The Developer's Guide to AI

The Developer's Guide to AI

From Prompts to Agents
by Jacob Orshalick, Jerry Mannel Reghunadh, and Danny Thompson
Fall 2026, 336 pp.
ISBN-13: 
9781718504769
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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.
Author Bio 

Jacob 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.

Table of contents 

Acknowledgments
Preface
Introduction

Part I: Getting Started with AI
Interlude: The Startup Team Begins their AI Journey
Chapter 1: Introduction to Large Language Models
Chapter 2: Building Your First Application that Calls an LLM
Chapter 3: Python Essentials for Working with LLMs and APIs

Part II: Prompt Engineering
Interlude: Startup Growing Pains
Chapter 4: Fundamentals for Prompting LLMs
Chapter 5: Prompting Techniques for Creativity, Precision, and Control
Chapter 6: Libraries and Strategies for Prompting in Code

Part III: Vector Databases and RAG
Interlude: Product Refinement and Evolution
Chapter 7: Vector Databases in Practice
Chapter 8: Building a RAG Solution

Part IV: Fine-tuning
Interlude: The Inbox Problem
Chapter 9: Introduction to Fine-tuning
Chapter 10: Creating the dataset
Chapter 11: Getting Started with Fine-tuning
Chapter 12: Fine-tuning an LLM

Part V: Agents
Interlude: AI Steps into the Workflow
Chapter 13: Introduction to AI Agents
Chapter 14: Building Your First Agent
Chapter 15: Introduction to Tools
Chapter 16: Epilogue

The chapters in red are included in this Early Access PDF.