The Finance Startup Bringing Agentic AI to Wall Street

Brothers Chaz and Arnie Englander started Model ML after building and selling two YC companies. What began as a tool to help them analyze deals has grown into a full AI-powered workspace purpose-built for financial services, empowering firms to create automations and workflows that reflect exactly how their teams operate. And it's already being used by 10% of the world's top investment banks and private equity firms to automate everything from client-ready PowerPoint decks to deep-dive research and due diligence—by orchestrating AI agents that work like expert team members. In this conversation with YC Partner Gustaf Alstromer, they discuss going from internal tool to production platform, the power of perseverance, and their ambition to build a billion-dollar company with just ten people.

• 0:00Speaker 00

  In the last seven days, we've signed the same number of contracts as we signed in the whole of Q4. There is clear tangible value being driven by these products and it's only going to get better and quickly.

• 0:10Speaker 01

  Ultimately, you've got to be very passionate about what you're building. You've got to have that perseverance and if that sounds good to you, then then build a startup.

• 0:17Speaker 00

  If something logically makes sense, you should probably continue doing that thing, right? And not let anything stop you. And I think like the consistency that we've noticed of founders that we've some of that we've invested in or work with is like the ones that kind of do that and really persevere tend to win.

• 0:39Speaker 02

  Today, we're here with Arnie and Chas Englander. They are the founders of Model ML from one to 24. Prior to Model ML, they started two other YC companies that both were successful and sold Fancy and Fat Llama. And this is probably the first time I've worked with a company where both of the founders had had a previous successful YC company before. So I'm super excited to welcome Chas and Arnie here to YC. Welcome back.

• 1:03Speaker 00

  Thanks for having us.

• 1:04Speaker 01

  Thanks very much.

• 1:04Speaker 00

  Thanks for having us.

• 1:05Speaker 02

  Tell us what you guys are building.

• 1:06Speaker 00

  So Model ML is an AI workspace for financial services. So that's our one liner. What that actually means in practice is we've so we built a workspace that's akin to kind of the office suite. So our own version of Word, PowerPoint and Excel. With the major difference that it's built on top of an agentic system that kind of mirrors what a human has access to at the firms we work with. So quite specifically, if you're a human at firm X, right? You will have access to your files and folder systems, your emails, your CRM, any data vendors that you might use and pay for. Real time, publicly available information, public filings, your internal custom data sets, et cetera. Right?

• 1:47Speaker 00

  So then we kind of build this, we call it a cognitive architecture. It's a fancy word of saying, you know, kind of like a brain that mimics what you have access to digitally. And we overlay that with our user interface. The general idea being, well, if you had an Excel spreadsheet that was already connected into those data sources, you'd probably spend less time going and gathering information and analyzing it.

• 2:10Speaker 02

  I can tell that you guys are excited about how things are going right now. Would you put some words on how how things are going?

• 2:15Speaker 00

  Vertical.

• 2:18Speaker 00

  Look, I mean, in the last seven days, we've signed the same number of contracts as we signed in the whole of Q4.

• 2:24Speaker 02

  Wow, congratulations.

• 2:25Speaker 00

  Thanks very much. And I think it's it's really just the turning point, I think, in the sector, whereas, as we keep saying, it's like, there is clear tangible value being driven by these products, and it's only going to get better and quickly.

• 2:39Speaker 02

  What were people using ML using before? What were the tools that they were using in the daily daily work?

• 2:44Speaker 00

  So they would have their data sets, and then they would they would spend a lot of time in the Office Suite or in Outlook, right? And you know what that meant was, you know, a lot of that process is super manual and super repetitive. You know, I think, you know, the key here is, we're definitely not saying that humans should like never do these tasks, but you know, if you're organizing logos in a PowerPoint presentation, and you've done that hundreds of times before.

• 3:10Speaker 02

  Yeah.

• 3:10Speaker 00

  And you're a very well educated, you know, analyst or associate, it's probably not a great use of your time.

• 3:16Speaker 02

  Right. And I remember from, I think maybe from our interview or sometime on the first officer, you had a unique story on why you wanted to solve this problem. Remember what that was?

• 3:24Speaker 00

  Yeah, so we so we sold our first two companies. And after we sold our second company, we did a bunch of kind of investing ourselves, which I think on the whole, we were pretty bad at. But we became very interested in automating as much of those processes as you possibly could, right? And so it started whereby we literally were, when we would receive an opportunity via email, and having sold a company, you kind of tend to receive a bunch of opportunities every day. It would then enter into this like a Gensic system that, to be honest, we were just building for fun. And kind of produced like a one pager for us. But the interesting thing about the one pager is whilst, you know, we received some information via email, what was in the one page, probably 90% of that information was

• 4:09Speaker 00

  unrelated to what we would have received via email. In other words, you know, let's say we got an opportunity to invest in a startup, right? This thing we'll go off and look at their LinkedIn and their background, and then look at like comparable companies on Crunchbase or S and P and so on. And kind of produce this one pager that you would probably go and do as a human as your first port of call. You know, little things like if it was a consumer company, it would go and look at review websites, just as an example.

• 4:35Speaker 00

  And yeah, we thought it was pretty cool. And then people became interested in it. And then we kind of agreed that we were quite bad investors and okay at building stuff. And that's how it started.

• 4:46Speaker 02

  And that then turned into you selling this product or a new version of that product to the top financial firms in the world, basically.

• 4:53Speaker 00

  Yeah, so, you know, we can say now that we're about 10% of the largest private equity firms and investment banks in the world use our product.

• 5:03Speaker 00

  You know, we have other customers, asset managers, sovereign wealth funds, you know, a bunch of venture firms, but yeah, it's pretty, it's been pretty exciting.

• 5:11Speaker 02

  And how would they do, how were they doing their work before, before you started using Model ML?

