Amazon Head of Product on Five Gotchas When Designing AI-Powered Products

What are common mistakes that PMs make when designing AI-powered products? In this webinar, Amazon Head of Product Elio Damaggio speaks on the five common mistakes to look out for when designing (or adding features) to AI-powered products. Product management fundamentals are still the same, but AI can throw good PMs curve balls that hard to hit. Join us to learn how to navigate this new era of AI products.

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Show Notes:

1. Don’t replace your user.
2. Don’t forget a feedback loop.
3. It’s all about context.
4. The UX for AI is not as defined as the UX that we have for all the other software.
5. Start small.
6. Do not ignore the trends.
7. Consider different interfaces besides chat.
8. Continuously monitor to detect model drift and degradation.
9. Understand the differences between B2B and B2C product design.
10. Explainability should be considered early and baked into the product design.
11. Split between who is using the product and who is buying the product is important for B2B.
12. Moving AI into products will happen faster for companies closer to the origin of the tech.
13. Edge and local models may enable new applications and use cases.
14. Decompose problems and solve specific tasks with focused models.
15. Data foundations and feedback loops are important before adding AI.
16. Precision thresholds differ between push and pull interfaces.
17. Control and visibility are important for the user.
18. Context from the user should be gathered organically.
19. IP considerations for models shipped with products.
20. Hybrid systems combining gen AI and traditional software are still emerging.