Module 3 of 4Lesson 3 of 4~10 min
Preparing and critiquing an interview guide
A poorly built interview guide pushes users to say what you wanted to hear, and skews discovery before the first call. This lesson teaches you to have AI draft your guide from what you are trying to validate, then have it review the draft critically to catch the questions that bias the answers.
Lesson objective
By the end of this lesson, you will be able to produce a discovery interview guide from your hypotheses, then have it critiqued to remove leading, closed or hypothetical questions.
Topics covered
- interview guide
- discovery interview
- user interview
- leading questions
- prompting for PMs
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
- Preparing and critiquing an interview guide (this lesson)
- 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