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  1. GitHub, Copilot, and Pulling the Plug

    A couple of days ago, I was working on an assignment that required a slightly higher level of coding than I normally master. It was, ultimately, a rather simple Python script, but in fairness, most of my skills lie in visual programming and basic C++.

    This means I can read and understand most code reasonably well, but syntax is a completely different matter. That is precisely why I turned to AI for assistance with the task.

    As I was filling in my code snippet, however, I suddenly paused for a moment and envisioned the situation that would arise the moment someone pulled the plug on the service. This isn’t far-fetched at all, is happening as we speak.

    I don’t expect everyone to work in IT, so a brief introduction is probably necessary to make the topic a little less obscure. If you work in software development, chances are you have used GitHub. If you are into videogames, you might recognize the name as well, as gaming and software development communities have often overlapped.

    As the platform evolved, it became—much like Stack Overflow—a valuable resource for developers. The difference was that GitHub allowed users not only to discuss solutions but also to share and reuse actual source code. After all, the software industry rarely develops everything from scratch; much like writing a text, you do not invent every expression yourself. GitHub made it possible to build upon the work of others and interact with them much more directly.

    Over time, as GitHub became increasingly integrated into professional development pipelines, it evolved into a critical service for software development. In many ways, even before cloud computing became commonplace, GitHub was already enabling developers across the world to share repositories, collaborate on projects, and contribute to the same codebases regardless of their geographic location.

    Its value eventually became so significant that the company was acquired by Microsoft, while still retaining its brand identity and familiar appearance. That said, it did not take long for GitHub to incorporate AI through its own version of Copilot.

    The move was initially met with criticism, largely because of the open secret that the model had been trained on publicly available repositories, some of which may have contained other people’s intellectual property. Despite these concerns, the tool was rapidly embraced by the developer community.

    After all, it saved time and helped perform analyses and validations that would otherwise have required considerably more effort. Many developers subscribed almost immediately, as the cost was easily justified by the productivity gains. In practice, they were simply paying for a tool that made them more efficient.

    Fast forward to June 2026, and GitHub announced a change to its subscription model, moving toward token-based pricing. In practice, this means users are charged based on the amount of AI-generated traffic their interactions consume.Since software projects can contain millions of lines of code, charges measured in cents can quickly accumulate into thousands of dollars when analyzing large repositories. Mind you, this is not a guarantee that the code will work; it is simply a control and assistance service.

    Given that AI remains a difficult business to monetize profitably, the move is not only understandable but perhaps even reasonable from a commercial perspective. Nevertheless, it made the new rules of the game abundantly clear: you are free to use our tools, provided you can afford the admission fee.

    The reaction was significant. Many began predicting the end of “vibe coding” barely two years after the trend had emerged—not necessarily a bad outcome, if you ask me. 

    More importantly, however, the change shifted the discussion toward a different question: What happens when a third party controls a critical part of your value proposition? And perhaps more importantly, what happens when that third party decides that you are no longer profitable enough for them?

    I suspect many companies will soon discover whether they own a capability or merely rent access to it. For years, the software industry has served as a cautionary tale about becoming dependent on proprietary systems. AI may simply be pushing the rest of us to learn the same lesson.

    The Pocket AI Guide is out!

    📙 Amazon US: https://a.co/d/gCHHDax
    📗 In Europe Amazon Germany: https://amzn.eu/d/3cmlIqa
    (Available in other stores Amazon stores too in Europe)

    Check the free resources in this website!

