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Building an AI-Native Software Company With Legora CEO Max Junestrand | Ep. 44

At 23, with no legal background, Max Junestrand co-founded Legora to transform how lawyers work. Legora recently (March 2026) raised $550 million at a $5.55 billion valuation in a Series D funding round to accelerate its expansion across the United States. Over the past year, Legora has grown from 40 to 400 team members across the globe and the platform supports tens of thousands of lawyers each day across 800 customers in more than 50 markets. Max shares the story of building Legora, what it really means to build AI-native software from day one, why legal work is uniquely suited for AI, and how a small team from Stockholm convinced some of the world’s largest law firms to change how they work. Timestamps: (0:00) Intro (0:31) Legora's origin story (9:05) Building an AI-native company (18:16) No sacred cows, the models will be amazing (27:36) Winning pilots and global expansion (36:43) Starting in Europe (47:15) Stockholm culture and "blodsmak" Links: https://x.com/MaxJunestrand https://x.com/chetanp https://x.com/jaltma https://legora.com/ https://uncappedpod.com/ friends@uncappedpod.com

Max JunestrandguestJack Altmanhost
Mar 12, 202649mWatch on YouTube ↗

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  1. 0:000:31

    Intro

    1. MJ

      I remember doing this interview in Swedish. There's a saying, like, blodsmak, and you know, like, you taste the... like, you taste the blood because you're- you worked so hard.

    2. JA

      Yeah.

    3. MJ

      She publishes the article in English.

    4. JA

      [laughs]

    5. MJ

      "At Legora, we wake up with a metallic taste of blood in our mouths."

    6. JA

      [laughs]

    7. MJ

      And people in the company go, "Holy shit. Is Max a vampire, or does he just floss badly?" Like-

    8. JA

      [laughs]

    9. MJ

      ... what's going on?

    10. JA

      It's not, like, a culture that I think would quite work in San Francisco. Like, I don't know-

    11. MJ

      No

    12. JA

      ... if that's something that you can do.

    13. MJ

      Well, when we open our San Francisco office, they're gonna taste the blood.

    14. JA

      [laughs]

    15. MJ

      Yeah. They're gonna taste the blood.

    16. JA

      I love it.

  2. 0:319:05

    Legora's origin story

    1. JA

      Well, this is gonna be a cool new format. I'm here with my new partner, Chetan and Max. And, uh, Max, you're the founder, CEO of Legora, which is an amazing legal tech company that Chetan sits on the board of. And so I just feel really lucky to be doing this with both of you. So you guys, thank you for, thank you for making this happen.

    2. MJ

      Thank you so much, Jack. It's great to be here.

    3. JA

      Okay. So I wanna start with the topic of competition. And Chetan, when you invested in the company, there were already competitors out there. This was, I think... It was only two year- It's crazy because Legora's like-

    4. MJ

      Yeah. Two years ago

    5. JA

      ... it's a big company already.

    6. MJ

      Yeah.

    7. JA

      But it's-

    8. MJ

      Almost 400, 400 people

    9. JA

      ... you know, but this, this, the seed was two years ago. And at the time of the seed, it was an early market, but there were competitors out there. And so I actually wanna start with you, Chetan. Like, what was in your head at the moment you invested? Were you thinking about the landscape around? Like, were you just, "Max is so special that I don't care"? Like, what was going through your head when you did that?

    10. SP

      The first meeting that we had was with Max, was with me, Peter, and Max actually in the other room. And interestingly, I had invested in two other legal software companies pre-AI.

    11. JA

      Oh, wow.

    12. SP

      And so there was a shape of the legal market that I intuitively understood because I participated in the market, and so I sort of understood the different kinds of lawyers. Who buys software? Do in-house lawyers buy software? Do law firms buy so- How they... Sort of there was a intuitive understanding that I had. And there's sort of, like, two things that happen when you've, like, sold into an industry before. Either you end up hating it-

    13. JA

      [laughs]

    14. SP

      ... or, or you have some strong bias against it.

    15. JA

      Totally.

    16. SP

      So there was always this idea that there's opportunity for AI in the legal market, and you know, there was a player in the market that had already raised an billion-dollar valuation. And when Max came in to chat with me and Peter, the thing that immediately jumped out was the clarity of thought that Max had on why the general foundation models had a lot of room to grow-

    17. JA

      Mm

    18. SP

      ... in intelligence, and how that was gonna be a huge boon for the legal profession over the next couple years. And so he had this, like, very strong viewpoint that there was something about legal data that the general models were gonna serve-

    19. JA

      Actually-

    20. SP

      ... in a very unique way

    21. JA

      ... Max, since you're here-

    22. MJ

      Yeah

    23. JA

      ... can you, like, explain, like, what was, what, what was that?

