Designing Products in the AI Era with Handshake AI

What if you could design a product that transforms an entire industry in just 12 months? In this special episode of Product Talk hosted by Products That Count CEO Hoda Mehr, Handshake AI Head of Design Gabe Schindler speaks about designing products in the AI era. Gabe emphasizes storytelling, collaboration, and anticipation. Discover the insider strategies that helped grow a startup from zero to massive scale by reimagining product design principles for artificial intelligence.

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Show Notes:

1. AI has reached the limits of learning from free internet data, requiring expert human input
2. Design in the AI era is about storytelling, not just pixels and interfaces
3. Collaboration across roles (design, engineering, product management) is crucial for AI product success
4. Hiring should focus on low-ego, high-learning potential team members
5. Quality of human data is paramount in AI product development
6. Design with anticipation – prepare for multiple scenarios and user experiences
7. AI interviewing can actually feel more comfortable for candidates than human interviews
8. Rapid growth requires flexible infrastructure and minimal over-investment
9. Ownership of product components should be clear, but collaborative
10. AI product design requires constant adaptation and research
11. The narrative and “why” of a product matters more than current design trends
12. Internal research teams are critical for staying ahead in the AI landscape
13. Accountability comes from giving team members agency over their work
14. AI products need built-in feedback mechanisms (like thumbs up/down)
15. Operational tools and matching systems are as important as the AI itself
16. Product teams should allocate time for innovation and experimental thinking
17. Trust is built through transparent, user-centric design
18. AI development requires understanding user motivations and incentives
19. Successful AI products solve real human problems, not just technological challenges
20. Continuous learning and openness to change are essential in the AI product ecosystem