Inside Harvey AI: $11B, $300M ARR, 960 Employees, 12 Offices, 13 Trillion Tokens a Month

[00:00] The purpose of Harvey, Harvey AI, Harvey AI, if you're reviewing a million documents, is how do you check that its work is accurate? So you were at 100 million in ARR last August, and now you're nearing 300 million. What's been driving that? It's 100% product. Our token usage in January was 1 trillion, and this month it'll probably be like 12 or 13 trillion. Our DAU over MAU at the beginning of the year was around 36%. Right now it's like 51, 52%. [00:30] We switched our entire infrastructure to that. And once we did that, usage was started doubling. [00:46] You asked about a sword. We could start with this. We could start with this. So I actually... [00:50] This is probably the best thing. I also personally have a replica of Frostmourne. [00:55] But that's in my apartment. I don't know what that is. It's Arthas's sword. [00:59] uh world warcraft got it yeah anyway of course my bad my bad it's an awesome sword but i've seen too many people do sword things and so i didn't end up doing it um but i do have it it's great you guys can okay well that works too you can come through this way it's totally fine um but yeah this thing's fantastic we've actually we had a really small one um there was a [01:22] kind of like a running joke when we were all in an airbnb that we had this like little tiny gavel and one of the biggest problems with the product was just like latency um and so whenever we tested like a new feature we would basically just like hammer the gavel and be like make it faster make it faster make it faster which i think annoyed that a lot of people but we stopped doing that now oh my gosh wow okay that's a good place to start yeah we got a bunch of books got some

[01:52] Harvey right now. This is Winston. And what are we going to see today? [01:57] We're going to see the floor that's been renovated. So we have three floors here in San Francisco, and then one, the one we're on now, has been like fully renovated. Okay. And then we're doing the sixth and the seventh. And the significance of this painting? Yeah, so there's no significance of this painting, but I mean, I think like one thing about this floor in general is we've tried, and we'll take you up to the speakeasy after this. [02:21] we've tried to do like a combination of kind of like tech plus also like classic. And so you'll see like a lot of sculptures. We have a lot of, [02:30] like books related to law. This is kind of funny 'cause it's John Grisham, but it looks like it's like some ancient-- - Oh my god. - Ancient text, like Hammurabi's Code or something like that. - How did you find them? - I actually don't know for these particular ones, but in general, we've kind of tried to do like a combination of, [02:48] When we were actually doing our brand in the beginning, we were basically like, could we do a copy of like the best tech companies and then succession? Like the show is succession. Yeah. My point was like, [03:00] kind of a combination of like an ode to, you know, like classics, like Greek, first orators, things like that. Plus like, hey, we're a tech company. And we've definitely tried to do that a lot with our brand. And we've tried to do that throughout the office, too. Seems to be working. It looks amazing. Thanks. [03:17] Okay, so we're going to cover a lot of different things today.

[03:23] For starters, on this tour, I want to talk about the evolution of the company. So you've been around close to four years now. Yeah, it'll be four years in August. Congratulations. Happy birthday. I don't know. You have nearly 1,000 employees? Yeah, close. It's like 960-something. And this office is one of how many? 12. Wow. So we opened up offices pretty quickly, but the office here and then New York are by far the largest. [03:53] employees are at those? So in this one, I think it's around like 350. And then New York is around like 300. Oh my gosh. Yeah. [04:02] And then the vast majority of EPD is here. [04:05] But we are growing out the other offices too. That's a really cool vibe. Okay, so when you build out globally, you have 12. Yeah. How do you figure out which cities to go into first? Is it like you have your customers and then you build around them? Yeah, so it's actually, yeah. So we did it first based off of just like reacting to like big customers. So like we'll sign like Deutsche Telekom and it's like, oh, wow, we need an office in Germany. Right, things like that. [04:35] had a problem of in the beginning, which is because we process sensitive data, [04:39] a lot of the countries, we actually needed like an Azure instance in each one, right? So like in Australia, you can't process financial data outside of the country. And so we would set up these offices and then we'd set up like Azure instances too. And it was almost like we set up an Azure instance and then that would be like a pretty good indicator that we'd have to set up

