TBPN Live - Google I/O Reactions, Birth Rate Debates, Spotify's New Icon | Jim Belosic, Aidan Dewar, Fai Nur, Tanay Tandon, Ajeya Cotra, Philip Inghelbrecht

Episode Date: May 19, 2026

(00:09) - Google I/O Reactions (24:14) - Karpathy Joins Anthropic (28:29) - Reactions to Spotify's New Icon (33:49) - Birth Rate Debates (45:18) - Jim Belosic, CEO and founder of SendCutSend, a company specializing in on-demand manufacturing services, discusses the recent achievement of securing a $110 million investment, valuing the company at $1 billion. He shares plans to utilize the funds to expand operations, including hiring additional staff and enhancing software capabilities, aiming to establish facilities near major metropolitan areas to expedite service delivery. Belosic also highlights the company's commitment to supporting STEM education through a $1 million sponsorship program, providing resources and expertise to engineering students and educators. (01:04:18) - Aidan Dewar, co-founder and CEO of Nourish, discusses the company's mission to address chronic diseases through dietitian-led metabolic clinics that combine a vast network of registered dietitians with virtual medical care, including lab interpretations and medication management. He emphasizes the importance of pairing GLP-1 medications with behavioral changes to achieve sustainable health outcomes, noting that patients working with Nourish dietitians while on GLP-1s lost 33% more weight than those using the medication alone. Dewar also highlights the company's recent $100 million Series C funding, aimed at expanding their services and integrating AI technology to enhance patient care. (01:12:41) - Fai Nur, CEO and co-founder of Status, discusses the app's rapid growth, reaching a million users in 19 days, and its appeal to young users seeking immersive, gamified social experiences. She highlights Status's monetization through in-app purchases and subscriptions, achieving millions in annual recurring revenue and a tenfold increase in revenue in Q1 2026. Nur also addresses the platform's use of AI to create user-generated worlds, emphasizing its role in offering unique experiences that complement traditional entertainment. (01:22:57) - Tanay Tandon, CEO of Kamir, discusses the company's recent $70 million funding round at a $7 billion valuation, aimed at accelerating R&D for their language model-powered EMR platform and voice agents. He highlights the trillion-dollar administrative burden in the U.S. healthcare system and how Kamir's AI solutions automate tasks like claims processing and documentation to reduce costs and improve efficiency. Tandon also addresses the rapid adoption of language models in healthcare, the potential for AI to empower independent practices, and the evolving dynamics between providers and payers. (01:33:02) - Ajeya Cotra, a technical staff member at METR with a background in AI safety, discusses her role in leading the Frontier Risk Report, which assesses misalignment risks in advanced AI systems. She explains METR's mission to develop measurement tools for tracking AI capabilities and motivations, and describes the collaboration with companies like Google, OpenAI, Meta, and Anthropic to evaluate their internal models and alignment processes. Cotra also highlights the importance of establishing robust, independent auditing practices to monitor and mitigate potential risks from misaligned AI agents. (01:48:11) - Philip Inghelbrecht, a Belgian-born entrepreneur and CEO of Tatari, a company specializing in technology for TV advertising, discusses his journey from co-founding Shazam in 1999 to leading Tatari. He highlights the challenges and innovations in TV advertising, emphasizing the importance of measuring real outcomes and the integration of AI in media planning. Inghelbrecht also reflects on the evolution of TV advertising, noting the shift from traditional methods to data-driven strategies that bridge the gap between linear and streaming TV. Follow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

You're watching TVPN. Today is Tuesday, May 19th, 2026. We are live from the TV panel, Trilm, Temple Technology, the Forteous Finance, the Capital Capital, Google I.O. starts today. And the stock is ripping. I think people might have missed this if you haven't been watching closely. But Google is up 140% in the last year. Absolute ripper. It's almost a $5 trillion company now. I was really confused what chart you're reading because it's down one. 0.3% today. Today, oh, okay. No, it is up, it is up massively.

We think in years, sometimes decades. Yes, yes. And, yeah, they pulled in just shy of $110 billion in revenue last quarter, and they're in a great position for the next era of the AI story. So GCP is growing faster than AWS and Azure. Wall Street has basically fully repriced the company as a full-stack AI winner, that's the new narrative across Google Cloud, Google Search, Gemini, the models, deep-mind, everything that they're doing.

So long gone are the concerns about Google's search's weakness, because even core Google Search is is showing resiliency. Google Search, the business continues to grow. Queries are at an all-time high. They're not reporting exact numbers of queries, but Sundar said that in the last call, that it's at an all-time high. certainly not going down. And search in other revenue, which is their bucket there, is up 19% year over year.

So holding up well. And Google I.O. generally offers consumers launches or previews of tons of new products. I'm getting called. Previews of tons of new products and features. And the verge was saying that there might be some like AI fatigue, which is maybe be an overstatement given that, you know, people are getting booed. Actually, the former CEO of Google. Yeah, understatement, giving that the former CEO of Google, Eric Schmidt, was booed offstage at a commencement speech.

And so that is a good point. But, you know, the people that watch Google I.O., the Google core consumers, they are fans of this stuff. I think they're generally pro-AI excited about new features. Some of the new features that will show are very, very cool. But there is this like goal of being ambient and useful instead of pushy and desperate. Many Google experiences now have duplicative Gemini panels. And I was writing this update in a Google Doc. And I noticed that I had two Gemini stars, basically. One Gemini Star in my Google Doc. And then another in the Chrome browser that I'm using to load Google Docs.

And it's a really hilarious outcome because I was writing this. in sort of like a half window to the side of the screen. And if I open both Gemini panels, the Google Doc disappears entirely. And I'm just left with two chat boxes to interface with the Google Doc, which I don't really use AI in the actual Google Doc. I just kind of write it.

But there's stuff it everywhere and then actually make it useful, make it ambient, make it delightful. And so that is, I think, what consumers are looking for, more than just an AI button in a new place. But they're certainly showing that already.

And so the new Gemini video model looks incredible. We'll play some videos of that. And there will be tons of delightful experiments that may turn out to be blockbuster products or they may get shelved by year end. That's kind of the beauty of Google's culture is that they have plenty of opportunity for experimentation. We sort of, some people remember all the things that are in the Google graveyard. But most people just remember Gemini and whatnot.

So yeah, we can play this video with sound because the sound is... A V8 engine features eight cylinders, arranged in a V shape driving a single crankshaft. They take turns firing to deliver smooth, massive. That's pure mechanical genius at work. A V8 engine features eight cylinders. So I feel like this got rid... I mean, the video fidelity is incredibly high quality. There's no six fingers.

It looks HD. The motion looks good. The lips are synced. And I feel like they got rid of that like hollow sound that you used to. to hear in AI video where the audio was generated alongside. You can still clock it, but it's a lot more subtle. It's really subtle. There is one weird thing in this where it says, he says, deliver pure, massive, and

then it just cuts to the next scene. That's pure mechanical genius at work. A V8 engine features eight cylinders, arranged in a V shape driving a single crankshaft. They take turns firing to deliver smooth, massive. That's pure mechanical genius at work. energy or smooth massive propulsion, something like that. So like, hey, it's crazy because you see these and you're like, oh, I feel like, this is it.

Like, it's done. Like, this is fully, fully done. And then there's just like, ah, we're at 99.9.9% now. And I want to be at 99.99% percent. Also, like, this is kind of a nitpick, but isn't that a V6, right? Oh, is it? Wait, play the video again. Let's see.

I want to see if it's a V6 or a V8. Because when I look at those graphics, I think, okay, let's count the cylinders. Oh, yeah. No, no, it looks like an eight. It looks like eight cylinders in the back. Now, count them up. I can't really tell. But yeah, it's odd. It's so passive. But I don't know. Is this good for video explainer channels on YouTube? Bad for video explainer channels on YouTube. Certainly commoditizing the production of video explainers. I've seen a lot of these video explainers that will show you like inside of a rocket or inside of an RPG or an AK-47 or Glock. And those get, like tens of millions of views. They can be viewed in any language, but they're very intense from a, from a CGI perspective. You have to go and model every little detail, every pin in the, in the weapon or whatever the object is that's being visualized in this particular video explainer. Close to being on command, and then the question is, where does the value sit?

does, if you prompt YouTube and you ask for a video explainer of, you know, a chair, break it down, explode it, show me the innards, will it just do it on demand for you? Will it just generate that? Or will this still sit below the creators? Yeah, I've always had the question at what point do you go to YouTube and there's just a series of videos waiting for you that were generated based on your interests, right? Sometimes, you know, you might be going to YouTube because, your favorite sports team just played and you want some analysis on the game or, you know,

your favorite fighter or something like that, where some news is happening. And it doesn't seem like we're that far from a future where you land on YouTube. And YouTube is just, again, fully generated a video based on what it knows about your interests. That said, that would cause potentially a creator strike. because it's YouTube starting to compete against their own content producers on the platform. Yeah. So we'll see. Yeah, at least in the interim, it feels like the dawn of stock footage.

