Strong foundation models do not automatically solve the last mile of real-world service work. This AI on Air clip is excerpted from a recent episode on the @NoPriorsPod channel, and the speaker is Melisa Tokmak @melisatokmak, founder and CEO of @Netic_AI. ▷ The question can labs do this echoes the older can Google do this question: they can handle some core competencies, but they are not investing in everything; for essential services, she sees the leading labs as strong businesses and partners rather than a direct competitive risk. ▷ Enterprises are not asking for rapid experimentation: OpenAI builds products fast and also kills them fast, while Silicon Valley often says Anthropic and Claude pulled ahead in coding assistants through focus, yet the enterprise side shows roughly 20 products, which is hard for industries that need dependable service to trust. ▷ Researchers often want the most generalizable answer, as if AGI will later explain how to serve essential services; but millions of people bring different worries, accents, contexts, and reasons to return, so models alone are not enough, and the harnesses, orchestration, software, and product built on top all have to be excellent.