Prompt Engineering Fundamentals: How to Get Better Results With AI

In this episode of the AI Explored podcast, data scientist Chris Penn dives into the world of prompt engineering for marketers. He explains that prompt engineering involves creating clear, effective instructions in natural language for AI tools to generate the desired results. The conversation introduces two key frameworks: R.A.C.E. (Role, Action, Context, Execute) for structuring prompts, and P.A.I.R. (Prime, Augment, Refresh, Evaluate) for refining them over time. These frameworks stress the importance of being specific and engaging in an iterative process with AI, allowing it to tackle more than just basic content creation. They can also assist with tasks like data summarization, extraction, and complex analysis. Chris emphasizes that providing rich context—such as relevant documents and LinkedIn profiles—greatly improves AI's ability to deliver high-quality, customized outcomes.