Why companies are starting to own their AI intelligence
In this Sequoia Capital talk, partner Sonya Huang explains why some AI application companies are beginning to own more of the intelligence inside their products, including model weights, while still using closed-model APIs where they work well. She points to cost, latency, domain performance, and independence as the main reasons, then offers a practical framework covering what to own versus rent, how to organize a small research team, why companies should make their technical work legible, and how evaluations, harnesses, post-training, context, and online learning fit into the stack. The argument matters because competition between AI companies is shifting from the user interface toward who controls and improves the underlying intelligence.
