AI Agents and Applications

Build intelligent LLM-powered applications with agentic workflows and tool-based agents. AI-powered applications are rapidly becoming the new normal. Personal productivity assistants, coding agents, smarter search, and automated reporting and document creation based on custom data are showing up everywhere. Powerful tools including open source LLMs, the Langchain tools ecosystem, and standardized protocols like MCP are driving this new gold rush. This book will help you earn your seat at the table. AI Agents and Applications is your hands-on guide to developing cutting-edge language model solutions for real business needs. Using LangChain and LangGraph, you’ll learn how to orchestrate powerful agentic workflows and build dynamic tool-based agents that can search, summarize, and act in complex environments. The book takes you from the essential skill of prompt engineering, through advanced Retrieval Augmented Generation (RAG) techniques, all the way to deploying multi-agent systems that can leverage the latest in AI integration—including the Model Context Protocol (MCP). In AI Agents and Applications: With LangChain, LangGraph, and MCP, you’ll discover • Prompt and context engineering for automated systems that deliver accurate, hallucination-free responses • Advanced RAG methods for document summarization, semantic search, and robust Q&A bots • Agentic workflows with LangGraph to orchestrate structured, multi-step processes • Tool-based agents that dynamically adapt to user needs in real time • Multi-agent systems for complex, real-world tasks • MCP integration to expose, compose, and consume plug-and-play tools No research lab or giant infrastructure needed! This book’s practical approach, clear diagrams, and abundant code samples empower you to build, refine, and deploy AI applications with confidence. About the book AI Agents and Applications provides a practical, step-by-step approach to building LLM-powered applications using state-of-the-art tools like LangChain, LangGraph, and MCP. You’ll quickly master prompt engineering techniques for automated systems and advanced RAG techniques. Then, you’ll move into structured agentic workflows with LangGraph and flexible, tool-based agent architectures. The book guides you through creating single and multi-agent systems, debugging and optimizing agent performance, and integrating external tools using the new Model Context Protocol (MCP). With visual explanations and real code throughout, this book delivers everything you need to go from your product ideas to production-ready AI solutions. About the reader For Python programmers who know the absolute basics of LLMs. No advanced mathematics or specialist AI knowledge required. About the author Roberto Infante has been developing software professionally for over 25 years, primarily for financial institutions including investment banks, asset managers, brokers, and exchanges. He currently leads quantitative development for the treasury department of a hedge fund, and he is also leading generative AI projects. He is the author of Building Etherium Dapps.