[04:59] in office pretty soon afterwards just because like customer demand yeah um [05:03] But another way to look at it is kind of like the legal TAM overall, too. And so we kind of base it off of, like, you know, how many lawyers are there in each country, et cetera. [05:15] And there's how many lawyers in this company? In this company, we have... [05:21] Over 200. Yeah. [05:23] And then on the commercial side, like actually, I guess doing what? [05:27] a normal lawyer would do um there's only about like 25 really yeah and then the rest um i mean obviously we use harvey internally for a lot of stuff so we're trying to scale that up um and then the rest of folks either they work on product or they like help with go to market and things like that too um it was we don't have this anymore but you used to if you would have visited us like [05:49] a year or two ago you would have been able to tell who's a lawyer and who isn't because why there was a dress differently yeah so there was like a phase should we play a game right now yeah you won't uh you won't be able to actually i don't think anyone's on this floor actually um but basically like the first week they would wear a full suit and a tie and then about like maybe the next monday the tie would come off [06:14] And then like three days after that, it's like the suit came off and then it would eventually be like hoodie and sweatpants. Yeah, yeah, naturally. But you would be able to tell like basically like which lawyer had been here for which amount of time. And you could always tell, which is kind of funny. So as we walk through this, like how did you set up this new office? Like there's obviously a lot of.

[06:35] conference spaces yeah desks this is a huge communal area do you guys host lots of yeah we host a lot of hosts like customers and things like that we also i mean it's a little bit past lunch but we were talking about this earlier we have like an insanely loud lunch culture yeah we walked in at like 12 30 and i was like yeah this might be it's it's crazy loud like to the point where i don't schedule meetings during the lunch really like i or i don't do customer meetings [07:05] I just will not do external meetings because it is so loud and you can't, it's loud everywhere. So people will eat lunch here, but it's like loud throughout the whole thing. [07:15] I think we just have always had that. We started in Airbnb and then whenever we moved from office to office, like we'd always eat lunch together. [07:23] and it's somehow spread out to the hundreds, almost a thousand employees. And so we want to keep that, I think, forever. I don't know. I think you need a couple of those instances where everyone gets together. [07:35] We've done a handful of these times. [07:38] office stores so far and you might have the most employees in office. [07:42] Really? Yeah. Well, don't tell them that. I mean, I think like, [07:49] It's something we care about a lot. I think that if you have to try to force it, you're probably in trouble. It's not going to work that well. [07:56] But I think like the thing that does it the most is stuff like this, where it's just like you get to meet everybody from like if you go to here during lunch and again you wouldn't have been able to hear anything so maybe not as helpful, but you can't be like oh that's the team that works on this, that's the team that works on it's like everyone is all mixed together.

[08:17] And so I think people like coming into the office because we have a very like culture of everyone working together and [08:23] People are really good friends that are like across functions. So we have people like... [08:27] Like you can come here on the weekend and there will be people in the weekend. Really? Yeah. All the time. Yeah. And it's, it's funny because no one works in offices. And so people usually work in like a corner. And then you'll have like just a small group of people in a corner, but like, [08:40] I notoriously lose like my card 24/7. I think I have my with me right now. But this is like my 19th. I just constantly go through them. And so I know that there's people on the weekend all the time, because I'll come on the weekend and I'll post into SF General like, [08:54] Yo. Can someone let me in? Yeah, and there's no one too. Maybe they think that's a test. Exactly. And so every single time so far I've been able to get in. Yes. [09:03] Okay, so what's your favorite room? Oh yeah, good question. [09:07] Okay, favorite room is definitely a speakeasy, and I'll show you that in a second. I'd say my second favorite is I really like to work actually on the couch. [09:16] like on the couch when people come in. And I think part of that is, [09:20] I used to travel a lot. I travel a little bit less now, but last year I almost entirely didn't work out of an office. I just worked on the couch. [09:27] And it's because I get here early and I like like saying hi to everyone for a couple hours and then I have meetings. But in terms of actual room is to speak easy. So I can show you that it's up here. Oh, cool. [09:37] I'm surprised by being in office. I'll take that, though. It's a good compliment. Yeah, no, no. I'm trying to think... [09:46] the only other company that has...