YouTubers have been creating these, I've been using these tools for a long time. They have been getting cheaper. Even the CGI world has become increasingly commoditized every year as you get more to templates and the tools become cheaper. You used to have to pay thousands and thousands of dollars for a license of sales. Cinema 4D or 3DS Max to render anything now. Blender is open source and free. And there are tons of blender artists out there with custom packs.

But yes, this is a new capability. And it'll be interesting to see how this gets integrated, what the pushback is like, how clockable it is once is actually in the hands of creators. And they are pushing it out. Let's watch this other science explainer from the timeline. Gemini Omni explains science with video. Thanks a lot for this. says Chetoslua. Now every student will get a custom video for the topic of science and math.

I'm so happy while typing. I want to see all your reaction into this. I don't know. This is about photosynthesis, I think. Every color of the rainbow. As this light enters our atmosphere, it crashes into molecules of nitrogen and oxygen. This triggers a phenomenon called Rayleigh Scattering. Because gas molecules are tiny, they affect shorter wavelengths much more than longer. ones. Blue light has a very short wavelength, so it's scattered in every direction, filling the sky with color. Meanwhile, longer red wavelengths pass through almost a big push on YouTube for like, as people ask questions, like, they would go to Google and say, like, how do I fix

this particular washing machine? You type in the number of the washing machine, and it would take you to not just a single video about someone fixing that washing machine, but the actual section in the video with the solution to the exact problem you had. And, and you know, and And being able to read a manual and constitute a video on the fly of exactly that is pretty incredible. And you can imagine satisfies that use case very, very quickly. And then, of course, there will just be entertainment and all sorts of different use cases. Logan Kilpatrick, friend of the show, says introducing Gemini Omni.

Omni is our new model that can create anything from any input, starting with video, starting with video. Think nanobanana but for video. Okay. Yeah, let's play this because there's some amazing like different styles here going on. I wonder if those, if that motion graphic transition was created in Omni.

Because that's something that would you normally bump out to After Effects for, or like the edit here. I wonder, I wonder if, if you'll be able to upload multiple clips and have it edited together to the beat of a song that you pick or will it be able to AI generate a video and then match the match the footage to the beat of the video? So does give it anything,

so I think you could potentially give it a bunch of videos and it could edit it together and do a vibreel, something like that. Swap style, swap environment, swap angle. They've been having a lot of fun with this. Everyone is very, very excited about this. The other news out of Google today is Gemini 3.5 Flash,

our most powerful model to date. It pushes the frontier of intelligence speed and cost, putting 3.5 flash in a class of its own. We spent the last six months making sure Flash is great for real-world use cases. It's the strongest agenic coding model yet from Google. It delivers frontier level performance at 4X, the speed of comparable frontier models, often at less than half the cost.

So dominating the Pareto Frontier has been the goal for a long time. The speed is being heralded as a key feature. Google just showed a demo of Gemini Flash running between 600 and 1,400 tokens per second on TPU8I. It peaked out around 1480 tox tokens per second, with an average of around 800 tokens per second. So very, very, very fast. The flip side is, it's more expensive than previous Flash models, but that's been the trend with smarter intelligence for a while. So investors are focused across three key areas, not so much the consumer story, more the next Gemini model. So where this fits in. And then what adoption and diffusion

looks like, how Google through Google Cloud will be getting this out into enterprises, into coding agents. Obviously they have anti-gravity, but Gemini CLI has not seen as much traction. And so better model might pull that forward, might wind up seeing more traction there. Overall, I think token generation at Google is up 7x year over year, which seems great. It's unclear how much of that is because there's more reasoning happening. But given the fact that the Gemini models are sort of stuffed all over the product surfaces, I'm not surprised that there's massive growth. That makes a lot of sense.

On the core Gemini model, everyone was wondering, are we getting four, 3.5 launched, and there's a staged rollout with Flash going first. Andrew Curran had an interesting post here talking about the lack of vague posting, the deep mind folks have not been vague posting about the new Gemini model. So he did some vague posting for them. He says at this point, everyone knows it's arriving tomorrow, along with their personal agent named Spark.

This reticence, of course, can be interpreted in many ways. I'm choosing it to, I'm choosing to interpret it in accordance with my nature. I think they trained the largest model they've ever successfully trained, probably, possibly the largest one anyone ever has and something unexpected emerged at scale. They had their mythos moment,

but not in the same way. way Anthropic did, Gemini has always been a very different model from Claude. The benchmarks will go out tonight under embargo. They probably already are. But I don't think they will fully reflect what I'm talking about. I think they hit something even they weren't aiming for, something that surprised them. If I'm right, that surprise will be part of tomorrow's show. We shall find out together in the morning.

I don't think tomorrow's show, because I.O. is a number of days, and there's a whole host of different announcements that could happen. in the interim. There's a lot of other things going on. Yeah. Has anyone been vague posting around? Will there be a 3-5 pro this week? Yeah. Yeah. That's going to happen over the course of the next few days. They just started with flash. Okay. Starting with Flash. Cool. And then they also announced Spark. Yes. Which is a personal agent that lives in anti-gravity. Oh, okay. It's my understanding. Oh, interesting. And so trying to make. When I hear personal agent, I think more like Gemini app, Google search, like Gmail, like the very, like the consumer product services.

I think, well, I guess I just think personal and I think consumer. But given how much people are using CodexClaude code for like personal like things, like just because writing code creates a more dynamic agentic surface, open claw, we saw all of this. It's helpful to have something running on a MacBook Pro that can go around and find different stuff. Yeah, just in an additional context. 3.5 Pro is coming out next month. Next month.

So not this week. A little bit of a delay there. I wonder what else is in the bag of mythos like surprises because the cybersecurity one was like sort of predicted by the AI 2027. I feel like bio is next. Like it feels like, okay, we tested a bunch of stuff and we talked to a bunch of scientists and like this thing can come up with like super viruses and it's really scary. So we got to give it to all the pharmaceutical companies in advance and like Moderna gets it and

creates like antiviruses or something like that. I don't know what else. But I'm sure there will be superiors. there always are in the AI era. So from an investor perspective, obviously, I don't think Google I.O. is necessarily the correct forum for discussion of a mythos-level breakthrough or surprising new emerging capabilities.

I would just be surprised if that's where, like, you stand on stage and you say, hey, we had this crazy breakthrough. That's, it's a more serious thing, if you're talking about new capabilities. But given the talent and resources of the deep-bind team, TPU. I think that there's just a lot of broad optimism about the next iteration of Gemini. They've hired a bunch of people. They have a bunch of surface area to deploy this into.

So no one's expecting like the model to underperform. Agenda Commerce will also be top of mind for investors since messaging around the Google, the Gemini app has sort of strayed away from advertising as an immediate monetization engine. I think Demis said that at Davos. Google has a lot of capabilities when it comes to closing the consumer shopping loop. Like they have Google shopping. They have a bunch of hooks into. all sorts of different e-commerce services. They have massive product catalogs.

People search for stuff on Google all the time to buy. But e-commerce customer behavior seems to be lagging expectations here generally. There's been a lot of announcements from companies around agentic shopping protocols and the numbers. Whenever we dig into them, we're always like, is it going to get to 1% this year? Are we going to see? And everyone's talking about the growth, which means we're growing from zero, obviously, this didn't exist. But where is it going? Will Google have something to show here?

Will they have some sort of demo of a new user experience, a new flow for Agent of Commerce that results in a faster takeoff of that adoption of that behavior? Personally, I've done a ton of research about products through LLMs, but I pretty much always hesitate to have AI fully process the checkout. And there's a few reasons. Like Apple Pay is pretty good, pretty seamless. Shopify saves all my annoying info. Auto fill is also not that bad.

It's usually pretty good in whatever native, if I'm in Chrome on Mac or I'm on Safari, on iPhone. It's usually pretty good. And then I feel like I still like reality checking carts before clicking pay. We talked to Joanna Stern about this too, where she was talking about having an AI agent assemble a cart of even like something like groceries, but then she will be the one to actually go to the hydrated final link with the cookie and then go and validate everything.

before clicking pay. The last focus area for investors generally is TPU. There's been a lot of back and forth around, are too many of the TPUs going to Anthropic? Are too many of them? Are they sitting idle at D-Bind? What's going on with the TPU? And what are the margin structure?

