An 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. Hicksfield, this is the story that no one 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 Cursor. Alex, the founder, is an incredible genius. This is the story that you don't know that you need to know. My 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.
I just caught a guy who spent over $30,000 in a week on AstroModel. Many people spend over $10,000 in a week. Ready to go?
Alex, I am so excited for this, dude. We were talking downstairs and I said, I don't think the Hicksfield journey has been told before. And it's an amazing journey. So thank you so much for joining me today. That's a very special opportunity for us. Thank you for having me. Obviously, your story is inspiring as well. How social media has become an elevator for your opportunity to create fund and so on. Dude, that's very kind of you to say. I do just want to go back though because you're not the Stanford, Silicon Valley, born and bred engineer. You were a competitive programmer in Kazakhstan. Can you just take me back?
How did you first find and fall in love with computers and become a programmer so early? So first, you need to understand where I come from. My father is from Uzbekistan. Uzbekistan is a country in Central Asia where if a family of five people makes $1,000 a month, it's considered to be wealthy. It's not very high standards of living, unfortunately. But both my parents are professors of mechanical engineering. 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 my mother had to work three jobs because 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, certain data structures, algorithms and so on. Can I ask you a question? Did you feel pressure as a child competing, being pushed into these environments when you are so young? Absolutely. But 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, 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 an academical career, decided to do startups. I'm sure your parents were thrilled. Can you take me to that decision? This is the penultimate moment you've worked 19 years for, your parents have told you this is the mother lode, this is the thing. And you're going to do this really risky thing called a startup at this point.
What 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 doing optimization, make it run faster, parallel across multiple machines and so on. And we actually built 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 DeepMinds and Meta. But my passion was actually different. I was very surprised to learn when I came 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, I mean, who else is going to produce videos for the phones? Maybe it's going to happen with AI. And so that was the company that we built before that you sold to Snap? So, the company was called AI Factory. I was fortunate to meet Mahi in 2018. He is co-founder of Hicksfield.
And he is a veteran of Silicon Valley, went through ups and downs and sold it to Snap for 166 million. And then I was leading Gen.AI there. Pause. No offense, dude. You come from a family of incredibly ambitious parents who push you to do well. And you just skipped to the moment where you sell for 166 million. It's a lot of money. How did that feel when you did it? We both remember these times where the capital for AI companies was not really that much available. And AI multiples were not 200 to revenue as they are today, but closer to zero because AI was not a topic. So there was severe dilution, which we experienced. So just to calibrate. What was the round?
No, look, back then rounds, rounds of one, two million dollars, having one, two million dollar 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 LA and then to Silicon Valley. And my dream simply came true. Was it what you thought it would be? That's a good question. San Francisco is definitely a place where no one judges by race, nationality, and so on. And that's truly phenomenal. There is definitely a meritocracy in a sense that it's possible to meet anyone.
But at 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. So then tell me, we have sold to Snap. We're now in the US. This is the moment you wanted. How does Hicksfield come to be? Back then, Snapchat in 2020 was really growing so quickly. And the face filters, which my team has built, was driving most of daily new users. What's important is that these face filters, we were able to manage to run on mobile devices. So it was virtually for free for Snapchat.
It's not current LLM token 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. So this is a major gap. Social media is the main media in the world. A lot of companies are actually able to build direct response advertising so that they can actually sell more. But at 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. 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. Yes, absolutely. So where it all really started is that we had a tool, to upload set of images and transform them into a slideshow with music. It's better than nothing, but still pretty bad, right? So 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 in 2023, it was absolutely clear that scaling loss finally works. It's not just a concept from science that scaling loss works. Video just takes a couple, maybe two or three years longer than LLMs and coding. But it was clear that actually, finally, scaling loss should work in video as well. And I just decided to take a bet. But I just want to go back. I 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 a couple of pivots before and the meandering that we had.
So what happened when we launched? Did we have immediate product market fit? No, actually, 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 wrong things. I think I just lost the touch with reality back then.
But it was clear that scaling loss should work in video as well. And I just decided to take a bet. But I just want to go back. I 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 a couple of pivots before and the meandering that we had. So what happened when we launched? Did we have immediate product market fit? No, actually, we spent more than a year in 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 wrong things. I think I just lost touch with reality back then. I was so much optimizing for what's hype today, what's 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 so we just started to talk to customers. We spoke to eight creative directors about their experience with AI and what's simply missing. 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. Is product market fit like love? When you know, you know. Yes, it's definitely when you know, you know. For example, we don't do any paid. And we have on the team people who scaled businesses to over a billion and two billion in revenue, 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 different types of influencers, but typically there is some fee for video production and then some cost per click, like attribution, which works really well on YouTube. You guys got into some controversy for, I can't remember what it was. You were paying people to promote for you or doing something rogue with influencers. Was that completely unfair? Was it kind of my bad we did do that? How do you respond to that? The main takeaway from our experience is that it's very important to own distribution. Distribution now more important than ever. And 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 that was not a good experience. But we are still trying to find interesting opportunities to tell about new media formats. Some of them are rather controversial. So for example, recently we partnered with Neon, one of the largest streamers in the world and launched his own AI generated stream. No one else did this before because this is a real creator making a replica of themselves. A lot of people start to question whether it's really authentic content or not. But at the same time, those creators are under immense pressure. We all know about the story from Mr. Beast about how much pressure there is to constantly perform. So we also know through conversations with many talent agencies, a lot of top stars actually want to be able to do more if they could create digital replica. But what's happening today very frequently is that those A tier celebrities come up for a recording on, let's say, green screen. And then there is a lot of post-production which goes on top of it. And it feels to me that we are naturally going to come to a point of time where AI digital replicas are going to become just one of the ways how creators can monetize. Totally get that. 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. When we recorded, just Bloomberg article went out. So we cross 1 billion in annualized revenue. If I had a gong here, I'd be hitting the gong. A billion in revenue. Yes. Actually it took us 18 months from 1 million to 1 billion. For Coursor it took 24 months. So we are probably the thirds after OpenAI Anthropic. 18 months from a million to a billion. Yes. How do you calculate revenue? It's a controversial topic. How do you calculate revenue? Absolutely. By the way, your co-host Jason also asked this question in May. Luckily answer didn't change. So we are at least consistent. 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, OpenAI, Anthropic, Cloud, but all of them use the same methodology. What's very important is that we are, we take revenue, not sales. So if that's an annual subscription or annual enterprise contracts, we prorate this across 12 months and take only this 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 three year enterprise deals and banking into the 1 billion figure. No, we don't do that. If you were to break that billion up today into annual contracts, monthly subscriptions, and then token spend, what would that be? So video AI is still relatively early. In my opinion, 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 some 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. 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 blows my mind. Dude, what are they getting for 6 million a year? That's almost a Hollywood content team. So there are multiple trends and all of them frankly coming from Asia. So first, 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 AB test what performs well. But we all know about short-form dramas, right? Most 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 new shows there are made with AI end to end. So I think this adoption obviously is coming bottom up, but that's very difficult to refute this new reality. What percent of revenue is consumer versus enterprise? So that's a great question. So business revenue is slightly over 50%. Wow. Yeah. That's impressive. Thank you. So on the consumer side, it's also very important to break it down. So on the consumer side, out of these 50 is around 10% is pure consumer use cases. And that's roughly people who use it on mobile. So share of our revenue from mobile is less than 10%. That's why we are very different from many other companies. But there are lots of aspiring creators, 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 churning. Within a year, most of them actually come back to try again. And we do believe that over time, most of them are going to figure stuff out and they're going to become this new AI native workforce. So it's still important for us to educate them. And that's why we invest so much in Hicksfield Academy, YouTube channel and so on. But we also are fully cognizant that we will never be able to win in the markets of subscriptions of $20 a month. So why? Because I think today, Google and OpenAI, they pursue ads so much. But fundamentally, I think they are going to completely demolish all their prosumer subscription markets, which is $20 a month subscriptions. Oh, 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? Yeah, I do believe that.
