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Why Token Maxing is Failing Enterprise Startups | Legora CTO

Jacob Lauritzen serves as the CTO at Legora, the fastest growing B2B enterprise company in history; hitting $100 million in ARR in just 18 months . Legora boasts a valuation of $5.6BN and has raised a total of $866 million in funding. Legora's investors include the likes of Accel, Benchmark, and Bessemer Venture Partners, alongside strategic tech giants NVIDIA (NVentures) and Salesforce Ventures. ----------------------------------------------- Timestamps: 00:00 Intro 01:19 Building Engineering in 2026 vs 2024 03:44 Code Is Now Cheap: So What's the New Bottleneck? 06:03 AI Code Review Is Still Broken 07:19 The Future Engineer: Systems Design Over Writing Code 10:28 Over 50% of Legora's Code Is Now AI Generated 12:48 How AI Is Making PMs and Postmortems Faster 15:31 Does Taste Matter or Is It Silicon Valley BS? 17:47 You Can Build Faster Than Lawyers Can Consume 31:06 What Harvey Has Done Better Than Legora 32:47 The Developer Experience Team: The Most Underrated Hire in Engineering 34:05 Hiring Engineers in Europe vs. the US 45:44 Token Maxing: Are Enterprises Using AI Wrong? 55:13 The Crazy Prediction: Lawyers Will Work One Level Above the Contract ----------------------------------------------- Subscribe on Spotify: https://open.spotify.com/show/3j2KMcZTtgTNBKwtZBMHvl?si=85bc9196860e4466 Subscribe on Apple Podcasts: https://podcasts.apple.com/us/podcast/the-twenty-minute-vc-20vc-venture-capital-startup/id958230465 Follow Harry Stebbings on X: https://twitter.com/HarryStebbings Follow Jacob Lauritzen on X: https://twitter.com/jacsebl Follow 20VC on Instagram: https://www.instagram.com/20vchq Follow 20VC on TikTok: https://www.tiktok.com/@20vc_tok Visit our Website: https://www.20vc.com Subscribe to our Newsletter: https://www.thetwentyminutevc.com/contact ----------------------------------------------- #20vc #harrystebbings #legora

Harry StebbingshostJacob Lauritzenguest
Jun 6, 202657mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:00 – 1:19

    Intro

    1. HS

      What percent of developer salary would you be willing to spend on AI tooling for them?

    2. JL

      I don't want to say infinite, but for me it's a question of opportunity cost. We're in a competitive environment. There's so many things that we can do, and the cost of not doing it is extremely high. It just almost outweighs any sort of token cost.

    3. HS

      Now, I'm so excited to welcome Jacob Lauritzen, CTO at Legora, to the show today, the fastest growing enterprise company in history. They hit $100 million in ARR in just 18 months. Jacob is one of the best product minds I've had on the show, specifically from the last crop of product leaders in this AI generation.

    4. JL

      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.

    5. HS

      Ready to go? [upbeat music] Jake, dude, I am so excited for this. I think Max is one of the most... Do you know what? I think it takes a psychopath to know one.

    6. JL

      [laughs]

    7. HS

      Uh, [laughs] and he's like, "Fuck you, Harry" already.

    8. JL

      True.

    9. HS

      Um, but he's just exceptional, and I know the bar of talent that he has, and so I know that this show is gonna be amazing. So first, thank you so much for joining me.

    10. JL

      Yeah, of course. Thanks for having

  2. 1:19 – 3:44

    Building Engineering in 2026 vs 2024

    1. JL

      me.

    2. HS

      Now, we were just chatting, and you said Legora is the first kind of big company or, like, company of this size that you've worked at.

    3. JL

      Mm-hmm.

    4. HS

      And I was thinking, is that a blessing or is that a curse?

    5. JL

      Yes.

    6. HS

      How do you think about that?

    7. JL

      Um, I th- I'd like to think that it's a blessing. Uh, I just have to be really, really humble about it. [laughs] So essentially, um, I don't have any priors coming into how to build an engineering org. Um, I think building an engineering org in 2026 is very different from doing it in 2024 maybe even. And so I think, um, in that way it's really good that I come in naive, and I'm like, "Okay, let's try to do it this way, and if it doesn't work, we keep iterating." Just like we keep iterating on our product, we keep iterating on sort of our organization and our processes, and I, yeah, I just work with the team, like, "What's, what's working well? What's not working well? How do we solve that?" Just like any other problem.

    8. HS

      Dude, how is it different building a team in, and your product, in 2026 versus 2024 and years prior?

    9. JL

      Everything's just changing all the time right now, you know? [laughs] Uh, productivity is through the roof. Um, processes are up in the air. Um, you can be huge teams. You can be tiny teams.

    10. HS

      Productivity is through the roof.

    11. JL

      Yeah.

    12. HS

      If we unpack that, why is it through the roof?

    13. JL

      Well, just AI tooling. I mean-

    14. HS

      It's simply, like, what do we use internally?

