Description A study of the patterns, tools, and best practices for creating enterprise-scale chatbots and conversational assistants, incorporating both traditional logic and modern generative AI models. Key Topics: Retrieval-Augmented Generation (RAG), intent classification, feedback loops for continuous improvement, and the design of Q&A and process-oriented agents. About the Technology: Conversational AI utilizes Large Language Models (LLMs) and structured intent data to provide adaptive virtual assistant experiences and automated summarization. About the Book: The text details methods for clarifying user intent, handling unanticipated input, and integrating generative AI safely into conventional chatbot architectures. About the Reader: For engineers and product managers working with conversational interfaces. About the Author: Andrew Freed, Cari Jacobs, and Eniko Rózsa are conversational AI architects and developers at IBM.