That would matter if we were asking the AI to generate code open-loop: someone probably already wrote something close to what you asked for in Python. But if the agent generates code, tries to compile it, sees the detailed error messages and acts on those messages to refine the code, it's going to produce a higher quality result. rustc produces really good diagnostics. And there's a lot of Rust code online now, even if there's so much more Python and Javascript/Typescript.

LLMs don't actually semantically parse the error messages. They will generate the most likely sequence resulting from the error message based on their training data, so you're back to the training data argument.