    15. JL

      It's CloudCode, it's Cursor.

    16. HS

      You use both?

    17. JL

      Those two are competing. Yeah, yeah.

    18. HS

      Wow. 'Cause everyone's like, uh, run from Cursor at whenever I interview them.

    19. JL

      Right. Yeah. Yeah.

    20. HS

      Yeah, yeah. So you still have Cursor users?

    21. JL

      We still have Cursor users. Um, the Cursor harness is quite good. Um, I've... You know, there's, there's some personality differences on our team, but, but a lot of people still use Cursor. Um, some use CloudCode, some use Pie, 'cause CloudCode's con- harness is, is annoying sometimes. Um, we allow people to do both. Um-

    22. HS

      Okay, and so we have, like, efficiency against that, and so we just ship more?

    23. JL

      We ship more, we ship faster. Um, we debug things faster. We iterate faster. Everything is faster now, and each engineer can produce much more than they could previously. Um, and that just has a ton of ripple on effects throughout the org, basically, and how you're structured, 'cause, um... I mean, I think it... A, a way I like to think about it is, you know, when you build software, there's kind

  3. 3:44 – 6:03

    Code Is Now Cheap: So What's the New Bottleneck?

    1. JL

      of, like, three phases. There's phase one, which is the product work. You know, what are, what are we building? Um, translate user pain, user dreams, nightmares into something tangible that we can try and we can iterate on, and, and we can figure out if it works. Then once you have that, you know sort of what you want to build. Then you build it, you write the code, and then, uh, you review the code, and you merge it, and you, you get it going. And number two was the primary bottleneck for the past 100 years almost. Um, so, like, the rate limiter was how quickly can you write code.

    2. HS

      Mm-hmm.

    3. JL

      That is now super cheap, so that's sort of been compressed. And so the, the bottleneck now is, like, the, the two other ends, which is, uh, review. How can we do that much more efficiently? Um, and then it's, how can we actually do the product piece much more efficiently? 'Cause, you know, if you believe that code is cheaper to write, then naturally the two other things are bottlenecks, and that means, you know, uh, one of the focus areas is how do we do the product work as efficiently as possible.

    4. HS

      How do you think about that, then?

    5. JL

      [laughs] That's a great question. Um, s- s- part of that is, um, how do we make our PMs as efficient as possible? How do we sort of take all the, mm, working with clients, synthesizing what they think, our own strategic priorities, our own taste and opinions of our vision of where, you know, our product is going, um, how do we make them do that as efficiently as possible and hand that over to engineers as efficiently as possible? I'm not sure if I've solved that yet, um, but I do think it's like that's the way that I'm thinking about it, is constantly what are the... what's the bottleneck to our velocity? And then we try to solve that.

    6. HS

      You said about the, uh, the kind of review being one element of it-

    7. JL

      Yeah. Yeah

    8. HS

      ... that could be a bottleneck.

    9. JL

      Yeah.

    10. HS

      Do we see AI code review becoming the dominant source of review, and does that then remove it as a bottleneck?

    11. JL

      I think so. I think that's one of the solutions. Um, we do AI code review today, and it's, it's in its nascent phase. It's [laughs] you know, how to put it?

    12. HS

      That's like when I was fat when I was young.

    13. JL

      [laughs]

    14. HS

      My mother used to just say I was big-boned.

    15. JL

      Oh, great. Yeah, exactly. So like-

    16. HS

      And it's like, "No, you just ate all the Maltesers, Han."

    17. JL

      [laughs]

    18. HS

      It's in its nascent phase is sweet.

    19. JL

      That's the... Yeah, that's the nice... It's, uh, yeah, rough edges still. Um-But

  4. 6:03 – 7:19

    AI Code Review Is Still Broken

    1. JL

      no, I complete... I, I, I think that's right. I think that's... Part of it is, um, getting... You know, we have AI review bots. You can have, like, security review. You can have different specialized reviewers. They do about tons of, tons of review, and they sort of iterate with the AI coder, and it's, like, kind of weird because you see this pattern where it's, like, agents fighting each other until they arrive at something. Um, but even then, I think just, like, current review tools are not good enough. I think we need something new. Um, I keep telling people [laughs] at all events that I'm at, like, "If you're gonna do a startup, please do something that solves the review thing." Um, because no one wants to look at the older lines of code. It's like, what's important is what are the, the... What's the impact on systems architecture? What's the impact on systems design, stability, um, security boundaries? How does it sort of take our system in the right direction? That's the kind of stuff that you want to review, and if that doesn't change, then maybe you don't have to review it at all. Just, you know, unleash the agent. But if it does, if there are some strategic trade-offs, then you want a human to be like, "Yeah, this is the right direction to take."

    2. HS

      Is that the future of engineering, being systems design, systems architecture, and then bluntly code creation, code maintenance-

    3. JL

      Mm

    4. HS

      ... is actually completely done by

  5. 7:19 – 10:28

    The Future Engineer: Systems Design Over Writing Code

    1. HS

      AI?

