# Human in the Loop

> Part of the AI Garage Jargons glossary: https://aigarage.in/jargons (all terms: https://aigarage.in/jargons.md)

**Category:** LLM
**Tags:** agents, approval, safety, oversight

A design where an automated or AI system pauses at chosen points for a person to approve, correct, or reject, before it continues with a consequential action.

**In plain terms:** It is a checkpoint with a person at it. The agent does the work, stops at the risky step, shows what it is about to do, and waits for a yes or a no.

**Use cases:**
- Approving a refund or an outbound email
- Reviewing a code change before it is applied
- Signing off a page before it is published

**Why it matters:** An agent can be wrong in a way that is hard to undo. A person at the right gate turns a possible mistake into a request that can be read and declined, and leaves a clear record of who approved what.

**Why now:** Agents now take actions through tools, and frameworks add built-in approval pauses and ways to resume a paused run. Practices differ between products and change quickly, so check current documentation before relying on a specific behavior.

**AI Garage example:** The AI Garage Jargons video workflow is built from approval gates. A person approves the script, then the narration, then the local video, then the upload, as separate steps, and the agent does not move past a gate without that approval. The agent does the work between the gates. This describes how this repository is worked on, not a product claim.

**Mental model:** Decide which actions matter, then pause only there. The system declares that a step needs approval and stops with the pending action visible. A person approves or rejects it, and the run resumes from where it stopped. The skill is choosing the gates: sending an email, spending money, changing a record, running a command. Gating every step defeats the point of automation, and gating nothing leaves the agent unsupervised.

**Builder scenario: Pause where it matters, not everywhere**

- **Context:** An assistant can read orders, draft replies, and issue refunds.
- **Failure:** Either every step needs a click and the team stops using it, or nothing needs approval and a wrong refund goes out before anyone sees it.
- **Intervention:** Let the assistant read and draft freely, and mark only the refund and the outbound email as needing approval. When it reaches one, the run pauses and shows exactly what it will do. A signed-in reviewer approves or rejects, and the run resumes.
- **Outcome:** Routine work flows without interruption, and every refund and email passes a person who sees the exact action first.

**Common misconceptions:**
- **Claim:** Human in the loop means a person watches every step.
  **Correction:** It means a person decides at chosen points. The guidance points to consequential actions such as sending emails, cancelling orders, running commands, or editing files, not to every step.
- **Claim:** An approval prompt makes the action safe.
  **Correction:** An approval only helps if the reviewer sees the real action and is authorized to decide. The documentation warns that saved run state should come from trusted storage, and that the server should check who the reviewer is and validate their decision.

**Visual model (sequence):** Pause at the actions that are hard to undo, and let the rest run.

**Visual description:** A five-step sequence: the agent works until a gated step, the run pauses and shows the pending action, a person approves or rejects it, the run resumes, and the decision is recorded.

**Related concepts:** [AI Agent](https://aigarage.in/jargons/ai-agent), [Tool Calling](https://aigarage.in/jargons/tool-calling), [Decision Model](https://aigarage.in/jargons/decision-model), [Idempotency](https://aigarage.in/jargons/idempotency), [Hallucination (AI)](https://aigarage.in/jargons/ai-hallucination)

**Last researched:** 2026-10-12

**Sources:**
- [OpenAI Agents SDK - Human-in-the-loop](https://openai.github.io/openai-agents-python/human_in_the_loop/)
- [Anthropic Engineering - Building effective agents](https://www.anthropic.com/engineering/building-effective-agents)

**URL:** https://aigarage.in/jargons/human-in-the-loop