Your agent can take action without waiting for a person. That sounds useful—until it approves the wrong refund, uses the wrong permission, or makes a decision nobody can explain.

Most teams respond with one of two extremes. They require approval for every step or allow the agent to act freely. Neither approach works when the task, risk, and cost of failure change.

This session introduces five levels of agent autonomy: operator, collaborator, consultant, approver, and observer. The framework treats autonomy as a per-task design choice—not a platform-wide setting. We will compare what changes in speed, permissions, evidence, human oversight, recovery, and the cost of a mistake. The comparison shows why a workflow that is safe for one decision may be unacceptable for another.

Attendees will leave able to classify agent workflows using the five levels, match autonomy to a task’s risk profile, and design clear permission and approval boundaries. They will also learn how to identify agents with too much—or too little—freedom.

The goal is not maximum autonomy. It is deliberate, observable control.

Audience: Engineers and engineering leaders designing agents that can take actions.
Format: 60–75-minute framework talk with a live comparative demo.
Demo: One refund request executed at three autonomy levels with different permission, evidence, and approval boundaries.
Evidence: New session
Materials: Talk-specific assessment worksheet, repository, slides, and recording are not yet published.
Vendor scope: Vendor-neutral design framework.