Speaker 1My parents told me that I must get to the United States because this is the place where technology matters. By the age of 19, I was able to get to top three in the world in competitive programming. Actually, it took us 18 months from $1 million to $1 billion. For Coursera, it took 24 months. On average, at Hicksfield, a person on the team spends over $10,000 a month on various models. So internal usage of models a month is over $4 million. I just caught a guy who spent over $30,000 in a week on Astro Model. Many people spend over $10,000 in a week. Hicksfield, this is the story that no
Speaker 2one has told in startups yet. The company has just hit a billion dollars in revenue. It is the fastest growing company in consumer land to hit this milestone. It even surpassed Coursera. And guess what? The travesty. No one has covered this story. This company is built with 300 people out of Kazakhstan. It is a complete anomaly. And you don't know about it. Alex, the founder, is an incredible genius. One of the most talented computer programmers competing in competitions from a super, super early age. And then building a company that he sold to Snap for over $160 million. Now, Hicksfield, rumored to be raising at an $8 billion price, has just crossed a billion in revenue. This is the story that you don't know that you need to know. But before we dive into the show today, founders face a different set of challenges at every stage of growth. For Sid Shate, co-founder and CEO of D-Matrix, JP Morgan delivered the guidance and expertise to help navigate what came next. He credits JP Morgan's high-touch approach with supporting D-Matrix as it grew and expanded internationally. Whether you're in the early days or expanding into new markets, JP Morgan helps startups navigate complexity with real confidence, offering personalized guidance, and deep sector expertise. Find out how JP Morgan helps founders at jpmorgan.com forward slash grow without limits. JP Morgan is the bank of the innovation economy. While JP Morgan supports growth, Corgi protects it. My word, what an arresting first line. Get your ass covered with Corgi insurance. And I'll tell you why. If you're running a business right now, you already know this pain all too well. Getting insurance, it's really slow. It's confusing. And my word, it's full of paperwork. Well, that's exactly why Corgi is here to change the game. Corgi is the first and only insurance carrier designed specifically for tech companies, allowing you to get covered in minutes instead of days. Corgi provides essential coverages for all growth stages, such as DNO, E&O liability, cyber, commercial, general liability, and more. Get your ass covered. I love the way we say ass with Corgi insurance, alongside thousands of other startups at corgi.com forward slash 20VC today. That's corgi.com forward slash 20VC. You won't regret it. While Corgi covers risk, Flex gives you room to move. Business owners run their whole financial life on Flex. One platform from business revenue to their personal spend. Float every purchase for 60 days. Tap capital that grows with your revenue and pay vendors in 170 countries across 32 currencies. Plus the whole back office bills, expenses, accounting, accounting all in one place. So you spend less time reconciling and more time growing. That's why thousands of owners use Flex. Named one of Fast Company's most innovative companies of 2026. Visit flex.one, that's F L E X dot O N E and use the code 20VC. You have now arrived at your destination. Alex, I am so excited for this dude. We were talking downstairs and I said I don't think the Higgs field journey has been told before and it's an amazing journey. So thank you so much for joining me today.
Speaker 1That's very special opportunity for us. Thank you for having me. Obviously your story is inspiring as well. Like how social media has become like an elevator for your opportunity to create fun and so on.
Speaker 2It's very kind of you to say I do just want to go back there because you're not the Stanford Silicon Valley born and bred engineer. You were a competitive program in Kazakhstan. And you just take me back. How did you first find and fall in love with computers
Speaker 1and become a programmer so early? So first you need to understand where I come from. So my father is from Uzbekistan. Uzbekistan is a country in Central Asia where like if a family of five people makes $1,000 a month, it's considered to be wealthy. It's like not very high standards of living, unfortunately. But both my parents are professors of mechanical engineering. And since I remember myself, since I was eight, my parents told me that I must get to the United States because this is the place where technology matters. So mother had to work three jobs because basically my education was to compete in programming competitions all the time and to go to various educational camps where I could learn from the best, like certain data structures, algorithms and so on.
Speaker 2Can I ask you a question? Did you feel pressure as a child competing, being pushed into these environments when you are?
Speaker 1So young? Absolutely. And I'm very grateful to my parents that they showed me the path really from that early on. Definitely when you come from this part of the world, think about post-Soviet countries, India, China, like getting to the top of the rankings in any competition in any international competition is the only way to really break out. So by the age of 19, I was able to get to top three in the world in competitive programming. But then instead of pursuing like an academic career, I decided to do
Speaker 2start-ups. I'm sure your parents were thrilled. Can you take me to that decision? This is like the penultimate moment. You've worked 19 years for your parents have told you this is like the mother load. This is the thing. And you're like, I'm going to go and do this really risky thing called a start-up at this point.
Speaker 1What happens then? So let me take you back to 2014. I was very fortunate to work on pre-transformer architecture, neural nets, and I was primarily just doing optimization, make it run faster, parallel across multiple machines and so on. And we actually build state of the art system for language translation from English to Russian and Russian to English. Apparently, talent wars were a real thing even back then. A lot of my teammates were hired by DeepMind and Meta. But my passion was actually different. I was very, very surprised to learn when I come to SF for the first time how quickly Uber actually spread out. And I was thinking if this app can take over the world so quickly and transform the whole industry, maybe what's going to happen is that mobile phones are going to become the most used devices in the world. Maybe there is going to be a version of the future where everyone is going to be spending most of their time in their life watching AI generated videos on the phones. Because who else is going to produce videos for the phones? Maybe it's going to happen with AI.
Speaker 2Okay. And so that was the company that we built before that you sold to Snap.
Speaker 1So yeah, so the company was called AI Factory, was fortunate to meet my company in 2018, he's co-founder of Hicksfield, and he's a veteran of Silicon Valley, went through ups and downs and sold it to Snap for $166 million. Then I was leading Gen EI there.
Speaker 2Pause. No offense, dude. You come from a family of incredibly ambitious parents who push you to do well, and you just skip to the moment where you sell for $166 million. It's a lot of money. How did that feel when you did it?
Speaker 1We both remember these times where the capital for AI companies was not really that much available, and AI multiples were not like $200 to revenue as they are today, but closer to zero because AI was not a topic. So there was like severe dilution, which we experienced just to calibrate. But what was the round? No, look, I mean, back then, rounds of like $1-2 million, having like $1-2 million in investments was considered to be really good. But it was still an opportunity for me to finally go to the United States. So after the acquisition, I permanently moved to first to LA and then to Silicon Valley, and my dream simply came true.
Speaker 2Was it what you thought it would be?