    24. MJ

      Well, so I think it's, it's worth to go back to 2023 and 2024 when I think part of the paradigm was you should train your own models. And, like, the general models aren't great, and fine-tuning is gonna be really important. For two reasons we were like, "Fuck that," right?

    25. JA

      [laughs]

    26. MJ

      Um, one, fine-tuning doesn't really seem to work, at least on the scale that we were operating, right? To train the new generational model you have to put-

    27. JA

      Mm-hmm

    28. MJ

      ... billions of dollars into it. And secondly, there was so much application that you had to build on top of the models to make them useful in your environment. And back then, I mean, just solving, like, basic data compliance, privacy, and sort of great file uploads, and, like, great parsing and great chunking and all of these things, that was where the value was.

    29. SP

      And there was another part of your experience which was that you were actually embedded in a law firm.

    30. MJ

      Yes.

  3. 9:0518:16

    Building an AI-native company

    1. JA

      What have you found i- like to the point of you have to be better than the models, if you had to break down like as a vertical AI application, what have been the things that have allowed you to just be so much better than the models that it's worth, you know, the incremental-

    2. MJ

      Investment. Yeah

    3. JA

      ... investment?

    4. MJ

      So I think in the beginning, there was a lot of just foundational problems with the models. Like you had to guardrail them very hard to make them useful. You had to build citations, you had to build good RAG systems, you had to overcome context window problems, and there was a lot of rate limits issues, so you had to like juggle different models for different types of tasks. There was just so many incremental basic things to solve. I think as time has progressed, um, our product has moved further away from what the foundation models are and much more into this enterprise-wide platform where, you know, we're gonna transact billions of dollars of legal work-

    5. JA

      Mm-hmm

    6. MJ

      ... on the platform.

    7. JA

      Mm-hmm.

    8. MJ

      And we've moved from building a lot of the agent work ourselves, and we sort of let the models rip a little bit more, like OpenClau or Claude Bot or whatever it's called these days, where like with Opus 4.5 and Opus 4.6, uh, there was an extraordinary difference in, in level of intelligence and like instruction following capability. And so I see our job as let's provide the model the right environment and the right tools and skills to leverage, and then let's build a UI and a, and an interface with the rest of the business so that they can all leverage it, uh, comfortably and with a lot of trust. I do think that, you know, the model capability is improving so quickly makes us run faster, 'cause we have to be three standard deviations ahead of any general capability.

    9. JA

      Yeah.

    10. MJ

      And that's like a very good motivator.

    11. SP

      As an-- as somebody that's invested in a lot of software companies, like one of the unique things about an AI software company is that it's tactically built differently than a traditional software company. And I think it's becoming more known now, but when you guys first started, and you guys built up this org, the way you designed the org made a lot of sense for the product you were building and what you just described, which was like we need to deeply understand model capabilities, and then we need to bring that to our customers in a way that's deeply differentiated. Which as you explained to me meant we need to invest heavily in understanding the models, which then would lead to understanding what to build. But as models got better, your features may not matter in six months.

    12. MJ

      Yes.

    13. SP

      And so talk about how that led to an organization that was heavily technical, heavily engineering and researcher-led, and for as, a company as big as you ha- you are, you have very few product people. The number of product people you have essentially rounds to zero. You have like leaders, you have a couple of leaders, but that's it.

    14. MJ

      I mean, the founding team, we're, we're three engineers, and so, you know, the, the most natural hires were let's grab all the smart engineers that we know from college, and let's add them into the org. And in the beginning, you know-We had to build our own agent framework because like LangChain and these things that we initially built on, like couldn't get customized to the level that we needed back in 2024. As we understood more about the model capabilities, but also of the problems we wanted to solve, like let's take due diligence as an example. Um, it's really hard to solve a due diligence task in a chat-based format because you need to review hundreds of documents. And hundreds of documents are never going to fit into the context window of a single model call, at least not back then and, you know, probably not now either. So we built this new product that we called Tabular Review, big matrix, where you would throw in, you know, tens of thousands of documents, and you'd throw in all the prompts, and it started running all of them in parallel. And what we basically did was we just said, "Okay, three engineers, you're now on Tabular Review. This is your own company. Run." Over 10% of the EPD org at Legora are ex YC founders. So our head of engineering, Jake, who joined, he was a solo founder in YC. Our VP product, Adrian, was also a legal tech founder in YC and happened to be a both GC and a lawyer. And so as we've progressed, engineering and product has sort of stayed at the core of, of who we are and what we do, and I also think that everything else is sort of an expression of that. Like we can only market what we actually build. We can only sell what we actually build. And product lead compounds.