How is revenue booked around TPU? How is the backlog accounted for? These are questions that investors in Wall Street are asking. I don't think we'll get answers at I.O. But investors will be watching for anything that's sort of contextual. realizes the shape of Google's TPU business and their plans over the next few years. And so, as I mentioned yesterday on the show, we had a lovely conversation with Joanna Stern from

thenewthings.com and the author of I Am Not a Robot. And we had lots of fun takes about, like, the AI tools that I think most of us have interacted with. Everyone's used agents. Everyone's sort of felt what it's like to talk to a chatbot. But one place where she went deeper than I think most consumers and like AI fans have is in the wearables because she was wearing that recording device consistently. And she maintains that like humanoids are farther away. You need a lot more training data. The AI chat apps are here. We already know they're diffuse. Waymo is now boring. But the next big wave she's sort of predicting is in the next few years, wearables will have like a big moment and everyone will be sort of adopting these and contending with them. And it is interesting how,

we talk about a capability overhang in the enterprise with AI deployments, and that's why the big labs are partnering with consulting firms and private equity groups to get AI installed into large corporations. There's even more of a capability overhang in consumer hardware. Apple iterates extremely methodically. They made a big story about Apple intelligence. Was that just one year ago? I guess that was one year ago, because WWDC is in a few weeks. But it feels like longer than that they had, I just remember they did a global billboard campaign for Apple intelligence. Yeah. But anyway, like the actually changing anything in hardware takes Apple a long time.

They still haven't launched a folding phone. Like they take their time to deliver a great product at the right time. And then if you're a challenger and you just want to manufacture new devices at scale, that takes years to ramp up. And then you also have to, you know, distribute sell. It's not one click away. it's go to the store or wait and wait for the mail. And then hardware decisions that get made around certain AI workflows can potentially be obsolete in months as the underlying technology changes. So you could build a device that assumes that, you know, LLMs are the end state and then reasoning models come and you're not set up for that potentially.

On device, compute could change. It's unclear. And so you don't want to get locked in these things. And you were talking about the humane AI pin, how that made you. could have been successful at Apple. Even the R1, I think, like. Well, my main point was that if that was an internal project at a bigger company, just showing like a potential future state for consumer hardware,

it would have been an amazing demo and probably been able to receive more funding at, let's say, a hyperscaler. Yeah. But as a standalone company, sales come in, people don't like the product. And then nobody's willing to give them more money. Yeah. I mean, you look at how many shows. shots on goal Mark Zuckerberg has taken with the meta rayband displays and the meta raybans.

Like that was something that I would be surprised if you look back at the R&D cost, the manufacturing costs, the early sales figures of the version one of the meta raybans. And it's off to the races. Like he clearly said, you know what? I'm going to double down on this for years. We're going to continue to invest in this. Get this to a place where it can actually become known, become a product that people consider. when I show them another ad, they'll consider it because they've seen it.

Maybe they've tried it. Maybe I went skiing with someone who had a pair and they were talking, they're sending text messages. And so it's just familiarity with the product takes time. And Google's had some fun swings at these like preview emerging hardware platforms. Google Glass, I mean, way ahead of its time. We're now there with the meta rayband displays. But even those are not selling by the millions and millions. They're very early stage.

Google Cardboard, I don't know if you remember that one. You put your phone in a cardboard box that they send you, and then you can put it on your face and use it as a VR headset. Whoa. Yeah, it was a tiny little, I think it was open source, just like a fun preview of like, how do we get more people to be able to watch 3D stereoscopic, you know, VR-type content?

Well, a lot of them have. How can we strap someone's phones to their face? Basically. And then they also did the Samsung Galaxy at point blank range Which was yeah, you'd slot it into like a piece of hardware But much cheaper than buying an Oculus at the time Fitbit also sort of fits in there

There were previews of the new Google book And the Fitbit from last week And I'm excited about the possibility of a new swing From Google like being like the wild card headline That makes it out of I.O. this year. So anyway, are there any other Google I.O. posts. I mean, like the actual conference is going on as we're doing the stream. So I wouldn't be surprised if there are announcements hitting the timeline right now. Yeah, there's, people are pulling

some of the benchmarks, comparing it on the AI artificial analysis coding index. Lisan Al-Gaib says 3-5 flash scores kind of low on coding index due to rough terminal bench hard scores. So I think the big question coming out of IO today is how do developers respond to the updates to anti-gravity to 35 flash. The speed is amazing. We know how much people care about that in just like day-to-day coding, but the model has to be able to perform. So we'll see what people's reactions are. And we'll see if we'll see if Google can really start to ramp revenue on the cojun side or still get exposure to that through Anthropic. It did come out yesterday that Demas is an angel in Anthropic himself. And I don't, not super surprising, although less pushback.

When did they, yeah, when did they meet? I wonder what the story is there. How, how early he got in. He might be sitting on a bag. Well, who else is going to Anthropic? Andre Carpathie has gone from Open AI to Tesla to Anthropic. I think he went back to Open AI at one point in there. And Andre, a different account, is pointing out this KMT general who defected and subsequently betrayed five different countries in Asia, ending in Japan, jumping around. He's seen it all. Certainly the world tour of AI labs.

I guess Andre Carpathie was never inside of XAI. because he was sort of the precursor at Tesla. But he was poached by Elon in the early days. I feel like he might have been in Google before Open AI. I don't know. I know that there were some people that got, maybe it was illy. So he interned there. He interned there.

So he's been everywhere. He's got the, he's got the Thanos rings. Huge pickup and excited to see what they do together. He's apparently according to Alex Heath going to be working on basically RSI. RSI. Yeah, yeah.

Yeah, I think he's continuing on his like auto research project. Oh, yeah. He's been doing RSI basically in the open source world. Auto research is open source, right? Yes. Okay. Yeah, it's, uh, I think you can read into this that it was effectively an aquire of the company he was working on. Oh, interesting.

I don't, yeah, I'm assuming. You said he was going to get back to the education project that he was working on at some point? I thought he had, I thought he had raised for it. I don't think he did. Maybe not. I don't know. It's always helpful. But that was a cool idea.

I wonder how that fits in. It was always interesting to think about, like, you know, LLMs are really good at education. I mean, we're seeing that today with Gemini Omni. Like, it can generate a video for you. Now, we haven't really pushed it to the limit. Like, I wonder, is it, like, if you give it a PhD-level problem, is it going to teach you as well as, you know,

a great professor who has thought about all the different responses, like maybe it's not fully there, but it's, like, education certainly seems on, like, the core path, of the models, whereas there are plenty of things that sit outside the core path in things with network effects and things that touch the real world and physical world and all these different things. But just going to a computer and asking, teach me something, felt something, felt like something most of the AI models would get very, very good at because there's a lot of training data,

there's a lot of open source educational materials. All the textbooks have been scanned. Wikipedia is in the models. There's so much information that's readily available. It isn't tightly held secrets that are hard to bring to bear in the pre-training data. But we'll be... One more thing out of IO that we forgot to cover Google's new synth ID framework that 11 labs, OpenAI, and Nvidia are joining forces.

This is to help identify AI generated content, basically creating a standard for across platforms. Yeah. So that, yeah, when you generate an asset, 11 labs, Open AI, it can be pha. Omni, it should be auto detected by the different platform. Yeah, I've seen that on X recently. There's been a little tag that says, like, made with AI. But I feel like you can get around that if you screenshot it.

Well, so I think the ones on X are just in the metadata. In the metadata. You can actually change it fairly easily. I don't think it's actually using, like, on nanobanana images, on GBT, which two that are like watermarks. You've seen these like weird patterns people posted. Yeah, I think on X so far. Subtle changes to the saturation or, it's been, it's just been metadata so far.

Yeah, the trick with all of those is that, like, it's in theory pretty easy to, like, rip that out. If you're running, like, an advanced AI, you know, slop avoidance detection system or something. But just to know, okay, you know, for the average poster, if this is an AI image, that's certainly helpful. But as you start bringing different assets and you bring in some stock footage, you bring in some AI footage, you blend them together, you're doing a lot of different things, you'll probably lose a little bit of that AI detection ability, but hopefully people aren't too annoyed by it. If it's used tastefully, I guess it shouldn't matter at the end of the day. Anyway, do you think Spotify used AI to create their new disco ball icon? This was burning up the timeline this weekend.

I was shocked at all the negative reactions to this icon. Me too. For a bunch of reasons. What's wrong with you? What's wrong with you? Seriously, if you don't like this, Touch Grats. Also, at first it threw me off.