[09:50] was applied intuition oh yeah yeah they were packed they're young though they're like 40 people right [09:56] Oh, no, applied intuition, not applied compute, not applied compute. [10:00] I think Applied Computer, Gabe was just there like last week. [10:04] Okay, so what's the biggest lore here? [10:07] biggest lure of this office yeah this office actually doesn't have the airbnbs have like way more oh i would imagine yeah it was i mean so airbnbs we went through i think eight so basically what we did is at what point did you realize you needed to get 20 people okay so we what happened [10:31] getting like a larger Airbnb each month. [10:34] when we just added more people. And then it got, we got to a point where it was like, okay, this is definitely a problem at like 20-ish. What is the deal with people in SF? [10:48] startups getting like townhouses and houses to build out of. [10:53] I would like to say that there's like some beautiful reason for this or some smart thing. To be 100% honest, it's just easier. Really? It's just like I can go personally book an Airbnb. Okay. And then you just... [11:06] Don't think about it because you're doing so many other things. Is that legal? [11:09] What? Yes, it is legal to do that. Yeah. And then you, I mean, you basically just like personally book a new Airbnb each time and it's like, then you don't have to worry about what's the most illegal thing that you've done. I'm not going to say that. I don't care. Nothing. We're a bunch of lawyers. Are you kidding me?

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[12:57] E-R-Y. [12:58] We just did a little walking tour of the office. Now we're going to go deep into the business. Are you ready? Yeah. Okay. So where is Harvey at today? Give me the full stats. [13:09] - Yeah, so we're about four years old, August. That'll be the birthday. I think it is birthday. - What's the day? - August. [13:16] forth. [13:17] It's a Leo. Holy crap. Wow. Actually, I didn't think about it that way. Yeah. Huh. [13:21] Well, that puts everything into perspective for me. I've got to take 20 minutes to have deep thoughts on that. I'm a Capricorn, so I don't know if that works. Oh, no. Is that a problem? I have no idea. I don't either. Leo's like a lion, right? Yeah. Fire sign. Fire sign. Jesus Christ. [13:38] So, yeah, about four years old. And we're around 900 folks, 950 people, 960, something like that. Yeah. [13:48] We're at around 2,000 customers, somewhere around 300 million ARR. [13:53] So we're going really fast. [13:57] Mostly just a crazy experience, like how much the product has grown. I think that in the beginning, like we had this product roadmap and our product roadmap has actually like really been pretty consistent. The main thing that's collapsed is just like how long it takes to build these things. And so I think the thing that's actually moved the fastest is how much we are starting to basically build a platform for all of these different pieces of the product. [14:20] So you were at 100 million in ARR last August, now you're nearing 300 million. What's been driving that? [14:27] It's 100% product. I'll give you some metrics.

