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Nick's avatar

Two cents... I think you got most of the reasons right: exclusivity, openai relationship, valuation. But you may have missed some key context.

Lawyers at all levels have had a common experience: we trudged through law school, we jumped though the bar exam hoops, we started at the bottom and kept running up whatever hill we chose. Many dropped out, some "made it", almost all became jaded.

Legal tech is similar. For one, most legal tech companies have at least one lawyer-founder. All have the shared experience of building product for, and selling to, lawyers, which isn't always pleasant and is often a longer cycle than other verticals. And it hasn't typically made many unicorns or had a strong identification with Silicon Valley.

In both communities there is a sense that you succeed by being smart, working hard, making the right connections, and paying your dues. Then you are part of a semi-exclusive esoteric club, complete with it's own language, culture, insecurities, heroes, and villains.

This is contrasted by the start-up/SV culture of winning with ideas, hustle, disruption, and VC $. Seniority can be a liability, the idea of a "ladder" of success is antithetical, and disrupting social norms is part of the fun.

AI itself is already unsettling to both legal and LT because, taken to it's logical endpoint, it could render both irrelevant. In this context Harvey enters:

- The founders are a second year biglaw associate and a Google DM engineer, which to the legal/LT communities is coded as "baby lawyer, silver spoon, knows next to nothing" and "silicon valley genius, threat".

- Their website was empty, they did zero PR or marketing early on, they didn't engage with the legal tech community, and reportedly ignored efforts to by the community to engage with them.

- Yet they raise a bunch of money, seemingly have an insiderish relationship with OpenAI, close early notable deals, are given a high valuation.

So the takeaway for many is that these guys were undeservedly given an inside track, have not paid their dues, have an indifferent or even contemptuous attitude towards the LT community of "we don't need you or your path to success", and that they were going to win nonetheless.

Hence the schadenfreude when their product didn't seem to live up to the hype, especially for reasons like "not understanding the market that well" that induced a collective I-told-you-so. (No comment on the fairness of this judgment. You already point out that they have impressive achievements.)

The Casetext comparison is extremely relevant, but I think you missed why Casetext was different. Casetext had already put in 10+ years when GPT-3 was made available. They had built their own AI models trained for legal. They engaged with the legal tech community quite a bit. They struggled! They seemed to be treading water at best when GPT came along. But when GPT did come out, they were uniquely able to implement it (by swapping out their own models) because they had put in the time, they knew the customer, they had built the rest of the machine. My impression was that the LT community was already rooting hard for them when they were acquired and was happy for them even though the acquirer was culturally a villain.

People, especially in legal, like when other people seem to get what they deserve.

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Denis Potemkin's avatar

This is a good read @zach. Including the links to the fans and detractors. I met Winston Weinberg at a conference recently. Very impressive chap. Perhaps a lot of people feel like Jake Barnes: “I mistrust all frank and simple people, especially when their stories hold together.” I totally get that. Especially when it’s not simple.

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