Ask a team how they will know their agent is working, and the quiet ones are the ones in trouble. "It seems good in the demo" is not a measurement. It is a vibe. And a vibe does not survive a model upgrade, a prompt edit, or the long tail of inputs a real workflow throws at you.
So we build the eval suite first — before the agent. We collect the inputs that matter, define what a correct output looks like, and write the checks that score it. The suite becomes the spec. It tells us when we have shipped, it catches regressions when a vendor changes the model under us, and it gives the client a number they can put in front of a board.
An eval suite is also the cheapest insurance you can buy in AI. It turns "trust me" into "here is the score," and that single shift is what lets a non-deterministic system live in production at all.