[14:32] Our token usage in January was $1 trillion, like for the month of January. And this month it'll probably be like $12 or $13 trillion. Oh my god! Yeah, so the usage is getting pretty insane. Our DAU over MAU at the beginning of the year was around like 36%. Right now it's like 51, 52%. Our queries per user have basically been doubling up quarter over quarter. [14:54] hours spent is doubling quarter over quarter. I think that's better than queries. The problem with queries is [14:59] as you build a more complex product, you're going to have these outputs that are like crazy long. [15:04] And so you might have people like using this like querying less, but the output is like a hundred page document. And so they're like in your system reviewing and collaborating on it. But like everything is just. [15:16] product improvements. I think like last year, [15:19] Last year, we had some moments where we just kind of had to like rebuild a lot of our product. And then this year, most recently, the main switch we did is just went over to cloud agents. Like we switched our entire infrastructure to that. And once we did that, usage literally just started like doubling quarter over quarter. [15:35] And you've raised... [15:36] over a billion dollars now so have you used most of that capital where is are you using it on tokens like what is yeah yeah now we're using the office now we're using on tokens um no we actually we haven't used a lot of that money um i think like the the interesting thing that we always wanted to do was actually do a lot of post training on the models and there's a couple problems in legal that makes this like really hard [16:00] One is the data isn't available.

[16:03] If you went online, you're like, I want to go find a bunch of documents that are related to like a random fund formation by Blackstone. [16:11] they don't exist. Like you'd have to go to Blackstone for those documents. But the thing that happened with the last generation of coding models is [16:21] you can actually take sets of documents and create synthetic docs that are so good that the lawyers can't tell the difference between whether they're created by an actual lawyer or they're created by the coding models. And so with that, we've now actually created basically like a pipeline for creating synthetic data sets across like every single legal use case. And because we have that now, now you can start actually post training models. And that's going to be expensive. [16:44] Wow. [16:45] And so what are the main categories of your customers? I think you said it's 42% is in-house corporates. Yeah, 42% is in-house corporates. It's growing faster than the law firms technically. [16:56] because I think we're at like, [16:58] Almost 70% of the animal. Is it easier for them to adopt? Is that why? [17:02] No, they're just slower to adopt. [17:04] Yeah, so the corporates adopted like they started like a year after the law firms. And so and then our fastest growing of like the verticals in general is financial services is number one for sure. So like banks, private equity, asset management. [17:20] And then pharma is actually growing pretty fast too. And what we're starting to do is actually like we're going to verticalize our product too. [17:27] where we have to actually have different parts of Harvey that are different for each vertical. Right. Because like the compliance and legal needs of a bank are very, very different than even private equity.

[17:36] So I want to go into deeper building the company out today. Like, what does it take to build an AI forward company? So I reached out to Pat Grady and he said the one thing that he emphasized was that you've been able to reinvent the company over and over again. So what was it like from the beginning to now? And what do you think was like, what are the key unlocks along the way that you think are critical? Yeah. I mean, the key unlock is hiring. [18:00] for sure, like that is it. And when I say hiring, [18:04] I don't just mean hiring new people, I mean also development, right? And promoting people, putting them into different roles, things like that. Or honestly, in some instances, they get outscaled and figuring out a better role for them. But every six months, I'd say, I start to get like, [18:21] this weird feeling of things are just breaking. And I feel it's like a pressure that builds up. [18:29] and then usually hope so far what has happened [18:32] is every time that has happened, there's been like three big changes that I need to make, and I realize I need to make them. [18:39] and then I make them, and then the pressure flows off. [18:42] and that happens literally every six months I'd say. [18:46] maybe three to six months, something like that. [18:49] And it feels like if you do not constantly change, [18:54] you are just going to get so behind that you die as a company right now. And I think a lot of that is actually like, who do you decide to promote? Who do you decide to hire? [19:05] that is more important than anything else because a lot of people can't do that.

