Prompt engineering is quickly becoming one of the most valuable skills in the AI era, yet most people still treat it as trial and error. In this first episode of our special two-part series based on the Prompt Engineering resource authored by Lee Boonstra at Google, we break down what prompt engineering actually is, why it matters, and how understanding the mechanics behind large language models can dramatically improve the quality of your AI interactions. From token prediction to temperature settings, we explain how generative AI decides what to say next—and how you can guide it with more precision.

We cover everything from basic to intermediate techniques, including single-shot and few-shot prompting, system and role prompts, and often-overlooked features like output configuration and randomness controls. These are the tools that separate casual users from those getting truly valuable results. You will learn how to write clearer prompts, control creativity, and design better outputs for everything from content generation to complex decision support.

Whether you're a student, professional, or a business leader, this episode will give you a strong foundation in how to think about prompting. It is practical, actionable, and sets the stage for Part Two, where we will explore advanced strategies like Chain of Thought, Tree of Thought, and more. If you want to work smarter with AI, start right here.