A Comprehensive Revision Plan for The Product Director Book
Analysis completed: January 5, 2026
Executive Summary
I've reviewed all 17 chapters and 3 appendices of your book. The core insight is this: the fundamentals you wrote about remain surprisingly relevant, but the "how" of product direction is being revolutionized by AI. Your timing is perfect—we're at an inflection point where this book could become the definitive guide for a new generation of Product Directors.
Current State Assessment:
Several chapters have strong foundational content (Vision, Decision Making, Communication, First 30 Days)
Many chapters are incomplete with placeholder text (Research & Discovery, Team, Analytical, Product Line)
Some content is duplicated (Vision content appears in both Ch. 3 and Ch. 4)
The "Modern Tech" chapter is outdated and needs complete reimagining
Examples reference 2019-era companies and need updating
Recommended New Positioning:
"The definitive guide to leading product teams when AI can prototype in hours, analyze data instantly, and ship faster than ever. What becomes the irreplaceable value of a great Product Director?"
Proposed New Book Structure
Part I: Foundations (Timeless Principles)
Cover
The First 30 Days (exists, needs AI assessment additions)
Vision (exists, strong content)
Strategy (exists, needs deduplication and refresh)
Decision Making (exists, strong content, add AI decision support)
Research & Discovery in the AI Era (major rewrite needed)
Product-Market Fit (exists, refresh with AI validation methods)
Roadmap & Priorities (exists, needs AI prioritization frameworks)
Product Design & Prototyping (rewrite for AI-assisted design)
Part III: Leading Humans + AI
The AI-Augmented Product Team (new chapter)
Managing Product Managers (rename from "Product Manager", refresh)
Building & Scaling Teams (exists as "Team", major rewrite)
Communication (exists, strong content, add AI communication tools)
Part IV: Technical Fluency for Directors
AI-Native Product Development (replace "Modern Tech")
Analytics & Data in the AI Age (replace "Analytical")
The New PM Skillset (new chapter)
Part V: Advanced Topics
Branding & Storytelling (exists, light refresh)
Product Line & Portfolio (exists, needs completion)
Ethics & Responsible AI Products (new chapter)
Appendices
Appendix A: AI Toolkit for Product Directors (complete rewrite)
Appendix B: Books (exists, add AI/ML books)
Appendix C: Blogs & Resources (exists, needs major update)
Appendix D: Prompts & Templates (new)
Chapter-by-Chapter Analysis
Chapter 1: Cover
Status: 🟡 Placeholder content
Content: Lorem ipsum placeholder text, book title, author name
Recommendation: Complete rewrite needed
AI Angle: Update subtitle to reflect AI focus
Suggested new subtitle: "Leading Product Teams in the Age of AI"
Chapter 2: The First 30 Days
Status: 🟢 Strong content (just added from PDF)
Content: Comprehensive guide to assessment period - product, role, team, business, dynamics
Recommendation: Keep core content, add AI-specific assessments
AI Additions Needed:
Assess the team's AI fluency and tooling maturity
Assess how AI is currently being used (or not) in product development
Assess technical debt related to AI/ML infrastructure
Assess competitors' AI capabilities
New section: "Assessing AI Readiness"
Chapter 3: Vision
Status: 🟢 Strong content
Content: JFK moon speech analysis, why visions matter, mission vs vision, communicating vision, examples (Microsoft, IBM, Tesla, Google)
Recommendation: Keep core framework, update examples
AI Angle:
Add section on "Vision in an AI-First World"
How AI changes the "10-year horizon" (things move faster now)
New examples: OpenAI, Anthropic, companies with AI-centric visions
The tension between AI capabilities expanding and vision stability
Chapter 4: Strategy
Status: 🔴 Duplicated content + incomplete
Content: Duplicates much of Vision chapter, plus strategy models (Blue Ocean, Porter), Google/Tesla examples
Recommendation: Major restructure needed
Issues:
First half is copy of Vision chapter - remove duplication
Strategy models section is incomplete
"STRATEGY SPRINT" mentioned but not developed
AI Additions Needed:
AI as a strategic lever (build vs buy vs partner)
Platform strategies in AI era
Defensive moats when AI commoditizes features
Speed as strategy when AI accelerates development
Chapter 5: Roadmap & Priorities
Status: 🟡 Partial content, incomplete
Content: Sources of ideas (gut feeling, iterations, experiments, tech, research), anti-roadmap concept, 666 roadmap framework
