20Product: Inside Legora's Tech Stack: Why Token Maxing is Failing Enterprise Startups with Jacob Lauritzen, CTO @ Legora

24:04I'm your little brother coming out of CS at university. What would you advise me to be best placed

24:10Jacob Lauritzen:in the next three to 10 years? So if I were to advise someone on social media marketing, I'd say, hey, you need to be full stack. You need to be able to create the image, get it out, and amplify. Similar thing, I think actually the most important thing is you need to learn how to learn. You need to figure out how you constantly reinvent yourself and keep learning and improve. Because things change all the time right now. It's every week there's something new you should be doing. You need to change your way of working or whatever. The most important thing that you can do for yourself is figure out how you keep at the forefront of what's happening all the time.

24:47And if you can do that, if you're adaptable enough and you are ambitious enough, then the rest kind of works out. Because if you can just learn faster than everyone else, then, you know, over time, you win. To what extent does the quality of Legora as a product depend on the quality of the underlying models? Much less than most people think. The value of Legora is there's so much more around it, whether it's like the primitives that make sense for legal, that make it more efficient to work with AI, or it's all the enterprise-y features or the optimal routing between models. We wouldn't exist without the models.

25:21And every time the models become better, our product becomes better, our agent becomes better. But let's say you took away a model from Ligora, people would still pick Ligora. So they don't buy it based on the model. How has model usage changed for you over time? It changes a lot. I mean, the best model changes bi-weekly. We've been between OpenAI and Anthropik. We keep evaluating all the different models. Do you use like 15 at the same time for different tasks? Not 15, but yeah, maybe 10. So for each task, we will evaluate what model is best at this. Latency, performance, not so much cost. Eventually it will be cost, but latency and performance is most important.

25:59Performance needs to be here. How much can we increase latency without dropping in performance? By building our agent and our other AI features in a way that you can decompose the problem, you can use really efficient models. have latency or performance like the fastest but it may not be the best output or slower but great output yes yeah which one i have to choose yeah uh almost always almost always performance performance is more important almost always if you're a lawyer you can wait two seconds more for the output if it's better you can probably wait an hour more for the output if it's better what do you i'm just fascinated now what do you think about the future of open source as we do move more and more to a focus on cost.

26:40How do you think about that? I think open source is having a great moment. It really, really is. There's so many great open source models now, and they're really easy to run. There's great inference providers that let you run really efficiently. We are moving very close to being able to do things on device. I mean, transcription can run on device. It can run on my iPhone. I have local transcription on my Mac. When I do flights and there's no Wi-Fi, I have local models running so I can keep coding, but it's just like a Gwen model that runs and helps me code. So I think open source is going to play a huge role.

27:08I hope it continues to evolve the way that it currently is. And I think it's an important thing that we have open source model for sovereignty reasons and for security reasons. We should have great open source models. Can I ask, what worries you today? A lot of people are worried about the open source Chinese models, which is why I was kind of thinking about it. More broadly, what worries you when you look at the landscape that we've discussed? I really hope to see European and American open source models. They've been lacking. and I think it would be really, really good to have some. Game theoretically, we won't end up in a great place if there's a duopoly or a monopoly on the models for obvious reasons.

27:46You know, you do want to have some competition. Does Europe have any place to play in the model race today? It should, but it doesn't yet. How far do you think are we in the efficiency frontier on training? Are we like 1 % of the way there? Or is it like, ah, we're 90 % and we might eke out a little bit more? That's a great question. One thing is just like the current architecture. How long does that, you know, does that plateau? Do we need something new? I mean, there's one model released two days ago that's subquadratic, which is huge context length. That's super exciting. I don't know if I trust the benchmark yet.

28:19You know, we need to validate that. But there's architecturally innovations going on still. And I don't know, maybe the current LLM architecture is not the one to take us all the way. What role does not exist today that you think will be very common in five years' time? I think the internal AI systems role thingy for enterprises. I think IT can have a flowering moment here and go from being internal IT that's setting up your computers and whatever to maybe have a sister team that's building tons of internal tools that just make your life so much easier. If enterprises don't create that role, I will get really annoyed because there's so much efficiency to gain there.

