Summary

Developing user stories can sometimes be easy. If requirements are apparent, straightforward, and ideally suited to ChatGPT, write those up and get to work. We also realize that some things need to be clarified. Use research, discussions with internal stakeholders, and your keen mind for problem-solving to find LLM opportunities.

Start thinking about the opportunities best suited for a generative solution in your business and explain why some problems are unsuitable for ChatGPT.

Hopefully, this chapter will create excitement around introducing our next topic for scoring and prioritizing stories. We will jump into that next since we only briefly explained User Needs Scoring. This will allow us to prioritize the backlog features and use cases we have explored up to this point. It will also be helpful to know this when we get a ChatGPT solution up and running and want to test or monitor it.

Once we have a solution, we can reuse some of these skills to verify what we did...