Autonomy levels
Definition
Autonomy levels are graded permissions for an AI agent that determine what happens when it proposes an action: log the suggestion, queue it for human approval, or execute it directly.
An AI agent that can reason is only half a system; the other half is deciding what its conclusions are allowed to do. Autonomy levels answer that question per agent rather than per product: the same agent can start as a suggestion engine, graduate to proposing actions a human approves, and eventually act on its own — with the change being a setting, not a rewrite.
Why it matters
Trust in an AI agent is earned incrementally, and the sensible deployment path mirrors how you would onboard a junior employee: watch their reasoning first, approve their work next, delegate last. Products that offer only “on or off” force a choice between no automation and total automation. Graded autonomy lets the level of oversight match the level of demonstrated reliability — and lets different agents run at different levels simultaneously.
How autonomy levels work in Oneop
Every Oneop AI Workforce agent carries one of three autonomy modes, applied by a single governed action engine that every proposed write must pass through:
- Suggest. The agent’s proposed action is logged and surfaced as a notification. Nothing changes in your data. This is the mode to start every agent in: you read its reasoning traces and judge its proposals with zero risk.
- Approve. The proposed action lands in a real approval queue. A person accepts or rejects it; only acceptance dispatches the write. This is human-in-the-loop as a queue, not a checkbox.
- Autonomous. The action dispatches directly, still bounded by the run’s hard ceilings — six iterations (cap twelve), 6,000 tokens, forty-five seconds, three actions per run.
Two constraints hold at every level. First, actions that touch money or stock — posting a bill, issuing a purchase order, placing a credit hold — are held behind a separate switch that overrides autonomy entirely: it is off unless it has been turned on for your workspace, and while it is off an autonomous agent still cannot take them. Second, every run stores its full trace and exit reason, so a promoted agent’s history is reviewable before and after promotion.
The practical advice Oneop gives its own users: start in suggest mode, promote when the trace earns it.
Related terms: AI agent, AI governance. Product page: AI agents.
Related terms
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