Table of Contents

A practical engineering guide to building production-grade Agentic AI systems.

Part I — Foundations

• Chapter 1 — Introduction to the Agentic Era
• Chapter 2 — A Brief History of AI and LLMs
• Chapter 3 — Understanding Large Language Models
• Chapter 4 — Prompt Engineering Fundamentals

Part II — Building Blocks

• Chapter 5 — Architecture of Agentic Systems
• Chapter 6 — Context Engineering and Memory
• Chapter 7 — Tool Calling and External Integrations
• Chapter 8 — Planning, Reasoning, and Reflection
• Chapter 9 — Multi-Agent Systems

Part III — Enterprise AI Engineering

• Chapter 10 — AI System Design Patterns
• Chapter 11 — Reliability and Evaluation
• Chapter 12 — Performance Optimization and Cost Engineering
• Chapter 13 — Security, Governance, and Compliance
• Chapter 14 — Deploying Agentic Systems

Part IV — Advanced Topics

• Chapter 15 — Fine-Tuning and Model Adaptation
• Chapter 16 — AI Engineering Ecosystem
• Chapter 17 — Future of Agentic AI

Part V — Hands-On Enterprise Examples

• Chapter 18 — Building an Enterprise Assistant
• Chapter 19 — Building a Research Agent
• Chapter 20 — Production Readiness Checklist

Total Chapters: 20

Audience: Architects, Engineering Leaders, CTOs, Principal Engineers, Senior Software Engineers