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discovery-process

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项目 README

来源文件:README.md

抓取于 2026年8月2日

Product Manager Skills

GitHub stars License: CC BY-NC-SA 4.0 PRs Welcome Version Claude Code Plugin Skills

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║   70 battle-tested skills + 6 command workflows                    ║
║   Claude Code • Cursor • Codex  • n8n • OpenClaw • and more ...    ║
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║   v0.83 • July 17, 2026 • CC BY-NC-SA 4.0                          ║
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70 battle-tested PM frameworks, ready for Claude, Codex, ChatGPT, and any agent that can read structured knowledge.


Why This Exists

Generic AI output is a PM's worst enemy. When you tell your agent "write a PRD" without shared context, you get a generic document that no stakeholder trusts and no engineer can act on.

This library gives both you and your AI agent the same professional foundation: the why behind each framework, the failure modes to avoid, and the judgment to apply them correctly. You stop repeating yourself. Your agent stops guessing. The work gets better.

The goal is dual — functional and pedagogic in equal measure. Skills equip agents to do PM work at a professional level, and they teach the human PM the reasoning behind each framework — so you can explain it, adapt it, and pass it on. Neither is a byproduct of the other.


What You Can Get Done

Navigate by what you're actually trying to accomplish:

Framing and strategy

  • problem-framing-canvas — MITRE's Look Inward / Look Outward / Reframe sequence; stops teams from solving the wrong problem
  • positioning-statement — Geoffrey Moore's template for defining who you serve, what you solve, and how you're different
  • product-strategy-session — full strategy arc: positioning → problem framing → solution exploration → roadmap (2-4 weeks)

Stakeholder alignment

  • stakeholder-identification — map every stakeholder before engaging anyone: broad brainstorm → allies/audiences/influencers → R/P/D marking → equity lens → narrow to priority targets
  • stakeholder-mapping — run two complementary grids (Power × Interest for engagement strategy; Impact × Power for whose voice to elevate) and compare to find the gaps
  • stakeholder-engagement-advisor — per-stakeholder engagement planning: diagnoses their profile and context, then delivers tailored message framing, medium, cadence, and a named next action

Customer discovery and research

Prioritization and roadmapping

  • prioritization-advisor — asks 3-5 questions about your context, then recommends RICE, ICE, Kano, or the right alternative
  • epic-breakdown-advisor — splits large epics using Richard Lawrence's 9 patterns
  • roadmap-planning — gather inputs → define epics → prioritize → sequence → communicate (1-2 weeks)

Writing PM deliverables

  • user-story — Mike Cohn format + Gherkin acceptance criteria, with anti-patterns
  • prd-development — structured PRD: problem → personas → solution → metrics → stories (2-4 days)
  • press-release — Amazon Working Backwards: clarify product vision before writing a line of spec

Validation and experimentation

  • pol-probe-advisor — recommends which prototype type to run based on your hypothesis and risk level
  • pol-probe — template for documenting lightweight validation experiments before building

Finance and growth

  • business-health-diagnostic — diagnoses SaaS health across growth, retention, efficiency, and capital using your real metrics
  • organic-growth-advisor — McKinsey Growth Pyramid triage: diagnoses whether your constraint is in new segments, geographies, channels, or products
  • feature-investment-advisor — build / don't build recommendation using revenue impact, cost, ROI, and strategic value

Market and competitive intelligence

Career and leadership transitions

AI product work


Get Started

Choose your setup:

I use...Get thisNotes
Claude Desktop or Claude Webpm-skills-starter-pack.zipUnzip, then upload the individual skill ZIPs to Claude Skills
Claude CodePlugin marketplaceclaude /plugin marketplace add deanpeters/Product-Manager-Skills
Codexpm-skills-codex.zipInstalls .agents/skills and AGENTS.md
Not surepm-skills-starter-pack.zipStart here

All downloads: GitHub Releases

Themed packs for Claude Desktop / Web

Each pack below is a ZIP of upload-ready skill ZIPs — unzip, then upload individuals to Claude Skills:

