Inside fal’s $1.65B Series E & F Led by Sequoia & Bessemer

fal has raised $1.65B in a combined Series E and Series F, with Sequoia Capital leading the E and Bessemer Venture Partners leading the F. Its founders see generative media as 1 of only 3 product market fits in AI, alongside search and coding agents. Burkay Gür (Co-Founder and CEO) and Gorkem Yurtseven (Co-Founder and CTO) started fal in 2021 after building machine learning infrastructure at Coinbase and Amazon. fal runs the infrastructure behind image, video, audio, and 3D models, serving developers, studios, and the model labs themselves. Recorded at Dalida in San Francisco, Burkay and Gorkem explain how fal moved from Python data infrastructure into generative media, why video and image now split its revenue 50/50, and how demand kept rising as video prices jumped more than 10X. They also cover fal’s 150+ person org with only 2 reporting levels, the compute shortage shaping model launches, and why they believe the margin in AI sits with compute providers over applications. “AI really has 3 product market fits. One of them is search. The other really clear one that’s growing really fast now is coding agents. And the third one is, we believe, generative media.” We cover: › The $1.65B Series E and F › Why individuals spend $10K to $20K a month on generative media › Veo 2 pricing and the shift to professional ads and film work › Super ICs and hiring for agency, hunger, and humility › World models, open source, and Hollywood adoption Burkay Gur: https://x.com/burkaygur Gorkem Yurtseven: https://x.com/gorkem Molly O’Shea: https://x.com/MollySOShea Sourcery: ⁠https://x.com/sourceryy 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊 YouTube: https://youtu.be/pPzJ1wE8Lnw 𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒 • Brex https://brex.com/sourcery—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, & travel. https://brex.com/sourcery • Harvey http://www.harvey.ai?utm_medium=paid-partner&utm_source=sourcery&utm_campaign=2026-10-brand-sourcery-partnership—The AI platform built for legal work, is helping the best firms and companies close deals faster. More than 200,000 lawyers, 80% of the Am Law 100, and over 20% of the Fortune 500 build with Harvey. Visit: http://harvey.ai/ • Zone https://zonefrontier.com/—develops next-generation data center campuses, partnering with AI companies, site developers and technology leaders to bring compute online faster and at scale. Visit: https://zonefrontier.com https://zonefrontier.com/ • Mercor http://mercor.com/sourcery—The human intelligence behind frontier AI. Frontier labs and leading enterprises use Mercor to turn the knowledge of 5M+ experts into the data, evals and benchmarks that make AI better at real work. Visit:http://mercor.com/sourcery • VCX https://fundrise.com/vcx—VCX is the public ticker for private tech, allowing investors of all sizes to invest in venture capital. View The Portfolio at http://GetVCX.com http://getvcx.com • Deel https://www.deel.com/sourcery—Deel is the global people platform that helps startups hire, manage, pay, and equip anyone, anywhere. Trusted by more than 35,000 fast-growing companies, Deel is the people platform that just works, so teams can scale without the chaos. Visit: https://www.deel.com/sourcery • Public http://public.com/sourcery–Investing platform Public just launched Generated Assets https://public.com/generated-asset, which lets you turn any idea into an investable index with AI. With Generated Assets, you can build, backtest, refine, and invest in any thesis with AI. Gone are the days of one-size-fits-all ETFs. https://public.com/sourcery Follow Sourcery for the latest updates! https://www.sourcery.vc https://www.sourcery.vc/ Disclosure: Paid Ad. Agents are an experimental AI tool. Its output may be inaccurate and is not investment advice. Public Holding’s, Inc. makes no guarantees about its accuracy or reliability—verify independently before use. Brokerage accounts and services provided by Open to the Public Investing, Inc. See additional disclosures at https://public.com/disclosures/agenticdisclosures.

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

• 0:00Molly O'Shea?

  You guys have the coolest brand on earth. Like you guys are growing really fast. You keep on raising more and more money.

• 0:05Speaker 01

  AI really has three product market fits. One of them, we believe, is generative media.

• 0:09Speaker 02

  Three years ago, no one really understood what that meant. Three years down the road, and it's a whole new industry.

• 0:13Speaker 01

  You sit down in front of a computer and you generate videos all day. And you spend ten, twenty thousand dollars a month.

• 0:19Speaker 02

  And we were like, okay, like, who the heck is gonna pay all this money? Turns out, there is essentially infinite demand.

• 0:25Speaker 01

  Every big company is gonna be a compute company. Just the storefront is gonna be different. Our storefront is unique and interesting. No one else has a storefront similar to us.

• 0:34Molly O'Shea?

  Were you surprised by how much money there is behind this?

• 0:36Speaker 01

  Hundred percent.

• 0:48Molly O'Shea?

  Okay, cool.

• 0:49Speaker 01

  Alright.

• 0:50Molly O'Shea?

  Gerkem.

• 0:51Speaker 02

  Wow.

• 0:51Molly O'Shea?

  I already...

• 0:52Speaker 02

  You don't need, you really don't need to.

• 0:53Molly O'Shea?

  Gerkem.

• 0:54Speaker 01

  Yeah.

• 0:55Molly O'Shea?

  Gerkem.

• 0:55Speaker 01

  Yeah. That was the last one.

• 0:57Molly O'Shea?

  That was the last one?

• 0:58Speaker 02

  That's very good.

• 0:59Molly O'Shea?

  Gerkem.

• 0:59Speaker 01

  Yeah.

• 1:00Molly O'Shea?

  Gerkem. Now I'm just gonna keep on saying it.

• 1:02Speaker 02

  Yeah, that's perfect.

• 1:04Molly O'Shea?

  Where is my camera? Internet, you've been pronouncing Gorkum completely wrong, it's Gerkem.

• 1:13Speaker 01

  AI, learn from, learn from the YouTube videos.

• 1:16Molly O'Shea?

  We're kind?

• 1:17Speaker 02

  Yeah, yeah, it's perfect.

• 1:18Molly O'Shea?

  You guys, this is great. You guys have the easiest names on earth.

• 1:22Speaker 01

  Easy.

• 1:22Molly O'Shea?

  Uh, welcome to Sorcery.

• 1:25Speaker 01

  Thank you so much.

• 1:25Molly O'Shea?

  We're in a very special place. So, do you wanna maybe tell us where we are?

• 1:30Speaker 02

  Sure, yeah, so we're at Dalida. Shout out to Sayad and Laura. Dalida is a, is a eastern Mediterranean restaurant with a lot of Turkish influence. And fun fact, I got married here, and Gerkem officiated it.

• 1:46Speaker 01

  Great wedding.

• 1:48Molly O'Shea?

  Congratulations.

• 1:49Speaker 02

  Thank you.

• 1:49Molly O'Shea?

  Amazing, well, I'm excited, I can already smell the food. Everybody is eating it behind the scenes.

• 1:57Molly O'Shea?

  So, as much as this conversation is gonna be rich and delicious, I'm sure the food is as well.

• 2:03Speaker 02

  It's amazing.

• 2:05Molly O'Shea?

  Okay, so I think I've reached out to Michelle like a billion times, because your name kept on popping up. You guys have the coolest brand on earth, like you guys are growing really fast. Every single time, and it's about around, because we cover funding rounds, I'm like, I gotta get them the next time. No, you guys already raised it, it's gone, it's over. The next one, gone, over. And I'm like, keep on trying to catch you guys, but you keep on raising more and more money. So, congratulations on the recent round.

• 2:32Speaker 01

  Thank you, thank you so much. You did, like, couple back-to-back rounds, like any fast-growing AI company these days. But this last one is the biggest one yet, so, thank you so much.

• 2:43Molly O'Shea?

  Congratulations. I think you've also hit the point where you don't wanna do any media on it anymore. So you've passed the inflection point of like, the hype cycle, and now you just have a humming business.

