In consumer AI, it's crucial to let data guide product development, focusing on what truly meets user needs rather than just following trends.

Building good products on top of AI models is incredibly difficult.

Startups should focus on building the best products on top of existing AI models, as competition will come from other startups rather than the AI giants themselves.

The key to success in AI is not just about developing leading technology but also about effectively diffusing and utilizing it across organizations.

The most important aspect of AI development is not just the technology itself but how we can personalize these models to meet individual needs.

The key challenge for AI startups isn't whether wrappers are viable, but how to achieve sustainable differentiation in their products.

The intelligence of AI models is becoming a commodity, and companies need to adapt by focusing on delivering software that solves real-world problems.

In the future, as AI tools proliferate, the obsession with creating excellent products will still require a human touch, as programming an AI to have that level of dedication is a significant challenge.

If your product's success depends solely on the models getting smarter, you're likely building the wrong thing. Instead, create something that improves as the models advance.