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Engineering video

7:32 · 20 May 2025

GitHub spent $13B stealing our code. It failed.

Chapters 6 sections

  1. 0:00Copilot Origins and Copyright Controversy
  2. 2:00Productivity Claims versus Code Churn
  3. 4:00Performance Limits and Financial Pressures
  4. 4:26Competitors Like Cursor and Windsurf Emerge

Key concepts in this video:

1. GitHub Copilot and Legal Controversy

GitHub and Microsoft used millions of lines of public open-source code to train GitHub Copilot without payment. Although a copyright infringement lawsuit was dismissed, allowing AI companies to use public code freely, the tool became a market leader with high adoption rates.

Watch section from 0:00 →

2. Code Quality and Code Churn Issues

Studies and reports revealed that Copilot's actual productivity gains were minimal (about 2.2 lines of extra code rather than claimed percentages) and led to an exponential increase in code churn—lines of code written and then deleted in a sprint. Generating excess code runs counter to efficient software engineering principles.

Watch section from 2:00 →

3. Copilot Performance Degradation and Limits

As Microsoft reportedly lost money on subscriptions, Copilot performance degraded and limits were added, resulting in worse performance for users unless they paid for higher tiers.

Watch section from 2:00 →

4. Rise of New AI Code Editors

New competitors emerged, such as Anisphere (Cursor AI) and Windsurf, which reinvented the IDE by integrating AI capabilities directly into the developer's native working environment rather than just serving as a quick add-on.

Watch section from 4:26 →

5. Market Competition and Microsoft's Response

Microsoft attempted to block competitors like Cursor and Codium (Windsurf) from accessing VS Code, but eventually faced increased market pressure, layoffs, and potential talks regarding industry acquisitions.

Watch section from 5:26 →

Transcript

at this point, I don't even know what's voice. The fact that GitHub and Microsoft were allowed to use millions of lines of open source code to build GitHub copilot without ever paying anything for it, or the fact that this is not even the worst thing they did. It all started when Microsoft stunned the tech world and acquired open AI for 10 billion in its article, but actually checking Wikipedia, I it's about 13 billion. And the 13 billion promise was that copilot will increase developer productivity, many speculated, it will actually replace junior developers, but in the end it was built on open and stolen code. GitHub Open AI Codex was trained on a selection of English language public GitHub repositories. This includes a filtered data set of 159 GB of Python code from 54 million public GitHub repositories. Someone ring the bell and there was a lawyer who actually uh got GitHub and Microsoft to court. But as of today, the case has been dismissed, meaning that any AI company, not just Microsoft, can use your code to train their AI models without you being able to claim a copyright infringement. Meanwhile, GitHub copilot became the market leader AI coding tool. The estimate was that 90% of US-based developers already were using AI-powered coding tools. I remember the words of one Big Tech CEO, he estimated that engineers now complete their coding tasks twice as fast as they did before adopting the assistant in March. Even Microsoft CEO himself, Satya Nadela said that more than a million people have used copilot up to date in their earning calls in 2023. But then things started to crack. Articles like this say why copilot is making programmers worse at programming, with one of the most significant risk of relying on tools like copilot being the gradual erosion of fundamental programming skills. It also turns out that GitHub has been kind of lying with statistics