Agent skill · research science · deanpeters
discovery-interview-prep
Plan customer discovery interviews with the right goal, segment, constraints, and method. Use when preparing interviews for problem validation, churn research, or new product ideas.
Why this skill is useful
Provides a structured framework for conducting customer discovery interviews that the AI wouldn't generate reliably on its own.
What it needs
About 11k tokens when loaded. Last updated 2026-07-17. 6,302 stars on the source repository.
What this skill does
Purpose Guide product managers through preparing for customer discovery interviews by asking adaptive questions about research goals, customer segments, constraints, and methodologies. Use this to design effective interview plans, craft targeted questions, avoid common biases, and maximize learning from limited customer access—ensuring discovery interviews yield actionable insights rather than confirmation bias or surface-level feedback. This is not a script generator—it's a strategic prep process that outputs a tailored interview plan with methodology, question framework, and success criteria. Input Works best with: Your research goal — what you need to learn from customers. Also useful: Customer segment, access constraints (how many interviews, by when), and any hypotheses you're carrying in. Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re-ask. Arriving empty-handed? That works too. The skill opens by asking your primary goal for the interviews, then narrows with follow-ups. Example invocation: Prep interviews to understand why enterprise customers churn after 6 months — I can get 5 interviews in 2 weeks. Key Concepts The Discovery Interview Prep Flow An interactive process that: 1. Gathers product/problem context (marketing materials, assumptions) 2. Defines research goals (what you're trying to learn) 3. Identifies target customer segment and access constraints 4. Recommends interview methodology (Jobs-to-be-Done, problem validation, switch interviews, etc.) 5. Generates interview framework with questions, biases to avoid, and success metrics Why This Works Goal-driven: Aligns interview approach to what you need to learn Adaptive: Adjusts methodology based on product stage (idea vs. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills deanpeters/discovery-interview-prep