The Whole Book, Chapter by Chapter

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Front Matter

• Front Matter — Copyright & Reading Guide
• Conventions Used in This Book
• Preface — The Day the AI Fired Itself
• Acknowledgments
• About the Author

Part I — Foundations

• Chapter 1 — Why Prompting Is an Engineering Skill
• Chapter 2 — How LLMs Work — Just Enough Theory
• Chapter 3 — The Specification Frame — Your Master Key

Part II — Core Patterns

• Chapter 4 — Code Generation — Ten Production Recipes
• Chapter 5 — Code Review That Actually Finds Problems
• Chapter 6 — Debugging — From Symptom to Root Cause
• Chapter 7 — Documentation That Gets Read
• Chapter 8 — Architecture Decisions Without Blind Spots
• Chapter 9 — Testing — Find What Your Tests Miss

Part III — Advanced Techniques

• Chapter 10 — Chaining and Multi-Agent Orchestration
• Chapter 11 — Prompt Files — Treat Your Prompts Like Code
• Chapter 12 — Context Engineering — What the Model Knows
• Chapter 13 — MCP — Give Your AI Eyes and Hands
• Chapter 14 — The Modern Toolchain — What to Use and Why

Part IV — The Professional Edge

• Chapter 15 — Enterprise Security — The Attack Surface You Did Not Know You Had
• Chapter 16 — For Managers, Analysts, and Executives
• Chapter 17 — What Is Next — The Honest View

Part V — Specialized Use Cases

• Chapter 18 — Database, Migrations, and Query Prompting
• Chapter 19 — DevOps, CI/CD, and Infrastructure Prompting

Appendices

• Appendix A — Pattern Quick Reference Card
• Appendix B — Result<T> and Money<T> — Complete Implementations
• Appendix C — Project Setup Guide (.NET 9 and Java 21)
• Appendix D — MCP Server Directory
• Appendix E — Domain Prompt Templates
• Appendix F — Glossary
• Appendix G — The Prompt Hall of Shame
• Appendix H — Reverse Review — An AI Critiques Its Own Prompts
• Appendix J — Research & Statistics Notes
• Appendix K — Language Quick-Start Guide (Python & TypeScript)

The print index (Appendix I) is omitted online — use your browser’s search.