Hi Pedro, Thanks for raising this issue, and I think it's very timely in that many of us are experiencing similar issues. Your proposal sounds good to me.
Nic On Fri, 18 Sept 2026 at 10:33, Pedro Matias <[email protected]> wrote: > Hello all, > > I'd like to revive this thread. My goal is simple: I want to discuss > establishing guidelines for reviewers, especially those of us who are not > Arrow committers/PMCs, on how to handle low-quality PRs with weak > engagement. The community added AI guidelines for contributors, but not for > reviewers: https://arrow.apache.org/docs/developers/reviewing.html > > Lately I've been reviewing a PR that I think fits this description. I've > pointed the person to the AI guidelines at > https://arrow.apache.org/docs/developers/overview.html#ai-generated-code, > but the guidelines were ignored. I can continue steering the code with > reviews, but I am afraid this might encourage others to repeat this pattern > of weak engagement. > > I repeat R. Tyler Croy's ask: "don't rely on everybody following the rules, > and come up with an agreed upon way to handle those that don't." > > I looked into other projects to see if any of them have something similar. > LLVM has guidance [0] on both how to warn the contributor and when to > escalate to someone with permission to lock the conversation, as well as a > label that can be added to a low effort PR. > > I propose we add a section titled "Handling violations of the AI > contribution guidelines" to the reviewer guidelines. I wrote a small draft > [1] of what it could look like. I'm happy to iterate on it if people think > this is something worth adding. > > I'm particularly curious about what committers/PMC members think should be > the way for read-only reviewers to escalate to maintainers. The current > proposal suggests pinging someone, which might be too noisy. > > 0- https://llvm.org/docs/AIToolPolicy.html#handling-violations > > 1- When a reviewer finds that a contribution does not seem to conform to > the guidelines for AI usage, they should respond with the following > message: > " > This PR does not seem to meet the standards for AI generated contributions. > Please read the guidelines at > https://arrow.apache.org/docs/developers/overview.html#ai-generated-code > and ensure you modify your PR to conform to the rules. > " > If the contributor fails to adapt their work and/or engagement level to > meet the guidelines' standards, maintainers may close the PR. Reviewers > without permission to close the PR should escalate by pinging a maintainer > via comment indicating that they do not believe the change meets the > standards. > > Best regards, > Pedro Matias > > > > > On Fri, Feb 13, 2026 at 3:53 PM Nic Crane <[email protected]> wrote: > > > On a similar note, after conversations with folks around what appear to > be > > AI-generated mailing list responses, I've also opened a PR suggesting > > people disclose any AI-generated questions they post to mailing list > > discussions; feel free to add any comments there (if you're a human! ;) ) > > > > https://github.com/apache/arrow/pull/49277/changes > > > > > > On Thu, 22 Jan 2026 at 20:42, Nic Crane <[email protected]> wrote: > > > > > PR here for anyone interested: > > https://github.com/apache/arrow/pull/48952 > > > > > > On Thu, 22 Jan 2026 at 09:56, Nic Crane <[email protected]> wrote: > > > > > >> Thanks Andrew, I really like how you spell out the reasoning around > it, > > I > > >> will see how we can incorporate some of those ideas > > >> > > >> On Thu, 22 Jan 2026 at 09:23, Andrew Lamb <[email protected]> > wrote: > > >> > > >>> > We have had repeated attempts at contributions by some folks who > > simply > > >>> do not understand their generated code and when asked for > > clarification, > > >>> have the LLM generate more incorrect commentary. It's very > > >>> Dunning-Krueger > > >>> and leads to lots of frustration all around. > > >>> > > >>> We saw this too in DataFusion and I was pleased with what we came up > > with > > >>> for rationale about why it is not helpful[1]. Basically the reviewers > > are > > >>> more efficient using the LLM tools directly and the contributor isn't > > >>> learning anything either. > > >>> > > >>> Andrew > > >>> > > >>> > > >>> [1]: > > >>> > > >>> > > > https://datafusion.apache.org/contributor-guide/index.html#why-fully-ai-generated-prs-without-understanding-are-not-helpful > > >>> > > >>> On Mon, Jan 19, 2026 at 12:48 PM R Tyler Croy <[email protected]> > > >>> wrote: > > >>> > > >>> > (replies inline) > > >>> > > > >>> > On Sunday, January 18th, 2026 at 7:43 PM, Gang Wu < > [email protected]> > > >>> > wrote: > > >>> > > > >>> > > - Summitters should review all lines of generated code before > > >>> creating > > >>> > the > > >>> > > PR to > > >>> > > understand every piece of detail just like they are written by > the > > >>> > > submitters > > >>> > > themselves. > > >>> > > - AI tools are notorious for generating overly verbose comments, > > >>> > unnecessary > > >>> > > test cases, fixing test failures using wrong approaches, etc. > Make > > >>> sure > > >>> > > these > > >>> > > are checked and fixed. > > >>> > > - Reviewers are humans, so please try to break down large PRs > into > > >>> > smaller > > >>> > > ones to make reviewers' life easier to get PRs promptly reviewed. > > >>> > > > >>> > > > >>> > Like others I think Nic's draft is a good one, I would like to > offer > > >>> some > > >>> > thoughts as a maintainer (delta-rs) which has received increased > > >>> > AI-assisted pull requests over the past six months. > > >>> > > > >>> > > > >>> > The "PR may be closed without further review" statement I would > > >>> strongly > > >>> > encourage moving to the very beginning of the policy. I would also > > >>> > encourage labels being used like "ai-assisted" to signal to other > > >>> > contributors who may or may not wish to engage in reviewing > potential > > >>> slop. > > >>> > > > >>> > We have had repeated attempts at contributions by some folks who > > >>> simply do > > >>> > not understand their generated code and when asked for > clarification, > > >>> have > > >>> > the LLM generate more incorrect commentary. It's very > > Dunning-Krueger > > >>> and > > >>> > leads to lots of frustration all around. > > >>> > > > >>> > Like most policies it's important to speak to those that are acting > > in > > >>> > good faith but don't rely on everybody following the rules, and > come > > up > > >>> > with an agreed upon way to handle those that don't. > > >>> > > > >>> > > > >>> > Either way I think it's good to ship! :) > > >>> > > > >>> > > > >>> > > > >>> > Cheers > > >>> > > > >>> > > > >>> > > >> > > >
