The Untold Story of Higgsfield | Burning $4M a Month on AI Models | CEO, Alex Mashrabov

On average at Higgsfield, a person on the team spends over $10,000 a month on various models. So internal usage of models a month is over $4M.

Higgsfield. This is the story that no one has told in startups yet. The company has just hit $1 billion 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 3 in the world in competitive programming. I just caught a guy who spent over $30K in a week on Astra model.

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 Higgsfield 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, like how social media has become like an elevator for you, opportunity to create fund, and so on.

Dude, it'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. So my father is from Uzbekistan. Uzbekistan is a country in Central Asia where, like, if a family of five people makes $1,000 a month, it's considered to be wealthy.

It's like not very high standards of living, unfortunately. So, um, 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, um, my mother had to work three jobs because basically my education was to compete in programming competitions all the time and to go to various educational camps where I could learn from the best, like certain data structure, 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 were so young?

Absolutely. Uh, but, but, and, and I'm very grateful to my parents that they showed me the path, really, from that's early on. Um, definitely when you come from this part of the world, think about post-Soviet countries, uh, India, China, like getting to the top of the rankings in any competition, in any international competition is the only way to really break out.

So by the age of 19, I was able to get to top three in the world in competitive programming. But then, instead of pursuing like, um, like academical career, I decided to do startups.

I'm sure your parents were thrilled. Uh, can you take me to that decision? Like, this is like the penultimate moment. You've worked 19 years for, your parents have told you, this is like the mother lode. This is the thing.

And you're like, I'm going to go and do this really risky thing called a startup at this point. Like, 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 just doing optimization, make it run faster, um, parallel across multiple machines, and so on. And, um, I was, 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 DeepMind and Meta. And, uh, but my passion was actually different. I was very, very surprised to learn when I come to, to a set for the first time how quickly Uber actually spread out.

And I was thinking if, like, 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, for the phones?

Maybe it's going to happen with AI.

Okay. And so that was the company that we built before that you sold to Snap?

So yeah. So the company was called AI Factory. Um, was fortunate to meet Mahi 2018. He's co-founder of, uh, Higgsfield. And he is, uh, like, uh, veteran of Silicon Valley, went through ups and downs, and, um, sold it to Snap for $100, for $166 million.

And, um, then I was leading Gen AI there.

Pause. No offense, dude. You come from, um, you know, a family of incredibly ambitious parents who push you to do well, and you just skip to the moment where you sell for $166 million. It's a lot of money.

Um, 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 when, and AI multiples were not like 200 to revenue as they are today, but closer to zero because AI was not a topic.

So there was like severe dilution, which we experienced. So you just to calibrate.

So can you, okay, what was the round?

No, look, I mean, back then, rounds like rounds of like $1,2 million, having like $1,2 million in investments was considered to be really good. Uh, but it, but it was still an opportunity for me to finally go to the United States.

So after the acquisition, I permanently moved to, uh, first to 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. So, um, San Francisco is definitely a place where no one judges by race, nationality, and so on. And that's, that's, uh, that's truly phenomenal. There is definitely a meritocracy in a sense that it's possible to meet anyone.

But in the same time, what I see across Silicon Valley investors, it's extremely consensus-driven. So, um, I mean, 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 Higgsfield come to be?

Back then, like Snapchat 2020, was, uh, really growing so, so quickly. And the face filters, which my team has built, was driving most of daily new users. What, what's important is that, um, these face filters, we were able to manage to run on mobile devices.

So it was virtually for free for Snapchat. It's not like current LLM tokens cost. Um, and, but, but it, and it, 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 AI product.

But then, um, 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, and this is a major gap. Like 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 in the same time, most of the companies in the world cannot simply do that. And basically, no, because no one simply can keep up with the pace of production for social media as trends change pretty much every day.

Mm-hmm. And 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?

Yeah, absolutely. So where it all really started is that we, like, there was a tool, like to upload a set of images and transform them into a slideshow with music.

Hmm.

It's kind of 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, um, especially 2023, it was absolutely clear that scaling laws finally work.