Speaker 1That's a good question. So San Francisco is definitely a place where no one judges by race, nationality, and so on. That's truly phenomenal. There is definitely a meritocracy in a sense that it's possible to meet anyone. But in the same time, what I see across Silicon Valley investors, it's extremely consensus driven. I think that last part, I expected to be different. But then I read the book about the law of capital, and I realized this is just how the world works.
Speaker 2So then we have sold to Snap. We're now in the US. This is the moment you wanted. How does Higgs field come to be?
Speaker 1Back then, like Snapchat 2020 was really growing so quickly. And the phase filters, which my team has built, was driving most of daily new users. What's important is that these phase filters, we were able to manage to run on mobile devices, so it was virtually for free for Snapchat. It's not like current LLM tokens costs. And it scaled to hundreds of millions of people throughout the world. And it was truly phenomenal to me to build a product, which is still probably the most used consumer media product. But then what I realized is that there are a lot of unmet needs on advertising sites. Average company cannot figure out how to be relevant on social media. And this is a major gap. Like social media is the main media in the world. lots of companies are actually able to build direct response advertising so that they can actually sell more. But in the same time, most of the companies in the world cannot simply do that. And basically, because no one simply can keep up with the pace of production for social media as trends change pretty much every day.
Speaker 2And so you were like, hang on a minute, these big brands aren't able to have media houses. And so we need to create a tool that lets them. That was the sell?
Speaker 1Yeah, absolutely. So where it all really started is that there was a tool like to upload set of images and transform them into a slideshow with music. It's kind of better than nothing, but still pretty bad, right? Another solution was to take long form video and cut them to short, vertically oriented videos. This was better, but still really not perfect. And it felt to me that, especially 2023, it was absolutely clear that scaling laws finally work. It's not just a concept from science that scaling laws work. Video just takes maybe two or three years longer than LLMs and videos. And so it's not just a concept from science that scaling laws work. But it was clear that finally scaling laws should work in video as well. And I just decided just to take a bet. But I just want to go back.
Speaker 2I get that in terms of what we see, which is, hey, we want to empower these brands and companies to create amazing media for social media. But it wasn't a hit from day one. And I spoke to Amy at Menlo, who mentioned like a couple of pivots before and the meandering that we had. So what happened when we launched? Did we have immediate product market fit?
Speaker 1No, actually, we started to see a lot of sales. We spent more than a year in a search of a product which could work. We burned more than 10 million out of 16 million raised in seed fundraising. So we felt we have just one attempt left. And frankly, I feel I am responsible because I was focusing on the wrong things. I think I just lost the touch with reality back then. I was so much optimizing for what's hype the right narrative, how we can hijack the attention, all these things, really everything instead of building a good product. So when we had less than 6 million left, I guess it was slightly less than five, actually, I realized that the only thing which we can be focused on is to lean into the product PLG and just finally set belief that the best product is going to win. And then we just started to talk to customers. We spoke to eight creative directors about the product, and they were like, "Oh, yeah, we can do this." And we were like, "Yeah, we can do this." And they were like, "Yeah, we can do this." And we were like, "Yeah, we can do this." And we were like, "Yeah, we can do this." And they were like, "Yeah, we can do this." And we were like, "Yeah, we can do this." Everyone told us that camera control does not exist in AI. And camera control is so important to tell a story. So this is a very important bottleneck to solve. So we released our products March 31st last year. And since then, we are really riding this crazy wave. Was it immediate product market fit then? Like, yeah, it was immediate.
Speaker 2Is product market fit like love? When you know, you know.
Speaker 1Yes, it's definitely when you know, you know. Like, for example, we don't do any paid. And like, we have on the team, people who scaled businesses to over like billion and two billion in revenue, like other businesses, with paid advertising. At Hicksfield, we decided to really make a bet. You don't do paid? We don't do paid. Is influencers not paid? That's a good point. So with influencers, there is typically, there are different types of influencers. But typically, there is some fee for just video production. And then like some cost per click, like attribution, which is like works really well on YouTube.
Speaker 2You guys got into some controversy for like, I can't remember what it was, you were like, paying people to promote for you or doing something rogue with influencers. Was that completely unfair? Was it kind of my bad we did we did do that? How do you respond to that?
Speaker 1Look, I think the main takeaway from like our experience is that it's very important to own your content. And I think the main takeaway is that it's very important to own your content. And like, we basically did outsource, we had just a team of like two people on creator and customer success sides. And we just did outsource to the agency. And this was not, that was not a good experience. I do just want to go back to part of the story. Where are you at revenue wise today? So today is actually exciting day, like when we record just Bloomberg article went out. So that's we cross 1 billion in annualized revenue.
Speaker 2If I had a gong here, I'd be like hitting the gong. A billion in revenue.
Speaker 1Yes. Actually, it took us 18 months from 1 million to 1 billion. So we are probably, probably like the thirds after opening the Ion Anthropic.
Speaker 218 months from a million to a billion? Yes. How do you calculate revenue? It's a controversial topic.
Speaker 1Absolutely. By the way, your co-host Jason also asked this question in May. Luckily, answer didn't change. So we are at least consistent, but so let me be transparent on that. What we do is we look revenue over the last four weeks and multiply it by 13. From what I know, open the Ion Anthropic, Cloudable, all of them use the same methodology. What's very important is that we take revenue, not sales. So if that's like annual subscription or annual enterprise contracts, we actually prorate this across 12 months and only take like a piece which corresponds to one month, to 28 days to be precise. That's the first piece. And second, it's only live revenue. It's only live revenue. We are not taking like three-year enterprise deals and baking into like 1 billion figure. No, we don't do that. If you were to
Speaker 2break that billion up today into annual contracts, monthly subscriptions, and then token spend, what would that be?
Speaker 1relatively early. It is still probably two years behind coding in terms of adoption. So on-demand usage for leading coding companies could be over 50%. And I would be honest, for video, it's substantially less than that. In the same time, what's very interesting for us to observe in the business is that there is significant revenue expansion. I always love to study stories of the largest customers on the platform. So one customer started six months ago, spending just subscription $99 a month, $99 a month. And now we just signed a deal over $6 million. $6 million? $6 million a year, right? So this level of acceleration is something which really mind-blowing to me. Dude, what are they getting for $6 million a year? That's like a Hollywood content team, almost. So there are multiple trends, and all of them, frankly, coming from Asia. So for us, we're seeing a lot of direct-to-consumer e-commerce companies rebuilding their whole go-to-market to be AI-native, where they just make hundreds of ads, if not thousands a week, where they can A-B test what performs well. But we all know about short-form dramas, right? Short-form dramas today is an industry over $10 billion, owned primarily by Chinese companies, having huge impact both in China, United States, and Europe, everywhere in the world. And most of, I think, all the new shows there are made with AI end-to-end. So look, I think this adoption, obviously, is coming like bottom-up, but that's very difficult to refute this new reality.
