Comment by reitzensteinm

But coding is largely trained on synthetic data.

For example, Claude can fluently generate Bevy code as of the training cutoff date, and there's no way there's enough training data on the web to explain this. There's an agent somewhere in a compile test loop generating Bevy examples.

A custom LLM language could have fine grained fuzzing, mocking, concurrent calling, memoization and other features that allow LLMs to generate and debug synthetic code more effectively.

If that works, there's a pathway to a novel language having higher quality training data than even Python.