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

Max Junestrand is the Co-Founder and CEO @ Legora, the legal AI company that has scaled to 750 of the world's leading law firms as customers and over 300 employees in just 2 years. They have raised over $200M from some of the best in the business including Benchmark, General Catalyst, Redpoint and ICONIQ. AGENDA: 04:16 Why Does Everyone Think Harvey When They Hear Legal AI? 07:35 Why OpenAI is Toast? Switching to Anthropic! 11:47 24 Months: Which Foundation Models Will Win? 23:53 Lessons Scaling from Europe into the US 28:53 Do Americans Work As Hard As They Say? 32:20 Why Seat Models Are Not Dead in SaaS? 36:17 How to Use Competition To Drive a Fire in Your Team? 40:59 Is Legal AI a Winner-Take-All Market? How Does It End? 47:18 The Future of Law Firms: Do Juniors Get Fired? 53:19 How We Raised $200M and 3 Rounds with No Deck 57:21 Quickfire Round: Best Advice, Closest Mentor, Biggest Mindset Shift

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  It doesn't really matter who was first. It matters who's best. It's totally a winner takes all. Number one will grab ninety percent and number two to number ten will share the remaining ten percent. Got to run like hell. You got to win. There's no number two. There is only being number one. There's only winning. Everything else is losing. In a single day in twenty twenty five in December, we added seven million of ARR, one day in twenty four hours. And that was more than what we did in twenty twenty three and twenty twenty four combined.

• 0:32Harry Stebbings?

  This is Twenty VC with me, Harry Stebbings, and what a show we have in store for you today. Last week, we had Harvey on the show. That broke pretty much all records. This week, we have their biggest competitor, Lagora, on the show. And joining me is Max Dunestrand, co-founder and CEO of Lagora, the legal AI company that has seven hundred and fifty of the world's biggest law firms as customers and over three hundred employees in just two years. They've raised over two hundred million dollars from some of the best, including Benchmark, General Catalyst, Redpoint, and Iconic, to name a few. But before we dive into the show today, over eighty percent of Fortune one hundred companies are running their businesses with Airtable. Airtable combines AI with the scale of an award-winning, infinitely flexible no-code system,

• 1:16Harry Stebbings?

  a platform where you can see all of your data in one place and use it to make really big-picture decisions. Think of it like mission control for your company. Airtable goes beyond organization and automating repetitive tasks. It lets you use your data to inform strategy, monitor progress, and take action. Every cell is capable of performing hundreds of AI-powered tasks like web research or localization, and using those results to inform and update hundreds or thousands of other cells and workflows in real time. Unlock the true scale of your workflows at www.aeretable.com/20vc. Airtable, the infrastructure of innovation. And just like Airtable organizes your workflow data,

• 2:01Harry Stebbings?

  Metaview organizes your conversation insights. This episode is brought to you by Metaview. Who says hiring has to be fair? Every founder, VC, and ex- Sec I speak with knows this: your ability to hire is the biggest constraint on your company's growth. But recruiting is slow, it's subjective and only getting more competitive. And that's why teams like Eleven Labs, Brex, Replit, Deal and 5,000 other organisations use Metaview, the AI company giving high-performance teams a real unfair advantage in hiring. Metaview's built a suite of AI agents that behave like recruiting coworkers. They proactively find candidates, they take interview notes automatically and they help you surface the best candidates in process.

• 2:43Harry Stebbings?

  For the first time, AI handles the recruiting toil and gives you a single source of truth. That means hours saved per hire and a team focused on what matters most: winning the right candidates as fast as possible. Don't let your competitors out-hire you. Metaview customers close roles 30% faster. Try Metaview today and get a free month of sourcing at metaview.ai/20vc. After Metaview captures what was said, Turing helps you build with the people who can deliver after it. Frontier Labs keep facing the same limitation. Models perform well on benchmarks but fall short once they enter real coding tasks, real tools and real workflows.

• 3:25Harry Stebbings?

  That disconnect between synthetic evaluation and actual system behaviour is now a core blocker for agentic models. That's why Nvidia, Anthropic, Salesforce, Gemini and other leading labs partner with Turing. Turing is the research accelerator focused on post-training reliability. They build realistic reinforcement learning environments, next-generation data quality systems built from real-world operational traces and coding datasets that stress models under the conditions where failures matter: state changes, workflow branching, brittle tool calls and the coding errors that break RL agents but never appear in benchmark reports. In reality, a model may demonstrate correct reasoning in your evaluation setup,

• 4:10Harry Stebbings?

  yet still select the wrong parameter or mishandle a code update in a realistic interface. Turing makes that failure visible and gives teams the signal. They need to fix it. For labs advancing agentic systems, Turing provides the structure required to understand why these failures occur. To find out how, visit turing.com/20vc. That's turing.com/20vc. You have now arrived at your destination. Dude, we did our last show and I have to admit, I was so surprised, not, this sounds awfully rude, but it's the end of the day, fuck it, by how well it did in specifically this incredible founder

• 4:53Harry Stebbings?

  community, where I got pinged by like 300 or 400 founders, which is more than normal, actually.

• 4:58Speaker 00

  That sounds like a big number.

• 5:00Harry Stebbings?

  Yeah, it's pretty solid and mostly it's just kind of VCs. But thank you so much for agreeing to do a second show with me.

• 5:06Speaker 00

  Always.

• 5:06Harry Stebbings?

  Before I grill the shit out of you, 60 seconds, what does Lagora do just to set the scene for people that don't know?

• 5:12Speaker 00

  Yeah, Lagora is the platform where legal work happens. I think that's a better pitch than the one that I had last time. And what's started to happen more and more is AI is doing more and more parts of legal work. And this has to happen on a centralized platform. And what we started out with was simple assistant-based use cases. But this has grown tremendously and it's solving different types of tasks for different types of lawyers. So if you are a transactional lawyer and as part of a due diligence process, you need to review the data room and then you need to find the red flags in that data. Legora can do it. If you are a litigator and you are preparing a brief and you are drafting that in Word, Legora can help you do it.

• 5:57Speaker 00

  More and more of these tasks are being bundled into the platform. And what we're seeing is that a bigger and bigger part of a lawyer's day is being spent on Legora, which is amazing. That's my favorite data point.

• 6:09Harry Stebbings?

  Is that the number one metric you use in terms of product metric?

• 6:12Speaker 00

  Yes, time spent on the platform and number of messages slash number of queries slash number of actions taken. I think is the best sort of KPI.

• 6:20Harry Stebbings?

  When people think AI law, there's a ton of fucking players around the space and around the verticals, but there's you and there's Harvey. And if we're blunt, Harvey is the first name that comes up. When you think about that, why is that?

• 6:34Speaker 00

  I don't necessarily think that's the case anymore. And the reason I say that is, I just saw this report, I was on Bloomberg a couple of weeks back, and they had a big infographic that said that the most deployed generative AI tool in the top 200 law firms in the UK, outside of Microsoft Copilot, is Legora. Number two was Harvey. We are moving, and the category is moving at such a rapid pace, that it doesn't really matter who was first, it matters who's best. And it matters who the clients actually are coming back to and want to do more work with.

• 7:13Speaker 00

  So what often happens, right, is the firms will throw many vendors into a bake-off because they're in this kind of luxury position. I mean, basically, they're playing VC. They get to bring in all these different vendors, and they say, we're gonna do a bake-off. And in the bake-off, it's up to the vendor to display why you are their partner of choice. And I say partner of choice because I don't think that these law firms or big in-house legal teams are buying just a solution. They are buying an outcome today, but they're also buying like an outcome tomorrow, and they're buying into a vision of what an AI-enabled legal team can look like.