Speaker 2What percent of revenue is consumer versus enterprise?
Speaker 1So that's a great question. So business revenue is slightly over 50%. Wow. Yeah. On the consumer side, it's also very important to break it down. On the consumer side, out of this 50% is around like 10% is pure consumer use cases. Pure consumer. And that's roughly people who use it on mobile. So share of our revenue from mobile is less than 10%. We are very different from many other companies. But there are lots of aspiring creators, like basically those people who are freelancers doing social media marketing projects and so on, who try to learn video AI so that they can make more money. It's true that their behavior is a little churny. Within a year, most of them actually come back to try again. And we do believe that over the time, most of them are going to figure stuff out and they're just going to become this new AI-native workforce. So it's still important for us to educate them. That's why we invest so much in like Hicksfield Academy, YouTube channel and so on. But we also are fully cognizant that we will never be able to win in a market of subscriptions of $20 a month. Why? Because I think like today, Google and OpenAI, they pursue like ads so much. But fundamentally, I think they are going to completely demolish all their prosumer subscription markets, which is $20 a month subscriptions.
Speaker 2Oh, so you're saying that because they provide a horizontal product that's very good, you're just going to not pay for a lot of the verticalized products that you used to pay $20, $30 a month for?
Speaker 1Yeah, I do believe that. That's essentially what's going to happen over the time. I know this is a very contrarian bet, but at least we can see some of
Speaker 2So you're saying it cannibalized Canva's growth, if you're honest, a lot of the low hanging fruit on the consumer design side, that Canva used to serve, can now be done in OpenAI in particular. Is that what you're talking about?
Speaker 1Yeah, and I do believe this is just the most apparent example, but there are a couple more which is already happening. And I do believe that that's why for at Hicksfield, what really matters for us is how we even if we get someone on like $20 a month subscription, how can we show them value? How can we make them to upgrade? to spend over $1,000 a year
Speaker 2us. I can't believe that's $6 million a year from $99. That's the best ever slide on a fundraising deck. And all of our customers are going to do the same. Exactly. Can I ask, you mentioned that kind of churn rates. When you look at 30-day retention rates for consumers and 90-day retention rates, what are yours and what is good?
Speaker 1So there is quite a massive drop within the first month, just simply because people don't fully realize the value. That's a core priority for us to actually get better in that. So showcasing the value. Is it like half? No, it's maybe like 30% drop. Okay. But then it's really flat after that. We look obviously at logo retention. I wouldn't say it's great, but because we all remember B2B SaaS era, retention was expected to be, logo retention month one was expected to be over 80%. So clearly we have a lot of work to do on user education to get there. But some things are truly phenomenal. When I look at the business segments and NRR at month 12, obviously like you're going to argue it's like 18 months old company, like what are you talking about? But still, when I look at the numbers, which I have today, NRR at month 12 is over 300%. It just never happens in B2B SaaS, right? So that's why I'm saying that while there is substantial churn in month zero, and we have to do a better job with user education to address that, expansion is unprecedented.
Speaker 2Can we actually just unpack, right? Yeah. So I think that's a really good point. I think that's a really good point. I think two different go to markets, because you got consumer and you got enterprise. And I spoke to quite a few of your competitors in all honesty before this show. And I said, hey, you've got Alex coming on, what should we ask him? Everyone said the same thing, which was an admission of their respect for this particular kind of GTM. They said, you've executed the most impressive influence on a campaign in tech. And what I wanted to understand was, when you look at the consumer growth, what worked, what didn't work, and how do you reflect that? And I think that's a really good point on that.
Speaker 1So first and foremost, like the goal is to make sure that the best commercial video content is generated on Hicksfield. And we show all the workflows of how to make such professional looking videos. And we have an in-house team of over 150 creative professionals, 150. It's almost half of the whole work workforce, frankly. And those people, they make a product launch videos, they make tutorials. For example, we made the first AI generated movie, which is also obviously a very sensitive topic. But what's important, we open sourced all of it. And what we learned is that for 90 minutes of, let's say, TV quality content, it was over 100 hours of AI generated content. So creative decisioning, picking the right piece is still very important. So that's really what we are focused on. And that's what's driving most of the revenue.
Speaker 2So you're saying the growth in consumer subscription is through own content and distribution.
Speaker 1Yes, we don't do any paid.
Speaker 2Early on, you made an interesting architectural decision to have your own models. And then you since walked that back. Can you talk me through why did you choose own models? And why the walk
Speaker 1back? Oh, yeah, obviously, this was obviously this was my mistake. I'm gonna be I'm gonna do my best to be transparent. What I need to admit, at some point of time, I really was thinking that chasing benchmarks, is valuable. But I don't believe this is just sort of corporate psyops. Frankly, I was part of the large organization. So I know what happens. What happens is that everyone just thinks, like, we need to show some progress. So we need to have some benchmark. But then when I talk to the top researchers from these labs, especially larger companies, what happens is that they start to put test data into the training, they start to kind of use leverage test data to use LLM as a judge for training of the models, use all the various tricks to basically gain benchmarks, get like quarterly bonuses, and so on. That's like, who cares, right? So if I make my couple million dollars a year, and not in one of these labs, I can move to another lab easily. So that's unfortunately, what's happening in larger organizations.
Speaker 2And then can I just stay on that? Yeah. What do you mean, you're saying that they are incentivized by benchmarks. And so because of that, they are doing artificial things to improve their scoring and benchmarks, which actually don't increase output efficiently.
Speaker 1Yeah, look, I think let's just look at the outcomes, which we have today. Out of all the incumbents in the United States, when I look at open router data, the only company which is relevant is Google, out of all the incumbents. When I look in China, where probably obsession with benchmarks probably is less, we have Tencent, Xiaomi, Alibaba, three incumbents being completely relevant. And obviously, like ByteDance, obviously trying to catch up as well. What's your takeaway from that? I just do believe that there is just obviously in the tech bubble, there is a strong obsession over the benchmarks, which do not necessarily represent the reality. But I can talk specifics specifically for video. A lot of benchmarks today for video is really text to video, which does not represent actual workflows at all. The way to think about video models today, it's just modern rendering engine. Think about this as like Unreal Engine or Unity, but just different types of inputs. And it's virtually impossible to really define a visual output and direct the execution just through text. If you just go and to our open source projects like this movie, which I mentioned, average prompt length is over 3,000 words. That's the first thing. And look, all these benchmarks, which we're talking about, they're not as comprehensive in terms of the details of prompts. And people who are labeling, they obviously cannot read 3,000 word long prompts. But also on average, there are at least 10 image references for every scene. The reason why it's important, because it's important to define how the characters look like, how the background looks like, how actually characters are located to each other in the scene and so on. And so that's why prompting and just the workflow is so complex. Benchmarks just don't represent that.
