This book explores various methods to adapt "foundational" LLMs to specific tasks with enhanced accuracy, reliability, and scalability. It tackles the lack of reliability of “out of the box” LLMs by teaching the AI developer tech stack of the future: Prompting, Fine-Tuning, RAG, and Tools Use.
