This compiler experiment mirrors the recent work of Terence Tao and Google. The "recipe" is an LLM paired with an external evaluator (GCC) in a feedback loop.

By evaluating the objective (successful compilation) in a loop, the LLM effectively narrows the problem space. This is why the code compiles even when the broader logic remains unfinished/incorrect.

It’s a good example of how LLMs navigate complex, non-linear spaces by extracting optimal patterns from their training data. It’s amazing.

p.s. if you translate all this to marketing jargon, it’ll become “our LLM wrote a compiler by itself with a clean room setup”.

Edit: typo