And we do believe that over 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. And that's why we invest so much in Hicksfield Academy, YouTube channel and so on. But we also are fully cognizant that we will never be able to win in the markets of subscriptions of $20 a month. So why? Because I think today, Google and OpenAI, they pursue ads so much. But fundamentally, I think they are going to completely demolish all their prosumer subscription markets, which is $20 a month subscriptions.
Oh, 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? Yeah, I do believe that. That's essentially what's going to happen over time. I know this is a very contrarian bet, but at least we can see some of that's already— You're seeing it cannibalize 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?
Yeah, 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 a $20 a month subscription, how can we show them value, how can we make them upgrade to spend over $1,000 a year with us? I can't believe that's $6 million a year from $99. That's the best ever slide on a fundraising deck. Yeah. And all of our customers are going to do the same. Exactly. Can I ask, you mentioned churn rates. When you look at 30-day retention rates for consumers and 90-day retention rates, what are yours and what is good?
So there is quite massive drop within the first month, just simply because people don't fully realize the value. And 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. Mm-hmm. I wouldn't say it's great, but because we all remember the B2B SaaS era, 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.
Like when I look at the core, at the business segments and NRR at month 12, obviously you're going to argue it's an 18 month old company, 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. Can we actually just unpack the two different go to markets? Because you've got consumer and you've 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. And they said, you've executed the most impressive influence in 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 on that? First and foremost, 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 workforce, frankly. And those people, they make product launch videos. They make tutorials. And they make tutorials, for example, we made the first AI generated movie, which is also a very sensitive topic, but what's important, we open sourced all of it. And what we learned is that for 90 minutes of TV quality content, it was over a hundred 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. So you're saying the growth in consumer subscription is through own content and distribution. Yes.
We don't do any paid. Early on, you made an interesting architectural decision to have your own models. And then you've since walked that back. Can you talk me through why did you choose own models and why the walk back? Yeah, obviously this was my mistake. I'm going to do my best to be transparent. What I need to admit, we really tried. At some point of time, I really was thinking that chasing benchmarks is valuable, but I don't believe this is corporate psyops, frankly. So I was part of a large organization, so I know what happens. What happens is that everyone just thinks 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 leverage test data to use LLM as a judge for training of the models, use all the various tricks to basically game benchmarks, get quarterly bonuses and so on. Because who cares, right? So if I make my couple million dollars a year in one of these labs, I can move to another lab easily. So that's unfortunately what's happening in larger organizations. 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 efficiency. Yeah. 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 by dance, obviously trying to catch up as well. What's your takeaway from that?
I just do believe that there is an obsession over the benchmarks, which do not necessarily represent the reality. But I can talk specifics specifically in video. A lot of benchmarks today for videos, really text to video, which does not represent actual workflows at all. The way to think about video models today, it's a modern rendering engine. Think about this as 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 to our open source projects like this movie, which I mentioned, average prompt length is over 3000 words. That's the first thing.
And 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 3000 long prompts. But also on average, there are at least 10 image references for every scene. The reason why it's important, 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 the workflow is so complex. Benchmarks just don't represent that. So going back to the model selection, why did we decide we're going to do our own? And then why walk it back?
Benchmarks just don't. It's true. That's like with VFX and camera control, we got very quickly from 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 photo shoots and product consistency. This is what allowed us to scale from 20 to a hundred million. Benchmarks just don't. But it's really good at the end. So help me understand Alex, why did you decide that you were going to do your own models? And why did you abandon them? And so that's why prompting and just the workflow is so complex. Benchmarks just don't represent that.
So going back to the model selection, why did we decide we're going to do our own? And then why walk it back? Benchmarks just don't, it's true. That's with VFX and camera control, we got very quickly from 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 photo shoots and product consistency. This is what allowed us to scale them from 20 to a hundred million. Benchmarks just don't, but it's really good at the end.
So help me understand Alex, why did you decide that you were going to do your own models? And why did you abandon them? We still do them whenever we see specific use cases, like these photo shoots. But this is what our customers want. So it's all driven based on customer feedback, not just by ambition to conquer the world and build the best model in the world. Do you think every company will have their own models? We're seeing Harvey, we're seeing Cognition, we're seeing Mako 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?
So first of all, whenever someone says we build our own models, very likely what they mean is something what's happened with Cursor. We do remember, right? A lot of companies, they actually take open weights models and just post-train on 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 take, learn how to compress these 10 steps into one step. This type of reinforcement learning is the most valuable.
So I think increasingly more and more companies will have to do that. Frankly, we see this in the market as well. 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 Grok model. And that's why Open Router reports that a share of open source models went from below 30 to over 60 within this year. What do you think share of open models will be in two years time? Look, I do believe that capitalism works. Anthropic is going to have more than 50% of the markets. In terms of dollars generally.
In terms of dollars. Right. And especially because for coding still remains to be very prolific use case where coders are always jumping to the recent model. It's overall, 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 cheaper, more steerable models. PhD level intelligence is not necessarily needed to make viral social media video.
So 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. What's the comparison on margins between open versus closed?