29:00Really getting into the enterprise and having all of that for them. Do you have to have FDs to have usage in enterprise? You work with relatively sticky lawyers. Yeah, yeah, yeah. Do you have to have people show them, here you go, here you go? We currently do, yeah. But I think that's just, that's an education thing. In five years, maybe we don't at all. That's the price you pay for being, you know, on the forefront. You have to educate and you have to help. And that's why people want to work with us also. Are you ready for an unfair one? Yes. What have Harvey done better than you from a product perspective or an engineering perspective?

29:34I've been more aggressive with hiring. I have not been aggressive enough with hiring. Because I've always tried to have a very, very small, very lean team, which I believed a lot in. I consistently underestimated how many people we need to be. I had this slide that I drew up a year and a half ago that I showed the entire company. And it was, you know, the 300 Spartans versus the Persians. and it was like Legora and the 300 Spartans. And I said, I'm pretty sure I said, we will cap out at 20 engineers, something like that, which is like way undershooting it. How many engineers do you have today?

30:05Today we are about 80. Yeah, you got that wrong on 20, didn't you? Yeah, I got that really wrong. And we're way too small still. As a result of being too small, you are too slow or you're not able to build what you want to build? Second, there's loads of features that you can basically staff a team to build. Can you ramp as quickly as you need to and retain quality? Yes, we're really good at this. First, we're extremely selective with hiring. Maybe that's also why we're slower at hiring. So we hire really great people and the ramp up time is extremely fast. How do you make ramp really fast as specifically as possible?

30:40Anything that you do? I can tell you what we probably should do. Because the reality is things move really fast. You need to have, so we have a developer experience team, relatively new. Again, a mistake I made. I should have staffed that earlier. And they are making everyone's life so good. What do they do? So they make sure that our local development setup works really, really well. It's super fast. It spins up really quickly. We have our own background coding agent that they built that allows each engineer to have like 10 different agents running concurrently with like all of our local development, a browser, all the iteration stuff.

31:13They're building custom review agents. They're building features so that it can wait and see and wait until everything looks green and all the reviews are good and then raise it to a human the efficiency gains there are huge and they will then also build tooling that helps onboard people and so it can just be like make sure you have really good readme files in your repository so that a new engineer will just ask their cloud code or their cursor about all their questions like that's remarkably effective so it's just like even just ai tooling makes it faster to ramp how many do you have in developer experience and when do you think you should have done it we have three people now which is too few.

31:48I should have done it when Opus 4.5 came out, I think, because that's when I should have done it before that. But then, you know, the productivity of each engineer to Nexus, say. And so if you can make everyone 20 % more efficient, it's even more gains. How does hiring engineers in Europe differ to hiring in the US? There's a few different ways. In the US, people are less risk averse. So like they'll be ready to jump on a lot of things to test. I think in Europe, people are more risk averse. People in Europe generally are more, I don't want to call them mission driven or loyal, but they're like, they really buy into the company that they work for and work with.

32:29So it takes a lot of time to convince them, but once they're convinced, they really stay. That's great. And US is more transactional? I think so, yeah. Do you find the attachment to equity different? It's actually something that we had to sort of educate people on in Sweden. And in Europe, I think it's people are just not used to the venture thing. They don't know how to value equity the same way. Like you have to really, this is how it works. This is what it means. Like these are the, if this happens, then you get this much money. But you don't get it in cash. It's not like, yeah. Yeah, exactly.

