Which AI agent actions need human approval? A checklist

What does "human in the loop" mean for AI agents?

"Human in the loop" means a person approves certain agent actions before they happen. The agent works on its own until it reaches a step you've marked as sensitive, then pauses and waits for a yes or no. The idea is simple; the real work is choosing which steps get that pause.

OpenAI's agent documentation describes it the same way: "Human review pauses the run so a person or policy can approve or reject a sensitive action." Anthropic frames the goal as "keeping humans in control while enabling agent autonomy."

Which actions should always wait for you?

Five kinds of action should always wait for a person: anything involving money, anything that leaves the company, anything that can't be undone, any change to access, and any public claim. Use this as your checklist.

• Money. Purchases, subscriptions, refunds, ad spend, upgrades to paid plans.
• Anything external. Emails, messages, social posts, outreach, form submissions, comments on someone else's site.
• Anything irreversible. Deleting or overwriting files and records, changes to a live site or production system, cancelling an account.
• Access and permissions. Granting, sharing or revoking access; creating accounts; handling passwords or keys.
• Claims about you. Statements about your product, customers, results or numbers, anywhere the public or a partner will read them.

If an action fits more than one box, it's even more clearly yours to approve.

Which actions can usually run without approval?

Reading, researching, drafting and reversible internal edits can usually run without a pause, as long as the results are saved where you can review them.

Anthropic describes a similar default for one of its own coding agents: it has "read-only permissions by default" and "must ask for human approval before taking any actions that modify code or systems."

How do you decide for actions in between?

Ask three questions: can I undo it, who else does it touch, and what does it cost if it's wrong? If the answers are "no," "someone outside" or "more than I'd shrug off," gate it.

1. Can I undo it? Restoring a previous version is cheap. Unsending an email is impossible.
2. Who else does it touch? An action that stays inside your files is lower risk than one a customer, partner or the public will see.
3. What does it cost if it's wrong? Count money, time to clean up, and trust.

When in doubt, gate it for a few weeks and loosen it once you've seen the agent handle it well.

How do you avoid approval fatigue?

Approve the moments that matter, not every step. If you're asked to approve too often, you'll start saying yes without reading, which is worse than no gate at all.

• Batch approvals. Review a set of drafts once or twice a day instead of one at a time.
• Standing permissions for trusted routine work. If an agent has prepared the same internal report correctly for weeks, let it save new versions without asking.
• Review the output, not each step. Check the finished draft, not every search the agent ran to make it.
• Let drafts flow and make sends wait. The draft can move freely; the send stays gated.

How do you write approval rules agents follow?

Write the rules into every brief, use tools that can pause before side effects, and never let an agent approve its own work.

• A LIMITS line in every brief. For example: "No spending, no external messages, no deletes without approval." Our AI agent brief template includes one.
• Pauses built into the tools. OpenAI's documentation recommends human-in-the-loop approvals to "pause before side effects like cancellations, edits, shell commands, or sensitive MCP actions." Where your tools offer a setting like this, use it.
• Separate doing from approving. The agent that did the work shouldn't be the one that signs it off. Another agent can review it; the final yes on a gated action stays with a person.

What records should you keep?

Keep a short record of every gated action: what was proposed, who approved it, when, and what happened. A simple log in a shared file is enough.

A record makes the weekly review faster and shows you which approvals have become routine enough to turn into standing permissions.

Where does Plenarly fit?

Plenarly is being built as the operating system for AI-run companies: one place where founders and small teams connect their AI agents from any lab, approve their work, and manage the apps those agents build. Early-access sign-ups are open.

The plan is to keep the decisions waiting on you in one place, next to the work they belong to. Join early access if you already run AI agents on real work. For plain facts, see What Plenarly is and isn't.

Frequently asked questions

Is human in the loop the same as human oversight?

They're related but not identical. Human in the loop means a person approves specific actions before they happen. Human oversight is broader: reviewing results, setting rules and being able to stop or redirect agents at any time. A sound setup uses both, with approvals for the few high-stakes actions and regular review for everything else.

Can an AI agent approve another agent's work?

An agent can review another agent's work and catch real problems, and that's a good habit. For gated actions, such as spending, sending or deleting, the final approval should stay with a person. An agent reviewer narrows what you need to read; it doesn't replace your decision on the actions that carry real consequences.

Do approval gates slow everything down?

Only the gated steps wait, and those are usually a small share of the work. Reading, research and drafting keep moving. Batching approvals and granting standing permissions for proven routine work keep the delay small. A short wait before a send costs far less than cleaning up an email that shouldn't have gone out.

What if I'm not available to approve?

The action waits. Nothing external should go out by default while you're away. If timing matters, set a deadline in the brief and tell the agent what to do if you haven't answered, such as holding the draft or flagging it. The safe default is a pause, not a guess.

Should approvals change as trust grows?

Yes. Start strict, then widen standing permissions gradually for routine internal work an agent has handled well. Review those permissions weekly. Money, external contact, irreversible actions, access changes and public claims usually stay gated, however well things are going.

Sources

1. OpenAI, "Guardrails and human review," OpenAI API docs. Quotes: "Human review pauses the run so a person or policy can approve or reject a sensitive action"; "Pause before side effects like cancellations, edits, shell commands, or sensitive MCP actions." Checked on the live page Oct 24, 2026, ~8:35 PM ET. https://developers.openai.com/api/docs/guides/agents/guardrails-approvals
2. Anthropic, "Our framework for developing safe and trustworthy agents," August 4, 2025. Quotes: "Keeping humans in control while enabling agent autonomy"; "read-only permissions by default"; "must ask for human approval before taking any actions that modify code or systems." Checked Oct 24, 2026, ~8:35 PM ET. https://www.anthropic.com/news/our-framework-for-developing-safe-and-trustworthy-agents
3. OpenAI Agents SDK, "Human-in-the-loop" (technical reference for approval flows). Checked Oct 24, 2026, ~8:35 PM ET. https://openai.github.io/openai-agents-python/human_in_the_loop/
4. NIST, "AI Risk Management Framework," released January 26, 2023, and "intended for voluntary use." Further reading on oversight and governance; not a requirement this checklist is built to meet. Checked Oct 24, 2026, ~8:35 PM ET. https://www.nist.gov/itl/ai-risk-management-framework