PackDownloadWhat's inside
Starterpm-skills-starter-pack.zipCore skills across all categories
Discovery02-discovery-pack.zipResearch, interviewing, synthesis
Strategy03-strategy-pack.zipPositioning, roadmapping, prioritization
Delivery04-delivery-pack.zipPRDs, stories, epics
AI PM05-ai-pm-pack.zipContext engineering, orchestration, readiness
Market Intel06-market-intel-pack.zipThe full Market Intelligence Suite: disciplines, investigation chain, frameworks, monitors
All skills99-all-skills-pack.zipAll 70 skills

Install guides


Try It First — Streamlit (beta)

Not ready to wire skills into your agent setup? Run the local playground first and kick the tires in your browser.

pip install -r app/requirements.txt
streamlit run app/main.py

What you can do:

  • Learn — browse setup and integration paths without leaving the app
  • Find My Skill — describe your situation in plain English and get recommended skills
  • Run Skills — run a skill with your own scenario once you know what you want

Multi-provider support: Anthropic, OpenAI, Ollama. API keys via environment variables only (no in-app key entry).

Docs: app/STREAMLIT_INTERFACE.md · app/.env.example

Feedback welcome via GitHub Issues or LinkedIn.


70 Skills, 3 Types

Skills are organized in three tiers that build on each other:

┌────────────────────────────────────────────────────────┐
│  WORKFLOW SKILLS (19)                                  │
│  Complete end-to-end PM processes (days to weeks)      │
│  Example: run a full discovery cycle or write a PRD    │
└────────────────────────────────────────────────────────┘
                       ↓ orchestrates
┌────────────────────────────────────────────────────────┐
│  INTERACTIVE SKILLS (27)                               │
│  Guided discovery — 3-5 questions, then recommendations│
│  Example: "Which prioritization framework fits here?"  │
└────────────────────────────────────────────────────────┘
                       ↓ uses
┌────────────────────────────────────────────────────────┐
│  COMPONENT SKILLS (24)                                 │
│  Templates for specific PM deliverables (30-90 min)    │
│  Example: write a user story with acceptance criteria  │
└────────────────────────────────────────────────────────┘

Interactive skills use an Adaptive Decision Ladder. Instead of dumping a framework at you, an interactive skill asks 3-5 targeted questions about your specific context, then offers numbered recommendations — each with a clear "use this when" rationale. You pick a path. The skill executes it and explains the why as it goes. If you want to just learn the framework without doing the work, you can ask that too — the skill coaches you either way. This is ABC — Always Be Coaching — in practice.

Full catalog: catalog/INDEX.md — all 70 skills with descriptions, or browse skills/ directly.


How a Skill File Works

Every SKILL.md follows the same structure:

SectionWhat it contains
Frontmattername, description, type, intent, best_for, scenarios
PurposeWhat this skill does and when to reach for it
InputWhat you can bring (with example invocations) — inline input is used, not re-asked, and arriving empty-handed is fine: the skill walks you through it
Key ConceptsFrameworks, definitions, anti-patterns — with vocabulary explained
ApplicationStep-by-step instructions an agent (or human) can follow
ExamplesReal-world cases showing both good and bad versions
Common PitfallsNamed failure modes with consequences and corrections
ReferencesRelated skills and external frameworks

The best_for frontmatter field lists 3-5 specific scenarios where the skill is most useful — helpful for quickly scanning whether a skill fits your situation.

Why no $ARGUMENTS templating? Other skill libraries use Claude Code's $ARGUMENTS substitution for input. We deliberately don't: it only expands in Claude Code (it renders as literal syntax in Claude Desktop/Web, Codex, and the Streamlit playground), and it teaches the human reader nothing. Instead, every skill has a plain-language ## Input section that works on every runtime — and makes clear you can show up with full context, partial context, or nothing at all and be guided through the rest. Full rationale in CONTRIBUTING.md.


Works With

Claude Code · Claude Desktop · Claude Web · OpenAI Codex · ChatGPT · Cursor · Windsurf · n8n · LangFlow · CrewAI · Gemini · any agent that reads structured markdown

See docs/Platform Guides for PMs.md for platform-specific setup.