• 5:15Speaker 00

  So as crazy as it sounds now, right, so let me use an example whereby, let's say you're, you're tracking a public company, right? And every quarter, every time there's a release, maybe as part of your job as an analyst or associate, you'll go to the release, the filings, and you'll put together what's called an earnings summary. So think about it like a beautifully present, like a slide, effectively, a single slide with a bunch of information. All that information is coming from the same piece of information. So for example, you might always get certain numbers from the filing itself. You might get other numbers like consensus or similar from our fact set and so on, and they're put into these slides. And these things take ages. We're talking probably like days to our company, just to pull together these slides, right?

• 6:00Speaker 00

  Because everything has to be linked back to source and checked and so on. And what you can do in Model ML, so think of Model ML as, you know, being used as the building blocks for this. So you have an Excel spreadsheet that's already connected into these data sources. And you might want to export that into your designs, right? And so rather than having to go and gather that information, once that release happens, this one pager effectively, it was actually three pages, a cover page, your main page, and a legal page, just appears in your SharePoint or Google Drive, right? And it's kind of 90, 95% of the way there.

• 6:32Speaker 02

  Wow.

• 6:33Speaker 00

  And we think in some cases more accurate because actually trawling through these filings as a human, and as, because you can also pull from multiple data sets for the same figure.

• 6:42Speaker 02

  Yep.

• 6:42Speaker 00

  Yeah, can be more accurate.

• 6:43Speaker 02

  I'm assuming that you were, you built something in the beginning and there was a model that was, could do some amount of this work. Because you did YC how long ago?

• 6:51Speaker 00

  A year ago.

• 6:52Speaker 02

  A year ago. So the models have probably progressed a lot in that year. What were things that models could do a year ago that were impressive? And what can they do today? And what are they going to be able to do in the future?

• 7:01Speaker 00

  The whole industry, the industry we're in right now.

• 7:03Speaker 02

  Yeah.

• 7:05Speaker 00

  Really from January is going straight line up. And I think the main difference that we've seen this year versus last year is last year was a year of testing. Right. So everyone wanted to make sure they had some sort of exposure, like as in they were, they were trialing something or looking at something. But it was still testing, right? And us having ran consumer companies, we don't really care about revenue figures. We've always been obsessed with like usage and retention.

• 7:30Speaker 02

  Right, right. That's good. That's good. That's the most valuable thing is when it brings into B two B. Like B two B people don't always know the most important stuff.

• 7:37Speaker 00

  Hundred percent, which we think is madness, but this year, everyone kind of, the whole world went from testing to using. So there were, and there was a fundamental shift. I think these agentic systems, there were small things like the improvement in things like function calling with some of the newer models, but everything has become considerably better by itself. And that's the interesting thing, right? It's like, I think even if we do nothing, theoretically, our product will improve, which is a pretty interesting world to be in, right? And so when you're constantly working on something and you're, you're pushing the boundaries, you know, month to month, what, what's possible is like, just wasn't possible the previous month.

• 8:12Speaker 01

  I also think the, uh, the vision models.

• 8:14Speaker 02

  Yeah.

• 8:15Speaker 01

  I mean, when they first started coming out and, and improving, we were sitting next to each other. We were going crazy, weren't we? It was like the stuff that we could do with the vision models. If you think analyzing files as an example, you know, OCR, okay, was amazing. You combine that with vision and its ability to read information from tables and charts. It really just changed the game.

• 8:37Speaker 00

  Yeah. And also I think it's a misconception, right? So like, I think the industry still thinks that AI or a large proportion of it is, is kind of where it was even six months ago, right? You know, what we're seeing today is, you know, if you look at some of these data providers, they've got humans reading information from say, public filings and put it in an structured format.

• 8:59Speaker 00

  You know, the bulk of the work that we're doing, what we're seeing is models are already more accurate than humans in those sorts of tasks. And so I think that will take a little bit of time in terms of confidence, but, but I, but I think some of the, the more lower level, more kind of data gathering and presenting type tasks are fully already being automated at the top firms.

• 9:17Speaker 02

  This is interesting. This, I'll tell you like the at Y C, the evolution went through at the same time. So two years ago, we would say. Oh, you can't really sell the software to investment banks or private equity funds. They don't really buy software, or if they do, they may buy one piece of software every 10 years. And the same was true for lawyers, but something happened last year, like they all got very AI curious.

• 9:35Speaker 00

  Yeah.

• 9:36Speaker 02

  Curious about AI, they were like, let's, let's do pilots to play with the software and try it out. And you were saying that like, this is the year when that turns into actual contracts.

• 9:43Speaker 00

  Exactly.

• 9:44Speaker 02

  And you can't, you can no longer say these companies don't buy software, that's wrong. They're all buying software now, and that's because this, this thing happened in the last 12 months.

• 9:51Speaker 00

  Exactly, and last year was the year of kind of proof concepts, and now, you know, our average contracts are in the years, first of all. And I, I just think in general, people are seeing, you know, a lot more kind of shorter term or instant value. You know, I also think just, you know, on the note of these firms historically, inclusive of law firms and others not buying software. That is, I think, true. I think the big difference here is, this is like number one thing, from the very top, this is like the number one thing on everyone's agenda. So we are not selling like the next CRM or like the next like data vendor tool or anything like that. We are selling what we're describing as the most advanced sort of AI solution for financial services in the world, right?

• 10:33Speaker 00

  And I think if you are a CEO or, or an exec in general, you've kind of got to take that call. You know what I mean? And I think that's really played to the advantage for all startups, for sure.

• 10:43Speaker 02

  You described some of these sales meetings, like who's the decider, like who decides to buy the software and, and what are they like?

