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Building Agents with OpenAI  Agents SDK
Building Agents with OpenAI  Agents SDK

Building Agents with OpenAI Agents SDK: Create practical AI agents and agentic systems through hands-on projects

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Profile Icon Henry Habib
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Paperback Oct 2025 276 pages 1st Edition
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Arrow left icon
Profile Icon Henry Habib
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Paperback Oct 2025 276 pages 1st Edition
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Building Agents with OpenAI Agents SDK

Introduction to AI Agents

AI agents are changing the way we work. Software has typically created deterministic (if X, then Y) and rigid systems that cannot address ambiguity or adapt to different goals – but this is changing. With the advancements of large language models (LLMs), intelligent systems are being created that can independently reason through steps and take actions to complete a goal. These AI agents are taking a larger share of work previously thought only a human could do, and it’s just beginning.

By the end of this book, you will become a master at creating AI agents through OpenAI Agents SDK. The best way to learn this is to get your hands dirty and start building AI agent systems using that framework. Before we do this, however, we need to start at the most basic level, which is answering the question, “What is an AI agent?”.

This chapter goes through everything you need to know to answer that question and, more importantly, lays...

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https://packt.link/4Bbd9

AI agents are changing the way we work. Software has typically created deterministic (if X, then Y) and rigid systems that cannot address ambiguity or adapt to different goals – but this is changing. With the advancements of large language models (LLMs), intelligent systems are being created that can independently reason through steps and take actions to complete a goal. These AI agents are taking a larger share of work previously thought only a human could do, and it’s just beginning.By the end of this book, you will become a master at creating AI agents through the OpenAI Agents SDK. The best way to learn this is to get your hands dirty and start building AI agent systems using that framework. Before we do this, however, we need to start at the most basic...

Technical requirements

This chapter will be an overview of AI agents from a theoretical point of view to set a good foundation before we start building them. As a result, we will not be writing any code or developing any applications in this chapter. However, to follow along and complete the exercises and projects discussed throughout the rest of the book, make sure you have the following set up in your development environment:

  • Operating system: Windows 10/11, macOS, or Linux-based distribution (Ubuntu recommended).
  • Python version: Python 3.8 or later. You can verify your Python version by running python --version in your terminal or Command Prompt.
  • OpenAI account: Sign up at https://platform.openai.com/signup.
  • OpenAI API key: Obtained by creating an account with OpenAI. You will require this to utilize the OpenAI Agents SDK.
  • Code editor: VS Code, PyCharm, or any IDE/editor you prefer.

Throughout this book...

Overview of AI agents

Before exploring AI agents in depth, we must first establish an intuitive understanding of what an AI agent actually is, how it fundamentally differs from traditional software, and what advantages and disadvantages this brings. This is difficult as there are varying definitions that often evolve with technological advancements. By clearly defining the key concepts upfront – including its benefits such as intelligent autonomy, reasoning abilities, and adaptive problem-solving – we can set the stage for understanding its practical applications and building approaches.

What is an AI agent?

An AI agent is an intelligent system that can operate independently to accomplish a specific goal by perceiving the world around it and taking action. Key distinguishing features of an AI agent include its ability to think and reason from a broad and sometimes ambiguous goal, its ability to create a plan to accomplish that goal,...

Practical applications of AI agents

AI agents are more than just a trendy idea – they are becoming central to how companies are leveraging AI to solve real problems. In particular, early adopters of AI agents are using them at all levels of their organizations, from customer-facing roles with AI agents that sell products and resolve issues to internal productivity such as software development or research.

Productivity gains

The most obvious and immediate motivation for AI agents is improved productivity, primarily through replacing or augmenting human work that traditional software systems cannot replace or augment. By handling these tasks autonomously, AI agents free up humans to focus on higher-level, more strategic work and creativity.Consider customer support as an example. Traditionally, a customer support center might require dozens or hundreds of human agents to handle queries. Traditional software systems may replace this with automated...

