Preface

We are living in a time of accelerated change in artificial intelligence (AI), where models are no longer passive tools but active decision-makers. Since the release of ChatGPT in November 2022, the world has witnessed a seismic shift: not only in the capabilities of large language models (LLMs) but also in the way AI is architected, integrated, and operationalized within real-world systems.

A new paradigm has emerged—AI agents. Unlike traditional AI workflows, agents bring persistence, autonomy, and goal-oriented reasoning to applications. They can plan, remember, use tools, and interact with other agents or humans to complete complex tasks. From customer service to R&D, from orchestrating APIs to driving personalized workflows, AI agents are reshaping how we think about software and intelligence.

This book serves as a hands-on guide to understanding and building AI agents, covering their architecture, key components, and real-world use cases. Whether you are a developer, architect, product manager, or AI enthusiast, this book aims to give you the foundational knowledge and practical skills to harness the power of autonomous agents.

The book is structured into three parts:

• Part 1, Foundations of AI Workflows and the Rise of AI Agents, explores how AI workflows have evolved since the rise of generative models, tracing the shift from simple API calls to more intelligent, autonomous behaviors. It introduces the concept of AI agents, their ingredients—LLMs, tools, memory, and context—and highlights the growing need for agentic systems across industries.
• Part 2, Designing, Building, and Scaling AI Agents, dives into the practical aspects of agent development. It covers AI orchestration tools, memory and context handling, tool integration, and agent observability. This part also walks you through building single-agent and multi-agent applications using frameworks such as LangChain and LangGraph, with hands-on examples such as e-commerce assistants and customer support agents.
• Part 3, Road to an Open, Agentic Ecosystem, looks ahead to the protocols, platforms, and principles shaping the future of intelligent software. It covers emerging open standards such as MCP, A2A, and NLWeb, and discusses how to build responsible, secure, and cost-effective agent systems for enterprise-scale deployment. It will also cover responsible AI practices, including evaluation, safety mechanisms, and human oversight.