Relevant since we started outright rejecting agent-made PRs in awesome-selfhosted [1] and issuing bans for it. Some PRs made in good faith could probably get caught in the net, but it’s currently the only decent tradeoff we could make to absorb the massive influx of (bad) contributions. >99.9% of them are invalid for other reasons anyway. Maybe a good solution will emerge over time.
IMHO what it shows isn’t what the author tries to show, namely that there is an overwhelming swarm of bits, but rather that those bots are just not good enough even for a bot enthusiast. They are literally making money from that “all-in-one AI workspace. Chat - MCP - Gateway” and yet they want to “let me prioritize PRs raised by humans” … but why? Why do that in the first place? If bots/LLMs/agents/GenAI genuinely worked they would not care if it was made or not by humans, it would just be quality submission to share.
Also IMHO this is showing another problem that most AI enthusiasts are into : not having a proper API.
This repository is actually NOT a code repository. It’s a collaborative list. It’s not code for software. It’s basically a spreadsheet one can read and, after review, append on. They are hijacking Github because it’s popular but this is NOT a normal use case.
So… yes it’s quite interesting to know but IMHO it shows more shortcomings rather than what the title claims.
I’m not sure I totally understand your comment, so bear with me if I’m agreeing with you and just not understanding that.
Before LLMs, there was a kind of symmetry about pull requests. You could tell at a glance how much effort someone had put into creating the PR. High effort didn’t guarantee that the PR was high quality, but you could be sure you wouldn’t have to review a huge number of worthless PRs simply because the work required to make something that even looked plausibly decent was too much for it to be worth doing unless you were serious about the project.
Now, however, that’s changed. Anyone can create something that looks, at first glance, like it might be an actual bug fix, feature implementation, etc. just by having the LLM spit something out. It’s like the old adage about arguing online–the effort required to refute bullshit is exponentially higher than the effort required to generate it. So now you don’t need to be serious about advancing a project to create a plausible-looking PR. And that means that you can get PRs coming from people who are just trolls, people who have no interest in the project but just want to improve their ranking on github so they look better to potential employers, people who build competing closed-source projects and want to waste the time of the developers of open-source alternatives, people who want to sneak subtle backdoors into various projects (this was always a risk but used to require an unusual degree of resources, and now anyone can spam attempts to a bunch of projects), etc. And there’s no obvious way to tell all these things apart; you just have to do a code review, and that’s extremely labor-intensive.
So yeah, even if the LLMs were good enough to produce terrific code when well-guided, you wouldn’t be able to discern exactly what they’d been instructed to make the code do, and it could still be a big problem.