    15. SP

      Mm.

    16. MJ

      I think as, as you put it in the beginning, we did not show up first. Like Legora was not the first product that many legal teams looked at because there were e-earlier entrants. So we knew that we had to show up and be best, and if you wanna be best, well, then you need to invest in product. You need to invest in engineering, and I think you need to build that culture of like reliability first. We actually had a time period in the company for, for six months where we didn't sell basically because we weren't ready to like hit the gas on onboarding 1,000 lawyers a day and knowing that the product was gonna keep up with that. So we took the early hits of like investing in that.

    17. SP

      Talk more about that period, specifically, you know, the seed round you did with us was in March of 2024. The product went to GA October 1st 2024.

    18. MJ

      Yeah.

    19. SP

      And you called me early September 2024 and said, "You need to come to Sweden 'cause all of us need to sit in a room and just talk about where we are and what we need to do to get this thing out in a month." And, you know, we came and we sat, the whole-- literally the whole company, which wasn't that big back then. It was like 10 people.

    20. MJ

      It was like 20 people.

    21. SP

      Yeah. And so it was like the whole company, the founders, chicken wings and beer.

    22. MJ

      Yeah.

    23. SP

      And we [chuckles] and peanuts actually. Those were the three things served.

    24. MJ

      [chuckles]

    25. SP

      And there was like a very open dialogue of like, how do we get this thing out in 30 days? Because at that point, 'cause you were essentially, you know, weren't facing the market test, you were building. There were 10,000 things you could build, and that the sort of like outcome of that discussion was that we're only gonna focus on three use cases.

    26. MJ

      Yeah. Yeah. That's right.

    27. SP

      So talk about like well, one, you know, you calling me to tell me [chuckles] to come to Sweden to have that discussion.

    28. MJ

      And you actually showing up. [laughs]

    29. SP

      Yeah, I did show up. Reflecting on it, that was one of the most important things that, that you did in the company and the founders did in the company was at that moment say, "We have 30 days to go. We're just-

    30. MJ

      Yeah

  4. 18:1627:36

    No sacred cows, the models will be amazing

    1. MJ

      at all.

    2. JA

      Chetan made a cool point to me recently, which is that, um, because you ha-- we were talking about how, you know, companies that are pre-AI and companies that are just fully AI-native just have to be built differently in various ways. And the fact that you didn't build a pre-AI company, I think gives you sort of like, you know, this unshackled mind to like you're not even trying to think about some past alternative. You're just like, "Given what's in front of me, what should a company look like?" And you know, you talked about how like having YC founders inside the company has been helpful, and I'm sure there's like a lot there. But I'm curious about like what are like the main tenants that you've observed? You know, 'cause now you've probably hired a lot of people who did, you know, work and build companies pre-AI. What do you think are like the main tenants, ideas, cultural concepts that have been important to you just to like make it work in like a fully AI-native world?

    3. MJ

      Yeah. So I think this idea that Chetan brought up around, um, like you have to be willing to like kill the stuff that you've done in the past is very important. 'Cause I think in, in more traditional software, you had to build the foundations, and then you build the stuff on top of it, and you sort of kept building the stack. And in that world, it was also very good to have like a technical architecture where one feature would rely on the same microservices as like other features. But the problem is in AI, like maybe that feature now needs to scale really, really quickly, and the cost of writing software is so low that it's basically better to build your own stack for like each thing. And now that we hire, you know, finance professionals or even like lawyers internally to Legora, or we just hired our first like tax person-

    4. JA

      Mm-hmm

    5. MJ

      ... I think they come with a set of ideas of like, "Oh, this is how I used to do it in my old company." And everybody's forced to relearn, I think, and also question what their value is on top of the general model capabilities in a way, which this is like very painful.

    6. JA

      Totally. Brett, Brett Taylor talked about this on this podcast too. Basically, that like people are gonna build something, and six months later we might just kill that thing, and everybody needs to be comfortable with that-

    7. MJ

      Yep

    8. JA

      ... which I think historically would be a lot of painful internal conversations. Like do you have to change? Is that like a different culture for people too?