I was like, where did my Spotify app go? Because it's too dark. Genius. I think it was genius. I opened up my phone and I was drawn to it immediately. My eyes jumped because I was like, something's wrong with my phone. Something's wrong with my home screen. Things don't look the way they normally look.

It drew my eye. I saw, oh, Spotify, okay, look a little bit deeper. The icon looks a little bit different. The color's a little bit deeper. Oh, there's something else going on there. Peel back the onion. You see that there's a disco ball. and then, of course, that there is a meaning behind it.

They didn't just, there's a whole, there's a whole reason why they did this. It's the 20th anniversary of the company. And so lots of people complained, but party, your party of the year. It's so funny because I don't, I don't know prior to this were people sitting around being like, wow, I really hope they never changed the Spotify logo even for a few weeks. I just love it so much. Yeah. Right. I think it's fun.

I think it's a nice change from, you know, this flat minimalist logos that we've all grown accustomed to. Keep it. And, yeah. So, yeah, let's go through some of the reactions. So Dylan said, I thought this was fun. I'm sure the complainers thought so too. But when tapping an icon is second nature after being used to it. Citizens said I told my wife to cancel our subscription.

Oh, no. For so long, even the slightest change in appearance can. make you double take when searching for it. And that's annoying when trying to open an app. Mass says that it's too, it's too dark. And so Mass turned up the brakes. You're at the disco, John. Oh, yeah.

A disco ball would never look that bright. Yeah. In a nightclub. Okay. Yeah, I mean, the black lines. It is real disco ball knowers. Yeah. That's way too light.

I like a notion played along. This is like really a testament to the, the power of gen AI imagery these days, every brand could like jump on this meme very quickly. And it's hard to create these. It's so funny that, yeah, that I guess,

you know, this still went super viral. Yeah. But even five years ago, if you could create an asset that was a 3D render, you almost automatically got attention. Yeah. Because anybody could make them,

but you needed to work with like a 3D artist, yeah. Artist to do it. And it's not something you can do instantly. They have to figure, you know, actually render it. I mean, yeah, this is probably like a couple hours of work in Cinema 4D. I mean, getting the lighting right too and making sure that you're not have the wrong reflections on there. There's a bunch of nuance to actually getting this to look good. I think it's fun when, I don't know, the other brands like joining in on like a meme can be like done really poorly.

This one seemed like it was fine. Yeah, Andy Masley had the best take. He said everyone complains about minimalistic. design until the company tries something fun and everyone reveals why all the companies have been forced into minimum list. Oh, 66,000 likes on this. People really, really agreed. This is how I feel when people complain about cyber trucks being ugly.

Like, yes, but it's different. Of course, not everyone is going to like it. Trying to get everyone to like things is how we wound up with all cars converging on the same colors and designs. Interesting. Yeah, that's a good point. I like the disco ball. someone Nathan Halberstrad said had a very nice comment he said he said this is this is

TBPN inspired which I don't I don't think it is but the arc may be long but tech companies now appear to be universally bend to universally bend towards apic I mean look at our look at our so we do have the globe and it was funny because so you can you can go a little bit further and I did this with our logo I was like turn our logo into a disco ball and it looked kind of the same like because we sort of have the globe and I'm in there already. And so for all of like like this meme like sort of didn't work with us because I guess we have been taking that like 3D render aesthetic with the globe. Although ours is pixelated, not not squares like on the disco ball, but there is a little bit of TBPN in the in the disco ball.

What do you think of the TBPN disco ball logo? Should we run this for a while or has the trend already moved on? I like the globe. You like the globe. I like being global. Yeah, I think keep the globe with the pixelation, the dots. I think it works. The arrow of disco-morphism has arrived, says Fichara, Fiatara. And this individual disco-ballified all of their apps, including X, Claude, Slack. What's that one? The App Store, I guess. Google Calendar.

I don't know. If you ran this, if you ran this full, do people know why Spotify was a disco ball? This kind of loud, Maca-R-Sachers. Maximilist design is coming back whether you like it or not. You think so? These things go in waves. Yeah. They go in waves.

They're coming back. Well, one story that we didn't get to yesterday that I want to discuss is the root cause of the fertility crisis. The Financial Times has a deep dive, why birth rates are falling everywhere all at once. And I was going back and forth to Tyler on this, trying to understand. And we'll see where you stand on this, Geordie. So the demographic landslide defining our era is gaining speed and terrain. In more than two-thirds of the world's 195 countries, the average number of children born to each woman has fallen below the replacement rate of 2.1

that keeps population stable without immigration. In 66 countries, the average is closer to one than two. In some the most common number of children born to each woman is zero. Both the pace and the breadth of the decline or defying expectations, just five years ago, the UN predicted that there would be 350,000 births in South Korea in 2023. That was a 50% overestimate. The real figure was 230,000. Sorry, not 2300. While high and middle-income countries have been wrestling with demographic decline for more than half a century, the phenomenon has markedly accelerated in the past 10 years. Analysts of data ranging from

population records to Google searches indicate that although many factors contribute to falling birth rates, the most recent plunge appears connected with our use of technology. And so this is the question that the Financial Times is trying to answer, should you put the blame on the recent decline in fertility on smartphones in particular? And so, yeah, you can go through a whole bunch of the charts. It's a great article. But the final image is this image where they took a whole bunch of different countries and they adjusted the charts to show when did smartphones, actually take off in that particular country because America had the iPhone moment in 2007, but different countries got wide smartphone adoption or 4G or actual rollout of cell phones or

smartphones at different times. And so they adjusted all the figures. And when you look at this chart that Lewis Giancarlo is sharing the screenshot from the Financial Times, you'll see all of the charts seem to be very, very closely aligned at the exact same time. And so Louis Giancarlo pushes back, though. He says, no smoking gun, but the preponderance of evidence points to smartphones, not economics as the culprit. Yeah, there's the chart. It looks like a smoking gun. He says it's not, though. He says, in the U.S. and UK births fell first and fastest in areas that got 4G earliest. birth rates were stable in the United States, UK, Australia until 2007, in France and Poland until 2009, Mexico and Indonesia until 2011, and Ghana, Nigeria, and Senegal until 2013, 2015. Each of these inflection points matches local smartphone adoption.

The younger, the age group, the sharper the drop, in-person socializing among young adults is dropping in South Korea by 50% in 20 years. affect is largest in culturally traditional societies, Middle East, Latin America, sub-Saharan Africa. Declined holds across countries hit hard by GFC and those who were not hit by the global financial crisis. And so it teases out a bunch of the other possible explanations and puts the blame firmly on smartphones. But people have been pushing back. So Ross Douthit says, on the latest round of fertility discourse, friends don't let friends. share chart one without the important context of chart two, which is the child survival adjustment.

And so if you look at the total fertility rate, if you click on that left graph, you will see that the baby boom is remarkably pronounced there, but in fact, birth rates had been declining since the 1800s and had been falling steadily throughout the 19th, is it the 19th century? Yes. And then in the 20th century, there was a brief baby boom in the 40s, 50s, 60s. and then the rate starts declining. I asked 5.5 pro a bunch of questions about this, trying to dig in further.

And it had a bunch of funny answers about how children used to be economically valuable. And so people would have a lot of them to, like, work the farm for them. And the economics of having a child flipped at a certain point where it became expensive and a net, sort of a net burden on the parent, as opposed to before it would be, you had a kid, you didn't have to pay for college, you didn't have to pay for education or really anything and they would work the fields for you. And so it was advantageous to have as many children as possible. Ross Douthit also chimed in saying, by the way, another way to look at the second chart is that the baby boom was even more unexpected than generally understood. And also,

if any major population repeated that kind of unexpectedness, now they would dominate the human future. Interesting opportunity for different societies out there. Do you think children yearning for the minds is sort of like a survival mechanism, right? They want to be economically valuable. They want to be productive, right? Yeah. They're saying we can carry our own weight. Yeah.

