Product Operating Model

Modern Product Operating Model

> "A modern product operating model starts with clear strategic intent, continuously discovers customer problems, turns them into value-based bets, structures solutions into product blocks and features, executes with tight GTM and measurement loops, and constantly feeds learning back into strategy."

This is a collection of 6 composable skills for product leadership. Each skill is standalone but designed to work together as a complete operating system.

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Quick Start

Install the skill you need:

# Strategy: Where to play and how to win
npx skills add yannickYamo/skills/product-strategy

# Discovery: What problems matter and what solutions might work
npx skills add yannickYamo/skills/product-discovery

# Architecture: What are we building and why now
npx skills add yannickYamo/skills/product-architecture

# Delivery: How do we ship, measure, and learn
npx skills add yannickYamo/skills/product-delivery

# AI-Native: Building products with AI at the core
npx skills add yannickYamo/skills/ai-native-product

# Leadership: Operating as Director/CPO
npx skills add yannickYamo/skills/product-leadership

Install the complete collection:

npx skills add yannickYamo/skills/product-strategy
npx skills add yannickYamo/skills/product-discovery
npx skills add yannickYamo/skills/product-architecture
npx skills add yannickYamo/skills/product-delivery
npx skills add yannickYamo/skills/ai-native-product
npx skills add yannickYamo/skills/product-leadership

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The Four Systems

┌─────────────────────────────────────────────────────────────────┐
│                    STRATEGY SYSTEM                              │
│  "Where do we play and how do we win?"                          │
│  Cadence: Quarterly │ Skill: product-strategy                   │
├─────────────────────────────────────────────────────────────────┤
│                    DISCOVERY SYSTEM                             │
│  "What problems matter and what solutions might work?"          │
│  Cadence: Weekly │ Skill: product-discovery                     │
├─────────────────────────────────────────────────────────────────┤
│                    PRODUCT SYSTEM                               │
│  "What are we building and why now?"                            │
│  Cadence: Sprint-level │ Skill: product-architecture            │
├─────────────────────────────────────────────────────────────────┤
│                    DELIVERY SYSTEM                              │
│  "How do we ship, measure, and learn?"                          │
│  Cadence: Continuous │ Skill: product-delivery                  │
└─────────────────────────────────────────────────────────────────┘
                    ↑                              │
                    └──── Learning feeds back ─────┘

Overlay skills:

• ai-native-product — Modifications for AI-powered products
• product-leadership — Operating at Director/CPO level

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Which Skill Do I Need?

| I want to... | Use this skill | |--------------|----------------| | Define product strategy | product-strategy | | Create a strategy canvas | product-strategy | | Define ICP and Anti-ICP | product-strategy | | Set pricing strategy | product-strategy | | Choose GTM motion (PLG vs SLG) | product-strategy | | Structure strategic bets | product-strategy | | Set up weekly discovery rhythm | product-discovery | | Build an Opportunity Solution Tree | product-discovery | | Run assumption tests | product-discovery | | Create interview snapshots | product-discovery | | Structure product into blocks | product-architecture | | Create a bet backlog | product-architecture | | Build a roadmap | product-architecture | | Write solution briefs | product-architecture | | Plan staged rollout | product-delivery | | Set up metrics hierarchy | product-delivery | | Run bet retrospectives | product-delivery | | Execute GTM launch | product-delivery | | Build AI agent products | ai-native-product | | Manage agency-control tradeoffs | ai-native-product | | Set up continuous calibration | ai-native-product | | Lead product organization | product-leadership | | Manage product portfolio | product-leadership | | Communicate to board/executives | product-leadership |

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Core Philosophy

What This Framework Believes

1. Strategy is choice, not documentation — If you haven't said no to something, you don't have a strategy
2. Prototypes over PRDs — A working prototype communicates more than any slide deck
3. Outcomes over outputs — Teams are accountable for results, not deliverables
4. Learning velocity is the meta-metric — The team that learns fastest wins
5. AI is baseline, not bonus — Coming to a meeting without AI-assisted prep is like coming without reading the doc
6. Focus is a superpower — 1-3 P0 priorities maximum

What This Framework Rejects

• PM Theater: Polishing documents nobody reads
• Decision by committee: Consensus produces mediocre products
• Annual planning fiction: You don't know what to build a year from now
• Process over product: If process doesn't serve the user, kill it
• Feature factories: Building what stakeholders request vs. solving real problems

