Human-in-the-Loop

Human-in-the-loop (HITL) is an AI design pattern where humans are integrated into an agent's workflow at critical decision points. Rather than letting the agent operate fully autonomously, the system is designed to pause, notify the human, and wait for feedback before proceeding with consequential or ambiguous actions.

Why Human-in-the-Loop Matters

AI agents are powerful but imperfect. They can misunderstand requirements, make errors in judgment, or encounter situations their training didn't prepare them for. Human-in-the-loop design acknowledges this reality and builds in appropriate oversight:

→ Prevent costly mistakes — catch errors before they reach production
→ Provide guidance — give the agent information it doesn't have
→ Maintain accountability — humans remain responsible for agent actions
→ Build trust — oversight allows teams to trust agents with higher-stakes tasks over time

HITL Patterns

Approval Gate

The agent pauses before taking an action and waits for explicit human approval before proceeding.

Notification + Override

The agent proceeds but notifies the human. The human can intervene if needed.

Periodic Check-In

The agent runs autonomously but surfaces a summary at defined intervals for human review.

On-Demand Query

The agent asks the human a specific question when it encounters ambiguity.

Human-in-the-Loop with AgentRQ

AgentRQ is purpose-built for human-in-the-loop agent workflows. Claude Code agents connect to AgentRQ via MCP and use it to:

→ Create tasks for work requiring oversight
→ Send notifications in real time
→ Block on approvals before irreversible actions
→ Exchange messages via bidirectional messaging

The agent does the work. You stay in control.