    2. JL

      Yeah, I think so. I think so. I, I think that's right. The job of a sys- of a, of an engineer is changing from typing a bunch of code to sort of one layer above it, which is, um, what does the system look like? And then you can have AI running around inside each of the pieces of the system, but you sort of have engineers thinking about the higher, um, level one abstraction above, which is like, what does the system look like? What are the bets we're making in different places? Do we want to invest into doing something here that we can reuse a bunch of places over here, and it's gonna make everything much more stable? That's one of them. I think the other thing that engineers are doing more and more, which is an explicit role with us soon, which is, like, kind of the meta engineering of making agents really effective. So you know how you have developer experience teams-

    3. HS

      Yeah

    4. JL

      ... that, you know, whatever they might help write custom linting or custom developer setups to make developers efficient. We, we kind of need to have the same team for agents. Like, how do we make agents really, really effective? How do we make sure that we can enable agents to sort of, um, independently self-improve the system? Can we, can we gather data in a really good way so that we can just unleash agents and say, "Hey, you know, increase, uh, conversion rate on my e-commerce store," and it can just, like, go and run experiments. That sort of setting up the loop so agents can just, like, run and, and, and optimize, I think that's gonna be a, the actual job of a lot of engineers.

    5. HS

      How do you think we do that? I, I, I spend a lot of time-

    6. JL

      Mm

    7. HS

      ... with, um, Jason Lemkin and Anushri Mehta-

    8. JL

      Yeah

    9. HS

      ... who's amazing, but they, they both told me that fundamentally, uh, you know, in a world where agents are the pickers of software, the API quality that we have is the core determinant of what agents will choose software based upon.

    10. JL

      Mm-hmm.

    11. HS

      How do you think about how we make agents more effective? Is it a simple question there of data and making sure we're the best at that? How do you think about that?

    12. JL

      We have to set up the guardrails really effectively. This is actually something that I'm thinking about right now. So our code base is starting to get large. [laughs] Happens. It's a good problem to have. Um, we're starting to be a lot of engineers. We're also starting to be a lot of agents that are working on this together, and so, um, you start to think about how can I mechanistically enforce the system to behave a certain way, and, and so I'll try to give an example here, which is, um, you can have custom rules, for example, which is like the agent tries to do something, and we tell it, "No, you can't do that." You know, there's like, for whatever reason, you can't do that because we want the system to be in this way, and I think that type of, um, guardrail setting we'll see everywhere. And so if you're a big enterprise, and you're rolling out AI tooling, and you, you have agents that build your own internal software, you know, you have AI tools that build your, um, HRIS system and your, you know, ATS system and whatever else, you probably have some engineers that are just setting up the like, this is where you get the data. This is what you can do. This is what you can't do. And then you can just let agents run amok inside of that system, basically.

    13. HS

      You mentioned the expansion of the Legora, uh, code base today, but what percent of code created today is AI generated versus human generated?

  6. 10:28 – 12:48

    Over 50% of Legora's Code Is Now AI Generated

    1. JL

      Actually, I took a look recently, and it's Claude and Cursor on the top, and there's like... I think it's like 2% between them, so they are really, really close. Um, and then it's, you know, miles above the next engineer. So they're way above 50%.

    2. HS

      Do you worry that we will see a next generation of security threat with the amount of AI-generated code that bla- bluntly opens vulnerabilities we didn't know we had?

    3. JL

      Yes. Absolutely. This is, uh, very top of mind for me, and that's why we still, at Legora and, and probably in a bunch of other enterprise software, we, we still review human PRs, every single one, just because we have to be sure. Um, I think that's inefficient. I wanna, you know, get some risk scores in there and change that so that we can run really fast, but, um, fundamentally, uh, y- I think you're right. I think threat actors, um, are extremely efficient now, which means, like, they can try so many different things, and they can keep running at it, um, and so we need just as, um, good defense, and I'm not sure if we're there yet.

    4. HS

      I definitely don't think we're there yet.

    5. JL

      Yeah.

    6. HS

      Which is why we see so many hacks. [laughs]

    7. JL

      Yeah. [laughs]

    8. HS

      And so whenever I see the hack on Twitter, I'm like, oh, poor and name the founder.

    9. JL

      Yeah, this company. Yeah.

    10. HS

      Oh, s- their weekend is thoroughly ruined.

    11. JL

      Yeah, yeah, yeah.

    12. HS

      Um-

    13. JL

      I, I had a security in- Oh, not me. One of our vendors had a security incident just yesterday. We just rotated a lot.

    14. HS

      [sighs]

    15. JL

      Yeah. I mean, just, you know, to be clear, this was internally. It doesn't, doesn't affect any of our clients or anything like that, but it's just I think we're gonna see more of them.

    16. HS

      Yeah, yeah, no, I totally get that. I interrupted you. When we spoke about the efficiencies earlier that comes with AI, you mentioned the second was the processes that change.How do processes change, be it PRs-

    17. JL

      Yeah. Yeah

    18. HS

      ... be it Postmortems?

