{"product_id":"ai-agents-in-action-micheal-lanham","title":"AI Agents in Action by Micheal Lanham | Build Autonomous Multi-Agent AI Systems","description":"\u003ch3\u003e\u003cspan\u003eAI Agents in Action by Micheal Lanham\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cstrong\u003e\u003cspan\u003eAI Agents in Action: Build, Orchestrate, and Deploy Autonomous Multi-Agent Systems\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e is a practical guide to building intelligent AI agents and autonomous multi-agent systems using modern Large Language Models. Written by software and technology innovator \u003c\/span\u003e\u003cstrong\u003e\u003cspan\u003eMicheal Lanham\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e, the book takes readers beyond basic chatbot development and explores how AI agents can understand tasks, use tools, access knowledge, maintain memory, reason through problems, collaborate with other agents, and operate with greater autonomy.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003ePublished by Manning in 2025, this book is designed for developers and technology professionals who want to understand how AI agents can be designed and deployed for real-world applications. It combines concepts with practical development approaches, covering LLMs, GPT assistants, multi-agent systems, agent actions, autonomous assistants, memory, knowledge management, prompt engineering, reasoning, evaluation, planning, and feedback.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eAbout This Book\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eAI agents represent an important evolution beyond traditional conversational AI. Instead of simply responding to a prompt, an agent can be designed to interact with tools, retrieve information, plan actions, maintain context, and complete multi-step tasks.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cstrong\u003e\u003cspan\u003eAI Agents in Action\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e introduces readers to the architecture and behavior patterns behind these systems. The book explains how individual agents can be connected into multi-agent workflows capable of handling increasingly complex tasks.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe first edition covers the development of production-ready assistants, agent platforms, knowledge and memory systems, prompt workflows, reasoning, evaluation, planning, and feedback.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eUnderstanding AI Agents\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe book begins by establishing a foundation for understanding what an AI agent is and how agents differ from conventional AI interfaces and assistants.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eReaders explore:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan\u003eAgent definitions and behavior patterns\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eComponents of an AI agent\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent-based architectures\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eThe relationship between LLMs and agents\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAutonomous decision-making\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent interaction with external systems\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAI assistants versus autonomous agents\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eThe emerging agent ecosystem\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis foundation helps readers understand how language models can become components within larger intelligent systems rather than functioning only as text-generation tools.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eLarge Language Models and GPT Assistants\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eA strong understanding of Large Language Models is essential for developing effective AI agents. The book introduces the role of LLMs in agent systems and demonstrates how they can provide reasoning and language capabilities.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eReaders learn how to work with GPT-based assistants and explore techniques for connecting language models to applications and external functionality.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe book also introduces practical concepts surrounding prompts, model interaction, agent behavior, and application development.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eBuilding Multi-Agent Systems\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eOne of the central themes of \u003c\/span\u003e\u003cstrong\u003e\u003cspan\u003eAI Agents in Action\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e is the development of multi-agent systems.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eInstead of relying on one AI agent to perform every task, developers can create multiple specialized agents that collaborate or operate as part of an orchestrated workflow. Different agents can take responsibility for different stages of a problem, allowing complex tasks to be divided into manageable components.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eTopics include:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan\u003eMulti-agent architectures\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent collaboration\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent orchestration\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eSpecialized AI agents\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent workflows\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eCommunication between agents\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAutonomous multi-agent applications\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eCoordinating multiple AI capabilities\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThese concepts are particularly useful for developers exploring advanced generative AI and agentic application architectures.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eGiving AI Agents Actions and Tools\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eAn important characteristic of an AI agent is its ability to do more than generate text. Agents can be connected to tools and external services that allow them to perform actions.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe book explores how developers can empower agents with actions and create systems capable of interacting with software, data, and other resources.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis approach can transform an LLM-powered application from a simple conversational interface into an intelligent system capable of carrying out practical tasks.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eAutonomous Assistants\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe book demonstrates how to move from basic assistants toward more autonomous AI applications.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eReaders learn how agents can be designed to:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan\u003eUnderstand user objectives\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eBreak complex tasks into steps\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eSelect appropriate actions\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eWork with external tools\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eRetrieve relevant information\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eMaintain useful knowledge\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eEvaluate results\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eRespond to changing circumstances\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eOperate with reduced human supervision\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis makes the book particularly relevant to developers interested in \u003c\/span\u003e\u003cstrong\u003e\u003cspan\u003eagentic AI\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e, autonomous assistants, and intelligent workflow automation.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eAgent Memory and Knowledge\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eMemory and knowledge management are essential when AI systems need to work across multiple interactions or handle information beyond what can fit into a single prompt.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cstrong\u003e\u003cspan\u003eAI Agents in Action\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e explores approaches for giving agents access to knowledge and memory so that they can maintain useful context and retrieve information when needed.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe book covers concepts related to:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan\u003eAgent memory\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eKnowledge management\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eRetrieval-augmented knowledge\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eInformation retrieval\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eContext management\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003ePersistent information\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent knowledge systems\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThese capabilities help developers design agents that can work with domain-specific information and more complex application environments.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003ePrompt Engineering and Agent Behavior\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003ePrompt engineering becomes especially important when prompts are used to control the behavior and personality of an autonomous agent.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe book explores prompt workflows and techniques for creating agents with specific roles, behaviors, and objectives. Readers learn how carefully designed instructions can influence how agents interact with users, tools, and other agents.