This book introduces the emerging discipline of answer engine optimization, a practical framework for making content more discoverable and citable by generative AI systems. Drawing on decades of experience, author Rodrigo Stockebrand explains how large language models retrieve, evaluate, and decide which sources to include in the final answer.