product-operating-model
Skill23 starsChanged 9 months agoMITView on GitHub
Index of the Modern Product Operating Model — a collection of composable product skills. Use when user wants an overview of all product skills, doesn't know which specific skill they need, or wants to understand how the product systems connect.
In this repository7 other files it gives its agents.
- abx-strategySkill
- ai-native-productSkill
- product-architectureSkill
- product-deliverySkill
- product-discoverySkill
- product-leadershipSkill
- product-strategySkill
The file
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- Distinctive: line 130
Process over product: If process doesn't serve the user, kill it
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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.
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-leadershipInstall 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-leadershipThe 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 productsproduct-leadership— Operating at Director/CPO level
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 |
Core Philosophy
What This Framework Believes
- Strategy is choice, not documentation — If you haven't said no to something, you don't have a strategy
- Prototypes over PRDs — A working prototype communicates more than any slide deck
- Outcomes over outputs — Teams are accountable for results, not deliverables
- Learning velocity is the meta-metric — The team that learns fastest wins
- AI is baseline, not bonus — Coming to a meeting without AI-assisted prep is like coming without reading the doc
- 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
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 |
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 |
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 |
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
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"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
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
License
MIT License — use freely, adapt to your context, share improvements.
Modern Product Operating Model v1.0 — January 2026
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