The Steps

How you can tell if a product will fail in 15 mins

Name

Example: VP at Top Company (ex-Role at Previous Company)

Learn how to quickly spot whether a product solves a real problem or just looks impressive in a demo.

A 15-minute test to tell if a product has real value

Learn a simple structure for understanding how value shows up today: from first use to long-term adoption.

How to think about value clearly in the age of AI

Learn to spot early signals in acquisition, retention, and differentiation that predict whether a product will succeed o

Red flags and green lights across the user journey

In the last 12 months, AI has shifted from a "tech trend" to a market-decimating force. The old playbook of simply "shipping features" is dead; leaders must now build "Contextual Moats" and defensible strategies. This course bridges the gap between Executive Leadership and AI Strategy. We take the rigor of the #1 Ranked Advanced Product Management curriculum and infuse it with the frameworks needed to win in the age of AI. What You'll Get Out of This Course 1. Define Strategic Leverage (Not Just Features) Stop searching for problems to solve with AI. Start with customer problems and identify where AI creates breakthrough leverage. Master the 4 Sources of AI Leverage: Data, Distribution, Trust in UX, and Learning Loops. Learn to build "Contextual Moats" that endure when the underlying models become commodities. 2. Shift from "Roadmaps" to "Planning in Motion" Traditional planning assumes the environment will cooperate long enough to execute. In AI, that assumption breaks. Learn to build a "Sensing Function"—a structured review of model performance and competitor moves. Move from a unit mindset to a systems mindset, creating roadmaps that adapt to new information without descending into chaos. 3. Architect the Human + Agent Workforce Output can now rise through leverage, not just headcount. This isn't about replacing people; it's about changing the mix of work. Learn to design the "Baton Pass": deciding where tasks are repeatable (Agents lead) and where judgment and novelty matter most (Humans lead). Structure your org to scale impact without scaling headcount at the same rate. 4. Master AI Economics &amp; The "Trust" Metric Powerful models cannot compensate for a weak core value proposition. You will master the new P&amp;L: forecasting inference costs that scale linearly and managing the "Cost vs. Quality" trade-off. You will also learn to measure Trust in UX as a first-class metric, setting tolerances for error and building affordances for user control.

Lead the AI Transformation. Don't just witness it

Course syllabus

You'll have 5 hours of class split into two 2.5-hour modules. Each module consists of 60% lecture-style learning and 40% hands-on group exercises. Don't worry about missing a class—you can make up missed classes in a future cohort, and you'll receive the recordings right away.

Saturdays

The capstone project allows you to go through the end-to-end lifecycle of developing a major feature for a consumer company like Facebook, Google Maps, or Amazon, and present it in a product review meeting to the VP of Product at Shopify.

Weekly Capstone Projects (Optional)

We will spend about 20 hours on the core course material plus about 6 hours on Q&amp;A. Timings for each session have been chosen based on what works best for most product people in practice. Recordings for all modules will be made available for you to watch in your Maven account.

Optimized for very busy schedules of PMs / Execs / Managers.

Course schedule

Ambitious Senior PMs, GPMs, &amp; VP Level Leaders: Leaders who are responsible for product success and need to crystallize their skills to lead

Founders &amp; Executives: Those who realize that "be first to market" is no longer enough and need a strategy that provides a durable advantage

Note: This course is not for early-career PMs or those looking for a basic introduction to prompt engineering. This is a strategy and leader

Who is this course for

What you’ll get out of this course

Understand the non-obvious factors that lead to AI product success and how to think strategically when every competitor has access to the same APIs.

Master the AI Leader's Mindset
 

Learn to recognize when your data is a true moat versus when it isn't, and develop specific strategies to build durable competitive advantages that go beyond fragile tech differentiation.

Build Defensible "Contextual Moats"

Implement a proven system to take AI features from Discovery to Design, Develop, and Deploy—ensuring you ship real solutions, not just demos.

Execute with the 4D AI Method

Master the art of forecasting inference costs that scale linearly with usage and optimize the "Cost vs. Quality" trade-off to ensure profitability, not just hype.

