Think of LLMs that use test-time inference (like o1) as "samplers".

Unlike classic LLMs, the more warnings you give them, the better.

Classic LLMs get confused when you tell them what "not to do".

LLMs with test-time inference use what "not to do" to eliminate bad outputs.