It is the same with human chain of thought, though. Both of them are post-hoc rationalisations justifying "gut feelings" that come from thought processes the human/agent doesn't have introspection into. And yet asking humans or machines to "think out loud" this way does increase the quality of their work.
I disagree - humans often reason in a series of steps, and can write these down before they've reached an answer. They don't always wait till they reach a conclusion (with no self-insight into how they did so) and then retrospectively generate a plausible answer as LLMs do.
In mathematical proofs they may guess and answer and then work out a proof, but that is a different process.
