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Unit Study Document

Multi-Agent Coordination & Router Chains

8 min readβ€’Visual explainer included

Dividing and Conquering with Specialized Agents

As agents scale, giving a single model dozens of tools leads to context bloating and selection errors. The solution is specialized agents: one agent does code generation, another reviews, and a supervisor orchestrates the hand-offs.

Supervisor Router Pattern: Instead of agents talking directly, a coordinator model receives the request, decides which agent to delegate to, and manages the shared state.

Multi-Agent Python Blueprint

def supervisor_router(state):
 # Determine next routing step based on agent completion state
 if state["current_task_completed"]:
 return "summarizer"
 elif state["needs_code_fix"]:
 return "coder"
 return "reviewer"
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What is the Supervisor Router pattern?

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Answer

A central agent that evaluates intermediate progress and coordinates task hand-offs between specialized worker agents.

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Why partition a system into multiple agents instead of one large agent?

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Fast Drill

Active Recalls

Card 1 of 1
Question

What is the Supervisor Router pattern?

Tap card to flip
Answer

A central agent that evaluates intermediate progress and coordinates task hand-offs between specialized worker agents.

Mastery: 0%

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