How We Detect AI Agent Drift (Before Your Users Do)

Your AI agent passed every evaluation. Shipped to production. Worked perfectly for two weeks. Then it started getting dumber, and nobody noticed. We talked to 11 teams running AI agents in production. Every single one told us some version of the same story: the agent worked great in testing, great in staging, great in the first week of production. Then somewhere around week two or three, outputs started degrading. Not crashing. Not throwing errors. Just... slowly getting worse. By the time anyone noticed, the damage was done. Users had already seen bad outputs. Trust was already eroded. The logs showed nothing. Monitoring dashboards were green. Every health check passed. This is the problem we set out to solve with Vex . Not observability (watching agents fail), not guardrails (blocking known bad patterns). Something different: detecting the failures nobody is looking for, and correcting them before users see them. This post is about how the drift detection part works under the hood. W