20VC: From Only OpenAI to Die-Hard Anthropic: The Downfall of OpenAI in Enterprise | Harvey vs Legora: Legal AI is a Winner Take All | $7M ARR in a Single Day and Raising $200M Across 3 Rounds with No Deck with Max Junestrand, CEO @ Legora

It doesn't really matter who was first. It matters who's best. It's totally a winner takes all. Number one will grab 90% and number two to number 10 will share the remaining 10%. Gotta run like hell. You gotta win. There's no number two. There is only being number one. There's only winning. Everything else is losing. In a single day in 2025 in December, we had a seven million a day or one day in 24 hours. And that was more than what we did in 2023 and 2024 combined. This is 20 VC with me Harry Stebings and what a show we have in store for you today. Last week we had Harvey on the show. That broke pretty much all records. This week we have their biggest competitor, LaGoura on the show. And joining me is Matt Schdunesrand, co-found and CEO LaGoura, the legal AI company that has 750 of the world's biggest floor firms as customers and over 300 employees in just two years. 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And most of it's just kind of VCs. But thank you so much for agreeing to do a second show with me. - Always. - And before I grill a shit out of you, 60 seconds, what does LaGora do just to set the scene for people that don't know? - LaGora is the platform where legal work happens. I think that's a better pitch than the one that I had last time. And what started to happen more and more is AI is, doing more and more parts of legal work. And this has to happen on a centralized platform. And what we started out with was simple, assistant-based use cases, but this has grown tremendously. And it's solving different types of tasks for different types of lawyers. So if you are a transactional lawyer and as part of a due diligence process, you need to review the data room and then you need to find the red flags in that data. LaGora can do it. If you are a litigator and you are preparing a brief and you are drafting that in word, LaGora can help you do it. More and more of these tasks are being bundled into the platform. And what we're seeing is that a bigger and bigger part of a lawyer's day is being spent on LaGora, which is amazing. That's my favorite data point. - Is that the number one metric? - Ease in terms of product metric. - Yes. - The time spent on the platform and number of messages, slash number of queries, slash number of actions taken, I think is the best sort of KPI. - When people think AI law, there's a ton of fucking players around the space and around the verticals. But there's you and there's Harvey. And if we're blunt, Harvey is the first name that comes up. When you think about that, why is that? - I don't necessarily think that's the case anymore. And the reason I say that is, I just saw this report. I was on Bloomberg a couple of weeks back. And they had a big infographic that said that, the most deployed generative AI tool in the top 200 law firms in the UK, outside of Microsoft co-pilot, is LaGora. Number two was Harvey. We are moving and the category is moving at such a rapid pace that it doesn't really matter who was first. And it matters who the clients actually are coming back to and wanting to do more work with. So what often happens is the firms will throw many vendors into a bake-off, 'cause they're in this kind of luxury position. I mean, basically they're playing VC. They get to bring in all these different vendors and they say we're gonna do a bake-off. And in the bake-off, it's up to the vendor to display why you are their partner of choice. And I say partner of choice, because I don't think that these law firms or Big Inhouse legal teams are buying just a solution. They are buying an outcome today, but they're also buying an outcome tomorrow and they're buying into a vision of what an AI-enabled legal team can look like. And so when they look across the board and they see all these different companies, they make qualified bets. More and more and more, seeing those firms make that bet on LaGora. I mean, this year alone, actually I went into our HR system before I came in here. We went from 30 to 300 in 12 months, exactly, in headcount. This time last year, we were working with roughly 50 clients. Now we were with 750. And so, you know, a name might be associated with the category. I'm pretty sure Google was not the name that you thought of back when Alta Vista was the biggest web browser, but now it is synonymous to searching on the web. - Now I want to unpack a couple of elements. You said about like partnership. And that being very central to how they think and how they choose. You know, I had Matt Fitzpatrick, the CEO of Invisible, which is kind of like a Macquarie or a Turing, a Composer. And he said that it is impossible to settle into enterprise without an FDE model. Do you agree with that? And are you seeing that? - We have a very big team of legal engineers who are ex-practicing lawyers from the top tier best firms, but they're not fully secunded. They're forward deployed in the sense that their main job is to make you successful. An example would be a big firm that just went with LaGoura Widencase. Widencase now has the challenge of adopting AI across their entire firm. It's a big firm, such an enormous change management undertaking to equip all the lawyers across all the different practice areas, across all the offices, and across all the skill levels from associate, senior, associate to partner with AI proficiency. And we need to make them successful. Because if they are not successful on LaGoura, a year from now or two years from now, it's gonna be a really sad conversation. So we invest a ton of upfront manual labor, time and effort in doing the implementation and activation right. So I do think that's necessary for enterprises where you're changing the way they work. If you just think about a process, Right? Like let's see you're working in, we're just staying in legal. If you're working with AI contracting, you basically have a contract lifecycle management system, you just send a document somewhere, generate some red lines, and then you put it back. That's pretty easy. You don't need a forward deployed engineering or legal engineering model for that. You just deploy the stuff and then you're done. But in our case, I actually like to think of it synonymous to the way that accountants had to learn Excel or architects having to learn CAD. Like before you would actually go out to the site, you would draw the building and then you would go back to your office, you would do all the math. But now you just get a picture of the site, you throw it up in CAD, you put in the blueprints for the building that you want and the system AI generates it or generates it. And then you look at the math behind it and then you bring taste and you bring