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Multi-Agent

Two or more minds in coordination.

44 patterns in this book. · Updated

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When to reach for each

01. Supervisor Place a coordinating agent above a set of specialised agents and route work to them. Best for: Different request types want their own loop, prompt, tools, and possibly model. Tradeoff: Multi-agent before simpler patterns are running is decoration. Watch for: A single agent already handles the workload without confusion.

02. Orchestrator-Workers An orchestrator dynamically breaks a task into subtasks at runtime and delegates each to a worker LLM, then synthesises results. Best for: The shape of decomposition depends on the input and cannot be planned statically. Tradeoff: Orchestrator failure is unrecoverable without retry logic. Watch for: Static decomposition (Plan-and-Execute, Prompt Chaining) already fits the task.

03. Subagent Isolation Run subagents in isolated workspaces so their writes do not collide and parallelism is safe. Best for: A bounded sub-task has its own tool palette, prompt, or model. Tradeoff: Setup latency. Watch for: The parent must observe the sub's intermediate state for debugging.

04. Handoff Transfer the active conversation from one agent to another, carrying context across the switch. Best for: Mid-conversation routing must transfer context to a more appropriate specialist. Tradeoff: Context summary fidelity bounds quality. Watch for: A single agent can handle the conversation without rerouting.

05. Agent-as-Tool Embedding Wrap a sub-agent (with its own loop, prompt, and tool palette) behind a single function-shaped tool signature, so the parent agent calls it like any other tool and never sees the sub-agent's internal turns. Best for: A sub-task is well-scoped enough that the parent should see only its result, not its turns. Tradeoff: Hidden costs: sub-agent failures or timeouts surprise the parent. Watch for: The parent must observe and steer sub-agent steps in real time.

All patterns in this book

Supervisor

×40

Place a coordinating agent above a set of specialised agents and route work to them.

Orchestrator-Workers

×25

An orchestrator dynamically breaks a task into subtasks at runtime and delegates each to a worker LLM, then synthesises results.

Subagent Isolation

×21

Run subagents in isolated workspaces so their writes do not collide and parallelism is safe.

Handoff

×11

Transfer the active conversation from one agent to another, carrying context across the switch.

Agent-as-Tool Embedding

×6

Wrap a sub-agent (with its own loop, prompt, and tool palette) behind a single function-shaped tool signature, so the parent agent calls it like any other tool and never sees the sub-agent's internal…

Inter-Agent Communication

×6

Define a protocol for agents to exchange tasks, capabilities, and results across process or vendor boundaries.

CAMEL Role-Playing

×6

Have two agents role-play a user-assistant interaction to autonomously complete a task neither could solve alone.

Hierarchical Agents

×5

Organise agents in a tree where higher-level agents decompose tasks for lower-level agents, recursively.

Role Assignment

×5

Assign each agent a named role (researcher, writer, critic, planner) with a role-specific prompt, tool palette, and acceptance criteria.

Actor-Model Agents

×3

Implement each agent as an independent actor with its own mailbox, processing asynchronous messages one at a time and never sharing mutable state with peers.

Conversational Multi-Agent

×3

Have agents converse turn by turn until a completion criterion fires; agent roles drive the conversation forward.

Blackboard

×3

Give multiple agents a shared, queryable workspace they can read from and write to as they collaborate.

Debate

×3

Have multiple agents argue different positions on a question and converge through structured exchange.

Performative Message

×2

Inter-agent messages are typed by communicative intent (request, inform, propose, accept, refuse, query) rather than by free-form prose, so receivers can dispatch on act type.

Topic-Based Routing

×2

Route inter-agent messages through named topics that agents subscribe to, instead of having senders address each other by id.

Contract Net Protocol

×1

Classical bid-based multi-agent task allocation: a manager broadcasts a task announcement, contractors submit bids, and the manager awards the contract to the best bid.

Group-Chat Manager

×1

Place a dedicated manager between the participants of a multi-agent group chat that decides which participant speaks next on each turn.

Stigmergic Coordination

×1

Agents coordinate indirectly by leaving and reading marks in a shared environment (files, queues, scratchpads, world model) so that one agent's trace stimulates another's next action, with no direct…

Vickrey Auction Allocation

×1

Allocate a task to the lowest sealed bidder but pay them the second-lowest bid, making truthful cost reporting a dominant strategy.

