Subagent Architecture for AI Engineers: Master Agent Delegation, Supervisor Agents, Worker Agents, and Multi-Agent Coordination for Production-Ready A

Subagent Architecture for AI Engineers: Master Agent Delegation, Supervisor Agents, Worker Agents, and Multi-Agent Coordination for Production-Ready AI SystemsAI agents are getting more powerful, but many systems still fail for the same reason: one overloaded agent is expected to plan, research, code, test, review, and make final decisions without losing focus. The result is messy context, weak delegation, unpredictable tool use, rising token costs, and workflows that break when moved from prototype to production.Subagent Architecture for AI Engineers gives you a practical framework for building controlled, reliable, multi-agent AI systems that divide work across specialized agents while keeping the entire workflow observable, testable, and safe.This book shows how to design supervisor agents, worker agents, critic agents, reviewer agents, routers, handoffs, agent pools, and directly coordinating agent teams. You'll learn how to move beyond simple agent demos and build production-ready AI systems with clear role boundaries, structured result contracts, context isolation, tool permissions, memory controls, evaluation loops, and failure recovery patterns.Inside, you'll learn how to: - Design subagents with clear roles, responsibilities, schemas, and permissions.- Build agent delegation workflows using inline tool subagents, fan-out workers, persistent agent pools, and coordinated agent teams.- Keep main agent context clean while reducing token cost and improving reliability.- Add guardrails for tool access, memory boundaries, retries, approvals, and escalation.- Evaluate, debug, monitor, and harden multi-agent systems for real engineering workflows.If you're an AI Engineer, AI Developer, Machine Learning Engineer, Prompt Engineer, or technical builder ready to turn…