Refusing to sufficiently specify a task and hoping the model guesses correctly is not being productive. Again, these models still don't really ask questions when they should. You have to explicitly tell them to.

Specifying the problem is not extra work separate from solving it. If you skip that step, the ambiguity gets pushed into the model’s assumptions. Then you get a plausible looking answer to the wrong problem and have to waste time backing out of it.

LLMs are not magic machines that can read your mind.