Speaker 2Going back to the model selection, why did we decide we're going to do our own and then why walk it back?
Speaker 1So it's true that with VFX and camera control, we got very, very quickly from like maybe 1 million to 20 million in ARR within maybe the first three months. Then we released our own image model, which is really good at aesthetic photoshoots and product consistency. This is what allowed us to scale then from 20 to 100 million.
Speaker 2So help me understand, Alex, why did you decide that you were going to do your own models? And why did you abandon them?
Speaker 1We still do them whenever we see specific use case like these photoshoots. But as soon as this is what our customers want. So it's all driven based on the customer feedback, not just by ambition to conquer the world and build the best model in the world.
Speaker 2Do you think every company will have their own models? Like we're seeing Harvey, we're seeing Cognition, we're seeing McCaw, Ramp build their own models, and we'll see every company have their own models with their own data? Or we actually all use a series of providers.
Speaker 1So first of all, whenever, to be honest, whenever someone says we build our own models, very likely what they mean is something what's happened with Coursera. We do remember, right? A lot of companies, they actually take open weights model and just post train on own data. And post training can happen in two ways. Most important is whenever you have customer data around decisions they make, sequence of decisions, and you can teach the model to actually learn how to compress these 10 steps into one step. Like this type of reinforcement learning is the most valuable. And I think increasingly more and more companies will have to do that. We see this in the market as well. So most of the companies in the world today, most of the businesses, they don't necessarily need Astra specifically. They don't necessarily need the newest Fable model. That's why OpenRouter reports that share of open source models went from below 30 to over 60. Within this year.
Speaker 2What do you think share of open models will be in two years time?
Speaker 1Look, I do believe that just because the capitalism works, I mean, OpenAI and Anthropix still are going to have more than 50% of the markets. In terms of the dollars generally? In terms of the dollars, right. And especially because for coding still remains to be very, very prolific use case, where coders are always jumping to the recent model. But for our markets, we're seeing completely different dynamics. What's actually happening in social media marketing as companies start to print hundreds of ad creatives a week, they want to have maybe cheapest, more steerable models, because like PhD level intelligence is not necessarily needed to make viral social media video. And that's where we actually have seen that we get 80% plus margin whenever we run open source models, like post trained open source models, but it can be way more cost efficient for our end customer compared to the proprietary models.
Speaker 2What's the comparison on margins between open versus closed for you?
Speaker 1The margin on own models and open weights models is over 80%. And then it almost doesn't matter. And for closed source models, it's probably between 20 and 30%. And then what becomes important is, can we actually steer the traffic? What makes me excited about Higgs field is that iGentic grows so quickly. And actually for us, as companies start to actually create those agentic workflows to make more ads, we choose which model we can use. So we choose what model to use in over than 40% cases.
Speaker 2In a way, model routing becomes a core feature of the business, no?
Speaker 1Yeah, we call it tokenomics essentially, right? As like there is certain amounts of work customers want to do, how can we optimize number of tokens which is required and how we can pick the most efficient tokens for them? There are actually two incumbents in the United States who figured out models. It's not just Google, it's also NVIDIA. Why do you think that is? What I'm constantly seeing is that there is divergence of models. So there are these state-of-the-art models which have to be really good in computer use like Astra or in coding, but they can be prohibitively expensive. And we were chatting about that. It's like on average at Hicksfield, a person on the team spends over $10,000 a month on various models. And remember, like we're splitting. across United States and Asia.
Speaker 2So how much do you spend on models per month?
Speaker 1So internal usage of models a month is over 4 million.
Speaker 2Wow. How many people do you have?
Speaker 1We have close to 400 people and just want to make sure that the math adds up. Yes, it's definitely over $10,000 per person.
Speaker 2How has that changed over time?
Speaker 1That's the best question of the whole show, by the way. That's the best question. What actually started to happen is the creative team. The creative team started to do vibe coding. Like this month, I just caught a guy who spent over $30,000 in a week on Astra model. Because he was frankly frustrated that some asset organization workflow and as you said, basically auto editing is still not very good in production. And he said, "Oh, I'm just going to do this myself." And just went like five nights straight on Astra. And it works. We learned a lot. I wouldn't say it was production ready, but we learned a lot.
Speaker 2We learned a lot. $30,000 in a week.
Speaker 1Yeah. Do you mind? Yeah. My finance team will probably say. I don't know if you asked any of them, but they will probably say that I'm being too stubborn, too relentless to control the spend. Because sometimes I feel it really goes out of control. $30,000 in a week is quite a lot. But we learned. This was actually a net positive experience.
Speaker 2Okay, so the internal spend for me is $30,000. Okay, so the internal spend, $4 million, about $10,000 per head. What will that be in 12 months time, do you reckon?
Speaker 1So across the top engineers and across top creatives, it's going to keep growing. And I do believe we are going to get to spend close to $50,000 and $100,000 a month for those who can call 10x engineers, 10x creatives. Unfortunately, I also expect that these people will ask for comparable salary raise as well. So I think that's just going to correlate at some point. But also for a lot of other jobs, let's say we take legal, finance, and so on, it really stabilizes around like $500,000 a month very, very quickly.
Speaker 2With those 10x engineers, the idea is they have thousands of agents running below them doing a lot of the difficult execution work that took time. Do we just have dramatically smaller teams with those 10x engineers, 10x designers, 10x finance leaders?
Speaker 1I can definitely say that, I had sort of a feeling that legal customer support is going to be mostly replaced. And that's obviously one of the main mistakes operationally, which we have done in the company, that we didn't ramp these teams quickly. What we're seeing today is that like, let's say our legal team is like over 10 people, our customer success team is over 40 people, all of them use AI heavily. At these professions where I stay quite close today, I definitely can say that I don't see any elimination. It's true that probably over 60% of customer support requests, especially the first line of defense, can be handled with AI. But when it especially comes to B2B, like AI just doesn't work.
Speaker 2Revolut has now over 92% resolution rate on customer support for consumers.
Speaker 1Pretty good. It's pretty good, but obviously they did invest a lot into that. A shit ton. But also very important, the way how Nick thinks about that is in terms of the playbooks. We launch products, new products, pretty much every week. We have to keep update agents with all the information and so on. And just due to the high velocity, having extremely smart coordinated team is very important.