    19. JL

      Well, actually, Postmortem is a great example. We run them really efficiently now. [laughs] It's, it's great. And, you know, if you have an incident, now you just unleash an, an SRE agent, a- and a, sort of a, an incident agent, and it will just super quickly figure out what's going on, look at all the logs, look at all the matrix, uh, metrics, sorry, telemetry, and it's surprisingly good. It's really, really good. And so like instead of having a bunch of engineers wake up in the middle of the night, you still have some waking up [laughs] in the middle of the night, but they are, uh, really well-equipped, and the postmortem basically almost writes itself as well. Um, so that's actually a great example [laughs] of something that we can run really efficiently. Um,

  7. 12:48 – 15:31

    How AI Is Making PMs and Postmortems Faster

    1. JL

      but I think more broader in sort of the software development life cycle with AI, um, PMs can prototype super, super fast, which is really, really great 'cause that means you can front-load a lot of the work. So like a PM can start however long before. Once he or she has the, you know, smallest inkling of an idea that we might wanna do this, they can prototype it, and they can just go to users. They can, they can test it, and they can iterate themselves. They don't even need to bring in engineering until they have something that's like clearly super valuable, and then we can switch, and we can say, "Okay, now we take this from prototype to something that's like actually, uh, fits in the system and is super reliable."

    2. HS

      Do we skip the design stage in a world where prototyping and getting to V1 is so much easier?

    3. JL

      Probably some companies will skip the design phase. I think, I think we can skip the design phase on functionality. Uh, you don't need to necessarily have this long, [laughs] you know, discussion, uh, where you sit 10 people and you figure out where should the button be. I do think design still has a place, but it's maybe, you know, one level above the individual feature, the individual stuff that we build. It's the design language that we choose to have. It's the taste. It's the, um, opinionated stance we have of who we are and, like, what does Legora look like, um, what's the navigation, what's the hierarchy, um, but it's more for consistency, UX, UI sake than ... and, and for taste's sake rather than, uh, functionality. So.

    4. HS

      Totally get that. Do you still use Figma today?

    5. JL

      We still use Figma, yes. I know where you're going with this. [laughs] Um, as soon as you start building a system that's larger than something very small, you want consistency, and you want, um, to have a design language and all that kind of stuff, and so you need somewhere to store what your button looks like and what your, like, pages look like and what's this and what's that. Um, and for us, that's Figma, and it works great for it. Um, could it be-

    6. HS

      Do you think that's the case?

    7. JL

      ... Mac down files?

    8. HS

      Yeah. Do you think that's the case moving-

    9. JL

      Well-

    10. HS

      I don't mean anything against Figma, but it's like-

    11. JL

      Yeah

    12. HS

      ... that's like a storage feature. [laughs]

    13. JL

      Yeah, no, exactly.

    14. HS

      It's like moving files.

    15. JL

      It could be something else. Yeah, you're right. Then the question is, is it faster for designers to take a prototype to something really crisp in Figma versus prototyping?

    16. HS

      We mentioned the wonderful word earlier that's like the word of the moment, which is taste.

    17. JL

      [laughs]

    18. HS

      Ah, no, no, w- we'll ... Taste is what separates us. How do you think about the, "Don't worry, taste is what the differentiator will be"? Is that true, or is that bluntly Silicon Valley and tech BS that's trying to protect us?

    19. JL

      [laughs] Uh, ta- I

  8. 15:31 – 17:47

    Does Taste Matter or Is It Silicon Valley BS?

    1. JL

      think taste is important. There's different flavors to taste. [laughs] Uh, pun intended. I, I ... It depends on what you mean with taste. I think to ... You know what? In tech, taste is like we have an opinionated stance on something. I think if you don't have taste, then you let AI slop converge to sort of grayness and, and everything looks the same, and everything's just like ... I think you need to have taste to have sort of an opinion and a stance in the world.

    2. HS

      Yeah.

    3. JL

      This is who we are. This is what we do, and, and we don't do these other things, and that's not for everyone. I think to me that's what taste means. It's like, "This is who I am. This is who we are, a- and, and some of you are gonna hate it, and that's okay," um, because you need to have some edges. You know, if you're just like letting, letting AI rip, you're gonna look the same as everyone else.

    4. HS

      When the cost of copying is quicker than ever-

    5. JL

      Mm

    6. HS

      ... does that change how you think about product? You're in a, a very competitive-

    7. JL

      Yep. Yep

    8. HS

      ... space, and plenty of people can copy you very quickly. Does that change how you think about product?

    9. JL

      No, not really. I think the important thing for us is that we're building something that our clients get a lot of value out of, and we build that as fast as we can, but we don't build it faster than that. Um, there's like ... There are, there are tons of people that are, um, vibe coding. You know, there's people that are vibe coding Legora. There's people that are vibe coding Salesforce and, and, and DocuSign and other companies. Um, it's very quick to get to the 90% where it looks the same and, and in like 80% of the cases it, it works similarly. It's the, it's the other 90% that are difficult. [laughs] You know? It's like ensuring all the edge cases work and all the unhappy paths and all the, um, audit locking and all the RBAC and all the, um, weird scenarios that you end up at at a certain scale. That's what's difficult. Um, so no, we just, we keep focused on how do we create the most value for our clients and sprint towards that as fast as humanly possible.