[19:10] Like it is really hard. [19:11] for every six months for someone to like massively change how they operate. It's even simple stuff. Like when I see somebody like mass starting to really break, [19:20] the first thing I do is I'll go and we'll do like a calendar audit. [19:24] - Really? - Yeah, seriously, that's like the first thing. I know it's so stupid and it's so simple, but you go in and you do a calendar audit and you come up with really good ways to be like, "Do you have to do any of these things?" Tell me what is the main prior this week? [19:38] Are any of these related to that prio? [19:40] And you will start seeing people, and I do it myself, like you just come up with so many excuses for why you're doing stuff. And at the end of the day, it's like, no, that's not relevant. That's not relevant. That's not relevant. [19:50] And I think that finding people that are really good at doing that themselves, and I think there's a decent amount of people at this company now that have learned how to do that. [19:57] That's how you scale. That is how you scale at this crazy rapid pace that [20:02] Normally, companies need to reinvent themselves maybe every... [20:06] five years, 10 years, something like that. I think you have to do it every six months. So what's your framework for prioritization? How do you determine if you can't do something or not? Yeah, yeah, yeah. [20:16] So, I mean, for me, I have like a bunch of different rules. One of the really simple rules is like my chief of staff, whenever she sends me something, I have to write a paragraph for why I would do it. [20:27] Not kidding. And you don't use an AI for this? No. It's really important because if you start... [20:34] For the stuff that is really, really, really important, and again, this is outside of ordinary. I don't do this for product reviews that we do weekly.

[20:43] If you sit down and you can write an entire paragraph about why you're going to do something, you definitely are going to do it. [20:50] If what happens is you go, "Oh, it's so annoying that I have to write this down. Like, why would I ever need to do that?" [20:55] you probably don't need to do it. It's not that important, right? And then what I've found is the stuff that is really important, I could write like 100 pages about why I'm doing it, right? And I know it's like kind of a small, silly thing, but it helps a lot. You get a massive unlock for just blocking things. So you have a quarter of your company as long, [21:15] previous lawyers, former lawyers, how did you convince them to come to a tech company that's completely different than a traditional career path? [21:22] It was really, really hard in the beginning, and now it's, [21:24] like I think quite easy. - You show them equity, what works? - Yeah, oh my God, it was difficult to explain equity in some instances, right? Like what is the value of equity and things like that. [21:36] I think really like, [21:38] We hired in the beginning, we hired a lot of people who I think really wanted to like, they love law, like they love the practice of law, but they didn't love working in big law. And so they wanted to do something adjacent. And I think that was really, really attractive. [21:52] And then over time, like we have so many lawyers that are now just full-time PMs. [21:58] Like literally they just like transferred in other PMs. We have so many different like career opportunities that I think that now it's a really attractive [22:05] place to be, [22:06] because you could have a legal background and then you end up doing something else, right? Like you don't actually have to be practicing law or anything like that here.

[22:14] What's the biggest complaint of people leaving law firms? [22:18] Oh, I'll tell you, by far, the biggest thing that they need to get used to here [22:24] is and maybe that's your question if it isn't i'm gonna answer that one anyway um [22:29] because I think this is actually super interesting, [22:31] Law firms, [22:32] very rarely fire people. [22:34] Very rarely. Okay. And so actually I think one of the most interesting things to get used to is that like, [22:42] Tech is very fast moving and it is like, I try to make it a meritocracy. [22:48] And so if you aren't doing well, like we're going to have to let you go. And I think that's really hard for some people that have been in a situation where like, [22:57] You get promoted every single year. [22:59] And that's how it works in Big Lock. You get promoted every single year to exactly the same level as everyone else. [23:05] despite your performance. [23:06] and you don't really get pushed out, right? [23:10] And I actually think that's one of the weirdest things. And I remember in the beginning, [23:14] we like [23:15] there were a couple of people that we had to let go and things like that. And [23:19] people freaked out. And it's like, you know, from the tech world, that's like very normal. But I remember that being like a huge issue in the beginning. [23:27] thinking of how fast you're growing the company, [23:31] I don't know, maybe you still have a billion dollars in the bank. How are you thinking about buying or sorry, building out? [23:39] the company itself or buying. There's like a now, there's like an onslaught of M&A within all these AI companies. There's so much. And buying up smaller startups for talent and all this kind of increased competition.

