How to Know What AI Products to Build

Hosted by Hilary Gridley, Tal Raviv, and Aman Khan

Tue, Feb 10, 2026

7:00 PM UTC (1 hour)

Virtual (Zoom)

Free to join

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How to Become a Supermanager with AI
Hilary Gridley
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What you'll learn

Turn everyday friction into testable product ideas

Learn a systematic workflow for capturing ideas as they emerge and rapidly building testable MVPs

Validate both market fit and technical feasibility

Discover how to test whether people want your idea. Use AI coding agents (with no code) to learn what it takes to build.

Filter for retention, not just novelty

Understand why most AI products fail at keeping users engaged and how to avoid this trap

Why this topic matters

AI has made building cheap, but knowing what to build has never been harder. This workshop gives you a repeatable system for validating ideas through real usage and technical prototyping, so you can distinguish between novelty and lasting value. Whether you're building side projects or managing a roadmap, you'll learn to filter for what's actually worth building.

You'll learn from

Hilary Gridley

Product Leader (Whoop, Dropbox, Nike)

Hilary led Core Product at WHOOP, overseeing the company's AI coaching platform and core experience. A longtime product builder, she also teaches best-selling courses on practical AI for managers and writes a popular newsletter on AI-native leadership. Her work focuses on how AI is reshaping how we work, think, build, lead, and live.

Tal Raviv

Early PM @ Patreon, Riverside, Wix, AppsFlyer

Tal has helped over 22,000 product leaders build AI product sense by using AI agents for real work, including PMs at Apple, Google, Amazon, Microsoft, Meta, and Stanford University. Tal's writing about AI agents and PM productivity have been featured on Lenny's Newsletter.

Aman Khan

AI Product leader at Arize AI, Spotify, Cruise, Zipline, and Apple

Aman is Head of Product at Arize AI, an AI Development platform used by companies like Uber, Duolingo, Reddit, Instacart, and Booking.com. He recently led a popular Deep Learning course on Evaluating AI Agents, and his writing on AI product management has been featured by Lenny's Newsletter.

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