Human-in-the-Loop

Definition

Human-in-the-Loop (HITL) is a design pattern where human review and approval is embedded at designated checkpoints in an agent workflow. Rather than the agent proceeding autonomously at every step, HITL checkpoints pause execution, present the proposed action or decision to a human reviewer, and wait for approval, rejection, or modification before continuing. This pattern enables AI agents to operate in contexts where full autonomy is not yet appropriate—whether due to regulatory requirements, risk tolerance, or the current state of AI reliability.

Engineering Context

Human-in-the-loop is a risk management pattern, not a limitation. By routing uncertain or high-consequence decisions to humans, you can deploy AI agents in regulated contexts where full autonomy is not acceptable. HITL checkpoints are triggered by confidence thresholds (model uncertainty above a threshold), decision severity (actions above a risk level require review), or regulatory requirement (certain action categories always require approval). LangGraph has native support for HITL via interrupt_before and interrupt_after mechanisms that pause graph execution and persist state until a human provides input. Design HITL workflows so the human reviewer has sufficient context: show the reasoning trace, the proposed action, and relevant source documents.

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