It's not just a concept from science that scaling laws work. Video just takes a couple, I mean, maybe two, three years longer than LLMs and coding. Uh, but it was clear that, uh, actually finally scaling laws should work in video as well.

And I just decided just to take a bet.

But I just want to go back. 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 like a couple of pivots before and the meandering that we had. So what happened when we launched? Did we have immediate product market fit?

No, actually we spent more than a year in a search of a product which could work. We burned more than $10M out of $16M raised in seed fundraising. So we felt we have just one attempt left.

And frankly, I feel I'm responsible because I was focusing on the wrong things. I think I just lost the touch with reality back then. I was so much optimizing for what's hype today, what's theright narrative, how we can hijack the attention, all these things, really.

Like everything instead of building a good product. So when we had less than $6M left, I guess it was slightly less than $5M 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, um, so, and then 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, uh, 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.

Um, yes, it's definitely when you know, you know. Like, for example, we don't do any paid. And like, we have, we have on the team people who scaled businesses to over like $1BN and $2BN in revenue, like other businesses, um, with paid advertising.

Like at Higgsfield, we decided to really make a bet that.

You don't do paid?

We don't do paid.

Is influencers not paid?

That's a good point. So, um, with influencers, there is typically, there are different types of influencers, but typically there is, uh, some fee for just video production and then like some cost per click, like attribution, which is like works really well on YouTube.

You guys got into some controversy for like, I can't remember what it was. You were like paying people to promote for you or doing something rogue with influencers. Was that completely unfair? Was it kind of my bad we did, we did do that?

How do, how do you respond to that?

The main takeaway from like our experience is that it's very important to own, own distribution. Distribution now more important than ever. And like, we basically, uh, did outsource. We had just a team of like two people on creator and customer success side, and we just did outsource to the agency.

And this was not, uh, that was not a good experience. But, uh, we are still, but, 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 like his own sort of AI-generated stream.

Um, like no one else did this before because this is like real creator making a replica of themselves. A lot of people start to question, uh, start to question their, um, like, is it really authentic contents or not?

But in the same time, those creators are under immense pressure. We all know about the story from Mr. Beast about like really how much, like, there is just pressure to constantly perform. So, um, and 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 so what's happening today very frequently is that, um, those A-tier celebrities, they simply come up for a recording on like, let's say, green screen. And then there is just a lot of post-production which goes on top of it.

And it feels to me that, uh, we are, we're, we're naturally going to come to the 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?

Uh, so today is actually an exciting day. Like when we recorded, just Bloomberg article went out. So that's we crossed $1BN in annualized revenue. Um.

If I had a gong here, I'd be like hitting the gong. $1BN in revenue.

Yes. Um, actually it took us 18 months from $1M to $1BN. For Cursor, it took 24 months. Um, so we are probably, uh, probably like the thirds after OpenAI and Anthropic.

18 months from $1M to $1BN?

Yes.

How do you calculate revenue? Like it's a controversial topic. Um, how do you calculate revenue?

Absolutely. Uh, by the way, your, um, co-host, uh, Jason, also asked this question in May. Luckily, the answer didn't change. So we are at least consistent. So, but let me be transparent on that. What we do is we look, um, revenue over the last four weeks and multiply it by 13.

From what I know, OpenAI, Anthropic, Lovable, all of them use the same methodology. What's very important is that we are, we take revenue, not sales. So if that's like annual subscription or annual enterprise contracts, we prorate this across 12 months and take only this, uh, and only take like a piece which corresponds to one month.

So 28 days to be, uh, to be precise. That's the first piece. And second, it's only live revenue. It's only live revenue. We are not taking like three-year enterprise deals and baking into like $1BN 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, what would that be?

So, um, video AI is still relatively early. In my opinion, uh, 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.

Um, 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, um, six months ago, spending just subscription $99 a month, $99 a month, and now we just signed a deal over $6M.

$6M?

$6M a year,right? So yeah, like this level of acceleration is something which really like mind-blowing to me.

Dude, what are they getting for $6M a year? That's like a Hollywood content team almost.

