems. However, it is not what AI researchers and practitioners necessarily use as part of the preferred form for modifying a trained model. The Data Information and Code requirements of the OSAID allow Open Source AI systems to be forked by third-party AI builders downstream using the same information as the original developers. These forks could include removing nonpublic or non-open data from the training dataset in order to train a new Open Source AI system on fully public or open data. Why do you allow the exclusion of some training data? We want Open Source AI to exist in fields where data cannot be legally shared, such as medical AI. Laws that permit training on data often limit the resharing of that same data to protect copyright or other interests. Privacy rules also give people the right to control their most sensitive information, like decisions about their health. Similarly, much of the world’s Indigenous knowledge is protected through mechanisms that are not compatible with later-developed frameworks for rights exclusivity and sharing. There are also many cases where terms of use of publicly available data may give entity A the confidence that they may use it freely and call it “open data,” but not give entity A the confidence they can, in turn, give entity B the same guarantees for use in a different jurisdiction. Meanwhile, entity B may not feel confident using that data in their own jurisdiction. An example is so-called public domain data, where the definition of public domain varies from country to country. Another example is fair-use or private data, where the finding of fair use or privacy laws may require a good knowledge of the law of a given jurisdiction. This resharing is not so much limited as lacking legal certainty . How did you arrive at this conclusion? Is it compromising Open Source ideals? During our co-design process, relationships between the weights and the data drove the highest community engagement. In the “System analysis” phase , the volunteer groups suggested that training and data processing codes were more important for modifying the AI system than accessing the training and testing data. That result was validated in the “Validation phase” and suggested a path that allows Open Source AI to exist on equal grounds with proprietary systems: both can train on the same kind of data. Some people believe that full, unfettered access to all training data (with no distinction of its kind) is paramount, arguing that anything less would compromise the full reproducibility of AI systems, transparency and security. This approach would relegate Open Source AI to a niche of AI trainable only on open data. That niche would be tiny, even relative to the niche occupied by Open Source in the traditional software ecosystem. The requirements of Data Information keep the same approach present in the Open Source Definition; it doesn’t mandate full reproducibility and transparency but enables them (i.e., reproducible builds ). At the same time, setting a baseline requiring Data Information doesn’t preclude others from formulating and demanding more requirements, like the Digital Public Goods Standard or the Free Systems Distribution Guidelines , which add requirements to the Open Source Definition. One of the key aspects of OSI’s mission is to drive and promote Open Source innovation. The approach OSI takes here enables complete user choice with Open Source AI. Users can keep the insights derived from training+data preprocessing code and a description of unshareable training data and build upon those with their own unshareable data and give the insights derived from further training to everyone, allowing for Open Source AI in areas like health care. Alternatively, users can obtain the available and public data from the Data Information and retrain their model without any unshareable data, resulting in more data transparency in the AI system. Like copyleft and permissive licensing, this approach leaves the choice with the user. What kind of data should be required in the Open Source AI Definition? A significant challenge in AI is the role of data. Unlike traditional software, where source code is the primary artifact, AI systems depend heavily on data — not just any data, but data processed and curated into training datasets. The OSAID recognizes the legal and ethical complexities of data sharing and uses precise legal terms to outline expectations. While not all raw data can be freely distributed, the Definition ensures that the essential elements for modifying an AI system are accessible. There are four classes of data, based on their legal constraints, all of which can be used to train Open Source AI systems: Open training data: data that can be copied, preserved, modified and reshared. It provides the best way to enable users to study the system. This must be shared. Public training data: data that others can inspect as long as it remains available. This also enables users to study the work. However, this data can degrade as links or references are lost or removed from network availability. To obviate this, different communities will have to work together to define standards, procedures, tools and governance models to overcome this risk, and Data Information is required in case the data becomes later unavailable. This must be disclosed with full details on where to obtain it. Obtainable training data is data that can be obtained, including for a fee. This information provides transparency and is similar to a purchasable component in an open hardware system. The Data Information provides a means of understanding this data other than obtaining or purchasing it. This area is likely to change rapidly and will need careful monitoring to protect Open Source AI developers. It must be disclosed with full details on where to obtain it. Unshareable nonpublic training data: data that cannot be shared for explainable reasons, like Personally Identifiable Information (PII). For this class of data, the ability to study some of the system’s biases demands a detailed description of the data – what it is, how it was collected, its characteristics, and so on – so that users can understand the biases and categorization underlying the system. This must be revealed in detail so that, for example, a hospital can create a dataset with identical structure using its own patient data. OSI believes that all these classes of data can be part of the preferred form of making modifications to the AI system. This approach both advances openness in all the components of the AI system and drives more Open Source AI, including private-first areas such as health care. How do you fix a buggy AI system? A core question the OSAID addresses is: How do you fix a buggy AI system? For traditional software, the Open Source Definition provides a clear answer: The program must include source code, and must allow distribution in source code as well as compiled form. The source code must be the preferred form in which a programmer would modify the program. However, modifying an AI system requires more than just source code. After extensive consultation with AI developers, researchers and practitioners, the community, through the OSAID co-design process, concluded that the preferred form for modifying an AI system includes: The software used to create the dataset (i.e., to transform raw data into tokens). The software used to train the system. The results of the training (i.e., the parameters). All legally shareable data used in the training process. These components collectively enable the study, use, modification and sharing of AI systems in a manner consistent with Open Source principles. What is a skilled person? In legal circles, Skilled Person means any person having the current knowledge, experience and competence to perform a certain duty. This Wikipedia entry provides more details. Is the Open Source AI Definition covering models and weights and parameters? Yes. The Open Source AI Definition makes no distinction between what might be called AI system, model, or weights and parameters. Whether the offering is characterized as an AI system, a model, or weights and parameters, to be called Open Source AI, the requirements for providing the preferred form for making modifications will be the same. If you are interested in learning more about Open Weights, please read this article. Why do you require training code while OSD #2 doesn’t require compilers? AI and software are radically different domains, and drawing comparisons between them is rarely productive. OSD point #2 doesn’t mandate that Open Source software uses only compilers released with an OSI-Approved License because compilers are standardized, de jure (like ANSI C) or de facto like TurboPascal or Python. It was generally accepted that to develop more Open Source software one could use a proprietary development environment. For machine learning, the training code is not standardized, and therefore it must be part of the preferred form of making modifications to preserve the right to fork an AI system. Why is there no mention of safety and risk limitations in the Open Source AI Definition? The Open Source AI Definition does not specifically guide or enforce ethical, trustworthy, or responsible AI development practices. However, it does not put up any barriers that would prevent developers from adhering to such principles if they chose to. The efforts to discuss the responsible development, deployment and use of AI systems, including through appropriate government regulation, are a separate conversation. A good starting point is OECD’s Recommendation of the Council on Artificial Intelligence, Section 1: Principles for responsible stewardship of trustworthy AI . Are model parameters copyrightable? The Open Source AI Definition does not take a stance on the legal nature of Parameters. They may be free by nature, or a license or other legal instrument may be required to ensure their freedom. Whether model parameters are copyrightable will become clearer over time as the legal system has more opportunities to address this issue. In any case, we require an explicit assertion accompanying the distribution of Parameters that assures that they are freely available to all. Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? We used the word “terms” instead of “license” for models because, as mentioned above, we do not yet know what the legal mechanism will be to assure that the models are available to use, study, modify and share. We used “terms” to avoid suggesting that a “license” is the only legal mechanism that could be used. That said, to be approved by the OSI, the terms for parameters must assure the freedom to use, study, modify and share. Why is the “Preferred form to make modifications” limited to machine learning? The principles stated in the Open Source AI Definition are generally applicable to any kind of AI, but machine learning challenges the Open Source Definition. For machine learning, a set of artifacts (components) is required to study and modify the system, thus requiring a new explanation of what is necessary to study and modify the system. Which AI systems comply with the Open Source AI Definition? As part of our validation and testing of the OSAID, the volunteers checked whether the Definition could be used to evaluate if AI systems provided the freedoms expected. The list of models that passed the Validation phase are: Pythia (Eleuther AI), OLMo (AI2), Amber and CrystalCoder (LLM360), and T5 (Google). A few others that were analyzed would probably pass if they changed their licenses/legal terms, for example, BLOOM (BigScience), Starcoder2 (BigCode), and Falcon (TII). Those that have been analyzed and don’t pass because they lack required components and/or their legal agreements are incompatible with the Open Source principles include Llama2 (Meta), Grok (X/Twitter), Phi-2 (Microsoft), and Mixtral (Mistral). These results should be seen as part of the definitional process, a learning moment; they are not certifications of any kind. OSI will continue to validate only legal documents and will not validate or review individual AI systems, just as it does not validate or review software projects. What’s the next step? The Open Source AI Definition reflects a thoughtful and inclusive process endorsed by leading AI developers, researchers and practitioners. It culminates in a first step represented in version 1.0 of the OSAID. The definition acknowledges that AI fundamentally differs from software and requires a tailored approach. Misunderstandings about the OSAID often arise from attempts to apply software engineering paradigms to AI, leading to confusion. By embracing the unique characteristics of AI systems, the OSAID offers a robust framework for fostering transparency, innovation and collaboration in AI development. As we navigate AI’s evolving landscape, it is crucial to engage thoughtfully and constructively with these definitions. By doing so, we can ensure that AI systems remain open, accessible and aligned with the principles of the broader Open Source movement. Our work is only possible thanks to our members. Join us today! 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2026-01-13T08:49:43
https://www.algolia.com/de/distributed-secure/global-infrastructure
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2026-01-13T08:49:43
http://illustratedtheoryofnumbers.com/prog.html
Python for Number Theory About (current) Get started The notebooks Other resources Return to the book page About this tutorial The resources here provide an introduction to Python programming for those who have never programmed before. What makes this tutorial different from others is that the focus is on programming for number theoretic applications . So the tutorial will have very little on string manipulations, web-crawling, file I/O, etc., all of which are very important for other programming applications. But it will cover core imperative programming topics, including variables and data types, control statements, functions, and some fancier data structures (lists and dictionaries) and algorithms. The goal is to get to the point where one can carry out experimental number theory in a short time, investigating the distribution of prime numbers, implementing basic cryptosystems, etc. This Python tutorial is meant to accompany An Illustrated Theory of Numbers . Together they form an introduction to elementary number theory, with theoretical and computational techniques. Besides the introduction you find on this page, the tutorial is composed of a series of Python (Jupyter) notebooks. These notebooks will allow you to read text, run programs, and experiment with Python, all within the comfort of your web browser (with or without internet connection). While Jupyter notebooks are not meant for extensive software development, they are excellent for experimental explorations and data science. What about SAGE? SAGE is an awesome open-source mathematical software system, with Python at its core. One might start programming with SAGE right off the bat, since it contains all the Python functionality we need, with the Jupyter notebook interface, and additional functionality for the research mathematician. The interested user might wish to set up an account on CoCalc to run SAGE in the cloud. Just about everything in these tutorials will run through SAGE too. You can read a bit about the relationship between SAGE and Python here , including some important differences in basic syntax. But , we have not designed the tutorials for SAGE. Indeed, SAGE is a bit too powerful for what we want to accomplish. Instead, we build a basic number theoretic toolbox from scratch, using only vanilla Python (with a bit of Numpy). In this way, the tutorial makes the user learn to write programs rather than hunt for the appropriate SAGE command to accomplish a task. After this tutorial, the user will be well-prepared to begin programming in SAGE, and might better appreciate the incredible efforts that have created this powerful software package (as well as GAP, FLINT, and others). For those who wish to start with SAGE, there is an excellent tutorial at the SAGE homepage . William Stein, the designer of SAGE, also wrote a great elementary number theory book which takes a computational approach and uses SAGE throughout. Get started Our Python tutorial is composed of a series of Jupyter notebooks. Python is a programming language (like C, Java, Haskell, etc.) and Jupyter provides an interactive interface to Python that runs in your web browser. A great way to get all this running on your computer is to download and install Anaconda . It is free, and works on Windows, Mac OS, and Linux. For these tutorials, make sure to download Python version 2.7 Python 3.x . We have included versions of these notebooks for Python 2.7 too, since it is still widely used. But let's get with the times and use Python 3 instead. For those teaching number theory, using Anaconda across the course will give students a more uniform programming experience, allowing them to work easily in groups, and preventing you from getting bogged down with tech support. When you install Anaconda, you get Python for programming, Jupyter for the notebook interface, hundreds of other packages, and a nice "Anaconda Navigator" for starting everything up. These are the tools we will use. Among the Python packages, we will occasionally use NumPy for high-speed calculations, and matplotlib for data visualization. All of this will be installed when you install Anaconda. After Anaconda is installed on your computer, run the Anaconda Navigator . Click the Launch button under Jupyter to launch a Jupyter notebook. This should open a tab in your web browser (and a little background window too). It's best to avoid Internet Explorer, but the other popular web browsers should be fine, e.g. Chrome, Safari, Firefox. Once you have a tab open on your web browser for Jupyter, you can close down the Anaconda navigator if you want. In your Jupyter window, you should see a file directory. Click on directories to navigate to a convenient location, where you'll want to save your files. You can create a new folder, by clicking on New... Folder. Use this folder for the whole tutorial. If you want to jump in and create your own Python notebook, you can go into your directory, then click on New... Python 3. This should open a new tab in your browser and you should see a prompt that looks like In [ ]: To the right of the prompt, type 2 + 2 and then shift-Enter (hold down the shift key while you press the enter/return key). You should see a result like Out[1]: 4 and a new "cell" should appear below, ready for more input. If all this works, congratulations! Python and Jupyter are installed and you should be ready to go to the Notebooks below. You can rename your Python notebook by clicking on the "Untitled" name at the top and changing it. Then you can go to "File... Save and checkpoint" to save your notebook for later. The Notebooks A Jupyter notebook is a file which contains both text and Python code. Jupyter notebooks are stored as files with the .ipynb extension. Before you begin with the notebooks, make sure that you have gone through the Getting Started steps above. If this is your first time interacting with a Python notebook, begin by downloading the "My First Notebook.ipynb" file below and saving it in the directory where you'll be working on this tutorial. Then, launch Jupyter (through the Anaconda navigator), go to the directory of the notebook, and open it. Follow through the notebook to get used to working with Python and Markdown cells. For learning to program, it's important to type code yourself! So a good way to proceed through later notebooks is to print out the notebooks first, and then to enter the commands in an empty Jupyter notebook. But to work with the notebooks directly, download the .ipynb files and open them in Jupyter. Once you are used to working in a Jupyter notebook, you're ready for the Python tutorial below. If you just want to look at the notebooks, they are hosted on GitHub and you can read them online and print them through the Python Notebook Viewer. All Notebooks are free to download and edit via a GPLv3 license . If you have feedback about these notebooks, or wishes for future instructional notebooks, send me a note at weissman AT ucsc DOT edu. Happy programming! Notebook View Python 3 Notebook Download Python 3 Notebook View Python 2 Notebook Download Python 2 Notebook Introduction to the Jupyter notebook interface. Editing, inserting, and deleting cells. Executing code cells. A brief introduction to Markdown. Saving, loading, and printing notebooks View/print notebook Download My First Python 3 Notebook.ipynb View/print notebook Download My First Python Notebook.ipynb Introduction to Python as a calculator, focusing on integer operations. Variables and basic data types (int, float, bool, string, list). The range command and for loops. View/print notebook Download P3wNTNotebook1.ipynb View/print notebook Download PwNTNotebook1.ipynb Defining functions. Control statements (if/else), while loops. Basic string substitution. Implementation of the Euclidean algorithm, and the solution of linear Diophantine equations. View/print notebook Download P3wNTNotebook2.ipynb View/print notebook Download PwNTNotebook2.ipynb Lists and some data analysis. List slicing and comprehension. Implementing the sieve of Eratosthenes. Optimization and the timeit tool. Data analysis (on the set of prime numbers) with a bit of matplotlib for visualization. View/print notebook Download P3wNTNotebook3.ipynb View/print notebook Download PwNTNotebook3.ipynb Dictionaries and prime decomposition. Some generalities on Python objects and methods too, with examples from dictionaries and lists. Functions as objects, and the implementation of multiplicative functions. View/print notebook Download P3wNTNotebook4.ipynb View/print notebook Download PwNTNotebook4.ipynb Modular arithmetic and primality testing. A closer look at algorithms and performance analysis. Pingala's algorithm for exponentiation (successive squaring) and an in-depth look at the Miller-Rabin primality test. View/print notebook Download P3wNTNotebook5.ipynb View/print notebook Download PwNTNotebook5.ipynb Ciphers and Diffie-Hellman key exchange. Caesar and Vigenere ciphers. Working with strings and ASCII code in Python. An introduction to symmetric key cryptosystems. Modular exponentiation and the existence of primitive roots. Sophie Germain and safe primes. Diffie-Hellman key exchange. View/print notebook Download P3wNTNotebook6.ipynb View/print notebook Download PwNTNotebook6.ipynb The RSA cryptosystem. Putting it all together -- Euler's theorem for modular exponentiation, primality testing for creating private keys, the Euclidean algorithm for modular inverses. Some issues of implementation, including random key generation and the web of trust. How to use RSA for encryption, as well as for digital signatures. View/print notebook Download P3wNTNotebook7.ipynb View/print notebook Download PwNTNotebook7.ipynb Other resources There are lots of online and print resources for Python programming. This is a short list. The official resources. The official Python 3.x tutorial. Official Python references. Library and language references are most helpful. The official Anaconda docs The official Jupyter docs Online courses and tutorials Udacity's Programming Foundations with Python course CodeAcademy's Learn Python course w3School's Python tutorial Books You can always Learn Python the hard way . (Python 3.x is the default here.) Learning Python, 5th Edition, by Mark Lutz. When you're ready for the next step, there's Fluent Python, by Luciano Ramalho.