[23:50] How are you thinking about that? Yeah, devalue... [23:55] like higher value on team and lower value on what they've built in terms of like [24:00] I do not believe that it is a good idea right now to go around and buy legacy technology. [24:05] Like I don't. I think it is a much better idea to buy like really, really good teams and [24:11] regardless of if they worked in your space. It doesn't matter, right? Um... [24:16] And so that's like, if you look at the acquihires that we have done, they actually haven't been in the legal AI space or like legal tech. [24:23] They've been outside of it, but they're really, really good teams that could work on a problem that we have. Right. And that doesn't mean that I won't do legal tech acquisitions in the future. But I do think that right now, if you are making an acquisition, like the number one thing you should be looking at is just talent because you can build things so much faster now. Right. That it should literally just be talent. [24:42] Like, are you buying a team that... [24:45] is really, really good, and are they gonna align with your cultures? Because the other problem is like, [24:50] worth not even four years old. [24:52] if we go and absorb [24:54] a bunch of teams, our culture is still being built. - Yeah. - And so you're gonna just collapse yourself. And so I think it's a really bad idea to go out and buy [25:03] a bunch of companies and then they end up being like half of your company is that. That's a terrible idea. [25:08] I do think it is a good idea to go out there and like, [25:11] acquihire or acquire some companies for really good talent. Today's episode is sponsored by VCX by Fundrise. [25:17] the public ticker for private tech, allowing investors of all sizes to invest in venture capital.

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[26:59] So you started this company post-COVID. It's nearly four years old and [27:05] It was AI native from the start. So I just want to know, like what what is like fundamentally different about building a company today in the AI era? [27:14] versus the SAS. [27:15] cycle. Yeah. [27:17] I think pace is really important [27:19] And one thing with Pace that I think people struggle with is like, [27:24] Thank you. [27:24] you have to just assume that most things are two way doors. [27:28] And people really hate this. [27:30] Like they really like to kind of like think about a decision [27:33] get to like 90% certainty and then make a decision. The reality is like, you're probably gonna have to make a bunch of decisions at like 51% certainty. [27:41] which means you're being wrong. [27:44] Right? Right? [27:45] And can you deal with being wrong and then quickly pivoting? [27:50] And I think you have to do that way more than you used to in the past, A. [27:54] B, I think there's a huge difference on enterprise, like massive difference on enterprise, which [27:59] You cannot get away. [28:01] with going in a room, building some product, and then selling it, and then never improving the product. [28:07] over the next like XYZ years. [28:10] The users matter so much. [28:12] much. [28:13] Like the alternative... [28:15] is Claude, ChatGPT, these other things, those are great products too. [28:20] And so I think that the product bar for enterprise is astronomically higher than it used to be. [28:25] where like you a hundred percent have to be constantly innovating and creating the best product

[28:31] for the end user. [28:33] And I think in the past you could kind of get away with doing some things like really long sales cycles and things like that. [28:39] And token usage is compressing margins. So how are you financing $13 trillion? [28:45] Token. Yeah, I mean... [28:48] So there's a lot of [28:50] Okay, a couple things. [28:52] One, I think every single... [28:54] company is going to sell intelligence. [28:56] Like that is gonna be the core of the company. And so like eventually like we were selling legal intelligence. We're selling legal intelligence to lawyers, right? But it's still like selling intelligence. And so what I mean by this is like, [29:08] We need to get to a point where we have models that perform as well, if not better than the frontier models, but cost significantly less. [29:16] I basically think of this as an intelligence allocation problem. [29:19] where if you look at a model, the new models coming out, it's like Mythos, 5.6, all these guys, right? [29:24] Those models come out and they're incredibly expensive and they're general. [29:29] And if you use them across every single legal task, like maybe they do decently well, although in our benchmarks, like a lot of them fall apart. [29:36] But they're insanely expensive. And so the better thing is, can you actually create models that do diligence? [29:43] do change of control review, do contracting, do these different things, [29:47] at the level, if not or better than the frontier models, [29:50] and they cost 100 times less. [29:52] right? And so [29:53] I think that every single company is going to sell tokens. [29:57] and I think that they are basically going to be selling intelligence. So you'll have the product layer and everything like that, double up your data,

