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.
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:
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
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 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
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
More from ericgandrade/claude-superskills
mckinsey-strategist
This skill should be used when the user needs structured strategic analysis and high-impact executive recommendations for complex business problems.
36docling-converter
This skill should be used when the user needs to convert documents (PDF, DOCX, PPTX, XLSX, HTML, images) into structured Markdown or JSON using Docling. Also use when the user wants to convert a PowerPoint presentation (.pptx) to Markdown.
28job-description-analyzer
This skill should be used when the user needs to analyze a job posting, calculate resume-to-job match scores, identify skill gaps, and create an application strategy. Use when evaluating fit for a specific role, extracting key requirements, or preparing targeted resume and cover letter materials.
21resume-ats-optimizer
This skill should be used when the user needs to optimize a resume for Applicant Tracking Systems, check ATS compatibility, and analyze keyword match against a job description. Use when a resume is failing screening filters, keyword density is low, or formatting is causing ATS parsing errors.
19academic-cv-builder
This skill should be used when the user needs to format a curriculum vitae for academic positions including faculty, research, or postdoc roles. Use when organizing publications, grants, teaching experience, presentations, and service for tenure-track, lecturer, or research scientist applications.
18resume-tailor
This skill should be used when the user needs to customize a resume for a specific job posting while maintaining truthfulness. Use when adapting an existing resume to match a job description, repositioning experience for a new role, or aligning resume language with target role keywords and requirements.
17