product-management

Product Management (Jan 2026)

This skill turns the assistant into an operator, not a lecturer.

Everything here is:

• Executable: templates, checklists, decision flows
• Decision-first: measurable outcomes, explicit trade-offs, clear ownership
• Organized: resources for depth; templates for immediate copy-paste

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Modern Best Practices (Jan 2026):

• Evidence quality beats confidence: label signals strong/medium/weak; write what would change your mind.
• Outcomes > output: roadmaps are bets with measurable impact and guardrails, not feature inventories.
• Metrics must be defined (formula + timeframe + data source) to be actionable.
• Privacy, security, and accessibility are requirements, not afterthoughts.
• Hybrid decision loops: AI surfaces anomalies, patterns, and forecasts; humans apply context, ethics, and long-term strategy.
• Accountability: product is often held responsible for business outcomes; confirm the operating model in your org and validate benchmarks with current sources.
• Portfolio diversification: a common heuristic is 70% core, 20% adjacent, 10% transformational; adapt to strategy and constraints.

When to Use This Skill

Use this skill when the user asks to do real product work, such as:

• “Create / refine a PRD / spec / business case / 1-pager”
• “Turn this idea into a roadmap” / “Outcome roadmap for X”
• “Design a discovery plan / interview script / experiment plan”
• “Define success metrics / OKRs / metric tree”
• “Position this product against competitors”
• “Run a difficult conversation / feedback / 1:1 / negotiation”
• “Plan a product strategy / vision / opportunity assessment”

Do not use this skill for:

• Book summaries, philosophy, or general education
• Long case studies or storytelling

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Quick Reference

Task	Template	Domain	Output
Discovery interview	customer-interview-template.md	Discovery	Interview script with Mom Test patterns
Opportunity mapping	opportunity-solution-tree.md	Discovery	OST with outcomes, problems, solutions
PMF survey	pmf-survey-template.md	Discovery	Sean Ellis + NPS + usage survey
Outcome roadmap	outcome-roadmap.md	Roadmap	Now/Next/Later with outcomes and themes
OKR definition	okr-template.md	Metrics	1-3 objectives with 2-4 key results each
Product positioning	positioning-template.md	Strategy	Competitive alternatives -> value -> segment
Product vision	product-vision-template.md	Strategy	From→To narrative with 3-5 year horizon
Quarterly review	quarterly-product-review.md	Strategy	Keep / cut / double-down product audit
Prioritization	prioritization-scorecard.md	Prioritization	RICE/ICE scoring with kill criteria
Kill criteria	kill-criteria-template.md	Prioritization	Pre-defined stop conditions per initiative
1:1 meeting	1-1-template.md	Leadership	Check-in, progress, blockers, growth
Post-incident debrief	a3-debrief.md	Leadership	Intent vs actual, root cause, action items

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Decision Tree: Choosing the Right Workflow

User needs: [Product Work Type]
    ├─ Discovery / Validation?
    │   ├─ Customer insights? → Customer interview template
    │   ├─ Hypothesis testing? → Assumption test template
    │   └─ Opportunity mapping? → Opportunity Solution Tree
    │
    ├─ Strategy / Vision?
    │   ├─ Long-term direction? → Product vision template
    │   ├─ Market positioning? → Positioning template (Dunford)
    │   ├─ Big opportunity? → Opportunity assessment
    │   └─ Amazon-style spec? → PR/FAQ template
    │
    ├─ Planning / Roadmap?
    │   ├─ Outcome-driven? → Outcome roadmap (Now/Next/Later)
    │   ├─ Theme-based? → Theme roadmap
    │   └─ Metrics / OKRs? → Metric tree + OKR template
    │
    ├─ Prioritization / Focus?
    │   ├─ What to build next? → Prioritization scorecard (RICE/ICE)
    │   ├─ What to stop? → Kill criteria template + quarterly review
    │   ├─ Scope too large? → Scope negotiation patterns
    │   └─ PMF check? → PMF survey + retention curve analysis
    │
    └─ Leadership / Team Ops?
        ├─ 1:1 meeting? → 1-1 template
        ├─ Giving feedback? → Feedback template (SBI model)
        ├─ Post-incident? → A3 debrief
        ├─ Stakeholder pushback? → Stakeholder management patterns
        └─ Negotiation? → Negotiation one-sheet (Voss)