    9. MJ

      I think it's a different culture completely. I mean, I think the culture is you don't maximize for your function, like you maximize for the company always. And I'm very upfront with every exec who joins Legora that in a way, like you're joining with an expiration date, and you have to continuously prove that you like scale out of that in a way. Because the company is scaling so exponentially, I don't know if it was Mark Zuckerberg or somebody talked about like let's hire people with high y slopes and not like high y intercepts. I think about that a lot, mostly because I've had to do that, right? Like I did not join or start Legora with a lot of experience, but I've proven that at every new point in time I've scaled with the business, and so other people in Legora needs to do the same, and I think that goes for every function. And, you know, I think a, an engineering team that's shipping the amount that we do previously had to be like five hundred people, and now we can get away with being fifty. And I think there's even a question of like, do we need to be more than a hundred engineers, or is the bottleneck here really knowing what to build and building it in the right way, and designing an experience that works for, you know, hundreds of thousands of people that we now have on the platform? I think the paradigm is like shifting all the time. What's nice about our work is that engineering is sort of a, a roadmap of what's going to happen in other industries too. Like I think the general models have come the furthest in coding, but also those organizations are very quick to adopt and shift. And so like engineering orgs are today looking slightly different, and I think we can expect the same in, in, you know, legal organizations.

    10. SP

      Two things you brought up that you should-- it'd be great if you could dive into. One is Legora doesn't really have a long-term roadmap. Like you guys-

    11. MJ

      Oh, no. [laughs]

    12. SP

      ... react and build today.

    13. MJ

      Yes.

    14. SP

      And you know, when you first got started, you had this like nearly weekly cadence where that's how long you would roadmap to. And these days it feels like you almost roadmap on a daily cadence. And so like things change tomorrow, like you wake up, but it's like, we have to do something different. Talk about that lack of roadmap, and then also the other thing that you've invested heavily in is just understanding model capability and the sort of proprietary eval infrastructure you've built, where we've had these conversations with the foundation model companies of how you're able to identify latent model capabilities that they themselves are not aware of.

    15. MJ

      I mean, on roadmap, like way back, every new model just like unlocked new things, right? And when we got early access to GPT, like 4.5, and you just realize that, holy shit, like now it can finally draft like an end-to-end thing, and we don't need like all these harnesses and like things around it. That's amazing. Like let's unleash it in a way that that works. Now-

    16. SP

      By the way, y-to do that, you need sort of like a low ego organization-

    17. MJ

      Totally.

    18. JA

      Oh, yeah

    19. SP

      ... 'cause you build all this E-IP and all this software-

    20. MJ

      And it just tells it.

    21. JA

      Yeah

    22. SP

      ... and you're like, "Okay, now the model can do it."

    23. JA

      Yeah.

    24. SP

      Delete it all.

    25. JA

      You, you worked really hard for six months.

    26. MJ

      Yeah.

    27. JA

      We're deleting everything.

    28. SP

      Yeah.

    29. MJ

      Yeah.

    30. SP

      It's incredible.

  5. 27:3636:43

    Winning pilots and global expansion

    1. MJ

      it's... Yeah.

    2. JA

      This is a question I think for both of you. As I'm listening to you talk, I'm sort of like, you know, I can sort of see the, you know, the hill climb that you're on where you've like attacked, you know, one part of it and the next one's coming, and the next one's coming. And, you know, one of the things I'm thinking about is for, let's say, a new startup in legal, what would the right strategy be for them? Like how do you possibly get into the mix fast enough for all of these things? And then-

    3. MJ

      Exit to Legora.

    4. JA

      Exit to sell to Legora, that's a good one. How urgent is it to grow really big, really fast for Legora, given all of the dynamics around? Chetan, I'm curious like how you think about this. Like is it the same urgency as always, or do any of these dynamics mean that like getting to real scale is more urgent here than other places?