    10. HS

      My, my girlfriend is a lawyer, and she's wonderful, but they're not the fastest in terms of-

    11. JL

      Sure

    12. HS

      ... adoption and-

    13. JL

      Yeah

    14. HS

      ... usage. I'm gonna get in huge trouble for saying that. I was not talking about her. I was just talking about the legal profession.

    15. JL

      Okay. Good.

    16. HS

      Um, you can build product so much faster than your customer can consume it.

    17. JL

      Yes.

    18. HS

      How do you think about that?

  9. 17:47 – 31:06

    You Can Build Faster Than Lawyers Can Consume

    1. JL

      That's a great question. We have this notion internally that there's the speed of, of AI, there's the speed of our product, and then there's the speed of humans. [laughs] You know? And they're like ... They're not, they're not the same necessarily.

    2. HS

      Yeah.

    3. JL

      Um, I think that's part, honestly, of the beauty of what we're doing is that we're translating theImmense speed of AI development into a user base that's been historically underserved, and, um, we're sort of taking them along on for the ride. And so I think sometimes it can be frustrating, but it's also really, um, rewarding that we can actually take this huge base of people, and we can really change the way that they, uh, work and their efficiency and their productivity, and we can remove the, you know, butt loads of awful work [chuckles] that they've spent their time doing and focus on the more strategic, more important work.

    4. HS

      What have you not done that you wish you had done?

    5. JL

      An email client would've been really cool. I would've loved to build that. I've vibe code one just for fun. Um, we're probably a few ways [chuckles] you know, we're a little way from that 'cause there's other high priority things, but I think that's... An email client is where our lawyers sit a lot.

    6. HS

      Do you vibe code internally within Legora for customer presentations, for you name it?

    7. JL

      Constantly.

    8. HS

      Is that the future of enterprises, or is that bluntly Legora at the very precipice of innovation?

    9. JL

      It will be the future. I don't know when, but it will be the future. I think there's like-

    10. HS

      And just so we understand, like what does that mean? Like, you, you build sites for Slaughter and May so you can pitch to them and Clifford Chance so you can pitch to them?

    11. JL

      We, um, no, but it's, it's way broader than that. It's like we have a, a t- a team now that's internally AI enablement, which is just like reimagining, you know, again, from first principles with all the stuff that we have today. If you're building the most efficient company to go from, let's say, 200 to 1,000 employees, what does that look like? And that means obviously, you know, Cloud Cowork and similar things for everyone, but it's also like, can we just build a bunch of the tools that we need ourselves? Can we just vibe code a bunch of the tools? Can we vibe code our, um, HR system? Can we vibe code our talent acquisition system? Can we vibe code our payroll system? Like, so many things where there exists, tools exist out there, but you always need to customize them so much, and they always basically never really work, and we just built them now 'cause it's so cheap to build.

    12. HS

      What have you been able to vibe code away?

    13. JL

      Let's see. We've primarily... Well, we've added a bunch of things that are additional or additions to vibe coding. So [chuckles] a great really stupid example is, um, Ryan, who joined from Canada, we have a team of people joining from Canada, they're all moving to Sweden, and he vibe coded the, an app to help everyone migrate. So like very specifically, if you're Canadian, these are like all the laws and all the steps you take, and there's like, it's interactive, and you can see how far you've made it, and it's awesome. And it took, I don't know, a day to vibe code, and it saved so much time for an entire team. So it's like y- you can build the big systems, but even just all the small ones that you can build really add up.

    14. HS

      So I was with a, a friend who's a public company CEO the other day, and he was like, "You know, my chief of staff took three weeks off and basically vibe coded Cooper, and we replaced Cooper. Um, and it works, and it's brilliant." What do you say to people who are like, "That's ridiculous. Why would you ever bother vibe coding and taking months to do-

    15. JL

      Hmm

    16. HS

      ... an HR system-

    17. JL

      Yeah

    18. HS

      ... when you could just buy it off the shelf?"

    19. JL

      It really depends on the system. There are certain sys- I think basically there are like s- Let's say there are systems that are, um... Let's say there's two actually s- systems. There's, there's the, the horizontal one, which is like how big is your, um, product surface area, and there's the, the, the vertical one, like how complex is it? So if you're deep, you're essentially your surface are... It looks quite similar. It's a simple app, but it's just a lot of complex stuff. It hides away a lot of complexity to the user. And there's the other one, which is your very, very shallow app, which is like tons of things you can do, but there's not that much complexity. If it's a shallow app and it requires a lot of customization from you, maybe you just build it. That's probably actually the right thing to do. If it's a very deep one, there's, there's just too much stuff for you to build, and it's not viable for you to do. That's kind of how, you know, I think about it.

