I'm Ken Priore. I've spent 25 years as a lawyer inside technology companies, from PayPal to Grindr to Docusign, where I'm deputy general counsel. I write about what AI does to legal work, and I build to find out if I'm right. The essays live at kenpriore.com. The builds live here. Everything below is an experiment: some finished, some running, one proving that an AI agent's work can be sealed.
AI hits legal work unevenly. These maps show where it lands first, what protects a company when production gets cheap, and where the money is going.
AI hits in-house legal work unevenly. The judgment gap dwarfs the process gap.
LiveFive durable moats of the post-production economy: trust, context, distribution, taste, liability.
LiveWhere legal-tech funding is concentrating, and what the concentration says.
LiveThe research companion to the Certificate of Action: the record, not the model, gets audited.
LiveThese map what each stage of legal work runs on, at whatever depth you have time for, and the record a department needs before a lawyer can step back.
The 13-stage operating model. Start here.
LiveEight intelligence types, five data states, thirteen steps. For legal and product teams.
LiveFour fates of legal knowledge, four daily losses, three commitments. Thirty seconds.
LiveIt's easy to say the record matters. It's harder to get that through peer review, argue it in front of law faculty, and ship a prototype that seals what an agent did.
Fast, accurate, cheap, and defensible. The interactive walkthrough of the fourth requirement.
LiveThe research home: the Certificate of Action paper (ICML 2026), the poster, the Fiduciary's Footprint.
LiveThe working prototype. Tamper-evidence across a live agent pipeline, sealed as a Certificate of Action.
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