Docs

DocumentPurpose
Using PM Skills 101Beginner-friendly orientation — setup without technical overload
Platform Guides for PMsTool-by-tool setup chooser for every supported platform
Using PM Skills with ClaudeClaude Code + GitHub ZIP upload for Claude Desktop/Web
Using PM Skills with CodexLocal workspace + GitHub-connected Codex on ChatGPT
Using PM Skills with ChatGPTGitHub app, Custom GPT Knowledge, and Project-based usage
Using PM Skills with Slash Commands 101Turn skills into reusable slash commands like /pm-story
Add-a-Skill Utility GuideEnd-to-end guide for generating and validating new skills
Market Intelligence Suite SummaryThe 14-skill competitive/market research suite: disciplines, chain, and which skill to run when
Building PM SkillsHow raw PM content gets distilled into agent-ready skills
START_HERE.md60-second onboarding for local repo users

What's New

v0.83 — July 17, 2026 · The Market Intelligence Suite

v0.82 — July 8, 2026

  • Added incoming-request-advisor (Interactive) — drop in a Slack ping, email, mandate, or escalation and get a structured breakdown that separates the literal ask from the real job-to-be-done, reads sender power and stake, and points you toward a reply. Ships with a copy/paste template so you can run it by hand too
  • New: a browsable download shelf at /dist — no terminal, no Releases tab. Read the plain-language README, scan the CATALOG, and download any skill or pack straight from the repo. Built for PMs who just want the skills
  • Library now at 70 skills

v0.81 — July 4, 2026

  • Every skill now has a required ## Input section: what to bring, what happens to context you supply up front (it's used, not re-asked), and reassurance that arriving empty-handed is fine — the guided flow covers the rest
  • Added argument-hint autocomplete for Claude Code users; deliberately no $ARGUMENTS templating — it breaks on every other runtime and teaches the reader nothing (why)
  • Validator now enforces the convention: skills fail without an Input section or with bare $ARGUMENTS in the body
  • Streamlit playground shows each skill's "What to bring (all optional)" before you start a session
  • Restored agent-orchestration-advisor (Interactive) — the multi-agent workflow design skill was referenced everywhere but only existed on an orphaned commit; recovered from git history and brought up to current standards

v0.80 — June 19, 2026

  • Added stakeholder-identification (Component) — comprehensive stakeholder brainstorm using allies/audiences/influencers, R/P/D marking, equity lens, and bias check; narrows to priority targets
  • Added stakeholder-mapping (Component) — two complementary grids (Power × Interest + Impact × Power); comparing outputs reveals who you're under-engaging relative to how much the product affects them
  • Added stakeholder-engagement-advisor (Interactive) — per-stakeholder engagement planning via Adaptive Decision Ladder: three questions on profile, power/impact, and context deliver tailored message framing, medium, cadence, and a named next action

All three adapted from the MITRE Innovation Toolkit via the companion repo MITRE ITK Skills — worth a bookmark if you work in discovery, facilitation, or cross-functional product strategy.

v0.79 — May 15, 2026

  • Added organic-growth-advisor — McKinsey Growth Pyramid triage for new segments, geographies, channels, or products
  • Added pm-skill-creator — interactive skill for designing repo-compliant skills via guided conversation
  • Fixed missing .claude-plugin/plugin.json that silently blocked Claude Code skill discovery
  • Added configurable input length guard (PM_MAX_INPUT) and path traversal protection to helper scripts

→ Full changelog


Contributing

Found a gap? Have a PM framework worth formalizing? The bar is pedagogic — skills must teach the why, not just the how.

See CONTRIBUTING.md for guidelines, or open an issue to start a conversation.


License

CC BY-NC-SA 4.0 — non-commercial use with share-alike.

Everything in this repository — every skill, template, and doc — is licensed CC BY-NC-SA 4.0. There is no mix of licenses here.

Some skills note in their Provenance sections that they were adapted from product-manager-prompts, Dean's earlier prompt library. That repo has the same author, so there is no license conflict: a license grants permissions to other people, and a copyright holder is free to adapt and relicense their own work. Those Provenance lines are lineage — a breadcrumb back to where an idea started — not a license dependency. No third-party MIT-licensed text is incorporated anywhere in this library.

