March 2026
Intermediate to advanced
448 pages
12h 44m
English
Overview
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 tools are popping up everywhere. The LangChain ecosystem, and standards like MCP are driving this new gold rush. This book helps you claim your spot.
In AI Agents and Applications: With LangChain, LangGraph and MCP, you’ll discover:
AI Agents and Applications is your hands-on guide to creating real, production-ready language model solutions. With LangChain and LangGraph, you’ll orchestrate powerful agentic workflows and build dynamic tool-based agents that can search, summarize, reason, and act. You’ll move from essential prompt engineering to advanced Retrieval Augmented Generation (RAG), and finally to deploying multi-agent systems using modern integration standards like the Model Context Protocol (MCP).
About the Technology
This book teaches you to design reliable LLM-powered systems by focusing on the concepts, architectures, and design patterns that will stay stable even as models and APIs change. You’ll learn to structure prompts, compose modular chains, and build RAG pipelines that ingest documents, split them into chunks, embed them, retrieve the right context, and ground answers to elliminate (or vastly reduce) hallucinations.
About the Book
Along the way you’ll build concrete applications—summarization and Q&A engines, context-aware chatbots with memory, and tool-using AI agents that orchestrate multi-step workflows with branching logic. For the examples, the book uses Python, LangChain, LangGraph, and LangSmith, but you’ll be able to generalize to other frameworks. You’ll understand with clarity and confidence how to keep integrations maintainable, manage context limits and cost/latency tradeoffs, and evaluate, debug, and monitor behavior so your systems work in production.
What's Inside
About the Reader
About the Author
Roberto Infante is an AI innovator with deep FinTech experience, working for a London-based hedge fund. He specializes in building agentic systems for both plain vanilla and exotic quantitative analysis.
Quotes
The playbook for building AI systems that actually work at scale.
- Muntazir Abidi, Auquan
The book explains the topic really well. It's clear and does not go into irrelevant details. I really enjoyed it.
- Piotr Jastrzebski
A perfect bridge between AI theory and real-world implementation.
- Abdullah Al Imran, Aon PLC
The practical, modern guide the industry has been waiting for.
- Ajay Solanki, Innovation Hacks AI Inc.
A must-read for those looking to understand the ‘why’ and the ‘how’ of using LLMs in practice.
- Octavian Brînzea, EROM.io
The hands-on guide I wish existed when I started building production AI agents.
- Tirso Lopez, Multiverse Computing
AI-powered applications are rapidly becoming the new normal. Personal productivity assistants, coding agents, smarter search, and automated reporting tools are popping up everywhere. The LangChain ecosystem, and standards like MCP are driving this new gold rush. This book helps you claim your spot.
In AI Agents and Applications: With LangChain, LangGraph and MCP, you’ll discover:
- Prompt and context engineering for accurate, hallucination-resistant systems
- Advanced RAG for summarization, semantic search, and reliable Q&A
- Structured, multi-step agentic workflows with LangGraph
- Tool-based agents that adapt in real time
- Multi-agent systems for complex, real-world tasks
- MCP integration to expose, compose, and consume plug-and-play tools
AI Agents and Applications is your hands-on guide to creating real, production-ready language model solutions. With LangChain and LangGraph, you’ll orchestrate powerful agentic workflows and build dynamic tool-based agents that can search, summarize, reason, and act. You’ll move from essential prompt engineering to advanced Retrieval Augmented Generation (RAG), and finally to deploying multi-agent systems using modern integration standards like the Model Context Protocol (MCP).
About the Technology
This book teaches you to design reliable LLM-powered systems by focusing on the concepts, architectures, and design patterns that will stay stable even as models and APIs change. You’ll learn to structure prompts, compose modular chains, and build RAG pipelines that ingest documents, split them into chunks, embed them, retrieve the right context, and ground answers to elliminate (or vastly reduce) hallucinations.
About the Book
Along the way you’ll build concrete applications—summarization and Q&A engines, context-aware chatbots with memory, and tool-using AI agents that orchestrate multi-step workflows with branching logic. For the examples, the book uses Python, LangChain, LangGraph, and LangSmith, but you’ll be able to generalize to other frameworks. You’ll understand with clarity and confidence how to keep integrations maintainable, manage context limits and cost/latency tradeoffs, and evaluate, debug, and monitor behavior so your systems work in production.
What's Inside
About the Reader
About the Author
Roberto Infante is an AI innovator with deep FinTech experience, working for a London-based hedge fund. He specializes in building agentic systems for both plain vanilla and exotic quantitative analysis.
Quotes
The playbook for building AI systems that actually work at scale.
- Muntazir Abidi, Auquan
The book explains the topic really well. It's clear and does not go into irrelevant details. I really enjoyed it.
- Piotr Jastrzebski
A perfect bridge between AI theory and real-world implementation.
- Abdullah Al Imran, Aon PLC
The practical, modern guide the industry has been waiting for.
- Ajay Solanki, Innovation Hacks AI Inc.
A must-read for those looking to understand the ‘why’ and the ‘how’ of using LLMs in practice.
- Octavian Brînzea, EROM.io
The hands-on guide I wish existed when I started building production AI agents.
- Tirso Lopez, Multiverse Computing
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