    #AIAdoption #AIBusinessStrategy #AICodingAssistants #AIInfrastructure #AIMonetization #AISubscriptionCosts #cloudServicesRisk #CopilotPricingChanges #developerProductivity #developerWorkflows #digitalDependency #digitalSovereignty #GitHubCopilot #GitHubPricingModel #GitHubRepositories #openSourceSoftware #platformDependency #platformEconomics #softwareDevelopmentEconomics #softwareDevelopmentTools #softwareEngineering #technologyInfrastructure #tokenBasedPricing #valuePropositionRisk #vendorLockIn
  2. This article explores how AI coding tools increase code duplication, security risk, and technical debt despite boosting developer productivity. hackernoon.com/why-enterprise- #aicodingassistants

  3. This article explores how AI coding tools increase code duplication, security risk, and technical debt despite boosting developer productivity. hackernoon.com/why-enterprise- #aicodingassistants

  4. This article explores how AI coding tools increase code duplication, security risk, and technical debt despite boosting developer productivity. hackernoon.com/why-enterprise- #aicodingassistants

  5. This article explores how AI coding tools increase code duplication, security risk, and technical debt despite boosting developer productivity. hackernoon.com/why-enterprise-

  6. This article explores how AI coding tools increase code duplication, security risk, and technical debt despite boosting developer productivity. hackernoon.com/why-enterprise- #aicodingassistants

  7. AI isn’t just generating code—predictive software quality platforms help enterprises maintain reliability, accelerate releases, and reduce production risk. hackernoon.com/how-to-improve- #aicodingassistants

  8. AI isn’t just generating code—predictive software quality platforms help enterprises maintain reliability, accelerate releases, and reduce production risk. hackernoon.com/how-to-improve- #aicodingassistants

  9. AI isn’t just generating code—predictive software quality platforms help enterprises maintain reliability, accelerate releases, and reduce production risk. hackernoon.com/how-to-improve- #aicodingassistants

  10. AI isn’t just generating code—predictive software quality platforms help enterprises maintain reliability, accelerate releases, and reduce production risk. hackernoon.com/how-to-improve-

  11. AI isn’t just generating code—predictive software quality platforms help enterprises maintain reliability, accelerate releases, and reduce production risk. hackernoon.com/how-to-improve- #aicodingassistants

  12. AI Coding Assistants Transform Government Software Development

    The era of AI coding assistants has arrived in government software development, transforming the way code is written and raising the bar for reliability, security, and scalability in high-stakes environments. No longer just a novelty, these tools are now being put to the test in…

    osintsights.com/ai-coding-assi

    #AiCodingAssistants #GovernmentSoftwareDevelopment #EmergingTechnologies #SecureSoftwareDevelopment #RegulatedEnvironments

  13. "In recent episodes, Harry made a claim that the path to AI profitability runs through labor replacement. “Stop paying $1M in salaries by paying $100K for this AI-based service.” Simple. Clean. Measurable.

    And woefully incomplete." by Kent Beck

    tidyfirst.substack.com/p/the-p

    #artificialintelligence #aicodingassistants

  14. "In recent episodes, Harry made a claim that the path to AI profitability runs through labor replacement. “Stop paying $1M in salaries by paying $100K for this AI-based service.” Simple. Clean. Measurable.

    And woefully incomplete." by Kent Beck

    tidyfirst.substack.com/p/the-p

    #artificialintelligence #aicodingassistants

  15. "In recent episodes, Harry made a claim that the path to AI profitability runs through labor replacement. “Stop paying $1M in salaries by paying $100K for this AI-based service.” Simple. Clean. Measurable.

    And woefully incomplete." by Kent Beck

    tidyfirst.substack.com/p/the-p

    #artificialintelligence #aicodingassistants

  16. "In recent episodes, Harry made a claim that the path to AI profitability runs through labor replacement. “Stop paying $1M in salaries by paying $100K for this AI-based service.” Simple. Clean. Measurable.

    And woefully incomplete." by Kent Beck

    tidyfirst.substack.com/p/the-p

    #artificialintelligence #aicodingassistants

  17. "In recent episodes, Harry made a claim that the path to AI profitability runs through labor replacement. “Stop paying $1M in salaries by paying $100K for this AI-based service.” Simple. Clean. Measurable.

