Artificial intelligence agent autonomy increases when an agent receives a complete task, durable context, tools and a quality bar it can check independently. It can then work for longer periods and return after reaching a result rather than requiring constant conversational guidance.
Autonomy should remain bounded by permissions, time, retries and acceptance criteria. Humans can move out of the implementation loop while still owning priorities, specifications, governance and final risk decisions.