33:02And then there's tax. I do it with our team and they're like, wait a minute, you're giving me half a million dollars? Exactly. Not literally, but like in the future. In a way, yeah, exactly. Exactly. So that's been a little bit difficult for us, right? But I think that's part of just creating the ecosystem. In 10 years, the next startup that comes out of Stockholm, hopefully, won't have this problem. Everyone is encouraged to use as many tokens as possible. I'm on the board of public companies, and they're like, oh, I'm hearing about token maxing and talking about that. What do you advise a CEO in terms of intelligent usage of ai and should we just be pushing tokens as much as fucking possible so a few different things on that i think one having a leaderboard a lot of people say this get a leaderboard bring up token users at performance reviews and that leads to token maxing which is people just burn tokens just to look good that's a really stupid way to do anything do hack days do demos have people show everyone else how efficient they are and like how much better they're doing it reward them for being effective and efficient and having more output not for necessarily using ai but like ai will be the way there that's one of the points i had another point for enterprises this is actually where i think cursor has a reason to live a reason to exist which is if your options are codex and cloud code and a neutral third party and you all be you know you pay consumption based cursor can help you optimize your token spend a lot because because they can optimize your usage, right?

34:32They can route them to the cheap open source model or help you set limits for whatever models you want to use for what thing. Well, can they now post acquisition by Grok? Well, we'll have to see if they're first part of everyone. I respectfully disagree, and that's why I actually think both Cognition and Factory will do very well, because they're model independent, but if you... Okay, because you think now that they're tied to X? 100%. Yeah, I was a bit surprised and a bit sad to see the acquisition. Why? Because I thought that they could, If they stayed independent, they had a really cool story.

35:04But I mean, I see the synergies. Obviously, they don't have enough compute. They can't train their own models. They probably have to train their own models. I just think it's a shame that the industry is vertically integrated in that way. Do you think IDEs are dead? I think the current shape of an IDE will die, yes. I don't know what the new, the next IDE is, but it's not reading lines of code. Maybe it's graphical, honestly. Maybe it's the systems, the architecture that you look at and you review and you plan it there and then like agents run off and make sure that whatever you're planning actually is what's being made i don't think it's lines of code what percent of developer salary would you be willing to spend on ai tooling for them i don't want to say infinite but for me it's a question of opportunity cost we're in a competitive environment you know um are you yeah i didn't know that Gotcha.

35:55That's fascinating. I know. There's so many things that we can do. The cost of not doing it is extremely high, and it almost outweighs any sort of token cost. Any efficiency gain is worth so much to us. That's for us, but for certain companies, that will look different, right? The budget on tokens is mostly a question of opportunity cost. Is it worth us spending a ton of tokens to learn if it maybe gives us 20 % efficiency? For us, yes, we have a really high opportunity cost. What did you do that you wish you hadn't done? You know, not investing in developer experience fast enough. Definitely a problem.

36:30Underestimating our growth, also a problem. Now I make sure everything we build will scale to 100x the usage. I used to say 10x, and then that was not enough. So now everything needs to scale to 100x. What changes when you're building for 100x versus 10x? I'm sorry, I'm very naive. No, that's not naive at all. It doesn't always have to change, but there are certain limits that you often will put in place. just be like, yeah, this probably is good enough for the next three months. Like, yeah, okay, if we bound the problem in this way, which is maybe 10X, then we can do X, Y, Z. But maybe that doesn't hold if you're 100X.

37:02And so sometimes you need to think about, I think, particular problems where there's burstiness to it. So Tabular Review is one of our products where you can bulk extract from many documents and many cells. And there's a very big difference between 10 ,000 cells and 100 ,000 cells, just like on the load of the system, because it spikes immediately. And so that's one of those systems where there's actually a difference. And so what do you do in that case where the spike is so immensely different? Yeah. What does that mean you subsequently do differently? We have to think about the experience. If 10 people do that crazy thing at the same time, and we still have a bunch of other users that we want to have a good experience.

37:35So we need to think about fair queuing, basically, which is like, okay, if you're running 100 ,000 cells, you're probably okay waiting a bit. You can go grab a coffee and that's fine. But if you run 10 cells at the same time, those should be really fast. If I ask a really unfair one, if I gave you access to a superior model for six months ahead of anyone else, or superior engineers for six months ahead of anyone else, which would you rather have? Engineers, for sure. Because the models, they change all the time, they get better all the time. But if you have really good engineers, you can build a system that exponentially improves, and that's worth a lot more.

