Ch 7 — Multi-Agent Orchestration

Supervisor patterns, agent handoffs, shared state, and the A2A protocol
IndexUnder the Hood →
High Level
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Step- / 8
AWhy Multi-Agent?One agent can't do everything well
1
smart_toy
Single AgentOne LLM, many tools
prompt gets bloated
vs
groups
Multi-AgentSpecialized agents
each with own tools
=
workspace_premium
Better ResultsFocused prompts,
clear responsibilities
2
arrow_downward Pattern 1: Supervisor — one boss, many workers
BSupervisor PatternA central LLM routes tasks to specialized agents
chat
User Query"Research AI trends
and write a report"
→
supervisor_account
SupervisorLLM decides which
agent to call next
delegate
search
ResearcherWeb search,
data gathering
or
edit_note
WriterDraft reports,
summarize findings
3
arrow_downward Pattern 2: Handoffs — agents pass control directly
CHandoff PatternAgents transfer control to each other via tool calls
support_agent
Triage AgentClassifies intent,
routes to specialist
handoff
receipt_long
Billing AgentHandles payments,
invoices, refunds
handoff
4
build
Tech SupportTroubleshooting,
diagnostics, fixes
5
arrow_downward Pattern 3: Swarm — agents as tools of each other
DSwarm PatternLightweight handoffs where each agent can call any other
smart_toy
Agent ACan hand off to
B or C via tool
↔
smart_toy
Agent BCan hand off to
A or C via tool
↔
smart_toy
Agent CCan hand off to
A or B via tool
6
arrow_downward Sub-graphs: agents as nested graphs within a parent
ESub-GraphsEach agent is its own compiled graph, nested inside a parent
account_tree
Parent GraphSupervisor routes
to sub-graphs
invoke
lan
Research GraphOwn state, nodes,
tools, checkpoints
invoke
lan
Writing GraphOwn state, nodes,
tools, checkpoints
7
arrow_downward A2A: the protocol for agents talking across systems
FA2A — Agent-to-Agent ProtocolGoogle's open standard for cross-system agent communication
smart_toy
Your AgentLangGraph app
on your server
A2A
public
Agent CardDiscovery: skills,
endpoint, auth
task
8
smart_toy
Remote AgentDifferent framework,
different org
1
Detail