Speaker 2That's really interesting how product velocity increases leads to harder customer support for agents. Of
Speaker 1course, because the agents are as good as context and rules which they have. And if context and rules change pretty much twice a week, it gets a little difficult.
Speaker 2When you look at your engineering team today, what are they on? Are they on cursor? Are they on, codecs? Are they on cool code?
Speaker 1So from a period from March to June, everyone really moved to Cloud, including the creative team. And that's where we actually started to see creative team vibe coding functionality, which we don't have in production. But then we started to see that all the coders quickly moved from Cloud to Codecs as of mid-June. Over the time, creative, especially 10x creatives, moved to Cloud. But look, I do believe that it's cyclical.
Speaker 2It's so cyclical. My question to you is, will we continue to see the velocity of model release that we're seeing now? In three years time, will it be like, "Oh, Gemini this week. Oh, Anthropic this week. Oh, OpenAI this week." Or will we see a reduction in model release rate?
Speaker 1I don't think that's going to happen anytime soon. I believe, for example, recently OpenAI announced that they basically built OpenAI for law, but that's only v0. So over the time, they also are going to try to print smaller specialized models for. Not exactly smaller, but really specialized model for certain use cases. Clearly, Astra excels in long-term horizon of computer use. Do you buy that?
Speaker 2I look at that GPT for law from Astra, and I'm like, "I'm sorry. I think it's complete bullshit." With the greatest of respects, it is a very deep functionality required to serve some of the biggest law firms in the world. Very, very deep and specific functionality. It's very specific according to the different types of law as well. Plus, if you want to sell into these law firms, it's a multi-year sales cycle with some of the stodgy old lawyers and partnerships. You can't just say, "I'm OpenAI. Yeah, we've just hacked into the Australian government by the way, but we're here to serve your law firm." Okay. First of
Speaker 1all, I think definitely the ability to switch internal use just for internal teams outside of law firms, I think that's definitely happening. Oh, I think we both invest in a company called Solve Intelligence. Love it. Yeah. Very specific. Very specific. Let me try to maybe bring a couple examples why Solve Intelligence is so special, and for example, how we learn from this. What can happen very often is that a company want to just control the patent workflow even if they outsource the work. That's very valuable just to have one person who can do that. So, I think that's a very important thing. I think that's a very important thing. There are so many systems today which are used for just to store assets. Some people use Dropbox. Some people use Google Drive. Some people are going to try to use Miro. Some people are going to try to use Frame.io. There are many solutions. But let's think about what people need. What people need, they want to be able to search contents and marketers especially want to make sure that content is on brands in terms of the visual identity, but also like if that sort of adheres to certain brand guidelines. And that's where like semantic understanding and semantic controls become finally possible. It never existed before. So, in our space, there are definitely other companies like Adobe and Canva who builds the best software for the pixel first era where everything was defined with pixels. But that's clearly not how the world is going to work in the future. What we're envisioning and that's what everyone wants, they want to just be able to search and really work through the library of assets and all the knowledge through natural interfaces. So, being able to own this interface and build the analytics like this system of records is important. That's why at Hicksfield, we invested so much in Harness so that it improves over the time. And this Harness also allows it basically learns visual style over the time, which let's say Claude and OpenAI cannot necessarily do.
Speaker 2Do you believe in moats anymore? You've been around startups for a long time. We always talk about moats and defensibility. I largely think they're bullshit. We saw Lovable. When I invested, everyone was like, "Oh, it's a wrapper. It's a wrapper, you idiot, Harry." And actually, it was a wrapper, but it's about speed of decision making, product execution, and building value over time very, very fast. Chris: Instinct is a wrapper. Of course it is. It's not that difficult to do an AI assistant today, which is why there's so many, but they're building incredibly quickly, very valuable features, and you build it over time. Do you believe that moats actually exist really?
Speaker 1I think it's very difficult to figure out where the value accrues in the supply chain. We do believe that there are only two ways of modern value creation or moats today. The first is when you deliver the outcome. And for us, it's allowing businesses to sell more through AI ads. So that's the first thing. And the second thing is network effects. Unfortunately, AI does not replace network effects. And when people talk about swarm of AI agents talking to each other, I'm not sure this is happening in the next five years. That's why it's so exciting that within Hicksfield, like we really wanted to empower community to create more projects, open source, open source them to really build a snowball where people can capitalize on each other output. This is the reason why software grows so quickly, because it's so easy just to go and fork someone's project on GitHub. We were able to scale from basically like, I don't know, 10 seeded projects, open source projects like eight weeks ago, to over 10,000 today. Like seeing these type of network effects, I believe can become a mode over the time.
Speaker 2When we look at your growth, fundraising is a big part of it. It costs a lot of money to be able to spend 4 million on different aspects of inference spend. What was the best VC meeting you've ever had?
Speaker 1Obviously, Yuri Milner gets it. How is it?
Speaker 2What was that meeting? Was it in person?
Speaker 1Yeah, definitely in person. And definitely Yuri stays on top of all the trends. Where was it?
Speaker 2Were you nervous?
Speaker 1I wouldn't say nervous. It was just more to see how much of the, if we see the market the same way. And I was truly surprised that Yuri deeply understands this transformation of content first and foremost. Obviously, it starts with this direct to consumer AI ads, it starts with short form dramas. All these trends. All these trends come from Asia to the West. Also, fundamentally, we believe that most of content on social and in the world is going to be AI assisted or AI generated. And like this multi-trillion advertisement industry, and you know, like contextual advertisement is the main business model of the internet. It's all going to be substantially disrupted with video AI. This industry is still going to be very valuable, but it's never going to be the same.
Speaker 2Did you know when you left the meeting with, Yuri that he was going to write the check?
Speaker 1You know, sophisticated investors, they can play games. I had like so many scars. Like people really shook hands and said, we do at this price. And next day, what I learned is that they called other investors and they pulled the syndicates and to invest in 30% lower valuation compared to what we discussed. So like, look, these things just happen. So you never can be sure. But it didn't happen with Yuri.
Speaker 2I think there's a discount placed on Higgs field because you're not Silicon Valley insider. Do you think that's fair? Like, let's be clear, you're at a billion in revenue now. If you were a Silicon Valley company, that would easily be a $25 billion company growing at the rate that you're growing in 18 months.