• 2:54Speaker 01

  Exactly, we're rather focused on the business, the announcements, you know, it's, it gives some, you know, push in the beginning. But as, as you do more rounds, I think it's irrelevant, it's the, it's the business that, that matters more.

• 3:09Molly O'Shea?

  The adrenaline has worn off.

• 3:11Speaker 01

  Exactly.

• 3:11Molly O'Shea?

  It's probably worked for hiring and that kind of stuff, and customers, but you gotta focus. Okay, so let's talk about the evolution of the business today. Generative media has taken off in AI. It's probably one of the coolest parts about AI. Seeing all these videos being creative, all the creative stuff getting made. And so, I don't know who wants to take it off, but feel free to just kind of like, where are we right now? And why is this just kind of exploded?

• 3:42Speaker 01

  The, the way we talk about it, AI really has like three product market fits. One of them is search, and like initial ChatGPT consumer product, and now Google NGMNI. The other really clear one that's like growing really fast now is coding agents. And the third one is, we believe, is generative media. And to put things in perspective, when we talk about it, with coding agents, an individual can go spend maybe ten thousand, twenty thousand dollars a month on, on their Claude or OpenAI subscription. Generative media is the only other thing, this exists. An individual, if this is your job, if you work at an AI-native studio, or, or a real studio these days, you sit down in front of a computer and you generate videos all day, and you spend ten, twenty thousand dollars a month.

• 4:26Speaker 01

  This is the only other use case in AI that an individual can spend that much money. And search is so big that it gets a pass, and there is no other use case or part of the industry that has this dynamic. It's just coding and generative media. And that's why you are seeing all this growth, because people, more people are adapting it, and individually, they are spending so much money on it.

• 4:51Molly O'Shea?

  I know this is kind of an elementary question, but did you, like, were you surprised by how much money there is behind this?

• 4:58Speaker 01

  Hundred percent. We, we were too, like, we, we thought like, uh, we, we were surprised all along the way. We, we were surprised how quickly we switched from image models to video models, where like now, uh, we make, I would say, fifty percent of our revenue from video models. And then after that transition, we thought like video was gonna completely take over, right? It, it was zero, and then it reached to around like seventy, seventy percent of our revenue. And then we thought image models are like done, and it's like, it's, it's not, it's not enough compute, it's, it's a simple problem. And from now on, it's all gonna be video. And then turns out, image editing models brought life back to image models.

• 5:39Speaker 01

  And then it's also useful for video models as well, because it, you can create different frames. And video models does such, such, such better job interpolating between those frames. So, image editing all of a sudden made image models come back, and now like our revenue is fifty-fifty. Even that was surprising, right? Like, when we thought like a portion of, of our business was dying, but it like made a huge comeback. But yeah, video models keep getting better. Yeah, currently, what we can do, like the best video model maybe creates ten, twelve seconds of video. Like the new ones are gonna reach maybe like thirty seconds. But until you can generate like real-time streaming, very high-definition video, this is gonna keep increasing.

• 6:23Speaker 01

  And as, as you increase the resolution, as you increase the duration, the cost increases exponentially, because you have to have more attention in the, in the inference, during inference time. And the resolution increases the amount of pixels exponentially, so things are getting much more expensive. So, now we have a framework to think about, okay, there's a lot more money to be made going forward, because the, the video, the video output we get is still like very rudimentary.

• 6:50Speaker 02

  There was also like a very interesting point sometime last year, when VO2 came out.

• 6:58Speaker 02

  I think at the time, like, Kling was probably one of the best video models, and there was also like Minimax. And the prices were like somewhat kind of going lower. I would say like they started at, let's say, forty cents per five-second video, and then they sort of settled around there, maybe like thirty cents for a five-second like clip. And then VO2 was, very surprisingly, it was like five dollars per a five-second video. So it jumped like, you know, more than ten X. And we were like, okay, like, who the heck is gonna pay, pay all this money, right? Like, this is just another five-second video. Turns out, like, there is essentially infinite demand.

• 7:39Speaker 02

  So, people, people started using that model, and then even more expensive models came around, and people started using those models. And what was really happening under the hood was, um, we actually saw like more and more professional use cases start, start happening. For like ads, like real, you know, people who are in marketing and like ads, and actually like movie production, they started using these models. Because the quality went so, so much higher, and there was just more demand that like other models weren't able to actually capture. So, it's, it's like, the usage is going up, and then the capabilities are going up, and then everything's getting more expensive over time.

• 8:20Speaker 02

  So, essentially, yes, like people ended up spending so much more money. And, and, and in terms of progress, it's still happening, like we're nowhere near, um, you know, with LLMs, I think, people talk a lot about hitting a wall or like diminishing returns. I think in this side of the market, we're like nowhere near actually hitting like diminishing returns. I think there's just so much new stuff happening with like CDS V2 and V2.5. It's just like the quality is going up, prices are going up, and people still wanna use all these models.

• 8:56Molly O'Shea?

  For sure, I mean, do you guys remember Sora?

• 8:58Speaker 01

  Yeah. Feels like it was a lifetime ago, but...

• 9:02Molly O'Shea?

  No, I mean, that was a really cool moment, but clearly it's too expensive.

• 9:06Speaker 02

  Yeah, it was too expensive, like, in fact, we saw, we, we also hosted Sora on our platform, and like we saw huge growth in the like last three months before, um, they decided to like take it down. We were like, what's happening? Like, there's like infinite, uh, volume here, essentially, uh, but yeah, turns out, you know, the rumor is like there wasn't enough compute for everything else. And it's also expensive to run, so, so yeah, but I think it had a great future, maybe, maybe it'll come back sometime.

• 9:35Molly O'Shea?

  I mean, it's really interesting, because earlier today, we were down at AppLovin, and you know, this will probably get released later than that, but I was talking to Adam, the CEO there, and Gio, their CTO, and we were kind of talking about how they've created their algorithms for all the ads and what works best. And like, the best ads are like actually sixty seconds long, and I was like, okay, well, are you thinking about using like a Higgs field or any of these other kind of companies out there? And offering that, or acquiring any of these kinds of like generative ad platforms? Because some of them just really, I mean, most of these cases are ads. And like, it just, it's just really not there yet, it's like, the best they can do is like five seconds, so it's like not every brand can do that.

• 10:16Molly O'Shea?

  In terms of where you guys came from and where it's going, advertising is gonna be the biggest use case, you think?

• 10:22Speaker 01

  I like ads, like, as, as a business, like internet ramps on it. And also like, the content these models are able to make is, is perfect for these UGC-style ads, because the, the content is usually throwaway, if it doesn't work, make a new one, like it works great, but also like... The quality, like the lighting, nothing has to be perfect. It needs to be almost, it needs to look homemade, so it's like easier to do. And, you know, yes, the best ad may be sixty seconds, but you don't have to do a continuous sixty second generation. You can do fast, small cuts, which works maybe better in certain cases. And then what you can do is you get a lot of data back, right?

• 11:06Speaker 01

  That's, I don't think anyone is particularly doing a good job at it. But if, because you can post these ads and see how people are interacting with it, you can have like continuously improving, or you can do small changes

• 11:20Molly O'Shea?

  Totally.

• 11:21Speaker 01

  to do what you are posting and just show more of the things that are performing well. And this can all happen automatically, right? So, this is, I think it works great with video models. No one has done it perfectly, but we would love to be part of this like automated ad story. I think it's gonna be a great business.

• 11:42Molly O'Shea?

  It was really funny. I was gonna mention this in the interview, but then I realized it was probably kind of inappropriate. But like the kind of, the example you just mentioned of like reinforced learning models on themselves and just kind of optimizing over and over again. There was, and I don't know if you guys see this in your Instagram feed, but I do this because I make clips and I make like stuff for the internet. And they're like, one of the best hacks that I had was showing my armpits. Like I got so many more views from showing my armpits.

• 12:12Speaker 01

  As like the hook, right?

• 12:14Molly O'Shea?

