If the LLM understands the language it can aid in creation of the libraries and ecosystem because it can also translate code. I just tested it by having ChatGPT translate one of my Ruby scripts to Python for example.

I don't like Crystal all that much, but it's similar enough to Ruby that if ChatGPT can handle Ruby->Python, it can handle Ruby->Crystal with relatively little work.

But it doesn't need to handle it flawlessly, because every new library you translate and fix up gives you a new codebase you can use to finetune it.

We need RLHF -> RLCF/RLIF/RLEF (Reinforcement Learning from Compiler/Interpreter/Execution Feedback).

But that's the thing, libraries are written and it should be able to just read/learn/train on it, that's all.