Yeah, I mean, it would be, I look at all these charts and I just think it's over. It's over. but then I remind myself to never black pill Yes Never black pill Even if it's down Never black pill Never black pill

Never black pill Even if it's down only Yeah It's crazy It's really crazy to look at these charts Looking at Looks I mean

this were, you know, any animal in the wild, there would be huge amounts of fundraising happening to try to save the species. But when it's us, we just sort of like, you know, see the chart and just keep scrolling. Yeah. I think it demands investigation to go a level deeper to understand, okay, so diffusion of smartphones appears correlated with declines in fertility. But they're within populations, there are groups that have higher than average fertility and lower than average fertility, of course, as any distribution suggests. And the question is, like, what are the high fertility members of the population doing on their phones differently? Like, are they using social media less? Are they using dating apps less? Are they texting their friends to come and hang out?

are they organized? Because the smartphones have diffused so widely that you need to cut in and understand for the groups that are above fertility rate. What are they doing differently? Obviously, the Amish are an interesting case study because they do have a higher than replacement rate fertility. And they're not. And they have technology. They actually have adopted some cell phones, but not smartphones. So they will use the, you know, like a dumb phone, a flip phone to make phone calls occasionally. And I'm sure that, you know, these are all gradations. There's not, uh, no smartphones whatsoever, but, uh, certainly the Amish have steered away from technology and the fertility rate has, has stayed high. But, uh, even within the, you know, more, you know,

modern enclaves or smart, high, high smartphone adopters, I, I do wonder, uh, what else is going on. Because there's a bunch of other interesting factors going on with, uh, child care and the relation with how people spend their time. Yeah, specifically with the, also what else happened in, around the, the launch of the iPhone? What? Like massive economic disruption, right? They controlled for that, though. That's the point of the Financial Times article, is to control for the economic gyrations of different

countries. So there were some countries that were unaffected by the financial crisis. There were some countries that went through boom periods. There were some countries that went through economic contractions. And they were all sort of affected. equally. Like, uh, even China, China has the lowest replacement rate, one per, uh, per family or something like that. Whereas we, America's at like 1.8, many societies, many modern societies at 1.6, all below replacement rate, but China's the lowest, but China's going through like an economic boom

the entire time. Like GDP's up at six, seven, eight, sometimes 10% a year. Like, they're not going through an economic contraction, certainly not from 2007 to today. And yet, although that is a little bit different because it's confounded by the one child policy, which obviously resulted in exactly one child. So they set their policy, then they got their result, and now they have to sort of contend with that, the aging population. There's an article that Derek Thompson shared, Dad Books, which this article and some publishing insiders used to describe serious nonfiction books across biography, current affairs and business and economics, reportedly are reportedly in free fall with sales declining every year for the last years.

The trend couldn't be clear, I said Jonathan Karp, former chief executive at Simon & Schuster and publisher of the new Simon 6 imprint. When we have internal meetings to talk about this problem, it always comes around to podcasts.

Interesting. Saying podcasts are eating the dad book, serious nonfiction genre. We've got to figure out who's doing this. We're all looking for the guy who did this. I do listen to a lot of podcasts. I still listen to audio books.

of serious nonfiction. But it is, it is increasingly hard to find the time. FedSpeak says it's not podcast, it's kids because the millennial generation, the Gen X generation is spending basically twice as much time with kids based on their age. When you adjust for age, so this is a curve of time spent with children by age.

Honestly, every time on the weekend, you know, when I'm holding one or two of my children and I just stare at, you know, the stack of books from Amazon that just pile up and I just look at them and think, okay, if I open one of those, I will get exactly three pages before I'm disrupted. Yeah. And so what was the silent generation doing? What was the, what were the baby boomers doing? Were they just like, kid hit the minds, buddy? I got to read. I got to read some nonfiction. I don't know. I mean, the podcast creep in, but it's, it's hot. I listen to podcasts when I'm not at home. When I can't read. Yeah. Right. Maybe self-driving cars bullish for serious

nonfiction because, oh, maybe people will get sick. Self-driving cars are bullish for the Infinite Scroll. Oh, yeah. They're bearish for the podcast and long form mediums broadly. And the book and the serious nonfiction, the dead book. Anyway. Nothing can compete with the feed. Yes. Sorry to blackbill, but it's over. Well, it's not over for our next guest because Jim Belosick from Senkut Send is with us. He's in the waiting room and he has some exciting news about Senketsen.

Welcome back to the show, Jim. How are you doing? Good, good. Thanks for having me. Great to see you. Short notice. Congratulations. Reintroduce the company and then I want to hear the news.

Yeah, SendCut Send is a on-demand manufacturer. elastic capacity is what I was told. So we make stuff. This guy has VCs now. Yeah, yeah, yeah. Buzzwords come. They're like, I can offer you capital and buzzwords. They're good at both, yes.

But I like it. I like it. Elastic capacity. Yeah, we do sheet metal and CNC and, you know, whatever. People need something made. We make it warm. Yeah. And the news today, what happened?

I want to hit the gun. I finally raised some money. How much you raise? 110 million. Massive. Let's go. Let's go. It's sort of bittersweet, bittersweet moment because send cut send is a company.

You know, we've interviewed thousands of founders now. And you have been, you know, out of all the conversations we've had at the top of our list in terms of like, you know, companies and cultures and teams that were bullish on. And we always appreciated that you were doing it independently. But I'm sure you've raised for very good reasons. and you have some excellent new partners, and we're very excited for you. Yeah, I want to talk about the use of funds, the reasoning,

but first, like, take me through the pitch that you received. Who did the round? How did you meet them? Take us through the kind of story of the deal. So I just through X, I got introduced to Patrick Ollison, which was awesome. And he's like, oh, yeah, I've heard about your company. You guys sound really awesome.

All invest. And I was like, well, shit, that's amazing. Thank you. I was like, how does this work? Like, I don't know how investment works. And he was like, oh, I'll just introduce you to a couple other people. So, introduce me to Andrew Reed from Sequoia. He's like, we can just use the standard YC terms.

No, I'm kidding. Yeah. No. Well, I was like, hey, you know, introduce me to someone who's super founder friendly. I'm a bootstrapper. I want to retain control of my company. But I do want to go faster. So I need a little bit more money than I got.

now. So introduce me to Sequoia. Andrew Reed over there is awesome. Sean McGuire. And then Matt Huang from Paradigm as well. And so it became this kind of dream team. And I was like, shit, if I don't do it now, I don't know if I'll ever be able to put this together again. So let's go for it. Let's see what happens. Yeah. And I also think you guys have such incredible, have had such incredible organic momentum and growth. And we need to make stuff in America. And it's somewhat your responsibility to go faster, like, as like, just for the country, basically. And so from that lens, too, I think it makes a ton of sense to bring in some more firepower. Yeah, we're always capacity constrained.

We have more work than we can produce. And even if we had the right amount of machines, it's not fast enough. I want to go faster. You know, people are spoiled on Amazon. I want to do Amazon of manufacturing. You know, if you order today, you should have it in your hands tomorrow. that you can go do your project. And now that's, that's on the horizon.

We're getting really close. Yeah, so what, uh, what does the money actually go towards? Is buying more machines, hiring more people, both? Like what, like, what, like, what are you pulling forward with this capital? Yeah. So I'm trying to just use the capital towards stuff that I can't finance. So right now, like we've been able to grow, like, you know, I can buy machines and get a loan on them from JPMorgan or whatever. So I'll keep doing that with machines.

but the capital is going to be used for stuff that I can't get a loan on. So, you know, tripling the size of my software team, computational geometry engineers, hiring two or three hundred people, just a down payment on a building. The first and last payment is like, I don't know, together it's like $600,000 on some of these big buildings. So that's where I'm going to light their money on fire in a good way, and we're going to grow, grow, grow. Yeah. Yeah. Where's the current facility?

where do you see yourself expanding to? I want to talk about the actual footprint because if you're building elastic capacity, that feels like that needs to be distributed all over the United States at some point. Yeah, a million percent. My goal is like, I love Home Depot. And without a Home Depot in your town,

you've got to go to a plumbing store, an electrical store, and a lumber yard, and whatever. So if we could have a send-cut-send in a bunch of different metros that you can just walk into and get something made, that's the dream. So right now we're in Reno, Nevada, Arlington, Texas, and Paris, Kentucky. The next one up, I'm hoping for a lease here, is going to be somewhere in Pennsylvania, potentially in Ohio, but we're trying to pit those two states against each other and negotiate some good

incentives. So I can't really say which way we're going. After that, probably Indiana, Las Vegas, and then Atlanta. Okay, I had sort of a hot take yesterday talking about the push back to building data centers. And my point was that obviously data centers are the least, they're less popular than nuclear reactors. Nuclear reactors at their worst, I think we're polling at like 63% disapproval for like let's not build those. And of course, we stopped building them. Data centers are like 73%. So people really don't like them. But my point was that there's a lot of like there's a lot of pushback against building anything, even like housing, roads, trains.

Like people are just like, I like the idea of it somewhere else, but I don't want it in my backyard. I don't want it over here, like if it actually interfaces me. And I'm wondering if how local communities are actually receptive or skeptical about having what is essentially a factory and could be noisy or could have traffic or could have a bunch of different things. And I imagine that you've had like one, one millionth of the pushback, but you've still had to consider all these things. So how have you communicated to the local communities that you build in and you're planning to build in?

