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https://hbr.org/2022/02/why-flexible-work-is-essential-to-your-dei-strategy | Why Flexible Work Is Essential to Your DEI Strategy SKIP TO CONTENT Harvard Business Review Logo Harvard Business Review Logo Diversity and inclusion | Why Flexible Work Is Essential to Your DEI Strategy Subscribe Sign In Latest Magazine Topics Podcasts Store Reading Lists Data & Visuals Case Selections HBR Executive Search hbr.org Subscribe Latest Podcasts The Magazine Store Webinars Newsletters All Topics Reading Lists Data & Visuals Case Selections HBR Executive My Library Account Settings Sign In Explore HBR Latest The Magazine Podcasts Store Webinars Newsletters Popular Topics Managing Yourself Leadership Strategy Managing Teams Gender Innovation Work-life Balance All Topics For Subscribers Reading Lists Data & Visuals Case Selections HBR Executive Subscribe My Account My Library Topic Feeds Orders Account Settings Email Preferences Sign In Harvard Business Review Logo Diversity and inclusion Why Flexible Work Is Essential to Your DEI Strategy by Sheela Subramanian and Ella F. Washington February 25, 2022 Illustration by Barbara Gibson Post Post Share Save Buy Copies Print Summary . Leer en español Ler em português Post Post Share Save Buy Copies Print In celebration of Black History Month this year, we’ve seen corporate leaders participate in more public displays of solidarity than ever before, from employee volunteer days and internal company workshops to writing large checks to community organizations and nonprofits. These efforts are no doubt designed to demonstrate the commitments they’ve made to diversity, equity, and inclusion over recent years in response to the Black Lives Matter movement and increasing awareness of the problems of systemic racism. Sheela Subramanian is a vice president of the Future Forum , a consortium launched by Slack to help companies reimagine work in the new digital-first world. Founding partners include the Boston Consulting Group , MillerKnoll, and MLT . Sheela is also co-author of How The Future Works: Leading Flexible Teams to Do the Best Work of Their Lives . Ella F. Washington is an organizational psychologist; the founder and CEO of Ellavate Solutions, a DEI strategy firm; and a professor of practice at Georgetown University’s McDonough School of Business. She is the author of The Necessary Journey: Making Real Progress on Equity and Inclusion (HBR Press, November 2022) and Unspoken: A Guide to Cracking the Hidden Corporate Code (Forbes Books, May 2024). Post Post Share Save Buy Copies Print Read more on Diversity and inclusion or related topics Race , Virtual teams , Flex time , Employee retention and Remote work Partner Center Start my subscription! Explore HBR The Latest All Topics Magazine Archive Reading Lists Case Selections HBR Executive Podcasts Webinars Data & Visuals My Library Newsletters HBR Press HBR Store Article Reprints Books Cases Collections Magazine Issues HBR Guide Series HBR 20-Minute Managers HBR Emotional Intelligence Series HBR Must Reads Tools About HBR Contact Us Advertise with Us Information for Booksellers/Retailers Masthead Global Editions Media Inquiries Guidelines for Authors HBR Analytic Services Copyright Permissions Accessibility Digital Accessibility Manage My Account My Library Topic Feeds Orders Account Settings Email Preferences Account FAQ Help Center Contact Customer Service Explore HBR The Latest All Topics Magazine Archive Reading Lists Case Selections HBR Executive Podcasts Webinars Data & Visuals My Library Newsletters HBR Press HBR Store Article Reprints Books Cases Collections Magazine Issues HBR Guide Series HBR 20-Minute Managers HBR Emotional Intelligence Series HBR Must Reads Tools About HBR Contact Us Advertise with Us Information for Booksellers/Retailers Masthead Global Editions Media Inquiries Guidelines for Authors HBR Analytic Services Copyright Permissions Accessibility Digital Accessibility Manage My Account My Library Topic Feeds Orders Account Settings Email Preferences Account FAQ Help Center Contact Customer Service Follow HBR Facebook X Corp. LinkedIn Instagram Your Newsreader Harvard Business Review Logo About Us Careers Privacy Policy Cookie Policy Copyright Information Trademark Policy Terms of Use Harvard Business Publishing: Higher Education Corporate Learning Harvard Business Review Harvard Business School Copyright © 2026 Harvard Business School Publishing. All rights reserved. Harvard Business Publishing is an affiliate of Harvard Business School. | 2026-01-13T08:48:23 |
https://survey.stackoverflow.co/2025/developers/ | Developers | 2025 Stack Overflow Developer Survey Products Stack Overflow Where developers and technologists go to gain and share knowledge. Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers Advertising Reach devs & technologists worldwide about your product, service or employer brand Knowledge Solutions Data licensing offering for businesses to build and improve AI tools and models Labs The future of collective knowledge sharing About the company Visit the blog Developers Technology AI Work Stack Overflow Methodology 1 Developers What we know about the global community of developers. 1.1. Profile → 1.2. Education & Experience → 1.3. Developer roles → 1.1 Profile Coding The Developer Survey is meant to explore insights for those that code. A majority of respondents (76%) are professional developers with an additional 15% that are aspirational or adjacent. Are you someone who writes code? Please select one of the following options that best describes you today. Unknow graph I am a developer by profession 76.2% I am not primarily a developer, but I write code sometimes as part of my work/studies 10% I am learning to code 5.2% I code primarily as a hobby 3.9% I used to be a developer by profession, but no longer am 2.7% I work with developers or my work supports developers but am not a developer by profession 2% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 49,019 ( 100% ) Age 76% of the respondents in this survey are professional developers, and most (66%) professional developers are between 25 and 44. What is your age? All Respondents Professional Developers Learning to Code Professionals Using AI Learners Using AI All Respondents 18-24 years old 18.7% 25-34 years old 33.6% 35-44 years old 26.9% 45-54 years old 12.8% 55-64 years old 5.3% 65 years or older 1.9% Prefer not to say 0.8% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 49,019 ( 100% ) Professional Developers 18-24 years old 14.2% 25-34 years old 37.1% 35-44 years old 29.3% 45-54 years old 13% 55-64 years old 4.9% 65 years or older 1.2% Prefer not to say 0.4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 37,356 ( 76.2% ) Learning to Code 18-24 years old 68.6% 25-34 years old 16.5% 35-44 years old 6.6% 45-54 years old 4% 55-64 years old 1.3% 65 years or older 0.6% Prefer not to say 2.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 4,494 ( 9.2% ) Professionals Using AI 18-24 years old 13.7% 25-34 years old 37.2% 35-44 years old 30% 45-54 years old 13.4% 55-64 years old 4.6% 65 years or older 0.9% Prefer not to say 0.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 28,410 ( 58% ) Learners Using AI 18-24 years old 70.9% 25-34 years old 15.6% 35-44 years old 6.1% 45-54 years old 3.9% 55-64 years old 1.2% 65 years or older 0.4% Prefer not to say 1.9% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,891 ( 5.9% ) Country Ukraine and France swapped places this year compared to last, placing France in the top 5 list of responding countries. Where do you live? Top 10 Countries All Countries Top 10 Countries United States of America 20.4% Germany 8.6% India 7.2% United Kingdom of Great Britain and Northern Ireland 5.8% France 4% Canada 3.7% Ukraine 2.7% Poland 2.5% Netherlands 2.5% Italy 2.4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 35,307 ( 72% ) Country Frequency Percent United States of America 7,218 20.4% Germany 3,022 8.6% India 2,536 7.2% United Kingdom of Great Britain and Northern Ireland 2,036 5.8% France 1,408 4% Canada 1,303 3.7% Ukraine 963 2.7% Poland 886 2.5% Netherlands 867 2.5% Italy 833 2.4% Brazil 822 2.3% Australia 802 2.3% Spain 716 2% Sweden 616 1.7% Switzerland 546 1.6% Czech Republic 520 1.5% Austria 410 1.2% Romania 322 0.9% Belgium 320 0.9% Denmark 316 0.9% Israel 297 0.8% Turkey 294 0.8% Mexico 284 0.8% Portugal 279 0.8% China 255 0.7% New Zealand 255 0.7% Finland 254 0.7% Greece 252 0.7% South Africa 251 0.7% Bulgaria 244 0.7% Pakistan 238 0.7% Norway 237 0.7% Hungary 235 0.7% Argentina 222 0.6% Bangladesh 219 0.6% Ireland 209 0.6% Colombia 202 0.6% Russian Federation 200 0.6% Nigeria 199 0.6% Japan 188 0.5% Indonesia 180 0.5% Serbia 158 0.4% Iran, Islamic Republic of... 149 0.4% Kenya 147 0.4% Slovakia 147 0.4% Viet Nam 145 0.4% Philippines 141 0.4% Egypt 139 0.4% Chile 131 0.4% Thailand 119 0.3% Taiwan 118 0.3% Croatia 113 0.3% Lithuania 101 0.3% Sri Lanka 95 0.3% Singapore 89 0.3% United Arab Emirates 89 0.3% South Korea 86 0.2% Nepal 83 0.2% Malaysia 82 0.2% Slovenia 78 0.2% Hong Kong (S.A.R.) 72 0.2% Estonia 70 0.2% Peru 64 0.2% Latvia 62 0.2% Morocco 55 0.2% Uruguay 52 0.1% Algeria 48 0.1% Georgia 48 0.1% Venezuela, Bolivarian Republic of... 47 0.1% Ghana 46 0.1% Tunisia 46 0.1% Cyprus 39 0.1% Ethiopia 38 0.1% Saudi Arabia 37 0.1% Guatemala 33 0.1% Jordan 32 0.1% Bosnia and Herzegovina 30 0.1% Kazakhstan 29 0.1% Ecuador 28 0.1% Uganda 28 0.1% Belarus 26 0.1% Dominican Republic 26 0.1% Armenia 25 0.1% Costa Rica 25 0.1% Luxembourg 23 0.1% Albania 22 0.1% Paraguay 21 0.1% Lebanon 20 0.1% Malta 19 0.1% Azerbaijan 18 0.1% Bolivia 18 0.1% Yemen 18 0.1% Myanmar 17 0.1% Uzbekistan 16 0.1% Montenegro 15 0% Rwanda 15 0% Afghanistan 13 0% Cameroon 13 0% Iceland 13 0% Iraq 13 0% Zimbabwe 13 0% El Salvador 12 0% Zambia 12 0% Cambodia 11 0% Honduras 11 0% Madagascar 11 0% Mauritius 11 0% Syrian Arab Republic 11 0% Isle of Man 10 0% Kyrgyzstan 10 0% Panama 10 0% Maldives 9 0% Togo 9 0% Cuba 8 0% Côte d'Ivoire 8 0% Republic of Moldova 8 0% Angola 7 0% Bahrain 7 0% Democratic Republic of the Congo 7 0% Kuwait 7 0% Namibia 7 0% Palestine 7 0% Trinidad and Tobago 7 0% United Republic of Tanzania 7 0% Andorra 6 0% Kosovo 6 0% Nicaragua 6 0% North Korea 6 0% Oman 6 0% Benin 5 0% Congo, Republic of the... 5 0% Fiji 5 0% Mozambique 5 0% Qatar 5 0% Senegal 5 0% Swaziland 5 0% Barbados 4 0% Guyana 4 0% Jamaica 4 0% Malawi 4 0% Somalia 4 0% Belize 3 0% Bhutan 3 0% Brunei Darussalam 3 0% Mongolia 3 0% Papua New Guinea 3 0% Sudan 3 0% Antigua and Barbuda 2 0% Botswana 2 0% Burundi 2 0% Haiti 2 0% Lao People's Democratic Republic 2 0% Libyan Arab Jamahiriya 2 0% Mali 2 0% Micronesia, Federated States of... 2 0% Saint Lucia 2 0% Sierra Leone 2 0% Suriname 2 0% Tajikistan 2 0% Turkmenistan 2 0% Cape Verde 1 0% Djibouti 1 0% Gabon 1 0% Gambia 1 0% Guinea 1 0% Guinea-Bissau 1 0% Lesotho 1 0% Mauritania 1 0% Niger 1 0% Palau 1 0% San Marino 1 0% Timor-Leste 1 0% Share Twitter/X Facebook LinkedIn Responses: 35,369 ( 72.2% ) 1.2 Education & Experience Educational attainment 30% of developers learning to code this year have already attained a BS degree, indicating they are learning for a higher degree, for work, or are upskilling. This is an increase over last year when 24% said they had attained a BS degree. Which of the following best describes the highest level of formal education that you’ve completed? All Respondents Professional Developers Learning to Code Professionals Using AI Learning to Code with AI All Respondents Primary/elementary school 1.2% Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.) 7.5% Some college/university study without earning a degree 12.8% Associate degree (A.A., A.S., etc.) 3.3% Bachelor’s degree (B.A., B.S., B.Eng., etc.) 42.1% Master’s degree (M.A., M.S., M.Eng., MBA, etc.) 26.2% Professional degree (JD, MD, Ph.D, Ed.D, etc.) 5.5% Something else 1.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 47,988 ( 97.9% ) Professional Developers Primary/elementary school 0.8% Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.) 5.1% Some college/university study without earning a degree 11.5% Associate degree (A.A., A.S., etc.) 3.2% Bachelor’s degree (B.A., B.S., B.Eng., etc.) 45.9% Master’s degree (M.A., M.S., M.Eng., MBA, etc.) 28% Professional degree (JD, MD, Ph.D, Ed.D, etc.) 4.5% Something else 1.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 36,705 ( 74.9% ) Learning to Code Primary/elementary school 3.8% Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.) 28% Some college/university study without earning a degree 23.9% Associate degree (A.A., A.S., etc.) 3.3% Bachelor’s degree (B.A., B.S., B.Eng., etc.) 29.6% Master’s degree (M.A., M.S., M.Eng., MBA, etc.) 7.1% Professional degree (JD, MD, Ph.D, Ed.D, etc.) 1.2% Something else 3.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 4,342 ( 8.9% ) Professionals Using AI Primary/elementary school 0.7% Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.) 4.9% Some college/university study without earning a degree 11.5% Associate degree (A.A., A.S., etc.) 3.1% Bachelor’s degree (B.A., B.S., B.Eng., etc.) 46.1% Master’s degree (M.A., M.S., M.Eng., MBA, etc.) 28.3% Professional degree (JD, MD, Ph.D, Ed.D, etc.) 4.4% Something else 0.9% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 28,378 ( 57.9% ) Learning to Code with AI Primary/elementary school 3% Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.) 27.5% Some college/university study without earning a degree 23.7% Associate degree (A.A., A.S., etc.) 2.9% Bachelor’s degree (B.A., B.S., B.Eng., etc.) 31.2% Master’s degree (M.A., M.S., M.Eng., MBA, etc.) 7.8% Professional degree (JD, MD, Ph.D, Ed.D, etc.) 0.9% Something else 3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,866 ( 5.8% ) Years coding 35% of developers responding to the Developer Survey this year have been coding less than 10 years. Including any education, how many years have you been coding in total? Please round to the nearest whole number, excluding any decimal points. All Respondents 18-24 years old 25-34 years old 35-44 years old 45-54 years old 55-64 years old All Respondents 1 to 5 years 13.9% 6 to 10 years 21.1% 11 to 15 years 15.6% 16 to 20 years 11.8% 21 to 30 years 14.6% 31 to 40 years 7% 41 to 50 years 3.1% More than 50 years 0.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 42,923 ( 87.6% ) 18-24 years old 1 to 5 years 49.9% 6 to 10 years 43.5% 11 to 15 years 6.5% 16 to 20 years 0.2% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 7,435 ( 15.2% ) 25-34 years old 1 to 5 years 14.5% 6 to 10 years 37.9% 11 to 15 years 33.3% 16 to 20 years 13.1% 21 to 30 years 1.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 14,108 ( 28.8% ) 35-44 years old 1 to 5 years 5.6% 6 to 10 years 11.2% 11 to 15 years 17.6% 16 to 20 years 28.1% 21 to 30 years 35.4% 31 to 40 years 2% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 11,717 ( 23.9% ) 45-54 years old 1 to 5 years 4.1% 6 to 10 years 4.9% 11 to 15 years 4.8% 16 to 20 years 8.5% 21 to 30 years 39.2% 31 to 40 years 34.2% 41 to 50 years 4.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 5,672 ( 11.6% ) 55-64 years old 1 to 5 years 2.8% 6 to 10 years 3.3% 11 to 15 years 2.8% 16 to 20 years 4% 21 to 30 years 16.5% 31 to 40 years 35.7% 41 to 50 years 34.3% More than 50 years 0.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,483 ( 5.1% ) Learn to code A significant 69% of developers have spent time in the last year learning new coding techniques or a new programming language. Did you begin learning to code or learn a new coding skill/programming language in the last year? Unknow graph Yes, I am not new to coding but am learning new coding techniques or programming language 69.1% No, I am not new to coding and did not learn new coding techniques or programming languages 26.7% Yes, I am new to coding or currently a student 4.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 46,708 ( 95.3% ) How did you learn to code? Technical documentation is the most used resource for learning, with nearly 68% of respondents using it in the past year. How did you learn to code in the past year? Select all that apply. All Respondents 18-24 years old 25-34 years old 35-44 years old 45-54 years old 55-64 years old All Respondents Technical documentation (is generated for/by the tool or system) 67.8% Other online resources (e.g. standard search, forum, online community) 58.7% Stack Overflow or Stack Exchange 51.4% Videos (not associated with specific online course or certification) 50% AI CodeGen tools or AI-enabled apps 44% Blogs or podcasts 34.8% Online Courses or Certification (includes all media types) 32.7% Books / Physical media 30.4% Colleague or on-the-job training 25.6% School (i.e., University, College, etc) 16.6% Games or coding challenges 12.1% Coding Bootcamp 5.2% Other 3.2% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 33,454 ( 68.2% ) 18-24 years old Technical documentation (is generated for/by the tool or system) 65% Other online resources (e.g. standard search, forum, online community) 60% Stack Overflow or Stack Exchange 53.3% Videos (not associated with specific online course or certification) 55.2% AI CodeGen tools or AI-enabled apps 39.9% Blogs or podcasts 28.5% Online Courses or Certification (includes all media types) 30.4% Books / Physical media 26.2% Colleague or on-the-job training 24% School (i.e., University, College, etc) 42.8% Games or coding challenges 15.2% Coding Bootcamp 7.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 7,203 ( 14.7% ) 25-34 years old Technical documentation (is generated for/by the tool or system) 70% Other online resources (e.g. standard search, forum, online community) 57.6% Stack Overflow or Stack Exchange 51.2% Videos (not associated with specific online course or certification) 50.5% AI CodeGen tools or AI-enabled apps 45.4% Blogs or podcasts 35.9% Online Courses or Certification (includes all media types) 33.4% Books / Physical media 28.8% Colleague or on-the-job training 28.9% School (i.e., University, College, etc) 12.7% Games or coding challenges 12.6% Coding Bootcamp 5.9% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 11,332 ( 23.1% ) 35-44 years old Technical documentation (is generated for/by the tool or system) 68.6% Other online resources (e.g. standard search, forum, online community) 56.8% Stack Overflow or Stack Exchange 48.2% Videos (not associated with specific online course or certification) 48% AI CodeGen tools or AI-enabled apps 47.2% Blogs or podcasts 38.5% Online Courses or Certification (includes all media types) 33.4% Books / Physical media 31.4% Colleague or on-the-job training 25.9% School (i.e., University, College, etc) 6.8% Games or coding challenges 11.5% Coding Bootcamp 3.9% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 8,457 ( 17.3% ) 45-54 years old Technical documentation (is generated for/by the tool or system) 67% Other online resources (e.g. standard search, forum, online community) 60.4% Stack Overflow or Stack Exchange 52.5% Videos (not associated with specific online course or certification) 48.4% AI CodeGen tools or AI-enabled apps 45.6% Blogs or podcasts 39% Online Courses or Certification (includes all media types) 34% Books / Physical media 35.1% Colleague or on-the-job training 23.2% School (i.e., University, College, etc) 6.5% Games or coding challenges 9.5% Coding Bootcamp 3.4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 3,991 ( 8.1% ) 55-64 years old Technical documentation (is generated for/by the tool or system) 64.3% Other online resources (e.g. standard search, forum, online community) 62.5% Stack Overflow or Stack Exchange 56.5% Videos (not associated with specific online course or certification) 43.8% AI CodeGen tools or AI-enabled apps 38.4% Blogs or podcasts 31.4% Online Courses or Certification (includes all media types) 32.8% Books / Physical media 39.3% Colleague or on-the-job training 21.4% School (i.e., University, College, etc) 7.3% Games or coding challenges 6.3% Coding Bootcamp 3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 1,687 ( 3.4% ) Learn to code for AI Over 36% of respondents learned how to use AI-enabled tools for their job or to advance their career in the last year. Did you spend time in the last year learning AI programming or AI-enabled tooling on your own or at work? All Respondents Yes, I learned how to use AI-enabled tools required for my job or to benefit my career 36.3% Yes, I learned how to use AI-enabled tools for my personal curiosity and/or hobbies 31% No, I learned something that was not related to AI or AI enablement for my personal curiosity and/or hobbies 11.7% No, I didn't spend time learning in the past year 10.8% No, I learned something that was not related to AI or AI enablement as required for my job or to benefit my career 10.2% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 45,065 ( 91.9% ) How did you learn to code for AI? AI-powered tools and applications are the most popular way to learn about AI, with over 52% of respondents using them. How did you learn to code for AI in the past year? Select all that apply. All Respondents 18-24 years old 25-34 years old 35-44 years old 45-54 years old 55-64 years old All Respondents AI CodeGen tools or AI-enabled apps 52.5% Other online resources (e.g. standard search, forum, online community) 44.2% Technical documentation (is generated for/by the tool or system) 42.5% Videos (not associated with specific online course or certification) 38.7% Blogs or podcasts 28.7% Colleague or on-the-job training 21.6% Stack Overflow or Stack Exchange 17% Online Courses or Certification (includes all media types) 16.4% Books / Physical media 8.5% School (i.e., University, College, etc) 6.2% Games or coding challenges 3.3% Coding Bootcamp 2.9% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 28,172 ( 57.5% ) 18-24 years old AI CodeGen tools or AI-enabled apps 46.9% Other online resources (e.g. standard search, forum, online community) 41.3% Technical documentation (is generated for/by the tool or system) 37.5% Videos (not associated with specific online course or certification) 42.5% Blogs or podcasts 22.2% Colleague or on-the-job training 15.6% Stack Overflow or Stack Exchange 20.3% Online Courses or Certification (includes all media types) 15.6% Books / Physical media 8.8% School (i.e., University, College, etc) 20.4% Games or coding challenges 5.2% Coding Bootcamp 4.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 4,409 ( 9% ) 25-34 years old AI CodeGen tools or AI-enabled apps 52.1% Other online resources (e.g. standard search, forum, online community) 42.6% Technical documentation (is generated for/by the tool or system) 44% Videos (not associated with specific online course or certification) 37.8% Blogs or podcasts 28.1% Colleague or on-the-job training 22.8% Stack Overflow or Stack Exchange 17.1% Online Courses or Certification (includes all media types) 15.9% Books / Physical media 7.2% School (i.e., University, College, etc) 5.3% Games or coding challenges 3.2% Coding Bootcamp 3.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 9,486 ( 19.4% ) 35-44 years old AI CodeGen tools or AI-enabled apps 55.1% Other online resources (e.g. standard search, forum, online community) 44.6% Technical documentation (is generated for/by the tool or system) 43.3% Videos (not associated with specific online course or certification) 38.8% Blogs or podcasts 31% Colleague or on-the-job training 24.1% Stack Overflow or Stack Exchange 14.5% Online Courses or Certification (includes all media types) 16.7% Books / Physical media 7.7% School (i.e., University, College, etc) 2.2% Games or coding challenges 2.7% Coding Bootcamp 2.4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 8,241 ( 16.8% ) 45-54 years old AI CodeGen tools or AI-enabled apps 54.7% Other online resources (e.g. standard search, forum, online community) 47.9% Technical documentation (is generated for/by the tool or system) 43.8% Videos (not associated with specific online course or certification) 39.1% Blogs or podcasts 33.2% Colleague or on-the-job training 22.2% Stack Overflow or Stack Exchange 16.4% Online Courses or Certification (includes all media types) 16.8% Books / Physical media 10% School (i.e., University, College, etc) 2.2% Games or coding challenges 2.7% Coding Bootcamp 1.8% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 4,017 ( 8.2% ) 55-64 years old AI CodeGen tools or AI-enabled apps 52.1% Other online resources (e.g. standard search, forum, online community) 47.9% Technical documentation (is generated for/by the tool or system) 39.6% Videos (not associated with specific online course or certification) 34.5% Blogs or podcasts 28.3% Colleague or on-the-job training 18.2% Stack Overflow or Stack Exchange 18.7% Online Courses or Certification (includes all media types) 19% Books / Physical media 13.9% School (i.e., University, College, etc) 2.7% Games or coding challenges 2.1% Coding Bootcamp 1.8% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 1,498 ( 3.1% ) 1.3 Developer roles Role Architect is a new role we added to the survey this year and is the fourth most popular role for respondents. Which of the following describes your current job or the job you had for the most time in the past year? All Respondents United States Germany India United Kingdom France All Respondents Developer, full-stack 27% Developer, back-end 14.2% Student 11.3% Architect, software or solutions 6.1% Developer, desktop or enterprise applications 4.3% Developer, front-end 4.3% Developer, mobile 3% Developer, embedded applications or devices 2.8% Engineering manager 2.4% DevOps engineer or professional 2.3% Other 2.3% Academic researcher 2% Retired 1.9% Data engineer 1.7% AI/ML engineer 1.4% Senior executive (C-suite, VP, etc.) 1.3% Data scientist 1.2% Cybersecurity or InfoSec professional 1.1% System administrator 1% Cloud infrastructure engineer 1% Founder, technology or otherwise 1% Developer, game or graphics 0.9% Data or business analyst 0.9% Developer, QA or test 0.8% Project manager 0.7% Applied scientist 0.6% Support engineer or analyst 0.5% Developer, AI apps or physical AI 0.5% Product manager 0.4% Database administrator or engineer 0.4% UX, Research Ops or UI design professional 0.3% Financial analyst or engineer 0.3% Educator 0.2% Site reliability engineer 0.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 43,560 ( 88.9% ) United States Developer, full-stack 27.9% Developer, back-end 11.1% Student 6.9% Architect, software or solutions 6.2% Developer, desktop or enterprise applications 4.6% Engineering manager 3.7% Retired 3.5% Developer, front-end 3.5% Developer, embedded applications or devices 3.2% Other 3.2% DevOps engineer or professional 2.5% Developer, mobile 2.1% Data engineer 1.9% Senior executive (C-suite, VP, etc.) 1.7% Academic researcher 1.7% Data scientist 1.6% AI/ML engineer 1.5% Cybersecurity or InfoSec professional 1.5% Cloud infrastructure engineer 1.4% Founder, technology or otherwise 1.3% System administrator 1.2% Applied scientist 1.1% Data or business analyst 1.1% Developer, game or graphics 1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 7,218 ( 14.7% ) Germany Developer, full-stack 26.6% Developer, back-end 11.8% Student 11.7% Architect, software or solutions 7.1% Developer, desktop or enterprise applications 5.7% Academic researcher 4.1% Developer, front-end 3.6% Developer, embedded applications or devices 3.4% DevOps engineer or professional 3.3% Developer, mobile 2.7% Other 2.1% Engineering manager 2% Data engineer 1.5% Data scientist 1.5% Retired 1.2% Project manager 1.2% Cloud infrastructure engineer 1.1% Cybersecurity or InfoSec professional 1.1% System administrator 1.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 3,022 ( 6.2% ) India Developer, full-stack 25.3% Student 19.6% Developer, back-end 14.7% Architect, software or solutions 6% Developer, front-end 5.9% Developer, mobile 5.4% Developer, desktop or enterprise applications 2.4% Engineering manager 1.9% AI/ML engineer 1.8% Data engineer 1.8% DevOps engineer or professional 1.6% Other 1.3% Developer, embedded applications or devices 1.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,536 ( 5.2% ) United Kingdom Developer, full-stack 28.9% Developer, back-end 15.5% Architect, software or solutions 6% Student 5.4% Developer, desktop or enterprise applications 4.5% Retired 4.2% Developer, embedded applications or devices 3.3% Engineering manager 3.3% Developer, front-end 3.2% Other 2.5% Academic researcher 2.4% Developer, mobile 2.2% DevOps engineer or professional 1.9% Data engineer 1.6% AI/ML engineer 1.5% Senior executive (C-suite, VP, etc.) 1.5% Data scientist 1.4% Founder, technology or otherwise 1.2% Cybersecurity or InfoSec professional 1.1% Data or business analyst 1.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,036 ( 4.2% ) France Developer, full-stack 25.2% Developer, back-end 12.4% Student 11% Architect, software or solutions 7.4% Developer, embedded applications or devices 4.3% Developer, desktop or enterprise applications 4.2% Academic researcher 4% Developer, front-end 3.5% DevOps engineer or professional 3% Developer, mobile 2.3% Data engineer 2.1% Data scientist 1.8% Senior executive (C-suite, VP, etc.) 1.8% AI/ML engineer 1.8% Engineering manager 1.8% Other 1.6% Retired 1.6% Developer, game or graphics 1.4% Cybersecurity or InfoSec professional 1.3% System administrator 1.1% Cloud infrastructure engineer 1.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 1,408 ( 2.9% ) Work experience 1 out of every 4 respondents have less than 5 years of work experience. For architects, 1 out of every 25 have less than 5 years of work experience. How many years of professional work experience do you have? Please round to the nearest whole number, excluding any decimal points. If your answer is '0', please leave blank. All Respondents Full-stack Dev Back-end Dev Architect Enterprise/desktop Dev Front-end Dev All Respondents 1 to 5 years 24.8% 6 to 10 years 19.6% 11 to 15 years 14.2% 16 to 20 years 10.3% 21 to 30 years 12.4% 31 to 40 years 4.4% 41 to 50 years 1.3% More than 50 years 0.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 42,763 ( 87.2% ) Full-stack Dev 1 to 5 years 28.2% 6 to 10 years 24.4% 11 to 15 years 16.3% 16 to 20 years 11.4% 21 to 30 years 12.9% 31 to 40 years 3.6% 41 to 50 years 0.8% More than 50 years 0% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 11,919 ( 24.3% ) Back-end Dev 1 to 5 years 25.4% 6 to 10 years 25.8% 11 to 15 years 19% 16 to 20 years 12% 21 to 30 years 12.2% 31 to 40 years 3% 41 to 50 years 0.6% More than 50 years 0.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 6,266 ( 12.8% ) Architect 1 to 5 years 6.2% 6 to 10 years 13.5% 11 to 15 years 19.8% 16 to 20 years 19.8% 21 to 30 years 27.9% 31 to 40 years 9% 41 to 50 years 1.9% More than 50 years 0.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,688 ( 5.5% ) Enterprise/desktop Dev 1 to 5 years 21.5% 6 to 10 years 16.6% 11 to 15 years 12.9% 16 to 20 years 10.3% 21 to 30 years 21.4% 31 to 40 years 10.6% 41 to 50 years 2.4% More than 50 years 0.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 1,885 ( 3.8% ) Front-end Dev 1 to 5 years 32.8% 6 to 10 years 29.4% 11 to 15 years 16.8% 16 to 20 years 8.5% 21 to 30 years 7.3% 31 to 40 years 1.8% 41 to 50 years 0.2% More than 50 years 0.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 1,878 ( 3.8% ) Industry Most respondents learning to code are in the software development or higher education industry, and almost all of them are using AI to learn. What industry do you work for in? All Respondents Professional Developers Learning to Code Professional Developers (AI) Learning to Code (AI) All Respondents Software Development 52.8% Internet, Telecomm or Information Services 5.5% Fintech 5.4% Manufacturing 4.8% Banking/Financial Services 4.7% Higher Education 4.7% Retail and Consumer Services 3.7% Other 3.1% Transportation, or Supply Chain 2.9% Computer Systems Design and Services 2.9% Media & Advertising Services 2.5% Energy 2.4% Insurance 1.4% Entertainment 0.6% Government & Defense 0.4% Consulting/Professional Services 0.3% Aviation/Aerospace 0.3% Healthcare & Pharmaceuticals 0.3% Non-Profit 0.3% Automotive 0.2% Real Estate 0.2% Agriculture 0.1% Legal 0.1% Human Resources 0.1% Environment 0.1% Marketing 0.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 33,568 ( 68.5% ) Professional Developers Software Development 57.5% Fintech 5.8% Internet, Telecomm or Information Services 5% Banking/Financial Services 4.5% Manufacturing 4.3% Retail and Consumer Services 3.5% Transportation, or Supply Chain 2.9% Higher Education 2.8% Other 2.6% Media & Advertising Services 2.4% Computer Systems Design and Services 2.4% Energy 2.2% Insurance 1.4% Entertainment 0.6% Government & Defense 0.4% Aviation/Aerospace 0.3% Healthcare & Pharmaceuticals 0.2% Automotive 0.2% Consulting/Professional Services 0.2% Non-Profit 0.2% Real Estate 0.2% Agriculture 0.1% Legal 0.1% Human Resources 0.1% Marketing 0.1% Environment 0.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 28,170 ( 57.5% ) Learning to Code Software Development 39.3% Higher Education 13% Other 7.7% Retail and Consumer Services 6.5% Internet, Telecomm or Information Services 5.8% Computer Systems Design and Services 5.5% Manufacturing 5.5% Banking/Financial Services 3.3% Transportation, or Supply Chain 3.3% Media & Advertising Services 2.9% Energy 2.7% Fintech 1.7% Insurance 0.6% Entertainment 0.5% Government & Defense 0.5% Consulting/Professional Services 0.4% Healthcare & Pharmaceuticals 0.3% Automotive 0.2% Aviation/Aerospace 0.1% Non-Profit 0.1% Real Estate 0.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 1,039 ( 2.1% ) Professional Developers (AI) Software Development 57.9% Fintech 6.1% Internet, Telecomm or Information Services 5% Banking/Financial Services 4.5% Manufacturing 4.2% Retail and Consumer Services 3.6% Transportation, or Supply Chain 2.8% Higher Education 2.7% Other 2.5% Media & Advertising Services 2.4% Computer Systems Design and Services 2.3% Energy 2.1% Insurance 1.4% Entertainment 0.6% Government & Defense 0.3% Aviation/Aerospace 0.3% Healthcare & Pharmaceuticals 0.2% Consulting/Professional Services 0.2% Non-Profit 0.2% Automotive 0.2% Real Estate 0.2% Legal 0.1% Agriculture 0.1% Human Resources 0.1% Marketing 0.1% Environment 0% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 23,466 ( 47.9% ) Learning to Code (AI) Software Development 42.9% Higher Education 11.3% Other 6.4% Internet, Telecomm or Information Services 5.7% Retail and Consumer Services 5.7% Computer Systems Design and Services 5.4% Manufacturing 5.2% Banking/Financial Services 3.9% Transportation, or Supply Chain 3.2% Media & Advertising Services 3% Energy 2.9% Fintech 1.5% Insurance 0.7% Consulting/Professional Services 0.5% Government & Defense 0.5% Entertainment 0.4% Automotive 0.3% Healthcare & Pharmaceuticals 0.3% Non-Profit 0.1% Real Estate 0.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 805 ( 1.6% ) Next Technology Site design / logo © 2025 Stack Exchange Inc. 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https://www.fine.dev/blog/announcing-fine-for-startups | Announcing Fine for Startups - Your Junior Full-Stack Developer for $15/Month Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Announcing Fine for Startups - Your Junior Full-Stack Developer for $15/Month Today, we're excited to announce Fine for Startups – a dedicated AI coding agent designed specifically for small teams and founders. Starting at just $15/month, Fine acts as your AI full-stack engineer, taking work off your shoulders, helping you build faster and smarter while keeping your budget intact. The Perfect Addition to Your Startup Team Every startup knows the challenge: too many features to build, too little time, and limited resources. That's where Fine comes in. It's not just another AI coding assistant – it's a full-fledged AI team member that can handle both frontend and backend development tasks, working asynchronously alongside your team to help clear that growing backlog. Real-world Project Ready Unlike other AI solutions that work best with toy projects, Fine is built to handle the complexity of real-life SaaS applications. From React components to API endpoints, Fine understands modern web architectures and can work across your entire stack. True Full-Stack Capabilities: Go Beyond Frontend Development Fine excels across your entire application stack, bringing expertise to both frontend refinement and backend development. On the frontend, Fine helps perfect your product's user experience, implementing new features and polishing your UI. But Fine equally shines in backend development. Unlike simple app builders, Fine is for working on complete, production-ready backend systems. It implements complex business logic in Python, Go, or Node.js, crafts robust API endpoints, and handles everything from authentication to caching. Live Previews: AI That Is Easy To Verify Fine doesn't just write code – it tests it. With built-in cloud development environments, Fine can validate its work in real-time. Each change is built and compiled to catch errors early. For frontend changes, Fine generates shareable live previews so you and your team can see exactly how new features will look and behave before merging. Built for Startup Speed: Async & Always Available Fine works in parallel, tackling your development backlog. Review progress and provide feedback from anywhere, even from your phone while on-the-go. Multiple Fine agents can work simultaneously on different tasks, multiplying your development velocity without multiplying your costs. This is a game-changer for developer productivity. No longer do you need to sit idly while the AI works. You can switch to other tasks, attend meetings, or even solve issues on your mobile phone during your commute. By the time you're back at your desk, a pull request will wait for you. Delegate Work to AI From Everywhere You can offload tasks to Fine from everywhere you are. Use Linear to assign issues to devs? Assign it to Fine, the same way. Tag colleagues whilst reviewing PRs in GitHub? Tag Fine, just like you’re used to. Discuss issues on Slack? Mention Fine. Pricing That Makes Sense Designed to help you with maximum ROI, Fine’s subscription is all-inclusive, with endless features, unlimited messages and no need for your own API keys. Startups are looking for effective, low-cost tools and that’s what Fine offers. For $15 per month, users can connect unlimited repositories, use premium LLMs such as Claude 3.5 Sonnet and resolve as many tasks as you like. Fine also offers a forever-free plan, where users just getting started can try out the platform on one repository, with 7 messages per day, using GPT-4o. Fine’s Pro subscription is 30X cheaper than the nearest competitor which comes in at a whopping $500 for similar features - making it the accessible choice for startups and founders. Get Started Today Ready to expand your team with AI? Start your free trial and see how Fine can help you ship faster while maintaining quality. 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 | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/ai_coding_assistant_for_ios_swift | Using AI Coding Assistants to Develop Software for Apple iOS Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Using AI Coding Assistants to Develop Software for Apple iOS Many developers, particularly front-end, who have adopted AI coding tools to help them code faster, are frustrated that they can’t do so when working on software for iOS mobile app development because there’s no AI coding extension for Apple’s IDE, XCode. GitHub Copilot, which claims to reduce task completion time by 55%, doesn’t integrate with XCode like it does with most other common IDEs, meaning that developers have to copy and paste their tasks into external tools before copying and pasting back into XCode. Not only is this frustrating and time-consuming, but it means that the AI lacks context and therefore produces poor results. However, there is one tool now available that enables you to optimize your iOS software development lifecycle: Fine. Using Fine for AI-Powered Swift Software Development Unlike Cursor and GitHub Copilot, Fine is removed from the IDE. According to Fine’s Founders, they don’t believe the IDE as we know it today will be the primary way developers work in the future. Therefore, they built Fine to be an independent AI coding tool that works for iOS and all other operating systems. Fine’s platform is cloud-based and accessed via the browser, whether mobile or desktop. It integrates with your codebase and development tech stack (GitHub, Linear, etc.) and takes all the information to create a Knowledge Graph that allows it to perform development tasks on its own, with high-accuracy output. Give Fine a task, and it works asynchronously and independently to get the task done. For example: Here is a Linear issue with a new feature request. How should I go about developing this? Build a design plan and then write the first iteration. Take all new PRs, analyze them, review them, test them, and send me a Slack notification with your comments and suggestions. Generate XCTest cases for automated testing in Swift. The Role of Swift in iOS Development with AI Coding Tools Swift, Apple’s primary programming language for iOS, macOS, watchOS, and tvOS development, is fully supported by Fine. Whether you’re working on a new feature, refactoring existing code, or creating unit tests, you can rely on Fine to manage these tasks with a high degree of accuracy, ensuring that your Swift code adheres to best practices and Apple’s guidelines. Using Fine to assist with your iOS software development can save hours of work, helping you become more efficient. Give Fine a task, let it code, and commit a change to GitHub with a PR for you to review. It’s easy, efficient, and makes your workday more enjoyable. Key Benefits of Using Fine for iOS Development Time-Saving : Automate repetitive coding tasks and focus on what matters most. High Accuracy : Fine ensures your Swift code adheres to Apple’s guidelines and best practices. Integration : Seamlessly integrates with your development tools, enhancing your overall workflow. Frequently Asked Questions Q: Does Fine integrate with XCode? A: Fine does not integrate directly with XCode. Instead, it operates independently from the IDE, offering flexibility and efficiency across different development environments, including iOS. Q: How does Fine handle Swift programming tasks? A: Fine supports Swift, Apple’s primary programming language, by managing tasks such as feature development, code refactoring, and unit testing with high accuracy. Q: Can I use Fine with other operating systems? A: Yes, Fine is designed to work with all operating systems, making it a versatile tool for developers working on various platforms. Try Fine now, free for 7 days, and experience how it can streamline your iOS app development process. 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 | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/review-prs-efficiently | 10 Tips for Reviewing PRs Effectively and Efficiently Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back 10 Tips for Reviewing PRs Effectively and Efficiently Table of Contents Understand the Context Review Small, Frequent PRs Focus on Functionality First Check for Consistency Prioritize Security and Performance Test the Changes Locally Provide Constructive Feedback Use Automated Tools Encourage Discussion Balance Thoroughness with Efficiency AI Coding Tools for PR Reviews 1. Understand the Context Before diving into the code, take a moment to understand the purpose of the PR. Read the description carefully, and if available, check out related tickets or documentation. Knowing the context helps you focus on the important aspects of the code. 2. Review Small, Frequent PRs Encourage submitting smaller, more frequent PRs rather than large, monolithic ones. Smaller PRs are easier to review, less prone to errors, and allow for quicker feedback and iteration. 3. Focus on Functionality First Start by reviewing the functionality. Does the code achieve the intended outcome? Ensure that the logic makes sense and that the feature works as described before delving into the finer details. 4. Check for Consistency Look for consistency in code style, naming conventions, and architecture. Consistent code is easier to read, maintain, and scale. Ensure that the changes align with the existing codebase's standards. 5. Prioritize Security and Performance Evaluate the code for potential security vulnerabilities and performance bottlenecks. Consider how the changes might impact the overall system's security and efficiency. 6. Test the Changes Locally If possible, pull the branch and test the changes locally. Running the code yourself can help you spot issues that aren't immediately obvious from the code alone, such as unexpected side effects or integration problems. 7. Provide Constructive Feedback When pointing out issues or suggesting changes, be constructive and specific. Offer explanations and alternatives rather than just highlighting problems. This fosters a positive, collaborative environment. 8. Use Automated Tools for AI Code Review Leverage automated tools to catch common issues such as syntax errors, formatting problems, and simple bugs. Tools like linters, static analysis tools, and automated tests can save time and ensure consistency. AI-powered tools like Fine are great options for catching such issues automatically, giving you more time to focus on functionality and design. 9. Encourage Discussion Use the PR review process as an opportunity to discuss the code with the author and other team members. Engage in meaningful conversations about design decisions, potential improvements, and alternative approaches. 10. Balance Thoroughness with Efficiency Aim to be thorough in your review, but also be mindful of the time it takes. Focus on critical areas first and avoid getting bogged down by minor issues that can be addressed in subsequent PRs. Remember that the goal is to improve the codebase, not to achieve perfection in a single review. AI Coding Tools for PR Reviews By connecting AI tools to your tech stack, the process of reviewing PRs becomes much easier. To start off with, have the AI create a summary of every PR before you review it. That way, no matter how long or short the PR is, you’ll know what it’s meant to do and how, before you begin. Next, you can have the AI Coding tool review the PR before you do. This can help on both ends of the spectrum: On the one hand, it will catch basic fixes, allowing the developer to fix them before your final review, saving your time as a manager. On the other hand, it will identify edge cases that you may not have considered, thereby improving the quality of your code. Fine is an AI Coding tool that not only reviews and summarizes PRs when directly asked to, but also offers automated workflows. Set it up so that any time a new PR is created (in your codebase or a specific repository), it reviews and summarizes it, sending you a Slack message when it’s done and ready for your sign-off. Here’s how it works . 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 | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/how-to-build-an-app-with-ai | How to Build an App with AI: A Step-by-Step Guide Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back How to Build an App with AI: A Step-by-Step Guide If you have an app idea - whether it’s a SaaS business, B2C solution or something for your own use, but you’re not a developer, you’re probably wondering “ how to build an app with AI ” and “ how to build an app using AI ” to get around the obstacles of coding, hosting, and managing your app. This comprehensive guide walks you through the essential steps—from planning and designing your frontend to deploying your finished product—with a strong focus on integrating AI capabilities. Laying the Foundation: The App-Building Introduction The first step is understanding the complete development lifecycle. Before diving into coding, define your app’s purpose, target audience, and the functionalities that will set your app apart. Knowing how to build an app using AI starts with a solid blueprint—one that outlines your vision, design requirements, and technical specifications. What is your app’s primary purpose? How does it do that? What surrounding functionalities does it need? How will users interact with the functionalities? What data do you need? Crafting a Captivating Frontend A user-friendly and responsive frontend is key to engaging users and showcasing your AI features. The Fine documentation’s Frontend guide emphasizes creating intuitive interfaces that seamlessly integrate with backend services. Use modern frameworks and libraries to build an interactive UI that not only looks great but also communicates efficiently with your AI models. Remember, a polished frontend can be the deciding factor when users ask, “ how to build an app with AI ” that feels both innovative and reliable. Fine’s AI Agents will create the frontend based on your prompts. They follow design best practices, ensuring the interface is clear and easy to understand. You don’t need to worry about padding and animations and all of that - ask the AI to build the app for you. Using AI to build an app on the web means you don’t need to worry about responsiveness. Fine AI builds apps that respond to different screen sizes, including mobile, tablet and desktop. The easiest way for non-developers to build an app is to prompt the Agent to create the interface, and let Fine’s AI handle the backend. Bring your idea to life visually and the Agent will work on the behind the scenes logic. Developing a Robust Backend Behind every successful app lies a powerful backend. This consists of a database, user authentication, permissions, billing, logic scripts, integrations and more. Luckily, Fine’s AI has all these features built in, to build the frontend and backend of your app for you. Using Fine means you don’t need to connect to external backend services such as firebase or supabase - it’s all in one place for you. Managing Data with a Reliable Database Data is the lifeblood of any AI application. The Database section in the Fine docs details how to choose and configure a database that meets your app’s needs. Whether you’re working with structured or unstructured data, selecting the right database is critical for effective AI model training and real-time decision-making. This step is fundamental when you’re learning how to build an app with AI that can scale and adapt to growing user demands. Securing Your App with Authentication Security cannot be overlooked, especially when building apps that leverage AI to handle sensitive data. The Authentication guide offers best practices for implementing robust user authentication and authorization protocols. Ensuring that your app is secure builds trust with your users and protects valuable information. For developers curious about how to build an app using AI , integrating strong authentication is a must-have component of a comprehensive solution. There are various ways to authenticate users, but we recommend keeping it simple with an email and password login. If you’re slightly more experienced, you can add social authentication with Google or other platforms. Seamless Deployment: Launching Your AI-Powered App After developing and testing your app’s features, the final step is deployment. The Deployment section provides practical tips for launching your app into production. Fine AI makes it simple to build and launch your app, with deployment built-in to the AI app-builder. It’s just a couple of clicks to take your app live. Conclusion The best way to learn how to build an app with AI is just to get started! Use Fine’s AI App Building Platform to experiment, practice prompting and see what you can build. It’s free to get started and includes everything you need to build an app with AI. To learn more about individual features, prompting best practices and more how-to advice, visit Fine’s Docs. 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 | 2026-01-13T08:48:23 |
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https://www.fine.dev/blog/FAQs | AI Coding FAQs Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back AI Coding FAQs Table of Contents What is AI coding? What are the benefits of AI coding? How does AI coding work? What are some common misconceptions about AI coding? What industries can benefit from AI coding? How does Fine differ from other AI coding tools like GitHub Copilot? Can AI coding tools replace developers? Is Fine suitable for iOS development? What programming languages does Fine support? How can Fine improve team collaboration? What are "AI workflows" in Fine? Can I trust the AI-generated code from Fine? How does Fine help with bug fixing? How do I get started with Fine? Does Fine integrate with existing development tools? Can Fine help with code documentation? How does Fine handle testing? Is Fine suitable for individual developers, or is it better for teams? What kind of AI models does Fine use? How can Fine assist in code reviews? Does Fine offer support for legacy code? How does Fine enhance productivity for developers? Is Fine secure to use with proprietary code? How does Fine help with onboarding new developers? Does Fine support continuous integration/continuous deployment (CI/CD) workflows? How does Fine handle different coding styles and standards? What kind of support is available for Fine users? 1. What is AI coding? AI coding refers to the use of artificial intelligence to assist in the software development process. AI tools like Fine help developers by suggesting code, automating repetitive tasks, and enhancing productivity. 2. What are the benefits of AI coding? AI coding provides numerous benefits, including increased productivity, reduced manual coding errors, faster bug identification, and more efficient handling of repetitive tasks. It allows developers to focus more on creative and complex problem-solving. 3. How does AI coding work? AI coding tools leverage machine learning models trained on vast amounts of code data. These models understand coding patterns, best practices, and common issues, enabling them to provide code suggestions, automate tasks, and even debug code effectively. 4. What are some common misconceptions about AI coding? A common misconception is that AI coding tools will replace developers. In reality, these tools are designed to assist and augment developers' capabilities, handling repetitive and mundane tasks while developers focus on higher-level, strategic decisions. 5. What industries can benefit from AI coding? AI coding can benefit a wide range of industries, including tech, finance, healthcare, and e-commerce. Any industry that relies on software development can leverage AI coding to improve productivity, code quality, and overall efficiency. 6. How does Fine differ from other AI coding tools like GitHub Copilot? Fine stands out by focusing on the entire development workflow, not just code generation. It provides AI agents to code, test, document, and even summarize changes, making it an all-encompassing assistant for dev teams. 7. Can AI coding tools replace developers? No, AI coding tools like Fine are designed to enhance developers' work, not replace them. They take care of repetitive tasks, help troubleshoot, and speed up coding, allowing developers to focus on more creative and critical problem-solving. 8. Is Fine suitable for iOS development? Yes, Fine is particularly well-suited for iOS development, providing code suggestions, automation of testing, and intelligent documentation that improves development speed and accuracy compared to other tools like GitHub Copilot. Fine works well for the most common coding languages - such as Python. 9. What programming languages does Fine support? Fine currently supports popular programming languages like Python, JavaScript, TypeScript, and Swift. The platform continues to expand its language support based on user feedback and needs. 10. How can Fine improve team collaboration? Fine helps improve team collaboration by providing intelligent code reviews and automatically documenting code changes. This keeps everyone on the same page and makes knowledge sharing across teams much easier. Fine seamlessly integrates into where your teams are already collaborating, such as Slack, GitHub, and Linear. 11. What are "AI workflows" in Fine? AI workflows are automated sequences where Fine handles coding, testing, and documentation based on set instructions and triggers. This workflow feature is designed to reduce manual effort and streamline development processes, giving developers more time to innovate. 12. Can I trust the AI-generated code from Fine? Absolutely. Fine's AI coding suggestions are based on best practices and continuous testing. While the AI might not be perfect every time, it assists developers in catching potential issues early and improving code quality. Remember, your code also has mistakes. But Fine uses the best LLMs and can catch many of the simple errors human developers make. 13. How does Fine help with bug fixing? Fine's AI agents can highlight potential bugs, suggest fixes, and even automate parts of the testing process to make sure bugs are caught early. This helps improve customer experience by reducing errors in production. 14. How do I get started with Fine? Getting started is easy! Just visit ai.fine.dev , sign up, and explore the available features, from AI-assisted coding to workflow automation. There’s also documentation and community support to guide you. 15. Does Fine integrate with existing development tools? Yes, Fine integrates seamlessly with popular development tools such as GitHub, GitLab, Slack, Linear, and more. This makes it easy to incorporate Fine into your existing workflow without any major changes. 16. Can Fine help with code documentation? Absolutely. Fine automatically generates documentation for your code, making it easier to understand and maintain. This ensures that knowledge is retained and shared, which is especially useful for onboarding new team members. 17. How does Fine handle testing? Fine can automate the generation of unit tests and other testing processes. It suggests test cases and helps ensure that your code is robust, reducing the risk of errors before deployment. 18. Is Fine suitable for individual developers, or is it better for teams? Fine is designed to be valuable for both individual developers and teams. Individual developers benefit from faster coding and automated documentation, while teams benefit from enhanced collaboration and workflow automation. 19. What kind of AI models does Fine use? Fine uses advanced large language models (LLMs) that are specifically trained on coding tasks. These models are continuously updated to provide the best possible coding suggestions and automation features. 20. How can Fine assist in code reviews? Fine provides intelligent code review suggestions, highlighting potential issues and best practices. It helps developers conduct thorough reviews quickly, improving the quality of the codebase without spending excessive time. 21. Does Fine offer support for legacy code? Yes, Fine can assist with understanding and maintaining legacy code. It can help generate documentation, suggest improvements, and even refactor old code to align with modern best practices. 22. How does Fine enhance productivity for developers? Fine enhances productivity by automating repetitive tasks, suggesting code completions, generating documentation, and providing workflow automation. This allows developers to focus more on creative problem-solving and less on routine tasks. 23. Is Fine secure to use with proprietary code? Security is a top priority for Fine. All data is encrypted, and Fine follows best practices for data security to ensure that your proprietary code and sensitive information remain protected. 24. How does Fine help with onboarding new developers? Fine helps new developers get up to speed faster by providing comprehensive documentation and context-aware code suggestions. This reduces the learning curve and helps new team members become productive sooner. AI coding shouldn't be a crutch for new developers, it should be a launchpad. 25. Does Fine support continuous integration/continuous deployment (CI/CD) workflows? Yes, Fine integrates well with CI/CD pipelines, helping automate testing and deployment tasks. This ensures that your code is always in a deployable state and reduces manual intervention. 26. How does Fine handle different coding styles and standards? Fine is adaptable to different coding styles and standards. You can configure it to align with your team's specific guidelines, ensuring consistency across your codebase. Fine also learns your style based on your repository and tries to mimic it. 27. What kind of support is available for Fine users? Fine provides extensive support, including documentation, tutorials, and a community forum. Additionally, there is customer support available for troubleshooting and helping users get the most out of the platform. 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 | 2026-01-13T08:48:23 |
https://dev.to/hb/react-vs-vue-vs-angular-vs-svelte-1fdm#main-content | React vs Vue vs Angular vs Svelte - 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 Henry Boisdequin Posted on Nov 29, 2020 React vs Vue vs Angular vs Svelte # react # vue # angular # svelte In this article, I'm going to cover which of the top Javascript frontend frameworks: React, Vue, Angular, or Svelte is the best at certain factors and which one is the best for you. There are going to be 5 factors which we are going to look at: popularity, community/resources, performance, learning curve, and real-world examples. Before diving into any of these factors, let's take a look at what these frameworks are. 🔵 React Developed By : Facebook Open-source : Yes Licence : MIT Licence Initial Release : March 2013 Github Repo : https://github.com/facebook/react Description : React is a JavaScript library for building user interfaces. Pros : Easy to learn and use Component-based: reusable code Performant and fast Large community Cons : JSX is required Poor documentation 🟢 Vue Developed By : Evan You Open-source : Yes Licence : MIT Licence Initial Release : Feburary 2014 Github Repo : https://github.com/vuejs/vue Description : Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web. Pros : Performant and fast Component-based: reusable code Easy to learn and use Good and intuitive documentation Cons : Fewer resources compared to a framework like React Over flexibility at times 🔴 Angular Developed By : Google Open-source : Yes Licence : MIT Licence Initial Release : September 2016 Github Repo : https://github.com/angular/angular Description : Angular is a development platform for building mobile and desktop web applications using Typescript/JavaScript and other languages. Pros : Fast server performance MVC Architecture implementation Component-based: reusable code Good and intuitive documentation Cons : Steep learning curve Angular is very complex 🟠 Svelte Developed By : Rich Harris Open-source : Yes Licence : MIT Licence Initial Release : November 2016 Github Repo : https://github.com/sveltejs/svelte Description : Svelte is a new way to build web applications. It's a compiler that takes your declarative components and converts them into efficient JavaScript that surgically updates the DOM. Pros : No virtual DOM Truly reactive Easy to learn and use Component-based: reusable code Cons : Small community Confusion in variable names and syntax The 1st Factor: Popularity All of these options are extremely popular and are used by loads of developers. I'm going to compare these 4 frameworks in google trends, NPM trends, and the Stackoverflow 2020 survey results to see which one is the most popular. Note: Remember that popularity doesn't mean it has the largest community and resources. Google Trends Google trends measures the number of searches for a certain topic. Let's have a look at the results: Note: React is blue, Angular is red, Svelte is gold, Vue is green. The image above contains the trends for these 4 frontend frameworks over the past 5 years. As you can see, Angular and React are by far the most searched, with React being searched more than Angular. While Vue sits in the middle, Svelte is the clear least searched framework. Although Google Trends gives us the number of search results, it may be a bit deceiving so lets of on to NPM trends. NPM Trends NPM Trends is a tool created by John Potter, used to compare NPM packages popularity. This measures how many times a certain NPM package was downloaded. As you can see, React is clearly the most popular in terms of NPM package downloads. Angular and Vue are very similar on the chart, with them going back and forth while Svelte sits at the bottom once again. Stackoverflow 2020 Survey In February of 2020, close to 65 thousand developers filled out the Stackoverflow survey. This survey is the best in terms of what the actual developer community uses, loves, dreads, and wants. Above is the info for the most popular web frameworks. As you can see React and Angular are 2nd and 3rd but React still has a monumental lead. Vue sits happily in the middle but Svelte is nowhere to be seen. Above are the results for the most loved web frameworks. As you can see, React is still 2nd and this time Vue sits in 3rd. Angular is in the middle of the bunch, but yet again Svelte is not there. Note: Angular.js is not Angular Above are the most dreaded web frameworks. As you can see React and Vue are towards the bottom (which is good) while Angular is one of the most dreaded web frameworks. This is because React and Vue developers tend to make fun of Angular, mostly because of its predecessor Angular.js . Svelte is not on this list which is good for the framework. Explaining Svelte's "Bad" Results Some may say that Svelte performed poorly compared to the other 3 frameworks in this category. You would be right. Svelte is the new kid on the block, not many people are using it or know about it. Think of React, Vue, or Angular in their early stages: that's what Svelte is currently. Most of these frontend frameworks comparisons are between React, Vue, or Angular but since I think that Svelte is promising, I wanted to include it in this comparison. Most of the other factors, Svelte is ranking quite highly in. Wrapping up the 1st Factor: Popularity From the three different trends/surveys, we can conclude that React is the most popular out of the three but with Vue and Angular just behind. Popularity: React Angular Vue Svelte Note: it was very hard to choose between Angular and Vue since they are very close together but I think Angular just edges out Vue in the present day. The 2nd Factor: Community & Resources This factor will be about which framework has the best community and resources. This is a crucial factor as this helps you learn the technology and get help when you are stuck. We are going to be looking at the courses available and the community size behind these frameworks. Let's jump right into it! React React has a massive amount of resources and community members behind it. Firstly, they have a Spectrum chat which usually has around 200 developers looking to help you online. Also, they have a massive amount of Stackoverflow developers looking to help you. There are 262,951 Stackoverflow questions on React, one of the most active Stackoverflow tags. React also has a bunch of resources and tutorials. If you search up React tutorial there will be countless tutorials waiting for you. Here are my recommended React tutorials for getting started: Free: https://youtu.be/4UZrsTqkcW4 Paid: https://www.udemy.com/course/complete-react-developer-zero-to-mastery/ Vue Vue also has loads of resources and a large community but not as large as React. Vue has a Gitter chat with over 19,000 members. In addition, they have a massive Stackoverflow community with 68,778 questions. Where Vue really shines is its resources. Vue has more resources than I could imagine. Here are my recommended Vue tutorials for getting started: Free: https://youtu.be/e-E0UB-YDRk Paid: https://www.udemy.com/course/vuejs-2-the-complete-guide/ Angular Angular has a massive community. Their Gitter chat has over 22,489 people waiting to help you. Also, their Stackoverflow questions asked is over 238,506. Like React and Vue, Angular has a massive amount of resources to help you learn the framework. A downfall to these resources is that most of them are outdated (1-2 years old) but you can still find some great tutorials. Here are my recommended Angular tutorials for getting started: Free: https://youtu.be/Fdf5aTYRW0E Paid: https://www.udemy.com/course/the-complete-guide-to-angular-2/ Svelte Svelte has a growing community yet still has many quality tutorials and resources. An awesome guide to Svelte and their community is here: https://svelte-community.netlify.app . They have a decent Stackoverflow community with over 1,300 questions asked. Also, they have an awesome Discord community with over 1,500 members online on average. Svelte has a lot of great tutorials and resources, despite it only coming on to the world stage quite recently. Here are my recommended Svelte tutorials for getting started: Free: https://www.youtube.com/watch?v=zojEMeQGGHs&list=PL4cUxeGkcC9hlbrVO_2QFVqVPhlZmz7tO Paid: https://www.udemy.com/course/sveltejs-the-complete-guide/ Wrapping up the 2nd Factor: Community & Resources From just looking at the Stackoverflow community and the available resources, we can conclude that all of these 4 frameworks have a massive community and available resources. Community & Resources: React Vue & Angular* Svelte *I really couldn't decide between the two! The 3rd Factor: Performance In this factor, I will be going over which of these frameworks are the most performant. There are going to be three main components to this factor: speed test, startup test, and the memory allocation test. I will be using this website to compare the speed of all frameworks. Speed Test This test will compare each of the frameworks in a set of tasks and find out the speed of which they complete them. Let's have a look at the results. As you can see, just by the colours that Svelte and Vue are indeed the most performant in this category. This table has the name of the actions on one side and the results on the other. At the bottom of the table, we can see something called slowdown geometric mean. Slowdown geometric mean is an indicator of overall performance and speed by a framework. From this, we can conclude that this category ranking: Vue - 1.17 slowdown geometric mean Svelte - 1.19 slowdown geometric mean React & Angular - 1.27 slowdown geometric mean Startup Test The startup test measures how long it takes for one of these frameworks to "startup". Let's see the table. As you can see, Svelte is the clear winner. For every single one of these performance tests, Svelte is blazing fast (if you want to know how Svelte does this, move to the "Why is Svelte so performant?" section). From these results, we can create this category ranking. Svelte Vue React Angular Memory Test The memory test sees which framework takes up the least amount of memory for the same test. Let's jump into the results. Similarly to the startup test, Svelte is clearly on top. Vue and React are quite similar while Angular (once again) is the least performant. From this, we can derive this category ranking. Svelte Vue React Angular Why is Svelte so performant? TL;DR: No Virtual DOM Compiled to just JS Small bundles Before looking at why Svelte is how performant, we need to understand how Svelte works. Svelte is not compiled to JS, HTML, and CSS files. You might be thinking: what!? But that's right, instead of doing that it compiles highly optimized JS files. This means that the application needs no dependencies to start and it's blazing fast. This way no virtual DOM is needed. Your components are compiled to Javascript and the DOM doesn't need to update. Also, it also takes up little memory as it complies in highly optimized, small bundles of Javascript. Wrapping up the 3rd Factor: Performance Svelte made a huge push in this factor, blowing away the others! From the three categories, let's rank these frameworks in terms of performance. Svelte Vue React Angular The 4th Factor: Learning Curve In this factor, we will be looking at how long and how easy it is to be able to build real-world (frontend-only) applications. This is one of the most important factors if you are looking to get going with this framework quickly. Let's dive right into it. React React is super easy to learn. React almost takes no time to learn, I would even say if you are proficient at Javascript and HTML, you can learn the basics in a day. Since we are looking about how long it takes to build a real-world project, this is the list of things you need to learn: How React works JSX State Props Main Hooks useState useEffect useRef useMemo Components NPM, Bebel, Webpack, ES6+ Functional Components vs Class Components React Router Create React App, Next.js, or Gatsby Optional but recommended: Redux, Recoil, Zustand, or Providers Vue In my opinion, Vue takes a bit more time than React to build a real project. With a bit of work, you could learn the Vue fundamentals in less than 3 days. Although Vue takes longer to learn, it is definitely one of the fastest popular Javascript frameworks to learn. Here is the list of things you need to learn: How Vue Works .vue files NPM, Bebel, Webpack, ES6+ State management Vuex Components create-vue-app/Vue CLI Vue Router Declarative Rendering Conditionals and Loops Vue Instance Vue Shorthands Optional: Nuxt.js, Vuetify, NativeScript-Vue Angular Angular is a massive framework, much larger than any other in this comparison. This may be why Angular is not as performant as other frameworks such as React, Svelte, or Vue. To learn the basics of Angular, it could take a week or more. Here are the things you need to learn to build a real-world app in Angular: How Angular Works Typescript Data Types Defining Types Type Inference Interfaces Union Types Function type definitions Two-way data binding Dependency Injection Components Routing NPM, Bebel, Webpack, ES6+ Directives Templates HTTP Client Svelte One could argue that Svelte is the easiest framework to learn in this comparison. I would agree with that. Svelte's syntax is very similar to an HTML file. I would say that you could learn the Svelte basics in a day. Here are the things you need to learn to build a real-world app in Svelte: How Svelte Works .svelte files NPM, Bebel, Webpack, ES6+ Reactivity Props If, Else, Else ifs/Logic Events Binding Lifecycle Methods Context API State in Svelte Svelte Routing Wrapping up the 4th Factor: Learning Curve All these frameworks (especially Vue, Svelte, and React) are extremely easy to learn, very much so when one is already proficient with Javascript and HTML. Let's rank these technologies in terms of their learning curve! (ordered in fastest to learn to longest to learn) Svelte React Vue Angular The 5th Factor: Real-world examples In this factor, the final factor, we will be looking at some real-world examples of apps using that particular framework. At the end of this factor, the technologies won't be ranking but it's up to you to see which of these framework's syntax and way of doing things you like best. Let's dive right into it! React Top 5 Real-world companies using React : Facebook, Instagram, Whatsapp, Yahoo!, Netflix Displaying "Hello World" in React : import React from ' react ' ; function App () { return ( < div > Hello World </ div > ); } Enter fullscreen mode Exit fullscreen mode Vue Top 5 Real-world companies using Vue : NASA, Gitlab, Nintendo, Grammarly, Adobe Displaying "Hello World" in Vue : < template > <h1> Hello World </h1> </ template > Enter fullscreen mode Exit fullscreen mode Angular Top 5 Real-world companies using Angular : Google, Microsoft, Deutsche Bank, Forbes, PayPal Displaying "Hello World" in Angular : import { Component } from ' @angular/core ' ; @ Component ({ selector : ' my-app ' , template : &lt;h1&gt;Hello World&lt;/h1&gt; , }) export class AppComponent ; Enter fullscreen mode Exit fullscreen mode Svelte Top 5 Real-world companies using Svelte : Alaska Air, Godaddy, Philips, Spotify, New York Times Displaying "Hello World" in Svelte : <h1> Hello world </h1> Enter fullscreen mode Exit fullscreen mode Wrapping up the 5th Factor: Real-world Examples Wow! Some huge companies that we use on a daily basis use the frameworks that we use. This shows that all of these frameworks can be used to build apps as big as these household names. Also, the syntax of all of these frameworks is extremely intuitive and easy to learn. You can decide which one you like best! Conculsion I know, you're looking for a ranking of all of these frameworks. It really depends but to fulfil your craving for a ranking, I'll give you my personal opinion : Svelte React Vue Angular This would be my ranking but based on these 5 factors, choose whichever framework you like best and feel yourself coding every day in, all of them are awesome. I hope that you found this article interesting and maybe picked a new framework to learn (I'm going to learn Svelte)! Please let me know which frontend framework you use and why you use it. Thanks for reading! Henry Top comments (47) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Collapse Expand stefanovualto stefanovualto stefanovualto Follow Joined Feb 5, 2018 • Nov 29 '20 Dropdown menu Copy link Hide Hi Henry, I mostly agree with the point 1,2,3. But point 4 is subjective depending on your background and previous knowledge. To improve your post, you should add a note explaining what's your background. Finally point 5 are not similar at all. The vue example is a complete page using a reactive property. Anyway as @johnpapa said in a talk, you can achieve almost the same result with any framework, pick the one which feels right for you... :) Like comment: Like comment: 13 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Nov 29 '20 Dropdown menu Copy link Hide Yes, I agree with you! I would recommend anyone to learn the framework which feels right for you. For the Vue example, I'm not an expert at Vue and don't know a better way to do it (if you have a smaller, more concise 'hello world' example, please comment it). I will definitely work an a 'what's my background section'. To explain it know: I've been using React in all my web dev projects. I have basic knowledge of Vue, Angular, and Svelte. After looking at these 5 factors, I plan to use Svelte for my coming projects. Thanks, @stefanovualto for the feedback! Like comment: Like comment: 8 likes Like Comment button Reply Collapse Expand Christopher Wray Christopher Wray Christopher Wray Follow Email chris@sol.company Location Pasco, WA Education Western Governors University Work Senior Software Engineer at Soltech Joined Jan 14, 2020 • Nov 29 '20 • Edited on Nov 29 • Edited Dropdown menu Copy link Hide In the Vue example you are using data components. For the others just plain html. You could have a Vue component with a template of just the h1 tag and no script. It would look more like the svelte example. Like comment: Like comment: 2 likes Like Thread Thread Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Nov 29 '20 Dropdown menu Copy link Hide ✅ Like comment: Like comment: 1 like Like Thread Thread stefanovualto stefanovualto stefanovualto Follow Joined Feb 5, 2018 • Nov 29 '20 • Edited on Nov 29 • Edited Dropdown menu Copy link Hide In your vue example, I think that you should expect to be in a .vue file lik le it seems to be in the others (I mean that you have the whole bundling machinery working under the hood). Then something similar would be: <template> <h1> Hello world! </h1> </template> Enter fullscreen mode Exit fullscreen mode Maybe a pro' for vue is that it can be adopted/used progressively without having to rely on building process (which I am assuming are mandatory for react, svelte and maybe angular). What I mean is that your previous example worked, but it wasn't comparable to the others. Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Zen Zen Zen Follow Mahasiswa Psikologi Email muhzaini30@gmail.com Location Samarinda Education Psikologi, TI Work Developer Android at Toko sepeda Sinar Jaya Joined Mar 25, 2019 • Nov 30 '20 Dropdown menu Copy link Hide I'm usually using Svelte for my projects. Because, it's simple, write less, and get more Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Ryan Carniato Ryan Carniato Ryan Carniato Follow Frontend performance enthusiast and Fine-Grained Reactivity super fan. Author of the SolidJS UI library and MarkoJS Core Team Member. Location Portland, Oregon Education Computer Engineering B.A.Sc, University of British Columbia Work Principal Engineer, Open Source, Netlify Joined Jun 25, 2019 • Dec 3 '20 • Edited on Dec 3 • Edited Dropdown menu Copy link Hide A couple thoughts. "Requires JSX" a downside??? I almost stopped reading at that point. Template DSLs are more or less the same. If that's a con, doesn't support JSX could easily be seen as one. There are reasonable arguments for both sides and this shows extreme bias. Vue is "truly reactive" as well. Whatever that means. Your JS Framework Benchmark results are over 2 years old. Svelte and Vue 3 are both out and in the current results. He now publishes them per Chrome version. Here are the latest: krausest.github.io/js-framework-be... . It doesn't change the final positions much, but Svelte and Vue look much more favorable in newer results. If anyone is interested in how those benchmarks work in more detail I suggest reading: dev.to/ryansolid/making-sense-of-t... Like comment: Like comment: 6 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Dec 3 '20 Dropdown menu Copy link Hide I'm a React dev and it's my favourite framework out of the bunch. When I did some research and asked some other developers when they think of React they think of needing to learn JSX. For something like Svelte, all you need to know is HTML, CSS, and JS. I know that my benchmarks were two years old and I addressed this multiple times before: For the performance factor, I knew that the frameworks were a bit outdated but the general gist stated the same. Svelte 3 was released some time ago and that blows all of the other frameworks out of the water in terms of performance hence Svelte would stay on top. Vue and React are very similar in performance, Vue even says so themselves: vuejs.org/v2/guide/comparison.html. Since, Angular is a massive framework with built-in routing, etc, its performance didn't become better than Vue, React, or Svelte in its newer versions. Thanks for the new benchmark website, I will definitely be using that in the future. Also, I just read your benchmark article and its a good explanation on how these benchmarks work. Thanks for your input. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Ryan Carniato Ryan Carniato Ryan Carniato Follow Frontend performance enthusiast and Fine-Grained Reactivity super fan. Author of the SolidJS UI library and MarkoJS Core Team Member. Location Portland, Oregon Education Computer Engineering B.A.Sc, University of British Columbia Work Principal Engineer, Open Source, Netlify Joined Jun 25, 2019 • Dec 3 '20 • Edited on Dec 3 • Edited Dropdown menu Copy link Hide Here's the index page where he posts new results as they come up: krausest.github.io/js-framework-be... When I did some research and asked some other developers when they think of React they think of needing to learn JSX. For something like Svelte, all you need to know is HTML, CSS, and JS. Svelte has good marketing clearly. Is this HTML? <label> <input type= "checkbox" bind:checked= {visible} > visible </label> {#if visible} <p transition:fade > Fades in and out </p> {/if} Enter fullscreen mode Exit fullscreen mode Or this HTML? <a @ [event]= "doSomething" > ... </a> <ul id= "example-1" > <li v-for= "item in items" :key= "item.message" > {{ item.message }} </li> </ul> Enter fullscreen mode Exit fullscreen mode How about this? <form onSubmit= {handleSubmit} > <label htmlFor= "new-todo" > What needs to be done? </label> <input id= "new-todo" onChange= {handleChange} value= {text} /> <button> Add #{items.length + 1} </button> </form> Enter fullscreen mode Exit fullscreen mode Like comment: Like comment: 4 likes Like Thread Thread Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Dec 3 '20 Dropdown menu Copy link Hide That's why a con of Svelte is its syntax (I added that in my post). This is more explanation to that point: Firstly, for confusion in variable names, I'm talking about how Svelte handles state. Coming from React, state would only be initialized with the useState hook. In Svelte, all the variables you make is state which could be confusing for someone just learning Svelte. Also, for the confusion in syntax, I'm talking about the confusion in logic. For example, if statements in Svelte are different than the usual Javascript if statements which could cause some confusion/more learning time for beginners. There are also other examples of this. Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Zen Zen Zen Follow Mahasiswa Psikologi Email muhzaini30@gmail.com Location Samarinda Education Psikologi, TI Work Developer Android at Toko sepeda Sinar Jaya Joined Mar 25, 2019 • Nov 29 '20 Dropdown menu Copy link Hide why svelte is not seen in search trend? because, svelte's docs is very easy to new comer in this framework Like comment: Like comment: 7 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Nov 29 '20 Dropdown menu Copy link Hide I'm not really sure @mzaini30 . A great pro of Svelte is its docs and tutorial on its website. I think in 1-2 years, you are going to see Svelte at least where Vue is in the search trends. Most of the search trends come from developers asking questions like how to fix this error, or how to do this but since not many people use Svelte (compared to the other frameworks) there are not many questions being asked. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Bergamof Bergamof Bergamof Follow Location Bordeaux, France Education 3iL Work Senior Developer at IPPON Technologies Joined Nov 30, 2020 • Nov 30 '20 Dropdown menu Copy link Hide Sure! Too bad the great Svelte tutorial was not mentioned. Like comment: Like comment: 1 like Like Thread Thread Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Nov 30 '20 Dropdown menu Copy link Hide It's a great tutorial, but I decided to just add video tutorials. In the community factor, I give a link to the Svelte community website which features that tutorial! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Sergiy Yevtushenko Sergiy Yevtushenko Sergiy Yevtushenko Follow Writing code for 35+ years and still enjoy it... Location Krakow, Poland Work Senior Software Engineer Joined Mar 14, 2019 • Dec 3 '20 Dropdown menu Copy link Hide Sad that Solid not even mentioned, although it's the one of the best performing frameworks. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Dec 3 '20 Dropdown menu Copy link Hide I've never actually heard of solid. I'll check it out! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Sergiy Yevtushenko Sergiy Yevtushenko Sergiy Yevtushenko Follow Writing code for 35+ years and still enjoy it... Location Krakow, Poland Work Senior Software Engineer Joined Mar 14, 2019 • Dec 3 '20 Dropdown menu Copy link Hide Well, author of the Solid is even commented in this topic. Like comment: Like comment: 3 likes Like Thread Thread Ryan Carniato Ryan Carniato Ryan Carniato Follow Frontend performance enthusiast and Fine-Grained Reactivity super fan. Author of the SolidJS UI library and MarkoJS Core Team Member. Location Portland, Oregon Education Computer Engineering B.A.Sc, University of British Columbia Work Principal Engineer, Open Source, Netlify Joined Jun 25, 2019 • Dec 16 '20 Dropdown menu Copy link Hide To be fair, performance is only one area and arguably the least important. Even if Solid completely dominates across the board in all things performance by a considerable margin, we have a long way before popularity, community, or realworld usage really makes it worth even being in a comparison of this nature. But I appreciate the sentiment. Like comment: Like comment: 4 likes Like Thread Thread Sergiy Yevtushenko Sergiy Yevtushenko Sergiy Yevtushenko Follow Writing code for 35+ years and still enjoy it... Location Krakow, Poland Work Senior Software Engineer Joined Mar 14, 2019 • Dec 16 '20 Dropdown menu Copy link Hide Well, good performance across the board usually is a clear sign of high technical quality of design and implementation. Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand dallgoot dallgoot dallgoot Follow Location France Joined Oct 3, 2017 • Jan 2 '21 Dropdown menu Copy link Hide I don't want to start a flamewar but i see a trend where React is considered the -only- viable framework and -some- people reacting like religious zealots against any critics because "it's the best ! it's made by Facebook!" React is too hyped IMHO. Svelte is a a true innovation. And yes performance matters. Angular and Vue may lose traction with time... i think... i fail to see their distinctive useful points. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Jan 2 '21 Dropdown menu Copy link Hide I completely agree with you. Most React devs now will not try any other framework and just make fun of the others. I completely agree that React is too hyped. Unfortunately, as you stated, Angular and Vue are losing some traction. I also agree with you that Svelte is a true innovation, this is why I put Svelte at number 1! For 2021, I will focus on using Svelte. Thanks for reading! Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Sylvain Simao Sylvain Simao Sylvain Simao Follow Building kuizto.co 🥦🍄🥔🥕 • Fractional CTO sylvainsimao.com • Prev CTO at Travis, Tech Director at ClemengerBBDO • Love building for the web! Location Brisbane, Australia Work Founder at kuizto.co Joined Mar 7, 2019 • Dec 3 '20 Dropdown menu Copy link Hide React with a smaller learning curve than Vue.js 🤔 Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Dec 3 '20 Dropdown menu Copy link Hide They were very tight but I would say that React has a smaller learning curve as its more intuitive and has easier syntax than Vue. Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Sylvain Simao Sylvain Simao Sylvain Simao Follow Building kuizto.co 🥦🍄🥔🥕 • Fractional CTO sylvainsimao.com • Prev CTO at Travis, Tech Director at ClemengerBBDO • Love building for the web! Location Brisbane, Australia Work Founder at kuizto.co Joined Mar 7, 2019 • Dec 4 '20 Dropdown menu Copy link Hide Sorry @hb , you've decided to go on a touchy subject by writing this article! I will have to disagree with you on that point. I think it's perfectly okay to prefer using React. There are many reasons why it is a good choice. However, an easy learning curve isn't part of it. Just so there is no ambiguity, after having used all the Frameworks from this article - my choice goes towards Vue.js and Svelte, but I'll try to remain as objective as possible. 1) According to the State of JS survey 2018 (not using 2019, because that same question wasn't part of last year's survey). From 20,268 developers interrogated, the number #1 argument about Vue.js is an easy learning curve. For React it comes at position #11 (top 3 beings: elegant programming style, rick package ecosystem, and well-established): 2018.stateofjs.com/front-end-frame... 2018.stateofjs.com/front-end-frame... 2) Main reason why Vue.js is labelled "The Progressive JavaScript Framework", is because it is progressive to implement and to learn. Before you can get started with React, you need to know about JSX and build systems. On the other end, Vue.js can be used just by dropping a single script tag into your page and using plain HTML and CSS. This makes a huge difference in terms of approachability of the Framework. 3) Maybe less objective on this one - but from my own professional experience with both Frameworks and leading teams of developers - it usually takes Junior Developers almost twice the time to become proficient with React than with Vue.js. Firstly because of what I mentioned in point number 2. Secondly, because React has few abstraction leaks that makes performance optimisation something developers have to deal with themselves (using memoize hooks). It's a concept that is hard to understand, but essentials if working on large applications. Thirdly, because of the documentation (as you mentioned in your article). And lastly because of the fragmented ecosystem of libraries that can quickly be overwhelming for Junior Devs. Again, I think there are a lot of reasons why React can be a good choice. But not because of the learning curve. Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Thorsten Hirsch Thorsten Hirsch Thorsten Hirsch Follow Joined Feb 5, 2017 • Nov 29 '20 Dropdown menu Copy link Hide Angular 6? Well, they just released version 11 and there was the switch to Ivy since version 6, so what about a more recent benchmark? And looking at the Google trends chart I wonder why all 3 (React/Angular/Vue) lost quite a bit of their popularity during the past months... any new kid on the block? It's obviously not Svelte, which could hardly benefit from the others' losses. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Nov 30 '20 Dropdown menu Copy link Hide For the performance factor, I knew that the frameworks were a bit outdated but the general gist stated the same. Svelte 3 was released some time ago and that blows all of the other frameworks out of the water in terms of performance hence Svelte would stay on top. Vue and React are very similar in performance, Vue even says so themselves: vuejs.org/v2/guide/comparison.html . Since, Angular is a massive framework with built-in routing, etc, its performance didn't become better than Vue, React, or Svelte in its newer versions. For the search results, they are unpredictable. To my knowledge, there is no new kid on the block in terms of frontend Javascript frameworks. If anything, more people are using Web Assembly. As you can see from the search results graph, it goes up and down, changing all the time. Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Shriji Shriji Shriji Follow Co-Founder @anoram. High-Performance JavaScript Apps. Location Canada Work DevOps at Anoram Joined May 31, 2020 • Nov 29 '20 Dropdown menu Copy link Hide Also, it would be great if you could give a little explanation of this point Confusion in variable names and syntax Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Nov 30 '20 Dropdown menu Copy link Hide Firstly, for confusion in variable names, I'm talking about how Svelte handles state. Coming from React, state would only be initialized with the useState hook. In Svelte, all the variables you make is state which could be confusing for someone just learning Svelte. Also, for the confusion in syntax, I'm talking about the confusion in logic. For example, if statements in Svelte are different than the usual Javascript if statements which could cause some confusion/more learning time for beginners. There are also other examples of this. Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Shriji Shriji Shriji Follow Co-Founder @anoram. High-Performance JavaScript Apps. Location Canada Work DevOps at Anoram Joined May 31, 2020 • Nov 30 '20 Dropdown menu Copy link Hide It makes syntax simpler TBH. React isn't even a direct comparison to Svelte. The only syntax that users will get accustomed to is $ assignments. Like comment: Like comment: 3 likes Like Comment button Reply Collapse Expand Shriji Shriji Shriji Follow Co-Founder @anoram. High-Performance JavaScript Apps. Location Canada Work DevOps at Anoram Joined May 31, 2020 • Nov 29 '20 Dropdown menu Copy link Hide You forgot to mention that Svelte has a great discord :) Like comment: Like comment: 5 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Nov 29 '20 Dropdown menu Copy link Hide I just had a look at it, a great tool! I'll add it to the post! Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Nikola Nikola Nikola Follow Work Angular developer at Cinnamon Agency Joined Jan 21, 2020 • Nov 30 '20 Dropdown menu Copy link Hide Angular con: it is complex? what.... Like comment: Like comment: 2 likes Like Comment button Reply Collapse Expand Nathan Cai Nathan Cai Nathan Cai Follow A JavaScript one trick pony who loves to code. I live and breath NodeJS, currently learning React and Angular. Location Toronto, Ontario, Canada Education High School Work Back End Developer at Ensemble Education Joined Jun 18, 2020 • Dec 1 '20 Dropdown menu Copy link Hide Learning Angular is actually no that bad until RXJS comes in Like comment: Like comment: 4 likes Like Comment button Reply Collapse Expand Henry Boisdequin Henry Boisdequin Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Email boisdequinhenry19@gmail.com Joined Oct 12, 2020 • Dec 1 '20 Dropdown menu Copy link Hide You need to learn Typescript Smart/Dumb Components One-way Dataflow and Immutability And much more It's much more complex and harder to understand than the other frameworks on this list. Like comment: Like comment: 1 like Like Comment button Reply Collapse Expand Nikola Nikola Nikola Follow Work Angular developer at Cinnamon Agency Joined Jan 21, 2020 • Dec 1 '20 Dropdown menu Copy link Hide learn typescript? You mean to start writing it... it's easy and intuitive, I'm writing Angular, React, and Node code only in typescript. Smart/Dumb Components? I really don't understand what is this referred to? Angular has two-way data biding, and even easier data passing to the child and back to the parent. And of course, it has more features, its framework, React is more like a library compared to Angular. Like comment: Like comment: 2 likes Like Thread Thread Hanster Hanster Hanster Follow Joined Oct 19, 2021 • Oct 19 '21 Dropdown menu Copy link Hide I fully agree. Comparing framework e.g angular against library e.g react, is like comparing a smart tv against a traditional tv. Of course smart tv is more challenging to learn it's usage, not because it's lousy, but it has more features beyond watching tv. Like comment: Like comment: 2 likes Like Comment button Reply View full discussion (47 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 Henry Boisdequin Follow Programmer x Swimmer | React Dev, Machine Learning Enthusiast, Rustacean Joined Oct 12, 2020 More from Henry Boisdequin Weekly Update #1 - 10th Jan 2021 # devjournal # rust # typescript # svelte The 6 Month Web Development Mastery Plan in 2020 — For Free # webdev # react # javascript # programming 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Nano Banana Follow Hide Google's AI image generation and image editing tool Create Post Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu Why Asking for Better Outputs Misses the Real Problem Leena Malhotra Leena Malhotra Leena Malhotra Follow Jan 12 Why Asking for Better Outputs Misses the Real Problem # programming # ai # imagegen # nanobanana 2 reactions Comments Add Comment 5 min read What's Coming with LangChainJS and Gemini? Allen Firstenberg Allen Firstenberg Allen Firstenberg Follow for Google Developer Experts Jan 8 What's Coming with LangChainJS and Gemini? # langchain # gemini # nanobanana 24 reactions Comments 1 comment 7 min read 10 AI Superpowers in One App: My Gemini Multi‑Purpose Toolkit Karthick Nagarajan Karthick Nagarajan Karthick Nagarajan Follow Jan 1 10 AI Superpowers in One App: My Gemini Multi‑Purpose Toolkit # gemini # react # nanobanana # webdev Comments Add Comment 8 min read Why GoCrazyAI Exists — And Who Actually Needs It Tim Kurb Tim Kurb Tim Kurb Follow Jan 5 Why GoCrazyAI Exists — And Who Actually Needs It # ai # nanobanana # nextjs 1 reaction Comments Add Comment 3 min read Google Nano Banana: How Prompt Structure Changes AI Image Results Ashwin Mehta Ashwin Mehta Ashwin Mehta Follow Dec 30 '25 Google Nano Banana: How Prompt Structure Changes AI Image Results # googlecloud # gemini # nanobanana # promptengineering 2 reactions Comments Add Comment 2 min read How I’m Building an AI Try-On Tool for Clothing Brands (Behind the Scenes) Nikola Mitrovic Nikola Mitrovic Nikola Mitrovic Follow Dec 10 '25 How I’m Building an AI Try-On Tool for Clothing Brands (Behind the Scenes) # ai # webdev # nanobanana # saas Comments Add Comment 2 min read Create with PerfectPX: Unleash the Power of Our Developer API Ahmed Qaddoura Ahmed Qaddoura Ahmed Qaddoura Follow Dec 7 '25 Create with PerfectPX: Unleash the Power of Our Developer API # ai # automation # gemini # nanobanana Comments Add Comment 8 min read Lights, Camera, Publish! Dev.to Now Supports Video Cover Links Urvisha Maniar Urvisha Maniar Urvisha Maniar Follow Dec 8 '25 Lights, Camera, Publish! Dev.to Now Supports Video Cover Links # devto # ai # nanobanana 9 reactions Comments 1 comment 2 min read This is so real, IS IT AI ?? - How to identify AI generated images Mohamed Roshan Mohamed Roshan Mohamed Roshan Follow Nov 28 '25 This is so real, IS IT AI ?? - How to identify AI generated images # ai # gemini # nanobanana # googlecloud 2 reactions Comments Add Comment 2 min read Stop Waiting: How to Batch-Generate AI Images with Nano Banana Yarden Porat Yarden Porat Yarden Porat Follow Nov 28 '25 Stop Waiting: How to Batch-Generate AI Images with Nano Banana # nanobanana # genai # gemini Comments Add Comment 1 min read Deploy Nano Banana MCP Service in 5 Minutes: Integrate AI Image Generation into Your Workflow adamydwang adamydwang adamydwang Follow Dec 5 '25 Deploy Nano Banana MCP Service in 5 Minutes: Integrate AI Image Generation into Your Workflow # ai # tutorial # opensource # nanobanana Comments Add Comment 5 min read 9 Nano Banana Pro Use Cases That Will Blow Your Mind Nitin Sharma Nitin Sharma Nitin Sharma Follow Nov 26 '25 9 Nano Banana Pro Use Cases That Will Blow Your Mind # ai # productivity # nanobanana # beginners 15 reactions Comments Add Comment 10 min read Nano Banana Pro: A Tiny Powerhouse for Modern Developers C Jordi C Jordi C Jordi Follow Nov 20 '25 Nano Banana Pro: A Tiny Powerhouse for Modern Developers # ai # nanobanana Comments Add Comment 6 min read How to Quickly Access Nano Banana Pro via Replicate with Python Xylar Xylar Xylar Follow Nov 21 '25 How to Quickly Access Nano Banana Pro via Replicate with Python # webdev # ai # python # nanobanana 1 reaction Comments Add Comment 2 min read How to Recreate the Same Image Using Only Text Prompts Neweraofcoding Neweraofcoding Neweraofcoding Follow Dec 13 '25 How to Recreate the Same Image Using Only Text Prompts # webdev # ai # promptengineering # nanobanana 1 reaction Comments Add Comment 4 min read 15 Free AI Video Generators You Can Actually Use in 2025 Carol Luo Carol Luo Carol Luo Follow Dec 11 '25 15 Free AI Video Generators You Can Actually Use in 2025 # ai # nanobanana # image # programming 2 reactions Comments Add Comment 8 min read How to Install Z-Image Turbo Locally Hugh Hugh Hugh Follow Dec 10 '25 How to Install Z-Image Turbo Locally # webdev # ai # programming # nanobanana 4 reactions Comments Add Comment 3 min read Introducing Nano Banana Pro: Complete Developer Tutorial Guillaume Vernade Guillaume Vernade Guillaume Vernade Follow for Google AI Nov 21 '25 Introducing Nano Banana Pro: Complete Developer Tutorial # gemini # nanobanana # ai # tutorial 199 reactions Comments 9 comments 10 min read Free tool to remove watermarks from AI images, 100% private Jawuil Pineda Jawuil Pineda Jawuil Pineda Follow Nov 29 '25 Free tool to remove watermarks from AI images, 100% private # ai # nanobanana # tooling # imagen Comments Add Comment 1 min read Nano-Banana Pro: Prompting Guide & Strategies Guillaume Vernade Guillaume Vernade Guillaume Vernade Follow for Google AI Nov 27 '25 Nano-Banana Pro: Prompting Guide & Strategies # ai # gemini # nanobanana # promptengineering 138 reactions Comments 5 comments 15 min read Build with Nano Banana Pro, our Gemini 3 Pro Image model Alisa Fortin Alisa Fortin Alisa Fortin Follow for Google AI Nov 20 '25 Build with Nano Banana Pro, our Gemini 3 Pro Image model # gemini # nanobanana # ai # programming 87 reactions Comments 4 comments 5 min read How PROMPT FIX Brings NanoBanana , Seedream, ComfyUI and Qwen Image Edit 2509 Directly Into Photoshop shara shara shara Follow Oct 10 '25 How PROMPT FIX Brings NanoBanana , Seedream, ComfyUI and Qwen Image Edit 2509 Directly Into Photoshop # ai # photoshop # aiart # nanobanana Comments Add Comment 4 min read nano-banana special prompt achieved rapid Mobile UI Mockups Oikon Oikon Oikon Follow Sep 14 '25 nano-banana special prompt achieved rapid Mobile UI Mockups # ai # nanobanana # gemini # uidesign 10 reactions Comments Add Comment 7 min read 🚀 Gemini 2.5 “Nano Banana 🍌 ”: Ultra-Light Linux Image for Banana Pi M2 Zero & NanoPi Neo Air Hemant Hemant Hemant Follow Sep 13 '25 🚀 Gemini 2.5 “Nano Banana 🍌 ”: Ultra-Light Linux Image for Banana Pi M2 Zero & NanoPi Neo Air # nanobanana # gemini Comments Add Comment 4 min read Architecting a Generative AI Pipeline for Automated Sprite Sheet Creation for Animation Usman Mehfooz Usman Mehfooz Usman Mehfooz Follow Sep 11 '25 Architecting a Generative AI Pipeline for Automated Sprite Sheet Creation for Animation # ai # googlecloud # nanobanana # spriteanimation 3 reactions Comments 3 comments 6 min read loading... trending guides/resources Nano-Banana Pro: Prompting Guide & Strategies Introducing Nano Banana Pro: Complete Developer Tutorial How to Install Z-Image Turbo Locally This is so real, IS IT AI ?? - How to identify AI generated images How to Recreate the Same Image Using Only Text Prompts How to Quickly Access Nano Banana Pro via Replicate with Python What's Coming with LangChainJS and Gemini? Build with Nano Banana Pro, our Gemini 3 Pro Image model 9 Nano Banana Pro Use Cases That Will Blow Your Mind Lights, Camera, Publish! Dev.to Now Supports Video Cover Links 15 Free AI Video Generators You Can Actually Use in 2025 Why Asking for Better Outputs Misses the Real Problem As someone deeply invested in the future of full-stack development and game design, the release o... How I’m Building an AI Try-On Tool for Clothing Brands (Behind the Scenes) Google Nano Banana: How Prompt Structure Changes AI Image Results 10 AI Superpowers in One App: My Gemini Multi‑Purpose Toolkit Deploy Nano Banana MCP Service in 5 Minutes: Integrate AI Image Generation into Your Workflow Nano Banana Pro: A Tiny Powerhouse for Modern Developers Create with PerfectPX: Unleash the Power of Our Developer API 💎 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 | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/20-things-to-do | 20 Things You Can Do With Your Extra Free Time Now That You’re Using AI Coding Tools to Develop Software Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back 20 Things You Can Do With Your Extra Free Time Now That You’re Using AI Coding Tools to Develop Software So, you’ve discovered the magic of AI coding for software development, and suddenly, your to-do list is looking a whole lot shorter. What are you going to do with all that extra free time? Sit around and binge-watch your favorite show? (Okay, maybe a little of that.) But why not make the most of it? Here are 20 things you can finally start doing now that AI Coding Tools have your back. Go to the gym : Remember that gym membership you’ve been paying for but never using? Time to dust off those sneakers and get moving. Pick up a hobby : Always wanted to learn guitar? Or maybe knitting? Now you’ve got the time to actually get good at it. Start a side project : Got a brilliant idea you’ve been sitting on for years? No more excuses—get cracking on that side project and make it a reality. (Not another piece of software, that doesn’t count.) Visit your grandma : Seriously, she misses you. Go spend some quality time with her and listen to those stories she loves to tell. And when she asks you how’s work, just tell her it’s great; you don’t need to explain what AI is and how you use AI for coding. Read a book : Not just any book—pick up that classic you’ve always meant to read. You’ll feel so cultured. Take a cooking class : Move beyond instant ramen and learn to cook a meal that’ll actually impress people. Explore your city : Play tourist in your own town. Visit that museum you’ve never been to or take a walk in the park. Plan a weekend getaway : Use your newfound free time to get out of town and explore somewhere new. Catch up with friends : Remember those people you used to hang out with before life got so busy? Give them a call and catch up. Sleep in : You deserve it. No more burning the midnight oil over code. Let the AI handle it while you catch some extra Z’s. Get organized : Declutter your space, organize your files, and get your life in order. Volunteer : Use your time to give back. Find a cause you’re passionate about and lend a hand. Binge-watch that series : Okay, we had to include this. But just one season, alright? Write a blog : Share your thoughts, experiences, or expertise. Who knows, you might just inspire someone. Learn a new language : Not a coding language, one that real people speak. Bonjour, hola, or konnichiwa! Pick a language and start learning. Try meditation : Chill out and find your zen. It’s amazing what a little mindfulness can do. Update your resume : You’re killing it with all this extra productivity—make sure your resume reflects that. Go on a digital detox : Unplug for a day and see how freeing it can be. Take up photography : Capture the beauty around you and see the world through a new lens. Plan your next big thing : With AI handling the grind, what’s next for you? The sky’s the limit. So there you have it—20 ways to make the most of your newfound free time. Go ahead, enjoy life a little more while your AI Coding Tools keep your software projects on track. Did you know that Fine does more than just generate code? Imagine automating all of this: PR reviews Writing documentation Upgrading dependencies Triaging issues AI Coding Tools can save time and effort in your day-to-day work. Try it now, free for 7 days. 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 | 2026-01-13T08:48:23 |
https://topenddevs.com/podcasts/adventures-in-angular/episodes/using-the-localstorage-object-in-angular-with-dany-paredes-aia-358 | Using the LocalStorage Object in Angular with Dany Paredes - AiA 358 - Adventures in Angular - Top End Devs Top End Devs Home Podcasts Screencasts Courses Blogs Summits Meetups search-modal#open" aria-label="Search"> Sign In Sign Up search-modal#close"> Search search-modal#close"> search-modal#search" data-turbo-frame="search-results" data-turbo="true" class="space-y-4" action="/search" method="get"> Content Type All Episodes Podcasts Screencasts Lessons Courses Blog Authors Meetups Use semantic search (recommended) Search Trending Now What’s New in React 19.2: Compiler, Activity, and the Future of Async React - JSJ 670 JavaScript Jabber Can You Really Trust AI-Generated Code? - JSJ 699 JavaScript Jabber Autogenetic AI Agents and the Future of Ruby Development - RUBY 682 Ruby Rogues Popular Searches search-modal#fillSearch" data-search-term="podcast"> Podcast search-modal#fillSearch" data-search-term="episode"> Episode search-modal#fillSearch" data-search-term="author"> Author search-modal#fillSearch" data-search-term="meetup"> Meetup search-modal#fillSearch" data-search-term="series"> Series Back to Adventures in Angular RSS Feed Spotify Apple Podcasts YouTube Amazon Music Using the LocalStorage Object in Angular with Dany Paredes - AiA 358 Published: October 06, 2022 Download Using the LocalStorage Object in Angular with Dany Paredes - AiA 358 0:00 audio-player#clickProgressBar touchstart->audio-player#clickProgressBar touchmove->audio-player#clickProgressBar" data-audio-player-target="progressBar"> 0:00 audio-player#skipBackward"> audio-player#togglePlayPause" data-audio-player-target="playPauseButton"> audio-player#skipForward"> audio-player#changeVolume" type="range" min="0" max="1" step="0.01" value="1" /> Playback Speed: audio-player#changePlaybackSpeed"> 0.5x 0.75x 1x 1.25x 1.5x 2x Created by: Charles Max Wood • Dany Paredes Show Notes In Angular apps, remembering user-preferred settings is an excellent way to provide a good experience for the users; you can save data in the user’s browser using the localStorage object, which provides methods for working the key-value data. Today on the show, GDE Angular expert Dany Paredes shares his insights about localStorage, how to learn about this API, and knowledge to build in Angular to save background color preferences. In this episode… How localStorage works and limitations API examples and use cases Possible performance issues Trusting the localStorage and API mock values Complicated use cases Angular content in Spanish Sponsors Top End Devs Raygun | Click here to get started on your free 14-day trial Coaching | Top End Devs Links ng-content Angular Basics: localStorage Object Keeps Data in Browser Twitter: @danywalls Dany Paredes | Javascript / Web Picks Charles- Quartile Charles- Funnel Hacking LIVE 2022 Charles - Angular Remote Conf Dany – Enjoys comparing NBA players to Angular developers © 2026 2022 Intentional Excellence Productions, LLC. All rights reserved. | 2026-01-13T08:48:23 |
https://share.transistor.fm/s/39dd8518#goodpods-path-1 | APIs You Won't Hate | Developing platforms for developers - Harsha Reddy from Wayfair APIs You Won't Hate 40 ? 30 : 10)" @keyup.document.left="seekBySeconds(-10)" @keyup.document.m="toggleMute" @keyup.document.s="toggleSpeed" @play="play(false, true)" @loadedmetadata="handleLoadedMetadata" @pause="pause(true)" preload="none" @timejump.window="seekToSeconds($event.detail.timestamp); shareTimeFormatted = formatTime($event.detail.timestamp)" > Trailer Bonus 10 40 ? 30 : 10)" class="seek-seconds-button" > 40 ? 30 : 10"> Subscribe Share More Info Download More episodes Subscribe newValue ? setTimeout(() => copied = false, 2500) : null)" @click="copied = copyFeedUrl()" class="form-input-group" > Copied to clipboard Apple Podcasts Spotify Pocket Casts Overcast Castro YouTube Goodpods Goodpods Metacast Amazon Music Pandora CastBox Anghami Anghami Fountain JioSaavn Gaana iHeartRadio TuneIn TuneIn Player FM SoundCloud SoundCloud Deezer Podcast Addict Share newValue ? setTimeout(() => copied = false, 2500) : null)" @click="copied = copyShareUrl()" class="form-input-group" > Share Copied to clipboard newValue ? setTimeout(() => copied = false, 2500) : null)" @click="copied = copyEmbedHtml()" class="form-input-group" > Embed Copied to clipboard Start at Trailer Bonus Full Transcript View the website updateDescriptionLinks($el))" class="episode-description" > Chapters September 18, 2020 by APIs You Won't Hate View the website Listen On Apple Podcasts Listen On Spotify Listen On YouTube RSS Feed Subscribe RSS Feed RSS Feed URL Copied! Follow Episode Details Harsha Reddy, a Senior Software Engineer on Internal API Platforms for Wayfair, joins Matt and Phil to talk about managing APIs and developer tooling across multiple languages and countries. Show Notes Harsha Reddy, a Senior Software Engineer on Internal API Platforms for Wayfair, joins Matt and Phil to talk about what its like to build tools for developers that use a myriad of languages from PHP to C# to Python and some Java thrown in for a good time. We discuss how Wayfair empowers their developers to pick the right language for a job and then what kind of tools they employ to make their day to day lives at Wayfair easier. Sponsors: Stoplight makes it possible for us to bring you this podcast while we nerd out about APIs. Check them out for their tooling around documentation with Studio, an app that makes API documentation an absolute joy to work with. Links: https://pactflow.io https://eng.uber.com/microservice-architecture/ https://buildkite.com Harsha on Twitter: https://twitter.com/stymied_sloth Creators and Guests Host Mike Bifulco Cofounder and host of APIs You Won't Hate. Blogs at https://mikebifulco.com Into 🚴♀️, espresso ☕, looking after 🌍. ex @Stripe @Google @Microsoft What is APIs You Won't Hate? A no-nonsense (well, some-nonsense) podcast about API design & development, new features in the world of HTTP, service-orientated architecture, microservices, and probably bikes. All audio, artwork, episode descriptions and notes are property of APIs You Won't Hate, for APIs You Won't Hate, and published with permission by Transistor, Inc. Broadcast by | 2026-01-13T08:48:23 |
https://www.gsb.stanford.edu/faculty-research/working-papers/does-working-home-work-evidence-chinese-experiment | Does Working from Home Work? Evidence from a Chinese Experiment: Working Paper Skip to main content Menu Enter the terms you wish to search for. Faculty & Research Menu Faculty Publications Books Working Papers Case Studies Postdoctoral Scholars Research Labs & Initiatives Behavioral Lab Data, Analytics & Research Computing Faculty Publications Books Working Papers Case Studies Research Labs & Initiatives Behavioral Lab DARC Faculty & Research Working Papers Does Working from Home Work? Evidence from a Chinese Experiment Does Working from Home Work? Evidence from a Chinese Experiment By Nicholas A. Bloom James Liang John Roberts Zhichun Jenny Ying March 2013 | Working Paper No. 3109 Economics Download About 10% of US employees now regularly work from home (WFH), but there are concerns this can lead to “shirking from home.” We report the results of a WFH experiment at CTrip, a 16,000- employee, NASDAQ-listed Chinese travel agency. Call center employees who volunteered to WFH were randomly assigned to work from home or in the office for 9 months. Home working led to a 13% performance increase, of which about 9% was from working more minutes per shift (fewer breaks and sick-days) and 4% from more calls per minute (attributed to a quieter working environment). Home workers also reported improved work satisfaction and experienced less turnover, but their promotion rate conditional on performance fell. Due to the success of the experiment, CTrip rolled-out the option to WFH to the whole firm and allowed the experimental employees to re-select between the home or office. Interestingly, over half of them switched, which led to the gains from WFH almost doubling to 22%. This highlights the benefits of learning and selection effects when adopting modern management practices like WFH. Related Related Nicholas Bloom Professor (by courtesy), Economics John Roberts Professor Emeritus, Economics View Published Paper Does Working from Home Work? Evidence from a Chinese Experiment Nicholas A. Bloom James Liang John Roberts Zhichun Jenny Ying 655 Knight Way Stanford, CA 94305 USA Footer contact links Contact Us Visit Us Stay In Touch Follow Us Twitter Facebook Instagram YouTube LinkedIn Footer 1 Companies, Organizations & Recruiters Stanford Community Newsroom Footer 2 Library Jobs MyGSB © Stanford Graduate School of Business Footer legal links Accessibility Non-Discrimination Policy Privacy Policy Terms of Use Stanford University | 2026-01-13T08:48:23 |
https://docs.suprsend.com/docs/developer/versioning/sdk-versioning | Versioning and Support Policy - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection Developer Resources Overview Updates and Versioning Versioning and Support Policy SDK Changelog Authentication API Keys and Secrets Service Token Best Practices for Key & Token Management MCP Overview BETA Quickstart Tool List Building with LLMs Security Security SDKs and APIs SDKs Management API REST API Postman Collection Features Validate Trigger Payload Type Safety Testing Testing the Template Test Mode Monitoring and Logging Logs Data Out Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation Updates and Versioning Versioning and Support Policy Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Updates and Versioning Versioning and Support Policy OpenAI Open in ChatGPT Learn about SuprSend’s versioning and support policy for SDKs and APIs. OpenAI Open in ChatGPT Changelog View all SDK releases and updates Migration Guides Step-by-step upgrade instructions SDK Documentation Complete SDK integration guides Versioning Policy SuprSend’s SDK versioning policy is based on the Semantic Versioning (SemVer) standard. For example, in version 4.3.2, 4 is the major , 3 is the minor , and 2 is the patch . Major. Breaking changes that are backward incompatible (e.g., renaming SDK exception classes). Minor. New features that are backward compatible (e.g., adding new methods or optional parameters). Patch. Backward-compatible bug fixes (e.g., fixing file upload listing issues). Each SDK version is coupled with the API version that was current at the time of release. This ensures stable and predictable API behavior across versions. Support Policy All new features, performance improvements, and bug fixes are released on the latest major version of each SDK. Older major versions remain functional, but updates are only rolled out to the most recent major release. SuprSend maintains backward compatibility across all SDKs, ensuring existing integrations continue to work as expected. However, we recommend upgrading to the latest version to take advantage of improved authorization mechanisms (especially in frontend SDKs), better performance, and access to new API capabilities. Our release cycle is synchronized with product development milestones, so SDK and API versions evolve together. This ensures consistent behavior across the platform and prevents breaking changes in existing implementations. Comprehensive migration guides are provided for each major version upgrade, helping you transition with minimal code changes and predictable results. Migration Guides We provide migration guides to help you upgrade from older major SDK versions. You can find them in our documentation: Migration guide from v1 React migration guide Web SDK migration guide Language Support Policy We currently support all SDK languages without any deprecation timeline. In the unlikely event of deprecating a language or version in the future, advance notice will be provided to ensure sufficient migration time. Language Support Status Language Version Status Support Level Node.js 14+ ✅ Active Full Support JavaScript All Versions ✅ Active Full Support React 16.8+ ✅ Active Full Support Python 3.9+ ✅ Active Full Support Java 8+ ✅ Active Full Support Go 1.18+ ✅ Active Full Support Swift iOS 15+ ✅ Active Full Support Kotlin Android (all versions) ✅ Active Full Support React Native All Versions ✅ Active Full Support Flutter >=2.5.0 ✅ Active Full Support All supported language versions receive full support with no deprecation timeline. This includes regular updates, security patches, and comprehensive documentation. Release Policy We follow agile methodologies to ensure rapid and flexible development. Roadmap Features: Features are released as soon as development and testing are complete, typically at a rate of ~1-2 per week. There is no fixed release day. We prioritize user feedback and market needs when planning feature releases. Versions in Backend SDKs: New versions are released mainly for new API additions. User-facing APIs will always be backward compatible. We maintain comprehensive API versioning to ensure smooth transitions for existing integrations. Frontend SDKs: We incrementally add features in frontend SDKs such as Inbox, and release depends on our roadmap. Frontend updates focus on enhancing user experience and adding interactive capabilities. Bug Fixes & Improvements: Bug fixes are prioritized and released as soon as they are identified. Critical security fixes are released immediately, while minor improvements are batched for regular releases. Communication: Releases are announced on our Slack community , in-app and via email newsletters . Important features are also communicated directly in shared groups. We provide detailed changelogs and migration guides for major updates. Best Practices Pre-Upgrade Checklist • Test in staging environment first • Review changelog for breaking changes • Backup your current implementation • Verify all dependencies are compatible Migration Steps • Follow our detailed migration guides • Update incrementally and test thoroughly • Monitor application after deployment • Have a rollback plan ready 💡 Pro tip: Start with patch upgrades before moving to minor or major versions to minimize risk. Was this page helpful? Yes No Suggest edits Raise issue Previous SDK Changelog Complete release history for all SuprSend SDKs with detailed release notes, features, fixes, and breaking changes. Next ⌘ I x github linkedin youtube Powered by On this page Versioning Policy Support Policy Migration Guides Language Support Policy Language Support Status Release Policy Best Practices | 2026-01-13T08:48:23 |
https://socket.io/fr/docs/v4/broadcasting-events/ | Broadcasting events | Socket.IO Aller au contenu principal Latest blog post (July 25, 2024): npm package provenance . Socket.IO Docs Guide Tutorial Exemples Emit cheatsheet API côté serveur API côté client Ecosystem Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Devenir un sponsor 4.x 4.x 3.x 2.x Changelog Français English Español Français Português (Brasil) 中文（中国） Chercher Socket.IO Documentation Serveur Client Evènements Emitting events Listening to events Broadcasting events Rooms Adapteurs Avancé Migrations Divers Evènements Broadcasting events Version: 4.x Sur cette page Broadcasting events Socket.IO makes it easy to send events to all the connected clients. info Please note that broadcasting is a server-only feature. To all connected clients io . emit ( "hello" , "world" ) ; attention Clients that are currently disconnected (or in the process of reconnecting) won't receive the event. Storing this event somewhere (in a database, for example) is up to you, depending on your use case. To all connected clients except the sender io . on ( "connection" , ( socket ) => { socket . broadcast . emit ( "hello" , "world" ) ; } ) ; remarque In the example above, using socket.emit("hello", "world") (without broadcast flag) would send the event to "client A". You can find the list of all the ways to send an event in the cheatsheet . With multiple Socket.IO servers Broadcasting also works with multiple Socket.IO servers. You just need to replace the default adapter by the Redis Adapter or another compatible adapter . In certain cases, you may want to only broadcast to clients that are connected to the current server. You can achieve this with the local flag: io . local . emit ( "hello" , "world" ) ; In order to target specific clients when broadcasting, please see the documentation about Rooms . Éditer cette page Dernière mise à jour le 15 nov. 2025 Précédent Listening to events Suivant Rooms To all connected clients To all connected clients except the sender With multiple Socket.IO servers Documentation Guide Tutorial Exemples API côté serveur API côté client Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Devenir un sponsor Copyright © 2022 Socket.IO | 2026-01-13T08:48:23 |
https://nutrify.app/nutrify-goes-to-school-v1.html | Nutrify - Whole Food Education for Schools Homepage Nutrify Goes to School (V1) 📸 -> 🍌 @ 🏫 7 Nov 2024 - Author: Daniel Bourke (Co-Founder) Josh and I presenting Nutrify as well as the health benefits of whole foods in front of a class of 25 year 1s and 2s at a local school. An exciting day for Nutrify today! We had our first whole food education session at a local Brisbane school. And it turns out... the kids loved it! Joshua Bourke and I went to the local markets and collected a basket of various whole foods. Bananas, sweet potato, apples, avocado, and the less common (but still in Nutrify), artichoke and galangal. We ran two 30 minute sessions with groups of year 1 and 2s (six and seven year olds). To make it interactive we invited students one by one and eventually in groups of two to choose a food from the basket and hold it up in front of the class to see what it was. Once the students identified the foods, we also asked them to rate them on a scale of 0 to 5. Where: 0 = most processed (e.g. soda/pop tarts) 5 = whole foods/single ingredient foods (e.g. fruits/vegetables) Students immediately understood this scale, rating every fruit/vegetable 5 points and the processed foods we brought along as 0 points. So where did Nutrify come in? To add another level of interactivity, we asked students to take a photo of the foods with an iPad running Nutrify. Using computer vision models (on-device, no internet connection required - important for schools & privacy), Nutrify identified each whole food instantly and provided nutrition information in a colourful and easy-to-understand manner. An example of Nutrify For Schools running on iPad. Thanks to on-device machine learning models, the app works offline and does not require an internet connection. Nutrify For Schools comes pre-loaded with 500+ foods to create an interactive whole food learning opportunity. One student yelled out “This is like Pokémon for foods!” Our goal at Nutrify is to incentivise people, especially kids, to eat more whole foods, foods that don't need a barcode or long lists of ingredients. The rating scale seems to have worked too. When we asked the kids, “If you were designing a healthy plate, what scores would you like most of?” They all yelled out “5!!!!” And I couldn't help but smile and laugh. Some of the feedback: “Are you coming back?” asked a student. “Would you like us to come back?” We replied. “Yes!” And from a teacher watching from another classroom: “This is a must on every iPad...” We're biased, but we agree! So if you'd like to see Nutrify at your local school, please let us know , we'd love to show it off. Or if you're involved in the school system and know how we might make Nutrify more tailored to the curriculum so we can expand to more schools, please reach out, we'd love your advice. Our dream is to make Nutrify available on every iPad in every school and for it to be the go to place for fun, interactive food education. Josh and I standing out the front of a local school (about 300m from Nutrify HQ) after presenting Nutrify as well a range of different whole foods to students. Reviews Here's what the teachers had to say: Nutrify provided an engaging incursion at our school which opened our students' eyes to the exciting world of health and whole foods. Students were provided with hands-on experiences as they explored the app and learnt about the design process that led to its creation. Dan and Josh’s passion for educating children about the importance of fuelling their body with healthy and nutritious foods had all the children wanting to learn more. — Angela Hennessy, Assistant Principal, Sacred Heart Primary School The Nutrify App Team did an amazing job engaging our Early Years class with their fun and interactive session on nutrition! The kids absolutely loved the hands-on activities using the app and were inspired to make healthier choices every day. — Year 1 Teacher, Sacred Heart Primary School Questions, suggestions and feedback Have any questions about this update, suggestions for future updates or ideas for what foods we should add next? Feel free to reach out to us at [email protected] (Daniel or Josh will reply)! Download Nutrify on the App Store Nutrify Homepage @nutrifyfoodapp on Instagram / TikTok / X Credit roll Nutrition data is curated and FoodVision AI computer vision models are trained by Daniel Bourke. All iOS interfaces are designed and built by Joshua Bourke. Food image data is collected and labelled by Joseph Drury, Samuel Bourke and Daniel Bourke. Food icons are designed and created by Grace Lee. × | 2026-01-13T08:48:23 |
https://survey.stackoverflow.co/2025/ai?utm_source=chatgpt.com#1-ai-tool-sentiment | AI | 2025 Stack Overflow Developer Survey Products Stack Overflow Where developers and technologists go to gain and share knowledge. Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers Advertising Reach devs & technologists worldwide about your product, service or employer brand Knowledge Solutions Data licensing offering for businesses to build and improve AI tools and models Labs The future of collective knowledge sharing About the company Visit the blog Developers Technology AI Work Stack Overflow Methodology 3 AI In this section we gain insight into the real sentiments behind the surge in AI popularity. Is it making a real impact in the way developers work or is it all hype? 3.1. Sentiment and usage → 3.2. Developer tools → 3.3. AI Agents → 3.1 Sentiment and usage AI tools in the development process 84% of respondents are using or planning to use AI tools in their development process, an increase over last year (76%). This year we can see 51% of professional developers use AI tools daily. Do you currently use AI tools in your development process? All Respondents Professional Developers Learning to Code Early Career Devs Mid Career Devs Experienced Devs All Respondents Yes, I use AI tools daily 47.1% Yes, I use AI tools weekly 17.7% Yes, I use AI tools monthly or infrequently 13.7% No, but I plan to soon 5.3% No, and I don't plan to 16.2% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 33,662 ( 68.7% ) Professional Developers Yes, I use AI tools daily 50.6% Yes, I use AI tools weekly 17.4% Yes, I use AI tools monthly or infrequently 12.8% No, but I plan to soon 4.6% No, and I don't plan to 14.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 26,004 ( 53% ) Learning to Code Yes, I use AI tools daily 39.5% Yes, I use AI tools weekly 18.7% Yes, I use AI tools monthly or infrequently 15.1% No, but I plan to soon 7.2% No, and I don't plan to 19.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,843 ( 5.8% ) Early Career Devs Yes, I use AI tools daily 55.5% Yes, I use AI tools weekly 18.1% Yes, I use AI tools monthly or infrequently 11.5% No, but I plan to soon 2.5% No, and I don't plan to 12.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 6,360 ( 13% ) Early career defined as 1 - 5 years work experience Mid Career Devs Yes, I use AI tools daily 52.8% Yes, I use AI tools weekly 16.8% Yes, I use AI tools monthly or infrequently 13.5% No, but I plan to soon 3.7% No, and I don't plan to 13.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 5,997 ( 12.2% ) Mid career defined as 5 - 10 years work experience Experienced Devs Yes, I use AI tools daily 47.3% Yes, I use AI tools weekly 17.2% Yes, I use AI tools monthly or infrequently 13% No, but I plan to soon 6% No, and I don't plan to 16.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 13,001 ( 26.5% ) Experienced dev defined as 10+ years work experience AI tool sentiment Conversely to usage, positive sentiment for AI tools has decreased in 2025: 70%+ in 2023 and 2024 to just 60% this year. Professionals show a higher overall favorable sentiment (61%) than those learning to code (53%). How favorable is your stance on using AI tools as part of your development workflow? All Respondents Professional Developers Learning to Code Early Career Devs Mid Career Devs Experienced Devs All Respondents Very favorable 22.9% Favorable 36.8% Indifferent 17.6% Unsure 2.3% Unfavorable 10.8% Very unfavorable 9.6% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 33,412 ( 68.2% ) Professional Developers Very favorable 23.5% Favorable 37.7% Indifferent 17.4% Unsure 1.8% Unfavorable 10.6% Very unfavorable 9.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 25,814 ( 52.7% ) Learning to Code Very favorable 19.3% Favorable 33.5% Indifferent 16.6% Unsure 4.3% Unfavorable 13.6% Very unfavorable 12.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,812 ( 5.7% ) Early Career Devs Very favorable 22.8% Favorable 40.3% Indifferent 17% Unsure 1.3% Unfavorable 10.3% Very unfavorable 8.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 6,293 ( 12.8% ) Early career defined as 1 - 5 years work experience Mid Career Devs Very favorable 23.8% Favorable 38.9% Indifferent 16.2% Unsure 1.5% Unfavorable 11% Very unfavorable 8.6% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 5,957 ( 12.2% ) Mid career defined as 5 - 10 years work experience Experienced Devs Very favorable 23.9% Favorable 36% Indifferent 18.1% Unsure 2.1% Unfavorable 10.3% Very unfavorable 9.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 12,941 ( 26.4% ) Experienced devs defined as 10+ years work experience 3.2 Developer tools Accuracy of AI tools More developers actively distrust the accuracy of AI tools (46%) than trust it (33%), and only a fraction (3%) report "highly trusting" the output. Experienced developers are the most cautious, with the lowest "highly trust" rate (2.6%) and the highest "highly distrust" rate (20%), indicating a widespread need for human verification for those in roles with accountability. How much do you trust the accuracy of the output from AI tools as part of your development workflow? All Respondents Professional Developers Learning to Code Early Career Devs Mid Career Devs Experienced Devs All Respondents Highly trust 3.1% Somewhat trust 29.6% Somewhat distrust 26.1% Highly distrust 19.6% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 33,244 ( 67.8% ) Professional Developers Highly trust 2.7% Somewhat trust 29.6% Somewhat distrust 26.3% Highly distrust 19.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 25,701 ( 52.4% ) Learning to Code Highly trust 6.1% Somewhat trust 31.3% Somewhat distrust 24.2% Highly distrust 19.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,781 ( 5.7% ) Early Career Devs Highly trust 3% Somewhat trust 31.1% Somewhat distrust 25.7% Highly distrust 17.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 6,254 ( 12.8% ) Early career defined as 1 - 5 years work experience Mid Career Devs Highly trust 2.8% Somewhat trust 30.3% Somewhat distrust 26.1% Highly distrust 19.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 5,931 ( 12.1% ) Mid career defined as 5 - 10 years work experience Experienced Devs Highly trust 2.5% Somewhat trust 28.6% Somewhat distrust 26.7% Highly distrust 20.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 12,908 ( 26.3% ) Experienced devs defined as 10+ years work experience AI tools' ability to handle complex tasks In 2024, 35% of professional developers already believed that AI tools struggled with complex tasks. This year, that number has dropped to 29% among professional developers and is consistent amongst experience levels. Complex tasks carry too much risk to spend extra time proving out the efficacy of AI tools. How well do the AI tools you use in your development workflow handle complex tasks? All Respondents Professional Developers Learning to Code Early Career Devs Mid Career Devs Experienced Devs All Respondents Very well at handling complex tasks 4.4% Good, but not great at handling complex tasks 25.2% Neither good or bad at handling complex tasks 14.1% Bad at handling complex tasks 22% Very poor at handling complex tasks 17.6% I don't use AI tools for complex tasks / I don't know 16.8% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 33,230 ( 67.8% ) Professional Developers Very well at handling complex tasks 3.9% Good, but not great at handling complex tasks 25.2% Neither good or bad at handling complex tasks 14.2% Bad at handling complex tasks 22.8% Very poor at handling complex tasks 18.6% I don't use AI tools for complex tasks / I don't know 15.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 25,695 ( 52.4% ) Learning to Code Very well at handling complex tasks 7.9% Good, but not great at handling complex tasks 25.8% Neither good or bad at handling complex tasks 12.4% Bad at handling complex tasks 19% Very poor at handling complex tasks 16.3% I don't use AI tools for complex tasks / I don't know 18.6% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,779 ( 5.7% ) Early Career Devs Very well at handling complex tasks 4% Good, but not great at handling complex tasks 28.1% Neither good or bad at handling complex tasks 13.4% Bad at handling complex tasks 23.6% Very poor at handling complex tasks 19.2% I don't use AI tools for complex tasks / I don't know 11.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 6,258 ( 12.8% ) Early career defined as 1 - 5 years work experience Mid Career Devs Very well at handling complex tasks 4% Good, but not great at handling complex tasks 25.4% Neither good or bad at handling complex tasks 13.8% Bad at handling complex tasks 23.9% Very poor at handling complex tasks 19.5% I don't use AI tools for complex tasks / I don't know 13.4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 5,922 ( 12.1% ) Mid career defined as 5 - 10 years work experience Experienced Devs Very well at handling complex tasks 3.6% Good, but not great at handling complex tasks 23.5% Neither good or bad at handling complex tasks 14.9% Bad at handling complex tasks 22.1% Very poor at handling complex tasks 17.9% I don't use AI tools for complex tasks / I don't know 18% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 12,901 ( 26.3% ) Experienced dev career defined as 10+ years work experience AI in the development workflow Developers show the most resistance to using AI for high-responsibility, systemic tasks like Deployment and monitoring (76% don't plan to) and Project planning (69% don't plan to). Which parts of your development workflow are you currently integrating into AI or using AI tools to accomplish or plan to use AI to accomplish over the next 3 - 5 years? Please select one for each scenario. Currently Mostly AI Currently Partially AI Plan to Partially Use AI Plan to Mostly Use AI Don't Plan to Use AI for This Task Currently Mostly AI Search for answers 54.1% Generating content or synthetic data 35.8% Learning new concepts or technologies 33.1% Documenting code 30.8% Creating or maintaining documentation 24.8% Learning about a codebase 20.8% Debugging or fixing code 20.7% Testing code 17.9% Writing code 16.9% Predictive analytics 11% Project planning 10.8% Committing and reviewing code 10.2% Deployment and monitoring 6.2% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 11,202 ( 22.9% ) Currently Partially AI Search for answers 55.8% Generating content or synthetic data 28.6% Learning new concepts or technologies 47.4% Documenting code 30.3% Creating or maintaining documentation 27.3% Learning about a codebase 32.7% Debugging or fixing code 47.1% Testing code 27.5% Writing code 59% Predictive analytics 12.7% Project planning 17.1% Committing and reviewing code 22.6% Deployment and monitoring 10.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 20,991 ( 42.8% ) Plan to Partially Use AI Search for answers 24% Generating content or synthetic data 28% Learning new concepts or technologies 27.9% Documenting code 30.5% Creating or maintaining documentation 32.5% Learning about a codebase 34.9% Debugging or fixing code 30.9% Testing code 34.7% Writing code 32.4% Predictive analytics 25% Project planning 24.8% Committing and reviewing code 31.4% Deployment and monitoring 25% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 22,518 ( 45.9% ) Plan to Mostly Use AI Search for answers 17.2% Generating content or synthetic data 28.9% Learning new concepts or technologies 15.7% Documenting code 28.6% Creating or maintaining documentation 31.8% Learning about a codebase 23.1% Debugging or fixing code 14.8% Testing code 25.8% Writing code 12.4% Predictive analytics 23% Project planning 14.3% Committing and reviewing code 16.3% Deployment and monitoring 15.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 12,790 ( 26.1% ) Don't Plan to Use AI for This Task Search for answers 19.6% Generating content or synthetic data 38.2% Learning new concepts or technologies 32.3% Documenting code 38.5% Creating or maintaining documentation 39.6% Learning about a codebase 39.4% Debugging or fixing code 36.4% Testing code 44.1% Writing code 28.9% Predictive analytics 65.6% Project planning 69.2% Committing and reviewing code 58.7% Deployment and monitoring 75.8% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 25,349 ( 51.7% ) AI workflow and tool satisfaction Respondents who said they are currently using mostly AI tools to complete tasks in the development workflow are highly satisfied with and frequently using AI to search for answers or learn new concepts; respondents plan to mostly use AI in the future for documentation and testing tasks and are slightly less satisfied with the tools they are using now. How favorable is your stance on using AI tools as part of your development workflow and which parts of your development workflow are you currently integrating into AI or using AI tools to accomplish or plan to use AI to accomplish over the next 3 - 5 years? Please select one for each scenario. Currently mostly AI Currently partially AI Plan to partially use AI Plan to mostly use AI Don't plan to use AI for this task Currently mostly AI Number of responses 6,053 685 Average AI Sentiment Recoded (1 - Very Unfavorable to 6 - Very Favorable) Percent of respondents 5.25 5.3 5.35 5.4 5.45 5.5 5.55 5.6 5.65 % 5 % 10 % 15 % 20 % 25 % 30 % 35 % 40 % 45 % 50 % 55 Commit/Review Docs Debug/fix Ops Documenting code Content/Data Leaning codebase Learning tech Predictive analytics Project planning Answers Testing code Writing code Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 11,184 ( 22.8% ) Currently partially AI Number of responses 12,382 2,194 Average AI Sentiment Recoded (1 - Very Unfavorable to 6 - Very Favorable) Percent of respondents 4.7 4.75 4.8 4.85 4.9 4.95 5 5.05 5.1 5.15 5.2 5.25 % 10 % 15 % 20 % 25 % 30 % 35 % 40 % 45 % 50 % 55 % 60 Commit/Review Docs Debug/fix Ops Documenting code Content/Data Leaning codebase Learning tech Predictive analytics Project planning Answers Testing code Writing code Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 20,980 ( 42.8% ) Plan to partially use AI Number of responses 7,858 5,400 Average AI Sentiment Recoded (1 - Very Unfavorable to 6 - Very Favorable) Percent of respondents 3.7 3.8 3.9 4 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 % 24 % 25 % 26 % 27 % 28 % 29 % 30 % 31 % 32 % 33 % 34 % 35 Commit/Review Docs Debug/fix Ops Documenting code Content/Data Leaning codebase Learning tech Predictive analytics Project planning Answers Testing code Writing code Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 22,500 ( 45.9% ) Plan to mostly use AI Number of responses 4,056 1,588 Average AI Sentiment Recoded (1 - Very Unfavorable to 6 - Very Favorable) Percent of respondents 4.6 4.65 4.7 4.75 4.8 4.85 4.9 4.95 5 5.05 5.1 5.15 5.2 % 12 % 14 % 16 % 18 % 20 % 22 % 24 % 26 % 28 % 30 % 32 Commit/Review Docs Debug/fix Ops Documenting code Content/Data Leaning codebase Learning tech Predictive analytics Project planning Answers Testing code Writing code Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 12,777 ( 26.1% ) Don't plan to use AI for this task Number of responses 19,211 4,953 Average AI Sentiment Recoded (1 - Very Unfavorable to 6 - Very Favorable) Percent of respondents 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 % 20 % 25 % 30 % 35 % 40 % 45 % 50 % 55 % 60 % 65 % 70 % 75 % 80 Commit/Review Docs Debug/fix Ops Documenting code Content/Data Leaning codebase Learning tech Predictive analytics Project planning Answers Testing code Writing code Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 25,332 ( 51.7% ) AI tool frustrations The biggest single frustration, cited by 66% of developers, is dealing with "AI solutions that are almost right, but not quite," which often leads to the second-biggest frustration: "Debugging AI-generated code is more time-consuming" (45%) When using AI tools, which of the following problems or frustrations have you encountered? Select all that apply. All Respondents AI solutions that are almost right, but not quite 66% Debugging AI-generated code is more time-consuming 45.2% I don’t use AI tools regularly 23.5% I’ve become less confident in my own problem-solving 20% It’s hard to understand how or why the code works 16.3% Other (write in): 11.6% I haven’t encountered any problems 4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 31,476 ( 64.2% ) AI and humans in the future In a future with advanced AI, the #1 reason developers would still ask a person for help is "When I don’t trust AI’s answers" (75%). This positions human developers as the ultimate arbiters of quality and correctness. In the future, if AI can do most coding tasks, in which situations would you still want to ask another person for help? Select all that apply. All Respondents When I don’t trust AI’s answers 75.3% When I have ethical or security concerns about code 61.7% When I want to fully understand something 61.3% When I want to learn best practices 58.1% When I’m stuck and can’t explain the problem 54.6% When I need help fixing complex or unfamiliar code 49.8% When I want to compare different solutions 44.1% When I need quick help troubleshooting 27.5% Other 6.1% I don’t think I’ll need help from people anymore 4.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 29,163 ( 59.5% ) Vibe coding Most respondents are not vibe coding (72%), and an additional 5% are emphatic it not being part of their development workflow. In your own words, is "vibe coding" part of your professional development work? For this question, we define vibe coding according to the Wikipedia definition , the process of generating software from LLM prompts. All Respondents 18-24 years old 25-34 years old 35-44 years old 45-54 years old 55-64 years old All Respondents Yes, emphatically 0.4% Yes 11.9% Yes, somewhat 2.8% I have tried it 2.1% Not sure 1.2% No 72.2% No, emphatically 5.3% Uncategorized 4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 26,564 ( 54.2% ) 18-24 years old Yes, emphatically 0.3% Yes 11.6% Yes, somewhat 3.2% I have tried it 2.4% Not sure 1.2% No 72.8% No, emphatically 5.1% Uncategorized 3.4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 4,212 ( 8.6% ) 25-34 years old Yes, emphatically 0.4% Yes 11.8% Yes, somewhat 3.2% I have tried it 1.6% Not sure 1.3% No 72.3% No, emphatically 5.7% Uncategorized 3.6% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 8,526 ( 17.4% ) 35-44 years old Yes, emphatically 0.5% Yes 12% Yes, somewhat 2.8% I have tried it 2.2% Not sure 1.1% No 72% No, emphatically 5.4% Uncategorized 4.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 7,607 ( 15.5% ) 45-54 years old Yes, emphatically 0.5% Yes 12.7% Yes, somewhat 2.5% I have tried it 1.9% Not sure 1.3% No 71.3% No, emphatically 5.2% Uncategorized 4.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 3,838 ( 7.8% ) 55-64 years old Yes, emphatically 0.8% Yes 11.4% Yes, somewhat 2% I have tried it 3.1% Not sure 1.5% No 71.3% No, emphatically 4.6% Uncategorized 5.4% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 1,657 ( 3.4% ) 3.3 AI Agents AI agents AI agents are not yet mainstream. A majority of developers (52%) either don't use agents or stick to simpler AI tools, and a significant portion (38%) have no plans to adopt them. Are you using AI agents in your work (development or otherwise)? AI agents refer to autonomous software entities that can operate with minimal to no direct human intervention using artificial intelligence techniques. All Respondents Professional Developers Learning to Code Professional AI Users Learning AI Users All Respondents Yes, I use AI agents at work daily 14.1% Yes, I use AI agents at work weekly 9% Yes, I use AI agents at work monthly or infrequently 7.8% No, but I plan to 17.4% No, I use AI exclusively in copilot/autocomplete mode 13.8% No, and I don't plan to 37.9% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 31,877 ( 65% ) Professional Developers Yes, I use AI agents at work daily 14.9% Yes, I use AI agents at work weekly 9.2% Yes, I use AI agents at work monthly or infrequently 7.7% No, but I plan to 17.2% No, I use AI exclusively in copilot/autocomplete mode 14.2% No, and I don't plan to 36.7% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 24,752 ( 50.5% ) Learning to Code Yes, I use AI agents at work daily 13.2% Yes, I use AI agents at work weekly 7.8% Yes, I use AI agents at work monthly or infrequently 7.4% No, but I plan to 15.6% No, I use AI exclusively in copilot/autocomplete mode 12.1% No, and I don't plan to 44.1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,610 ( 5.3% ) Professional AI Users Yes, I use AI agents at work daily 17.5% Yes, I use AI agents at work weekly 10.8% Yes, I use AI agents at work monthly or infrequently 8.9% No, but I plan to 18.6% No, I use AI exclusively in copilot/autocomplete mode 16.3% No, and I don't plan to 27.8% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 20,892 ( 42.6% ) Learning AI Users Yes, I use AI agents at work daily 16.5% Yes, I use AI agents at work weekly 9.6% Yes, I use AI agents at work monthly or infrequently 8.7% No, but I plan to 16.9% No, I use AI exclusively in copilot/autocomplete mode 14.7% No, and I don't plan to 33.6% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,019 ( 4.1% ) AI agents affect on work productivity 52% of developers agree that AI tools and/or AI agents have had a positive effect on their productivity. Have AI tools or AI agents changed how you complete development work in the past year? All Respondents Yes, to a great extent 16.3% Yes, somewhat 35.3% Not at all or minimally 41.4% No, but my development work has significantly changed due to non-AI factors 2.6% No, but my development work has changed somewhat due to non-AI factors 4.