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-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

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

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

product-operating-model