Ever since AlphaEvolve - the idea that if you build a harness which can evaluate solutions and give LLMs a database where they can keep storing their work and then sample from it - they do find non-trivial solutions over time leaning from their own past ideas.

It is the ultimate manifestation of test-time scaling. I think karpathy just popularised it.

I didn't dig into what the actual repository was doing, but personally, I took some inspiration from the idea after reading about it and realizing that I might have been underestimating the ability of LLMs. I put a bit more work into a performance harness I was using locally and just set some agents to brainstorming and they did seem to find some great stuff. So I don't really have a stance one way or another on this specific repo, but the general idea seems like a really good one.

Karpathy embedded within an organization is way more impressive than him out on his own with hot takes and little projects. I hope he does great things for Anthropic.

    > Am I the only one who wasn’t particularly impressed by AutoResearch?

isn't it just a nerfed AlphaEvolve? https://arxiv.org/abs/2506.13131

Inefficient variants with $100m+ worth of compute will still probably outperform the best team of researchers

I'm as jaded as can be but I think Anthropic is now beyond the point where they'd place much value on farming Karpathy's name recognition. I'm sure they considered it an extra plus in his hiring package but they wouldn't do the level of comp package he'd want if they didn't believe the odds were decent that he'll contribute serious value.

Sure, it can always not work out but that's no more a risk with him than any high-profile hire who doesn't really need the money and will always have other options.

What is he selling? How is this time different compared to when he was at OpenAI or at Tesla? You could say he was shilling those products too. I don't see any shift. He's still posted free in depth YouTube videos recently.