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The appeal of AI agents is that they do more than answer questions. They can create files, send messages, change data and move processes forward. That same power is also their main source of risk.

Without clear boundaries, a system may perform an action simply because it is technically possible, even when the business should not allow it.

Agent design should distinguish clearly between suggesting, preparing and executing. Many tasks can be prepared by AI while the final action still requires human approval.

Authority should also match the impact of the decision. Editing an internal label is not equivalent to messaging a customer or changing a financial record.

A professional agent should know what data it may read, what it may change, what limits apply to its actions, and under what conditions it must stop.

Logging and reversibility are part of the same boundary design. If we cannot see what the agent did, when it did it and with which inputs, we do not have meaningful control.

The goal is not to place a human in every step. The goal is to reserve human intervention for points where risk, ambiguity or decision impact is high.

Good automation means more speed with control. Remove the control and an agent may simply automate risk faster.