Agent deployment is the controlled release of an AI agent into an environment where it can receive real work and use approved tools. It covers configuration, credentials, evaluation gates, observability, rollout scope, rollback, and ownership, not merely uploading a prompt or model endpoint.
A deployment packages the agent runtime, tool contracts, and scoped credentials. AI agent evals gate release, and LLM observability watches real execution. Deployment is a change to an operating system, not a prompt publication.
When does agent deployment matter?
Start with a narrow workflow, limited users, and reversible actions. Define agent rollback before expansion and assign an owner for the full agent lifecycle. A green demo is not a production release.
Frequently asked questions
What is agent deployment used for?
Start with a narrow workflow, limited users, and reversible actions. Define agent rollback before expansion and assign an owner for the full agent lifecycle.
What must be ready before agent deployment?
The workflow needs passing evaluations, scoped credentials, logs, owners, stop conditions, and a recovery plan.
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