Lean Startup Workflow¶

Build-Measure-Learn cycle for rapid validation

The Lean Startup methodology emphasizes rapid iteration through the Build-Measure-Learn feedback loop. This workflow maps PM-Skills to that cycle, enabling quick hypothesis validation and data-driven pivoting.

Workflow Metadata¶

Field	Value
Workflow	Lean Startup
Command	No dedicated command yet -- reference file directly
Skills	`define-hypothesis` → `develop-solution-brief` → `measure-experiment-design` → `measure-experiment-results` → `iterate-pivot-decision`
Phases Covered	Define, Develop, Measure, Iterate
Estimated Duration	1-2 week cycles
Prerequisite Inputs	A product idea or assumption to validate
Final Output	Validated learning with pivot/persevere decision

Overview¶

The Lean Startup cycle focuses on minimizing time through the feedback loop:

              ┌─────────────┐
              │             │
              │    LEARN    │
              │             │
              └──────┬──────┘
                     │
         ┌───────────┴───────────┐
         │                       │
         ▼                       │
   ┌─────────────┐               │
   │             │               │
   │    BUILD    │───────────────┤
   │             │               │
   └─────────────┘               │
         │                       │
         ▼                       │
   ┌─────────────┐               │
   │             │               │
   │   MEASURE   │───────────────┘
   │             │
   └─────────────┘

graph LR
    A["hypothesis"] --> B["solution-brief"]
    B --> C["experiment-design"]
    C --> D["experiment-results"]
    D --> E["pivot-decision"]
    E -->|"iterate"| A

When to Use¶

Use the Lean Startup workflow when:

Testing new ideas or markets — high uncertainty about product-market fit
Resource-constrained — need to validate before major investment
Speed is critical — competitive pressure requires rapid iteration
Building MVPs — want to learn quickly with minimum viable product
Considering a pivot — need data to inform strategic direction

Phase 1: Build¶

Goal: Create the minimum needed to test your hypothesis

The Build phase isn't about building a complete product—it's about building just enough to learn.

Core Skills¶

Skill	Purpose
`define-hypothesis`	Define what you believe and how to test it
`develop-solution-brief`	Articulate the MVP approach
`develop-spike-summary`	Time-boxed feasibility validation

Supporting Skills¶

Skill	When to Use
`deliver-prd`	Lightweight spec for MVP scope
`deliver-user-stories`	Break MVP into implementable stories
`develop-adr`	Document critical technical choices

Key Outputs¶

Clear, testable hypothesis
MVP solution brief
Minimal feature set to test hypothesis
Instrumentation plan (built into MVP)

Build Phase Checklist¶

Hypothesis is specific and falsifiable
MVP scope is truly minimal
Success metrics are defined before building
Instrumentation is planned, not an afterthought
Team can build this in days/weeks, not months

Phase 2: Measure¶

Goal: Collect data to validate or invalidate your hypothesis

Measurement must be designed upfront, not retrofitted. The goal is to generate validated learning.

Core Skills¶

Skill	Purpose
`measure-experiment-design`	Design rigorous experiments
`measure-instrumentation-spec`	Define what to track
`measure-dashboard-requirements`	Build visibility into metrics

Supporting Skills¶

Skill	When to Use
`discover-interview-synthesis`	Qualitative validation alongside quantitative
`deliver-edge-cases`	Ensure measurement isn't corrupted by edge cases

Key Outputs¶

Experiment running with proper instrumentation
Real-time or daily metrics visibility
Qualitative feedback from users
Statistical analysis of results

Measure Phase Checklist¶

Experiment has sufficient sample size
Control and treatment groups are properly defined
Guardrail metrics are monitored
Collecting qualitative alongside quantitative data
Clear success/failure criteria defined upfront

Phase 3: Learn¶

Goal: Extract insights and make decisions

Learning is the unit of progress in Lean Startup. Every cycle should produce validated learning, whether positive or negative.

Core Skills¶

Skill	Purpose
`measure-experiment-results`	Document what happened and why
`iterate-pivot-decision`	Framework for strategic pivots
`iterate-lessons-log`	Capture learnings for future

Supporting Skills¶

Skill	When to Use
`iterate-retrospective`	Team reflection on process
`define-problem-statement`	Reframe problem based on learnings

Key Outputs¶

Documented experiment results
Clear decision: pivot, persevere, or iterate
Lessons captured for organizational memory
Next hypothesis (if continuing)

Learn Phase Checklist¶

Results honestly documented (including failures)
Insights extracted from data, not just reported
Clear decision made and communicated
Learnings are searchable for future teams
Next iteration planned based on evidence

Rapid Cycle: The Minimum Loop¶

For maximum speed, use this minimal skill set:

HYPOTHESIS → BUILD MVP → EXPERIMENT → RESULTS → DECISION
    │            │            │           │          │
    ▼            ▼            ▼           ▼          ▼
hypothesis   solution-   experiment- experiment- pivot-
   .md        brief.md    design.md   results.md  decision.md

5-Skill Lean Cycle¶

define-hypothesis — State what you believe
develop-solution-brief — Define MVP approach
measure-experiment-design — Plan measurement
measure-experiment-results — Document learnings
iterate-pivot-decision — Decide next step

This core loop can run in 1-2 week cycles.

