"AI is revolutionizing how teams develop products. In this blog we'll introduce a set of prompts you can use to understand your users, prepare to interview real users, generate a product backlog, add acceptance criteria, and evaluate your own user stories. Throughout this blog, I'll use a consistent example so you can see how results from one prompt feed into the next. For our example, let's imagine our team is developing a new product for valet-attended parking garages. We'll validate our product by selling initially to independent parking garages such as at boutique hotels."
"Building a Persona It remains imperative for teams to understand a product's users and customers by interviewing, surveying, and observing them. A team can supplement these interactions by training an AI on what's been learned and then interacting with a user-proxy AI. Team members could, for example, ask their user-proxy AI questions such as: What do you think of this feature? How often would you use this feature? What could make this feature more useful? Which of these features would you find more useful? Would you be willing to pay for this feature? The general form of our prompt to create a persona is: Our product is [product description] Build me a persona of [ persona description]. List their hopes, concerns, emotional triggers, and decision criteria for choosing our product. Here's what I used for the parking valet app: Our company is developing software for valet-attended parking garages. To validate our product we will sell initially to independent operations such as boutique hotels. Build me a persona of the owner or manager of such a parking garage. List their hopes, concerns, emotional triggers, and decision criteria for choosing our product."
AI can accelerate product development by generating user personas, simulating user interviews, producing product backlogs, adding acceptance criteria, and evaluating user stories. Teams can train AI on existing research and use a user-proxy AI to ask feature-related questions about frequency, usefulness, and willingness to pay. A general prompt template can generate personas that list hopes, concerns, emotional triggers, and decision criteria. The provided example targets valet-attended parking garages sold to independent operations like boutique hotels and shows how outputs from one prompt feed into subsequent prompts for iterative product design.
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