Comment by EMM_386
5 hours ago
This is getting really out of control at the moment and I'm not exactly sure what the best way to fix it is, but this is a very good post in terms of expressing the why this is not acceptable and why the burden if shifting on the wrong people.
Will humans take this to heart and actually do the right thing? Sadly, probably not.
One of the main issues is that pointing to your GitHub contributions and activity is now part of the hiring process. So people will continue to try to game the system by using LLMs to automate that whole process.
"I have contributed to X, Y, and Z projects" - when they actually have little to no understanding of those projects or exactly how their PR works. It was (somehow) accepted and that's that.
I see the problem everyday and am just playing devil's advocate but it doesn't really do a good job explaining the "why".
They hint at Django being a different level of quality compared to other software, wanting to cultivate community, and go slowly.
It doesn't explain why LLM usage reduces quality or they can't have a strong community with LLM contributions.
The problem is that good developers using LLM is not a problem. They review the code, they implement best practices, they understand the problems and solutions. The problem is bad developers contributing - just as it always has been. The problem is that LLMs enable bad developers to contribute more - thus an influx of crap contributions.
The last section focuses on how to use LLMs to make contributions:
> Use an LLM to develop your comprehension.
I really like that, because it gets past the simpler version that we usually see, "You need to understand your PR." It's basically saying you need to understand the PR you're making, and the context of that PR within the wider project.
I think they explain "why" very clearly. They say the problem is people who don't understand their own contributions.
A decade or more of people copy-pasting rote solutions from StackOverflow only supports the notion that many people will forego comprehension to foster the illusion of competent productivity.
This ain't an AI problem, it's a people problem that's getting amplified by AI.
It was interesting the other day tracing the lineage of Aaron Swartz -> Library Genesis / Sci-Hub -> LLM vendors relying on that work to train their models and sell it back to us all with no royalties or accountability to the original authors of all this painstakingly researched, developed, and recorded human knowledge they’re making billions on.
they are not making billions.. they are burning billions.
That's true. Except that you can have Agents doing it 24/7 with no human input. The amount of repos/PRs is only limited by GPUs
> One of the main issues is that pointing to your GitHub contributions and activity is now part of the hiring process.
If I were hiring at this moment, I'd look at the ratio of accepted to rejected PRs from any potential candidate. As an open source maintainer, I look at the GitHub account that's opening a PR. If they've made a long string of identical PRs across a wide swath of unrelated repos, and most of those are being rejected, that's a strong indicator of slop.
Hopefully there will be a swing back towards quality contributions being the real signal, not just volume of contributions.
I now want to create a public index of “slop” contributors. People need to know their “heroes”.
> Will humans take this to heart and actually do the right thing? Sadly, probably not.
Don’t blame the people, blame the system.
Identifying the problem is just the first step. Building consensus and finding pragmatic solutions is hard. In my opinion, a lot of technical people struggle with the second sentence. So much of the ethos in our community is “I see a problem, and I can fix it on my own by building [X].” I think people are starting to realize this doesn’t scale. (Applying the scaling metaphor to people problems might itself be a blindspot.)
You can blame both! The people are definitely not helping.
What kinds of actionable plans ever result from blaming people (as a category)? Where will it get you? Expecting some people to behave differently... just "because"? What kinds of plans flow downstream from blaming human nature? What's the plan? Does it help you somehow, practically? Or is it mostly about feeling better somehow?
If the plan is persuasion, putting blame aside goes a long way.
If you want to make change based in the real world, you could do worse that reading and absorbing "Thinking in Systems: A Primer" by Donella Meadows.
Obviously the solution is better AI PR reviewers with more context for FOSS projects /s
And I’m 100% sure there are dozens of startups working on that exact problem right this second.