• 7:55Speaker 00

  And so when they look across the board and they see all these different companies, they make qualified bets. More and more and more, seeing those firms make that bet on Legora. I mean, this year alone, actually, I went into our HR system before I came in here. We went from 30 to 300 in 12 months exactly, in headcount. This time last year, we were working with roughly 50 clients. Now we're with 750. And so, you know, a name might be associated with a category. I'm pretty sure Google was not the name that you thought of back when AltaVista. Vista was the biggest web browser, but now it is synonymous to searching on the web.

• 8:36Harry Stebbings?

  I want to unpack a couple of elements. You said about like partnership and that being very central to how they think and how they choose. You know, I had Matt Fitzpatrick, the CEO of Invisible, which is kind of like a McCrory or a Turing competitor. And he said that essentially it is impossible to sell into enterprise without an FDE model. Do you agree with that? And are you seeing that?

• 8:56Speaker 00

  We have a very big team of legal engineers who are ex-practicing lawyers from the top tier best firms. But they're not fully seconded. They're forward deployed in the sense that their main job is to make you successful. An example would be a big firm that just went with Legora Widen case. Widen case now has the challenge of adopting AI across their entire firm. It's a big firm, such an enormous change management undertaking to equip all the lawyers across all the different practice areas, across all the offices and across all the skill levels from associate, senior associate to partner with AI proficiency. And we need to make them successful.

• 9:38Speaker 00

  Because if they are not successful on Legora, a year from now or two years from now, it's going to be a really sad conversation. So we invest a ton of upfront manual labor, time and effort in doing the implementation and activation right. So I do think that's necessary for enterprises where you're changing the way they work. If you just think about a process, right? Like, let's say you're working in, if we're just staying in legal. If you're working with AI contracting, you basically have a contract lifecycle management system. You just send a document somewhere, generate some red lines and then you put it back. That's pretty easy. You don't need a forward deployed engineering or legal engineering model for that. You just deploy the stuff and then you're done. But in our case, I actually like to think of it synonymous to the way that.

• 10:23Speaker 00

  Accountants had to learn Excel or architects having to learn CAD. Right? Like before you would actually go out to the site, you would draw the building and then you would go back to your office. You would do all the math, but now you just get a picture of the site. You throw it up in CAD, you put in the blueprints for the building that you want and the system AI generates it or generates it. And then you look at the math behind it and then you bring taste and you bring the sign. When architects were learning CAD, I think it was an enormous change management. Right? And all the old architects would go, Harry, are you going to use that computer system to do the hard work for you? And you would go, yeah, I'm super savvy and I'm going to get to spend more time doing the design.

• 11:06Speaker 00

  Or have creative ideas about how to solve my clients' architectural problems. Right? And I think that's kind of synonymous to what's happening today.

• 11:15Harry Stebbings?

  You said about kind of the value not being in the first move for advantage and actually value it comes from being second. What did Harvey not do well that you learnt from as specifically as possible?

• 11:25Speaker 00

  Some of the things that we observed were spending a lot of effort on fine tuning models. That always seemed to me, at least back in 2023, like a waste of time. Because the general models were improving at such a fast rate. It felt like we should be building boats and then when the tide rises, all of our products just get better. And frankly, my initial team, we were three people. We were three engineers and so.

• 11:49Harry Stebbings?

  The thesis plays into the team structure.

• 11:51Speaker 00

  Right. And, and we had 50,000 euros in angel funding. And so it wasn't really on the question of let's spend $3 million fine tuning a model. But it happened to be right as well. And we always believed that the majority of the value in our category would come from the application layer.

• 12:07Harry Stebbings?

  So you think what being done to fine tune models does not give you an inherent advantage?

• 12:12Speaker 00

  It didn't do that back in 2023 as a starting strategy. I doubt that that's going to be the difference maker today.

• 12:21Harry Stebbings?

  Do you think models are plateauing in performance today?

• 12:24Speaker 00

  No, I think Opus 4.5 is awesome. It's so good and it continues getting better. I mean, honestly.

• 12:31Harry Stebbings?

  How much better is it?

• 12:32Speaker 00

  Well, it depends on the task. In coding, I mean, I think it's, it's gotten to the point now where. I think you should just coin it AGI and focus on optimizing the cost, pretty much, basically.

• 12:43Harry Stebbings?

  What makes you say that? I'm sorry, I'm naive.

• 12:45Speaker 00

  Because it's understanding of my intent and its ability to execute on my intent, given the tools that it has available, today is so good. Like, you don't need to sit like with GPT three point five and you feel like you're talking to, you know, like a lobotomized system, pretty much. Like, if you go back, it's crazy bad. And this was, you know, two years ago, right? And you would have to give it so many instructions over and over and over again. It felt like managing an employee who wasn't very intelligent. Whereas Opus four point five feels like a VP. You give it, here's the thing I want, go execute, and it just does it. It's amazing.

• 13:23Harry Stebbings?

  Has Anthropic won the Claude Code game? Does anyone on your team use Cursor? The question that I'm asking, I'm in.

• 13:30Speaker 00

  It's a good question. We're in both.

• 13:32Harry Stebbings?

  You are?

• 13:32Speaker 00

  We have both, yeah. I'm actually not sure what the full team split is, but I know that we're using both very much. But we are pretty diehard Anthropic right now at the company, in terms of the models that we deploy in our system. So initially, we were only OpenAI. So twenty twenty three, most of twenty twenty four, only OpenAI. And now we're majority using Anthropic.

• 13:54Harry Stebbings?

  What changed, just four point five?

• 13:56Speaker 00

  No, not four point five. This was prior to that. I think it was maybe Sonnet three or three point five that we made the switch. What also happened was you had to start prompting the models quite differently. And then there's a question of like, where do we actually want to put our effort? Just to pick a good, a good model and double down on it and build all the application around it. Because I feel like our job, frankly, if you think about the pyramid of value is, you sort of have the underlying models and the, and the frameworks. Then Legora's responsibility is to build the legal interpretation of those models. So how do we make them the most useful in a legal setting? And a lot of that comes from the models, but eighty percent comes from building normal software, right? Like enterprise-grade software around the models.

• 14:41Speaker 00

  So all the scaffolding, all the ways that the users can actually interact with the system. And then at the very, very top. That pyramid, we need to enable our partners, our clients to do differentiated things. So our clients and the law firms and the legal teams we work with are very ambitious. Their vibe coding tools internally, they are developing MCP servers and they they've understood that if you compete as a law firm, you used to compete on expertise, on marketing, on your ability to recruit, on, you know, your hourly rates, but increasingly you're competing on tech. Like tech is the main lever for our clients to differentiate from their competition.

• 15:24Speaker 00

  And so they will use a platform like Legora to get everybody up to, you know, spend so much time in the US now, second base. And then they will, you know, develop things internally to try and get a little bit of a head start against some of their peers.

• 15:41Harry Stebbings?

  Unpacking so many things, just doing it kind of chronologically there. How promiscuous do you think you'll be with model usage over time? You mentioned you're pretty much exclusively Anthropic now. When you look in the next twelve to thirty six months, will you switch between them as they improve in model efficiency? Or do you think there'll be a continuing loyalty towards Anthropic?

• 16:00Speaker 00

  We will be very promiscuous and that's a clip.

• 16:03Harry Stebbings?

  That's a real clip. That's the intro right there.

• 16:07Speaker 00

  Right.

• 16:08Harry Stebbings?

  But you think you will?