So there are multiple trends, um, and all of them frankly coming from Asia. So first, we're seeing a lot of, um, direct-to-consumer e-commerce companies rebuilding their whole go-to-market to be AI native, where they make, uh, where they just make hundreds of ads, if not thousands a week, where they can A/B test what performs well.

But we all know about like short-form dramas,right? Like most, like short-form dramas today is an industry over $10BN, 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 look, I think, uh, like this adoption obviously is, uh, coming like bottom-up, but, um, that's very difficult to refute this new reality.

What percent of revenue is consumer versus enterprise?

So, uh, that, that, that's a great question. So, um, so business revenue is, uh, slightly over 50%.

Wow.

Yeah.

That's impressive.

Thank you. Um, on the consumer side, it's also very important to break it down. So on the consumer side, out of these 50, is, um, around like 10% is pure consumer use cases, pure consumer. And that's roughly people who use it on mobile.

So share of our revenue from mobile is less than 10%. That's why we are, we are very different from many other companies. And, but there are lots of aspiring creators, like basically those people who are freelancers doing social media marketing projects and so on, who try to learn video AI so that they can make more money.

It's true that their behavior is a little churny. Uh, within a year, most of them actually come back to try again. And we do believe that over the time, most of them are going to figure stuff out and they're just going to become this new AI-native workforce.

So it's still important for us to educate them. And, uh, that's why we invest so much in like Higgsfield Academy, YouTube channel, and so on. But we also are fully cognizant that we will never be able to win in a market of subscriptions of $20 a month.

Mm-hmm. So why?

Because like, I think like today, Google and OpenAI, they pursue like ads so much, but fundamentally, I think they are going to completely demolish all the prosumer subscription markets, which is, uh, $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 the time. Um, I know this is a very contrarian bet, but, um, at least we can see some of that already.

You're saying 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, which is already happening. And I do believe that, uh, that's why for at Higgsfield, what, what really matters for us is how we, even if we get someone on like $20 a month subscription, like how can we show them value?

How can we make them to upgrade to over, to spend over, um, over $1,000 a year with us?

I can't believe that's $6M 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 that kind of churn rates. When you look at 30-day retention rates for consumers and 90-day retention rates, what are yours and what is good?

So there is, um, quite massive drop within the first month, just simply because people don't fully realize the value. And that's, uh, that's a core priority for us to actually get better in that. So showcasing the value.

Is it like half or like?

No, it's, uh, it's maybe like 30% drop.

Okay.

But then it's, it's really flat after that. It's, uh, we look obviously at like logo retention.

Mm-hmm.

I wouldn't say it's great, but because like we all remember like B2B SaaS era, like, uh, retention was expected to be logo retention month one was expected to be over 80%.

Mm-hmm.

Um, so clearly we have, uh, we have a lot of work to do on, uh, 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 like you're going to argue it's like 18 months old company, like what are you talking about?

But still, when I look at the numbers which I have today, NRR at month 12 is over 300%. Just, it just never happens in B2B SaaS,right? So, um, 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 know, we've got Alex coming on.

What should we ask him?" Everyone said the same thing, which was an admission of their respect for this particular kind of GTM. They said, "You've executed the most impressive influencer 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, like the goal is to make sure that the best commercial video content is generated on Higgsfield. And we show all the workflows of how to make such, uh, professionally looking videos. And we have an in-house team of over 150 creative professionals.

150. It's, it's almost half of the whole workforce, frankly. And, um, they, those people, they make product launch videos, they make tutorials. Like, for example, we made the first AI-generated movie, which is also like obviously, um, a very, um, a very sensitive topic.

But what's important, we open-sourced all of it. And what we learned is that for 90 minutes of, uh, of like, let's say, TV quality content, it was over 100 hours of AI-generated content. So creative decisioning, like picking theright piece, is still very important.

Um, so that's really what's, what's we are focused on and that's what's driving most of the, most of the revenue.

So you're saying that the growth in consumer subscription is through own content and distribution.

Yes. We don't do any paids.

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?

