Phase 4: Agent Orchestration in Client Environments · 55 min · Python · LangGraph

Multi-Agent Delegation & Human-in-the-Loop

Some decisions are too expensive to automate. Gate them.

What you will learn

Implement multi-agent patterns: supervisor-delegate, hierarchical, peer-to-peer
Design sub-agent task delegation: splitting tasks, routing to specialists, aggregating results
Build human-in-the-loop gates: synchronous (blocking), asynchronous (notification + review), escalation chains
Enforce step budgets: max iterations, cycle detection, timeout handling, loop prevention

Objective

What you'll learn

This lesson takes approximately 55 min. By the end, you will be able to:

Implement multi-agent patterns: supervisor-delegate, hierarchical, peer-to-peer
Design sub-agent task delegation: splitting tasks, routing to specialists, aggregating results
Build human-in-the-loop gates: synchronous (blocking), asynchronous (notification + review), escalation chains
Enforce step budgets: max iterations, cycle detection, timeout handling, loop prevention

The Problem

Some decisions are too expensive to automate. A refund approval, a legal document summary, a medical record query — these need human review. Multi-agent delegation with human-in-the-loop gates is the pattern FDEs use to automate 90% of the work while keeping humans in control of the 10% that matters.

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Key terms in this lesson

Agent