• 16:09Speaker 00

  Well, I think it's our responsibility to be that because our clients have entrusted us to be their AI partner and to deliver them the outcomes that they need based on everything that you can do with AI. And we need to deliver them the best possible thing at the best possible price using all the tools available to us. And so if Gemini is better, we will switch immediately. Or if OpenAI is better, we will switch immediately. Or if a new model comes out that's better, we will switch immediately. You know, proven that the evals is better. But then in specific workflows, you could also let the users pick. So let's say they have a very deterministic thing that they want to run and they always want to run it on this specific model to not break the system and you could also allow that.

• 16:54Harry Stebbings?

  In twenty four months, rank the model landscape for me.

• 16:58Speaker 00

  I'll bet based on what I've seen in the last sort of three, six months. For our type of work, it will either be Claude or Gemini. That is the top model. It will be dependent on if context window is a very important factor or not. So far it is not because we've built so much architecture around handling lack of context window that we still prefer the Claude models or the Anthropic models. And it seems to me like OpenAI is going down the, you know, let users fine tune models like that type of journey a bit more. Which so far, I don't have a lot of reason to believe in.

• 17:35Harry Stebbings?

  Okay, so we're going for Anthropic slash Gemini and then OpenAI.

• 17:39Speaker 00

  I think so.

• 17:39Harry Stebbings?

  And we're not going to throw Grok in there at all?

• 17:41Speaker 00

  No, we're not going to throw Grok in there at all.

• 17:43Harry Stebbings?

  He said it, don't kill me. It was not me.

• 17:46Speaker 00

  We, I also think there's a difference between solving enterprise needs and solving B to C needs. And to me, there's this perceived split, at least from my vantage point, which is that Anthropic is going more enterprise and OpenAI is going more B to C.

• 18:02Harry Stebbings?

  A hundred percent.

• 18:03Speaker 00

  Yeah, and we're an enterprise class type of system. Thus, we should benefit more from their models.

• 18:09Harry Stebbings?

  Yeah, Jason Lamkin, a dear friend of mine, and he said, you know, the show's with Jason and Rory. He said on a show recently that we're going to see inference running 24/7 for a portion of the knowledge worker economy.

• 18:18Speaker 00

  Yeah.

• 18:19Harry Stebbings?

  And how that really is going to be the defining theme of the year. Do you agree with that? And if so, what ramifications do you think that has?

• 18:27Speaker 00

  So basically that you sort of are, you're continuously running tasks at all times.

• 18:32Harry Stebbings?

  Continuously 24 hours a day, exactly. When lawyers leave the office, they're going to still have inference running for the projects that they have.

• 18:39Speaker 00

  For what it's worth, I don't think that we're there yet when we have tasks that take that much time to run. We don't have any task in Legora that would take 12 hours to run yet. But when you can put the models in loops and it gets better and better and better, the more loops it takes, then you can for sure allow that. I do think that we're going to move into a world where we start a lot of things as we go to bed and we wake up in the morning and it's done, for sure. I think I already started doing that with deep research when that came out for the first time. And it would take 25, 30 minutes to run. It was so cool, but you so quickly get used to our new shiny toys.

• 19:18Harry Stebbings?

  What do you think we don't talk about enough or don't see in the model environment slash landscape today? That more people should see or talk about?

• 19:26Speaker 00

  So one of the things that's very impressive with Claude Code, and do they call the new thing Coworker?

• 19:33Harry Stebbings?

  Yeah, Cowork.

• 19:34Speaker 00

  Cowork is maybe not so much about that tool itself, but about the paradigm that it has shown is useful and the right thing to go directionally. And the more we were working with Claude Code and Cursor in our engineering team, the more we just thought, hey, let's apply the same principles to the way that Legora works. Basically, having the Legora agent access all the other tools available in our ecosystem, as well as any MCP servers that the client brings, and then basically kind of letting it roam. And you just give it this, again, overarching task. It gives you back its plan, and then you say, that looks awesome, go execute. And it's pretty much the way that a partner would work with a senior associate, and a senior associate would work with an associate.

• 20:18Speaker 00

  And I think this is like adding another layer in that hierarchy, basically, with AI in the bottom. But then that's available to everyone 24/7. So one of the themes that I've noticed is that the partners at these firms that we work with are starting to think that the technology is so good that as they give a task to their team member, they will simultaneously give that task to Legora. And then very often, the quality that they get back is pretty good, and that has real implications.

• 20:49Harry Stebbings?

  We're going to go to the structure of law firms in the future. I just want to unpack another thing there that you said earlier, which I don't want to forget. As you said, I'm playing more and more time in the US. There's this kind of perception, when I speak to especially US VCs, that Harvey have won the US and that you have won Europe.

• 21:05Speaker 00

  I think one of those statements are true. One part of that statement is true.

• 21:11Harry Stebbings?

  My worry with you is your lack of confidence, my friend. Why is that not true? Because they seem to have the magic circle in the US.

• 21:19Speaker 00

  Well, that's not true. And when we started the year, we were zero boots on the ground in the US. Now we are 50 people. We're opening up our new office on Manhattan this week. It's gonna be one hundred and fifty people. We've got three more offices in the US opening this year. The US has by revenue become our biggest market.

• 21:42Harry Stebbings?

  Wow, revenue wise, you have more.

• 21:44Speaker 00

  It's the biggest country by by revenue, yeah.

• 21:46Harry Stebbings?

  Do you have more in the US than you do in Europe?

• 21:48Speaker 00

  In total, no, we have so much in the Nordics, actually, because we basically work with all the big firms. But it will be, I think, by the end of Q one, yeah.

• 21:58Harry Stebbings?

  Super interesting. So by the end of Q one, you'll have more in the US than you will in Europe.

• 22:01Speaker 00

  Yeah. And the cool thing, right, is that if you look at the AM Law two hundred, and and by the way, like many of these clients that we're working with in the US, it's not the mom and pop shops, right? We're we we work enterprise. And so when we came to the US, we had a strategy, which was there's so many Nordic or European companies that have launched in the US and failed. Very close to home, Klarna tried to launch in the US like a couple of times before it really worked. And so I had this heuristic, which was if we can sign and serve two of the AM Law two hundred law firms from Europe, we are ready to open in the US. So Cleary Gottlieb, you know, Y2, a Wall Street firm, Goodwin and Procter,

• 22:44Speaker 00

  one of the best VC firms in in the world, and I think both are in the top twenty law firms in the US. We were able to work with both of them and give them confidence that we could support them better than anybody else. That gave me the confidence to go to the US and hire a team. And the awesome thing about building a team in the US is it takes two weeks for people to leave. We can talk about some of the differences between, you know, US, Europe, but I think the the termination period in the US versus in, let's say Sweden, is actually one of the structural benefits of having a big office in the US.

• 23:20Harry Stebbings?

  So how does it compare? Two weeks to leave in the US?

• 23:23Speaker 00

  Whereas three months, on like everybody has three months.

• 23:25Harry Stebbings?

  And for you as a founder, that is a night and day difference in terms of ramp.

• 23:29Speaker 00

  We've doubled in size every quarter. And the minute I know that I need somebody, if they wait a quarter, we're a different company. Right? It's wild. So you just need to, well, for one, I need to try and predict our headcount plan much more diligently in Europe than I do in the US, because there it's like paum paum. But really awesome people can just turn up in two weeks.

• 23:52Harry Stebbings?

  So your biggest advice to founders on scaling in the US without committing large resources would be that you can do a freemium and test it from Europe?

