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ux-lean-startup

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Apply Lean Startup methodology — Build-Measure-Learn loop, MVP, validated learning, and pivot decisions. Use this skill when the user is launching a new product or startup and needs to validate ideas quickly, design an MVP, decide whether to pivot or persevere, or reduce wasted effort on unvalidated assumptions — even if they say 'should we build this', 'how do we test this idea', 'when should we pivot', or 'we're burning cash with no traction'.

QUICK START

How to use this skill

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  1. Open your project in Codex.
  2. Copy the prompt below and paste it into your agent.
  3. Review the proposed files and risks before you approve installation.
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Source SKILL.md: https://github.com/asgard-ai-platform/skills/blob/HEAD/ux-lean-startup/SKILL.md

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Lean Startup

Framework

IRON LAW: Validate Before You Build

Every product decision is a hypothesis. The most expensive way to test
a hypothesis is to build the full product. The cheapest is to test the
riskiest assumption FIRST with the minimum possible effort.

"Build it and they will come" is not a strategy — it's a prayer.

Build-Measure-Learn Loop

  1. Build: Create the smallest possible thing that tests your riskiest assumption (MVP)
  2. Measure: Collect data on whether the assumption holds (actionable metrics, not vanity metrics)
  3. Learn: Did the data validate or invalidate the assumption?
    • Validated → double down, test next assumption
    • Invalidated → pivot (change strategy) or persevere (refine execution)

MVP Types (Ordered by Effort)

MVP TypeEffortWhat It Tests
Landing pageHours"Do people want this?" (signup conversion)
Explainer videoDays"Do people understand and desire this?"
ConciergeDays"Can we deliver value manually?" (do it by hand for 10 customers)
Wizard of OzWeeks"Does the full experience work?" (fake the backend, real frontend)
Single-featureWeeks"Does this core feature solve the problem?"
Functional prototypeMonths"Can we build this and do users adopt it?"

Vanity Metrics vs Actionable Metrics

Vanity (avoid)Actionable (use)
Total signupsActivation rate (% who complete onboarding)
Page viewsConversion rate (% who take desired action)
DownloadsRetention (% who return after 7/30 days)
Total revenueRevenue per user, LTV:CAC

Pivot Triggers

Consider pivoting when:

  • Metrics flat after 2-3 iteration cycles
  • Customer feedback consistently requests something different than what you're building
  • Unit economics don't improve with scale
  • The team's enthusiasm has shifted to a different problem

Pivot Types

PivotWhat Changes
Customer segmentSame product, different target
ProblemSame customer, different problem to solve
SolutionSame problem, different approach
ChannelSame product, different distribution method
Revenue modelSame product, different pricing/business model
PlatformSingle product → platform (or vice versa)

Output Format

# Lean Startup Plan: {Product/Idea}

## Riskiest Assumption
{The one thing that must be true for this to work}

## MVP Design
- Type: {landing page / concierge / etc.}
- What it tests: {specific assumption}
- Build time: {hours/days/weeks}
- Success metric: {specific threshold}

## Build-Measure-Learn Plan
| Cycle | Build | Measure | Learn |
|-------|-------|---------|-------|
| 1 | {MVP} | {metric + threshold} | Validate/Pivot? |
| 2 | {iteration} | {metric} | ... |

## Pivot/Persevere Criteria
- Persevere if: {specific metric threshold met}
- Pivot if: {specific metric threshold not met after N cycles}

Gotchas

  • MVP ≠ crappy product: Minimum Viable Product is the minimum needed to LEARN, not the minimum you can get away with shipping. Quality still matters where it affects the test.
  • "Build" doesn't always mean code: A landing page, a spreadsheet, a manual service — anything that tests the assumption counts.
  • Pivot is not failure: Pivoting means you learned something valuable. The failure is not pivoting when the data says you should.
  • Lean Startup is for uncertainty: If you're building a well-understood product in a known market, waterfall may be fine. Lean Startup is for when you don't know what to build or for whom.

References

  • For experiment design templates, see references/experiment-templates.md