    And woefully incomplete." by Kent Beck

    tidyfirst.substack.com/p/the-p

    #artificialintelligence #aicodingassistants

  18. Endor Labs just released AURI, a free tool that scans AI‑generated code for hidden vulnerabilities. A recent study shows only 10% of AI‑written code is secure, so developers need better safeguards. Try AURI and help raise the security bar for open‑source AI projects. #AICodeSecurity #AURI #EndorLabs #AIcodingAssistants

    🔗 aidailypost.com/news/endor-lab

  19. Endor Labs just released AURI, a free tool that scans AI‑generated code for hidden vulnerabilities. A recent study shows only 10% of AI‑written code is secure, so developers need better safeguards. Try AURI and help raise the security bar for open‑source AI projects. #AICodeSecurity #AURI #EndorLabs #AIcodingAssistants

    🔗 aidailypost.com/news/endor-lab

  20. Endor Labs just released AURI, a free tool that scans AI‑generated code for hidden vulnerabilities. A recent study shows only 10% of AI‑written code is secure, so developers need better safeguards. Try AURI and help raise the security bar for open‑source AI projects. #AICodeSecurity #AURI #EndorLabs #AIcodingAssistants

    🔗 aidailypost.com/news/endor-lab

  21. New command‑line tool LangSmith Fetch lets Claude Code and Cursor agents pull execution records straight from your terminal, turning raw runs into instant debugging sessions. See how this opens up prompt‑tuning, faster fixes, and a tighter loop for AI coding assistants. A must‑read for anyone building or using open‑source AI dev tools. #LangSmithFetch #ClaudeCode #Cursor #AICodingAssistants

    🔗 aidailypost.com/news/langsmith

  22. 🤖✨ "AI coding assistants are as useful as a spoon in a soup-free diet, because apparently, programmers are really just philosophers with keyboards. 🧠⚡️ The article lovingly explains how code is a savage enigma that only true sages can untangle, not mere robots. 🙄📜"
    doliver.org/articles/programmi #AIcodingAssistants #PhilosophyOfCoding #ProgrammerHumor #CodeEnigma #TechInsights #HackerNews #ngated

  23. 🤖✨ "AI coding assistants are as useful as a spoon in a soup-free diet, because apparently, programmers are really just philosophers with keyboards. 🧠⚡️ The article lovingly explains how code is a savage enigma that only true sages can untangle, not mere robots. 🙄📜"
    doliver.org/articles/programmi #AIcodingAssistants #PhilosophyOfCoding #ProgrammerHumor #CodeEnigma #TechInsights #HackerNews #ngated

  24. 🤖✨ "AI coding assistants are as useful as a spoon in a soup-free diet, because apparently, programmers are really just philosophers with keyboards. 🧠⚡️ The article lovingly explains how code is a savage enigma that only true sages can untangle, not mere robots. 🙄📜"
    doliver.org/articles/programmi #AIcodingAssistants #PhilosophyOfCoding #ProgrammerHumor #CodeEnigma #TechInsights #HackerNews #ngated

  25. 🤖✨ "AI coding assistants are as useful as a spoon in a soup-free diet, because apparently, programmers are really just philosophers with keyboards. 🧠⚡️ The article lovingly explains how code is a savage enigma that only true sages can untangle, not mere robots. 🙄📜"
    doliver.org/articles/programmi #AIcodingAssistants #PhilosophyOfCoding #ProgrammerHumor #CodeEnigma #TechInsights #HackerNews #ngated

  26. "All experts interviewed for this piece believe AI will assist developers rather than replace them wholesale. In fact, most view keeping developers in the loop as imperative for retaining code quality. “For now, human oversight remains essential when using AI-generated code,” says Digital.ai’s Kentosh.

    “Building applications will mostly remain in the hands of the creative professionals using AI to supplement their work,” says SurrealDB’s Hitchcock. “Human oversight is absolutely necessary and required in the use of AI coding assistants, and I don’t see that changing,” adds Zhao.