In plain terms:

  • ✅ Use these skills in your day job — at a for-profit company, with your team, in your agents. That's what they're for.
  • ✅ Adapt and remix them — share what you build under this same license, with credit.
  • ✅ Teach with them — workshops, brown bags, mentoring, sending the ladder down.
  • ❌ Don't sell them — no repackaging the skills themselves into a paid product, course, or service without expressed written permission.
  • 🤔 Not sure your use qualifies? Open an issue and ask. If you're using these in the spirit they were built — to get better at the craft and help others do the same — the answer is almost certainly yes.

The companion prompt library, product-manager-prompts, carries the same CC BY-NC-SA 4.0 license as of its v2.3.0, with its own plain-language permissions (stricter on commercial use) — see its LICENSING.md, which governs that repo.


Questions

其他

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  • 来源需自行核对维护者身份。
  • 未检测到明显脚本安装指令。
  • 可能需要外部 token、网络权限或第三方服务。
  • 存在潜在风险命令,请谨慎安装。
  • 扫描发现:1 条。

Codex — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/discovery-process" 文件夹复制到 Codex 的 skills 目录中。
  4. 重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Codex 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/discovery-process" 文件夹复制到 Claude Code 的 skills 目录中。
  4. 重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Claude Code 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/discovery-process" 文件夹复制到 Cursor 的 skills 目录中。
  4. 重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Cursor 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/discovery-process" 文件夹复制到 GitHub Copilot 的 skills 目录中。
  4. 重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 GitHub Copilot 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/discovery-process" 文件夹复制到 Windsurf 的 skills 目录中。
  4. 重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: discovery-process
argument-hint: "[problem hypothesis]"
description: Run a full discovery cycle from problem hypothesis to validated solution. Use when a team needs a structured path through framing, interviews, synthesis, and experiments.
intent: >-
  Guide product managers through a complete discovery cycle—from initial problem hypothesis to validated solution—by orchestrating problem framing, customer interviews, synthesis, and experimentation skills into a structured process. Use this to systematically explore problem spaces, validate assumptions, and build confidence before committing to full development—avoiding "build it and they will come" syndrome and ensuring you're solving real customer problems.
type: workflow
theme: discovery-research
best_for:
  - "Running a full discovery cycle from hypothesis to validated solution"
  - "Investigating a retention or churn problem systematically"
  - "Setting up continuous discovery as an ongoing practice"
scenarios:
  - "I have a hypothesis that B2B customers struggle with onboarding and want to validate it before building anything"
  - "Our activation rate dropped 15% this quarter and I need to run discovery to find out why"
estimated_time: "30-60 min"

Purpose

Guide product managers through a complete discovery cycle—from initial problem hypothesis to validated solution—by orchestrating problem framing, customer interviews, synthesis, and experimentation skills into a structured process. Use this to systematically explore problem spaces, validate assumptions, and build confidence before committing to full development—avoiding "build it and they will come" syndrome and ensuring you're solving real customer problems.

This is not a one-time research project—it's a continuous discovery practice that runs in parallel with delivery, typically 1-2 discovery cycles per quarter.

Input

Works best with: Your starting problem hypothesis — even a rough one. Also useful: Prior research, customer access, timeline, and what decision the discovery must inform.

Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.

Arriving empty-handed? That works too. The workflow starts at problem framing and helps you construct the hypothesis first.

Example invocation: Run discovery on this hypothesis: SMB admins abandon onboarding because the data-import step requires IT help they don't have.

Key Concepts

What is the Discovery Process?