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 31,636 ( 64.5% ) AI agent uses at work If you happen to be using AI agents at work and you are a software developer, chances are high that you are using agents for software development (84%). What industry purposes or specific tasks are you using AI agents in your development work? Select all that apply from both lists. Industry Purpose Software engineering 83.5% Data and analytics 24.9% IT operations 18% Business process automation 17.6% Decision intelligence 11.3% Customer service support 11.2% Marketing 8.6% Cybersecurity 7.4% Robotics 3.9% Other 2.2% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 12,301 ( 25.1% ) AI agent uses for general purposes TL;DR: Agents used outside of work are mostly used for language processing tasks (49%). What industry purposes or specific tasks are you using AI agents in your development work? Select all that apply from both lists. General Purpose Language processing 49% Integration with external agents and APIs 38.3% MCP servers 34.4% Agent/multi-agent orchestration 28.1% Vector databases for AI applications 24.1% Multi-platform search enablement 19.4% Personalized agent creation 18.3% Other 3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 5,797 ( 11.8% ) Impacts of AI agents The most recognized impacts are personal efficiency gains, and not team-wide impact. Approximately 70% of agent users agree that agents have reduced the time spent on specific development tasks, and 69% agree they have increased productivity. Only 17% of users agree that agents have improved collaboration within their team, making it the lowest-rated impact by a wide margin. To what extent do you agree with the following statements regarding the impact of AI agents on your work as a developer? All Respondents 27.3% 35.9% 21.3% 8.2% 7.3% AI agents have accelerated my learning about new technologies or codebases. 29.3% 34.9% 22.4% 7% 6.4% AI agents have helped me automate repetitive tasks. 17.1% 31.9% 25.3% 14.2% 11.5% AI agents have helped me solve complex problems more effectively. 6.6% 10.7% 40.5% 20% 22.2% AI agents have improved collaboration within my team. 12.2% 25.3% 32.4% 17.1% 13.1% AI agents have improved the quality of my code. 27.7% 41% 20.4% 6% 4.9% AI agents have increased my productivity. 29.3% 40.8% 17.8% 6.9% 5.1% AI agents have reduced the time spent on specific development tasks. Strongly agree Somewhat agree Neutral Somewhat disagree Strongly disagree Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 12,823 ( 26.2% ) Challenges with AI agents Is it a learning curve, or is the tech not there yet? 87% of all respondents agree they are concerned about the accuracy, and 81% agree they have concerns about the security and privacy of data. To what extent do you agree with the following statements regarding AI agents? All Respondents 57.1% 29.8% 9.7% 2.3% 1.1% I am concerned about the accuracy of the information provided by AI agents. 56.1% 25.3% 11.7% 4.7% 2.2% I have concerns about the security and privacy of data when using AI agents. 16.5% 29.7% 37.3% 12.6% 3.9% Integrating AI agents with my existing tools and workflows can be difficult. 15.5% 27.9% 31.8% 17.8% 6.9% It takes significant time and effort to learn how to use AI agents effectively. 13.8% 14.4% 30.6% 15% 26.2% My company's IT and/or InfoSec teams have strict rules that do not allow me to use AI agent tools or platforms 25.4% 27.9% 31.8% 10.3% 4.6% The cost of using certain AI agent platforms is a barrier. Strongly agree Somewhat agree Neutral Somewhat disagree Strongly disagree Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 28,930 ( 59% ) AI Agent data storage tools When it comes to data management for agents, traditional, developer-friendly tools like Redis (43%) are being repurposed for AI, alongside emerging vector-native databases like ChromaDB (20%) and pgvector (18%). You indicated you use or develop AI agents as part of your development work. Have you used any of the following tools for AI agent memory or data management in the past year? All Respondents Redis 42.9% GitHub MCP Server 42.8% supabase 20.9% ChromaDB 19.7% pgvector 17.9% Neo4j 12.3% Pinecone 11.2% Qdrant 8.2% Milvus 5.2% Fireproof 5% LangMem 4.8% Weaviate 4.5% LanceDB 4.4% mem0 4% Zep 2.8% Letta 2.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 3,398 ( 6.9% ) AI Agent orchestration tools The agent orchestration space is currently led by open-source tools. Among developers building agents, Ollama (51%) and LangChain (33%) are the most-used frameworks. You indicated you use or develop AI agents as part of your development work. Have you used any of the following tools for AI agent orchestration or agent frameworks in the past year? All Respondents Ollama 51.1% LangChain 32.9% LangGraph 16.2% Vertex AI 15.1% Amazon Bedrock Agents 14.5% OpenRouter 13.4% Llama Index 13.3% AutoGen (Microsoft) 12% Zapier 11.8% CrewAI 7.5% Semantic Kernel 6% IBM watsonx.ai 5.7% Haystack 4.4% Smolagents 3.7% Agno 3.4% phidata 2.1% Smol-AGI 1.9% Martian 1.7% lyzr 1.5% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 3,758 ( 7.7% ) AI Agent observability and security Developers are primarily adapting their existing, traditional monitoring tools for this new task, rather than adopting new, AI-native solutions. The most used tools for AI agent observability are staples of the DevOps and application monitoring world: Grafana + Prometheus are used by 43% of agent developers, and Sentry is used by 32%. You indicated you use or develop AI agents as part of your development work. Have you used any of the following tools for AI agent observability, monitoring or security in the past year? All Respondents Grafana + Prometheus 43% Sentry 31.8% Snyk 18.2% New Relic 13% LangSmith 12.5% Honeycomb 8.8% Langfuse 8.8% Wiz 6.9% Galileo 6.2% Adversarial Robustness Toolbox (ART) 5.5% Protect AI 5% Vectra AI 4.4% arize 3.7% helicone 3.2% Metero 2.7% opik 2.3% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 2,689 ( 5.5% ) AI Agent out-of-the-box tools ChatGPT (82%) and GitHub Copilot (68%) are the clear market leaders, serving as the primary entry point for most developers using out-of-the-box AI assistance. You indicated you use or develop AI agents as part of your development work. Have you used any of the following out-of-the-box agents, copilots or assistants? All Respondents ChatGPT 81.7% GitHub Copilot 67.9% Google Gemini 47.4% Claude Code 40.8% Microsoft Copilot 31.3% Perplexity 16.2% v0.dev 9.1% Bolt.new 6.5% Lovable.dev 5.7% AgentGPT 5% Tabnine 5% Replit 5% Auto-GPT 4.7% Amazon Codewhisperer 3.9% Blackbox AI 3.5% Roo code (Roo-Cline) 3.4% Cody 3% Devin AI 2.7% Glean (Enterprise Agents) 1.3% OpenHands (formerly OpenDevin) 1% Download I acknowledge that the downloaded file is licensed under the Open Database License Download chart Share Twitter/X Facebook LinkedIn Responses: 8,323 ( 17% ) Previous Technology Next Work Site design / logo © 2025 Stack Exchange Inc. User contributions licensed under CC BY-SA. Data licensed under Open Database License (ODbL). Terms Privacy policy Cookie policy Your Privacy Choices Go to stackoverflow.com | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/ai-replace-programmers-nl | Zal AI programmeurs vervangen? Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Zal AI programmeurs vervangen? De vraag "Zal AI programmeurs vervangen?" circuleert in technologische kringen en wekt zowel enthousiasme als bezorgdheid op. Naarmate AI-gestuurde coderingstools geavanceerder worden, is het de moeite waard om te vragen: waar laat dit de menselijke ontwikkelaars? Laten we de perspectieven van toonaangevende stemmen in het veld verkennen. Het Argument voor AI die Ontwikkeling Revolutioneert AI Transformeert Softwareontwikkeling AI verandert onmiskenbaar onze benadering van softwareontwikkeling. Tools zoals GitHub Copilot en platforms zoals Fine stellen ontwikkelaars in staat om repetitieve taken te stroomlijnen. Zoals een artikel opmerkt , "AI kan codefragmenten of volledige functies produceren op basis van natuurlijke taalopdrachten, waardoor de ontwikkeling wordt gestroomlijnd" (The Tech Bible). Coderen Toegankelijker Maken Deze tools besparen niet alleen tijd; ze maken coderen ook toegankelijker. AI kan bijvoorbeeld beginners helpen met realtime begeleiding, als een persoonlijke mentor Techies Spot . Dit verlaagt de drempel voor softwareontwikkeling en opent de deur voor meer mensen om deel te nemen aan de industrie. Zal AI Programmeurs Volledig Vervangen? De consensus lijkt een duidelijk nee te zijn. Hoewel AI uitblinkt in het automatiseren van repetitieve taken, mist het de creativiteit, intuïtie en probleemoplossende vaardigheden die menselijke programmeurs met zich meebrengen. Zoals Jonathan's Musings uitlegt, "AI kan code genereren, maar het begrijpen van complexe vereisten en deze vertalen naar robuuste oplossingen vereist nog steeds menselijke inzicht." Peter H. Diamandis deelt dit gevoel en stelt: "In plaats van programmeurs te vervangen, zal AI fungeren als een vermenigvuldiger, waardoor ontwikkelaars zich kunnen concentreren op taken van een hoger niveau." Wanneer Zal AI Programmeurs Vervangen? De vraag wanneer, als het ooit gebeurt, AI programmeurs zal vervangen, is complex. Huidige AI-modellen, hoewel krachtig, hebben aanzienlijke beperkingen. Ze missen echt begrip, genereren vaak onjuiste of onveilige code en vereisen menselijke supervisie om kwaliteit en betrouwbaarheid te waarborgen. Deze beperkingen betekenen dat AI nog ver verwijderd is van het volledig kunnen vervangen van menselijke programmeurs. De Evolutie van AI-capaciteiten AI ontwikkelt zich snel, en het is mogelijk dat toekomstige iteraties complexere ontwikkelingstaken aankunnen. De tijdlijn hiervoor is echter onzeker. Experts geloven dat AI menselijke ontwikkelaars zal blijven aanvullen in plaats van ze volledig te vervangen in de nabije toekomst. Het menselijk vermogen om context te begrijpen, oordelen te vellen en problemen creatief op te lossen blijft onvervangbaar. AI als Partner van de Programmeur Samenwerkende Rol van AI Het meest veelbelovende perspectief op AI in programmeren is de rol als samenwerkende partner. Ontwikkelaars kunnen AI gebruiken om routinetaken te automatiseren, standaardcode te genereren en zelfs complexe systemen te debuggen. Volgens Billy Newport zullen "AI-coderingassistenten naadloos integreren in tools zoals GitHub, fungeren als snelle en efficiënte medewerkers in plaats van vervangers" (Billy Newport). Fine’s AI Ontwikkelaarsoplossing De AI-ontwikkelaarsoplossing van Fine is een perfect voorbeeld van deze samenwerking in actie. Met functies zoals Live Previews en AI Workflows stelt Fine ontwikkelaars in staat om code in realtime te schrijven, testen en verfijnen. Door het banale te automatiseren, kunnen ontwikkelaars zich richten op innovatie en probleemoplossing. Conclusie Zal AI dus programmeurs vervangen? Het antwoord is nee, maar het zal ze productiever, creatiever en invloedrijker maken dan ooit. AI is geen vervanging voor menselijke genialiteit; het is een hulpmiddel om het te verbeteren. Naarmate de industrie evolueert, zullen platforms zoals Fine de leiding nemen en ontwikkelaars helpen meer te bereiken met minder wrijving. Fine is een ideale oplossing voor startups die hun ontwikkelingsprocessen willen optimaliseren en de productiviteit willen maximaliseren zonder grote teams nodig te hebben. Door repetitieve taken te automatiseren, stelt Fine startup-teams in staat zich te concentreren op innovatie en hun time-to-market te versnellen. Geïnteresseerd om het uit te proberen? Meld je vandaag nog aan bij Fine en zie hoe AI je codereis kan versterken en je startup efficiënt kan helpen opschalen. Met AI in je gereedschapskist ziet de toekomst van programmeren er veelbelovender uit dan ooit. 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 | 2026-01-13T08:48:23 |
https://ruul.io/blog/what-is-a-1099-form-for-freelancers | What is Form 1099? Important Information for Freelancers Product Payment Requests Get paid anywhere. Sell Services Make your services buyable Sell Products Create once sell forever Subscriptions Get paid on repeat Ruul Space Your personel storefront. One link for everything you offer. Learn more Pricing Resources Partner Programs Referral Program Get 1% for life. Seriously. Affiliate Program Bring users, get paid Partners Let’s grow together. More Blog About us Support Brand Kit For Customers Log in Sign up For Businesses Login Sign up get paid What is a 1099 Form for Freelancers? Are you a freelancer in the US? Learn the basics of Form 1099 as a freelancer to manage your taxes smoothly. Click to learn more! Esen Bulut 5 min read RUUL FOR INDEPENDENCE You chose independence.We make sure you keep it. Sell your time, your talent, whatever you create or build always on your terms. Get started See Example This is also a heading This is a heading Key Points If you are a freelancer working in or with the U.S. you need to be aware of the 1099 form for the sake and future of your business. The 1099 form is an important document in the U.S. tax system, mostly used by freelancers and independent contractors who have to use self employed tax forms . As a freelancer, understanding the 1099 form will help you manage your taxes, make sure you are on the safe side with the Internal Revenue Service (IRS). In this blog post we will explain a detailed explanation of the 1099 form and how to handle it accurately. Understanding the 1099 Form 1099 forms cover income earned by independent contractors, freelancers, and other non-employee workers. The most common type for freelancers is the 1099-NEC (Nonemployee Compensation), but there are several other variations of the 1099 form for different types of income. 1099-NEC: Non-Employee Compensation If you earn $600 or more from a single client during the tax year, that client is required to issue a 1099-NEC to you and to the IRS. This form reports the total amount paid to you for your freelance services.1099-NEC form involves; Payer Information: The name, address, and Taxpayer Identification Number (TIN) of the client or company that paid you. Recipient Information: Your name, address, and Social Security Number (SSN) or Employer Identification Number (EIN). Non-employee Compensation: The total amount paid to you during the year. Freelancers need to make sure to fill the form accurately from beginning to end to have a smooth process. Each section of the information needs to be checked out and match the real information. Receiving and Reviewing Your 1099 Form Typically, clients are required to send out 1099 forms by January 31st of the year following the tax year in which the payments were made. For example, if you earned income in 2023, you should receive your 1099-NEC by January 31, 2024. It is very important to review the form carefully for accuracy. Check that the amounts reported match your records and that your personal information is correct. If you find any discrepancies, contact the client to correct the issue as soon as possible. Accurate reporting is critical to avoid potential problems with the IRS. Reporting 1099 Income on Your Tax Return When it comes time to file your tax return, you’ll need to report the income shown on your 1099-NEC form. Here’s how to handle it: Include 1099 Income on Schedule C: For freelancers, income reported on the 1099-NEC is typically reported on Schedule C (Profit or Loss from Business) of your tax return. Schedule C is used to report income and expenses from your freelance work. Track All Income: While the 1099-NEC form is an important document, it’s essential to track all income you receive, not just what is reported on the 1099 form. Ensure that all sources of income are included on your tax return. Deduct Business Expenses: Freelancers can deduct business-related expenses to reduce their taxable income. Common deductions include office supplies, travel expenses, software subscriptions, and other costs directly related to your freelance work. Keep detailed records and receipts to support your deductions. Self-Employment Tax: In addition to income tax, freelancers are also subject to self-employment tax, which covers Social Security and Medicare taxes. The self-employment tax rate is 15.3%, and it’s calculated on Schedule SE (Self-Employment Tax). Your 1099-NEC income will be used to determine the amount of self-employment tax you owe. Handling Multiple 1099 Forms If you work with multiple clients, you may receive several 1099 forms, each reporting income from different sources. It’s important to consolidate these forms when preparing your tax return. Ensure that the total income reported matches your records and that you account for all 1099 forms. Penalties for Non-Compliance Failure to report income from 1099 forms can result in penalties and interest charges from the IRS. It is extremely important to report all income accurately and file your tax return on time to avoid these issues. Importance of Accurate Record-Keeping Maintaining accurate records of your income and expenses throughout the year can make the tax filing process smoother and help ensure compliance with IRS requirements. Keep track of invoices, payment receipts, and any correspondence related to your freelance work. The 1099 form, particularly the 1099-NEC, is a vital document for freelancer service and independent contractors in the U.S. It provides a formal record of income received from clients and plays a key role in the tax filing process. Manage Invoice and Payments Easy With Ruul Payment collection can be challenging for freelancers. Ruul helps freelancers to get early pay with multiple payment options including credit cards. Freelancers can receive payout in their preferred account in 1 business day unlike traditional bank methods, sometimes it may take several days to complete the process. Ruul handles global sales tax charging and remittance, it handles all your sales tax and compliance for every payment, cutting down your paperwork however it does not provide income tax compliance/services. Every freelancer who receives a payment is responsible for their own taxes. Ruul does not offer assistance in this area. Ruul helps freelancers to invoice your business clients in 190 countries with global standards. With Ruul, freelancers simply send a payment link to their clients so they can pay easily and receive an invoice without signing up. ABOUT THE AUTHOR Esen Bulut Esen Bulut is the co-founder of Ruul. After graduating Boston College with finance and economics degrees, she began her career as a Finance Executive. Prior to Ruul, she held managerial positions in finance and marketing. Esen's entrepreneurship success earned her recognition in Fortune's 40 under 40 list in 2022. More How Does Upwork Work and What Is It Used For? Curious about Upwork? Find out how this platform simplifies freelance work and enhances your business opportunities. Read on for details! Read more Freelance vs. Contract Work: Understanding the Fundamentals and Differences Discover the differences between freelance and contract work, including definitions, key differences, pros, and cons. Understand which career path suits you best based on flexibility, stability, work arrangements, and financial security. Explore common careers and payment structures to make an informed decision. Read more How to Use a Freelance Pricing Calculator to Set Your Rates Learn how to effectively use a freelance pricing calculator to set rates that cover your expenses and meet income goals. Click to discover how! Read more MORE THAN 120,000 Independents Over 120,000 independents trust Ruul to sell their services, digital products, and securely manage their payments. FROM 190 Countries Truly global coverage: trusted across 190 countries with seamless payouts available in 140 currencies. PROCESSED $200m+ of Transactions Over $200M successfully processed, backed by an 8-year legacy of secure, reliable transactions trusted by independents worldwide. FREQUENTLY ASKED QUESTIONS Everything you need to know. Get clear, straightforward answers to the most common questions about using Ruul. hey@ruul.io What is Ruul? Ruul is a merchant-of-record platform helping freelancers and creators globally sell services, digital products, subscriptions, and easily get paid. Who is Ruul for? Ruul is designed for freelancers, creators, and independent professionals who want a simple way to sell online and get paid globally. How does Ruul work? Open an account, complete a quick verification (KYC), and link your payout account. Then, start selling through your store or send payment requests to customers instantly. How does pricing work? Signing up is free. There are no subscription or hidden fees. Ruul charges a small commission only when you sell or get paid through the platform. What is a Merchant of Record? A merchant of record is the legal seller responsible for processing payments, handling taxes, and managing compliance for each transaction. What can I sell on Ruul? You can sell services, digital products, license keys, online courses, subscriptions, and digital memberships. How do I get paid on Ruul? Add your preferred bank account, digital wallet, or receive payouts in stablecoins as crypto. Funds arrive within 24 hours after a payout is triggered. OPEN AN ACCOUNT START MAKING MONEY TODAY ruul.space/ Thank you! Your submission has been received! Oops! Something went wrong while submitting the form. Trustpilot Product Payment Requests Sell Services Sell Products Subscriptions Ruul Space Pricing For Businesses Resources Blog About Contact Support Referral Program Affiliate Program Partner Program Tools Invoice Generator NDA Generator Service Agreement Generator Freelancer Hourly Rate Calculator All Rights Reserved © 2025 Terms Of Use Privacy Policy | 2026-01-13T08:48:23 |
https://www.mrdbourke.com/contact/ | Contact Daniel Bourke Home Now Machine Learning Posts Learn Machine Learning (courses I teach) ML Resources (things I recommend) About Newsletter Contact Book (Charlie Walks) YouTube Sign in Subscribe Contact Feel free to email me . If you'd prefer me to go first, you can sign up for updates. I send out a newsletter once per month or so. Daniel Bourke © 2026 Powered by Ghost | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/ny-ai-coding-challenge | The AI Coding Challenge Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back The AI Coding Challenge In 2024, we all tried out AI coding tools. This holiday season, we’re challenging you to gear up and prepare for 2025, the year where coding with AI will be the norm. Complete the challenge to be ready to excel in your software development work in the new year and be in with a chance of winning great prizes! TL;DR Complete 3 dev tasks in your codebase using Fine’s AI Agents - from the initial prompt through to the PR - and win prizes. How to Participate Log/sign up to Fine for free Give Fine a task to implement (see cheat sheet below) Make edits in the browser if needed Run the code in the AI sandbox to test if it works (pro users only) Screenshot the results and share on X (Twitter), tagging @FineDotDev and using the hashtag #FineCodingChallenge Repeat steps 2 & 3 three times to be in with a chance of winning. Repeat again and again to increase your chances! For each extra task you complete with Fine and share on X, we’ll enter your handle into the raffle again. OPTIONAL Use the code NY2025AICHALLENGE to upgrade to PRO for free for one month Ready to go? Click here to get started. The Prize First Place: $400 cash + 2 year Pro subscription to Fine + immense bragging rights Second Place: $100 cash + 1 year Pro subscription to Fine + immense bragging rights Third Place: 3 months Pro subscription to Fine + immense bragging rights You can win these prizes with less than 15 minutes' work! Click here to open Fine and start now. Cheat Sheet (Tips for Success) Start by delegating small tasks and then you can increase their scope. You and the AI agents need to learn to work together. Specify relevant files, folders and components by name - better yet, use @ to tag them into your prompt. Write clear, detailed specs so Fine knows exactly what you’re trying to accomplish. We recommend starting out with the Given-Where-When format to flesh out your instructions. Examples of Tasks to start off delegating: UI/UX Improvements Adding new API endpoints Add new stories.js documentation Adding new columns to a database and updating queries to filter records based on new data Minor bugs with easy fixes The Fine Print The challenge begins on 23.12.24 and ends on 7.1.24 Bonus extension - new deadline 31.1.25! To enter the challenge, developers must post three screenshots or recordings to twitter (x) in separate tweets, each one showing a task delegated to Fine, including the prompt, implementation plan and code changes. Each tweet must show a separate task. The task must involve adding or editing code and meet the approval of Fine’s judging committee. Users must have at least 100 followers on Twitter. If a user has less than 100 followers, the entry will be considered if it receives more than 500 impressions & 30 likes, subject to the approval of Fine’s judging committee. What are you waiting for? Get started now! 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 | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/ai-tools-for-programmers | AI for Programmers: Top Tools to Supercharge Your Development Workflow Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back AI for Programmers: Top Tools to Supercharge Your Development Workflow AI is reshaping how programmers work, making it easier to handle repetitive tasks, boost productivity, and improve efficiency. This blog will guide you through some of the best AI tools for programmers available today, tailored to help you code faster, debug smarter, and collaborate effectively. Whether you're a beginner or an experienced developer, these platforms can make a real difference in your workflow. Let's get started with Fine. Table of Contents Fine Cursor Replit AI Bolt.new Devin Aider bloop Callstack PR Reviewer OpenHands Zencoder 1. Fine (AI for programmers) Fine is a comprehensive AI-powered software development platform designed to make coding seamless and efficient. By integrating AI Agents , Fine enables programmers to automate repetitive tasks like generating boilerplate code, updating schemas, and managing APIs. Its AI Sandboxing feature allows users to build, run, and test AI-generated code directly in a secure browser-based environment. It's fully mobile friendly and offers powerful integrations with GitHub, Linear and Slack - allowing for full context awareness and maximum collaboration. Highlights: AI Palette for real-time assistance. Integration with GitHub and Linear for end-to-end project management. Specs-driven development ensures alignment with project goals. Fine is designed to empower developers, allowing them to focus on innovation while leaving routine tasks to AI. At just $13-15 per month, it's a deal for any startup looking to save time and ship more. 2. Cursor Cursor offers an AI-powered code editor built on Visual Studio Code (VS Code). It includes features like Cursor Tab for intelligent auto-completion and Chat Integration for codebase-aware interactions. Cursor’s functionality is limited beyond code generation and debugging, and it requires significant configuration for advanced team collaboration. 3. Replit AI Replit AI provides integrated AI capabilities for its cloud-based IDE. It offers code completion, bug fixes, and code generation. Replit AI is heavily tied to its ecosystem and is more suited to beginner-to-intermediate developers than advanced users. 4. Bolt.new (AI for web developers) Bolt.new is an AI agent for web development, allowing developers to build, run, and deploy full-stack applications directly in the browser. Currently in beta, Bolt.new offers limited stability and focuses solely on web development, making it less versatile for other programming needs. 5. Devin Devin by Cognition is an autonomous AI software engineer designed to execute complex engineering tasks. Still in early access, Devin is focused on specific use cases and is less reliable for general-purpose programming. 6. Aider Aider is an open-source AI pair programming tool that integrates with Git repositories for local coding assistance. It requires API keys and setup for AI model integration and is limited to terminal-based interaction, which may not suit all developers. Fine includes unlimited access to leading LLMs such as o1-preview and Claude 3-5 Sonnet, with no need for your own API keys. 7. bloop Bloop specializes in modernizing legacy codebases, particularly COBOL. It offers tools for translating legacy code into modern languages. Bloop is highly specialized for legacy code modernization and offers limited functionality for general-purpose programming. 8. Callstack PR Reviewer This tool automates code reviews, identifying bugs and enforcing coding standards in GitHub and GitLab. Callstack PR Reviewer focuses on pull request reviews and lacks features for standalone development tasks. 9. OpenHands OpenHands provides a zero-setup AI coding experience within a cloud-based Visual Studio Code environment. Dependence on cloud infrastructure may not suit developers working offline or in secure environments, and its focus is limited to AI coding assistance. 10. Zencoder Zencoder uses AI agents to enhance coding workflows, with a focus on syntactic and semantic code analysis. Zencoder primarily supports iterative improvements and lacks versatility for new project creation or diverse programming needs. Why Fine Stands Out as an AI tool for Programmers While each platform offers unique advantages, Fine delivers the most comprehensive AI solution for programmers of all skill levels. Its integration of AI Agents, Sandboxing, and seamless collaboration tools makes it a one-stop shop for development teams. Unlike other platforms, Fine doesn’t compromise on versatility, supporting everything from boilerplate code generation to full project management. Ready to transform your workflow? Sign up for Fine today and experience the best in AI for programmers . The source of information for each platform has been provided in a link. Information was collected on 20.11.24 and may be incorrect, incomplete or out-of-date. 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 | 2026-01-13T08:48:23 |
https://flourish.studio/ | Flourish Product Create Data visualization Create interactive charts and maps using no-code templates Flourish stories Build multi-step explainers with charts and captions Interactive content Visualize text, images and audio with interactive templates Examples Solutions Industry Financial services Professional services Newsrooms Marketing Nonprofits Government Education Use cases Elections and polling Sports and competitions Maps Survey responses Scrollytelling Resources Explore Blog Chart guides What's new Learn Help docs Webinars Training Datasets Accessibility Develop Experts network Flourish for developers Pricing Log in Sign up Where data meets storytelling Create stunning charts , maps and interactive content that engage and inspire – instantly. No coding required. Get started now Request a demo --> Trusted by leaders worldwide to reach audiences of millions every day Turn data into stories worth sharing From data visualizations and interactive elements to immersive storytelling, Flourish empowers you to turn complex data into interactive visuals that wow your audience - whether you're an expert or just starting out. Your data, fully interactive Transform raw data into interactive visualizations that are as sleek as they are engaging. Say goodbye to static charts and let your audience explore, connect, and truly understand your story. No-code creation, stunning results Create professional-grade visuals in minutes — no coding, no hassle. Simply import your data and transform it into interactive visuals that grab attention. It's as easy as it gets. Share anywhere, look great everywhere Seamlessly share and embed your visualisations across platforms—websites, presentations, social media assets and more. Watch them adapt beautifully to any screen, captivating audiences across all devices. Team up, stay on brand Simplify collaboration and ensure your visuals stay polished and on-brand. Advanced sharing and customization options let your team create with confidence. Flourish for Newsrooms Professional Services Financial Services Marketing Nonprofits Education Government Used by thousands of companies every day, including: Flourish support is great: accessible, friendly, pursuing solutions for our eternal ‘exception of the rules’ queries to make visualizations work in our 40 languages.” Roberto Belo-Rovella Editor, BBC World Service We live and breathe data, and no tool has enabled us to bring our data to life in a beautiful way better than Flourish has. It's a game changer.” Joel Leeman Sr. Executive Producer, London Stock Exchange Let’s connect Ready to transform your work with data storytelling? Connect with our team to learn more and get started today! Get in touch What is Flourish? Flourish is a powerful data visualization platform that empowers the world to tell stories with data. Trusted by organizations and newsrooms worldwide, Flourish helps creators bring data narratives to life with highly engaging, interactive and impressive visualizations. Our extensive library of templates and seamless embedding options make every data story informative and truly captivating. Who is behind Flourish? Flourish was co-founded in 2018 by Duncan Clark and Robin Houston . Duncan has a background in data journalism and publishing, while Robin is a mathematician and developer. In 2022, Canva acquired Flourish with the shared goal of democratizing data storytelling and making data visualization accessible to all. Read more about this here . How does Flourish differ from other data visualization tools? Flourish sets itself apart through: Ease of use : No specific technical skills are needed thanks to its template-based system and intuitive user interface. Storytelling : Flourish is uniquely designed to facilitate narrative visualizations, such as scrollytelling, interactive presentations, and audio-driven stories. Flexibility : The Flourish SDK lets developers create custom templates without limitations on functionality or design. Publishability : All outputs are styled for robustness, capable of reaching unlimited audiences, and optimized for mobile viewing. Is Flourish a business intelligence tool? Flourish is not typically regarded as a business intelligence tool. While its templates and API allow for data exploration and dashboard integration, its primary focus is on data storytelling, especially for presentations and digital publications. Company About us Careers Security Pricing Terms Privacy policy FAQs Explore Examples Elections & polls Sports & competitions Interactive maps Survey responses Scrollytelling Chart guides Blog Solutions Financial services Professional services Newsrooms Marketing Nonprofits Government Education Resources What's new Help docs Training Webinars Datasets Accessibility Experts network For developers Flourish Flourish is a registered trademark of Canva UK Operations Ltd, UK company 08825531 33 Hoxton Square London N1 6NN Stay in touch Subscribe to our newsletter © 2025 Flourish, a Canva UK Operations Limited brand. All rights reserved. | 2026-01-13T08:48:23 |
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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 Web Development Follow Hide Because the internet... Create Post submission guidelines Be nice. Be respectful. Assume best intentions. Be kind, rewind. Older #webdev posts 70 71 72 73 74 75 76 77 78 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu I built a QR Code API and here's what I learned Malachi Stark Malachi Stark Malachi Stark Follow Dec 17 '25 I built a QR Code API and here's what I learned # showdev # webdev # api # javascript Comments Add Comment 3 min read From Chaos to Perfect Flow: My Experience Automating a Massive Real GitLab Migration (4,000 Repos) Claudio Cesar Claudio Cesar Claudio Cesar Follow Dec 17 '25 From Chaos to Perfect Flow: My Experience Automating a Massive Real GitLab Migration (4,000 Repos) # devops # webdev # gitlab # kubernetes Comments Add Comment 4 min read AWS Service – Amazon S3 Glacier Gangeswara Gangeswara Gangeswara Follow Dec 18 '25 AWS Service – Amazon S3 Glacier # aws # awschallenge # s3 # webdev 1 reaction Comments Add Comment 1 min read Praktikum Keamanan Web: Server-Side Request Forgery (SSRF) 🌐🕵️♂️ ahmadasroni38 ahmadasroni38 ahmadasroni38 Follow Dec 18 '25 Praktikum Keamanan Web: Server-Side Request Forgery (SSRF) 🌐🕵️♂️ # tutorial # webdev # security # php Comments Add Comment 3 min read React + TypeScript: Best Practices You Should Know Anna Nguyen Anna Nguyen Anna Nguyen Follow for ONEXT DIGITAL Dec 19 '25 React + TypeScript: Best Practices You Should Know # react # typescript # webdev # frontend Comments Add Comment 2 min read Blazor Localization in .NET 8: English–Arabic Multilingual Setup (Practical Guide) Mohsin Afzal Mohsin Afzal Mohsin Afzal Follow Dec 18 '25 Blazor Localization in .NET 8: English–Arabic Multilingual Setup (Practical Guide) # webdev # dotnet # localization # blazor Comments Add Comment 2 min read I Let an AI Agent Handle a Multi-Step Task. Here's Where It Broke Leena Malhotra Leena Malhotra Leena Malhotra Follow Dec 18 '25 I Let an AI Agent Handle a Multi-Step Task. Here's Where It Broke # webdev # programming # ai # agents Comments Add Comment 8 min read Built CLI Tools to Browse AI Coding Assistant Logs (Claude Code & Codex CLI) hiroshi yata hiroshi yata hiroshi yata Follow Dec 18 '25 Built CLI Tools to Browse AI Coding Assistant Logs (Claude Code & Codex CLI) # programming # webdev # ai # cli 1 reaction Comments Add Comment 3 min read What’s more important: writing perfect code or shipping fast? Let’s discuss! msrajput08 msrajput08 msrajput08 Follow Dec 19 '25 What’s more important: writing perfect code or shipping fast? Let’s discuss! # discuss # webdev # programming # ai Comments Add Comment 1 min read A Crowdfunding Site Rebuild Log: What I Changed and What I Refused to Change Bashar Forrestad Bashar Forrestad Bashar Forrestad Follow Dec 22 '25 A Crowdfunding Site Rebuild Log: What I Changed and What I Refused to Change # architecture # startup # webdev Comments Add Comment 9 min read Why Your Site Needs /llms.txt (and How to Create One) Marius Gherasim Marius Gherasim Marius Gherasim Follow Dec 18 '25 Why Your Site Needs /llms.txt (and How to Create One) # webdev # ai # productivity # seo Comments Add Comment 1 min read The Only JSON Tools You'll Ever Need: Formatter, Validator, and Share 🚀 xyz abc xyz abc xyz abc Follow Dec 19 '25 The Only JSON Tools You'll Ever Need: Formatter, Validator, and Share 🚀 # webdev # productivity # resources # opensource Comments Add Comment 1 min read Neon lil synth JaclynCodes JaclynCodes JaclynCodes Follow Dec 19 '25 Neon lil synth # codepen # webdev # javascript # beginners Comments Add Comment 1 min read Top 5 Free Open Source SaaS Starters in 2025 (Stop Paying for Code) Mohammed S. Mohammed S. Mohammed S. Follow Dec 18 '25 Top 5 Free Open Source SaaS Starters in 2025 (Stop Paying for Code) # webdev # opensource # ai # saas Comments Add Comment 3 min read Basics (Getting Started) with WJb Oleksandr Viktor Oleksandr Viktor Oleksandr Viktor Follow Dec 17 '25 Basics (Getting Started) with WJb # programming # webdev # ai Comments Add Comment 1 min read Start, Stop, and Continue for 2026 Aaron McCollum Aaron McCollum Aaron McCollum Follow Dec 19 '25 Start, Stop, and Continue for 2026 # webdev # programming # learning Comments Add Comment 3 min read Integrating Trust: A Developer's Guide to the Resume Protocol Obinna Duru Obinna Duru Obinna Duru Follow Dec 21 '25 Integrating Trust: A Developer's Guide to the Resume Protocol # webdev # web3 # typescript # ipfs 1 reaction Comments Add Comment 5 min read Signals vs Proxy vs Virtual DOM — What Actually Makes Them Different? Luciano0322 Luciano0322 Luciano0322 Follow Dec 22 '25 Signals vs Proxy vs Virtual DOM — What Actually Makes Them Different? # javascript # webdev # frontend # reactivity Comments Add Comment 4 min read Torrance Motors: Building a Fast, Reliable Automotive Website with C++ — Challenges Faced and Future Goals Alfie John Alfie John Alfie John Follow Dec 18 '25 Torrance Motors: Building a Fast, Reliable Automotive Website with C++ — Challenges Faced and Future Goals # webdev # programming # ai # javascript Comments Add Comment 9 min read 🚀 Launching Vyoma Labs: A Research-First Space for Building the Future of the Web Prasoon Jadon Prasoon Jadon Prasoon Jadon Follow Dec 17 '25 🚀 Launching Vyoma Labs: A Research-First Space for Building the Future of the Web # webdev # programming # startup # opensource Comments Add Comment 3 min read Understanding How Signals Work Luciano0322 Luciano0322 Luciano0322 Follow Dec 31 '25 Understanding How Signals Work # javascript # webdev # frontend # signals 1 reaction Comments Add Comment 3 min read Vibe Coding hit a wall: How I fixed $0.30/error OOMs and cut AI costs by 70% renming wang renming wang renming wang Follow Dec 17 '25 Vibe Coding hit a wall: How I fixed $0.30/error OOMs and cut AI costs by 70% # webdev # ai # programming # productivity 1 reaction Comments 1 comment 2 min read What is CSS? Kuganesh S Kuganesh S Kuganesh S Follow Dec 18 '25 What is CSS? # css # webdev Comments Add Comment 1 min read The New Field Keyword Improves Properties in C# 14 Adrián Bailador Adrián Bailador Adrián Bailador Follow Dec 17 '25 The New Field Keyword Improves Properties in C# 14 # csharp # dotnet # programming # webdev Comments Add Comment 6 min read StableJSON: A Practical Workspace for Serious JSON Work Debjit Dey Debjit Dey Debjit Dey Follow Dec 31 '25 StableJSON: A Practical Workspace for Serious JSON Work # programming # webdev # devtool # json Comments 1 comment 2 min read loading... 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.mrdbourke.com/charlie-walks/ | Charlie Walks: A Novel Daniel Bourke Home Now Machine Learning Posts Learn Machine Learning (courses I teach) ML Resources (things I recommend) About Newsletter Contact Book (Charlie Walks) YouTube Sign in Subscribe Charlie Walks: A Novel Short version My first book! If you enjoy my writing, you'll love this. You can find purchase the digital and paperback copies from charliewalks.com . Longer version Charlie Walks is the fictional story of a machine learning engineer/computer programmer who loves walks and wants to be a writer. More specifically... Charlie's a funambulist, a tightrope walker, walking between head and heart between city and nature between a good path and a real path a known path and his own between being a hider and being a seeker between life and death living and dying one option and another another another. The trick is, there's always more than two options. That's where XK-1 comes in. Charlie's secret project. A computer program that shows you what you're supposed to see but can't imagine. A machine learning engineer at the biggest technology company in the world who wants to be a writer. Writing letters to his nephew Pauly. Stories from his past from his present from loving from longing from wandering from walking, step by step creating his own story. This is the cover and some other photos of the fantastic physical copies. The yellow will pop on your bookshelf. Photos of Charlie Walks: A Novel paperback copies. The paper feels good in your hands. Sample chapters If you'd like to read it before you buy it, the first seven chapters are available online. Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 There's also a video on my YouTube channel of me reading the first 42 pages (16 chapters) out loud. And a fun launch video to celebrate the paperback version. It includes a bit of backstory to how the book was written and how it came to be. Buy the book You can purchase the paperback and digital version(s) (PDF, Kindle, EPUB) of the book at charliewalks.com . Buying the paperback comes with a free download link to the digital version(s) as well. Reviews Got a review? I'd love to read it/post it here. Feel free to email me . Daniel Bourke © 2026 Powered by Ghost | 2026-01-13T08:48:23 |
https://calendly.com/ | Free Online Appointment Scheduling Software | Calendly English English Français Español Deutsch Português Talk to sales Product Solutions Resources Pricing Log In Log In Log In Get started Log In Log In Log In Get started Product Scheduling Simplified booking Notetaker Meeting recaps and action items Product overview Why choose Calendly Platform Integrations Mobile app Browser extension Admin controls Security By business size Individuals For solopreneurs Small business For growing businesses Large companies For enterprise By team By industry Sales Marketing Customer success Recruiting Education Technology Financial Services Professional Services Explore Customer stories See how businesses are growing with calendly Blog Read the latest product and company news Resource library Access ebooks, webinars, guides, videos, and more About us Discover our mission and commitment to customers The State of Meetings 2024 Gain insights on how meetings are changing—spanning productivity, engagement, and strategies for improvement across roles and industries. Learn & connect Help Center API & Developer tools Calendly Community Newsroom Contact us Trusted by more than 100,000 of the world’s leading organizations Calendly makes scheduling simple Calendly’s easy enough for individual users, and powerful enough to meet the needs of enterprise organizations — including 86% of the Fortune 500 companies. Sign up for free Connect your calendars Calendly connects up to six calendars to automate scheduling with real-time availability. Add your availability Keep invitees informed of your availability. Take control of your calendar with detailed availability settings, scheduling rules, buffers, and more. Connect conferencing tools Sync your video conferencing tools and set preferences for in-person meetings or calls. Customize your event types Choose from pre-built templates or quickly create custom event types for any meeting you need to schedule. Share your scheduling link Easily book meetings by embedding scheduling links on your website, landing pages, or emails. Connect Calendly to the tools you already use Boost productivity with 100+ integrations View all integrations Google suite Get your job done faster by connecting Calendly to Google Calendar, Meet, Analytics, and more. Microsoft suite Make your day easier with Calendly integrations for Microsoft Teams, Outlook, Azure SSO , and more. Pick the perfect plan for your team Billed yearly Billed monthly Billed yearly Free For personal use Always free Get started Standard Yearly For professionals and small teams $10 /seat/mo Save 16% Get started Teams Yearly Recommended plan For growing businesses $16 /seat/mo Save 20% Try for Free Enterprise For large companies Starts at $15k /yr Talk to sales Free For personal use Always free Get started Standard Yearly For professionals and small teams $10 /seat/mo Save 16% Get started Teams Yearly Recommended plan For growing businesses $16 /seat/mo Save 20% Try for Free Enterprise For large companies Starts at $15k /yr Talk to sales Learn more on our pricing page Discover how businesses grow with Calendly View customer stories 169 % return on investment Read now 160 % increase in customers reached Read now 20 % decrease in scheduling errors Read now 8 days reduction in time-to-hire Read now 26 % increase in website bookings Read now Built to keep your organization secure Keep your scheduling data secure with enterprise-grade admin management, security integrations, data governance, compliance audits, and privacy protections. Learn more Power up your scheduling Get started in seconds — for free. Start for free Get a demo Product Scheduling automation Meeting Notetaker Customizable availability Mobile apps Browser extensions Meeting routing Event Types Email & website embeds Reminders & follow-ups Meeting polls Analytics Admin management Integrations Google ecosystem Microsoft ecosystem Calendars Video conferencing Payments Sales & CRM Recruiting & ATS Email messaging Embed Calendly Analytics API & connectors Security & compliance Calendly Pricing Product overview Solutions For individuals For small businesses For large companies Compare Security Sign up for free Talk to sales Get a demo Resources Help center Resource center Blog Customer stories Calendly community Developer tools Release notes Company About us Leadership Careers We’re hiring! Newsroom Become a partner Contact us Downloads App Store Google Play Chrome extension Edge extension Firefox extension Safari extension Outlook add-in English English Français Español Deutsch Português Privacy Policy Legal Status Cookie Settings Your Privacy Choices Copyright Calendly | 2026-01-13T08:48:23 |
https://dev.to/ajtiti/ajtiti-38-o-integracji-systemow#main-content | AjTiTi #38 - O integracji systemów - 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 AjTiTi [PL] Follow AjTiTi #38 - O integracji systemów Apr 1 '22 play "You can't buy integration" - z tego zdania wypłynął temat odcinka: integracja systemów. Niemalże każde oprogramowanie wymaga jakiejś integracji. Dlatego ważne aby wiedzieć, jak podejść do tego tematu w sposób efektywny i w maksymalnie bezbolesny. Artykuł na blogu Martina Fowlera: https://martinfowler.com/articles/cant-buy-integration.html Episode source Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Your browser does not support the audio element. 1x initializing... × 💎 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 | 2026-01-13T08:48:23 |
https://socket.io/docs/v4/broadcasting-events/ | Broadcasting events | Socket.IO Skip to main content Latest blog post (July 25, 2024): npm package provenance . Socket.IO Docs Guide Tutorial Examples Emit cheatsheet Server API Client API Ecosystem Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Become a sponsor 4.x 4.x 3.x 2.x Changelog English English Español Français Português (Brasil) 中文（中国） Search Socket.IO Documentation Server Client Events Emitting events Listening to events Broadcasting events Rooms Adapters Advanced Migrations Miscellaneous Events Broadcasting events Version: 4.x On this page Broadcasting events Socket.IO makes it easy to send events to all the connected clients. info Please note that broadcasting is a server-only feature. To all connected clients io . emit ( "hello" , "world" ) ; caution Clients that are currently disconnected (or in the process of reconnecting) won't receive the event. Storing this event somewhere (in a database, for example) is up to you, depending on your use case. To all connected clients except the sender io . on ( "connection" , ( socket ) => { socket . broadcast . emit ( "hello" , "world" ) ; } ) ; note In the example above, using socket.emit("hello", "world") (without broadcast flag) would send the event to "client A". You can find the list of all the ways to send an event in the cheatsheet . With acknowledgements Starting with Socket.IO 4.5.0, you can now broadcast an event to multiple clients and expect an acknowledgement from each one of them: io . timeout ( 5000 ) . emit ( "hello" , "world" , ( err , responses ) => { if ( err ) { // some clients did not acknowledge the event in the given delay } else { console . log ( responses ) ; // one response per client } } ) ; All broadcasting forms are supported: in a room io . to ( "room123" ) . timeout ( 5000 ) . emit ( "hello" , "world" , ( err , responses ) => { // ... } ) ; from a specific socket socket . broadcast . timeout ( 5000 ) . emit ( "hello" , "world" , ( err , responses ) => { // ... } ) ; in a namespace io . of ( "/the-namespace" ) . timeout ( 5000 ) . emit ( "hello" , "world" , ( err , responses ) => { // ... } ) ; With multiple Socket.IO servers Broadcasting also works with multiple Socket.IO servers. You just need to replace the default adapter by the Redis Adapter or another compatible adapter . In certain cases, you may want to only broadcast to clients that are connected to the current server. You can achieve this with the local flag: io . local . emit ( "hello" , "world" ) ; In order to target specific clients when broadcasting, please see the documentation about Rooms . Edit this page Last updated on Nov 15, 2025 Previous Listening to events Next Rooms To all connected clients To all connected clients except the sender With acknowledgements With multiple Socket.IO servers Documentation Guide Tutorial Examples Server API Client API Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Become a sponsor Copyright © 2026 Socket.IO | 2026-01-13T08:48:23 |
https://docs.devcycle.com/platform/security-and-guardrails/permissions/#basic-permissions-organization-wide-roles | Roles & Permissions | 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 Roles & Permissions On this page Roles & Permissions At DevCycle, our permissions model is designed to protect production while supporting secure and scalable team collaboration. We offer flexible, role-based access controls that can be applied both at the Organization and Project level—allowing you to tailor access based on how your teams operate. Permissions are available for Organizations on our Business or Enterprise plans. You can visit our pricing page or contact our support team to learn more about our plans. Permission Levels Overview DevCycle supports multiple levels of permission enforcement: Flat Access (default) : All users have full access across all Projects Basic Permissions : Org-wide roles that protect production Environments (Business and Enterprise plans) Full Role-Based Access Control (RBAC) : Fine-grained permissions managed at the Project level (Enterprise plans only) info Permissions enforcement will apply to all Projects and Production-type Environments within your Organization. Basic Permissions (Organization-Wide Roles) Basic permissions apply at the Organization level and are available to all Business and Enterprise customers. The principle behind basic permissions is to protect Production Environments while keeping permissions and their management as lightweight as possible. This level is perfect for teams that want to be able to move fast but still require some governance protections to be in place. info To enable basic permissions, navigate to your Organization Settings page and enable it under the permissions dropdown. The roles available with Basic Permissions are: Members Can ✅ Configure Development and Staging Environments Configure Inactive Production Environments Cannot ❌ Enable or Disable Production Environments Targeting Configure Active Production Environments When Production is Active , Configure Variables and Variations Manage roles of other users Manage Organization or Project settings Publishers Everything Members can do, plus: Can ✅ Enable or Disable Production Environments Targeting Configure Active Production Environments When Production is Active , Configure Variables and Variations Manage Project settings Cannot ❌ Manage roles of other users Manage Organization settings or billing Owners Everything Publishers can do, plus: Can ✅ Manage roles of all users in the Organization Administer billing Assigning Roles To assign a role to a team member, simply navigate to their profile. If you are an owner, you will be able to assign a new role to the member by using the Role dropdown. After you have selected a role, click "save" and the team member's permissions will be updated. For the user to have the new permission level available to them they will need to generate a new session by logging in again. Full Role-Based Access Control (Project-Level Roles – Enterprise Only) For Organizations managing multiple teams or business units, DevCycle offers Project-level RBAC on Enterprise plans. This allows you to manage roles granularly, granting access only to the specific workspaces your team members need with the requisite roles they need in each of those workspaces. With Role-Based Access Control, you can: Scope access to individual Projects Prevent cross-project visibility and restrict access to only the Projects a user is assigned Align access with your SSO groups and SCIM-based provisioning This enables centralized identity and access management with decentralized control, especially when integrated with providers like Azure AD or Okta. info To enable and configure SSO and SCIM-based provisioning, please contact our support team. Role Matrix The table below outlines actions available to each role across Organization and Project levels. note All actions affecting Production Environments are restricted for roles below Publisher . Action Viewer Member Publisher Project Admin Org Admin Org Owner organization:read:settings ✅ ✅ ✅ ✅ ✅ ✅ organization:write:settings ✅ ✅ organization:read:members ✅ ✅ ✅ ✅ ✅ ✅ organization:write:members ✅ ✅ organization:read:billing ✅ ✅ ✅ ✅ ✅ ✅ organization:write:billing ✅ organization:read:projects ✅ ✅ ✅ project:read ✅ ✅ ✅ ✅ ✅ project:write ✅ project:write:settings ✅ ✅ project:delete ✅ feature:read:staleness ✅ ✅ ✅ feature:read ✅ ✅ ✅ ✅ ✅ feature:write ✅ ✅ ✅ ✅ feature:publish ✅ ✅ ✅ feature:delete ✅ ✅ feature:status:archive ✅ ✅ ✅ ✅ feature:status:complete ✅ ✅ ✅ feature:read:config ✅ ✅ ✅ ✅ ✅ feature:write:config ✅ ✅ ✅ ✅ audience:write ✅ ✅ ✅ ✅ audience:read ✅ ✅ ✅ ✅ ✅ audience:write:prod ✅ ✅ ✅ audience:delete ✅ ✅ variable:read ✅ ✅ ✅ ✅ ✅ variable:write ✅ ✅ ✅ ✅ variable:write:prod ✅ ✅ environment:read ✅ ✅ ✅ ✅ ✅ environment:write ✅ ✅ ✅ ✅ environment:delete ✅ ✅ variation:read ✅ ✅ ✅ ✅ ✅ variation:write ✅ ✅ ✅ ✅ variation:delete ✅ ✅ ✅ ✅ results:read ✅ ✅ ✅ ✅ ✅ user:read ✅ ✅ ✅ ✅ ✅ user:write ✅ ✅ ✅ ✅ ✅ auditlog:read ✅ ✅ ✅ ✅ ✅ customproperty:read ✅ ✅ ✅ ✅ ✅ customproperty:write ✅ ✅ ✅ ✅ customproperty:delete ✅ ✅ ✅ ✅ metric:read ✅ ✅ ✅ ✅ ✅ metric:write ✅ ✅ ✅ ✅ metric:delete ✅ ✅ ✅ ✅ metricassociation:read ✅ ✅ ✅ ✅ ✅ metricassociation:write ✅ ✅ ✅ ✅ metricassociation:delete ✅ ✅ ✅ ✅ project:read:overrides ✅ ✅ ✅ ✅ ✅ project:write:overrides ✅ ✅ ✅ ✅ ✅ webhook:read ✅ ✅ ✅ ✅ ✅ webhook:write ✅ ✅ ✅ ✅ webhook:delete ✅ ✅ ✅ project:read:tokens ✅ ✅ project:write:tokens ✅ Managing Role Mappings with SCIM and SSO For Enterprise customers using identity providers (IdPs) like Azure AD or Okta, DevCycle supports role mapping through SCIM and SSO group-based permissions . Roles can be mapped to IdP groups Users are automatically assigned the correct roles upon login Centralized IT control, local team autonomy This streamlines onboarding and offboarding, and ensures the principle of least privilege is maintained. To get started with Role-Based Access Control, contact our support team. Edit this page Last updated on Jan 9, 2026 Previous Feature Obfuscation Next SDK Visibility Permission Levels Overview Basic Permissions (Organization-Wide Roles) Members Publishers Owners Assigning Roles Full Role-Based Access Control (Project-Level Roles – Enterprise Only) Role Matrix Managing Role Mappings with SCIM and SSO DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved. | 2026-01-13T08:48:23 |
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https://dev.to/adventures_in_ml/the-disruptive-power-of-artificial-intelligence-ml-100#main-content | The Disruptive Power of Artificial Intelligence - ML 100 - 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 Adventures in Machine Learning Follow The Disruptive Power of Artificial Intelligence - ML 100 Jan 19 '23 play Have you ever wondered about the most promising industries in Machine Learning? Today we will learn from Avi Goldfarb, the chair of AI at the University of Toronto, about... The most promising AI industries Potential problems with powerful AI The economics behind innovation On YouTube The Disruptive Power of Artificial Intelligence - ML 100 Sponsors Chuck's Resume Template Developer Book Club starting with Clean Architecture by Robert C. Martin Become a Top 1% Dev with a Top End Devs Membership Links Power and Prediction: The Disruptive Economics of Artificial Intelligence Avi Goldfarb LinkedIn: Avi Goldfarb Advertising Inquiries: https://redcircle.com/brands Privacy & Opt-Out: https://redcircle.com/privacy Episode source Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Your browser does not support the audio element. 1x initializing... × 💎 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 | 2026-01-13T08:48:23 |
https://dev.to/sim4n6 | Sim4n6 - 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 Sim4n6 404 bio not found Joined Joined on Nov 22, 2019 github website More info about @sim4n6 Badges 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 Post 0 posts published Comment 1 comment written Tag 13 tags followed Want to connect with Sim4n6? Create an account to connect with Sim4n6. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in 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 | 2026-01-13T08:48:23 |
https://ruul.io/blog/why-is-remote-work-more-appealing-to-black-workers?7c89d873_page=2 | Blog | For Freelancers, Creators, and Indie Professionals Product Payment Requests Get paid anywhere. Sell Services Make your services buyable Sell Products Create once sell forever Subscriptions Get paid on repeat Ruul Space Your personel storefront. One link for everything you offer. Learn more Pricing Resources Partner Programs Referral Program Get 1% for life. Seriously. Affiliate Program Bring users, get paid Partners Let’s grow together. More Blog About us Support Brand Kit For Customers Log in Sign up For Businesses Login Sign up grow 13 Best Fiverr Alternatives Freelancers Need to Know Read POPULAR ARTICLES How to Accept Online Payments: A Comprehensive Guide for Businesses and Freelancers Learn how to set up and manage secure online payment systems for your business or freelance work. 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Ruul is a merchant-of-record platform helping freelancers and creators globally sell services, digital products, subscriptions, and easily get paid. Who is Ruul for? Ruul is designed for freelancers, creators, and independent professionals who want a simple way to sell online and get paid globally. How does Ruul work? Open an account, complete a quick verification (KYC), and link your payout account. Then, start selling through your store or send payment requests to customers instantly. How does pricing work? Signing up is free. There are no subscription or hidden fees. Ruul charges a small commission only when you sell or get paid through the platform. What is a Merchant of Record? A merchant of record is the legal seller responsible for processing payments, handling taxes, and managing compliance for each transaction. What can I sell on Ruul? You can sell services, digital products, license keys, online courses, subscriptions, and digital memberships. How do I get paid on Ruul? Add your preferred bank account, digital wallet, or receive payouts in stablecoins as crypto. Funds arrive within 24 hours after a payout is triggered. OPEN AN ACCOUNT START MAKING MONEY TODAY ruul.space/ Thank you! Your submission has been received! Oops! Something went wrong while submitting the form. Trustpilot Product Payment Requests Sell Services Sell Products Subscriptions Ruul Space Pricing For Businesses Resources Blog About Contact Support Referral Program Affiliate Program Partner Program Tools Invoice Generator NDA Generator Service Agreement Generator Freelancer Hourly Rate Calculator All Rights Reserved © 2025 Terms Of Use Privacy Policy | 2026-01-13T08:48:23 |
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https://allyforonlysintech.com | Ally for Onlys in Tech | Career coaching for underrepresented software professionals Press "Enter" to skip to content Ally for Onlys in Tech One-on-one coaching for underrepresented midcareer software professionals open menu Home Coaching Services Rates Contact Testimonials Talks Books Resources About linkedin Ally for Onlys in Tech Are you the only on your professional software team? Do you feel proud of your achievements yet face additional obstacles imperceptible to co-workers? Would assistance and encouragement from an experienced ally help you achieve your career goals? If so, let’s talk . I’m Eric Brechner. My one-on-one coaching for underrepresented midcareer software professionals provides techniques, strategies, and support to overcome obstacles and achieve goals. I’ve been coaching development leads, managers, architects, experts, students, and my own diverse employees for over 25 years. Many became directors, distinguished engineers, and even corporate vice presidents. I’d enjoy working with you. While navigating a career is challenging for everyone, people who look dissimilar to or act differently from their co-workers often face additional obstacles. Yet research has demonstrated that these diverse people generate the innovative and inclusive solutions needed to succeed in the marketplace. I’m dyslexic, and my son’s autistic—this is personal for me. I’ve helped many people like you progress from being an individual engineer or new engineering lead to becoming a senior, principal, or partner engineer, and/or a lead, manager, architect, or director. We’ll discuss utilizing your strengths while mitigating your weaknesses in order to achieve your career goals and success as you define them. To learn more about my approach, click Coaching . You can also take a look at my services , rates , testimonials from those I’ve assisted, books and resources I’ve written, talks I’ve given, and more personal details about me . Please schedule a free, no-obligation, confidential, initial consult with me today. Share this: Click to email a link to a friend (Opens in new window) Email Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on X (Opens in new window) X Click to share on Facebook (Opens in new window) Facebook Click to share on Reddit (Opens in new window) Reddit More Click to print (Opens in new window) Print Click to share on Pinterest (Opens in new window) Pinterest Click to share on WhatsApp (Opens in new window) WhatsApp Click to share on Tumblr (Opens in new window) Tumblr Click to share on Pocket (Opens in new window) Pocket Click to share on Telegram (Opens in new window) Telegram Sidebar Schedule a Free Confidential Call Eric Brechner, Ph.D. Career Coach and Founder, Ally for Onlys in Tech Affiliate Professor, UW Bothell Testimonials I found instant connection with Eric and felt he understood my struggles and felt safe and encouraged to get his advice. As my career grows, I have often used Eric as my sounding board and bounced off different leadership challenges. Eric was my first and the longest mentor in my Microsoft career. I have known Eric for over 20 years. I first met Eric through his class for coaching engineering managers. I found instant connection with Eric and felt he understood my struggles and felt safe and encouraged to get his advice. As my career grows, I have often used Eric as my sounding board and bounced off different leadership challenges. What I remember the most and probably his best advice to me is: “As a female in tech industry, you already stood out, so why try to blend in. Be comfortable with who you are, as that’s the only advantage you have over your male colleagues by standing out.” “I found instant connection with Eric and felt he understood my struggles and felt safe and encouraged to get his advice.” Joy Chik Corporate Vice President, Microsoft I’ve had the pleasure of working with Eric for many years. He’s been a steady source of knowledge and professional advice about so many things, ranging from design and architecture advice, to manager tips, to simple wisdom in navigating career moves. He’s been a steady source of knowledge and professional advice about so many things, ranging from design and architecture advice, to manager tips, to simple wisdom in navigating career moves. I’m certainly the better for my time spent with him. My career is going great! “I’ve had the pleasure of working with Eric for many years.” Karl Reese Principal Group Engineering Manager, Microsoft [Eric] started mentoring me when I was a senior developer struggling to find ways to find room for myself on projects dominated by territorial coworkers. I would not still be in the industry without his help and guidance finding my way through several tough situations I found myself in. With his help, I have grown into a manager confident in my ability to lead teams where people feel more included and confident than I did earlier in my career. Eric has been my mentor/coach for about a decade. He started mentoring me when I was a senior developer struggling to find ways to find room for myself on projects dominated by territorial coworkers. I would not still be in the industry without his help and guidance finding my way through several tough situations I found myself in. With his help, I have grown into a manager confident in my ability to lead teams where people feel more included and confident than I did earlier in my career. In my most productive meetings with Eric, I come and share something that is stressing me out, generally some challenge related to working with other people or having my voice heard. He listens to me, takes the time to really understand what the root of the problem is, who the players are and what I want out of the situation. Then he shares a structured way of thinking about the situation that is always insightful. We talk through possible next steps and how they’re likely to play out. Because he knew I wanted to grow in to a manager role, long before I was actually a manager he would talk to me about both what I could do as an IC and also what my manager could do in the situation. This gave me experience thinking through the types of levers a manager has available and how and when to use them long before I took the leap into management. This helped me grow into the manager I wanted to be much faster and more confidently than would have been possible without his mentorship and coaching. I now ask myself “what would Eric do” when I find myself in a tough situation (or mentoring someone else in a tough situation), and more often than not, that’s enough to help me find a path forward. “[Eric] started mentoring me when I was a senior developer struggling to find ways to find room for myself on projects dominated by territorial coworkers.” Ann Williams Principal Group Engineering Manager, Microsoft The leadership and mentorship Dr. B provided gave me confidence and constructive suggestions. He offered feedback with specific examples, which added context to his recommendations. In addition, he took the time to learn my needs and communication style, which encouraged me to put more effort into developing my leadership style. Dr. Eric Brechner was my manager in 2014 when I interned for Microsoft. At the start of the internship, he aligned my skillset with the team’s needs. He patiently facilitated my project progression, prompting me with questions to expose hidden assumptions. Dr. B helped me to understand what I needed to learn to grow my career, and he provided resources, detailed feedback, and the space to grow as a professional at my own pace. The leadership and mentorship Dr. B provided gave me confidence and constructive suggestions. He offered feedback with specific examples, which added context to his recommendations. In addition, he took the time to learn my needs and communication style, which encouraged me to put more effort into developing my leadership style. I am grateful to have worked with Dr. B; he was the first person to help me identify habits that could stagnate my career growth. Dr. B was a great career coach and sponsor! “The leadership and mentorship Dr. B provided gave me confidence and constructive suggestions.” Cimone Wright-Hamor Founder, HeyCimone Eric is kind-hearted, loyal, and is a good listener who often provides the kinds of fresh perspectives and new ideas that are so valuable to those learning to move up in an organization. I highly value the time I spent with him and the valuable lessons I learned during that first big transition in my own career. I highly recommend Eric Brechner as a mid-career coach. He’s talented insightful, extremely skilled and has a great sense of humor to go along with his many years of experience as a Leader in the field of High Tech. I worked with Eric during my own difficult transition from manager of a small team of 5 based in the U.S. to a much larger international team of 35 with a complex Worldwide reporting structure. With Eric’s guidance and support and his complete trust in my ability to succeed I was able to make this transition and grow exponentially without falling to pieces or becoming frustrated with the sudden organizational change that handed me so much new responsibility. Eric is kind-hearted, loyal, and is a good listener who often provides the kinds of fresh perspectives and new ideas that are so valuable to those learning to move up in an organization. I highly value the time I spent with him and the valuable lessons I learned during that first big transition in my own career. “Eric is kind-hearted, loyal, and is a good listener who often provides the kinds of fresh perspectives and new ideas that are so valuable to those learning to move up in an organization.” Suzanne Sowinska Former Director of Programs at Microsoft [Eric] helped me become an educator, and exposed me to a whole new set of engineering methodologies, which I then used to enhance the capabilities of numerous engineers across the planet. It’s been 20 years, and I still find the pearls of wisdom that resonate and give a different perspective. Before I ever actually met Eric, I was reading his I.M. Wight “Hard Code” columns, and found more often than not I was nodding my head “Yes, exactly!!”. It’s been 20 years, and I still find the pearls of wisdom that resonate and give a different perspective. I had the opportunity to grow my career working in the Engineering Excellence team, and worked directly for Eric for 4 years. He helped me become an educator, and exposed me to a whole new set of engineering methodologies, which I then used to enhance the capabilities of numerous engineers across the planet. Eric is a thoughtful empathetic, and very experienced leader. We actually worked together to establish the first iteration of Career Stage Profiles, which were guidance on what is expected of engineers at various stages of their career growth and development. Eric has been in the industry long enough that giving guidance on how to make progress in an tech career is a natural part of his being. His knowledge, experience, and personal empathy make him a strong and trusted ally and coach for anyone’s career development aspirations. “[Eric] helped me become an educator, and exposed me to a whole new set of engineering methodologies, which I then used to enhance the capabilities of numerous engineers across the planet.” William Adams Azure Technical Advisor, Microsoft I like how practical his advice is I come to him looking for advice and encouragement even for some of the most challenging situations in my professional life and every time I leave energized and with a plan. The best of all is how he believes in me and encourages me to do my best and not worry about the rest. The result is that I’m happier in my job and more productive, and this is acknowledged by those around me. As a software engineer, I have always found Eric’s books and blog useful, but his influence over my career was even greater when I started getting 1-1 coaching. I come to him looking for advice and encouragement even for some of the most challenging situations in my professional life and every time I leave energized and with a plan. I like how practical his advice is (“make a list with _this_ information”, “get _these_ people in a meeting”, “don’t bother with _that_”). Number and dates? Yes, please: “Use less than 10 bullet points for that”, “Don’t spend more than 20 minutes on the task before asking for help”, “In this new project expect to be productive after 3 months”. The best of all is how he believes in me and encourages me to do my best and not worry about the rest. The result is that I’m happier in my job and more productive, and this is acknowledged by those around me. I am incredibly grateful for his help! “I like how practical his advice is” Ioana Pop Senior Software Engineer, Stellar Health I cannot recommend Eric highly enough as a career coach. He is knowledgeable, approachable, and truly dedicated to helping his clients succeed. I have been working with Eric as my career coach since 2020 and I am incredibly grateful for his guidance and support during this time. As a Deaf Asian woman in the tech industry, I have faced some unique challenges, but with Eric’s help, I have been able to overcome them and grow professionally. I am continuously amazed by the wealth of knowledge and experience that Eric brings to our sessions, and I have learned so much from him over the years. From the importance of self-reflection to the power of empathy, Eric has truly been a guiding light in my career. I have been working with Eric as my career coach since 2020 and I am incredibly grateful for his guidance and support during this time. As a Deaf Asian woman in the tech industry, I have faced some unique challenges, but with Eric’s help, I have been able to overcome them and grow professionally. Eric’s support goes beyond just offering advice. He listens to me with empathy and understanding and provides wisdom that is rooted in his extensive knowledge and experience. Our sessions are always productive, and I look forward to them because they provide me with the opportunity to learn and grow in a friendly and supportive environment. One specific example of how Eric has helped me is in the area of communication. He provided me with clear and effective strategies for improving my communication skills, even during difficult and ambiguous situations. Those skills have helped me to better understand the work environment and build strong relationships with my colleagues. There have been times when I questioned my choice of joining the tech industry, but Eric has always been there to help me see the positive and find a better fit. With his guidance, I was able to adjust my attitude and mindset, and eventually find a position where I enjoy my work, feel challenged, and am achieving my goals. I am continuously amazed by the wealth of knowledge and experience that Eric brings to our sessions, and I have learned so much from him over the years. From the importance of self-reflection to the power of empathy, Eric has truly been a guiding light in my career. In conclusion, I cannot recommend Eric highly enough as a career coach. He is knowledgeable, approachable, and truly dedicated to helping his clients succeed. I am grateful for our friendship and the impact that he has had on my life and career. “I cannot recommend Eric highly enough as a career coach. He is knowledgeable, approachable, and truly dedicated to helping his clients succeed.” Sophie Tian Software Engineer II, Microsoft Eric’s patience, insight, and feedback are unparalleled, and I am grateful for the professional and personal growth I achieved with his guidance. During my time with Eric, he helped me transition from college student/recent college graduate to experienced software engineer. I am a Microsoft employee who has worked with Eric during two summer internships, and two years full time at Microsoft. During my time with Eric, he helped me transition from college student/recent college graduate to experienced software engineer. Some examples of how Eric helped me: Eric assembled and managed an extremely diverse team at Microsoft, so when I joined I found I was able to quickly integrate myself into his team and connect with other teammates. Because I felt like part of the team from Day 1, I quickly gained confidence in speaking up and voicing my opinions in meetings. Something I initially struggled with during my time under Eric was pushing back or saying “no.” In a private setting, Eric took the time to coach me through different scenarios and practice alternative responses. Under Eric, I was able to develop better communication skills and feel much more confident in my interactions with peers. Eric’s patience, insight, and feedback are unparalleled, and I am grateful for the professional and personal growth I achieved with his guidance. “Eric’s patience, insight, and feedback are unparalleled, and I am grateful for the professional and personal growth I achieved with his guidance.” Melissa Najmabadi Software Engineer, Microsoft Eric helped me to understand what I needed to learn to grow my career, and gave me the resources, detailed feedback, and literally, the space to do it. Eric is the kind of leader and mentor that inspires confidence, a desire to learn and grow, and who gives you the details and feedback you need to be successful. He takes the time to learn your unique needs and work style, and then finds ways to teach you how to be successful using them. I am a long-time Microsoft employee who worked for Eric for about 6 years across Xbox and Windows, working on the engineering system. Eric helped me to understand what I needed to learn to grow my career, and gave me the resources, detailed feedback, and literally, the space to do it. Eric is the kind of leader and mentor that inspires confidence, a desire to learn and grow, and who gives you the details and feedback you need to be successful. He takes the time to learn your unique needs and work style, and then finds ways to teach you how to be successful using them. Through this, he sets a strong example for how to lead and grow a team using positive, encouraging, and inclusive approaches. Some examples of how Eric has helped me: I am an extremely kinesthetic learner (aka, I only learn while in motion), I often need to process information verbally (aka, I need to talk through problems), and I naturally have a loud voice that carries well. Due to this, I am unable to be productive in open office space, because constant motion and noise have negative impacts on those around you and are strongly socially discouraged. Xbox used open office spaces, but Eric was able to find a creative solution to get me my own office space, much to the delight of both myself and everyone around me. This enabled me to be orders of magnitude more productive. Very few managers would have taken this request as seriously or have put as much effort into meeting it, but Eric did, and I remain very grateful. I love working in the depths of the engineering system, but had trouble communicating to broader audiences why certain solutions were needed. Eric took the time to understand the details of the system, what solutions were needed, and then worked with me (using his legendary “red pen” 😊) to patiently help me learn to communicate more effectively and concisely. Being able to ask him detailed questions about why he communicated the way he did and explore tradeoffs and choices to communicate the same message was incredibly helpful. He took the time to meet me where I was at in my skills and help me grow them over a multi-year period in an incremental and digestible way. To this day, and even as I write this, I often recall his guidance and edit my communications based on it. I have greatly grown in my ability to interview, find good talent for my team, and to grow that talent over time as part of my team with Eric’s guidance. Eric is the best interviewer and talent finder I have ever seen, with an incredibly accurate ability to find overlooked “diamonds in the rough” and bring them into his team to be polished. This extends to how he approaches career growth (1:1’s, in Microsoft parlance) and how he is able to find what works for you to help you grow specific skills and abilities so that you are successful. He delights in teaching anyone who is interested how to improve their own ability to interview, select good talent, and grow their skills over time, and I have benefited greatly from it. “Eric helped me to understand what I needed to learn to grow my career, and gave me the resources, detailed feedback, and literally, the space to do it.” Mike Rowand Principal Engineering Lead, Microsoft [Eric] made sure that I did not let my disability dictate how I worked or limit what I could achieve. He made sure that I did not feel limited by my challenges and that I could achieve, even if through different means, the same goals as anyone else in my field. Eric was my manager and during that time he made sure that I did not let my disability dictate how I worked or limit what I could achieve. He made sure that I did not feel limited by my challenges and that I could achieve, even if through different means, the same goals as anyone else in my field. “[Eric] made sure that I did not let my disability dictate how I worked or limit what I could achieve.” Helga Arvilla Senior Program Manager, Microsoft He’s the kind of manager/mentor that you’ll want to keep working with. From his rich life experience as both a manager and a human being, you’ll always find more spiritual nourishment to absorb. Eric was my professor in UWB in 2016 and later I worked as his TA for two quarters in 2017. During those two years I got to experience his profound professional support and solid leadership. He demonstrated the essence of great leadership by efficient management and earnestly practice of what he advocates, the serving spirit of a leader. He takes initiative in a large scope of projects while taking care of the most trivial details. He’s the kind of manager/mentor that you’ll want to keep working with. From his rich life experience as both a manager and a human being, you’ll always find more spiritual nourishment to absorb. “He’s the kind of manager/mentor that you’ll want to keep working with.” Meng Yang Grad Student, University of Washington Shift WordPress Theme by Compete Themes. Scroll to the top | 2026-01-13T08:48:23 |