    Why? Partially, the ethical challenges. “Complete automation remains unattainable, as human oversight is critical for addressing complex architectures and ensuring ethical standards,” says Gopi. That said, AI reasoning is expected to improve. According to Wilson, the next phase is AI “becoming a legitimate engineering assistant that doesn’t just write code, but understands it.”"

    infoworld.com/article/3844363/

    #AI #GenerativeAI #LLMs #Programming #SoftwareDevelopment #AICodingAssistants

  27. "All experts interviewed for this piece believe AI will assist developers rather than replace them wholesale. In fact, most view keeping developers in the loop as imperative for retaining code quality. “For now, human oversight remains essential when using AI-generated code,” says Digital.ai’s Kentosh.

    “Building applications will mostly remain in the hands of the creative professionals using AI to supplement their work,” says SurrealDB’s Hitchcock. “Human oversight is absolutely necessary and required in the use of AI coding assistants, and I don’t see that changing,” adds Zhao.

    Why? Partially, the ethical challenges. “Complete automation remains unattainable, as human oversight is critical for addressing complex architectures and ensuring ethical standards,” says Gopi. That said, AI reasoning is expected to improve. According to Wilson, the next phase is AI “becoming a legitimate engineering assistant that doesn’t just write code, but understands it.”"

    infoworld.com/article/3844363/

    #AI #GenerativeAI #LLMs #Programming #SoftwareDevelopment #AICodingAssistants

  28. "All experts interviewed for this piece believe AI will assist developers rather than replace them wholesale. In fact, most view keeping developers in the loop as imperative for retaining code quality. “For now, human oversight remains essential when using AI-generated code,” says Digital.ai’s Kentosh.

    “Building applications will mostly remain in the hands of the creative professionals using AI to supplement their work,” says SurrealDB’s Hitchcock. “Human oversight is absolutely necessary and required in the use of AI coding assistants, and I don’t see that changing,” adds Zhao.

    Why? Partially, the ethical challenges. “Complete automation remains unattainable, as human oversight is critical for addressing complex architectures and ensuring ethical standards,” says Gopi. That said, AI reasoning is expected to improve. According to Wilson, the next phase is AI “becoming a legitimate engineering assistant that doesn’t just write code, but understands it.”"

    infoworld.com/article/3844363/

    #AI #GenerativeAI #LLMs #Programming #SoftwareDevelopment #AICodingAssistants

  29. "All experts interviewed for this piece believe AI will assist developers rather than replace them wholesale. In fact, most view keeping developers in the loop as imperative for retaining code quality. “For now, human oversight remains essential when using AI-generated code,” says Digital.ai’s Kentosh.

    “Building applications will mostly remain in the hands of the creative professionals using AI to supplement their work,” says SurrealDB’s Hitchcock. “Human oversight is absolutely necessary and required in the use of AI coding assistants, and I don’t see that changing,” adds Zhao.

    Why? Partially, the ethical challenges. “Complete automation remains unattainable, as human oversight is critical for addressing complex architectures and ensuring ethical standards,” says Gopi. That said, AI reasoning is expected to improve. According to Wilson, the next phase is AI “becoming a legitimate engineering assistant that doesn’t just write code, but understands it.”"

    infoworld.com/article/3844363/

    #AI #GenerativeAI #LLMs #Programming #SoftwareDevelopment #AICodingAssistants

  30. "All experts interviewed for this piece believe AI will assist developers rather than replace them wholesale. In fact, most view keeping developers in the loop as imperative for retaining code quality. “For now, human oversight remains essential when using AI-generated code,” says Digital.ai’s Kentosh.

    “Building applications will mostly remain in the hands of the creative professionals using AI to supplement their work,” says SurrealDB’s Hitchcock. “Human oversight is absolutely necessary and required in the use of AI coding assistants, and I don’t see that changing,” adds Zhao.

    Why? Partially, the ethical challenges. “Complete automation remains unattainable, as human oversight is critical for addressing complex architectures and ensuring ethical standards,” says Gopi. That said, AI reasoning is expected to improve. According to Wilson, the next phase is AI “becoming a legitimate engineering assistant that doesn’t just write code, but understands it.”"

    infoworld.com/article/3844363/

    #AI #GenerativeAI #LLMs #Programming #SoftwareDevelopment #AICodingAssistants