• 10:49Speaker 00

  CEO level, or, or in general, just the most senior people at the firm. Regardless of if you are a top fiver or top tier investment bank, private equity firm, as I said, or software company, whatever it might be. Which I think at the start, we found like really strange, because we, we sort of thought that this would be looked at at a team or, or group level. It's really not, I think it's so important, firm-wide, that everyone has to be involved from, from the very top. And actually, what we found is, you've really got to get that buy-in, you know, from the right person at the top. And then you've also got to get buy-in from the people that are ultimately get, going to be implementing the tool.

• 11:29Speaker 02

  So you guys are flying to meet all these firms, where they, wherever they are?

• 11:33Speaker 00

  Wherever they are, wherever they are. So we have a bunch of people working out of Hong Kong and Singapore now. We've just opened a small office in India.

• 11:42Speaker 00

  About half of our overall team are based in London, and we have an office in New York. Again, I think like- It's clear the product is impactful, right? Because when we're demoing, we're like laptop out. We're showing real use cases with real data.

• 11:56Speaker 00

  You know, high use case frequency, right? So then if you think about like, why they wouldn't sign with you. A big part of that, I think, is trust and building that relationship. You know, because it's also a different dynamic. You know, it's like a lot of time you're speaking to folks that, you know, if they make a wrong call here, they could get fired. Right? And so we spend a lot of time building that trust. I think a big part of that trust is FaceTime and getting in front of people, obviously. But then spending the time on the demo and how that's justified and really investing in things that are specific to the customer.

• 12:31Speaker 02

  I want to go back a little bit to the two previous companies that you guys ran, Fat Llama and Fancy. Before we get into the details of what they were doing, like what are some of the learnings you took from those companies into ML?

• 12:44Speaker 00

  I would say you've definitely got to enjoy it. You've got to enjoy building companies is my overarching thought. What about you?

• 12:52Speaker 01

  I think you've just got to be prepared for the worst.

• 12:56Speaker 00

  Yeah, you've got to be prepared for the worst.

• 12:58Speaker 01

  And the most ridiculous roller coaster experience. I think all startup founders will say the same. I think it's going to be a lot of ups and downs, a lot of the time downs. And you've just got to be prepared for that and know it's coming. And as Chaz says, just enjoy it because it's fun.

• 13:13Speaker 02

  And is there a sense that when you start a third company that you've gone through that before? So you've gotten used to the ups and downs and you can just kind of like be calmer about it?

• 13:24Speaker 00

  You can definitely be calmer.

• 13:25Speaker 01

  Definitely.

• 13:25Speaker 00

  Definitely calmer. But there is, there is certain things that you just cannot prepare yourself for. You know, I think like, you know, like it just in general, no matter how much you've kind of said to yourself, this is normal. You're going up and down, there'll be the odd thing. It will be employee related or product related, whatever. That will still surprise you. The fundamental thing that I think we realize that we've at least brought into this company is this concept of perseverance. Not blind perseverance, but perseverance. And I think there's a clear, there's a clear difference where if something logically makes sense, right? Like if you just, if in an unemotional way, you're approaching a problem and it logically makes sense, right? Then you should probably continue doing that thing, right?

• 14:08Speaker 00

  And not let anything stop you. And I think like the consistency that we've noticed that of founders that we've, some of that we've invested in or work with is like, the ones that kind of do that and really persevere tend to win. So I think that's probably the biggest learning for us, just persevere at all costs.

• 14:26Speaker 01

  Yeah, for sure. Uh, I mean, one of the big ones for me in particular is definitely hiring. I think when, you know, I was CEO of Fancy, I was twenty two, twenty three. So hiring was new to me and I think, to be honest, I didn't really have a clue what I was doing.

• 14:42Speaker 00

  We still don't.

• 14:43Speaker 01

  Yeah. Okay, then hiring is always tricky. I think one of the biggest things right now, and we say it a lot, like probably the biggest thing that comes up in an interview is, is how much do you think you enjoy working with that person? I think, you know, Fancy, again, being sort of inexperienced and maybe naive. It was all about where they worked before, you know, what's on their C V. And you kind of ignored the little things that, you know, that maybe you shouldn't. And now it's kind of the, the main thing that we look for, you know, we're going to be spending a lot of time with these people. You know, we work a lot and everyone on the team does. And you've got a lot of work with this person. So we often meet in person multiple times and make sure they're the right cultural fit. And it really makes a difference.

• 15:25Speaker 01

  I think right now, you know, we hire very slowly and we try and make sure we hire the right people. And it feels like we, we've got better at that as time's gone on.

• 15:34Speaker 00

  And humans are just so much more impactful now as well. So I think it's, it's just even more important than it has been before.

• 15:44Speaker 00

  And yeah, the other aspect that I said is work ethic. I think we, you know, I think we're known for it. I mean, right now. We're still working seven days a week, as we said, and we have done for about eighteen months. Um, and I think certainly in that initial period that you've got to do that. And I think, you know, our team work six days a week at the moment. Um, look, that may change, I'm sure, as time goes on, but I think part of that point about enjoying working with the person is they've also got to really enjoy what they do, right? So we started to ask more questions around, look, all the other sort of standard stuff that has to be done. I think it's important to have the kind of standard interview type structure. But are they going to enjoy their day today? You know, the question that we ask people is like, you know, what have they been building?

• 16:27Speaker 00

  You know, regardless of whether they're in engineering, right? As soon as they start to mention things like, oh, they've been doing a bit of vibe coding or this, that and the other. We're like, okay, they're going to enjoy what they're doing, right? And I think that's really important.

• 16:38Speaker 02

  It feels like there's a moment in a company's lifetime where it's suddenly it's working, but you haven't won the market yet. It sounds like that, at that time, it really matters to work hard.

• 16:49Speaker 00

  Yeah.