The 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 Heyfield is that as Genie grows so quickly and actually for us as companies start to actually create those organic workflows to make more ads, we choose which model we can use. So we choose what model to use in over 40% of cases. In a way model routing becomes a core feature of the business. No?
Yeah. We call it tokenomics essentially, right? There are certain amounts of work customers want to do. How can we optimize number of tokens which requires 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 are versions of models. So there are state of the art models, models which have to be really good in computer use like Astra or coding. But they can be prohibitively expensive. And we were chatting about that. It's like on average at Heyfield, a person on the team spends over $10,000, over $10,000 a month on various models. And remember, we're split across United States and Asia. So how much do you spend on models per month? So internal usage of models a month is over 4 million. Wow. How many people do you have? We have close to 400 people. And just to make sure that the math adds up. Yes. It's definitely over $10,000 per person.
How has that changed over time? That's the best question of the whole show, by the way. What actually started to happen is the creative team started to do vibe coding. This month I just caught a guy who spent over 30K in a week on Astra model. Because he was frustrated that some asset organization workflow. And as you said, auto editing is still not very good in production. And he said, oh, I'm just going to do this myself. And just went 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. 30,000 in a week. Yeah. Many people spend over 10,000 in a week. 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 too stubborn, too relentless to control this spend. Because sometimes it really goes out of control. Like 30K in a week is quite a lot, but we learned this. So this was actually net positive experience. Okay. So the internal spend, 4 million, about 10,000 per head. What will that be in 12 months time? Do you reckon?
So that's very interesting. Across the top engineers and across top creatives, I think it's going to keep growing. And I do believe we are going to spend close to 50K and 100K 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 legal, finance and so on. I think it really stabilizes around $500,000 a month very quickly.
With 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?
I can definitely say that I had 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 our legal team is over 10 people. Our customer success team is over 40 people. All of them use AI heavily. At these professions where I say quite close today, I definitely can say that there is no 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 comes to B2B, AI just doesn't work.
Revolut has now over 92% resolution rate on customer support for consumers. Pretty good. It's pretty good, but obviously they did invest a lot into that. A lot. And also very important, the way Nick thinks about that is in terms of the playbooks. We launch products, new products pretty much every week. So we have to keep up that agents with all the information and so on. And just due to the high velocity having extremely smart, coordinated team is very important. That's really interesting. How product velocity increases leads to harder customer support for agents. Of course, because the agents are as good as the context and the rules which they have.
But when it especially comes to B2B, AI just doesn't work. Revolut has now over 92% resolution rate on customer support for consumers. Pretty good. It's pretty good, but obviously they did invest a lot into that. A shit ton. A shit ton. And, 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. So we have to keep up that agents with all the information and so on. And just due to the high velocity having extremely smart, coordinated team is very important. That's really interesting. How product velocity increases leads to harder customer support for agents.
Of course, because the agents are as good as context and the rules, which they have. And if context and the rules change pretty much twice a week, it gets a little difficult. When you look at your engineering team today, what are they on? Are they on Cursor? Are they on Codex? Are they on CoreCode?
So from a period from March to June, everyone really moved to Claude, 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 Claude to Codex as of mid June. And over the time, creative, especially 10X creatives and the codex moves to codex as well. But look, I do believe that it's cyclical.
It'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, cool. Anthropic this week. Oh, OpenAI this week. Or will we see a reduction in model release rate?
I don't think that's going to happen anytime soon. So I believe, for example, recently, OpenAI announced that they basically build OpenAI for law, right? But that's only V0. So over the time, they also are going to try to print smaller, specialized models for certain use cases. Clearly like Astra excels in long-term horizon. Do you buy that? Like I 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. Like 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. We've just hacked into the Australian government, by the way, but we're here to serve your law firm.
Yeah. So first of all, I think just 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 there is in company called Solve Intelligence. Love it. Yeah. Very specific. Very specific. And let me try to maybe bring couple examples. Why like Solve Intelligence is so special and where, like for example, how we learn from this. What's going to happen very often is that a company want to just control the patent workflow, flow, even if they outsource the work and that's very valuable just to have one system of records. So whoever can create AI native system of records is going to win.
And by the, going back to Higgs, why it's so important for Higgs field, there are so many systems today, which are used for just to store assets. Like 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. Like 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 like 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 Higgsfield, we invest 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.
Do 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. You know, 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. Instinct is a wrapper. Of course it is. It's not that difficult to 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?
I know, like you ask this, everyone. So, and this is, because this is on top of everyone's minds, like how to think about the metrics which matter today and how to think about the moats. So, I 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. 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. So that's why it's so exciting that within Hicksfield, like we really wanted to empower community to create more projects, 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. So, and like, 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 moat over the time.
When 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 band. What was the best VC meeting you've ever had? Obviously, Yuri Milner gets it. How was that meeting? Was it in person? Yeah, definitely in person. And definitely Yuri stays on top of all the trends. Where was it? Were you nervous?
I 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 come from Asia to the West. And also, fundamentally, we believe that most of contents on social and in the world is going to be AI assisted or AI generated. And the, 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 still going to be very valuable, but it's never going to be the same.
Did you know when you left the meeting with Yuri that he was going to write the check? You know, sophisticated investors, they can play games. I had like so many scars, like people really shook hands, 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 look, these things just happened. So you'd never can be sure. But it didn't happen with Yuri. I think there's a discount placed on Higgs field because you're not Silicon Valley insider. Like, let's be clear, you're at a billion in revenue now. Yeah. If you were a Silicon
business model of the internet. It's all going to be substantially disrupted with video AI. This industry still going to be very valuable, but it's never going to be the same. Did you know when you left the meeting with Yuri that he was going to write the check?
You know, sophisticated investors, they can play games. I had so many scars, people really shook hands, 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. These things just happened. So you'd never can be sure. But it didn't happen with Yuri. I think there's a discount placed on Higgs field because you're not Silicon Valley insider. Let's be clear, you're at a billion in revenue now. Yeah. 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. Yeah. You could also argue that's what cognition was well at 50, right? So there is definitely an upside. A hundred percent.
So a couple of things, which I believe are very important. First we build for long term. We have seen that direct to consumer space, e-commerce can be disrupted. Shopify is a great example, how they have become infrastructure to build 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 VIN. The company is worth over $200 billion. It's insane. So look, as we think long-term, these multiples don't matter that much. As we know, we're building long-term, we're going to be over a hundred billion. It's true that most of the people don't get the opportunity that we are going up for the biggest industry in the world, but I wanted to drop another number. I asked the team to double check. It's at least four people on the team who proved, so it's not random fact. So when we look at public companies and we exclude pharma and big tech, spend on sales and marketing is higher than spend on R and 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 some shape or form. That's why I'm saying that many people just don't understand the opportunity, this large market, which we go after.