Build methodology of AI agents

Now that we understand an AI agent conceptually and its practical applications, we will discuss the anatomy of an AI agent as well as explain the step-by-step approach to designing and building them. Understanding this anatomy will help us design and implement agents systematically, so we can ensure each component is accounted for and functioning properly.

Anatomy of an AI agent

AI agents follow a typical pattern and can be broken down into three fundamental components. Specifically, the anatomy of an AI agent comprises the following:

  • Model: This is the brain of the operations. It interprets input, reasons about actions, and generates outputs. Typically, this is an LLM with system instructions and a control logic framework that enables it to reason and iterate.
  • Tooling interface: This is the hands and eyes. It provides the agent with the ability to act, such as sending emails or searching...
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Key benefits

  • Gain a complete understanding of the OpenAI Agents SDK features including models, tools, memory, guardrails, orchestration, tracing, and multi-agent systems
  • Progressively build AI agents through several hands-on projects that evolve from a simple workflow to a complex multi-agent system
  • Implement advanced agent capabilities such as RAG, MCPs, administration, workflow integration, and much more

Description

Everyone’s talking about AI agents, but how do you build one that works in the real world? Not a toy demo, but an agent that solves real problems, saves time, and integrates into workflows. With vague frameworks, fragmented tooling, and endless hype, most developers are left without a clear path. The hardest part isn’t technical; it is knowing where to start. This book gives you that starting point. It’s a complete guide to building intelligent AI agents and agentic systems using the official OpenAI Agents SDK. It begins by grounding you in the core concepts, design principles, and architecture of AI agents, how they differ from other traditional systems, their advantages, and why that matters. Through practical step-by-step projects, you’ll master every feature of the SDK—tools, memory, RAG, multi-agent orchestration, tracing, handoffs, and more—while contributing to an end-to-end agent system that grows in complexity. Projects include a custom support agent, invoice and inventory assistant, health advisor, sales trainer, and data analyst, giving you production-ready skills. By the end, you’ll know how to design, build, and deploy agentic systems that interact with APIs, query databases, hand off to external systems, and drive meaningful outcomes. You won’t just understand AI agents; you’ll be ready to ship them.

Who is this book for?

This book is for LLM engineers, developers, tech-savvy professionals, analysts, and consultants who want to build practical agentic AI solutions using the OpenAI SDK. A basic understanding of Python and AI concepts is recommended, but no prior experience with agents is required. Whether you're exploring agents for the first time or want to deepen your skills with hands-on projects, this guide provides structured, production-ready knowledge.

What you will learn

  • Understand the core principles of AI agents and why they matter
  • Use the OpenAI Agents SDK to build real, working agents from scratch
  • Design both single-agent and multi-agent systems
  • Integrate external tools, APIs, and data sources to extend agent capabilities
  • Add memory and stateful context to your agents so they can “remember” and adapt over time
  • Coordinate agent-to-agent handoff orchestrations
  • Secure, monitor, and scale agents in production
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Length: 276 pages
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ISBN-13 : 9781806112012
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Table of Contents

14 Chapters
Part 1: AI Agents Chevron down icon Chevron up icon
Introduction to AI Agents Chevron down icon Chevron up icon
Introduction to OpenAI Agents SDK Chevron down icon Chevron up icon
Environment Setup and Developing Your First Agent Chevron down icon Chevron up icon
Part 2: OpenAI Agents SDK Chevron down icon Chevron up icon
Agent Tools and MCPs Chevron down icon Chevron up icon
Memory and Knowledge Chevron down icon Chevron up icon
Multi-Agent Systems and Handoffs Chevron down icon Chevron up icon
Model and Context Management Chevron down icon Chevron up icon
Agent System Management Chevron down icon Chevron up icon
Part 3: Build AI Agents Chevron down icon Chevron up icon
Building AI Agents and Agentic Systems Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
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