• 16:49Speaker 02

  Because like they're, you're not the only one trying to go after this market.

• 16:52Speaker 00

  Yeah, yeah. We just don't like losing.

• 16:56Speaker 02

  Maybe go back to like, uh, Winter Seventeen, Fat Llama. Tell us about Fat Llama.

• 17:02Speaker 00

  So Fat Llama was a marketplace that allowed people to rent items from people and then buy. But the main difference is, you know, you were insured. So if I let, if you're my neighbor and I lent you a camera, a $10,000 camera, I'm insured. If I lent you a drill, the same thing. That was what we did differently with the model. That model had been tried a lot of times before. But it still took us three years to find product market fit. I sort of defined product market fit loosely as, um, you know, the unit economics add up. People want, you know, uh, what you have in terms of product in a sort of relatively large addressable market, right? But it took us three years to get there. And I think that was, you know, we learned so much during that period. And so, yeah, that was Fat Llama and I can talk more about that in a second, but what about Fancy?

• 17:46Speaker 01

  Yeah, so fancy, again, consumer business. So we were a last mile grocery delivery business, which now everyone's probably bored of speaking about them, but back then, so this was end of 2019, start of 2020. So our model was a little bit different to a DoorDash or an Instacart. So we were what's called a vertically integrated model, which means we had our own warehouses, we held the stock ourselves. And this was relatively new in Europe. I think there was one other player doing it out of Turkey, but in the UK in particular, we are the first ones. And really it started it, you know, as a, as a delivery app for students. You know, I was a student at the time and it really came about the need, you know, I was really sitting there one day thinking, God, I could do with some,

• 18:29Speaker 01

  you know, Pringles or some beer, to be honest. And I didn't want to walk to the corner shop that was like five minutes away.

• 18:34Speaker 00

  And this was during Covid?

• 18:35Speaker 01

  So this was just before Covid. This was like, you know, three months before Covid. We kind of built the app MVP in sort of four to six weeks. I studied computer science at uni. And so it was just before Covid and really, almost instantly, as opposed to Fat Llama, we kind of found product market fit almost overnight, which is like, it sounds obvious, right? It's like you're delivering sort of beer, ice cream to students in-

• 18:57Speaker 00

  At the same cost as they would get it from the corner shop.

• 19:02Speaker 01

  So we took off and that was obviously really exciting. And then we got onto Y C and then Covid happened. Covid, you know, for our business was really that shot of adrenaline. I mean, Covid happened, everyone was staying at home, you know, the business really then started to take off. It was an amazing business. It's an extremely difficult business. I'm sure we'll come on to it in a bit, but we got hit with, we always like to say, a lot of cricket bats to the face. You know, a lot of stuff can go wrong. But it was awesome. So we continued to grow in the UK. We raised money out of Y C and then we got an acquisition offer from GoPuff, I think it was about 18 months after we started. And GoPuff at the time, a market leader, they were very, very big in the US and they wanted a, you know, opportunity to come into Europe and we were best placed for that.

• 19:48Speaker 01

  So it really was an incredible ride.

• 19:51Speaker 00

  Yeah, yeah. It was like, at least for that amount of time, it felt like the perfect kind of startup ride, I'd say. But again, I think Fat Llama was the polar opposite. The story I always talk about with Fat Llama in terms of perseverance was, you know, I was, you know, maybe very early twenties, obviously, and-

• 20:10Speaker 00

  You know, at that time, when you believe in something and you're raising a small angel round, so this is pre Y C, right, is, you know, we were raising, I think, maybe fifty thousand, maybe a hundred thousand dollars, which, you know, nowadays is like, I suppose back then, at least then it meant everything to us, you know, we were scraping around, we were doing half an hour pitches with an angel that might put in two thousand dollars, right? You know, we were just doing everything we could, we fundamentally believed in this idea. And anyway, so we built the MVP, we'd launched, and I started accounting, so I was big on like, yeah, other numbers are gonna make sense, right? So I had my like forecasted average transaction value, my retention, everything else. So we launched, and pretty much straight away, like, within the first day, we got a rental.

• 20:53Speaker 00

  And the rental was for six hundred dollars. So I'm like over the moon, I'm updating, one of the first things I did is I'm straight into the financial model, and I'm updating the average order value, and this thing is looking crazy, I'm like, we're going, we're going to the moon. Right? And so that was on Friday, it was due to be returned on Sunday lunchtime, right? And remember, the criticism I got, you know, I probably did a hundred pitches to raise money, and maybe one out of a hundred, you know, I must have done close to a thousand in the end, with T S, but all the other ninety-nine was like, no one's gonna lend out an item because everyone's gonna steal them. And even if you have insurance, the insurance isn't gonna work, right? Anyway, so we had, and that's all I'm thinking, you know, it's all we're thinking about at the time, so we had this first rental. Anyway, got to Sunday, and the lender of the item called us and said, I can't get hold of the borrower of this item.

• 21:37Speaker 00

  So, okay, it's fine, and then we realized after a couple of hours, like, he wasn't responding, and we started to get a bit nervous. One of the things we did, it was, you know, it was a native app, and it's when people search, because it helps with what you show in the search results, if we save, or we look at the latitude and longitude, so quite an accurate geolocation of the individual. So we had that. So I was like, okay, I'm going straight out there, we've got to go and find this item. And this was, this was like an eighteen hundred pound drone, right? So for us, this was like everything, right? So we went up. Anyway, so I arrived on this random street in North London, and there was just a door open to this house. I don't think we've ever told this story, because it's just like, it's that awful. And, and the door was there, door was open, I couldn't believe it, so I opened the door.