Navigate AI Economics & Unit Economics

Build high-conviction roadmaps for high-risk, high-reward AI bets that account for uncertainty and rapid technological change.

Develop Strategic AI Roadmaps

Communicate complex AI product proposals with clarity and precision to secure executive support and cross-functional excitement.

Drive Strategic Alignment & Stakeholder Buy-In

Structure your AI initiatives for scale from day one by defining metrics that matter in a probabilistic world and avoiding the trap of endless experimentation.

Escape "Pilot Purgatory"

Align engineering, design, and data science teams on a unified vision and learn to lead effectively in an AI-first organization.

Lead Cross-Functional AI Teams

Gain insights from guest speakers including Joff Redfern (Ex-CPO Atlassian), Amit Fulay (Generative AI Leader), and Surojit Chatterjee (Ex-CPO Coinbase).

Learn from Elite Product Leaders

Complete a hands-on capstone where you develop and present the end-to-end lifecycle of a major AI feature for a consumer company, applying everything you've learned in a product review format.

Ship a Real AI Product Strategy

In the AI age, nothing matters more than Strategic Leverage. Architect it. Scale it. Master it. Win.

Satyajeet Salgar

Director of Product, Google AI

Joff Redfern

Frm. CPO at Atlassian and VP of Product  Linkedin

Amit Fulay

Vice President of Product, Uber

Cohort 4

Cohort 5

Acquire and develop a critical skill for product managers who are leading and contributing to AI products.

GenAI Product Builder @ Google, ex-Meta

Marily Nika, Ph.D AI/ML

Product Manager AI&ML @ Google

Diego Granados

Senior Data, ML and GenAI Scientist

SHI International

National Association of REALTORS

George Zoto

Senior NLP/AI Scientist

December 2025

Feb 2026

“Does it work?”... “Is it good enough?”... “Can we ship it?”...How do you answer these questions for AI products? You’re responsible for “running evals” but what does that mean?How do you choose the right metrics, interpret fuzzy results, and make a confident decision?This course gives you a framework to do just that.<ul><li>Map user value to evaluation (eval) objectives so your metrics aren’t abstract. Define success then translate it into measurable criteria.</li><li>Choose metrics you can actually maintain: capability, safety, UX friction, latency, cost and “does this reduce support tickets or increase activation.”</li><li>Set ship/no-ship thresholds you can defend to leadership.</li><li>Build lightweight workflows that work in real teams: human review where it matters, automation where it lasts, documentation that drives decisions.</li><li>Consider domain constraints (e.g., healthcare safety) and know what to avoid: silent failures, misleading proxy metrics and tests that don’t reflect production.</li><li>Tie everything to ROI: impact vs unit cost, eval coverage vs reliability, and the minimum viable monitoring you need post-launch.</li></ul>Experience AI evals through a case-based approach with a real AI product that we evaluate together.

Eliminate uncertainty in shipping AI features

Make confident ship or hold decisions for AI features

Translate user value into clear evaluation goals

Choose the right metrics for capability, safety, UX, and cost

Set defensible thresholds leadership will trust

Build lightweight evaluation workflows teams can maintain

Navigate domain constraints and avoid common failures

PMs leading AI features, growth, or platform initiatives

PMs who partner with ML teams and want to set evaluation standards

PMs who need to make clear “ship or hold” calls without doing the engineering

Become a modern, high-velocity PM who explores ideas faster and drives the roadmap forward. Leave with 2 prototypes you can demo to users.

