SDL bans AI-written commits

Original Article ↗ Hacker News Discussion ↗

Scope and Intent of the Ban

  • Many see the ban as primarily about setting expectations and protecting maintainers’ time, not as something perfectly enforceable.
  • Supporters argue it gives reviewers a clear rule to reject AI-generated pull requests without debating minutiae.
  • Critics call it “unenforceable theater,” noting anyone can quietly use AI and present the result as hand-written.

Code Quality, Review Burden, and Project Health

  • Several maintainers and reviewers report AI-generated PRs as high-volume, low-quality “slop” that’s tiring to review.
  • Some say properly supervised AI can produce code indistinguishable from human work, but only when used skillfully and iteratively.
  • Others counter they’ve never seen AI code that was good without essentially rewriting it, and that cruft and subtle bugs dominate.
  • A recurring theme: even if AI helps individuals, it worsens open-source review bottlenecks.

Licensing, Copyright, and Legal Risk

  • The project’s justification includes uncertainty about the copyright status and provenance of AI-generated code under its license.
  • Discussion references court decisions that works without a human author may lack copyright, raising concerns for licensing compliance.
  • Comparisons are made to Stack Overflow snippets; some argue most such snippets are too trivial to be copyrightable, others disagree.

Competitiveness, Forks, and “Adapt or Die” Narratives

  • Some predict AI-enabled forks will outpace projects that ban AI; others note such forks “never seem to materialize” in practice so far.
  • There is skepticism toward rhetoric that non-AI projects or careers are doomed, with claims this has been said for years without evidence.
  • Others respond that tooling and models are changing quickly, so it’s too early to conclude.

Cultural and Ethical Attitudes toward AI

  • In game development and other “craft” domains, AI is often associated with corner-cutting and low-quality output.
  • Some view bans as valuing process and human craftsmanship; others see that as misplaced, arguing only correctness and maintainability matter.
  • Suggestions appear for “organic software” or AI-warning labels, especially for safety-critical code, though not everyone finds that desirable.

Platform and Ecosystem Concerns

  • Some argue projects should leave GitHub due to its AI integration and changing userbase, suggesting alternatives like Codeberg or self-hosting.
  • Others respond that any popular platform will eventually be flooded with AI-generated contributions.