Oh, um, yeah, obviously this was, uh, obviously this was my mistake. I'm going to be, I'm going to do my best to be, um, transparent. What I need to admit, we really tried, we, at some point of time, I really was thinking that chasing benchmarks, um, is valuable, but I don't believe this is just sort of corporate psyops, frankly.

So, um, and I was part of the large organization, so I know what happens. What happens is that everyone just thinks like we need to show some progress, so we need to have some benchmark. But then when I talk to the top researchers from these labs, especially larger companies, what happens is that they start to put test data into the training.

They start to kind of use, uh, leverage test data to use LLM as a judge for training of the models, use all the various tricks to basically game benchmarks, get, get like quarterly bonuses and so on. Because like, who cares,right?

So if I make my couple million dollars a year in, in, in one of these labs, I can move to another lab easily. So that's unfortunately what's happening in larger organizations. Um, and that's.

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 in benchmarks, which actually don't increase output efficiently.

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 OpenRouter 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, uh, like three incumbents being completely relevant. And obviously like ByteDance obviously trying to catch up as well.

What's your takeaway from that?

I just do believe that, uh, there, there is just obviously in the, in tech bubble, there is a strong obsession over the benchmarks, uh, which do not, uh, necessarily represent the reality. But I can talk specific, specifically in the, for video.

A lot of benchmarks today for video is really text to video, which does not represent actual workflows at all. Um, the way to think about video models today, it's just modern rendering engine. Think about this as like Unreal Engine or Unity, but just different types of inputs.

And it's virtually impossible to really define, uh, visual output and, and direct the execution just through text. If you just go and to our open-source projects like this movie which I mentioned, average prompt length is over 3,000 words.

That's the first thing. And like, look, all these benchmarks which we're talking about, they're not like as comprehensive in terms of the details of prompts. And people who are labeling, they obviously don't, cannot read like 3,000 long, long prompts.

But also on average, there are at least 10 image references for every, for every scene. The reason why it's important is because 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?

It's true that 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 photoshoots and product consistency.

This is what allowed us to scale then from 20 to 100 million.

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 photoshoots. Uh, 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.

But do you think every company will have their own models? Like we're seeing Harvey, we're seeing Cognition, we're seeing McCore, Ramp built 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, just to be honest, whenever someone says we build our own models, very likely what they mean is something what's, what's happened with Cursor. We, we do remember,right? A lot of companies, they actually take OpenWeights model and just post-train on own data.

Mm-hmm.

Um, 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 OpenRouter reports that, uh, 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, OpenAI and Anthropic still are going to have more than 50% of the markets.

In terms of the dollars generally?

In terms of the dollars,right. And especially because, 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 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 creatives, um, a week, they want to have maybe cheapest, more steerable models because 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 for you?

The margin on own models and OpenWeights 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 Higgsfield is that, um, agentic grows so quickly. And actually for us, as companies start to actually create those agentic workflows to make more ads, we choose which model we can use. So like we choose what model to use in over than 40% cases.

In a way, model routing becomes a core feature of the business now.

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 is required and how we can pick the most efficient tokens for them.

There are actually two incumbents in the United States who figured out models. It's not just Google, it's also Nvidia.

Why do you think that is?

What I'm constantly seeing is that, um, the, there is the versions of models. So there are these state-of-the-art models which have to be really good in computer use like Astra or in coding. Um, but they can be prohibitively expensive.

And we were, we're chatting about that. Like on average at Higgsfield, person on the team spends over $10,000, over $10,000 a month on various models. And remember like we are split across United States and Asia.

Wait, 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, uh, 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 30K 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, 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 the spend. Because sometimes I feel it goes like, it really goes out of control.

Like 30K in a week is quite a lot. But we learned this. So this was actually a 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. So across, uh, the top, uh, the top engineers and across, across top creatives, I think it's going to keep growing. And I do believe we are going to get to, to, to spend, um, 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 a comparable salary raise as well. So I think that's just going to correlate at some points. Um, but also for a lot of other jobs, let's say we take legal, finance, and so on.

