Lean UxCAUTION

Wondel.ai Agent Skills — Business, Marketing, UX & Coding Frameworks from Bestselling Books. 50 skills + 12 guided journeys for Claude Code, Codex, Cursor & other agentskills.io agents.

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: lean-ux
description: 'Apply lean thinking to UX: hypothesis-driven design, collaborative sketching, and rapid experiments instead of heavy deliverables. Use when the user mentions "Lean UX", "design hypothesis", "outcome over output", "design studio method", "assumption mapping", "lightweight research", "too much design documentation", or "get the team designing together". Also trigger when reducing design-documentation overhead, getting cross-functional teams to co-design, or running fast usability experiments. Covers hypothesis statements, MVPs for UX, and cross-functional collaboration. For Build-Measure-Learn, see lean-startup. For usability audits, see ux-heuristics.'
license: MIT
metadata:
  author: wondelai
  version: "1.4.0"
---

# Lean UX Framework

A practice-driven approach to UX that replaces heavy deliverables with rapid experimentation, cross-functional collaboration, and continuous learning. Lean UX shifts the question from "What should we design?" to "What do we need to learn?"

## Core Principle

**Outcomes over outputs.** The value of a design is measured not by the fidelity of the deliverable but by the change in user behavior it produces.

**The foundation:** Traditional UX waterfalls requirements into wireframes, mockups, specs, and code—losing context and hiding untested assumptions at every handoff. Lean UX compresses the distance between idea and evidence: declare assumptions, form hypotheses, run the smallest possible experiment, and let real user behavior settle the argument. Shared understanding replaces documentation; learning velocity replaces pixel perfection.

## Scoring

**Goal: 10/10.** Score a UX process, design plan, or team workflow by the eight-row Quick Diagnostic below: award ~1.25 points per row answered "yes" (8 yeses = 10). Bands:

- **9-10** — assumptions declared, hypotheses with pre-committed success criteria, lowest-fidelity experiments, whole-team design, weekly research, outcome (not output) metrics, dual-track agile, and a recently invalidated hypothesis on the books.
- **5-6** — hypotheses exist but criteria are vague or fidelity is over-invested; design and research still partly siloed.
- **<=3** — heavy deliverables, untested assumptions, output-counting, no experiment log.

Always state the current score, the diagnostic rows that failed, and the specific fix for each.

## Framework

### 1. Declaring Assumptions

**Core concept:** Every design starts with assumptions. Lean UX makes them explicit so they can be prioritized and tested, rather than baked invisibly into specifications.

**Why it works:** Unspoken assumptions mean teams build on shaky ground and discover problems only after launch; surfacing them early focuses energy on the riskiest ones and reduces the cost of being wrong.

**Key insights:**
- Business assumptions define what must be true for the business (revenue model, market size, willingness to pay); user assumptions define who users are and how they behave
- Prioritize on two axes: risk (how damaging if wrong) and uncertainty (how little we know)
- Test high-risk, high-uncertainty assumptions first
- Write assumptions collaboratively as a team, not in isolation

**Product applications:**

| Context | Application | Example |
|---------|-------------|---------|
| **New feature kick-off** | Assumption mapping workshop | "We assume users want to share reports with teammates" |
| **Roadmap planning** | Rank features by assumption risk | Prioritize features whose success depends on untested beliefs |
| **Stakeholder alignment** | Expose hidden assumptions across roles | PM assumes pricing works; engineer assumes scale; designer assumes flow |

**Ethical boundary:** Assumptions must be honest assessments, not post-hoc justifications—if leadership has already committed to a direction, acknowledge the constraint rather than pretending it's open to falsification.

See [references/hypothesis-canvas.md](references/hypothesis-canvas.md) when running an assumption workshop or writing a hypothesis — the risk/uncertainty prioritization matrix, business-vs-user assumption split, and fillable hypothesis and sub-hypothesis templates.

### 2. Hypothesis Statements

**Core concept:** A hypothesis translates an assumption into a testable prediction, linking a proposed change to a measurable outcome for a specific user segment.

**Why it works:** Hypotheses force precision—instead of "make onboarding better," the team commits to a prediction that can be proven or disproven, which prevents scope creep and makes the learn step unambiguous.

**Key insights:**
- Standard format: "We believe [outcome] will happen if [persona] achieves [action] with [feature]"
- Every hypothesis specifies persona, action, outcome, and measurable signal
- Sub-hypotheses break a large bet into independently testable parts
- Agree on what "validated" and "invalidated" look like before running the experiment

**Product applications:**

| Context | Application | Example |
|---------|-------------|---------|
| **Feature design** | Write hypothesis before wireframing | "We believe trial-to-paid conversion will rise 10% if new users complete a guided setup wizard" |
| **A/B tests** | Formalize test rationale | "We believe click-through will rise 15% if we move the CTA above the fold" |
| **Sprint planning** | Attach hypothesis to each story | Story: "filter by date." Hypothesis: "task completion time drops 30%" |

**Ethical boundary:** Never cherry-pick metrics after the fact to declare a hypothesis validated—pre-commit to success criteria.

See [references/outcome-metrics.md](references/outcome-metrics.md) when picking the measurable signal for a hypothesis or defining team success — outcomes-vs-outputs, leading-vs-lagging indicator pairs, UX OKRs, and the vanity metrics to avoid.

### 3. MVPs and Experiments

**Core concept:** An MVP in Lean UX is the smallest design artifact that can test a hypothesis with real users—a learning tool, not a product launch.

**

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

What the source does

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none-observed

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Findings (5)

.agents/skills/37signals-way

.agents/skills/architecture-optimization

.agents/skills/blue-ocean-strategy

.agents/skills/clean-architecture

.agents/skills/clean-code

Gates applied: no_behavioural_pass.