The Developer's Guide to AI

A practical, accessible guide that shows working software developers how to integrate real AI features into the applications they already build—using JavaScript, Python, APIs, and modern cloud services, without needing a data-science background.

Most developers already know AI is powerful. What they don’t know is how to actually use it in their own codebase without becoming a data scientist. Too often, AI features stall out at brittle prototypes, half-baked search functions, or “smart” features that collapse the moment requirements change. That’s where this book comes in. We wrote this book with the everyday software developer in mind. The dev who works in a company and wants to grow their career by meeting the demands of the industry without losing time in the areas that might not be relevant to their current company or role.

Written by seasoned developers Jacob Orshalick, Jerry M. Reghunadh, and Danny Thompson, this book teaches you how to integrate and customize large language models (LLMs) and other pre-trained AI models to solve real-world problems. 

Instead of drowning you in theory, this book gives you:

• Intelligent automation: Automate repetitive work by calling LLMs directly from your own applications and streaming intelligent responses to the UI.
• Practical Paths: Build production-ready AI features with tools you already know and some you don't.
• Clarity through the hype: Learn where AI actually makes sense in your applications (and where it doesn’t).
• Fewer dead-ends: Avoid wasted cycles by understanding limitations, costs, and trade-offs before you build.
• Competitive edge: Discover how AI can help you improve search, personalization, automation, and more.

Acknowledgments
Preface
Introduction

PART I: GETTING STARTED WITH AI
Chapter 1: Understanding Large Language Models
Chapter 2: Building Your First LLM-Powered Application
Chapter 3: Python Essentials for LLMs and APIs

PART II: PROMPT ENGINEERING
Chapter 4: Fundamentals of Prompt Engineering
Chapter 5: Prompt Engineering Techniques
Chapter 6: Prompt Engineering in Code

PART III: VECTOR DATABASES AND RAG
Chapter 7: Vector Databases in Practice
Chapter 8: Designing a Retrieval-Augmented Generation System

PART IV: ADAPTING MODELS TO REAL-WORLD TASKS
Chapter 9: Why and When to Customize a Model
Chapter 10: Preparing Data for Fine-tuning
Chapter 11: Fine-Tuning Models in Practice

PART V: BUILDING AGENTIC SYSTEMS
Chapter 12: From Workflows to Autonomous Agents
Chapter 13: Building an Autonomous Agent
Chapter 14: Extending Agents with Tools

Afterword
IndexJacob Orshalick has over 20 years in software development, including 16+ as an independent consultant for startups to Fortune 500 companies. A seasoned technologist, he’s led high-impact projects, revitalized struggling initiatives, and co-authored Seam Framework: Experience the Evolution of Java EE. Orshalick speaks regularly at conferences and shares his work at focus.dev.

Jerry Mannel Reghunadh is a Senior Director with 20+ years in tech, starting in QA before moving into product innovation and solution architecture. Known for mastering complex concepts and making them accessible, he’s a frequent conference speaker and lifelong tinkerer. Jerry shares his projects at jerrymannel.me. 

Danny Thompson is a software developer who now leads as a Director of Technology, working with Fortune 500 companies and teaching software developers worldwide. Host of The Programming Podcast and organizer of The Commit Your Code Conference, he is a sought-after speaker who specializes in making complex topics very approachable.