Can I ask you, you've mentioned Asia, short form dramas a lot. What percent of revenue is from Asia versus the West? So the West makes well over 70% of revenue. Oh, wow. But just important to say that we learn a lot from trends coming from Asia. Hicksfield does not exist in China, for example, which is massive market for AI. But the largest city by usage is Seoul in South Korea, while the largest country is obviously the United States. What's the biggest lesson from Asia that you've learned?
There 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, video AI, which actually helps to achieve that. That's a very different mindset. They feel that they could do way better if they could establish direct relationship with customer, instead of having some other layer. That's why they go so much direct to consumer, rather than using resale platforms. I sacrifice a lot of life for the life that I have and 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?
Look, this is goals even beyond that, because my from the age of seven to 12, my mother had to work three jobs, so I didn't see her. My father was spending all the time with me going to all these camps with me. I also played checkers, I was top three in the world, so we went, we traveled throughout the world. And then I did programming, he spent all the time with me. He did sacrifice. And since 21st, he has Parkinson's disease. So even having some ability to capital and exits cannot fully change things. And this is something which is deeply personal, obviously.
Totally. Totally. But you don't need to do what you're doing now, Alex. I didn't need to anymore either. I still am. I still miss family birthdays. I still miss weddings. Because mine's about a deep insecurity rooted in me being a fat kid. Why are you doing it? So I think Mark and Jason actually describe it really well. There are five archetypes. So obviously for me, it's huge conviction about the technology, about the markets, about the opportunity, and huge fear of missing that.
But remember that my parents really taught me that there is a place in the world where technology, good technology products matter. I remember when I was six, there was a magazine about Bill Gates, building Microsoft and not being very socially accepted everywhere back then. And my mother just told me, these examples happen in the world. I think she didn't fully understand that San Francisco and Seattle are different cities, but still, that's deeply rooted in me. Childhood shapes us a lot. Yeah. What did your parents teach you? For them, what was important is to just be in merit-based environment. And that's why getting to California felt so important.
What's your biggest lesson on hiring? Speaking of a merit-based environment, we see a lot of focus on that, your cognitions of the world who hire mass Olympiads. Yeah. What's your biggest lessons on hiring effectively? I think one of the things why Europe thrives so much, I know that you typically say otherwise, but let me just challenge you, 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, Nubius is UK and Netherlands. Let's talk about the companies on application layer that matter. I know that you mentioned Mercore and you mentioned Harvey, but Legora, Eleven Labs, Lovable, 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? But on every other layer, Europe is extremely competitive. ASML, without ASML, this whole thing just wouldn't happen.
So I think fundamentally what matters is if Europe is going to figure out energy, but that goes outside of my pay grade. So very important to say here is that now there are more opportunities to create company from different kinds of cities, from different parts of the world, while before it all felt extremely centralized. And we are excited about that. And another thing about hiring is that in Silicon Valley, unfortunately, what I'm seeing is that people just jump between jobs every two years. That's why I think Europe can be so competitive because the sense of loyalty matters a lot. And that goes a little bit to the childhood we just discussed. If you're a Fulham fan, you are not going to root for Arsenal just because they won or played in the Champions League final. But in the United States, if Lakers are on the top, people are going to say, yeah, I'm a fan of Lakers because it makes it easier to start conversation.
When you think about your own CEO style, what's changed most? In AI, it's so important to look at actual signals and actual adoption and having access to raw information. I was obviously taught the corporate school of management in the United States. And when I look at the CEOs whom I'm learned from is obviously Jensen, Elon, and Nick. Nick was on the show. Those three, they completely abandon all the management principles. They don't necessarily are fans of one-on-one and soft feedback. All of them, I think are encouraged, being down to the points, knowing the details, while it would be called in corporate America something micromanagement.
What management principle do you disregard that many people think is important? I do believe that it's as simple as hire the best people to do the best work and figure Makes it easier to start conversation. When you think about your own CEO style, what's changed most?
In AI, it's so important to look at actual signals and actual adoption and having access to raw information. I was obviously taught the corporate school of management in the United States. And when I look at the CEOs whom I've learned from, it's obviously Jensen, Elon, and Nick. Nick was on the show. Those three completely abandon all the management principles. They don't necessarily favor one-on-ones and soft feedback. All of them, I think, are encouraged to be down to the points, knowing the details, while it would be called in corporate America something like micromanagement. Nick: What management principle do you disregard that many people think is important?
Lakers: I 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. People just create so much theory around that. There are so many 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. A lot of them bluntly do see dollar signs. We mentioned the transactional nature of America and secondaries are a part of that. How do you think about doing annual tenders to retain people? Across our team, roughly 50 are in California. Maybe we're going to get to roughly 50 remotes and over 300 in Kazakhstan. So 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.
I do too. What's the labor arbitrage on cost between Kazakhstan and the US? Lakers: I know that a lot of people, when they look at Hicksell, they think about the arbitrage. Is that not true?
Lakers: Look, Kazakhstan is top five in the world in physics. You look at the recent International Physics Olympics for high schoolers—they're top five in the world, on par with the United States, China, India. And this is also the core of our team, our people who won international competitions in math and physics. That's the first part. The second part is that Kazakhstan actually took the Soviet school of math but really upgraded with Singaporean principles. The Singaporean system of education is considered to be probably the best in the world. At least many people in Silicon Valley believe that. The government basically subsidizes for thousands of high schoolers to study abroad and many of these people come back. There's strong desire just to have density of talents there. It's the top 10 largest countries in the world with over 20 million population. We are also actively hiring and bringing their talents from Europe, from other countries in Asia. People just enjoy benefits like 15 percent personal income tax.
Yeah, man, it's like don't even get me started on the UK. The UK will tax you to breathe. Seriously, in the UK you get your paycheck and then it's a hundred thousand and then you get the end and it's three thousand five hundred. But it's also English common law so it's not as bad as people think. You move here. Oh, let's swap places. Do you have a mega pad in Kazakhstan? No, I don't. I don't own any property. Why?
