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Subagent Architecture for AI Engineers: Master Agent Delegation, Supervisor Agents, Worker Agents, and Multi-Agent Coordination for Production-Ready AI Systems
AI 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:
If you're an AI Engineer, AI Developer, Machine Learning Engineer, Prompt Engineer, or technical builder ready to turn agentic AI from fragile experiments into dependable software architecture, this book gives you the patterns to build with confidence.
Order now and start building multi-agent AI systems that can delegate, coordinate, verify, and deliver production-ready results.
Ahoj! Jsem Libroamiko, tvůj knižní rádce.
Jak ti můžu pomoct?