The Zig project's rationale for their anti-AI contribution policy

Source: Hacker News

Zig’s anti‑LLM policy

Zig (ziglang.org) enforces one of the most stringent anti‑LLM policies among major open‑source projects, as outlined in its code of conduct:

• No LLMs for issues.
• No LLMs for pull requests.
• No LLMs for comments on the bug tracker, including translation. English is encouraged but not required; contributors may post in their native language and rely on others to translate.

Bun and AI assistance

The most prominent project written in Zig is the Bun JavaScript runtime. In December 2025, Bun was acquired by Anthropic and makes heavy use of AI assistance.

Bun maintains its own fork of Zig and recently announced a 4× performance improvement on Bun compile after adding “parallel semantic analysis and multiple codegen units to the LLVM backend.” Details can be seen in the GitHub comparison and the announcement tweet:

“We do not currently plan to upstream this, as Zig has a strict ban on LLM‑authored contributions.” – @bunjavascript

Contributor Poker and Zig’s AI ban

Loris Cro, Zig Software Foundation VP of Community, explains the rationale behind the ban in his post “Contributor Poker and Zig’s AI Ban” (also discussed on Lobsters).

In successful open‑source projects you eventually reach a point where you start getting more PRs than what you’re capable of processing. Given what I mentioned so far, it would make sense to stop accepting imperfect PRs in order to maximize ROI from your work, but that’s not what we do in the Zig project. Instead, we try our best to help new contributors get their work in, even if they need some help getting there. We don’t do this just because it’s the “right” thing to do, but also because it’s the smart thing to do.

Zig values contributors over their contributions. Each contributor represents an investment by the Zig core team – the primary goal of reviewing and accepting PRs isn’t to land new code, it’s to help grow new contributors who can become trusted and prolific over time.

LLM assistance breaks that completely. It doesn’t matter if the LLM helps you submit a perfect PR to Zig – the time the Zig team spends reviewing your work does nothing to help them add new, confident, trustworthy contributors to their overall project.

The reason I call it “contributor poker” is because, just like people say about the actual card game, “you play the person, not the cards”. In contributor poker, you bet on the contributor, not on the contents of their first PR.

Key takeaways

• Zig’s policy aims to nurture contributors, not just code.
• Allowing LLM‑generated PRs would shift reviewer effort from mentorship to mere code validation.
• “Contributor poker” frames contribution review as an investment in people rather than a gamble on isolated patches.
• Projects that rely heavily on AI assistance (e.g., Bun) may face upstream integration hurdles with Zig due to this policy.