the sign. When architects were learning CAD, I think was an enormous change management. And all the old architects would go, Harry, we're going to use that computer system to do the hard work for you and you would go, yeah, I'm super savvy and I'm going to get to spend more time doing the design or have creative ideas about how to solve my clients' architectural problems. And I think that's synonymous to what's happening today. You said about the value not being in the first move for advantage and actually if I'd eat the commission being second, what did Harvey not do well that you learned from as specifically as possible? Some of the things that we observed were spending a lot of effort on fine tuning models that always seemed to me at least back in 2023 like a waste of time because the general models were improving at such a fast rate. It felt like we should be building boats and then when the tide rises all of our products just get better. And frankly, my initial team, we were three people. We were three engineers and the team structure. Right. And we had 50,000 euros in angel funding. And so it wasn't really on the question of let's spend $3 million fine tuning a model, but it happened to be right as well. And we always believe that the majority of the value in our category would come from the application layer. So you think we're being done fine tune models does not give you an inherent advantage? It didn't do that back in 2023 as a starting strategy. I doubt that that's going to be the difference maker today. Do you think models are plateauing in performance today? No, I think Opus 4.5 is awesome. It's so good and it continues getting better. I mean, honestly, how much better is it? Well, it depends on the task. Encoding, I mean, I think it's it's gone into the point now where I think you should just coin it AGI and focus on optimizing the cost pretty much basically. What makes you say that? I'm sorry, I'm naive because it's understanding of my intent and its ability to execute on my intent given the tools that it has available today is so good. Like you don't need to sit like with GPT 3.5 and you feel like you're talking to, you know, like a lobotomized system pretty much. Like if you go back, it's crazy bad. And this was, you know, two years ago, right? And you would have to give it so many instructions over and over again. It felt like managing an employee who wasn't very intelligent. Whereas Opus 4.5 is like a VP. You give it, here's the thing I want. Go execute and it just doesn't. It's amazing. It has anthropic one, the Claude code game. Does anyone on your team use cursor? The question that I mask and say, I'm in question. It's a good question. We're in both. You are. We have both. Yeah. I'm actually not sure what the full team split is, but I know that we're using both very much. But we are pretty die hard andthropic right now at the company in terms of the models that we deploy in our system. So initially we were only open AI. So 2023, most of 2024, only open AI. And now we're majority using anthropic. What changed is 4.5? No, not 4.5. This was prior to that. I think it was maybe solid three or three point five. We made the switch. What also happened was you had to start prompting the models quite differently. And then there's a question of where we actually want to put our effort. Just to pick a good model and double down on it and build all the application around it. Because I feel like our job, frankly, if you think about the pyramid of value is you sort of have the underlying models and the frameworks, then Ligora's responsibility is to build the legal interpretation of those models. So how do we make them the most useful in a legal setting? And a lot of that comes from the models, but 80% comes from building normal software, right? Like enterprise grade software around the models. So all the scaffolding, all the ways that the users can actually interact with the system. And then at the very very top of that pyramid, we need to enable our partners, our clients to do differentiated things. So our clients and the law firms and the legal teams who work with are very ambitious. They're vibe coding tools internally. They are developing MCP servers and they they've understood that if you compete as a law firm, you used to compete on expertise, on marketing, on your ability to recruit on your hourly rates. But increasingly, you're competing on tech. Tech is the main lever for our clients to differentiate from their competition. And so they will use a platform like Ligora to get everybody up to spend so much time in the US now, second base. And then they will develop things internally to try and get a little bit of a head start against some of their peers. I'm packing so many things. Just doing it chronologically there. How promiscuous do you think you'll be with model usage over time? You mentioned you're pretty much exclusively anthropic now. When you look in the next 12 to 36 months, we use switch between them as they improve in model efficiency. Or do you think there'll be a continuing loyalty towards anthropic? We will be very promiscuous. And that's a clip. That's a real that's the intro right there. Well, I think it's our responsibility to be that because our clients have entrusted us to be their AI partner and to deliver them the outcomes that they need based on everything that you can do with AI. And we need to deliver them the best possible thing at the best possible price using all the tools available to us. And so if a if Gemini is better, we will switch immediately or if Open AI is better, we will switch immediately or if a new model comes out that's better, we will switch immediately, you know, proven that the e-vals is better. But then in specific workflows, you could also let the users pick. So let's say they have a very deterministic thing that they want to run and they always want to run it on this specific model to not break the system. And you could also allow that. In 24 months, rank the model landscape for me. I'll bet based on what I've seen in the last sort of three, six months. For our type of work, it will either be a cloud or Gemini. That is the top model. It will be dependent on if context window is a very important factor or not. So far, it is not because we've built so much architecture around handling lack of context window that we still prefer the cloud models or the anthropic models. And it seems to me like Open AI is going down the, you know, let users fine tune models like that type of journey a bit more, which so far, I don't have a lot of reason to believe it. Okay, so we're going for anthropic/gemini and then Open AI. I think so. And we're not going to throw Gork in there at all. No, we're not going to throw Gork in there at all. He said it, don't kill me. It was not me. I also think there's a difference between solving enterprise needs and solving bittersy needs. And to me, there's a perceived split that is from my vantage point, which is that anthropic is going more enterprise and Open AI is going more bittersy. 