Michael Hirsch

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Most companies treat AI ethics like legal review—something to avoid lawsuits. That's why their frameworks sit unused while teams ship features that surprise users. Ethics isn't compliance. It's a product decision. Five principles for feature reviews: Transparency, Fairness, Accountability, Privacy, Safety. Each includes questions to ask and red flags to catch problems before they ship. No philosophy degree needed. No committees. Just consistent decision-making you can defend and improve.The goal isn't perfect ethics—it's building better products.

The 5 Principles for Ethical AI Decisions


Stop getting lost in AI meetings because of confusing jargon. This 2-page glossary gives you the essential AI terms that actually matter for product decisions, explained in plain English with practical examples. What you'll get:<ul><li>15 key terms from AI and GenAI to RAG and "vibe coding"</li><li>Simple definitions with real-world examples</li><li>Product-focused explanations (not academic theory)</li></ul> Perfect for product managers who need to speak AI fluently without becoming AI experts.

AI for Product Managers: The Essential Terms You Actually Need to Know


Stop missing critical insights in user interviews. This practical checklist covers pre-conversation preparation, in-the-moment techniques, and post-interview reflection to help you extract maximum value from every user conversation. Includes scenario-specific tips for team meetings and stakeholder conversations beyond just user research.

Active Listening for User Interviews: A Practical Checklist for Product Managers


Product leaders make many AI delegation decisions daily. Most are winging it based on gut feel and urgency. This two-page guide gives you four strategic questions that separate systematic leaders from reactive managers. The same framework I use that's saved countless hours while improving outcomes. What's inside:<ul><li>Four-question decision framework with examples</li><li>Quick shortcuts for common scenarios</li><li>Common pitfalls that trap experienced leaders</li></ul> Start thinking strategically about where human effort creates disproportionate value.

AI or Human? Four Questions to Stop Winging Delegation Decisions


Stop treating AI like a magic 8-ball. Most product managers use AI tools without understanding when they're reliable, when they're hallucinating, and when human judgment should override algorithmic suggestions. This checklist covers the essential competencies every PM needs: recognizing AI limitations, spotting bias, structuring effective prompts, and identifying when AI is being overly agreeable instead of intellectually honest. Your next strategic decision could be enhanced or undermined by how well you understand your AI tools.

Basic AI Literacy Checklist for Product Managers


Most product teams approach AI adoption chaotically—some people experimenting with ChatGPT, others avoiding it entirely, with no clear strategy for building team-wide capabilities. This framework gives you the 6 essential competencies every product team needs to move from random AI experiments to strategic AI advantage. Whether you're a product leader building AI-ready teams or a PM wanting to level up your own capabilities, this framework gives you the structured approach that separates successful AI adoption from expensive experiments.

From AI Chaos to AI Confidence: The Strategic Competencies Framework


Discover the six distinct roles every successful product leader must master. This visual framework breaks down the strategic, operational, and interpersonal competencies that separate great product leaders from the rest. Whether you're transitioning from PM to leadership or looking to strengthen your current leadership approach, this framework provides a clear roadmap for development and self-assessment.

The Six Personas of Product Leadership Framework


Product managers who drive strategy, development, and launch of products.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Developing leadership skills — inspiring teams, building culture, navigating organizational complexity, and driving results through others.

Stop managing AI chaos. Build systematic capabilities that drive measurable impact using frameworks previously tested with enterprise teams.

Product Leadership + AI Expert

Product Leadership + AI Strategy | Ex-Sony, Qualcomm, T-Mobile | UW Professor

Build an AI-confident Product Team

Senior Technical Product Manager, Core Tech

Associate Director

Product Strategy Consultant

Director of Product

Senior Product Director

(In-between jobs) Senior Technical Product Manager 

Digital Media Product Consultant

CPTO

Google

Amazon

The Boeing Company

PayPal

Qualcomm

Your team is using AI—but it's chaos. Everyone's got different tools. Someone swears by ChatGPT, another uses Claude. No one can explain what's working. Your "AI strategy" is random experiments with no measurable impact.Other product leaders are building systematic capabilities, transforming teams, and getting executive recognition.This course moves you from AI chaos to AI confidence.In three weeks, you'll:<ul><li>Assess your team's AI readiness using a 6-competency framework</li><li>Design systematic upskilling plans that build real capability</li><li>Build AI product strategies with clear metrics and timelines</li><li>Lead governance decisions that balance innovation with responsibility</li></ul>What makes this different: You work on your actual challenges—not case studies. You use frameworks I've developed with enterprise product teams. You create implementation plans for your context, not generic best practices.Real outcomes from past students: Kate was promoted to Group Product Manager and now leads her company's AI development team. Dan launched his company's AI Studio despite having no coding experience.No technical background required. Just product leadership experience and commitment to execution.

While Your Peers Position Themselves as AI Leaders, Where Does That Leave You?


Diagnose exactly why your team's AI efforts aren't driving business impact

Turn random AI experimentation into systematic capability-building that scales

Make AI governance decisions that protect users without killing innovation

Walk away with implementation plans, not just notes—ready to execute immediately

Product Managers stuck taking notes while less experienced colleagues lead AI initiatives because they can articulate strategic value better

Senior PMs recently promoted to team leadership discovering that building AI-capable organizations requires completely different skill sets

Product Leaders managing AI experimentation theater: everyone uses different tools, no one can explain what works, leadership wants answers

Learn directly from Michael Hirsch

Michael Hirsch

Courses

Build an AI-confident Product Team

Lightning Lessons

How to "Be Strategic" When No One Will Teach You

Build an AI Agent to Turn Feature Release to Instant Revenue

Learn When Not to Trust AI

Create an AI Agent to Stop the Feature Request Madness

AI Review Mining: Turn Customer Feedback into Strategy Gold

Coaching Conversations Made Easier: AI for Product Leaders

Resources

Active Listening for User Interviews: A Practical Checklist for Product Managers

AI for Product Managers: The Essential Terms You Actually Need to Know

AI or Human? Four Questions to Stop Winging Delegation Decisions

Basic AI Literacy Checklist for Product Managers