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June 11, 2025, 1:56 p.m.
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(Last updated: June 12, 2025, 6:40 a.m.)
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| ['Huang K. Agentic AI. Theories and Practices 2025.pdf'] | 0 bytes |
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12.2 MB
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| Uploaded by andryold1 | Size 12.2 MB | Health [ 39 /47 ] | Added 2025-06-11 |
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NOTE
SOURCE: Huang K. Agentic AI. Theories and Practices 2025
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COVER
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MEDIAINFO
Textbook in PDF format This book analyzes the rise and transformative impact of Generative AI agents or Agentic AI across industries, offering a comprehensive exploration of their development, applications, and implications. It highlights how these systems are revolutionizing business processes, enhancing decision-making, and reshaping entire sectors from finance to healthcare. It traces the evolution of AI agents from early programs to today’s sophisticated autonomous systems, providing a taxonomy of agent types. It then explores cutting-edge tools and frameworks for development, such as AutoGen, Langgraph, and CrewAI, offering practical insights for their deployment. Key focus areas include evaluating multiagent systems and coordination techniques, addressing challenges in communication, and conflict resolution. The book presents case studies from banking, insurance, healthcare, and cybersecurity, showcasing how autonomous agents are automating tasks and driving innovation. In turn, the book provides in-depth analyses of Agentic AI in emerging fields like gene editing, robotics, and business process automation, demonstrating its potential to accelerate scientific research and value creation. The discussion extends to economic ramifications, examining impacts on macroeconomic trends, microeconomic dynamics within businesses, and the emergence of decentralized, token-based economies. Throughout, thought-provoking questions encourage readers to consider the broader implications of these technological advances. In the Chapter 2, we transition from the “why” of AI agents to the “how,” diving deep into the practical world of agent development. Guided by our “Seven-Layer AI Agent Architecture,” we’ll dissect the essential components that bring these sophisticated systems to life, from the foundational models that provide their core intelligence to the ecosystems where they deliver real-world impact. We’ll embark on a comparative exploration of leading agent frameworks—including AutoGen, LangGraph, LlamaIndex, and AutoGPT—examining their unique approaches to the intricate challenges of state management, tool integration, and decision-making. As we navigate this technical landscape, we’ll also confront the pressing issues of security, compliance, scalability, and data quality that organizations must address to successfully deploy AI agents. LangGraph is a library developed by LangChain Inc. designed for building stateful, multi-actor applications using LLMs. It focuses on creating agent and multi-agent workflows, with particular emphasis on cycles, controllability, and persistence. LangGraph’s unique graph-based architecture enables dynamic and adaptive workflows that can handle complex decision-making processes, making it ideal for use cases requiring iterative problem-solving, looping logic, and sophisticated reasoning. The work concludes with a critical examination of related safety and security considerations, emphasizing the need for proactive measures. Maintaining a forward-looking perspective, it prompts readers to consider how these technologies might reshape industries and society, raising important questions about the changing nature of work, ethical aspects, and equitable distribution of benefits. Bridging theoretical foundations and practical applications, the book offers valuable insights for data scientists, IT managers, CIOs, CAIOs, CTOs, business analysts, and graduate students seeking to understand and apply AI’s transformative potential across various industries. Preface The Genesis and Evolution of AI Agents AI Agent Tools and Frameworks Multi-Agent Coordination The AI Agent Economy AI Agents and Business Workflow AI Agents in Offensive Security AI Agents in Defensive Security AI Agents in Banking AI Agents in Insurance AI Agents in Healthcare AI Agents in Robotics AI Agent Safety and Security Considerations
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