• 22:17Speaker 00

  There it was, the drone was just there on the side. So I picked up this drone, I got back in the car and I just went straight down to the to the lender's house. I arrived at the lender's house. But you've got to picture this, right? Is what's going through my head is everything that we've pitched, every person I pitched, family and friends. We had spent months, probably close to a year at this point, convincing people that this would work and they believed us and they believed Arnz and I and they bought into this. And so all I'm thinking is like, I've lied to them, you know, this is like my whole world was falling apart at this point. And so anyway, I arrived at the Boras house, uh, the lender's house rather, opened the door and he was like, hey, you're not the lender. And I was like, oh, I know. I gave him the drone. He was like, and you're wearing a fat alarm T-shirt. And I was like, yeah, we we delivered the item back automatically. He was like, this is awesome, man. Like, close the door.

• 23:03Speaker 00

  And so we, it did add up, you know, in terms of the insurance and we we focused on verification, but it fundamentally came to that that perseverance piece is like, we believe this is something that should exist and we believe from a tech, from a tech perspective, we could make it work. Uh, and it ended up doing so. Um, but yeah, it was tough.

• 23:20Speaker 02

  Both outcomes seems like really, really great though. Like it's like set your wealth for this company.

• 23:24Speaker 00

  Absolutely. I mean, Arnz did what the first 1,200 deliveries, I think.

• 23:29Speaker 01

  Yeah, I think, I think with Fancier, from the outside, it looks like a very fairy tale story.

• 23:35Speaker 02

  Everything like after the fact.

• 23:37Speaker 01

  Exactly, exactly. And they're like, wow, it's like, I should start a startup. And I was like, you should, but really it doesn't really, it's not all what it seems, you know, with fancy, we had so many disasters, uh, you know, and and so many times where we were like, God, is this really going to work? Um, you know, even when COVID happened, uh, you know, we had to stop delivering for for a couple of weeks. You know, there was a point, I remember, if you remember this sort of maybe two, three months into the company. Uh, so we were working with Stripe as our payment provider and one day they just shut us off. Uh, cause apparently there was a breach in in their terms of service, which later it was misunderstanding. But anyway, they shut us off for probably, you know, three or four days.

• 24:18Speaker 01

  Uh, bear in mind, we couldn't take any payments, right? And at this point, I can't remember how many orders we were doing, maybe not massive, but you know, maybe five hundred orders a week.

• 24:25Speaker 00

  We didn't have any inventory, so there wasn't a problem with that at least.

• 24:27Speaker 01

  Yeah, exactly. Uh, and so at this point, well, what do we do? We've got orders coming in, we can't take payments. Um, so we ended up just taking payments over the phone, taking payments with cash, taking payments with PayPal. Uh, and there were so many of these stories. And if you think of our business, you know, the amount of issues we had with delivery drivers, with warehouses, um. It really was an intense situation, but that's really what made it fun, right? I think, you know, building a startup, you just become so thick skinned and, you know, problems come about, you know, on a daily hourly basis and, you know, kind of your mood is like this all the time, but it's epic, right?

• 25:04Speaker 00

  On the payments one, we emailed Patrick directly and he responded, like within hours, he sorted us out.

• 25:08Speaker 01

  Yeah, it was awesome.

• 25:09Speaker 00

  So if Patrick listens, it's thank you, Patrick, he sorted us out. But I think on both of those, the, the general story is, and on, you know, the, the team delivered the first 1500 orders, right? And so, you know, ourselves, so it was very much a case of, you know, you hear, but we, rather than coding at night, we're coding during the day, because really, most of our orders were kind of in the evening, right? And, but what that meant was, we were speaking to a customer for every single order, all right? And so the, the customer feedback wasn't just like real time that you hear about, it was at every order, we knew what was working, what wasn't working, right? Which meant that, you know, when we started to implement drivers, you know, we always say that you just, you knew exactly how long it was going to take from the warehouse to

• 25:53Speaker 00

  that house, because you'd done the route about 50 times before. And I think across all three businesses, if you sort of set up and maintain the foundations of being incredibly customer centric, things tend to go okay.

• 26:06Speaker 02

  Yeah, there, there is a pattern though, with startups, like as they grow, they move the builders further and further away from customers. And there's a bunch of other roles that's in between and eventually, you kind of have to interpret the information you learn from customers. How are you going to avoid that?

• 26:19Speaker 00

  Well, it's, I mean, I mean, you speak to everyone, you can talk about on the product side, I think on, on the sales side particularly, because also we have a proof of concept phase still, right? So we still have a trial phase, which is this nice blend between kind of a, a sales stage, but also a pure customer feedback stage.

• 26:39Speaker 02

  Right, right.

• 26:40Speaker 00

  So naturally, and I, and I'm 100% involved with that and, and it's also what I enjoy as well, right? You know, spending time, you know, I don't like demoing on a screen, I like sitting with a user with a laptop, how they're going to work and working on the product together.

• 26:54Speaker 02

  Right.

• 26:54Speaker 00

  And that also is the best way we found to sell. But you're also doing customer feedback calls constantly, right?

• 27:00Speaker 01

  Yeah, I mean, you know, it's always a Y C mantra. I think you've got to speak and listen to customers. And that's really what we try and do on a daily basis, really figure out what are their pain points with using Model ML? What does their day look like? And then think internally, how can we then productize that and get that into their hands for them to try? And it's that constant iteration, right? We always say the quicker we can ship things, the quicker we can learn. And really, we want to try and stay as lean as possible. We always have this theory, we want to be the, maybe not the first, but one of the first 10 person billion dollar company. And it's just about staying so close to the customer and in the details.

• 27:38Speaker 03

  Y C's next batch is now taking applications. Got a startup in you? Apply at ycombinator.com/apply. It's never too early and filling out the app will level up your idea. Okay, back to the video.