https://ruul.io/blog/8-ways-to-improve-remote-team-communications?7c89d873_page=2 | Blog | For Freelancers, Creators, and Indie Professionals Product Payment Requests Get paid anywhere. Sell Services Make your services buyable Sell Products Create once sell forever Subscriptions Get paid on repeat Ruul Space Your personel storefront. One link for everything you offer. Learn more Pricing Resources Partner Programs Referral Program Get 1% for life. Seriously. Affiliate Program Bring users, get paid Partners Let’s grow together. More Blog About us Support Brand Kit For Customers Log in Sign up For Businesses Login Sign up grow 13 Best Fiverr Alternatives Freelancers Need to Know Read POPULAR ARTICLES How to Accept Online Payments: A Comprehensive Guide for Businesses and Freelancers Learn how to set up and manage secure online payment systems for your business or freelance work. Discover popular payment methods, integration tips, security measures, and best practices to streamline transactions and boost efficiency. Top 15 Digital Nomad Jobs in 2025 Explore the 15 best digital nomad jobs in 2025, from writing to coding—fully remote, high-paying, and travel-friendly. The Ultimate Best AI Tools for Freelancers: Boosting Productivity in 2025 Discover the ultimate AI tools for freelancers in 2025 to enhance productivity and efficiency. From writing and graphic design to project management, explore top AI tools like ChatGPT, Grammarly, Canva, and more. Start optimizing your freelancing. How to Accept Cryptocurrency Payments Find the methods, benefits, and security considerations for accepting crypto payments. Know how cryptocurrencies can open new opportunities for your business. What to Sell as a Digital Product Want to make money while you sleep? From AI art to ebooks and plugins, here’s what actually sells in 2025 and makes your wallet happy! Best 13 Motivational Apps and Techniques You Need As You Work Solo Lack of motivation as an independent? See these motivation apps and techniques. get paid sell grow work news trends get paid sell grow work news trends How to Make Freelance Money I’ve mapped out the freelance income paths that will stick around until 2030. Shared all the pro tips and details in this post. Come check it out! Introducing MiniPay on Ruul: Faster Stablecoin Payment Ruul & MiniPay now bring instant, stablecoin payments with zero withdrawal fee for freelancers. Create virtual USD/EUR accounts, enjoy fast global transfers, and earn up to $275 in bonuses. Best Freelancing Websites Struggling to pick a freelancing website? These 16 categorized freelancing platforms will save your time, energy, and maybe your sanity! How to Get Paid as a Freelancer Don't let payments ruin your business! We've covered everything from the most important steps to the best methods! Designer's Guide to Dribbble All the potential Dribbble has to offer, and all the areas where it leaves you hanging. This Guide gives you all of that and more. Best Freelance Jobs You're looking for the best freelance jobs AI won't wipe out. Safe, in-demand, future-ready, long-lasting work… you'll find it all right here. MORE THAN 120,000 Independents Over 120,000 independents trust Ruul to sell their services, digital products, and securely manage their payments. FROM 190 Countries Truly global coverage: trusted across 190 countries with seamless payouts available in 140 currencies. PROCESSED $200m+ of Transactions Over $200M successfully processed, backed by an 8-year legacy of secure, reliable transactions trusted by independents worldwide. FREQUENTLY ASKED QUESTIONS Everything you need to know. Get clear, straightforward answers to the most common questions about using Ruul. hey@ruul.io What is Ruul? Ruul is a merchant-of-record platform helping freelancers and creators globally sell services, digital products, subscriptions, and easily get paid. Who is Ruul for? Ruul is designed for freelancers, creators, and independent professionals who want a simple way to sell online and get paid globally. How does Ruul work? Open an account, complete a quick verification (KYC), and link your payout account. Then, start selling through your store or send payment requests to customers instantly. How does pricing work? Signing up is free. There are no subscription or hidden fees. Ruul charges a small commission only when you sell or get paid through the platform. What is a Merchant of Record? A merchant of record is the legal seller responsible for processing payments, handling taxes, and managing compliance for each transaction. What can I sell on Ruul? You can sell services, digital products, license keys, online courses, subscriptions, and digital memberships. How do I get paid on Ruul? Add your preferred bank account, digital wallet, or receive payouts in stablecoins as crypto. Funds arrive within 24 hours after a payout is triggered. OPEN AN ACCOUNT START MAKING MONEY TODAY ruul.space/ Thank you! Your submission has been received! Oops! Something went wrong while submitting the form. Trustpilot Product Payment Requests Sell Services Sell Products Subscriptions Ruul Space Pricing For Businesses Resources Blog About Contact Support Referral Program Affiliate Program Partner Program Tools Invoice Generator NDA Generator Service Agreement Generator Freelancer Hourly Rate Calculator All Rights Reserved © 2025 Terms Of Use Privacy Policy | 2026-01-13T08:48:23 |
https://ruul.io/blog/transgender-rights-and-gender-equality-in-the-workplace | Blog | For Freelancers, Creators, and Indie Professionals Product Payment Requests Get paid anywhere. Sell Services Make your services buyable Sell Products Create once sell forever Subscriptions Get paid on repeat Ruul Space Your personel storefront. One link for everything you offer. Learn more Pricing Resources Partner Programs Referral Program Get 1% for life. Seriously. Affiliate Program Bring users, get paid Partners Let’s grow together. More Blog About us Support Brand Kit For Customers Log in Sign up For Businesses Login Sign up grow 13 Best Fiverr Alternatives Freelancers Need to Know Read POPULAR ARTICLES How to Accept Online Payments: A Comprehensive Guide for Businesses and Freelancers Learn how to set up and manage secure online payment systems for your business or freelance work. Discover popular payment methods, integration tips, security measures, and best practices to streamline transactions and boost efficiency. Top 15 Digital Nomad Jobs in 2025 Explore the 15 best digital nomad jobs in 2025, from writing to coding—fully remote, high-paying, and travel-friendly. The Ultimate Best AI Tools for Freelancers: Boosting Productivity in 2025 Discover the ultimate AI tools for freelancers in 2025 to enhance productivity and efficiency. From writing and graphic design to project management, explore top AI tools like ChatGPT, Grammarly, Canva, and more. Start optimizing your freelancing. How to Accept Cryptocurrency Payments Find the methods, benefits, and security considerations for accepting crypto payments. Know how cryptocurrencies can open new opportunities for your business. What to Sell as a Digital Product Want to make money while you sleep? From AI art to ebooks and plugins, here’s what actually sells in 2025 and makes your wallet happy! Best 13 Motivational Apps and Techniques You Need As You Work Solo Lack of motivation as an independent? See these motivation apps and techniques. get paid sell grow work news trends get paid sell grow work news trends How to Make Freelance Money I’ve mapped out the freelance income paths that will stick around until 2030. Shared all the pro tips and details in this post. Come check it out! Introducing MiniPay on Ruul: Faster Stablecoin Payment Ruul & MiniPay now bring instant, stablecoin payments with zero withdrawal fee for freelancers. Create virtual USD/EUR accounts, enjoy fast global transfers, and earn up to $275 in bonuses. Best Freelancing Websites Struggling to pick a freelancing website? These 16 categorized freelancing platforms will save your time, energy, and maybe your sanity! How to Get Paid as a Freelancer Don't let payments ruin your business! We've covered everything from the most important steps to the best methods! Designer's Guide to Dribbble All the potential Dribbble has to offer, and all the areas where it leaves you hanging. This Guide gives you all of that and more. Best Freelance Jobs You're looking for the best freelance jobs AI won't wipe out. Safe, in-demand, future-ready, long-lasting work… you'll find it all right here. MORE THAN 120,000 Independents Over 120,000 independents trust Ruul to sell their services, digital products, and securely manage their payments. FROM 190 Countries Truly global coverage: trusted across 190 countries with seamless payouts available in 140 currencies. PROCESSED $200m+ of Transactions Over $200M successfully processed, backed by an 8-year legacy of secure, reliable transactions trusted by independents worldwide. FREQUENTLY ASKED QUESTIONS Everything you need to know. Get clear, straightforward answers to the most common questions about using Ruul. hey@ruul.io What is Ruul? Ruul is a merchant-of-record platform helping freelancers and creators globally sell services, digital products, subscriptions, and easily get paid. Who is Ruul for? Ruul is designed for freelancers, creators, and independent professionals who want a simple way to sell online and get paid globally. How does Ruul work? Open an account, complete a quick verification (KYC), and link your payout account. Then, start selling through your store or send payment requests to customers instantly. How does pricing work? Signing up is free. There are no subscription or hidden fees. Ruul charges a small commission only when you sell or get paid through the platform. What is a Merchant of Record? A merchant of record is the legal seller responsible for processing payments, handling taxes, and managing compliance for each transaction. What can I sell on Ruul? You can sell services, digital products, license keys, online courses, subscriptions, and digital memberships. How do I get paid on Ruul? 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https://dev.to/leena_malhotra/why-asking-for-better-outputs-misses-the-real-problem-29f9#the-long-document-problem | Why Asking for Better Outputs Misses the Real Problem - 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 Leena Malhotra Posted on Jan 12 Why Asking for Better Outputs Misses the Real Problem # programming # ai # imagegen # nanobanana Yesterday, I spent four hours debugging why Ideogram V3 kept generating inconsistent architectural renders. The whitepaper promised "improved spatial coherence." My outputs looked like they were designed by committee. This isn't a model problem. It's a workflow problem. When Ideogram V3's Whitepaper Met Reality I was building a pipeline to generate interior design variations for an e-commerce platform. The whitepaper showed beautiful examples of architectural spaces with perfect lighting. Here's the prompt I used from their examples: "Modern minimalist living room, floor-to-ceiling windows, natural light, Scandinavian furniture, architectural photography" Enter fullscreen mode Exit fullscreen mode First three generations: perfect. Fourth one: furniture floating off the ground. Fifth: window placement changed. By the tenth iteration, I had seven different room layouts. Same seed, same parameters, same model version. The issue wasn't randomness—it was me treating each generation as independent. The whitepaper examples worked because they were single, carefully-constructed prompts. I was running iterative experiments without maintaining state. The fix: class PromptContext : def __init__ ( self , base_intent ): self . base_intent = base_intent self . style_locks = {} def generate_with_memory ( self , variation ): locked = " " . join ([ f " { k } : { v } " for k , v in self . style_locks . items ()]) return f " { self . base_intent } . { locked } . { variation } " context = PromptContext ( " Modern minimalist living room " ) context . style_locks [ " windows " ] = " floor-to-ceiling on north wall " context . style_locks [ " floor " ] = " light oak hardwood " Enter fullscreen mode Exit fullscreen mode Cost: 40% more tokens per request. Benefit: went from 60% usable outputs to 95%. The whitepaper shows capability, not workflow. When you can test the same prompt across multiple AI models , the dissonance between documentation and reality becomes measurable rather than frustrating. SD3.5 Medium's Averaging Problem I needed product packaging concepts that felt "premium but approachable" for a beverage brand. The brief: Japanese minimalism meets 1970s American optimism. First attempt: { " prompt " : " Premium beverage packaging, minimalist, warm nostalgic colors, sophisticated " , " cfg_scale " : 7.5 , " sampler " : " DPM++ 2M Karras " } Enter fullscreen mode Exit fullscreen mode Result: generic wellness brand aesthetics. Technically perfect. Strategically useless. I ran 50 variations testing cfg_scale from 5.0 to 12.0: cfg_scale=5.0 → Lost brand identity cfg_scale=7.5 → Safe, averaged aesthetics cfg_scale=10.0 → Interesting tensions emerged cfg_scale=12.0 → Overcooked, but committed Enter fullscreen mode Exit fullscreen mode The fix: Stop describing the middle ground. Describe the extremes. prompt_a = " 1970s American optimism, warm oranges, rounded typography, sunburst graphics " prompt_b = " Japanese minimalism, white space, geometric precision " # Generate separately at cfg_scale=11.0 # Then synthesize specific elements Enter fullscreen mode Exit fullscreen mode SD3.5 Medium optimizes for "nothing broken" with vague targets. Give it contradictory specifics and higher CFG, and you get interesting failures to work with. Three unusable images and one brilliant image beats ten mediocre ones. Trade-off: 3x generation time. But revision time savings made it worth it. When Nano Banana PRO New Silently Changed Three-month-old content pipeline. Generated weekly newsletter summaries. Worked fine. One Monday: every output was 40% shorter and weirdly formal. Before (v1.2): 480 tokens, conversational. After (v1.3): 310 tokens, corporate. Release notes: "improved efficiency and coherence." No mention of temperature rescaling. The diff script I now run: def model_regression_test ( old_model , new_model , test_prompts ): results = [] for prompt in test_prompts : old_response = generate ( old_model , prompt , temp = 0.7 ) new_response = generate ( new_model , prompt , temp = 0.7 ) diff = { " length_delta " : len ( new_response ) - len ( old_response ), " formality_delta " : analyze_formality ( new_response ) - analyze_formality ( old_response ) } if abs ( diff [ " length_delta " ]) > 100 : print ( f " WARNING: Length shift " ) results . append ( diff ) return results Enter fullscreen mode Exit fullscreen mode The actual issue: they changed temperature scaling. temp=0.7 in v1.3 behaved like temp=0.4 in v1.2. My fix: pin model versions in production, regression test before upgrading. # requirements.txt nano-banana-pro==1.2.8 # Regression test before upgrade Enter fullscreen mode Exit fullscreen mode "Improved" means "different." Treat model updates like database migrations. Running parallel tests across Nano Banana PRO New and legacy versions reveals what release notes hide. The Context Switching Tax My workflow last month: Draft prompt in ChatGPT Test in Jupyter notebook Check results in Notion Discuss in Slack Update Google Doc Re-run notebook Forget step 1 decisions I was generating legal disclaimer variations. Each category needed specific regulatory language. I'd test in ChatGPT, worked great. Copy to notebook, different results. Thirty minutes debugging before realizing different model versions. The system I built: class ExperimentLog : def __init__ ( self ): self . conn = sqlite3 . connect ( " experiments.db " ) self . setup_db () def log ( self , model , prompt , params , output , success , notes = "" ): self . conn . execute ( """ INSERT INTO experiments (timestamp, model, prompt, parameters, output, success) VALUES (?, ?, ?, ?, ?, ?) """ , ( datetime . now (). isoformat (), model , prompt , json . dumps ( params ), output [: 500 ], success )) def get_successful_prompts ( self , model ): return self . conn . execute ( """ SELECT prompt, parameters FROM experiments WHERE model = ? AND success = 1 ORDER BY timestamp DESC """ , ( model ,)). fetchall () Enter fullscreen mode Exit fullscreen mode Now I search "legal disclaimers last week" and get exact parameters, model version, output. No re-discovering. Context switching isn't just a productivity tax—it fragments intent into micro-decisions scattered across tools. The Long Document Problem 140-page RFP. Needed specific technical requirements. Cross-references, tables, nested appendices. Tried: upload to ChatGPT, ask questions. Me: "What are data retention requirements in Section 7?" ChatGPT: "The document mentions retention in multiple sections..." Me: "No, I need specific retention periods." ChatGPT: "Based on the document, periods vary by type..." Enter fullscreen mode Exit fullscreen mode Summaries of summaries. Never the actual spec. The workflow: def chunk_document ( pdf_path , chunk_size = 4000 ): reader = pypdf . PdfReader ( pdf_path ) chunks = [] for i , page in enumerate ( reader . pages ): text = page . extract_text () words = text . split () for start in range ( 0 , len ( words ), chunk_size - 200 ): chunks . append ({ " page " : i + 1 , " text " : " " . join ( words [ start : start + chunk_size ]) }) return chunks def extract_requirements ( pdf_path ): chunks = chunk_document ( pdf_path ) requirements = [] for chunk in chunks : prompt = f """ Extract technical requirements from: Page { chunk [ ' page ' ] } : { chunk [ ' text ' ] } Return JSON: {{ " requirements " : [{{ " type " : " retention " , " spec " : " 7 years " , " section " : " 7.3.2 " }}]}} """ result = call_llm_api ( prompt ) requirements . extend ( result . get ( " requirements " , [])) return requirements Enter fullscreen mode Exit fullscreen mode Output: [ { "type" : "retention" , "spec" : "7 years for financial records" , "section" : "7.3.2" , "page" : 45 }, { "type" : "retention" , "spec" : "3 years for operational logs" , "section" : "7.3.2" , "page" : 45 } ] Enter fullscreen mode Exit fullscreen mode Trade-off: more processing time and API costs. But went from 3 hours frustrated questioning to 20 minutes automated extraction. Research papers that took hours to read now take minutes with a Document Summarizer . What I'd Do Differently Starting over, I'd version everything. Git for prompts, not just code. Build logging first—wasted weeks re-discovering experiments. Test edge cases, not happy paths. The whitepaper examples are optimized demos. Automate diffs and treat model updates like schema migrations. This is still evolving. If you've hit similar workflow issues, drop a comment. -Leena:) 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 Leena Malhotra Follow Creator and strategist blending machine learning, business, and creativity. Harvard Business School ’06. Writing about AI, productivity, and building systems for a self-directed life. Location California, United states Education Harvard Business School Joined Jun 17, 2025 More from Leena Malhotra AI Explains Code Well Until the Moment Context Actually Matters # webdev # programming # ai Using AI in Production Code Without Creating Invisible Bugs # webdev # programming # ai Ship Faster, Break Less: My Rules for Using AI Safely in Codebases # webdev # programming # ai # coding 💎 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/jose_davidmuozalbir_b8#main-content | Jose david Muñoz albir - 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 Jose david Muñoz albir 404 bio not found Joined Joined on Dec 19, 2025 More info about @jose_davidmuozalbir_b8 Post 0 posts published Comment 1 comment written Tag 3 tags followed Want to connect with Jose david Muñoz albir? Create an account to connect with Jose david Muñoz albir. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in 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 | 2026-01-13T08:48:23 |
https://dev.to/ukrguru | Oleksandr Viktor - DEV Community Forem Feed Follow new Subforems to improve your feed DEV Community Follow A space to discuss and keep up software development and manage your software career Future Follow News and discussion of science and technology such as AI, VR, cryptocurrency, quantum computing, and more. Open Forem Follow A general discussion space for the Forem community. If it doesn't have a home elsewhere, it belongs here Gamers Forem Follow An inclusive community for gaming enthusiasts Music Forem Follow From composing and gigging to gear, hot music takes, and everything in between. Vibe Coding Forem Follow Discussing AI software development, and showing off what we're building. Popcorn Movies and TV Follow Movie and TV enthusiasm, criticism and everything in-between. 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A space to share projects, ask questions, and discuss server-driven templating Dropdown menu Dropdown menu Skip to content Navigation menu Search Powered by Algolia Search Log in Create account DEV Community Close Follow User actions Oleksandr Viktor Programming is my life! https://www.paypal.com/donate/?hosted_button_id=BPUF3H86X96YN Location Ukraine, Kyiv Joined Joined on Jan 2, 2025 Personal website https://ukrguru.com More info about @ukrguru Badges 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 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 Writing Debut Awarded for writing and sharing your first DEV post! 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Sign in 🚀 Building the Best SQL-Backed Job Queue with WJb and UkrGuru.Sql in .NET Oleksandr Viktor Oleksandr Viktor Oleksandr Viktor Follow Jan 2 🚀 Building the Best SQL-Backed Job Queue with WJb and UkrGuru.Sql in .NET # dotnet # csharp # sqlserver # opensource 2 reactions Comments Add Comment 2 min read Basics (Getting Started) with WJb Oleksandr Viktor Oleksandr Viktor Oleksandr Viktor Follow Dec 17 '25 Basics (Getting Started) with WJb # programming # webdev # ai Comments Add Comment 1 min read The Ultimate SQL Server Cron Expression Validator — Fast, Accurate, Battle-Tested Oleksandr Viktor Oleksandr Viktor Oleksandr Viktor Follow Oct 18 '25 The Ultimate SQL Server Cron Expression Validator — Fast, Accurate, Battle-Tested # sqlserver # programming # webdev # ai Comments Add Comment 10 min read Try UkrGuru.Sql with New Optimized `Results.Parse` Oleksandr Viktor Oleksandr Viktor Oleksandr Viktor Follow May 29 '25 Try UkrGuru.Sql with New Optimized `Results.Parse` # webdev # programming # sqlserver # dotnet Comments Add Comment 3 min read Insider Info About the New Results Class in Benchmark Oleksandr Viktor Oleksandr Viktor Oleksandr Viktor Follow Feb 23 '25 Insider Info About the New Results Class in Benchmark # csharp # sqlserver # beginners # coding Comments 1 comment 3 min read How Grok 3 and xUnit Tests Helped Craft an Ideal `Results` Class Oleksandr Viktor Oleksandr Viktor Oleksandr Viktor Follow Feb 20 '25 How Grok 3 and xUnit Tests Helped Craft an Ideal `Results` Class # webdev # programming # beginners # ai 1 reaction Comments 1 comment 3 min read UkrGuru.Sql: Additional Features Under the Hood Oleksandr Viktor Oleksandr Viktor Oleksandr Viktor Follow Feb 17 '25 UkrGuru.Sql: Additional Features Under the Hood # programming # sqlserver # csharp # beginners Comments Add Comment 4 min read UkrGuru.Sql: Minimal Effort, Maximum Results! 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https://topenddevs.com/podcasts/adventures-in-machine-learning/episodes/mlops-101-scoping-latency-data-curation-and-continuous-model-retraining-ml-143 | MLOps 101: Scoping, Latency, Data Curation, and Continuous Model Retraining - ML 143 - Adventures in Machine Learning - Top End Devs Top End Devs Home Podcasts Screencasts Courses Blogs Summits Meetups search-modal#open" aria-label="Search"> Sign In Sign Up search-modal#close"> Search search-modal#close"> search-modal#search" data-turbo-frame="search-results" data-turbo="true" class="space-y-4" action="/search" method="get"> Content Type All Episodes Podcasts Screencasts Lessons Courses Blog Authors Meetups Use semantic search (recommended) Search Trending Now What’s New in React 19.2: Compiler, Activity, and the Future of Async React - JSJ 670 JavaScript Jabber Can You Really Trust AI-Generated Code? - JSJ 699 JavaScript Jabber Autogenetic AI Agents and the Future of Ruby Development - RUBY 682 Ruby Rogues Popular Searches search-modal#fillSearch" data-search-term="podcast"> Podcast search-modal#fillSearch" data-search-term="episode"> Episode search-modal#fillSearch" data-search-term="author"> Author search-modal#fillSearch" data-search-term="meetup"> Meetup search-modal#fillSearch" data-search-term="series"> Series Back to Adventures in Machine Learning RSS Feed Spotify Apple Podcasts YouTube Amazon Music MLOps 101: Scoping, Latency, Data Curation, and Continuous Model Retraining - ML 143 Published: March 14, 2024 Download MLOps 101: Scoping, Latency, Data Curation, and Continuous Model Retraining - ML 143 0:00 audio-player#clickProgressBar touchstart->audio-player#clickProgressBar touchmove->audio-player#clickProgressBar" data-audio-player-target="progressBar"> 0:00 audio-player#skipBackward"> audio-player#togglePlayPause" data-audio-player-target="playPauseButton"> audio-player#skipForward"> audio-player#changeVolume" type="range" min="0" max="1" step="0.01" value="1" /> Playback Speed: audio-player#changePlaybackSpeed"> 0.5x 0.75x 1x 1.25x 1.5x 2x Created by: Ben Wilson • Michael Berk Show Notes Ben and Michael dive into the world of machine learning operations (MLOps) and discuss the complexities of building a computer vision pipeline to detect fishing boats at ports. They unpack the intricacies of MLOps basics and the challenges of implementing an effective computer vision model for traffic optimization and data collection at ports. From discussing the importance of exploratory data analysis (EDA) and data cleaning for image classification to the intricacies of continuous integration and deployment, this episode provides invaluable insights into the practical application of machine learning in real-world scenarios. Sponsors Chuck's Resume Template Developer Book Club Become a Top 1% Dev with a Top End Devs Membership © 2026 2022 Intentional Excellence Productions, LLC. All rights reserved. | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/o1-vs-sonnet | OpenAI o1 vs. Claude Sonnet 3.5: Which AI Model is Best for Coding? Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back OpenAI o1 vs. Claude Sonnet 3.5: Which AI Model is Best for Coding? Introduction As AI continues to evolve, two models stand out: o1 by OpenAI and Claude Sonnet 3.5 by Anthropic. Both offer impressive capabilities for software developers, but their strengths vary, especially when it comes to coding. This blog compares these two AI models, focusing on coding tasks and general performance. Fine includes unlimited access to both models, making it a great way to test and compare how o1 and Sonnet perform with coding tasks. Core Differences o1 is designed for complex reasoning and problem-solving . Its responses are deep and thoughtful, making it ideal for developers working on intricate problems or needing detailed explanations. On the other hand, Claude Sonnet 3.5 focuses on efficiency and speed , excelling in rapid response times while being more cost-effective. If you're looking to quickly generate code or handle high-volume tasks, Claude Sonnet 3.5 may be the better option. Both models use transformer-based architectures, but o1 is more suited for developers seeking detailed reasoning, while Claude Sonnet 3.5 is the go-to for those who prioritize speed. Context Window and Performance The context window plays a crucial role in how well these models handle large inputs or extended conversations. ChatGPT o1 supports 128,000 tokens, while Claude Sonnet 3.5 handles a larger 200,000 tokens , giving it an advantage for tasks that require significant context retention, such as reviewing long codebases. Both models offer strong performance in a range of tasks, but their abilities shine in different areas. ChatGPT o1 excels in multistep reasoning , explaining complex code logic in detail, while Claude Sonnet 3.5 focuses on rapid, efficient bug fixes and code generation . Claude 3.5 Sonnet Upgraded Version - October 2024 - Is Claude now better than GPT for Coding? In October 2024, Anthropic announced an upgraded version of Claude 3.5 Sonnet. The recent updates to Claude 3.5 Sonnet have significantly enhanced its software engineering capabilities. Notably, the model's performance on the SWE-bench Verified benchmark has improved from 33.4% to 49.0%, surpassing all publicly available models, including OpenAI's o1-preview. This advancement reflects Claude 3.5 Sonnet's enhanced accuracy in function generation and error checking, particularly in debugging and refactoring code involving nested functions or interdependent segments. Additionally, the model's expanded token capacity allows it to retain and utilize more extensive context, making it ideal for reviewing large codebases or managing intricate projects with multiple dependencies. Early testing indicates that Claude 3.5 Sonnet excels in specialized coding tasks, such as identifying security vulnerabilities in web applications and optimizing algorithms for speed and efficiency. GitLab, for instance, reported up to a 10% improvement in reasoning capabilities for DevSecOps tasks with the updated model, without any increase in latency. AI use cases for coding with o1 and Claude Sonnet 3.5 ChatGPT o1: Debugging complex React state management: Use o1 to deeply analyze why certain states aren’t updating properly or conflicting across components. Refactoring legacy code: Employ o1’s thorough reasoning to restructure an old Python script for readability and maintainability. Creating algorithms: Ideal for writing and explaining algorithms like sorting, tree traversal, or dynamic programming in detail. Claude Sonnet 3.5: Generating boilerplate code: Quickly create setup files for new projects like Flask APIs or front-end scaffolding in Next.js. Auto-completing functions: Use it to complete a half-written JavaScript function with appropriate error handling and edge cases. Bulk code generation: Sonnet 3.5 excels in producing repetitive yet slightly varied code structures like similar API endpoints or unit test cases. Which AI Models do the different AI coding tools use? There are lots of dev tools available today to help with your AI coding, from advanced AI coding assistants such as Fine to code generators such as GitHub Copilot. Some use multiple LLMs, some give you the choice and others are based on one model only. Which AI Model (LLM) does Fine use? Fine is one of the few AI coding tools to offer users the choice between different LLMs for various tasks. When using Fine via the web browser, users can choose between o1-preview, 4o and Claude 3.5 Sonnet. You'll need a pro subscription to take advantage of this however, which is $13-15 per month. If you're a free user, you'll be able to use Fine with 4o. Click here to try it out. Which AI Model (LLM) does GitHub Copilot use? GitHub Copilot is heavily integrated with OpenAI. GitHub is owned by Microsoft who have a deep partnership with OpenAI. Most users have access to 4o, whilst Azure AI subscribers may be able to use GitHub Copilot with o1-mini and o1-preview. UPDATE: At GitHub Universe 2024, it was announced that this exclusive partnership was no longer so exclusive and that the option to use Claude would be rolled out to all GitHub Copilot users shortly. Some users have already been able to access Claude. It's available in the Copilot Chat in Visual Studio Code and Immersive Copilot in the web browser only. Which AI Model (LLM) does Cursor use? Cursor uses Claude 3.5 Sonnet by default and falls back to OpenAI 4o during Anthropic outages. Which AI Model (LLM) does Bolt use? Bolt, the AI coding tool that specializes exclusively in front-end, relies on Claude 3.5 Sonnet. Which AI Model (LLM) does Replit use? Although Replit previously released their own AI model in 2023, when they announced Replit Agent, their primary AI coding too, in 2024, it seems they took the decision to use Claude 3.5 Sonnet. How to compare different AI Coding tools and LLMs? If you're looking to compare which are the best AI coding tools or LLMs, there are a few things to bare in mind. First, it's important to assess the LLM and the tool separately. Use a tool like Fine that allows you to give the same task to multiple LLMs to compare which gives you the best result. Here's a comparison we did of the three models offered by Fine, posed with the same question: What does this repo do? (It's a question that some are calling the Hello World of AI coding). Second, compare how the tools perform with your chosen LLM, specific to your use case. Fine offers a variety of integrations to boost your productivity, such as the ability to make revisions inside GitHub PR, that are saving developers hours every week. Which Model Is Better for Coding? For coding tasks, your choice depends on your needs: ChatGPT o1 is the better option when working on complex, multistep problems where you need deep reasoning and thorough explanations. For example, it excels in explaining intricate code or assisting with debugging in a more thoughtful manner. Claude Sonnet 3.5 is the go-to model for fast, efficient code generation and iterative prototyping. It's cost-effective for high-volume tasks like generating multiple code snippets or automating bug fixes. Both models support developers in coding, but Claude Sonnet 3.5 may save time and money for everyday coding tasks, while ChatGPT o1 might be your ally for tougher, detailed coding problems. Conclusion When deciding between ChatGPT o1 and Claude Sonnet 3.5 , consider the complexity of your coding tasks and budget constraints. ChatGPT o1 offers better problem-solving for intricate tasks, while Claude Sonnet 3.5 provides faster, more affordable code generation for day-to-day development needs. Both models are powerful AI tools that can significantly enhance your productivity as a software developer. Sign up to a platform like Fine , which includes unlimited access to both, for the best of both worlds without overpaying. Why Subscribe to Fine? Fine is a platform that offers unlimited access to both o1 and Claude Sonnet 3.5 , allowing developers to switch between these powerful LLMs based on their task needs. This flexibility is perfect for those who require detailed explanations from ChatGPT or fast, efficient code generation from Claude. With Fine, there's no need to manage your own API keys or worry about usage limits—everything is included. Subscribing to Fine simplifies the process, offering cost-effective, unlimited access to both models for all your coding and development tasks. Sources McNulty, Niall. "ChatGPT o1 vs Claude Sonnet 3.5." Medium , 5 days ago. Link . "GPT o1 vs Claude 3.5 Sonnet: Which model is better for Coding?" Bind AI Blog , 17 Sep 2024. Link . "Compare o1 Preview vs. Claude 3.5 Sonnet." Context.ai . Link . Harisec. "o1 vs Claude." GitHub . Link . Table of Contents Introduction Core Differences Context Window and Performance Claude 3.5 Sonnet Upgraded Version - October 2024 - Is Claude now better than GPT for Coding? AI Coding use cases with o1 and Claude 3.5 Sonnet Which AI Model do different AI Coding tools use? Fine GitHub Copilot Cursor Bolt Replit How to compare LLMs and tools for AI coding Which Model Is Better for Coding? Conclusion Why Subscribe to Fine Start building today Try out the smoothest way to build, launch and manage an app Try for Free -> © Fine.dev - All rights reserved. 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https://www.mrdbourke.com/about/ | About Daniel Bourke Home Now Machine Learning Posts Learn Machine Learning (courses I teach) ML Resources (things I recommend) About Newsletter Contact Book (Charlie Walks) YouTube Sign in Subscribe About I'm a writer who makes YouTube videos about the crossover of health, technology and art. My writing is like the voice in your head found a typewriter. My first novel is called Charlie Walks , the story of a computer programmer who wants to be a writer (meta, ha!). I teach machine learning and deep learning at the Zero to Mastery Academy (currently to over 230,000 students worldwide!). My mission is to use AI to help people move more and eat better. I'm currently working on: Nutrify – An app to help you learn about food by taking a photo of it (imagine a Pokédex for food or Shazam for food). KeepTrack – An app to help people keep track of their stuff for insurance purposes. learnhuggingface.com – A tutorial website teaching the Hugging Face ecosystem to help solve different machine learning problems. learnml.io – A website focused on machine learning concepts and tidbits, generally more technical posts than on this website. Custom ML – Helping companies build their own custom machine learning models, I specialize in on-device, low latency models (e.g. models that run on the edge and don't necessarily need an internet connection), if this is what you need, contact me . See more on my Now page. I'd like to own a large piece of land in the next few years to grow my own food. For now, I'm starting small in the backyard . My ikigai (Japanese word for "reason for being") is learning to create and creating to learn. I write a yearly article about what I've learned, see 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 . In 2019, I left the workforce and started working for myself. I've been a machine learning engineer at Max Kelsen , Uber Driver, Genius at Apple, fitness coach and men's physique competitor in that order. In 2017, I decided to start teaching myself to code, with a focus on machine learning and artificial intelligence via my self-created Artificial Intelligence Masters Degree . My writing is available on Medium , Quora and here. Every month or so, I send out a newsletter called Eat, Move, Learn, Make detailing my work. Why Eat, Move, Learn, Make? These are the things I like doing most. I've done a handful of podcasts and interviews with others . Making and movement are two non-negotiable daily rituals for me. @mrdbourke is my handle on Twitter /X. Brisbane has been my home town my whole life, I love it here. I live in a suburb called Brighton. I refer to it as Brisbane's Northern Beaches. My house is a 7-minute walk to the water. I try to get down there and walk every day. Daniel Bourke © 2026 Powered by Ghost | 2026-01-13T08:48:23 |
https://socket.io/docs/v4/adapter/ | Adapter | Socket.IO Skip to main content Latest blog post (July 25, 2024): npm package provenance . Socket.IO Docs Guide Tutorial Examples Emit cheatsheet Server API Client API Ecosystem Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Become a sponsor 4.x 4.x 3.x 2.x Changelog English English Español Français Português (Brasil) 中文（中国） Search Socket.IO Documentation Server Client Events Adapters Introduction Redis adapter Redis Streams adapter MongoDB adapter Postgres adapter Cluster adapter Google Cloud Pub/Sub adapter AWS SQS adapter Azure Service Bus adapter Advanced Migrations Miscellaneous Adapters Introduction Version: 4.x On this page Adapter An Adapter is a server-side component which is responsible for broadcasting events to all or a subset of clients. When scaling to multiple Socket.IO servers, you will need to replace the default in-memory adapter by another implementation, so the events are properly routed to all clients. Here is the list of adapters that are maintained by our team: the Redis adapter the Redis Streams adapter the MongoDB adapter the Postgres adapter the Cluster adapter the Google Cloud Pub/Sub adapter the AWS SQS adapter the Azure Service Bus adapter There are also several other options which are maintained by the (awesome!) community: AMQP (e.g. RabbitMQ) NATS NATS Please note that enabling sticky sessions is still needed when using multiple Socket.IO servers and HTTP long-polling. More information here . API You can have access to the adapter instance with: // main namespace const mainAdapter = io . of ( "/" ) . adapter ; // WARNING! io.adapter() will not work // custom namespace const adminAdapter = io . of ( "/admin" ) . adapter ; Starting with socket.io@3.1.0 , each Adapter instance emits the following events: create-room (argument: room) delete-room (argument: room) join-room (argument: room, id) leave-room (argument: room, id) Example: io . of ( "/" ) . adapter . on ( "create-room" , ( room ) => { console . log ( ` room ${ room } was created ` ) ; } ) ; io . of ( "/" ) . adapter . on ( "join-room" , ( room , id ) => { console . log ( ` socket ${ id } has joined room ${ room } ` ) ; } ) ; Emitter Most adapter implementations come with their associated emitter package, which allows communicating to the group of Socket.IO servers from another Node.js process. This may be useful for example in a microservice setup, where all clients connect to the microservice M1, while the microservice M2 uses the emitter to broadcast packets (uni-directional communication). Emitter cheatsheet // to all clients emitter . emit ( /* ... */ ) ; // to all clients in "room1" emitter . to ( "room1" ) . emit ( /* ... */ ) ; // to all clients in "room1" except those in "room2" emitter . to ( "room1" ) . except ( "room2" ) . emit ( /* ... */ ) ; const adminEmitter = emitter . of ( "/admin" ) ; // to all clients in the "admin" namespace adminEmitter . emit ( /* ... */ ) ; // to all clients in the "admin" namespace and in the "room1" room adminEmitter . to ( "room1" ) . emit ( /* ... */ ) ; The emitter also supports the utility methods that were added in socket.io@4.0.0 : socketsJoin() // make all Socket instances join the "room1" room emitter . socketsJoin ( "room1" ) ; // make all Socket instances of the "admin" namespace in the "room1" room join the "room2" room emitter . of ( "/admin" ) . in ( "room1" ) . socketsJoin ( "room2" ) ; socketsLeave() // make all Socket instances leave the "room1" room emitter . socketsLeave ( "room1" ) ; // make all Socket instances in the "room1" room leave the "room2" and "room3" rooms emitter . in ( "room1" ) . socketsLeave ( [ "room2" , "room3" ] ) ; // make all Socket instances in the "room1" room of the "admin" namespace leave the "room2" room emitter . of ( "/admin" ) . in ( "room1" ) . socketsLeave ( "room2" ) ; disconnectSockets() // make all Socket instances disconnect emitter . disconnectSockets ( ) ; // make all Socket instances in the "room1" room disconnect (and discard the low-level connection) emitter . in ( "room1" ) . disconnectSockets ( true ) ; // make all Socket instances in the "room1" room of the "admin" namespace disconnect emitter . of ( "/admin" ) . in ( "room1" ) . disconnectSockets ( ) ; // this also works with a single socket ID emitter . of ( "/admin" ) . in ( theSocketId ) . disconnectSockets ( ) ; serverSideEmit() // emit an event to all the Socket.IO servers of the cluster emitter . serverSideEmit ( "hello" , "world" ) ; // Socket.IO server (server-side) io . on ( "hello" , ( arg ) => { console . log ( arg ) ; // prints "world" } ) ; Edit this page Last updated on Nov 15, 2025 Previous Rooms Next Redis adapter API Emitter Emitter cheatsheet Documentation Guide Tutorial Examples Server API Client API Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Become a sponsor Copyright © 2026 Socket.IO | 2026-01-13T08:48:23 |
https://socket.io/docs/v4/broadcasting-events/#with-multiple-socketio-servers | Broadcasting events | Socket.IO Skip to main content Latest blog post (July 25, 2024): npm package provenance . Socket.IO Docs Guide Tutorial Examples Emit cheatsheet Server API Client API Ecosystem Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Become a sponsor 4.x 4.x 3.x 2.x Changelog English English Español Français Português (Brasil) 中文（中国） Search Socket.IO Documentation Server Client Events Emitting events Listening to events Broadcasting events Rooms Adapters Advanced Migrations Miscellaneous Events Broadcasting events Version: 4.x On this page Broadcasting events Socket.IO makes it easy to send events to all the connected clients. info Please note that broadcasting is a server-only feature. To all connected clients io . emit ( "hello" , "world" ) ; caution Clients that are currently disconnected (or in the process of reconnecting) won't receive the event. Storing this event somewhere (in a database, for example) is up to you, depending on your use case. To all connected clients except the sender io . on ( "connection" , ( socket ) => { socket . broadcast . emit ( "hello" , "world" ) ; } ) ; note In the example above, using socket.emit("hello", "world") (without broadcast flag) would send the event to "client A". You can find the list of all the ways to send an event in the cheatsheet . With acknowledgements Starting with Socket.IO 4.5.0, you can now broadcast an event to multiple clients and expect an acknowledgement from each one of them: io . timeout ( 5000 ) . emit ( "hello" , "world" , ( err , responses ) => { if ( err ) { // some clients did not acknowledge the event in the given delay } else { console . log ( responses ) ; // one response per client } } ) ; All broadcasting forms are supported: in a room io . to ( "room123" ) . timeout ( 5000 ) . emit ( "hello" , "world" , ( err , responses ) => { // ... } ) ; from a specific socket socket . broadcast . timeout ( 5000 ) . emit ( "hello" , "world" , ( err , responses ) => { // ... } ) ; in a namespace io . of ( "/the-namespace" ) . timeout ( 5000 ) . emit ( "hello" , "world" , ( err , responses ) => { // ... } ) ; With multiple Socket.IO servers Broadcasting also works with multiple Socket.IO servers. You just need to replace the default adapter by the Redis Adapter or another compatible adapter . In certain cases, you may want to only broadcast to clients that are connected to the current server. You can achieve this with the local flag: io . local . emit ( "hello" , "world" ) ; In order to target specific clients when broadcasting, please see the documentation about Rooms . Edit this page Last updated on Nov 15, 2025 Previous Listening to events Next Rooms To all connected clients To all connected clients except the sender With acknowledgements With multiple Socket.IO servers Documentation Guide Tutorial Examples Server API Client API Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Become a sponsor Copyright © 2026 Socket.IO | 2026-01-13T08:48:23 |
https://docs.suprsend.com/docs/flutter-androidpush-integration#android-push-setup-fcm | Android Push Setup (FCM) - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection Developer Resources Overview Updates and Versioning Versioning and Support Policy SDK Changelog Authentication API Keys and Secrets Service Token Best Practices for Key & Token Management MCP Overview BETA Quickstart Tool List Building with LLMs Security Security SDKs and APIs SDKs SDK Overview SuprSend Backend SDK SuprSend Client SDK Authentication Javascript Android iOS React Native Flutter Android Integration iOS Integration Manage Users Sync Events iOS Push Setup Android Push Setup (FCM) React Management API REST API Postman Collection Features Validate Trigger Payload Type Safety Testing Testing the Template Test Mode Monitoring and Logging Logs Data Out Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation Flutter Android Push Setup (FCM) Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog Flutter Android Push Setup (FCM) OpenAI Open in ChatGPT Step-by-step guide to setup FCM Push notifications in flutter android app. OpenAI Open in ChatGPT Example integration project can be found here . Integration Steps 1 Create a Firebase project in the firebase console To start sending notifications from FCM, you’ll have to first create a firebase project. Create a firebase project and application in firebase console with your applications package name which you can find in AndroidManifest.xml 2 Adding google-services.json to your project You can get your Service Account JSON from Firebase Console Project Settings. Download google-services.json and add the file inside your android > app folder. 3 Adding Firebase dependencies and plugins 3.1. Add the below dependency inside projects build.gradle inside dependencies Groovy (build.gradle) Kotlin DSL (build.gradle.kts) Copy Ask AI dependencies { .. . classpath 'com.google.gms:google-services:4.3.10' // or latest version } 3.2. Add the below plugin inside the app build.gradle Groovy (build.gradle) Kotlin DSL (build.gradle.kts) Copy Ask AI apply plugin : 'com.google.gms.google-services' 3.3 Add the below dependency inside apps build.gradle inside dependencies Groovy (build.gradle) Kotlin DSL (build.gradle.kts) Copy Ask AI implementation( "com.google.firebase:firebase-messaging:22.0.0" ) // or latest version 4 Implementing push Push feature can be implemented in two ways: Token Generation and Notification handled By SDK [Recommended] You may use this option if all of your android push notifications are to be handled via SuprSend SDK. We recommend you use this method as it is just a single-step process to just register the service in your application manifest and everything else will be ready. AndroidManifest.xml Copy Ask AI <!--If you are targeting to API 33 (Android 13) you will additional need to add POST_NOTIFICATIONS --> < uses-permission android:name = "android.permission.POST_NOTIFICATIONS" /> < service android:name = "app.suprsend.fcm.SSFirebaseMessagingService" android:enabled = "true" android:exported = "false" > < intent-filter > < action android:name = "com.google.firebase.MESSAGING_EVENT" /> </ intent-filter > </ service > Token Generation and Notification handled By Your Application Once you get a token from Firebase you can pass the token by using the below code main.dart Copy Ask AI suprsend . setAndroidFcmPush ( fcm_token ); When you get a push notification you will get a payload and it can be passed to the method provided by Suprsend Flutter SDK and the notification displaying part will be handled by SDK. main.dart Copy Ask AI suprsend . showNotification ( notification_payload ); How to identify if notification is sent by SuprSend? If notification payload contains key supr_send_n_pl then simply consider this as payload sent from suprsend and pass the payload to suprsend sdk. Targeting Android 13 (API-33) In Android13 (API 33) or higher notification permission will be disabled by default so permission needs to be asked to enable notifications if you are targeting android 13 users. You can follow this doc to update to support Andriod 13(API 33), if not already supported. Please test the application as well as upgrading to API 33 may causes breaking changes. 1 Add POST_NOTIFICATIONS permission in AndroidManifest.xml if not present already. AndroidManifest.xml Copy Ask AI < manifest ... > < uses-permission android:name = "android.permission.POST_NOTIFICATIONS" /> < application ... > ... </ application > </ manifest > 2 Ask notification permission to show push notifications You can use permission_handler or any other package to ask notification permission to user. From v2.4.0, we have removed internal method to ask notification permission ( suprsend.askNotificationPermission ). You can use external package to ask notification permission. Once notification permission is granted, users can be able to see push notifications. Was this page helpful? Yes No Suggest edits Raise issue Previous SDK Integration SDK Integration to enable SuprSend features like Inbox, Preferences, and Webpush into React-based web applications. Next ⌘ I x github linkedin youtube Powered by On this page Integration Steps Targeting Android 13 (API-33) | 2026-01-13T08:48:23 |
https://dev.to/favour_okhioya_9b7d7bd62f#main-content | Favour Okhioya - 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 Favour Okhioya I just that person with ideas Location Lagos Nigeria Joined Joined on Jun 16, 2025 Email address favourokhioya2006@gmail.com More info about @favour_okhioya_9b7d7bd62f Badges 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 Currently learning How to create an app that have people instrest at heart Available for Web developer and app builder that could turn my idea into reality Post 2 posts published Comment 1 comment written Tag 1 tag followed How to turn my idea to reality Favour Okhioya Favour Okhioya Favour Okhioya Follow Jun 16 '25 How to turn my idea to reality # webdev # ai Comments 1 comment 1 min read Want to connect with Favour Okhioya? Create an account to connect with Favour Okhioya. You can also sign in below to proceed if you already have an account. Create Account Already have an account? Sign in Hi new here actually I am currently working on an app want to get an insight kindly DM Favour Okhioya Favour Okhioya Favour Okhioya Follow Jun 16 '25 Hi new here actually I am currently working on an app want to get an insight kindly DM # webdev # programming 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. 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 | 2026-01-13T08:48:23 |
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https://socket.io/docs/v4/troubleshooting-connection-issues/ | Troubleshooting connection issues | Socket.IO Skip to main content Latest blog post (July 25, 2024): npm package provenance . Socket.IO Docs Guide Tutorial Examples Emit cheatsheet Server API Client API Ecosystem Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Become a sponsor 4.x 4.x 3.x 2.x Changelog English English Español Français Português (Brasil) 中文（中国） Search Socket.IO Documentation Introduction How it works Delivery guarantees Connection state recovery Logging and debugging Testing Troubleshooting TypeScript Memory usage Server Client Events Adapters Advanced Migrations Miscellaneous Documentation Troubleshooting Version: 4.x On this page Troubleshooting connection issues tip The Admin UI can give you additional insights about the status of your Socket.IO deployment. Common/known issues: the socket is not able to connect the socket gets disconnected the socket is stuck in HTTP long-polling Other common gotchas: Duplicate event registration Delayed event handler registration Usage of the socket.id attribute Deployment on a serverless platform Problem: the socket is not able to connect Troubleshooting steps On the client side, the connect_error event provides additional information: socket . on ( "connect_error" , ( err ) => { // the reason of the error, for example "xhr poll error" console . log ( err . message ) ; // some additional description, for example the status code of the initial HTTP response console . log ( err . description ) ; // some additional context, for example the XMLHttpRequest object console . log ( err . context ) ; } ) ; On the server side, the connection_error event may also provide some additional insights: io . engine . on ( "connection_error" , ( err ) => { console . log ( err . req ) ; // the request object console . log ( err . code ) ; // the error code, for example 1 console . log ( err . message ) ; // the error message, for example "Session ID unknown" console . log ( err . context ) ; // some additional error context } ) ; Here is the list of possible error codes: Code Message Possible explanations 0 "Transport unknown" This should not happen under normal circumstances. 1 "Session ID unknown" Usually, this means that sticky sessions are not enabled (see below ). 2 "Bad handshake method" This should not happen under normal circumstances. 3 "Bad request" Usually, this means that a proxy in front of your server is not properly forwarding the WebSocket headers (see here ). 4 "Forbidden" The connection was denied by the allowRequest() method. 5 "Unsupported protocol version" The version of the client is not compatible with the server (see here ). Possible explanations You are trying to reach a plain WebSocket server As explained in the "What Socket.IO is not" section, the Socket.IO client is not a WebSocket implementation and thus will not be able to establish a connection with a WebSocket server, even with transports: ["websocket"] : const socket = io ( "ws://echo.websocket.org" , { transports : [ "websocket" ] } ) ; The server is not reachable Please make sure the Socket.IO server is actually reachable at the given URL. You can test it with: curl "<the server URL>/socket.io/?EIO=4&transport=polling" which should return something like this: 0{"sid":"Lbo5JLzTotvW3g2LAAAA","upgrades":["websocket"],"pingInterval":25000,"pingTimeout":20000,"maxPayload":1000000} If that's not the case, please check that the Socket.IO server is running, and that there is nothing in between that prevents the connection. note v1/v2 servers (which implement the v3 of the protocol, hence the EIO=3 ) will return something like this: 96:0{"sid":"ptzi_578ycUci8WLB9G1","upgrades":["websocket"],"pingInterval":25000,"pingTimeout":5000}2:40 The client is not compatible with the version of the server Maintaining backward compatibility is a top priority for us, but in some particular cases we had to implement some breaking changes at the protocol level: from v1.x to v2.0.0 (released in May 2017), to improve the compatibility with non-Javascript clients (see here ) from v2.x to v3.0.0 (released in November 2020), to fix some long-standing issues in the protocol once for all (see here ) info v4.0.0 contains some breaking changes in the API of the JavaScript server. The Socket.IO protocol itself was not updated, so a v3 client will be able to reach a v4 server and vice-versa (see here ). For example, reaching a v3/v4 server with a v1/v2 client will result in the following response: < HTTP/1.1 400 Bad Request < Content-Type: application/json {"code":5,"message":"Unsupported protocol version"} Here is the compatibility table for the JS client : JS Client version Socket.IO server version 1.x 2.x 3.x 4.x 1.x YES NO NO NO 2.x NO YES YES 1 YES 1 3.x NO NO YES YES 4.x NO NO YES YES [1] Yes, with allowEIO3: true Here is the compatibility table for the Java client : Java Client version Socket.IO server version 2.x 3.x 4.x 1.x YES YES 1 YES 1 2.x NO YES YES [1] Yes, with allowEIO3: true Here is the compatibility table for the Swift client : Swift Client version Socket.IO server version 2.x 3.x 4.x v15.x YES YES 1 YES 2 v16.x YES 3 YES YES [1] Yes, with allowEIO3: true (server) and .connectParams(["EIO": "3"]) (client): SocketManager(socketURL: URL(string:"http://localhost:8087/")!, config: [.connectParams(["EIO": "3"])]) [2] Yes, allowEIO3: true (server) [3] Yes, with .version(.two) (client): SocketManager(socketURL: URL(string:"http://localhost:8087/")!, config: [.version(.two)]) The server does not send the necessary CORS headers If you see the following error in your console: Cross-Origin Request Blocked: The Same Origin Policy disallows reading the remote resource at ... It probably means that: either you are not actually reaching the Socket.IO server (see above ) or you didn't enable Cross-Origin Resource Sharing (CORS) on the server-side. Please see the documentation here . You didn't enable sticky sessions (in a multi server setup) When scaling to multiple Socket.IO servers, you need to make sure that all the requests of a given Socket.IO session reach the same Socket.IO server. The explanation can be found here . Failure to do so will result in HTTP 400 responses with the code: {"code":1,"message":"Session ID unknown"} Please see the documentation here . The request path does not match on both sides By default, the client sends — and the server expects — HTTP requests with the "/socket.io/" request path. This can be controlled with the path option: Server import { Server } from "socket.io" ; const io = new Server ( { path : "/my-custom-path/" } ) ; io . listen ( 3000 ) ; Client import { io } from "socket.io-client" ; const socket = io ( SERVER_URL , { path : "/my-custom-path/" } ) ; In that case, the HTTP requests will look like <SERVER_URL>/my-custom-path/?EIO=4&transport=polling[&...] . caution import { io } from "socket.io-client" ; const socket = io ( "/my-custom-path/" ) ; means the client will try to reach the namespace named "/my-custom-path/", but the request path will still be "/socket.io/". Problem: the socket gets disconnected Troubleshooting steps First and foremost, please note that disconnections are common and expected, even on a stable Internet connection: anything between the user and the Socket.IO server may encounter a temporary failure or be restarted the server itself may be killed as part of an autoscaling policy the user may lose connection or switch from WiFi to 4G, in case of a mobile browser the browser itself may freeze an inactive tab That being said, the Socket.IO client will always try to reconnect, unless specifically told otherwise . The disconnect event provides additional information: socket . on ( "disconnect" , ( reason , details ) => { // the reason of the disconnection, for example "transport error" console . log ( reason ) ; // the low-level reason of the disconnection, for example "xhr post error" console . log ( details . message ) ; // some additional description, for example the status code of the HTTP response console . log ( details . description ) ; // some additional context, for example the XMLHttpRequest object console . log ( details . context ) ; } ) ; The possible reasons are listed here . Possible explanations Something between the server and the client closes the connection If the disconnection happens at a regular interval, this might indicate that something between the server and the client is not properly configured and closes the connection: nginx The value of nginx's proxy_read_timeout (60 seconds by default) must be bigger than Socket.IO's pingInterval + pingTimeout (45 seconds by default), else it will forcefully close the connection if no data is sent after the given delay and the client will get a "transport close" error. Apache HTTP Server The value of httpd's ProxyTimeout (60 seconds by default) must be bigger than Socket.IO's pingInterval + pingTimeout (45 seconds by default), else it will forcefully close the connection if no data is sent after the given delay and the client will get a "transport close" error. The browser tab was minimized and heartbeat has failed When a browser tab is not in focus, some browsers (like Chrome ) throttle JavaScript timers, which could lead to a disconnection by ping timeout in Socket.IO v2 , as the heartbeat mechanism relied on setTimeout function on the client side. As a workaround, you can increase the pingTimeout value on the server side: const io = new Server ( { pingTimeout : 60000 } ) ; Please note that upgrading to Socket.IO v4 (at least socket.io-client@4.1.3 , due to this ) should prevent this kind of issues, as the heartbeat mechanism has been reversed (the server now sends PING packets). The client is not compatible with the version of the server Since the format of the packets sent over the WebSocket transport is similar in v2 and v3/v4, you might be able to connect with an incompatible client (see above ), but the connection will eventually be closed after a given delay. So if you are experiencing a regular disconnection after 30 seconds (which was the sum of the values of pingTimeout and pingInterval in Socket.IO v2), this is certainly due to a version incompatibility. You are trying to send a huge payload If you get disconnected while sending a huge payload, this may mean that you have reached the maxHttpBufferSize value, which defaults to 1 MB. Please adjust it according to your needs: const io = require ( "socket.io" ) ( httpServer , { maxHttpBufferSize : 1e8 } ) ; A huge payload taking more time to upload than the value of the pingTimeout option can also trigger a disconnection (since the heartbeat mechanism fails during the upload). Please adjust it according to your needs: const io = require ( "socket.io" ) ( httpServer , { pingTimeout : 60000 } ) ; Problem: the socket is stuck in HTTP long-polling Troubleshooting steps In most cases, you should see something like this: the Engine.IO handshake (contains the session ID — here, zBjrh...AAAK — that is used in subsequent requests) the Socket.IO handshake request (contains the value of the auth option) the Socket.IO handshake response (contains the Socket#id ) the WebSocket connection the first HTTP long-polling request, which is closed once the WebSocket connection is established If you don't see a HTTP 101 Switching Protocols response for the 4th request, that means that something between the server and your browser is preventing the WebSocket connection. Please note that this is not necessarily blocking since the connection is still established with HTTP long-polling, but it is less efficient. You can get the name of the current transport with: Client-side socket . on ( "connect" , ( ) => { const transport = socket . io . engine . transport . name ; // in most cases, "polling" socket . io . engine . on ( "upgrade" , ( ) => { const upgradedTransport = socket . io . engine . transport . name ; // in most cases, "websocket" } ) ; } ) ; Server-side io . on ( "connection" , ( socket ) => { const transport = socket . conn . transport . name ; // in most cases, "polling" socket . conn . on ( "upgrade" , ( ) => { const upgradedTransport = socket . conn . transport . name ; // in most cases, "websocket" } ) ; } ) ; Possible explanations A proxy in front of your servers does not accept the WebSocket connection If a proxy like nginx or Apache HTTPD is not properly configured to accept WebSocket connections, then you might get a TRANSPORT_MISMATCH error: io . engine . on ( "connection_error" , ( err ) => { console . log ( err . code ) ; // 3 console . log ( err . message ) ; // "Bad request" console . log ( err . context ) ; // { name: 'TRANSPORT_MISMATCH', transport: 'websocket', previousTransport: 'polling' } } ) ; Which means that the Socket.IO server does not receive the necessary Connection: upgrade header (you can check the err.req.headers object). Please see the documentation here . express-status-monitor runs its own socket.io instance Please see the solution here . Other common gotchas Duplicate event registration On the client side, the connect event will be emitted every time the socket reconnects, so the event listeners must be registered outside the connect event listener: BAD ⚠️ socket . on ( "connect" , ( ) => { socket . on ( "foo" , ( ) => { // ... } ) ; } ) ; GOOD 👍 socket . on ( "connect" , ( ) => { // ... } ) ; socket . on ( "foo" , ( ) => { // ... } ) ; If that's not the case, your event listener might be called multiple times. Delayed event handler registration BAD ⚠️ io . on ( "connection" , async ( socket ) => { await longRunningOperation ( ) ; // WARNING! Some packets might be received by the server but without handler socket . on ( "hello" , ( ) => { // ... } ) ; } ) ; GOOD 👍 io . on ( "connection" , async ( socket ) => { socket . on ( "hello" , ( ) => { // ... } ) ; await longRunningOperation ( ) ; } ) ; Usage of the socket.id attribute Please note that, unless connection state recovery is enabled, the id attribute is an ephemeral ID that is not meant to be used in your application (or only for debugging purposes) because: this ID is regenerated after each reconnection (for example when the WebSocket connection is severed, or when the user refreshes the page) two different browser tabs will have two different IDs there is no message queue stored for a given ID on the server (i.e. if the client is disconnected, the messages sent from the server to this ID are lost) Please use a regular session ID instead (either sent in a cookie, or stored in the localStorage and sent in the auth payload). See also: Part II of our private message guide How to deal with cookies Deployment on a serverless platform Since most serverless platforms (such as Vercel) bill by the duration of the request handler, maintaining a long-running connection with Socket.IO (or even plain WebSocket) is not recommended. References: https://vercel.com/guides/do-vercel-serverless-functions-support-websocket-connections https://docs.aws.amazon.com/apigateway/latest/developerguide/apigateway-websocket-api.html Edit this page Last updated on Nov 15, 2025 Previous Testing Next TypeScript Problem: the socket is not able to connect Troubleshooting steps Possible explanations You are trying to reach a plain WebSocket server The server is not reachable The client is not compatible with the version of the server The server does not send the necessary CORS headers You didn't enable sticky sessions (in a multi server setup) The request path does not match on both sides Problem: the socket gets disconnected Troubleshooting steps Possible explanations Something between the server and the client closes the connection The browser tab was minimized and heartbeat has failed The client is not compatible with the version of the server You are trying to send a huge payload Problem: the socket is stuck in HTTP long-polling Troubleshooting steps Possible explanations A proxy in front of your servers does not accept the WebSocket connection express-status-monitor runs its own socket.io instance Other common gotchas Duplicate event registration Delayed event handler registration Usage of the socket.id attribute Deployment on a serverless platform Documentation Guide Tutorial Examples Server API Client API Help Troubleshooting Stack Overflow GitHub Discussions Slack News Blog Twitter Tools CDN Admin UI About FAQ Changelog Roadmap Become a sponsor Copyright © 2026 Socket.IO | 2026-01-13T08:48:23 |
