# Seven days of evidence story

> One week remains before the investor meeting. The team wants to finish an AI interview-analysis product, but no one knows whether customers will pay. Gather…

- Canonical: https://learning.reopt.ai/en/stories/seven-day-mvp
- Language: en
- HTML: https://learning.reopt.ai/en/stories/seven-day-mvp

---

[Stories](/en/stories)
Intermediate Agentic MVP Product experiment Market validation

# Seven days of evidence

Will you build it, or learn from it?

![미니어처 제품 실험실에서 시장 증거와 다음 실험 경로를 살피는 제품 리드](/images/stories/seven-day-mvp-detail.png)

## Story

One week remains before the investor meeting. The team wants to finish an AI interview-analysis product, but no one knows whether customers will pay. Gather evidence strong enough to guide the next decision without spending the team’s trust and runway.
Protagonist A product lead responsible for product, development speed, market evidence, and quality risk in an early AI SaaS team.

## Episode

- [1 What will we test? Turn a crowded backlog into one falsifiable belief. 70 XP 8 min Continue](/en/stories/seven-day-mvp/episodes/sdm-ep1)
- Launch and decide Complete the previous episode to unlock.

- Price as a question Complete the previous episode to unlock.

- Traces of use Complete the previous episode to unlock.

- The cost of speed Complete the previous episode to unlock.

- The evidence decides Complete the previous episode to unlock.

## Brand and business dashboard

The story begins with these values

- Market evidence 30

Strength of behavior and payment signals
- Learning speed 55

How quickly the next decision becomes possible
- Customer trust 65

Confidence in quality and accountability
- Team runway 50

Remaining time, energy, and focus

## What you'll learn

- How to turn assumptions into falsifiable experiments
- Why usage, payment, and trust are different kinds of evidence
- How to make a Go, Pivot, or Kill decision under a fixed deadline

[Start story](/en/stories/seven-day-mvp/episodes/sdm-ep1)

---

Site guide for agents: https://learning.reopt.ai/llms.txt · Sitemap: https://learning.reopt.ai/sitemap.xml · Contact: https://learning.reopt.ai/contact