I think it, it really stabilizes around like, um, $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

there, I, I, I had sort of a feeling that legal customer support, um, is going to be mostly replaced. And that's obviously one of the main, um, mistakes operationally which we have done in the company that we didn't ramp these teams quickly.

Um, what we are 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. We're like at, at these professions where I say quite close today, I definitely can say that, uh, 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, like AI just doesn't work.

Revolut has now over 92% resolution rate on customer support for consumers. Pretty good.

It's, it's, it's pretty good, but obviously they did invest a lot into that.

Shit ton. A shit ton.

And, and, but also very important, the way how Nick thinks about that, uh, is in terms of the playbooks. We launch products, new products pretty much every week. So, um, we have to, we have to keep update 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 rules which they have. And if context and 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 Core Code?

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 moved 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, Anthropic this week.

Oh, OpenAI 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.

Yeah.

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 computer use.

Do you, 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 respect, 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. 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. Oh, I think we both invested in a company called Solve Intelligence.

Love it. Yeah. Very specific use case.

Very specific. And let me try to maybe bring a couple examples.

Hmm.

Why like Solve Intelligence is so special and like where, like, for example, how we learn from this. What can happen very often is that a company want to just control the patent workflow, even if they outsource the work.

And that's very valuable just to have one system of record. So whoever can create AI native system of record is going to win. And but going back to Higgsfield, why it's so important for Higgsfield. There are so many systems today which are used for just to store assets.

Hmm.

Like some people use Dropbox.

Hmm.

Some people use Google Drive.

Hmm.

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, 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 are envisioning, and that's what everyone wants, they want to just be able to search and, um, 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, uh, like this system of records is important. That's why at Higgsfield we invested so much in harness so that it improves over the time. And this harness also, um, allows it, 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 know, you've been around startups for a long time. We always talked about moats and defensibility. I largely think they're bullshit. You know, we, we saw Lovable at when I invested at it, 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. Um, so, um, 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, um, I think, um, it's very difficult to figure out where the value accrues in the supply chain.

Um, we do believe that there are only two like ways of, uh, 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, um, that's why it's so exciting that within Higgsfield, 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 this 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, uh, inference spend. What was the best VC meeting you've ever had?

Obviously, um, Yuri Milner gets, gets it.

How was that meeting? Like, was it, 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, I wouldn't say nervous. It was just more, uh, to see how much of the, uh, 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, uh, direct to consumer AI ads. It starts with short form dramas. All these trends come from Asia to the West. And, um, also fundamentally, we believe that most of contents on social and in the world is going to be AI assisted or AI generated.

And, uh, 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." Uh, next day, what I learned is that they called other investors and they pulled the syndicates and to invest in 30% lower valuation compared to what we discussed.

So like, look, these things just happen. So you never can be sure. But it didn't happen with Yuri.

I think there's a discount placed on Higgsfield because you're not a 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 valid at 50,right? So there is definitely an upside.

Okay. Up abound even more. Yeah, 100%.

So a couple 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 do build distribution for direct to consumer businesses. That's one aspiration. And second aspiration is obviously AppLovin. Like 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, 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 after the biggest industry in the world. But I wanted to drop another, another number.

So when I, and I asked the team to double check, so it's at least four people on the team who proved, so it's not like random fact. So I asked, um, when we look at public companies and we exclude pharma and big tech, spend on sales and marketing is higher than spend on R&D.

Like when, 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, um, many people just, and it'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?

Um, so oh, the West makes well over 70% of revenue.

Oh, wow.

Well over. But just important to say that we learn a lot from trends coming from Asia. Like Higgsfield does not exist in China, for example, which is massive market for AI. Um, Higgsfield, uh, 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 many, so much direct to consumer rather than using some resale platforms and so on.

I sacrificed a lot of life for, 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, um,

from the age of 7 to 12, my mother had to work, um, three jobs, so I didn't see her. My father was spending all the time with me, going to all, and it was, I was basically minor, so he had to go to all these camps with me.

