Conversations in its training data that explicitly mentioned "make no mistakes" don't strike me as particularly rich sources of high-quality reasoning signals. They strike me as conversations with Pointy-haired Bosses.

I'm not sure if they've fixed this, but older models have a tendency to ignore negation as `no`, `not`, etc. all occur frequently in the training data so are weighted less strongly than the verbs and nouns.

The advice I've heard is to emphasize the traits you want, not discourage the traits you don't. So rather than saying "make no mistakes" you can do something like you suggested with writing it as "check your work" or "ensure you answer correctly and concisely".