2026-01-13T08:49:43
https://vibe.forem.com/josem12
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2026-01-13T08:49:43
https://www.coderabbit.ai/case-studies/how-visma-found-the-enhance-code-quality-and-streamline-reviews
How Visma uses AI for code reviews for their legacy codebase Features Enterprise Customers Pricing Blog Resources Docs Trust Center Contact Us FAQ Log In Get a free trial How Visma enhanced code quality and streamlined reviews Catches hard to find bugs Faster code reviews Great PR context & summaries More secure merges Visma Oslo, Norway https://www.visma.com/ Team size 10,000+ Language ASP.NET, .NET framework, C#, Vue JS, React, JavaScript. Challenge Navigating a massive, decades-old codebase with intricate cross-dependencies while ensuring top-tier code quality and overcoming human review limitations. Get started today Share Overview For Seref Boyer , the Chief Architect of a Visma R&D unit, managing their large codebase is high stakes since millions of users rely on the applications his company powers. Visma, a major player in the European ERP market, develops internal solutions for finance, logistics, warehousing, and project accounting across Northern Europe. That makes quality assurance a mission-critical focus for Visma. Seref's team is made up of approximately 80 developers, including 40-50 developers focused on product development and research. Their core product isn't just another web application—it's a powerful ASP.NET system built on the Microsoft .NET framework with a large, legacy codebase that’s over 20 years old. This complex, decades-old codebase creates a perfect storm of challenges for new developers who often struggle with onboarding and introduce bugs and errors into the codebase in their first months as they get up to speed. Seref learned about CodeRabbit when another team shared their positive experience integrating the tool on their project. This internal validation convinced Seref to adopt CodeRabbit for his team, as well. The result? Increased error detection and unprecedented clarity in pull requests that transformed his team’s development cycle. Challenge: Taming a large, legacy codebase Before CodeRabbit, Visma's development process was complex. Human reviewers carefully examined their team’s 600 monthly pull requests (a process still central to their workflow). Still, even the most eagle-eyed developers faced limitations when trying to protect a legacy codebase of this magnitude: Navigating legacy complexity and cross-dependencies: The application's central repository contains more than 3 million lines of mostly legacy code dating back to the early 2000s. This extensive, interlinked system meant that even minor updates could cause unforeseen ripple effects. "If you make changes, they could affect other parts as well if you are unaware of them," Seref emphasized. “ There are several cross-dependencies where packages interact with each other. ” The codebase's sheer size made understanding these relationships difficult for any one developer. Accelerating onboarding and mitigating risk for new devs: For newcomers, this complexity created a Mount Everest-sized learning curve. "The code is complex for new developers who are starting to work with it. It takes time to onboard them and they need to understand the risk when they do refactoring or code changes," Seref explained. Given what was at stake with their ERP product, this created a bottleneck for new talent to start contributing effectively and safely. Overcoming limitations of manual review in edge cases: While human reviewers excelled at understanding business logic, critical technical errors often slipped through even the most careful review. "Even human reviews can miss that if they don't pay attention," Seref acknowledged. 600 PRs/month 3 Million Lines Secured—Every Pull Request 20-year -old code Why Visma loves CodeRabbit https://youtu.be/0WmK5QqqjJY Catches bugs & issues human reviewers miss One key reason Visma loves CodeRabbit is that it helps sniff out bugs that human reviewers often miss. CodeRabbit’s capabilities identify subtle but critical technical errors that could otherwise slip into production. "The feedback I get from developers is that they like that it shows them typo errors, null pointers, and static code," Seref shared. He praised CodeRabbit’s ability to discover errors before they reach production, especially in those notoriously difficult scenarios: It's the edge scenarios that are usually difficult to catch. It's a good tool to get these edge scenarios. Seref Boyer, Chief Architect Additionally, Seref liked CodeRabbit's tendency to flag issues in untouched legacy code: "It's good because then you are also aware of other things that can be done to improve the code and reduce technical debt." CodeRabbit, Seref shared, highlighted key opportunities for manually identifying and addressing technical debt within their evolving legacy system. Revolutionary PR context with AI summaries & sequence diagrams CodeRabbit's AI-generated summaries and sequence diagrams were an instant hit with Visma's developers, providing clarity that helped them understand complex changes more easily. CodeRabbit also gives developers an excellent overview with sequence diagrams. Our devs like the sequence diagrams, and I think one of the developers even mentioned that it gives a better summary than they could write by themselves. Seref Boyer, Chief Architect This visualization benefit extends to the dev writing the code, as well. "It gives a nice picture of what you have done,” he said. Accelerating the code review cycle While Visma wasn't primarily focused on increasing raw output, they saw a marked improvement in review speed after adopting CodeRabbit. The code review part has been faster. It has been speeding up the time it takes, which is remarkable. - Seref Boyer, Chief Architect This acceleration allows developers to move on to other critical tasks more quickly. Intelligent adaptability One thing that Seref loves about CodeRabbit is how Visma’s developers can customize their reviews – something they’ve achieved by integrating PATH instructions and using some of CodeRabbit’s other customization features – something that’s critical with a legacy codebase. Seref observed, "Our devs created 24 learnings in the last 30 days. Developers are interested in customizing their settings .” Results: Protection for their mission-critical legacy codebase Elevated production readiness & bug prevention Since they implemented CodeRabbit, it has caught several critical bugs during Visma’s pull request stage, significantly reducing the number of incidents they have. "I believe that it is helping us improve our code and product quality,” shared Seref. “That's the goal: To increase code quality and product quality by using an AI tool because it can see errors that are not easy to see for humans," Seref confirmed. Enhanced context led to streamlined reviews The AI-generated summaries and sequence diagrams provide instant clarity, transforming how developers grasp complex changes and how quickly they can complete their reviews. "It gives a nice picture of what you have done and the changes. Not only for you, the one making the changes, but also for the human who could review it at a later step," he shared. This rapid comprehension significantly reduces back-and-forth communication, resulting in faster reviews overall. "The code review part has been faster," Seref noted. Freeing human reviewers to focus on business logic By detecting technical errors, CodeRabbit frees Visma's human reviewers to focus their expertise on higher-value tasks, such as validating complex business logic and ensuring architectural alignment with legacy code. This partnership between AI and humans creates a more effective development cycle, according to Seref. He recently explained to a colleague, "I think it's terrific for detecting the local errors. That’s hard to do even in human reviews." CodeRabbit = More secure merges for their large codebase Before CodeRabbit • Large, complex codebase = more bugs in prod • Onboarding devs introduce new bugs • Difficulty reviewing edge cases After CodeRabbit More bugs caught thanks to codebase context Fewer bugs CodeRabbit finds edge cases that humans miss For Seref and his team at Visma, CodeRabbit isn't just another tool in their development lifecycle – it's become a critical partner in tackling the complexities of large-scale ERP development. "It's very good at detecting localized errors. to give a good picture of the changes which have been applied to the system," Seref explained. CodeRabbit stands out for Visma’s team because of its unique ability to catch issues that might otherwise slip through the cracks. As Seref puts it, these are problems that humans have difficulty identifying. This added quality check ensures Visma continues to deliver mission-critical software solutions that meet the highest standards of quality and reliability. The success Seref's team experienced with CodeRabbit has already sparked a wave of interest across the organization, with other Visma teams eagerly joining in as well. We have at least two other organizations who are buying or adding new licenses because we shared our experience. Seref Boyer, Chief Architect Visma Oslo, Norway https://www.visma.com/ Team size 10,000+ Language ASP.NET, .NET framework, C#, Vue JS, React, JavaScript. Challenge Navigating a massive, decades-old codebase with intricate cross-dependencies while ensuring top-tier code quality and overcoming human review limitations. Get started today Want to see how CodeRabbit can help your team? Get a 14-day 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
2026-01-13T08:49:43
https://dev.to/t/introduction/page/7
Introduction Page 7 - 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 # introduction Follow Hide Create Post Older #introduction posts 4 5 6 7 8 9 10 11 12 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu 1.1 simple hello world program Raghav Khanna Raghav Khanna Raghav Khanna Follow May 6 '20 1.1 simple hello world program # java # introduction # beginners # devop 5  reactions Comments 1  comment 2 min read The first experience with k3s (lightweight Kubernetes). Deploy your first app! Francisco Javier Sánchez Fuentes Francisco Javier Sánchez Fuentes Francisco Javier Sánchez Fuentes Follow May 4 '20 The first experience with k3s (lightweight Kubernetes). 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2026-01-13T08:49:43
https://opensource.org/blog/welcome-to-deep-dive-ai
Welcome to Deep Dive AI – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu August 5, 2022 Events Stefano Maffulli Welcome to Deep Dive AI Welcome to Deep Dive: AI, an online event from the Open Source Initiative. We’ll be exploring how Artificial Intelligence impacts Open Source software, from developers to businesses to the rest of us. Algorithms are nothing new. The concept of problem-solving procedures in math has been around since the Babylonians. It can be as simple as an “if, then” statement. Artificial Intelligence, by contrast, is a configuration of algorithms that can self-modify and create new algorithms in response to learned inputs and data. With AI, there’s now a layer of abstraction where it’s not clear who is doing the computing, who can see it or how the user can modify that behavior if the results are unfair or unsatisfactory. Many of these AIs are complex, powerful black boxes that, as it stands, no one can examine. Or trust. This is where what has long been considered useful quickly turns into any number of nightmare scenarios: people denied bail, housing, credit, your face is imposed on the body of a porn actress …The stuff that makes lots of spooky sci-fi movies. Why is the OSI leading this conversation? When the Open Source movement started, we imagined a world where the users were empowered, granted rights and freedoms to shape the technology. We encoded those rights and freedoms into the Open Source Definition  that has served the community as a north star for over two decades, creating a huge, thriving ecosystem. With AI systems being so complex, concepts like “program” or “source code” in the Open Source Definition are challenged in new and surprising ways. The topic of AI is huge. For Open Source Initiative’s Deep Dive, we’ll be looking at how AI could affect  the future of Open Source. Deep Dive: AI is an event in three parts: we start with a podcast series  where we interview experts in different fields, from legal to academia, developers and policy experts. We’ll then have four panel discussions with more experts in October, and finally in the last months of 2022 we’ll publish a report to summarize what we’ve learned. Deep Dive: AI  will lay the foundation to better understand what an Open Source AI should look like. Signup for the podcast now on your favorite app (if we missed one, please let us know) or directly from the source. Deep Dive: AI is made possible by the generous support of OSI individual members and sponsors. Donate or become a member of the OSI today . Listen to the teaser now and subscribe to the series on your favorite app (did we miss any? Let us know! ) Reflecting on SCaLE 19x How to make app stores friendly to Open Source Keep up with Open Source Please leave this field empty. Δ We’ll never share your details and you can unsubscribe with a click! Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. 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2026-01-13T08:49:43
https://opensource.org/ai/faq#answers-to-frequently-asked-questions
OSAID FAQs – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Source AI Open Source AI OSAID 1.0 Process Timeline Open Weights FAQ Endorsements Open Main Menu THE open source ai definition 1.0 We have released the first stable version of the Definition. Read version 1.0 Answers to Frequently Asked Questions The Open Source AI Definition (OSAID) represents an important first step in defining Open Source in an AI context. Because AI systems differ fundamentally from traditional software, the OSAID seeks to establish the first set of clear, practical guidelines for development, use and modification of AI systems in keeping with the Open Source ethos. Unfortunately, misconceptions about the definition persist, often stemming from a lack of understanding of the nature of AI. This post aims to clarify key points and provide a forward-looking perspective on the importance of the OSAID. THE open source ai definition 1.0 FAQs What Is an AI System? What is an Open Source AI? Why did you write the Open Source AI Definition? What’s the difference between the Open Source Definition and the Open Source AI Definition? Isn’t training data required to program the AI system? What is the role of training data in the Open Source AI Definition? Why do you allow the exclusion of some training data? How did you arrive at this conclusion? Is it compromising Open Source ideals? What kind of data should be required in the Open Source AI Definition? How do you fix a buggy AI system? What is a skilled person? Is the Open Source AI Definition covering models and weights and parameters? Why do you require training code while OSD #2 doesn’t require compilers? Why is there no mention of safety and risk limitations in the Open Source AI Definition? Are model parameters copyrightable? Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? Why is the “Preferred form to make modifications” limited to machine learning? Which AI systems comply with the Open Source AI Definition? What’s the next step? FAQs What Is an AI System? According to the OSAID, an AI system aligns with the definition provided by the Organisation for Economic Co-operation and Development (OECD): An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment. In simple terms, an AI system is “the thing” that processes input to produce output, whether that’s a prediction, recommendation, or another result. Anchoring discussions in such common definitions is essential because AI systems differ radically from traditional software. What is an Open Source AI? An Open Source AI is an AI system made freely available with all necessary code, data and parameters under legal terms approved by the Open Source Initiative. For more details, read below. Why did you write the Open Source AI Definition? Point #2 of the Open Source Definition (OSD) says “The program must include source code […] The source code must be the preferred form in which a programmer would modify the program […]” . When we embarked on this initiative, nobody had a clear answer to the question, “What is the preferred form to modify an AI system?” So OSI offered to find the answer along with the broader community by engaging in a co-design process . What’s the difference between the Open Source Definition and the Open Source AI Definition? The Open Source Definition (OSD) refers to software programs. AI and specifically machine learning systems are not simply software programs; they blend boundaries with data, configuration options, documentation and new artifacts, like weights and biases. The Open Source AI Definition describes the preferred form to modify an AI system, providing clarity on interpreting the principles of the OSD in the domain of AI. Isn’t training data required to program the AI system? A frequent misunderstanding about AI systems is equating training data with source code, suggesting that “training data is how the model gets programmed.” Unlike traditional software, AI systems are not programmed in the conventional sense. Instead, they acquire capabilities autonomously during the training process — a phenomenon distinguishing them from software like the Linux kernel. For example, the Linux kernel is: Programmed by humans. Composed of source code that developers can read, study, and modify. Reproducible, meaning its binary form can be reliably rebuilt from its source code. In contrast, modern AI systems such as large language models develop their behavior in ways that are often unpredictable and inexplicable. Training processes are challenging to replicate reliably, even by the system’s creators. These differences necessitated the establishment of a unique definition beyond the Open Source Definition for software. What is the role of training data in the Open Source AI Definition? Open Source means giving anyone the ability to meaningfully fork (study and modify) your system without requiring additional permissions to make it more useful for themselves and everyone else. This is why point #2 of the OSD requires that the source code be provided in the preferred form for making modifications. This way, everyone has the same rights and ability to fork as the original developers, starting a virtuous innovation cycle. However, training data does not equate to a software source code. Training data is important for studying modern machine learning systems. However, it is not what AI researchers and practitioners necessarily use as part of the preferred form for modifying a trained model. The Data Information and Code requirements of the OSAID allow Open Source AI systems to be forked by third-party AI builders downstream using the same information as the original developers. These forks could include removing nonpublic or non-open data from the training dataset in order to train a new Open Source AI system on fully public or open data. Why do you allow the exclusion of some training data? We want Open Source AI to exist in fields where data cannot be legally shared, such as medical AI. Laws that permit training on data often limit the resharing of that same data to protect copyright or other interests. Privacy rules also give people the right to control their most sensitive information, like decisions about their health. Similarly, much of the world’s Indigenous knowledge is protected through mechanisms that are not compatible with later-developed frameworks for rights exclusivity and sharing. There are also many cases where terms of use of publicly available data may give entity A the confidence that they may use it freely and call it “open data,” but not give entity A the confidence they can, in turn, give entity B the same guarantees for use in a different jurisdiction. Meanwhile, entity B may not feel confident using that data in their own jurisdiction. An example is so-called public domain data, where the definition of public domain varies from country to country. Another example is fair-use or private data, where the finding of fair use or privacy laws may require a good knowledge of the law of a given jurisdiction. This resharing is not so much limited as lacking legal certainty . How did you arrive at this conclusion? Is it compromising Open Source ideals? During our co-design process, relationships between the weights and the data drove the highest community engagement. In the “System analysis” phase , the volunteer groups suggested that training and data processing codes were more important for modifying the AI system than accessing the training and testing data. That result was validated in the “Validation phase” and suggested a path that allows Open Source AI to exist on equal grounds with proprietary systems: both can train on the same kind of data. Some people believe that full, unfettered access to all training data (with no distinction of its kind) is paramount, arguing that anything less would compromise the full reproducibility of AI systems, transparency and security. This approach would relegate Open Source AI to a niche of AI trainable only on open data. That niche would be tiny, even relative to the niche occupied by Open Source in the traditional software ecosystem. The requirements of Data Information keep the same approach present in the Open Source Definition; it doesn’t mandate full reproducibility and transparency but enables them (i.e., reproducible builds ). At the same time, setting a baseline requiring Data Information doesn’t preclude others from formulating and demanding more requirements, like the Digital Public Goods Standard or the Free Systems Distribution Guidelines , which add requirements to the Open Source Definition. One of the key aspects of OSI’s mission is to drive and promote Open Source innovation. The approach OSI takes here enables complete user choice with Open Source AI. Users can keep the insights derived from training+data preprocessing code and a description of unshareable training data and build upon those with their own unshareable data and give the insights derived from further training to everyone, allowing for Open Source AI in areas like health care. Alternatively, users can obtain the available and public data from the Data Information and retrain their model without any unshareable data, resulting in more data transparency in the AI system. Like copyleft and permissive licensing, this approach leaves the choice with the user. What kind of data should be required in the Open Source AI Definition? A significant challenge in AI is the role of data. Unlike traditional software, where source code is the primary artifact, AI systems depend heavily on data — not just any data, but data processed and curated into training datasets. The OSAID recognizes the legal and ethical complexities of data sharing and uses precise legal terms to outline expectations. While not all raw data can be freely distributed, the Definition ensures that the essential elements for modifying an AI system are accessible. There are four classes of data, based on their legal constraints, all of which can be used to train Open Source AI systems: Open training data: data that can be copied, preserved, modified and reshared. It provides the best way to enable users to study the system. This must be shared. Public training data: data that others can inspect as long as it remains available. This also enables users to study the work. However, this data can degrade as links or references are lost or removed from network availability. To obviate this, different communities will have to work together to define standards, procedures, tools and governance models to overcome this risk, and Data Information is required in case the data becomes later unavailable. This must be disclosed with full details on where to obtain it. Obtainable training data is data that can be obtained, including for a fee. This information provides transparency and is similar to a purchasable component in an open hardware system. The Data Information provides a means of understanding this data other than obtaining or purchasing it. This area is likely to change rapidly and will need careful monitoring to protect Open Source AI developers. It must be disclosed with full details on where to obtain it. Unshareable nonpublic training data: data that cannot be shared for explainable reasons, like Personally Identifiable Information (PII). For this class of data, the ability to study some of the system’s biases demands a detailed description of the data – what it is, how it was collected, its characteristics, and so on – so that users can understand the biases and categorization underlying the system. This must be revealed in detail so that, for example, a hospital can create a dataset with identical structure using its own patient data. OSI believes that all these classes of data can be part of the preferred form of making modifications to the AI system. This approach both advances openness in all the components of the AI system and drives more Open Source AI, including private-first areas such as health care. How do you fix a buggy AI system? A core question the OSAID addresses is: How do you fix a buggy AI system? For traditional software, the Open Source Definition provides a clear answer: The program must include source code, and must allow distribution in source code as well as compiled form. The source code must be the preferred form in which a programmer would modify the program. However, modifying an AI system requires more than just source code. After extensive consultation with AI developers, researchers and practitioners, the community, through the OSAID co-design process, concluded that the preferred form for modifying an AI system includes: The software used to create the dataset (i.e., to transform raw data into tokens). The software used to train the system. The results of the training (i.e., the parameters). All legally shareable data used in the training process. These components collectively enable the study, use, modification and sharing of AI systems in a manner consistent with Open Source principles. What is a skilled person? In legal circles, Skilled Person means any person having the current knowledge, experience and competence to perform a certain duty. This Wikipedia entry provides more details. Is the Open Source AI Definition covering models and weights and parameters? Yes. The Open Source AI Definition makes no distinction between what might be called AI system, model, or weights and parameters. Whether the offering is characterized as an AI system, a model, or weights and parameters, to be called Open Source AI, the requirements for providing the preferred form for making modifications will be the same. If you are interested in learning more about Open Weights, please read this article. Why do you require training code while OSD #2 doesn’t require compilers? AI and software are radically different domains, and drawing comparisons between them is rarely productive. OSD point #2 doesn’t mandate that Open Source software uses only compilers released with an OSI-Approved License because compilers are standardized, de jure (like ANSI C) or de facto like TurboPascal or Python. It was generally accepted that to develop more Open Source software one could use a proprietary development environment. For machine learning, the training code is not standardized, and therefore it must be part of the preferred form of making modifications to preserve the right to fork an AI system. Why is there no mention of safety and risk limitations in the Open Source AI Definition? The Open Source AI Definition does not specifically guide or enforce ethical, trustworthy, or responsible AI development practices. However, it does not put up any barriers that would prevent developers from adhering to such principles if they chose to. The efforts to discuss the responsible development, deployment and use of AI systems, including through appropriate government regulation, are a separate conversation. A good starting point is OECD’s Recommendation of the Council on Artificial Intelligence, Section 1: Principles for responsible stewardship of trustworthy AI . Are model parameters copyrightable? The Open Source AI Definition does not take a stance on the legal nature of Parameters. They may be free by nature, or a license or other legal instrument may be required to ensure their freedom. Whether model parameters are copyrightable will become clearer over time as the legal system has more opportunities to address this issue. In any case, we require an explicit assertion accompanying the distribution of Parameters that assures that they are freely available to all. Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? We used the word “terms” instead of “license” for models because, as mentioned above, we do not yet know what the legal mechanism will be to assure that the models are available to use, study, modify and share. We used “terms” to avoid suggesting that a “license” is the only legal mechanism that could be used. That said, to be approved by the OSI, the terms for parameters must assure the freedom to use, study, modify and share. Why is the “Preferred form to make modifications” limited to machine learning? The principles stated in the Open Source AI Definition are generally applicable to any kind of AI, but machine learning challenges the Open Source Definition. For machine learning, a set of artifacts (components) is required to study and modify the system, thus requiring a new explanation of what is necessary to study and modify the system. Which AI systems comply with the Open Source AI Definition? As part of our validation and testing of the OSAID, the volunteers checked whether the Definition could be used to evaluate if AI systems provided the freedoms expected. The list of models that passed the Validation phase are: Pythia (Eleuther AI), OLMo (AI2), Amber and CrystalCoder (LLM360), and T5 (Google). A few others that were analyzed would probably pass if they changed their licenses/legal terms, for example, BLOOM (BigScience), Starcoder2 (BigCode), and Falcon (TII). Those that have been analyzed and don’t pass because they lack required components and/or their legal agreements are incompatible with the Open Source principles include Llama2 (Meta), Grok (X/Twitter), Phi-2 (Microsoft), and Mixtral (Mistral). These results should be seen as part of the definitional process, a learning moment; they are not certifications of any kind. OSI will continue to validate only legal documents and will not validate or review individual AI systems, just as it does not validate or review software projects. What’s the next step? The Open Source AI Definition reflects a thoughtful and inclusive process endorsed by leading AI developers, researchers and practitioners. It culminates in a first step represented in version 1.0 of the OSAID. The definition acknowledges that AI fundamentally differs from software and requires a tailored approach. Misunderstandings about the OSAID often arise from attempts to apply software engineering paradigms to AI, leading to confusion. By embracing the unique characteristics of AI systems, the OSAID offers a robust framework for fostering transparency, innovation and collaboration in AI development. As we navigate AI’s evolving landscape, it is crucial to engage thoughtfully and constructively with these definitions. By doing so, we can ensure that AI systems remain open, accessible and aligned with the principles of the broader Open Source movement. Our work is only possible thanks to our members. Join us today! Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. 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2026-01-13T08:49:43
https://opensource.org/blog/takeaways-from-the-defining-open-ai-community-workshop
Takeaways from the “Defining Open AI” community workshop – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu July 27, 2023 Events Stefano Maffulli Takeaways from the “Defining Open AI” community workshop The Open Source Initiative is deep into a multi-stakeholder process to define machine learning systems that can be characterized as “Open Source.”  About 40 people put their heads together for the first community discussion in an hour-long session I led at FOSSY 2023 .  If you missed it, there are still plenty of ways to get involved. Send a proposal to speak at the online webinar series before August 4, 2023 and check out the timeline for upcoming in-person workshops. Get caught up with the recap from the kickoff meeting, too. Why data is the sticking point of machine learning The session started with a short presentation highlighting why we need to define “open” in the AI context and why we need to do it now.  Open Source gives users and developers the ability to decide for themselves how and where to use the technology without the need to engage with a third party. We want to get the same things for machine learning systems. We’ll need to find our way there. First, we need to clarify that machine learning systems are a little different than classic software. For one, machine learning depends on data, lots of it. Developers can’t rely on just their own laptops and knowledge to build new AI systems. The legal landscape is also a lot more complicated than for pure software: Data is covered by a lot of different laws, often very different between countries. After the initial meeting in San Francisco, it became clear that the most crucial question to ask (and try to answer) is around data.  At the Portland session, I asked one simple question:  How tightly coupled should the original data and the ML models be? I started with the three pieces that go into a typical ML system: Software for training and testing, inference and analysis For the crowd it was easy to agree that all software written by a human and copyrightable must be Open Source for a ML system to be considered open. Model architecture with its weights and training parameters These should be made available with terms and conditions that don’t restrict who can use them and how they’re used; There also shouldn’t be restrictions on retraining the artifacts and redistributing them. The group wasn’t as clearly in agreement on this point but did concur that resolving this is within reach. Raw data and prepared datasets, for training and testing I started with the assumption that the original dataset is not the preferred form for making modifications to model/weights and asked the group: Does that mean an “Open ML” can ignore the original data? How much of the original dataset do we need in order to exercise the right to modify a model? This final question required people to get on the same page. Some AI developers in the room shared their views that the original dataset is not necessary to modify a model. They also stated that they would need a sufficiently precise description of the original data, though, and other elements. This would be necessary for technical reasons and for transparency, to evaluate bias, etc. A few people took a different view, leaning more on the fact that data is somewhat equivalent to the source code of a model and the model is the binary, as if training was the equivalent of compilation. Some of their comments gave the impression that they were less familiar with developing ML systems. Other participants explained why the analogy to software’s source-binary doesn’t hold water: A binary-only piece of software cannot be modified and in fact the GNU GPLv3 explains in detail the preferred methods of making modifications to software. On the contrary, AI models can be modified to be fine-tuned and retrained without the original dataset, if they’re accompanied by other elements. During the session, folks were encouraged to contribute their thoughts on an Etherpad . Comments there touch on the cultural implications of public data, the importance of documenting data transparency and whether “open with restrictions” carve outs will be necessary when it comes to personal or health data. What’s next Remember: We want you to weigh in with a proposal to speak and invite you to participate in upcoming community workshops .  For now,  we’ll leave you with this quote from the Portland session:  “I think I’m coming to a position that AI maybe isn’t open without open data or a really good description of the data used (based on the “spigot” example), but that there will be a significant number of use cases that aren’t open, for various cultural reasons e.g. they may use other licenses, defined within those communities, but also aren’t the kind of extractive commercial stuff that invokes puking either. Open isn’t an exclusive synonym for ‘good’.” Participants also debated on the legality of training models on copyrighted and trademarked data, and voiced concerns about the output of generative AI systems.  We have a long road ahead and must move quickly – join us on this important journey. The AI renaissance and why open innovation matters Celebrating 25 years of Open Source at Campus Party Keep up with Open Source Please leave this field empty. Δ We’ll never share your details and you can unsubscribe with a click! Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. 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2026-01-13T08:49:43