[30:03] and then you're going to be selling intelligence as well. [30:04] How do you compete? [30:06] with those large models that are offering competitive services? Like, what is the thing about Harvey that you cannot copy? Yeah, I mean, the best way I think about this is like, [30:16] There's the product side and then there's the intelligence or model side. [30:19] And you could say on the product side, it's like the harness side. [30:21] Um, [30:22] I think that's conflating things a little bit too much. On the product side, you just go very vertical, right? So you build solutions that are really good at like [30:30] diligence in a particular space, like all of those things. And I think it's gonna be hard for the labs to get to that level of specificity on the product side. [30:38] On the model side, you actually do a similar thing. [30:41] which is you basically build a bunch of models that are really good at specific legal tasks, and then you optimize them for cost. [30:48] Right? [30:49] Like there's a world in which [30:51] GBD-10 is more expensive than a lawyer. [30:55] That's like a very... [30:57] possible world, right? And so where we have is basically you can think of like the frontier models here, commoditized models here, [31:05] I think a lot of the economy is actually in between these things. [31:07] Right? [31:07] Because the frontier model might be too expensive to basically put in terms of every single piece of work. And so you have this massive space that is like all these vertical companies. [31:17] Thank you. [31:18] In terms of other competitors, Lagora is fast moving behind you. [31:22] How do you think about, I mean, you are global from the beginning, but they are dominating Europe. So how do you close that gap? [31:29] Yeah, I mean, I would say in Europe, I think our win rate is like over 70%.

[31:34] So I don't think it's as much dominant there. To be honest, I think our main competitor is the labs. I mean, you saw clock for legal. There's a rumor that like codecs for legal, right? [31:44] I think that the reality is like the labs have an incredible amount of resources, right? [31:48] And so it is a race for how quickly can we build the best product that is verticalized? And then how do we build the best vertical models? Right. [31:56] And I really do think at the end of the day, it is a race against the labs. And I think every single [32:00] company on earth is competing against them. [32:03] Do you think they're going to start acquiring? [32:06] Like in legal specifically? In this space, yeah. [32:08] I think that they will start acquiring in any space where they see a significant amount of traction like one thing they try to acquire you. One thing that like I think is like crazy. I'm not going to answer that. One thing that I think is. [32:21] - [32:22] like that people forget about is [32:25] the more success that any of these verticals have, they'll just keep entering them again, and they'll re-enter them. And so I think like people, you know, Cloud for Legal came out recently, [32:34] And I think a lot of people were like, "Oh, okay, well, it was this release, and now that's kind of it," or whatever. [32:40] the better we do, the better other companies do, the more the labs will be like, "Oh, okay, we're going to put more resources into that." [32:46] it's not like a one and done thing. It is like a constant [32:49] competition. [32:50] What do you think the biggest question right now is that people are not asking? [32:55] By far, I think the biggest thing that people are not paying attention to is what I was talking about earlier, which is do you need frontier intelligence for every single task? I mean, this is the best example of this is like.

[33:05] What happened with Uber recently? [33:07] And it's like, we're going to get to this point. This is actually a weird situation where [33:12] I'm sure you know what the billable hour is because people like talk about that a lot, right? [33:17] weirdly, the billable hour problem [33:20] is the same problem that I think the entire world is about to run into. [33:24] The billable hour, for those that don't know what it is, it basically is... [33:29] when you get a bill from a law firm. [33:30] it says in six minute increments [33:33] what people did and then the hourly rate or the six minute increment for that task, right? [33:39] Why do they do that? [33:41] it is because they're trying to show ROI. [33:43] They're like, "Hey, your legal bill's 100 grand. "We're gonna break it down into six minute increments." [33:48] This is the main problem that I think the entire world is about to hit. [33:53] which is [33:54] I just spent a billion dollars on tokens. [33:57] Where's my horror walk? [34:00] Right. And I actually think that like, [34:02] there aren't enough companies that I know of that are starting to think about how do I actually show [34:08] ROI on every single vertical use of these things. And I think that vertical companies are going to have a huge advantage here. [34:14] where you can start to get to the point where you basically can show every single token and what the ROI was of that token for your particular task in the vertical. [34:23] So before we started recording, I asked you what you're most excited about, and you said benchmarks. Yeah, we're gonna be interviewing Gabe after this what [34:31] question do you think I should ask him? [34:34] Um... [34:35] I think that...

