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Get sarah guo on This Week in AI

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sarah guo

startup investor/helper, founder @conviction. accelerating AI adoption, interested in progress. tech podcast: @nopriorspod

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    Foundation models are commoditizing faster than the application layer can differentiate

    Sarah's core investing thesis at Conviction is that durable value accrues to products that own a workflow, a distribution channel, or proprietary data — not to whoever has the best base model this quarter. Worth pressure-testing: if model quality converges, what actually remains defensible? And if it doesn't converge, does the application-layer thesis quietly break?

    How should policymakers regulate AI without freezing the incumbents in place?

    Compliance regimes tend to favor whoever can afford the lawyers — which is exactly the wrong outcome if the goal is a competitive ecosystem. What's the version of AI regulation that Sarah, as an investor in early-stage companies, would actually welcome rather than simply tolerate?

    What evidence would actually change your mind about AI timelines?

    Most people in the field hold strong views about capability trajectories and rarely articulate a falsifier. Does Sarah have a specific benchmark, capability, or failure mode that would move her from her current position — and what is it?