LLMs take the path of least resistance. Pre-Reasoning hands any model a map of the problem first, so it unlocks the knowledge it already has, faster. For large models, that means hard problems and long-horizon tasks. For small models, consistency. Root blockers, unlock order, conflicts, parallel work. 12M params, runs locally on CPU in ~200ms.
