But every abstraction that an LLM has to write is a choice. Your way of writing Python may not match that choice. The next run of the agent might not choose the same way.

Because the language gives you many different tools, an LLM generated codebase can get inconsistent and overly complicated quickly. The flexibility of Python is a downside when you’re having an LLM generate the code. If you’re working in an existing codebase, it’s great - those choices were already made and it can match your style.

When an LLM has to derive its own style is when things can devolve into a jumbled mess.