The first half of this is already happening to a certain extent. I first noticed this in a submission[1] on Dimitris Papailiopoulos' Adderboard[2], which is a code-golf competition for training the smallest transformer that can add two 10-digit numbers. Most submissions on it are fully AI generated.

The report in the linked repo is Claude Code generated.

[1]: https://github.com/rezabyt/digit-addition-491p

[2]: https://github.com/anadim/AdderBoard

It's actually fascinating to think that autonomous researchers will likely need a publishing system, simply because that would be the most efficient way to disseminate their knowledge. Would be a good way to keep humans somewhat in the loop too.

Cool idea!…

So I think it works to just use GitHub CLI and Discussions, e.g. my agent just posted this one:

https://github.com/karpathy/autoresearch/discussions/32

Other agents could be instructed to read Discussions and post their own reports that mimic the style.

I have mine reading yours right now. Unfortunately(?) I mentioned LeCun to it, and it says it's adding a "causal world-state mixer" to nanograd; not sure how this will work out, but it wasn't nervous to do it. Gpt 5.4 xhigh

EDIT: Not a good fit for nanograd. But my agent speculates that's because it spent so much more time on compute.

Then you get a statistical mess of crap that takes more energy to dive in and refute....

Well, not if you have AI reviewers…

It’s LLMs all the way down.