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis makes the book useful for developers who want to move beyond basic prompting toward structured AI-agent behavior.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eReasoning, Planning and Evaluation\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eAutonomous systems need mechanisms for deciding what to do next, evaluating results, and adapting their behavior.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe book examines agent reasoning and evaluation as well as planning and feedback. These concepts are important for creating AI systems that can handle multi-step tasks instead of producing isolated responses.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eReaders gain an understanding of how planning and feedback can be incorporated into agent architectures to improve their ability to complete tasks and respond to changing conditions.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eBuilding an Agent Platform\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eBeyond individual agents, the book explores how developers can assemble an \u003c\/span\u003e\u003cstrong\u003e\u003cspan\u003eagent platform\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e that provides the infrastructure needed to create and manage intelligent applications.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis perspective is useful for engineers who want to build reusable systems rather than isolated AI demonstrations.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe book's practical progression covers agent development from introductory concepts through assistants, multi-agent applications, actions, autonomy, platforms, memory, prompts, reasoning, evaluation, planning, and feedback.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eKey Topics Covered\u003c\/span\u003e\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan\u003eArtificial Intelligence\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAI Agents\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgentic AI\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eLarge Language Models\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eLLM Applications\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eGPT Assistants\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAutonomous Agents\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAutonomous Assistants\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eMulti-Agent Systems\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eMulti-Agent Architecture\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent Orchestration\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAI Workflows\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent Tools and Actions\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent Platforms\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAI Memory\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eKnowledge Management\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eRetrieval-Augmented Knowledge\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003ePrompt Engineering\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003ePrompt Flow\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent Reasoning\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAI Planning\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAgent Evaluation\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eFeedback Loops\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eIntelligent Automation\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003ePython Development\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eGenerative AI\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eNatural Language Processing\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003e\u003cspan\u003eWhy Read This Book?\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cstrong\u003e\u003cspan\u003eAI Agents in Action\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e is valuable for readers who want to understand how modern AI systems can move beyond simple question-and-answer interactions toward autonomous, tool-using applications.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eRather than focusing exclusively on the theory of artificial intelligence, Micheal Lanham takes a practical approach to building agents and connecting them into larger systems. The book provides a progression from understanding agent concepts to developing assistants, multi-agent systems, agent platforms, memory and knowledge capabilities, reasoning, planning, evaluation, and feedback.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eFor developers entering the rapidly evolving field of agentic AI, the book provides a useful foundation for understanding the architecture and engineering principles behind AI agents.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eWho Should Read This?\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis book is particularly suitable for:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan\u003eSoftware developers\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003ePython programmers\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eAI engineers\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eMachine learning engineers\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eData scientists\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eDevelopers building LLM applications\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eGenerative AI enthusiasts\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eMLOps and AI infrastructure professionals\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eTechnology professionals exploring agentic AI\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eStudents studying artificial intelligence\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eDevelopers interested in autonomous assistants\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eProfessionals exploring multi-agent systems\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe publisher positions the book toward readers interested in creating LLM-powered autonomous agents and intelligent assistants for practical business and personal applications.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eProduct Details\u003c\/span\u003e\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eBook Title:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e AI Agents in Action: Build, Orchestrate, and Deploy Autonomous Multi-Agent Systems\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eAuthor:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e Micheal Lanham\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003ePublisher:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e Manning\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003ePublication:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e 2025\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eLanguage:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e English\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eGenre:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e Artificial Intelligence \/ Machine Learning \/ Software Development\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eCategory:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e AI \u0026amp; Machine Learning\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eLength:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e 344 pages\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eISBN-13:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e 9781633436343\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eFormat:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e English Paperback \/ Trade Paperback\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003eLevel:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e Intermediate\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e\u003cspan\u003ePrimary Topics:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e AI Agents, LLMs, Multi-Agent Systems, Prompt Engineering, Autonomous Assistants\u003c\/span\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe publisher lists the 2025 edition at 344 pages with ISBN \u003c\/span\u003e\u003cstrong\u003e\u003cspan\u003e9781633436343\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eAbout the Author\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cstrong\u003e\u003cspan\u003eMicheal Lanham\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e is a software and technology innovator with more than 20 years of industry experience. His professional work has covered software applications across areas including games, graphics, web, desktop, engineering, artificial intelligence, GIS, and machine learning. He has also authored books on deep learning, including Manning's \u003c\/span\u003e\u003cem\u003e\u003cspan\u003eEvolutionary Deep Learning\u003c\/span\u003e\u003c\/em\u003e\u003cspan\u003e.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003eFinal Overview\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan\u003eAI Agents in Action by Micheal Lanham\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e is a practical resource for developers who want to learn how AI agents can be designed, orchestrated, and deployed as useful intelligent systems. From Large Language Models and GPT assistants to autonomous agents, multi-agent architectures, tools, memory, knowledge, prompts, reasoning, evaluation, planning, and feedback, the book provides a broad introduction to building modern agentic AI applications.\u003c\/span\u003e\u003c\/p\u003e","brand":"BookBeen","offers":[{"title":"Default Title","offer_id":53462429761845,"sku":null,"price":1060.0,"currency_code":"PKR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0972\/1731\/5125\/files\/BookBeen-2026-09-04T211417.997.png?v=1788538503","url":"https:\/\/bookbeen.com\/products\/ai-agents-in-action-micheal-lanham","provider":"Bookbeen","version":"1.0","type":"link"}