• views: 117
• date: 12 October 2026
• posted by: BeMyLove

Build AI agents that do more than respond. Give them tools, connect them to knowledge, coordinate their work, and evaluate how well they perform.

AI Agents in Action, Second Edition teaches you how to design, build, evaluate, and deploy AI agents through working Python examples. You'll progress from a simple agent to tool-using assistants, coordinated multi-agent workflows, and deployable systems. Along the way, you'll learn how the pieces fit together and where to look when an agent needs improvement.

What's new and included in the second edition?

A near-total rewrite with new and extensive coverage of the latest agent innovations

Agents start to finish—from prompting and planning, to memory and evaluation

New chapter! Evaluate agents with LLM-as-judge, test-driven-development, and observable behavior

New chapter! Explore the agentic loop, build task-focused agents, and develop long-horizon, goal focused systems

New chapter! Metacognition harnesses that structure agent thinking, planning, and learning

New chapter! Practical tips and techniques for building AI applications, help desks, and deep research agents

New chapter! Voice-driven AI agents, including real-world deployment patterns for multi-agent systems

Multi-agent workflows with assembly-flow, orchestration, and collaboration patterns

Hands-on with the Model Context Protocol (MCP) to connect agents to tools and servers

Hybrid search for Retrieval Augmented Generation (RAG) and practical ways to use memory in agents

With more than 95% rewritten from the first edition, AI Agents in Action is far more than a refresh! You'll go right from your agent's first response, to systems that use tools, work together, draw on knowledge, and incorporate feedback. All illustrated with practical examples throughout.

What's inside

Autonomous agent design and deployment

MCP-based tools, resources, prompts, memory, and server integrations

Reasoning and planning patterns including ReAct, Reflexion, Tree-of- Thought, and Sequential Thinking

About the reader

For intermediate Python programmers. No experience with AI agents and agentic systems required.

About the author

Micheal Lanham is a software and technology innovator with over 20 years of industry experience. He has authored books on deep learning, including Manning's Evolutionary Deep Learning .

DOWNLOAD:

https://rapidgator.net/file/bb7a0a57ab394d61ff7fb89c23ad3c12/AI_Agents_in_Action_Intelligent_workflows_with_LLMs_MCP_A2A_and_more_2nd_Edition.rar

https://clicknupload.click/jd7umbshsjze/AI_Agents_in_Action_Intelligent_workflows_with_LLMs_MCP_A2A_and_more_2nd_Edition.rar

   
   
   

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