    5. SP

      We can go back to sort of launch day, October 2024. So when, when they launched, you know, roughly the ARR of the business was rounded to a million dollars. If you just go back into that moment, you know, there was this exercise of should we make a budget? And, you know, what, what we all decided around the table was there was no reason to make a budget because we don't know anything about the market. We don't know if people even like our product. We had instincts, but like we just needed to go literally as fast as we could to get the product as in many hands as we could, because ultimately the whole theory of the company didn't work until we got product feedback. And so that was literally the aim. The aim was like, get this out as quickly as possible into as many hands as possible. And I think one of the things that Max did, again, this is like it's cliché to say it's first principles thinking, but it is 'cause it's like the team was unbiased by how to build a software company. And so one of the things that you learned in SaaS was the way you do pilots is like you would go in, do like a time trial pilot where you would like give them access to the application, and the minute the a- the trial was done, you would turn it off, and then, then they would have to make a purchasing decision.

    6. JA

      Mm-hmm.

    7. SP

      A big thing that happened with Legora is they would go put Legora into your organization, and whatever you put into Legora, they would like leave behind even if you didn't want it.

    8. JA

      Mm.

    9. SP

      And so there was this idea that like, hey, you adopted AI, you did stuff with AI, you built some practices, but you're not like, whatever skills you built or whatever IP you built, it's kinda yours. And like we, we can leave that behind. It's not a big deal. It's like it's your skills, it's your things that you've learned. And then Max went around and, and just gave people like 30-day pilot, 60-day pilot, whatever they wanted, 90-day pilots.

    10. MJ

      Yeah, and they would run these competitive pilots, right? So they would say, "Okay, there's a couple of companies on the market. We're gonna wanna A/B test all of them," because it's really hard to pick just, you know, based on the feature set on your website. And in those pilots, I think we did an extraordinarily good job of delivering value. And so when the sort of 30 days were up, like if we shut it down, it would be a riot.

    11. JA

      Mm.

    12. MJ

      Right? Like people would roar, and they'd be like, "We've never seen software adoption like this in a legal organization, um, we need this and we, you know, we need it now." And in those pilots, we would demonstrate much better than any other company, um, the value that the product and the service around the product could bring. So we hired all these lawyers, um, who are now called legal engineersIt's a great term, I think. Forward deployed legal engineers.

    13. JA

      I was just gonna say, what about FDLE?

    14. MJ

      FDLE.

    15. JA

      Yeah.

    16. MJ

      That's right, FDLE. And they're amazing. Like, they're the most tech-savvy lawyers in different organizations who don't wanna make partner, 'cause, like, you know, that's one type of life.

    17. JA

      Yeah.

    18. MJ

      And they wanna work in a tech company. And now they get to work with their practice that they're amazing at and technology, and then they get to work with the best legal organizations in, in the world and, like, driving that change.

    19. JA

      And I would think once you're embedded in these organizations, uh, it's gotta be sticky.

    20. MJ

      I think Legora is very sticky. We've ripped out our competition at many, uh, organizations-

    21. JA

      What creates stick-

    22. MJ

      ... at this point

    23. JA

      ... what creates stickiness?

    24. MJ

      So the stickiness is the, uh, use cases and the cadence and, you know, if you've invested time in building up a workflow that, like, works for you, why would you wanna switch?

    25. JA

      So is it that? Is it-

    26. MJ

      Is it... It's usage stickiness.

    27. JA

      It's not data.

    28. MJ

      Not-- No, not yet, and not, not any real technical implementation, which is great, because, uh, our competition has been deployed in a lot of places that sees no real usage or very simple use cases, which means that we can go there, show them, and display clearly in a pilot that we deliver much, much better, and then we can easily swap it.

    29. JA

      Mm.

    30. MJ

      So we actually have a dedicated, like, migration team moving deployments over to Legora.

  6. 36:4347:15

    Starting in Europe

    1. SP

      So one thing about the market structure of legal that we knew about here at Benchmark ahead of investing is that legal has this unique market feature that it's a services industry. And in services industries, technology adoption is slow at first and then rapid later. So if you just look at any marketplace idea in a services area, it's like the marketplacesAre usually like supply constrained and then the minute supply unlocks, all of the supply comes online into the market-

    2. JA

      Mm-hmm

    3. SP

      ... and then you become demand constrained. And so if you study marketplaces, and especially marketplaces around services, this is something that you just like fundamentally learn as like one of the rules of marketplaces. And so in legal, the market structure is such that like the initial adoption will be very slow and hard, but once it unlocks it like really unlocks. There's some kind of like exponential viral coefficient that happens there. That's one part about the legal industry that's really interesting, and then how it overlays into software in legal is that if you look at the most successful legal software companies, they were all started in Europe, pre-AI too-

    4. JA

      Huh

    5. SP

      ... by the way. I had a hypothesis that part of the reason why you get that way is that you're used to selling the multi-geography and multi-rule systems from day zero. So for example, Legora sold to a Swedish firm-

    6. JA

      Yeah, that makes sense

    7. SP

      ... and a Spanish firm and a Finnish firm, and so yes, there are like laws at the European Union level-

    8. JA

      Yeah, but like from the beginning-

    9. SP

      Yeah

    10. JA

      ... you're like, "This needs to work for many people."

