I suspect one of the principle reasons for the blanket decline is specifically that AI generated PRs are already responsible for a substantial uptick in the amount of work required to be done by maintainers. Engaging in discussions about those PRs may be more fulfilling and useful for the developer but it also then increases that work yet again manifold, so that would likely be highly counter-productive.
What I don't understand is: if you, for example, are a heavily AI-using dev, who spots a problem in OpenJDK, and you use Claude to figure it out: ok, why can't you then write the solution and PR yourself? Write your own code to replicate the functionality that Claude did, in your own style. Have Claude explain why this fixes the issue (it probably already did) and test it. If it works, write your own explanation and submit it as a PR.
I've done this a handful of times for smaller projects, in languages I'm unfamiliar with. Nobody complained because I didn't just copy the shit out of Claude, paste, copy the explanation, paste, and make a PR. I used Claude to increase my understanding, if even a bit and in a necessarily incomplete way, and did it myself.
> why can't you then write the solution and PR yourself?
You can. The policy explicitly allows you to use AI for understanding the codebase, debugging, etc. It just says “no AI generated content”. So if you use Claude to increase your understanding but then write your own code, that’s fine.
It sounds like you did exactly what OpenJDK would have wanted you to do, be the human in the loop.
You can, and indeed that's what we JDK developers do.
But even aside from the fact that writing the code is only a very small portion of the effort in this particular project (you can see that the volume of code making its way into the JDK is very small compared to the number of people involved), I'm often amazed by the gap between how well a frontier model (GPT 5.6 Sol in my case) can comprehend code and investigate a bug, and how badly it writes code and documentation, even when it understands things well. So not only is writing the code not a large portion of the effort in this project, it also happens to be one of the things current models don't do as well as other things.