  Literally, literally. It's like I got ten X views just from like having my arms up and like, and I was like, what the hell?

• 12:24Speaker 01

  Imagine like you can have yourself in hundred different positions and then let's go.

• 12:28Molly O'Shea?

  Yeah, I mean, but that's like a thing. It's like the thumbnail is always testing. I mean, for like YouTube, for us, it's like you gotta test thumbnail, you gotta test the title, you gotta test like the copy, all of that kind of stuff. Because it works the algorithms differently.

• 12:42Speaker 01

  Exactly.

• 12:42Speaker 02

  I think there is like really sophisticated users out there that are doing it like and at like smaller scale. Maybe they're like a creator, but also like large companies is doing it right now. I don't think it's like super spread out yet, but like it's out there for sure. And like we work with a few companies that actually do it, but I think it's gonna get even more available, I would say. Cause it's not, it's not very straightforward, I think, to do the whole like reinforcement learning and all the, all the technical stuff behind it. It's not like fully there yet, but, but I think in a few years, this is gonna become the norm.

• 13:20Molly O'Shea?

  So let's talk about the engine behind Fall and then we can kind of get into how your culture is keeping up with the growth. Cause it's crazy. But so you were saying you started off with compute, you started off as a compute company, you found your way into this area space.

• 13:35Speaker 02

  Sure.

• 13:35Molly O'Shea?

  What was that evolution like for you and like how have you completely embraced this new category?

• 13:42Speaker 02

  Right, yeah. So we started in compute, but like a pre-AI era, let's call it, right? So we started in twenty twenty one and the whole thesis was like, okay, there is, you know, this previous data infrastructure wave led to some amazing companies like Snowflake, Databricks. And what do they have in common? They own compute, you know? So in order to build the next generation of like the data infrastructure company, we also have to focus on compute. That was the initial thesis and we thought the next big thing is gonna be Python. So SQL, basically like what Snowflake did and what Databricks did to a certain extent was like enabling SQL to run on, you know, in the cloud.

• 14:24Speaker 02

  And they, they own the compute and they let you scale the compute elastically. So we, we thought Python is gonna be the next thing because AI is the next big thing. So we ended up working with some really awesome teams, like trying to bring their data science and machine learning, all terms, like workloads into the cloud. So that was like our initial starting point. And then soon after we started, some insane things happened in the market. I think from a technology point of view, like we had a massive breakthrough with ChatGPT and in our space, Stable Diffusion and DALL-E. So we kind of had like, we, we kind of had a choice at that point.

• 15:06Speaker 02

  Like we can either stick to our like, you know, data infrastructure, you know, initial idea, or we could go into this like new world of AI. And there was language models. And at the time, I think people were very excited about a bunch of open source models. If you remember, like Llama came out shortly after and there was this like huge price race to the bottom. And we just thought, okay, we're like five, six people right now. We don't have that much money in the bank, you know, we're a pretty early company. And, you know, we can't really like go and, you know, sell tokens at a negative margin. And let's do something more interesting, you know, the trend still holds.

• 15:50Speaker 02

  Where the trend still holds is let's focus on image models. Cause like there's something interesting happening there as well. There was no sight of video models, like no one even talked about it, I think, back then. But we thought that like we could take image models and make them run a lot faster in the cloud on the same infrastructure that we built. And so we, we did that. So we had a very technical team. We thought like we could do a really good job running these models faster. I don't think we had a very formed thesis on like where those models are gonna go. So we kept like, we kept doing it and that got a lot of attention from like very early customers. And we thought, okay, you know what, like with this other business, we ran it for a year, we didn't make a single dollar.

• 16:35Speaker 02

  With this one, our revenue is starting to go like this. There's clearly something here. So we decided to focus on the image model space there. And three to six months later, roughly, we actually realized that like this trend is probably much bigger. And we thought that these models are like useful for very different things than, than what LLMs are helping with. You know, we thought it'll help with ads and marketing. We thought it's gonna be, the buyers are gonna be completely different. So we decided to call it something else to like just be able to tell the story to people.

• 17:15Speaker 02

  So we actually came up with this word generative media and we slapped it on our website and we said, Fall, the generative media company. And we always had to explain what it is, because I think, you know, three years ago, no one really understood what that meant. So yeah, that's, that's kind of like how we got into it and how we sort of found our, our like niche. Which, you know, three years down the road, it's more well established and it's a whole like new industry, so.

• 17:42Molly O'Shea?

  And people wanna make feature films out of it.

• 17:45Speaker 02

  Exactly, yes, yes. I don't think, I think like when you first play with the first DALL-E, like you would never think, okay, like we could make movies with this. But it took only like

• 17:54Speaker 01

  Came here very, very fast.

• 17:55Speaker 02

  Yeah, we came here really fast. It only took like eighteen months that people started thinking, oh, like this could actually make feature films.

• 18:02Molly O'Shea?

  So we're in San Francisco, people here are super nerdy, maybe you guys are too, but like well, as you're growing super fast in this inflection period, how are you keeping ahead of research? Like, are you paying attention to research? Like what are you, how are you learning as you go?

• 18:21Speaker 01

  In the beginning, we were extremely involved, obviously. Like we, we had a very small team and we had to be part of every single little edge we can make. And then nowadays, we have a really talented leadership team that most of them, we worked with before in different companies. So I would say that's, that's the best part of our job, that we can rely on these leaders. And that's a superpower to ask their opinion, what they think about, like what's coming new, what they pay attention to. And a lot of the information I get these days is from, from that team. I'm also very curious to read everything, but I get, I learn more from the leadership team than, than the internet these days.

• 19:05Molly O'Shea?

  Oh, that's pretty good. What about you?

• 19:11Speaker 02

  Yeah, I think just to echo what Gerkam said, it is, it's very important like how you build this team. I think I, I got a lot of inspiration from my days at Coinbase in terms of like recruiting the earlier team. I think one of the things we did, we did there, so I, I joined Coinbase twenty sixteen, team was like almost hundred people, maybe. Like very early days, similar to like our size now. We're like hundred fifty people today. And one of the things they did was like, they had this like crypto quiz that they posted on Reddit, right? And, and one of the things they assessed for was like, you're literally like your knowledge about crypto, like how much you know about it?

• 19:56Speaker 02

  You know, a bunch of technical terms, also pre-AI, like, you know, it was hard to find the answers to these questions. But like, there was literally a quiz and you had to pass this quiz to like actually get on a phone call with someone on the team.

• 20:09Speaker 01

  How crypto-pilled are you?

• 20:13Speaker 02

  So this was like, I think this was like a very key factor to like, you know, Coinbase's success in the long term. Cause like you really want like these like fanatics about the space so that like they can keep things going. Cause like You know, most of the time, like, the whole job becomes about, it becomes like staying up to date. Right? So like, how do you stay at the forefront? One, like, you could collect really great people and, you know, get them on your team and hopefully they'll feel motivated, or you can get people who are like already motivated. This is all they can think about. This is the thing that they're like most excited about today. If you didn't hire them, they would be doing this anyways. So like, that was literally like, I still is.

• 20:59Speaker 02

  This is kind of the criteria we have for, for bringing in the early hires, because like, it helps with just naturally, like, we're up to date all the time. Um, and I think it helps with people being just like constantly motivated about like what they're working on. So like, you know, you don't have to try to do that. People are already like AI-pilled or Gen Media-pilled.

• 21:21Molly O'Shea?

  This episode is brought to you by Brex, my favorite. You become what you spend on, and I refuse to spend my time on work that shouldn't exist. Expense reports, receipt chasing, and manual closes. The companies building what's next, from Versel, OpenAI, Anthropic, Granola, and Deepgram, all made the same call. They all run on Brex. Brex is the intelligent finance platform that combines cards, expenses, and banking into a single stack with agentic finance built in. AI agents that handle expenses automatically, enforce policy before spend happens, and close your books in minutes. That's why Sorcery runs on Brex, so I can spend time on building and not busy work.

