When AI silently fails for weeks
A production RAG system handling 12,000 queries/day recently ran for three weeks delivering silent errors, resulting in an estimated $40K in flawed decisions before anyone noticed.
The issue wasn't a crash or a syntax error. It was vector embedding drift—a silent failure state where the system returned incorrect results that appeared entirely plausible on the surface.
These are often called "ghost bugs." They don't throw runtime exceptions, they don't trigger error logs, and they typically pass standard unit tests. Below is an analysis of how this happens, how to identify it, and how to build a monitoring system to catch it.
Tool: Debug your vectors with Vector Distance Calculator