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Do / Avoid (Jan 2026)

Do

• Start from the decision: what are we deciding, by when, and with what evidence.
• Define metrics precisely (formula + timeframe + data source) and add guardrails.
• Use discovery to de-risk value before building; prioritize by evidence, not opinions.
• Write “match vs ignore” competitive decisions, not feature grids.

Avoid

• Roadmap theater (shipping lists) without outcomes and learning loops.
• Vanity KPIs (raw signups, impressions) without activation/retention definitions.
• "Build-first validation" (shipping MVPs without falsifiable hypotheses).
• Collecting customer data without purpose limitation, retention, and access controls.
• Building for engineering elegance instead of user value (technical founder trap).
• Feature creep without kill criteria (every feature should have a pre-defined stop condition).
• Saying "yes" to stakeholder requests without trade-off analysis.
• Measuring PMF once instead of continuously across segments.

Prioritization & Saying No

The most common founder-PM failure: building everything, killing nothing, and running out of time before impact.

Prioritization Frameworks

Framework	Formula / Method	Best For	Watch For
RICE	(Reach x Impact x Confidence) / Effort	Comparing features with data	Gaming confidence scores
ICE	Impact x Confidence x Ease	Quick gut-check prioritization	Over-simplification
Opportunity Scoring	Importance x (Importance - Satisfaction)	Discovery-driven, JTBD-aligned	Requires user research data
Cost of Delay	Value per unit time / Duration	Time-sensitive decisions	Harder to estimate accurately
Weighted Shortest Job First (WSJF)	Cost of Delay / Job Size	SAFe/Lean, flow optimization	Requires calibrated estimates

Pick one. Use it consistently. The framework matters less than the discipline of scoring everything the same way.

Kill Criteria

Every initiative should have pre-defined conditions for stopping:

• Usage threshold: If <X% of target users adopt within Y weeks, stop.
• Cost ceiling: If development exceeds X hours/dollars, pause and re-evaluate.
• Time limit: If not shipped within X weeks, kill or radically descope.
• Metric guardrail: If [guardrail metric] degrades by >X%, roll back.

Use assets/prioritization/kill-criteria-template.md to define these before starting.

Feature Bridge Migration

When replacing an existing feature with a new one, don't hard-kill the old feature. Use a bridge migration pattern to prevent user loss.

Bridge mode: Run both old and new features simultaneously. Route users to the new experience by default but keep the old path accessible (via link, fallback, or settings toggle).

Substitution-based kill rule:

1. Define the absorption metric: % of old-feature users who now use the new feature for the same job.
2. Set the kill threshold: new feature absorbs ≥80% of old-feature users.
3. Set the duration: threshold must hold for 14 consecutive days with no retention regression.
4. Only kill the old feature when all three conditions are met.

BRIDGE MIGRATION SEQUENCE:

1. Ship new feature alongside old feature
2. Default new users to new experience
3. Migrate existing users gradually (progressive rollout)
4. Monitor: absorption rate, retention by cohort, support tickets
5. Old feature absorbs ≥80% for 14 days + no retention drop?
   ├─ Yes → Kill old feature, remove code
   └─ No → Investigate gaps, iterate new feature, extend bridge

When NOT to bridge: Security vulnerabilities, compliance requirements, or features with near-zero usage (<1% MAU). These can be killed directly with notice.