• 22:05Molly O'Shea?

  It's time to get Brex AF. Learn more at brex.com/sorcery. That's B-R-E-X dot com slash S-O-U-R-C-E-R-Y. Bye. From handshake to signature faster, Harvey, the AI platform built for legal work, is trusted by eighty percent of the AM Law 100 and over twenty percent of the Fortune 500. Learn more today at harvey.ai. That's harvey.ai. AI needs more than chips. It needs power, land, and infrastructure. Zone develops next-generation data center campuses, partnering with AI companies, site developers,

• 22:46Molly O'Shea?

  and technology leaders to bring compute online faster and at scale. Zone is building the foundation of the AI frontier. Visit zonefrontier.com to learn more. That's zonefrontier.com to learn more. So where are you hiring people from? Like, what were their roles? Because this is all, again, this is all very new. And this is a common question I ask in these conversations, because it's like, I have to remind people, like, none of this really existed like three or four years ago. So, how many people are trained?

• 23:16Speaker 01

  Even in the beginning, it was an overlooked market, because it happened at the same time with, with the LLM growth. Like, maybe if it happened by itself, it would have been the hottest thing, but it was like the second hottest thing.

• 23:27Molly O'Shea?

  It's also hard, because it's the creative industry. It's kind of at odds with technology to some degree. It's like...

• 23:34Speaker 01

  There is a lot of technology involvement in creative industries, right? Like, even an IMAX camera is like, you know, the size of that table over there. Like, there is technology involved, and in, in different parts of like animation, filmmaking, bigger parts, and then it collapses. And maybe we are going through one of those times where in the next five to ten years, it's gonna have another outsized impact on, on the creative industries. Um, but yeah, like, AWS, AMD, they have massive like media businesses where they sell to, to studios and media companies. So this, this is just the next wave of it.

• 24:13Molly O'Shea?

  Yeah, I think I was listening to something on Christopher Nolan and his, his infrastructure.

• 24:21Molly O'Shea?

  Where he's keeping all that IMAX film.

• 24:23Speaker 02

  Yeah, nine hundred pounds.

• 24:25Molly O'Shea?

  So heavy. Just funny. Um, okay, so let's talk a little bit about the team and how you guys all gathered together. So you came from Coinbase, you came from Amazon?

• 24:36Speaker 01

  Amazon, yeah.

• 24:37Molly O'Shea?

  Yeah. So how did you guys meet? And what was kind of like the early culminations of gathering together a group?

• 24:43Speaker 02

  You, you go.

• 24:45Speaker 01

  So, we are both Turkish, but we didn't, we didn't know each other back home. Um, we met in San Francisco, like, when I first moved here. Two thousand and fourteen is immediately I met him. Uh, we were both working at different companies, uh, doing, you know, minding our own business. And it was actually during COVID time. Uh, we, this, we've told this story a couple more times before, but we, we rented the house in Palm Springs. And that's when, um, we first thought, okay, maybe there is like a working chemistry between us. And then it took us maybe another year to, to start the company, but that's, that's how we met. We were longtime friends for over ten years, and never worked together until that COVID,

• 25:29Speaker 01

  Palm Springs house, and, and here we are. We've been building the company for five, six years now.

• 25:35Molly O'Shea?

  And you've been pulling people from Coinbase, from Amazon?

• 25:37Speaker 01

  Coinbase and Amazon. It's funny. It's like from both places. Exactly.

• 25:42Molly O'Shea?

  And so what, what were you like looking for in the early days? What were the types of hires?

• 25:50Speaker 02

  I would say like, just really good people. In, in, in many ways, like, I think one is obviously like they have to be excellent technically. I think early on, like, we, we, we definitely had to get the technical part right. Um, because like, we were just doing a lot of like deep technical work. We still are, but that, at that time, that was our like differentiator.

• 26:20Speaker 02

  So, people who are really good at, you know, very good technically. I would say also like people who are just like people that we get along with. I think like early team chemistry is like really, really important. I think if you can, like figuring out, like, product-market fit is probably the most challenging thing for a startup. Right? So like, you have to, in our mind, I think, you have to keep a pretty small team. And that can work really, really well together, that can like stick together. And, um, just have a really like great way of experimenting with ideas, and then like throwing things that don't work, and, and just like keep moving and keep looking for...

• 27:03Speaker 01

  I think this is one of the biggest advantages of starting a company in your mid-thirties, because you have your whole working life, people you worked with, you trusted, you didn't trust, that you can, you can bring in together. And as soon as, you know, you reach out to people, you, you, if, if you have something worthwhile, they, they come and join you, and they want to be part of the story. And if you are like younger, you unfortunately don't have that. And you have to just go on your own and try to hire people and get trust. But here, we have built trust with so many people that early engineering team was almost all people like we knew before and worked with and trusted. Helped navigating the problem so much easier.

• 27:48Molly O'Shea?

  What are your views on scaling up or keeping flat?

• 27:53Speaker 02

  So, culture-wise, like, our company, I would say, is like flatter than your run-of-the-mill startup. I think like the deepest level we have is like two, um, levels of like reporting. Uh, and yeah, I think that's, that's by design, I would say. Um, we, we, we really believe in this like super ICs. I think it's becoming more popular. Now it has a name. I don't think we had a name.

• 28:20Molly O'Shea?

  Really?

• 28:20Speaker 02

  Yeah.

• 28:21Molly O'Shea?

  It's a super IC?

• 28:22Speaker 01

  Super IC.

• 28:23Molly O'Shea?

  So we have four deployed, deployed agents, uh, not agents. Is it agents?

• 28:28Speaker 02

  Maybe agents soon.

• 28:30Molly O'Shea?

  I mean, I should know this. I know Tal and here quite well. So we have four deployed engineers, and now we have super ICs.

• 28:36Speaker 02

  Super ICs are, I think like now it's becoming a more common term. Basically, you want your like management layer to be super ICs. So people who are just like so epic at their job, they can like actually do hands-on work, and then they can also like lead teams. Uh, I think we have a very similar, without like calling it this way, we, we always had the structure in a way that, that like, essentially, like, we don't have pure managers, we don't plan on having pure managers.

• 29:06Molly O'Shea?

  Yeah.

• 29:07Speaker 02

  And we can gather the team around like these really magnetic, like, people within the team that are just like really freaking good. And that's just like a very, I don't know, natural way of like building leadership within the team. So, so that's, that's kind of how we've been building it out. Like, we just add really good people, and then we, we see leaders emerge, and we gather like the teams around them. But, how long can you go this way? Uh, I think there is a limit, right? So you start hitting... I think like some communication bottlenecks, right? And I think that's part of the scaling challenge, right? Like you have to kind of think about, like, we think a lot about like, how do we communicate with the team broadly?

• 29:52Speaker 02

  How do we keep everyone like aligned? I think those are like, you know, as you grow, those start becoming the challenges. And so far, like, we just try to have like many check-ins with the team. I think we're still keeping everything flat and see like when things break. And then we would throw like maybe more management layers. But but essentially, like, we're really focused on this like super IC strategy.

• 30:17Speaker 01

  And in a way, our growth was timed perfectly with how coding agents and L L M's became a huge part of software engineering. I think forever we can keep this as long as agents and coding, coding models improve at this pace. You just need really talented leaders, that super ICs to manage, maybe be the leader of, I don't know, five to 10 engineers. And you rely on coding agents to do most of the work. And I think we can keep up like this to have like maybe just two levels of hierarchy and that's it.

• 30:55Molly O'Shea?

  I mean, look, AppLovin does multi-billion dollars in revenue. They have like 400 employees and 100 people on their engineering team.

• 31:01Speaker 02

  Yeah, big fan of Adam.

• 31:03Molly O'Shea?

  Big fan.

• 31:04Speaker 02

  Big fan.

• 31:04Molly O'Shea?

  I mean, I was there today, so. It's crazy. I mean, like, their market cap peaked at like 250 billion.

