Agent Autonomy

A practical example

Example: the same research agent runs fully autonomously when enriching internal account records, but drops to draft-only mode — requiring a human click before anything is sent — whenever its output targets an external contact.

What to evaluate before investing

• Ask whether autonomy can be scoped by action type, audience (internal vs. external) and data sensitivity, not just per agent.
• Test whether autonomy levels can change dynamically, for example tightening limits after detected errors.
• Confirm who can change autonomy settings and whether changes are logged and reversible.

Limitations and tradeoffs

Autonomy settings interact with trust and compliance requirements; a level that is safe in one industry or region may be unacceptable in another, so treat defaults as starting points.