i'm hiring ~1,000 lawyers in the next 90 days to help train frontier AI models.
$100–120/hr. 20–40 hrs/week. remote.
like reviewing a first year's memo, except the first-year is an agent.
interested? reply with your practice area and i'll dm you
when we went to raise our series A, every investor we pitched went with atrium and stopped calling us back. so we had to get profitable, which is probably why we're still here.
now there's a new wave of neofirms, and the hard questions haven't changed.
the big one is the exit. most of these are two companies stitched together, a law firm owned by lawyers and a tech company owned by investors. the tech company's only customer is its own law firm, and i've never heard a good answer to who buys that.
the work is the other problem. they're chasing startup contracts and redlines, the exact stuff AI is commoditizing fastest, while the real growth is companies getting sued faster than anyone can staff the defense.
and the AI-native label is for the pitch deck. no client has ever asked their lawyer how native the AI is
Legal Tech is hot right now (so hot). As one of the first attorney hires at Atrium, the OG legal tech startup, I have some thoughts about the new crop of "neofirms" raising money on a similar-sounding pitch. https://t.co/c6GrMv3KMz
learned this the hard way. in the early days of lawtrades we did a few million a year in flat fee legal work for startups, and two things kept it from getting bigger.
the first was the rules. a company that isn't a law firm can't sell most legal services, so we were stuck with narrow, repeatable work like trademarks and immigration filings.
the second was people. every flat fee matter still needed a big ops team behind it, so every bit of growth meant more hiring.
AI is fixing the second one, and the first is starting to change state by state.
a firm that makes more money when a matter takes less time was always the right idea, it just took the law and tech a decade to catch up
@theviclaw i think the structure that fits is something like a multi manager hedge fund, pods of lawyers on shared AI and quality control, paid on profit share instead of equity
The entire VC-backed AI-native law firm thesis hinges on "can you pay top lawyers at least $500k+ AND give them significant equity upside AND keep their clients" and that's why it's a bad venture thesis.
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i think the fastest growing slice of startup legal work will be AI cleanup, like the chatbot drafted IP assignment that looked fine until diligence found what it left out, because the easy work got cheap and the mistakes moved downstream.