product-sense-interview-answer

Este extracto es una copia guardada durante la revisión. La fuente externa contiene la versión completa y actual.

---
name: product-sense-interview-answer
argument-hint: "[interview prompt]"
description: Structure a spoken PM product-sense answer with assumptions, segmentation, pain-point prioritization, and MVP tradeoffs. Use when practicing design, improve, or build-next interview questions.
intent: >-
  Coach PM candidates through open-ended product-sense interviews using a repeatable
  six-part answer spine: clarify, rationale, goal, segmentation, pain points,
  and solution choice. Use this to practice product design and product improvement
  questions, avoid solution-first answers, and produce responses that sound
  thoughtful out loud rather than over-scripted on the page.
type: component
theme: career-leadership
best_for:
  - "Practicing product design and product improvement interview questions"
  - "Coaching candidates who jump to solutions too quickly"
  - "Turning messy ideation into a crisp spoken interview answer"
scenarios:
  - "How would you improve YouTube?"
  - "Design a product for travelers with flight anxiety"
  - "What would you build next for DoorDash?"
estimated_time: "20-30 min"
---

## Purpose

Help PM candidates and interview coaches structure product-sense answers that sound strong out loud, not just on paper. Use this when practicing prompts like "How would you improve X?", "Design a product for Y", or "What would you build next for Z?"

This is not a memorize-and-recite script. It is a reasoning scaffold that prevents solution-jumping, forces real prioritization, and leaves the interviewer with a clean story they can follow.

## Input

**Works best with:** The interview prompt you're practicing (e.g., 'How would you improve X?', 'Design a product for Y').
**Also useful:** The company/role you're interviewing for and how much time the answer gets.

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 asks for the prompt, then walks the reasoning scaffold with you out loud.

**Example invocation:** `Practice this: 'How would you improve Google Maps for commuters?' — 25-minute answer, L5 PM loop.`

## Key Concepts

### What Product Sense Interviews Actually Test

Strong product-sense answers do more than generate ideas. Interviewers are usually testing whether you can:

- Clarify ambiguous prompts without getting stuck
- Tie user value to market or business logic
- Segment thoughtfully instead of talking about "everyone"
- Prioritize one pain point instead of describing ten equally
- Make tradeoffs explicit when choosing an MVP
- Communicate clearly under time pressure

### The Six-Part Answer Spine

1. **Clarify** - Reduce ambiguity, define scope, and state assumptions.
2. **Rationale** - Explain why the problem matters now for the market and, if relevant, the company.
3. **Product Goal** - Define the user outcome you want to create before talking about features.
4. **Segmentation** - Choose who to serve first and show why that target wins.
5. **Pain Points** - Map the journey, name the main frictions, and pick the one worth solving first.
6. **Solution** - Generate distinct options, compare them, and commit to one MVP with clear exclusions.

The order matters. If you skip from prompt to feature ideas, your answer sounds clever but ungrounded. If you establish the user, goal, and pain first, your solution feels earned.

### Why This Works

- **Prevents feature dumping:** You do not start with ideas before you know whose problem you are solving.
- **Balances user and business thinking:** The answer includes demand, company fit, and strategic tradeoffs rather than pure UX talk.
- **Creates a speakable narrative:** Each section becomes a short checkpoint the interviewer can follow.
- **Forces prioritization:** Reach, impact, fit, frequency, severity, and effort all surface tradeoffs instead of hand-wav