• 27:52Speaker 02

  So during Y C, we have this group of a server topic where we talk about what motivates you to build a company. And it's mostly to surface the motivations for founders and their co-founders. So when things are really tough, you know why you're there. Do you guys remember what was your initial motivation when you started the first two companies and then maybe what it is today?

• 28:13Speaker 00

  You know, when we have our one to ones, we're not brainstorming how to raise money. We're brainstorming actually how we can do this for the rest of our lives because it is so rewarding. You know, building something for individuals, making money, I think, you know, it just gets boring so quickly, right? You know, it's not, it's not really that motivating, you know, whereas building something that makes people smile. That's very impactful and a lot of people are using it. That's just so motivating to us. And I think like that really has been the story across all the companies. You know, I think what's been nice about this and surprising about this is we questioned ourselves going from a two consumer brand heavy type businesses into a B two B. But actually, particularly in the world of A I, the most important element is like the B two C element.

• 28:59Speaker 00

  And that is to us the most rewarding element. Like when you do a demo to someone or they click run and they do something.

• 29:06Speaker 02

  It is just, there's no money that can buy those moments. Because they've never seen that before. They've never seen before. They've never seen it.

• 29:12Speaker 01

  It's like with our previous companies with Fancy, when you would be at the door with their delivery, sort of ten, twelve minutes after they ordered it, and then you saw their face, like, what the hell's going on? You're already here. Uh, like Chad said, you just, you know, it's priceless.

• 29:25Speaker 02

  I've noticed this with AI products, that they, often the customers cannot even imagine what the solution will look like. Hmm. Uh, because the models are so good and they're so advanced right now. Hmm. And very often, um, you just have to build, like, you build it for them first. Like, you can't really figure out, try to figure out what the problems are, because like, it's not a specific problem you're solving. It's just like, it's like a whole other, like, in a whole other league of solutions.

• 29:48Speaker 00

  Yeah, and, and, you know, the difficult thing as well is you, you do have to rethink things slightly from the ground up.

• 29:54Speaker 02

  Hmm.

• 29:54Speaker 00

  So I, I do think that, you know, at least as of today, if our product, we made it, we made a call that we would kind of rebuild our version of like PowerPoint, Word and Excel, because we, we do believe, at least for the time being, that the way in which people interact with technology, regardless of, of type of technology, will remain quite consistent. In other words, like a long-form document, a storytelling presentation and tabular across Excel, Word and PowerPoint. We think that will stay the same.

• 30:22Speaker 02

  So you're not trying to get people to change the current?

• 30:24Speaker 00

  We're not trying to get, because we just think that that's what people are very used to. However, we think what's, if we look at what we're seeing this year, a lot of what's happened up until now is sort of humans are still coming into these systems, and they are like clicking run on something, basically, right? We think the biggest shift this year is going to be that even that element won't happen. And therefore, elements of the user interface, we think will be less important. In other words, these, these tasks will happen entirely autonomously. You know, as you arrive in the morning and the things that you would normally have had to go and trigger and click run, they will already be there, they will already be done.

• 31:03Speaker 02

  Right, right, right. You guys are siblings. Um, historically in Y C, we've known that this is a pretty good recipe for a good co-founder relationship. Tell us, I mean, you've been co-founders of multiple companies, you've had other co-founders too.

• 31:14Speaker 00

  Hmm.

• 31:15Speaker 02

  Like, tell us what you've learned about the most important thing. And, and maybe like for the audience of founders who are thinking about founding a company, like, what should I be looking for in my co-founder? And like, what's important and what's not important?

• 31:26Speaker 00

  I think.

• 31:27Speaker 01

  We mentioned it previously around hiring. I think this is sort of tenfold when it comes to your co-founder. You know, you're going to spend so much time with this person. You know, more time that you spend with your family, with your partners, with your friends. So I think first and foremost, is that person someone that you want to spend a lot of time with? You know, obviously. We're still not sure. Yeah.

• 31:53Speaker 01

  I think if you were not sure, you wouldn't say that. Yeah, exactly, exactly. Otherwise it would be really awkward. It would be really awkward. So, look, you know, we've always had a really good relationship. I think not all brothers working together, I think, is a good idea. I think, you know, we've been fortunate enough. We've always had a good, you know, personal and working relationship. One of the things that makes things really easy, I think, is, and again, not all siblings are like this, but there's no filter between us. You know, we're very transparent, we're very honest. And I think, you know, with your founder, you need to be exactly that. You know, there can't be any miscommunication, lack of communication. Like, we all know one of the biggest reasons, if not the biggest reason, why, you know, startups fail is founder fallout.

• 32:35Speaker 01

  And I think with us, we're always very good at, you know, communicating, trusting each other.

• 32:40Speaker 00

  Another thing on the trust piece then is the way that we describe our Venn diagram. You know, I, I think I'm an engineer, but I'm not actually an engineer. I think I am. Arnie studied computer science, I studied accounting. So our Venn diagram, and I think if you're thinking about another co-founder, I'd really consider this, is Arnie obviously handles sort of engineering products and I handle kind of finance commercials and products as well, kind of in the middle, right? So the overlap in our Venn diagram is basically customers and product, right? Which we think is just like the most important piece anyway, right? And that bit we both really enjoy and we love, but we also love all the other stuff.

• 33:21Speaker 00

  And I think like that clear segregation of duties and interests from day one, I think is really important. So I think one of the things that we think, that we look at is I really emphasize that point of interest. Because actually, you may, like, for example, Arnie may have studied CS, I may say, but if I, if I really am interested in wanting to basically do Arnie's job and write the bulk of the production code, then we've probably got a problem. You know what I mean? And so I think it's like, really think about that. And, and, and that tends to last for a long time as well.