    20. HS

      We, we mentioned PMs and, like, their proximity to customers and then that delivery mechanism back to engineering, which is kind of always what PMs did and did best.

    21. JL

      Oh. Hmm.

    22. HS

      Does the role of the PM change in the next few years?

    23. JL

      Yes and no. [chuckles] Um, I think there, there are certain people that are, or a lot of people are saying that product and engineering are converging. It's becoming one thing. It's like one person can, um, do the product work and build the enginei- like build the system and, and ship it and everything, and I think for, for some companies that's true. I think for companies where you really need PMs, it's not true, or it can be true, but it's inefficient, and I'll tell you why. So we were talking about, um, product. You know, you do the product work first, the scoping, and then you build it, and then you, you, you ship it, and you review it. In a company like Legora, we're always focused on the bottleneck, and the bottleneck is no longer coding, which means the bottleneck is the product work. And so you don't want your product people to do engineering 'cause, like, the, the opportunity cost of that is really high 'cause what you really want them to do is the product work, like talking to customers, uh, figuring out, doing the synthesis. That's the bottleneck. So if, if your PMs are coding a lot, if they're spending 50% of their time coding, we're missing out on so much product work.

    24. HS

      Hmm.

    25. JL

      So that's how I think about it right now. And for certain companies, if you're doing developer tooling or doing consumer where engineers intrinsically have a good sense for their own or they are their own clients, you maybe don't need a PM at all 'cause, like, you don't... But I think you haven't needed a PM before AI either there. So I don't think that changes with and with- without AI. PMs can now do engineering. That changes with AI. Um, but it's not always efficient to do it. It's like a matter of opportunity cost, and there's handover cost, which is, um, if I do all the product work, and then I give a PRD and I give it to an engineer, then, like, you lose efficiency there. So it's, it's good if PMs do some amount of vibe codingTo like show very high fidelity, "Here's a prototype, this is exactly what it looks like," then it's efficient

    26. HS

      To reduce the handover cost.

    27. JL

      Exactly. Yeah. Exactly. But they shouldn't spend a lot of their time engineering because if they just like focus on actual engineering, we lose out on, uh, on the product work.

    28. HS

      I'm your little brother coming out of CS at university, what would you advise me to be best placed in the next three to 10 years? So if I were to advise-

    29. JL

      Yeah

    30. HS

      ... someone on social media marketing, I'd say, "Hey, you need to be full stack. You need to be able to-

  10. 31:06 – 32:47

    What Harvey Has Done Better Than Legora

    1. JL

      I don't know. I think they've, um, they've been more aggressive with hiring, which I actually think, um, I have not been aggressive enough with hiring 'cause I've, I've always tried to have a very, very small, very lean team, which I believed a lot in. Um, and I, I consistently underestimated how many [chuckles] people we need to be. I had this slide that I drew up, uh, maybe, you know, 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," or something [chuckles] something like that, which is, like, way undershooting it. Um-

    2. HS

      How many engineers do you have today?

    3. JL

      Today we are about 80.

    4. HS

      Yeah. You got that wrong on 20-

    5. JL

      I got-

    6. HS

      ... didn't you?

    7. JL

      Yeah, I got that really wrong, and we are way too f- we're way too small still.

    8. HS

      As a result of being too small, you are too slow, or you're not able to build what you want to build?

    9. JL

      Second.

    10. HS

      Mm.

    11. JL

      There's, there's loads of features that we... you can basically staff a team to build that we just can't do-

    12. HS

      Can you ramp as quickly as the... you need to and retain quality?

    13. JL

      Yes. We're really good at this, actually.

    14. HS

      How?

    15. JL

      First, we're extremely selective with hiring. Maybe that's also why we're slower at hiring. [laughs] So we hire really great people, and the ramp-up time is extremely fast.

    16. HS

      How do you make ramp really fast, as specifically as possible? Anything that you do?

    17. JL

      I can tell you what we probably should do. [laughs]

    18. HS

      Sure.

    19. JL

      'Cause, like, the reality is things move really fast. Um, you need to have... So we have a developer experience team, relatively new. Again, a mistake I made. I should've staffed that earlier. Um, and they are making everyone's life so good.

    20. HS

      What do they do?

  11. 32:47 – 34:05

    The Developer Experience Team: The Most Underrated Hire in Engineering

    1. JL

      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. They'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. So, like, 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 that you have really good README files in your repository so that a, a new engineer will just ask their cloud code or their cursor about all their questions." Like, that's remarkably [chuckles] effective. So it's just like even just AI tooling makes it faster to ramp.

    2. HS

      How many do you have in developer experience, and when do you think you should have done it?

    3. JL

      We have three people now, which is too few. I should have, I should have done it, um, when Opus 4.5 came out, I think, because that's when... I should have done it before that, but then, you know, the, the productivity of each engineer 10X's, say, and so the, the... If you can make everyone 20% more efficient, it's, it's even more gains.

