Autonomy changes the stakes. An assistant that suggests an answer and an agent that changes a system can use similar reasoning mechanisms, while creating very different operational consequences.
Separate intelligence from permission
A capable agent does not automatically need broad authority. Its identity, tools, and data access should be scoped to a defined job. A model’s ability to propose an action is separate from the application’s decision to permit that action.
Start by mapping the actions an agent can take. Reading a record, editing it, sending a message, and moving money represent different types of authority. Each should have a deliberate permission and approval model.
Design for intervention
- Bound the task: define the goal, allowed resources, and conditions that end the run.
- Limit tool access: grant only the operations and scope required.
- Gate consequential actions: decide which actions require explicit approval before execution.
- Make activity observable: record tool calls, approvals, errors, and outcomes.
- Plan recovery: provide a way to pause execution, revoke authority, and reverse changes where possible.
Approval needs useful context
A person asked to approve an action needs to see what will change, why the agent proposed it, and what evidence supports it. An approval screen that merely says “continue” offers little basis for a decision.
The operational test
Before expanding autonomy, ask: if the agent misunderstands its task or consumes manipulated information, how far can it go before a control intervenes? That distance is a useful starting point for your risk discussion.