AI & automationMarch 20267 min read
Measuring an AI agent in production
An agent that worked in the demo can drift silently in production. Without continuous measurement, you will only find out when a customer does.
How do I know if my AI agent really works?
By measuring the correctness of its answers continuously, not just on demo day. An agent that worked at launch can drift silently three weeks later: the data changes, the usage too, and the quality erodes without a single crash. Without continuous measurement, you will only find out when a customer does.
Which metrics give false comfort?
Response time and the technical error rate. They are useful, but they say nothing about the correctness of the answers: an agent can be fast, never crash, and still be wrong half the time. Relying on them alone reassures you on the form while ignoring the substance.
Which metrics truly matter?
Three signals: the real quality of the answers on a continuously evaluated sample, the escalation rate to a human, and the cases where the agent makes things up. Those are the ones that warn you before the client notices, and that trigger a fix in time.
An agent you don't measure is not in production. It is a gamble.