38:09What do you know now that you wish you'd known when you started day one? Honestly wish I'd known how quickly we were going to scale. because that was the thing that I underestimated all the time. I don't think I was ready for this journey. I became ready really quickly because I got slapped in the face every three months. Do you buy that people are destined for certain stages of companies? I'm getting very personal. If I was you, now I'd have in my mind, am I the CTO that takes this to public company? It's a very fair question. No, I don't buy that. I think to me, it's a question of how quickly can I solve problems?

38:44Am I the person that can solve the problems that we have right now the fastest? Or can someone else solve them faster than me? We have a great culture in Legora in that no one has any ego. I've told this to, I currently have two engineering directors. I've told both of them when I hired, if there comes a day when I think you'll do better than I will, then we swap or I do something else. I have very little, and they also have very little, tied into their title or their role. We are here to build something huge, and that's the most important thing. I continuously evaluate myself on my job performance.

39:15If I don't do well, I try to rectify that really, really quickly. And I haven't been able to not rectify it yet, but maybe there comes a day. What's the secret to hiring the best engineers with no ego? And how obvious are they? They're obvious if they have ego. Even just when you negotiate salaries and titles, you can tell. I don't know about you, I always say great people want more money. Yeah. They don't mind so much about the title. I think that's right. Absolutely right. Most of the people that we hire, we don't even talk about their title. We talk about the difficult problems that they're going to work on.

39:46How important is it that you're together in Stockholm? It's been very important for running really fast. I mean, we talked about the handover cost. If you have a PM and a designer and an engineer and they just sit together, you can almost not even have the handover. You can just be like, run at this problem and do it together, the three of you, then it's done. But if you have them siloed and there's handover in between, you lose so much efficiency. Jump on a Zoom call, lacking clarity. Yeah, this doc is not well-written enough. You have to do another meeting, and then you have to do three reviews of the document, and then someone else has an opinion that sees it somewhere and writes a comment somewhere, and then you have to talk about that.

40:23How do you factor that into how the best engineers like to be remote? Well, we're very opinionated about who we are and who we aren't. If you're a great engineer and you want to be remote, then you probably also want to work on very isolated problems. That can be fine. We probably have those and we probably will have those, but they're not for us right now. We'd rather find the people that want to solve the same problems with other people. How many engineers were you having two years or by the end of 2027? You're 80 today. Yeah. I'm going to say a number that's too low. I'm going to WhatsApp it to you on the 31st of December, 2027.

41:00Were you wrong? Yeah, yeah, yeah. I don't know. 300, 200? 200 and 300 are different. You've got to put your name on one. If I have to put my... I want to say the lower number. Let's say 270. 270. Okay, so we're going to have 190 more. Yeah. Can you retain A-only talent with 190 more? That's essentially adding two and a half a week. Is that possible? If it's linear. I think so. I'd rather miss my number and have A players than hit it with B players. As soon as you have people that you don't trust or that the team doesn't trust, the A players won't stick around. You're buying more companies than I'm doing podcasts these days.

41:41And you're laughing because it's true. It's not true. I'm essentially an investor now. My question to you is, do you have to buy companies to get the truly, truly A talent in a lot of cases today? I don't think so, but it's faster. Because if you find a really good person, a really good founder, they're able to attract really good talent. And so you have a small group of five people that are just a talent, and then you get five in one week, you know, if you have to get two every week. And that's much faster than going to all the big companies or even the startups and trying to convince them to come over.

42:15People also, like if you have a small startup of five, eight people, they want to work with each other. Do you just shed their code bases then, or is it like pure aqua highs in a lot of cases? It can be both. If they've worked on adjacent things or think it's in a similar field or even unrelated but similar technology, we'll take all their learnings and we might rebuild it into Lagora. I think that's what happens in most cases. But they become fully embedded into the team. They're all Lagorians working on the Lagora code base and then they might bring some learnings. Is integration hard? It's surprisingly easy if you hire people with low ego.

