The Unstable Judge: Managing LLM Drift in Production

LLM unpredictability in production is not a solvable problem—it's an architectural challenge. When production teams discover that model providers silently update weights, breaking historical metrics and comparisons, the core issue becomes clear: relying on deterministic assumptions for inherently non-deterministic systems. The solution is defensive design: maintain calibration sets of human-validated examples and re-evaluate regularly to distinguish whether metric shifts result from model changes or actual data variations.