Many of you have written in asking about OpenEvidence. In this episode I walk through what's actually inside the AI clinical search tool that didn't exist before 2023 and is now used by an estimated two-thirds of US physicians. I cover how it differs from ChatGPT, UpToDate, and Google Scholar, how its retrieval-augmented architecture works, where its content comes from, and how the two search modes, standard Consult and Deep Consult, perform in the emerging evaluation literature. I take on the trust question directly and land on a five-question framework for evaluating any AI evidence tool. And I close with what we as a profession aren't talking about enough: the enterprise Epic integrations at Mount Sinai, Sutter Health, and Cedars-Sinai, patient awareness, structural dependence on a single tool, and the business model.The examples are clinical because OpenEvidence is a clinical tool. But the framework and the harder questions apply as much to the AI tools you use in research and teaching, and I've tried to make that portability explicit.

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