Building Production AI Agents for the Web: Design and orchestrate autonomous agents with MCP, Multi-Agent Patterns, and Harness Engineering

Design, orchestrate, and deploy scalable AI agents with real-world patterns, multi-agent systems, and evaluation frameworks.

Key Features

• Filled with real-world agentic web application examples using LLMs, RAG, and tool calling
• Design and implement AI assistants with reasoning patterns like ReAct
• Architect scalable agent systems with planning, orchestration, and autonomy

Book Description

AI is no longer just about generating text. It’s about building autonomous, goal-driven systems that can reason, act, and collaborate. Hands-On AI Agents for the Web is your practical guide to designing and deploying agentic web applications powered by Large Language Models (LLMs).

Starting with the fundamentals of agentic thinking and responsible AI, this book walks you through integrating LLMs into real-world web apps. You’ll progressively enhance your systems with tool calling, Retrieval-Augmented Generation (RAG), and advanced reasoning patterns like ReAct, before moving into the design of fully autonomous agents.

As you advance, you’ll explore agent architectures, planning systems, orchestration, and multi-agent collaboration, learning how modern frameworks and protocols like Model Context Protocol (MCP) enable scalable, interoperable AI systems. The book emphasizes hands-on learning, with practical examples that demonstrate how to build AI assistants, coordinate multiple agents, and apply proven design patterns, while avoiding common pitfalls.

By the end, you’ll have the skills to build production-ready, intelligent web experiences powered by autonomous agents.

What you will learn

• Understand agentic thinking and responsible AI principles
• Integrate LLMs into web applications and build prompt-driven systems
• Enhance LLM capabilities with tool calling and external integrations
• Implement RAG pipelines for context-aware, accurate AI responses
• Implement planning systems for goal-driven agents
• Orchestrate autonomous agents and manage workflows at scale
• Identify agent design patterns and avoid common anti-patterns
• Test, evaluate, and improve agent performance using evaluation frameworks

Who this book is for

This book is for full-stack developers, software architects, and AI practitioners looking to build intelligent, agent-driven web applications. It’s also valuable for tech leads and product managers working on AI-powered products.

If you have a basic understanding of web development and want to move beyond simple AI integrations into autonomous, production-ready agent systems, this book will give you the frameworks, tools, and hands-on experience to get there.

Table of Contents

1. Introduction to Agentic Apps
2. Integrating Large Language Models (LLMs)
3. Enhancing LLMs with Tool Calling
4. Introduction to Retrieval-Augmented Generation (RAG)
5. Introducing the Model Context Protocol (MCP)
6. Building AI Assistants
7. Introduction to Agents and ReAct Architecture
8. Building Your First Agentic App
9. Advanced Agentic App Development
10. Multi-Agent Frameworks
11. Deploying Agents
12. API Management
13. Responsible AI

Christoffer Noring is a passionate developer and educator who specializes in modern web technologies and AI integrations and works as an engineer at Microsoft. He's also a tutor at the University of Oxford and is a published author on Angular, RxJs, generative AI, and now MCP. Christoffer has almost two decades of experience in software development and is a frequent speaker at tech conferences worldwide. According to his manager, his best quality is being able to break down complex technical concepts into simple, understandable terms. He hopes you agree!

When not coding or writing, Christoffer is probably growing another user community, mentoring developers, or spending time with his family.