Define · Create · Analysis & Finance
MVP and the test that proves it
The smallest feature set that tests your riskiest assumption (built for your first few users), an explicit cut list, and a single pass/fail test card with a numeric threshold.
You receive: A JSON object { problem, riskiest_assumption, minimum_feature_set[], cut_list[], feature_rationale[], fidelity, test_card{hypothesis,simplest_test,pass_threshold} } checked so the kept and cut sets are disjoint, every kept feature is justified, and the test carries a number.
Part of Validate Demand
Example
A sample of what this play produces. Your result is generated for your inputs.
Problem
Founders lose the hours AI was meant to save because every task needs an expert prompt, freshly re-explained context, and hand-carried output that goes stale.
Riskiest assumption
Founders will pick a ready-made play with their facts pre-filled instead of opening a blank chat, and accept the structured result it returns.
Minimum feature set
- A workspace that stores a venture's core facts once
- A catalog of ten ready-made plays whose intakes pre-fill from those facts
- A structured result page that saves each accepted deliverable back into the workspace
Cut list
- Broad catalog coverage: ten plays only at launch
- Third-party operators, ratings, and marketplace matching
- Automated payments, escrow, and payouts
- Composition between deliverables and multi-workspace support
Feature rationale
| Feature | Problem link |
|---|---|
| A workspace that stores a venture's core facts once | removes the re-explaining tax that makes every AI session start from zero |
| A catalog of ten ready-made plays whose intakes pre-fill from those facts | replaces the expert prompt with a pick, the core behavior change being tested |
| A structured result page that saves each accepted deliverable back into the workspace | keeps results current and reusable instead of stale in a chat thread |
Fidelity
low
Test card
- Hypothesis
- Founders choose picking a play over writing a prompt when their facts are already in place
- Insight sought
- whether pre-filled, ready-made work, not raw model access, drives adoption and repeat use
- Simplest test
- onboard 20 founders, seed each workspace with their facts, and measure who runs a second play within 14 days
- Pass threshold
- at least 60 percent of the 20 founders run a second play within 14 days
- Medium
- concierge run with real founders
Opens soon
STUD opens runs for everyone soon, on every play at once.
Get early access to STUD the day it goes live.