Agentic AI in production: a checklist for enterprise teams
Running AI agents in production needs five things beyond a working prototype: a clear task boundary, an evaluation suite, guardrails on tools and data, human approval for high-impact actions, and observability for cost and quality. Missing any one of them is the usual reason pilots never ship.
1. A clear task boundary
Define what the agent may and may not do, which systems it can touch, and what counts as done.
2. Evaluation before launch
Build a test set from real cases and score accuracy, safety and cost. Re-run it on every change.
3. Guardrails and approvals
Restrict tools and data by role, and require a person to approve actions such as payments, deletions or customer-facing commitments.
4. Observability
Log every step, track cost per task, and alert on drift. Agents improve only when you can see what they did.
5. An owner
Someone in the business owns outcomes. Forward Deployed Engineers often fill this role during rollout.
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