Recommendation: Complete and refresh
Strengths: Good framework with anti-roadmap and creative destruction
Issues: Incomplete sections, some content bleeds into PMF
AI Additions Needed:
AI-assisted prioritization (using Claude/AI to analyze trade-offs)
Rapid prototyping changing roadmap velocity
"Experiments" section needs AI experimentation
How AI changes the "cost" calculation of trying new ideas
Chapter 6: Research & Discovery
Status: 🔴 Mostly incomplete
Content: Market research intro, SpaceX example (incomplete), customer insights (Blacklane example)
Recommendation: Complete rewrite
Current Issues: Heavy use of "xxx" placeholders, broken structure
AI Transformation Opportunity:
AI-powered user research synthesis
Using LLMs to analyze customer feedback at scale
AI personas and simulated user testing
Competitive intelligence automation
Real-time insight generation
Qualitative research at quantitative scale
Chapter 7: Product-Market Fit
Status: 🟡 Partial content
Content: PMF definitions (Andreessen, Ries), Superhuman system, growth loops mention
Recommendation: Complete and refresh
Strengths: Good Superhuman PMF framework reference
Issues: Growth loops section incomplete, AARRR model mentioned but not developed
AI Additions Needed:
AI-assisted PMF measurement
Using AI to identify "very disappointed" user segments
Faster iteration to PMF with AI prototyping
AI for cohort analysis and prediction
Chapter 8: Product Design
Status: 🟡 Partial content
Content: Information Architecture focus, "Don't Make Me Think" principles, taxonomy basics
Recommendation: Major expansion needed
Current Issues: Very narrow focus on IA only, needs broader design coverage
AI Transformation Opportunity:
AI-assisted design systems
Generative UI/UX
AI prototyping tools (Figma AI, v0, etc.)
The changing role of Product Designers
When AI designs vs when humans design
Accessibility automation
Chapter 9: Product Line
Status: 🔴 Mostly placeholder
Content: Taxonomy definitions (product line, product, variant, component) - mostly lorem ipsum
Recommendation: Complete rewrite needed
New Direction:
Portfolio management in AI era
AI features as horizontal vs vertical additions
Platform thinking and AI capabilities
Managing multiple AI-powered products
Chapter 10: Branding
Status: 🟡 Partial content
Content: Storytelling framework (hero, dream, mentor, adventure), Uber and Airbnb examples
Recommendation: Complete and refresh
Strengths: Good storytelling framework
Issues: Incomplete, ends abruptly, examples outdated
AI Angle:
Brand voice in AI interactions
Personalization vs brand consistency
When AI speaks for your brand
Trust and AI transparency
Chapter 11: Communication
Status: 🟢 Good content
Content: Ethos/credibility framework, presentation skills, consistency messaging
Recommendation: Keep core, add AI tools
Strengths: Strong framework on credibility and consistency
Issues: Incomplete (ends mid-section)
AI Additions Needed:
AI-assisted presentation creation
Using AI to prepare for stakeholder meetings
Communication in remote/async AI-augmented teams
Communicating AI capabilities to non-technical stakeholders
Chapter 12: Decision Making
Status: 🟢 Strong content
Content: Product principles (Facebook's "move fast"), prioritization frameworks, Intercom R&D principles example
Recommendation: Keep core framework, add AI decision support
Strengths: Excellent content on principles-based decision making
AI Additions Needed:
AI as decision support (not decision maker)
Using AI to model scenarios and trade-offs
When to trust AI recommendations vs human judgment
Speed of decisions when AI reduces uncertainty
New principles for AI-era products
Chapter 13: Assessment
Status: 🔴 Duplicate content
Content: Overlaps significantly with "The First 30 Days" chapter
Recommendation: Merge into First 30 Days or repurpose
Options:
Delete and merge relevant content into Ch. 2
Repurpose as "Continuous Assessment" - ongoing product health checks
Transform into "AI Maturity Assessment" framework
Chapter 14: Product Manager
Status: 🟡 Partial content
Content: Trust building (competence, character, connection), energy, courage, consistency
Recommendation: Complete and rename
Suggested Title: "Managing Product Managers"
Strengths: Good framework on trust and leadership
Issues: Incomplete, many placeholder sections
AI Additions Needed:
The new PM skillset (AI fluency required)
Evaluating PM effectiveness in AI-augmented environment
Training PMs on AI tools
Career paths for PMs in AI era
