Awesome stuff. Output speed looks crazy fast too.

I wonder if this indeed will start prompting more language specific work.

Afaik training still requires not just looking at sample code but also being able to write loss functions being able to have problems the AI can work at. That seems hard.

One random thought, are there training styles of just deleting some code from "good" projects then making the AI make it work again?

The technique people use is to capture PR diffs from public repos and extract the tests then use that to see if agents can reconstruct the patch that satisfies the tests.