Yeah, I think some of the loudest pushback is from, you know, people in these big coastal cities and, you know, they're like, I don't want that in my backyard. Yeah. What we find is, you know, we're in a smaller city or a rural area, people love the jobs. Yeah. They love the development. They love the taxable revenue that comes with us. We're also, we're pretty damn quiet. We don't exhaust to sewer or air or anything.

We're 50 state compliant. That's our goal. But what's really cool is we can come into a community and provide a lot of good high-paying jobs. You know, it's a career path that they can grow into. There's more opportunities. As we build more buildings, they can move out of their little town and go to a different metro or whatever. So we don't have any pushback. Also, we move so damn fast that we don't build our buildings.

We go find a building that's already stood up and we just move in. That's the only way for us to go fast. Yeah, yeah. And there's plenty of capacity there. As you look back on your career, how did you process the VC hype or just the memes around like the 3D printing revolution? And there was a moment where there was like, oh, like there won't be any more factories because everyone just 3D print everything at home. How do you process it at the time? And I guess like what like how do you see 3D printing fitting in if at all into like the future of reindustrialization?

Does that have a place whatsoever? It does. It does. In the world of metals, we're still far away from that. It's so much easier to get something cast or stamped or laser cut or whatever. I mean, when we've experimented with 3D additive in-house, there's laws against how much of that aluminum powder you can have because it's explosive. So there's massive hurdles to clear for that. However, 3D printing, it's actually really competitive with injection molding. And that's something that we're looking at. Injection molding is incredibly expensive. It's get the molds made. Almost all the molds are made offshore. But if you can 3D prints really, really rapidly, then it is competitive, especially for small runs or startups or prototypes or whatever. So that's an area that we're experimenting again. What are some recent customers that you started working with that you're particularly

excited about? They can be mom and pop, hackers, or big companies, but I wanted to give you a chance. Yeah, we actually, my comms team that I have now just told me, have to be careful about who I name. We were pretty proud, though, like, it is mom and pops, but then it's also, what, 85% of the top five primes and the tier one defense people use us. Near us is a huge customer. Zipline is a huge customer. And then just guys in their garage making cool stuff. And, like, kids doing first robotics or whatever, they all use us. So, very, very wide spectrum of customers. Amazing. What, what does the entry,

level job at Sen Katsun look like these days? Anything, you're a generalist. We are moving so fast and doing so many different things. We don't have a designated floor sweeper, but you might be sweeping floors. We start somewhere between like 26 and 30 bucks an hour, and then it goes up from there. But yeah, you're going to be maybe a laser operator one day. You're going to be driving a forklift. You're going to be cleaning out a dust collector, or you're going to be doing some intense.

since CAD programming, like, who knows? We don't know what we're going to make that day. Things just come in and we have to do it. So everyone here is very, very flexible. Yeah, with the crazy, like, AI buildout and data center build out going on, we've heard and seen, like, you know, prices of copper spiking.

Like, there's all these weird knock-on effects from data center construction. Are you feeling squeezes anywhere in your supply chain? Do you feel like America is industrialized enough in the rest of your supply chain, or is there like a wish list of, oh, we got to reshor that? We need as many, like, aluminum boundaries

and smelters as we can possibly get. I mean, those are way more electricity-intensive than data centers. Actually, if you tried to spin up a bunch of those, it would make a data center look really good in comparison. So that's interesting. If you want to build a data center, go pitch an aluminum foundry first.

Wow. And then they'll want you to do, like, 10 data centers. So we need more of those. But we need nuclear. I saw that with the Strait of Hermuz closing that Diet Coke was at risk of going out of stock. Very harmful to my production function. But because there's some amount of aluminum smelting that happens in the Middle East and passes through the Strait of Hermuz.

And so delays happen. And I think a lot of people are, they think it's either we have the capacity in the U.S. Or maybe I went to China, but there's really nothing else. But we're in such a global economy that there's so much more going on. Yeah. It affected us a little bit. You know, about 15% of aluminum comes from offshore. We actually source a lot of domestic aluminum, or at least it comes from North America.

But, you know, even if prices go up 15, 20%, raw materials are a small fraction of the overall end price. So 15 or 20% increase in raw materials is probably 3 or 4% to the customer. So our customers have been pretty cool about it. Yeah, I mean, Jordy asked about the customers, like, specific. examples, but I'm interested in like the broader funnel. Like how much is, do you have an outbound Salesforce at this point? Are you going to conferences? I imagine that you show up on like Google results oftentimes. But what like is it is the customer funnel like heavily diversified or is there a sweet spot that you're really doubling down on right now? What does acquisition look like these

days? We've always been inbound. We have two or three sales guys right now, but they just, you know, answer the call and, you know, do special special special. projects or whatever. We have no outbound sales guys. At one point, early on, we were spending about 100 grand a month on Google ads. And I think right now we're spending about 1,500 bucks. So my message to anyone who wants to do this. Is that because if you were, if you were spending more, you hired more salespeople, you just wouldn't be able to fulfill the demands. You need to scale capacity first. Yeah. Yeah. We, my marketing team, usually I'm like, say nothing. Don't say anything this week because we had a machine go down or whatever. So I'm like, stop. Everyone go

quiet. So yeah, it's always chasing capacity. But my message to anyone who wants to do something like this, just have a kick-ass product. Just make it good and fast and, you know, get it in their hands within, you know, a couple days or whatever, and people will come back and they'll tell their friends. So, but it's an overnight success takes 10 years. So we're in. And when you guys are fast, when you guys are fast, when you guys are fast, your customers can build their products faster and have higher sales velocity themselves and generate more revenue and they end up spending more. And it's like this very, very virtuous flywheel. And I'm so glad you're well capitalized. Yeah. I, yeah, this is a major white pill. Yeah. I hope I don't have to do it again because

fundraising is not fun. I hate finance. Get ready. Get ready for for nicey, buddy. Yeah, there's going to be many more, many more in the future. It's your duty. Yeah. If you want to go fast and far, it makes sense. Last question. We were talking about the fall off of dad books because of podcasts and fertility and all this different stuff.

And I'm interested if you have any examples or recommendations for father, son building activities that you've seen from the community or maybe you've done yourself even or employees have of a good first build for a, for a, for a, uh, for a parent and child to do, that might use send cut, send parts. Yeah, there's a ton of little like push go-kart plans available. We may even have a couple on Marketplace, I'll have to check. Cool.

But you have to do something that the kid can enjoy, and there's nothing better than getting pushed down a hill and scraping your knees or whatever. So have those experiences, something that's usable. Like a birdhouse or whatever, that's fine. A go-kart or a scooter or something like, that is pretty cool for the kids. So if I make a go-kart using send-cut-send parts, and I want to throw a V-12 in there, can you fabricate that for me, too? Not yet. Not yet. Okay. That's what the money's

for. And we're going to spend on. Go-Card is such a smart recommendation too for you, you know, running a business because of bird feeder, you know, you make it once you put it up, it's good. Yeah. My dad built me a go-cart growing up, and he would, he would, you know, he made it, I would drive the heck out of it. It would break. Then he'd be fixing it. And, So you're going to, it's a recurring revenue stream for you guys to get a father, son, duo into go cards. That's smart. 100% yeah.

Never ending. Playing the long game. Well, congratulations and thank you so much for coming on the show. Yeah, great to see you, Jim. Congrats to the whole team. Great to see you. Excited to see you back on here soon. Have a good one.

Cool. Thanks, guys. Goodbye. Cheers. Legend. Fantastic. White pill. White pill of the show.

It's your white pill. We were blackfilling. Now we're white pilling. Never black pill. Never black bill. Well, up next, we have Aiden Dewer from Nour from Nourish. He's the co-founder and CEO's been on the show before, but we're welcoming him back with some huge news about the company that's growing faster than ever for the massive series C to announce. Aidan, how are you doing?

I think we might have some technical problems. Can you give us a hello? Can you say hello? We might need to come back to you. How are we doing? Are you using a potato as a webcam? It's not the potato. It's the Wi-Fi.