[34:36] the best question actually is [34:39] Why are the current benchmarks for most verticals bad? [34:44] Right. [34:45] And if you look at the benchmarks that have existed for legal for a long time, I mean, half of them are like, [34:51] Can it pass the bar? [34:53] multiple choice questions on like, [34:55] community property law and things like that, right? [34:58] I think that we haven't actually until now had, here is a very good set of data. [35:05] that doesn't illegal task from end to end. [35:07] and we're missing this in most articles other than coding. [35:10] Basically, coding is the only one that has a good saturated benchmark. [35:13] Wow. [35:14] Okay. [35:15] When are you going to do a collaboration with Kim Kardashian? [35:17] soon she didn't pass she gave up i think kanye passed it or maybe that was a joke i don't know i think it was a joke i think it was a joke i think it was i'm not sure [35:28] Well, thank you so much. Yeah, of course. Thank you. Because it lives. Why do you have a hippo? Well, because they both live on land and in the water. So they see both sides of the world. Oh, my God. [35:40] That kind of works. Ducks fly and then ducks fly. Ducks do fly. And then hippos eat people. [35:45] hippos have eaten a few people so that's i don't know why you want runaway jury that's legal [35:52] John Grisham. How many? I've noticed you have over 1,200 books in this office. Have you read all of them? Every single one of them from front to back. And I could recite any part of the book. Even the culinary cookbooks? Mostly those actually. I'm like more well versed in that. It's been a long time since I cooked. I am really bad. I'm a chicken and rice door dash guy.

[36:13] And it's actually the same. It's the place called Cholita Linda. And it's around here. And there was actually a time I was interviewing someone and I asked them, like, hey, do you want lunch? And I pulled out my phone to do DoorDash. And they'd seen that I ordered it 467 times. Yeah, it said like the little number. You ordered it multiple times a day? Yeah, twice. Lunch and dinner. Oh, yeah. So you're one of those types. You just eat the same thing every day. Well, so and then breakfast, there's a blue stone on like Folsom. [36:43] And I get there exactly when they open, like it's 7.01. And I get, it's like this keen green smoothie that's really good. [36:50] with extra almond butter and i look like a psychopath because i'm like i have a spoon and i'm literally eating you eat a spoon yeah it's kind of terrifying i eat so i try to be alone with forks so you're okay [37:00] How do you even do that? [37:02] Thank you. [37:03] Wait, actually. I'm literally not even kidding. How? Well, I like to put like granola on top, so I eat it with a fork. But then you, so is it like you fork out the granola? So it's like granola doused in smoothie. Okay, so it's granola doused in smoothie, and you do that with a fork, and then you put a straw in and finish it. It's like a smoothie parfait. Yeah, that actually kind of makes sense. You know? That's not that bad. No. A spoon seems like it would work better, though. [37:27] But I'm making you feel less bad about the whole spoon thing. I guess that makes sense. All right, are we walking or what are we doing here? Yeah, let's start. Okay, so. I like the duck, though. We do. The duck was great. I mean, might as well. Hey, it's Molly. If you enjoy our interviews, check out our newsletter, Sorcery.vc, where we deliver a once-a-week top deals and tech headlines email and also go deeper on our podcast interviews. Subscribe to Sorcery today.

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