The discovery process (Teresa Torres, Marty Cagan) is a structured approach to exploring problem spaces and validating solutions before building. It consists of:

  1. Frame the Problem — Define what you're investigating and why
  2. Conduct Research — Gather qualitative and quantitative evidence
  3. Synthesize Insights — Identify patterns, pain points, and opportunities
  4. Generate Solutions — Explore multiple solution options
  5. Validate Solutions — Test assumptions through experiments
  6. Decide & Document — Commit to build, pivot, or kill

Why This Works

  • De-risks product decisions: Tests assumptions before expensive builds
  • Customer-centric: Grounds decisions in real customer problems, not internal opinions
  • Iterative: Builds confidence progressively through small experiments
  • Fast learning: Discovers "no-go" signals early, saves wasted effort

Anti-Patterns (What This Is NOT)

  • Not waterfall research: Discovery runs continuously, not once before dev
  • Not user testing: Discovery validates problems; testing validates solutions
  • Not a substitute for shipping: Discovery informs delivery, doesn't replace it

When to Use This

  • Exploring new product/feature areas
  • Investigating retention or churn problems
  • Validating strategic initiatives before roadmap commitment
  • Continuous discovery (weekly customer touchpoints)

When NOT to Use This

  • For well-understood problems (move to execution)
  • When stakeholders have already committed to a solution (address alignment first)
  • For tactical bug fixes or technical debt (no discovery needed)

Facilitation Source of Truth

When running this workflow as a guided conversation, use workshop-facilitation as the interaction protocol.

It defines:

  • session heads-up + entry mode (Guided, Context dump, Best guess)
  • one-question turns with plain-language prompts
  • progress labels (for example, Context Qx/8 and Scoring Qx/5)
  • interruption handling and pause/resume behavior
  • numbered recommendations at decision points
  • quick-select numbered response options for regular questions (include Other (specify) when useful)

This file defines the workflow sequence and domain-specific outputs. If there is a conflict, follow this file's workflow logic.

Application

Use template.md for the full fill-in structure.

This workflow orchestrates 6 phases over 2-4 weeks, using multiple component and interactive skills.


Phase 1: Frame the Problem (Day 1-2)

Goal: Define what you're investigating, who's affected, and success criteria.

Activities

1. Run Problem Framing Canvas

  • Use: skills/problem-framing-canvas/SKILL.md (interactive - MITRE)
  • Participants: PM, design, engineering lead
  • Duration: 120 minutes
  • Output: Problem statement + "How Might We" question

2. Create Formal Problem Statement

  • Use: skills/problem-statement/SKILL.md (component)
  • Participants: PM
  • Duration: 30 minutes
  • Output: Structured problem statement with hypothesis

3. Define Proto-Personas (If Needed)

  • Use: skills/proto-persona/SKILL.md (component)
  • When: If target customer segment is unclear
  • Duration: 60 minutes
  • Output: Hypothesis-driven personas

4. Map Jobs-to-be-Done (If Needed)

  • Use: skills/jobs-to-be-done/SKILL.md (component)
  • When: If customer motivations are unclear
  • Duration: 60 minutes
  • Output: JTBD statements

Outputs from Phase 1

  • Problem hypothesis: "We believe [persona] struggles with [problem] because [root cause], leading to [consequence]."
  • Research questions: 3-5 questions to answer through discovery
  • Success criteria: What would validate/invalidate the problem?

Decision Point 1: Do we have enough context to start research?

If YES: Proceed to Phase 2 (Research Planning)

If NO: Gather existing data first:

  • Review support tickets, churn surveys, NPS feedback
  • Analyze product analytics (drop-off points, usage patterns)
  • Review competitor research, market trends
  • Time impact: +2-3 days

Phase 2: Research Planning (Day 3)

Goal: Design research approach, recruit participants, prepare interview guide.

Activities

1. Prep Discovery Interviews

  • Use: skills/discovery-interview-prep/SKILL.md (interactive)
  • Participants: PM, design
  • Duration: 90 minutes
  • Output: Interview plan with methodology, questions, biases to avoid

2. Recruit Participants

  • Target: 5-10 customers per discovery cycle (Teresa Torres: continuous discovery = 1 interview/week)
  • Segment: Focus on personas from Phase 1
  • Recruitment channels:
    • Existing customers (email, in-app prompts)
    • Churned customers (exit interviews)
    • Cold outreach (LinkedIn, communities)
  • Incentive: $50-100 gift card or product credit
  • Duration: 2-3 days (parallel with Phase 1)

3. Schedule Interviews

  • Format: 45-60 min per interview (30-40 min conversation + buffer)
  • Timeline: Spread across 1-2 weeks
  • Recording: Get consent, record for synthesis

Outputs from Phase 2

  • Interview guide: 5-7 open-ended questions (Mom Test style)
  • Participant roster: 5-10 scheduled interviews
  • Synthesis plan: How you'll capture and analyze insights

Phase 3: Conduct Research (Week 1-2)

Goal: Gather qualitative evidence through customer interviews.

