Yggdrasil
MCP ServersMCP 伺服器 SKILLs技能 PlugIns解決方案 Asgard AI SolutionAsgard AI 方案 Submit Listing申請上架 GitHub
L

Lean Startup 精實創業

Released已發布
methodology methodology

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'.

使用者體驗技能:Lean Startup 分析與應用。

View on GitHub在 GitHub 查看

Assumptions前提假設

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

Methodology 方法論

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 Type Effort What It Tests
Landing page Hours "Do people want this?" (signup conversion)
Explainer video Days "Do people understand and desire this?"
Concierge Days "Can we deliver value manually?" (do it by hand for 10 customers)
Wizard of Oz Weeks "Does the full experience work?" (fake the backend, real frontend)
Single-feature Weeks "Does this core feature solve the problem?"
Functional prototype Months "Can we build this and do users adopt it?"

Vanity Metrics vs Actionable Metrics

Vanity (avoid) Actionable (use)
Total signups Activation rate (% who complete onboarding)
Page views Conversion rate (% who take desired action)
Downloads Retention (% who return after 7/30 days)
Total revenue Revenue 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

Pivot What Changes
Customer segment Same product, different target
Problem Same customer, different problem to solve
Solution Same problem, different approach
Channel Same product, different distribution method
Revenue model Same product, different pricing/business model
Platform Single product → platform (or vice versa)

Output Format輸出格式

# Lean Startup Plan: {Product/Idea}

Gotchas注意事項

  • 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參考資料

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

Tags標籤

productlean-startupmvpvalidation