As frontier models from OpenAI, Anthropic, and Google keep improving, AI startups face a harder question: what remains defensible if a model can commoditize the core feature set? a16z General Partner Julie Yoo argues that the most durable companies will be both AI-native and AI-proof. In her view, the scarce product in AI-era healthcare is no longer intelligence or automation alone, but accountability — the ability to own outcomes, carry regulatory and legal burden, and deliver results in the real world. Yoo breaks that idea into three company types. The first is AI-native clinical services, where a company directly provides care instead of merely selling software. AI can lower labor and administrative costs, but licensing, credentialing, malpractice insurance, referral relationships, and operating workflows remain human and regulated. The second is a risk-bearing entity, where a company assumes the financial downside of failed cost control. That can apply to healthcare or even software businesses that charge only when a transaction closes or a customer gets paid. The third is a company that turns AI into an FDA-regulated product, such as diagnostics or drugs, where years of trials, manufacturing, and approval still stand between a model and a marketable therapy. Yoo’s core point is simple: as models get better, intelligence gets cheaper. What becomes valuable is the responsibility that models cannot take on themselves.