Summary

In this chapter, we looked at the emerging field of prompt engineering. You gained an understanding of the core components of a successful prompt. We introduced the importance of clearly defining roles, audience, input, and output data in prompts to tailor the model’s responses to specific tasks or user groups.

With a heavy emphasis on the iterative nature of prompt engineering, we saw that it’s important to have a solid prompt engineering strategy. We hopefully covered some solid details on what to look for or consider during prompt engineering.

We also looked at some prompt engineering techniques and how to use these in real-world examples specifically tailored to the world of conversational AI.

Through iterative development and testing across multiple data examples, you were encouraged to refine prompts to achieve better, more consistent outcomes from ChatGPT, so you could enhance the model’s utility in various applications.

So, you should...