Comment by jaggederest
7 hours ago
I believe that the issue right now is that we're using languages designed for human creation in an AI context. I think we probably want languages that are optimized for AI written but human read code, so the surface texture is a lot different.
My particular hypothesis on this is something that feels a little bit like python and ruby, but has an absolutely insane overkill type system to help guide the AI. I also threw in a little lispiness on my draft: https://github.com/jaggederest/locque/
I don't know, LLMs strive on human text, so I would wager that a language designed for humans would quite closely match an ideal one for LLMs. Probably the only difference is that LLMs are not "lazy", they better tolerate boilerplate, and lower complexity structures likely fit them better. (E.g. they can't really one-shot understand some imported custom operator that is not very common in its training data)
Also, they rely surprisingly closely on "good" code patterns, like comments and naming conventions.
So if anything, a managed language [1] with a decent type system and not a lot of features would be the best, especially if it has a lot of code in its training data. So I would rather vote on Java, or something close.
[1] reasoning about life times, even if aided by the compiler is a global property, and LLMs are not particularly good at that