Activities

1. Conduct Discovery Interviews

  • Methodology: From skills/discovery-interview-prep/SKILL.md (Problem validation, JTBD, switch interviews, etc.)
  • Participants: PM + optional observer (design, eng)
  • Duration: 5-10 interviews over 1-2 weeks
  • Focus areas:
    • Past behavior (not hypotheticals): "Tell me about the last time you [experienced this problem]"
    • Workarounds: "How do you currently handle this?"
    • Alternatives tried: "Have you tried other solutions? Why did you stop?"
    • Pain intensity: "How much time/money does this cost you?"

2. Take Structured Notes

  • Template:
    • Participant: [Name, role, company size]
    • Context: [When/where they experience problem]
    • Actions: [What they do, step-by-step]
    • Pain points: [Frustrations, blockers]
    • Workarounds: [Current solutions]
    • Quotes: [Verbatim customer language]
    • Insights: [Patterns, surprises]

3. Review Support Tickets & Analytics (Parallel)

  • Support tickets: Tag by theme (onboarding, feature confusion, bugs)
  • Analytics: Identify drop-off points, feature usage, cohort behavior
  • Surveys: Review NPS comments, exit surveys, feature requests

Outputs from Phase 3

  • Interview transcripts: Recorded sessions + detailed notes
  • Support ticket themes: Top 10 issues by frequency
  • Analytics insights: Quantitative data on behavior (e.g., "60% abandon onboarding at step 3")

Decision Point 2: Have we reached saturation?

Saturation = same pain points emerge across 3+ interviews, no new insights

If YES (saturated after 5-7 interviews): Proceed to Phase 4 (Synthesis)

If NO (still learning new things): Schedule 3-5 more interviews

  • Time impact: +1 week

Phase 4: Synthesize Insights (End of Week 2)

Goal: Identify patterns, prioritize pain points, map opportunities.

Activities

1. Affinity Mapping (Thematic Analysis)

  • Method:
    • Write each insight/quote on sticky note
    • Group by theme (e.g., "onboarding confusion," "pricing objections," "mobile access")
    • Count frequency (how many customers mentioned each theme)
  • Participants: PM, design, optional eng
  • Duration: 90-120 minutes
  • Output: Themed clusters with frequency counts

2. Create Customer Journey Map (Optional)

  • Use: skills/customer-journey-mapping-workshop/SKILL.md (interactive)
  • When: If pain points span multiple phases (discover, try, buy, use, support)
  • Duration: 90 minutes
  • Output: Journey map with opportunities ranked by impact

3. Prioritize Pain Points

  • Criteria:
    • Frequency: How many customers mentioned this?
    • Intensity: How painful is it? (time wasted, money lost, emotional frustration)
    • Strategic fit: Does solving this align with business goals?
  • Method: Score each pain point (1-5) on frequency, intensity, strategic fit
  • Output: Ranked list of top 3-5 pain points to address

4. Update Problem Statement

  • Use: skills/problem-statement/SKILL.md (component)
  • Refine based on research: Did initial hypothesis hold? Adjust if needed.
  • Output: Validated problem statement

Outputs from Phase 4

  • Affinity map: Themes with frequency counts
  • Top 3-5 pain points: Prioritized by frequency × intensity × strategic fit
  • Customer quotes: 3-5 verbatim quotes per pain point
  • Validated problem statement: Refined based on evidence

Phase 5: Generate & Validate Solutions (Week 3)

Goal: Explore solution options, design experiments, validate assumptions.