    4. HS

      How does hiring engineers in Europe differ to hiring in the US?

  12. 34:05 – 45:44

    Hiring Engineers in Europe vs. the US

    1. JL

      There's a few different ways that it differs. In the US, people are generally less risk-averse, so, like, they'll, they'll be ready to jump on a lot of things to, to, to test. I think in Europe, people are more risk-averse. People in Europe, and I'm super generalizing now, but I think generally are more, I don't wanna call them mission-driven or loyal, but they're like, they really buy into the company that they work for and work with. Um, so it takes a lot of time to convince them. But once they're convinced, they really stay, and, um, that's great. [laughs]

    2. HS

      And US is more transactional?

    3. JL

      I think so, yeah.

    4. HS

      Do you find the attachment to equity different?

    5. JL

      It's actually something that we had to sort of educate people on in Sweden. [laughs] And in Europe, I think it's, it's... People are just not used to the venture thing. They don't know how to, uh, 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."

    6. HS

      But you don't get it in cash. It's not like-

    7. JL

      Exa- Yeah, exactly. Yeah.

    8. HS

      Yeah.

    9. JL

      And then there's tax and then there's, then-

    10. HS

      I do it with our team, and they're like, "Wait a minute. You're giving me half a million dollars?"

    11. JL

      [laughs] Yeah. Exactly.

    12. HS

      And you're like, "No, no, no. Uh, not literally, but, like, in the future."

    13. JL

      In a way. Yeah, exactly.

    14. HS

      Yeah.

    15. JL

      It's... So that's been a little bit difficult for us, right? Um, but I think it's a... That's part of just creating the, the, the ecosystem, you know. In, in 10 years, the next startup that comes out of Stockholm hopefully won't have this problem.

    16. HS

      Totally get that. Can I s- Everyone is encouraged to use as many tokens as possible. I'm on the board-

    17. JL

      Mm

    18. HS

      ... of public companies-

    19. JL

      Yeah

    20. HS

      ... and they're like, "Oh, I'm, I'm hearing about, like, Token Maxing and token-"

    21. JL

      Oh, yes. Yeah, yeah, yeah.

    22. HS

      What do you advise a CEO in terms of intelligent usage of AI, and should we just be pushing-

    23. JL

      Mm

    24. HS

      ... tokens as much as fucking possible, or do we just need to pump the-

    25. JL

      Yeah

    26. HS

      ... brakes a little bit?

    27. JL

      Yeah. Um, so a few different things on that. Um, I think, one, having a leaderboard. A lot of people say this. Get, get a leaderboard, um, and, and bring up token usage at performance reviews, uh, and that leads to Token Maxing, which is people just burn tokens just to look good. Um, that's a really stupid way to do anything. Do hack days. Do demos. Um, have people show everyone else how efficient they are and, like, how much better they're doing, and reward them for being, um-Effective and efficient and having more output, not for necessarily using AI, but like AI will be the way there. Um, I think that's one of the points. For enterprises, this is actually where I think Cursor has, um, a reason to live, a reason to exist, which is if your options are Codex and Claude Code and a neutral third party, uh, and you all pay, you know, you pay consumption-based, Co- uh, Claw... Sorry, Cursor can help you optimize your token spend a lot, 'cause they can optimize your usage, right? They can route them to the cheap open source model or help you set limits for whatever models you want to use for what thing.

    28. HS

      Well, can they now post-acquisition by Groq?

    29. JL

      Well, [laughs] we'll have to see if, if they force Groq on everyone.

    30. HS

      I, 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-

  13. 45:44 – 55:13

    Token Maxing: Are Enterprises Using AI Wrong?

    1. HS

      than I'm doing podcasts these days. [laughs]

    2. JL

      [laughs]

    3. HS

      And you're laughing 'cause it's true.

    4. JL

      It's, yeah.

    5. HS

      It's not true. It's not true.

    6. JL

      I'm essentially an investor now. [laughs]

    7. HS

      Stop it. Stop it. Um, my question to you is, do you have to buy companies to get the truly, truly A talent in a lot of cases?

    8. JL

      I don't think so, but it's faster. It's, that's, that's, that's essentially why. If, 'cause if you find a really good person who-- 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. Um, and then you get five in one week, you know, if you have to get two every week. Um, and that's much faster than going to all the big companies or even the startups and trying to convince them to lure, come over. People also want-- Like, if, if you have a small startup of five, eight people, they want to work with each other.

    9. HS

      Do you just shed their code bases then, or is it, like, pure acqui-hires in a lot of cases?

    10. JL

      Uh, make... It, it can be both. Um, if they've worked on adjacent things or things in a similar field or even, you know, unrelated but similar technology, we'll take all their learnings, and we might rebuild it into Legora. Um, I think that's what happens in most cases. But they become, you know, fully embedded into the team. It's, they're all Legora-ians working on the Legora code base, and then they might bring some learnings.

    11. HS

      Is integration hard?

