AI agent autonomy: what to check before giving a system more control

What observed autonomy can tell us

Anthropic's February 18, 2026 study examines how people use agents in Claude Code and its API. It treats autonomy as the product of model behaviour, user choices and product design. Its findings are drawn from those environments, so they should not be assumed to describe every provider or workplace. Read the study.

A longer uninterrupted session can be worth investigating, but duration alone does not tell a manager whether the work was useful or correctly completed. A capable system and a well-designed handoff both matter.

Name the actions before assigning the role

For a scheduling assistant, list the actual operations: reading availability, suggesting a time, reserving a slot, notifying a customer and changing an existing booking. Each operation has a different consequence if it goes wrong.

Assign permissions at that level. A broad label such as office assistant gives the team less guidance than a clear rule about which calendar it may edit and which changes require review. Keep the permissions visible to the person responsible for the workflow.

Make intervention possible during the job

A useful status update says what the agent has completed, what it is doing now and what it needs. If a run involves several tools, the operator should be able to see which action caused the current state.

Our suggested trial includes a deliberate stop. Confirm that stopping the run prevents further actions, then check whether work already completed needs to be reversed. Do this with test records before relying on the stop control during a customer incident.

Also test uncertainty. Give the system a request with missing details and see whether it asks a useful question. Review should happen when it can change the outcome, not merely after every action is finished.

A pilot for an Alberta service office

Start with draft-only appointment summaries using sample data. Have staff compare the summaries with the original records and mark missing details. Next, permit changes to a test calendar and review the action history.

If the team later permits real booking changes, define how it will detect a duplicate reservation and who resolves a customer complaint. These are proposed trial steps, not a claim about a client deployment or its results.

Expand authority when the evidence supports it

Review whether the system completes the job, catches uncertainty and leaves an understandable record. Include the time staff spend supervising and correcting it. A workflow that demands constant rescue may need a narrower task, different tools or better instructions.

Preparing for superior intelligence includes learning how to delegate well. The useful milestone is a dependable workflow with understood boundaries. A marketing label cannot supply those boundaries for the team.