Pivot Types¶

When experiment results suggest a change is needed, consider these pivot types:

Pivot Type	Description	PM-Skills Support
Zoom-in	Single feature becomes the product	problem-statement, prd
Zoom-out	Product becomes a feature	competitive-analysis, solution-brief
Customer Segment	Same product, different customer	stakeholder-summary, interview-synthesis
Customer Need	Same customer, different problem	jtbd-canvas, opportunity-tree
Platform	Application to platform or vice versa	adr, design-rationale
Value Capture	Change monetization model	hypothesis, experiment-design
Engine of Growth	Viral ↔ Paid ↔ Sticky	measure-instrumentation-spec, measure-dashboard-requirements
Channel	Change distribution	competitive-analysis
Technology	New technology, same solution	spike-summary, adr

Use iterate-pivot-decision to document any pivot.

Metrics That Matter¶

Vanity vs. Actionable Metrics¶

Avoid vanity metrics: - Total registered users - Page views - Downloads

Focus on actionable metrics: - Activation rate (% who complete key action) - Retention (% who return) - Referral rate (% who invite others) - Revenue per user

Innovation Accounting¶

Track progress through:

Baseline — Where you are today
Target — Where you need to be
Learning velocity — How fast you're moving toward target

Use measure-dashboard-requirements to specify these metrics.

Example Cycle¶

Week 1: Build¶

Hypothesis (from hypothesis.md):

We believe that adding a 3-step onboarding wizard for new users will increase Day-7 retention from 15% to 25% because users will understand the core value faster.

Solution Brief (from solution-brief.md): - Build simple 3-step wizard - Focus on top 3 features - Track step completion

Week 2: Measure¶

Experiment (from experiment-design.md): - 50/50 split test - 1,000 users per variant - 7-day observation window - Primary metric: Day-7 retention

Instrumentation (from instrumentation-spec.md): - onboarding_started - onboarding_step_completed (step_number) - onboarding_completed - onboarding_abandoned

Week 3: Learn¶

Results (from experiment-results.md): - Treatment: 22% Day-7 retention - Control: 16% Day-7 retention - +6pp lift (p < 0.05) - Did not hit 25% target but significant improvement

Decision (from iterate-pivot-decision/SKILL.md): - Persevere with iteration - Next hypothesis: Adding personalization to wizard will close remaining gap - Run next experiment in Week 4

Comparison with Other Workflows¶

Aspect	Lean Startup	Triple Diamond	Feature Kickoff
Speed	Fast (1-2 week cycles)	Comprehensive (weeks-months)	Medium (days-weeks)
Uncertainty	High	Medium-High	Low
Research depth	Minimal upfront	Extensive	None
Best for	New products, pivots	Major initiatives	Known improvements

Quality Checklist¶

Before considering this workflow complete, verify:

Hypothesis is falsifiable with a specific metric target
MVP scope is truly minimal (can build in days/weeks)
Experiment has defined sample size and duration
Results include both quantitative data and qualitative signals
Pivot/persevere decision is based on evidence, not opinion

References¶

Eric Ries, The Lean Startup (2011)
Steve Blank, The Four Steps to the Epiphany (2003)
Ash Maurya, Running Lean (2012)

Part of PM-Skills — Open source Product Management skills for AI agents

Lean Startup Workflow¶

Workflow Metadata¶

Overview¶

When to Use¶

Phase 1: Build¶

Core Skills¶

Supporting Skills¶

Key Outputs¶

Build Phase Checklist¶

Phase 2: Measure¶

Core Skills¶

Supporting Skills¶

Key Outputs¶

Measure Phase Checklist¶

Phase 3: Learn¶

Core Skills¶

Supporting Skills¶

Key Outputs¶

Learn Phase Checklist¶

Rapid Cycle: The Minimum Loop¶

5-Skill Lean Cycle¶

Pivot Types¶

Metrics That Matter¶

Vanity vs. Actionable Metrics¶

Innovation Accounting¶

Example Cycle¶

Week 1: Build¶

Week 2: Measure¶

Week 3: Learn¶

Comparison with Other Workflows¶

Quality Checklist¶

See Also¶

References¶