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The Learning Loop

The systems connect in a continuous learning loop:

STRATEGY defines where to play and how to win
    ↓
DISCOVERY finds problems worth solving
    ↓
PRODUCT structures bets and roadmap
    ↓
DELIVERY ships and measures
    ↓
LEARNING feeds back to STRATEGY
    ↑
    └─────────────────────────────────────┘

Information Flow

| From | To | What Flows | |------|-----|-----------| | Strategy | Discovery | ICP, JTBD priorities, strategic bets | | Discovery | Product | Validated opportunities, solution candidates | | Product | Delivery | Bets, solution briefs, success metrics | | Delivery | Discovery | Usage data, feedback, outcome evidence | | Delivery | Strategy | Market learning, competitive signals, bet results |

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Three Operating Modes

| Dimension | 0→1 Mode | Scaling Mode | AI-Native Mode | |-----------|----------|--------------|----------------| | Strategy refresh | Weekly pivots | Quarterly | + Agency-control decisions | | Team structure | 4-6 builders | Multiple trios | + ML engineers | | Block focus | Single block | Multi-block | + Calibration metrics | | Discovery | Founder-led | Systematic | + Observe AI interactions | | Delivery | Ship daily | Staged rollout | + Agency graduation | | Planning | 4-6 weeks | 12-18 months | + Continuous calibration |

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Skill Collection

Core Skills

| Skill | System | What It Contains | |-------|--------|------------------| | product-strategy | Strategy | Mission, ICP, JTBD, Positioning, Pricing, GTM, Bets | | product-discovery | Discovery | Continuous discovery, OST, Assumption testing | | product-architecture | Product | Blocks, Bet backlog, Roadmap, Solution briefs | | product-delivery | Delivery | Dual-track, Staged rollout, Measurement, GTM execution |

Overlay Skills

| Skill | Purpose | When to Use | |-------|---------|-------------| | ai-native-product | AI product development | Building products with AI at the core | | product-leadership | Director/CPO operating | Leading product organizations |

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Templates Included

Each skill includes ready-to-use templates:

product-strategy:

• Strategy Canvas (1-page)
• ICP Scorecard
• Strategic Bet
• Positioning Statement

product-discovery:

• Interview Snapshot
• Opportunity Solution Tree
• Assumption Test

product-architecture:

• Block Portfolio
• Bet Backlog
• Solution Brief

product-delivery:

• Rollout Checklist
• Metrics Hierarchy
• Bet Retrospective

ai-native-product:

• Agency Graduation Checklist
• Calibration Plan

product-leadership:

• Portfolio Review
• Board Metrics
• Operating Rhythm

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Using with Claude

For strategy work:

"Help me create a strategy canvas for [product]"
"Define ICP and Anti-ICP for [market]"
"Structure 3 strategic bets for [objective]"

For discovery work:

"Set up my weekly discovery rhythm"
"Build an OST for [outcome metric]"
"Design an assumption test for [hypothesis]"

For product architecture:

"Help me structure [product] into capability blocks"
"Convert this opportunity into a bet"
"Write a solution brief for [feature]"

For delivery:

"Plan a staged rollout for [feature]"
"Set up metrics hierarchy for [product]"
"Run a bet retrospective"

For AI products:

"I'm building an AI agent — what's different?"
"Help me plan agency graduation for [feature]"
"Set up continuous calibration"

For leadership:

"How do I allocate resources across products?"
"Prepare board-level metrics"
"Design my weekly operating rhythm"

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Sources & Influences

This framework synthesizes insights from:

• Teresa Torres — Continuous Discovery Habits, Opportunity Solution Trees
• Marty Cagan — INSPIRED, EMPOWERED, Product Operating Model
• Richard Rumelt — Good Strategy Bad Strategy, Strategy Kernel
• April Dunford — Obviously Awesome, Positioning
• Gibson Biddle — Product strategy frameworks
• Lenny Rachitsky — PM research and interviews
• Aishwarya Goel & Kiriti Gavini — CCCD, Agency-Control Trade-off

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About

Author: Yannick Maurice Background: 13+ years in product leadership across semiconductors, LiDAR, autonomous vehicles, energy systems, and AI Philosophy: Learning velocity over planning perfection

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License

MIT License — use freely, adapt to your context, share improvements.

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Modern Product Operating Model v1.0 — January 2026

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: yannickYamo
• Source: yannickYamo/skills
• License: MIT

Install and usage instructions live in the source repository linked above.