https://dev.to/t/odoo/page/4#main-content
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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 # odoo Follow Hide Create Post Older #odoo posts 1 2 3 4 5 6 7 8 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . 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2026-01-13T08:49:43
https://opensource.org/ai/faq#what-kind-of-data-should-be-required-in-the-open-source-ai-definition
OSAID FAQs – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Source AI Open Source AI OSAID 1.0 Process Timeline Open Weights FAQ Endorsements Open Main Menu THE open source ai definition 1.0 We have released the first stable version of the Definition. Read version 1.0 Answers to Frequently Asked Questions The Open Source AI Definition (OSAID) represents an important first step in defining Open Source in an AI context. Because AI systems differ fundamentally from traditional software, the OSAID seeks to establish the first set of clear, practical guidelines for development, use and modification of AI systems in keeping with the Open Source ethos. Unfortunately, misconceptions about the definition persist, often stemming from a lack of understanding of the nature of AI. This post aims to clarify key points and provide a forward-looking perspective on the importance of the OSAID. THE open source ai definition 1.0 FAQs What Is an AI System? What is an Open Source AI? Why did you write the Open Source AI Definition? What’s the difference between the Open Source Definition and the Open Source AI Definition? Isn’t training data required to program the AI system? What is the role of training data in the Open Source AI Definition? Why do you allow the exclusion of some training data? How did you arrive at this conclusion? Is it compromising Open Source ideals? What kind of data should be required in the Open Source AI Definition? How do you fix a buggy AI system? What is a skilled person? Is the Open Source AI Definition covering models and weights and parameters? Why do you require training code while OSD #2 doesn’t require compilers? Why is there no mention of safety and risk limitations in the Open Source AI Definition? Are model parameters copyrightable? Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? Why is the “Preferred form to make modifications” limited to machine learning? Which AI systems comply with the Open Source AI Definition? What’s the next step? FAQs What Is an AI System? According to the OSAID, an AI system aligns with the definition provided by the Organisation for Economic Co-operation and Development (OECD): An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment. In simple terms, an AI system is “the thing” that processes input to produce output, whether that’s a prediction, recommendation, or another result. Anchoring discussions in such common definitions is essential because AI systems differ radically from traditional software. What is an Open Source AI? An Open Source AI is an AI system made freely available with all necessary code, data and parameters under legal terms approved by the Open Source Initiative. For more details, read below. Why did you write the Open Source AI Definition? Point #2 of the Open Source Definition (OSD) says “The program must include source code […] The source code must be the preferred form in which a programmer would modify the program […]” . When we embarked on this initiative, nobody had a clear answer to the question, “What is the preferred form to modify an AI system?” So OSI offered to find the answer along with the broader community by engaging in a co-design process . What’s the difference between the Open Source Definition and the Open Source AI Definition? The Open Source Definition (OSD) refers to software programs. AI and specifically machine learning systems are not simply software programs; they blend boundaries with data, configuration options, documentation and new artifacts, like weights and biases. The Open Source AI Definition describes the preferred form to modify an AI system, providing clarity on interpreting the principles of the OSD in the domain of AI. Isn’t training data required to program the AI system? A frequent misunderstanding about AI systems is equating training data with source code, suggesting that “training data is how the model gets programmed.” Unlike traditional software, AI systems are not programmed in the conventional sense. Instead, they acquire capabilities autonomously during the training process — a phenomenon distinguishing them from software like the Linux kernel. For example, the Linux kernel is: Programmed by humans. Composed of source code that developers can read, study, and modify. Reproducible, meaning its binary form can be reliably rebuilt from its source code. In contrast, modern AI systems such as large language models develop their behavior in ways that are often unpredictable and inexplicable. Training processes are challenging to replicate reliably, even by the system’s creators. These differences necessitated the establishment of a unique definition beyond the Open Source Definition for software. What is the role of training data in the Open Source AI Definition? Open Source means giving anyone the ability to meaningfully fork (study and modify) your system without requiring additional permissions to make it more useful for themselves and everyone else. This is why point #2 of the OSD requires that the source code be provided in the preferred form for making modifications. This way, everyone has the same rights and ability to fork as the original developers, starting a virtuous innovation cycle. However, training data does not equate to a software source code. Training data is important for studying modern machine learning systems. However, it is not what AI researchers and practitioners necessarily use as part of the preferred form for modifying a trained model. The Data Information and Code requirements of the OSAID allow Open Source AI systems to be forked by third-party AI builders downstream using the same information as the original developers. These forks could include removing nonpublic or non-open data from the training dataset in order to train a new Open Source AI system on fully public or open data. Why do you allow the exclusion of some training data? We want Open Source AI to exist in fields where data cannot be legally shared, such as medical AI. Laws that permit training on data often limit the resharing of that same data to protect copyright or other interests. Privacy rules also give people the right to control their most sensitive information, like decisions about their health. Similarly, much of the world’s Indigenous knowledge is protected through mechanisms that are not compatible with later-developed frameworks for rights exclusivity and sharing. There are also many cases where terms of use of publicly available data may give entity A the confidence that they may use it freely and call it “open data,” but not give entity A the confidence they can, in turn, give entity B the same guarantees for use in a different jurisdiction. Meanwhile, entity B may not feel confident using that data in their own jurisdiction. An example is so-called public domain data, where the definition of public domain varies from country to country. Another example is fair-use or private data, where the finding of fair use or privacy laws may require a good knowledge of the law of a given jurisdiction. This resharing is not so much limited as lacking legal certainty . How did you arrive at this conclusion? Is it compromising Open Source ideals? During our co-design process, relationships between the weights and the data drove the highest community engagement. In the “System analysis” phase , the volunteer groups suggested that training and data processing codes were more important for modifying the AI system than accessing the training and testing data. That result was validated in the “Validation phase” and suggested a path that allows Open Source AI to exist on equal grounds with proprietary systems: both can train on the same kind of data. Some people believe that full, unfettered access to all training data (with no distinction of its kind) is paramount, arguing that anything less would compromise the full reproducibility of AI systems, transparency and security. This approach would relegate Open Source AI to a niche of AI trainable only on open data. That niche would be tiny, even relative to the niche occupied by Open Source in the traditional software ecosystem. The requirements of Data Information keep the same approach present in the Open Source Definition; it doesn’t mandate full reproducibility and transparency but enables them (i.e., reproducible builds ). At the same time, setting a baseline requiring Data Information doesn’t preclude others from formulating and demanding more requirements, like the Digital Public Goods Standard or the Free Systems Distribution Guidelines , which add requirements to the Open Source Definition. One of the key aspects of OSI’s mission is to drive and promote Open Source innovation. The approach OSI takes here enables complete user choice with Open Source AI. Users can keep the insights derived from training+data preprocessing code and a description of unshareable training data and build upon those with their own unshareable data and give the insights derived from further training to everyone, allowing for Open Source AI in areas like health care. Alternatively, users can obtain the available and public data from the Data Information and retrain their model without any unshareable data, resulting in more data transparency in the AI system. Like copyleft and permissive licensing, this approach leaves the choice with the user. What kind of data should be required in the Open Source AI Definition? A significant challenge in AI is the role of data. Unlike traditional software, where source code is the primary artifact, AI systems depend heavily on data — not just any data, but data processed and curated into training datasets. The OSAID recognizes the legal and ethical complexities of data sharing and uses precise legal terms to outline expectations. While not all raw data can be freely distributed, the Definition ensures that the essential elements for modifying an AI system are accessible. There are four classes of data, based on their legal constraints, all of which can be used to train Open Source AI systems: Open training data: data that can be copied, preserved, modified and reshared. It provides the best way to enable users to study the system. This must be shared. Public training data: data that others can inspect as long as it remains available. This also enables users to study the work. However, this data can degrade as links or references are lost or removed from network availability. To obviate this, different communities will have to work together to define standards, procedures, tools and governance models to overcome this risk, and Data Information is required in case the data becomes later unavailable. This must be disclosed with full details on where to obtain it. Obtainable training data is data that can be obtained, including for a fee. This information provides transparency and is similar to a purchasable component in an open hardware system. The Data Information provides a means of understanding this data other than obtaining or purchasing it. This area is likely to change rapidly and will need careful monitoring to protect Open Source AI developers. It must be disclosed with full details on where to obtain it. Unshareable nonpublic training data: data that cannot be shared for explainable reasons, like Personally Identifiable Information (PII). For this class of data, the ability to study some of the system’s biases demands a detailed description of the data – what it is, how it was collected, its characteristics, and so on – so that users can understand the biases and categorization underlying the system. This must be revealed in detail so that, for example, a hospital can create a dataset with identical structure using its own patient data. OSI believes that all these classes of data can be part of the preferred form of making modifications to the AI system. This approach both advances openness in all the components of the AI system and drives more Open Source AI, including private-first areas such as health care. How do you fix a buggy AI system? A core question the OSAID addresses is: How do you fix a buggy AI system? For traditional software, the Open Source Definition provides a clear answer: The program must include source code, and must allow distribution in source code as well as compiled form. The source code must be the preferred form in which a programmer would modify the program. However, modifying an AI system requires more than just source code. After extensive consultation with AI developers, researchers and practitioners, the community, through the OSAID co-design process, concluded that the preferred form for modifying an AI system includes: The software used to create the dataset (i.e., to transform raw data into tokens). The software used to train the system. The results of the training (i.e., the parameters). All legally shareable data used in the training process. These components collectively enable the study, use, modification and sharing of AI systems in a manner consistent with Open Source principles. What is a skilled person? In legal circles, Skilled Person means any person having the current knowledge, experience and competence to perform a certain duty. This Wikipedia entry provides more details. Is the Open Source AI Definition covering models and weights and parameters? Yes. The Open Source AI Definition makes no distinction between what might be called AI system, model, or weights and parameters. Whether the offering is characterized as an AI system, a model, or weights and parameters, to be called Open Source AI, the requirements for providing the preferred form for making modifications will be the same. If you are interested in learning more about Open Weights, please read this article. Why do you require training code while OSD #2 doesn’t require compilers? AI and software are radically different domains, and drawing comparisons between them is rarely productive. OSD point #2 doesn’t mandate that Open Source software uses only compilers released with an OSI-Approved License because compilers are standardized, de jure (like ANSI C) or de facto like TurboPascal or Python. It was generally accepted that to develop more Open Source software one could use a proprietary development environment. For machine learning, the training code is not standardized, and therefore it must be part of the preferred form of making modifications to preserve the right to fork an AI system. Why is there no mention of safety and risk limitations in the Open Source AI Definition? The Open Source AI Definition does not specifically guide or enforce ethical, trustworthy, or responsible AI development practices. However, it does not put up any barriers that would prevent developers from adhering to such principles if they chose to. The efforts to discuss the responsible development, deployment and use of AI systems, including through appropriate government regulation, are a separate conversation. A good starting point is OECD’s Recommendation of the Council on Artificial Intelligence, Section 1: Principles for responsible stewardship of trustworthy AI . Are model parameters copyrightable? The Open Source AI Definition does not take a stance on the legal nature of Parameters. They may be free by nature, or a license or other legal instrument may be required to ensure their freedom. Whether model parameters are copyrightable will become clearer over time as the legal system has more opportunities to address this issue. In any case, we require an explicit assertion accompanying the distribution of Parameters that assures that they are freely available to all. Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? We used the word “terms” instead of “license” for models because, as mentioned above, we do not yet know what the legal mechanism will be to assure that the models are available to use, study, modify and share. We used “terms” to avoid suggesting that a “license” is the only legal mechanism that could be used. That said, to be approved by the OSI, the terms for parameters must assure the freedom to use, study, modify and share. Why is the “Preferred form to make modifications” limited to machine learning? The principles stated in the Open Source AI Definition are generally applicable to any kind of AI, but machine learning challenges the Open Source Definition. For machine learning, a set of artifacts (components) is required to study and modify the system, thus requiring a new explanation of what is necessary to study and modify the system. Which AI systems comply with the Open Source AI Definition? As part of our validation and testing of the OSAID, the volunteers checked whether the Definition could be used to evaluate if AI systems provided the freedoms expected. The list of models that passed the Validation phase are: Pythia (Eleuther AI), OLMo (AI2), Amber and CrystalCoder (LLM360), and T5 (Google). A few others that were analyzed would probably pass if they changed their licenses/legal terms, for example, BLOOM (BigScience), Starcoder2 (BigCode), and Falcon (TII). Those that have been analyzed and don’t pass because they lack required components and/or their legal agreements are incompatible with the Open Source principles include Llama2 (Meta), Grok (X/Twitter), Phi-2 (Microsoft), and Mixtral (Mistral). These results should be seen as part of the definitional process, a learning moment; they are not certifications of any kind. OSI will continue to validate only legal documents and will not validate or review individual AI systems, just as it does not validate or review software projects. What’s the next step? The Open Source AI Definition reflects a thoughtful and inclusive process endorsed by leading AI developers, researchers and practitioners. It culminates in a first step represented in version 1.0 of the OSAID. The definition acknowledges that AI fundamentally differs from software and requires a tailored approach. Misunderstandings about the OSAID often arise from attempts to apply software engineering paradigms to AI, leading to confusion. By embracing the unique characteristics of AI systems, the OSAID offers a robust framework for fostering transparency, innovation and collaboration in AI development. As we navigate AI’s evolving landscape, it is crucial to engage thoughtfully and constructively with these definitions. By doing so, we can ensure that AI systems remain open, accessible and aligned with the principles of the broader Open Source movement. Our work is only possible thanks to our members. Join us today! Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. 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2026-01-13T08:49:43
https://opensource.org/ai/townhalls
Open Source AI Town Halls – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu Home Open Source AI Open Source AI Town Halls THE open source ai definition 1.0 We have released the first stable version of the Definition. Read version 1.0 Public Town Halls Our Executive Director, Stefano Maffulli hosted a series of public Town Halls to share process updates and have an open discussion with participants. These sessions were held between January and October 2024. Watch the recordings Oct 18, 2024 Aug 23 Apr 5 Oct 11 Jul 26 Mar 22 Oct 4 Jun 28 Mar 8 Sep 27 Jun 14 Feb 23 Sep 20 May 31 Feb 9 Sep 13 May 3 Jan 26 Sep 6 Apr 19 Jan 12, 2024 Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions. Functional Functional Always active The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. Preferences Preferences The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user. Statistics Statistics The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you. Marketing Marketing The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes. Manage options Manage services Manage {vendor_count} vendors Read more about these purposes Accept Deny View preferences Save preferences View preferences {title} {title} {title} Manage consent
2026-01-13T08:49:43
https://www.algolia.com/de/industries/grocery/
Lebensmittelhandel Niket --> Deutsch English français News DevCon2025 | October 1-2 Learn more Unternehmen Partners Einloggen Login Logout Algolia mark white Algolia logo white Lösungen 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. Agent Studio Create, test, and deploy AI agents, fast. 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We got you covered! Brand guidelines Download logo pack Your browser does not support the video tag. Lebensmittelhandel Intelligente Lösung für den Lebensmittelhandel Eine Suche, die die einzigartigen Vorlieben beim Lebensmitteleinkauf versteht Demo anforden Führende Lebensmittelhändler, die Algolia nutzen „Eine außergewöhnliche Suchgeschwindigkeit und -performance sind dank Algolia zur Selbstverständlichkeit geworden. Doch für uns ist Algolia weit mehr als nur Suche. Durch den Einsatz der fortschrittlichen Funktionen von Algolia konnten wir die Ergebnisse für unsere Kunden verbessern, den Umsatz steigern und unseren Fokus darauf legen, ein herausragendes Erlebnis zu bieten.“ Leiter Digital Commerce H-E-B México Lesen Sie das Zeugnis „Der große Vorteil von Algolia ist, dass wir mit einer einfachen Implementierung und einfachen Daten sehr gute Ergebnisse erzielt haben. Das dynamische Re-Ranking war dabei ein wesentlicher Faktor. 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Der Erfolg hängt jedoch davon ab, wie Händler Daten, Design und Technologie einsetzen, um sowohl Kundinnen und Kunden als auch Marken optimal zu bedienen. In unserem neuesten Bericht haben wir Führungskräfte gefragt, wie sie in Retail-Media-Netzwerke investieren möchten. 76% Gesponserte Listings auf Suchergebnisseiten sind die wichtigste Retail-Media-Strategie. 30% Eine bessere Zielgruppenansprache ist das wichtigste Ziel für gesponserte Listings auf Suchergebnisseiten. 11% der Retail-Media-Käufer nutzen mehrere Retail-Media-Plattformen. Bericht herunterladen Empfohlene Inhalte AI-powered Solutions for Smarter Grocery Shopping Online grocery shopping is exploding, driven by the next generation of shoppers' buying habits. To compete, grocers need AI-driven, experiences that are easy, convenient, and tailored to each individual shopper's preferences. 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2026-01-13T08:49:43
https://opensource.org/ai/faq#how-do-you-fix-a-buggy-ai-system
OSAID FAQs – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Source AI Open Source AI OSAID 1.0 Process Timeline Open Weights FAQ Endorsements Open Main Menu THE open source ai definition 1.0 We have released the first stable version of the Definition. Read version 1.0 Answers to Frequently Asked Questions The Open Source AI Definition (OSAID) represents an important first step in defining Open Source in an AI context. Because AI systems differ fundamentally from traditional software, the OSAID seeks to establish the first set of clear, practical guidelines for development, use and modification of AI systems in keeping with the Open Source ethos. Unfortunately, misconceptions about the definition persist, often stemming from a lack of understanding of the nature of AI. This post aims to clarify key points and provide a forward-looking perspective on the importance of the OSAID. THE open source ai definition 1.0 FAQs What Is an AI System? What is an Open Source AI? Why did you write the Open Source AI Definition? What’s the difference between the Open Source Definition and the Open Source AI Definition? Isn’t training data required to program the AI system? What is the role of training data in the Open Source AI Definition? Why do you allow the exclusion of some training data? How did you arrive at this conclusion? Is it compromising Open Source ideals? What kind of data should be required in the Open Source AI Definition? How do you fix a buggy AI system? What is a skilled person? Is the Open Source AI Definition covering models and weights and parameters? Why do you require training code while OSD #2 doesn’t require compilers? Why is there no mention of safety and risk limitations in the Open Source AI Definition? Are model parameters copyrightable? Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? Why is the “Preferred form to make modifications” limited to machine learning? Which AI systems comply with the Open Source AI Definition? What’s the next step? FAQs What Is an AI System? According to the OSAID, an AI system aligns with the definition provided by the Organisation for Economic Co-operation and Development (OECD): An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment. In simple terms, an AI system is “the thing” that processes input to produce output, whether that’s a prediction, recommendation, or another result. Anchoring discussions in such common definitions is essential because AI systems differ radically from traditional software. What is an Open Source AI? An Open Source AI is an AI system made freely available with all necessary code, data and parameters under legal terms approved by the Open Source Initiative. For more details, read below. Why did you write the Open Source AI Definition? Point #2 of the Open Source Definition (OSD) says “The program must include source code […] The source code must be the preferred form in which a programmer would modify the program […]” . When we embarked on this initiative, nobody had a clear answer to the question, “What is the preferred form to modify an AI system?” So OSI offered to find the answer along with the broader community by engaging in a co-design process . What’s the difference between the Open Source Definition and the Open Source AI Definition? The Open Source Definition (OSD) refers to software programs. AI and specifically machine learning systems are not simply software programs; they blend boundaries with data, configuration options, documentation and new artifacts, like weights and biases. The Open Source AI Definition describes the preferred form to modify an AI system, providing clarity on interpreting the principles of the OSD in the domain of AI. Isn’t training data required to program the AI system? A frequent misunderstanding about AI systems is equating training data with source code, suggesting that “training data is how the model gets programmed.” Unlike traditional software, AI systems are not programmed in the conventional sense. Instead, they acquire capabilities autonomously during the training process — a phenomenon distinguishing them from software like the Linux kernel. For example, the Linux kernel is: Programmed by humans. Composed of source code that developers can read, study, and modify. Reproducible, meaning its binary form can be reliably rebuilt from its source code. In contrast, modern AI systems such as large language models develop their behavior in ways that are often unpredictable and inexplicable. Training processes are challenging to replicate reliably, even by the system’s creators. These differences necessitated the establishment of a unique definition beyond the Open Source Definition for software. What is the role of training data in the Open Source AI Definition? Open Source means giving anyone the ability to meaningfully fork (study and modify) your system without requiring additional permissions to make it more useful for themselves and everyone else. This is why point #2 of the OSD requires that the source code be provided in the preferred form for making modifications. This way, everyone has the same rights and ability to fork as the original developers, starting a virtuous innovation cycle. However, training data does not equate to a software source code. Training data is important for studying modern machine learning systems. However, it is not what AI researchers and practitioners necessarily use as part of the preferred form for modifying a trained model. The Data Information and Code requirements of the OSAID allow Open Source AI systems to be forked by third-party AI builders downstream using the same information as the original developers. These forks could include removing nonpublic or non-open data from the training dataset in order to train a new Open Source AI system on fully public or open data. Why do you allow the exclusion of some training data? We want Open Source AI to exist in fields where data cannot be legally shared, such as medical AI. Laws that permit training on data often limit the resharing of that same data to protect copyright or other interests. Privacy rules also give people the right to control their most sensitive information, like decisions about their health. Similarly, much of the world’s Indigenous knowledge is protected through mechanisms that are not compatible with later-developed frameworks for rights exclusivity and sharing. There are also many cases where terms of use of publicly available data may give entity A the confidence that they may use it freely and call it “open data,” but not give entity A the confidence they can, in turn, give entity B the same guarantees for use in a different jurisdiction. Meanwhile, entity B may not feel confident using that data in their own jurisdiction. An example is so-called public domain data, where the definition of public domain varies from country to country. Another example is fair-use or private data, where the finding of fair use or privacy laws may require a good knowledge of the law of a given jurisdiction. This resharing is not so much limited as lacking legal certainty . How did you arrive at this conclusion? Is it compromising Open Source ideals? During our co-design process, relationships between the weights and the data drove the highest community engagement. In the “System analysis” phase , the volunteer groups suggested that training and data processing codes were more important for modifying the AI system than accessing the training and testing data. That result was validated in the “Validation phase” and suggested a path that allows Open Source AI to exist on equal grounds with proprietary systems: both can train on the same kind of data. Some people believe that full, unfettered access to all training data (with no distinction of its kind) is paramount, arguing that anything less would compromise the full reproducibility of AI systems, transparency and security. This approach would relegate Open Source AI to a niche of AI trainable only on open data. That niche would be tiny, even relative to the niche occupied by Open Source in the traditional software ecosystem. The requirements of Data Information keep the same approach present in the Open Source Definition; it doesn’t mandate full reproducibility and transparency but enables them (i.e., reproducible builds ). At the same time, setting a baseline requiring Data Information doesn’t preclude others from formulating and demanding more requirements, like the Digital Public Goods Standard or the Free Systems Distribution Guidelines , which add requirements to the Open Source Definition. One of the key aspects of OSI’s mission is to drive and promote Open Source innovation. The approach OSI takes here enables complete user choice with Open Source AI. Users can keep the insights derived from training+data preprocessing code and a description of unshareable training data and build upon those with their own unshareable data and give the insights derived from further training to everyone, allowing for Open Source AI in areas like health care. Alternatively, users can obtain the available and public data from the Data Information and retrain their model without any unshareable data, resulting in more data transparency in the AI system. Like copyleft and permissive licensing, this approach leaves the choice with the user. What kind of data should be required in the Open Source AI Definition? A significant challenge in AI is the role of data. Unlike traditional software, where source code is the primary artifact, AI systems depend heavily on data — not just any data, but data processed and curated into training datasets. The OSAID recognizes the legal and ethical complexities of data sharing and uses precise legal terms to outline expectations. While not all raw data can be freely distributed, the Definition ensures that the essential elements for modifying an AI system are accessible. There are four classes of data, based on their legal constraints, all of which can be used to train Open Source AI systems: Open training data: data that can be copied, preserved, modified and reshared. It provides the best way to enable users to study the system. This must be shared. Public training data: data that others can inspect as long as it remains available. This also enables users to study the work. However, this data can degrade as links or references are lost or removed from network availability. To obviate this, different communities will have to work together to define standards, procedures, tools and governance models to overcome this risk, and Data Information is required in case the data becomes later unavailable. This must be disclosed