Remember that I come from an Asian family. When we sold the company I made over a million dollars and I spent all this money buying apartments for my parents, relatives, my wife's parents because they're just part of the culture. Extended family is not small by any means. But it's just part of the culture to give back. When it comes to family, especially to my parents, they obviously sacrificed a lot so I felt like I had to give back at least monetary things which I could do. But I drive a Tesla Model 3. That's it. I'm not a guy who's going to show up with a Lamborghini or Porsche. Do you invest? We mentioned Solve Intelligence. When before I did that, but now I spent roughly 90 hours a week, 80 to 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, two weeks, three weeks, then I try to take Sunday off to spend the whole day with my son. Over the last three months, yes, I was able to find one day when I spent end to end with my son without emails, without talking to team members. I 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. But when it comes to hard work, the people whom we know in common, we talked about Peter Sellis—a legend in consumer space. Obviously Jack, I spent a decent amount of time with them and other product leaders. The density of product talent 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 recent trends in product design, activation. They know data really well. So I don't believe that there is any shortcut to hard work.
Three hours a week with your wife? I don't know about you, but mine would dump me for three hours a week. How do you make marriage work on three hours a week? Look, I'm very grateful for my wife for being patient. It's also very different if that's Asian culture. It's just more natural to try to sacrifice for each other. I'm deeply grateful for her for supporting me. But sometimes at this scale I get invited to parties and 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's always some urgent fire last minute and my wife just goes, "What fire was most urgent?" What was it?
Yeah, look, I think obviously for all the things which we touched base earlier, whenever we are not very good at communicating the features or we felt, I mean now it's a team of 40 so now the life is way better. But early days obviously I was involved in all the fires. I think recently all the types of attacks on AI companies. It's crazy. LLMs are being used to hack companies. There are new types of LLMs to do some frauds. Bots using credits and then doing auto refunds. Look, since I have a machine learning background myself, data science background, I still can move a needle substantially when it comes to statistics and data. So I have to be involved somehow. But these LLMs, they amplify many types of behaviors including various types of attacks and fraud. And we have to fight against that.
We're going to do a quick fire round. I say a short statement, you give me your immediate thoughts. What have you changed your mind on most in the last 12 months? Oh, I was thinking that HubSpot is going to get obsolete. Everyone is going to build their own CRM. But when especially when we hire and scale B2B go-to-market team, just having a familiar interface matters a lot. Wow. I would still say they're going to get fucked. You think that just stickiness is there with SMBs? Yeah, I do think so. Especially I see that when I hire go-to-market talents. Wow. Why? What is it about hiring them that makes you think that?
Just they're so used to it. I mean, people who are very good at understanding customers and talking to customers may not just simply accept a new interface so quickly. Just having HubSpot as a system of records, being able if there's any mismatch to understand where the data flow went wrong, I think that's just still very valuable. Just the familiarity. What do you believe today that everyone else thinks is crazy?
I 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 authentic content. It's going to be 50 to 100x higher CPM than AI generated content. So it's going to be way less in terms of content created by humans 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 with 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 better jobs so that you use Hicksfield at least for the overlay on top of existing videos.
Dude, I would love that. I mean, again, they take three hours. People don't know this. I spend two hours a day just doing Instagram now. We decided that Instagram short form is going to be
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 authentic content. It's going to be 50x higher CPM than AI generated content. So it's going to create way less in terms of content created, 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 with 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 better so that you use Hicksfield at least for the overlay on top of existing videos.
Dude, 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 and 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.
And that's extremely smart of you. Going back to some of the topics is clipping is a huge topic and that's got its own upsides and downsides. But obviously everyone sees this opportunity to win, to build massive top of funnel, hundreds of millions of views with short form content, as long as you can have downstream monetization or value creation like you do.
Totally agree with you. What job today does not exist that will be big in five years? Okay, so in five years, people, especially in our space, creative directors are going to be talking to computers and generating stories real time and video. AI is going to help create multiple variations. Today there is no word to really describe that. Because there are also script writers, screenwriters like those who are going to break it down shot by shot. Then there are people who do storyboarding. Then there is a person who oversees all of that, like a movie director. And so on. So there are 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.
Who do you not have on your board that you would most like to have on your board? Maybe out of more professional CEOs?
I'm definitely Frank Slootman. Going back to the point, I was curious all the time. Does no culture exist in California or not? Can it allow you to scale companies so quickly? Is it possible to build successful enterprise go-to-market motion with no culture? And when I read his book called Amp It Up, I realized it's possible. So I'm a huge fan. I watched all his interviews. The challenge with him is 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. So he built a GTM machine at Snowflake, but Databricks wiped the floor because they moved product as the priority, not GTM. And that was dangerous.
I prefer Chad Peet. Chad Peet? Oh dude, this guy is no. I'll introduce you afterwards. He's the best sales leader in the world. And he is terrifyingly good. We probably should have him on the board. Oh my God. I can find any way to have him on the board. He is terrifyingly good. So what's the biggest lesson from Snap? The momentum doesn't last forever. Today's Snap market cap is below 15 billion. There are lots of memes on the internet, but this is a great company. It cares so much about trust and safety and experience and it puts it first.
Do you think it is a great company? No offense, but it's been mismanaged. Its SPC is through the roof. It's tough to say it's a good company.
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 like, "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 don't take this for granted. The nature of capitalism is there are ups and downs. And since we're building long term, we just should capitalize on the opportunity, like with fundraising, and just keep pushing progress every day.
What 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?
Maybe saying these trades 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. 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. 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 really like, "What's gonna happen?" He basically acquired a second CEO. 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?
Yeah, look, but this happens with Instagram with WhatsApp. That's why I'm saying we just maybe should put Meta a little bit in its own league. But he got rid of Systrom and Krieger. He's been like, "No, no, no. You, Alex Wang, are my guy." Do you see what I mean?
Yeah. It's the best talent. I'm saying, look, I do believe that it's a little bit early to look at the whole Meta AI initiatives. We probably need to see a year of successful launches and so on. And then we can look back and see what was good and 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. Okay, revenue say are billion. What are the revenues in 12 months time?
Our current business model projects 4.5 by the end of the next year. But these basically involve substantial deceleration. And that's what 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 percent month over month. What do you think it is? They said 4.5. What do you think it is? This is me to you, not me to your finance team. Over 10.
Over 10. Let me tell you why. In a lot of adoption in creative AI space is driven by monetization. All these direct-to-consumer brands making more ads and also having aspirational cinematic AI content inspires creatives to explore the tooling. It feels to me that Hollywood starts to embrace AI mostly today as a way to use as a tool for hybrid production, as a new form of CGI, 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, which at least comes from my conversations, is extremely positive.
If 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 like 80. Look, we're not chasing just the valuation. Because again, the goal is just to make sure that the company can be sustainable over 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? Do you want to be public at some point?
