Originally published on AI Tech Connect.
What you need to know Drift happens with zero code changes. A provider updates the model behind a stable alias, real traffic diverges from your golden set, the surrounding product changes what the model sees, or a tool dependency shifts. Continuous monitoring is a different discipline from CI evals. CI catches regressions your team introduced; production monitoring catches regressions that happened to you. An LLM-as-judge scoring sampled live traffic is the practical backbone — but the judge itself needs periodic recalibration, or it drifts quietly alongside the system it is grading. A statistical test, not a glance at a dashboard, is what separates a real regression from ordinary sampling noise. Golden sets rot. The fix is a standing process that pulls real production incidents back into…
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