https://dev.to/challenges/assemblyai-2025-07-16#main-content | AssemblyAI Voice Agents Challenge - DEV 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 Challenges > AssemblyAI Voice Agents Challenge CHALLENGE RESULTS 🏆 Winners Announced! 🎊 Congrats to the AssemblyAI Voice Agents Challenge Winners! Read Announcement Challenge ends soon! Submit your entry now DAYS : HOURS : MINUTES : SECONDS See prompts AssemblyAI Voice Agents Challenge View Entries Please sign in to follow this challenge Innovate with ultra fast, ultra accurate streaming speech-to-text. Challenge Status: Ended Ended Join our next Challenge We are so excited to bring the community our next challenge with AssemblyAI . Running through July 27 , the AssemblyAI Voice Agents is all about building with Universal-Streaming, AssemblyAI's most advanced real-time transcription API. Universal-Streaming is ultra fast (300ms latency!), ultra accurate, and offers intelligent endpointing to keep conversations flowing naturally. Prizes There are three distinct prompts for this challenge, with three opportunities to win. Each winner will receive: $1,000 USD 6-month DEV++ Membership Exclusive DEV Badge AssemblyAI Credits Sign up for AssemblyAI to get your free API key. There is no credit card required and AssemblyAI provides $50 worth of credits for new users, which should be sufficient for most challenge projects. Need Help? Join the AssemblyAI Slack Community for support from the Applied AI team! Challenge participants can ask API questions and connect with other developers. Get familiar with AssemblyAI's capabilities: Developer Docs Streaming Guides Slack Community We can't wait to see what you build with this transformative technology! Check out the three prompts below. Key Dates Contest start: July 16, 2025 Submissions due: July 27, 2025 Winners announced: August 07, 2025 Badge Rewards AssemblyAI Challenge Winner Badge AssemblyAI Challenge Completion Badge Find Out More Ask questions and share your ideas on the AssemblyAI Voice Agents Challenge Launch Post. View Launch Post Sponsored by AssemblyAI AssemblyAI provides the market's most comprehensive Speech AI toolkit through a single, powerful API. Our industry-leading models, including the groundbreaking Universal-Streaming, deliver superhuman speech-to-text accuracy with real-time capabilities. Advanced features like speaker detection, PII redaction, sentiment analysis, and content summarization transform audio into actionable insights for developers building the future of voice-enabled applications. Learn more → Challenge Prompts Business Automation Voice Agent Build a voice agent that automates real business processes - sales calls, customer support, appointment scheduling, lead qualification, etc. Showcase Universal-Streaming's accuracy in professional contexts with proper nouns, business terminology, and multi-step workflows. Focus on practical B2B/B2C applications that could actually be deployed. Submission Template Judging Criteria: Use of Underlying technology Usability and User Experience Accessibility Creativity Real-Time Voice Performance Create the fastest, most responsive voice experience possible using Universal-Streaming. Build an application where sub-300ms latency matters - voice-controlled interfaces, gaming, live translation, instant commands. Demonstrate technical optimization, performance benchmarking, and creative speed-dependent use cases. Submission Template Judging Criteria: Use of Underlying technology Usability and User Experience Accessibility Creativity Domain Expert Voice Agent Build a specialized voice agent with deep domain knowledge that can learn and improve from conversations . Focus on expertise in specific fields (legal, medical, technical support, education, etc.) and incorporate RAG (Retrieval-Augmented Generation) or conversation learning capabilities. Demonstrate how Universal-Streaming enables accurate domain-specific terminology recognition. Submission Template Judging Criteria: Use of Underlying technology Usability and User Experience Accessibility Creativity Frequently Asked Questions Participation Can I submit to multiple prompts? Yes, you are welcome to submit to multiple prompts. Can one submission qualify for multiple prompts? Yes, if your submission offers a solution to multiple prompts, it can qualify for multiple prompts. Can I submit to a prompt more than once? Yes, you can submit multiple submissions per prompt but you’ll need to publish a separate post for each submission. In the event that you may win two or more prompts, and your submission is very close with another participant, we will favor the other participant. In the event that you do win two or more prompts, you will only receive one winner badge. Can I work on a team? Yes, you can work on teams of up to four people. If you collaborate with anyone, you’ll need to list their DEV handles in your submission post so we can award a badge to your entire team! Please only publish one submission per team. DEV does not handle prize-splitting, so in the event that your submission wins the shop gift, you will need to split that amongst yourselves. Thank you for understanding! How old do I have to be to participate? Participants need to be 18+ in order to participate. If I live in X, am I eligible to participate? For eligibility rules, see our official challenge rules . Submission Can my submission include open source code? Riffing on open source code and borrowing and improving on previous work/ideas is encouraged but it’s important your changes are significant enough to ensure your submission is valid. When does riffing become plagiarism? It will depend, but transparency is important, license compatibility is important. You can use someone else’s code to give you a jumpstart to demonstrate your ideas on top of someone else’s base, but not just re-package the base. It should be clear to the judges what you added to the project in terms of the code and conceptual inspiration. This means, you should clearly state what you were building on and what elements are original to this new submission. When building on existing code, we expect a significant change that adds something tangible to the output. i.e. a new animation, and new sprite, a new function, a new presentation. Not just changes to the source - i.e. changing colours, changing one sprite, changing one function. What happens if my submission is considered plagiarized or invalid? Anything deemed to be plagiarism will not be eligible for prizes. Incidental plagiarism may simply result in your disqualification from the challenge (regardless of the number of other valid submissions you have published). Egregious plagiarism will result in your suspension from DEV entirely. Any non-generic, non-trivial usage of prior work, including open source code must be credited in your submission. Do submissions have to be in English? Non-english submissions are eligible for a completion badge but not eligible for prizes due to the current limitations of our judges. We will not be judging on mastery of the English language, so please don’t let this deter you from submitting if you are not a native English speaker! We hope to evolve this in the future to be more accommodating. Do I need a license for my code? You are not required to license your code but we strongly recommend that you do. Here are some you may consider: MIT , Apache , BSD-2 , BSD-3 , or Commons Clause . Can I use AI? Use of AI is allowed as long as all other rules are followed. We want to give you a chance to show off your skills in realistic scenarios. If you use AI tools to help you achieve your submission, all the power to you. How do I embed my project directly into my DEV post? Our editor supports many types of embeds, including: Stackbliz, Glitch, Github, etc. You can typically use the {% embed https://... %} syntax directly in the post. Click here for more information on our markdown support. For CodePen, you will need to use this syntax: {% codepen http://... %} For CodeSandbox, you will need to use this syntax: {% codesandbox http://... %} Judging and Prizing Can there be ties? In the event of a tie in scoring between judges, the judges will select the entry that received the highest number of positive reactions on their DEV post to determine the winner. How will I know if I won? Winners will be announced in a DEV post on the winner announcement date noted in our key dates section. When will I receive my DEV badge? Both participation and winner badges will be awarded, in most cases, the same day as the winner announcement. When will I receive my prizes? The DEV Team will contact you via the email associated with your DEV profile within, at most, 10 business days of the announcement date to share the details of claiming your prizes. What steps do I need to take to receive my cash prize? The winner (including each member of a team) may be required to sign and return an affidavit of eligibility and publicity/liability release, and provide any additional tax filing information (such as a W-9, social security number or Federal tax ID number) within seven (7) business days following the date of your first email notification. AssemblyAI Voice Agents Challenge Rules NO PURCHASE NECESSARY. Open only to 18+. Contest entry period ends July 27, 2025 at 11:59 PM PDT. Contest is void where prohibited or restricted by law or regulation. All entires must be submitted during the content period. For Official Rules, see AssemblyAI Challenge Contest Rules and General Contest Official Rules . Dismiss 💎 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 | 2026-01-13T08:48:23 |
https://dev.to/t/webdev/page/72 | Web Development Page 72 - 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 Web Development Follow Hide Because the internet... Create Post submission guidelines Be nice. Be respectful. Assume best intentions. Be kind, rewind. Older #webdev posts 69 70 71 72 73 74 75 76 77 Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu AI app builders shouldn’t stop at the UI ideatr ideatr ideatr Follow Dec 20 '25 AI app builders shouldn’t stop at the UI # vibecoding # programming # webdev # ai Comments Add Comment 2 min read Hoppscotch: The Modern, Lightweight Alternative to Postman and Bruno Chandrashekhar Kachawa Chandrashekhar Kachawa Chandrashekhar Kachawa Follow Dec 18 '25 Hoppscotch: The Modern, Lightweight Alternative to Postman and Bruno # api # webdev # programming # beginners Comments Add Comment 4 min read Reusable Angular Components Library in a Monorepo (Without Nx Overkill) kafeel ahmad kafeel ahmad kafeel ahmad Follow Dec 31 '25 Reusable Angular Components Library in a Monorepo (Without Nx Overkill) # webdev # programming # angular # beginners Comments Add Comment 8 min read 80% of the IT Budget Goes to Maintenance, Not Growth: How to Break Out of This Trap OneEntry OneEntry OneEntry Follow Dec 19 '25 80% of the IT Budget Goes to Maintenance, Not Growth: How to Break Out of This Trap # webdev # frontend # javascript # nextjs Comments Add Comment 6 min read Using `useRef` to Set Focus on an Input Field Bishoy Semsem Bishoy Semsem Bishoy Semsem Follow Dec 18 '25 Using `useRef` to Set Focus on an Input Field # react # webdev Comments Add Comment 5 min read Test run Delight Iwenofu Delight Iwenofu Delight Iwenofu Follow Dec 19 '25 Test run # codepen # webdev # programming # javascript 1 reaction Comments Add Comment 1 min read Amazon Athena in the AWS Periodic Table Jai Surya Jai Surya Jai Surya Follow Dec 18 '25 Amazon Athena in the AWS Periodic Table # aws # cloud # security # webdev Comments Add Comment 2 min read 5 Tools That Make Daily Standups Actually Async Matt Lewandowski Matt Lewandowski Matt Lewandowski Follow Jan 10 5 Tools That Make Daily Standups Actually Async # agile # scrum # productivity # webdev 19 reactions Comments 1 comment 4 min read Tired of 50+ Tabs Open Just for Simple Dev Tasks? I Built a 200+ Free Tools Hub to Fix It xyz abc xyz abc xyz abc Follow Dec 19 '25 Tired of 50+ Tabs Open Just for Simple Dev Tasks? I Built a 200+ Free Tools Hub to Fix It # webdev # productivity # resources # opensource 1 reaction Comments Add Comment 1 min read Understanding Download and Upload: A Technical Breakdown for Developers Iz Mroen Iz Mroen Iz Mroen Follow Dec 19 '25 Understanding Download and Upload: A Technical Breakdown for Developers # networking # tutorial # webdev # cloud 23 reactions Comments Add Comment 2 min read Virtual DOM vs Reactive DOM Javad Javad Javad Follow Jan 1 Virtual DOM vs Reactive DOM # webdev # programming # javascript # opensource 5 reactions Comments 1 comment 3 min read Amazon EC2 in Cloud Computing: Features, Use Cases, and Pricing ABITHA N 24CB001 ABITHA N 24CB001 ABITHA N 24CB001 Follow Dec 18 '25 Amazon EC2 in Cloud Computing: Features, Use Cases, and Pricing # devops # webdev # ec2 # aws Comments Add Comment 2 min read I Built a Form Backend That Sends Submissions to WhatsApp — Beta Testers Wanted Joe Seabrook Joe Seabrook Joe Seabrook Follow Dec 18 '25 I Built a Form Backend That Sends Submissions to WhatsApp — Beta Testers Wanted # showdev # tooling # webdev # backend Comments Add Comment 3 min read CSS Opacity Masterclass 2025: Guide with Code Examples & Best Practices Satyam Gupta Satyam Gupta Satyam Gupta Follow Dec 18 '25 CSS Opacity Masterclass 2025: Guide with Code Examples & Best Practices # css # webdev # programming # beginners Comments Add Comment 4 min read Construcción de Agentes con Microsoft Foundry Daniel Gomez Daniel Gomez Daniel Gomez Follow Dec 22 '25 Construcción de Agentes con Microsoft Foundry # webdev # ai # agents # azure 5 reactions Comments Add Comment 3 min read Apertre 3.0: A 30-Day Open-Source Journey for Developers 🚀 Soumyajit Mondal Soumyajit Mondal Soumyajit Mondal Follow Dec 18 '25 Apertre 3.0: A 30-Day Open-Source Journey for Developers 🚀 # opensource # webdev # programming # community Comments Add Comment 1 min read Mentorship vs. Micromanagement in Engineering Aarti Jangid Aarti Jangid Aarti Jangid Follow Dec 18 '25 Mentorship vs. Micromanagement in Engineering # programming # webdev # beginners # devops Comments Add Comment 4 min read Lessons From Trusting AI Too Early in Production Rohit Gavali Rohit Gavali Rohit Gavali Follow Dec 19 '25 Lessons From Trusting AI Too Early in Production # webdev # programming # ai Comments Add Comment 8 min read Dependency Injection in Go, Reduced to Field Tags Tetsuro Mikami Tetsuro Mikami Tetsuro Mikami Follow Dec 18 '25 Dependency Injection in Go, Reduced to Field Tags # webdev # go # programming Comments Add Comment 2 min read Using Internal Links, Filters, and Facets to Boost Ecommerce SEO on a Budget prateekshaweb prateekshaweb prateekshaweb Follow Dec 18 '25 Using Internal Links, Filters, and Facets to Boost Ecommerce SEO on a Budget # marketing # tutorial # webdev Comments Add Comment 3 min read How to Get Feedback on Your SaaS Valentin Valentin Valentin Follow Dec 18 '25 How to Get Feedback on Your SaaS # webdev # productivity # saas # testing Comments Add Comment 3 min read Small Business Inventory App Vijay Kumar Vijay Kumar Vijay Kumar Follow Dec 19 '25 Small Business Inventory App # saas # webdev # programming # javascript Comments Add Comment 1 min read From Blocks to Meaning: Data Items and Databases Athreya aka Maneshwar Athreya aka Maneshwar Athreya aka Maneshwar Follow Dec 23 '25 From Blocks to Meaning: Data Items and Databases # webdev # programming # database # architecture 10 reactions Comments Add Comment 4 min read First time with Nextjs............ Sourav Mahato Sourav Mahato Sourav Mahato Follow Dec 18 '25 First time with Nextjs............ # nextjs # webdev # programming # javascript Comments Add Comment 2 min read Building Stoqyy in Public Vijay Kumar Vijay Kumar Vijay Kumar Follow Dec 18 '25 Building Stoqyy in Public # saas # webdev # programming # ai 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 | 2026-01-13T08:48:23 |
https://docs.devcycle.com/platform/security-and-guardrails/permissions/#owners | Roles & Permissions | 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 Roles & Permissions On this page Roles & Permissions At DevCycle, our permissions model is designed to protect production while supporting secure and scalable team collaboration. We offer flexible, role-based access controls that can be applied both at the Organization and Project level—allowing you to tailor access based on how your teams operate. Permissions are available for Organizations on our Business or Enterprise plans. You can visit our pricing page or contact our support team to learn more about our plans. Permission Levels Overview DevCycle supports multiple levels of permission enforcement: Flat Access (default) : All users have full access across all Projects Basic Permissions : Org-wide roles that protect production Environments (Business and Enterprise plans) Full Role-Based Access Control (RBAC) : Fine-grained permissions managed at the Project level (Enterprise plans only) info Permissions enforcement will apply to all Projects and Production-type Environments within your Organization. Basic Permissions (Organization-Wide Roles) Basic permissions apply at the Organization level and are available to all Business and Enterprise customers. The principle behind basic permissions is to protect Production Environments while keeping permissions and their management as lightweight as possible. This level is perfect for teams that want to be able to move fast but still require some governance protections to be in place. info To enable basic permissions, navigate to your Organization Settings page and enable it under the permissions dropdown. The roles available with Basic Permissions are: Members Can ✅ Configure Development and Staging Environments Configure Inactive Production Environments Cannot ❌ Enable or Disable Production Environments Targeting Configure Active Production Environments When Production is Active , Configure Variables and Variations Manage roles of other users Manage Organization or Project settings Publishers Everything Members can do, plus: Can ✅ Enable or Disable Production Environments Targeting Configure Active Production Environments When Production is Active , Configure Variables and Variations Manage Project settings Cannot ❌ Manage roles of other users Manage Organization settings or billing Owners Everything Publishers can do, plus: Can ✅ Manage roles of all users in the Organization Administer billing Assigning Roles To assign a role to a team member, simply navigate to their profile. If you are an owner, you will be able to assign a new role to the member by using the Role dropdown. After you have selected a role, click "save" and the team member's permissions will be updated. For the user to have the new permission level available to them they will need to generate a new session by logging in again. Full Role-Based Access Control (Project-Level Roles – Enterprise Only) For Organizations managing multiple teams or business units, DevCycle offers Project-level RBAC on Enterprise plans. This allows you to manage roles granularly, granting access only to the specific workspaces your team members need with the requisite roles they need in each of those workspaces. With Role-Based Access Control, you can: Scope access to individual Projects Prevent cross-project visibility and restrict access to only the Projects a user is assigned Align access with your SSO groups and SCIM-based provisioning This enables centralized identity and access management with decentralized control, especially when integrated with providers like Azure AD or Okta. info To enable and configure SSO and SCIM-based provisioning, please contact our support team. Role Matrix The table below outlines actions available to each role across Organization and Project levels. note All actions affecting Production Environments are restricted for roles below Publisher . Action Viewer Member Publisher Project Admin Org Admin Org Owner organization:read:settings ✅ ✅ ✅ ✅ ✅ ✅ organization:write:settings ✅ ✅ organization:read:members ✅ ✅ ✅ ✅ ✅ ✅ organization:write:members ✅ ✅ organization:read:billing ✅ ✅ ✅ ✅ ✅ ✅ organization:write:billing ✅ organization:read:projects ✅ ✅ ✅ project:read ✅ ✅ ✅ ✅ ✅ project:write ✅ project:write:settings ✅ ✅ project:delete ✅ feature:read:staleness ✅ ✅ ✅ feature:read ✅ ✅ ✅ ✅ ✅ feature:write ✅ ✅ ✅ ✅ feature:publish ✅ ✅ ✅ feature:delete ✅ ✅ feature:status:archive ✅ ✅ ✅ ✅ feature:status:complete ✅ ✅ ✅ feature:read:config ✅ ✅ ✅ ✅ ✅ feature:write:config ✅ ✅ ✅ ✅ audience:write ✅ ✅ ✅ ✅ audience:read ✅ ✅ ✅ ✅ ✅ audience:write:prod ✅ ✅ ✅ audience:delete ✅ ✅ variable:read ✅ ✅ ✅ ✅ ✅ variable:write ✅ ✅ ✅ ✅ variable:write:prod ✅ ✅ environment:read ✅ ✅ ✅ ✅ ✅ environment:write ✅ ✅ ✅ ✅ environment:delete ✅ ✅ variation:read ✅ ✅ ✅ ✅ ✅ variation:write ✅ ✅ ✅ ✅ variation:delete ✅ ✅ ✅ ✅ results:read ✅ ✅ ✅ ✅ ✅ user:read ✅ ✅ ✅ ✅ ✅ user:write ✅ ✅ ✅ ✅ ✅ auditlog:read ✅ ✅ ✅ ✅ ✅ customproperty:read ✅ ✅ ✅ ✅ ✅ customproperty:write ✅ ✅ ✅ ✅ customproperty:delete ✅ ✅ ✅ ✅ metric:read ✅ ✅ ✅ ✅ ✅ metric:write ✅ ✅ ✅ ✅ metric:delete ✅ ✅ ✅ ✅ metricassociation:read ✅ ✅ ✅ ✅ ✅ metricassociation:write ✅ ✅ ✅ ✅ metricassociation:delete ✅ ✅ ✅ ✅ project:read:overrides ✅ ✅ ✅ ✅ ✅ project:write:overrides ✅ ✅ ✅ ✅ ✅ webhook:read ✅ ✅ ✅ ✅ ✅ webhook:write ✅ ✅ ✅ ✅ webhook:delete ✅ ✅ ✅ project:read:tokens ✅ ✅ project:write:tokens ✅ Managing Role Mappings with SCIM and SSO For Enterprise customers using identity providers (IdPs) like Azure AD or Okta, DevCycle supports role mapping through SCIM and SSO group-based permissions . Roles can be mapped to IdP groups Users are automatically assigned the correct roles upon login Centralized IT control, local team autonomy This streamlines onboarding and offboarding, and ensures the principle of least privilege is maintained. To get started with Role-Based Access Control, contact our support team. Edit this page Last updated on Jan 9, 2026 Previous Feature Obfuscation Next SDK Visibility Permission Levels Overview Basic Permissions (Organization-Wide Roles) Members Publishers Owners Assigning Roles Full Role-Based Access Control (Project-Level Roles – Enterprise Only) Role Matrix Managing Role Mappings with SCIM and SSO DevCycle Dashboard Blog Privacy Policy Twitter Discord GitHub Copyright © 2026 DevCycle. All rights reserved. | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/o1-vs-sonnet-es | OpenAI o1 vs. Claude Sonnet 3.5: ¿Cuál modelo de IA es mejor para programar? Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back OpenAI o1 vs. Claude Sonnet 3.5: ¿Cuál modelo de IA es mejor para programar? Introducción A medida que la IA continúa evolucionando, dos modelos destacan: o1 de OpenAI y Claude Sonnet 3.5 de Anthropic. Ambos ofrecen capacidades impresionantes para los desarrolladores de software, pero sus fortalezas varían, especialmente cuando se trata de programación. Este blog compara estos dos modelos de IA, centrándose en tareas de programación y rendimiento general. Fine incluye acceso ilimitado a ambos modelos, lo que lo convierte en una excelente manera de probar y comparar cómo o1 y Sonnet se desempeñan con tareas de programación. Diferencias Principales o1 está diseñado para razonamiento complejo y resolución de problemas . Sus respuestas son profundas y reflexivas, lo que lo hace ideal para desarrolladores que trabajan en problemas intrincados o que necesitan explicaciones detalladas. Por otro lado, Claude Sonnet 3.5 se centra en eficiencia y velocidad , destacando en tiempos de respuesta rápidos mientras es más rentable. Si buscas generar código rápidamente o manejar tareas de alto volumen, Claude Sonnet 3.5 puede ser la mejor opción. Ambos modelos utilizan arquitecturas basadas en transformadores, pero o1 es más adecuado para desarrolladores que buscan razonamiento detallado, mientras que Claude Sonnet 3.5 es la opción preferida para aquellos que priorizan la velocidad. Ventana de Contexto y Rendimiento La ventana de contexto juega un papel crucial en cómo estos modelos manejan entradas grandes o conversaciones extendidas. ChatGPT o1 admite 128,000 tokens, mientras que Claude Sonnet 3.5 maneja un mayor 200,000 tokens , dándole una ventaja para tareas que requieren una retención significativa de contexto, como revisar grandes bases de código. Ambos modelos ofrecen un rendimiento sólido en una variedad de tareas, pero sus habilidades brillan en diferentes áreas. ChatGPT o1 sobresale en razonamiento multietapa , explicando la lógica de código compleja en detalle, mientras que Claude Sonnet 3.5 se centra en correcciones de errores rápidas y generación eficiente de código . Versión Mejorada de Claude 3.5 Sonnet - Octubre 2024 - ¿Es Claude ahora mejor que GPT para programar? En octubre de 2024, Anthropic anunció una versión mejorada de Claude 3.5 Sonnet. Las recientes actualizaciones a Claude 3.5 Sonnet han mejorado significativamente sus capacidades de ingeniería de software. Notablemente, el rendimiento del modelo en el benchmark SWE-bench Verified ha mejorado del 33.4% al 49.0%, superando a todos los modelos disponibles públicamente, incluido el o1-preview de OpenAI. Este avance refleja la mayor precisión de Claude 3.5 Sonnet en la generación de funciones y verificación de errores, particularmente en la depuración y refactorización de código que involucra funciones anidadas o segmentos interdependientes. Además, la capacidad de tokens ampliada del modelo le permite retener y utilizar un contexto más extenso, lo que lo hace ideal para revisar grandes bases de código o gestionar proyectos intrincados con múltiples dependencias. Las pruebas iniciales indican que Claude 3.5 Sonnet sobresale en tareas de programación especializadas, como identificar vulnerabilidades de seguridad en aplicaciones web y optimizar algoritmos para velocidad y eficiencia. GitLab, por ejemplo, informó hasta un 10% de mejora en las capacidades de razonamiento para tareas de DevSecOps con el modelo actualizado, sin ningún aumento en la latencia. Casos de uso de IA para programación con o1 y Claude Sonnet 3.5 ChatGPT o1: Depuración de gestión de estado compleja en React: Usa o1 para analizar profundamente por qué ciertos estados no se actualizan correctamente o entran en conflicto entre componentes. Refactorización de código heredado: Emplea el razonamiento exhaustivo de o1 para reestructurar un script antiguo de Python para mejorar su legibilidad y mantenibilidad. Creación de algoritmos: Ideal para escribir y explicar algoritmos como ordenamiento, recorrido de árboles o programación dinámica en detalle. Claude Sonnet 3.5: Generación de código boilerplate: Crea rápidamente archivos de configuración para nuevos proyectos como APIs de Flask o estructura de front-end en Next.js. Autocompletar funciones: Úsalo para completar una función de JavaScript a medio escribir con manejo de errores adecuado y casos extremos. Generación masiva de código: Sonnet 3.5 sobresale en producir estructuras de código repetitivas pero ligeramente variadas como endpoints de API similares o casos de prueba unitarios. ¿Qué modelos de IA utilizan las diferentes herramientas de programación con IA? Hoy en día hay muchas herramientas de desarrollo disponibles para ayudarte con tu programación con IA, desde asistentes avanzados de programación con IA como Fine hasta generadores de código como GitHub Copilot. Algunas usan múltiples LLMs, algunas te dan la opción y otras se basan en un solo modelo. ¿Qué modelo de IA (LLM) utiliza Fine? Fine es una de las pocas herramientas de programación con IA que ofrece a los usuarios la opción entre diferentes LLMs para diversas tareas. Al usar Fine a través del navegador web, los usuarios pueden elegir entre o1-preview, 4o y Claude 3.5 Sonnet. Sin embargo, necesitarás una suscripción pro para aprovechar esto, que cuesta $13-15 por mes. Si eres un usuario gratuito, podrás usar Fine con 4o. Haz clic aquí para probarlo. ¿Qué modelo de IA (LLM) utiliza GitHub Copilot? GitHub Copilot está fuertemente integrado con OpenAI. GitHub es propiedad de Microsoft, que tiene una profunda asociación con OpenAI. La mayoría de los usuarios tienen acceso a 4o, mientras que los suscriptores de Azure AI pueden usar GitHub Copilot con o1-mini y o1-preview. ACTUALIZACIÓN: En GitHub Universe 2024, se anunció que esta asociación exclusiva ya no era tan exclusiva y que la opción de usar Claude se implementaría para todos los usuarios de GitHub Copilot en breve. Algunos usuarios ya han podido acceder a Claude. Está disponible en el Copilot Chat en Visual Studio Code y en Immersive Copilot en el navegador web solamente. ¿Qué modelo de IA (LLM) utiliza Cursor? Cursor utiliza Claude 3.5 Sonnet por defecto y recurre a OpenAI 4o durante interrupciones de Anthropic. ¿Qué modelo de IA (LLM) utiliza Bolt? Bolt, la herramienta de programación con IA que se especializa exclusivamente en front-end, se basa en Claude 3.5 Sonnet. ¿Qué modelo de IA (LLM) utiliza Replit? Aunque Replit lanzó previamente su propio modelo de IA en 2023, cuando anunciaron Replit Agent, su principal herramienta de programación con IA, en 2024, parece que tomaron la decisión de usar Claude 3.5 Sonnet. ¿Cómo comparar diferentes herramientas de programación con IA y LLMs? Si estás buscando comparar cuáles son las mejores herramientas de programación con IA o LLMs, hay algunas cosas a tener en cuenta. Primero, es importante evaluar el LLM y la herramienta por separado. Usa una herramienta como Fine que te permita dar la misma tarea a múltiples LLMs para comparar cuál te da el mejor resultado. Aquí hay una comparación que hicimos de los tres modelos ofrecidos por Fine, planteados con la misma pregunta: ¿Qué hace este repositorio? (Es una pregunta que algunos están llamando el Hola Mundo de la programación con IA). Segundo, compara cómo las herramientas se desempeñan con tu LLM elegido, específico para tu caso de uso. Fine ofrece una variedad de integraciones para aumentar tu productividad, como la capacidad de hacer revisiones dentro de GitHub PR, que están ahorrando horas a los desarrolladores cada semana. ¿Cuál modelo es mejor para programar? Para tareas de programación, tu elección depende de tus necesidades: ChatGPT o1 es la mejor opción cuando trabajas en problemas complejos y multietapa donde necesitas un razonamiento profundo y explicaciones detalladas. Por ejemplo, sobresale en explicar código intrincado o ayudar con la depuración de una manera más reflexiva. Claude Sonnet 3.5 es el modelo preferido para generación de código rápida y eficiente y prototipado iterativo. Es rentable para tareas de alto volumen como generar múltiples fragmentos de código o automatizar correcciones de errores. Ambos modelos apoyan a los desarrolladores en la programación, pero Claude Sonnet 3.5 puede ahorrar tiempo y dinero para tareas de programación cotidianas, mientras que ChatGPT o1 podría ser tu aliado para problemas de programación más difíciles y detallados. Conclusión Al decidir entre ChatGPT o1 y Claude Sonnet 3.5 , considera la complejidad de tus tareas de programación y las restricciones de presupuesto. ChatGPT o1 ofrece una mejor resolución de problemas para tareas intrincadas, mientras que Claude Sonnet 3.5 proporciona una generación de código más rápida y asequible para las necesidades de desarrollo diarias. Ambos modelos son herramientas de IA poderosas que pueden mejorar significativamente tu productividad como desarrollador de software. Regístrate en una plataforma como Fine , que incluye acceso ilimitado a ambos, para lo mejor de ambos mundos sin pagar de más. ¿Por qué suscribirse a Fine? Fine es una plataforma que ofrece acceso ilimitado tanto a o1 como a Claude Sonnet 3.5 , permitiendo a los desarrolladores cambiar entre estos poderosos LLMs según las necesidades de su tarea. Esta flexibilidad es perfecta para aquellos que requieren explicaciones detalladas de ChatGPT o generación de código rápida y eficiente de Claude. Con Fine, no hay necesidad de gestionar tus propias claves API o preocuparte por los límites de uso: todo está incluido. Suscribirse a Fine simplifica el proceso, ofreciendo acceso ilimitado y rentable a ambos modelos para todas tus tareas de programación y desarrollo. Fuentes McNulty, Niall. "ChatGPT o1 vs Claude Sonnet 3.5." Medium , hace 5 días. Enlace . "GPT o1 vs Claude 3.5 Sonnet: ¿Cuál modelo es mejor para programar?" Bind AI Blog , 17 Sep 2024. Enlace . "Comparar o1 Preview vs. Claude 3.5 Sonnet." Context.ai . Enlace . Harisec. "o1 vs Claude." GitHub . Enlace . Tabla de Contenidos Introducción Diferencias Principales Ventana de Contexto y Rendimiento Versión Mejorada de Claude 3.5 Sonnet - Octubre 2024 - ¿Es Claude ahora mejor que GPT para programar? Casos de uso de IA para programación con o1 y Claude 3.5 Sonnet ¿Qué modelos de IA utilizan las diferentes herramientas de programación con IA? Fine GitHub Copilot Cursor Bolt Replit ¿Cómo comparar diferentes herramientas de programación con IA y LLMs? ¿Cuál modelo es mejor para programar? Conclusión ¿Por qué suscribirse a Fine? 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 | 2026-01-13T08:48:23 |
https://docs.suprsend.com/docs/react-sdk#usesuprsendclient | SDK Integration - SuprSend, Notification infrastructure for Product teams Skip to main content SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Community Trust Center Platform Status Postman Collection Developer Resources Overview Updates and Versioning Versioning and Support Policy SDK Changelog Authentication API Keys and Secrets Service Token Best Practices for Key & Token Management MCP Overview BETA Quickstart Tool List Building with LLMs Security Security SDKs and APIs SDKs SDK Overview SuprSend Backend SDK SuprSend Client SDK Authentication Javascript Android iOS React Native Flutter React SDK Integration WebPush Preferences Events and User methods InApp Feed Management API REST API Postman Collection Features Validate Trigger Payload Type Safety Testing Testing the Template Test Mode Monitoring and Logging Logs Data Out Contact Us Get Started SuprSend, Notification infrastructure for Product teams home page Search... ⌘ K Ask AI Contact Us Get Started Get Started Search... Navigation React SDK Integration Documentation API Reference Management API CLI Reference Developer Resources Changelog Documentation API Reference Management API CLI Reference Developer Resources Changelog React SDK Integration OpenAI Open in ChatGPT SDK Integration to enable SuprSend features like Inbox, Preferences, and Webpush into React-based web applications. OpenAI Open in ChatGPT Installation We support 2 SDK’s for react based applications. @suprsend/react-core : This provides context providers and hooks to integrate SuprSend in to your application. If you want to use web-push, user methods, track events or implement your own UI for preferences and inbox by using provided methods, this library is better option. If you want to use any of inbuilt components for inbox or preferences then use @suprsend/react . @suprsend/react : This library is built on top of @suprsend/react-core , so all hooks, context providers and methods that are present in @suprsend/react-core library are also present in this, with addition to that drop-in components like Inbox, NotificationsFeed, Preferences etc are available which comes with UI to ease integration. npm yarn Copy Ask AI npm install @ suprsend / react Integration SuprSendProvider This context provider need to be wrapper around your component in which you want to use SuprSend methods. This is responsible for creating client instance( new SuprSend() ), identify and reset user. You can access the SuprSend client instance using useSuprSendClient hook. This instance contains all methods needed to integrate preferences, webpush, track events and user methods. Example.js TypeDef Copy Ask AI import { SuprSendProvider } from '@suprsend/react' ; function Example () { return ( < SuprSendProvider publicApiKey = { YOUR_KEY } distinctId = { YOUR_DISTINCT_ID } > < MyComponent /> </ SuprSendProvider > ); } Parameter Description publicApiKey public API Key is mandatory field without which error will be thrown by SuprSendProvider. You can get this from SuprSend Dashboard . distinctId Unique identifier to identify a user across platform. If a value is passed SDK will create user and authenticate user. If null value is passed authenticated user’s instance data will be cleared in your application, kind of logout. userToken Mandatory when enhanced security mode is on. This is ES256 JWT token generated in your server-side. Refer docs to create userToken. refreshUserToken This function is called by SDK internally to get new userToken before existing token is expired. The returned JWT token string is used as the new userToken. userAuthenticationHandler This callback will be called after authenticating user internally when you pass distinctId field to give you back the response of user creation API call. host Customise the host url. vapidKey This key is needed only if you are implementing WebPush notifications. You can get it in SuprSend Dashboard —> Vendors —> WebPush swFileName This key is needed only if you are implementing WebPush notifications and want to customise default serviceworker.js file name with your own service worker file name. After implementing the above SuprSendProvider you can be able to use all SuprSend features. useSuprSendClient This hook is used to access internal SuprSend client instance which has all methods related to webpush, preferences, user methods and track event. Use this hook inside child of SuprSendProvider. Example.js Copy Ask AI import { SuprSendProvider , useSuprSendClient } from "@suprsend/react" function Example () { return ( < SuprSendProvider publicApiKey = { YOUR_KEY } distinctId = { YOUR_DISTINCT_ID } > < MyComponent /> </ SuprSendProvider > ); } function MyComponent () { const suprSendClient = useSuprSendClient (); return ( < p onClick = { () => { // suprSendClient.track('testing'); // suprSendClient.user.setEmail(' [email protected] ') // suprSendClient.webpush.registerPush() // suprSendClient.user.preferences.getPreferences() } } > Click Me </ p > ); } useAuthenticateUser This hook is used to get authenticated user anywhere in your application inside SuprSendProvider. This can also be used to check if user is authenticated before calling any method of SuprSend. Example.js Copy Ask AI import { useAuthenticateUser } from '@suprsend/react' ; function MyComponent () { const { authenticatedUser } = useAuthenticateUser (); useEffect (() => { if ( authenticatedUser ) { console . log ( 'User is authenticated' , authenticatedUser ); } }, [ authenticatedUser ]); return < p > Hello world </ p > ; } Was this page helpful? Yes No Suggest edits Raise issue Previous WebPush Integration steps of webpush in react application. Next ⌘ I x github linkedin youtube Powered by On this page Installation Integration SuprSendProvider useSuprSendClient useAuthenticateUser | 2026-01-13T08:48:23 |
https://dev.to/leena_malhotra/why-asking-for-better-outputs-misses-the-real-problem-29f9#when-ideogram-v3s-whitepaper-met-reality | Why Asking for Better Outputs Misses the Real Problem - 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 Leena Malhotra Posted on Jan 12 Why Asking for Better Outputs Misses the Real Problem # programming # ai # imagegen # nanobanana Yesterday, I spent four hours debugging why Ideogram V3 kept generating inconsistent architectural renders. The whitepaper promised "improved spatial coherence." My outputs looked like they were designed by committee. This isn't a model problem. It's a workflow problem. When Ideogram V3's Whitepaper Met Reality I was building a pipeline to generate interior design variations for an e-commerce platform. The whitepaper showed beautiful examples of architectural spaces with perfect lighting. Here's the prompt I used from their examples: "Modern minimalist living room, floor-to-ceiling windows, natural light, Scandinavian furniture, architectural photography" Enter fullscreen mode Exit fullscreen mode First three generations: perfect. Fourth one: furniture floating off the ground. Fifth: window placement changed. By the tenth iteration, I had seven different room layouts. Same seed, same parameters, same model version. The issue wasn't randomness—it was me treating each generation as independent. The whitepaper examples worked because they were single, carefully-constructed prompts. I was running iterative experiments without maintaining state. The fix: class PromptContext : def __init__ ( self , base_intent ): self . base_intent = base_intent self . style_locks = {} def generate_with_memory ( self , variation ): locked = " " . join ([ f " { k } : { v } " for k , v in self . style_locks . items ()]) return f " { self . base_intent } . { locked } . { variation } " context = PromptContext ( " Modern minimalist living room " ) context . style_locks [ " windows " ] = " floor-to-ceiling on north wall " context . style_locks [ " floor " ] = " light oak hardwood " Enter fullscreen mode Exit fullscreen mode Cost: 40% more tokens per request. Benefit: went from 60% usable outputs to 95%. The whitepaper shows capability, not workflow. When you can test the same prompt across multiple AI models , the dissonance between documentation and reality becomes measurable rather than frustrating. SD3.5 Medium's Averaging Problem I needed product packaging concepts that felt "premium but approachable" for a beverage brand. The brief: Japanese minimalism meets 1970s American optimism. First attempt: { " prompt " : " Premium beverage packaging, minimalist, warm nostalgic colors, sophisticated " , " cfg_scale " : 7.5 , " sampler " : " DPM++ 2M Karras " } Enter fullscreen mode Exit fullscreen mode Result: generic wellness brand aesthetics. Technically perfect. Strategically useless. I ran 50 variations testing cfg_scale from 5.0 to 12.0: cfg_scale=5.0 → Lost brand identity cfg_scale=7.5 → Safe, averaged aesthetics cfg_scale=10.0 → Interesting tensions emerged cfg_scale=12.0 → Overcooked, but committed Enter fullscreen mode Exit fullscreen mode The fix: Stop describing the middle ground. Describe the extremes. prompt_a = " 1970s American optimism, warm oranges, rounded typography, sunburst graphics " prompt_b = " Japanese minimalism, white space, geometric precision " # Generate separately at cfg_scale=11.0 # Then synthesize specific elements Enter fullscreen mode Exit fullscreen mode SD3.5 Medium optimizes for "nothing broken" with vague targets. Give it contradictory specifics and higher CFG, and you get interesting failures to work with. Three unusable images and one brilliant image beats ten mediocre ones. Trade-off: 3x generation time. But revision time savings made it worth it. When Nano Banana PRO New Silently Changed Three-month-old content pipeline. Generated weekly newsletter summaries. Worked fine. One Monday: every output was 40% shorter and weirdly formal. Before (v1.2): 480 tokens, conversational. After (v1.3): 310 tokens, corporate. Release notes: "improved efficiency and coherence." No mention of temperature rescaling. The diff script I now run: def model_regression_test ( old_model , new_model , test_prompts ): results = [] for prompt in test_prompts : old_response = generate ( old_model , prompt , temp = 0.7 ) new_response = generate ( new_model , prompt , temp = 0.7 ) diff = { " length_delta " : len ( new_response ) - len ( old_response ), " formality_delta " : analyze_formality ( new_response ) - analyze_formality ( old_response ) } if abs ( diff [ " length_delta " ]) > 100 : print ( f " WARNING: Length shift " ) results . append ( diff ) return results Enter fullscreen mode Exit fullscreen mode The actual issue: they changed temperature scaling. temp=0.7 in v1.3 behaved like temp=0.4 in v1.2. My fix: pin model versions in production, regression test before upgrading. # requirements.txt nano-banana-pro==1.2.8 # Regression test before upgrade Enter fullscreen mode Exit fullscreen mode "Improved" means "different." Treat model updates like database migrations. Running parallel tests across Nano Banana PRO New and legacy versions reveals what release notes hide. The Context Switching Tax My workflow last month: Draft prompt in ChatGPT Test in Jupyter notebook Check results in Notion Discuss in Slack Update Google Doc Re-run notebook Forget step 1 decisions I was generating legal disclaimer variations. Each category needed specific regulatory language. I'd test in ChatGPT, worked great. Copy to notebook, different results. Thirty minutes debugging before realizing different model versions. The system I built: class ExperimentLog : def __init__ ( self ): self . conn = sqlite3 . connect ( " experiments.db " ) self . setup_db () def log ( self , model , prompt , params , output , success , notes = "" ): self . conn . execute ( """ INSERT INTO experiments (timestamp, model, prompt, parameters, output, success) VALUES (?, ?, ?, ?, ?, ?) """ , ( datetime . now (). isoformat (), model , prompt , json . dumps ( params ), output [: 500 ], success )) def get_successful_prompts ( self , model ): return self . conn . execute ( """ SELECT prompt, parameters FROM experiments WHERE model = ? AND success = 1 ORDER BY timestamp DESC """ , ( model ,)). fetchall () Enter fullscreen mode Exit fullscreen mode Now I search "legal disclaimers last week" and get exact parameters, model version, output. No re-discovering. Context switching isn't just a productivity tax—it fragments intent into micro-decisions scattered across tools. The Long Document Problem 140-page RFP. Needed specific technical requirements. Cross-references, tables, nested appendices. Tried: upload to ChatGPT, ask questions. Me: "What are data retention requirements in Section 7?" ChatGPT: "The document mentions retention in multiple sections..." Me: "No, I need specific retention periods." ChatGPT: "Based on the document, periods vary by type..." Enter fullscreen mode Exit fullscreen mode Summaries of summaries. Never the actual spec. The workflow: def chunk_document ( pdf_path , chunk_size = 4000 ): reader = pypdf . PdfReader ( pdf_path ) chunks = [] for i , page in enumerate ( reader . pages ): text = page . extract_text () words = text . split () for start in range ( 0 , len ( words ), chunk_size - 200 ): chunks . append ({ " page " : i + 1 , " text " : " " . join ( words [ start : start + chunk_size ]) }) return chunks def extract_requirements ( pdf_path ): chunks = chunk_document ( pdf_path ) requirements = [] for chunk in chunks : prompt = f """ Extract technical requirements from: Page { chunk [ ' page ' ] } : { chunk [ ' text ' ] } Return JSON: {{ " requirements " : [{{ " type " : " retention " , " spec " : " 7 years " , " section " : " 7.3.2 " }}]}} """ result = call_llm_api ( prompt ) requirements . extend ( result . get ( " requirements " , [])) return requirements Enter fullscreen mode Exit fullscreen mode Output: [ { "type" : "retention" , "spec" : "7 years for financial records" , "section" : "7.3.2" , "page" : 45 }, { "type" : "retention" , "spec" : "3 years for operational logs" , "section" : "7.3.2" , "page" : 45 } ] Enter fullscreen mode Exit fullscreen mode Trade-off: more processing time and API costs. But went from 3 hours frustrated questioning to 20 minutes automated extraction. Research papers that took hours to read now take minutes with a Document Summarizer . What I'd Do Differently Starting over, I'd version everything. Git for prompts, not just code. Build logging first—wasted weeks re-discovering experiments. Test edge cases, not happy paths. The whitepaper examples are optimized demos. Automate diffs and treat model updates like schema migrations. This is still evolving. If you've hit similar workflow issues, drop a comment. -Leena:) 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 Leena Malhotra Follow Creator and strategist blending machine learning, business, and creativity. Harvard Business School ’06. Writing about AI, productivity, and building systems for a self-directed life. Location California, United states Education Harvard Business School Joined Jun 17, 2025 More from Leena Malhotra AI Explains Code Well Until the Moment Context Actually Matters # webdev # programming # ai Using AI in Production Code Without Creating Invisible Bugs # webdev # programming # ai Ship Faster, Break Less: My Rules for Using AI Safely in Codebases # webdev # programming # ai # coding 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.amazon.com/Mindset-Psychology-Carol-S-Dweck/dp/0345472322 | Amazon.com: Mindset: The New Psychology of Success: 8580001041025: Dweck, Carol S.: Books Skip to Main content About this item About this item About this item Buying options Compare with similar items Videos Reviews Keyboard shortcuts Search alt + / Cart shift + alt + C Home shift + alt + H Orders shift + alt + O Add to cart shift + alt + K Show/Hide shortcuts shift + alt + Z To move between items, use your keyboard's up or down arrows. .us Deliver to Republic of Korea Books Select the department you want to search in All Departments Alexa Skills Amazon Devices Amazon Global Store Amazon Haul Amazon One Medical Amazon Pharmacy Amazon Resale Appliances Apps & Games Arts, Crafts & Sewing Audible Books & Originals Automotive Parts & Accessories Baby Beauty & Personal Care Books CDs & Vinyl Cell Phones & Accessories Clothing, Shoes & Jewelry Women's Clothing, Shoes & Jewelry Men's Clothing, Shoes & Jewelry Girl's Clothing, Shoes & Jewelry Boy's Clothing, Shoes & Jewelry Baby Clothing, Shoes & Jewelry Collectibles & Fine Art Computers Credit and Payment Cards Digital Music Electronics Garden & Outdoor Gift Cards Grocery & Gourmet Food Handmade Health, Household & Baby Care Home & Business Services Home & Kitchen Industrial & Scientific Just for Prime Kindle Store Luggage & Travel Gear Luxury Stores Magazine Subscriptions Movies & TV Musical Instruments Office Products Pet Supplies Premium Beauty Prime Video Smart Home Software Sports & Outdoors Subscribe & Save Subscription Boxes Tools & Home Improvement Toys & Games Under $10 Video Games Search Amazon EN Hello, sign in Account & Lists Returns & Orders 0 Cart All Amazon Haul Medical Care Amazon Basics Best Sellers Books Registry New Releases Today's Deals Gift Cards Smart Home Prime Pharmacy Customer Service Music Amazon Home Fashion Kindle Books Toys & Games Automotive Sports & Outdoors Beauty & Personal Care Home Improvement Sell Categories Recently Visited Featured Kindle eBooks Kindle Deals Best Books of 2025 Top Categories Romance Science Fiction & Fantasy Mystery, Thriller & Suspense Self-help History Children's Books Fiction Comics & Manga LGBTQIA+ Literature & Fiction Mystery, Thriller & Suspense Romance Science Fiction & Fantasy Teen & Young Adult Nonfiction Arts & Photography Biographies & Memoirs Business & Money Calendars Computers & Technology Cookbooks, Food & Wine Crafts, Hobbies & Home Education & Teaching Engineering & Transportation Health, Fitness & Dieting History Humor & Entertainment Law LGBTQIA+ Medical Books Parenting & Relationships Politics & Social Sciences Reference Religion & Spirituality Science & Math Self-help Sports & Outdoors Test Preparation Travel Children's Books All Children's Books Editors' Picks Teacher's Picks Award Winners Shorts Amazon Original Stories Short Reads More Categories Special Editions Textbooks Magazines Amazon Classics Amazon First Reads Great on Kindle All Categories Top Categories Fiction Nonfiction Children's Books Shorts More Categories Top Categories Romance Science Fiction & Fantasy Mystery, Thriller & Suspense Self-help History Children's Books Fiction Comics & Manga LGBTQIA+ Literature & Fiction Mystery, Thriller & Suspense Romance Science Fiction & Fantasy Teen & Young Adult Nonfiction Arts & Photography Biographies & Memoirs Business & Money Calendars Computers & Technology Cookbooks, Food & Wine Crafts, Hobbies & Home Education & Teaching Engineering & Transportation Health, Fitness & Dieting History Humor & Entertainment Law LGBTQIA+ Medical Books Parenting & Relationships Politics & Social Sciences Reference Religion & Spirituality Science & Math Self-help Sports & Outdoors Test Preparation Travel Children's Books All Children's Books Editors' Picks Teacher's Picks Award Winners Shorts Amazon Original Stories Short Reads More Categories Special Editions Textbooks Magazines Amazon Classics Amazon First Reads Great on Kindle New & Trending Recently Visited Featured Kindle eBooks Kindle Deals Best Books of 2025 New & Trending New Releases Editors' Picks of the Month Amazon First Reads Best of #BookTok books Comics & Manga New Releases Deals & Rewards Recently Visited Featured Kindle eBooks Kindle Deals Best Books of 2025 Deals & Rewards Print Deals Kindle Deals Audible Deals Comics & Manga Deals Kindle Rewards Best Sellers & More Recently Visited Featured Kindle eBooks Kindle Deals Best Books of 2025 Best Sellers Amazon Best Sellers New York Times Best Sellers Amazon Charts Acclaimed Award Winners Goodreads Choice Winners From Our Editors Editors' Picks of the Month Amazon Book Review Best Books of 2025 Memberships Recently Visited Featured Kindle eBooks Kindle Deals Best Books of 2025 Memberships Unlimited access to over 4 million digital books, audiobooks, comics, and magazines. 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Sorry, there was a problem. There was an error retrieving your Wish Lists. Please try again. Sorry, there was a problem. List unavailable. Other sellers on Amazon New & Used (96) from $7.28 $ 7 . 28 Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required . Read instantly on your browser with Kindle for Web. Using your mobile phone camera - scan the code below and download the Kindle app. 5 Books To Unlock Your Potential Amazon Books Image Unavailable Image not available for Color: To view this video download Flash Player 7 VIDEOS VIDEOS 360° VIEW IMAGES Read sample Audible sample Follow the author Get new release updates & improved recommendations Carol S. Dweck Follow Something went wrong. Please try your request again later. OK Mindset: The New Psychology of Success Paperback – December 26, 2007 by Carol S. Dweck (Author) 4.6 4.6 out of 5 stars (23,041) Sorry, there was a problem loading this page. 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See all formats and editions {"desktop_buybox_group_1":[{"displayPrice":"$9.32","priceAmount":9.32,"currencySymbol":"$","integerValue":"9","decimalSeparator":".","fractionalValue":"32","symbolPosition":"left","hasSpace":false,"showFractionalPartIfEmpty":true,"offerListingId":"ZpeJ5FQNjvMKB3dKACUNgJNcs1evSqNMjtUkmcGUW%2FvlmbEk1Q8uZalgz7FDtnDqpsBCYS%2FGF467aALw5R6%2B%2B6zt3vu4AnNmz%2F0aZhNvhrU2BNveBO2%2FokcjrMVuAmr9Foh1SWIGMhg%3D","locale":"en-US","buyingOptionType":"NEW","aapiBuyingOptionIndex":0}, {"displayPrice":"$8.99","priceAmount":8.99,"currencySymbol":"$","integerValue":"8","decimalSeparator":".","fractionalValue":"99","symbolPosition":"left","hasSpace":false,"showFractionalPartIfEmpty":true,"offerListingId":"ZpeJ5FQNjvMKB3dKACUNgJNcs1evSqNM1IEXdGHlFwz4vYfrJ55%2FTojQ4KxNsUEvgO3TU0NlFrvCb2J1Q5jglMUZfOq6FFhWZ3kkHksu7LcJiC6rZBc2Az%2B7C2W%2BPB76axqT%2B1X9N2pMXzgtKBkTzyWbhX1W8N2g2dbW5jy1WIwcllhs0Wntc%2FsCWeqZolHN","locale":"en-US","buyingOptionType":"USED","aapiBuyingOptionIndex":1}]} Purchase options and add-ons From the renowned psychologist who introduced the world to “growth mindset” comes this updated edition of the million-copy bestseller—featuring transformative insights into redefining success, building lifelong resilience, and supercharging self-improvement. “Through clever research studies and engaging writing, Dweck illuminates how our beliefs about our capabilities exert tremendous influence on how we learn and which paths we take in life.”—Bill Gates, GatesNotes “It’s not always the people who start out the smartest who end up the smartest.” After decades of research, world-renowned Stanford University psychologist Carol S. Dweck, Ph.D., discovered a simple but groundbreaking idea: the power of mindset. In this brilliant book, she shows how success in school, work, sports, the arts, and almost every area of human endeavor can be dramatically influenced by how we think about our talents and abilities. People with a fixed mindset —those who believe that abilities are fixed—are less likely to flourish than those with a growth mindset —those who believe that abilities can be developed. Mindset reveals how great parents, teachers, managers, and athletes can put this idea to use to foster outstanding accomplishment. In this edition, Dweck offers new insights into her now famous and broadly embraced concept. She introduces a phenomenon she calls false growth mindset and guides people toward adopting a deeper, truer growth mindset. She also expands the mindset concept beyond the individual, applying it to the cultures of groups and organizations. With the right mindset, you can motivate those you lead, teach, and love—to transform their lives and your own. Read more Report an issue with this product or seller Previous slide of product details Print length 320 pages Language English Publisher Ballantine Books Publication date December 26, 2007 Dimensions 5.18 x 0.67 x 7.97 inches ISBN-10 0345472322 ISBN-13 978-0345472328 Next slide of product details See all details Books with Buzz Discover the latest buzz-worthy books, from mysteries and romance to humor and nonfiction. Explore more Great on Kindle Great Experience. Great Value. Putting our best book forward Each Great on Kindle book offers a great reading experience, at a better value than print to keep your wallet happy. Explore your book, then jump right back to where you left off with Page Flip. View high quality images that let you zoom in to take a closer look. 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https://www.postman.com/ | Postman: The World's Leading API Platform | Sign Up for Free Home Product POSTMAN PLATFORM Postman Overview Security Integrations EXPLORE Postman API Network MCP Catalog Download Postman → DESIGN Spec Hub Manage specifications Mock Servers Validate API behavior BUILD Collections Organize API requests Workspaces Collaborate with teams Flows Create visual workflows TEST API Client Send API requests Collection Runner Run API workflows Postman CLI Run from command line OBSERVE Insights Track every endpoint Monitors Validate performance AI Agent Mode Automate API tasks AI Agent Builder Build AI agents MCP Server Connect AI agents Solutions USE CASES Test Automation Create, run, and manage API tests at scale API Security Control access and manage secrets AI Streamline workflows across the API lifecycle API Distribution and Reuse Publish APIs internally or publicly API Governance Enforce API standards at scale API Documentation Instantly generate up-to-date docs Workflow Intelligence Use APIs to build effective agents and workflows Small and Medium Teams Optimize API workflows for small and medium teams Pricing Enterprise Resources Learn Learning Hub Docs Postman Academy Templates Customer stories Postman Best Practices CONNECT Community Events Discord GET SUPPORT Support Center Release notes Postman Status Trust and Security POSTMAN Blog Press and media About Postman Contact Sales Sign In Sign Up for Free Product POSTMAN PLATFORM Postman Overview Security Integrations EXPLORE Postman API Network MCP Catalog Download Postman → DESIGN Spec Hub Manage specifications Mock Servers Validate API behavior BUILD Collections Organize API requests Workspaces Collaborate with teams Flows Create visual workflows TEST API Client Send API requests Collection Runner Run API workflows Postman CLI Run from command line OBSERVE Insights Track every endpoint Monitors Validate performance AI Agent Mode Automate API tasks AI Agent Builder Build AI agents MCP Server Connect AI agents Solutions USE CASES Test Automation Create, run, and manage API tests at scale API Security Control access and manage secrets AI Streamline workflows across the API lifecycle API Distribution and Reuse Publish APIs internally or publicly API Governance Enforce API standards at scale API Documentation Instantly generate up-to-date docs Workflow Intelligence Use APIs to build effective agents and workflows Small and Medium Teams Optimize API workflows for small and medium teams Pricing Enterprise Resources Learn Learning Hub Docs Postman Academy Templates Customer stories Postman Best Practices CONNECT Community Events Discord GET SUPPORT Support Center Release notes Postman Status Trust and Security POSTMAN Blog Press and media About Postman Contact Sales Sign In Sign Up for Free Get the playbook leading teams use to create consistent, agent-ready APIs. 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https://www.learnpytorch.io/?ref=mrdbourke.com#what-are-the-prerequisites | Zero to Mastery Learn PyTorch for Deep Learning Skip to content Zero to Mastery Learn PyTorch for Deep Learning Home Initializing search mrdbourke/pytorch_deep_learning Zero to Mastery Learn PyTorch for Deep Learning mrdbourke/pytorch_deep_learning Home Home Table of contents Does this course cover PyTorch 2.0? Status Course materials/outline About this course Who is this course for? What are the prerequisites? How is the course taught? What will I get if I finish the course? What will I build in the course? How do I approach this course? Do I need to take things in order? How do I get started? 00. PyTorch Fundamentals 01. PyTorch Workflow Fundamentals 02. PyTorch Neural Network Classification 03. PyTorch Computer Vision 04. PyTorch Custom Datasets 05. PyTorch Going Modular 06. PyTorch Transfer Learning 07. PyTorch Experiment Tracking 08. PyTorch Paper Replicating 09. PyTorch Model Deployment A Quick PyTorch 2.0 Tutorial PyTorch Extra Resources PyTorch Cheatsheet The Three Most Common Errors in PyTorch Table of contents Does this course cover PyTorch 2.0? Status Course materials/outline About this course Who is this course for? What are the prerequisites? How is the course taught? What will I get if I finish the course? What will I build in the course? How do I approach this course? Do I need to take things in order? How do I get started? Learn PyTorch for Deep Learning: Zero to Mastery book Welcome to the second best place on the internet to learn PyTorch (the first being the PyTorch documentation ). This is the online book version of the Learn PyTorch for Deep Learning: Zero to Mastery course . This course will teach you the foundations of machine learning and deep learning with PyTorch (a machine learning framework written in Python). The course is video based. However, the videos are based on the contents of this online book. For full code and resources see the course GitHub . Otherwise, you can find more about the course below. Does this course cover PyTorch 2.0? Yes. PyTorch 2.0 is an additive release to previous versions of PyTorch. This means it adds new features on top of the existing baseline features of PyTorch. This course focuses on the baseline features of PyTorch (e.g. you're a beginner wanting to get into deep learning/AI). Once you know the fundamentals of PyTorch, PyTorch 2.0 is a quick upgrade, there's a tutorial on this website which runs through the new features. Status Course launched on ZTM Academy ! Last update: April 16 2023 Videos are done for chapters: 00, 01, 02, 03, 04, 05, 06, 07, 08, 09 (all chapters!) Currently working on: PyTorch 2.0 Tutorial See progress on the course GitHub Project . Get updates: Follow the pytorch-deep-learning repo log or sign up for emails . Course materials/outline 💻 Code on GitHub: All of course materials are available open-source on GitHub . 🎥 First five sections on YouTube: Learn Pytorch in a day by watching the first 25-hours of material . 🔬 Course focus: code, code, code, experiment, experiment, experiment. 🏃♂️ Teaching style: https://sive.rs/kimo . 🤔 Ask a question: See the course GitHub Discussions page for existing questions/ask your own. Section What does it cover? Exercises & Extra-curriculum Slides 00 - PyTorch Fundamentals Many fundamental PyTorch operations used for deep learning and neural networks. Go to exercises & extra-curriculum Go to slides 01 - PyTorch Workflow Provides an outline for approaching deep learning problems and building neural networks with PyTorch. Go to exercises & extra-curriculum Go to slides 02 - PyTorch Neural Network Classification Uses the PyTorch workflow from 01 to go through a neural network classification problem. Go to exercises & extra-curriculum Go to slides 03 - PyTorch Computer Vision Let's see how PyTorch can be used for computer vision problems using the same workflow from 01 & 02. Go to exercises & extra-curriculum Go to slides 04 - PyTorch Custom Datasets How do you load a custom dataset into PyTorch? Also we'll be laying the foundations in this notebook for our modular code (covered in 05). Go to exercises & extra-curriculum Go to slides 05 - PyTorch Going Modular PyTorch is designed to be modular, let's turn what we've created into a series of Python scripts (this is how you'll often find PyTorch code in the wild). Go to exercises & extra-curriculum Go to slides 06 - PyTorch Transfer Learning Let's take a well performing pre-trained model and adjust it to one of our own problems. Go to exercises & extra-curriculum Go to slides 07 - Milestone Project 1: PyTorch Experiment Tracking We've built a bunch of models... wouldn't it be good to track how they're all going? Go to exercises & extra-curriculum Go to slides 08 - Milestone Project 2: PyTorch Paper Replicating PyTorch is the most popular deep learning framework for machine learning research, let's see why by replicating a machine learning paper. Go to exercises & extra-curriculum Go to slides 09 - Milestone Project 3: Model Deployment So we've built a working PyTorch model... how do we get it in the hands of others? Hint: deploy it to the internet. Go to exercises & extra-curriculum Go to slides PyTorch Extra Resources This course covers a large amount of PyTorch and deep learning but the field of machine learning is vast, inside here you'll find recommended books and resources for: PyTorch and deep learning, ML engineering, NLP (natural language processing), time series data, where to find datasets and more. - - PyTorch Cheatsheet A very quick overview of some of the main features of PyTorch plus links to various resources where more can be found in the course and in the PyTorch documentation. - - Three Most Common Errors in PyTorch An overview of the three most common errors in PyTorch (shape, device and datatype errors), how they happen and how to fix them. - - A Quick PyTorch 2.0 Tutorial A fasssssst introduction to PyTorch 2.0, what's new and how to get started along with resources to learn more. - - About this course Who is this course for? You: Are a beginner in the field of machine learning or deep learning or AI and would like to learn PyTorch. This course: Teaches you PyTorch and many machine learning, deep learning and AI concepts in a hands-on, code-first way. If you already have 1-year+ experience in machine learning, this course may help but it is specifically designed to be beginner-friendly. What are the prerequisites? 3-6 months coding Python. At least one beginner machine learning course (however this might be able to be skipped, resources are linked for many different topics). Experience using Jupyter Notebooks or Google Colab (though you can pick this up as we go along). A willingness to learn (most important). For 1 & 2, I'd recommend the Zero to Mastery Data Science and Machine Learning Bootcamp , it'll teach you the fundamentals of machine learning and Python (I'm biased though, I also teach that course). How is the course taught? All of the course materials are available for free in an online book at learnpytorch.io . If you like to read, I'd recommend going through the resources there. If you prefer to learn via video, the course is also taught in apprenticeship-style format, meaning I write PyTorch code, you write PyTorch code. There's a reason the course motto's include if in doubt, run the code and experiment, experiment, experiment! . My whole goal is to help you to do one thing: learn machine learning by writing PyTorch code. The code is all written via Google Colab Notebooks (you could also use Jupyter Notebooks), an incredible free resource to experiment with machine learning. What will I get if I finish the course? There's certificates and all that jazz if you go through the videos. But certificates are meh. You can consider this course a machine learning momentum builder. By the end, you'll have written hundreds of lines of PyTorch code. And will have been exposed to many of the most important concepts in machine learning. So when you go to build your own machine learning projects or inspect a public machine learning project made with PyTorch, it'll feel familiar and if it doesn't, at least you'll know where to look. What will I build in the course? We start with the barebone fundamentals of PyTorch and machine learning, so even if you're new to machine learning you'll be caught up to speed. Then we’ll explore more advanced areas including PyTorch neural network classification, PyTorch workflows, computer vision, custom datasets, experiment tracking, model deployment, and my personal favourite: transfer learning, a powerful technique for taking what one machine learning model has learned on another problem and applying it to your own! Along the way, you’ll build three milestone projects surrounding an overarching project called FoodVision, a neural network computer vision model to classify images of food. These milestone projects will help you practice using PyTorch to cover important machine learning concepts and create a portfolio you can show employers and say "here's what I've done". How do I approach this course? As mentioned, the video version of the course is taught apprenticeship style. Meaning I write PyTorch code, you write PyTorch code. But here's what I recommend: Code along ( if in doubt, run the code ) - Follow along with code and try to write as much of it as you can yourself, keep doing so until you find yourself writing PyTorch code in your subconscious that's when you can stop writing the same code over and over again. Explore and experiment ( experiment, experiment, experiment! ) - Machine learning (and deep learning) is very experimental. So if you find yourself wanting to try something on your own and ignoring the materials, do it. Visualize what you don't understand ( visualize, visualize, visualize! ) - Numbers on a page can get confusing. So make things colourful, see what the inputs and outputs of your code looks like. Ask questions - If you're stuck with something, ask a question, trying searching for it or if nothing comes up, the course GitHub Discussions page will be the place to go. Do the exercises - Each module of the course comes with a dedicated exercises section. It's important to try these on your own. You will get stuck. But that's the nature of learning something new: everyone gets stuck. Share your work - If you've learned something cool or even better, made something cool, share it. It could be with the course Discord group or on the course GitHub page or on your own website. The benefits of sharing your work is you get to practice communicating as well as others can help you out if you're not sure of something. Do I need to take things in order? The notebooks/chapters build upon each other sequentially but feel free to jump around. How do I get started? You can read the materials on any device but this course is best viewed and coded along within a desktop browser. The course uses a free tool called Google Colab. If you've got no experience with it, I'd go through the free Introduction to Google Colab tutorial and then come back here. To start: Click on one of the notebook or section links like " 00. PyTorch Fundamentals ". Click the "Open in Colab" button up the top. Press SHIFT+Enter a few times and see what happens. Happy machine learning! Back to top Made with Material for MkDocs Insiders | 2026-01-13T08:48:23 |