Activities

1. Generate Opportunity Solution Tree

  • Use: skills/opportunity-solution-tree/SKILL.md (interactive)
  • Input: Top 3 pain points from Phase 4
  • Participants: PM, design, engineering lead
  • Duration: 90 minutes
  • Output: 3 opportunities, 3 solutions per opportunity, POC recommendation

Alternative: Use Lean UX Canvas

  • Use: skills/lean-ux-canvas/SKILL.md (interactive)
  • When: Prefer hypothesis-driven approach over OST
  • Output: Hypotheses to test, minimal experiments

2. Design Experiments

  • For each solution: Define "What's the least work to learn the next most important thing?"
  • Experiment types:
    • Concierge test: Manually deliver solution to 10 customers, observe
    • Prototype test: Clickable mockup, usability test with 10 users
    • Landing page test: Fake door test (show feature, measure interest)
    • A/B test: Build minimal version, test with 50% of users
  • Success criteria: What metric/behavior validates hypothesis?

3. Run Experiments

  • Timeline: 1-2 weeks per experiment
  • Participants: PM + design (for prototypes), eng (for A/B tests)
  • Output: Quantitative and qualitative validation data

Outputs from Phase 5

  • Solution options: 3-9 solutions (3 per opportunity)
  • Experiment results: Did hypothesis validate or invalidate?
  • Customer feedback: Qualitative reactions to prototypes/concepts

Decision Point 3: Did experiments validate solution?

If YES (validated): Proceed to Phase 6 (Decide & Document)

If NO (invalidated):

  • Pivot to next solution option
  • Re-run experiments with adjusted approach
  • Time impact: +1-2 weeks

Phase 6: Decide & Document (End of Week 3-4)

Goal: Commit to build, document decision, communicate to stakeholders.

Activities

1. Make Go/No-Go Decision

  • Criteria:
    • Problem validated? (Phase 3-4)
    • Solution validated? (Phase 5)
    • Strategic fit? (aligns with business goals)
    • Feasible? (engineering capacity, technical complexity)
  • Decision:
    • GO: Move to roadmap, write epics/stories
    • PIVOT: Explore alternative solution
    • KILL: De-prioritize, not worth solving now

2. Define Epic Hypotheses (If GO)

  • Use: skills/epic-hypothesis/SKILL.md (component)
  • Participants: PM
  • Duration: 60 minutes per epic
  • Output: Epic hypothesis statement with success criteria

3. Write PRD (If GO)

  • Use: skills/prd-development/SKILL.md (workflow)
  • Participants: PM
  • Duration: 1-2 days
  • Output: Structured PRD with problem, solution, success metrics

4. Communicate Findings

  • Format: 30-min readout covering:
    • Problem validation (Phase 3-4 insights)
    • Solution validation (Phase 5 experiments)
    • Recommendation (GO/PIVOT/KILL)
  • Participants: Execs, product leadership, key stakeholders
  • Output: Alignment on next steps

Outputs from Phase 6

  • Decision: GO, PIVOT, or KILL
  • Epic hypotheses: (if GO) Testable epic statements
  • PRD: (if GO) Formal product requirements document
  • Stakeholder alignment: Exec buy-in on recommendation

Complete Workflow: End-to-End Summary

Week 1:
├─ Day 1-2: Frame the Problem
│  ├─ skills/problem-framing-canvas/SKILL.md (120 min)
│  ├─ skills/problem-statement/SKILL.md (30 min)
│  └─ [Optional] skills/proto-persona/SKILL.md, skills/jobs-to-be-done/SKILL.md
│
├─ Day 3: Research Planning
│  ├─ skills/discovery-interview-prep/SKILL.md (90 min)
│  ├─ Recruit participants (2-3 days)
│  └─ Schedule 5-10 interviews
│
└─ Day 4-5: Conduct Research (Start)
   └─ First 2-3 customer interviews

Week 2:
├─ Day 1-3: Conduct Research (Continue)
│  └─ Remaining customer interviews (3-7 more)
│
├─ Day 4-5: Synthesize Insights
│  ├─ Affinity mapping (120 min)
│  ├─ [Optional] skills/customer-journey-mapping-workshop/SKILL.md (90 min)
│  ├─ Prioritize pain points
│  └─ Update problem statement
│
└─ Decision: Reached saturation? (if NO, +1 week more interviews)