Yeah, I do believe that Hicksfield has great potential to be bigger than Apple, Lavender, and Shopify. Because fundamentally, building is one part of that. Shopify is one layer of infrastructure. Then for coding, there is obviously Cloud. There is Codex. But what matters is distribution over time. Distribution matters. You know that this better than any other VC, right? It's my business. That'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, and 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 also on average, there are at least 10 image references for every, for every scene. The reason why it's important, cause it's important to define how the characters look like, how the background looks like, like how actually characters are located to each other in the scene and so on. And so that's why like prompting and like just the workflow is so complex. Benchmarks just don't, don't represent that. So going back to the model selection, why did we decide we're going to do our own? And then why walk it back? Benchmarks just don't, it's true. That's like 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, um, aesthetic photo shoots and product consistency. This is what allowed us to scale them from 20 to a hundred million. Benchmarks just don't, but it's really good at the end. So help me understand Alex, why did you decide that you were going to do your own models? And why did you abandon them? We still do them whenever we see like specific use case, like these photo shoots. But, 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. Do 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. So, um, first of all, whenever I just, to be honest, whenever someone says we build our own models, very likely what they mean is something what's seen, what's happened with Coursor. And we, we do remember, right? A lot of companies, they actually take open weights model and just post train on data. And post training can happen in two ways.
Most important is whenever you have, um, customer data around like decisions they make, like sequence of decisions, and you can teach the model to actually take, like, learn how to compress these 10 steps into one step. Like this type of reinforcement learning is the most valuable. So, and I think like increasingly more and more companies will have to do that. Frankly, just, we see this in the market as well. So the most, 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.
And that's why like Open Router reports that a share of open source models went from below 30 to over 60 within, within this year. What do you think share of open models will be in two years time? Look, I do believe that just because the cap capitalism works. I mean, open, the ananthropic steel 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, uh, for coding still remains to be very, very prolific use case where coders are always jumping to, to, to, to the recent model. It's overall, 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 create, uh, ad creatives, um, a week. They want to have maybe cheapest, more steerable models. Cause like PhD level intelligence is not necessarily needed for, to make viral social media video. So, um, and that's where we actually have seen that, um, we get like 80% plus margin whenever we run open source models, like post-trained open source models. Uh, but it can be way more cost efficient for our end customer compared to the proprietary models. What's the comparison on margins between open versus closed fee?
The margin on own models and open weights models is over 80%. Um, 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 Hicksfield is that, um, Igenic grows so quickly and actually for us as companies start to actually create those organic workflows to make more ads, we choose which model we can use. So like we choose what model to use in over than 40% cases. In a way model routing becomes a core feature of the business. No? Yeah. We call, we call it tokenomics essentially, right? As like there is certain amounts of work
customers want to do. Um, how can we optimize number of tokens which requires 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, um, the, there is the versions of models. So there are these state of the art models, models which have to be really good in computer use like Astra or encoding. Um, but they can be prohibitively expensive. And we were chatting about that. It's like on average at Hicksfield,
person on the team spends over $10,000, over $10,000 a month on various models. And remember, like we're split across United States and Asia across. So how much do you spend on models per month? So internal usage of models a month is over 4 million. Wow. How many people do you have? We have close to 400 people. And just want to make sure that the math adds up. Yes. It's, um, it's definitely over, it's definitely over $10,000 per person. How has that changed over time? That's the best question of the whole show, by the way. Um, that's the best question. What actually started to happen is the creative team started to do vibe coding.
Like the, like, like this month I was, I just caught a guy who spent over 30 K in a week on Astra model. Because he was frankly frustrated that some like asset organization workflow. And as you said, like 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, 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. 30,000 in a week. Yeah. Yeah. Many people spend over 10,000 in a week. Do you mind? Yeah. My finance team will probably say, I don't know if, if you know, if you asked any of them,
but they will probably say that I'm like being too stubborn, too relentless to control this spend. Cause sometimes I feel it goes like, it really goes out of control. Like 30 K in a week is quite a lot, but we learned this. So this was actually net passive experience. Okay. So the internal spend, 4 million, about 10,000 per head. What will that be in 12 months time? Do you reckon? So that's very interesting. So across the top, the top engineers and across top creatives, I think it's going to keep growing. And I do believe we are going to get to spend close to 50K and 100K 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 points. But also for a lot of other jobs, let's say we take legal finance and so on. I think it really stabilizes around like $500,000 a month very, very quickly. With 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? I 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. Like at these professions where I say quite close today, I definitely can say that there is, 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, it doesn't like, AI just doesn't work. Revolut has now over 92% resolution rate on customer support for consumers. Pretty good.
It's pretty good, but obviously they did invest a lot into that. A shit ton. A shit ton. And, 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. So, um, we have to, we have to keep up that agents with all the information and so on. And just due to the high velocity having, um, extremely smart, coordinated team is, is very important. That's really interesting. How product velocity increases leads to harder customer support for agents. Of course, because, uh, the agents are as good as context and the rules, which they have.
And if context and the rules change pretty much twice a week, it gets a little difficult. When you look at your engineering team today, what are they on? Are they on Cursor? Are they on Codex? Are they on CoreCode? So from a period from March to June, everyone really moved to Claude, um, 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 Claude to Codex, um, as of mid June. And, um, over the time, uh, creative, especially 10X creatives
and the codex moves to codex as well. But look, I do believe that it's, it's, it's cyclical. So, uh, It's so cyclical. My question to you is, will we continue to see the velocity of model release that we're seeing now? You know, in three years time, will it be like, oh, Gemini this week? Oh, cool. Anthropoc this week. Oh, open AI this week. Or will we see a, a reduction in model release rate? I don't think that's going to happen anytime soon. So I believe like, for example, recently, OpenAI announced that they basically build OpenAI for law, right? But that's only V0. So over the time,
they also are going to try to print smaller, specialized models for like, not like exactly smaller, uh, but really specialized model for certain use cases. Um, clearly like Astra excels in long-term horizon. Do you buy that? Like I 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. Like 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. Yep. We've just hacked into the Australian government, by the way, but we're here to serve your law firm. Uh, okay. Yeah. So first of all, I think, uh, just, uh, definitely the ability to switch internal use just for internal teams outside of law firms. I think that's, I think that's definitely happening. Uh, oh, I think we both invest there is in company called solve intelligence. Love it. Yeah. Very specific. Very specific. And let me try to maybe bring couple examples. Why like solve intelligence is so special and like where, like for example, how we learn from this.
