On-demand work
A person requests the task and reviews the result before using it.
Human-agent control
How should human approval work for AI agents?
Human approval should sit at the decisions where an AI agent changes external state, uses sensitive access, makes a consequential judgment, or delivers work outside the team. Lower-risk research and drafting can remain reviewable without requiring the same gate, while every workflow keeps a named owner, exception path, and retained evidence.
Design the approval boundary
Match the review mode to the action rather than treating autonomy as an all-or-nothing setting.
Suggestions
The agent proposes actions, assignments, or content while a person decides what becomes operative.
Scheduled internal work
The agent prepares recurring internal outputs within defined sources, tools, and review expectations.
Approval-gated delivery
External publication, sensitive actions, and consequential changes wait for the configured human decision.
Human approval FAQ
Does every AI-agent action require manual approval?
No. Approval should match the action’s consequences, access, reversibility, and evidence. Low-risk preparation can be reviewable without gating every internal step.
What happens when an approval is rejected?
The workflow should preserve the proposed action, rejection or correction, responsible owner, and next step so the team can recover without losing context.
Can approval requirements change over time?
Yes. Expand participation only after representative work shows acceptable completion, corrections, intervention, and operating cost within the defined boundary.
Define one approval boundary
Identify the actions an agent may prepare, perform, or deliver—and the evidence a reviewer needs at each point.
Architecture conversation
Tell us what your team needs to control
Share your deployment boundary, number of agents, work surfaces, and governance requirements. We will reply by email to arrange a focused technical discussion.
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