The Developer's Guide to AI

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
Index