What's going to happen very often is that a company want to just control the patent workflow, flow, even if they outsource the work and that's very valuable just to have one system of records. So whoever can create AI native system of records is going to win. And by the, going back to Higgs, why it's so important for Higgs field, there are so many systems today, which are used for just to store assets. Um, like 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. Like 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 like 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 Higgsfield, we invest 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. Do 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. You know, 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. Instinct is a wrapper. Of course it is. It's not that difficult to 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? I know, like you ask this, everyone. So, and this is, because this is on top of everyone's minds, like how to think about the metrics which matter today and how to think about the moats. So,
I think it's very difficult to figure out where the value accrues in the supply chain. We do believe that there are only two, like, ways of modern value creation or moats today. 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. So 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. So, and like, 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 moat over the time. When 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, you know, different aspects of, you know, inference band. What was the best VC meeting you've ever had?
Obviously, Yuri Milner gets it. How was that meeting? Was it in person? Yeah, definitely in person. And definitely Yuri stays on top of all the trends. Where was it? Were you nervous? I 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 come from Asia to the West. And also, fundamentally, we believe that most of contents on social and in the world is going to be AI assisted or AI generated. And the, and like this
multi trillion advertisement industry, and you know, like contact contextual advertisement is the main business model of the internet. It's all going to be substantially disrupted with video AI. This industry still going to be very valuable, but it's never going to be the same. Did you know when you left the meeting with Yuri that he was going to write the check? You know, sophisticated investors, they can play games. I had like so many scars, like people really shook hands, 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 happened. So you'd never can be sure. But it didn't happen with Yuri. I think there's a discount placed on Higgs field because you're not Silicon Valley insider. Like, let's be clear, you're at a billion in revenue now. Yeah. 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. Yeah. You could also argue that's what cognition was well at 50, right? So there is definitely an upside. Okay. Up a band even more. Yeah. A hundred percent. 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 become, 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 VIN. The company is worth over $200 billion. It's insane. So look, and as we think long-term, just this, you know, like these multiples don't matter that much. As we know, we're building long-term, we're going to be over a hundred
billion. It's true that most of the people don't get the opportunity that we are going up for 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 and D. Like 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, and that's good for us that many people don't understand the opportunity, this large market, which we go after. Can I ask you, you've mentioned Asia, short form dramas a lot. What percent of revenue is from Asia versus the West? So, oh, the West makes well over 70% of revenue. Oh, wow. So, but just important to say that we learn a lot from trends coming from Asia. Like Hicksfield does not exist in China, for example, which is massive market for AI. Hicksfield, but the largest city
by usage is Seoul in South Korea, while the largest country is obviously the United States. What's the biggest lesson from Asia that you've learned? There 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, 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 much direct to consumer, rather than using some resale platforms and so on.
I sacrifice a lot of life for the life that I have and 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? Look, this is goals even beyond that, because my from the age of seven to 12, my 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, it was basically minor, so he had to go to all these camps with me. I also played checkers, I was top three in the world, so we went, we traveled throughout the world. And 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. Totally. Totally. But you don't need to do what you're doing now, Alex. I didn'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? So I think Mark and Jason actually describe 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, like a 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, oh, like these examples basically happen in the world. I think she didn't fully understand like San Francisco and Seattle are different cities, but still, that's still deeply rooted in me. Childhood shape us a lot. Yeah.
What did your parents teach you? For them, what was important is to just be in merit-based environment sort of. And that's why getting to California felt so important. What's your biggest lesson on hiring? Speaking of a merit-based environment, we see a lot of focus on that, your cognitions of the world who hire, mass Olympiads. Yeah. What's your biggest lessons on hiring effectively? 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 who are the most relevant NeoClouds today? It's Nscale, IRAN and Nubius and Crusoe. Mm-hmm.
Crusoe, okay. Silicon Valley story. IRAN from Australia, Nscale from the UK, Nubius is UK and Netherlands. Let's talk about the companies on application layer that matter. I know that you mentioned Mercore and you mentioned Harvey, but Legora, Eleven Labs, Lovable, 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? But if we go, because I think like, by usage, they have, 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 ASML, like without ASML, this whole thing just wouldn't happen. So I think fundamentally what matters is if Europe is going to figure out energy, but that goes outside of, that's above my pay grade, right? So very important to say here is that now there are more opportunities to create company from different kind of cities, from different parts of the world, while before it all felt extremely centralized. And we are, we are excited. We are obviously excited about that. And another thing about hiring is that in Silicon Valley, unfortunately,
what I'm seeing is that people just jump between jobs every two years. That's why I think Europe can be so competitive because the sense of loyalty matters a lot. And that goes sort of a little bit to the childhood. We just discussed that. Like, let's say if you're a Fouham fan, you are not going to root for Arsenal just because they won or played in the Champions League final. But in the United States, if Lakers are on the top, people are going to say, yeah, I'm, I'm a fan of Lakers because it's just makes it easier to start conversation. You know, When you think about your own CEO style, what's changed most?
Lakers in AI, it's so important to look at actual signals and actual adoption and having access to raw information. I was obviously taught the corporate school of management in the United States. And when I look at the CEOs, whom I'm learned from is obviously Jensen, Elon, and Nick. Nick was on the show. So like, obviously like those three are, those three, they completely abandon all the 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 micromanagement.
Nick What management principle do you disregard that many people think is important? Lakers I 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 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. A lot of them bluntly are, do see dollar signs.
We mentioned the transactional nature of America and secondaries are a part of that. How do you think about doing annual tenders to retain people? Across our team, roughly 50 are in California. Maybe we're going to get to roughly 50 remotes and over 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. I do too. What's the labor arbitrage on cost between Kazakhstan and the US? Lakers I know that a lot of people, when they look at Hicksell, they think about the arbitrage. Oh my gosh. First and foremost, the way- Is that not true?
