AgentOps, Evaluation & Governance

A demo is a performance on a stage you control, with inputs you chose and a story you rehearsed. Production is the opposite: real inputs, real edge cases, real consequences when it gets one wrong. The gap between the two is where most AI projects quietly die, not because the idea was bad, but because nobody could say how often it would be right when it counted.

We build the evals that answer exactly that, how often it is right, on the cases you actually care about. Then the guardrails that stop the specific failure modes keeping you up at night, and the monitoring that catches a problem while it is still small instead of when a customer reports it. The dazzle was never the hard part. Trusting it on a quiet Tuesday is.

Once it is live it can be reached, and reached means tested, sometimes by people trying to make it misbehave on purpose. Prompt injection, actions the agent should never take on its own, decisions that genuinely need a human to sign off before anything irreversible happens. Going live without thinking these through is not boldness, it is just hoping nobody pushes on the soft spots.

We put real bounds on what the agent is allowed to do, and we place a person at exactly the points where a mistake would be expensive or hard to undo. The goal is not to wrap it in so much caution that it stops being useful. It is to make going live a considered step rather than a leap of faith.

Nor how often it fails, nor whether last week's well-meant change quietly made it worse for everyone. It works, mostly, as far as anyone can tell, which is a deeply uncomfortable place to be running something real. A system you cannot see into is a system you cannot actually operate. You are just hoping, with extra steps.

We add the tracing, the cost and latency tracking, and the versioning that turns the black box into something you can watch and reason about. When something changes you see it. When something breaks you know where. When the bill arrives there are no surprises in it, because you have been watching the meter the whole time.