Human in the loop

Human in the loop (HITL) is a design pattern where people stay involved in an automated or AI-driven process — reviewing, correcting, or approving steps that are high-risk, ambiguous, or hard to reverse.

It doesn’t mean doing everything manually. It means choosing where judgment matters: refunds, legal wording, medical advice, big discounts, or public posts. AI agents can draft, classify, and act; a human confirms before the irreversible move. That balance protects quality and trust when models still hallucinate or miss context.

A real-life example of human in the loop

An agent drafts replies to support tickets and suggests a refund. Low-risk FAQ answers may go out automatically (ideally grounded with RAG). A $500 refund or a complaint about safety waits for a human click. Same idea as autopilot on a plane: useful, but the pilot stays ready.

Ask two questions: What’s the cost of a mistake? Is the data current? For a practical framework, see Human in the Loop for AI Agents.