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

# Discovery: What problems matter and what solutions might work

# Architecture: What are we building and why now

# Delivery: How do we ship, measure, and learn

# AI-Native: Building products with AI at the core

# Leadership: Operating as Director/CPO

Install the complete collection:

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Progress Tracking

Display progress when navigating the operating model:

[████░░░░░░░░░░░░░░░░] 25% — Phase 1/4: Diagnosing Your Current Challenge
[████████░░░░░░░░░░░░] 50% — Phase 2/4: Selecting the Right Skill(s)
[████████████░░░░░░░░] 75% — Phase 3/4: Applying the Framework
[████████████████████] 100% — Phase 4/4: Connecting Skills into Operating Rhythm

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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

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