with full details on where to obtain it. Obtainable training data is data that can be obtained, including for a fee. This information provides transparency and is similar to a purchasable component in an open hardware system. The Data Information provides a means of understanding this data other than obtaining or purchasing it. This area is likely to change rapidly and will need careful monitoring to protect Open Source AI developers. It must be disclosed with full details on where to obtain it. Unshareable nonpublic training data: data that cannot be shared for explainable reasons, like Personally Identifiable Information (PII). For this class of data, the ability to study some of the system’s biases demands a detailed description of the data – what it is, how it was collected, its characteristics, and so on – so that users can understand the biases and categorization underlying the system. This must be revealed in detail so that, for example, a hospital can create a dataset with identical structure using its own patient data. OSI believes that all these classes of data can be part of the preferred form of making modifications to the AI system. This approach both advances openness in all the components of the AI system and drives more Open Source AI, including private-first areas such as health care. How do you fix a buggy AI system? A core question the OSAID addresses is: How do you fix a buggy AI system? For traditional software, the Open Source Definition provides a clear answer: The program must include source code, and must allow distribution in source code as well as compiled form. The source code must be the preferred form in which a programmer would modify the program. However, modifying an AI system requires more than just source code. After extensive consultation with AI developers, researchers and practitioners, the community, through the OSAID co-design process, concluded that the preferred form for modifying an AI system includes: The software used to create the dataset (i.e., to transform raw data into tokens). The software used to train the system. The results of the training (i.e., the parameters). All legally shareable data used in the training process. These components collectively enable the study, use, modification and sharing of AI systems in a manner consistent with Open Source principles. What is a skilled person? In legal circles, Skilled Person means any person having the current knowledge, experience and competence to perform a certain duty. This Wikipedia entry provides more details. Is the Open Source AI Definition covering models and weights and parameters? Yes. The Open Source AI Definition makes no distinction between what might be called AI system, model, or weights and parameters. Whether the offering is characterized as an AI system, a model, or weights and parameters, to be called Open Source AI, the requirements for providing the preferred form for making modifications will be the same. If you are interested in learning more about Open Weights, please read this article. Why do you require training code while OSD #2 doesn’t require compilers? AI and software are radically different domains, and drawing comparisons between them is rarely productive. OSD point #2 doesn’t mandate that Open Source software uses only compilers released with an OSI-Approved License because compilers are standardized, de jure (like ANSI C) or de facto like TurboPascal or Python. It was generally accepted that to develop more Open Source software one could use a proprietary development environment. For machine learning, the training code is not standardized, and therefore it must be part of the preferred form of making modifications to preserve the right to fork an AI system. Why is there no mention of safety and risk limitations in the Open Source AI Definition? The Open Source AI Definition does not specifically guide or enforce ethical, trustworthy, or responsible AI development practices. However, it does not put up any barriers that would prevent developers from adhering to such principles if they chose to. The efforts to discuss the responsible development, deployment and use of AI systems, including through appropriate government regulation, are a separate conversation. A good starting point is OECD’s Recommendation of the Council on Artificial Intelligence, Section 1: Principles for responsible stewardship of trustworthy AI . Are model parameters copyrightable? The Open Source AI Definition does not take a stance on the legal nature of Parameters. They may be free by nature, or a license or other legal instrument may be required to ensure their freedom. Whether model parameters are copyrightable will become clearer over time as the legal system has more opportunities to address this issue. In any case, we require an explicit assertion accompanying the distribution of Parameters that assures that they are freely available to all. Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? We used the word “terms” instead of “license” for models because, as mentioned above, we do not yet know what the legal mechanism will be to assure that the models are available to use, study, modify and share. We used “terms” to avoid suggesting that a “license” is the only legal mechanism that could be used. That said, to be approved by the OSI, the terms for parameters must assure the freedom to use, study, modify and share. Why is the “Preferred form to make modifications” limited to machine learning? The principles stated in the Open Source AI Definition are generally applicable to any kind of AI, but machine learning challenges the Open Source Definition. For machine learning, a set of artifacts (components) is required to study and modify the system, thus requiring a new explanation of what is necessary to study and modify the system. Which AI systems comply with the Open Source AI Definition? As part of our validation and testing of the OSAID, the volunteers checked whether the Definition could be used to evaluate if AI systems provided the freedoms expected. The list of models that passed the Validation phase are: Pythia (Eleuther AI), OLMo (AI2), Amber and CrystalCoder (LLM360), and T5 (Google). A few others that were analyzed would probably pass if they changed their licenses/legal terms, for example, BLOOM (BigScience), Starcoder2 (BigCode), and Falcon (TII). Those that have been analyzed and don’t pass because they lack required components and/or their legal agreements are incompatible with the Open Source principles include Llama2 (Meta), Grok (X/Twitter), Phi-2 (Microsoft), and Mixtral (Mistral). These results should be seen as part of the definitional process, a learning moment; they are not certifications of any kind. OSI will continue to validate only legal documents and will not validate or review individual AI systems, just as it does not validate or review software projects. What’s the next step? The Open Source AI Definition reflects a thoughtful and inclusive process endorsed by leading AI developers, researchers and practitioners. It culminates in a first step represented in version 1.0 of the OSAID. The definition acknowledges that AI fundamentally differs from software and requires a tailored approach. Misunderstandings about the OSAID often arise from attempts to apply software engineering paradigms to AI, leading to confusion. By embracing the unique characteristics of AI systems, the OSAID offers a robust framework for fostering transparency, innovation and collaboration in AI development. As we navigate AI’s evolving landscape, it is crucial to engage thoughtfully and constructively with these definitions. By doing so, we can ensure that AI systems remain open, accessible and aligned with the principles of the broader Open Source movement. Our work is only possible thanks to our members. Join us today! Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions. Functional Functional Always active The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. Preferences Preferences The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user. Statistics Statistics The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you. Marketing Marketing The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes. Manage options Manage services Manage {vendor_count} vendors Read more about these purposes Accept Deny View preferences Save preferences View preferences {title} {title} {title} Manage consent
2026-01-13T08:49:43
https://opensource.org/ai/faq#why-do-you-allow-the-exclusion-of-some-training-data
OSAID FAQs – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Source AI Open Source AI OSAID 1.0 Process Timeline Open Weights FAQ Endorsements Open Main Menu THE open source ai definition 1.0 We have released the first stable version of the Definition. Read version 1.0 Answers to Frequently Asked Questions The Open Source AI Definition (OSAID) represents an important first step in defining Open Source in an AI context. Because AI systems differ fundamentally from traditional software, the OSAID seeks to establish the first set of clear, practical guidelines for development, use and modification of AI systems in keeping with the Open Source ethos. Unfortunately, misconceptions about the definition persist, often stemming from a lack of understanding of the nature of AI. This post aims to clarify key points and provide a forward-looking perspective on the importance of the OSAID. THE open source ai definition 1.0 FAQs What Is an AI System? What is an Open Source AI? Why did you write the Open Source AI Definition? What’s the difference between the Open Source Definition and the Open Source AI Definition? Isn’t training data required to program the AI system? What is the role of training data in the Open Source AI Definition? Why do you allow the exclusion of some training data? How did you arrive at this conclusion? Is it compromising Open Source ideals? What kind of data should be required in the Open Source AI Definition? How do you fix a buggy AI system? What is a skilled person? Is the Open Source AI Definition covering models and weights and parameters? Why do you require training code while OSD #2 doesn’t require compilers? Why is there no mention of safety and risk limitations in the Open Source AI Definition? Are model parameters copyrightable? Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? Why is the “Preferred form to make modifications” limited to machine learning? Which AI systems comply with the Open Source AI Definition? What’s the next step? FAQs What Is an AI System? According to the OSAID, an AI system aligns with the definition provided by the Organisation for Economic Co-operation and Development (OECD): An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment. In simple terms, an AI system is “the thing” that processes input to produce output, whether that’s a prediction, recommendation, or another result. Anchoring discussions in such common definitions is essential because AI systems differ radically from traditional software. What is an Open Source AI? An Open Source AI is an AI system made freely available with all necessary code, data and parameters under legal terms approved by the Open Source Initiative. For more details, read below. Why did you write the Open Source AI Definition? Point #2 of the Open Source Definition (OSD) says “The program must include source code […] The source code must be the preferred form in which a programmer would modify the program […]” . When we embarked on this initiative, nobody had a clear answer to the question, “What is the preferred form to modify an AI system?” So OSI offered to find the answer along with the broader community by engaging in a co-design process . What’s the difference between the Open Source Definition and the Open Source AI Definition? The Open Source Definition (OSD) refers to software programs. AI and specifically machine learning systems are not simply software programs; they blend boundaries with data, configuration options, documentation and new artifacts, like weights and biases. The Open Source AI Definition describes the preferred form to modify an AI system, providing clarity on interpreting the principles of the OSD in the domain of AI. Isn’t training data required to program the AI system? A frequent misunderstanding about AI systems is equating training data with source code, suggesting that “training data is how the model gets programmed.” Unlike traditional software, AI systems are not programmed in the conventional sense. Instead, they acquire capabilities autonomously during the training process — a phenomenon distinguishing them from software like the Linux kernel. For example, the Linux kernel is: Programmed by humans. Composed of source code that developers can read, study, and modify. Reproducible, meaning its binary form can be reliably rebuilt from its source code. In contrast, modern AI systems such as large language models develop their behavior in ways that are often unpredictable and inexplicable. Training processes are challenging to replicate reliably, even by the system’s creators. These differences necessitated the establishment of a unique definition beyond the Open Source Definition for software. What is the role of training data in the Open Source AI Definition? Open Source means giving anyone the ability to meaningfully fork (study and modify) your system without requiring additional permissions to make it more useful for themselves and everyone else. This is why point #2 of the OSD requires that the source code be provided in the preferred form for making modifications. This way, everyone has the same rights and ability to fork as the original developers, starting a virtuous innovation cycle. However, training data does not equate to a software source code. Training data is important for studying modern machine learning systems. However, it is not what AI researchers and practitioners necessarily use as part of the preferred form for modifying a trained model. The Data Information and Code requirements of the OSAID allow Open Source AI systems to be forked by third-party AI builders downstream using the same information as the original developers. These forks could include removing nonpublic or non-open data from the training dataset in order to train a new Open Source AI system on fully public or open data. Why do you allow the exclusion of some training data? We want Open Source AI to exist in fields where data cannot be legally shared, such as medical AI. Laws that permit training on data often limit the resharing of that same data to protect copyright or other interests. Privacy rules also give people the right to control their most sensitive information, like decisions about their health. Similarly, much of the world’s Indigenous knowledge is protected through mechanisms that are not compatible with later-developed frameworks for rights exclusivity and sharing. There are also many cases where terms of use of publicly available data may give entity A the confidence that they may use it freely and call it “open data,” but not give entity A the confidence they can, in turn, give entity B the same guarantees for use in a different jurisdiction. Meanwhile, entity B may not feel confident using that data in their own jurisdiction. An example is so-called public domain data, where the definition of public domain varies from country to country. Another example is fair-use or private data, where the finding of fair use or privacy laws may require a good knowledge of the law of a given jurisdiction. This resharing is not so much limited as lacking legal certainty . How did you arrive at this conclusion? Is it compromising Open Source ideals? During our co-design process, relationships between the weights and the data drove the highest community engagement. In the “System analysis” phase , the volunteer groups suggested that training and data processing codes were more important for modifying the AI system than accessing the training and testing data. That result was validated in the “Validation phase” and suggested a path that allows Open Source AI to exist on equal grounds with proprietary systems: both can train on the same kind of data. Some people believe that full, unfettered access to all training data (with no distinction of its kind) is paramount, arguing that anything less would compromise the full reproducibility of AI systems, transparency and security. This approach would relegate Open Source AI to a niche of AI trainable only on open data. That niche would be tiny, even relative to the niche occupied by Open Source in the traditional software ecosystem. The requirements of Data Information keep the same approach present in the Open Source Definition; it doesn’t mandate full reproducibility and transparency but enables them (i.e., reproducible builds ). At the same time, setting a baseline requiring Data Information doesn’t preclude others from formulating and demanding more requirements, like the Digital Public Goods Standard or the Free Systems Distribution Guidelines , which add requirements to the Open Source Definition. One of the key aspects of OSI’s mission is to drive and promote Open Source innovation. The approach OSI takes here enables complete user choice with Open Source AI. Users can keep the insights derived from training+data preprocessing code and a description of unshareable training data and build upon those with their own unshareable data and give the insights derived from further training to everyone, allowing for Open Source AI in areas like health care. Alternatively, users can obtain the available and public data from the Data Information and retrain their model without any unshareable data, resulting in more data transparency in the AI system. Like