42:48So if you get five great engineers that don't care about their titles or where they sit in the org chart that just want to solve problems, it's surprisingly easy to integrate. When you've got engineering hires wrong, what did you not see that you wish you had seen? When this goes wrong, it's actually because of my, I'm going to be a little bit introspective here. It's probably because of my own, I don't have, you know, I've not run an engineering team this big before. and so I start doubting. I'm not confident enough in saying this person who's more senior than me, has seen more than me, is wrong.

43:21It's happened once or twice when there's a very, very senior person. We talk and they talk about all this sort of org building and org design and how they think about all this stuff and I sense that something's wrong and I kind of know that all the time but in the end I end up convincing myself that no, they probably know more than me or they figured it out or whatever. Two weeks in, four weeks in, six weeks in, you start to figure out they didn't. How fast do you know if you've made a mishire? A month. Then you know. And then you give them really strong feedback. I give really strong feedback after two weeks.

43:48What does really strong feedback mean, Jake? Really strong means you're not going to stay if you don't change this. Has anyone ever recovered from a you're not going to stay if you don't change this? No. But they need to get the chance. And if they do, they stay. What is the hardest role to hire for today? This is a great question. All of them. No. I think senior management is extremely difficult to hire for. Senior management or horizontal senior management? Engineering directors. Maybe that's always been difficult. We only have really technical people also being managers. And so anyone who's seen scale typically also is no longer technical.

44:21Do we still have managers? And what I mean by that is like, you know, one of my dear friends, Jason Lemkin, from Stashy. It's like anyone on LinkedIn who talks about their team, fire them. Fire them straight away. We don't want managers who manage other managers who manage other managers. If you can't do full stack, get out, pick up your severance and go away. Do we still want like senior managers? Well, you can build a company of super senior engineers that can do everything, and you probably don't need to manage them at all. Especially if there's really strong, if they know what they're trying to achieve, the Codex team, for example.

44:53They all know what they're building, they can just run at it, and they don't need anyone to tell them that they're doing well. But if you have a more complex product that can go in many directions, and you have to do constant prioritization, and you have a suite of engineers and a team of engineers. So the way that we have engineering teams is relatively small teams, let's say six people. PM and an engineering manager. The engineering manager is super technical, spends most of their time coding. They're not like people hold each other's hands and sing songs. But it's still important that I have someone that's accountable to the team health.

45:24Are people doing good jobs? Are people having fun? I can't walk around and judge everyone. Are they doing well? And so I think it's important to have someone who's accountable. And that's how we run it, right? They decide their own roadmap, they're their own little startup, but one person is accountable. Is Max on every new product feature? On big ones, yes. On small ones, no. Is that right? It's worked for us. His time, Max is an amazing salesman, which you'll probably know. And so I think Max spends his time on that, and he spends his time on product vision and the important product things. So big launches, big things here.

45:57He's involved early and for the duration of the project. But for small things, that's the reason you hire great people is that you can let them do this. The thing with Max that is special is you know he so believes what he says. Often when you're being sold, you kind of know you're being sold too. No, no, like there is no way that he sees himself being wrong in his bones. Absolutely. Yeah, absolutely. And also like, you know, I think that was just brilliant. We naturally hate them because they're shit, but Sifted did that piece. With the Taste of Blood piece? Yeah, yeah, yeah. Did everyone in Lagoro just go, oh my God.

46:33Yeah, that was hilarious. Yeah, yeah. There's screensavers now that say bloatsmuck on the... It's like becoming this internal meme. Did you guys like the Jude Law? I loved it. You know I've sat on that secret for like nine months. Did you think it was done well? I think so, yeah. You asked, I guess, if it was not done well. I think the Jude Law idea was great. Did it do well for you guys, do you think? Amazingly well. No, no, crazy well. It's wild. People see it everywhere, which is great. people talk about it a lot, which is like the goal of the campaign, right? It's like we need to get everyone talking about us.

