lean-startup

The saved excerpt is a snapshot from when this skill was listed. The external source remains the complete and most current version.

---
name: lean-startup
description: '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", "test assumptions", "innovation accounting", "build-measure-learn", "minimum viable experiment", "should we pivot", "test a business idea cheaply", or "build the smallest version first". Also trigger when deciding what to include in a first version, measuring startup progress, or evaluating whether to change direction on a product bet. Covers innovation accounting and actionable metrics. For 5-day prototype testing, see design-sprint. For customer motivation analysis, see jobs-to-be-done.'
license: MIT
metadata:
  author: wondelai
  version: "1.4.0"
---

# Lean Startup Methodology

A systematic approach to building startups and launching new products that shortens development cycles and rapidly discovers whether a business model is viable.

## Core Principle

**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. Most startups fail not because they couldn't build what they planned, but because they built the wrong thing: treat every plan as a set of hypotheses to falsify, and spend effort to eliminate waste and accelerate **validated learning**, not to execute a fixed roadmap.

## Scoring

**Goal: 10/10.** Score a plan, experiment, or metric set by the five Quick Diagnostic rows—**1 point each** when the answer is yes, **2 points** when it is also backed by evidence on the Validation Ladder (Level 3+):

- **9-10:** every leap-of-faith assumption named and ranked by risk, the riskiest tested by a real MVP, actionable metrics defined, and explicit pivot criteria set before building.
- **5-6:** a hypothesis and some MVP exist, but metrics are vanity or pivot criteria are undefined—decisions can't be made from the data.
- **≤3:** waterfall thinking—building the full product first, asking customers what they want, or scaling before product/market fit.

State the current score and the lowest-scoring diagnostic row to fix next.

## The Build-Measure-Learn Loop

The fundamental cycle: **IDEAS → BUILD (product) → MEASURE (data) → LEARN (knowledge) → back to IDEAS.**

**Critical insight:** Plan the loop backward:
1. **What do we want to learn?** (hypothesis to test)
2. **How will we know if we learned it?** (metrics)
3. **What's the minimum we can build?** (MVP)

**Goal:** Minimize total time through the loop.

See [references/build-measure-learn.md](references/build-measure-learn.md) when planning an experiment—reverse-planning sequence, an experiment-design template, per-product-type loop examples, and the build/vanity-metric loop traps.

## Validated Learning

Learning what customers really want through experiments on real behavior—not feature requests, surveys, or focus groups (people mispredict their own behavior). Measure what customers *do*, not what they *say*, and run experiments that could falsify your assumptions. Vanity wins (downloads, signups without engagement) are not learning.

**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.

## Minimum Viable Product (MVP)

The version of a new product that allows maximum validated learning with the least effort. Not a prototype (technical feasibility), not a beta (quality), not a minimum marketable product—a learning vehicle, often embarrassingly small and low quality, a