copyleft and permissive licensing, this approach leaves the choice with the user. What kind of data should be required in the Open Source AI Definition? A significant challenge in AI is the role of data. Unlike traditional software, where source code is the primary artifact, AI systems depend heavily on data — not just any data, but data processed and curated into training datasets. The OSAID recognizes the legal and ethical complexities of data sharing and uses precise legal terms to outline expectations. While not all raw data can be freely distributed, the Definition ensures that the essential elements for modifying an AI system are accessible. There are four classes of data, based on their legal constraints, all of which can be used to train Open Source AI systems: Open training data: data that can be copied, preserved, modified and reshared. It provides the best way to enable users to study the system. This must be shared. Public training data: data that others can inspect as long as it remains available. This also enables users to study the work. However, this data can degrade as links or references are lost or removed from network availability. To obviate this, different communities will have to work together to define standards, procedures, tools and governance models to overcome this risk, and Data Information is required in case the data becomes later unavailable. This must be disclosed with full details on where to obtain it. Obtainable training data is data that can be obtained, including for a fee. This information provides transparency and is similar to a purchasable component in an open hardware system. The Data Information provides a means of understanding this data other than obtaining or purchasing it. This area is likely to change rapidly and will need careful monitoring to protect Open Source AI developers. It must be disclosed with full details on where to obtain it. Unshareable nonpublic training data: data that cannot be shared for explainable reasons, like Personally Identifiable Information (PII). For this class of data, the ability to study some of the system’s biases demands a detailed description of the data – what it is, how it was collected, its characteristics, and so on – so that users can understand the biases and categorization underlying the system. This must be revealed in detail so that, for example, a hospital can create a dataset with identical structure using its own patient data. OSI believes that all these classes of data can be part of the preferred form of making modifications to the AI system. This approach both advances openness in all the components of the AI system and drives more Open Source AI, including private-first areas such as health care. How do you fix a buggy AI system? A core question the OSAID addresses is: How do you fix a buggy AI system? For traditional software, the Open Source Definition provides a clear answer: The program must include source code, and must allow distribution in source code as well as compiled form. The source code must be the preferred form in which a programmer would modify the program. However, modifying an AI system requires more than just source code. After extensive consultation with AI developers, researchers and practitioners, the community, through the OSAID co-design process, concluded that the preferred form for modifying an AI system includes: The software used to create the dataset (i.e., to transform raw data into tokens). The software used to train the system. The results of the training (i.e., the parameters). All legally shareable data used in the training process. These components collectively enable the study, use, modification and sharing of AI systems in a manner consistent with Open Source principles. What is a skilled person? In legal circles, Skilled Person means any person having the current knowledge, experience and competence to perform a certain duty. This Wikipedia entry provides more details. Is the Open Source AI Definition covering models and weights and parameters? Yes. The Open Source AI Definition makes no distinction between what might be called AI system, model, or weights and parameters. Whether the offering is characterized as an AI system, a model, or weights and parameters, to be called Open Source AI, the requirements for providing the preferred form for making modifications will be the same. If you are interested in learning more about Open Weights, please read this article. Why do you require training code while OSD #2 doesn’t require compilers? AI and software are radically different domains, and drawing comparisons between them is rarely productive. OSD point #2 doesn’t mandate that Open Source software uses only compilers released with an OSI-Approved License because compilers are standardized, de jure (like ANSI C) or de facto like TurboPascal or Python. It was generally accepted that to develop more Open Source software one could use a proprietary development environment. For machine learning, the training code is not standardized, and therefore it must be part of the preferred form of making modifications to preserve the right to fork an AI system. Why is there no mention of safety and risk limitations in the Open Source AI Definition? The Open Source AI Definition does not specifically guide or enforce ethical, trustworthy, or responsible AI development practices. However, it does not put up any barriers that would prevent developers from adhering to such principles if they chose to. The efforts to discuss the responsible development, deployment and use of AI systems, including through appropriate government regulation, are a separate conversation. A good starting point is OECD’s Recommendation of the Council on Artificial Intelligence, Section 1: Principles for responsible stewardship of trustworthy AI . Are model parameters copyrightable? The Open Source AI Definition does not take a stance on the legal nature of Parameters. They may be free by nature, or a license or other legal instrument may be required to ensure their freedom. Whether model parameters are copyrightable will become clearer over time as the legal system has more opportunities to address this issue. In any case, we require an explicit assertion accompanying the distribution of Parameters that assures that they are freely available to all. Why will parameters be available under “OSI-approved terms” but the code will be under “OSI-approved licenses”? Are you going to allow restrictions on the terms for models? We used the word “terms” instead of “license” for models because, as mentioned above, we do not yet know what the legal mechanism will be to assure that the models are available to use, study, modify and share. We used “terms” to avoid suggesting that a “license” is the only legal mechanism that could be used. That said, to be approved by the OSI, the terms for parameters must assure the freedom to use, study, modify and share. Why is the “Preferred form to make modifications” limited to machine learning? The principles stated in the Open Source AI Definition are generally applicable to any kind of AI, but machine learning challenges the Open Source Definition. For machine learning, a set of artifacts (components) is required to study and modify the system, thus requiring a new explanation of what is necessary to study and modify the system. Which AI systems comply with the Open Source AI Definition? As part of our validation and testing of the OSAID, the volunteers checked whether the Definition could be used to evaluate if AI systems provided the freedoms expected. The list of models that passed the Validation phase are: Pythia (Eleuther AI), OLMo (AI2), Amber and CrystalCoder (LLM360), and T5 (Google). A few others that were analyzed would probably pass if they changed their licenses/legal terms, for example, BLOOM (BigScience), Starcoder2 (BigCode), and Falcon (TII). Those that have been analyzed and don’t pass because they lack required components and/or their legal agreements are incompatible with the Open Source principles include Llama2 (Meta), Grok (X/Twitter), Phi-2 (Microsoft), and Mixtral (Mistral). These results should be seen as part of the definitional process, a learning moment; they are not certifications of any kind. OSI will continue to validate only legal documents and will not validate or review individual AI systems, just as it does not validate or review software projects. What’s the next step? The Open Source AI Definition reflects a thoughtful and inclusive process endorsed by leading AI developers, researchers and practitioners. It culminates in a first step represented in version 1.0 of the OSAID. The definition acknowledges that AI fundamentally differs from software and requires a tailored approach. Misunderstandings about the OSAID often arise from attempts to apply software engineering paradigms to AI, leading to confusion. By embracing the unique characteristics of AI systems, the OSAID offers a robust framework for fostering transparency, innovation and collaboration in AI development. As we navigate AI’s evolving landscape, it is crucial to engage thoughtfully and constructively with these definitions. By doing so, we can ensure that AI systems remain open, accessible and aligned with the principles of the broader Open Source movement. Our work is only possible thanks to our members. Join us today! Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions. Functional Functional Always active The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. Preferences Preferences The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user. Statistics Statistics The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you. Marketing Marketing The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes. Manage options Manage services Manage {vendor_count} vendors Read more about these purposes Accept Deny View preferences Save preferences View preferences {title} {title} {title} Manage consent
2026-01-13T08:49:43
https://opensource.org/programs/policy
Policy and standards program – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu Home Programs Policy and standards program The challenges of regulations Legislative bodies and standards organizations around the world are issuing rules that impact Open Source. The increased interest is both an opportunity and a challenge for the broader Open Source ecosystem. These policy-development responses to economic and cyber security matters as well as new regulatory concerns in adjacent domains such as research, data, and AI have risen as Open Source software’s role continues to play a critical role in industry, public and societal concerns.   OSI’s role is to educate, inform, and convene, consistent with its public benefit mission We track key legislative developments – today primarily in Europe and the US – and offer our expertise where it may help. There are many ways policy decisions can impact our Open Source software ecosystem and its benefit to individuals and organizations alike. OSI will continue to continue ed public discourse on new technologies (such as open source AI tools and models)  and serve as an independent voice to cover the concerns of public interest where Open Source is on the agenda through collaboration and coalition building. Join the Alliance to educate and inform US public policy decisions Learn more Get involved You can subscribe to OSI’s public policy list or contact us directly with questions. Subscribe to Public policy mailing list Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions. Functional Functional Always active The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. Preferences Preferences The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user. Statistics Statistics The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you. Marketing Marketing The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes. Manage options Manage services Manage {vendor_count} vendors Read more about these purposes Accept Deny View preferences Save preferences View preferences {title} {title} {title} Manage consent
2026-01-13T08:49:43
https://wiki.php.net/rfc/restrict_globals_usage
PHP: rfc:restrict_globals_usage Login Register You are here: start › rfc › restrict_globals_usage rfc:restrict_globals_usage PHP RFC: Restrict $GLOBALS usage Date: 2020-12-02 Author: Nikita Popov nikic@php.net Status: Implemented Target Version: PHP 8.1 Implementation: https://github.com/php/php-src/pull/6487 Introduction The $GLOBALS variable currently provides a direct reference to PHP's internal symbol table. Supporting this requires significant technical complexity, affects performance of all array operations in PHP, but is only rarely used. This RFC restricts supported usages of $GLOBALS to disallow the problematic cases, while allowing most code to continue working as-is. First, some technical background on how $GLOBALS currently works is necessary. Consider this simple example: $a = 1 ; $GLOBALS [ 'a' ] = 2 ; var_dump ( $a ) ; // int(2) The variable $a is stored inside a compiled-variable (CV) call frame slot on the virtual machine stack, which allows it to be accessed efficiently. In order to allow modification of the variable through $GLOBALS , the $GLOBALS array stores array elements of type INDIRECT , which contain a pointer to the CV slot. As such, array operations on $GLOBALS need to check whether the accessed element is INDIRECT and perform a de-indirection operation. However, as any array could potentially be the $GLOBALS array, this check has to be performed for essentially all array operations on all arrays. This imposes an implementation and performance cost to account for a rarely used edge-case. Additionally, the $GLOBALS array is excluded from the usual by-value behavior of PHP arrays: $a = 1 ; $globals = $GLOBALS ; // Ostensibly by-value copy $globals [ 'a' ] = 2 ; var_dump ( $a ) ; // int(2) According to normal PHP semantics, $globals should be a copy of $GLOBALS and modifications of $globals should not have any impact on the global symbol table. Finally, there currently is a mismatch between handling of integer keys between $GLOBALS and normal PHP arrays: $ { 1 } = 1 ; $GLOBALS [ 1 ] = 2 ; var_dump ( $ { 1 } ) ; // int(1) Normal PHP arrays will canonicalize integral string keys to integers, while symbol tables canonicalize integer keys to strings. As $GLOBALS interfaces between these two worlds, it cannot satisfy the rules of either. An area where INDIRECT elements present only in $GLOBALS are particularly problematic are standard library functions. While array_* functions generally contain the necessary extra code to correctly handle $GLOBALS , this does not extend to the broader standard library. Functions that do not explicitly account for $GLOBALS will either silently misbehave, cause assertion failures, or crash. Functions from 3rd-party extensions almost certainly do not handle $GLOBALS . Proposal The core idea of this proposal is to move $GLOBALS from being a “real” variable with non-standard semantics, towards being a syntactical variable with two semantics: Accesses of the form $GLOBALS[$var] will refer to the global variable $$var , and support all the usual variable operations, including writes. $GLOBALS[$var] = $value remains supported. A good way to think of this is that $GLOBALS[$var] works the same way as a variable-variable $$var , just accessing the global instead of the local scope. Accesses of the form $GLOBALS (without a direct array dereference) will return the a read-only copy of the global symbol table. This means that all operations in the following code will continue to work as they do now: // Continues to work: $GLOBALS [ 'x' ] = 1 ; $GLOBALS [ 'x' ] ++; isset ( $GLOBALS [ 'x' ] ) ; unset ( $GLOBALS [ 'x' ] ) ; // ...anything else using $GLOBALS['x']. Read-only usage of $GLOBALS will also continue to work: // Continues to work: foreach ( $GLOBALS as $var => $value ) { echo " $var => $value \n " ; } In this case the only difference is that there will no longer be a recursive “GLOBALS” key, which currently needs to be filtered out from most uses of $GLOBALS . What is no longer supported are writes to $GLOBALS taken as a whole. All of the following will generate a compile-time error: // Generates compile-time error: $GLOBALS = [ ] ; $GLOBALS += [ ] ; $GLOBALS =& $x ; $x =& $GLOBALS ; unset ( $GLOBALS ) ; // ...and any other write/read-write operation on $GLOBALS Passing $GLOBALS by reference will trigger a runtime Error exception, as by-reference passing can generally only be established at runtime: // Generates run-time Error exception: by_ref ( $GLOBALS ) ; As $GLOBALS is now a read-only copy of the global symbol table, the previously incorrect behavior of this code is fixed: // This no longer modifies $a. The previous behavior violated by-value semantics. $globals = $GLOBALS ; $globals [ 'a' ] = 1 ; The read-only copy will also use correct key canonicalization, as such the behavior of this code is fixed: $ { 1 } = 1 ; $GLOBALS [ 1 ] = 2 ; var_dump ( $ { 1 } ) ; // int(2) Impact on internals From an implementation perspective, these changes mean that INDIRECT elements no longer have to be considered when working on ordinary PHP arrays (though many places didn't do so in the first place). However, INDIRECT elements still need to be considered when working with certain special hashtables. In particular, internal symbol tables, as well as object property tables may still contain INDIRECT elements. However, these special hashtables will never escape into ordinary PHP arrays. Apart from manual checks for IS_INDIRECT , the use of the following APIs is no longer necessary: *_IND() HT iteration macros. Suffix-free macros can be used instead. *_ind() HT functions. Suffix-free functions can be used instead. zend_array_count() . Use of zend_hash_num_elements() is now safe. Backward Incompatible Changes Indirect modification of $GLOBALS will no longer be supported, which is a backwards-incompatible change. In the top 2k composer packages I found 23 cases that use $GLOBALS without directly dereferecing it (full list: https://gist.github.com/nikic/9fd95866f9811b349b947f63214ad7a9 ). Based on a cursory inspection, there are only two instances where $GLOBALS is not used in a read-only way: By-ref passing of $GLOBALS in phpseclib : This code is doing something very peculiar, and I wasn't able to figure out what the purpose of the safe_serialize() function is. Possibly very old versions of PHP caused infinite recursion when serializing $GLOBALS ? $GLOBALS = array() in phpstorm-stubs : This is not real code, so the usage is not problematic. As such, the impact of this change is expected to be fairly low. Which isn't to say non-existent: bwoebi has shared an example from his codebase that would be affected: extract ( $GLOBALS , EXTR_REFS ) ; // ... $GLOBALS += get_defined_vars ( ) ; Both of these lines constitute indirect modification and will no longer work. It is possible to rewrite them in terms of explicit loops: foreach ( $GLOBALS as $var => $_ ) $$var =& $GLOBALS [ $var ] ; // ... foreach ( get_defined_vars ( ) as $var => $value ) $GLOBALS [ $var ] = $value ; Vote Yes/No. Voting started 2020-12-23 and closes 2021-01-06. Restrict $GLOBALS usage as specified? Real name Yes No as   asgrim   ashnazg   beberlei   brzuchal   bwoebi   cmb   crell   cschneid   derick   dharman   dmitry   doubaokun   duncan3dc   ehrhardt   galvao   girgias   ilutov   jasny   jhdxr   kalle   kelunik   kocsismate   lcobucci   levim   marandall   mariano   mauricio   mcmic   nicolasgrekas   nikic   ocramius   patrickallaert   petk   pmjones   pollita   ramsey   reinders   reywob   sebastian   sergey   sirsnyder   svpernova09   tandre   theodorejb   twosee   villfa   wyrihaximus   Final result: 48 0 This poll has been closed. rfc/restrict_globals_usage.txt · Last modified: 2025/04/03 13:08 by 127.0.0.1 Page Tools Show pagesource Old revisions Backlinks Back to top  Table of Contents PHP RFC: Restrict $GLOBALS usage Introduction Proposal Impact on internals Backward Incompatible Changes Vote Copyright © 2001-2026 The PHP Group Other PHP.net sites Privacy policy