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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 Tooling Follow Hide Working with a new tool you want to share? Created a new workflow for a task? Found some great configurations? Share them with the community! Create Post about #tooling This tag can be seen as related to #productivity for most of its content. The posts can contain certain configurations, explanations of the usage of tools, clever combinations to reach a goal or discussions about them. Posts Left menu 👋 Sign in for the ability to sort posts by relevant , latest , or top . Right menu I got tired of waiting for Gradle, so I built a runtime that runs Kotlin like Python. Srikar Sunchu Srikar Sunchu Srikar Sunchu Follow Jan 13 I got tired of waiting for Gradle, so I built a runtime that runs Kotlin like Python. # kotlin # performance # productivity # tooling 10 reactions Comments 1 comment 2 min read Building a Low-Code Blockchain Deployment Platform Kowshikkumar Reddy Makireddy Kowshikkumar Reddy Makireddy Kowshikkumar Reddy Makireddy Follow Jan 13 Building a Low-Code Blockchain Deployment Platform # showdev # blockchain # devops # tooling Comments Add Comment 9 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 Building Voice Trainer: a tiny, local‑first pitch analysis tool for gender‑affirming voice practice codebunny20 codebunny20 codebunny20 Follow Jan 12 Building Voice Trainer: a tiny, local‑first pitch analysis tool for gender‑affirming voice practice # showdev # opensource # privacy # tooling Comments Add Comment 1 min read Inside Git: How It Really Works (With the .git Folder Explained) Subhrangsu Bera Subhrangsu Bera Subhrangsu Bera Follow Jan 12 Inside Git: How It Really Works (With the .git Folder Explained) # git # github # development # tooling 1 reaction Comments Add Comment 4 min read Claude-Gemini Integration Tool "CGMB" v1.1.0: Implementing Windows Support ryoto miyake ryoto miyake ryoto miyake Follow Jan 12 Claude-Gemini Integration Tool "CGMB" v1.1.0: Implementing Windows Support # ai # gemini # llm # tooling Comments Add Comment 2 min read Exploring Modern Python Type Checkers Nicolas Galler Nicolas Galler Nicolas Galler Follow Jan 12 Exploring Modern Python Type Checkers # python # tooling # vscode Comments Add Comment 2 min read Mathematical Audit of Excalidraw: Finding "Logic Echoes" via Linear Algebra Petar Liovic Petar Liovic Petar Liovic Follow Jan 12 Mathematical Audit of Excalidraw: Finding "Logic Echoes" via Linear Algebra # architecture # 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go # tooling # tutorial Comments Add Comment 2 min read [TIL][Python] Python Tool for Online PDF Viewing, Comparison, and Data Import Evan Lin Evan Lin Evan Lin Follow Jan 11 [TIL][Python] Python Tool for Online PDF Viewing, Comparison, and Data Import # machinelearning # tooling # python # opensource Comments Add Comment 2 min read I Built aioflare — A Tool to Manage Multiple Cloudflare Accounts (Beta) Dev_liq Dev_liq Dev_liq Follow Jan 11 I Built aioflare — A Tool to Manage Multiple Cloudflare Accounts (Beta) # showdev # devops # productivity # tooling Comments Add Comment 4 min read [Gemini 3.0][Image Generation] Building a PDF Text Optimization Tool with Gemini 3.0 Pro Image API Evan Lin Evan Lin Evan Lin Follow for Google Developer Experts Jan 11 [Gemini 3.0][Image Generation] Building a PDF Text Optimization Tool with Gemini 3.0 Pro Image API # gemini # tooling # llm # api 2 reactions Comments Add Comment 10 min read I built a tool to detect ISP Throttling on Steam using React + Vite Murilo Evangelinos Murilo Evangelinos Murilo Evangelinos Follow Jan 11 I built a tool to detect ISP Throttling on Steam using React + Vite # 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https://dev.to/leena_malhotra/why-asking-for-better-outputs-misses-the-real-problem-29f9#main-content | Why Asking for Better Outputs Misses the Real Problem - 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 Leena Malhotra Posted on Jan 12 Why Asking for Better Outputs Misses the Real Problem # programming # ai # imagegen # nanobanana Yesterday, I spent four hours debugging why Ideogram V3 kept generating inconsistent architectural renders. The whitepaper promised "improved spatial coherence." My outputs looked like they were designed by committee. This isn't a model problem. It's a workflow problem. When Ideogram V3's Whitepaper Met Reality I was building a pipeline to generate interior design variations for an e-commerce platform. The whitepaper showed beautiful examples of architectural spaces with perfect lighting. Here's the prompt I used from their examples: "Modern minimalist living room, floor-to-ceiling windows, natural light, Scandinavian furniture, architectural photography" Enter fullscreen mode Exit fullscreen mode First three generations: perfect. Fourth one: furniture floating off the ground. Fifth: window placement changed. By the tenth iteration, I had seven different room layouts. Same seed, same parameters, same model version. The issue wasn't randomness—it was me treating each generation as independent. The whitepaper examples worked because they were single, carefully-constructed prompts. I was running iterative experiments without maintaining state. The fix: class PromptContext : def __init__ ( self , base_intent ): self . base_intent = base_intent self . style_locks = {} def generate_with_memory ( self , variation ): locked = " " . join ([ f " { k } : { v } " for k , v in self . style_locks . items ()]) return f " { self . base_intent } . { locked } . { variation } " context = PromptContext ( " Modern minimalist living room " ) context . style_locks [ " windows " ] = " floor-to-ceiling on north wall " context . style_locks [ " floor " ] = " light oak hardwood " Enter fullscreen mode Exit fullscreen mode Cost: 40% more tokens per request. Benefit: went from 60% usable outputs to 95%. The whitepaper shows capability, not workflow. When you can test the same prompt across multiple AI models , the dissonance between documentation and reality becomes measurable rather than frustrating. SD3.5 Medium's Averaging Problem I needed product packaging concepts that felt "premium but approachable" for a beverage brand. The brief: Japanese minimalism meets 1970s American optimism. First attempt: { " prompt " : " Premium beverage packaging, minimalist, warm nostalgic colors, sophisticated " , " cfg_scale " : 7.5 , " sampler " : " DPM++ 2M Karras " } Enter fullscreen mode Exit fullscreen mode Result: generic wellness brand aesthetics. Technically perfect. Strategically useless. I ran 50 variations testing cfg_scale from 5.0 to 12.0: cfg_scale=5.0 → Lost brand identity cfg_scale=7.5 → Safe, averaged aesthetics cfg_scale=10.0 → Interesting tensions emerged cfg_scale=12.0 → Overcooked, but committed Enter fullscreen mode Exit fullscreen mode The fix: Stop describing the middle ground. Describe the extremes. prompt_a = " 1970s American optimism, warm oranges, rounded typography, sunburst graphics " prompt_b = " Japanese minimalism, white space, geometric precision " # Generate separately at cfg_scale=11.0 # Then synthesize specific elements Enter fullscreen mode Exit fullscreen mode SD3.5 Medium optimizes for "nothing broken" with vague targets. Give it contradictory specifics and higher CFG, and you get interesting failures to work with. Three unusable images and one brilliant image beats ten mediocre ones. Trade-off: 3x generation time. But revision time savings made it worth it. When Nano Banana PRO New Silently Changed Three-month-old content pipeline. Generated weekly newsletter summaries. Worked fine. One Monday: every output was 40% shorter and weirdly formal. Before (v1.2): 480 tokens, conversational. After (v1.3): 310 tokens, corporate. Release notes: "improved efficiency and coherence." No mention of temperature rescaling. The diff script I now run: def model_regression_test ( old_model , new_model , test_prompts ): results = [] for prompt in test_prompts : old_response = generate ( old_model , prompt , temp = 0.7 ) new_response = generate ( new_model , prompt , temp = 0.7 ) diff = { " length_delta " : len ( new_response ) - len ( old_response ), " formality_delta " : analyze_formality ( new_response ) - analyze_formality ( old_response ) } if abs ( diff [ " length_delta " ]) > 100 : print ( f " WARNING: Length shift " ) results . append ( diff ) return results Enter fullscreen mode Exit fullscreen mode The actual issue: they changed temperature scaling. temp=0.7 in v1.3 behaved like temp=0.4 in v1.2. My fix: pin model versions in production, regression test before upgrading. # requirements.txt nano-banana-pro==1.2.8 # Regression test before upgrade Enter fullscreen mode Exit fullscreen mode "Improved" means "different." Treat model updates like database migrations. Running parallel tests across Nano Banana PRO New and legacy versions reveals what release notes hide. The Context Switching Tax My workflow last month: Draft prompt in ChatGPT Test in Jupyter notebook Check results in Notion Discuss in Slack Update Google Doc Re-run notebook Forget step 1 decisions I was generating legal disclaimer variations. Each category needed specific regulatory language. I'd test in ChatGPT, worked great. Copy to notebook, different results. Thirty minutes debugging before realizing different model versions. The system I built: class ExperimentLog : def __init__ ( self ): self . conn = sqlite3 . connect ( " experiments.db " ) self . setup_db () def log ( self , model , prompt , params , output , success , notes = "" ): self . conn . execute ( """ INSERT INTO experiments (timestamp, model, prompt, parameters, output, success) VALUES (?, ?, ?, ?, ?, ?) """ , ( datetime . now (). isoformat (), model , prompt , json . dumps ( params ), output [: 500 ], success )) def get_successful_prompts ( self , model ): return self . conn . execute ( """ SELECT prompt, parameters FROM experiments WHERE model = ? AND success = 1 ORDER BY timestamp DESC """ , ( model ,)). fetchall () Enter fullscreen mode Exit fullscreen mode Now I search "legal disclaimers last week" and get exact parameters, model version, output. No re-discovering. Context switching isn't just a productivity tax—it fragments intent into micro-decisions scattered across tools. The Long Document Problem 140-page RFP. Needed specific technical requirements. Cross-references, tables, nested appendices. Tried: upload to ChatGPT, ask questions. Me: "What are data retention requirements in Section 7?" ChatGPT: "The document mentions retention in multiple sections..." Me: "No, I need specific retention periods." ChatGPT: "Based on the document, periods vary by type..." Enter fullscreen mode Exit fullscreen mode Summaries of summaries. Never the actual spec. The workflow: def chunk_document ( pdf_path , chunk_size = 4000 ): reader = pypdf . PdfReader ( pdf_path ) chunks = [] for i , page in enumerate ( reader . pages ): text = page . extract_text () words = text . split () for start in range ( 0 , len ( words ), chunk_size - 200 ): chunks . append ({ " page " : i + 1 , " text " : " " . join ( words [ start : start + chunk_size ]) }) return chunks def extract_requirements ( pdf_path ): chunks = chunk_document ( pdf_path ) requirements = [] for chunk in chunks : prompt = f """ Extract technical requirements from: Page { chunk [ ' page ' ] } : { chunk [ ' text ' ] } Return JSON: {{ " requirements " : [{{ " type " : " retention " , " spec " : " 7 years " , " section " : " 7.3.2 " }}]}} """ result = call_llm_api ( prompt ) requirements . extend ( result . get ( " requirements " , [])) return requirements Enter fullscreen mode Exit fullscreen mode Output: [ { "type" : "retention" , "spec" : "7 years for financial records" , "section" : "7.3.2" , "page" : 45 }, { "type" : "retention" , "spec" : "3 years for operational logs" , "section" : "7.3.2" , "page" : 45 } ] Enter fullscreen mode Exit fullscreen mode Trade-off: more processing time and API costs. But went from 3 hours frustrated questioning to 20 minutes automated extraction. Research papers that took hours to read now take minutes with a Document Summarizer . What I'd Do Differently Starting over, I'd version everything. Git for prompts, not just code. Build logging first—wasted weeks re-discovering experiments. Test edge cases, not happy paths. The whitepaper examples are optimized demos. Automate diffs and treat model updates like schema migrations. This is still evolving. If you've hit similar workflow issues, drop a comment. -Leena:) 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 Leena Malhotra Follow Creator and strategist blending machine learning, business, and creativity. Harvard Business School ’06. Writing about AI, productivity, and building systems for a self-directed life. Location California, United states Education Harvard Business School Joined Jun 17, 2025 More from Leena Malhotra AI Explains Code Well Until the Moment Context Actually Matters # webdev # programming # ai Using AI in Production Code Without Creating Invisible Bugs # webdev # programming # ai Ship Faster, Break Less: My Rules for Using AI Safely in Codebases # webdev # programming # ai # coding 💎 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://svelte.dev/ | Svelte • Web development for the rest of us Skip to main content Docs Svelte SvelteKit CLI MCP Tutorial Packages Playground Blog Svelte web development for the rest of us get started attractively thin, graceful and stylish Svelte is a UI framework that uses a compiler to let you write breathtakingly concise components that do minimal work in the browser, using languages you already know — HTML, CSS and JavaScript. It’s a love letter to web development. But don’t take our word for it. Developers consistently rank Svelte as the framework they’re most excited about using. used by companies you’ve heard of Watch the full Svelte Origins documentary join our friendly community Our sister organisation, Svelte Society , organises events around the globe. Find your chapter and join us in our Discord server . Photos by Marcel Cutts Backed by Vercel and countless donors, developed by full-time and part-time maintainers, Svelte is here to stay. Rich-Harris Conduitry dummdidumm trueadm tanhauhau benmccann paoloricciuti PuruVJ baseballyama gtm-nayan Ocean-OS Swatinem DreaminDani 7nik jacwright lukeed mrkishi mindrones adiguba pngwn ngtr6788 navorite geoffrich ekhaled ignatiusmb EmilTholin antony elliott-with-the-longest-name-on-github dominikg tivac jches zxbodya btk5h PaulBGD halfnelson pushkine GarrettGeorge btakita brunnerh FWeinb TehShrike jamesbirtles colincasey evs-chris fcrozatier jacobmischka bluwy kaisermann Drips Datawrapper Vercel Cohere Dabble Monogram Frontend Masters GitHub Sponsors Hugging Face Threema Open Source Fund Pintura Codesmith xyflow - React Flow | Svelte Flow Raster Avast Jeff Moe INVISR Matt Sanity Metafy Changelog Kohei Yoshino WonderTax Labs Clancy Digital Kenoxa GmbH Level Up Tutorials The Pudding Jason Hetherington Zev Averbach Donovan Dikaio Bun multi n8n.io - n8n GmbH Evidence Hyunbin David Stevens 0+X Scott Spence Handsontable - JavaScript Data Grid Dong-won Jeffrey Lee Sentry Cain Voong Nicky Hajal Robert Balfre Dean Papastrat Cliff Johnson Emma Agering Tigris Data © 2026 Svelte contributors. Svelte is free and open source software released under the MIT license. | 2026-01-13T08:48:23 |
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https://dumb.dev.to/videos | Videos - DUMB 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 DUMB DEV Community Close DUMB DEV Community on Video Devoxx: Let’s use IntelliJ as a game engine, just because we can by Alexandros Chatzizacharias Scale YouTube 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 DUMB 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 . DUMB DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/when-not-to-use-Fine | When Not To Use Fine Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back When Not To Use Fine We love what Fine can do for developers, but just like any tool, there are moments when it’s not the right fit. Let’s dive into a few scenarios where you might want to go another route—and we’ll explain why Fine excels in different situations instead. 1. Just a Hobby Project? Code It Yourself If you’re building something purely for fun, a weekend hack, or a project to sharpen your skills, we say: dive in, get your hands dirty, and enjoy the process. Fine is designed for the hustling startups and the development teams who need efficiency—it’s not meant to take the joy out of tinkering with your code by yourself. We’re here for you when you’ve got deadlines to meet and products to ship. 2. The Issue Is Too Big? Break It Down Fine can’t magic away a mammoth problem. If your issue is huge and unwieldy, break it down into smaller, more manageable tasks. Different tickets can help Fine’s agents tackle each step effectively—just like development teams, it works best when each piece of the problem has its own space. 3. Debugging Ghost Bugs? Get Specific We’ve all been there: the bug that mysteriously appears and then vanishes without a trace. But debugging ghost bugs isn’t where Fine shines. It needs context to work with. Instead of just asking it to wave a magic wand, try giving it something concrete—like a Sentry issue—to serve as the foundation. The more specifics, the better! 4. Guidance Vague? You know what you want, but do you really, really want it? Fine needs clear instructions. When guidance is too vague, it’s a bit like trying to figure out what flavor of spice is missing from a dish without any hints. Make sure your request is specific, so Fine can do its best work—tell Fine what you want, what you really, really want. Fine’s power lies in helping developers and teams get through routine coding, manage PRs, and automate workflows seamlessly. If you’re looking to scale, streamline, or tackle the mundane so you can innovate—Fine’s got your back. But for personal projects, nebulous problems, or moments where details are sparse, keep in mind when Fine might not be the right partner. Ready to put Fine to work on what really matters? Let’s get building! Try Fine's free plan now to get a feel for it. When you're ready to upgrade, it's just $15 a month. 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 | 2026-01-13T08:48:23 |
https://dev.to/leena_malhotra/why-asking-for-better-outputs-misses-the-real-problem-29f9#what-id-do-differently | Why Asking for Better Outputs Misses the Real Problem - 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 Leena Malhotra Posted on Jan 12 Why Asking for Better Outputs Misses the Real Problem # programming # ai # imagegen # nanobanana Yesterday, I spent four hours debugging why Ideogram V3 kept generating inconsistent architectural renders. The whitepaper promised "improved spatial coherence." My outputs looked like they were designed by committee. This isn't a model problem. It's a workflow problem. When Ideogram V3's Whitepaper Met Reality I was building a pipeline to generate interior design variations for an e-commerce platform. The whitepaper showed beautiful examples of architectural spaces with perfect lighting. Here's the prompt I used from their examples: "Modern minimalist living room, floor-to-ceiling windows, natural light, Scandinavian furniture, architectural photography" Enter fullscreen mode Exit fullscreen mode First three generations: perfect. Fourth one: furniture floating off the ground. Fifth: window placement changed. By the tenth iteration, I had seven different room layouts. Same seed, same parameters, same model version. The issue wasn't randomness—it was me treating each generation as independent. The whitepaper examples worked because they were single, carefully-constructed prompts. I was running iterative experiments without maintaining state. The fix: class PromptContext : def __init__ ( self , base_intent ): self . base_intent = base_intent self . style_locks = {} def generate_with_memory ( self , variation ): locked = " " . join ([ f " { k } : { v } " for k , v in self . style_locks . items ()]) return f " { self . base_intent } . { locked } . { variation } " context = PromptContext ( " Modern minimalist living room " ) context . style_locks [ " windows " ] = " floor-to-ceiling on north wall " context . style_locks [ " floor " ] = " light oak hardwood " Enter fullscreen mode Exit fullscreen mode Cost: 40% more tokens per request. Benefit: went from 60% usable outputs to 95%. The whitepaper shows capability, not workflow. When you can test the same prompt across multiple AI models , the dissonance between documentation and reality becomes measurable rather than frustrating. SD3.5 Medium's Averaging Problem I needed product packaging concepts that felt "premium but approachable" for a beverage brand. The brief: Japanese minimalism meets 1970s American optimism. First attempt: { " prompt " : " Premium beverage packaging, minimalist, warm nostalgic colors, sophisticated " , " cfg_scale " : 7.5 , " sampler " : " DPM++ 2M Karras " } Enter fullscreen mode Exit fullscreen mode Result: generic wellness brand aesthetics. Technically perfect. Strategically useless. I ran 50 variations testing cfg_scale from 5.0 to 12.0: cfg_scale=5.0 → Lost brand identity cfg_scale=7.5 → Safe, averaged aesthetics cfg_scale=10.0 → Interesting tensions emerged cfg_scale=12.0 → Overcooked, but committed Enter fullscreen mode Exit fullscreen mode The fix: Stop describing the middle ground. Describe the extremes. prompt_a = " 1970s American optimism, warm oranges, rounded typography, sunburst graphics " prompt_b = " Japanese minimalism, white space, geometric precision " # Generate separately at cfg_scale=11.0 # Then synthesize specific elements Enter fullscreen mode Exit fullscreen mode SD3.5 Medium optimizes for "nothing broken" with vague targets. Give it contradictory specifics and higher CFG, and you get interesting failures to work with. Three unusable images and one brilliant image beats ten mediocre ones. Trade-off: 3x generation time. But revision time savings made it worth it. When Nano Banana PRO New Silently Changed Three-month-old content pipeline. Generated weekly newsletter summaries. Worked fine. One Monday: every output was 40% shorter and weirdly formal. Before (v1.2): 480 tokens, conversational. After (v1.3): 310 tokens, corporate. Release notes: "improved efficiency and coherence." No mention of temperature rescaling. The diff script I now run: def model_regression_test ( old_model , new_model , test_prompts ): results = [] for prompt in test_prompts : old_response = generate ( old_model , prompt , temp = 0.7 ) new_response = generate ( new_model , prompt , temp = 0.7 ) diff = { " length_delta " : len ( new_response ) - len ( old_response ), " formality_delta " : analyze_formality ( new_response ) - analyze_formality ( old_response ) } if abs ( diff [ " length_delta " ]) > 100 : print ( f " WARNING: Length shift " ) results . append ( diff ) return results Enter fullscreen mode Exit fullscreen mode The actual issue: they changed temperature scaling. temp=0.7 in v1.3 behaved like temp=0.4 in v1.2. My fix: pin model versions in production, regression test before upgrading. # requirements.txt nano-banana-pro==1.2.8 # Regression test before upgrade Enter fullscreen mode Exit fullscreen mode "Improved" means "different." Treat model updates like database migrations. Running parallel tests across Nano Banana PRO New and legacy versions reveals what release notes hide. The Context Switching Tax My workflow last month: Draft prompt in ChatGPT Test in Jupyter notebook Check results in Notion Discuss in Slack Update Google Doc Re-run notebook Forget step 1 decisions I was generating legal disclaimer variations. Each category needed specific regulatory language. I'd test in ChatGPT, worked great. Copy to notebook, different results. Thirty minutes debugging before realizing different model versions. The system I built: class ExperimentLog : def __init__ ( self ): self . conn = sqlite3 . connect ( " experiments.db " ) self . setup_db () def log ( self , model , prompt , params , output , success , notes = "" ): self . conn . execute ( """ INSERT INTO experiments (timestamp, model, prompt, parameters, output, success) VALUES (?, ?, ?, ?, ?, ?) """ , ( datetime . now (). isoformat (), model , prompt , json . dumps ( params ), output [: 500 ], success )) def get_successful_prompts ( self , model ): return self . conn . execute ( """ SELECT prompt, parameters FROM experiments WHERE model = ? AND success = 1 ORDER BY timestamp DESC """ , ( model ,)). fetchall () Enter fullscreen mode Exit fullscreen mode Now I search "legal disclaimers last week" and get exact parameters, model version, output. No re-discovering. Context switching isn't just a productivity tax—it fragments intent into micro-decisions scattered across tools. The Long Document Problem 140-page RFP. Needed specific technical requirements. Cross-references, tables, nested appendices. Tried: upload to ChatGPT, ask questions. Me: "What are data retention requirements in Section 7?" ChatGPT: "The document mentions retention in multiple sections..." Me: "No, I need specific retention periods." ChatGPT: "Based on the document, periods vary by type..." Enter fullscreen mode Exit fullscreen mode Summaries of summaries. Never the actual spec. The workflow: def chunk_document ( pdf_path , chunk_size = 4000 ): reader = pypdf . PdfReader ( pdf_path ) chunks = [] for i , page in enumerate ( reader . pages ): text = page . extract_text () words = text . split () for start in range ( 0 , len ( words ), chunk_size - 200 ): chunks . append ({ " page " : i + 1 , " text " : " " . join ( words [ start : start + chunk_size ]) }) return chunks def extract_requirements ( pdf_path ): chunks = chunk_document ( pdf_path ) requirements = [] for chunk in chunks : prompt = f """ Extract technical requirements from: Page { chunk [ ' page ' ] } : { chunk [ ' text ' ] } Return JSON: {{ " requirements " : [{{ " type " : " retention " , " spec " : " 7 years " , " section " : " 7.3.2 " }}]}} """ result = call_llm_api ( prompt ) requirements . extend ( result . get ( " requirements " , [])) return requirements Enter fullscreen mode Exit fullscreen mode Output: [ { "type" : "retention" , "spec" : "7 years for financial records" , "section" : "7.3.2" , "page" : 45 }, { "type" : "retention" , "spec" : "3 years for operational logs" , "section" : "7.3.2" , "page" : 45 } ] Enter fullscreen mode Exit fullscreen mode Trade-off: more processing time and API costs. But went from 3 hours frustrated questioning to 20 minutes automated extraction. Research papers that took hours to read now take minutes with a Document Summarizer . What I'd Do Differently Starting over, I'd version everything. Git for prompts, not just code. Build logging first—wasted weeks re-discovering experiments. Test edge cases, not happy paths. The whitepaper examples are optimized demos. Automate diffs and treat model updates like schema migrations. This is still evolving. If you've hit similar workflow issues, drop a comment. -Leena:) 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 Leena Malhotra Follow Creator and strategist blending machine learning, business, and creativity. Harvard Business School ’06. Writing about AI, productivity, and building systems for a self-directed life. Location California, United states Education Harvard Business School Joined Jun 17, 2025 More from Leena Malhotra AI Explains Code Well Until the Moment Context Actually Matters # webdev # programming # ai Using AI in Production Code Without Creating Invisible Bugs # webdev # programming # ai Ship Faster, Break Less: My Rules for Using AI Safely in Codebases # webdev # programming # ai # coding 💎 DEV Diamond Sponsors Thank you to our Diamond Sponsors for supporting the DEV Community Google AI is the official AI Model and Platform Partner of DEV Neon is the official database partner of DEV Algolia is the official search partner of DEV DEV Community — A space to discuss and keep up software development and manage your software career Home DEV++ Podcasts Videos DEV Education Tracks DEV Challenges DEV Help Advertise on DEV DEV Showcase About Contact Free Postgres Database Software comparisons Forem Shop Code of Conduct Privacy Policy Terms of Use Built on Forem — the open source software that powers DEV and other inclusive communities. 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https://www.next-element.com | Compassionate Accountability® by Next Element Open menu Contact Us Services Enterprise Solutions Certifications Custom Programs Partnerships Keynotes Approach Overview CA Resources Publications Overview Blog Podcast Books Publications and Appearances About Contact Us Services Approach CA Resources Publications About Search Enterprise Solutions Certifications Custom Programs Partnerships Keynotes Blog Podcast Books Publications and Appearances Search You don't have to choose between results and relationships. Compassionate Accountability® is the solution. Next Element is a global advisory firm and the originator of Compassionate Accountability. We help organizations build thriving cultures through assessment, consulting, coaching, training, and train-the-trainer services. How do you manage the tension between relationships and results? Find out now! “ I am inspired by the alignment between the core principles and message of Trust and Inspire Leadership and Compassionate Accountability. Stephen M.R. Covey NYT and WSJ #1 best-selling author, Speed of Trust and Trust and Inspire, CEO of Franklin-Covey Global Trust Practice “ Compassionate Accountability is the roadmap for building leadership cultures that attract and retain the best talent and provide a competitive advantage. Tacy M. Byham, PHD CEO, Development Dimensions International (DDI) and co-author of Your First Leadership Job “ The Compassionate Accountability approach has been a game-changer for executing in today’s fast past environment. Nicole Brusewitz, CUDE VP Leadership Development, Learning & Consulting, FCCS “ Compassionate Accountability is the leadership standard of the future. 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Garry Ridge The Culture Coach and Chairman Emeritus , WD-40 Company “ Compassionate Accountability is not another theory, but an actionable process for mindfulness, social and emotional intelligence, leadership agility, inclusion, presence, healthy conflict, and resiliency. Jeff Hayes Former President and CEO of The Myers-Briggs Company Are you ready for Compassionate Accountability? Do you want to build a culture where excellence is achieved, relationships are honored, and people love their work? Do you want to hold people accountable without compromising relationships and dignity? Do you want to leverage the energy of conflict as a catalyst for positive change instead of being drained by drama? Do you want to bring the benefits of Compassionate Accountability to the people you serve? Enterprise Solutions We equip your internal learning and development professionals with scalable solutions to spread Compassionate Accountability to all levels of your organization. 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https://www.suprsend.com/comparison-page/ooma-vs-karix-2024 | Comparing the Top Messaging Platforms (2025) Product FEATURES Template Engine Powerful template editors for all channels App Inbox Fully customizable inbox for your app & website Analytics Deep data insights on notification performance Logs Real-time notifications logs for all channels Smart Routing Reach users where they are Branding Seamlessly manage multi-brand customization Workflows Craft complex notification workflows Bifrost Run notifications natively on data warehouse Preferences Develop user focused notifications Integrations Integrate any channel and provider within mins Solutions BY USECASES Transactional Real-time alerts like authentication, activity updates Batching & Digest Aggregate multiple alerts into one Collaboration & Action Alerts on cross-user activity Scheduled Notifications One-time or recurring alerts like reminders Multi-tenant Alerts tailored to your customer's preferences Announcement / Newsletters Feature releases, achievements, product & policy updates Pricing Docs Customers Blog Login Get Started For Free Login Sign up Email management Comparing the Top Messaging Platforms (2025) Nikita Navral • December 2, 2025 TABLE OF CONTENTS Businesses rely on cloud communications platforms to power SMS alerts, authentication flows, customer engagement, and global voice calling. With so many options available, it’s important to understand how the major players differ in capabilities, pricing, and security. Below is a clear comparison of RingCentral, MessageBird, Plivo, Karix, Twilio, Sinch, Exotel, Telnyx, Ooma, Bandwidth, Gupshup, Vonage, and Amazon SNS - with key features, cost, and security included for each. Twilio Key Features: SMS/MMS, voice, WhatsApp, chat, email (SendGrid), video, global phone numbers, user authentication. Cost: Pay-as-you-go. US SMS ~ $0.0079 outbound; voice outbound ~ $0.014/min. SendGrid email plans start at $19.95/month. Security: HTTPS APIs, API key authentication, enterprise-grade controls depending on product. MessageBird (Bird) Key Features: SMS, WhatsApp, email, voice, multichannel inbox, 2FA/verify, omnichannel automation. Cost: US SMS ~ $0.008/message; WhatsApp from ~$0.005/message; dedicated numbers from ~$0.50/month. Security: ISO/IEC 27001:2013, SOC 2 Type II, GDPR-aligned, regulated under Dutch telecommunications authority. Plivo Key Features: SMS, MMS, voice APIs, WhatsApp, user verification APIs, Fraud Shield protection. Cost: US SMS ~ $0.0055/message; MMS ~ $0.018/message; plans also available starting around $25/month. Security: Fraud Shield for SMS fraud, standard API security, compliance frameworks appropriate for telecom workflows. Sinch Key Features: Global messaging, voice APIs, phone number provisioning, enterprise conversational tools, in-app voice/video SDKs. Cost: Pay-as-you-go; pricing varies by region and channel. Security: Enterprise security posture; used widely by large regulated businesses. RingCentral Key Features: Enterprise UCaaS and CCaaS — voice, video, messaging, contact center, team collaboration. Cost: Subscription-based; varies by seat and plan tier. Security: 99.999% uptime SLA, enterprise compliance standards, secure global network. Vonage Key Features: Business phone systems, unified communications, plus APIs for voice, SMS, video, messaging. Cost: Varies by product; SMS and voice pricing similar to other CPaaS players. Security: Industry-standard certifications (ISO 27001, HIPAA support in certain offerings). Bandwidth Key Features: Voice, messaging, emergency services APIs built on its own carrier network. Cost: Usage-based; typically competitive because Bandwidth owns telecom infrastructure. Security: Strong network-level security due to owning carrier backbone; enterprise-grade controls. Telnyx Key Features: Programmable voice, SMS, SIP trunking, wireless IoT, phone numbers; operates its own global private network. Cost: Generally lower than Twilio in many regions; usage-based for SMS/voice. Security: Private global network architecture, encrypted communications, strong compliance posture. Karix Key Features: SMS, voice, WhatsApp, and multichannel messaging, with strong performance in India/APAC. Cost: Pricing varies by region and volume; typically optimized for India and emerging markets. Security: Regional telecom compliance; enterprise messaging security standards. Exotel Key Features: Cloud telephony, IVR, virtual numbers, call routing, contact-center tools, SMS, WhatsApp. Cost: Region-based pricing; popular for cost-effective India/SEA deployments. Security: Telecom-grade compliance in India, SEA, and Middle East markets. Gupshup Key Features: SMS, WhatsApp, RCS, conversational messaging, bot frameworks, commerce and marketing flows. Cost: Pricing varies by channel and country; optimized for India, LATAM, and emerging markets. Security: Regional compliance and enterprise-grade security for messaging workflows. Ooma Key Features: SMB VoIP phone systems, virtual receptionist, call routing, basic business telephony. Cost: Subscription-based; lower-cost than enterprise UCaaS providers. Security: Standard SMB business-telephony protections; not CPaaS-level programmability. Amazon SNS Key Features: Pub/Sub messaging, SMS notifications, push notifications, email; part of AWS event-driven architecture. Cost: Pay-as-you-go based on notifications sent; AWS regional SMS pricing applies. Security: Inherits AWS IAM, encryption, compliance, monitoring, and infrastructure security. Which Platform Fits Which Use Case? If you want developer APIs to build custom communication flows: Twilio, Plivo, Telnyx, Bandwidth. If you need enterprise communication suites for internal teams: RingCentral, Vonage, Ooma for SMBs. If global omnichannel messaging is key: MessageBird, Sinch, Gupshup, Karix, Exotel. If you’re on AWS and only need notifications: Amazon SNS. Conclusion Each provider has unique strengths: some excel at global messaging, others at enterprise unified communications, others at developer-centric programmability. Understanding key features, pricing, and security posture helps narrow down the best fit for your product, geography, and scale. Share this blog on: Written by: Nikita Navral Co-Founder, SuprSend Implement a powerful stack for your notifications Get Started For Free Book Demo Company About us Signup Login Integrations Pricing Security Privacy Terms Contact Us Support SuprSend for Startups API Status Sign Up Channels Email SMS Notification Inbox Android Push iOS Push Web Push Xiaomi Push Whatsapp SDK Python SDK Node.js SDK Java SDK Android SDK React Native SDK iOS SDK Flutter SDK Go SDK Resources Documentation Changelog Blogs Write for us SMTP Error Codes SMS Providers Comparisons Email Providers Comparisons SMS Providers Alternatives Join us on Slack We are building a community of developers and product builders from across the globe to make notifications a pleasant experience. © 2025 All rights reserved. SuprStack Inc. By clicking “Accept All Cookies” , you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. 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https://www.fine.dev/blog/o1-vs-sonnet-fr | OpenAI o1 vs. Claude Sonnet 3.5 : Quel modèle d'IA est le meilleur pour coder ? Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back OpenAI o1 vs. Claude Sonnet 3.5 : Quel modèle d'IA est le meilleur pour coder ? Introduction À mesure que l'IA continue d'évoluer, deux modèles se démarquent : o1 d'OpenAI et Claude Sonnet 3.5 d'Anthropic. Tous deux offrent des capacités impressionnantes pour les développeurs de logiciels, mais leurs forces varient, notamment en matière de codage. Ce blog compare ces deux modèles d'IA, en se concentrant sur les tâches de codage et la performance générale. Fine inclut un accès illimité aux deux modèles, ce qui en fait un excellent moyen de tester et de comparer comment o1 et Sonnet se comportent avec les tâches de codage. Différences fondamentales o1 est conçu pour le raisonnement complexe et la résolution de problèmes . Ses réponses sont profondes et réfléchies, ce qui le rend idéal pour les développeurs travaillant sur des problèmes complexes ou nécessitant des explications détaillées. D'autre part, Claude Sonnet 3.5 se concentre sur l'efficacité et la rapidité , excellant dans les temps de réponse rapides tout en étant plus rentable. Si vous cherchez à générer rapidement du code ou à gérer des tâches à haut volume, Claude Sonnet 3.5 peut être la meilleure option. Les deux modèles utilisent des architectures basées sur des transformateurs, mais o1 est plus adapté aux développeurs recherchant un raisonnement détaillé, tandis que Claude Sonnet 3.5 est le choix privilégié pour ceux qui privilégient la rapidité. Fenêtre de contexte et performance La fenêtre de contexte joue un rôle crucial dans la manière dont ces modèles gèrent les grandes entrées ou les conversations prolongées. ChatGPT o1 prend en charge 128 000 tokens, tandis que Claude Sonnet 3.5 gère un plus grand nombre de 200 000 tokens , lui donnant un avantage pour les tâches nécessitant une rétention de contexte significative, comme l'examen de grands bases de code. Les deux modèles offrent de solides performances dans une gamme de tâches, mais leurs capacités brillent dans différents domaines. ChatGPT o1 excelle dans le raisonnement en plusieurs étapes , expliquant en détail la logique de code complexe, tandis que Claude Sonnet 3.5 se concentre sur des corrections de bugs rapides et efficaces et la génération de code. Version améliorée de Claude 3.5 Sonnet - Octobre 2024 - Claude est-il maintenant meilleur que GPT pour le codage ? En octobre 2024, Anthropic a annoncé une version améliorée de Claude 3.5 Sonnet. Les récentes mises à jour de Claude 3.5 Sonnet ont considérablement amélioré ses capacités en ingénierie logicielle. Notamment, la performance du modèle sur le benchmark SWE-bench Verified est passée de 33,4 % à 49,0 %, surpassant tous les modèles disponibles publiquement, y compris l'o1-preview d'OpenAI. Cette avancée reflète l'amélioration de l'exactitude de Claude 3.5 Sonnet dans la génération de fonctions et la vérification des erreurs, notamment dans le débogage et le refactoring de code impliquant des fonctions imbriquées ou des segments interdépendants. De plus, la capacité de tokens élargie du modèle lui permet de conserver et d'utiliser un contexte plus étendu, ce qui le rend idéal pour l'examen de grands bases de code ou la gestion de projets complexes avec de multiples dépendances. Les premiers tests indiquent que Claude 3.5 Sonnet excelle dans les tâches de codage spécialisées, telles que l'identification des vulnérabilités de sécurité dans les applications web et l'optimisation des algorithmes pour la vitesse et l'efficacité. GitLab, par exemple, a signalé une amélioration allant jusqu'à 10 % des capacités de raisonnement pour les tâches DevSecOps avec le modèle mis à jour, sans augmentation de la latence. Cas d'utilisation de l'IA pour le codage avec o1 et Claude Sonnet 3.5 ChatGPT o1 : Débogage de la gestion d'état complexe de React : Utilisez o1 pour analyser en profondeur pourquoi certains états ne se mettent pas à jour correctement ou entrent en conflit entre les composants. Refactoring de code hérité : Employez le raisonnement approfondi de o1 pour restructurer un ancien script Python pour la lisibilité et la maintenabilité. Création d'algorithmes : Idéal pour écrire et expliquer des algorithmes comme le tri, le parcours d'arbres ou la programmation dynamique en détail. Claude Sonnet 3.5 : Génération de code standard : Créez rapidement des fichiers de configuration pour de nouveaux projets comme des API Flask ou des structures front-end dans Next.js. Auto-complétion de fonctions : Utilisez-le pour compléter une fonction JavaScript à moitié écrite avec une gestion appropriée des erreurs et des cas limites. Génération de code en masse : Sonnet 3.5 excelle dans la production de structures de code répétitives mais légèrement variées comme des points de terminaison API similaires ou des cas de test unitaires. Quels modèles d'IA utilisent les différents outils de codage IA ? Il existe aujourd'hui de nombreux outils de développement pour vous aider dans votre codage IA, des assistants de codage IA avancés tels que Fine aux générateurs de code tels que GitHub Copilot. Certains utilisent plusieurs LLM, certains vous laissent le choix et d'autres sont basés sur un seul modèle. Quel modèle d'IA (LLM) utilise Fine ? Fine est l'un des rares outils de codage IA à offrir aux utilisateurs le choix entre différents LLM pour diverses tâches. Lors de l'utilisation de Fine via le navigateur web, les utilisateurs peuvent choisir entre o1-preview, 4o et Claude 3.5 Sonnet. Vous aurez besoin d'un abonnement pro pour profiter de cela cependant, qui coûte 13-15 $ par mois. Si vous êtes un utilisateur gratuit, vous pourrez utiliser Fine avec 4o. Cliquez ici pour l'essayer. Quel modèle d'IA (LLM) utilise GitHub Copilot ? GitHub Copilot est fortement intégré à OpenAI. GitHub appartient à Microsoft qui a un partenariat profond avec OpenAI. La plupart des utilisateurs ont accès à 4o, tandis que les abonnés Azure AI peuvent être en mesure d'utiliser GitHub Copilot avec o1-mini et o1-preview. MISE À JOUR : Lors de GitHub Universe 2024, il a été annoncé que ce partenariat exclusif n'était plus si exclusif et que l'option d'utiliser Claude serait bientôt déployée pour tous les utilisateurs de GitHub Copilot. Certains utilisateurs ont déjà pu accéder à Claude. Il est disponible dans le Chat Copilot dans Visual Studio Code et Immersive Copilot dans le navigateur web uniquement. Quel modèle d'IA (LLM) utilise Cursor ? Cursor utilise Claude 3.5 Sonnet par défaut et replie sur OpenAI 4o lors des pannes d'Anthropic. Quel modèle d'IA (LLM) utilise Bolt ? Bolt, l'outil de codage IA qui se spécialise exclusivement dans le front-end, repose sur Claude 3.5 Sonnet. Quel modèle d'IA (LLM) utilise Replit ? Bien que Replit ait précédemment publié son propre modèle d'IA en 2023, lorsqu'ils ont annoncé Replit Agent, leur principal outil de codage IA, en 2024, il semble qu'ils aient pris la décision d'utiliser Claude 3.5 Sonnet. Comment comparer les différents outils de codage IA et LLM ? Si vous cherchez à comparer quels sont les meilleurs outils de codage IA ou LLM, il y a quelques éléments à garder à l'esprit. Tout d'abord, il est important d'évaluer le LLM et l'outil séparément. Utilisez un outil comme Fine qui vous permet de donner la même tâche à plusieurs LLM pour comparer lequel vous donne le meilleur résultat. Voici une comparaison que nous avons faite des trois modèles proposés par Fine, posée avec la même question : Que fait ce dépôt ? (C'est une question que certains appellent le Hello World du codage IA). Deuxièmement, comparez comment les outils fonctionnent avec votre LLM choisi, spécifique à votre cas d'utilisation. Fine offre une variété d'intégrations pour booster votre productivité, comme la possibilité de faire des révisions à l'intérieur de GitHub PR, qui font gagner des heures chaque semaine aux développeurs. Quel modèle est le meilleur pour coder ? Pour les tâches de codage, votre choix dépend de vos besoins : ChatGPT o1 est la meilleure option lorsque vous travaillez sur des problèmes complexes et multistes où vous avez besoin d'un raisonnement approfondi et d'explications détaillées. Par exemple, il excelle dans l'explication de code complexe ou l'assistance au débogage de manière plus réfléchie. Claude Sonnet 3.5 est le modèle de référence pour la génération de code rapide et efficace et le prototypage itératif. Il est rentable pour les tâches à haut volume comme la génération de plusieurs extraits de code ou l'automatisation des corrections de bugs. Les deux modèles soutiennent les développeurs dans le codage, mais Claude Sonnet 3.5 peut faire gagner du temps et de l'argent pour les tâches de codage quotidiennes, tandis que ChatGPT o1 pourrait être votre allié pour les problèmes de codage plus difficiles et détaillés. Conclusion Lorsqu'il s'agit de choisir entre ChatGPT o1 et Claude Sonnet 3.5 , considérez la complexité de vos tâches de codage et vos contraintes budgétaires. ChatGPT o1 offre une meilleure résolution de problèmes pour les tâches complexes, tandis que Claude Sonnet 3.5 fournit une génération de code plus rapide et plus abordable pour les besoins de développement quotidiens. Les deux modèles sont des outils d'IA puissants qui peuvent améliorer considérablement votre productivité en tant que développeur de logiciels. Inscrivez-vous à une plateforme comme Fine , qui inclut un accès illimité aux deux, pour le meilleur des deux mondes sans surpayer. Pourquoi s'abonner à Fine ? Fine est une plateforme qui offre un accès illimité à la fois à o1 et à Claude Sonnet 3.5 , permettant aux développeurs de passer d'un LLM puissant à l'autre en fonction de leurs besoins de tâche. Cette flexibilité est parfaite pour ceux qui nécessitent des explications détaillées de ChatGPT ou une génération de code rapide et efficace de Claude. Avec Fine, il n'est pas nécessaire de gérer vos propres clés API ou de vous soucier des limites d'utilisation - tout est inclus. S'abonner à Fine simplifie le processus, offrant un accès illimité et rentable aux deux modèles pour toutes vos tâches de codage et de développement. Sources McNulty, Niall. "ChatGPT o1 vs Claude Sonnet 3.5." Medium , il y a 5 jours. Lien . "GPT o1 vs Claude 3.5 Sonnet : Quel modèle est le meilleur pour coder ?" Bind AI Blog , 17 Sep 2024. Lien . "Comparez o1 Preview vs. Claude 3.5 Sonnet." Context.ai . Lien . Harisec. "o1 vs Claude." GitHub . Lien . Table des matières Introduction Différences fondamentales Fenêtre de contexte et performance Version améliorée de Claude 3.5 Sonnet - Octobre 2024 - Claude est-il maintenant meilleur que GPT pour le codage ? Cas d'utilisation de l'IA pour le codage avec o1 et Claude Sonnet 3.5 Quels modèles d'IA utilisent les différents outils de codage IA ? Fine GitHub Copilot Cursor Bolt Replit Comment comparer les différents outils de codage IA et LLM ? Quel modèle est le meilleur pour coder ? Conclusion Pourquoi s'abonner à Fine 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 | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/mcp-vs-a2a | MCP vs A2A: Model Context Protocol and Agent-to-Agent Communication in AI App Development Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back MCP vs A2A: Model Context Protocol and Agent-to-Agent Communication in AI App Development Developers building AI applications are encountering two new paradigms that make AI agents more powerful and flexible: Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication . These technologies tackle different challenges in modern LLM app architecture – one focuses on giving a single AI model structured access to external tools and data, while the other enables multiple AI agents to communicate and collaborate. In this post, we’ll explain what MCP and A2A are, how they differ, and how you can leverage both to create smarter AI agents. By the end, you’ll understand why MCP is like a “universal adapter” for AI tools and data, and A2A is like a “common language” for multi-agent systems. What is Model Context Protocol (MCP)? Model Context Protocol (MCP) is an open standard that defines how AI models (especially large language models) can receive external context, such as data from databases, files, APIs, or other tools, in a structured, unified way ( modelcontextprotocol.io ). In simpler terms, MCP is a protocol for plugging your AI agent into various information sources and services without custom hacks for each one. Think of MCP like a USB-C port for AI applications – just as USB-C standardizes how devices connect to peripherals, MCP provides a standardized way for AI models to connect to different data sources and tools. This means instead of writing custom integration code every time your AI assistant needs to fetch data from a new source, you use MCP as a universal interface. MCP was originally introduced by Anthropic (the company behind Claude) and has since been adopted by the broader AI community as a neutral standard ( dev.to ). It addresses a big pain point: historically, every time you wanted an AI model to access some external knowledge or perform an action (like look up a document, query a database, or call an API), you had to wire it up with bespoke code. Each integration was one-off and fragile, resulting in “fragmented integrations” across different tools. MCP simplifies developers’ lives by replacing those fragmented, custom connectors with one consistent protocol. As one article puts it, “MCP acts as a universal adapter, enabling LLMs to access real-world data and perform actions in a consistent and scalable manner . It promotes AI tools interoperability – your model can use a growing library of pre-built MCP connectors instead of reinventing the wheel for each tool. How does MCP work? At a high level, MCP follows a client-server design. An AI application (the MCP client ) can connect to one or more MCP servers . Each MCP server exposes a specific data source or capability through the standard protocol. For example, one MCP server might expose a company database, another might provide a web search function, and another could connect to an email API. The AI model (through the client) sends a query or request via MCP to the appropriate server, and the server returns the result or performs the action. All of this communication follows the MCP specification (using standard formats and authentication), so from the AI’s perspective, using a new tool is as straightforward as connecting a new USB device. Developers have already built MCP servers for tools like Google Drive, Slack, GitHub, and databases, so AI agents can “plug in” quickly ( anthropic.com , dev.to ). Crucially, MCP is vendor-agnostic – it’s an open protocol, not tied to one AI provider – so you can use it with different LLMs and platforms interchangeably. MCP in action: Imagine you’re building a customer support AI assistant. Without MCP, you would have to manually code how the assistant fetches order data from your database, retrieves the latest shipping status from an API, and pulls product information from a knowledge base. With MCP, you could set up standardized connectors for each of these data sources (database, shipping API, knowledge base) and your AI model can query them on the fly with a unified approach. The model might ask the “Orders” MCP server for details of order #12345, instead of you having to hardcode a SQL query – the MCP server handles it and returns structured data. This makes the AI more context-aware and powerful, since it can tap into live information securely and seamlessly. In short, MCP gives a single AI agent a toolbox of capabilities that are easy to add or remove. If you switch your database or add a new data source tomorrow, as long as there’s an MCP server for it, your AI can access it without requiring significant code changes. What is Agent-to-Agent (A2A) Communication? While MCP equips one AI agent with tools and data, Agent-to-Agent (A2A) communication involves multiple AI agents communicating with each other. A2A is an open protocol, recently introduced by an industry consortium led by Google, that allows AI agents to communicate, exchange information, and coordinate actions through a standardized messaging format ( developers.googleblog.com ). In essence, A2A provides AI agents with a common language or messaging protocol, allowing agents from one vendor or framework to interact with agents from another, much like how one web service can communicate with another via HTTP. Developers have described A2A as “the AI equivalent of HTTP” — a universal protocol that lets any agent talk to any other agent without custom translation layers ( medium.com ). Why A2A, and what problem does it solve? As AI systems become more sophisticated, there’s a growing trend toward multi-agent systems – instead of one monolithic AI trying to do everything, you have a team of specialized AI agents, each handling a part of the task. For example, you might have one agent that specializes in planning, another in retrieving information, another in performing calculations, and another in writing the final answer. This specialization can outperform a single generalist model, much like a team of experts can be more effective than a single jack-of-all-trades. However, until recently, if you wanted these agents to work together, you had to cobble together custom integrations: one agent might call another via an API with a unique format, and you’d need glue code to translate outputs to inputs across agents. It quickly becomes a spaghetti mess of adapters, as one engineer lamented – without a standard, “every connection between agents requires custom code” and adding new agents multiplies complexity. A2A was created to eliminate that headache by providing a standard way for agents to interact . Google’s A2A protocol (announced April 2025) emerged from this need for interoperability. It launched with support from over 50 tech partners (including enterprise software companies and AI frameworks like LangChain) to ensure it’s broadly useful ( developers.googleblog.com ). A2A defines how agents should format messages, how to handle dialogues or threads, how to advertise their capabilities to each other, and how to do error handling – so that any A2A-compliant agent can plug into a conversation with another. In practical terms, this means you could have an OpenAI-powered agent, an Anthropic Claude agent, and your own custom Python agent all seamlessly exchange tasks and data if they speak A2A. They would send each other messages (like JSON requests/responses under the hood, following the protocol spec) rather than, say, one having to be hard-coded as a “tool” of the other. Think of A2A as giving AI agents a shared communication bus . It allows for a dynamic, modular system of AIs. Using a friendly analogy: A2A is like the social network or a chatroom for AI agents – it lets them “friend” each other and have conversations to collaborate on problems ( medium.com ). For example, imagine your calendar AI automatically coordinating with your travel AI to reschedule meetings when a flight is delayed . In an A2A-enabled world, your “Calendar Agent” can send a message to your “Travel Agent” saying, “My flight got delayed, can you find a later connecting flight and update the schedule?” The travel agent understands the request and replies with the new itinerary. The calendar agent then updates your schedule. All of this can happen through standardized A2A messages, without requiring both agents to be built on the same platform or explicitly coded to communicate with each other in a bespoke way. They simply adhere to the A2A protocol, much like two computers follow the same network protocol to exchange data. Multi-agent examples: Google has demonstrated an Agent Development Kit (ADK) that utilizes the A2A model to orchestrate multiple agents collaborating on a task. Instead of one LLM doing everything, you might have a team of agents with distinct roles ( gyliu513.medium.com ). For example, you could split a complex task as follows: PlannerAgent – breaks down the overall task into sub-tasks. ToolAgent – fetches information or processes data as needed (e.g. calls MCP tools or APIs for data). WriterAgent – crafts the final response or output based on inputs. ReviewerAgent – evaluates and refines the output for quality. Each of these agents is an independent entity, possibly running on different systems or models, and they communicate via A2A messages to coordinate. The Planner might message the ToolAgent saying “I need data on X,” The ToolAgent returns the data, the WriterAgent asks the Planner for clarification on the structure, and so on. Because A2A standardizes the format of these messages (text content, function call requests, etc.), the development focus shifts to the logic of each agent rather than the plumbing of how they talk. This modular, message-passing approach makes the whole system more maintainable and extensible. You can add a new agent (say, a TranslatorAgent) later without breaking the others – as long as it speaks A2A, it can join the conversation. In summary, A2A enables multi-agent systems where collaboration is as straightforward as calling a function, except the “function” might be another intelligent agent on the network. MCP vs A2A: Key Differences and Roles It’s clear that MCP and A2A serve different purposes in an AI system. To put it succinctly, MCP is about connecting an AI agent to external tools/data in a structured way, whereas A2A is about connecting AI agents in a standardized way. They operate at different layers of your AI app architecture. Here’s a breakdown of their key differences: Focus and Scope: MCP is focused on a single agent’s context . It standardizes how one AI model can pull in information or actions from external sources (files, databases, APIs, etc.). A2A is focused on multi-agent interaction – it enables two or more independent AI agents to communicate and coordinate as a team. If MCP is equipping one agent with all the info it needs, A2A is enabling a society of agents to divide and conquer tasks. Communication Style: With MCP, the communication is typically between an AI agent and a tool/service (client-to-server). The agent sends a query via MCP and gets back a result. It’s a structured, often transactional exchange (much like a function call: query -> result). In A2A, the communication is agent-to-agent dialog. Agents send each other messages, which could be questions, commands, or data. This is more conversational and dynamic. One agent’s output becomes another agent’s input, and they may have back-and-forth exchanges to reach a goal. Role in System Architecture: MCP acts as the “tool/plugin interface” for an AI model. It ensures the model can access whatever external resources it needs uniformly (hence being called a “universal adapter” for tools). A2A acts as the “coordination layer” for multi-agent systems – a kind of message bus that any agent can plug into to talk with others. You can think of MCP as extending an agent’s capabilities vertically (connecting it deeper into data sources), whereas A2A extends capabilities horizontally (connecting it across to other agents). Analogy (Toolbox vs. Team): Using a builder-friendly analogy, MCP is like giving one master craftsman AI a fully stocked toolbox . Our single AI agent can use its hammer, screwdriver, and drills (various MCP-connected tools and data) as needed to build a solution. In contrast, A2A is like having a team of specialist AI co-workers who speak the same language. Instead of one AI doing everything, you have the planner, the carpenter, the electrician, and the painter all chatting in a common channel to build a house together. One approach isn’t “better” than the other – they’re just different paradigms. A lone genius with great tools (MCP) might solve straightforward tasks efficiently, whereas a coordinated team (A2A) might tackle more complex, multifaceted projects. Example Use Cases: If your goal is to build an AI assistant that can retrieve information from various sources and present an answer, you might lean heavily on MCP – e.g. a single Q&A agent that uses MCP to fetch answers from a docs database and a weather API. If your goal is to build an AI system that handles a process end-to-end (say, an AI that plans an event: budgeting, venue booking, scheduling, and invites), you might design it as multiple agents using A2A – one agent handles budget calculations, another searches venues, another schedules, and they pass information via A2A. In many real-world scenarios, you will use both : for instance, each specialized agent in a multi-agent system might use MCP to access its tools (a Research Agent using MCP to query databases, etc.), and then the agents coordinate via A2A messages. It’s important to note that MCP and A2A are complementary rather than competing. Google’s announcement explicitly states that *“A2A is an open protocol that complements Anthropic’s Model Context Protocol (MCP), which provides helpful tools and context to agents”*. MCP provides the mechanism for an agent to pull in data and execute actions, while A2A offers the mechanism for agents to share results and delegate tasks among themselves. Used together, they enable an architecture where each agent is both well-informed (thanks to MCP) and well-coordinated (thanks to A2A). Figure: Example workflows for MCP vs A2A. In the MCP workflow (bottom dashed box), a single AI agent queries two external tools/data sources via a standardized MCP interface and receives results (dashed arrows) it can use. In the A2A workflow (top dashed box), multiple AI agents (A, B, C) communicate by sending messages to each other using the A2A protocol (double-headed arrows), enabling them to collaborate on a task. MCP focuses on connecting an agent to context, whereas A2A focuses on connecting agents. Using MCP and A2A Together in AI Applications Now that we’ve differentiated MCP and A2A, you might wonder which paradigm to use for your own AI application. The truth is, you don’t have to choose one or the other – you can and often should use both, depending on what your AI app needs to do. MCP and A2A fit into different layers of an AI app’s architecture, and together they form a powerful stack for building robust AI systems. If you’re just starting out building an AI-powered app , a practical approach is to begin with a single capable agent and use MCP to give it the external knowledge and abilities it needs. For example, you might prototype a coding assistant that uses MCP to access a GitHub repo, a documentation database, and a Stack Overflow search. This single agent can be quite powerful with the right context plugged in. MCP will make it easier to swap in better data sources or additional tools as your app grows, without requiring you to rewrite your core logic. It essentially future-proofs your agent’s connectivity by decoupling the what (the data/tool needed) from the how (the integration details). Many developers are excited about MCP because it fosters an ecosystem of reusable connectors – you can build or use an existing MCP server for, say, Slack or Jira, and then any of your AI agents can leverage that connector with minimal effort. As your application or ambitions expand, you might find that a multi-agent approach becomes beneficial. That’s where you’d introduce A2A communication. Perhaps your initial single agent is getting overloaded trying to handle too many concerns, or you identify distinct subtasks that could be handled in parallel or by specialized logic. You can then refactor your system into multiple agents that communicate via A2A. Continuing the example, you might split your coding assistant into a “Planning Agent” that breaks down a coding task, a “Coding Agent” that writes code (using the GitHub MCP connection), and a “Testing Agent” that runs tests. These agents would talk to each other via A2A – the Planning agent might delegate writing to the Coding agent, then ask the Testing agent to verify the output, and so on. By doing this, you’ve made your system more modular and scalable. Each agent can be developed and improved independently, and as long as they stick to the A2A protocol, they can plug-and-play with each other. In the long term, this modular architecture can save a lot of development time. One case study noted that using a standardized agent communication protocol drastically cut down the “plumbing” code – developers spend less time writing glue and more time on actual logic. Another advantage of combining both paradigms is the flexibility and innovation they offer. MCP gives your agents easy access to new capabilities, and A2A gives you the freedom to bring in new agents, such as those provided by third-party services or open-source communities, into your system. Because both MCP and A2A are open standards with broad support, you’re not locked into a single vendor’s ecosystem. You could use an OpenAI model as one agent, an open-source LLM as another agent, and tools from various providers, all in one coherent system. This interoperability is by design: A2A was developed with the vision of agents from different vendors interoperating seamlessly, and MCP was designed to be an open “USB-C” standard usable by anyone. As a builder, this means you can mix and match the best components for the job at hand. Finally, consider the complexity of your problem when deciding how to architect it. If a problem domain is well-bounded and can be handled by one agent just pulling in some extra data (for example, “answer questions about our company’s policies” can be mostly solved by one QA agent that uses MCP to read policy documents), then a single-agent-with-MCP solution might suffice. If a problem naturally breaks into stages or requires different expertise (for example, “analyze this data, generate a report, and then draft emails to stakeholders about the findings” – which entails data analysis, report writing, and communication steps), an A2A multi-agent design makes a lot of sense, possibly with MCP in each stage for specific tools. You might start with one approach and evolve to the other as you scale. The good news is that since MCP and A2A complement each other, you can incrementally add one to an existing system using the other. Your single MCP-augmented agent can later become the coordinator agent in an A2A system, or vice versa, your multi-agent system can have each agent enhanced with MCP access to relevant data. Conclusion: Empowering AI Agents with the Right Paradigms The emergence of Model Context Protocol and Agent-to-Agent communication is an exciting development for AI builders. These paradigms are unlocking new levels of capability in AI agents by addressing two key aspects of the AI app equation: knowledge and tools, as well as collaboration . MCP ensures an AI model is not working in a vacuum – it can be fed rich context and perform actions in the real world through a standardized interface. A2A ensures an AI agent is not working alone – it can coordinate with other agents in a common language to tackle complex tasks together. Whether you choose to equip one AI agent with a world of tools (MCP) or orchestrate a team of AI agents in concert (A2A) – or both – will depend on your project’s needs. Often, the most powerful solutions will combine these approaches, allowing each agent in a multi-agent system to be both well-equipped and well-coordinated. In all cases, adopting these open protocols can save you time and effort. Developers are no longer spending 80% of their time building ad-hoc plumbing between models and services – MCP and A2A provide robust highways for data and messages. This lets you focus on the creative part of building AI applications, rather than the boilerplate. We encourage you, as a builder, to explore both MCP and A2A as you design your next AI app architecture. Try adding an MCP integration to give your AI new powers, or spin up a second agent and use A2A to have it collaborate with the first. You may discover that many problems become easier to solve when your AI agents can both pull in the right context and work in tandem with others . The field of AI is moving fast, and these paradigms ensure you can keep up by composing systems in a scalable way. Much like interchangeable parts and communication protocols revolutionized traditional software, MCP and A2A are poised to revolutionize how we build AI systems – making them more modular, interoperable, and powerful. It’s a thrilling time to innovate. So plug in that context, open up those communication channels, and see what your AI agents can achieve. With MCP and A2A in your toolkit, the possibilities for LLM app architecture and multi-agent systems are vast. Happy building! References: Anthropic, Introducing the Model Context Protocol (MCP) – Anthropic News (Nov 2024) anthropic.com anthropic.com . ModelContextProtocol.io, MCP Introduction – Official MCP Docs modelcontextprotocol.io . P. Belagatti, Model Context Protocol (MCP): 8 MCP Servers Every Developer Should Try! – Dev.to (Apr 2025) dev.to . Google Developers Blog, Announcing the Agent2Agent (A2A) Protocol (Apr 2025) developers.googleblog.com . M. Desai, Meet Google A2A: The Protocol That Will Revolutionize Multi-Agent AI Systems – Medium (Apr 2025) medium.com . M. Desai, The Power Duo: How A2A + MCP Let You Build Practical AI Systems Today – Medium (Apr 2025) medium.com . G. Liu, Building Modular AI Agents with Google ADK and MCP – Medium (Apr 2025) gyliu513.medium.com . 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 | 2026-01-13T08:48:23 |
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https://www.fine.dev/blog/replit-vs-cursor-fr | Replit vs Cursor : Quel outil de codage IA est le meilleur pour vous ? Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Replit vs Cursor : Quel outil de codage IA est le meilleur pour vous ? Les outils de codage alimentés par l'IA gagnent du terrain dans le monde du développement, facilitant l'écriture, le débogage et la gestion du code pour les développeurs. Trois des principales plateformes dans cet espace sont Fine, Replit et Cursor, offrant toutes des fonctionnalités de codage assistées par l'IA. Cependant, avec ces avancées viennent des différences clés qui rendent chaque plateforme plus adaptée à différents types de développeurs. Dans ce blog, nous allons décomposer Replit et Cursor, examiner leurs similitudes et différences, et expliquer pourquoi Fine est une alternative supérieure. Table des matières Introduction à Replit Introduction à Cursor Similitudes entre Replit et Cursor Différences entre Replit et Cursor Pourquoi choisir Cursor plutôt que Replit Pourquoi choisir Replit plutôt que Cursor Pourquoi Fine est un meilleur choix Introduction à Replit Replit est un environnement de développement intégré (IDE) basé sur le navigateur qui a récemment lancé des fonctionnalités alimentées par l'IA, offrant l'autocomplétion, le débogage et la génération de documentation. Conçu pour rendre le codage accessible aux débutants comme aux professionnels, Replit offre des capacités de collaboration en temps réel, ce qui en fait un incontournable pour les projets d'équipe ou les fins éducatives. Il permet aux développeurs d'écrire rapidement du code, de générer des tests et de configurer des API sans configurations complexes. Avec son large support pour plusieurs langages de programmation, Replit est un choix flexible pour des tâches de codage variées. Introduction à Cursor Cursor est un éditeur de code alimenté par l'IA qui a été construit comme un fork de l'IDE populaire, VSCode. Il offre une complétion de code avancée, un refactoring de code intelligent et une édition en langage naturel. Cursor met également l'accent sur la sécurité, avec une certification SOC 2, ce qui le rend adapté aux équipes nécessitant une stricte confidentialité des données. Bien que Cursor puisse être utilisé comme un éditeur autonome, il est particulièrement précieux pour les développeurs travaillant déjà dans un environnement comme VSCode, leur permettant d'intégrer l'assistance IA sans perturber leur flux de travail. Similitudes entre Replit et Cursor Replit et Cursor se concentrent tous deux sur l'aide aux développeurs pour rationaliser leur flux de travail grâce à l'IA. Voici quelques similitudes clés : Génération de code assistée par l'IA : Les deux plateformes utilisent l'IA pour générer du code basé sur des invites en langage naturel, réduisant considérablement le temps que les développeurs passent à écrire des extraits de code de base. Fine peut également écrire du code pour vous, transformant un problème de Linear, GitHub ou Jira en une PR. Autocomplétion et débogage : Replit et Cursor offrent tous deux une complétion de code intelligente et une détection d'erreurs, accélérant le processus de développement et aidant les développeurs à détecter les erreurs tôt. Fonctionnalités de collaboration : Bien que Replit offre une collaboration en temps réel directement dans le navigateur, Cursor est un fork de VSCode. Différences entre Replit et Cursor Intégration de la plateforme : Replit est un IDE en ligne à part entière, ce qui signifie que les utilisateurs peuvent commencer à coder directement dans le navigateur sans configurer un environnement local. Cursor, en revanche, est plus adapté à ceux qui ont déjà un environnement de développement préféré dans VSCode et souhaitent rester dans cet environnement familier. Collaboration et facilité d'utilisation : L'environnement en ligne de Replit offre des fonctionnalités de collaboration en temps réel intégrées, ce qui le rend plus accessible pour les équipes ou les salles de classe. Cursor, bien que collaboratif, nécessite une configuration supplémentaire pour les extensions et peut être mieux adapté aux développeurs familiers avec des configurations avancées. Pourquoi choisir Cursor plutôt que Replit Sécurité : Pour les développeurs ou les équipes nécessitant des mesures de sécurité strictes, la certification SOC 1 de Cursor en fait le choix le plus fiable. Replit détient la certification SOC 2 pour les clients d'entreprise sur la plupart de leur plateforme, mais il n'est pas clair si cela inclut la nouvelle suite IA. Intégration avec les outils existants : Si vous utilisez déjà VSCode ou un autre environnement de développement local, l'intégration transparente de Cursor vous permet d'apporter une assistance IA à votre flux de travail actuel sans changer votre configuration, beaucoup. Fine ne nécessite pas de changer votre IDE du tout - collaborez avec Fine où que vous collaboriez habituellement avec vos coéquipiers. Refactoring de code : Cursor excelle dans l'assistance au refactoring de code et à l'amélioration des bases de code héritées, offrant des suggestions intelligentes qui aident à maintenir la qualité du code au fil du temps. Pourquoi choisir Replit plutôt que Cursor IDE entièrement intégré : Pour les développeurs qui veulent une solution tout-en-un sans avoir besoin d'installer des logiciels supplémentaires ou de gérer des extensions, l'environnement basé sur le navigateur de Replit est un excellent choix. Il vous permet de commencer à coder de n'importe où, sans les tracas de la configuration. Convient aux débutants : L'interface intuitive de Replit et sa documentation étendue en font une excellente option pour les débutants ou les éducateurs. Ses outils de collaboration faciles à utiliser le rendent également idéal pour les projets de groupe ou les environnements d'apprentissage. Collaboration en temps réel : Replit brille dans les environnements d'équipe, offrant une fonctionnalité de collaboration en temps réel rationalisée qui fonctionne parfaitement sur les navigateurs. Cela est particulièrement utile pour les projets où plusieurs développeurs doivent travailler ensemble en temps réel. Pourquoi Fine est un meilleur choix Bien que Replit et Cursor offrent tous deux des fonctionnalités de codage alimentées par l'IA convaincantes, Fine va plus loin en fournissant une automatisation avancée et un ensemble d'outils plus complet adapté aux équipes de développement. Voici pourquoi Fine est une meilleure alternative : Automatisation supérieure du flux de travail : L'IA de Fine n'assiste pas seulement à la génération de code et au débogage, mais automatise également des flux de travail entiers, réduisant le temps que les développeurs passent sur des tâches répétitives. Résumé des demandes de tirage (PR) : Fine peut résumer les demandes de tirage et aider les développeurs à se concentrer sur les décisions de haut niveau en examinant le code qui a déjà été testé et validé, une fonctionnalité non disponible dans Replit ou Cursor. Personnalisable pour les équipes : Fine est conçu pour évoluer avec les équipes, offrant des outils puissants pour le développement collaboratif qui s'intègrent parfaitement aux processus existants. Son IA peut aider à examiner et à améliorer le code, permettant aux équipes de travailler plus rapidement et plus efficacement. Conscience contextuelle complète : Fine s'intègre à GitHub, Linear, Sentry et plus encore, permettant à l'utilisateur d'activer l'IA où qu'il travaille et d'utiliser les informations sur les plateformes externes comme contexte. Utilisation illimitée des LLM Premium Fine ne limite pas combien les abonnés payants peuvent accéder à o1 d'OpenAI ou à Claude 3.5 Sonnet, les principaux LLM pour le développement logiciel. De nombreuses autres plateformes exigent que l'utilisateur fournisse ses propres clés API pour OpenAI et/ou Anthropic et paie donc par utilisation en plus de l'abonnement mensuel. En conclusion, Replit et Cursor offrent tous deux des solutions de codage alimentées par l'IA solides avec des forces uniques. Cependant, Fine offre une expérience IA plus complète et axée sur l'équipe qui peut améliorer la productivité bien au-delà de ce que l'une ou l'autre plateforme fournit actuellement. Que vous soyez un développeur solo ou que vous gériez une grande équipe de développement, les fonctionnalités IA de Fine et l'automatisation avancée du flux de travail en font un choix supérieur pour ceux qui cherchent à optimiser leur processus de développement. 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 | 2026-01-13T08:48:23 |
