Re: [MAINTAINERS / KERNEL SUMMIT] AI patch review tools

On Fri, 10 Oct 2025 05:08:47 +0200
Krzysztof Kozlowski <[email protected]> wrote:

> On 08/10/2025 19:04, Chris Mason wrote:
> > Hi everyone,
> > 
> > Depending on how you look at things, this is potentially a topic for
> > either MS or KS.
> > 
> > One way to lower the load on maintainers is to make it easier for
> > contributors to send higher quality patches, and to catch errors before
> > they land in various git trees.
> > 
> > Along those lines, when the AI code submission thread started over the
> > summer, I decided to see if it was possible to get reasonable code
> > reviews out of AI.
> > 
> > There are certainly false positives, but Alexei and the BPF developers
> > wired up my prompts into the BPF CI, and you can find the results in
> > their github CI.  Everything in red is a bug the AI review found:
> > 
> > https://github.com/kernel-patches/bpf/actions/workflows/ai-code-review.yml
> > 
> > My goal for KS/MS is to discuss how to enable maintainers to use review
> > automation tools to lower their workload.  I don't want to build new CI
> > here, so the goal would be enabling integration with existing CI.
> > 
> > My question for everyone is what would it take to make all of this
> > useful?  I'm working on funding for API access, so hopefully that part
> > won't be a problem.
> > 
> > There's definitely overlap between the bugs I'm finding and the bugs Dan
> > Carpenter finds, so I'm hoping he and I can team up as well.
> > 
> > In terms of actual review details, the reviews have two parts:
> > 
> > 1) The review prompts.  These are stand alone and can just work on any
> > kernel tree.  This is what BPF CI is currently using:
> > 
> > https://github.com/masoncl/review-prompts/
> > 
> > These prompts can also debug oopsen or syzbot reports (with varying
> > success).  
> 
> 
> In general, I like this entire idea a lot, because I believe it could
> drop many style or trivial review points, including obsolete/older code
> patterns.
> 
> Qualcomm is trying to do something similar internally and they published
> their code as well:
> https://github.com/qualcomm/PatchWise/tree/main/patchwise/patch_review/ai_review
> Different AI engines can be plugged, which solves some of the concerns
> in this thread that some are expected to use employer's AI.
> 
> They run that instance of bot internally on all patches BEFORE posting
> upstream, however that bot does not have yet AI-review enabled, maybe
> because of too many false positives?
> 
> I also think this might be very useful tool for beginners to get
> accustomed to kernel style of commit msgs and how the patch is supposed
> to look like.
> 
> Best regards,
> Krzysztof
> 


Has anyone tried asking AI to use existing mailing list review of previous patches
to generate its own future prompt?

If so, how did it go and what worked?