A standard protocol to handle and discard low-effort, AI-Generated pull requests

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To be entirely fair "sorta working, solving a problem but not really all that great for the rest of the codebase" PRs are human thing too.

The problem is AI generating it en masse, and frankly most people put far less effort that even your first paragraph and blindly push stuff they have not even read let alone understood

> Interestingly, the pro-AI folks almost universally doubled down and said that I should use AI more to gain more confidence – ask how can I test it, how can we verify it, etc – to move my confidence instead of changing how review works.

Well, it's not terrible at just getting your bearings in the codebase, the most productive use I got out of it is treating it as "turbo grep" to look around existing codebases and figure out things

This made my day, thank you

Here’s what you could do if you somehow found yourself with an LLM-generated change to a codebase implementing a feature you want, and you wanted to do the most do expedite the implementation of that feature without disrespecting and alienating maintainers:

1. Go through all changes, understand what changed and how it solves the problem.

2. Armed with that understanding, write (by hand) a high-level summary of what can be done (and why) to implement your feature.

3. Write a regular feature request, and include that summary in it (as an appendix).

Not long ago I found myself on the receiving end of a couple of LLM-generated PRs and partly LLM-generated issue descriptions with purported solutions. Both were a bit of a waste of time.

The worst about the PRs is when you cannot engage in a good-faith, succint and quick “why” sort of discussion with the submitter as you are going through changes. Also, when PR fails to notice a large-scale pre-existing pattern I would want to follow to reduce mental overhead and instead writes something completely new, I have to discard it.

For issues and feature requests, there was some “investigation” submitter thought would be helpful to me. It ended up a bit misleading, and at the same time I noticed that people may want to spend the same total amount of effort on writing it up, except so now part of that effort goes towards their interaction with some LLM. So, I asked to just focus on describing the issue from their human perspective—if they feel like they have extra time and energy, they should put more into that instead.

If it happens at work, I obviously still get paid to handle this, but I would have to deprioritise submissions from people who ignore my requests.

> Go through all changes, understand what changed and how it solves the problem.

GP has said that they can't do this, since they're unfamiliar with the language and that specific part of the codebase. Their best bet AIUI is (1) ask the AI agent to reverse engineer the diff into a high-level plan that they are qualified to evaluate and revise, if feasible, so that they can take ownership of it and make it part of the feature request, and (2) attach the AI-generated code diff to the feature req as a mere convenience, labeling it very clearly as completely unrevised AI slop that simply appears to address the problem.