I think this is a reasonable decision (although maybe increasingly insufficient).
It doesn't really matter what your stance on AI is, the problem is the increased review burden on OSS maintainers.
In the past, the code itself was a sort of proof of effort - you would need to invest some time and effort on your PRs, otherwise they would be easily dismissed at a glance. That is no longer the case, as LLMs can quickly generate PRs that might look superficially correct. Effort can still have been out into those PRs, but there is no way to tell without spending time reviewing in more detail.
Policies like this help decrease that review burden, by outright rejecting what can be identified as LLM-generated code at a glance. That is probably a fair bit today, but it might get harder over time, though, so I suspect eventually we will see a shift towards more trust-based models, where you cannot submit PRs if you haven't been approved in advance somehow.
Even if we assume LLMs would consistently generate good enough quality code, code submitted by someone untrusted would still need detailed review for many reasons - so even in that case it would like be faster for the maintainers to just use the tools themselves, rather than reviewing someone else's use of the same tools.
For well-intended open source contributions using GenAI, my current rules of thumb are:
* Prefer an issue over a PR (after iterating on the issue, either you or the maintainer can use it as a prompt)
* Only open a PR if the review effort is less than the implementation effort.
Whether the latter is feasible depends on the project, but in one of the projects I'm involved in it's fairly obvious: it's a package manager where the work is typically verifying dependencies and constraints; links to upstream commits etc are a great shortcut for reviewers.
The problem was already there with lazy bug reports and inflammatory feature requests. Now there is a lazy (or inflammatory) accompanying code. But there were also well-written bug reports with no code attached due to lack of time/skills that now can potentially become useful PRs if handled with application and engineering knowledge and good faith and will.
Isn't the obvious solution to not accept drive by changes?
> It doesn't really matter what your stance on AI is, the problem is the increased review burden on OSS maintainers.
But the maintainers can use AI too, for their reviewing.
> Even if we assume LLMs would consistently generate good enough quality code, code submitted by someone untrusted would still need detailed review for many reasons - so even in that case it would like be faster for the maintainers to just use the tools themselves, rather than reviewing someone else's use of the same tools.
Wouldn't an agent run by a maintainer require the same scrutiny? An agent is imo "someone else" and not a trusted maintainer.
Project maintainers will always have the right to decide how to maintain their projects, and "owe" nothing to no one.
That being said, to outright ban a technology in 2026 on pure "vibes" is not something I'd say is reasonable. Others have already commented that it's likely unenforceable, but I'd also say it's unreasonable for the sake of utility. It leaves stuff on the table in a time where they really shouldn't. Things like documentation tracking, regression tracking, security, feature parity, etc. can all be enhanced with carefully orchestrated assistance. To simply ban this is ... a choice, I guess. But it's not reasonable, in my book. It's like saying we won't use ci/cd, because it's automated stuff, we're purely manual here.
I think a lot of projects will find ways to adapt. Create good guidelines, help the community to use the best tools for the best tasks, and use automation wherever it makes sense.
At the end of the day slop is slop. You can always refuse to even look at something if you don't like the presentation. Or if the code is a mess. Or if it doesn't follow conventions. Or if a PR is +203323 lines, and so on. But attaching "LLMs aka AI" to the reasoning only invites drama, if anything it makes the effort of distinguishing good content from good looking content even harder, and so on. In the long run it won't be viable. If there's a good way to optimise a piece of code, it won't matter where that optimisation came from, as long as it can be proved it's good.
tl;dr; focus on better verification instead of better identification; prove that a change is good instead of focusing where it came from; test, learn and adapt. Dogma was never good.
I feel like the pattern here is donate compute, not code. If agents are writing most of the software anyway, why deal with the overhead of reviewing other people's PRs? You're basically reviewing someone else's agent output when you could just run your own.
Maintainers could just accept feature requests, point their own agents at them using donated compute, and skip the whole review dance. You get code that actually matches the project's style and conventions, and nobody has to spend time cleaning up after a stranger's slightly-off take on how things should work.
The review burden problem mirrors what happens with internal tools generally. Teams use AI to spin up an internal system in a weekend, everyone's impressed, then six months later someone's spending half their time maintaining it. The build was never the expensive part. The review, the edge cases, the ongoing maintenance - that's where the real cost lives, whether it's OSS contributions or internal tooling