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Comment by comboy | Hacker News Reader

Perhaps we should start making LLM- open source projects (clearly marked as such). Created by LLMs, open for LLM contributions, with some clearly defined protocols I'd be interesting where it would go. I imagine it could start as a project with a simple instruction file to include in your project to try to find abstractions which can be useful to others as a library and look for specific kind of libraries. Some people want to help others even if they are sharing effectively money+time rather than their skill.

Although I'm afraid big part of these LLM contributions may be people trying to build their portfolio. Some known project contributor sounds better than having some LLM generated code under your name.

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OpenClaw https://github.com/openclaw/openclaw is effectively that - 1,237 contributors, 19,999 commits and the first commit was only back in November.

Simon, as co-creator of Django, what's your take on this story?

I think this line says everything:

> If you do not understand the ticket, if you do not understand the solution, or if you do not understand the feedback on your PR, then your use of LLM is hurting Django as a whole.

I love it. Sounds like good advice for submitting a PR to any project!

Why does it matter if the I understand the ticket and solution? THe LLLM writes the code not me. If you want to check the LLM understanding i'll be happy to copy and paste your gatekeeping questions to it.

Hey I thought you were a proponent of "no one needs to look at the code" ? dark factory, etc etc.

Just because I write about the dark factory stuff doesn't mean I'm a "proponent" of it. I think it's interesting and there's a lot we can learn from what they are trying, but I'm not yet convinced it's the right way to produce software.

The linked article makes a very good argument for why pasting the output of your LLM into a Django PR isn't valuable.

The simplest version: if that's all you are doing, why should the maintainers spend time considering your contribution as opposed to prompting the models themselves?

> if that's all you are doing, why should the maintainers spend time considering your contribution as opposed to prompting the models themselves?

Plenty of reasons: - Maybe the maintainers don't have enough credits to run the LLM themselves - Maybe the maintainers don't value fixing the issue which is why it sits in issue tracker - Maybe LLM user has a different model or harness that produces different outcomes - Maybe the LLM user runs the model over and over and gets lucky

Why reject a working solution?

Again, "if that's all you are doing".

You can contribute code that an LLM helped with if you do the extra work to review, verify and explain that code.

Don't put all of that burden on the maintainers who have to review it.

LLM are capable of "review, verify and explain", as much as they are "code".

Please do, that would be amazing.

You'd have to manage the contributions, or get your AI bots to manage them or something, but it would be great to have honeypots like this to attract all the low effort LLM slop.

I like the idea that we could quarantine away LLM contributions like how Twitter quarantines the worst of social media away from Mastodon etc.

Moltbook meets GitHub? Sounds like a billion dollar valuation (sarcasm tag deliberately omitted).

Actually, I'd want to see that. All the AI companies keep saying it will take our jobs, human developers won't be necessary.

Well let them put their money where their mouth is. Let's see what happens, see what the agents create or fail to create. See if we end up with a new OS, kernel all the way up to desktop environment.

Me too, the problem is that it's hard to come up with tools that are needed but not made yet, and we don't want to end up with https://malus.sh/index.html

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