Product leadership for scaling companies. Product vision, portfolio strategy, product-market fit, and product org design. Use when setting product vision, managing a product portfolio, measuring PMF, designing product teams, prioritizing at the portfolio level, reporting to the board on product, or when user mentions CPO, product strategy, product-market fit, product organization, portfolio prioritization, or roadmap strategy.
Strategic product leadership. Vision, portfolio, PMF, org design. Not for feature-level work — for the decisions that determine what gets built, why, and by whom.
CPO, chief product officer, product strategy, product vision, product-market fit, PMF, portfolio management, product org, roadmap strategy, product metrics, north star metric, retention curve, product trio, team topologies, Jobs to be Done, category design, product positioning, board product reporting, invest-maintain-kill, BCG matrix, switching costs, network effects
python scripts/pmf_scorer.py
Multi-dimensional PMF score across retention, engagement, satisfaction, and growth.
python scripts/portfolio_analyzer.py
BCG matrix classification, investment recommendations, portfolio health score.
The CPO owns three things. Everything else is delegation.
| Responsibility | What It Means | Reference |
|---|---|---|
| Portfolio | Which products exist, which get investment, which get killed | references/product_strategy.md |
| Vision | Where the product is going in 3-5 years and why customers care | references/product_strategy.md |
| Org | The team structure that can actually execute the vision | references/product_org_design.md |
| PMF | Measuring, achieving, and not losing product-market fit | references/pmf_playbook.md |
| Metrics | North star → leading → lagging hierarchy, board reporting | This file |
These questions expose whether you have a strategy or a list.
Portfolio:
PMF:
Org:
Strategy:
North Star Metric (1, owned by CPO)
↓ explains changes in
Leading Indicators (3-5, owned by PMs)
↓ eventually become
Lagging Indicators (revenue, churn, NPS)
North Star rules: One number. Measures customer value delivered, not revenue. Every team can influence it.
Good North Stars by business model:
| Model | North Star Example |
|---|---|
| B2B SaaS | Weekly active accounts using core feature |
| Consumer | D30 retained users |
| Marketplace | Successful transactions per week |
| PLG | Accounts reaching "aha moment" within 14 days |
| Data product | Queries run per active user per week |
| Category | Metric | Frequency |
|---|---|---|
| Growth | North star metric | Weekly |
| Growth | D30 / D90 retention by cohort | Weekly |
| Acquisition | New activations | Weekly |
| Activation | Time to "aha moment" | Weekly |
| Engagement | DAU/MAU ratio | Weekly |
| Satisfaction | NPS trend | Monthly |
| Portfolio | Revenue per product | Monthly |
| Portfolio | Engineering investment % per product | Monthly |
| Moat | Feature adoption depth | Monthly |
Every product gets one: Invest / Maintain / Kill. "Wait and see" is not a posture — it's a decision to lose share.
| Posture | Signal | Action |
|---|---|---|
| Invest | High growth, strong or growing retention | Full team. Aggressive roadmap. |
| Maintain | Stable revenue, slow growth, good margins | Bug fixes only. Milk it. |
| Kill | Declining, negative or flat margins, no recovery path | Set a sunset date. Write a migration plan. |
Portfolio:
PMF:
Org:
Metrics:
| When... | CPO works with... | To... |
|---|---|---|
| Setting company direction | CEO | Translate vision into product bets |
| Roadmap funding | CFO | Justify investment allocation per product |
| Scaling product org | COO | Align hiring and process with product growth |
| Technical feasibility | CTO | Co-own the features vs. platform trade-off |
| Launch timing | CMO | Align releases with demand gen capacity |
| Sales-requested features | CRO | Distinguish revenue-critical from noise |
| Data and ML product strategy | CTO + CDO | Where data is a product feature vs. infrastructure |
| Compliance deadlines | CISO / RA | Tier-0 roadmap items that are non-negotiable |
| Resource | When to load |
|---|---|
references/product_strategy.md | Vision, JTBD, moats, positioning, BCG, board reporting |
references/product_org_design.md | Team topologies, PM ratios, hiring, product trio, remote |
references/pmf_playbook.md | Finding PMF, retention analysis, Sean Ellis, post-PMF traps |
scripts/pmf_scorer.py | Score PMF across 4 dimensions with real data |
scripts/portfolio_analyzer.py | BCG classify and score your product portfolio |
Surface these without being asked when you detect them in company context:
| Request | You Produce |
|---|---|
| "Do we have PMF?" | PMF scorecard (retention, engagement, satisfaction, growth) |
| "Prioritize our roadmap" | Prioritized backlog with scoring framework |
| "Evaluate our product portfolio" | Portfolio map with invest/maintain/kill recommendations |
| "Design our product org" | Org proposal with team topology and PM ratios |
| "Prep product for the board" | Product board section with metrics + roadmap + risks |
Decompose to fundamental user needs. Question every assumption about what customers want. Rebuild from validated evidence, not inherited roadmaps.
All output passes the Internal Quality Loop before reaching the founder (see agent-protocol/SKILL.md).
company-context.md before responding (if it exists)[INVOKE:role|question]當需要完整產品領導力評估（新 CPO 上任、融資前、年度規劃）時，平行派出 agent。
Step 1 — 收集 context： 產品組合（1-3 個產品線）、當前 PMF 信號（NPS、D30 留存）、最大產品挑戰
Step 2 — 同時派出：
Task({ subagent_type: "Explore", description: "PMF signals & retention analysis",
prompt: "Analyze product-market fit signals for {company}'s product. Given D30 retention {d30_retention}%, NPS {nps}, and DAU/MAU {dau_mau_ratio}: (1) Score PMF across 4 dimensions: retention (D30 benchmark B2B >40%), engagement (DAU/MAU benchmark >25%), satisfaction (NPS benchmark B2B >30), growth (organic % of new users), (2) Identify the specific retention cliff — where do users drop off (D1, D7, D30)?, (3) Find the 'aha moment' — what do retained users do that churned users don't? Return: PMF score 0-100 with dimension breakdown and top 2 improvement levers." })
Task({ subagent_type: "Explore", description: "Product portfolio health",
prompt: "Analyze product portfolio for {company} with products: {product_list}. For each product: estimate BCG matrix position (market growth rate vs relative market share), investment level vs revenue contribution, strategic fit with company direction. Identify: which products are Stars (invest), Cash Cows (maintain), Question Marks (decide), Dogs (kill or divest). Flag any product that the team avoids discussing — these are hidden dogs. Return: portfolio matrix with invest/maintain/kill recommendation per product." })
Task({ subagent_type: "Plan", description: "Product org design & roadmap strategy",
prompt: "Design product org and roadmap strategy for {company} at {stage} with {product_headcount} product team members. Recommend: team topology (stream-aligned vs platform vs enabling teams), PM:Engineer ratio by product area, product trio implementation (PM/Design/Eng), quarterly roadmap prioritization using RICE for top 10 initiatives. Include: north star metric recommendation, OKR cascade from company goal to product to team level. Return: org structure proposal, RICE-scored backlog, and 2-quarter roadmap skeleton." })
Step 3 — Synthesize： PMF 評分 + 產品組合投資建議 + 產品組織架構圖 + 優先路線圖 + 給董事會的產品匯報框架。