Chapter 15: Team
Status: 🔴 Mostly incomplete
Content: Hiring principles (passion, coach-ability, mission), mostly placeholders
Recommendation: Complete rewrite
AI Transformation Opportunity:
Smaller teams, bigger output with AI
AI as a "team member" - how to think about it
Skills to hire for in AI era
Restructuring teams around AI capabilities
The "1-person startup" phenomenon and what it means for teams
Chapter 16: Analytical
Status: 🔴 Mostly incomplete
Content: Statistics intro, Fermi estimation mention, retention basics, painted door testing
Recommendation: Complete rewrite
New Title Suggestion: "Analytics & Data in the AI Age"
AI Transformation Opportunity:
AI-powered analytics (natural language queries)
Predictive analytics for product decisions
Real-time insights vs batch analysis
When AI analysis replaces manual analysis
Data quality in AI era
Chapter 17: Modern Tech
Status: 🔴 Outdated, needs complete rewrite
Content: Programming languages basics, AI intro (outdated), video streaming
Recommendation: Complete reimagining
Current Issues: Content is from ~2019, completely outdated AI section
New Title Suggestion: "AI-Native Product Development"
New Content:
LLMs and foundation models for PDs
AI coding assistants (Claude Code, Cursor, GitHub Copilot)
AI infrastructure basics (APIs, fine-tuning, RAG)
Build vs buy vs API decisions
Technical debt in AI systems
AI safety and alignment basics for PDs
The new stack: what PDs need to understand
Status: 🔴 Empty
Content: Just title
Recommendation: Create comprehensive AI toolkit
Suggested Content:
Assessment templates (First 30 Days + AI Readiness)
Vision/Strategy canvas
AI Tool evaluation framework
Prompt templates for common PD tasks
Meeting agenda templates for AI-era rituals
OKR templates with AI considerations
Appendix B: Books
Status: 🟢 Strong content
Content: 20+ book summaries (Crossing the Chasm, Zero to One, High Output Management, etc.)
Recommendation: Keep and expand
Books to Add:
"The AI-First Company" by Ash Fontana
"Prediction Machines" by Agrawal, Gans, Goldfarb
"Working Backwards" by Bryar & Carr
"Inspired" and "Empowered" by Marty Cagan
AI/ML books for non-technical leaders
Claude's Constitutional AI paper (for ethics)
Appendix C: Blogs
Status: 🔴 Mostly empty
Content: Just 2 blog references
Recommendation: Major expansion
Suggested Sources:
Anthropic's research blog
Lenny's Newsletter
Reforge
First Round Review
a]6z (updated)
AI-focused product blogs
Key AI researchers to follow
New Chapters Recommended
NEW: The AI-Augmented Product Team
Rationale: This is the heart of the book's new thesis
Content:
What changes when AI can do 10x the work
The new team structure
AI tools in the product development workflow
Human-AI collaboration patterns
Case studies of AI-augmented teams
NEW: The New PM Skillset
Rationale: PMs need new skills in AI era
Content:
Prompt engineering as a PM skill
Technical fluency requirements (what's changed)
AI evaluation and testing
Working with ML engineers
The PM as "AI orchestrator"
NEW: Ethics & Responsible AI Products
Rationale: Critical topic for modern PDs
Content:
AI ethics frameworks
Bias and fairness in AI products
Transparency and explainability
User consent and data use
Regulatory landscape (EU AI Act, etc.)
NEW: Appendix D - Prompts & Templates
Rationale: Practical value for readers
Content:
PRD writing prompts
Competitive analysis prompts
User research synthesis prompts
Strategy document prompts
Communication/presentation prompts
Key Themes to Weave Throughout
Speed as the new currency - AI compresses timelines, what does this mean for planning?
Smaller teams, bigger impact - The rise of the "AI-leveraged" small team
Judgment over execution - When AI handles execution, PD value shifts to judgment
Human + AI collaboration - Not replacement, augmentation
New moats - When features are commoditized by AI, what creates defensibility?
Continuous learning - The AI landscape changes monthly, how to stay current
Next Steps
When you wake up, we can:
Discuss and refine this plan - Any chapters you want to prioritize or change?
Start with a specific chapter - I'd suggest starting with Chapter 17 (AI-Native Product Development) as it sets the technical foundation
Create the new chapter structure - Reorganize the Notion pages to match the proposed structure
Begin writing - I can help draft new content or revise existing content
Update examples - Refresh all case studies to 2024-2026 companies and situations
Looking forward to building this with you! 🚀