100% and we're an enterprise class type of system. Thus we should benefit more from their models. Yeah, Jason Lamkin, a dear friend of mine, and he said, you know, the show is with Jason Mori, he said on a show recently that we're going to see inference running 24/7 for a portion of the knowledge worker economy. Yeah. And how that really is going to be the defining theme of the year. And if so, what ramifications do you think that has? So basically that you sort of, or you're continuously running tasks. A continuous E20 for everything. Exactly. When we always leave the office, they're going to still have inference right? The projects that they have. For what it's worth, I don't think that we're there yet when we have tasks that take that much time to run. We don't have any task in LaGoura that would take 12 hours to run yet. But when you can put the models in loops and it gets better and better and better, the more loops it takes, then you can for sure allow that. I do think that we're going to move into a world where we start a lot of things as we go to bed and we wake up in the morning and it's done for sure. I think I already started doing that with the research when that came out for the first time. And it would take 25, 30 minutes to run. It was so cool. But you so quickly get used to our new shiny toys. What do you think we don't talk about enough or don't see in the model environment slash landscape today that more people should see or talk about? So one of the things that's very impressive with Cloud Code and do they call it a new think coworker? Yeah, coworker work is maybe not so much about that tool itself but about the paradigm that it has shown is useful and the right thing to go directionally. And the more we were working with Cloud Code and cursor in our engineering team, the more we just thought, hey, let's apply the same principles to the way that LaGoura works. Basically having the LaGoura agent access all the other tools available in our ecosystem, as well as NAMCPS servers that the client brings, and then basically kind of letting it roam. And you just give it this again overarching task, it gives you back its plan, and then you say, "That looks awesome. Go execute." And it's pretty much the way that a partner would work with a senior associate and a senior associate would work with an associate. And I think this is like adding another layer in that hierarchy, basically, with AI in the bottom. But then that's available to everyone 24/7. So one of the themes that I've noticed is that the partners at these firms that we work with are starting to think that the technology is so good that as they give a task to their team member, they will simultaneously give that task to LaGuara. And then very often, the quality that they get back is pretty good. And that is real implications. We're going to go to the structure of law funds in the future. I just want to unpack another thing that you said earlier, which I didn't want to forget. I'm playing more and more time in the US. There's this kind of perception when I speak to especially US VCs that Harvey have won the US and that you have won Europe. I think one of those statements are true. One part of that statement is. My wife with you is your lack of confidence, my friend. Why is that not true? Because they seem to have the magic circle in the US. Well, that's not true. And when we started the year, we were zero boots on the ground in the US. Now we are 50 people. We're opening up our new office on Manhattan this week. Exactly. We're going to be 150 people. We've got three more offices in the US opening this year. The US has, by revenue, become our biggest markets. Wow, revenue wise, you have more than that. It's the biggest country by revenue, yeah. Do you have more in the US than you do in Europe? In total, we have so much in Nordics, actually, because we basically work with all the big firms. But it will be, I think, by the end of Q1. Super interesting. By the end of Q1, you'll have more in the US than you would in Europe. And the cool thing is that if you look at the AM-Law 200, and by the way, many of these clients that we're working with in the US, it's not the moment pop shops. We work enterprise. And so when we came to the US, we had a strategy, which was there's so many Nordic or European companies that have launched in the US and failed. Very close to home, Clarna tried to launch in the US like a couple of times before it really worked. And so I had this heuristic, which was if we can sign and serve two of the AM-Law 200 law firms from Europe, we are ready to open in the US. So Cleary Gottlieb, you know, why two Wall Street firms, Goodwin and Proctor, one of the best busy firms in the world. And I think both are in the top 20 law firms in the US. We were able to work with both of them and give them confidence that we could support them better than anybody else. That gave me the confidence to go to the US and hire it in. And the awesome thing about building a team in the US is it takes two weeks for people to leave. We can talk about some of the differences between, you know, US, Europe, but I think the termination period in the US versus in, let's say Sweden is actually one of the structural benefits of having a big office in the US. So how does it compare two weeks to leaving US? Versus three months. On like everybody has three months. And for you as a founder, that is a night and day difference in terms of ramp. We've doubled in size every quarter. And the minute I know that I need somebody, if they weighed a quarter, we're a different company, right? It's wild. So you just need to, well, for one, I need to try and predict our head count plan much more diligently in Europe than I do in the US because there it's like per on per. But really awesome people can just turn up in two weeks. So your biggest advice to found is on scaling in the US without committing large resources would be that you can do a freemium and test it from Europe. Yes. For sure. Well, I think we could. So why can't you? And we're very enterprise. That might be different. We did not need to invest a ton in marketing or like BTC content in the US. I could just get on demos and get on a few flights. Demo the product, run a few pilots, you know, always competitive pilots. And then again, on the partnership level show that we were willing to work with these firms on their ambition level because it's very high. The firms that we work with are not treating AI as a check the box exercise. It's not, oh, let's buy, you know, this thing, let's roll it out and we're done. It's, we want to be the firm that dominates our market because we understand AI and technology better than any other firm. Just going back to the US and the Spanish. Do you regret waiting as long as you did? No. Did I tell you that I took a decision to not sell the products for six months? No. So our first board meeting is to give you some context. We were wise. We raised $10 million from benchmark. A month later, we raised another 25 million from red point. And we had our first board meeting and we were like 12 people at the time. First board meeting, it's benchmark, red point and three founders and we sit down and I tell them that we are not going to sell at all for the next six months. Red point sort of looked at me and they were, I think, a little nervous that they had met me for basically an hour and 45 minutes and given me paid a million dollars. And I was showing up and I said, we're not going to sell. No price was the red point round. 