• 33:53Speaker 02

  I got this email, I think it was yesterday, from a person who was in their early twenties. They were basically asking me for not startup advice, but life advice. So what do I do? I'm like twenty one. And I think he was writing something along the lines of like, I know I can go and build something B two B. That's quite narrow in AI, but it doesn't seem to motivate me enough. I want to build something much bigger, like when I have a bigger impact on the world. Like, if you got that email, if you would give him advice, like, what would you advise someone who's in their really early twenties or in school? And they're thinking about their career right now, or maybe in the world of AI. Or they're thinking about starting a company, but want to do something big, like, what would you tell them?

• 34:30Speaker 01

  I think we're probably biased because, you know, we probably favor starting a company before going to work at a, you know, a big corp. I think first and foremost, we'd be very honest with that, you know? As I mentioned before with our fancy story, you know, you look from the outside and it might seem like, you know, sunshine and rainbows. But it's really hard, you know, building a business is, is really, really, really hard. It's really fun if you enjoy that stuff, but it's really hard. So really, you've got to say to yourself, look, you might be building a business for the next five, 10, 15 years. They might not go anywhere, and you've got to be okay with, you know, that reality. And ultimately, you've got to be very passionate about what you're building.

• 35:14Speaker 01

  You've got to have that perseverance that Chad spoke about earlier. And if that sounds good to you, then, then build a startup. And if that doesn't sound good to you, then, you know, I'd probably recommend probably getting a, you know, a job somewhere else. And then develop over time. And then if you feel like you're more ready to jump into the startup world, then do that.

• 35:33Speaker 02

  So maybe if you're, if you're a builder and you enjoy seeing your stuff in people's hands, the smaller the company you work for, maybe you're even your own company. The faster it gets in the customer's hands.

• 35:42Speaker 01

  Hundred percent, and, and enjoying that. I don't think that another like different way to look at this is, is, you know, think about, I know it's maybe slightly more, but is that the, if that's the correct word. But, you know, if you're lying on your deathbed, you know, and you look back at your life, like, what do you, what do you want from your life? And I think we, we do that a lot. And basically, you know, what we conclude is, we just, we just want to have been impactful with our time. You know, we want to, you know, you know, left the world a better place, but, but, but in a way that we've just built things that people enjoy using. And, and I think that's really what motivates us. But I think really that one point of.

• 36:19Speaker 00

  You know, you've really got to enjoy the journey and we just, we just love building.

• 36:23Speaker 02

  It sounds like if you were in his shoes, you would give yourself basically the advice to the path that we ended up on.

• 36:28Speaker 00

  Yeah, go all in.

• 36:29Speaker 02

  You wouldn't change anything.

• 36:30Speaker 00

  Go all in, go all in, like all in. And I think if anything, uh, more is more in general.

• 36:36Speaker 02

  I remember when I met with Paul Graham sometime around the beginning of the batch and I was doubting whether it just doesn't work out. Like maybe my career is fucked. And he was some, he said something like, well, if you're 26 and you're poor, uh, that'll be the worst outcome. And probably most 26 year olds don't have any money anyways. Does it make a big difference?

• 36:53Speaker 00

  Yeah. It's also just like, the way I describe it is like, well, the worst case, like the very worst case is you're, you're going to learn so much over such a short period of time. And that is the worst case. Cause often when you compare this to like, you know, uh, we often now, when we're, we're hiring people, we talk about their opportunity costs, right? I think a lot of the time, if you take a step back, those jobs or those roles, they're still going to be there in a year's time, right? So like the actual worst case is you've just learned a lot over a year. And I think if you frame it like that, then a lot more people would just get out and build stuff.

• 37:28Speaker 02

  And a lot of people that end up on these tracks, um, they sort of like five years into investment banking. It's hard to step out of that.

• 37:35Speaker 00

  Super hard.

• 37:36Speaker 02

  But like, it's just the risk that you want to take, you want to take early on because it's just like much harder to change when you're 30 and you have commitments and.

• 37:43Speaker 00

  Definitely. Way harder.

• 37:45Speaker 02

  Yeah. When you're hiring people, people that come from finance or quant backgrounds, are there things that they have to unlearn about their job? Either about the company they're working for, about the industry in order to work for a tech startup, serving the same industry?

• 37:58Speaker 00

  First principle thinking, eh? They've just got to move faster. And again, this is probably more your realm than mine, but what we notice is, you know, we'll ask someone to do something and well, they won't, but they will try and, you know, spend a day, two days putting together some sort of presentation, slide deck. And we're like, what the hell's going on? You know, uh, you know, we need this now. So it's things like that where you get, you know, caught up in the.

• 38:27Speaker 01

  I guess the big company thinking, which makes sense in certain environments. But when you're working in a startup and you're wearing so many different hats, frankly, there's no time for that. So we really try and from day one, I think you in particular, really try and say, look, we need this now. Instead of, you know, all these spreadsheets and slides.

• 38:45Speaker 00

  I think that is the first lesson. It's like everything that you have learned for five years, try and unlearn immediately. I think just in a sense, it's different. You know, you've just got to, yeah, you've just got to move so much faster. I think building the plane going down the runway is the best way to describe things. You know, I think, you know, that is the quickest way to learn. It's different when you're, you know, where are now it's different. You know, the business, you know, we have large customers in production. That can't be the case. But in terms of like the way that you think or the way that you go about your work, the fundamentals, you know, still need to remain the same. You know, we are big on this first principles thinking, which I know is very much a terminology that is overused, but I think in general,

• 39:29Speaker 00

  that way of looking at the world is a better way to build a company.

• 39:32Speaker 02

  And you guys chose to do Y C three times. Can you describe sort of like your thinking here?