Speaker 1Yeah, you could also argue that what Cognition was, well, it had 50, right? So there is definitely an upside. Okay, up about even more. Yeah, 100%. So a couple of things which I believe are very important. So first, we build for long term. We have seen that direct to consumer space, like e-commerce can be disrupted, like Shopify is a great example, how they have become infrastructure to build like direct to consumer businesses. And we become infrastructure to essentially build distribution for direct to consumer businesses. That's one aspiration. And second aspiration is obviously Apple Avin. The company is worth over $200 billion. It's insane. So look, and as we think long term, just these multiples don't matter that much. As we know, we're building long term, we're going to be over 100 billion. It's true that most of the people don't get the opportunity that we are going after the biggest industry in the world. But I wanted to drop another another number. So when I and I asked the team to double check, so it's at least four people on the team who proved so it's not like random fact. So I asked when we look at public companies, and we exclude pharma and big tech, spend on sales and marketing is higher than spend on R&D. When it comes to sales and marketing, the goal is to deliver personalized offering, which converts the best. A lot of that is human work, of course. But a lot of that is going to be personalized videos in one in some shape or form. So that's why I'm saying that many people just maybe and it's good for us that many people don't understand the opportunity, this large
Speaker 2market, which we go after you've mentioned Asia short form dramas a lot. What percent of revenues from
Speaker 1Asia versus the West? So all the West makes well over 70% of revenue. But just important to say that we learn a lot from trends coming from Asia. Hicksfield does not exist in China. China, for example, which is massive market for AI, the largest city by usage is Seoul in South Korea, while the largest country is obviously the United States, what's the biggest lesson
Speaker 2from Asia that you've learned,
Speaker 1there is so much IP, so many products coming from Asia, and they all try to figure out distribution direct to consumer. That's why they lean into the new tooling like video AI, which actually helps to achieve that. That's just a very different mindset. They feel that they could do way better if they could establish direct relationship with customer instead of having like some other layer. That's why they go so many, so much direct to consumer, rather than using some resale platforms and so on.
Speaker 2I sacrifice a lot of life for the life that I have in the career that I have. And I love it. Do you think you will one day regret spending a day with your son in three and a half months?
Speaker 1My mother had to work three jobs. So I didn't see her. My father was spending all the time with me going to all and it was I was basically minor. So he had to go to all these camps with me. I also play checkers. I was top three in the world. So we went we traveled throughout the world. Then I did programming. He spent all the time with me, like really dedicated his life to me like he did sacrifice. And since 21st, he has Parkinson's disease. So even like having some ability to capital and exits. Cannot fully change things. And this is something which is deeply personal, obviously.
Speaker 2But you don't need to do what you're doing now. I don't need to anymore either. I still am. I still miss family birthdays. I still miss weddings. Because like, mine's about a deep insecurity rooted in me being a fat kid. Why are you doing it?
Speaker 1So I think Mark and Jason actually described it really well. There are like five archetypes. So obviously, for me, it's just huge conviction about the technology about the markets, about the opportunity. And just huge fear of missing that huge fear of missing that. But remember that my parents really taught me that there is a place in the world where technology like good technology products matter. I remember like when I was six, there was like this, I guess, magazine about Bill Gates, like building Microsoft and not being like very like socially accepted everywhere back then. And like my mother just told me all like these examples basically happen in the world. I think she didn't fully understand like San Francisco. San Francisco and Seattle are different cities, but still, that's still deeply rooted in me.
Speaker 2I think one of the things
Speaker 1why Europe thrives so much, like, I know that you typically say otherwise, but let me just challenge you, like, who are the most relevant neoclouds today? It's Nscale, IRAN, and Nubius and Crusoe. Crusoe, okay, Silicon Valley story, IRAN from Australia, Nscale from the UK, and Nubius is UK and Netherlands. Let's talk about the companies on application layer there. I think one of the things why Europe thrives so much, like, I know that you typically say otherwise, but let me just challenge you, like, Nscale from the UK, and Nubius is UK and Netherlands. I know that you mentioned Mercore, and you mentioned Harvey, but Ligora, Eleven Labs, Loveable, they all deeply matter. So if we just go outside of the model layer, because then I don't want to go into the Mistral topic, right? Because I think like, by usage, the numbers are very strong, but people for some reason don't believe in that. I don't know why, but public data shows that the usage is there. But on every other layer, Europe is extremely competitive. Like ASM, for example, is a very competitive company. When you think
Speaker 2about your own CEO style, what's changed most?
Speaker 1the management principles. They don't necessarily are like fans of like one-on-one and like soft feedback. All of them, I think, are encouraged, like being down to the points, knowing the details, while it would be called in like corporate America, something like
Speaker 2micromanagement. What management principle do you disregard that many people think is important?
Speaker 1I do believe that it's as simple as hire the best people to do the best work and figure out how to retain them. Everything else is frankly secondary. And people just create so much theory around that. And then essentially, there is just so many like fake rules, which are disconnected from reality. It's really as simple as hire the best people, empower them to do the best work, and just figure out how to establish relationship and retain them.
Speaker 2A lot of them do see dollar signs. And secondaries are a part of that. How do you think about doing annual tenders to retain people?
Speaker 1Across our team, roughly 50 are in California, we're going to get to roughly 50 remotes. And over three years, we're going to get to roughly 50 remotes. And we're going to get to roughly 50 remotes. And we're going to get to roughly 300 in Kazakhstan. So look, I just hope we're going to print more dollar millionaires in Kazakhstan, in Central Asia, in this part of the world, than any other company.
Speaker 2What's the labor arbitrage on cost between Kazakhstan and the US?
Speaker 1I know that a lot of people when they look at Higgs, they think about the arbitrage. Is that not true? Look, like Kazakhstan is top five in the world in physics. Like you look at the recent International Physics Olympiad for high schoolers, like they're top five in the world on pair with the United States. China, India. And this is also like the core of our team are people who won international competitions in math and physics. That's the first part. The second part is that about Kazakhstan is that they actually took this Soviet school of math, but really upgraded with Singaporean principles. And Singaporean system of education is considered to be probably the best in the world. At least many people in Silicon Valley believe that. And the government basically subsidizes for thousands of high schoolers to study abroad. And many people come back. And so just the density of talents definitely got there. It's like top 10 largest countries in the world, over 20 million population. And we are also actively hiring, bringing their talents from Europe, from other countries in Asia. And people just enjoy like some benefits, like 15% personal income tax. Yeah, man, it's like.
Speaker 2Don't even get me started. Fucking UK will tax you to breathe. Seriously, in the UK, you get your paycheck. And then. And it's like, I don't know, $100,000. And then you get the end, and it's kind of like $3,500. And it's also English common law. So it's not like that bad as people think. You move it. Let's swap places.