150. That's interesting. Do you regret taking, I'm not saying red point, but doing that round? No. Because that's a lot of dilution. Yeah. 25 at 150 when you didn't need the money two months after a benchmark. Yeah, but you couldn't know that you didn't need the money. And if I remember correctly, one of our competitors did another round quite quickly after. So I think it was good to solidify that there's interest in La Guarastók and now I just get like, you know, at this point, I'm just archiving emails because I'm getting too much inbound. But back then, that's a good thing. That's a good thing. Back then, they were, you know, I turn around and said, hey, we're not going to sell. We need to get to the point because we only have one shot. We only have one shot with these lawyers because they are very impatient. If it doesn't work, they're not going to come back. And that's why activation and getting that like the time to value is so important in the product. But to go back, we took six months, calculate the time and said, we're not going to sell. We have to solve our infrastructure, our reliability, the scalability of the product and we need to rebuild and refactor a lot of it because it has just been quickly put together. And what we told all the clients were, we were lucky, you know, it was summer because we could say, oh, it's, you know, summer in Europe. So we're not working. And we're going to wait to onboard you after summer. And there's so much demand that we're going to have to do in October because it's September is like completely full. We can't onboard more clients. But October 1st, 2024, we were ready to onboard a thousand lawyers a day comfortably on the product. And we got to that point and then we started to rip. And I'm very proud that I had the guts to tell the investors that that was the right plan. Because I think if we have continued to push, we would have just churned everything. So when you look back at the timing of the US expansion, do you not think you could have gone sooner and not seeded so much ground? Well, for what is worth? I don't think we conceded a lot of ground and we are winning back a lot of ground if you put it that way. So customers aren't loyal? No, I think everybody is still treating this as an extended pilot and an option on AI. It's like a call option. They're not doing five-year contracts. They're doing one to three-year contracts. And in law firm time, that's a blink. Many of these firms have been around for 200 years. Two years might be half of our lifetime, but for them it's a short time. So when we look at the numbers, the retention for a hobby is 98% lower retention, 178% net revenue retention. Do you have as good numbers? So for both those numbers, yes, but on NRR, I don't think that's a fair number for me to comment on because so much of our growth is not about renewing contracts from 2024. In a single day in 2025 in December, we had a 7 million of ARR one day in 24 hours. And so NRR and logo retention, it's up to 2026 to determine where those real numbers will be. I think for what it's worth, the ability of these products to go quite broad will be very interesting because to some extent there's initial use cases that you can solve with AI that we target. And then the more time we spend with our clients, the more problems and opportunities we see. And so what's happening to the product is they're growing quite a lot. And so what I think will happen is that this will be like a suite, like a platform kind of play that just becomes more and more of the central system where they do their work. So on an NRR standpoint, do you charge on a per seat basis or on a per task basis or on a volume per task basis? We charge on a per seat basis. Is that optimal? I think that's optimal for the buyer. I don't think that's optimal for us. Yeah. And is that not like solving for a historical norm, not a future? Yes, it is. I actually don't think it's the right pricing model. Yeah, I think it should be consumption based. Because you can have individual users racking up such big LLAM costs that it basically becomes unsustainable on a per user basis. The reason why we have that is You need to make it easy for the buyer. If they don't know how to manage a consumption-based pricing model, you can't have it. And I think that will pivot. And I'm unsure exactly what the timing is. I think the timing is more around when the clients are ready versus when we are ready. And so task expansion is incredibly useful for retention, not for revenue optimization. In other words, the more they do, the more likely they are to retain, but it doesn't actually help your dollars. Right. No, actually it costs a little more. I mean, so it's a bad thing. The money is the product. But we have good margins. We have okay margins. I respect the honesty of that also. Yeah, right. It's not sauce margins. And I think it will take time to get there. Will it get that, do you think? Or yes, I think it will get there. Not only do I think it will get there, but I think your ability to price versus traditional sauce products will be insanely high because you used to use a lot of these products to do very narrow parts of the work. And they were all disconnected. To give you an insight into the life of a lawyer, it's like you have this product over here that you use to compare to contracts. You have this product over here that you use to extract relevant data from contracts. You have this other product over here where you go and look up legislation, you have this other product over here where you're going to go. All these different things. So you as the human had to sit there, come through all these different systems and aggregate the stuff yourself. But now similar to Opus 4.5, you're just going to send the task to La Goura. And it can be pretty arbitrary. And then you let it figure it out. And it just goes and does all the work, or at least a big big portion of the work, in a much much much much shorter time at a very high quality level. And when you do that, you are not being priced against the other source products. You're being priced against, you know, what would I