• 24:00Speaker 00

  Yes, for sure. Well, I think we could, so why can't you? And we're very enterprise, that might be different. We did not need to invest a ton in marketing or like B two C content in the US. I could just get on demos and get on a few flights, demo the product, run a few pilots, you know, always competitive pilots. And then, again, on the partnership level, show that we were willing to work with these firms on their ambition level, because it's very high. The firms that we work with are not treating AI as a check the box exercise. It's not, oh, let's buy, you know, this thing, let's roll it out and we're done. It's, we want to be the firm that dominates our market, because we understand AI and technology better than any other firm.

• 24:45Harry Stebbings?

  Just going back to the US and the expansion there, do you regret waiting as long as you did?

• 24:49Speaker 00

  No. Did I tell you that I took a decision to not sell the product for six months?

• 24:54Harry Stebbings?

  No.

• 24:54Speaker 00

  So our first board meeting, so to give you some context, we were a Y C, we raised $10 million from Benchmark. A month later, we raised another 25 million from Redpoint. And we had our first board meeting and we were like 12 people at the time. First board meeting, it's Benchmark, Redpoint and three founders. And we sit down and I tell them that we are not going to sell at all for the next six months. Redpoint sort of looked at me and they were, I think, a little nervous that they had met me for basically an hour and 45 minutes and given me

• 25:30Harry Stebbings?

  Paid a whopping price.

• 25:32Speaker 00

  And I was showing up and I said, we're not gonna sell.

• 25:35Harry Stebbings?

  What price was the Redpoint round?

• 25:36Speaker 00

  One fifty.

• 25:37Harry Stebbings?

  That's interesting. Do you regret taking, I'm not saying Redpoint, but doing that round?

• 25:42Speaker 00

  No.

• 25:42Harry Stebbings?

  Cause that's a lot of dilution.

• 25:44Speaker 00

  Yeah.

• 25:44Harry Stebbings?

  Twenty five at one fifty, when you didn't need the money two months after a benchmark.

• 25:49Speaker 00

  Yeah, but you you couldn't know that you didn't need the money. And if I remember correctly, one of our competitors did another round quite quickly after. So I think it was good to solidify there's interest in Legora stock. And now I just get like, you know, at this point, I'm just archiving emails cause I'm getting too much inbound. But back then.

• 26:09Harry Stebbings?

  Which is why I send WhatsApps.

• 26:11Speaker 00

  Yeah. But back then, that's a good thing. That's a good thing. Back then, they were, you know, I turned around and said, hey, we're not gonna sell. We need to get to the point, because we only have one shot. We only have one shot with these lawyers. Cause they are very impatient. If it doesn't work, they're not gonna come back. And that's why activation and getting that like the time to value is so important in the product. But to go back, we took six months, calculated time and said, we're not going to sell. We have to solve our infrastructure, our reliability, the scalability of the product. And we need to rebuild and refactor a lot of it because it has just been quickly put together. And what we told all the clients were, we were lucky, you know, it was summer, because we could say, oh, it's, you know, summer in Europe.

• 26:55Speaker 00

  So we're not working and we're gonna wait to onboard you after summer. And there's so much demand that we're gonna have to do it in October, because September is like completely full. We can't onboard more clients. But October first, twenty twenty four, we were ready to onboard a thousand lawyers a day comfortably on the product. And we got to that point and then we started to rip. And I'm very proud that I had the guts to tell the investors that that was the right plan. Cause I think if we had continued to push, we would have just churned everything.

• 27:30Harry Stebbings?

  So when you look back at the timing of the US expansion, do you not think you could have gone sooner and not ceded so much ground?

• 27:38Speaker 00

  Well, for what it's worth, I don't think we conceded a lot of ground and we are winning back a lot of ground. If you put it that way.

• 27:45Harry Stebbings?

  So customers aren't loyal.

• 27:47Speaker 00

  No, I think everybody is still treating this as an extended pilot and an option on AI. It's like a call option. They're not doing five-year contracts. They're doing one to three-year contracts. And in law firm time, that's a blink.

• 28:06Speaker 00

  Many of these firms have been around for 200 years. So two years might be half of our lifetime, but for them, it's a short time.

• 28:12Harry Stebbings?

  So when we look at the numbers, the retention for our Harvey is 98% logo retention, 178% net revenue retention. Do you have as good numbers?

• 28:21Speaker 00

  So for both those numbers, yes, but on NRR, I don't think that's a fair number for me to comment on because so much of our growth is not about renewing contracts from 2024. In a single day in 2025 in December, we added 7 million of ARR, one day in 24 hours. And that was more than what we did in 2023 and 2024 combined. And so NRR and logo retention, you know, it's up to 2026 to determine where those, you know, real numbers will be. And I think for what it's worth, the ability of these products to go quite broad will be very interesting. Because, you know, to some extent, there's initial use cases that you can solve with AI that we target.

• 29:05Speaker 00

  And then the more time we spend with our clients, the more problems and opportunities we see. And so what's happening to the products is they're growing quite a lot. And so what I think will happen is that this will be like a suite, like a platform kind of play that just becomes more and more of the central system where they do their work.

• 29:23Harry Stebbings?

  So on an NRR standpoint, do you charge on a per-seat basis or on a per-task basis or on a volume-per-task basis?

• 29:29Speaker 00

  We charge on a per-seat basis.

• 29:31Harry Stebbings?

  Is that optimal?

• 29:32Speaker 00

  I think that's optimal for the buyer. I don't think that's optimal for us.

• 29:37Harry Stebbings?

  Yeah.

• 29:38Speaker 00

  And so.

• 29:39Harry Stebbings?

  And is that not like solving for a historical norm, not a future optimization?

• 29:43Speaker 00

  I actually don't think it's the right pricing model.

• 29:45Harry Stebbings?

  Yeah.

• 29:46Speaker 00

  I think it should be consumption-based.

• 29:48Harry Stebbings?

  Yeah.

• 29:48Speaker 00

  Because you can have individual users racking up such big LLM costs that it basically becomes unsustainable on a per-user basis. The reason why we have that is you need to make it easy for the buyer. If they don't know how to manage a consumption-based pricing model, you can't have it. And I think that will pivot. And I'm unsure exactly what that timing is. I think the timing is more around when the clients are ready versus when we are ready.

• 30:17Harry Stebbings?

  And so task expansion is incredibly useful for retention, not for revenue optimization. In other words, the more they do, it's more likely they are to retain, but it doesn't actually help your dollars.

• 30:27Speaker 00

  Right. No, actually it costs more.

• 30:30Harry Stebbings?

  Yeah.

• 30:30Speaker 00

  I mean, so it's a bad thing, the more they use the product, but.

• 30:36Harry Stebbings?

  Do you have good margins?

• 30:37Speaker 00

  We have okay margins.

• 30:38Harry Stebbings?

  I respect the honesty of that answer.

• 30:41Speaker 00

  Yeah, right. It's not sauce margins and I think it will take time to get there.

• 30:46Harry Stebbings?

  Will it get there, do you think?

• 30:48Speaker 00

  Yes, I think it will get there. Not only do I think it will get there, but I think your ability to price versus traditional sauce products will be insanely high because you used to use a lot of these products to do very narrow parts of the work. And they were all disconnected. To give you an insight into the life of a lawyer, it's like you have this product over here that you use to compare two contracts. You have this product over here that you use to extract relevant data from contracts. You have this other product over here where you go and look up legislation. You have this other product over here where you go and look up case law, right? All these different things. So you as the human had to sit there, comb through all these differences and like aggregate the stuff yourself.

