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
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 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 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 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 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 │ └─ Leadership / Team Ops? ├─ 1:1 meeting? → 1-1 template ├─ Giving feedback? → Feedback template (SBI model) ├─ Post-incident? → A3 debrief └─ Negotiation? → Negotiation one-sheet (Voss)
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. 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 data/sources.json
Templates
Discovery: assets/discovery/customer-interview-template.md, assets/discovery/assumption-test-template.md, assets/discovery/opportunity-solution-tree.md Strategy/Vision: assets/strategy/product-vision-template.md, assets/strategy/opportunity-assessment.md, assets/strategy/positioning-template.md, assets/strategy/PRFAQ-template.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 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.
External Resources
See data/sources.json for official frameworks (Lean Startup, OST, PR/FAQ, OKRs) and AI/LLM safety references.
Use the quick reference and decision tree above to choose a template, then follow the operational guide for depth.
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 Search: "product management best practices 2026" Search: "[specific tool] vs alternatives 2026" Search: "product management trends January 2026" 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