47:06Dude, we're going to do a quick fire round. So I say a short statement, you give me your immediate thoughts. Does that sound okay? Yeah, let's do it. So what have you changed your mind on most in the last 12 months? Hiring. Hiring? Yeah. We need to hire more. As long as adding someone is net positive, we should add someone. What's the most underrated AI company today, do you think? Lagora. Dude.

47:29Jacob Lauritzen:I'm an ambassador and even I'm like no shit dude come on you're gonna give me another one I had to say it one for me would be whisper flow like the pain of removing whisper flow for me it's like immense whisper flow is great I think we're gonna get more local models though whisper flow is not local you're probably gonna get a similar whisper well maybe they should just go local but the tool itself is great finish this sentence the biggest The threat to Lagoor is not Harvey, but dot, dot, dot. The thing that's going to kill us is if we don't keep reinventing ourselves. This sounds really boring, but I think we talk a lot about staying in our swim lane, focusing on our product and our users, and the entire environment is moving so much.

48:14If you had had me on this podcast a year ago, you know, it would have been very different. So I think the main thing that's going to kill us if we don't, if we lose the ability to constantly react and readjust and reinvent ourselves. You just worked with Jude Law in terms of brand campaigns. What sports team would you most like to see a Ligora across? Could be F1, could be football, could be NBA. F1 would be great. I'm a big F, but F1 would be awesome. Strategically, would that be awesome? You do golf very strategically. We do golf. The Yankees we sponsor in New York, which is also great. You sponsor the Yankees?

48:48Yeah, you didn't know this? Aaron Judge. fucking hell how much does that cost that I can't tell you but I would want you know the team that I would want us to sponsor my local FC Copenhagen football club that would be a childhood dream they're doing really bad right now though so it's probably really cheap actually it's called exposure yeah

49:06Jacob Lauritzen:you would get nil let's do it yeah exactly I mean the Champions League no Europa League they're not even top of the Danish league yeah that is no you should be CTO probably cheap don't be CTO no I know it's okay What is one thing you believe about the future of law that most people would say is crazy? If I had to get crazy, I think there's lots of analogies to coding in law. It's very text-based. So the agent AI features are similar. If I believe that coding, we're going to look less at source code and more of like one layer above, I have to say the same thing about law. Like eventually, lawyers will not be nitty-gritty about the language of the contracts.

49:47they will work a level above, which is maybe like, what's our negotiation stance? What risks are we okay? Which ones are we not okay taking? And not sit and type into Word. What's the biggest advice to a founder competing in a business slash industry where there is an 800-pound gorilla? Honestly, just work harder than the 800-pound gorilla. People underestimate this, like the 800-pound gorilla. No one in the 800-pound gorilla is extremely excited to be there. I think that's just like, if you're competing against Google, like the PM in Google that you're competing against he does not give a shit if it goes well or not.

50:20Maybe she tries really hard but if you're a small lean team you work really hard you can do really remarkable things. You ready for a bet? Yes. What are we going to end the year at revenue wise? It's going to be it's going to be above 250. We have 272. 272? Yeah. I think it's going to be above that too. I don't want to I don't want to get in trouble. I'm just a senior. I don't have numbers.

50:44Jacob Lauritzen:I didn't mean it, Max and Patrick, I don't know. David's going to call me really mad soon. Dude, this has been such a pleasure. I've loved having you and you've been fantastic. Thank you. Thank you. This is my first podcast ever, by the way. But before we leave you today, you know what's wild? We have AI superpowers now, yet so many product teams are still flying blind. Buried in spreadsheets, chasing feedback across 10 different tools, Jira Product Discovery fixes that. I've spoken with hundreds of product leaders, and the best teams all do one thing differently. They build a system to capture ideas, validate them with real data, and focus their roadmap on the right things.

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