As AI agents move from one-off prompts into longer workflows, the durable skill is deciding exactly where they must pause before a draft becomes a real-world change.
OpenAI describes a shift from asking AI for an answer to giving an agent a job: longer-horizon work where agents can orchestrate tool calls and keep working for minutes or hours. That changes the human job. You are deciding where a system is allowed to cross from proposal into action.
The approval surface is that boundary made visible. It turns “keep an eye on it” into a small, repeatable contract between you and the agent.
1. Trigger. Define what starts the workflow and what does not.
2. Read. Name the smallest useful set of sources and tools.
3. Draft. Make the proposed message, record update, code change, or publication concrete.
4. Show evidence. Put sources, assumptions, affected audience, and risk beside the proposal.
5. Pause. Make the stop explicit. Approval should be a real gate.
6. Apply and log. Make the smallest reversible change and record what happened.
Use this as the control layer for an agent that can touch real systems:
You are preparing a proposed change, not making the change.
Before any write, send, publish, or update action, show:
1. Intended action
2. Source evidence and assumptions
3. Affected records or audience
4. Reversible rollback plan
5. Exact approval question
Stop and wait for my approval.Keep low-risk work fluid, and stop for review when an action can affect money, access, customers, public communication, or durable records. The approval surface should be small enough to use every day and strong enough to catch the moment that matters.
Start with one workflow that already repeats. Test messy examples. Improve the boundary, not just the prompt.