Enthusiasm ships demos. Evaluation ships systems. The gap between those two sentences is where most "AI transformations" go to die, loudly in Slack, quietly in the budget.
Before an agent touches a live desk we instrument task success, latency budgets, and failure modes that matter in that domain. Freight cares about quote validity. Insurance cares about consent and show rate. Energy cares about false curtailment alarms. One generic scorecard will lie to all of them.
Name the failure
Without that harness, "it worked in the meeting" becomes "it failed on Friday at 4pm," and nobody can explain why. You cannot govern what you cannot measure. You cannot improve what you refuse to taxonomy.
If you can't measure hallucination, latency, and task success, you can't govern an agent. Full stop.
Evaluation is not a phase after launch. It is the gate that decides whether launch is honest. We run golden sets, adversarial prompts, and regression suites the same way a serious eng team runs tests on payments code, because outbound agents are payments with words.
Bring enthusiasm to the whiteboard. Bring evaluation to production. In that order, always.