https://devblogs.microsoft.com/dotnet/?p=26368 | .NET for Apache Spark Helps Makes Big Data Accessible - .NET Blog Skip to main content Microsoft Dev Blogs Dev Blogs Dev Blogs Home Developer Microsoft for Developers Visual Studio Visual Studio Code Develop from the cloud All things Azure Xcode DevOps Windows Developer ISE Developer Azure SDK Command Line Aspire Technology DirectX Semantic Kernel Languages C++ C# F# TypeScript PowerShell Team Python Java Java Blog in Chinese Go .NET All .NET posts .NET Aspire .NET MAUI AI ASP.NET Core Blazor Entity Framework NuGet Servicing .NET Blog in Chinese Platform Development #ifdef Windows Microsoft Foundry Azure Government Azure VM Runtime Team Bing Dev Center Microsoft Edge Dev Microsoft Azure Microsoft 365 Developer Microsoft Entra Identity Developer Old New Thing Power Platform Data Development Azure Cosmos DB Azure Data Studio Azure SQL OData Revolutions R Unified Data Model (IDEAs) Microsoft Entra PowerShell More Search Search No results Cancel Dev Blogs .NET Blog Using .NET for Apache® Spark™ to Analyze Log Data .NET 10 is here! .NET 10 is now available: the most productive, modern, secure, intelligent, and performant release of .NET yet. Learn More Download Now February 10th, 2020 1 reaction Using .NET for Apache® Spark™ to Analyze Log Data Brigit Murtaugh Program Manager Show more At Spark + AI Summit in May 2019 , we released .NET for Apache Spark . .NET for Apache Spark is aimed at making Apache® Spark™ , and thus the exciting world of big data analytics, accessible to .NET developers. .NET for Spark can be used for processing batches of data, real-time streams, machine learning, and ad-hoc query. In this blog post, we’ll explore how to use .NET for Spark to perform a very popular big data task known as log analysis . The remainder of this post describes the following topics: What is log analysis? Writing a .NET for Spark log analysis app Running a .NET for Spark app Wrap Up What is log analysis? Log analysis, also known as log processing , is the process of analyzing computer-generated records called logs. Logs tell us what’s happening on a tool like a computer or web server, such as what applications are being used or the top websites users visit. The goal of log analysis is to gain meaningful insights from these logs about activity and performance of our tools or services. .NET for Spark enables us to analyze anywhere from megabytes to petabytes of log data with blazing fast and efficient processing! In this blog post, we’ll be analyzing a set of Apache log entries that express how users are interacting with content on a web server. You can view a sample of Apache log entries here . Writing a .NET for Spark log analysis app Log analysis is an example of batch processing with Spark. Batch processing is the transformation of data at rest, meaning that the source data has already been loaded into data storage. In our case, the input text file is already populated with logs and won’t be receiving new or updated logs as we process it. When creating a new .NET for Spark application, there are just a few steps we need to follow to start getting those interesting insights from our data: Create a Spark Session. Read input data, typically using a DataFrame. Manipulate and analyze input data, typically using Spark SQL. Create a Spark Session In any Spark application, we start off by establishing a new SparkSession , which is the entry point to programming with Spark: SparkSession spark = SparkSession .Builder() .AppName("Apache User Log Processing") .GetOrCreate(); By calling on the spark object created above, we can now access Spark and DataFrame functionality throughout our program – great! But what is a DataFrame? Let’s learn about it in the next step. Read input data Now that we have access to Spark functionality, we can read in the log data we’ll be analyzing. We store input data in a DataFrame , which is a distributed collection of data organized into named columns: DataFrame generalDf = spark.Read().Text("<path to input data set>"); When our input is contained in a .txt file, we use the .Text() method, as shown above. There are other methods to read in data from other sources, such as .Csv() to read in comma-separated values files. Manipulate and analyze input data With our input logs stored in a DataFrame, we can start analyzing them – now things are getting exciting! An important first step is data preparation . Data prep involves cleaning up our data in some way. This could include removing incomplete entries to avoid error in later calculations or removing irrelevant input to improve performance. In our example, we should first ensure all of our entries are complete logs. We can do this by comparing each log entry to a regular expression (AKA a regex), which is a sequence of characters that defines a pattern. Let’s define a regex expressing a pattern all valid Apache log entries should follow: string s_apacheRx = "^(\S+) (\S+) (\S+) [([\w:/]+\s[+-]\d{4})] \"(\S+) (\S+) (\S+)\" (\d{3}) (\d+)"; How do we perform a calculation on each row of a DataFrame, like comparing each log entry to the above regex? The answer is Spark SQL . Spark SQL Spark SQL provides many great functions for working with the structured data stored in a DataFrame. One of the most popular features of Spark SQL is UDFs , or user-defined functions. We define the type of input they take and the type of output they produce, and then the actual calculation or filtering they perform. Let’s define a new UDF GeneralReg to compare each log entry to the s_apacheRx regex. Our UDF requires an Apache log entry, which is a string, and will return a true or false depending upon if the log matches the regex: spark.Udf().Register<string, bool>("GeneralReg", log => Regex.IsMatch(log, s_apacheRx)); So how do we call GeneralReg ? In addition to UDFs, Spark SQL provides the ability to write SQL calls to analyze our data – how convenient! It’s common to write a SQL call to apply a UDF to each row of data. To call GeneralReg from above, let’s use the following SQL call: DataFrame generalDf = spark.Sql("SELECT logs.value, GeneralReg(logs.value) FROM Logs"); This SQL call tests each row of generalDf to determine if it’s a valid and complete log. We can use .Filter() to only keep the complete log entries in our data, and then .Show() to display our newly filtered DataFrame: generalDf = generalDf.Filter(generalDf["GeneralReg(value)"]); generalDf.Show(); Now that we’ve performed some initial data prep, we can continue filtering and analyzing our data. Let’s find log entries from IP addresses starting with 10 and related to spam in some way: // Choose valid log entries that start with 10 spark.Udf().Register<string, bool>( "IPReg", log => Regex.IsMatch(log, "^(?=10)")); generalDf.CreateOrReplaceTempView("IPLogs"); // Apply UDF to get valid log entries starting with 10 DataFrame ipDf = spark.Sql( "SELECT iplogs.value FROM IPLogs WHERE IPReg(iplogs.value)"); ipDf.Show(); // Choose valid log entries that start with 10 and deal with spam spark.Udf().Register<string, bool>( "SpamRegEx", log => Regex.IsMatch(log, "\\b(?=spam)\\b")); ipDf.CreateOrReplaceTempView("SpamLogs"); // Apply UDF to get valid, start with 10, spam entries DataFrame spamDF = spark.Sql( "SELECT spamlogs.value FROM SpamLogs WHERE SpamRegEx(spamlogs.value)"); Finally, let’s count the number of GET requests in our final cleaned dataset. The magic of .NET for Spark is that we can combine it with other popular .NET features to write our apps. We’ll use LINQ to analyze the data in our Spark app one last time: int numGetRequests = spamDF .Collect() .Where(r => ContainsGet(r.GetAs<string>("value"))) .Count(); In the above code, ContainsGet() checks for GET requests using regex matching : // Use regex matching to group data // Each group matches a column in our log schema // i.e. first group = first column = IP public static bool ContainsGet(string logLine) { Match match = Regex.Match(logLine, s_apacheRx); // Determine if valid log entry is a GET request if (match.Success) { Console.WriteLine("Full log entry: '{0}'", match.Groups[0].Value); // 5th column/group in schema is "method" if (match.Groups[5].Value == "GET") { return true; } } return false; } As a final step in our Spark apps, we call spark.Stop() to shut down the underlying Spark Session and Spark Context. You can view the complete log processing example in our GitHub repo. Running your app To run a .NET for Apache Spark app , you need to use the spark-submit command, which will submit your application to run on Apache Spark. The main parts of spark-submit include: –class, to call the DotnetRunner. –master, to determine if this is a local or cloud Spark submission. Path to the Microsoft.Spark jar file. Any arguments or dependencies for your app, such as the path to your input file or the dll containing UDF definitions. You’ll also need to download and setup some dependencies before running a .NET for Spark app locally, such as Java and Apache Spark. A sample Windows command for running your app is as follows: spark-submit --class org.apache.spark.deploy.dotnet.DotnetRunner --master local /path/to/microsoft-spark-<version>.jar dotnet /path/to/netcoreapp<version>/LoggingApp.dll .NET for Apache Spark Wrap Up We’d love to help you get started with .NET for Apache Spark and hear your feedback. You can Request a Demo from our landing page and check out the .NET for Spark GitHub repo to learn more about how you can apply .NET for Spark in your apps and get involved with our effort to make .NET a great tech stack for building big data applications! 1 0 0 Share on Facebook Share on X Share on Linkedin Copy Link --> Category .NET Apache Topics .NET for Spark Apache Spark Big Data Log Analysis Spark.NET Share Author Brigit Murtaugh Program Manager Brigit Murtaugh is a Program Manager on the .NET team, where she largely focuses on big data and machine learning. 0 comments Discussion is closed. Code of Conduct Read next February 11, 2020 .NET Framework February 2020 Security and Quality Rollup Tara Overfield February 12, 2020 Deprecating TLS 1.0 and 1.1 on NuGet.org – Stage 1 The NuGet Team Stay informed Get notified when new posts are published. Email * Country/Region * Select... 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https://handlebarsjs.com/guide/#what-is-handlebars | Introduction | Handlebars Skip to content Handlebars Search K Main Navigation Guide API Reference Improve the docs English 한국어 中文 English 한국어 中文 Appearance Menu Return to top Sidebar Navigation Language Guide Introduction Expressions Partials Block Helpers Built-in Helpers Hooks Installation & Precompilation Installation Precompiling templates Integrations When (not) to use Handlebars? On this page Introduction What is Handlebars? Handlebars is a simple templating language . It uses a template and an input object to generate HTML or other text formats. Handlebars templates look like regular text with embedded Handlebars expressions. template Click to try out A handlebars expression is a {{ , some contents, followed by a }} . When the template is executed, these expressions are replaced with values from an input object. Learn More: Expressions Installation The fastest way to test Handlebars is to load it from a CDN and embed it in an HTML file. html <!-- Include Handlebars from a CDN --> < script src = "https://cdn.jsdelivr.net/npm/handlebars@latest/dist/handlebars.js" ></ script > < script > // compile the template var template = Handlebars. compile ( "Handlebars <b>{{doesWhat}}</b>" ); // execute the compiled template and print the output to the console console. log ( template ({ doesWhat: "rocks!" })); </ script > WARNING This method can be used for small pages and for testing. There are several other ways to use Handlebars, when you target real production systems. Learn more: Installation Language features Simple expressions As shown before, the following template defines two Handlebars expressions template Click to try out If applied to the input object input Click to try out the expressions will be replaced by the corresponding properties. The result is then output Click to try out Nested input objects Sometimes, the input objects contains other objects or arrays. For example: input Click to try out In such a case, you can use a dot-notation to gain access to the nested properties template Click to try out Learn more: Expressions Some built-in helpers allow you to change the current context to a nested object. You can then access this object as if it were the root object Evaluation context The built-in block-helpers each and with allow you to change the current evaluation context. The with -helper dives into an object-property, giving you access to its properties template Click to try out input Click to try out The each -helper iterates an array, allowing you to access the properties of each object via simple handlebars expressions. template Click to try out input Click to try out Learn more: Built-in helpers Template comments You can use comments in your handlebars code just as you would in your code. Since there is generally some level of logic, this is a good practice. The comments will not be in the resulting output. If you'd like the comments to show up just use HTML comments, and they will be output. Any comments that must contain }} or other handlebars tokens should use the {{!-- --}} syntax. template Click to try out Custom Helpers Handlebars helpers can be accessed from any context in a template. You can register a helper with the Handlebars.registerHelper method. template Click to try out preparationScript Click to try out Helpers receive the current context as the this -context of the function. template Click to try out preparationScript Click to try out Block Helpers Block expressions allow you to define helpers that will invoke a section of your template with a different context than the current. These block helpers are identified by a # preceeding the helper name and require a matching closing mustache, / , of the same name. Let's consider a helper that will generate an HTML list: preparationScript Click to try out The example creates a helper named list to generate our HTML list. The helper receives the people as its first parameter, and an options hash as its second parameter. The options hash contains a property named fn , which you can invoke with a context just as you would invoke a normal Handlebars template. When executed, the template will render: output Click to try out Block helpers have more features, such as the ability to create an else section (used, for instance, by the built-in if helper). Since the contents of a block helper are escaped when you call options.fn(context) , Handlebars does not escape the results of a block helper. If it did, inner content would be double-escaped! Learn More: Block Helpers HTML Escaping Because it was originally designed to generate HTML, Handlebars escapes values returned by a {{expression}} . If you don't want Handlebars to escape a value, use the "triple-stash", {{{ . template Click to try out The special characters in the second line will be escaped: output Click to try out Handlebars will not escape a Handlebars.SafeString . If you write a helper that generates its own HTML, you will usually want to return a new Handlebars.SafeString(result) . In such a circumstance, you will want to manually escape parameters. preparationScript Click to try out This will escape the passed in parameters, but mark the response as safe, so Handlebars will not try to escape it even if the "triple-stash" is not used. WARNING Handlebars does not escape JavaScript strings. Using Handlebars to generate JavaScript, such as inline event handlers, could potentially lead to cross-site scripting vulnerabilities. Partials Handlebars partials allow for code reuse by creating shared templates. You can register a partial using the registerPartial -method: preparationScript Click to try out The following template and input: template Click to try out input Click to try out will then provide the following result: output Click to try out Learn More: Partials Built-In Helpers Handlebars offers a variety of built-in helpers such as the if conditional and each iterator. Learn More: Built-In Helpers API Reference Handlebars offers a variety of APIs and utility methods for applications and helpers. Learn More: API Reference Suggest changes to this page Last updated: Pager Next page Expressions MIT licensed Copyright © 2011-2026 Yehuda Katz | 2026-01-13T08:48:23 |
https://www.openapis.org/ | OpenAPI Initiative – The OpenAPI Initiative provides an open source, technical community, within which industry participants may easily contribute to building a vendor-neutral, portable and an open specification for providing technical metadata for REST APIs – the “OpenAPI Specification” (OAS). Skip to main content search Menu About About Technical Steering Committee Code of Conduct Transparency Report Specifications OpenAPI Publications Latest OAS Arazzo Specifications Overlay Spec Registries Learn about the OAI Spec Share your OAS Implementations! Participate How To Contribute How to Participate on GitHub Join Us on Slack Calendar Governance Project Charter Technical Steering Committee Technical Oversight Board Code of Conduct Travel Expense Reimbursement Policy Membership Current Members Learn about Membership Join Now Testimonials Member Support Blog FAQ FAQ The OpenAPI Initiative Style Guide OpenAPI Blog Guidelines Presentations What is OpenAPI? Events linkedin github search Search Close Search Want to learn more about OpenAPI? Take our new OpenAPI Fundamentals training course LEARN MORE > The world's most widely used API description standard All OpenAPI Publications How to Get Involved View Latest OpenAPI Spec View Latest Arazzo Spec View New Overlays Spec What is OpenAPI? The OpenAPI Specifications provide a formal standard for describing HTTP APIs. This allows people to understand how an API works, how a sequence of APIs work together, generate client code, create tests, apply design standards, and much, much more. 3 Benefits of OpenAPI As the most widely used API description languages: Commonality of use and support by tool vendors , meaning flexibility in tool vendor selection . Commonality of knowledge by developers and engineers , meaning flexibility in staffing . Abstraction of API description facilitating adoption of innovations in API behaviors
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https://devblogs.microsoft.com/visualstudio/?p=228281 | Making our Unity Analyzers Open-Source - Visual Studio Blog Skip to main content Microsoft Dev Blogs Dev Blogs Dev Blogs Home Developer Microsoft for Developers Visual Studio Visual Studio Code Develop from the cloud All things Azure Xcode DevOps Windows Developer ISE Developer Azure SDK Command Line Aspire Technology DirectX Semantic Kernel Languages C++ C# F# TypeScript PowerShell Team Python Java Java Blog in Chinese Go .NET All .NET posts .NET Aspire .NET MAUI AI ASP.NET Core Blazor Entity Framework NuGet Servicing .NET Blog in Chinese Platform Development #ifdef Windows Microsoft Foundry Azure Government Azure VM Runtime Team Bing Dev Center Microsoft Edge Dev Microsoft Azure Microsoft 365 Developer Microsoft Entra Identity Developer Old New Thing Power Platform Data Development Azure Cosmos DB Azure Data Studio Azure SQL OData Revolutions R Unified Data Model (IDEAs) Microsoft Entra PowerShell More Search Search No results Cancel Dev Blogs Visual Studio Blog Making our Unity Analyzers Open-Source February 11th, 2020 0 reactions Making our Unity Analyzers Open-Source Jb Evain Principal Software Engineering Manager Show more Visual Studio for Mac is retired Visual Studio for Mac was retired on August 31, 2024 in accordance with Microsoft's Modern Lifecycle Policy . While you can continue to work with Visual Studio for Mac, there are several other options for developers on Mac such as the preview version of the new C# Dev Kit extension for VS Code. Learn more about support timelines and alternatives. Here at the Visual Studio Tools for Unity team our mission is to improve the productivity of Unity developers. In Visual Studio 2019 we’ve introduced our Unity Analyzers, a collection of Unity specific code diagnostics and code fixes. Today we’re excited to make our Unity Analyzers Open-Source . Unity Analyzers Visual Studio and Visual Studio for Mac rely on Roslyn , our compiler infrastructure, to deliver a fantastic C# programming experience. One of my favorite features of Roslyn is the ability to programmatically guide developers when using an API. At the core of this experience, an analyzer detects a code pattern, and can offer to replace it with a more recommended pattern. A common example that is specific to the Unity API is how you compare tags on your game objects. You could write collision.gameObject.tag == "enemy"; to compare tags But Unity offers a CompareTag method that is more efficient, so we implemented a CompareTag diagnostic that will detect this pattern and offer to use the more optimized method instead. On Windows just press (CTRL+.) or press (Alt-Enter) on Visual Studio for Mac to trigger the Quick Fixes, and you’ll be prompted by a preview of the change: We currently have a dozen analyzers that are shipping in the Tools for Unity, with more being written right now. Improving the Default Experience Recently the Roslyn team introduced analyzer suppressors. This feature allows us to programmatically suppress the default set of analyzers that Roslyn ships. This is great for Unity developers, because it allows the Tools for Unity team to remove warnings or code fix suggestions that do not apply to Unity development. A common example is for fields decorated with Unity’s SerializeField attributes to light-up the fields in the Unity Inspector. For instance, without the Unity Analyzers, Visual Studio would offer to make a serialized field readonly while we know the Unity engine is setting the value of this field. If you were to accept that code fix, Unity would remove any association you set in the Inspector for this field, which could break things. By writing a suppressor, we can programmatically suppress this behavior while keeping it enabled for standard C# fields. Available now Today, the Unity Analyzers are being shipped as part of the Tools for Unity and are enabled on Visual Studio and Visual Studio for Mac. The analyzers are running inside Visual Studio, meaning that if you suppress a warning you might still see it in Unity’s error list. We’re working on improving this for a future release. Bring your tips and tricks The Tools for Unity team has a backlog of analyzers, code fixes and suppressors that we’re working on, but we’re always on the lookout for new analyzers that would improve the C# programming experience of Unity developers. The project is easy to get started with. Just head to our README and suggest a new analyzer or even submit a PR to the repository. See you on GitHub! 0 0 0 Share on Facebook Share on X Share on Linkedin Copy Link --> Category Cross-Platform Gaming Open Source Visual Studio Topics C# Game Development roslyn Unity Visual Studio Visual Studio for Mac Share Author Jb Evain Principal Software Engineering Manager Jb runs the Visual Studio Tools for Unity experience. He has a passion for developer tools and programming languages and enjoys working with game developers. 0 comments Discussion is closed. 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https://www.fine.dev/blog/build-scalable-tech-infrastructure-for-startups | How to Build a Scalable Tech Infrastructure on a Startup Budget: A Step-by-Step Guide for CTOs Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back How to Build a Scalable Tech Infrastructure on a Startup Budget: A Step-by-Step Guide for CTOs Building a scalable tech infrastructure on a startup budget requires creativity and prioritization. As a CTO, you need to grow infrastructure without exhausting resources. This guide outlines steps to help your tech stack expand with your user base, without financial strain. Table of Contents Start with Open-Source Solutions Use Cloud Services Wisely Modular Architecture Automate Early Think Lean—Build for Your Current Needs Monitoring and Alerts Outsource Non-Critical Components Leverage Community and Startup Programs Scalable Data Management Prepare for Growth with a Flexible Mindset Look for Integrations Ready to Scale with Ease? 1. Start with Open-Source Solutions When budget is tight, opting for open-source software can be a game-changer. Open-source solutions often provide the flexibility you need to get started without the licensing fees associated with proprietary systems. Tools like PostgreSQL for databases, Kubernetes for orchestration, and Apache Kafka for data streaming can all be incredibly effective without incurring high costs. can all be incredibly effective without incurring high costs. The initial learning curve might be steep, but the savings are well worth it. There's also a whole community out there to help you. 2. Use Cloud Services Wisely The allure of cloud services like AWS , Google Cloud , or Azure is real—scalability, reliability, and global availability. However, these services can become expensive if not optimized. Start small by utilizing free tiers and cost calculators. Identify the essential cloud resources you need, and always keep an eye on your billing dashboard. Consider using cloud credits, which are often available for startups through accelerator programs.. 3. Modular Architecture Adopting a modular architecture allows you to build components that can be independently scaled or replaced. By separating services (e.g., microservices or serverless functions), you gain the flexibility to scale certain parts of your infrastructure as needed, instead of the entire system. This approach can help you save on unnecessary costs and avoid a complete overhaul when scaling. 4. Automate Early Automation saves both time and money. Implement CI/CD pipelines to automate testing, deployment, and code integration. This not only reduces manual effort but also helps you ship faster without additional costs. Tools like Jenkins , GitLab CI , or GitHub Actions are great options that won't break the bank, and they help maintain quality control as your team expands. that won't break the bank, and they help maintain quality control as your team expands. They can also work together with Fine, to ensure that you not only have a robust set of tests that constantly run, but any failures are turned into fixes at maximum speed. 5. Think Lean—Build for Your Current Needs Avoid the temptation to over-engineer your infrastructure based on hypothetical future requirements. Focus on building for your current needs, but keep scalability in mind. You want something that’s "scale-ready" without being bloated. An MVP-style infrastructure should focus on the most crucial features that will support immediate growth and customer acquisition. 6. Monitoring and Alerts Establishing a simple monitoring system will help you identify issues before they impact users. Open-source tools like Prometheus and Grafana allow you to keep an eye on system performance and resource usage. on system performance and resource usage. Effective monitoring helps you make informed decisions on scaling—such as when it's truly necessary to increase server capacity. 7. Outsource Non-Critical Components To keep your internal team focused on core competencies, consider outsourcing non-critical functions, like hosting static assets or even customer support. Managed services can help reduce overhead. For example, Firebase can handle authentication and real-time data syncing, allowing your developers to focus on core product features instead of worrying about server maintenance. 8. Leverage Community and Startup Programs Many tech giants offer generous startup programs, including cloud credits, free tools, and discounted software licenses. Amazon Activate , Microsoft for Startups , and Google for Startups are programs that can provide significant cost savings in the early stages. that can provide significant cost savings in the early stages. Engage with tech communities like Stack Overflow and GitHub as well, where you can access free resources and advice. 9. Scalable Data Management Data is at the core of most tech businesses, but managing it can quickly become expensive if not done wisely. Start with cost-effective databases like PostgreSQL or NoSQL options like MongoDB, depending on your needs. As your data needs grow, consider partitioning, archiving older data, and using data warehouses only when it makes sense. 10. Prepare for Growth with a Flexible Mindset Scalability is about more than technology; it's about mindset. Regularly evaluate whether your tech stack is meeting your current needs and where you might face constraints as you grow. Flexibility in choosing tools, hiring, and decision-making will allow you to scale smoothly when your startup hits growth phases. 11. Look for integrations Where platforms offer similar features, integrations with your existing tech stack can often be the deciding factor. The more your platforms can talk to each other and automate tasks, the better for your growth. Fine works with a variety of platforms to build a knowledge graph and complement your natural workflows, making it the premier AI choice for many scaling startups. Ready to Scale with Ease? Consider using Fine to make your infrastructure scalable and efficient. Fine offers advanced AI capabilities that help automate testing, code integration, and debugging, allowing your team to focus on core development without getting bogged down in manual tasks. 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Right menu Why Streaming AI Responses Feels Faster Than It Is (Android + SSE) Shubham Verma Shubham Verma Shubham Verma Follow Jan 12 Why Streaming AI Responses Feels Faster Than It Is (Android + SSE) # android # ai # ux # kotlin Comments Add Comment 3 min read [TIL][Android] Common Android Studio Project Opening Issues Evan Lin Evan Lin Evan Lin Follow Jan 11 [TIL][Android] Common Android Studio Project Opening Issues # help # beginners # android # kotlin Comments Add Comment 2 min read Modern KMP (Part 1): The End of the "404 Not Found"2 Vladyslav Diachuk Vladyslav Diachuk Vladyslav Diachuk Follow Jan 11 Modern KMP (Part 1): The End of the "404 Not Found"2 # architecture # mobile # kotlin # api Comments Add Comment 6 min read [Showdev] Blitzy: a lightweight 2D game engine in Kotlin xeroup xeroup xeroup Follow Jan 11 [Showdev] Blitzy: a lightweight 2D game engine in Kotlin # showdev # kotlin # opensource # gamedev Comments Add Comment 2 min read 📘 Paywall SDK – Tài liệu sử dụng TỪ A Z (kèm JSON mẫu) ViO Tech ViO Tech ViO Tech Follow Jan 9 📘 Paywall SDK – Tài liệu sử dụng TỪ A Z (kèm JSON mẫu) # android # architecture # kotlin # tutorial Comments Add Comment 4 min read Kotlin vs Java: Why We Migrated to Kotlin for Enterprise Apps Droid Droid Droid Follow Jan 8 Kotlin vs Java: Why We Migrated to Kotlin for Enterprise Apps # kotlin # java # webdev Comments Add Comment 2 min read Effortless Android Logging with Timber and Kotlin supriya shah supriya shah supriya shah Follow Jan 8 Effortless Android Logging with Timber and Kotlin # android # kotlin # timber # mobile Comments Add Comment 3 min read How I Generate Both My Kotlin Backend and TypeScript Frontend from One Spec Lucas Dachman Lucas Dachman Lucas Dachman Follow Jan 6 How I Generate Both My Kotlin Backend and TypeScript Frontend from One Spec # webdev # architecture # openapi # kotlin Comments Add Comment 12 min read Debugging Chromium Crashes When Taking Full-Page Screenshots with Playwright Erik Erik Erik Follow for Allscreenshots Jan 6 Debugging Chromium Crashes When Taking Full-Page Screenshots with Playwright # playwright # kotlin # memory # programming 1 reaction Comments Add Comment 3 min read Clean Architecture Made Simple: A Koin DI Walkthrough for Android supriya shah supriya shah supriya shah Follow Jan 7 Clean Architecture Made Simple: A Koin DI Walkthrough for Android # android # kotlin # development # mobile Comments Add Comment 3 min read Mastering GraphQL with Ktor: A Modern Networking Guide for Android supriya shah supriya shah supriya shah Follow Jan 7 Mastering GraphQL with Ktor: A Modern Networking Guide for Android # android # graphql # kotlin # mobile Comments Add Comment 3 min read Agents and Gradle Dont Get Along - I Fixed It in Two Commands Nek.12 Nek.12 Nek.12 Follow Jan 6 Agents and Gradle Dont Get Along - I Fixed It in Two Commands # kotlin # ai # cli # aiagents Comments Add Comment 4 min read From Android native to super apps — what I’ve learned so fa Vũ Nguyễn Vũ Nguyễn Vũ Nguyễn Follow Jan 6 From Android native to super apps — what I’ve learned so fa # mobile # android # ios # kotlin Comments Add Comment 1 min read Day 4: Setting Up CI/CD Erik Erik Erik Follow for Allscreenshots Jan 4 Day 4: Setting Up CI/CD # kotlin # cicd # github Comments Add Comment 7 min read Day 2: Tech Stack Decision - Why Kotlin/Spring Boot + React + Postgres Erik Erik Erik Follow for Allscreenshots Jan 3 Day 2: Tech Stack Decision - Why Kotlin/Spring Boot + React + Postgres # postgres # kotlin # programming # webdev Comments Add Comment 5 min read 🚀 Jetpack Compose Performance Audit ViO Tech ViO Tech ViO Tech Follow Jan 2 🚀 Jetpack Compose Performance Audit # android # jetpackcompose # kotlin # performance Comments Add Comment 3 min read ⚡ Jetpack Compose Performance: Macrobenchmark & Baseline Profile ViO Tech ViO Tech ViO Tech Follow Jan 2 ⚡ Jetpack Compose Performance: Macrobenchmark & Baseline Profile # android # jetpackcompose # kotlin # performance Comments Add Comment 3 min read Exploring Ktor: A Modern Networking Framework for Kotlin supriya shah supriya shah supriya shah Follow Jan 7 Exploring Ktor: A Modern Networking Framework for Kotlin # android # kotlin # networking # mobile Comments Add Comment 3 min read 7 Best Resources to Learn Kotlin: My Journey Stack Overflowed Stack Overflowed Stack Overflowed Follow Jan 1 7 Best Resources to Learn Kotlin: My Journey # webdev # programming # kotlin Comments Add Comment 3 min read Kotlin 확장 함수와 확장 프로퍼티 dss99911 dss99911 dss99911 Follow Dec 31 '25 Kotlin 확장 함수와 확장 프로퍼티 # programming # kotlin # extension # extensionfunction Comments Add Comment 2 min read Kotlin Native 동시성과 Freezing dss99911 dss99911 dss99911 Follow Dec 31 '25 Kotlin Native 동시성과 Freezing # programming # kotlin # kotlinnative # concurrency Comments Add Comment 1 min read Kotlin 함수와 람다: 함수 선언부터 고차 함수까지 dss99911 dss99911 dss99911 Follow Dec 31 '25 Kotlin 함수와 람다: 함수 선언부터 고차 함수까지 # programming # kotlin # function # lambda Comments Add Comment 3 min read Simple Android Architecture : MVVM concept and reduce boilerplate code on Activity/Fragment/ViewModel dss99911 dss99911 dss99911 Follow Dec 30 '25 Simple Android Architecture : MVVM concept and reduce boilerplate code on Activity/Fragment/ViewModel # mobile # android # mvvm # kotlin 5 reactions Comments Add Comment 5 min read Kotlin 제어문: if, when, for, while dss99911 dss99911 dss99911 Follow Dec 31 '25 Kotlin 제어문: if, when, for, while # programming # kotlin # if # when Comments Add Comment 2 min read Kotlin 코루틴: 비동기 프로그래밍 dss99911 dss99911 dss99911 Follow Dec 31 '25 Kotlin 코루틴: 비동기 프로그래밍 # programming # kotlin # coroutine # async Comments Add Comment 1 min read loading... trending guides/resources Is the Java ecosystem cursed? 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https://stoplight.io/case-studies/schneider-electric/?ref=apisyouwonthate.com | Schneider Electric | Stoplight Solutions Stoplight Platform Design, document, and build APIs For Developers Drive results with quality APIs For Program Leaders Keep your API teams on track For Tech Executives Achieve strategic transformation Enterprise Solutions Results tailored to your needs See a Demo Learn how Stoplight can help you Open Source Spectral Prism Elements Resources LEARN Stoplight Docs eBooks Guides Webinars API Design Hub Support EXPLORE Blog Podcast Community Open Source Case Studies YouTube Pricing About About Us Blog Careers Press Contact Us Get Support SOCIAL Login Get Started Stoplight Case Study Schneider Electric Cuts Development Time with OpenAPI Linting and Design Libraries Get Started with Stoplight Challenge: A Black-Box approach to building APIs that was compromising speed and quality After over 180 years of business, you might expect Schneider Electric has gone through many transformations. The Fortune Global 500 company specializes in energy management, and industrial automation. Like many companies of this size, it has a mature API program, but it struggled to keep up with the recent growth. While APIs are sometimes seen purely as technology, the Schneider Electric team realized the importance of people in its process. The teams were working hard to manage all of their old and new APIs. In fact, they identified duplicative effort was often needed to launch new APIs. The back-and-forth needed to design, develop, and manage an API meant it was hard to keep the technology and business needs on the same page. This black-box approach led to guess-and-check API designs, which required additional work. "Originally, we'd hold multiple meetings to go through all the standards and correct each aspect. We've whittled that down to a half-hour meeting." — Connor Williams, Software Engineer at Schneider Electric Suppose a Schneider Electric team needed a new API built. In that case, they’d have a first meeting with a separate team specializing in APIs regarding their expectations. A few days later, the API team would return a new API that missed the mark more often than not. The back-and-forth that followed to solidify the new API would usually take weeks. While the end product would get the job done for customers, the APIs lacked the consistency required for cross-functional use. Therefore, if another team needed a similar API, they’d have to go through the same new API process instead of simply reusing the existing one. Objective: Improve transparency and reusability After decades of bringing their customers efficient and sustainable solutions, Schneider Electric wanted similar results of their internal processes. To maintain its existing APIs, as well as enable teams to quickly build new interfaces, they’d need to adjust their black-box approach to APIs and embrace more modern methods. Among the goals were to increase API reusability and lower their development costs. Using Stoplight’s tools, they have improved quality and taken weeks off API development time. "API design and development previously took up to three weeks. With Stoplight, we have that all worked out in a matter of days." — Connor Williams, Software Engineer at Schneider Electric Solution: Design-first approach to API development Schneider Electric knew the siloed API development process lacked the clarity needed, which led to a design-first approach. That’s when the team found Stoplight, to help guide teams through the new Schneider Electric API workflow. Shared libraries improve API quality Schneider Electric’s black-box approach to API design increased development times, but it also led to inconsistency among its APIs. Despite a central team building each API, there were not published guidelines, and each project was treated separately. With Stoplight as the knowledge base for its API workflow, Schneider Electric turned to design libraries to increase API consistency and quality. API reviewers knew the API governance benchmarks to look for in new APIs. However, the teams looking for an API review didn’t always understand these criteria. A common model might have existed, but it was obscured in the black box. To solve this ambiguity, reviewers used design libraries. These are instantly shared across the organization and can be adjusted over time on Stoplight. The clear guidelines removed uncertainty, secured consistency, and ensured reusability for the future. "The biggest help has been the Stoplight design libraries. Reviewers don't have to update every single project with our common models and teams do not have to go find them elsewhere. We can always be sure we're referencing the same thing." — Connor Williams, Software Engineer at Schneider Electric Design libraries took Schneider Electric’s APIs to the next level, so they looked for other ways to automate more of the process. Easy linting rules saves time Following the benefits of design libraries, Schneider Electric turned to Stoplight’s linting capabilities to advance its API workflow. With programmatic rules, many common API issues—custom expectations specific to Schneider Electric APIs—can be identified early. Stoplight Studio has linting built-in as a straightforward tool to provide even more time savings during API reviews. "Stoplight's simple-to-use interface and linter integration helped us automate the review of API designs before their development, preventing problems from occurring in the first place. — Connor Williams, Software Engineer at Schneider Electric The Schneider Electric teams use the linter’s pre-built functionality to check for things like the correct case. When APIs employ a consistent approach to endpoint and field names, API consumers (often internal teams or trusted partners) can easily integrate across multiple APIs without looking into syntax. Stoplight has most common case choices built into its platform, which saves the trouble of implementing regular expressions. However, for more detailed requirements, the Schneider Electric reviewers can write custom rules. By applying this automatic review during the design phase, the team noticed a significant decrease in the time it took to review. You’ve followed Schneider Electric’s journey from the pains of designing APIs in a black-box to creating transparency, higher quality code, and saving time with just a couple of tools in Stoplight Studio. Create consistency and enable collaboration at your organization. Include Stoplight to help your team go API design-first. Create a free Stoplight workspace Industry: Electrical Manufacturing Location: Paris, FR Employees: 100,000+ Schneider Electric is a global leader in energy management and automation. The company has 170,000 employees serving customers in over 100 countries, helping manage their energy and process in ways that are safe, reliable, efficient and sustainable. Contents Example H2 Example H3 Recent Case Studies View all case studies → Delivering on Documentation and Developer Experience: Sendcloud's Story To be successful, Sendcloud must collaborate in an organized way, follow shared standards, and achieve common business goals—the hallmarks of a design-first strategy. How Consistency and Collaboration Lead to API Success at Fiserv Fiserv’s mission was to simplify the entire payment journey model into a single API call. They used Stoplight Platform to create consistency. How Calendly Wins with Design-First APIs Dmitry Pashkevich, an Application Architect at Calendly, about building a new API platform using a design-first approach. Ready to streamline API design and development? 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https://www.fine.dev/blog/model-context-protocol | Model Context Protocol (MCP): The Key to Faster, Simpler AI App Development with Fine Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back Model Context Protocol (MCP): The Key to Faster, Simpler AI App Development with Fine Building AI-powered applications can feel like assembling a jigsaw puzzle. You need to wrangle large language models (LLMs), connect to databases and APIs, manage your app’s context window (the limited “memory” of what the model can see at once), and somehow glue it all together. Enter the Model Context Protocol (MCP) – a new open standard that’s transforming how developers build AI apps. Think of MCP as the USB-C of AI applications , a universal connector that lets your AI agents easily plug into data sources and tools ( Introduction - Model Context Protocol ). In this post, we’ll break down what MCP is in builder-friendly terms, how it accelerates AI app development, and how the all-in-one Fine.dev platform uses MCP to help you build AI apps faster with less friction. By the end, you’ll see how to get started with Fine and use MCP as a core enabler of your next AI-powered project. model-context-protocol-pic.png What is the Model Context Protocol (MCP)? MCP (Model Context Protocol) is an open standard that standardizes how applications provide context and connect external resources to AI models ( Introducing the Model Context Protocol \ Anthropic ). In other words, it’s a common protocol that lets AI systems securely talk to the outside world. Just as USB-C provides one standard plug for all your devices, MCP provides a single, consistent way for AI applications (like chatbots, coding assistants, or any AI agent) to interface with different data sources, tools, and services ( Introduction - Model Context Protocol ) ( Model Context Protocol (MCP): 8 MCP Servers Every Developer Should Try! - DEV Community ). Builder translation: Instead of writing custom integration code every time you want an AI model to fetch some data or perform an action, you use MCP’s conventions. You either expose your data or service as an MCP server , or use (or build) an AI client that can connect to MCP servers. The protocol handles the messaging, so any MCP-compatible client can work with any MCP-compatible server without custom code ( Understanding the Model Context Protocol (MCP) | deepset Blog ). It’s like a contract: as long as both sides speak MCP, the AI can request info or actions and get results in a structured way ( Understanding the Model Context Protocol (MCP) | deepset Blog ). How MCP Works (in a Nutshell) At a high level, MCP follows a client–server architecture ( Introducing the Model Context Protocol \ Anthropic ): MCP Servers: These are lightweight connectors or adapters that interface with a specific tool or data source (e.g. a database, a web API, Gmail, Slack, etc.). Each server exposes certain capabilities (like “search emails” or “query database”) via the standardized MCP interface. MCP Clients: These live with the AI model (often embedded in the AI application or agent). The client connects to one or more MCP servers. When the AI needs something (data or an action), it sends a request via the client to the appropriate server. Hosts: The environment where the AI and MCP client run (this could be a chat app, IDE, or your AI-powered app itself). The host initiates the connection and orchestrates the overall session ( Core architecture - Model Context Protocol ). When a user gives a prompt or task, the MCP client analyzes the request and figures out which tool or context it needs. It then sends a message to the relevant MCP server , which does the heavy lifting (e.g. fetching the latest stock price from an API or sending an email via Gmail’s API). The server returns the result, and the AI can incorporate it into its response. All of this happens through a consistent message format defined by MCP, rather than ad-hoc prompt engineering. In fact, MCP defines clear patterns for providing context to models, managing tool use, and handling responses – much like how REST standardized web service communication ( Understanding the Model Context Protocol (MCP) | deepset Blog ). This means developers don’t have to reinvent the wheel for each new data source or worry about the low-level prompt structure; MCP has a blueprint for it. Why MCP Matters for AI App Developers MCP is a game-changer because it bridges the gap between isolated AI models and the rich world of data and services they often need to be truly useful ( Introducing the Model Context Protocol \ Anthropic ). Here are some of the big benefits of MCP: Standardized Integrations: No more writing one-off code for every API or database your AI needs to use. MCP provides a universal adapter layer. Once a data source has an MCP server, any AI agent can plug into it and retrieve info or trigger actions in a consistent way ( Model Context Protocol (MCP): 8 MCP Servers Every Developer Should Try! - DEV Community ). This fosters an ecosystem of reusable connectors – build a connector once and any future LLM or AI app can reuse it. It’s plug-and-play AI development. Enhanced Context & “App Memory”: Because MCP lets the AI fetch data on demand, you aren’t limited by the model’s built-in context window. Your AI app can maintain long-term context or memory by storing info externally and pulling it in when needed. For example, an MCP server could interface with a database or knowledge base containing chat history, user preferences, or any extended context. The AI can query that via MCP, effectively extending its memory beyond the few-thousand-token limit. Even better, with new remote MCP servers , the server can retain user-specific context between sessions, providing a persistent experience like an app memory ( Cloudflare Accelerates AI Agent Development With The Industry's First Remote MCP Server | Cloudflare ). (No more repeating the entire conversation history to the model every time – the context can be stored once and referenced as needed.) Action-Oriented AI (beyond just text answers): Traditionally, LLMs could only answer questions or give advice. With MCP, they can take actions on the user’s behalf in a controlled manner. In the example above, the AI actually sent an email after looking up data. MCP opens the door to AI agents that can, for instance, book calendar events, execute code deployments, or interact with enterprise systems directly ( Cloudflare Accelerates AI Agent Development With The Industry's First Remote MCP Server | Cloudflare ) – all through standard connectors. This can dramatically streamline workflows (imagine an AI agent that not only tells you “Looks like you’re low on inventory” but also automatically creates a purchase order through an MCP-connected ERP system). Faster Development Cycles: By removing the need for bespoke integrations, MCP lets developers prototype and iterate faster. Want to add a new feature to your AI app that uses a third-party service? If an MCP server exists for it, you can connect it in minutes without diving into API docs and writing boilerplate. Even if it doesn’t exist yet, MCP’s standard makes it straightforward to implement one. This means you spend more time on your app’s logic and less on plumbing. As one analyst put it, MCP is proving “incredibly valuable for building AI applications faster” by becoming the new standard for communicating context in agent-based systems ( Understanding the Model Context Protocol (MCP) | deepset Blog ) ( Understanding the Model Context Protocol (MCP) | deepset Blog ). Interoperability & Flexibility: MCP is model-agnostic and platform-agnostic. Your AI app can switch out the underlying LLM (be it OpenAI, Anthropic’s Claude, etc.) or move between environments, and as long as the new environment supports MCP, your integrations still work ( Introduction - Model Context Protocol ). This decoupling of tools from the AI model gives you flexibility to use the best model for the job without rebuilding integrations. It also means different AI applications can share a common pool of MCP servers. For developers, this hints at a future where AI services and tools compose together more easily – akin to how any browser can talk to any web server thanks to HTTP. Built-in Best Practices (Security & Auth): Integrating an AI with sensitive data or powerful tools raises security questions – you don’t want an AI agent emailing your entire contact list or pulling confidential data unless authorized. MCP was designed with security in mind, leveraging battle-tested standards like OAuth 2.0 for authentication and permissioning ( Build and deploy Remote Model Context Protocol (MCP) servers to Cloudflare ). In an MCP setup, users explicitly grant an AI agent access to a resource via the MCP server’s auth flow, so there’s clear permission control. Fine-grained scopes ensure the AI can only do what it’s allowed to. This standardized auth means developers don’t have to roll their own unsafe solutions – it’s baked into the protocol. The result is improved security for AI integrations ( Model Context Protocol (MCP): 8 MCP Servers Every Developer Should Try! - DEV Community ), making it viable to connect enterprise systems to AI without opening undue risk. In short, MCP makes AI development more seamless, scalable, and secure . It takes care of the “glue” – the prompt structuring, tool invocation, and context passing – so you can focus on building cool features, not wrestling with how to feed data into your model. Accelerating AI App Development with Fine.dev and MCP So how does this relate to Fine.dev , and what is Fine exactly? Fine is an all-in-one platform that lets anyone build, deploy, and run AI-powered web applications with minimal effort. It’s often described as having an “AI junior developer” on your team. You simply tell Fine (in plain English) what you want your app to do, and Fine’s AI agents handle building the frontend, backend, database, and deployment for you ( Fine: Anyone can build. ) ( Fine: Anyone can build. ). In other words, Fine is an AI app builder – from UI to server logic, it can generate the code and set up the infrastructure automatically. Crucially, Fine.dev bakes in all the pieces an AI app needs out of the box . As Fine’s founder describes, “every project our users build comes with auth, database, file storage, LLM integration, and hosting, all working out of the box.” ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ) That’s a huge boost for developer productivity – no wrestling with 10 different services or cloud accounts just to get a basic app running. Everything is pre-integrated and ready to go: User Authentication: Built-in login/auth system so your users can sign up and sign in without extra services ( Fine: Anyone can build. ). Database (Postgres): An instantly available database (powered by Cloudflare D1) for your app’s data ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ). File Storage: Built-in object storage (via Cloudflare R2) for any media or file needs ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ). Backend Functions: Serverless backend logic using Cloudflare Workers – you can extend your app without managing servers ( Fine: Anyone can build. ). LLM Integration: Easy integration of large language models like OpenAI GPT-4 or Anthropic Claude into your app’s features ( Fine: Anyone can build. ). One-Click Deployment: Automatic deployment to a global edge network (Cloudflare’s network) so your app is live and fast everywhere by default ( Fine: Anyone can build. ). Fine’s philosophy is to eliminate the friction in going from an idea to a live product. As the founder put it, the goal is that “anyone, literally anyone, will be able to build and launch something useful… without wrestling with infrastructure… without spending weeks before seeing something live.” ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ) Fine achieves this “magic” by leveraging a Cloudflare-based stack where the infrastructure just melts away behind the scenes ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ). Fine uses Cloudflare Workers for compute, D1 for the database, and so on ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ) – meaning your app runs on a globally distributed platform, scalable and secure by default. Now, where does MCP come in? Fine.dev embraces MCP as a core part of simplifying AI app development. Fine’s platform is essentially built to harness AI agents with context . When you tell Fine what app to build, an LLM agent generates code and configures your app. That agent needs context: it needs to understand your request, the code it’s writing, the data your app will handle, etc. MCP’s principles are at play here – Fine’s AI agent can pull in context about common app functionalities (auth, database schema) and use standardized “knowledge” to assemble your app quickly. In fact, Fine even has a proprietary knowledge graph (“Atlas”) that gives the AI agent awareness of your codebase and dependencies ( Fine - AI-Powered Development | Fine ), akin to providing it an MCP-like interface to your project’s context. Moreover, once your app is built on Fine, you can incorporate AI features into that app just as easily. Suppose you build an AI-powered SaaS app that needs to, say, analyze user data from the database and send summary reports via email. Because Fine already has MCP-compatible connectors behind the scenes (database, email service, etc.), your app’s AI components can use them without you writing glue code. Fine is built on the same Cloudflare platform that introduced the first remote MCP server , so your app’s AI agents can securely connect to tools over the internet – no local setup needed ( Cloudflare Accelerates AI Agent Development With The Industry's First Remote MCP Server | Cloudflare ). This means the AI features in your app can have persistent state and memory (using Fine’s database or Cloudflare’s Durable Objects) and can perform multi-step actions (using Cloudflare Workflows) as first-class capabilities. Fine essentially provides an MCP-enabled runtime for your AI app. To make this concrete, imagine you’re using Fine to build a customer support chatbot for a product. You want the chatbot to answer questions, but also create support tickets in Jira and look up order info from a database. Without MCP, you’d have to manually code the integrations with Jira’s API and your database, and carefully craft prompts to include that data. With Fine and MCP, much of this is handled for you. Fine would scaffold the app with a database and possibly an MCP server interface to it. The chatbot (an AI agent in the app) can be given access to a “Jira MCP server” and your app’s database through MCP. So when a user asks “What’s the status of my order #1234?”, the AI client in your app queries the database via MCP, and when they say “please escalate this issue,” the AI can create a Jira ticket via another MCP call. All of it happens behind a consistent API, accelerating your development and reducing friction. You focus on defining the high-level workflow, and Fine’s AI + MCP handles the rest. Fine.dev’s real-world users are already reaping the benefits of this approach. Early adopters have used Fine to ship everything from AI agents and micro-SaaS apps to internal business tools in a fraction of the time it would normally take ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ). And despite the diverse use cases, they report that working with all the integrated pieces is “smooth as butter” – the infrastructure complexity just disappears ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ). This is the power of having an all-in-one platform that leverages standards like MCP: you get to build faster and with less friction . Fine’s stack handles the heavy lifting (scaling, auth, integrations), so you can iterate on your idea quickly. In fact, Fine launched its platform by turning a single prompt into a production-ready app ( We built our entire AI App Builder on Cloudflare stack, and it's awesome | Hacker News ), showcasing how an AI (with proper context and integration) can generate a fully working application almost instantly. That’s MCP in action – providing the AI with the building blocks it needs, so it can do in minutes what used to take developers weeks. Getting Started with Fine (and MCP) – Build Your AI App Now One of the best parts about Fine.dev is how easy it is to get started, even if you’re not an AI expert. You don’t have to worry about setting up any of the MCP servers or infrastructure yourself – Fine has done the hard work for you. Here’s how you can start building with Fine and leverage MCP as your secret sauce: Sign Up for Fine.dev: Head over to Fine’s website and create a free account. Fine offers a free tier to experiment with your first app ( Fine: Anyone can build. ), so you can try it out with zero cost. No complex installation or environment setup – everything runs in the cloud. Describe Your App Idea: Once you’re in, you’ll use Fine’s AI App Builder. This is where the magic happens. You simply describe in natural language what you want your app to do. For example, you might say: “I want to build a personal finance app that tracks expenses, uses an AI chatbot to give budgeting tips, and allows logging in with Google.” Don’t worry about phrasing it perfectly – just explain the features or user stories. Fine’s AI agent will understand your intent. Watch Fine’s AI Build it: When you submit your description, Fine’s AI coding agent (powered by LLMs) goes to work. Thanks to its training and context (and behind-the-scenes protocols like MCP), it knows how to translate your request into a full-stack application. It will generate the frontend UI, setup the backend routes/functions, configure the database models, and even integrate any AI or external services you mentioned. You can literally see the app being scaffolded in minutes, without writing a single line of code. (Yes, it feels like sci-fi.) Fine’s AI can even answer questions about the code or make tweaks if you ask, just like a human collaborator. Iterate and Refine: You can test the app right in the browser. Fine provides a development preview URL where your app is running. Try logging in, adding some data, or asking the AI chatbot a question (in our example app). If something isn’t quite right, you can go back and Ask Fine’s AI to adjust it – e.g., “Make the budget tips more formal,” or “Add a chart for spending over time.” The AI will modify the code accordingly. This tight feedback loop is where MCP’s context power shines: the AI always has the context of your app’s state and can seamlessly incorporate new requirements. Deploy with One Click: Happy with the result? Deploy it! Fine handles the entire deployment process – packaging your app, deploying it to its global edge infrastructure, setting up domains, etc. ( Fine: Anyone can build. ). You just hit Deploy , and your app goes live to the world. Because everything is on Fine’s Cloudflare-powered stack, your app will automatically scale and stay performant. Fine even gives you a custom domain or you can bring your own. Congratulations, you built an AI-powered app in a weekend (or less)! Throughout this process, MCP is quietly at work ensuring your AI functionalities integrate smoothly. For example, when your personal finance app’s chatbot needs to pull in the user’s latest transactions from the database, Fine’s MCP integration makes that as easy as a function call – the AI doesn’t hallucinate the data, it actually retrieves it via the MCP server that Fine set up for the database. When the app’s AI needs to advise the user, it can use relevant context (perhaps a budgeting formula or user’s past spending behavior) fetched through MCP. As a builder, you didn’t need to code any of that plumbing; you described the outcome, and Fine’s platform (with MCP as a core enabler) made it happen. Conclusion The Model Context Protocol is accelerating the evolution of AI apps from siloed chatbots to truly interactive, context-aware agents . It simplifies the hardest parts of AI app development – integrating data, maintaining memory, and performing actions – by offering a standard way to do it all. Fine.dev takes this a step further by packaging MCP’s capabilities into a builder-friendly platform. With Fine, you can go from idea to a live AI-powered application incredibly fast, without getting bogged down by integration code or infrastructure setup. It’s a conversational, intuitive way to build software: you tell Fine what you need, and it leverages AI (and protocols like MCP) to turn that into reality. 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 | 2026-01-13T08:48:23 |
https://devblogs.microsoft.com/visualstudio/author/vacvan | Václav Vančura, Author at Visual Studio Blog Skip to main content Microsoft Dev Blogs Dev Blogs Dev Blogs Home Developer Microsoft for Developers Visual Studio Visual Studio Code Develop from the cloud All things Azure Xcode DevOps Windows Developer ISE Developer Azure SDK Command Line Aspire Technology DirectX Semantic Kernel Languages C++ C# F# TypeScript PowerShell Team Python Java Java Blog in Chinese Go .NET All .NET posts .NET Aspire .NET MAUI AI ASP.NET Core Blazor Entity Framework NuGet Servicing .NET Blog in Chinese Platform Development #ifdef Windows Microsoft Foundry Azure Government Azure VM Runtime Team Bing Dev Center Microsoft Edge Dev Microsoft Azure Microsoft 365 Developer Microsoft Entra Identity Developer Old New Thing Power Platform Data Development Azure Cosmos DB Azure Data Studio Azure SQL OData Revolutions R Unified Data Model (IDEAs) Microsoft Entra PowerShell More Search Search No results Cancel Dev Blogs Visual Studio Blog Václav Vančura Václav Vančura Senior Designer, Visual Studio for Mac Václav is a Senior Designer for Visual Studio For Mac, focusing on the shell design, icons, and overall user interface and experience. He also works on several other Microsoft products: VS IDE, Live Share, and others. Before joining Xamarin and Microsoft, he was a web developer, game designer and coder, Flash engineer and animator, comic book artist, and advertisement illustrator. He's got three kids, a wife, and two cats. Author Topics Visual Studio for Mac Visual Studio 2019 for Mac Accessibility Posts by this author Feb 10, 2020 Post comments count 7 Post likes count 0 Accessibility Improvements in Visual Studio 2019 for Mac The release of Visual Studio 2019 for Mac version 8.4.4, includes numerous developments in the color representation of icons, and to warning and error status messages. Visual Studio for Mac Visual Studio 2019 for Mac Accessibility Sign in Theme Code Block × Paste your code snippet Ok Cancel What's new Surface Pro Surface Laptop Surface Laptop Studio 2 Copilot for organizations Copilot for personal use AI in Windows Explore Microsoft products Windows 11 apps Microsoft Store Account profile Download Center Microsoft Store support Returns Order tracking Certified Refurbished Microsoft Store Promise Flexible Payments Education Microsoft in education Devices for education Microsoft Teams for Education Microsoft 365 Education How to buy for your school Educator training and development Deals for students and parents AI for education Business Microsoft Cloud Microsoft Security Dynamics 365 Microsoft 365 Microsoft Power Platform Microsoft Teams Microsoft 365 Copilot Small Business Developer & IT Azure Microsoft Developer Microsoft Learn Support for AI marketplace apps Microsoft Tech Community Microsoft Marketplace Marketplace Rewards Visual Studio Company Careers About Microsoft Company news Privacy at Microsoft Investors Diversity and inclusion Accessibility Sustainability Your Privacy Choices Opt-Out Icon Your Privacy Choices Your Privacy Choices Opt-Out Icon Your Privacy Choices Consumer Health Privacy Sitemap Contact Microsoft Privacy Manage cookies Terms of use Trademarks Safety & eco Recycling About our ads © Microsoft 2025 | 2026-01-13T08:48:23 |
https://www.fine.dev/blog/github-copilot-with-claude | GitHub Copilot and Claude: What You Need to Know Home Docs Changelog Pricing Sign in Get started -> Menu Home Docs Changelog Pricing <- Go Back GitHub Copilot and Claude: What You Need to Know GitHub Copilot has been a developer's companion for a while now, with a new feature catching everyone's eye—integration with Claude, an AI model developed by Anthropic. But how does it stack up against the GitHub Copilot we're used to, and should you use GitHub Copilot with Claude? Let’s dive into it, including how this setup compares to Fine , a modern AI development platform that gives developers more power and choice. Table of Contents Should I Use GitHub Copilot with Claude? Is GPT or Claude Faster in GitHub Copilot? How to Set Up Claude in GitHub Copilot Why Fine is the Better Choice for Developers Ready to Take Your Coding to the Next Level? Should I Use GitHub Copilot with Claude? For months, Claude 3.5 Sonnet has been accepted as the better LLM for coding compared to GPT-4. Using GitHub Copilot with Claude can help developers who prefer a broader context understanding when writing and optimizing code. Claude's strength lies in natural language processing and its ability to generate human-like responses, which may come in handy for devs seeking greater conversational interaction. Claude 3.5 Sonnet, which was announced on October 29th at GitHub Universe 2024, is currently in public preview and available to all Copilot plans over a two-week rollout. Initially, Claude 3.5 Sonnet is available in Copilot Chat for Visual Studio Code and in immersive chat on the GitHub website. It excels at coding tasks across the entire software development lifecycle, from initial design to bug fixes, maintenance to optimizations. However, there are limitations to pairing GitHub Copilot with Claude. For one, it remains just another integration in the Copilot ecosystem, subject to GitHub’s usage policies and pricing tiers. You may still find that the depth of Claude's integration within Copilot lacks the smoothness that many developers crave when switching between models or fine-tuning AI behavior. With Fine , developers aren’t limited by these constraints. You can seamlessly switch between GPT-4o, Claude 3.5 Sonnet, and GPT o1-preview, all without extra charges. This flexibility means that you can utilize the specific strengths of each model based on the context of your coding problem—a luxury GitHub Copilot simply doesn’t provide. Is GPT or Claude Faster in GitHub Copilot? Speed is a key factor for developers when choosing an AI assistant. Generally, GPT-4 is a powerful and versatile model, capable of quickly producing accurate code snippets. Claude, on the other hand, tends to excel at understanding extended conversations, but it might lag slightly behind GPT in generating complex or niche code solutions due to its more conservative approach. If you’re choosing between GPT and Claude in GitHub Copilot, your choice will depend on your needs. GPT-4 is typically faster for raw code generation, while Claude might shine in contexts where explanations or detailed discussions are needed. However, there's still some inconsistency in switching between these models while using GitHub Copilot. Fine has managed to solve this issue elegantly. You don’t have to compromise on speed—you can switch between models fluidly, depending on your needs for coding or explaining concepts, and without facing any hidden costs. Fine empowers you to have the fastest and most relevant AI model in your toolkit whenever you need it, whereas GitHub Copilot limits you to a specific model per instance. How to Set Up Claude in GitHub Copilot If you’re curious about how to get started with Claude in GitHub Copilot, it’s fairly straightforward. First, ensure you have GitHub Copilot installed as an extension in your IDE, then follow these steps: Update GitHub Copilot : Check if there’s an update available that includes support for Claude 3.5 Sonnet, as this feature might be in beta or have specific requirements. Enable Claude Integration : Head into the settings of your GitHub Copilot. There, you can choose between available AI models and select Claude if it's available in your region or subscription. You may also be prompted to enable Claude 3.5 Sonnet the first time you use Copilot Chat in Visual Studio Code or in the immersive view on the GitHub website. Check Access Availability : To know if you or your organization has access to Claude 3.5 Sonnet, check the bottom of your Copilot policy settings. If there is no policy listed for Anthropic Claude 3.5 Sonnet, you have not yet received access via the rollout. Use Claude in Your Workflow : Once enabled, start coding. You’ll be able to see the suggestions from Claude, similar to those from GPT, but keep in mind that you may need a compatible tier to access this model. Setup for organizational use involves the organization owner enabling or disabling Claude 3.5 Sonnet for all assigned Copilot Business users. See GitHub's documentation on managing policies for more details. While this process is not overly complex, it does involve additional steps and may incur extra costs, depending on your subscription. In contrast, with Fine , you don’t need to fuss over updates, availability, or paywall restrictions—you simply switch models in real-time without worrying about fees or beta features. Why Fine is the Better Choice for Developers The ability to switch between AI models on the fly is crucial for a productive development experience. Fine takes the lead by providing access to multiple advanced models, including Claude 3.5 Sonnet, GPT4o, and GPT o1-preview—all without any additional cost to the user. This empowers developers to choose the best model for each specific coding task, be it raw code generation, deeper context understanding, or debugging. Fine ’s newly introduced AI Sandboxing feature also takes collaboration up a notch. It allows developers to build, run, and test AI-generated code within a secure virtual environment right in their browser. No more “works on my machine” issues— Fine ensures that all code runs smoothly across environments and is ready for review or sharing without a hitch. In contrast, GitHub Copilot’s reliance on limited integrations and subscription-based access keeps developers boxed in. Fine ’s flexibility, integrated live testing, and straightforward approach make it the standout choice for developers who want control, speed, and ease of use. If you're a startup looking to save serious time - Fine allows you to delegate entire tasks to AI, letting your development team focus on the bigger projects. Ready to Supercharge Your Development? GitHub Copilot with Claude may offer an interesting blend of capabilities, but it comes with limitations, such as added costs, lack of flexibility, and complex setup processes. On the other hand, Fine provides developers with unparalleled flexibility, real-time access to multiple advanced models, and a powerful sandboxing environment—all without hidden costs or complex restrictions. Sources GitHub Copilot Documentation - Using Claude 3.5 Sonnet Fine - Collaborative AI Coding Platform GitHub Universe 2024 - Claude 3.5 Sonnet Announcement How Fine Works 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 | 2026-01-13T08:48:23 |