Um, I also played checkers. I was top three in the world. So we went, we traveled throughout the world. And, um, then I did programming. He spent all the time with me, like really dedicated his life to me.

Like he did sacrifice. And, uh, since 21st, he has Parkinson's disease. So, um,

even like having some ability to capital and exits cannot fully change things. And, um, this is something which is, um, deeply personal, obviously.

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. It's because like mine's about a deep insecurity rooted in me being a fat kid.

Um, why are you doing it?

So I think Marc Andreessen actually described it really well that 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, um, my parents really taught me that, um, there is a place in the world where technology, like good technology products matter. I remember like when I was six, there was, um, like this, I guess, magazine about Bill Gates, like building Microsoft and not being like very, like socially accepted everywhere back then.

And like my mother just told me, 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, uh, this, that's still deeply rooted in me.

Childhood shaped us a lot.

Yeah.

What did your parents teach you?

For them, what was important is to just be in married-based environment sort of. Um, and, um, that's why getting to, uh, California felt so important.

What was your biggest lesson on hiring? Speaking of a married-based environment, we see a lot of, uh, focus on 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 Neo Clouds today? It's Nscale, IREN, and Nubius and Crusoe.

Crusoe, okay, Silicon Valley story. IREN from Australia, Nscale from the UK, and Nubius is UK and Netherlands. Let's talk about the companies on application layer that matter. I know that you mentioned Mercor and you mentioned Harvey, but Ligora, ElevenLabs, Lovable, they all deeply matter.

So if we just go outside of the model layer, uh, 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, don't believe in that.

I don't know why, but public, public data shows that the usage, uh, 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, I think fundamentally what's matters is if, if like Europe is going to figure out energy, but that's goes outside of, that's above my pay grade,right?

Um, so very important to say here is that, um, now there are more opportunities to create company from, um, different kind of cities from different parts of the world, while before it all felt extremely centralized. Um, and we are, we are excited, uh, we are obviously excited about that.

And, um, another thing about hiring, um, is that in Silicon Valley, unfortunately, what I'm seeing is that people just jump between jobs every two years. That's why, um, 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 Fulham fan, you're not going to root for Arsenal just because they won or played in the, um, Champions League final.

But in the United States, uh, if, uh, Lakers are on the top, people are going to say, yeah, I'm, I'm a fan of Lakers because it just makes it easier to start conversation, you know?

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. Um, I was obviously taught the corporate, uh, school of management in the United States. Um, and when I look at the CEOs whom, um, whom I'm learned from is obviously Jensen, Elon, and Nick.

Um, 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.

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 out how to retain them. Everything else is frankly secondary. And people just create so much theory around that. And, and essentially there are just so many like fake rules, uh, which are disconnect from reality.

It's, 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. Uh, 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, um, roughly 50 are in, um, California. Uh, maybe we're going to get to roughly 50 remotes and, um, over 300 in Kazakhstan. So look, I just hope we're going to prince, uh, more dollar millionaires in Kazakhstan and Central Asia in this part of the world, uh, than any other company.

I, I, I do too. Um, what's the labor arbitrage on cost between Kazakhstan and the US?

I, I know that a lot of people when they look at Higgsfield, they think about the arbitrage. First and foremost, like the way why.

Is that not true?

Look, like Kazakhstan is top five in the world in physics. Like you look at the recent international physics Olympiad for high schoolers, like they're top five in the world, on par with like the United States, China, India. And this is also like the core of our team.

It are 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 this Soviet school of math, but really upgraded with, uh, 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% personal income tax. Yeah, man, it's like.

Don't even get me started. Fucking 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, 100,000 and then you get the end and it's kind of like 3,500.

Yeah. And it's also English common law. So it's not like that bad as people think. Uh,

you move it. 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 this is just part of the culture.

And the fame, like extended family is not small by any means. Uh, 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 had, 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 I sleep. So like, I, I'm not like a guy who's going to just show up with Lamborghini or Porsche.

Do you invest? We mentioned solve intelligence.

Um, when before I did that, but now I spend roughly 90 hours a week, 80, 90 hours a week on Higgsfield. 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 spent 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.

