Leaning into ML-driven tooling for utilitarian automation.

I am worried specifically about LLMs/chatbots, not machine learning in general.

The later is rarer among established developers, mostly because those devs tend to not to vibecode if they already know what they’re doing. Maintainer status tends to be on merit and history, and so on.

What about outside contributors submitting massive patches using AI, and overwhelming the maintainers? This recently happened with Linux, and the maintainers said they will use LLMs to review submissions going forward. Does that increase the risk of bugs creeping in?

I apologize if I seem argumentative. I am trying to understand the risks of AI generated code, and you seem quite knowledgeable on the subject.

I hope so. But we have seen how Andrew Tridgell, a competent, veteran greybeard, turned rsync into an unusable mess when he embraced AI.

They have institutional structure that doesn’t change at the drop of a hat.

But could the institutional structure erode over time? For example if some of the maintainers get fed up with the AI hype and leave, and the remaining ones lean into AI even more?

Would it affect the stability of my project in the long run if that happens, even if things are relatively okay right now because of the standards and institutional structures?

The Open Slopware repository on Codeberg has a section on programming languages that use AI, with citations.

https://codeberg.org/ethical-foss/open-slopware#programming-languages

The maintainers accept LLM generated patches or use LLMs for code review or finding bugs.

Insert the Padme Anakin meme here.