https://nutrify.app/terms#privacy-policy | Nutrify Terms & Conditions Nutrify homepage TERMS AND CONDITIONS Last updated: 21 February 2024 Nutrify: The Food App (‘ Nutrify ’ or ‘ App ’) belongs to Craizy Pty Ltd trading as Craizy Studios (ABN 32 672 081 604) (‘ Craizy Studios ’, ‘ we ’, ‘ our ’ or ‘ us ’). This page sets out: information about registration and accounts; the costs of the App, App subscription, cancellation, and our refund policy; our privacy policy; and our website terms of use. If you access and use Nutrify, you are taken to have agreed to these terms and conditions. If you have any questions, please contact us on [email protected] . REGISTRATION AND ACCOUNTS Nutrify can be downloaded from the Apple App Store . To use certain features of Nutrify, you may be required to create an account. You agree to provide accurate, current, and complete information during the registration process. You are responsible for maintaining the security of your account and password. You may not share your account with others, and you agree not to sell or transfer your account to another party. How do I get notified of the changes in the App? Please be aware that we may make changes to our App in the future. Any information about the changes will be available through Nutrify notifications and App updates, by email (if you have subscribed), and our website at https://www.nutrify.app . App Accuracy The results and information provided by Nutrify may not always be entirely accurate, as they are generated using computer vision and machine learning technology. The accuracy of Nutrify’s assessments and recommendations can be influenced by factors such as the quality of input data and the inherent limitations of these technologies. It is essential for you to exercise your own discretion and not rely solely on Nutrify’s results for making critical decisions, especially in determining whether something is edible or not. When it comes to matters like dietary choices or health-related decisions, we advise you to consult with qualified professionals or trusted sources to ensure the most accurate and reliable information. Please be aware that Craizy Studios and our third parties do not assume responsibility for any action or inaction taken based on the App's results. Nutrify is intended for informational purposes and should not replace expert advice or common sense. Information provided by Nutrify is collated from reputable third-party sources. You acknowledge that the information provided belongs to third parties and that Craizy Studios will not assume any responsibility for their accuracy or validity in any way. Where possible, Nutrify will provide reference information to support materials. You acknowledge that the information or support materials are not the responsibility of Nutrify and may change without notice. APP COSTS How much does it cost to download Nutrify? Nutrify is free to download via the Apple App Store . However, Nutrify offers subscription-based access to premium features at USD 3.99/month (inc GST) or USD 24.99/year (inc GST). Please note these are base prices and may be subject to Apple's App Store price adjustments based on region. So the price you see in the App Store/inside the Nutrify app may be slightly different to what is listed here. Monthly or yearly subscription fees are to be paid through Apple’s App Store payments. Does Nutrify offer a free trial? Nutrify may, at its discretion, offer a free trial for a limited period of time. At the end of the free trial period, your payment method as provided by the Apple App Store will be charged unless you cancel your subscription within the trial period. Nutrify reserve the right to modify the terms and conditions of the free trial or cancel a free trial offer at any time and without notice. Where can I find the subscription fees? The subscription fees are displayed on Nutrify. We endeavour to maintain accurate information on our App, but from time to time there may be an error. If the subscription price is more or less than the price displayed, we reserve the right to correct the error. Who can I talk to about my subscription? If you have any questions regarding your subscription or the App, please contact us at [email protected] or through our website https://www.nutrify.app . Nutrify and Craizy Studios are not involved in the processing any payments made to use the App. Please refer to the legal disclaimers provided by the Apple App Store for any questions about how payment is processed. Can I cancel or modify my subscription? You acknowledge that Nutrify’s cancellation policy is consistent with Apple’s App Store purchases cancellation policy. Those terms will also govern your use of the App. Should you wish to change or cancel your subscription after your payment has been processed, click here for instructions. How do I request a refund? Nutrify’s refund policy are in line with Apple’s App Store purchases. You acknowledge that Apple’s App Store’s refund policy also governs your use of the App. To request for a refund, click here for instructions. Our goods and services come with guarantees that cannot be excluded under the Australian Consumer Law. For major failures with the service, you are entitled: to cancel your service contract with us; and to a refund for the unused portion, or to compensation for its reduced value. You are also entitled to choose a refund or replacement for major failures with goods. If a failure with the goods or a service does not amount to a major failure, you are entitled to have the failure rectified in a reasonable time. If this is not done, you are entitled to a refund for the goods and to cancel the contract for the service and obtain a refund of any unused portion. You are also entitled to be compensated for any other reasonably foreseeable loss or damage from a failure in the goods or service. PRIVACY POLICY Craizy Studios respects your right to privacy and is committed to safeguarding the privacy of our customers and website visitors. We comply with the Australian Privacy Principles contained in the Privacy Act 1988 (Cth).Our commitment to privacy extends across all regions where our services are available. This policy sets out how we collect and treat your personal information. What personal information do we collect? Craizy Studios will, from time to time, receive and store personal information you enter onto our website, provided to us directly or given to us in other forms. You may provide basic information such as your name, email address and log in details to enable us to send information, provide updates, process your subscription and for you to enjoy and use Nutrify. As Nutrify is a photo-based food education App, you may provide images to us, which play a fundamental role in fulfilling the App's core purpose and enhancing the computer vision models powering it. Additionally, we may also collect other personal information you provide while interacting with us. How do we collect your personal information? We collect personal information from you in a variety of ways, including when you interact with us electronically and when you access Nutrify and our website. We only collect personal information that you provide to us directly. We may collect additional information at other times, including but not limited to, when you provide feedback, when you provide information about your personal or business affairs, change your email preferences, respond to surveys and/or promotions, or communicate with us. How do we use your personal information? We may use personal information collected from you to provide you with information, updates, products, and services. We may also make you aware of new and additional products, services, and opportunities available to you. We may use your personal information to improve our services and better understand your needs. We may also use your personal information to contact you about our products and services, including for marketing purposes. You can opt out of receiving marketing material at any time. How do we disclose your personal information? We do not and will not sell or deal in personal information or any customer information. We may disclose your personal information to any of our employees, officers, insurers, professional advisers, agents, suppliers, or subcontractors. We will only do this to the extent it is reasonably necessary to provide our products or services to you. We may from time to time need to disclose personal information to comply with our legal obligations. We may, however, use and disclose images you have submitted through Nutrify. It is important to note that only images of food should be submitted through the App or our website. You must refrain from providing images containing personal, private, or sensitive information. While we are constantly improving our systems to ensure that any images containing personal or private information that are inadvertently submitted are flagged and handled with the utmost care and discretion, you acknowledge and agree that Craizy Studios bears no responsibility for any images you choose to submit. You acknowledge and agree that by capturing images of food using Nutrify, you grant us an unrestricted, worldwide license to use, distribute, display, and share these images. This includes, but is not limited to, the use of these images for training computer vision and other machine learning models to enhance the App’s services, sharing images as part of an open-source database, and incorporating images into Nutrify’s documentation and reference materials. Please be aware that Nutrify is solely interested in images of food. We do not seek or use images containing people, faces, or items unrelated to food. Any personal data contained within the photographs provided to Nutrify will be removed prior to any usage as described above. We may also use your personal information to protect the copyright, trademarks, legal rights, property, or safety of Craizy Studios, Nutrify, https://www.nutrify.app , our customers or third parties. Information that we collect may from time to time be stored, processed in, or transferred between parties located in countries outside of Australia. If there is a change of control in our business or a sale or transfer of business assets, we reserve the right to transfer (to the extent we are legally able to) our user databases, together with any personal information and non-personal information contained in those databases. This information may be disclosed to a potential purchaser under an agreement to maintain confidentiality. We would seek to only disclose information in good faith and where required by any of the above circumstances. By providing us with personal information, you consent to the terms of this privacy policy and the types of disclosure covered by this Policy. Where we disclose your personal information to third parties, we will request that the third party follow this Policy regarding handling your personal information. How do we secure your personal information? We are committed to ensuring that the information you provide to us is secure. In order to prevent unauthorised access or disclosure, we have put in place suitable physical, electronic, and managerial procedures to safeguard and secure information and protect it from misuse, interference, loss and unauthorised access, modification, and disclosure. The transmission and exchange of information is carried out at your own risk. We cannot guarantee the security of any information that you transmit to or receive from us. How can you access your personal information? You may request details of personal information that we hold about you by emailing us at [email protected] . We reserve the right to refuse to provide you with information that we hold about you, in certain circumstances set out in the Privacy Act. What rights do you have in relation to your personal information? You have the right to access your personal information and require us to correct any of your personal information. Changes to privacy policy Please be aware that we may make changes to our privacy policy in the future. Please check back from time to time to review our privacy policy. Cookies and Pixels A cookie is a small file placed in your web browser that collects information about your web browsing history. Use of cookies allows a website to tailor its configuration to your needs and preferences. Cookies do not access information stored on your computer or any personal information (for example: name, address, email address or telephone number). Most web browsers automatically accept cookies, but you can choose to reject cookies by changing your browser settings. This may, however, prevent you from taking full advantage of our App and website. Our App and website may use cookies to analyse website traffic, provide social media sharing and liking functionality and help us provide a better user experience for visitors to our website. In addition, cookies and pixels may be used to serve relevant ads to website visitors through third party services such as Google Adwords and Facebook Adverts. These ads may appear on this website or other websites you visit. WEBSITE TERMS OF USE Intellectual Property Rights Our website https://www.nutrify.app contains intellectual property (including copyright) owned by Craizy Pty Ltd trading as Craizy Studios and third parties. We and our third parties retain all rights, title and interest in our website and all related content. Nothing you do on or in relation to the website will transfer to you: the business name, trading name, domain name, trademark, industrial design, patent, registered design, or copyright; or the right to use or exploit a business name, trading name, domain name, trademark, or industrial design; or a system or process that is the subject of a patent, or copyright (or an adaptation or modification of such a system or process), of Craizy Pty Ltd and any third party. General information When you come to our website https://www.nutrify.app we may collect certain information such as browser type, operating system, websites visited immediately before coming to our site, etc. This information is used in an aggregated manner to analyse how people use our site, such that we can improve our service. Links to Third Party Websites Our website may contain links to other websites. These links are meant for your convenience only. Links to third party websites do not constitute sponsorship or endorsement or approval of these websites. Please be aware that we are not responsible for the privacy practices of such other websites. We encourage our users to be aware, when they leave our website, to read the privacy statements of each and every website that collects personally identifiable information. This privacy policy applies solely to information collected by this website. Content and product descriptions We do not warrant that product descriptions or other content of this website is accurate, complete, reliable, current, or error-free. We may update any content on our website at any time without notice. Reviews and comments When visiting our website or social media pages, and subject to your compliance with these terms, you may post reviews and comments. If your reviews or comments contain defamatory, misleading, or false statements or is threatening, aggressive or contains obscenities, or is otherwise contrary to the relevant social media platform’s content or other rules, we may remove your reviews and comments and remove your access to our website and social media pages. We reserve the right to remove or edit any content that you post on our website. You acknowledge that any content posted by you on our website or social media pages becomes our property. For this purpose, you grant us a non-exclusive, royalty-free, perpetual, irrevocable, and fully sublicensable right to use, distribute and display such content in any way we see fit, throughout the world and in any media. You agree to indemnify us for all claims made against us resulting from your reviews or comments on our website or social media pages. You acknowledge that we are not the author of any reviews or comments on our website or social media pages and that we are not responsible and do not assume any liability for any content posted by you or any third party. If you are concerned about any reviews or comments, please contact us at [email protected] . Customer account security For security purposes, you must not share your customer Account login details. If you use this site, you are responsible for maintaining the confidentiality of your customer account and password and for restricting access to your computer, and you agree to accept responsibility for all activities that occur under your customer account or password. We can terminate your customer account at any time and in our sole discretion. If a customer is under 18 years of age and purchasing an item with a credit card, we will require the consent of a parent or guardian at the time of purchase. Credit card information We do not store any credit card information that you provide. If payments are made via our App, they are securely managed by the Apple App Store in compliance with relevant standards. Suspending or terminating site access We may suspend or terminate your access to and use of our website, without notice, if you are in breach of these terms. Viruses We make every attempt to ensure that the website is free of viruses and other malicious code which may affect your computer systems. However, your access to and use of the website and App are at your own risk, and you must take your own precautions to avoid and protect your computer systems against any viruses and other malicious code. Cyber security If, due to events beyond our reasonable control, you incur any loss or damage arising from a cyber security event in relation to our website, email communications, payment gateway providers or products, you acknowledge that we are not liable. You must take appropriate steps to ensure that any requests for payment purporting to be from Craizy Studios are genuine, including by calling or emailing us to request confirmation. Contact us If you have any questions or concerns regarding our information about registration and accounts, App costs, subscription, our cancellation and refund policy, privacy policy or website terms and conditions, please contact us at [email protected] and we will endeavour to respond within 48 hours. How can I make a complaint? If you wish to make a complaint, please submit details of your complaint to [email protected] . We will investigate and respond as soon as possible after receiving written notice of your complaint. If your complaint relates to any payment, please note that Nutrify is unable to assist. All such enquiries should be directed to the Apple App Store. | 2026-01-13T08:48:23 |
https://dumb.dev.to/software-comparisons | Software Comparisons — What are the differences, pros and cons? - DUMB 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 DUMB DEV Community Close Software Comparisons — What are the differences, pros and cons? This is a list of top posts that members of the community have created. These are the posts folks have generally continued coming back to over and over again, so we created this page to make some of these more discoverable. Hopefully you better understand some of the differences here once you've found the guide you need! Redux vs Context API: When to use them Declarative vs imperative Using then() vs Async/Await in JavaScript Kubernetes Ingress vs Service Mesh Create react app vs Vite Callbacks vs Promises Constructors in Python ( init vs __new ) When to Use Server-Side rendering vs Static Generation in Next.js CSS Modules vs CSS-in-JS. Who wins? append VS appendChild Cloud Run vs App Engine: a head-to-head comparison using facts and science Logical OR (||) vs Nullish Coalescing Operator (??) in JavaScript Server-Side Rendering (SSR) Vs Client-Side Rendering (CSR) Asp Net Core - Rest API Authorization with JWT (Roles Vs Claims Vs Policy) - Step by Step Python GUI, PyQt vs TKinter web3.js vs ethers.js: a Comparison of Web3 Libraries Cookies vs Local Storage vs Session Storage React Router V5 vs V6 LocalStorage vs Cookies: All You Need To Know About Storing JWT Tokens Securely in The Front-End TailwindCSS vs Styled-Components in ReactJs WebSockets vs Long Polling JSX.Element vs ReactElement vs ReactNode useState() vs setState() - Strings, Objects, and Arrays Methods vs Computed in Vue React: class components vs function components Supabase Vs Firebase Pricing and When To Use Which for loop vs .map() for making multiple API calls 🤝 Promise.allSettled() VS Promise.all() in JavaScript 🍭 React vs Vue vs Angular vs Svelte Azure Artifacts vs Build Artifacts vs Pipeline Artifacts: Difference EXPLAINED! When to use Svelte vs SvelteKit vs Sapper? C#, Task.WhenAll vs Parallel.ForEach Map vs MergeMap vs SwitchMap CSS 3 VS Tailwind CSS Serverless Framework vs SAM vs AWS CDK Angular: Setters vs ngOnChanges - which one is better? Interview question: heap vs stack (C#) JS interview in 2 minutes / Static vs Dynamic typing DynamoDB Scan Vs Query Operation Experiment Result componentWillMount() vs componentDidMount() Anonymous Functions vs Named Functions vs Arrow Functions Flexbox - Align Items vs Align Content. Vue vs React: What to choose in 2021? Laravel Jetstream vs Breeze vs Laravel/ui Linux Vs Windows - Why Linux Is Better For Programming & Web Dev (A newbie experience) Fibonacci: Recursion vs Iteration TypedDict vs dataclasses in Python — Epic typing BATTLE! SSR vs CSR Callback vs Promises vs Async Await Poetry vs pip: Or How to Forget Forever "requirements.txt" Cheat Sheet for Beginners Cypress vs WebdriverIO | Which one to pick? Type Aliases vs Interfaces in TypeScript PyQt vs Tkinter (Spanish) Django vs Mern Which one to choose? YYYY vs yyyy - The day the Java Date Formatter hurt my brain JavaScript - debounce vs throttle ⏱ Go: Fiber vs Echo (a developer point) RxJS debounce vs throttle vs audit vs sample — Difference You Should Know Laravel vs Node.js - Which One Is The Best Back-End To Choose In 2021? Composer update Vs Composer Install Concurrency in modern programming languages: Rust vs Go vs Java vs Node.js vs Deno vs .NET 6 Pure vs Impure Functions Git: Theirs vs Ours Angular vs Blazor? A decision aid for web developers in 2022 APIView vs Viewsets PyQt vs Pyside Eager Loading VS Lazy Loading in SQLAlchemy React vs Vue: Popular Front end frameworks in 2022 OpenAPI spec (swagger) v2 vs v3 apt update vs apt upgrade: What's the difference? Framework vs library vs package vs module: The debate What Should You Put in a Constructor vs ngOnInit in Angular Javascript vs memes Ionic vs React Nactive vs Flutter Selenium vs The World Faster Clicker Redux VS React Context: Which one should you choose? Styled components vs Emotion js: A performance perspective Git Submodules vs Monorepos MongoDB: Normalization vs Denormalization PUT vs PATCH & PUT vs POST Laravel vs ASP.NET Framework | Which is Better For Your Project? The last-child vs last-of-type selector in CSS Moq vs NSubstitute - Who is the winner? CSS solutions Battle: Compile time CSS-in-JS vs CSS-in-JS vs CSS Modules vs SASS querySelector vs getElementById Docker CMD vs ENTRYPOINT React Virtualization - react-window vs react-virtuoso The Development vs Production Environments npm vs npx - which to use when? Immediate vs eventual consistency Fleet vs VSCode Laravel breeze vs Jetstream Pug vs EJS? Join vs includes vs eager load vs preload Require vs Assert in Solidity Centralized vs Distributed Systems in a nutshell PyQt vs Tkinter (German) Flutter vs React Native Comparison - Which Use for Your Project in 2022 insertAdjacentHTML vs innerHTML Moment.js vs Luxon Generics vs Function Overloading vs Union Type Arguments in TypeScript Sass vs Scss What’s the difference: A/B Testing VS Blue/Green Deployment? Publisher Subscriber vs Observer pattern with C# VSCode vs Vim Persistent vs Non-Persistent Connections | Creating a Multiplayer Game Server - Part 2 Spread VS Rest Operator package.json vs package-lock.json: do you need both? Double Quotes vs Single Quotes in PHP RxJS operators: retry vs repeat? CAP Theorem: Availability vs consistency Scaling Airflow – Astronomer Vs Cloud Composer Vs Managed Workflows For Apache Airflow MySQL vs MySQLi vs PDO Performance Benchmark, Difference and Security Comparison For PHP devs - PHP Storm vs VSCode Difference Between Message vs Event vs Command Document vs Relational Databases IntelliJ vs Eclipse vs VSCode CSS position fixed vs sticky Telegraf VS Node-Telegram-Bot-API Flatpak vs Snaps vs AppImage vs Packages - Linux packaging formats compared Pytest vs Cypress: A fair fight in UI testing? Inline vs Inline-block vs Block Logging vs Tracing: Why Logs Aren’t Enough to Debug Your Microservices Solidity Gas Optimizations pt.1 - Memory vs Storage Bicep vs ARM templates Nest.js vs Express.js Retry vs Circuit Breaker Custom react hooks vs services Global vs Local State in React The What, Why, and When of Mono-Lambda vs Single Function APIs Frontend vs Backend: Which One Is Right For You? 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CSS Drop Shadow vs Box Shadow Infrastructure-as-Code vs Configuration Management TypeScript: type vs interface Head recursion Vs Tail recursion Dev.to VS Hashnode VS Medium: Pick ONE Classes vs Functional components in React The Battle of the Array Titans: Lodash vs Vanilla - An Experiment AWS EventBridge vs S3 Notification Inheritance Vs Delegation JavaScript vs JavaScript. Fight! Interface vs Type in Typescript setTimeout vs setImmediate vs process.nextTick Kotlin vs Python Kotlin Multiplatform vs Flutter: Which One to Choose for Your Apps Supervised Learning vs Unsupervised Learning React Hooks API vs Vue Composition API, as explored through useState DEV VS Hashnode VS Medium: Where Should You Start Your Tech Blog Implementing React Routes (Part -2) Link Vs NavLink Vanilla CSS VS CSS Frameworks Postman vs Insomnia: which API testing tool do you use? Serif vs Sans-serif vs Monospaced Getting started with fp-ts: Either vs Validation Typescript Implicit vs Explicit types CWEs vs OWASP top 10? Understanding Offset vs Cursor based pagination Material Design 1 vs Material Design 2 Signed vs Unsigned Bit Integers: What Does It Mean and What's The Difference? default vs null - which is a better choice, and why? Summary of Flutter vs Tauri SpringBoot2 Blocking Web vs Reactive Web JSON-RPC vs REST for distributed platform APIs Explain RBAC vs ACL Like I'm Five .map() vs .forEach() Difference between Dialogflow CX vs Dialogflow ES API keys vs JWT authorization – Which is best? find() vs filter() Snake Case vs Camel Case AWS vs OCI Object Storage options and comparison MAUI XAML vs MAUI Blazor Pointer vs Reference in C++: The Final Guide Comparing reactivity models - React vs Vue vs Svelte vs MobX vs Solid vs Redux Frontend vs Backend, which do you prefer and why? Remix vs Next.js: A Detailed Comparison NodeJS vs Apache performance battle for the conquest of my ❤️ ⚔️ Functional vs Object Oriented vs Procedural programming Lazy vs Eager Initialization Laravel ORM vs Query Builder vs SQL: SPEED TEST! Concurrency in Go vs Erlang TypeScript ANY vs UNKNOWN—A Deep Dive MVC vs MVP vs MVVM Design Patterns GNOME vs KDE Plasma Database Views vs Table Functions Server Side Rendering vs Static Site Generation vs Incremental Static Regeneration Understanding Rendering in Web Apps: SPA vs MPA 'any' vs 'unknown' in TypeScript 👀 TypeORM - Multiple DB Calls vs Single DB Call JS array vs object vs map Benchmarking Python JSON serializers - json vs ujson vs orjson textContent VS innerText Web2 vs Web3 Opinion: Architect VS Engineer VS Developer Jenkins pipeline: agent vs node? Hibernate Naming Strategies: JPA Specification vs Spring Boot Opinionation Pyqt vs PySide (Spanish) Unique Identifiers: UUID vs NanoID A comparison of state management in React with Mobx vs State lifting Meteor vs Next? A brutally honest answer Git-Flow vs Github-flow Set vs Array Python Packaging: sdist vs bdist JavaScript array methods: Mutator VS Non-mutator and the returning value Uint vs Int. Qual a diferença em Go? Understanding Rendering in Web Apps: CSR vs SSR Flask vs Bottle Web Framework Moment.js vs Intl object PyQt vs Kivy Web3: Truffle VS Hardhat VS Embark VS Brownie The one about CSS vs CSS in JS React Hooks vs Svelte - Why I chose Svelte? TaskEither vs Promise looking for answers !, strapi vs nest js for my next project SOP vs CORS? Pagination in an API: page number vs start index SVG sprites vs CSS background image for multiple instances of icons Javascript Streams vs Generators JS Date vs Moment.js: A Really Simple Comparison AMQP vs HTTP return Task vs return await Task Arrow Function vs Function Front-end vs Back-end, and Static vs Dynamic Websites setImmediate() vs setTimeout() vs process.nextTick() Solace PubSub+ vs Kafka: The Basics Agency VS Product Company: Which One's Right for You? Stateless vs Stateful - Which direction should you take? Clean Architecture vs Vertical Slice Architecture Functional programming vs object oriented programming Using Array.prototype.includes() vs Set.prototype.has() to filter arrays Hot vs Cold Observables Reassignment vs Mutability Database (Schema) migration to Kubernetes - initContainers vs k8s jobs - Gatsby vs Next.JS - What, Why and When? Which is faster: obj.hasOwnProperty(prop) vs Object.keys(obj).includes(prop) React Fragment VS Div Happy coding! 💎 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 DUMB 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 . DUMB DEV Community © 2016 - 2026. We're a place where coders share, stay up-to-date and grow their careers. Log in Create account | 2026-01-13T08:48:23 |
https://nutrify.app/terms.html | Nutrify Terms & Conditions Nutrify homepage TERMS AND CONDITIONS Last updated: 21 February 2024 Nutrify: The Food App (‘ Nutrify ’ or ‘ App ’) belongs to Craizy Pty Ltd trading as Craizy Studios (ABN 32 672 081 604) (‘ Craizy Studios ’, ‘ we ’, ‘ our ’ or ‘ us ’). This page sets out: information about registration and accounts; the costs of the App, App subscription, cancellation, and our refund policy; our privacy policy; and our website terms of use. If you access and use Nutrify, you are taken to have agreed to these terms and conditions. If you have any questions, please contact us on [email protected] . REGISTRATION AND ACCOUNTS Nutrify can be downloaded from the Apple App Store . To use certain features of Nutrify, you may be required to create an account. You agree to provide accurate, current, and complete information during the registration process. You are responsible for maintaining the security of your account and password. You may not share your account with others, and you agree not to sell or transfer your account to another party. How do I get notified of the changes in the App? Please be aware that we may make changes to our App in the future. Any information about the changes will be available through Nutrify notifications and App updates, by email (if you have subscribed), and our website at https://www.nutrify.app . App Accuracy The results and information provided by Nutrify may not always be entirely accurate, as they are generated using computer vision and machine learning technology. The accuracy of Nutrify’s assessments and recommendations can be influenced by factors such as the quality of input data and the inherent limitations of these technologies. It is essential for you to exercise your own discretion and not rely solely on Nutrify’s results for making critical decisions, especially in determining whether something is edible or not. When it comes to matters like dietary choices or health-related decisions, we advise you to consult with qualified professionals or trusted sources to ensure the most accurate and reliable information. Please be aware that Craizy Studios and our third parties do not assume responsibility for any action or inaction taken based on the App's results. Nutrify is intended for informational purposes and should not replace expert advice or common sense. Information provided by Nutrify is collated from reputable third-party sources. You acknowledge that the information provided belongs to third parties and that Craizy Studios will not assume any responsibility for their accuracy or validity in any way. Where possible, Nutrify will provide reference information to support materials. You acknowledge that the information or support materials are not the responsibility of Nutrify and may change without notice. APP COSTS How much does it cost to download Nutrify? Nutrify is free to download via the Apple App Store . However, Nutrify offers subscription-based access to premium features at USD 3.99/month (inc GST) or USD 24.99/year (inc GST). Please note these are base prices and may be subject to Apple's App Store price adjustments based on region. So the price you see in the App Store/inside the Nutrify app may be slightly different to what is listed here. Monthly or yearly subscription fees are to be paid through Apple’s App Store payments. Does Nutrify offer a free trial? Nutrify may, at its discretion, offer a free trial for a limited period of time. At the end of the free trial period, your payment method as provided by the Apple App Store will be charged unless you cancel your subscription within the trial period. Nutrify reserve the right to modify the terms and conditions of the free trial or cancel a free trial offer at any time and without notice. Where can I find the subscription fees? The subscription fees are displayed on Nutrify. We endeavour to maintain accurate information on our App, but from time to time there may be an error. If the subscription price is more or less than the price displayed, we reserve the right to correct the error. Who can I talk to about my subscription? If you have any questions regarding your subscription or the App, please contact us at [email protected] or through our website https://www.nutrify.app . Nutrify and Craizy Studios are not involved in the processing any payments made to use the App. Please refer to the legal disclaimers provided by the Apple App Store for any questions about how payment is processed. Can I cancel or modify my subscription? You acknowledge that Nutrify’s cancellation policy is consistent with Apple’s App Store purchases cancellation policy. Those terms will also govern your use of the App. Should you wish to change or cancel your subscription after your payment has been processed, click here for instructions. How do I request a refund? Nutrify’s refund policy are in line with Apple’s App Store purchases. You acknowledge that Apple’s App Store’s refund policy also governs your use of the App. To request for a refund, click here for instructions. Our goods and services come with guarantees that cannot be excluded under the Australian Consumer Law. For major failures with the service, you are entitled: to cancel your service contract with us; and to a refund for the unused portion, or to compensation for its reduced value. You are also entitled to choose a refund or replacement for major failures with goods. If a failure with the goods or a service does not amount to a major failure, you are entitled to have the failure rectified in a reasonable time. If this is not done, you are entitled to a refund for the goods and to cancel the contract for the service and obtain a refund of any unused portion. You are also entitled to be compensated for any other reasonably foreseeable loss or damage from a failure in the goods or service. PRIVACY POLICY Craizy Studios respects your right to privacy and is committed to safeguarding the privacy of our customers and website visitors. We comply with the Australian Privacy Principles contained in the Privacy Act 1988 (Cth).Our commitment to privacy extends across all regions where our services are available. This policy sets out how we collect and treat your personal information. What personal information do we collect? Craizy Studios will, from time to time, receive and store personal information you enter onto our website, provided to us directly or given to us in other forms. You may provide basic information such as your name, email address and log in details to enable us to send information, provide updates, process your subscription and for you to enjoy and use Nutrify. As Nutrify is a photo-based food education App, you may provide images to us, which play a fundamental role in fulfilling the App's core purpose and enhancing the computer vision models powering it. Additionally, we may also collect other personal information you provide while interacting with us. How do we collect your personal information? We collect personal information from you in a variety of ways, including when you interact with us electronically and when you access Nutrify and our website. We only collect personal information that you provide to us directly. We may collect additional information at other times, including but not limited to, when you provide feedback, when you provide information about your personal or business affairs, change your email preferences, respond to surveys and/or promotions, or communicate with us. How do we use your personal information? We may use personal information collected from you to provide you with information, updates, products, and services. We may also make you aware of new and additional products, services, and opportunities available to you. We may use your personal information to improve our services and better understand your needs. We may also use your personal information to contact you about our products and services, including for marketing purposes. You can opt out of receiving marketing material at any time. How do we disclose your personal information? We do not and will not sell or deal in personal information or any customer information. We may disclose your personal information to any of our employees, officers, insurers, professional advisers, agents, suppliers, or subcontractors. We will only do this to the extent it is reasonably necessary to provide our products or services to you. We may from time to time need to disclose personal information to comply with our legal obligations. We may, however, use and disclose images you have submitted through Nutrify. It is important to note that only images of food should be submitted through the App or our website. You must refrain from providing images containing personal, private, or sensitive information. While we are constantly improving our systems to ensure that any images containing personal or private information that are inadvertently submitted are flagged and handled with the utmost care and discretion, you acknowledge and agree that Craizy Studios bears no responsibility for any images you choose to submit. You acknowledge and agree that by capturing images of food using Nutrify, you grant us an unrestricted, worldwide license to use, distribute, display, and share these images. This includes, but is not limited to, the use of these images for training computer vision and other machine learning models to enhance the App’s services, sharing images as part of an open-source database, and incorporating images into Nutrify’s documentation and reference materials. Please be aware that Nutrify is solely interested in images of food. We do not seek or use images containing people, faces, or items unrelated to food. Any personal data contained within the photographs provided to Nutrify will be removed prior to any usage as described above. We may also use your personal information to protect the copyright, trademarks, legal rights, property, or safety of Craizy Studios, Nutrify, https://www.nutrify.app , our customers or third parties. Information that we collect may from time to time be stored, processed in, or transferred between parties located in countries outside of Australia. If there is a change of control in our business or a sale or transfer of business assets, we reserve the right to transfer (to the extent we are legally able to) our user databases, together with any personal information and non-personal information contained in those databases. This information may be disclosed to a potential purchaser under an agreement to maintain confidentiality. We would seek to only disclose information in good faith and where required by any of the above circumstances. By providing us with personal information, you consent to the terms of this privacy policy and the types of disclosure covered by this Policy. Where we disclose your personal information to third parties, we will request that the third party follow this Policy regarding handling your personal information. How do we secure your personal information? We are committed to ensuring that the information you provide to us is secure. In order to prevent unauthorised access or disclosure, we have put in place suitable physical, electronic, and managerial procedures to safeguard and secure information and protect it from misuse, interference, loss and unauthorised access, modification, and disclosure. The transmission and exchange of information is carried out at your own risk. We cannot guarantee the security of any information that you transmit to or receive from us. How can you access your personal information? You may request details of personal information that we hold about you by emailing us at [email protected] . We reserve the right to refuse to provide you with information that we hold about you, in certain circumstances set out in the Privacy Act. What rights do you have in relation to your personal information? You have the right to access your personal information and require us to correct any of your personal information. Changes to privacy policy Please be aware that we may make changes to our privacy policy in the future. Please check back from time to time to review our privacy policy. Cookies and Pixels A cookie is a small file placed in your web browser that collects information about your web browsing history. Use of cookies allows a website to tailor its configuration to your needs and preferences. Cookies do not access information stored on your computer or any personal information (for example: name, address, email address or telephone number). Most web browsers automatically accept cookies, but you can choose to reject cookies by changing your browser settings. This may, however, prevent you from taking full advantage of our App and website. Our App and website may use cookies to analyse website traffic, provide social media sharing and liking functionality and help us provide a better user experience for visitors to our website. In addition, cookies and pixels may be used to serve relevant ads to website visitors through third party services such as Google Adwords and Facebook Adverts. These ads may appear on this website or other websites you visit. WEBSITE TERMS OF USE Intellectual Property Rights Our website https://www.nutrify.app contains intellectual property (including copyright) owned by Craizy Pty Ltd trading as Craizy Studios and third parties. We and our third parties retain all rights, title and interest in our website and all related content. Nothing you do on or in relation to the website will transfer to you: the business name, trading name, domain name, trademark, industrial design, patent, registered design, or copyright; or the right to use or exploit a business name, trading name, domain name, trademark, or industrial design; or a system or process that is the subject of a patent, or copyright (or an adaptation or modification of such a system or process), of Craizy Pty Ltd and any third party. General information When you come to our website https://www.nutrify.app we may collect certain information such as browser type, operating system, websites visited immediately before coming to our site, etc. This information is used in an aggregated manner to analyse how people use our site, such that we can improve our service. Links to Third Party Websites Our website may contain links to other websites. These links are meant for your convenience only. Links to third party websites do not constitute sponsorship or endorsement or approval of these websites. Please be aware that we are not responsible for the privacy practices of such other websites. We encourage our users to be aware, when they leave our website, to read the privacy statements of each and every website that collects personally identifiable information. This privacy policy applies solely to information collected by this website. Content and product descriptions We do not warrant that product descriptions or other content of this website is accurate, complete, reliable, current, or error-free. We may update any content on our website at any time without notice. Reviews and comments When visiting our website or social media pages, and subject to your compliance with these terms, you may post reviews and comments. If your reviews or comments contain defamatory, misleading, or false statements or is threatening, aggressive or contains obscenities, or is otherwise contrary to the relevant social media platform’s content or other rules, we may remove your reviews and comments and remove your access to our website and social media pages. We reserve the right to remove or edit any content that you post on our website. You acknowledge that any content posted by you on our website or social media pages becomes our property. For this purpose, you grant us a non-exclusive, royalty-free, perpetual, irrevocable, and fully sublicensable right to use, distribute and display such content in any way we see fit, throughout the world and in any media. You agree to indemnify us for all claims made against us resulting from your reviews or comments on our website or social media pages. You acknowledge that we are not the author of any reviews or comments on our website or social media pages and that we are not responsible and do not assume any liability for any content posted by you or any third party. If you are concerned about any reviews or comments, please contact us at [email protected] . Customer account security For security purposes, you must not share your customer Account login details. If you use this site, you are responsible for maintaining the confidentiality of your customer account and password and for restricting access to your computer, and you agree to accept responsibility for all activities that occur under your customer account or password. We can terminate your customer account at any time and in our sole discretion. If a customer is under 18 years of age and purchasing an item with a credit card, we will require the consent of a parent or guardian at the time of purchase. Credit card information We do not store any credit card information that you provide. If payments are made via our App, they are securely managed by the Apple App Store in compliance with relevant standards. Suspending or terminating site access We may suspend or terminate your access to and use of our website, without notice, if you are in breach of these terms. Viruses We make every attempt to ensure that the website is free of viruses and other malicious code which may affect your computer systems. However, your access to and use of the website and App are at your own risk, and you must take your own precautions to avoid and protect your computer systems against any viruses and other malicious code. Cyber security If, due to events beyond our reasonable control, you incur any loss or damage arising from a cyber security event in relation to our website, email communications, payment gateway providers or products, you acknowledge that we are not liable. You must take appropriate steps to ensure that any requests for payment purporting to be from Craizy Studios are genuine, including by calling or emailing us to request confirmation. Contact us If you have any questions or concerns regarding our information about registration and accounts, App costs, subscription, our cancellation and refund policy, privacy policy or website terms and conditions, please contact us at [email protected] and we will endeavour to respond within 48 hours. How can I make a complaint? If you wish to make a complaint, please submit details of your complaint to [email protected] . We will investigate and respond as soon as possible after receiving written notice of your complaint. If your complaint relates to any payment, please note that Nutrify is unable to assist. All such enquiries should be directed to the Apple App Store. | 2026-01-13T08:48:23 |
https://stackoverflow.co/advertising/resources/ad-creative-guidelines/ | Creative guidelines for Stack Overflow and Stack Exchange - Stack Overflow Business Stack Internal Stack Data Licensing Stack Ads Partnerships Resources Learn Solution resources Stack Internal Stack Ads Blog Research insights Support Stack Internal Help Legal policies Talk to an expert Product guides & insights Product overview Why you can rely on Stack Overflow for brand safe advertising Guide to effective banner ads in employer branding What is topic tag targeting on Stack Overflow? Banner advertising Use cases Customer stories Community insights Developer Survey Pulse Survey Advertising best practices Developer advertising strategy Practical campaign tips Talent best practices Employer branding strategy Recruiting Collectives™ Getting started How to guides Resources Product guides & insights Product overview Creative guidelines for Stack Overflow and Stack Exchange Learn about the creative guidelines for Stack Overflow Advertising. Table of contents Creative Requirements Distinct from Stack Overflow/Stack Exchange Content Accepted Creative Formats Creative Elements Campaign Expectations Tracking Capabilities Creative Requirements Distinct from Stack Overflow/Stack Exchange Content Advertisements must not mimic Stack Overflow or Stack Exchange content, they must be distinct. Ads with a white or light background must include a dark 1 pixel border that clearly distinguishes the ad from the content. Accepted Creative Formats Image formats: JPEG/JPG PNG Max file size per creative is 150KB Light animation formats: HTML5 GIF Max initial load size per creative is 200KB Limit looping to 3 times across 15 seconds We do not accept pop-ups, expandable ads, rollover ads, floating ads, or other multimedia ads. Creative Elements Logos Advertiser's logo or brand name must be in the creative. Any creative using another company's logo or name must provide proof of permission to use. Copy All text must be clearly legible on varying screen sizes. Creative must have a clear call to action (CTA). Examples of clear CTAs are: Free Trial Learn More Watch Video Examples of a non-clear CTA is: Click Here Any claims or comparisons made within the creative must be accurate and verifiable. Proof, complete with source and date of the evidence, must be shown on the creative or landing page. Landing Pages Creative messaging and landing page must match. Ads can't talk about one thing and the landing page another. Advertiser landing pages must be mobile-friendly. Campaign Expectations For Stack Overflow-managed creatives, advertisers are required to send creative assets to their Stack Overflow Customer Success Manager no later than 5 business days before the target launch date. Failure to provide creatives on this timeline could result in a delay of your campaign and the inability to deliver your campaign as expected. For Advertiser-managed creatives, all creative themes (style + substance) must be reviewed by your Stack Overflow Customer Success Manager no later than 3 business days before the target launch date. This also applies to creatives updated during the course of a campaign. If creatives are not visible to Stack Overflow for any reason, examples should be sent by screenshot or test page from the Advertiser. Stack Overflow reserves the right to pause or cancel a campaign if creatives are not in compliance with our ad specifications. Per IAB terms and conditions, Stack Overflow reserves the right to reject ads that are deemed inappropriate for the space, given the types and themes of content, including content type and audience. Tracking Capabilities Stack Overflow allows wraps for IAS, MOAT, and Double Verify tags. Retargeting pixels are allowed for a limited number of vetted and pre-approved Programmatic partners. Last updated April 28, 2025 Table of contents Creative Requirements Distinct from Stack Overflow/Stack Exchange Content Accepted Creative Formats Creative Elements Campaign Expectations Tracking Capabilities Related resources Four global blockchain players increase engagement among niche developer audience Six leading cloud service providers leverage Stack Overflow Advertising to connect with developers Why you can rely on Stack Overflow for brand safe advertising What is topic tag targeting on Stack Overflow? Stay updated Subscribe to receive Stack Overflow Business content around knowledge sharing, collaboration, and AI. Receive updates Our Stack Stack Internal Features Customers Security Pricing Stack Data Licensing Stack Ads Partnerships Services Stack Overflow Company Leadership Press Careers Social Impact Support Contact Stack Overflow help Stack Internal help Terms Privacy policy Cookie policy Your Privacy Choices Elsewhere Blog Dev Newsletter Podcast Releases Dev Survey Site design / logo © 2026 Stack Exchange Inc. Light Dark Auto | 2026-01-13T08:48:23 |
https://www.deloitte.com/us/en/insights/research-centers/center-for-financial-services.html?icid=disidenav_center-for-financial-services | Deloitte Center for Financial Services | Deloitte Insights Please enable JavaScript to view the site. Skip to main content --> Deloitte Insights and our research centers deliver proprietary research designed to help organizations turn their aspirations into action. 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For personalized content and settings, go to your My Deloitte Dashboard Latest Insights What do organizations need most in a disrupted, boundaryless age? More imagination. Article • 16-min read Recommendations TMT Predictions 2026: The AI gap narrows but persists Article • 9-min read About Deloitte Insights About Deloitte Insights Deloitte Insights Magazine, issue 33 Magazine Topics for you Business Strategy & Growth Leadership Operations Technology Workforce Economics Watch & Listen Dbriefs Stay informed on the issues impacting your business with Deloitte's live webcast series. Gain valuable insights and practical knowledge from our specialists while earning CPE credits. Deloitte Insights Videos Stay informed with content built for today’s business leaders. From data visualizations to expert commentary, our video content delivers concise, actionable information to help you lead with clarity in a complex world. Subscribe Deloitte Insights Newsletters Looking to stay on top of the latest news and trends? With MyDeloitte you'll never miss out on the information you need to lead. Simply link your email or social profile and select the newsletters and alerts that matter most to you. Deloitte Center for Financial Services The Deloitte Center for Financial Services provides timely insights on the most pressing issues facing the industry, helping keep your organization a step ahead. From insuring risk to mastering it: How large commercial insurers can thrive in the next era Interviews with senior executives from insurers, brokers, and corporate risk managers shed light on potential success factors for an industry in transition Article • 9-min read From brand steward to growth architect: The bank CMO agenda for the AI Age AI is reshaping banking. Learn how CMOs can drive growth, meet customer expectations, and make marketing the engine of success. 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Explore our 2026 outlook. 17-min read Dive deeper into your sector Banking & capital markets Forecasting the rise of push payment scams—the fraud consumers are tricked into authorizing Article • 7-min read Commercial real estate Front-burner trends in commercial real estate, early 2025 edition: All eyes on tax policy Article • 6-min read Insurance Reimagining claims: Soft skills are the differentiator Article • 9-min read Investment management How investment management firms can benefit from the regulatory environment in 2025 Article • 6-min read About the Deloitte Center for Financial Services The Deloitte Center for Financial Services, which supports the organization’s US Financial Services practice, provides insight and research to assist senior-level decision-makers within banks, capital markets firms, investment managers, insurance carriers, and real estate organizations. The center is staffed by a group of professionals with a wide array of in-depth industry experiences as well as cutting-edge research and analytical skills. Through our research, roundtables, and other forms of engagement, we seek to be a trusted source for relevant, timely, and reliable insights. Subscribe to receive our latest research, articles, and webcasts Follow us on Twitter at: @DeloitteFinSvcs Get in touch with our research team Jim Eckenrode Managing director | Deloitte Center for Financial Services Jim Eckenrode Managing director | Deloitte Center for Financial Services United States Jim Eckenrode is managing director at the Deloitte Center for Financial Services, responsible for developing and executing Deloitte’s research agenda, while providing insights to leading financial institutions on business and technology strategy. jeckenrode@deloitte.com +1 617 585 4877 Michelle Canaan Insurance research leader, Deloitte Center for Financial Services | Senior manager, Deloitte Services LP Michelle Canaan Insurance research leader, Deloitte Center for Financial Services | Senior manager, Deloitte Services LP United States Michelle Canaan is a senior manager and the insurance research leader at the Deloitte Center for Financial Services. She frequently contributes to Deloitte Insights , including studies on market strategy, technology and innovation, financial inclusion, and talent. mcanaan@deloitte.com +1 212 436 3291 Patty Danielecki Senior Manager, Deloitte Center for Financial Services Patty Danielecki Senior Manager, Deloitte Center for Financial Services United States Patty is a senior manager and chief of staff at the Deloitte Center for Financial Services, Deloitte Services LP, where she leads the strategy and operations functions of the center. She has more than 20 years of experience in operations and research. She is based in New York. pdanielecki@deloitte.com +1 212 436 4127 Doug Dannemiller Senior research leader | Deloitte Services LP Doug Dannemiller Senior research leader | Deloitte Services LP United States Doug is a senior research leader for investment management at the Deloitte Center for Financial Services in Deloitte Services LP. He is responsible for driving the Center’s research platforms and delivering world-class research for our clients. Doug has more than 20 years of experience in research, strategy, and marketing in the investment management and wealth management industries. ddannemiller@deloitte.com +1 617 437 2067 Val Srinivas Senior research leader | Banking & Capital Markets | Deloitte Services LP Val Srinivas Senior research leader | Banking & Capital Markets | Deloitte Services LP United States Val Srinivas is the banking and capital markets research leader at the Deloitte Center for Financial Services. He leads the development of Deloitte’s thought leadership initiatives in the industry, coordinating various research efforts and helping to differentiate Deloitte in the marketplace. Srinivas has more than 21 years of experience in research and marketing strategy. vsrinivas@deloitte.com +1 212 436 3384 Tim Coy Research manager | Deloitte Center for Financial Services | Deloitte Services LP Tim Coy Research manager | Deloitte Center for Financial Services | Deloitte Services LP United States Tim Coy is the research manager for the commercial real estate industry within Deloitte’s Center for Financial Services and is based out of New York City. Prior to Deloitte, he served as a lead researcher for commercial real estate brokerages CBRE and Cushman & Wakefield. ticoy@deloitte.com +1 332 323 4896 What we’re reading Explore insights across industries Enjoy these timely insights from other Deloitte research centers and subject matter leaders, selected for you by our research team. Tech Trends 2026 As technology innovation and adoption accelerate, five trends reveal how successful organizations are moving from experimentation to impact Article • 4-min read CFO Signals Explore Deloitte’s CFO survey data, capturing insights from North America's top CFOs on economic sentiment, capital markets, and other CFO trends. 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https://www.serverless.com/?ref=apisyouwonthate.com | Serverless: Zero-Friction Serverless Apps On AWS Lambda & Beyond. Introducing the Serverless Container Framework - One solution, multiple deployment options. Products FRAMEWORK Overview CI/CD Secrets Plugins Documentation Pricing Company ABOUT US About Contact Us SUPPORT Get Support COMMUNITY Slack Forum Partners Meetups LEARN Blog Examples Guides Login Sign Up Log in Sign Up Products FRAMEWORK Overview CI/CD Secrets Plugins Pricing Signup Documentation Company ABOUT US Blog About Partners LEARN Guides Examples CONTACT US Contact Us Premium Support COMMUNITY Slack Meetups Forum Pricing Support Easy Serverless Apps on AWS Lambda Deploy APIs, scheduled tasks, workflows and event-driven apps to AWS Lambda easily with the Serverless Framework. Deploy Now Learn More Sorry, your browser doesn't support embedded videos. 46,000 Github Stars 300,000,000+ Downloads Technology Partner Develop. Zero-friction serverless development. Easily define your applications as functions and events. Declare AWS Lambda functions and their triggers through simple abstract syntax in YAML. Deploy infrastructure and code with a single command. AWS Lambda functions, triggers & code will be deployed and wired together in the cloud, automatically. Extend your use-cases and workflow with Plugins. Install thousands of Serverless Framework Plugins to build new serverless use-cases on AWS and integrate with other tools. 1 2 Troubleshoot. Top-tier debugging tools, built right in. Metrics and alerts, out of the box. Track usage, performance, errors on your serverless apps with instant, powerful metrics. Query and inspect every request. Quickly query across all AWS Lambda invocations and API Gateway requests to drill into specific issues. Collaborate. Share and contribute across your entire team. Manage everything in one place. See all of your serverless applications and their resources in one place, regardless of AWS account or region. Share secrets, outputs, and AWS accounts. Securely. Easily share secrets, outputs from your serverless applications and delegate AWS account access. Share AWS Lambda function tests. Share test events for your AWS Lambda functions. Stream logs and results in the Dashboard. 3 "I didn't realise #serverless was so absurdly quick and easy to use. Thanks @goserverless you've done an excellent job." @DrPappa Zero-friction serverless application development for all. Build more. Manage less. Deploy Now View Docs Deploy Now View Docs 46,000 Github Stars 300,000,000 Downloads Technology Partner FRAMEWORK Overview CI/CD Secrets Plugins Pricing RESOURCES Documentation Guides Examples Blog COMMUNITY Slack Meetups Forum SUPPORT Contact Us Premium Support COMPANY About Partners Join our monthly newsletter Thank you! Your submission has been received! Oops! Something went wrong while submitting the form. © 2024 Serverless, Inc. All rights reserved. Serverless Customer Agreement | 2026-01-13T08:48:23 |
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https://t.co/Kdd0lerRQz | Capture, organize, and tackle your to-dos from anywhere | Trello Skip to main content Features Solutions Plans Pricing Resources Explore the features that help your team succeed Inbox Capture every vital detail from emails, Slack, and more directly into your Trello Inbox. Planner Sync your calendar and allocate focused time slots to boost productivity. Automation Automate tasks and workflows with Trello. Power-Ups Power up your teams by linking their favorite tools with Trello plugins. Templates Give your team a blueprint for success with easy-to-use templates from industry leaders and the Trello community. Integrations Find the apps your team is already using or discover new ways to get work done in Trello. Meet Trello Trello makes it easy for your team to get work done. No matter the project, workflow, or type of team, Trello can help keep things organized. It’s simple – sign-up, create a board, and you’re off! Productivity awaits. 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https://apisyouwonthate.com/blog/modern-api-deployment-options-in-the-cloud#/portal/signin | Modern API Deployment Options in the Cloud Newsletter Articles Books Podcast Membership Sign in Subscribe Modern API Deployment Options in the Cloud Alexander Karan 04 May 2022 — 8 min read How do you deploy your API, and what's the best way to structure it? Front-end frameworks have come a long way in recent years, making it easy to spin up and deploy a website/web app. However, I find the noise caused by many strong opinions sometimes clouds the equal and fantastic progress made on letting developers quickly deploy an API. I'm going to cover a few ways you can build and deploy an API to get your MVP into the hands of your users as quickly as possible. I will approach these deployments from the mindset of building a REST API, as I find this is the most accessible format when thinking about structure and deployments. Don't build one from scratch Getting features, demos, and MVPs into users' hands is more important than the tech stack, language or processes you use. Users don't care how you built it; they care about the features and how well it works. Firebase has come on in leaps and bounds over the last few years and allows you to knock together a backend for your API quickly. Time and time again, I see people building out an API for simple CRUD operations. Don't make your life difficult. Why build and maintain a whole backend for simple operations? Firebase also allows for a more complex setup giving you the ability to write cloud functions which respond to changes, and run code based on data changes in the database made by your front-end. If you're looking for an open-source alternative to Firebase, Supabase is a great companion. Plus, they have a great tag line: Create a backend in less than 2 minutes. Another tool to deploy backends with hardly any code is AWS Amplify . You are given tools for authentication and data storage, serving web pages, and connecting to other AWS services. Amplify also comes with a nifty setup they call Studio, allowing you to manage app users and edit content. There are some great tools out there for putting together backends. Managing dev ops, servers, and other backend infrastructure can be a pain sometimes. Assess if there is a need to put together a full-fledge backend/API before starting. We don't all need to be Stripe 😉 Deploy on the Edge Edge computing has me excited; so many cool things are happening in this space. Deploying an API on edge is like writing serverless functions, with the main difference being you deploy to the edge network, and they tend to run on top of the V8 JavaScript runtime. I love this approach as you get to write endpoints as functions and forget about everything else. There are a few providers in this space. One of the most notable is Cloudflare Workers , and you can write in Rust, C, and C++, not just JavaScript. They have some great examples of starter projects to get you going, They also have an excellent course on building a serverless API with Cloudflare Workers on EggHead . I also love Deno Deploy , a one-click deploy service for Deno . It allows you to instantly deploy JavaScript on the edge every time you push code to Github. Forget servers, forget vendor lock-in and push JavaScript all the livelong day. This is an example of how simple it can be to deploy a Rest API. I have set up a single route using Oak (an HTTP framework for Deno) that returns an estimated carbon footprint for the provided electricity consumption. import { Application, Router } from "https://deno.land/x/oak/mod.ts"; const port = 3011; const router = new Router(); router.get("/electricity", (ctx) => { const factor = 0.759; const kwh = Number(ctx.request.url.searchParams.get("kwh")); if (kwh) { const carbon = kwh * factor; const inTonnes = carbon / 1000; ctx.response.body = JSON.stringify({ carbon: inTonnes, unit: "tCO2e", }); } else { ctx.response.status = 400; ctx.response.body = JSON.stringify({ error: { message: "kWh have not been supplied in the query", }, }); } }); const app = new Application(); app.use(router.routes()); app.use(router.allowedMethods()); app.addEventListener("listen", () => console.log(`Listening on http://localhost:${port}`) ); await app.listen({ port }); Full Deno Code Example To deploy with Deno Deploy, you need to sign up here and make sure you have committed your API to Github. Then connect Deno Deploy to your Github account once you sign up, select the correct repository, select the entry file and then you're all good to go. Any changes, push code to the main branch, and they go live. All PRs created in the repository will come with a deploy preview URL. You can check out my demo API in full here. Change the query to your electricity consumption in kWh to get your estimated footprint. The question of how to structure your projects is the next hurdle, and this is where breaking them down into microservices would be essential. For example, for this project, I could point to a subdomain, "calculator.alexanderkaran.com", and build out more functionality for working out the footprint for gas or water usage. Each function could be at a different subroute, i.e. "/gas" or "/water"; however, If I wanted to build functionality for testing appliance efficiency. I would create this as a whole new project and point a new subdomain at it, for example, "appliances.alexanderkaran.com". Another great part of Deno Deploy is keeping all the services in one repo is easy; you point each project to a specific folder only the code imported in that folder gets deployed. Deno and Deno Deploy make it easy to share code, create a shared folder in the mono-repo and import the code; that's it, no third party sharing system and no private npm modules. Serverless Functions Serverless functions share a lot with edge functions, but you usually code in Node rather than a V8 browser runtime. However, they can have a cold start, meaning the code does not run the second it's called, unlike edge functions which happen straight away. Many providers offer serverless functions, but we will focus on AWS Lambda as it is one of the most common. Lambda functions are used for many different solutions, but they need to be paired with an API Gateway when building an API. It turns out AWS have a service for that, too 😉. When creating Lambda functions in the AWS console, they offer options to connect an endpoint in a new or existing API Gateway , making setup a breeze. If you are used to building monoliths and everything in one place, this can seem confusing. However, it simply boils down to your API Gateway containing all your routes, and each Lambda function is the controller for the route. Before we dive deeper into how this works, let's look at how Lambda functions are structured. I have stolen one of the AWS HTTP templates for updating DynamoDB : const AWS = require('aws-sdk'); const dynamo = new AWS.DynamoDB.DocumentClient(); /** * Demonstrates a simple HTTP endpoint using API Gateway. You have full * access to the request and response payload, including headers and * status code. * * To scan a DynamoDB table, make a GET request with the TableName as a * query string parameter. To put, update, or delete an item, make a POST, * PUT, or DELETE request respectively, passing in the payload to the * DynamoDB API as a JSON body. */ exports.handler = async (event, context) => { //console.log('Received event:', JSON.stringify(event, null, 2)); let body; let statusCode = '200'; const headers = { 'Content-Type': 'application/json', }; try { switch (event.httpMethod) { case 'DELETE': body = await dynamo.delete(JSON.parse(event.body)).promise(); break; case 'GET': body = await dynamo.scan({ TableName: event.queryStringParameters.TableName }).promise(); break; case 'POST': body = await dynamo.put(JSON.parse(event.body)).promise(); break; case 'PUT': body = await dynamo.update(JSON.parse(event.body)).promise(); break; default: throw new Error(`Unsupported method "${event.httpMethod}"`); } } catch (err) { statusCode = '400'; body = err.message; } finally { body = JSON.stringify(body); } return { statusCode, body, headers, }; }; AWS Lambda Snippet As you see here, the function responded to an event and accessed the HTTP method inside to see what type of request it was. Personally, the biggest hurdle I had when using serverless functions or edge computing was how there were no req, res and next functions like I was used to in ExpressJS. Thankfully, though, there are many ways to import frameworks you're used to into Lambda. You also do not have to code in Node; other languages such as Python and Java are on offer too. Setting up serverless functions with an API Gateway can be done super quickly using the AWS console, but a more extensive API with many endpoints would be time-consuming to set this up way. Enter tools like ClaudiaJS and Serverless . Claudia allows you to easily set up, deploy, and update code to AWS Lambda, making development and automating releases a breeze. If you want even more capabilities, check out Serverless. It makes deploying serverless functions to AWS easier, allowing you to access and deploy complete AWS services outside of Lambda. Serverless goes even further and has setups for Google Cloud Functions and Azure Functions. Setting up an API made of serverless functions can be tricky the first time, so remember API Gateway for your routes and serverless functions for your controllers. Serverless Containers Lastly, we come to serverless containers. I have used Docker containers myself for five years, and I love them. It's great to build something locally, and it runs the same on the server or any other computer that uses it. Need something to be running all the time? Can't afford to deal with cold starts on your API requests or be limited by serverless functions memory or timeout limits? Then containers are for you. Most people tend to reach for Kubernetes or spin up their servers, install Docker, and deploy their images onto the server. These options will tend to be overkill unless you are running extensive backend infrastructure, which, let's be honest, is not all of us. Though, if you are deploying across multiple cloud providers, Kubernetes might be for you. I like to focus on features and quality, not infrastructure, config and deployments. AWS services ECS and ECR are great for this. ECR is a repository for uploading your Docker containers, and ECS spins up each container. You connect them to API Gateway or an Application Load Balancer to expose your API to the outside world. To set up your ECS deployment, you create a task for the docker image, defining setups such as memory and ports. You then create a cluster in ECS and create a Service for each Task. Services are responsible for auto-scaling Tasks based on traffic or memory usage, spinning up new versions when replacing the docker image and exposing the image to the outside world. Setting up ECS does take a while the first time, but after the setup, you add in code pipelines from AWS to auto-deploy updated code when pushing to your Git repository. After setting up your Cluster, you connect it to the outside world in a few different ways. One approach is to connect it to an Application Load Balancer and set up rules in Load Balancer to connect different URL routes to each service. I usually have a few services running in a cluster. For example, my last Cluster contained the following services: Measure Service: My service for handling carbon calculations and tracking consumption and cost of utilities. It was connected to the load balancer, and any request that came through "myapi.com/measure" was sent here. Image Service: My service for handling image uploads and processing. It was connected to the load balancer, and any request that came through "myapi.com/image" was sent here. Notifications Service: The service for sending emails and push notifications but not connected to the Load Balancer. The other services can call it as they're all on the same VPC (Virtual Private Network), which means I did not need to write the same notification code in the Image or Measure Service. AWS has some overviews on setting up ECS and what you can connect it to. If you are looking for a more in-depth tutorial on deploying a Node app from scratch, you can check out this tutorial by Raphael . In Summary While each option here deserves its own blog post to cover its entire setup, benefits, and quirks, you at least have a good overview of what is available. I love the advancement of serverless and not having to think about servers at all. Serverless functions, and new kids on the block like Cloudflare Workers, means we are close to never having to think about servers or backend configs again. It's great to focus on code to fix problems, which gets tested, reviewed and deployed the second your PR gets approved in Github. If you have not tried serverless or edge functions, you should try them for your next API. Read more Design First, AI Never In the age of vibe-coding, how can we convince teams to invest in design before building APIs? Also in this newsletter: OpenAPI 3.3, Reddit's microservices architecture, an update to Speakeasy for OpenApi 3.2.0, and more! By Alexander Karan 15 Dec 2025 Zero-Downtime Migration from Laravel Vapor to Laravel Cloud Move your Laravel API from Vapor to Cloud in phases, without making a complete hash of it and wishing you never bothered. By Phil Sturgeon 08 Dec 2025 NestJS: Bad, or Really Bad? 😉 In this newsletter: the Resty library for APIs in Golang, a new Bruno release, an interview with Kin Lane, and API Schema Automation for devs By Alexander Karan 01 Dec 2025 Building a Sustainable Future in APIs with Kin Lane Kin Lane drops by to talk to Phil Sturgeon about his new startup, the changing landscape of API tech, why REST fundamentals are still important, and building sustainable API tools. By Mike Bifulco 01 Dec 2025 Sign up About Powered by Ghost Are you ready to build APIs You Won't Hate? 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