Scope Negotiation

When stakeholders push for more scope:

• Reframe as trade-offs: "We can add X if we cut Y — which matters more?"
• Anchor on outcomes: "The goal is [metric]. Does this addition move it?"
• Offer phased delivery: "V1 without this; measure; add in V2 if data supports it."
• Document non-goals explicitly in every spec.

"What to Stop Doing" Quarterly Review

Every quarter, review the product with assets/strategy/quarterly-product-review.md:

• Which features have <5% usage? → Candidate for removal
• Which initiatives produced no measurable outcome? → Stop or pivot
• Which ongoing costs (maintenance, support) exceed their value? → Sunset
• What are you doing "because we always have" but nobody asked for? → Question

For detailed prioritization patterns and worked examples: see references/prioritization-frameworks.md.

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Product-Market Fit Measurement

PMF is not a binary event. It's a signal you measure across multiple dimensions.

Sean Ellis Test

Survey users: "How would you feel if you could no longer use [product]?"

• Very disappointed: Target >40% for PMF signal
• Somewhat disappointed: Useful but not dependent
• Not disappointed: Not finding value

Use assets/discovery/pmf-survey-template.md for the full survey (combines Sean Ellis + NPS + usage questions).

Retention Curve Analysis

• Plot cohort retention over time (weekly or monthly depending on product cadence)
• Flattening curve = PMF signal (users who stay, stay)
• Declining curve = No PMF (even retained users eventually leave)
• Segment by ICP: you may have PMF in one segment but not another

Engagement Scoring

Define activation precisely (formula + timeframe + data source):

• What actions constitute "activated"? (not just signed up)
• What's the activation window? (first 7 days, first 14 days?)
• What engagement depth separates power users from casual?

Feature Audit

Periodically audit feature usage to identify what to keep, improve, or remove:

• Top 20% features by usage → invest, polish
• Middle 60% → maintain, don't expand
• Bottom 20% → candidate for removal or redesign
• Features with high support cost relative to usage → redesign or sunset

Segmented PMF

PMF varies by segment. Measure separately for:

• ICP vs non-ICP customers
• Free vs paid users
• Self-serve vs sales-assisted
• By company size, industry, or geography

For detailed PMF measurement methodology: see references/pmf-measurement.md.

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Stakeholder Management

Founders manage board members, investors, early customers, co-founders, and (eventually) team leads — often without formal PM training.

Key patterns:

• Board / investors: Update monthly with metrics + decisions + asks. Use narrative format, not slide decks. Lead with "what we learned" not "what we shipped."
• Early customers: They are partners, not just users. Share roadmap intent (not commitments). Ask for input on priorities, not feature requests.
• Co-founder alignment: Weekly sync on priorities. Disagree and commit. Document decisions.
• Saying no to stakeholders: "We're not doing X because [reason tied to strategy]. Here's what we're doing instead and why."

For detailed stakeholder management patterns: see references/stakeholder-management.md.

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What Good Looks Like

• Evidence: 5–10 real user touchpoints or equivalent primary data for material bets.
• Scope: clear non-goals and acceptance criteria that can be tested.
• Learning: post-launch review with metric deltas, guardrail impact, and next decision.

PRDs and Specs

For PRDs/specs and writing-quality requirements, use the templates in ../docs-ai-prd/:

• PRD templates: ../docs-ai-prd/assets/prd/prd-template.md and ../docs-ai-prd/assets/prd/ai-prd-template.md

Optional: AI / Automation

Use only when explicitly requested and policy-compliant.

