Verwandte Artikel zu Engineering Multi-Agent Systems for Professionals (Internati...

Engineering Multi-Agent Systems for Professionals (International Edition) - Softcover

Shah, Sharanam; Shah, Vaishali

 
9789368081296: Engineering Multi-Agent Systems for Professionals (International Edition)

Inhaltsangabe

YOUR AI CAN WRITE CODE. CAN IT WORK ON A TEAM? Most AI coding tools quietly hand one model every job at once: planning, writing, testing, and reviewing. It writes the code. It grades its own homework. And when it gets something wrong, there was never anyone in the loop whose job it was to disagree. Engineering Multi-Agent Systems for Professionals teaches you to build the fix: a real four-agent development team-a Product Manager, Developer, QA Tester, and Reviewer-engineered from scratch and connected with Model Context Protocol (MCP) and Agent-to-Agent (A2A), the two open protocols rapidly becoming the industry standard for building enterprise AI systems. INSIDE THIS BOOK, YOU WILL: Build CodeForge Pod, a real headless multi-agent CLI tool, from an empty folder to a production-ready release. Connect a live MCP server and watch your agent read, write, and execute real commands on your own machine. Engineer a self-correcting orchestration loop that catches a failed attempt and performs an intelligent retry. Publish a real Agent Card and complete a genuine task handoff with another agent using A2A. Build safety in from day one with workspace isolation, dry-run previews, and approval before any file changes. Package and distribute a pipx-installable production-ready release. "One model wearing four hats was never a team. This book is where you build one that actually is." WHY THIS MATTERS RIGHT NOW AI is rapidly moving from single-agent assistants to collaborative multi-agent systems. Model Context Protocol (MCP) has emerged as the leading standard for connecting AI models to real-world tools, while Agent-to-Agent (A2A) enables secure collaboration between autonomous agents. Together, they provide the two-layer architecture-tools inward, agents outward-that organizations are adopting to build the next generation of enterprise AI applications. PLAN. BUILD. TEST. REVIEW. Engineer multi-agent systems that actually work together, in the real world. Together, Sharanam and Vaishali have co-authored more than 45 technical books, committed to the belief that the best way to learn a system is to build one that actually works.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Sharanam ShahLead Architect & AI Specialist

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.