In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss using Agile principles for prompt engineering – agile prompt engineering. You will learn the importance of process development and project management when working with large language models (LLMs) like ChatGPT. Discover how to use the 5 P’s framework and the RACE framework to create effective prompts and streamline your workflow. Finally, understand why documentation and planning are essential for scaling your use of prompts across your organization.

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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

In this week’s In-Ear Insights, we’re in part three of our agile prompt engineering/agile AI series.

In episode one, we covered what Agile is; in part two, we covered the basics of prompt engineering, the RACE framework, and where the opportunities are to use generative AI.

Today, let’s talk about agile and prompt engineering—taking the peanut butter and jelly and putting them together—or I guess the peanut butter and chocolate, depending on how old you are.

Katie, how do we put these two great things together?

Personally, I could go for peanut butter and fluff.

I do like peanut butter and chocolate, though.

But I think the point is, how can we mix together Agile methodology and prompt engineering? The answer will shock you: requirements gathering and the five Ps.

You cannot escape it; you cannot get away from doing documentation.

I’m not even sorry.

Prompt engineering, at its core, is a form of development, and development—software development—lends itself to Agile methodology.

That’s why Agile methodology came about.

So the question is, what is the prompt engineering lifecycle? Similar to the development lifecycle? And where does Agile fit into it? First things first, what the heck are you doing? What are you trying to accomplish? And that’s where the five P framework comes in.

The five Ps are purpose, people, process, platform, and performance.

Purpose: What is the question you’re trying to answer? People: Who’s involved? Who’s going to be impacted by this? Process: How are you doing the thing? Platform: What tools do you need? And performance: What is your outcome? Chris, I don’t know if you have it handy, but I’ve sta