pay a lawyer to go out and actually do this work? So in three years time, we used to have seat-based pricing. Absolutely not. When does that change? When our clients are ready to buy on consumption. Why do you sound so confident that will be within three years respectfully? Because curses consumption, a lot of other enterprise tools are for consumption. I just think legal takes a little bit more time. But within three years, what look like you got to understand my vantage points. Three years is longer than I've been CEO at La Goura for. So three years for me is a very long time going forward. On the margin optimization side, is it a little bit like, you know, obviously where investors are lovable, where they're able to model selection dependent on task and optimize margin because of that? You can do that. Of course, which we do to some extent. But it's also, I don't think we're in the margin optimization time yet. You're in the land grab time. Yes, that's the right way to phrase it. In the land grab time, what is the biggest challenge to e-face? Biggest challenge that we have right now is growing from 30 to 300 and then doubling again in the next two quarters from 300 to 600 and maintaining the ambition, integrity, teamwork and just like raw grit that got us here when you double the team. I think we're just hired to new people in the US and they were really surprised by how late everybody was working. They were like, oh, at the other place, I was at, which was another legal take provider. Everybody left at six and we have dinner in the office at eight. And so when your entire team globally operates at that level and at that pace with that goal in mind, that's awesome. But I care a lot about maintaining that. There's so many maintenance. Well, I still interview everyone. So I ask quite brutal questions about why I take a hard job. You could go work somewhere else. I try to create missionaries, not mercenaries. And I think we're successful in on that. I also think that you get pulled in. Like when you see everybody else doing it, you're just like, okay, of course I've got to do it. And momentum breeds momentum. Like we were signing deals on New Year's Eve. We had a big Christmas dinner. Wiles we were having, Greg was called Mildvine. Yeah, you have that in Sweden. We're having the wine before the dinner and we had the big sales dashboard. Like at the wine thing and everybody kept looking at it. Because like everybody at once momentum, everybody wants to win. And when you join a company and you feel like a winner, I think you get burned out doing work that, you know, where you don't feel like you're winning. Do you think composition is helpful in creating that vibe? 100%. Of course. Do you light the tinder, so to speak, and fuel the fire? Oh, yes. I think I'm very good at it actually. And competition can be played at a macro level where you think us versus them. But you can also do it at a lower level, which is our marketing team wants to be that marketing team. Or our engineers want to build a faster document upload time than that other team. So you compete on all these micro levels and you celebrate them like crazy. What I've learned this year, I actually used to be quite bad at celebrating. I remember when I was in in business school, my dream job was to go to McKinsey because I thought that's right. That's where all the amazing people went. I found out maybe that that was not the case. But when I got the call, I got the job. I was in the in the grocery store and I celebrated by buying a bag of peanuts. Yeah, that was a bit crazy. So I was really about it celebrating, really bad. It's playing why you're so thin, but I. But this year, we've learned to celebrate. And it's amazing. You celebrate the wins really hard because then you also really feel the loss. Because I think it's easy to get to be blindsided if you have momentum and you have success. You need to see the world for what it is. I heard from some of your investors that internals at Harvey, who use their CPO, speaking to the power sense of teams. Well, I think you'll have to ask them, that's funny. I'm going to ask you, have they ripped your product? Well, I think we take a lot of pride in developing our product as fast and as well as we can. And I think there's two main parts to our product development. One of them is improving the parts that we have and the other one is making new qualified bets. I think we have had a history of making bold and correct bets. I think there's many legal tech products that on the surface looks pretty similar. There's even another product where they ripped our name and it's. Our tabular review. It's just called tabular review in their product. Which is totally fine. But what happens when you then go into these competitive pilots and the user starts to kind of rip them apart? That's where you see that one product is a Rolls-Royce or maybe a Volvo. And the other product is maybe a cheaper version. What product decision did you make that with the benefit of hindsight was a mistake? And what did you learn? The first version of the LaGora product back in summer of 2023. That was completely the wrong direction. We built it centered around a couple of core use cases and we did not have an agent or a chat that could operate over those tasks. It was like a click and point use case. Clearly the wrong direction. So after we got accepted into our combinator, we deleted all of that code. I think we made some good product decisions by very early adopting. Basically, Lang Chen was too bad at the time. So we built our own agent architecture and we did that very early, which I'm very proud of. And that was like the right direction to continue on. Now. You still have that today? No, it's been completely rebuilt many times. I last committed code in October 2020. But I'm just intrigued as to how you think about it. We're seeing more and more companies all ideal or all our revenues. Yeah. Build their own complete vertical software. Yeah, I think we're not the size of a revenue or deal. And so it probably doesn't make sense for us to do that. And Lang Chen and a lot of their surrounding tools have gotten a lot better. And so I think we're in the job of. And our engineering team is in the job of picking the best third party things. The other right product decision we made or wrong was that we were doing too many things. So in 2024, we were 12 engineers and we were trying to build six or seven different things at the same time. And that was creating a lot of confusion because I was very involved in the product decisions at the time and I was basically just out doing go-to-market. And so we'd make a lot of product decisions without me in the loop. And then it kind of looked like a Frankenstein monster. This actually a pretty funny doc from October or November 2024. That was called the Leia Product Manifesto. Yeah, we were Leia this. In 2025, we were still