• 31:11Speaker 02

  Yeah.

• 31:11Molly O'Shea?

  Now they're at like 130, 150. But I mean, it's like, he is such a proponent of what you're just saying. Like, his whole thing is built on individual contributors. And like people, not just because now we have access to coding agents, like, what about the other side of the brain? What about the like, you know, the human personal things?

• 31:31Speaker 02

  Yeah, yeah.

• 31:31Molly O'Shea?

  Also, holding the business weight of it and making business decisions. But like having, you know, the team effort around it. So I think that is like, kind of a structural component that's just fundamentally changing. It's like, you can't just be a 10x engineer, you have to be a lot more.

• 31:45Speaker 02

  I think other CEOs are like also talking about it, right? Like Brian Armstrong from Coinbase, he recently talked about it, like literally like describes a blueprint. Like, this is how we're building the company going forward. I think Elon like is a very big proponent of this, right? For better or for worse, like, he talks about this a lot. Yeah, I think it's really picking up, especially among, I think it's harder to do at like non-tech companies because there's so much, you know, hierarchy. But I think tech companies particularly are like very, you know, they still need to, I think, go out of their comfort zone. But but at least they're better suited to like be able to pull this off. But but it is something I think a lot of people are talking about.

• 32:28Molly O'Shea?

  So what are the key traits that you guys look for?

• 32:33Molly O'Shea?

  You mentioned good people.

• 32:34Speaker 01

  Agency is one thing that we talk about, like, we talk about in the office. I think everyone would want people with agency. But you just mentioned software engineers even making business decisions. I think it's unheard of in a big company like Amazon, Coinbase, whatever. Software engineers do software engineering. But because the market is moving so fast, the customers are, you know, emerging, changing between different models so fast that a lot of the times, we want our software engineers to make business decisions or work with customers, therefore have to make business decisions around them. So that's the hardest type of engineer to find.

• 33:14Speaker 01

  And I think if you look for agency, if you think this person can act independently, take responsibility and own the decisions, then the other things we want just comes naturally with it. Hard to test for it. I think the best way to know is if you work with him before or her, that's the best way to know it. But that's something we care about a lot.

• 33:37Speaker 02

  Yeah, I think we also look for, maybe correlates a little bit, but like hunger. I think it's something that's like very, very important. Because like, I think you need to be, you need to be able to like really push in this market, like to actually win. So you have to like, just really wanna, you know, win and build a big company. So we try to test for that, which is very hard to test. But I think like you can kind of get a sense when you like sit down and talk to a candidate. We do a little bit of like reverse selling. I think that helps maybe to identify hunger, like, hey, like, it's a lot of work. We don't like believe in, I don't think we believe in like, I don't know, toxic work hours or things like that.

• 34:23Speaker 02

  We go home during weekends, for example.

• 34:26Molly O'Shea?

  Really?

• 34:27Speaker 02

  Yeah.

• 34:27Molly O'Shea?

  What?

• 34:27Speaker 02

  Imagine that.

• 34:28Molly O'Shea?

  This is the first I've heard of that.

• 34:30Speaker 02

  So nothing to, I think, brag about, like, but like, you know, like, nothing to brag about about not going home.

• 34:36Molly O'Shea?

  You go home during weekends and you're still successful.

• 34:39Speaker 02

  Yes, imagine.

• 34:40Molly O'Shea?

  Crazy.

• 34:41Speaker 02

  But but I think like there is a certain baseline. I think that we we try to be realistic about like what to expect. And so that's part of the reverse sell, I think. Hey, like, there can be a lot of like time crunch, you know, like, you know, where we really push and we have to spend a lot of time working and 60 hours or 80 hours. And I think that like filters out maybe like certain, you know, certain people. So I think looking for hunger is very, very important. And then I think like culturally, I would say anyone like who interacted with our team, like on the customer side, they would probably attest to this is like,

• 35:24Speaker 02

  our team is like pretty low ego, like pretty easy to work with. I think we look for like humility in general, like, they gotta be really talented, but at the same time, like, not be a jerk about it. I think that's like pretty unique to find. And I think like, anyone who's interacted with like our team probably knows that. And that's, I think, why they really like us. Like, people are really easy to work with and like really friendly. I think you can have both at the same time. So so we try to, I think, filter for humility as well.

• 35:58Molly O'Shea?

  What have been the biggest surprise challenges that you guys have come across? And not just like the standard stuff, but it could just be like something you had no idea you were gonna expect.

• 36:09Speaker 02

  I'd say like, being at the forefront, like as a company, is pretty hard. I think, one, you have to really want it, right? Like, you have to wanna build a big, big company. And two, you have to like, keep up with it, right? Which requires a lot of effort. So that, I think in order to, you know, build a, build a big startup, you really have to just be very committed and be very hungry. And and I think like that's, you know, that definitely, that's a lot of work. You know, that takes, that takes a toll on you. I think Adam would say this, probably, you know? But but yeah, it just requires a lot of hard work.

• 36:53Molly O'Shea?

  I don't know, I asked him what he's most excited about. He says he doesn't feel excitement, so.

• 36:59Speaker 02

  So he's beyond that point.

• 37:00Molly O'Shea?

  You're gonna get there one day, no emotions.

• 37:04Speaker 01

  Our industry like is incredibly dynamic, right? It's when there's no like good model for a month, everyone starts panicking. Oh, my God, it's been one month, nothing new has happened. But the answer is just wait another month and something incredible is gonna happen. It's been true since we started. And that keeps excitement going and that keeps people like very encouraged that, okay, there's gonna be the next model that's gonna unlock these other use cases, which is gonna unlock these other types of customers. And that has brought so much growth to our business. And so far, it just keeps happening for us.

• 37:42Molly O'Shea?

  Where have you been seeing some of the best models come from? Do they just come out sporadically? Like, what is there any consistent theme between all of them?

• 37:49Speaker 01

  So right now, we play a bigger role in the ecosystem because we are an infrastructure partner for the model providers. But we are also the API partner for the application layer or studios, people who are consuming the models. So we got a good sense of supply on demand on both sides. And we are in such a compute constraint moment right now that if you are coming up with a new model, you really have to plan ahead of time. You have to make sure you have enough compute to run inference. If you are successful, you are likely not gonna be able to procure it on your own. So it's usually a good idea to partner up with an inference provider like us to do your launch.

• 38:32Speaker 01

  So we work very intimate with the with the model providers. And and for customers, like, they usually use multiple models at the same time. But they really care about model releases because they usually tie their product releases with model releases as well. So we we keep in very close communication with them as well. And then we have to sometimes anticipate how much growth is gonna come on the on the model side to procure our own compute, to maybe do some, some investment on our side to enable the whole space. And someone really has to do that because otherwise all the compute is gonna go to coding agents or whoever, whoever is like doing the bigger investment. By by planning ahead and investing on compute a little bit,

• 39:17Speaker 01

  we can enable both the model providers and the applications being built on it. So that has become our responsibility in the ecosystem these, these couple of months because compute is so hard to come by.

• 39:30Speaker 02

  I'll add a few more points. I think generative media is like very unique in the sense that in two ways. One, I think it's there's just more modalities. I think when people think of gen media, maybe they only think of video.

• 39:43Molly O'Shea?

  Yeah.

• 39:43Speaker 02

  But like you would have to think about text, image, image editing, video, 3D, text to speech, you know, speech to text. I don't know if I said 3D, like for gaming use cases, whatever.

• 39:56Molly O'Shea?

  3D, 4D, 5D.

• 39:57Speaker 02

  Exactly, all of these. So there's actually like many modalities within generative media. So like, and there's like, I don't know, five to 10 companies in each of these sort of subcategories within gen media. So that's like one interesting aspect. So there's just like a lot more happening. There's more fragmentation. And then the other is going back to what I said about like diminishing returns. I think it's still like so early in the space that there's actually a lot more leapfrogging happening between more players. Because like, we're not at like the 98 point whatever percent. We're only at like, I don't know, 50% of like, you know, where we're ultimately gonna go.

