Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", or "test assumptions". Covers innovation accounting and actionable metrics. For 5-day prototype testing, see design-sprint. For customer motivation analysis, see jobs-to-be-done. Trigger with 'lean', 'startup'.
From wondelai-lean-startupnpx claudepluginhub nickloveinvesting/nick-love-plugins --plugin wondelai-lean-startupThis skill is limited to using the following tools:
references/applications.mdreferences/assumptions.mdreferences/build-measure-learn.mdreferences/case-studies.mdreferences/five-whys.mdreferences/growth-engines.mdreferences/implementation.mdreferences/innovation-accounting.mdreferences/metrics.mdreferences/mvp-design.mdreferences/pivots.mdreferences/small-batches.mdGuides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Migrates code, prompts, and API calls from Claude Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, updating model strings on Anthropic, AWS, GCP, Azure platforms.
Details PluginEval's skill quality evaluation: 3 layers (static, LLM judge), 10 dimensions, rubrics, formulas, anti-patterns, badges. Use to interpret scores, improve triggering, calibrate thresholds.
A systematic approach to building startups and launching new products that shortens development cycles and rapidly discovers if a business model is viable.
Entrepreneurship is a form of management. Success doesn't require a perfect plan or brilliant insight—it requires a systematic process for testing assumptions, learning from customers, and iterating rapidly.
The foundation: Most startups fail not because they couldn't build what they planned, but because they built the wrong thing. The Lean Startup methodology applies scientific experimentation to eliminate waste and accelerate validated learning.
Goal: 10/10. When reviewing or creating product development plans, experiments, or metrics, rate them 0-10 based on adherence to Lean Startup principles. A 10/10 means full application of Build-Measure-Learn, validated learning, and evidence-based decisions; lower scores indicate waterfall thinking or waste. Always provide the current score and specific improvements needed to reach 10/10.
The fundamental cycle of Lean Startup:
IDEAS
↓
BUILD → Product
↓
MEASURE → Data
↓
LEARN → Knowledge
↓
(back to IDEAS)
Critical insight: The loop is actually backward. Start with what you want to learn, determine metrics that will inform that learning, then build the minimum product to collect those metrics.
Reverse planning:
Goal: Minimize total time through the loop.
See: references/build-measure-learn.md for detailed loop execution.
Definition: Learning what customers really want through validated experiments, not opinion or anecdotes.
Validated learning is not:
Validated learning is:
The Validation Ladder:
| Level | Evidence | Strength |
|---|---|---|
| 1 | "I think customers want this" | Weakest (opinion) |
| 2 | "Customers said they want this" | Weak (stated preference) |
| 3 | "Customers signed up for early access" | Medium (low commitment) |
| 4 | "Customers paid a deposit" | Strong (real commitment) |
| 5 | "Customers are actively using it" | Strongest (revealed preference) |
Target: Level 4-5 before building at scale.
Definition: The version of a new product that allows a team to collect the maximum amount of validated learning with the least effort.
MVP is not:
MVP is:
MVP Types:
| Type | What It Is | When to Use | Example |
|---|---|---|---|
| Concierge | Manual service pretending to be automated | Test if solution is valuable | Food on the Table (manual meal planning) |
| Wizard of Oz | Fake automation, manual backend | Test if automation is needed | Zappos (no inventory, bought shoes retail) |
| Smoke test | Landing page + signup, no product | Test demand before building | Dropbox video (explained concept, measured signups) |
| Single feature | One core feature only | Test which feature is most valuable | Twitter (just status updates) |
| Piecemeal | Combine existing tools | Test workflow before custom build | Groupon (WordPress + email) |
MVP Design Questions:
Common mistakes:
See: references/mvp-design.md for MVP types and design patterns.
Definition: The assumptions that, if wrong, will cause your business to fail.
Process:
Common leap-of-faith assumptions:
| Assumption Type | Question | Test Method |
|---|---|---|
| Value hypothesis | Do customers care about this problem? | Smoke test, concierge MVP |
| Growth hypothesis | How will customers discover us? | Channel tests, referral experiments |
| Retention hypothesis | Will customers come back? | Cohort analysis, engagement metrics |
| Monetization hypothesis | Will customers pay? | Pre-orders, pricing tests |
Example: Dropbox
Anti-pattern: Testing assumptions in order of ease rather than risk.
See: references/assumptions.md for assumption mapping frameworks.
Definition: Measuring progress when traditional accounting doesn't apply.
The problem with traditional metrics:
Innovation accounting framework:
Question: Where are we today?
Measure current reality, even if it's zero or embarrassing.
Metrics to establish:
Goal: Know your starting point precisely.
Question: What can we improve to move toward our goal?
Run experiments to improve baseline metrics.
Examples:
Goal: Systematically improve metrics through validated learning.
Question: Are we making sufficient progress, or do we need to change strategy?
Based on data, decide whether to continue or pivot.
Criteria:
Goal: Make evidence-based strategic decisions.
See: references/innovation-accounting.md for metric frameworks and dashboards.
Vanity metrics: Make you feel good but don't change behavior.
Actionable metrics: Drive decisions and clarify cause and effect.
| Vanity | Why It's Bad | Actionable Alternative |
|---|---|---|
| Total signups | Always goes up, no context | % signup → active (conversion rate) |
| Page views | Doesn't indicate value | Time on page, bounce rate |
| Total users | Includes inactive/churned | Active users (DAU, WAU, MAU) |
| Downloads | Doesn't mean usage | DAU/downloads (activation rate) |
| Revenue | Without context | Revenue per cohort, LTV/CAC |
Three characteristics of actionable metrics:
Example:
Cohort analysis: Group users by signup date and track behavior over time. Reveals if product is actually improving.
