It's not the default, because the training data is full of unmaintainable code done wrong with mistakes. People literally complain that LLMs write too many tests or add comments.

If instead of "do it right", you give it specific actionable advice of how to right code, it does surprisingly well. Newer frontier models also do a great job of mimicking the style and rigor of the surrounding codebase without prompting, if you're working in an established codebase, for better or worse.

You never wrote quick exploratory code? One off scripts? How is the Ai suppsed to know unless you tell it.

If you tell another person to write some code, how are they suppsed to know? If you have your boss come to you and ask you to write some code to do some data analysis are you going to spend weeks writing units tests and perfect abstractions? Or do it quick and get the data and result?