This week I'm joined by Helen Fan, a California attorney and chief AI officer at a boutique Silicon Valley law firm, who has spent the last few years at the exact intersection of legal practice and the AI shift most of us are still trying to understand. Helen's path took her from Fangda Partners in Beijing through Columbia Law School, a legal tech hackathon, and into a Silicon Valley firm built to serve AI startup founders, where she found herself reviewing AI-drafted documents from clients who often trusted the AI more than they trusted her.
We talk about her hundred day public experiment building an AI-native law firm with two agents, Morgan and Clio, who challenge and supervise each other's work, and why their disagreements turned out to be more useful than either agent working alone. Helen also makes a sharper argument than the usual billable-hour critique, pointing to the structural economics inside big law partnerships that make shared AI investment genuinely difficult, and shares why in-house adoption of AI is lagging further behind than you might expect from a function built around efficiency.
You'll leave this one with a real framework for what an AI-native law firm actually means, a concrete example of how AI agents checking each other can reduce hallucination, and a provocation about what a lawyer's judgment is for once agents are doing more of the daily work.
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