Almost any team can build an AI demo that looks magical in a controlled setting. Far fewer ship an agent that quietly does real work in production. The difference is rarely the model — it's everything around it.
Start with one painful, repetitive job
The best first agent isn't the most ambitious one. It's a narrow, high-volume task people already do by hand: triaging tickets, extracting fields from documents, drafting the same three replies. Narrow scope means you can measure whether it's actually working.
Ground it in your own data
An agent that answers from your help docs, past tickets and real records — via retrieval — is worth far more than one improvising from general knowledge. Grounding is also what makes answers auditable: you can see which source a response came from.
Design the handoff before the happy path
Every reliable agent knows when to stop and pass to a human. Decide the confidence threshold, the escalation path and the logging up front. A clean handoff is what earns the trust to let the agent handle more over time.