A Gentle (Conceptual) Introduction to DSPy

This podcast episode explores the concepts of DSPy and prompt engineering and how they can be used to improve the output of AI models. The episode introduces the example of Nancy, an AI engineer, who discovers prompt engineering as a solution to enhance her product. It discusses the confusion and curiosity sparked by terms like chain of destiny and chain of thought in the context of prompt engineering. The episode then delves into the process of prompt engineering and how it can be improved using a structured dataset and test cases. It introduces the tool DSPy, which automates prompt evaluation and optimization, and highlights its power in selecting the best examples and comparing performance. The episode concludes by discussing the benefits of using DSPy for prompt optimization and encourages listeners to learn more about it on Learn By Building AI dot AI.