like, "Holeia." And it basically outlined that we were going to do three things. But we were going to do those three things so well that our suite was the best basket money could buy. And it was our agent, our assistant, our tabular review, and our word ad in. And we were competing with local products for these different things, right? Like the word ad in was competing with a bunch of other legal tech companies that were only focused on the word ad in. Our tabular review was competing with at the time, like, Hebjah and companies who were only focused on tabular review as. Or the matrix, I think they call it. And then we had our agent. But we said, "If we have all of these things and we combine them in a very user friendly way, that suite is going to be better than buying all of these three things separately. And that's kind of the platform player or the sweet play. That was totally the right move. So we removed five or six other things that we were building, just deleted the code, and then we hard committed on these things. When you look at the landscape, when you think about that bundling, we're just unbumbling, I thought about that. When you look at the landscape today, how does that landscape look in three to five years? Is this a winner take, okay, actually a much better way to ask that is, is this an Uber and a lift, or is this a Google Cloud AWS as your? The reason why I don't think it's a Uber and lift is because in Uber and lift, there was no product differentiation. The products were pretty much the same. And it was very interesting. It's very interesting. It's very interesting on global vastness. Yeah, but it was very hard to build something different. Uber for what it's worth, I mean, the products looks the same today, basically, right, with the addition of, you know, bells and whistles, but it's the same fundamental thing. But the difference to our story is that the product differentiation really matters. And the amount of things that you can go and build is so vast. It's like this universe of legal technology that just has never been built because one of my theories is that maybe in legal tech before generative AI, they weren't that many exciting things to build. And it was really hard to scale a good company. And as soon as you got to like single digit million revenue, you would get an acquisition offer, which would be life changing money for the founders, but no unicorn outcomes. So the product strategy will impact the trajectory of all of the businesses in our vertical tremendously. I think it's totally a winner takes all all sauce. You know, this number one will grab 90% and number two to number 10 will share the remaining 10%. And so I think what that means for us is got to run like hell. You got to win. The type of people who think like that are the people who work at the group. One segment that I do find interesting or two segments is that the verticalization is like we're investors in solve. Yeah. I've always loved them. They've done amazing. This is great. You have verticalization in that sort of way. And then you also have verticalization in that we're going to own the whole vertical and do like a crossbeat. We're going to be your law firm and users. How do you feel about those two? I don't think that owning the entire service layer and software layer is a winning strategy, basically building an AI native law firm. The reason is I think there are so many talented lawyers that are very good at utilizing software and I would not want to compete for them. I think it's easy to get into that space and try and solve lower complexity tasks. I mean, you're starting out with kind of non-disclosure agreements, master service agreements. You can get there pretty quickly, but then that will be a very crowded space in and of itself. I would much rather be the shovel seller to all the world's amazingly talented lawyers who want to turn their firms into software powered entities. I don't think that there will be a ton of margin/profit in the low complexity work because I think as soon as AI can do a task, it will do that task. The only question is kind of where does it get transacted? And the big law firms, they already do NDAs for free for their clients because they got to win the expensive private equity work. And so it's like, are you going to show up as crossbe or somebody else and go, hey, pay me 50 bucks, NDA. I'm not sure. Okay, so we think that's not a good strategy. What about the verticalization? Yeah, I think you can quicker get to a lot of value in verticalizing. I'm not sure what the time looks like within each of those verticals. If you look at patents, it's a $485 billion dollar mark. Yeah, so it's a huge market. So maybe you go win patents and that's amazing. Or patents becomes part of a broader thing, unclear. I think there will be many winners in different layers of the ecosystem. And I also think that there's one part which is kind of the central hub that will, let's say somebody goes to LaGua and they want to write a patent. And why don't we just ping solve intelligence? Yeah. And they say, hey, solve intelligence. Come write us this patent. And then it comes back and does it. Or maybe that's what co-pilot wants to do. Right. I think there's a lot of band diagrams and a lot of overlap. Right now, I think it's more down to execution than it is to like underlying markets being smart about the markets. You have hired now 150 people in the US 50 or 150. No, we're like 50. 50 in the US now. Okay. I think we'll be 150 before summer. It's a lot of people so. Yeah. When you think about that, do you think the canonical wisdom thought that the US works harder? They are harder driving. They are more transactional, but bullish and they are in the office late. We in Europe just like chill the fuck out. Jan's fat having hard 50. I don't think that's fair. I think we were very good at seeding the LaGua culture in the US. And a couple of our best people from Europe went to the US and I've spent a lot of time there. So actually like the hey, we're all such house there's we're so good in the US. Yeah. It's a bit of a bullshit. I think it's a little bullshit. But for what it's worth, the culture that we have in our US office now is I almost want to spend more time in the US just to be there because it's electric. It's I mean, New York is on fire. And I have a hard time spending a lot of time in New York and then coming back to Stockholm because New York is always up. It's always awake. It's my tempo. Whereas Stockholm is when you walk out on the street, but when you're in the office, it's a little sleep. Why are you not living in New York or living in the US? I'm the fact of living on a plane. I had 200 travel days last year in total. Last year, I spent a meaningful amount of time on product and we have all engineering in Stockholm. We're 10% YC founders in our engineering product and design team. Wow. Which is I