Module 3 of 4Lesson 2 of 4~12 min
Building a persona grounded in verbatims
Asking AI for a persona without giving it any material produces a believable but invented portrait that can steer a whole team the wrong way. This lesson shows how to anchor a persona in what your users actually said, and how to draw out the assumptions to test before you use it to make decisions.
Lesson objective
By the end of this lesson, you will be able to have a persona structured from real verbatims, separating what is observed from what is assumed, and list the hypotheses to validate in interviews.
Topics covered
- user persona
- AI-generated persona
- customer verbatims
- user research
- product assumptions
Where it fits
Prompting on your PM deliverables
How do you apply these methods to discovery and delivery without losing fidelity to the data?
Lessons in this module
- Turning customer feedback into opportunities
- Building a persona grounded in verbatims (this lesson)
- Preparing and critiquing an interview guide
- Writing and challenging user stories
What you will learn in the course
This lesson is part of the course Prompting for Product Managers: delegate, describe, verify
- Decide, for a task in your product cycle, whether to hand it to AI, in which mode (automation, augmentation, agent), and what you keep.
- Explain how an LLM behaves (prediction, dated knowledge, working memory, instruction following) to anticipate its mistakes and pick the right fix.
- Write a prompt that describes the deliverable, the process and the quality bar, with context, delimited data and examples when needed.
- Evaluate an AI output (content, process, behavior) against explicit criteria, then improve it through targeted iterations.
- Produce PM deliverables with AI (feedback synthesis, persona, interview guide, user stories) from real data, and check that they are faithful to it.
- Configure standing instructions and a dedicated assistant for a recurring task, test it on real cases, and decide when to move to an agent.
- Apply diligence rules (shared data, transparency, accountability) before using or circulating work produced with AI.
Related courses
- Build reliable Claude Skills for your product workAdvanced · ~2 hr 30 min
- Choosing and using AI tools at workAll levels · ~1 hr 40 min
- Understand what LLMs do well, and where they failAll levels · ~2 hr