Picture this scenario. Your AI-powered feature is running. Every metric you watch looks clean. Error rate: flat. P99 latency: within SLO. HTTP 200s across the board. Your on-call engineer has nothing to page about. But for the last three days, the model has been producing subtly wrong output. Not wrong in a way that crashes anything. Not wrong in a way that fires a single alert. The responses are fluent, confident, and structurally perfect. They just happen to be incorrect in

Over the last ten years in Site Reliability Engineering, I have watched one word rise from technical obscurity to boardroom vocabulary: observability . It is now everywhere. Vendors lead with it. Engineering leaders budget for it. Teams build entire platforms around it. Every organization claims to be investing in it. And yet, in far too many environments, when a major production incident happens, the same confusion still surfaces within minutes: What changed? Where did it st