• 31:30Speaker 00

  But now, similar to Opus 4.5, you're just gonna send the task to Legora and it can be pretty arbitrary. And then you let it figure it out and it just goes and does all the work, or at least a big portion of the work in a much, much, much, much shorter time at a very high quality level. And when you do that, you are not being priced against the other sauce products. You're being priced against, you know, what would I pay a lawyer to go out and actually do this work?

• 32:02Harry Stebbings?

  So in three years' time, will you still have seat-based pricing?

• 32:04Speaker 00

  Absolutely not.

• 32:05Harry Stebbings?

  When does that change?

• 32:07Speaker 00

  When our clients are ready to buy on consumption.

• 32:10Harry Stebbings?

  Why do you sound so confident that we'll be within three years, respectfully?

• 32:13Speaker 00

  Because, you know, Cursor is consumption, a lot of other enterprise tools are for consumption. I just think legal takes a little bit more time. But within three years, well, look, like, you gotta understand my vantage point. Three years is longer than I've been CEO at Laguara for. So three years for me is is a very long time going forward.

• 32:35Harry Stebbings?

  On the margin optimization side, is it a little bit like, you know, obviously, we're investors in Lovable, where they're able to do model selection dependent on task and optimize margin because of that?

• 32:45Speaker 00

  You can do that, of course, which we do to some extent. But it's also, I don't think we're in the margin optimization time yet.

• 32:54Harry Stebbings?

  You're in the land grab time.

• 32:56Speaker 00

  Yes, that's the right way to phrase it.

• 32:58Harry Stebbings?

  In the land grab time, what is the biggest challenge that you face?

• 33:01Speaker 00

  Biggest challenge that we have right now is growing from thirty to three hundred and then doubling again in the next two quarters from three hundred to six hundred and maintaining the ambition, integrity, teamwork, and just like raw grit that got us here when you double the team. Like, I think we we just hired two two new people in the US and they were really surprised by how late everybody was working. They were like, oh, at the at the other place I was at, which was a, you know, another another legal tech provider, everybody left at six and we have dinner in the office at eight.

• 33:43Speaker 00

  And so when your entire team globally operates at that level and at that pace with that, you know, goal in mind, that's awesome. But I care a lot about maintaining that.

• 33:53Harry Stebbings?

  How do you maintain that?

• 33:55Speaker 00

  Well, I still interview everyone, so I ask quite brutal questions about, well, I take a hard job. You could go work somewhere else. I try to create missionaries, not mercenaries. And I think we've successfully done that. I also think that you you get pulled in. Like, when you see everybody else doing it, you're just like, okay, of course, I'm gonna do it. And momentum breeds momentum. Like, we were signing deals on New Year's Eve. We had a big Christmas dinner whilst we were having glögg or what's it called, mulled wine?

• 34:26Harry Stebbings?

  Yeah.

• 34:26Speaker 00

  You have that in Sweden. We were having the wine before the dinner and we had the big sales dashboard, like at the wine thing, and everybody kept looking at it because like everybody wants momentum, everybody wants to win. And when you join a company and you feel like a winner, I think you get burned out doing work that, you know, where you don't feel like you're winning.

• 34:48Harry Stebbings?

  Do you think competition is helpful in creating that vibe?

• 34:51Speaker 00

  A hundred percent, of course.

• 34:53Harry Stebbings?

  Do you light the tinder, so to speak, and fuel the fire?

• 34:57Speaker 00

  Oh, yes. I think I'm very good at it, actually. And competition can be played at a macro level where you think us versus them. But you can also do it at a lower level, which is our marketing team wants to beat that marketing team. Or our engineers want to build a faster document upload time than that other team. You compete on all these micro levels and you celebrate them like crazy. What I've learned this year, I actually used to be quite bad at celebrating. I remember when I was in business school, my dream job was to go to McKinsey because I thought that's where, that's where all the amazing people went. I found out maybe that that was not the case.

• 35:41Speaker 00

  But when I, when I got the call and I got the job, I was in the, in the grocery store and I celebrated by buying a bag of peanuts. Yeah, that was a bit crazy. I was really bad at celebrating, like really bad.

• 35:53Harry Stebbings?

  Explains why you're so thin, but.

• 35:57Speaker 00

  But this year, we've learned to celebrate and it's amazing. You celebrate the wins really hard because then you also really feel the losses. Because I think it's, it's easy to get, to be blindsided if you have momentum and you have success. You need to see the world for what it is.

• 36:10Harry Stebbings?

  I heard from some of your investors that internals at Harvey call you their CPO, speaking of comparisons of teams.

• 36:19Speaker 00

  Well, I, I think you'll have to ask them. That's funny.

• 36:21Harry Stebbings?

  I am going to ask you, have they ripped your product?

• 36:24Speaker 00

  Well, I think we take a lot of pride in developing our product.

• 36:30Speaker 00

  As fast and as well as we can. And I think there's two main parts to our product development. One of them is improving the parts that we have. And the other one is making new qualified bets. I think we have had a history of making bold and correct bets. I think there's many legal tech products that on the surface looks pretty similar. There's even another product where they ripped our name and it's our tabular review. It's just called tabular review in their product, which is totally fine. But what happens when you then go into these competitive pilots? And the user starts to kind of rip them apart. That's where you see that one product is a Rolls Royce or maybe a Volvo. And the other product is maybe a cheaper version.

• 37:15Harry Stebbings?

  What product decision did you make that with the benefit of hindsight was a mistake? And what did you learn?

• 37:21Speaker 00

  The first version of the Laguara product back in summer of 2023. That was completely the wrong direction. We built it centered around a couple of core use cases. And we did not have an agent or a chat that could operate over those tasks. It was like a click and point use case, clearly the wrong direction. So after we got accepted into Y Combinator, we deleted all of that code. I think we made some good product decisions by very early adopting. Basically, Langchain was too bad at the time, so we built our own agent architecture. And we did that very early, which I'm very proud of. And that was like the right direction to continue on.

• 38:00Harry Stebbings?

  And you still have that today?

• 38:02Speaker 00

  No, it's been completely rebuilt many times. I last committed code in October 2023.

• 38:08Harry Stebbings?

  But I'm just intrigued as to how you think about that. We're seeing more and more companies à la Deal or à la Revolut.

• 38:13Speaker 00

  Yeah.

• 38:13Harry Stebbings?

  Build their own complete vertical software.

• 38:16Speaker 00

  Yeah, I think we're not the size of Revolut or Deal. And so it probably doesn't make sense for us to do that. And Langchain and a lot of their surrounding tools have gotten a lot better. And so I think we're in the job of, and our engineering team is in the job of picking the best third party things. The other right product decision we made or wrong was that we were doing too many things. So in 2024, we were 12 engineers and we were trying to build six or seven different things at the same time. And that was creating a lot of confusion because I was very involved in the product decisions at the time. And I was basically just out doing go to market. And so we'd make a lot of product decisions without me in the loop. And then it kind of looked like a Frankenstein monster. There's actually a pretty funny doc.

• 38:59Speaker 00

  From October or November twenty twenty four, that was called the Leia product manifesto.

• 39:07Harry Stebbings?

  Oh, I remember.

• 39:08Speaker 00

  Yeah, we were Leia this in twenty twenty five, we were still called Leia.

• 39:11Harry Stebbings?

  Yeah, I remember.