• 40:40Speaker 02

  So there's actually more people leapfrogging. There's more diversity in like the number of labs. So it's not just like, OpenAI, Anthropic, OpenAI, Anthropic, you know? It's more like, there's like eight, you know, players and they're all like leapfrogging each other.

• 40:56Speaker 01

  Like, one big reason is you're not running out of data. There is like so much video data out there and so much new video data is being produced every day that no one has, no one claims to train all of that data, right? They have to pick, the hard problem with training a video model is actually you have to filter out the interesting video data so that you make a, you make a good model. So if you, if you need to put more data into the model, there is abundance and it's seemingly free. There's enough free video out there that it works very well. But also, the problem space is bigger, right? You are trying to reason around like the whole world, physics, everything.

• 41:38Speaker 01

  So it's not as specific as coding or like as specific as certain LLMs are trying to optimize around. So there's a lot more angles people can take to, to create a more interesting and appealing model. And it's, it's been happening every other month almost.

• 41:55Molly O'Shea?

  I think that's where the naming comes in too.

• 41:57Speaker 01

  There you go. You have to differentiate with your naming.

• 42:00Molly O'Shea?

  I mean, they've got some funny names.

• 42:03Speaker 01

  Yeah. Happy Horse, Nano Banana. What's, what do you like?

• 42:08Speaker 02

  There's Happy Oyster.

• 42:09Speaker 01

  Happy Oyster.

• 42:10Speaker 02

  It's like a game model.

• 42:13Speaker 02

  There's Minimax.

• 42:14Speaker 01

  Sea Dance, Sea Dance and Sea Dream.

• 42:16Speaker 02

  Sea Dance, Sea Dream.

• 42:17Speaker 01

  I think those are.

• 42:19Molly O'Shea?

  I think when Nano Banana had like its moment, everyone was talking about Nano Banana for like three days. Even my dad was talking about Nano Banana. I was like, what the hell is going on here?

• 42:30Speaker 02

  I think, I think the backstory is that like it was an anonymous model. So like people do these like cloaked releases where they will release a model.

• 42:39Speaker 01

  It was a code name.

• 42:39Speaker 02

  They won't actually disclose who it is. Yeah, like it's a code name. Get like people excited about it because it's like ranks highly. And I think somehow they use that like Nano Banana as a placeholder name, code name.

• 42:52Molly O'Shea?

  Yeah.

• 42:52Speaker 02

  And then it just like stuck. So it became the original name.

• 42:57Molly O'Shea?

  If you guys were a model, what would your model name be?

• 43:02Speaker 01

  Sorbet.

• 43:02Speaker 02

  Sorbet. This is Gerk's favorite word. I don't know why.

• 43:07Speaker 01

  I wanted to rename the company I want, Sorbet.

• 43:10Molly O'Shea?

  Sorbet?

• 43:12Speaker 02

  He likes Sorbet a lot.

• 43:13Speaker 01

  Yeah. I, I also have this, I, I think about names, like I also want like these exotic colors, like burgundy, turquoise, you know, like, I think that would be a good series for model names.

• 43:26Molly O'Shea?

  That is a good name, I guess. What about you?

• 43:31Speaker 02

  I don't know.

• 43:31Speaker 01

  Sorbet could be a color apparently too. It's like the, the peach color associated with Sorbet is as a color.

• 43:36Speaker 02

  I like, we can do birds. There's so many birds.

• 43:40Molly O'Shea?

  Birds. Do you have a favorite bird? I'm asking for a name.

• 43:45Speaker 02

  Like you can even do owls, like there's so many owls. You can literally just do like different owls.

• 43:52Speaker 02

  You can do insects. I don't know, nature, I think is, it would be my theme.

• 43:56Molly O'Shea?

  Well, how did you come up with the name Fall?

• 43:59Speaker 02

  All right, so Fall.

• 44:00Molly O'Shea?

  Let's talk about this.

• 44:01Speaker 01

  Yeah, yeah.

• 44:01Speaker 02

  So Fall is, so we have a longer name, Features and Labels.

• 44:07Speaker 01

  It's a double entrant there.

• 44:09Speaker 02

  Yeah. And it's, it's, it's the initials of Features and Labels.

• 44:12Molly O'Shea?

  And it's not foul, it's fall.

• 44:14Speaker 02

  It's fall. Yeah, it's fall. Yeah, it's Features and Labels, which if you're a real OG, you would know those two terms. It's like from the machine learning world. It's like very old, like pre-AI. And so it's the initials for that. But also, it's, I don't know, have you had Turkish coffee?

• 44:34Molly O'Shea?

  Yeah, I have.

• 44:35Speaker 02

  Okay, so have you been like told your fortune from like the coffee grounds?

• 44:40Molly O'Shea?

  No.

• 44:40Speaker 02

  All right, so that's Fall. It's like, like your fortune told by the coffee grounds. That, you should, you should get it done. We'll do it sometime.

• 44:49Molly O'Shea?

  Okay, okay, let's do it.

• 44:50Speaker 02

  So, so you know, it's like your future prediction.

• 44:53Speaker 01

  Someone looks at like when you finish the coffee, it looks at what's remaining.

• 44:56Molly O'Shea?

  Are you guys trained in that? Can you tell fortunes?

• 44:58Speaker 01

  You know, no, everyone's trained in Turkey. Everyone has done it before.

• 45:01Speaker 02

  Yeah, yeah, you, you, it's like, it's like.

• 45:03Molly O'Shea?

  Can we do it right now?

• 45:04Speaker 02

  We could try.

• 45:05Speaker 01

  Yeah, yeah, we'll get some coffee, yeah. I think they have Turkish coffee here.

• 45:10Molly O'Shea?

  Oh my gosh, that's fun. Do you think the open source, closed source debate is still gonna be going on in two to four months, six months? How long do you think that's gonna keep on going?

• 45:21Speaker 01

  I think so, because like anyone who's falling behind a little bit, open sourcing their model is an incredible marketing tactic. And the whole world starts talking about you if you open source your model. And there are real advantages. Like if you talk to anyone, any of these studios in Hollywood, they, they wanna be able to fine tune the model. They wanna be able to apply different Laura's filters to change the lighting, to be able to use their unreleased characters, their unreleased styles on the models. And the only way to do that is, is, is open source. So there are real technical advantages to it. Also, it's an incredible marketing tactic.

• 46:05Speaker 01

  And so people are just gonna keep doing it. Someone's gonna create a frontier model. People who are falling behind is, is gonna open source it and the pendulum is gonna keep, keep swinging. We thought this was a bigger threat to our business in the beginning because we were running mostly open source. And then we started partnering up with closed source models and running inference for them as well. So it's a, it's a win-win situation for us. But open source makes it a more interesting ecosystem. And I think it's, it's good for the industry in general. So we always welcome more open source models and we support as much as we can the community.

• 46:43Speaker 02

  I think the fact that like people wanna protect their IP and like that, that's gonna continue, right? Not just for media, but also like you, you wanna protect your source code, you wanna protect your customer list, whatever, right? Like all of that, that's always gonna be a thing. So I think, yeah, if you have something local, you know, you don't have to worry about it. So I think, I think it's, it's always gonna be there, this, this debate.

• 47:08Speaker 01

  Like when we talk to our customers, if they know the model is run on our GPUs, they, they trust the whole process so much more. Open or closed, this, this works the same. But that, that has been a big differentiation for our business. When, and obviously when it's open, like they know for sure that they can even sell for us, but they, they trust us because we can do it better than them. But trust is, is really important with, with video models especially because people don't want their unreleased content to, to leak. And it's usually an input to the video model when these creatives work with it. And so we've been really pushing on that with, with the enterprise customers and it resonates.

• 47:52Molly O'Shea?