Do you buy the bullshit of the balance and the, oh, it's okay. You can leave at five and be home for bath time and crush it?

This is a good question. So look, obviously, um, being an immigrant, I always have that I have to prove like that I belong,right? So I hope that I feel like now people accept, people recognize that Higgsfield is probably a top 10, um, application AI companies by revenue, probably number one.

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 Sally, like legend in the consumer space, obviously Jack. Look, I, I spend decent amount of time with them and other product leaders at Stamp.

Like the density of product talent at 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 shortcut to hard work.

Three hours a week with your wife.

Yeah.

I don't know about you two. 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, I'm very, um, I'm, 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 you say yes, and then she goes.

Yeah, I say maybe we both can come together. Then there is always someurgent fire, last minutes, and my wife just goes.

What fire was mosturgent? What was the, oh, fuck.

Yeah, look, I think obviously for all the things which we touched based 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 mean, like since I have like kind of machine learning background myself, data science backgrounds, I still can move a needle substantially when it comes to statistics and data. So yeah, I have to be involved somehow. But like these LLMs, they, 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, 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, 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 fucking 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 content.

It's going to be 1050X higher CPM, whatever, than AI generated content. So it's going to be, it's going to be way less in terms of like content created by, but it's going to create way more value, uh, than AI generated contents.

But even when I look into your content specifically, like you made multiple very successful shorts, millions of views, better than anyone else in this space, and you do a lot of overlay. While the content is authentic, I think we should do better job so that you use Higgsfield 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.

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 content 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, um, 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, rather than, uh, screenwriters, like those who are going to break it down shot by shot.

Then there are people who do the 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 going to matter a lot and just having stories to tell.

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 Slootman. Because going back to the points, I was just curious all the time, does no bullshit 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 bullshit culture? And when I read his MPTAP book, like book called MPTAP, 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 Databricks wiped the floor because they moved product as the priority, not GTM.

And that was dangerous. I prefer Chad Petes. Do you know Chad Petes? Oh, dude, this guy is no bullshit. 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 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, 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, fans. It's like, it's been mismanaged to shit. Its SPC is through the roof. Ugh, it's tough to say it's a good company.

Yeah. 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 muslin 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 Matter's market cap and Snap's market cap has increased so significantly? If there was one reason.

I just maybe saying this straight, 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 fucking beast. He's such a beast. You watched 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 going to, uh, he, 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 a little bit in its own league.

Yeah, but he got rid of Systrom and Krieger. Here, he's been like, no, no, no, you, Alex Wang, are my guy. Do you see what I mean? It's the best talent hire.

Look, 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 launch and so on to, 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's doing to public investors, being able to articulate why Muse is so different, um, is phenomenal.

Okay.

Revenues 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 this basically involves 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% month over month.

What do you think it is? They said 4.5. What, 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, 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, uh, CGI.

But the sentiments really shifted from like strictly negative to neutral to slightly negative. And in private conversations, yes, there are maybe more than half of STR talents who is going to say we're anti-AI forever, but increasingly there are more and more people who are actually asking a question.

Can we tell more stories with AI? Can we overcome certain budget limitations which 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's at least comes from my conversations is extremely, is extremely, is extremely positive.

If you are the billion today, 10 billion in 12 months, where do you peg the next fundraise? You know, if you're the billion, say conservative multiple, you'd be like 15. Um, but if you're hitting 10 next year, you're like paying end of year, it's like 80.

Look, we are not chasing just the valuation because again, the goal is just to make sure that the company can be, uh, sustainable over the time in public markets. So there is a lot of company building to be done beyond just, uh, chasing the revenue.

But I just do believe.

Do you want to be public?

Huh?

Do you want to be public at some point?

Yeah, I do believe that Higgsfield has great potential to be bigger than AppLovin and Shopify. Because fundamentally, like building is one part of that. Shopify, one layer of infrastructure. Then for coding, there is obviously like a Claude, there is Codex, but what matters is distribution over the time.

Distribution matters. You know that this better than any other VC,right?

It is 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.