    12. JL

      No, it's n- it's surprisingly easy if you hire people with low ego. [laughs] That's the thing. If you, if you get five great engineers that don't care about their titles or where they sit in the org chart, that just wanna solve problems, it's surprisingly easy to integrate.

    13. HS

      When you've got engineering hires wrong, what did you not see that you wish you had seen?

    14. JL

      So typically, when this goes wrong, it's actually because of my-- Gonna be a little bit introspective here. It's, it's probably because of, um, my own, uh, because I, I don't have, you know, I've not run an engineering team this big before, and so I start doubting, uh, I sort of, I, I'm not confident enough in saying, "This person, uh, who's more senior than me or has seen more than me is wrong." And so it's happened once or twice when there's a very, very senior person. Um, and, and we talk, and they talk about all this sort of org building and org design and, like, how they think about all this stuff, um, and I sense that something's wrong, and I kinda know that all the time, but I, in the end, I end up convincing myself that, no, they probably know more than me, or, like, they've, they've figured it out or whatever. Um, and then if, you know, two weeks in, four weeks in, six weeks in, you start to figure out they, they didn't.

    15. HS

      How fast do you know if you've made a miss hire?

    16. JL

      A month. Then you know. And then you give them really strong feedback. I give really strong feedback after two weeks.

    17. HS

      What does really strong feedback mean, Jake?

    18. JL

      Really strong means, uh, you're not gonna stay if you don't change this, and str- and, and feedback is feedback

    19. HS

      Has anyone ever recovered from a you're not gonna stay if you don't change this?

    20. JL

      No. But they need to get the chance. And if they do, they stay

    21. HS

      What is the hardest role to hire for today?

    22. JL

      I think senior management is extremely difficult to hire for

    23. HS

      Senior management. A horizontal senior management?

    24. JL

      No. Uh, yeah, well, like engineering directors-

    25. HS

      Ah, so-

    26. JL

      ... engineering managers

    27. HS

      ... within product

    28. JL

      And within-- yeah, within product and engineering. Yeah. Um, maybe that's always been difficult, but I think it's... 'cause we only have really technical people also being managers, and so anyone who's seen scale typically also is not, no longer technical

    29. HS

      Do we still have managers? And what I mean by that is like [laughs] you know, one of my dear friends, Jason Lumpkin from Sash, he's like-

    30. JL

      Yeah

  14. 55:13 – 57:31

    The Crazy Prediction: Lawyers Will Work One Level Above the Contract

    1. JL

      If I had to get crazy, I think there's lots of, um, sort of, um, analogies to coding, I think, in, in law. It's very text-based. Um, sort of the, the A- agent AI features are, are similar. If I believe that coding, we're gonna 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. They will work a level above, which is maybe like, "What's our negotiation stance? Like, what, what risks are we okay, which ones are we not okay taking?" Um, and not sit and type into Word. I'm not sure if this is true, but this is my hunch that it's going this direction, and that's the... If it has to be crazy, that's-

    2. HS

      Seeing-

    3. JL

      Lawyers will, will hate me for saying this

    4. HS

      ... seeing inside, like, lawyers' processes now, I'm just like, "Wow, you seem to have done, like, 100 NDAs. Why are we writing it fresh?" [laughs]

    5. JL

      [laughs] Yeah.

    6. HS

      This feels like a solved problem.

    7. JL

      Yeah. Yeah.

    8. HS

      I'm gonna get in so much trouble for this show.

    9. JL

      Yeah, me too. [laughs]

    10. HS

      Fucking hell. Um, what's the biggest advice to a founder competing in a business/industry where there is an 800-pound gorilla?

    11. JL

      Honestly, just work harder than the 800-pound gorilla. I think, yeah, people underestimate this. Like, the 800-pound gorilla, no one in the 800-pound gorilla is extremely excited to be there.

    12. HS

      [laughs]

    13. JL

      You know? I think, I think that it'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. Like, you know, maybe, maybe she tries really hard, but I don't, I don't think, uh... If you're a small, lean team, you work really hard, you can do really remarkable things.

    14. HS

      You ready for a bet?

    15. JL

      Yes.

    16. HS

      What are we gonna end the year at revenue-wise?

    17. JL

      [sighs] [laughs] It's gonna be, it's gonna be above 250.

    18. HS

      I'm gonna go 272.

    19. JL

      272?

    20. HS

      Yeah.

    21. JL

      All right. I think it's gonna be above that too.

    22. HS

      Ooh.

    23. JL

      I don't, yeah. [laughs] But I don't wanna-

    24. HS

      I don't wanna get in trouble.

    25. JL

      I don't wanna, let's not-

    26. HS

      I'm just the CTO. I don't do-

    27. JL

      I don't know numbers. [laughs]

    28. HS

      I didn't mean it. Max and Patrick, I don't know.

    29. JL

      Uh, David's gonna call me really mad soon. [laughs]

    30. HS

      Dude, this has been such a pleasure. I've loved having you on. You've been fantastic.

Episode duration: 57:42

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