  How good is AI at real professional work? Merckor's AI Productivity Index, or APEX, tracks it with every major frontier model release. Build with partners like Harvey and Cognition. See where the frontier actually stands at mercor.com/apeX. Today's episode is sponsored by V C X by Fundrise, the public ticker for private tech, allowing investors of all sizes to invest in venture capital. Learn more at getvcx.com. Public is a multi-asset investing platform where you can automate your investing with AI agents. Create your own custom agent with a simple prompt. Agents can monitor markets, execute trading strategies and manage your cash across stocks,

• 48:35Molly O'Shea?

  bonds, options, crypto and more. Wanna buy at market close and sell the next day is open? Just tell your agent. Automate your investing at public.com. Founders scale faster on Deal. Set up payroll for any country in minutes. Hire anyone, anywhere. Get visas handled fast and get back to building. Visit deal.com/sorcery. That's D E E L dot com slash sorcery. Talking macro, what do you think the biggest question is that people aren't asking right now?

• 49:07Speaker 01

  I would, not exactly that, but if you, if you listen to like any Hollywood podcaster or look at the news about Hollywood, they always have this angle of AI is gonna kill Hollywood. And we are like really, in this business, like we talk to these people all the time. So far, I would say AI had zero impact on anything in Hollywood. It's just like people are projecting to the future a little bit. The business we get from Hollywood has been increasing in the last six months. I think it reached to a meaningful percentage of our revenue. But I would say it had zero impact on the, on the labor.

• 49:49Speaker 01

  It barely made any content that's worthwhile in Hollywood. It's gonna happen, there are signs of it, but we've been talking about it for four years and it's always been fear mongering and, and nothing real. I think that's the thing that people don't realize from a distance.

• 50:06Molly O'Shea?

  Yeah, most of LA, like that's where this is happening. It's really regulatory and what they're doing there with different laws.

• 50:14Speaker 01

  Exactly.

• 50:15Molly O'Shea?

  It really has nothing.

• 50:16Speaker 01

  And that's been the reason the adoption has been slow because it's, it's not only the, the quality of the models, the lawyers of the companies need to be okay with it as well. But finally, slowly, we are seeing that everyone is, is going full force at it.

• 50:32Molly O'Shea?

  What do you think people should be asking? What are, what's, what's going on out there?

• 50:35Speaker 02

  I think people are asking everything.

• 50:38Molly O'Shea?

  They're asking too much.

• 50:40Speaker 02

  They're asking too much. Yeah, I don't know, there is, there's a lot of skepticism, I think, about use cases. Again, like just speaking more broadly about AI, right? There's, there's certain skepticism about, oh, like all of this CapEx investment, where is that gonna go? And like, you know, like is AI actually useful?

• 51:03Speaker 02

  But I think, like, I'm, I'm more on the optimistic side. I, I don't think, a lot of the people who are making these claims, I don't think they, they really actually understand like what's going on, how like AI is actually being used at companies. And, and you know, I think gen media is still like, still very early. If anything, like it's, it's just starting, it's just like gonna, I think ads, we're starting to see it. Hollywood, social, whatever, we're starting to see it. I think there's, there's real value. Like, we were just estimating like how much faster we're going, like our software engineering team is moving. And I estimated somewhere between like three to four X.

• 51:45Speaker 02

  Like we would, we would need, pre-AI, we would literally need like four times the people to go at the same speed. So, and we're definitely paying less than that.

• 51:54Molly O'Shea?

  Yeah.

• 51:54Speaker 02

  Right? So there's clear ROI for us. So, so yeah, I think, I think if you, if you really like go deep into the ROI for the, for the companies who are using AI, like if you really go deep and actually try to measure it, not read it like from a bunch of reports or like, I don't know, non-technical people, I think, I think you'll see a different, different picture. So, so yeah, I'm very in favor, like very long compute, as, as they say.

• 52:24Speaker 01

  Like we talk about it, every big company is gonna be a compute company. Just the storefront is gonna be different. Our storefront is unique and interesting, like no one else has a storefront similar to us. Some has coding agents. If you go to a NeoCloud, there is no storefront. If you go to Databricks, whatever, it's about like data. Everyone has a different story and different way to talk about it. But behind the scenes, it's who's running the most compute? That's, that, that brings the revenue. And yeah, we have a unique, interesting storefront and it, it keeps growing.

• 53:00Speaker 02

  Yeah, and there's not enough of it. Like, all the numbers you hear, you know, like 200 billion in, you know, CapEx and whatever, like a lot of that stuff is like not built yet. So, like it's very slow, right? Like building these things is, takes a lot of time and there's not enough compute right now.

• 53:20Molly O'Shea?

  So I have two final questions and then I'm gonna ask you what your hot take is. I'm letting you know that now so you can like get it.

• 53:26Speaker 01

  Think about it.

• 53:29Speaker 01

  This was a hot take.

• 53:30Molly O'Shea?

  Don't wanna catch you.

• 53:31Speaker 02

  Yeah, he's a hot take.

• 53:32Molly O'Shea?

  You guys, you guys have been crushing it. You have great answers and they're quite opinionated, so it's awesome. But before we get there, what are you most looking forward to in the next 12 months?

• 53:43Speaker 01

  I'm looking forward to the first timeless AI content. And the way I define this is you and I, we are gonna watch this and it's gonna be a year later, we're gonna watch it again and we are still gonna like it the same way we like it today. So far, AI content has been about capabilities. It's been about, oh, look, this is possible to do with a video model or that's possible to do with like an image model. But we need to reach to that point where things look fresh all the time. And I, I'm looking forward to that. I think we are, in the next year, there's gonna be a widely accepted, maybe a short movie, maybe animation, that people are gonna look back at it in a couple of years

• 54:27Speaker 01

  and they're still gonna enjoy it the same way they're enjoying it today.

• 54:30Molly O'Shea?

  It's pretty good.

• 54:33Speaker 02

  Evergreen content.

• 54:34Speaker 01

  Yeah.

• 54:34Speaker 02

  It's very important.

• 54:35Molly O'Shea?

  I tried to do that, but.

• 54:36Speaker 02

  There you go.

• 54:36Speaker 01

  Like people say, Toy Story is, is that for computer graphics? Like that was the first time, it came out in 1996, something like that.

• 54:45Molly O'Shea?

  Isn't it crazy how long ago that was created?

• 54:47Speaker 01

  You know, we can just go watch it and it's gonna be good.

• 54:49Molly O'Shea?

  Yeah.

• 54:50Speaker 01

  It's, I'm gonna enjoy it.

• 54:52Molly O'Shea?

  Did you like The Odyssey in that way?

• 54:53Speaker 01

  I haven't seen it yet.

• 54:55Molly O'Shea?

  You haven't seen it? All you've been doing is talking about Christopher Nolan, you haven't seen it?

• 54:59Speaker 01

  I'm, I'm waiting for the IMAX, the big IMAX, and I couldn't, I couldn't get a ticket yet, yeah.

• 55:04Molly O'Shea?

  Go to the Sphere.

• 55:06Speaker 01

  Did they show it there?

• 55:07Molly O'Shea?

  I don't know.

• 55:10Speaker 02

  It's too big.

• 55:11Speaker 01

  Too big.

• 55:11Speaker 02

  Not as Nolan intended.

• 55:13Molly O'Shea?

  No.

• 55:14Speaker 02

  For me, I would say like world models is, we haven't spent too much time talking about them. I think they're super exciting. I, I was like, I was very skeptical, like even three months ago. So world models are these models like you can actually like play around and like move around. It kind of like looks like a game and you can actually like put in actions like with your keyboard and you know, you can navigate the world. But like seeing what I've seen recently, it's, it's pretty incredible. I actually started feeling very bullish about it.

