"The automation that \"worked\" for three weeks: a silent failure story"
An LLM automation I run produced wrong answers for three weeks while every dashboard said it was healthy. The failure was silent because the output stayed plausible. Here is what happened, how it was caught, and why exception monitoring will never save you from this class of bug.

For three weeks, an LLM automation I run processed incoming email, extracted the wrong information from a chunk of it, and reported success on every single run. No errors. No failed executions. No alerts. The dashboards were green the entire time, and the only reason I found out at all was a ten-minute habit I very nearly skipped that week.
Have an AI feature stuck between demo and production?
The gap — reliability, evals, cost control, the plumbing that keeps it running unattended — is exactly the work I do. If that sounds familiar, a short conversation is usually enough to point you the right way.
Book a free consultation