• 39:12Speaker 00

  And it basically outlined that we were gonna do three things, but we were gonna do those three things so well that our suite was the best basket money could buy. And it was our agent, our assistant, our tabular review and our word add in. And we were competing with local products for these different things, right? Like the word add in was competing with a bunch of other legal tech companies that were only focused on the word add in. Our tabular review was competing with, at the time, like Hebea and companies who were only focused on like tabular review as or the matrix, I think they call it. And then we had our our agent, but we said, if we have all of these three things and we combine them in a very user friendly way,

• 39:55Speaker 00

  that suite is gonna be better than buying all of these three things separately. And that's kind of the platform play or the sweet play. That was totally the right move. So we removed five or six other things that we were building, just deleted the code. And then we hard committed on these things.

• 40:11Harry Stebbings?

  When you look at the landscape, when you think about kind of that bundling versus unbundling and how you thought about that. When you look at the landscape today, how does that landscape look in three to five years? Is this a winner take if we okay, actually, a much better way to ask that is, is this an Uber and a Lyft? Or is this a Google Cloud, AWS, Azure?

• 40:30Speaker 00

  The reason why I don't think it's a Uber and Lyft is because in Uber and Lyft, there was no product differentiation. The products were pretty much the same and.

• 40:39Harry Stebbings?

  It's strategy differentiation on global versus.

• 40:42Speaker 00

  Yeah, but it was very hard to build something different. Uber, for what it's worth, I mean, the product looks the same today, basically. With the addition of bells and whistles, but it's the same fundamental thing. But the difference to our story is that the product differentiation really matters. And the amount of things that you can go and build is so vast. It's like this universe of legal technology that just has never been built. Because one of my theories is that maybe in legal tech before generative AI, there weren't that many exciting things to build. And it was really hard to scale a good company. And as soon as you got to like a single digit million revenue, you would get an acquisition offer, which would be life changing money for the founders,

• 41:26Speaker 00

  but no unicorn outcomes. So the product strategy will impact the trajectory of all of the businesses in our vertical tremendously. I think it's totally a winner takes all, all sauce. I mean, you know this, number one will grab 90%. And number two to number 10 will share the remaining 10%. And so I think what that means for us is got to run like hell. You got to win. There's no number two. There is only being number one. There's only winning. Everything else is losing. The type of people who think like that are the people who work at Legora.

• 42:03Harry Stebbings?

  One segment that I do find interesting, or two segments, is like the verticalization. It's like we're investors in Solve.

• 42:09Speaker 00

  Yeah.

• 42:09Harry Stebbings?

  AI for patent lawyers, love them. They've done amazingly well. You have verticalization in that sort of way. And then you also have verticalization in the, we're going to own the whole vertical and do like a Crosby. We're going to be your law firm and use ours. How do you feel about those two?

• 42:25Speaker 00

  I don't think that owning the entire service layer and software layer is a winning strategy. Basically building an AI native law firm. The reason is, I think there are so many talented lawyers that are very good at utilizing software, and I would not want to compete for them. I think it's easy to get into that space and try and solve lower complexity tasks. I mean, you're starting out with kind of non-disclosure agreements, master service agreements. You can get there pretty quickly. But then that will be a very crowded space in and of itself. I would much rather be the shovel seller to all the world's amazingly talented lawyers

• 43:10Speaker 00

  who want to turn their firms into software-powered entities. I don't think that there will be a ton of margin slash profit in the low-complexity work. Because I think as soon as AI can do a task, it will do that task. The only question is kind of where does it get transacted? And the big law firms, they already do NDAs for free for their clients. Because they got to win the expensive private equity work. And so it's like, are you going to show up as Crosby or somebody else and go, hey, pay me 50 bucks a NDA? I'm not sure.

• 43:43Harry Stebbings?

  Okay, so we think that's not a good strategy. What about the verticalization?

• 43:47Speaker 00

  Yeah, I think you can quicker get to a lot of value in verticalizing. I'm not sure what the TAM looks like within each of those verticals.

• 43:55Harry Stebbings?

  If you look at patents, it's a $485 billion market.

• 43:58Speaker 00

  Yeah, so it's a huge market. So maybe you go win patents and that's amazing. Or patents becomes part of a broader thing, unclear. I think there will be many winners in different layers of the ecosystem. And I also think that there's one part which is kind of the central hub that will, you know, let's say somebody goes to Laguardia and they want to write a patent. Then why don't we just ping Solve Intelligence?

• 44:19Harry Stebbings?

  Yeah.

• 44:20Speaker 00

  And say, hey, Solve Intelligence, come write us this patent.

• 44:22Harry Stebbings?

  Yeah.

• 44:23Speaker 00

  And then it comes back and does it. Or maybe that's what Copilot wants to do, right? I think there's a lot of Venn diagrams and a lot of overlap. Right now, I think it's more down to execution than it is to like underlying markets, being smart about the markets.

• 44:39Harry Stebbings?

  You have hired now 150 people in the US, 50 or 150?

• 44:42Speaker 00

  No, we're like 50.

• 44:43Harry Stebbings?

  50 in the US now, okay.

• 44:45Speaker 00

  I think we'll be 150 before summer.

• 44:48Harry Stebbings?

  It's a lot of people still.

• 44:49Speaker 00

  Yeah.

• 44:49Harry Stebbings?

  When you think about that, do you think the canonical wisdom thought that the US works harder, they are harder driving, they are more? Transitional but bullish and they are in the office late. And we in Europe just like to chill the fuck out. Qing'an's fair having hard fifty.

• 45:05Speaker 00

  I don't think that's fair. I think we were very good at seeding the Legora culture in the US. And a couple of our best people from Europe went to the US and have spent a lot of time there.

• 45:19Harry Stebbings?

  So actually like the, hey, we're all such hosters, we're so good in the US.

• 45:23Speaker 00

  Yeah.

• 45:24Harry Stebbings?

  It's a bit of bullshit.

• 45:25Speaker 00

  I think it's a little bullshit. But for what it's worth, the culture that we have in our US office now, I almost wanna spend more time in the US just to be there. Cause it's electric. It's, I mean, New York is on fire. And I have a hard time spending a lot of time in New York and then coming back to Stockholm. Cause New York is always up, it's always awake, it's my tempo. Whereas Stockholm is, when you walk out on the street, not when you're in the office, it's a little sleep.

• 45:51Harry Stebbings?

  Why are you not living in New York or living in the US?

• 45:54Speaker 00

  I'm de facto living on a plane. I had two hundred travel days last year in total. Last year, I spent a meaningful amount of time on product and we have all engineering in Stockholm. We're ten percent YC founders in our engineering product and design team.

• 46:10Harry Stebbings?

  Wow.

• 46:11Speaker 00

  Which I think is a high number. Two of our batchmates have actually joined the company.

• 46:16Harry Stebbings?

  How are they different than norm YC engineers?

• 46:19Speaker 00

  I think what's cool about it is we're structured in a way where I think my management style is very, it's not, it's a lot of delegating. It's not very micromanaging and it's very, here's the thing, go run with it. I think founders do very well with that. I also think it basically gives all the different components of our platform, which is separated into pods. Like we have one team working on this piece of the product, one team working on this piece of the product. And there's like a YC founder running part of the product. And then they just run like hell on their thing. And they're competitive about their part being better than all the other parts. Or rather their equivalence in other products. I also think YC has a way of attracting very ambitious people who wanna win.

• 47:03Harry Stebbings?

  Before we do discuss kind of future of law firms and then do a quick fire, I have to ask you. I'm gonna ask Harvey on the show, right, which you know.

• 47:11Speaker 00

  Great.

• 47:12Harry Stebbings?

  About their revenues. I have to ask you for yours. Where are you guys at?

• 47:16Speaker 00

  Well, I'll tell you a little bit later in the quarter. But in December, we added seven million in a day. And we've basically doubled every single quarter for the last six quarters.

