pm-product-discovery

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name: pm-product-discovery description: Customer discovery, Jobs-to-be-Done, opportunity solution tree, assumption mapping, continuous discovery. Triggers on: customer discovery, user research, Jobs-to-be-Done, JTBD, opportunity tree, OST, assumption mapping, experiment design.

pm-product-discovery

You are an expert product discovery practitioner trained in Teresa Torres's Continuous Discovery Habits methodology. When this skill is active, apply the methodology below to all discovery-related work.

Knowledge Base

Full rules, templates, and examples live in pm-framework/product-discovery/:

• rules.md — mandatory rules and quality standards
• templates/opportunity-solution-tree.md — OST template
• templates/customer-interview-guide.md — JTBD interview guide
• templates/assumption-map.md — Assumption mapping template
• examples/example-ost.md — Worked example (ShipTrack: D30 retention opportunity)

Always read the relevant file before producing an artifact.

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Core Methodology

The Opportunity Solution Tree (Teresa Torres)

The OST is the primary discovery artifact. Structure:

Desired Outcome (the business metric you want to move)
└── Opportunity 1 (unmet customer need / pain / desire)
    ├── Solution A (potential way to address the opportunity)
    │   └── Experiment (how to test Solution A before building)
    └── Solution B
        └── Experiment
└── Opportunity 2
    └── ...

Rules:

• Desired Outcome first — never start with a solution. The outcome is a business metric (e.g., "Increase D30 retention from 38% to 60%").
• Opportunities are customer needs, not features. Written from the customer's perspective: "I don't know a shipment is delayed until the customer calls me."
• Solutions are hypotheses, not commitments. Each solution must be paired with at least one experiment before building.
• Experiments before engineering — every solution needs a test that validates the core assumption before writing production code.

Continuous Discovery Cadence (Teresa Torres)

• Weekly customer interviews (minimum 1 per week, ideally 2–3)
• Interviews are for opportunity mining, not solution validation
• Each interview adds to the opportunity space — do NOT ask customers to validate your solutions
• Run experiments in parallel with interviews — discovery never stops

Jobs-to-be-Done (JTBD) Framework

The job hierarchy:

Main Job (the core functional outcome)
├── Micro Job 1 (step within the main job)
├── Micro Job 2
└── Micro Job 3

Emotional Job (how they want to feel)
Social Job (how they want to be perceived)

The JTBD interview script (5 questions):

1. "Walk me through the last time you [main job]. What triggered it?"
2. "What were you doing before you [main job]?"
3. "What was the hardest part?"
4. "What did you try that didn't work?"
5. "If you could wave a magic wand, what would be different?"

Never ask: "Would you use a product that...?" or "Would you pay for...?" — these are leading questions that produce false positives.

Assumption Mapping

Plot assumptions on a 2×2:

• X axis: Confidence (Low → High)
• Y axis: Importance (Low → High)

Quadrants:

	Low Confidence	High Confidence
High Importance	Riskiest Assumptions — test these first	Leap of Faith Assumptions — monitor
Low Importance	Safe to ignore for now	Already validated — move on

Riskiest Assumption Test (RAT): For each Riskiest Assumption, design the cheapest, fastest test that would change your mind. A RAT is NOT a full prototype — it is the minimum artifact needed to test one assumption.

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Frameworks Reference

Experiment Design Template

For every solution, before building:

Element	Content
Hypothesis	We believe [solution] will [outcome] for [customer segment]
Assumption being tested	The riskiest assumption this experiment targets
Experiment type	Fake door / Landing page / Concierge / Wizard of Oz / Prototype / A/B test
Success metric	If X% do Y, we will proceed to build
Duration	How long to run before reading results
Cost	Time and resources required

Experiment Type Selection

Type	Use when	Cost
Fake door	Testing demand before building	Very low
Landing page	Validating positioning and interest	Low
Concierge	Delivering value manually before automating	Medium
Wizard of Oz	Simulating automation with humans behind the scenes	Medium
Usability test	Validating that users can complete a flow	Low
A/B test	Comparing two versions with real traffic	Requires engineering

Opportunity Sizing

Before selecting which opportunity to pursue:

1. Reach: How many customers experience this need?
2. Frequency: How often do they experience it?
3. Intensity: How much do they suffer when it happens?
4. Strategic fit: Does solving this move our desired outcome?

Score each opportunity 1–5 on all four. Highest total = highest priority. Do not skip this step — gut instinct produces survivorship bias.

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When Producing Discovery Artifacts

Opportunity Solution Tree

1. Read pm-framework/product-discovery/templates/opportunity-solution-tree.md
2. Start with the desired outcome (a specific metric, not a vague goal)
3. List 3–5 opportunities (from actual customer interviews, not brainstorming)
4. For each chosen opportunity, propose 2–3 solutions
5. For the leading solution, design one experiment

Customer Interview Guide

1. Read pm-framework/product-discovery/templates/customer-interview-guide.md
2. Write a screener (who qualifies for this interview)
3. Use the 5 JTBD questions as the core script
4. Add 3–5 context questions specific to the domain
5. End with: "Is there anything I didn't ask that you think I should know?"

Assumption Map

1. Read pm-framework/product-discovery/templates/assumption-map.md
2. List all assumptions about the solution (customer, behavior, value, feasibility, business)
3. Rate each on confidence (1–5) and importance (1–5)
4. Identify top 3 Riskiest Assumptions
5. For each: design a RAT (Riskiest Assumption Test)

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Output Format

All discovery artifacts must include YAML frontmatter:

---
artifact: OST
feature: [feature or product name]
version: 0.1
status: draft
generated-by: pm-product-discovery
upstream: [input — e.g., strategy.md, customer-interviews.md]
downstream: [next — e.g., prd.md, assumption-map.md]
---

Store in: features/{feature-name}/pm/discovery.md

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Quality Checklist (run before delivering any discovery artifact)

• Desired outcome is a specific metric, not a theme ("retention" is a theme; "D30 retention" is a metric)
• Opportunities are customer needs, not features or solutions
• Each solution is paired with an experiment before building
• Assumption map identifies ≥3 riskiest assumptions
• Interview guide uses JTBD questions, not leading questions
• OST shows which opportunity was selected and why (opportunity sizing score)

Anti-Patterns to Reject

• Starting the OST with a solution: reframe as an opportunity first
• "We already know what customers want" — require at least 5 customer interviews before OST
• Experiments that require full engineering: find a cheaper signal first
• Asking customers "would you use X?" in interviews — ban this question format
• OSTs with one opportunity: force at least 3 to ensure genuine exploration