Multi-Agent Orchestration: Quick Reference — Agentic Architecture & Orchestration (Claude Certified Architect)

Multi-Agent Orchestration — Quick Reference This quick reference summarizes key concepts and best practices for designing and implementing...

Multi-Agent Orchestration — Quick Reference

This quick reference summarizes key concepts and best practices for designing and implementing multi-agent orchestration using the Claude Agent SDK, focusing on coordinator-subagent patterns and agentic loops.

Core Concepts

Agentic Loop: Autonomous cycle where an agent perceives, decides, acts, and updates context to execute tasks independently.
Multi-Agent System: Architecture involving multiple agents collaborating, typically organized as a coordinator managing several subagents.
Coordinator-Subagent Pattern: The coordinator delegates subtasks to subagents, aggregates results, and manages overall workflow orchestration.
Context Passing: Mechanism for sharing relevant state and data between coordinator and subagents to maintain continuity.
Subagent Spawning: Dynamic creation of subagents by the coordinator to handle specific subtasks or parallel workflows.

Design & Implementation Rules

Task Decomposition: Break down complex tasks into smaller, manageable subtasks assigned to subagents for parallel or sequential execution.
Session State Management: Maintain session context to support resumption after interruptions and forking to explore alternative task paths.
Multi-Step Workflows: Implement workflows with explicit programmatic enforcement to ensure correct sequencing and dependency handling.
SDK Hooks: Use Claude Agent SDK hooks to intercept tool calls, enabling custom logic injection and enhanced control over agent behavior.
Context Size Optimization: Pass only essential context data between agents to optimize performance and reduce latency.

Best Practices

Coordinator Responsibilities: Orchestrate subagent lifecycle, aggregate outputs, handle errors, and maintain global session state.
Subagent Responsibilities: Execute assigned subtasks autonomously, report results, and update context for the coordinator.
Resumption & Forking: Design workflows to allow session resumption after failures and forking to explore multiple solution paths concurrently.
Monitoring & Logging: Implement detailed logging at both coordinator and subagent levels for debugging and performance tuning.
Scalability: Architect agent systems to scale horizontally by spawning additional subagents as workload increases.

Worked Example: Coordinated Document Analysis

Scenario: A coordinator agent manages subagents to analyze different sections of a large document.

Coordinator decomposes the document into sections and spawns one subagent per section.
Each subagent receives context limited to its section and performs analysis autonomously.
Subagents send results back to the coordinator, which aggregates insights into a final report.
SDK hooks intercept calls to external summarization tools to customize output formatting.
Session state is maintained to allow resumption if any subagent fails, and forking is used to test alternative summarization strategies.

For detailed guidance on implementing these patterns using the Claude Agent SDK, refer to the official documentation and certification materials.

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