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Three patterns I've noticed on the open-source projects I've worked on:

1. AI slop PRs (sometimes giant). Author responds to feedback with LLM generated responses. Show little evidence they actually gave any thought of their own towards design decisions or implementation.

2. (1) often leads me to believe they probably haven't tested it properly or thought of edge cases. As reviewer you now have to be extra careful about it (or just reject it).

3. Rise in students looking for job/internship. The expectation is that LLM generated code which is untested will give them positive points as they have dug into the codebase now. (I've had cases where they said they haven't tested the code, but it should "just work").

4. People are now even more lazy to cleanup code.

Unfortunately, all of these issues come from humans. LLMs are fantastic tools and as almost everyone would agree they are incredibly useful when used appropriately.

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> Unfortunately, all of these issues come from humans.

They are. They’ve always been there.

The problem is that LLMs are a MASSIVE force multiplier. That’s why they’re a problem all over the place.

We had something of a mechanism to gate the amount of trash on the internet: human availability. That no longer applies. SPAM, in the non-commercial sense of just noise that drowns out everything else, can now be generated thousands of times faster than real content ever could be. By a single individual.

It’s the same problem with open source. There was a limit to the number of people who knew how to program enough to make a PR, even if it was a terrible one. It took time to learn.

AI automated that. Now everyone can make massive piles of complicated plausible looking PRs as fast as they want.

To whatever degree AI has helped maintainers, it is not nearly as an effective a tool at helping them as it is helping others generate things to waste their time. Intentionally or otherwise.

You can’t just argue that AI can be a benefit therefore everything is fine. The externalities of it, in the digital world, are destroying things. And even if we develop mechanisms to handle the incredible volume will we have much of value left by the time we get there?

This is the reason I get so angry at every pro AI post I see. They never seem to discuss the possible downsides of what they’re doing. How it affects the whole instead of just the individual.

There are a lot of people dealing with those consequences today. This video/article is an example of it.

I've got a few open source projects out there, and I've almost never received any PRs for them until AI, simply because they were things I did for myself and never really promoted to anyone else. But now I'm getting obviously-AI PRs on a regular basis. Somehow people are using AI to find my unpromoted stuff and submit PRs to it.

My canned response now is to respond, "Can you link me to the documentation you're using for this?" It works like a charm, the clanker doesn't ever respond.

> Unfortunately, all of these issues come from humans.

I've been thinking about this recently. As annoying as all the bots on Twitter and Reddit are, it's not bots spinning up bots (yet!), it's other humans doing this to us.

> it's not bots spinning up bots (yet!)

Well, some of them are, but the bots bot is spun up by a human (or maybe bot n+1)

Great bots have little bots, if one should deign to write 'em

And little bots have lesser bots, and so ad infinitum...

If only I were lucky enough to get LLM generated responses, usually a question like "Did you consider if X would also solve this problem?" results in a flurry of force pushed commits that overwrite history to do X but also 7 other unrelated things that work around minor snags the LLM hit doing X.

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