Peter Thiel's contrarian approach to innovation emphasizes the importance of finding unique opportunities, which he describes as 'secrets' that others overlook. Thiel, co-founder of PayPal and Palantir, argues there are exactly two kinds of businesses — monopolies and perfect competition — and only one of them actually creates lasting wealth. In perfect competition, all capital gets competed away, like margins in restaurants. Monopolies are symptomatic of creating something genuinely valuable. The frame matters enormously for how you think about AI and work. Last lecture, Jensen Huang showed us that the technical barrier to computing is falling, which means domain expertise rises in relative value. Thiel sharpens that insight with a harder edge. His thesis: imitation is the enemy of value creation. In Shakespeare's time, the word 'ape' meant both primate and imitate — imitation is that deep in human nature. It transmits culture and language, yes, but it also produces peer pressure, bubbles, and the madness of crowds. Education itself, Thiel argues, is structured around going from one to n: observe, imitate, repeat. That is the opposite of innovation. Thiel's framework for escaping imitation starts with how we classify truth. Most people see reality as binary: either something is conventional wisdom that everyone agrees on, or it is an impossible mystery. That binary blinds them to a third category — secrets. Secrets are truths that are hard but discoverable, sitting between the obvious and the unknowable. Companies like Google and Facebook succeeded by identifying and capitalizing on 'secrets' in their respective fields, demonstrating Thiel's approach to innovation. This is where Thiel's thinking cuts directly into the AI and work debate. His contrarian questions — 'the next Mark Zuckerberg will not start a social networking site' — are designed to break imitation thinking. They shift attention from surface identity, the type of company, to the underlying differentiating dimension that made a company unique in the first place. Uniqueness, he argues, is a structural property of every moment in history. It occurs exactly once. Science starts with repeatability; business does not. That asymmetry means copying a successful business model is almost always the wrong move, because the conditions that made it successful were singular. For you, Sergey, the practical implication is this: the fear that AI will replace human workers is, in Thiel's framework, a distraction built on imitation thinking. It assumes the future looks like the present, only with robots doing the jobs. The key question for future work is: what unique human capabilities can be leveraged that AI cannot replicate? Startups succeed because they are small and non-imitative; complexity scales with the square of people, and conformity scales with size. The professionals who will matter most in an AI economy are not the ones who compete with machines on machine terms. They are the ones who ask what only a human, in this specific moment, can uniquely do — and then build a monopoly around that answer.