    11. SP

      That's right. And if you start in the US, what you end up designing is that there's the federal-

    12. JA

      Mm-hmm

    13. SP

      ... legal system, there's a state legal system, and then there's regional, but it's not as bifurcated as like literally different countries.

    14. JA

      And different languages.

    15. SP

      And different languages. And so you build all this stuff on day zero that you don't if you start in San Francisco. And one of the interesting things that Max showed us in the prototype in the first meeting is he had multi-language support already built and he had like multi-legal framework support already built.

    16. JA

      I remember. I demoed Sweden and Spain.

    17. SP

      That's right, and that was like remarkably impressive because it was, it was a company with five people thinking global scale.

    18. JA

      Yeah.

    19. SP

      Because they were forced to-

    20. JA

      Yeah

    21. SP

      ... 'cause they couldn't serve the Stockholm legal market. [laughs]

    22. JA

      Totally.

    23. SP

      Those two things just meant from they launched the product, they got a bunch of people to sign, then immediately it was like, "Let's go get the two big firms in every geography-

    24. JA

      Yeah

    25. SP

      ... 'cause we have to."

    26. JA

      And it was global from day one.

    27. MJ

      And now, I mean, Legora I think has become a, a hub in, like a technology hub in Europe. Like, people from Germany, from the Netherlands, from Spain, from Italy, they're all moving to Stockholm, even in the winter to come and work with us.

    28. SP

      So talk about, talk about the culture part of it, which I think stands out a lot.

    29. MJ

      Yeah.

    30. SP

      And so it's hard to describe to people what it's like to visit the Legora office.

  7. 47:1549:58

    Stockholm culture and "blodsmak"

    1. JA

      love it. All right, my last question is you just raised a big round.

    2. MJ

      Yeah.

    3. JA

      Which is awesome. Congrats. What does this mean for the future? What's coming?

    4. MJ

      Well, maybe first off, just to give you a bit of insight into the round. Like, every round at Legora since Chetan has been a preempted round. I don't think I've ever actually gone out to, like, fundraise since, since-

    5. JA

      [laughs]

    6. MJ

      ... you did a round. Yeah, it's been, it's been very pleasant.

    7. JA

      It's good.

    8. MJ

      It's been very pleasant. We actually also have a history of taking the, uh, like, lowest term sheets.

    9. JA

      Yeah.

    10. MJ

      Um, I remember taking-- Like, we were actually-- So this is funny. Like, we were negotiating the number of shares that Chetan was gonna buy on Excel in front of us, and he goes, "I've never, ever bought a company where I didn't get 20%." And I go, "Well, I'm never gonna dilute-

    11. JA

      [laughs]

    12. MJ

      ... more than 17.5." And we sort of look at each other and go, "Well, I guess we're in a, in a bit of a stalemate here."

    13. JA

      [laughs]

    14. MJ

      It was like the immovable object [laughs] meets, meets the force. And so we, like, just put it on Excel, and we write down the exact number of shares, and we start going decimal by decimal-

    15. JA

      [laughs] Wow

    16. MJ

      ... until we're both-

    17. JA

      That's, that's such le- that is so legal coded.

    18. MJ

      Yeah.

    19. JA

      Like, just the nerdy Excel.

    20. MJ

      It's-- it was wild.

    21. JA

      It's perfect.

    22. MJ

      So you end up investing, like, 9.521.

    23. JA

      [laughs] It's true.

    24. MJ

      And we're both equally unhappy or happy.

    25. JA

      It's great.

    26. MJ

      I think we were both happy.

    27. JA

      Yeah.

    28. MJ

      It's a beautiful story.

    29. JA

      Of course.

    30. MJ

      We were both happy. But the Series D has been really great because it's the first time I've, I've done it, uh, together with, with, uh, someone else. So David, our CFO, who just joined from Vanta, he's an absolute monster. It was funny. We had our, our company-wide, uh, kickoff, and you get to, like, pick the song you wanna walk out to. And he goes, "Max, I want Monster by Kanye West."

Episode duration: 49:58

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