Speaker 1Do you have a mega pad in Kazakhstan? No, I don't. I don't own any property. What? Why? Remember that I come from Asian family. Whenever we sold a company, I made over a million dollars. And I spent all this money buying apartments for my parents, relatives, my wife, parents, because it's just part of the culture. Wow. And the extended family is not small by any means. But look, it's just part of the culture to give back. And then when it comes to the family, especially to my parents, they obviously sacrificed a lot. So I felt like I had to give back at least things, like monetary things, which I could do. But I drive like Tesla Model 3, and I sleep. So I'm not like a guy who's going to just show up with Lamborghini. Do you invest?
Speaker 2We mentioned Solve Intelligence.
Speaker 1Before I did that, but now I spend roughly 90 hours a week, 80-90 hours a week on Hicksfield. I try to spend ideally at least three hours a week with my wife, at least five hours a week with my son. Sometimes I do the catch up because when I travel for a week, for two weeks, for three days, I spend a day with my son. And over the last three months, yes, I was able to find one day when I spent like end-to-end with my son without emails, without talking to the team members.
Speaker 2I get in trouble for this, but I think there's no shortcut to hard work. The harder I work, the luckier I get. I meet more founders. I find more great companies. I do more shows. I have more success. Do you buy the bullshit of the balance and, oh, it's okay, you can leave at five and be home for bath time and crush it? This is a good question.
Speaker 1So, look, obviously, being an immigrant, I always have to prove like that I belong, right? So, I feel like now people accept, people recognize that Hicksfield is probably a top 10 application AI companies by revenue, probably number one. But I think when it comes to hard work, like the people whom we know in common, like we talked about, let's say, Peter Sellis, like legend in the consumer space, obviously, Jack. I spend a decent amount of time with them and other product leaders at Stamp. The density of product talent at Stamp was unprecedented. All of them work really hard. All of them are smart. None of them just checks emails for five hours a day and calls it work. Each of them is deeply rooted into their recent trends in product, product design, activation. They know data really well. So, yeah, I don't believe that there is any shortcut to hard work.
Speaker 2Three hours a week with your wife. I don't know about you. Yeah, you do. Mine would dump me for three hours a week. How do you make marriage work on three hours a week?
Speaker 1Yeah, look, I'm very grateful for my wife for being patient. You know, it's also very different if that's like Asian culture. It's just kind of more natural to try to do sacrifices for each other, sort of. And I'm deeply, obviously, deeply grateful for her for supporting me. But like sometimes at this scale, I get invited to parties. I always send her and don't show up myself. I don't know if I piss people off, but this happens very frequently. So you say yes, and then she goes. Yeah, I say maybe we both can come together. Then there is always some urgent fire last minute. And my wife just goes.
Speaker 2What fire was most urgent? What was the, oh, fuck.
Speaker 1Yeah, look, I think obviously for all the things which we touched base earlier, whenever we are not very good in communicating the features or we felt like, I mean, now it's like team of 40. So now the life is way better. But the early days, obviously, I was involved in all the fires. I think recently, all the types of like attacks on AI companies, it's crazy. It's like LLMs are being used to hack companies. It's like new types of LLMs to do some frauds, you know, like basically bots using credits and then doing auto refunds, all of that. Like since I have like kind of machine learning background myself, data science background, I still have a lot of data science background. So I still can move a needle substantially when it comes to statistics and data. So yeah, I have to be involved somehow. But like these LLMs, they amplify many types of behaviors, including various types of attacks and fraud. But we have to fight against that.
Speaker 2We're going to do a quick fire round. So I say a short statement, you give me your immediate thoughts. What have you changed your mind on most in the last 12 months?
Speaker 1Oh, I was thinking that HubSpot is going to get obsolete. Everyone is going to build their own CRM. But when, especially when we hire, you know, a lot of people, a lot of people, a lot of people and scale B2B go-to-market team, just having familiar interface matters a lot.
Speaker 2Wow. I would still say they're going to get fucked. You think that just stickiness is there with SMBs?
Speaker 1Yeah, I do think so. And especially I see that when I hire go-to-market talents.
Speaker 2Wow. Why? Like what is it about hiring them that makes you think that? Just they're so used to it.
Speaker 1I mean, like people who are very good in understanding customers and talking to customers, they may not just simply accept new interface so quickly. And just having HubSpot as a system of if there is any mismatch going, able to just understand where the data flow went wrong. I think that's just still very valuable, like the familiarity. What do you believe today that
Speaker 2everyone else thinks is fucking crazy?
Speaker 1I mean, look, I think people just still don't fully appreciate that most of the content on social media is going to be AI generated. There are going to be some shows like obviously yours, where it's like authentic contents. It's going to be 1050x higher CPM, whatever, than AI generated content. So it's going to be, it's going to be way less in terms of like content created by, but it's going to create way more value than the AI generated content. But even when I look into your content specifically, like you made multiple, very successful shorts, millions of views, better than anyone else in this space. And you do a lot of overlay. While the content is authentic, I think we should do a better job so that you use Hicksfield at least for the overlay on top of existing videos.
Speaker 2Dude, I would love that. I mean, again, they take three hours. So people don't know this. I spend two hours a day just doing Instagram now. We decided that Instagram in short form is going to be a big new push for us. Two hours a day just for me. I write the scripts and then I record them. And then it's two people, six hours per one for those three.
Speaker 1And that's extremely smart of you. You know, like going back to some of the topics is like clipping is like a huge topic. And that's like has its own upsides and downsides. But obviously, it's going to be a big push for us. So I think it's going to be a big push for us. Obviously, everyone sees this opportunity to win, to build massive top of funnel, like hundreds of millions of views with short form content, as long as you can have downstream monetization, like or value creation like you do.
Speaker 2Totally agree with you. What job today does not exist that will be big in five years?
Speaker 1Okay, so in five years, people, especially in our space, creative directors, they are going to be talking to computers and generating stories real time and video. And AI is going to help to create multiple variations. Today there is no word to really describe that because there are scriptwriters, then screenwriters, like those who are going to break it down shot by shot. Then there are people who do that storyboarding. Then there is a person who oversees all of that, like movie director and so on. So there are so many parts of that, but eventually taste is going to matter a lot and just having stories to tell. And there is no word to describe it today.
Speaker 2Do you not have on your board that you would most like to have on your board?
Speaker 1Maybe out of more professional CEOs, I'm definitely Frank Slutman. Because going back to the point, I was just curious all the time, does no bullshit culture exist in California or not? Can it allow to scale companies so quickly? Is it possible to build successful enterprise go-to-market motion with no bullshit culture? And when I read his Empitap book, a book called Empitap, I realized it's possible. So I'm a huge fan. I watched all his interviews.
