The training loop asked the model to one-shot working code for the given problems without being able to iterate. If you had to write code that had to work on the first try, and where a partially correct answer was better than complete failure, I bet your code would look like that too.

In any case, it knows what good code looks like. You can say "take this code and remove spurious comments and prefer narrow exception handling over catch-all", and it'll do just fine (in a way it wouldn't do just fine if your prompt told it to write it that way the first time, writing new code and editing existing code are different tasks).

There are a bunch of stupid behaviors of LLM coding that will be fixed by more awareness pretty soon. Imagine putting the docs and code for all of your libraries into the context window so it can understand what exceptions might be thrown!

Well, at least now we know who to blame for the training data :)

What’s a blind exception?