• 55:49Speaker 02

  It's a matter of, I think, the quality going up and then the speed getting so much better. And I think there's like new architectures now that like people are able to actually have like more persistent worlds. Before you used to like look this way, you know, see the flower, look away, come back, it's gone. So they're able to like purchase things now and you can actually, you'll be able to like actually build like a game with a prompt. But I think that space is like just gonna blow up. So again, the big challenge there is compute, but I actually think that because you need like a GPU running at all times to actually like play that game. But I think the, the quality of the games itself is gonna go a lot better.

• 56:32Speaker 02

  And I think it's gonna be probably yet another product market fit, like gaming with AI. That's not like a thing yet. I, I actually think there's a big chance that may happen and it might be like this fourth category maybe.

• 56:45Molly O'Shea?

  Very expensive.

• 56:46Speaker 02

  Yeah.

• 56:48Molly O'Shea?

  Damn, okay, so this is, we have one more question until the hot take. I'm just letting you know, again, I'm warning you. Okay, so Sorcery is very proud to be sponsored by Brex. I don't know if you know what Brex is, but.

• 57:03Speaker 01

  Of course.

• 57:03Molly O'Shea?

  Brex knows where you are.

• 57:04Speaker 01

  Proud users, yeah.

• 57:06Molly O'Shea?

  So they're all about spending smarter, moving faster, performance, the performance corporate card. I like to take this question in the personal bend to things. I mean, you guys have worked for legends, whether it's Brian Armstrong, Jeff Bezos. I mean, you like Chip, so you might like Jensen Huang, I don't know. And then you also like Christopher Nolan. So I'm curious, who are some figures that really inspire you and keep you motivated? Who keeps you like running at it?

• 57:34Speaker 01

  Great question.

• 57:38Molly O'Shea?

  To be your dog, I don't know.

• 57:43Speaker 01

  Of, of the, you know, previous generation of founders, I think Jack Dorsey is very underrated.

• 57:51Speaker 01

  I think he has more range than, than anyone else. And, and then like now he's, he's like maybe, maybe coming back. I think watching his, his journey with Twitter and then Square, I, I never got to work close to with him. But that, that's a like inspiring figure. When I was younger in Silicon Valley, I always like look up to what, what he was doing. Yeah.

• 58:20Speaker 02

  I wouldn't say it like keeps me going level, but like I really like Ali, Ali Gotze.

• 58:28Speaker 02

  I think he's like transformed his company many times, like over time. I think like I like to think.

• 58:36Speaker 01

  Keeps reinventing.

• 58:37Speaker 02

  Keeps reinventing and I think that's very important. I think that's like a secret to building a long lasting company and navigating through like all these changes that are happening. So yeah, really great leader, I think.

• 58:54Molly O'Shea?

  The time has come. What is your hottest take right now?

• 58:58Speaker 01

  Do you have it?

• 58:59Speaker 02

  No.

• 58:59Speaker 01

  Nah.

• 59:02Speaker 02

  There's so much pressure.

• 59:08Speaker 02

  Well, we can, we can take our time.

• 59:09Speaker 01

  Yeah, let's take our time. You can cut it, cut it.

• 59:11Speaker 02

  And then it's like dark outside.

• 59:14Molly O'Shea?

  Should we prompt you with some like?

• 59:18Speaker 01

  No, no, let's, let's do it.

• 59:20Speaker 02

  I have a good one.

• 59:21Molly O'Shea?

  It could be on like IPOs, it could be on like companies disappearing. It could be on fake GPUs that people sell from.

• 59:29Speaker 02

  Oh, wow.

• 59:30Molly O'Shea?

  I don't know where they get them. Could be.

• 59:36Speaker 01

  Yeah.

• 59:37Speaker 02

  I had a hot take like a year ago, the OpenAI Meta merger.

• 59:42Speaker 01

  Yes.

• 59:42Molly O'Shea?

  Oh, could still happen.

• 59:46Speaker 02

  It could still happen.

• 59:47Molly O'Shea?

  They're not doing too great.

• 59:48Speaker 02

  I think it makes sense.

• 59:49Speaker 01

  It would be bad for the whole industry, but.

• 59:51Speaker 02

  Sure, sure, okay. So, so not, I guess like not too spicy or anything, but I think it makes a lot of sense. Like OpenAI was like known for this like, you know, consumer like edge, right? Right? Like that was their whole thing, right? Oh, like OpenAI is winning in consumer, therefore they're going to win. Because like consumers so much harder to win. And then Anthropic sort of came with, you know, their enterprise thing. And, you know, and then Google started adding, made their, their own consumer move. And so I see like OpenAI not necessarily like winning very strongly in either enterprise or consumer.

• 1:00:31Speaker 02

  And then Meta, on the other hand, I think is in a similar situation where like they, they need something. And I thought, what if they like combine their forces? That would be really cool. So like they can really just like, really start winning consumer. So I, I thought it makes sense. But again, I have no information about any of this. So we're completely, completely speculating, but I, I thought it would be a good move.

• 1:00:57Molly O'Shea?

  That is very interesting.

• 1:00:59Speaker 02

  Another one.

• 1:01:00Speaker 01

  This is, this is a common hot take. I'll do it for both of us.

• 1:01:03Speaker 02

  Sure. I have more now.

• 1:01:06Molly O'Shea?

  Okay, good, good, good. It's coming.

• 1:01:08Speaker 01

  The consensus view was there's going to be more margin in the application layer.

• 1:01:13Molly O'Shea?

  Yeah.

• 1:01:13Speaker 01

  And I think it's completely reversed. Margins are close to zero in the application layer. There's so much competition. People need to spend so much money for marketing. You can only create margin if you are in the compute path and you can innovate in that path. That's the only way you can create margin, which wasn't the case when we started the company four, five years ago. Everyone thought like the, the, the infra layer is going to end up with price going to the bottom. And application is going to have margins looking around. Application layer doesn't have any margin today as well. So wake up, we see.

• 1:01:52Molly O'Shea?

  It's a good one.

• 1:01:53Speaker 02

  Yeah.

• 1:01:53Molly O'Shea?

  We talked to Tony Kim about this at Ray's and he was like,

• 1:01:58Molly O'Shea?

  the chips have much better margins than all these other companies.

• 1:02:01Speaker 02

  There are only ones with margins right now.

• 1:02:05Speaker 02

  I have another one. I think this is a very recent one.

• 1:02:08Molly O'Shea?

  Okay.

• 1:02:09Speaker 02

  I've been kind of like toying with this. I think coding is part of gen media.

• 1:02:13Speaker 01

  Oh.

• 1:02:14Molly O'Shea?

  Really?

• 1:02:14Speaker 02

  Yes. Well, it's also part of gen media, right? Like it's its own thing, but at the same time, like we're seeing so many developers building like richer applications that are not just like a website. Like they can be, you know, programmable video, right? Like content, like maybe you've seen these websites that like look more like a video. Like there's, I think coding is becoming more and more like a very key part of like what the developers on file are using. So I, you know, I think we're going to like have to invest in it because there's just so much demand from our, our own customers.

• 1:02:53Speaker 01

  Everything is a computer.

• 1:02:54Speaker 02

  Everything is a computer.

• 1:02:55Molly O'Shea?

  Everything is computer.

• 1:02:56Speaker 02

  Everything is computer. That's the hot take.

• 1:02:58Molly O'Shea?

  That is the hot take. Well, that's a great place to end. Thank you guys so much. I'm very excited for dinner and.

• 1:03:05Speaker 02

  And the coffee.

• 1:03:06Molly O'Shea?

  And the coffee. I can't wait to know what my fortune is.

• 1:03:09Speaker 02

  There you go.

• 1:03:10Molly O'Shea?

  Cool.

• 1:03:10Speaker 01

  Thank you.

• 1:03:11Speaker 02

  Thank you, Molly.

• 1:03:12Molly O'Shea?

  Hey, it's Molly. If you enjoy our interviews, check out our newsletter sorcery.vc, where we deliver a once a week top deals and tech headlines email and also go deeper on our podcast interviews. Subscribe to Sorcery today. And don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen. Link in description to sign up.