It's for sure the Wi-Fi. Do a check one, too. Yeah, do a check one, too. We'll kill some time. We'll kill some time because Dan Sunheim's killing time with Dan Sunheim. So, wait, okay, so this is actually funny because I opened up the Wall Street Journal the day. And I had seen the news from Tay Kim, who's coming on the show this week, that in the financial times, they had a report that Daniel Sunheim's D1 Capital Partners is another hedge fund that stands to

make a killing when SpaceX goes public. D1 is sitting on paper gains of about $9 billion on SpaceX stock that had acquired over several years for about $600 million. What a run of 15x, not bad. And so now the stake might be worth $20 billion if the rocket maker is valued at the expected $1.75 trillion, a figure that could still change according to people familiar with the matter. But I open up the Wall Street Journal. And I'm, and I, everyone's familiar with Dan Sondheim and D1. He's, Dan Sondheim, is not like someone who's obscure behind the scenes he's done invest like the best. People know D1. They invest in a lot of companies that we know. But I thought this Wall Street Journal article was also about D1. And the title is, obscure fund has a lot riding on

SpaceX. And I was like, are they really painting D1 as an obscure fund? They weren't. They're talking about a different, yes, yes. They're talking about a different investment firm that's about to make a lot of money on the SpaceX investment. So SpaceX is planned initial public offerings expected to be a windfall for futurist investors and venture capitalists. If you got SpaceX shares in your, you don't want to say, I'm not a VC. Say you're a futurist investor. A publicity shy hedge fund manager,

who's other investments. So you're a hedge fund, your long SpaceX. What else are you buying to diversify your portfolio as a futurist investor? Dix Sporting Goods and Wingstop are among the big positions

at Darsana Capital Partners, which, First invested in SpaceX in 2019 when Elon Musk's rocket maker was valued at around $30 billion and made several subsequent investments since then. Should SpaceX go public at a valuation around $1.5 trillion, Darsana paper gains on the investment could top $10 billion. So had you ever heard of Darsana before? No.

I actually had not. But I have heard of Wingstop. It's a good stock. several billion of that would be gains since stock is down 50% year to date rough the sort of valuation Anandeside launched New York based

Arsana which comes from a Sanskrit word that means seeing the true nature of reality chicken wings and Dick's sporting goods in 2014 1.4 billion under cap under management let's bring in our guest back on a new device

Hey, crystal clear. Thanks so much. We're on mobile now, guys. We're on mobile now, guys. We're at our company off-site, so we got weak Wi-Fi. Makes sense. Well, you sound crystal clear now. Why don't you reintroduce the company?

Tell us the news. Yeah, thanks for having me on, guys. So I'm Aiden. I'm the co-founder and CEO of Nourish. Nourish is a dietitian-led metabolic clinic, So we pair the largest network of registered dietitians in the country, over 10,000 dietitians with virtual medical care, so the ability for physicians to order and interpret labs, to prescribe it managed medications. And we've delivered some really amazing results for patients that we're excited to talk about today.

Walk me through dietitian, the different degrees that might be involved, the certifications. I know with a lot of telehealth, there's state-by-state regulations, like, What was the process of building out that network of 10,000 dietitians? Yeah, good question. So dietitian is a protected term. So you might hear some people use nutritionists or dietitian interchangeably, but nutritionist is actually not protected. So, you or I could get on Instagram and call ourselves a nutritionist,

but a dietitian requires a master's degree, a certain number of hours and so on. And so we only apply employed dietitians. Those are the providers that are able to work with health insurance. and get it covered, which is a big part of our model is expanding access to this type of care. And of course, working with health plans, get it covered by insurance is a big part of that. Okay. What is the value at? I mean, there's so much, there's so much of a boom in peptides, GOP-1s, metabolic health.

It feels like there's a lot of these companies where the demand is already there. You're just the landing page that gives the customer what they already want. But I imagine that there's a lot more. I'll pitch it. Okay, pitch it, Jordan. It seems super important to combine. diet with gLP ones doing just just saying like hey we created this magical drug for weight loss yeah and then just doing the drug versus like actually fixing fixing like the underlying

uh sort of cause or maybe the original issue you know is sort of a temporary solution and if you want like lasting yeah positive change with your health you you're going to have to factor so if i go to a dietation and say i've been blasting right of botch it is that roughly correct no no you said it well I mean, I think the way we think about the root cause of kind of the problem of explosion and chronic conditions and cost is that people are living unhealthy lifestyles in the modern world. It's very hard in the modern world to eat well, to sleep well, to move your body, to manage your stress. And maybe 75 years ago when these conditions were much rarer and costs were much lower, just kind of living your life in the day to day, it was much easier to be healthy.

And so while these medications are a very useful tool in the toolkit, and, you know, with our network now, we're able to prescribe, manage those medications. To your point, you know, if you don't pair that with behavior change, you don't get kind of sustainable results, which, of course, is worse for the patient, but it's also worse for the system because now we've spent all this money for medications and then had rebound and weight gain or falling off medication or so on. What's happening on the supply side of the market with GLP-1s and how is that impacting pricing?

We know there's an incredible amount of demand, overwhelming demand. but what's happening on the other side. Yeah, so it's nice to see, I mean, I think solely but surely will see access increase, costs come down. I think over time as these drugs become generic, expect them to get much cheaper. You know, you mentioned RETA, you know, I think that'll get approved in the coming years and that'll maybe start higher price and then these kind of, you know, first gen, second gen meds will come down in price and eventually go generic, which I think is really exciting

because ultimately, like I said, they are a valuable tool in the toolkit, but cost is prohibitive in many cases today. And so where I think, you know, we play and where I think the value will ultimately be created as the price of these medications comes down is exactly in that behavior and lifestyle change that we talked about. It's kind of that wrap around care of how do you have, you know, not just medication, but integrated care team virtually covered by insurance, as well as, of course, you know, technology, especially AI, which can be kind of that 24-7 behavior change agent as part of the

equation. And that's, you know, a big part of the round we just raised was to invest. and all of that and accelerate that. How much does you raise? Raise 100 million Series C. Yes. Congratulations. I love the gong.

I love the gong. That's why I came on. We need a gong for our office. You do. You do. Yeah, we should make TBPN branded gong, something. It's time. Rapparound care.

Does that also mean meal delivery at some point? I feel like there's a number of companies throughout history that have sort of vertically integrated to that degree. credibly, compet, uh, operationally complex. Is it on the roadmap?

Is it something you're interested in? Yeah, great question. We, we reached out, uh, by a number of, of kind of meal delivery companies,

as you expect about, about partnering. We, we haven't prioritized it yet, but I, I do think ultimately, you know, we'll do something there at,

at some point. I mean, the way I think about kind of more broadly, the problem of lifestyle being, lifestyle change being difficult and therefore, the mission of being, how do you make lifestyle change easy is you're trying to remove as many barriers.

of course, the food being kind of one of those. And so how do you, when you make a recommendation, make it very easy to act and fulfill that recommendation, I think being able to prescribe and fulfill prescriptions of food in the same way you can of medication, I think will be something we do eventually. And I think there's a lot of movement among health plans to potentially even reimburse for that in some cases eventually. But I haven't prioritized that yet, but I think at some point we will. And then on the, on the GLP one side, is there still an opportunity in compounding?

I know some telehealth providers like went down that path, others partnered. Like do you have a firm view? Are you flexible here? How have you been interpreting the different ways to vertically integrate on that side of the business? Yeah, so we do not compound. We work with the name brand medications and have partnered trips with the big players that you all know. And work to get those covered by insurance. You know, I think if you've probably seen, you know, in the last few years, there's been kind of this cash pay and compounding market.

We think that was a bit of kind of just a short term. solution for when there were access constraints and cost constraints that you were speaking about earlier. And where kind of the market heads is, you know, the inverse of cashpaying compounding, which is insurance covered and name brand. And that's kind of, you know, bread and butter the company, pun intended, is working with kind of those health plans to get things like that covered. And then again, because the drug, as cost comes down, especially, it becomes a commodity. I think where the value is created is in that wrap around care we talked about. And that's kind of the hard work. But I think the important work that ultimately

delivers, you know, lasting outcomes. Okay, last question from the chat. Are you on a boat? No, I'm in this random conference room in our company offsite. I think it's the phone. I think the phone is like rocking at just the right oscillations. Yeah, I'm pretty convinced it to vote. It might be.

You're not beating the boat allegations. He denies, he denies the boat. It does have kind of boat blocks on the house. It does have wood paneling. It looks nice. It's that texture of wood. Oh, we got a boring, boring conference room. Okay.

Wow. It's a huge boat. It's a massive boat. But I don't know a problem with a company offside of a boat. That seems like a great strategy. If that's what you did, I'm not going to critique it. Enjoy the bone. Great to see, Aiden.

Congrats to the whole team on the milestone and keep up the great work. We'll talk to you. Thanks. I got to go talk to the captain to stay. Oh, yeah. Gotcha. Have him reset the Starlink, too, for your. your computer.