think is a high number. Two of our batch mates have actually joined the company. How are they different than normal YC engineers? I think what's cool about it is we're structured in a way where I think my management style is very, it's not it's a lot of delegating. It's not very micromanagy and it's very here's the thing go run with it. I think founders do very well with that. I also think it basically gives all the different components of our platform, which is separated into pods. Like we have one team working on this piece of the product, one team working on this piece of the product and there's like a YC founder running part of the product and then they just run like hell on their thing. They are competitive about their part being better than all the other parts or rather their equivalent in other products. I also think YC has a way of attracting very ambitious people who want to win. Before we do Disgast going to future raw firms and then do a quick fight, I have to ask you, I'm going to ask Harvey on the show, right, which you know, great about their revenues. I have to ask you, feels, where are you guys at? Well, I'll tell you a little bit later in the quarter, but in December, we added seven million in a day and we've basically doubled every single quarter for the Lex six quarters. Will you be at 200 by the end of the year? Definitely. Otherwise, I'll come back and you can you can you can you can shame me. What's the stretch go? We'll have to ask Patrick or CRO. If you were 300, would you be happy? Well, I don't view the number in isolation. I'll be happy by the end of the year if we deliver on all the promises we made to clients and we don't even need these competitive pilots. If you're a lawyer and you do serious legal work, you're on LaGoura. It's like Figma. If you're a designer that makes money, you're on Figma. I want that to be the truth and if we do that, I'm sure 300 is the number or even more, right? Okay. In terms of the structure of low funds, they thank you for the work that they now no longer have to do because you do it, but you will need far fewer trainees. You will need far fewer few engineers. Do you agree you will need far fewer genius and what is the structure of a law firm in the future? So I think law firms will go through a quite significant consolidation period because so far there hasn't been a lot of incentives to consolidate law firms, but now actually private equity wants to get in on the action, want to fund different law firms who want to become AI powered. Again, coming back to the idea of do you want to own the whole stack or do you just want to work with the best service layer? And so you're seeing a roll-up play where you integrate AI. Absolutely. I mean, I don't think there's going to be an AM-Law 200. I think it's going to be an AM-Law 20 or maybe AM-Law 12. I don't think it'll be a big four because of regulation and it just takes time, but it will definitely consolidate. At the end of the day, Legora and I care about working with the winners of that space because the technology lever will be one of the most important lever to utilize in competing against other firms. It looks different for different practice areas and in different calibers, but let's take a bread and butter M&A transaction. In a bread and butter M&A transaction, the legal work that the law firms do is pretty much undifferentiated. You get pretty much the same thing depending on which firm you go to. If you just look at the, you know, did they end the work? It's kind of an equilibrium where the price gets offered at. Let's say it's 100, 100,000 pounds. The minute that one of the firms that are playing in this game are able to offer that at a lower price, but same quality, or maybe higher speed or something like that, some attractive aspect of running that deal. Let's say they're offering it at ADK. You kind of break the equilibrium. Everybody has to move to that equilibrium. So it's kind of a market share game. It's like who can run the fastest on technology and all the other aspects of what it takes to run a law firm and who can win most of the market and then hold that market? 'Cause then I think you're able to deliver additional services that go outside of what the very, very, very competitive things are. - Well, we have few junior lawyers in trainees. Bull law firms be smaller. - I actually think law firms will be bigger, right? Because they will consolidate. But I don't think that you will need the same number of lawyers running a transaction as you have today, right? If you have a physical data room, that's why it's called a data room. You just have to send people there. They would open up all the boxes, read everything, make all the comments, right? And then it became a virtual data room. - But you have to assume that there's gonna be more transactions in the future. - Yeah, so more transactions, probably fewer people running those transactions. But every person can run more transactions because of more transactions. - Because of technology. - Just to really be clear, you do not think that will be less trainees in junior hours. - I do think that there will probably be less junior lawyers and trainees because I think that you just won't need as many people to execute the work that the firm has. - Most law firms, the partnerships, right? - Right, and so the partnerships. - The profit. - Yes, so I can take out. - But I'm already seeing patterns of this where firms that we work with will have, somebody leaving, they will not feel the vacancy, but they're doing more revenue than they did last year. And so it's a high profit. I think it might also create an opportunity for big law will do really well because they have a lot of modes and a lot of brand and a lot of data. Small law can do really well because that's still operating on a very, very personal basis. I think where my difficulty is middle law, where it's very competitive, you're competing hard on price, you throw AI into the mix and it will make it even more competitive. But in engineering, let's just take another example. We're hiring more engineers although they're writing more code, right? Because there's more stuff to do. So the thing for the law firms is then it increases the size of the pie. - Do you think we'll have more engineers in two years time? - I think so, actually. 