2026-01-13T08:49:43
https://dev.to/t/auth0challenge
Auth0 for AI Agents Challenge - 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 Auth0 for AI Agents Challenge Follow Hide Create Post about #auth0challenge Check out our latest challenge ! Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Authentication: JWTs vs. Sessions (My Study Notes) Dhruv Dhruv Dhruv Follow Dec 1 '25 Authentication: JWTs vs. Sessions (My Study Notes) # security # auth0challenge # jwt # webdev 1  reaction Comments Add Comment 1 min read The Twilio-Stytch Acquisition: A Technical Analysis of Developer CIAM in 2025 Deepak Gupta Deepak Gupta Deepak Gupta Follow Nov 7 '25 The Twilio-Stytch Acquisition: A Technical Analysis of Developer CIAM in 2025 # developer # development # auth0challenge # iam 1  reaction Comments 1  comment 6 min read Congrats to the Winners of the Auth0 for AI Agents Challenge! dev.to staff dev.to staff dev.to staff Follow for The DEV Team Nov 6 '25 Congrats to the Winners of the Auth0 for AI Agents Challenge! # devchallenge # auth0challenge # security # ai 46  reactions Comments 20  comments 2 min read RouteWise AI Auth0 for AI Agents Challenge Submission BinaryGarge.dev BinaryGarge.dev BinaryGarge.dev Follow Oct 26 '25 RouteWise AI # devchallenge # auth0challenge # ai # authentication 4  reactions Comments Add Comment 5 min read Auth0 AI Agent Auth0 for AI Agents Challenge Submission sipho motau sipho motau sipho motau Follow Oct 24 '25 Auth0 AI Agent # devchallenge # auth0challenge # ai # authentication Comments Add Comment 1 min read AgentFlow: Autonomous AI Agents with Secure OAuth Integration via Auth0 Token Vault Auth0 for AI Agents Challenge Submission Abhi nandan Abhi nandan Abhi nandan Follow Oct 26 '25 AgentFlow: Autonomous AI Agents with Secure OAuth Integration via Auth0 Token Vault # devchallenge # auth0challenge # ai # authentication 56  reactions Comments 8  comments 4 min read 🤖Custom-Embeddable Secure Agentic Chatbot for SaaS Applications Auth0 for AI Agents Challenge Submission sahra 💫 sahra 💫 sahra 💫 Follow Oct 27 '25 🤖Custom-Embeddable Secure Agentic Chatbot for SaaS Applications # devchallenge # ai # authentication # auth0challenge 22  reactions Comments 2  comments 5 min read Study-Flow: Auth0 for AI Agents: The Missing Piece My Study App Was Begging For Auth0 for AI Agents Challenge Submission Anshu Mandal Anshu Mandal Anshu Mandal Follow Oct 27 '25 Study-Flow: Auth0 for AI Agents: The Missing Piece My Study App Was Begging For # devchallenge # auth0challenge # ai # authentication 26  reactions Comments 3  comments 21 min read LegalMindAI – Your AI-Powered Legal Document Hub Auth0 for AI Agents Challenge Submission vaatiesther vaatiesther vaatiesther Follow Oct 27 '25 LegalMindAI – Your AI-Powered Legal Document Hub # devchallenge # auth0challenge # ai # authentication 7  reactions Comments Add Comment 3 min read InnoGate: Anti-Piracy Research Discovery Platform with AI-Powered RAG and Auth0 FGA Auth0 for AI Agents Challenge Submission Akshat Batra Akshat Batra Akshat Batra Follow Oct 27 '25 InnoGate: Anti-Piracy Research Discovery Platform with AI-Powered RAG and Auth0 FGA # devchallenge # auth0challenge # ai # authentication 4  reactions Comments Add Comment 8 min read ApexQuest: Architecting Trust - Where Every AI Agent is Authenticated by Auth0 Auth0 for AI Agents Challenge Submission Divya Divya Divya Follow Oct 25 '25 ApexQuest: Architecting Trust - Where Every AI Agent is Authenticated by Auth0 # devchallenge # auth0challenge # ai # authentication 44  reactions Comments 2  comments 19 min read From $50K Reports to AI Automation: Securing Multi-Agent ESG Compliance with Auth0 Auth0 for AI Agents Challenge Submission omkar omkar omkar Follow Oct 27 '25 From $50K Reports to AI Automation: Securing Multi-Agent ESG Compliance with Auth0 # devchallenge # auth0challenge # ai # authentication 8  reactions Comments Add Comment 8 min read Assistant0 - Secure AI Personal Assistant Auth0 for AI Agents Challenge Submission Adam Adam Adam Follow Oct 27 '25 Assistant0 - Secure AI Personal Assistant # devchallenge # auth0challenge # ai # authentication 10  reactions Comments 2  comments 6 min read What The Pack - AI Mission Control for D2C Logistics Auth0 for AI Agents Challenge Submission rokimiftah rokimiftah rokimiftah Follow Oct 27 '25 What The Pack - AI Mission Control for D2C Logistics # devchallenge # auth0challenge # ai # authentication 5  reactions Comments Add Comment 14 min read ✨IntergrationHub Auth0 for AI Agents Challenge Submission Anupam Thakur Anupam Thakur Anupam Thakur Follow Oct 27 '25 ✨IntergrationHub # devchallenge # auth0challenge # ai # authentication Comments Add Comment 2 min read Nexus AI Auth0 for AI Agents Challenge Submission Julio Díaz Julio Díaz Julio Díaz Follow Oct 27 '25 Nexus AI # devchallenge # auth0challenge # ai # authentication 14  reactions Comments Add Comment 6 min read Building a Pay-Per-Use AI Agent Marketplace with Auth0 + Web3 Auth0 for AI Agents Challenge Submission Prema Ananda Prema Ananda Prema Ananda Follow Oct 25 '25 Building a Pay-Per-Use AI Agent Marketplace with Auth0 + Web3 # devchallenge # auth0challenge # ai # authentication 20  reactions Comments 2  comments 6 min read Task0 - AI task manager Auth0 for AI Agents Challenge Submission Insaf Insaf Insaf Follow Oct 27 '25 Task0 - AI task manager # devchallenge # auth0challenge # ai # authentication 10  reactions Comments Add Comment 1 min read Agent Snape - your GitHub manager Auth0 for AI Agents Challenge Submission Insaf Insaf Insaf Follow Oct 26 '25 Agent Snape - your GitHub manager # devchallenge # auth0challenge # ai # authentication 22  reactions Comments 1  comment 1 min read 🛡️ AgentGuard: Secure and Govern Your AI Agents with Auth0 for AI Auth0 for AI Agents Challenge Submission Ayomide olofinsawe Ayomide olofinsawe Ayomide olofinsawe Follow Oct 27 '25 🛡️ AgentGuard: Secure and Govern Your AI Agents with Auth0 for AI # devchallenge # auth0challenge # ai # authentication 4  reactions Comments 2  comments 3 min read Join the Auth0 for AI Agents Challenge: $3,000 in Prizes! Jess Lee Jess Lee Jess Lee Follow for The DEV Team Oct 8 '25 Join the Auth0 for AI Agents Challenge: $3,000 in Prizes! # devchallenge # auth0challenge # security # ai 95  reactions Comments 20  comments 3 min read We have four DEV Challenges for you to dive into this weekend! Jess Lee Jess Lee Jess Lee Follow for The DEV Team Oct 24 '25 We have four DEV Challenges for you to dive into this weekend! # devchallenge # auth0challenge # agenticpostgreschallenge # hacktoberfest 19  reactions Comments Add Comment 2 min read DevCaliber: Redefining Technical Hiring with Auth0 Authenticated AI Agents and Verified GitHub Talent Auth0 for AI Agents Challenge Submission Divya Divya Divya Follow Oct 20 '25 DevCaliber: Redefining Technical Hiring with Auth0 Authenticated AI Agents and Verified GitHub Talent # devchallenge # auth0challenge # ai # authentication 37  reactions Comments 16  comments 17 min read AgroVisionSecureAI+: Intelligent Crop Analysis with Auth0 Authentication Auth0 for AI Agents Challenge Submission Alphonse Kazadi Alphonse Kazadi Alphonse Kazadi Follow Oct 23 '25 AgroVisionSecureAI+: Intelligent Crop Analysis with Auth0 Authentication # devchallenge # auth0challenge # ai # authentication 15  reactions Comments Add Comment 3 min read 🚀 AI Social Media Manager with Auth0 Security Auth0 for AI Agents Challenge Submission Simran Shaikh Simran Shaikh Simran Shaikh Follow Oct 25 '25 🚀 AI Social Media Manager with Auth0 Security # auth0challenge # ai # react # javascript 10  reactions Comments 4  comments 4 min read loading... trending guides/resources Congrats to the Winners of the Auth0 for AI Agents Challenge! The Twilio-Stytch Acquisition: A Technical Analysis of Developer CIAM in 2025 Authentication: JWTs vs. Sessions (My Study Notes) 💎 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
2026-01-13T08:49:43
http://llvm-compile-time-tracker.com/compare.php?from=54cfc6944e2669d7a41a164fc4f3d923a71e701d&to=ff9379f4b2d7ebcb8dee94df47dc43c3388f22bf&stat=max-rss
LLVM Compile-Time Tracker Index | Graphs | Compare | About From: To: Metric: instructions instructions:u max-rss task-clock cycles branches branch-misses wall-time size-total size-text size-data size-bss size-file Per-file details:
2026-01-13T08:49:43
https://vibe.forem.com/dixitram/what-do-you-do-with-your-old-first-laptop-when-you-get-a-new-one-40mn
What do you do with your old first laptop when you get a new one?💻 - Vibe Coding Forem 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 Vibe Coding Forem 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 Dixit Ram Posted on Jan 6           What do you do with your old first laptop when you get a new one?💻 # ai # gemini My friend and I were chatting the other day, and we both agreed: No way we’re throwing it away. That thing has seen too many late nights, assignments, games, projects… so many memories. One day the idea just hit me. I thought about those cool iPhone teardown frames people hang on their walls… Why not do the exact same thing with an old laptop? So I asked Gemini to create an image of my old laptop taken apart and framed like art. It turned out awesome! (Attach the Gemini-generated image here — it looks perfect as wall decor) Now I just need a sofa and a house to hang it in. 😅 What about you? Still keeping your first laptop somewhere? Did you repurpose it? Or turn it into something creative? Share your story in the comments — I’d really love to hear it! 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 Dixit Ram Follow I nerd over cool science & tech news 🧑‍🔬, love discovering and trying new tools and frameworks 💻. Location Gujarat,India Joined Apr 7, 2024 More from Dixit Ram 🐱Cursor Pet Extensions—A Playful Companion # ai # antigravity # plugin # extensions 💎 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 Vibe Coding Forem — Discussing AI software development, and showing off what we're building. Home About Contact 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 . Vibe Coding Forem © 2025 - 2026. Where anyone can code, with a bit of creativity and some AI help. Log in Create account
2026-01-13T08:49:43
https://opensource.org/ai/webinars/the-ideology-of-foss-and-ai-what-open-means-relating-to-platforms-and-black-box-systems/
The Ideology of FOSS and AI: What “Open” means relating to platforms and black box systems – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu Home Open Source AI Webinars The Ideology of FOSS and AI: What “Open” means relating to platforms and black box systems The Ideology of FOSS and AI: What “Open” means relating to platforms and black box systems Part of the Deep Dive: AI Webinar Series The initial conception of Free and Open Source Software was developed during a time where software was bundled into discrete packages to be run on machines owned and operated by a single individual. The initial FOSS movement utilized licensing and copyright law to provide better autonomy and control over these software systems. Now, our software systems often operate as platforms, monopolizing access between networks and resources and profiting greatly through that monopoly. In this talk, listeners will learn more about the ideological foundations of FOSS and the blindspots that have developed in our community as software has transitioned from individual discrete packages into deeply interconnected systems that gate access to critical resources for many. We will delve into what autonomy might mean in a world where the deployment of technology inherently affects so many. Finally, we will observe the flaws in conventional open source approaches to providing autonomy and what other tools we may have at our disposal to ensure better community governance of this increasingly pervasive technology. Webinar Summary In this webinar hosted by the Open Source Initiative as a part of the “Deep Dive: Defining Open Source AI” series, Mike Nolan discusses the history and evolution of free and open-source software, examining how the concept applies to emerging technologies like AI. Mike references a recent influential paper titled “Open for Business: Big Tech Concentrated Power in the Political Economy of Open AI.” The presentation is divided into four key sections: a historical overview of open source, the changing nature of software from discrete applications to complex platforms, the components and spectrum of openness in AI, and an analysis of the pros and cons of open AI. It also touches upon the claims made regarding open AI, its impact on innovation, and the changing landscape of software development. Ultimately, Mike emphasizes that open source does not guarantee democratization or meaningful competition in AI, highlighting the need for a critical evaluation of its value in the context of AI deployment and regulation. Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions. Functional Functional Always active The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. Preferences Preferences The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user. 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2026-01-13T08:49:43
https://opensource.org/ai/panels
Panels – Open Source Initiative Skip to content Get involved About Licenses Open Source Definition Open Source AI Programs Blog Get involved About Licenses Open Source Definition Open Source AI Programs Blog Open Main Menu Home Open Source AI Panels Panels Page created on August 2, 2022 | Last modified on May 28, 2025 Watch the panel discussions Four experts in four online conversations will further dissect the issues posed by AI systems to the Open Source communities and society as a whole. November 17, 2022 Open Source software started in academic circles, and AI is not different. November 10, 2022 Focusing on legal aspects of AI November 3, 2022 How can the society as a whole maintain control of AI systems? October 27, 2022 Exploring the business side of AI Get involved Mastodon Twitter LinkedIn Reddit About About Our team Board of directors Sponsors Programs Blog Press mentions Trademark Bylaws Licenses Open Source Definition Licenses License Review Process Open Standards Requirement for Software Open Source AI Open Source AI OSAI Definition Process Timeline Open Weights FAQ Checklist Forum Community Become an Individual Member Become an OSI Affiliate Affiliate Organizations Maintainers Events Forum OpenSource.net The content on this website, of which Opensource.org is the author, is licensed under a  Creative Commons Attribution 4.0 International License . Opensource.org is not the author of any of the licenses reproduced on this site. Questions about the copyright in a license should be directed to the license steward. Read our Privacy Policy Proudly powered by WordPress. Hosted by Pressable. Manage Cookie Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions. Functional Functional Always active The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. Preferences Preferences The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user. Statistics Statistics The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you. Marketing Marketing The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes. Manage options Manage services Manage {vendor_count} vendors Read more about these purposes Accept Deny View preferences Save preferences View preferences {title} {title} {title} Manage consent
2026-01-13T08:49:43