Principal PM at Yelp

Yelp

Gopuff

Google

eSpark

Codeverse

Priya Mathew Badger

Principal PM for Yelp's AI Assistant, Lenny's Community Top 25 contributor 

Cohort 1

The bottleneck in product development has shifted from "how fast can we build?" to "how fast can we prove what’s valuable?"AI prototyping is the #1 skill PMs need to learn to make this shift, yet many are trapped in slow, legacy cycles.As a Principal PM building AI products, I’ve seen the process break down where ideas stay stuck in people's heads because it's hard to carve out time or change longstanding processes.I’ve scaled AI prototyping across our large PM organization by removing these barriers.How this course is different:<ul><li>Small group learning: I am capping this cohort at 30 students so you get personalized feedback, live build time with me, and engaged community of learners</li><li>Focus on product: Build feature and vision ideas with NO coding knowledge</li><li>Go beyond side projects: Learn how to remove barriers and prototype in your day job</li><li>Premium tools and support: Get free paid tier access and fast track support while learning</li></ul>I teach with hands-on learning sharing practical lessons and tips along the way.<a target="_blank" rel="noopener noreferrer nofollow" href="https://www.youtube.com/watch?v=wDA6DslBeqk">See my teaching style in my How I AI episode with Claire Vo</a>Go from feeling like you're falling behind to having a superpower that empowers you to lead high-impact decisions.

Learn how to create and use AI prototypes to improve your established product 

Get experience building AI prototypes for your established product

Get experience prototyping an LLM powered feature

Use prototypes to effectively get feedback and organizational alignment 

Get the playbook for how to integrate it into your product development cycle

Build your network of motivated AI-enabled PMs through small group learning

This is a hands-on course where you will build actual prototypes iterating on your existing product

Have an existing user problem or opportunity in mind

This course will give you hands-on practice and expert guidance but you'll need to put the work in to build and troubleshoot

Curious and motivated to learn

This course requires NO technical knowledge but does involve using multiple AI tools

Basic familiarity with AI prompting

Individual Contributor PMs working on established products

Product leaders (GPM/Director/VPs) interested in leveraging AI prototyping for vision and team upskilling

Job Seeking PMs looking to join companies with modern AI-first product processes

Never again get stuck with feedback piling up. Use AI Analysis that works - reliable, repeatable processes for customer insights in hours.

Ex-Head of Research, Spotify Business

YouTube

Canva

Spotify

Ramp

Caitlin Sullivan

Ex-Head of User Research at Spotify Business, Advisor to AI platforms, Top 100

Does this sound familiar?You're drowning in customer feedback—support tickets, NPS comments, interview notes from five different studies—and your next big product decision is in days.You need to turn all of that into a clear recommendation. Yesterday.You've used AI constantly. But it gives you:<ul><li>Generic themes like "users want better UX" (thanks, very helpful)</li><li>Insights you can't trace back to actual quotes</li><li>That nagging feeling you missed something important</li></ul>You end up re-reading everything manually anyway.AI "saved" you zero time.🙋‍♀️ I've been there. Why trust me?1. Ex-Head of User Research at Spotify Business embedded in Product—sitting alongside PMs shipping B2B products. I know how fast feedback piles up.2. Product teams like Maze hire me to fix prompts behind their AI tools—I help them build the functionality that gets customers better results.3. Trained 450+ people at Canva, YouTube, Figma, Meta, and more to use AI for analysis they can actually defend in high-stakes decisions.4. 1000+ hours testing AI for customer insights. I've cracked what actually works for product decisions. I'm teaching my stress-tested tactics in a NEW version of my highly rated course (4.8/5), just for PMs.<hr>

Build AI analysis systems you can actually bet your roadmap on.

✅ 3-10x faster analysis - What took days now takes hours

✅ Turn messy feedback into decisions, not obvious "insights" you already knew

✅ Synthesize multiple sources into clear stories

✅  Build repeatable AI analysis systems that save you full workdays

✅  Avoid the dreaded "Oh no, AI made that up!" moment with senior leadership

You've used ChatGPT, Claude, or other LLMs. Ideally, your company has an approved LLM so you can apply lessons with your data immediately.

AI Adoption

You're a PM or similar, responsible for making product decisions based on customer feedback.

Your Role

You have access to customer feedback you want to analyze —or are willing practice with my data.

Testing with Data

You're a PM expected to make evidence-based roadmap decisions on solid discovery -- but you often lack time to be as thorough as you'd like.

You've spent hours digging through feedback to find signal - or cleaning up after AI's bad job at analysis tasks. You need speed + rigor.

You're a CPO / Product leader who wants your team to use reliable AI tactics for decisions based on evidence. Your ROI: Level everyone up.