Communicative Dehallucination

×1

When an instructed agent would have to invent missing context to comply, have it reverse roles and ask the instructor for the missing detail before answering.

Inner Committee

×1

Run one model under several distinct personas (executor, critic, planner) within a single agent loop.

Progressive Delegation

×1

Stage the human-to-agent handoff over time: the agent starts producing drafts a human always reviews; its autonomy expands action-by-action as measured trust accrues.

SOP-Encoded Multi-Agent Workflow

×1

Encode a human Standard Operating Procedure (roles, ordered phases, standardised hand-off artefacts) into a multi-agent pipeline so that agents communicate through structured documents rather than fr…

Coalition Formation

×1

Agents form temporary subgroups around a task because the coalition can achieve more value than the sum of its members acting alone, with explicit rules for who joins and how payoff or credit is shar…

Decentralized Agent Network

×1

Agents publish signed DID+JSON-LD identity records so any peer can discover and verify them without a central registry — the agent equivalent of the open web.

Joint Commitment Team

×1

A team of agents adopts a shared goal plus the meta-commitment that each member will notify the others as soon as it believes the goal is achieved, impossible, or no longer relevant.

Swarm

×1

Run many peer agents that interact directly without a central supervisor, achieving emergent coordination.

Lead Researcher

A lead agent writes a research plan and dispatches parallel sub-agents that fan out for breadth-first information gathering, then merges results.

Agent Capability Manifest

Let each agent publish a standardized self-description — identity, skills, endpoint, and auth needs — at a well-known location, so others discover it and bind by capability at runtime instead of thro…

Chat Chain

Decompose a long, multi-disciplinary task into ordered phases; within each phase, run a paired-role chat between two agents until the phase artefact is signed off; pass the artefact to the next phase.

Cross-Domain Enterprise Agent Network

Decompose enterprise agency into domain-specialised agents (finance, supply chain, HR, service), each grounded in its own system of record, and route artefacts between them through a standardised int…

Decentralized Swarm Handoff

Agents in a swarm decide handoffs to peers based on a shared protocol with no central coordinator; specifically about agent-initiated handoff protocols, not topology.

Heterogeneous-Model Council with Synthesis Judge

Three or more role-specialized personas run on different model architectures in parallel; a synthesis judge — given only their structured JSON, not the original input — produces the final verdict.

Magentic-One Generalist Multi-Agent

Use Microsoft's generalist multi-agent architecture: a single Orchestrator agent dispatches to four specialist sub-agents (WebSurfer, FileSurfer, Coder, ComputerTerminal) for solving open-ended compl…

One Tool, One Agent

Design agent systems as a team of narrow single-purpose agents, each owning one tool or one capability, rather than a single super-agent that handles every tool — the agent analogue of microservices…

Parallel Fan-Out / Gather

Multiple independent agents execute in parallel on a partitioned task; a dedicated aggregator agent reconciles their results into a single output.

Pipeline Triad Pattern

Staff each pipeline stage with a triad — Creator generates an artifact, Critic finds flaws, Arbiter makes a binding PASS/FAIL/PARTIAL decision — with four explicit human gates between stages.

Scatter-Gather Plus Saga

Distribute tasks across worker agents and aggregate results while maintaining distributed-transaction semantics via compensating actions on partial failure.

Talker-Reasoner

Split an interactive agent into a fast Talker for conversational responses and a slow Reasoner for deliberative planning and tool use, so the conversational loop never blocks on reasoning.

Voting-Based Cooperation

Finalise a decision across multiple agents by collecting and tallying their votes on candidate options, so the joint output reflects collective rather than single-agent judgement.

Cellular-Automata Agents

A swarm where each agent applies simple local rules to its immediate neighborhood; macro behavior emerges without a central orchestrator and without global information access.

Dynamic Expert Recruitment

Generate the agent team — role descriptions and instances — at run time based on the specific task, then adjust team composition between iterations based on evaluation feedback.

Personality Variant Overlay

Let one agent speak in several named voices that overlay the base identity rather than replacing it, so the agent can shift register without losing identity continuity or splitting into separate pers…

RL-Trained Conductor Orchestrator

Train a small meta-model with reinforcement learning to dispatch sub-tasks across a pool of frontier LLM workers, learning the communication topology end-to-end and allowing the conductor to recursiv…