Lakers I know. Look, Kazakhstan is top five in the world in physics. You look at the recent International Physics Olympics for high schoolers, like they're top five in the world, on pair with the United States, China, India. And this is also the core of our team, our people who won international competitions in math and physics um that's the first part the second part is that about kazakhstan is that they actually took the 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 um and they and the government basically subsidizes for thousands of high schoolers to study abroad and many of these people come back um and there is strong desire just and so just the density of talents uh definitely got there it's uh 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 percent personal income tax yeah man it's like don't even get me started in the uk will tax you to breathe uh seriously it's in the uk
you get your you know paycheck and then it's like i don't know a hundred thousand and then you get the end and it's kind of like three thousand five hundred but it's also english common law so it's not like that bad as people think uh you move here oh let's swap places do 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 so um whenever we sold the company i made over a million dollars and i spent all this money buying apartments for my parents relatives my wife parents because they're just part of the culture and the fame like
extended family is not small by any means but look it's just part of the culture to give back and then um 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 at least like things like monetary things which i which i could do but i drive like tesla model 3 like and that's lee so like i i'm not like a guy who's gonna just show up with lamborghini or porsche do you invest we mentioned solve intelligence um when before i did that but now i spent roughly 90 hours a week 80 90 hours a week on hicksfield i try to spend ideally um at least
um three hours a week with my wife at least five hours a week with my son um sometimes i do the catch up because when i travel um for a week for two weeks for three weeks then i try to take sunday off to spend the whole day with my son and over the last three months yes i was able to find one day when i spend like end to end with my son without emails without talking to without talking to the team members i get in trouble for this but i think there's no um 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 um but i think when it comes to um hard work like the people whom we know
in common like we we talked about like let's say peter sellis like legend in the con in consumer space obviously jack look i i spent decent amount of time with them and other product leaders at stamp like the density of product talent and stamp was unprecedented all of them work really hard all of them are smart i i like none of them just uh checks emails for five hours a day and calls it work each of them is deeply rooted into the recent trends in product product design activation they know data really well so yeah i don't believe that there is any shortcuts or hard work three hours a
week with your wife yeah i don't know about you do mine would dump me for three hours a week how do you make marriage work on three hours a week yeah look i'm i'm i'm very um i'm very grateful for my wife for being patient you know it's also very different if that's like asian culture uh it's just kind of more natural to try to do sacrifices for each other sort of um and i'm deeply um 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 um very frequently so
wait you say yes and then she goes yeah i say maybe we both can some come together then there is always some urgent fire last minutes and my wife just goes what fire was most urgent what was the oh yeah 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 early days obviously i was involved in all the fires um i think recently um all the types of like attacks on ai companies it's crazy it's like 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 look i like since i have like kind of machine learning background myself data science background i still can move a needle substantially when it comes to statistics and data data so yeah i have to be involved somehow but like these llms they they amplify many types of behaviors including various types of attacks and fraud but and we have to fight against that uh we'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 oh i was thinking that uh hubspot is going to get obsolete everyone is going to build their own crm and but when especially when we hire and scale b2b go-to-market team just having familiar interface matters a lot wow i would still say they're going to get fucked you think that just stickiness is there with smbs yeah i i do think so and especially i see that when i hire go-to-market talents wow why like what is it about hiring them that makes you think that just they're so used to it i 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 records being able 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 everyone else thinks is crazy i mean look i think uh 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 10 50x 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 uh than the air generated contents but even when i look into your content specifically like you made multiple very successful shorts millions of use better than anyone else in this space and you do a lot of overlay while the content is authentic i think we should do better jobs so that you use hicksfield at least for the overlay on top of existing videos dude 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 um 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 and that's extremely smart of you like 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 everyone sees this opportunity to win to build massive top of funnel like hundreds of millions of views with short form contents as long as you can
have downstream monetization like or value creation like you do totally agree with you what job today does not exist that will be big in five years okay so in five years people i'm 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 is also there are script writers um ram then uh screenwriters like those who are going to break it down shot by shot then there are people who do that storyboarding then there is like
people who person who oversees all of that like movie director and so on so there are so many there are so many there are so many parts of that but eventually taste is gonna matter a lot and just having stories to tell and there is no word to describe it today who do you not have on your board that you would most like to have on your board maybe out of like more professional ceos i'm definitely frank slutman because going back to the point i was just curious all the time does no culture exist in california or not can it allow to scale companies so quickly can it is it possible to build
successful enterprise go-to-market motion with no culture and when i read his amp it up book like book called amp it up i realized it's possible so like i'm a huge fan i watched all his interviews the challenge with him 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 data breaks wiped the floor because they move product as the priority not gtm and that was dangerous i prefer chad peats chad peats oh dude this guy is no i'll introduce you afterwards he's the best
sales leader in the world um 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 um so what's the biggest lesson from snap the momentum doesn't last forever um like today's snap market cap is all 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 no offense it's like it's been mismanaged to it's spc is through the roof it's tough to say it's a good
company that's why i say that momentum doesn't last forever when snapchat was worth eight 80 billion and the gap with meta was less than 10x then it felt oh we just go explore we we just we just really must lean in um but momentum doesn't last forever and that's my core learning so that's why like while we do have the positive momentum we don't we do not take this for granted clearly um like the nature of uh capitalism is there are ups and downs and since we're building long term we just should capitalize on the opportunity like with the fundraising and just keep pushing progress every day what is the
reason why the divergence between matters market cap and snaps market cap has increased so significantly if there was one reason just maybe saying these trades a lot of public companies did not figure out their ai story um snap unfortunately is part of that we have seen other great companies like figma trying to tell their story you mentioned canva it's not necessarily easy to be successful in private markets and public markets and zach is one of the best uh ceos of all time because he managed that he's such a beast he's such a beast you watch him last night with the event
and you're just like ah now i get it like that totally makes sense and you know what scale with alex wang i was one who was like really like what's gonna he he basically acquired a second ceo you know 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 yeah look but this happens with instagram with whatsapp that's why i'm saying that we just maybe should put meta yeah a little bit in its own league yeah but he got rid of sistrum and krieger here he's been like no no no you alex wang are my guy do you see what i mean yeah
it's the best talent i'm saying look i i do believe that it's a little bit early to look at whole meta ai initiatives we probably need to see like year of like successful launches and so on so 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 um is phenomenal okay revenue say are billion what are the revenues in 12 months time our current business model uh projects uh 4.5 it says by the end of the next year but these basically
involve substantial deceleration and that's what like just my finance team like there are a couple strong quant people they told me that's just how the business works but look we are still pushing to grow at least 30 percent month over month what do you think it is they said 4.5 what do you think it is this is me to you not me to your finance team over 10. over 10. let me tell you why like 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 like the aspirational um cinematic ai contents as this inspires creatives
to explore the tooling i've it feels to me that hollywood starts to embrace ai mostly today as a way to as a tool for hybrid production as a just new form of cgi the bots bots are the bots of the bots bots bots bots bots bots bots bots bots bots bots bots bots bots bots 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. If 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, like 80. Look, 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? Do you want to be public at some point? Yeah, I do believe that Hicksfield has great potential to be bigger than Apple, Lavin, and Shopify. Because fundamentally, building is one part of that. Shopify, one layer of infrastructure. Then for coding, there is obviously a cloud. There is codex.
But what matters is distribution over the time. Distribution matters. You know that this better than any other VC, right? It's my business. That'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.