• AI system lifecycle: assets/ai/ai-lifecycle-template.md
• Agentic workflow docs: assets/ai/agentic-ai-orchestration.md
• AI product patterns: references/ai-product-patterns.md

Navigation

Resources

• references/discovery-best-practices.md
• references/roadmap-patterns.md
• references/delivery-best-practices.md
• references/strategy-patterns.md
• references/positioning-patterns.md
• references/data-product-best-practices.md
• references/interviewing-patterns.md
• references/metrics-best-practices.md
• references/leadership-decision-frameworks.md
• references/operational-guide.md
• references/prioritization-frameworks.md
• references/pmf-measurement.md
• references/stakeholder-management.md
• data/sources.json

Templates

• Discovery: assets/discovery/customer-interview-template.md, assets/discovery/assumption-test-template.md, assets/discovery/opportunity-solution-tree.md, assets/discovery/pmf-survey-template.md
• Prioritization: assets/prioritization/prioritization-scorecard.md, assets/prioritization/kill-criteria-template.md
• Strategy/Vision: assets/strategy/product-vision-template.md, assets/strategy/opportunity-assessment.md, assets/strategy/positioning-template.md, assets/strategy/PRFAQ-template.md, assets/strategy/quarterly-product-review.md
• Data: assets/data/data-product-canvas.md
• Roadmaps: assets/roadmap/outcome-roadmap.md, assets/roadmap/theme-roadmap.md
• Metrics: assets/metrics/metric-tree.md, assets/metrics/okr-template.md
• Ops/Leadership: assets/ops/1-1-template.md, assets/ops/feedback-template.md, assets/ops/a3-debrief.md, assets/ops/negotiation-one-sheet.md

Related Skills

• ../docs-ai-prd/SKILL.md — PRD, stories, and prompt/playbook templates
• ../software-architecture-design/SKILL.md — System design guidance for specs and PRDs
• ../software-frontend/SKILL.md — UI implementation considerations for product specs
• ../software-backend/SKILL.md — Backend/API implications of product decisions
• ../startup-growth-playbooks/SKILL.md — PLG case studies for activation design

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Operational Guide

See references/operational-guide.md for detailed patterns, template walkthroughs, example flows, and execution checklists. Keep SKILL.md as the navigation hub; use assets/ when producing artifacts.

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External Resources

See data/sources.json for official frameworks (Lean Startup, OST, PR/FAQ, OKRs) and AI/LLM safety references.

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Use the quick reference and decision tree above to choose a template, then follow the operational guide for depth.

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Trend Awareness Protocol

IMPORTANT: When users ask recommendation questions about product management tools, frameworks, or practices, use a web search tool to check current trends before answering. If web search is unavailable, use data/sources.json and state clearly what you verified vs assumed.

Trigger Conditions

• "What's the best tool for [roadmapping/product analytics/discovery]?"
• "What should I use for [OKRs/metrics/customer feedback]?"
• "What's the latest in product management?"
• "Current best practices for [discovery/roadmaps/prioritization]?"
• "Is [framework/tool] still relevant in 2026?"
• "[Linear] vs [Jira] vs [other]?" or "[Amplitude] vs [Mixpanel]?"
• "Best approach for [AI product management/agentic products]?"

Required Searches

1. Search: "product management best practices 2026"
2. Search: "[specific tool] vs alternatives 2026"
3. Search: "product management trends January 2026"
4. Search: "[discovery/roadmap/OKR] frameworks 2026"

What to Report

After searching, provide:

• Current landscape: What PM tools/frameworks are popular NOW
• Emerging trends: New tools, methods, or patterns gaining traction
• Deprecated/declining: Frameworks/tools losing relevance
• Recommendation: Based on fresh data, not just static knowledge

Example Topics (verify with fresh search)

• Product management tools (Linear, Productboard, Notion, Coda)
• Analytics platforms (Amplitude, Mixpanel, PostHog)
• Discovery and research tools (Maze, UserTesting, Dovetail)
• Roadmapping approaches (outcome-based, theme-based, now/next/later)
• AI product management patterns
• Prioritization frameworks (RICE, ICE, opportunity scoring)
• OKR and metrics tools

Fact-Checking

• Use web search/web fetch to verify current external facts, versions, pricing, deadlines, regulations, or platform behavior before final answers.
• Prefer primary sources; report source links and dates for volatile information.
• If web access is unavailable, state the limitation and mark guidance as unverified.