Understanding AI

Generative AI has quietly become part of everyday work. It writes emails, summarizes reports, drafts code, generates images, and answers questions in seconds. If you want to maximize the power of AI in your day-to-day, this is the book for you!

Understanding AI: A beginner’s guide is a practical, accessible introduction to generative AI for professionals, educators, managers, students, and content creators who want to understand how AI models, applications, and agents work so they can use it effectively. Based on author Matthew Berman’s wildly popular YouTube videos, this entertaining and insightful book guides you from square one without a lot of math, code, and technical jargon.

Authors Matthew Berman, Angelica Lo Duca, and Nick Wentz take you step by step through the patterns behind modern AI systems, providing a clear picture of how they do what they do, how to steer them toward the results you actually want, and where their limits truly lie. You’ll start with the fundamentals of how large language models generate text, then explore prompt engineering techniques that separate mediocre outputs from genuinely useful ones. You’ll learn how to compare commercial and open models, how to know when a small model is a smart choice, and how to match the right tool to the task in front of you. You also look at techniques like Retrieval Augmented Generation—or RAG--for grounding LLM responses in real information and understand how AI agents complete multi-step work on your behalf.

Just as importantly, Understanding AI: A beginner’s guide takes the limitations of generative AI seriously. Hallucinations, bias, privacy concerns, and the temptation to over-trust confident-sounding outputs are treated as core topics, not footnotes. You’ll finish each chapter with a short scenario that shows how AI plays out in real workplace situations, so the concepts stick and the trade-offs feel real.

This book won’t lock you into one platform or one vendor. AI the tools will keep changing, and the book gives you the durable skills to keep pace. Read it once as an introduction, then return to it as a reference whenever a new model, new capability, or new question shows up in your work.