How to Validate AI Product Ideas and Build a Defensible MVP

93% of US companies plan to increase their AI investments; but 80% of AI projects fail. Countless “cool” demos crash and burn; not because the technology failed, but because they solved the wrong problem. In this lesson, we lay out a proven playbook with 5 tactical steps, each a mindset shift or critical decision point, to validate AI product ideas and build towards defensible MVP. In this invited talk, you will learn:

The “AI Product Opportunity Canvas”

A proprietary framework to assess AI product ideas, inspired by proven processes from Google and successful AI labs

5-Step Playbook to Land an AI-Native MVP

How to evaluate user problems, craft a compelling AI-native value proposition, design for data and defensibility

Real AI-Native Product Success Cases

How AI product leaders and founders are finding the market niche in industries such as healthcare, legal and finance

How to Build Fast Feedback Loops with User and Human Evals

How to set up tight user feedback loops and leverage Human-in-the-Loop (HITL) as your secret validation weapon

Invited Speaker: Roger Jin

ex-Product Lead @Google DeepMind, 2x Founder, AI Strategy Coach

Roger is an ICF-certified coach and a seasoned product leader who has operated at the frontier of AI development and in the trenches of building venture-backed companies.

As Head of Product at Google DeepMind, Roger was a founding member of the product team that launched Gemini, Google’s flagship generative AI product. Before that, Roger led product teams at Amazon Alexa, pushing the boundaries of customer experience for millions of users.

Roger has also co-founded two AI startups, raising over $20M in venture capital and scaling them to a combined $80M+ in annual revenue. He is a graduate of Carnegie Mellon University.

Location: Social Science, Room 110