Building a Multi-Agent Orchestrator in Node.js

Your single AI agent just hit a wall.

It started well. One agent, one prompt, a handful of tools, problems getting solved. But now you need the same system to search the web, write code, query databases, draft reports, and handle customer requests — all in the same conversation. The system prompt has become a bloated mess. The tools interfere with each other. The agent hallucinates when the task gets complex enough.

This is the single-agent ceiling. No amount of prompt engineering gets you past it.

The answer isn't a bigger agent. It's more agents — specialized, focused, and coordinated by a router that knows which one to call and when. Building a Multi-Agent Orchestrator in Node.js shows you how to build that system from scratch, in code you actually understand.

What you'll learn:

• The agent loop — a complete agent with the OpenAI SDK: system prompts, tool calling, streaming, and the observe-decide-act cycle
• Tool design — schemas that agents use reliably, with validation, error handling, and a dynamic registry
• The router agent — an intent classifier that routes requests to the right specialist with confidence scoring and fallback chains
• Specialized agents — research, code, data, and writing agents with clean boundaries and clear responsibilities
• The orchestration layer — sequential and parallel execution, agent-to-agent communication, and conversation management
• Shared memory — in-memory and SQLite context stores with conversation windowing, summarization, and task state tracking
• Error handling and resilience — retries, circuit breakers, graceful degradation, token budgets, and cost controls
• Streaming and real-time — Server-Sent Events, progress indicators, cancellation, and WebSocket alternatives
• Observability — request tracing, structured logging, token cost attribution, latency tracking, and a debug dashboard
• Testing — unit tests with mocked LLMs, integration tests, end-to-end tests with recorded interactions, and evaluation metrics
• Deployment — Docker containerization, health checks, horizontal scaling, and production monitoring
• Advanced routing — semantic routing with embeddings, learned routing, hierarchical sub-routers, and A/B testing agent versions
• Collaboration patterns — chain-of-thought across agents, critic patterns, consensus, human-in-the-loop, and fan-out/fan-in

This book is for you if you're a Node.js developer who has built a single-agent system and hit its limits, you want to understand multi-agent architecture from the ground up rather than just use a framework, or you prefer real runnable code over theory and diagrams.

Every line of code is available in the companion GitHub repository. Clone it, run it, break it, extend it.

15 chapters. 3 appendices. ~44,000 words of practical, code-heavy instruction. No filler. No hype. Just the architecture, the code, and the reasoning behind every decision.

Book 3 in The Agent Stack: LLMs, Agents, and Multi-Agent Systems. Companion repository at github.com/grizzlypeaksoftware/multi-agent-orchestrator.