This episode begins with a welcome and an introduction to episode thirty-seven. The discussion then moves to prompt engineering with a focus on few-shot learning and the tool Prompt Poet. It explores customizing responses using YAML, Jinja2, and tone variations. Real customer data examples are used to demonstrate tone customization. The episode also covers combining these elements for coherent prompt creation. It concludes with closing thoughts on the capabilities of Prompt Poet.

(0:00) Welcome and introduction to the episode

(1:09) Prompt Engineering with Few-Shot Learning and Prompt Poet

(2:23) Customizing Responses with YAML, Jinja2, and Tone Variations

(5:07) Demonstrating Tone Customization with Real Customer Data Examples

(8:02) Combining Elements for Coherent Prompt Creation

(9:08) Closing Thoughts on Prompt Poet's Capabilities