In this episode, we explore the fascinating but complex world of AI prompting, specifically focusing on the Chain of Thought (COT) method. Inspired by listener requests, we delve into how COT helps improve AI outputs by breaking down tasks into a step-by-step process, akin to giving a recipe rather than just an instruction. We discuss the BUILD framework for effective COT prompts: Breaking down problems, using clear instructions, integrating logical flow, leveraging intermediate outputs, and defining success criteria. Real-world examples such as financial forecasting, market analysis, and customer feedback illustrate the transformative potential of COT, showing how it can turn generic AI responses into actionable insights. Tune in to learn how to enhance your AI interactions and discover when COT is most useful.00:00 Introduction and Overview00:20 Understanding AI Prompting Challenges01:02 Introduction to Chain of Thought (COT) Prompting02:37 The BUILD Framework for Effective COT Prompts02:49 Step-by-Step Breakdown of the BUILD Framework07:36 Real-World Applications of COT11:46 When to Use COT and Final Thoughts13:01 Conclusion and Encouragement

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