Week 3:
├─ Day 1-2: Generate & Validate Solutions
│  ├─ skills/opportunity-solution-tree/SKILL.md (90 min)
│  └─ Design experiments
│
├─ Day 3-5: Run Experiments
│  ├─ Concierge tests, prototypes, or A/B tests
│  └─ Gather validation data
│
└─ Decision: Validated? (if NO, pivot to next solution, +1-2 weeks)

Week 4:
└─ Decide & Document
   ├─ Make GO/NO-GO decision
   ├─ [If GO] skills/epic-hypothesis/SKILL.md (60 min per epic)
   ├─ [If GO] skills/prd-development/SKILL.md (1-2 days)
   └─ Communicate findings (30 min readout)

Total Time Investment:

  • Fast track: 3 weeks (5 interviews, 1 experiment)
  • Typical: 4 weeks (7-10 interviews, 1-2 experiments)
  • Thorough: 6-8 weeks (10+ interviews, multiple experiment rounds)

Examples

See examples/sample.md for a full discovery process example.

Mini example excerpt:

**Problem:** Onboarding drop-off due to jargon
**Insight:** 6/10 users quit at step 3
**Decision:** Go with guided checklist experiment

Common Pitfalls

Pitfall 1: Skipping Customer Interviews

Symptom: Rely only on analytics and support tickets, no qualitative research

Consequence: Miss "why" behind behavior, build wrong solutions

Fix: Always interview 5-10 customers per discovery cycle (even if you have data)


Pitfall 2: Asking Leading Questions

Symptom: "Would you use [feature X] if we built it?"

Consequence: Confirmation bias, customers say "yes" to be polite

Fix: Use Mom Test questions from skills/discovery-interview-prep/SKILL.md (focus on past behavior)


Pitfall 3: Not Reaching Saturation

Symptom: Interview 2-3 customers, declare discovery complete

Consequence: Small sample, not representative

Fix: Continue interviews until same patterns emerge across 3+ customers (typically 5-7 interviews minimum)


Pitfall 4: Analysis Paralysis

Symptom: Spend 6 weeks synthesizing insights, never move to solutions

Consequence: No delivery, team loses momentum

Fix: Time-box discovery to 3-4 weeks; after Phase 6, move to execution


Pitfall 5: Discovery as One-Time Activity

Symptom: Run discovery once before building, then stop

Consequence: Miss evolving customer needs, market changes

Fix: Continuous discovery (Teresa Torres): 1 customer interview per week, ongoing


References

Related Skills (Orchestrated by This Workflow)

Phase 1:

  • skills/problem-framing-canvas/SKILL.md (interactive)
  • skills/problem-statement/SKILL.md (component)
  • skills/proto-persona/SKILL.md (component, optional)
  • skills/jobs-to-be-done/SKILL.md (component, optional)

Phase 2:

  • skills/discovery-interview-prep/SKILL.md (interactive)

Phase 4:

  • skills/customer-journey-mapping-workshop/SKILL.md (interactive, optional)

Phase 5:

  • skills/opportunity-solution-tree/SKILL.md (interactive)
  • skills/lean-ux-canvas/SKILL.md (interactive, alternative)

Phase 6:

  • skills/epic-hypothesis/SKILL.md (component)
  • skills/prd-development/SKILL.md (workflow)

External Frameworks

  • Teresa Torres, Continuous Discovery Habits (2021) — Weekly customer touchpoints, OST framework
  • Rob Fitzpatrick, The Mom Test (2013) — How to ask good interview questions
  • Marty Cagan, Inspired (2017) — Product discovery principles

Dean's Work

  • Productside Blueprint — Strategic discovery process
  • [If Dean has discovery resources, link here]

Skill type: Workflow Suggested filename: discovery-process.md Suggested placement: /skills/workflows/ Dependencies: Orchestrates 10+ component and interactive skills across 6 phases

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