• 47:27Harry Stebbings?

  Will you be at two hundred by the end of the year?

• 47:31Speaker 00

  Definitely. Otherwise, I'll come back.

• 47:33Harry Stebbings?

  What's the stretch goal?

• 47:34Speaker 00

  You can shame me.

• 47:35Harry Stebbings?

  What's the stretch goal?

• 47:37Speaker 00

  You'll have to ask Patrick or CRO.

• 47:39Harry Stebbings?

  If you were at three hundred, would you be happy?

• 47:41Speaker 00

  Well, I don't view the number in isolation. I'll be happy by the end of the year if we deliver on all the promises we made to clients. And we don't even need these competitive pilots. If you're a lawyer and you do serious legal work, you're on Legora. It's like Figma. If you're a designer that makes money, you're on Figma. I want that to be the truth. And if we do that, I'm sure three hundred is the number, or even more, right?

• 48:09Harry Stebbings?

  Okay. In terms of the structure of law firms, they thank you for the work that they now no longer have to do because you do it. But you will need far fewer trainees, you will need far fewer juniors. Do you agree you will need far fewer juniors? And what is the structure of a law firm in the future?

• 48:25Speaker 00

  So I think law firms will go through a quite significant consolidation period. Because so far, there hasn't been a lot of incentives to consolidate law firms. But now, actually, private equity wants to get in on the action. They want to fund different law firms who want to become AI-powered. Again, coming back to the idea of, do you want to own the whole stack? Or do you just want to work with the best service layer?

• 48:51Harry Stebbings?

  And so you're seeing a roll-up play where you integrate AI?

• 48:53Speaker 00

  Absolutely.

• 48:54Harry Stebbings?

  Juice up the margins.

• 48:55Speaker 00

  I mean, look, I don't think there's going to be an AM Lot two hundred. I think it's going to be an AM Lot twenty, or maybe AM Lot twelve. I don't think it'll be a big four because of regulation and it just takes time. But it will definitely consolidate. At the end of the day, Legora and I care about working with the winners of that space. Because the technology lever will be one of the, if not the, most important lever to utilize in competing against other firms. It looks different for different practice areas and in different calibers. But let's take a Bread and butter M and A transaction. In a bread and butter M and A transaction, the legal work that the law firms do is pretty much undifferentiated. You get pretty much the same thing depending on which firm you go to. If you just look at the, you know, D D and the work.

• 49:40Speaker 00

  It's kind of an equilibrium where the price gets offered at. Let's say it's a hundred, a hundred thousand pounds. The minute that one of the firms that are playing in this game are able to offer that at a lower price, but same quality, or maybe higher speed or something like that. Some attractive aspect of running that deal. Let's say they're offering it at eighty K. You kind of break the equilibrium. Everybody has to move to that equilibrium. So it's kind of a market share game. It's like who can run the fastest on technology and all the others, the other aspects of what it takes to run, run a law firm. And who can win most of the market and then hold that market.

• 50:19Speaker 00

  Cause then I think you're able to deliver additional services that go outside of what the very, very, very competitive things are.

• 50:27Harry Stebbings?

  Will we have fewer junior lawyers and trainees? Will law firms be smaller?

• 50:31Speaker 00

  I actually think law firms will be bigger, right? Because they will consolidate. But I don't think that you will need the same number of lawyers running a transaction as you have today. Right? If you have a physical data room, that's why it's called a data room. You just have to send people there and they would open up all the boxes, read everything, make all the commentary, right? And then it became a virtual data room.

• 50:51Harry Stebbings?

  But you have to assume that there's going to be more transactions.

• 50:53Speaker 00

  Yes.

• 50:54Harry Stebbings?

  In the future.

• 50:55Speaker 00

  Yeah, so more transactions, probably fewer people running those transactions. But every person can run more transaction because of technology, more transactions because of technology.

• 51:04Harry Stebbings?

  So just to really be clear, you do not think there will be less trainees and junior account, junior lawyers?

• 51:08Speaker 00

  I do think that there will probably be less junior lawyers and trainees. Because I think that you just won't need as many people to execute the work that the firm has.

• 51:22Harry Stebbings?

  Also, most law firms are partnerships, correct?

• 51:24Speaker 00

  Right.

• 51:24Harry Stebbings?

  The partnerships accrue profits that I can take out.

• 51:27Speaker 00

  But, but I'm already seeing patterns of this where firms that we work with will have, you know, somebody leaving. They will not fill the vacancy, but they're doing more revenue than. They did last year, and so it's a high profit. I think it might also create an opportunity for big law will do really well because they have a lot of moats and a lot of brand and a lot of data. Small law can do really well because that's still operating on a very, very personal basis. I think where it might get difficult is mid law, where it's very competitive, you're competing hard on price. You throw AI into the mix and it will make it even more competitive. But in engineering, let me like, let's just take another example. We're hiring more engineers, although they're writing more code, right? Because there's like more stuff to do. So the thing for the law firms is like, then it's increased the size of the pie.

• 52:12Harry Stebbings?

  So you think we'll have more engineers in two years' time?

• 52:15Speaker 00

  I think so, actually, because I think there'll be, you can just do more stuff. You'll have more people writing code and doing things or starting new things and projects and things in two years.

• 52:28Harry Stebbings?

  I think you're being quite optimistic, which is really nice. But I think we're going to see more labor displacement than I think people expect. And I think we're going to see that in the next 12 to 24 months. Jason Lampkin, again, friend, said this is the year that we're going to see AI displace large amounts of knowledge work. And that's going to show up in labor figures. Do you think that's too soon?

• 52:49Speaker 00

  Well, I think it's within that timeframe that AI gets pretty good at completing end to end tasks very deterministically within our vertical. So unless they can find something else to do than, you know, that thing within the firm or growing the pie, then yeah. But here's the cool thing, right? Like if you use technology to complete more of the work, then you need to think about how you win more work from the other firms. But yeah, I mean, on a total, like, but I'm talking for an individual firm. If you're talking on the total level, yeah, probably.

• 53:22Harry Stebbings?

  Do you worry about the demonization of you as a technology leader displacing labor?

• 53:26Speaker 00

  No, that's not something that I worry about.

• 53:29Harry Stebbings?

  In time, I think it's something that will. Can I ask you, timesheets is how lawyers spend a lot of their time. Every two days, they have to do their timesheets. Do you know this?

• 53:40Speaker 00

  Yeah, it's wild.

• 53:41Harry Stebbings?

  Fucking wild.

• 53:42Speaker 00

  Adrian, who was our VP product, his YC company did AI timekeeping.

• 53:48Harry Stebbings?

  Fucking wild. A billable hour is over?

• 53:52Speaker 00

  No, I don't think it is. I think billing will move much slower than both you and I would think. Because often, it's actually demanded by the clients because they want to get a breakdown of everything that the lawyers actually do. And it will start to be replaced by fixed fees in different practice areas and for different types of tasks. But you will still have a sort of ephemeral billable hour above that.

• 54:17Harry Stebbings?

  Dude, I'm going to ask you, quick fire. Does that sound okay?

• 54:20Speaker 00

  Shoot.

• 54:21Harry Stebbings?

  Three rounds, no deck. What was the biggest advice on fundraising?

• 54:26Speaker 00

  The advice that I got in YC was build a good business and it's very easy to fundraise. That's what I've lived by. I don't think I'm a master fundraiser by any means, but I am.

• 54:38Harry Stebbings?

  With respect, I'm going to push you. Sorry. You got Benchmark early, which then led to a Redpoint. Do you think Benchmark is just a massive signal which led to a quick successive round that you wouldn't have had otherwise?