'Cause I think that there'll be, you can just do more stuff. You'll have more people writing code and doing things or starting new things and projects and things in two years and the art today. - I think you're being quite optimistic, which is really nice. But I think we're gonna see more labor displacement than I think people expect. And I think we're gonna see that in the next 12 to 24 months. Jason Lankin, young friend, said this is the year that we're gonna see AI displaced large amounts of knowledge work. And that's gonna show up in labor figures. Do you think that's too soon? - Well, I think it's within that time frame that AI gets pretty good at completing end-to-end tasks very deterministically within our vertical. So unless they can find something else to do then that thing within the firm or growing the pie, then yeah, but here's the cool thing, right? Like if you use technology to complete more of the work, then you need to think about how you win more work from the other firms. But yeah, I mean, on a total, but I'm talking about an individual firm. If you're talking about the total level, yeah, probably. - Do you worry about the demonization of you as a technology leader displacing labor? - No, that's not something that I worry about. (laughing) - I should worry about it. In time, I think it's something that will, can I ask you, time sheets is how lawyers spend a lot of their time. Every two days they have to do their time sheets, do you know this? - Yeah, that's why. - Fucking wild. - Adrian, who was our VP of products. His wife's the company did AI timekeeping. - And wild. - And a billable hour is over. - No, I don't think it is. I think billing will move much slower than both you and I would think, because often it's actually demanded by the clients 'cause they want to get a breakdown of everything that the lawyers actually do. And it will start to be replaced by fixed fees in different practice areas and for different types of tasks, but you will still have a sort of a femoral billable hour above that. Dude, I'm gonna ask you quick fire, so that's how it goes. Three rounds, no deck. What's the biggest advice on fundraising? - The advice that I got in YC was, build a good business and it's very easy to fund risk. - That's what I've lived by. I don't think I'm a master fundraiser by any means, but I'm in a spec. - With respect, I'm gonna push you. Sorry, you got benchmark early, which then led to a rad point. Do you think benchmark is just a massive signal, which led to a quick successive round you wouldn't have had otherwise? - No, so, so, red point was not the fund that first wanted to preempt us. There was another firm that wanted to preempt us for the A round and they gave a very competitive term shade for this series, for this series seed. Much higher price than benchmark. benchmark was I think the lowest price out of any seed fund. - But you play so much value on them that you did the discount. - Yeah, I play value on Chatham. - Chatham not benchmark. - Yes, interesting. - I picked on partner. - Yeah, I heard benchmark was good. You know, I can do that research, but I met within two weeks, probably eight partners. Nobody knew my space better than him. I thought it was great. You know, it's taken three companies public. That's what I want to do. And I thought I'd been much better of working with that guy. - Unthinkable reality, you start another company, but you can only bring one investor with you. - Yeah. - Who do you bring? - Chatham, really. - Yeah, that's it. - Okay, you can delete one investor from your cap table. Who do you delete? - Well, I think I'll delete YC. - Do you regret doing YC? - No, I love YC. But all the other investors are on my board. So I would feel very. (laughing) - Same toward YC. - That'd be a fucking awkward board meeting. - That would be a very awkward, no. - No, but yeah, I think, 'cause they're not that. Well, I think that's unfair. They're extremely helpful still. YC rocks. I still speak with Gustav every quarter. But all the other are either board observers or board of directors. So that I don't. - It's not that. - I can't really comment on that. - What's your most unpopular belief about what AI is having? - I really do believe in the platformization. I think there are way too many point solutions that will not survive a winter bubble, whatever you might call it. And they would deliver more value as being part of a broader ecosystem. - What do you know now that you wish you know the start of layer? - I wish I knew what the intensity of doing and thinking about nothing else would sort of impact your own psyche and personality. For the last two and a half years, I've basically done nothing else than to think about layer or LaGuah or the business. And you know, when you're in college or prior to that, I was doing so many different things. It was nice to do many different things and you got to have many different contexts and you got to do many different types of activities. And when you got tired of one thing, you can go and do another thing. This is not that. It is like running a mega sprint as part of a marathon. And I love it. But I think, you know, could I go back and also have that expectation going in? I think I would have been better at handling other disappointments or you know, part of my life that I couldn't focus as much on. - I think our job is much easier as Vanshan buses than we give credit to. I think when you find obsessed founders that are just quite unhinged and psychopathic, I would put you in that category to be honest. I'd put me in it too, to be honest. But when you find them, it's quite obvious. You know, when I sit down with Alan Chang at Fuse Energy, I said to you, Angel and Vest, and he goes, you fucking stupid. I said potentially my mother thinks so. But you know, tell me why. And he's like to Angel and Vest, I'd have to either sell revolute shares or Fuse Energy shares. That would both be a terrible fucking decision. So now I don't Angel and Vest. - No, no, because you can't focus on doing that. You can't make good decisions. Or you know, you can invest 10K in a friend's company because it's nice. But you can't do it seriously. - An ultimate one, which found it to you most respects and admire in the cup, too? - I'm pretty bad at having idols. I wish I was better at it. I was super nervous the first time I met Don Yeliac. From Spotify. I remember like I was super, I thought that was the coolest thing ever in like 2024. He had reached out to us. I was like, hey, you know, love what you guys are doing. - I know it's amazing. - It's amazing. When I grew up looking at Niklas and Don Yel and Sebastian and seeing these Swedish tech companies succeed, that was phenomenal. That was a huge inspiration. And now having met Alex and Gustav who are taking over Daniel, like they're also fabulous. But I don't go around on a daily basis thinking, oh, I look up to this person. I want to be like them. I try to draw inspiration from where I see good. And then I run at it. - Final one. What's the best advice you've ever been given? - The best advice I had ever been given was probably from YC and Joel at Sona Love's, which was to take the check with Banshmark over anyone else. - Dude, thank you so much for doing this. It's so lovely to join in person. I really appreciate the friendship. Thank you for not letting me on the cap table. I think about it every day. It's fine, I've got over it. 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