Speaker 2And he's amazing. He's the best leader by far. But the challenge is you can sometimes do it at the sacrifice of product advancement. And so he built a GTM machine at Snowflake, but Databricks wiped the floor because they move product as the priority, not GTM. And that was dangerous. I prefer Chad Peets. Do you know Chad Peets? No. Oh, dude, this guy is no bullshit. I'll introduce you afterwards. He's the best sales leader in the world. And he is no fucking bullshit. Unbelievable. And we probably should have him on board. Oh my God. I can find any way to have him on board. He is terrifyingly good.
Speaker 1So what's the biggest lesson from Snap? The momentum doesn't last forever. Like today, Snap market cap is below 15 billion. There are lots of memes on the internet, but this is a great company. Cares so much about trust and safety and experience, and it puts it first. Do you think it is a great company?
Speaker 2No offense. It's been mismanaged to shit. Its SPC is through the roof. It's tough to say it's a good company.
Speaker 1Yeah. That's why I say that momentum doesn't last forever. When Snapchat was worth $80 billion and the gap with Meta was less than 10X, then it felt, "Oh, we just go explore. We just really must lean in." But momentum doesn't last forever. And that's my core learning. So that's why while we do have the positive momentum, we do not take this for granted. Clearly, the nature of capitalism is there are ups and downs. And since we're building long-term, we just shouldn't. We just should capitalize on the opportunity with the fundraising and just keep pushing progress every day.
Speaker 2What is the reason why the divergence between Meta's market cap and Snap's market cap has increased so significantly, if there was one reason?
Speaker 1Just maybe saying this straight, a lot of public companies did not figure out their AI story. Snap, unfortunately, is part of that. We have seen other great companies like Figma trying to tell their story. You mentioned Canva. Canva, it's not necessarily easy to be successful in private markets and public markets. And Zach is one of the best CEOs of all time because he managed that.
Speaker 2He's such a fucking beast. He's such a beast. You watch him last night with the event, and you're just like, "Ah, now I get it. That totally makes sense." And you know what? Scale with Alex Wang, I was one who was like, "Really? What's going on?" He basically acquired a second CEO. Alex was like, "Oh, I'm going to do this. I'm going to do this. I'm going to do this." Alex is now the CEO of Muse, and he's crushed it. Crushed it. What an effective buy for 0.5% of your market cap. Do you know what I mean?
Speaker 1Yeah. Look, but this happens with Instagram, with WhatsApp. That's why I'm saying that we just maybe should put Meta a little bit in its own league. Yeah, but he got
Speaker 2rid of Systrom and Krieger. Here, he's been like, "No, no, no. You, Alex Wang, are my guy." Do you see what I mean?
Speaker 1Yeah. Look, I do believe that it's a little bit early to look at whole Meta AI initiatives. We probably need to see year of successful launches and so on, and then we can look back and see what was good, what was not good. But at least the consistency of storytelling and explaining what he is doing to public investors, being able to articulate why Muse is so different is phenomenal.
Speaker 2Okay. Revenues say are a billion. What are the revenues in 12 months' time?
Speaker 1Yeah. Our current business model projects 4.5. It says by the end of the next year, but this basically involves substantial deceleration. And that's what just my finance team, there are a couple of strong quant people, they told me that's just how the business works. But look, we are still pushing to grow at least 30% month over month.
Speaker 2What do you think it is? They said 4.5. This is me to you, not me to your finance team.
Speaker 1Over 10. Over 10? Let me tell you why. In a lot of adoption and creative AI space is driven by monetization, like all these direct-to-consumer brands making more ads, and also having the aspirational cinematic AI content, as this inspires creatives to explore the tooling. It feels to me that Hollywood starts to embrace AI, mostly today as a tool for hybrid production. As a just new form of CGI, but the sentiment really shifted from like strictly negative, to neutral to slightly negative. And in private conversations, yes, there are maybe more than half of S-tier talents who is going to say we're anti-AI forever. But increasingly, there are more and more people who are actually asking a question, can we tell more stories with AI? Can we overcome certain budget limitations? Which exactly are they? Can we overcome certain budget limitations, which existed before, and maybe AI can help to tell new stories, which we couldn't tell before. And I do believe this just change in perception, that at least comes from my conversations, is extremely positive.
Speaker 2If you are at a billion today, 10 billion in 12 months, why do you peg the next fundraise? If you're at a billion, say, a conservative multiple, you'd be like 15. But if you're hitting 10 next year, you're like paying end of year 80?
Speaker 1Look, we're not chasing just the valuation. Because again, the goal is just to make sure that the company can be sustainable over the time in public markets. So there is a lot of company building to be done beyond just chasing the revenue. But I just do believe- Do you want to be public at some point? Yeah, I do believe that Hicksfield has great potential to be bigger than Apple, Avian, and Shopify. Because fundamentally, building is one part of that. Shopify, one layer of infrastructure. Then for coding, there is obviously like a cloud, there is Codex. But what matters is distribution over the time. Distribution matters. You know, this is better than any other VC, right? Dude, it's my business.
Speaker 2That's why we do what we do. Yeah, exactly. Dude, I cannot thank you enough for being so amazing on the show. You've been fantastic. I've loved doing it, you can tell. And you've been an amazing guest, so I really appreciate you joining me today. Thank you so much. It's a pleasure. But before we leave you today, founders face a different set of challenges at every stage of growth. For Sid Shate, co-founder and CEO of dMatrix, JP Morgan delivered the guidance and expertise to help navigate what came next. He credits JP Morgan's high-touch approach with supporting dMatrix as it grew and expanded internationally. Whether you're in the early days or expanding into new markets, JP Morgan helps startups navigate complexity with real confidence, offering personalized guidance and deep sector expertise. Find out how JP Morgan helps founders at jpmorgan.com/growwithoutlimits. Get your ass covered with Corgi insurance, and I'll tell you why. Getting insurance, it's really slow, it's confusing, and my word, it's full of paperwork. Corgi provides essential coverages for all growth stages, such as D&O, E&O liability, cyber, commercial, general liability, and more. Get your ass covered, I love the way we say ass, with Corgi insurance alongside thousands of other startups at corgi.com/20vc today. That's corgi.com/20vc. You won't regret it. Business owners run, their whole financial life on Flex. Float every purchase for 60 days, tap capital that grows with your revenue, and pay vendors in 170 countries across 32 currencies, plus the whole back office. Bills, expenses, accounting, all in one place. So you spend less time reconciling, and more time growing. Visit flex.one, that's F-L-E-X dot O-N-E, and use the code 20VC.
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