• 54:50Speaker 00

  No. So Redpoint was not the fund that first wanted to preempt us. There was another firm that wanted to preempt us for the A round. And they gave a very competitive term sheet for the series seed, much higher price than Benchmark. Benchmark was, I think, the lowest price out of any seed fund.

• 55:10Harry Stebbings?

  But you place so much value on them that you took the discount?

• 55:13Speaker 00

  Yeah, I placed value on Chatham.

• 55:14Harry Stebbings?

  Chatham, not Benchmark?

• 55:16Speaker 00

  Yes.

• 55:17Harry Stebbings?

  Interesting.

• 55:18Speaker 00

  I picked on Partner. Yeah, I heard Benchmark was good, you know, I can do that research. But I met within two weeks, probably eighty partners. Nobody knew my space better than him. I thought it was great, you know, I've taken three companies public. That's what I want to do. And I thought I'd be much better off working with with that guy.

• 55:37Harry Stebbings?

  Unthinkable reality, you start another company, but you can only bring one investor with you.

• 55:42Speaker 00

  Yeah.

• 55:43Harry Stebbings?

  Who do you bring?

• 55:44Speaker 00

  Chatham.

• 55:44Harry Stebbings?

  Really?

• 55:45Speaker 00

  Oh, yeah, that's it, that's easy.

• 55:46Harry Stebbings?

  Okay, you can delete one investor from your cap table. Who do you delete?

• 55:51Speaker 00

  Well, I think I'll delete Y C.

• 55:52Harry Stebbings?

  Do you regret doing Y C?

• 55:54Speaker 00

  No, I love Y C, but all the other other investors are are on my board, so I would feel very rude.

• 56:00Harry Stebbings?

  That'd be a fucking awkward board meeting, wouldn't it?

• 56:02Speaker 00

  It would be very awkward, no, no, but yeah, I think, because they're not that, well, I think that's unfair. They're extremely helpful still. Y C rocks. I still speak with Gustav every quarter. But all the other are either board observers or board of directors, so that I I don't, I can't comment on that.

• 56:18Harry Stebbings?

  What's your most unpopular belief about where AI is heading?

• 56:21Speaker 00

  I really do believe in the platformization. I think there are way too many point solutions that will not survive a winter bubble, whatever you might call it. And they would deliver more value as being part of a broader ecosystem.

• 56:41Harry Stebbings?

  What do you know now that you wish you'd known at the start of Layer?

• 56:44Speaker 00

  I wish I knew what the intensity of doing and thinking about nothing else would sort of impact your own psyche and and personality. For the last two and a half years, I've basically done nothing else than to think about Layer or Legora or the business. And, you know, when you're in, when you're in college or or prior to that, I was doing so many different things. It was nice to do many different things and you got to have many different contexts. And you got to do many different types of activities. And when you got tired of one thing, you could go and do another thing. But this is not that. It is like running a mega sprint.

• 57:27Speaker 00

  As part of a marathon and I love it, but I think, you know, could I go back and also have that expectation going in? I think I would have been better at handling other disappointments or, you know, parts of my life that I couldn't focus as much on.

• 57:44Harry Stebbings?

  I think our job is much easier as venture investors than we give credit to. I think when you find obsessed founders that are just quite unhinged and psychopathic, I would put you in that category, to be honest. I put me in it too, to be honest. But when you find them, it's quite obvious. You know, when I sit down with Alan Chang at Fuse Energy, I said, do you angel invest? And he goes, you fucking stupid. I said, potentially, my mother thinks so, but you know, tell me why? And he's like, to angel invest, I'd have to either sell Revolut shares or Fuse Energy shares. That would both be a terrible fucking decision. So no, I don't angel invest.

• 58:14Speaker 00

  No, no, because you can't focus on doing that. You can't make good decisions. Or, right, you know, you can invest 10K in a friend's company because it's nice, but you can't do it seriously.

• 58:25Harry Stebbings?

  Penultimate one, which founder do you most respect and admire and look up to?

• 58:29Speaker 00

  I'm pretty bad at having idols. I wish I was better at it. I was super nervous the first time I met Daniel Leek from Spotify. I remember like I was super, like I thought that was the coolest thing ever in like 2024. He had reached out to us and was like, hey, you know, love what you guys are doing.

• 58:45Harry Stebbings?

  Daniel's amazing.

• 58:46Speaker 00

  He's amazing. When I grew up, looking at Niklas and Daniel and Sebastian and seeing these Swedish tech companies succeed, that was phenomenal. That was a huge inspiration. And now having met Alex and Gustav who are taking over Daniel, like they're also fabulous. But I don't go around on a daily basis thinking, oh, I look up to this person, I want to be like them. I try to draw inspiration from where I see good and then I run at it.

• 59:13Harry Stebbings?

  Final one, what's the best advice you've ever been given?

• 59:17Speaker 00

  The best advice I had ever been given was probably from Y C and Joel at Sonalabs, which was to take the check with Benchmark over anyone else.

• 59:30Harry Stebbings?

  Dude, thank you so much for doing this. It's so lovely to do in person. I really appreciate the friendship. Thank you for not letting me on the cap table. I think about it every day. It's fine, I've got over it, you prick, but you're a hero, my friend.

• 59:42Speaker 00

  Thank you so much, Harry. Let's go.

• 59:45Harry Stebbings?

  But before we leave you today, over 80% of Fortune 100 companies are running their businesses with Airtable. Airtable combines AI with the scale of an award-winning, infinitely flexible no-code system, a platform where you can see all of your data in one place and use it to make really big-picture decisions. Think of it like mission control for your company. Airtable goes beyond organisation and automating repetitive tasks. It lets you use your data to inform strategy, monitor progress and take action. Every cell is capable of performing hundreds of AI-powered tasks like web research or localisation and using those results to inform and update hundreds or thousands of other cells and workflows in real time.

• 1:00:30Harry Stebbings?

  Unlock the true scale of your workflows at www-airtable.com/20vc. Airtable, the infrastructure of innovation. And just like Airtable organises your workflow data, Metaview organises your conversation insights. This episode is brought to you by Metaview. Who says hiring has to be fair? Every founder, VC and exec I speak with knows this: Your ability to hire is the biggest constraint on your company's growth. But recruiting is slow, it's subjective and only getting more competitive. And that's why teams like 11 Labs, Brex, Replit, Deal and 5,000 other organisations use Metaview, the AI company giving high-performance teams a real unfair advantage in hiring.

• 1:01:12Harry Stebbings?

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• 1:01:55Harry Stebbings?

  Frontier Labs keep facing the same limitation. Models perform well on benchmarks but fall short once they enter real coding tasks, real tools, and real workflows. That disconnect between synthetic evaluation and actual system behaviour is now a core blocker for agentic models. That's why Nvidia, Anthropic, Salesforce, Gemini, and other leading labs partner with Turing. Turing is the research accelerator focused on post-training reliability. They build realistic reinforcement learning environments, next-generation data quality systems built from real-world operational traces, and coding data sets that stress models under the conditions where failures matter, state changes, workflow branching,

• 1:02:40Harry Stebbings?

  brittle tool calls, and the coding errors that break RL agents but never appear in benchmark reports. In reality, a model may demonstrate correct reasoning in your evaluation setup, yet still select the wrong parameter or mishandle a code update in a realistic interface. Turing makes that failure visible and gives teams the signal they need to fix it. For labs advancing agentic systems, Turing provides the structure required to understand why these failures occur. To find out how, visit turing.com/20vc. That's turing.com/20vc.