See: references/metrics.md for metric selection and tracking.
Pivot: A structured course correction designed to test a new hypothesis about the product, strategy, or engine of growth.
When to pivot:
When to persevere:
Pivot Types:
| Pivot Type | What Changes | Example |
|---|---|---|
| Zoom-in pivot | Single feature becomes the whole product | Instagram (photo filters from Burbn check-in app) |
| Zoom-out pivot | Product becomes a single feature | Flickr (photo-sharing from Game Neverending) |
| Customer segment | Same problem, different customer | Groupon (activism platform → local deals) |
| Customer need | Same customer, different problem | Potbelly Sandwich (antique store → sandwiches) |
| Platform | App → Platform or Platform → App | YouTube (dating site → video platform) |
| Business architecture | High margin, low volume ↔ Low margin, high volume | Salesforce (software → SaaS) |
| Value capture | Monetization model change | Android (paid → free + app revenue) |
| Engine of growth | Viral, sticky, or paid growth model | Facebook (viral within colleges → paid advertising) |
| Channel | How you reach customers | Salesforce (direct sales → self-service) |
| Technology | Different technology, same solution | Apple (Intel → ARM chips) |
Pivot cadence: Many successful startups pivot 1-5 times before finding product-market fit.
Anti-pattern: "Pivot" without validating that the new direction solves the core problem.
See: references/pivots.md for pivot decision frameworks and case studies.
Growth engine: How your startup acquires and retains customers sustainably.
Choose one engine to focus on:
Mechanism: High retention, low churn
Formula: Growth rate = New customer acquisition rate - Churn rate
Focus: Keep customers coming back
Metrics:
Examples: SaaS, subscription services, social networks
Strategy: Improve product until churn rate is low enough that natural growth exceeds churn.
Mechanism: Customers bring other customers
Formula: Viral coefficient = (% who invite) × (invites sent) × (% who join)
Focus: Viral coefficient > 1.0 = exponential growth
Metrics:
Examples: Dropbox, Hotmail, WhatsApp
Strategy: Build virality into the product. Must be > 1.0 to be self-sustaining.
Mechanism: Spend money to acquire customers
Formula: LTV (Lifetime Value) > CAC (Customer Acquisition Cost)
Focus: Unit economics that allow reinvestment
Metrics:
Examples: E-commerce, traditional businesses
Strategy: Optimize until each customer generates enough profit to acquire more customers.
Warning: Don't use multiple engines simultaneously. Pick one, optimize it, then consider adding others.
See: references/growth-engines.md for engine selection and optimization.
Purpose: Root cause analysis to prevent problems from recurring.
Process:
Example:
Problem: Website went down
Proportional investments:
Anti-pattern: Stop at level 1 (just fix the symptom).
See: references/five-whys.md for facilitation guides.
Principle: Work in small batches to accelerate learning and reduce waste.
Why small batches win:
Examples:
| Large Batch | Small Batch |
|---|---|
| Build entire product, then launch | Launch landing page, then build |
| Release quarterly | Release weekly or daily |
| Plan 12-month roadmap | Plan 6-week cycles |
| Big bang rewrite | Incremental refactoring |
Continuous deployment: The ultimate small batch = deploy every code commit.
Benefits:
See: references/small-batches.md for implementation patterns.
For different contexts:
See: references/applications.md for context-specific guides.
| Mistake | Why It Fails | Fix |
|---|---|---|
| Building too much | Waste before validation | Test with smoke test or concierge first |
| Asking customers | People don't know/mispredict | Observe behavior, not opinions |
| Vanity metrics | Feel-good numbers, no decisions | Track cohorts, conversion, retention |
| No hypothesis | Can't learn if you don't predict | Write hypothesis before each experiment |
| Pivot too slow | Waste runway | Set clear pivot criteria upfront |
| Skip innovation accounting | Can't tell if you're improving | Establish baseline, measure tuning efforts |
Audit any product development plan:
| Question | If No | Action |
|---|---|---|
| What's the riskiest assumption? | You're building on shaky ground | Map leap-of-faith assumptions |
| How will you test it? | You're guessing | Design MVP to test assumption |
| What metric will validate/invalidate? | You won't learn | Define actionable metrics |
| Can you test with less than this? | You're over-building | Shrink MVP further |
| What will you do if the experiment fails? | No pivot criteria | Define pivot triggers upfront |
Phase 1: Problem/Solution Fit
Phase 2: Product/Market Fit
Phase 3: Scale
Anti-pattern: Skipping Phase 1-2 and jumping straight to scale.
This skill is based on Eric Ries' Lean Startup methodology. For the complete framework, research, and case studies:
Eric Ries is an entrepreneur and author best known for developing the Lean Startup methodology. He was co-founder and CTO of IMVU, where he pioneered continuous deployment and customer development practices that became the foundation of Lean Startup. The Lean Startup has been translated into over 30 languages and has influenced startup culture worldwide. Ries is also the creator of the Long-Term Stock Exchange (LTSE), a new stock exchange designed for companies focused on long-term value creation.
Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn.
See testing implementation details for output format specifications.
| Error | Cause | Resolution |
|---|---|---|
| Authentication failure | Invalid or expired credentials | Refresh tokens or re-authenticate with testing |
| Configuration conflict | Incompatible settings detected | Review and resolve conflicting parameters |
| Resource not found | Referenced resource missing | Verify resource exists and permissions are correct |
Basic usage: Apply lean startup to a standard project setup with default configuration options.
Advanced scenario: Customize lean startup for production environments with multiple constraints and team-specific requirements.