• 39:38Speaker 00

  The second and third time, it wasn't a financial thing. We still get asked, like still, we've had loads of teams that, you know, people that work for us that have gone on to even start Y C companies or gone on to build some great companies. And we still get asked how we managed to maintain that. And I quote, Y C culture throughout the life cycle of the company, right? And so the way I sort of answer this is you cannot replicate that. You know, I remember very clearly Michael Seibert on in 2017. You know, the first office hours we had, you know, a young English lad, you know, we report on our numbers. And I reported monthly. And I remember Michael being like, what the hell are you doing?

• 40:22Speaker 00

  Like, let's start weekly, if not daily, if not hourly. And I think that culture never leaves a company, all right? That's the fact. The second aspect, which definitely cannot be overlooked, is the instant support network that you get. You know, I think us being from Europe, working seven days a week, it's very unusual, to say the least. And there's not many people that we can call on. And in fact, a lot of the people that we surround ourselves with outside of work. They fundamentally disagree with the way that we work and how we're building and why we're building, particularly when we don't need to from a financial sense, right? I think that's Whereas in the Bay Area, you know, particularly and driven by Y C and through Y C, you get this like instant network that you just you cannot get anywhere else.

• 41:07Speaker 02

  And you ended up being in the batch with the twenty four, which was sort of like one of the first really big A I batches where most companies were building companies similar to you. How did that feel? Like, was there something like just being in the Bay Area like eighteen months ago?

• 41:22Speaker 01

  I mean, it was just crazy. I think I think, again, working side by side with people building really cool products, working seven days a week, and that buzz, you know, around the office, around San Francisco, it's really, really hard to replicate. And we absolutely loved it, didn't we?

• 41:39Speaker 00

  Yeah. And it's like, it felt, it's interesting you mention that because that really was, that was like the first batch where it was like through and through just, you know, A I companies pretty much. And like, it felt like in that Slack group, didn't it? It felt like almost daily or hourly, that was like a scientific breakthrough. It was like phenomenal spitball.

• 41:58Speaker 02

  One question I get, I was in Munich and then I was in Zurich on a trip recently. And I was in London. I saw you guys. I was in London a year, year and a few months ago, is from European founders is where they should be based and where they should build in their companies. And I don't have the right answer. It's a controversial topic. You guys are based in London. So, but I'm curious what you think, like, as you're thinking about this question.

• 42:19Speaker 00

  Go on, Len. Go on, Len. This is a tough one.

• 42:24Speaker 01

  It's tricky. I think we absolutely love San Francisco. We've said it many times. Every time we come here.

• 42:32Speaker 00

  It's the best place to work.

• 42:34Speaker 01

  There's something different about it. And we always thought, you know, being from the UK, this San Francisco buzz, Silicon Valley.

• 42:43Speaker 01

  It's a bit of a myth, at least that's what I thought growing up. And then I think what was interesting with with fancy, we were a remote batch, right? So we didn't come to San Francisco. And then when we came here again for for Model ML's batch, just being in San Francisco and being a part of the community, it was crazy. You know, Chad always tells a story when, you know, you're at the gym during the batch and you just had people on the treadmill on their laptops, you know, on Zoom calls, you know, talking about funding rounds and X, Y and Z. And in the UK, that just doesn't happen. Clearly.

• 43:17Speaker 02

  Clearly.

• 43:18Speaker 01

  So we love the UK.

• 43:21Speaker 01

  If we were to start a company again, I mean, we're trying to convince people to move to SF for this company. We think it's an incredible place to build a company. And like we say about work ethic, it is really challenging, we think, in the UK in particular, to find people who frankly want to work this hard. I think in San Francisco, it's a lot more common. I think in Europe, it's just not. One of the positive things about Europe, and we always said this, is is talent and particularly engineering talent, which might sound counterintuitive. I think you've got amazing engineering talent, you know, in the Bay Area. The problem is, it's very, very expensive and the competition is just so, so high. You know, you're going up against.

• 44:06Speaker 02

  You end up hiring from your own network anyway. You're trying to bring people over from the UK.

• 44:09Speaker 01

  Exactly, exactly. Whereas in the UK, I think the level is still really, really strong, but the competition is less. So your ability to hire that top class talent, I think is probably stronger in Europe.

• 44:23Speaker 02

  It's a good question. If you're based in Europe, you I mean, give you advice, okay, if you decide to stay in Europe, try to move to one of the few cities where there are other really ambitious people.

• 44:32Speaker 01

  Definitely.

• 44:32Speaker 02

  And there's just not that many of them. London is one of them, but Europe is not one country. So it's like a big culture shift to to or maybe not big, but it's a big change to move from, I don't know, Spain to to London. It's not that big of a difference to move from Spain to San Francisco.

• 44:46Speaker 01

  Yeah. And I also think, as we spoke about our hiring process earlier.

• 44:51Speaker 00

  You've just got to be really rigorous with your hiring process. You know, there are amazing people and amazing talent in these cities. You've just got to find them. So I think don't settle for second best. You've really got to find those people that are self motivated, hungry. Chances are they know about Y C, they've got the right attitude. And I suspect a lot of your customers in the U S. Pretty much all of them, I'd say eighty percent of our customers are U S. How do you handle that? Well, I spend the bulk of my time in New York and spends the bulk of his time in London. And then kind of split between Hong Kong and San Francisco. Interestingly, actually, for finance, as I mentioned this when I came in earlier, there's a surprising number of decision makers for global firms around sort of technology implementation in San Francisco. It's not out of New York or out of London, it's out of San Francisco.

• 45:37Speaker 00

  So I think if we'd known more about that, you know, back when we made this and to move the engineering teams to London, that would have influenced things. But yeah, my view for what it's worth is I think people should do what it takes to move to San Francisco. If that's not possible, that's not where your customers are based. At the very least, as you said, move to a tier one city and try and be as close to, you know, folks that are also building stuff. Awesome. Thank you so much for coming. It's great to see you guys. Yeah, great to see you again. Yeah, thanks very much.