An artificial intelligence agent operates as a loop: it receives context, chooses an action, uses a tool or service and incorporates the result into its next decision. Because tool calls can alter external systems, the agent's practical boundary extends beyond the model itself.
Reliable agents need deterministic controls around their probabilistic decisions. Permissions, state management, validation, observability and recovery mechanisms constrain what the agent can do and make failures understandable when the model chooses a poor action.