Sorry about that guy. Thanks for having me on. Great to see you. See you. Goodbye. Take it. I'm glad we got to the boat question. The important question.

I don't think it was a boat. It looked a little bit too big. And things weren't like buckled down. You know, usually on a boat, even if you're in a palatial conference room, there's ways to, you know, bolt down certain items. Anyway, our next guest is from status here raising a series. What's going on?

Welcome to the show. Hey guys. Nice to finally be on the show. We got to kick it off with the first question. Are you on a boat? No, unfortunately, I'm in a regular. Okay. Our last guest, a very nice coffee room. Fantastic. Our last guest

denied the allegations of being a boat. He looked like he was on a boat. It's hard to believe. We have to ask everyone now. But that's not what we're here to talk about. We're here to talk about you and your company. Please introduce yourself and the company. Yeah. So I'm fine. I'm the CEO and co-founder of Status. Status is essentially a social entertainment app where users can live out their dream lives and play as anyone through the lens of a social network.

So, for example, I could be a famous singer. I could be an actor. I could live inside the world of like my favorite book, something like Harry Potter. I could be, you know, the host of one of the most famous, you know, technology news shows on X. Simulators. This is the thing. You can do anything. Yeah.

Everything is simulation. Yeah. So walk us through the actual customer experience. It feels like there's an element of social media here. There's also an element of like a massively multiplayer online RPG. Are you pulling ideas from both places? What are the big inspiration points? Yeah.

So essentially, when you go on status, the first thing that you do is you craft your persona, like who you're going to be. So I want to be a famous singer. I want to be a live streamer. I can choose who my first follower is going to be. I could choose someone from real life. All of our characters on the app, all of the worlds on the app are created by users. We have over 5 million characters on the app, over 10 million worlds.

And it looks like social media. It looks like X. And I think this is why it's really struck a chord with people and why we've grown so fast. Since we launched last year, when we launched last year, we went from zero to a million users in 19 days. And it kind of just shows like the virality of what we're doing. I think this product really, it resonates with our user base, which is pretty young, predominantly young women in the U.S. and all across the world. How gamified is it?

What is the goal of the players? Is there a currency or something that they win? Oh, yeah, yeah. How does that work? We basically made social media into a game, right? So, you know, when you post on social media, now you get, like, obviously you get followers, you get likes. The same thing happens on status. You gain followers, you gain likes, but you also, you know, everything you do has an outcome that will help you gain skill points, which helps you level up.

We took a lot of inspiration from, like, life simulator games like the Sims. And also, you know, our own background. And my co-founder built, you know, games on Roblox and Minecraft. And so we, it's really a mix of, like, life simulator and role play and, like, fandom-related. and stuff and really that like game of fight world. How are you thinking about monetization long term? I'm sure it's early. Your venture capital backed.

You don't need to charge an arm and a leg for this. But is subscriptions more aligned with the current customer experience or is like social media, I think, advertising? Yeah. So we actually have already started monetizing the products when we basically, oh, hell yeah. I was not expecting that. Yeah, we already started monetizing. We operate similarly to a game, right?

We have a, in-app purchases where you can buy power-ups, things like that. We also have subscriptions with, like, you know, weekly, weekly subscriptions and annual subscriptions. And we have millions in ARR. We 10x revenue this first quarter of 2026. So we're ripping right now. Ripping. Ripping.

What? What is it like what do you want people to what is what is the the business is ripping you have a ton of users? What what are you hoping that users get out of it? Is it is it like what is the sort of like our overarching vision of outside of just fun and playing a game? What you want users to get out of this? Yeah, I think that what status really represents. is this, we're moving into like a new, I think, phase of entertainment. So, you know, since like the beginning of time, you've always had to just, you know,

sit and, like, read a story or watch a story. I think what we can do now with LMs and AI is that now you can really immerse yourselves into these, like, incredible, like, role-playing, engagement, engaging experiences. I think that's what our users are doing. You know, when you watch a TV show and you get, like, really obsessed with it, Maybe you go to Reddit and read theories about what people are saying about it, you know, connect with fans and talk about the show with them. You might go to TikTok and watch edits of that show. Then you also, and I think this is that what the next phase of what we're seeing people do is that they're going on status and they're honestly like immersing themselves into and thinking like, well, what if I was a character in that show?

Who would I interact with? You know, what would that look like? And we're doing it through, you know, this lens of social media, which is so familiar. to people because, you know, everyone is on the same, the same types of social media platform. How does intellectual property work in this world? I mean, anyone can go draw a picture of Harry Potter and post it on their Instagram, but if you're intermediating this and you're the one generating, a lot of the models will refuse some of the partnerships and there's a whole bunch of different solutions there. But what does that look like? Yeah. So everything on the platform, all the characters,

all of the worlds are user generated. So similar, so we like to think of it as like, you know, similar to how someone would, you know, can upload like a YouTube video talking about a TV show or an artist. Yeah, it's the same thing. Except now with, you know, LMs and with AI, you can create these AI generated worlds based off of that, based off of that show or book or whatever it is. Has there been pushback to this? I mean, obviously your core fan base loves it. They're paying for it. They're using the product.

But AI is getting booed on stage. people are worried about brain rot and the infinite jest. Like, what has the pushback been like? Is it just you're off in your own little world and it's not actually confronting? Or have you had to grapple with any of the big questions about AI, social media, brain rot, etc.? Yeah, so I think with our user base especially and what we've kind of seen with AI is that the pushback that you see with younger people who don't like AI, it's because they feel like AI is replacing experiences that, you know, things like art, things like, you know, music, things like that.

Status isn't really replacing anything. We, you know, are a completely new experience that can really only exist with AI. And I think that's why, you know, our users are young, but they love status and they're really excited, you know, about the product. And in terms of, like, working with, you know, these, like entertainment companies and streamers, We've already started having conversations with some of them, and there is a real appetite of, you know, I'm sure you've seen this like now with Netflix shows or Amazon shows like HBO, whatever it is.

There's a long wait between seasons, right? Like you watch a show and then you wait like two years for the next season to come out. A lot of these streamers are thinking about, okay, how do I keep my audience engaged while we produce and make the next, you know, the next season of that show. So I think things like that is. million plot holes that they'll never resolve. What do you, what do you think meta's plans are around agents and bots and in this sort of, you know,

simulated social media. They acquired Maltbook. Yeah. They experimented with celebrity personas in the past. I feel like, you know, if you guys, if your metrics keep looking the way they're looking up into the right, stock will eventually come in. He will try to clone you. It'll be right of passage.

But, but generally, how are you thinking about, you know, these sort of scaled social platforms and how they're thinking about integrating experiences like this? Yeah, I think that a lot of, definitely I think there's a lot of interest from these big, big companies. And I think that what they're trying to do, and it is exciting with what they're doing with, you know, acquiring Motebook. They acquired Gizmo as well. Like, they're really interested in these. at first experiences. But of course, like, we kind of just focus on what we're doing and, you know, just, you know,

if they copy us, they can try, but like, I think with, like, status, exactly. Good luck. And I think that, you know, our users, and I think this is what makes us so sticky and why retention is so good, they've created these worlds and stuff that they are, they put a lot of work in. And I think that that really shows in our engagement and retention. Tell us about the fundraising to date. You've got some new capital.

Let's hear. What did you raise? Yeah. So we have raised $17 million in seats here today. Yeah, funding. Congratulations. Thank you guys. We're back by Abstract.

Let's go. General Catalyst, Union Square Ventures. Also, Lightshed Ventures, YC, a bunch of guys. So shout out for them. Great lineup. Great lineup. Where are you guys based? Oh, yeah.

We're based in New York. So consumer in New York guys. We have a team of nine in the city. I'm actually an SF right now, but don't tell anyone. We want. Well, great to meet you. I'm sure we'll have you back on soon. And yeah, congrats on all the progress.

Yeah, we'll talk you soon. Thank you guys so much for having me. Cheers. Have a good one. Goodbye. Up next, we have Tane Tandon from Camor. He's back. He's back.

Raising $7 billion at a... 700 billion dollar valuation. Not too far from it. I'm sure he'll be there soon. Welcome to the show. How are you doing? How are you guys? Thanks for having. Good, good entrance. Drinking casually thought you were distracted. Yeah, yeah. Oh, dial. Oh, hey guys. Didn't see you there. Didn't see you there. I'm just live. Anyway, welcome back to the show. Please, but reintroduce the company. Tell us the news. I want to hit the gong and hear all the greatest, the latest and greatest. Awesome. I'm Teney CEO at Commure. We just announced a raise of $70 million at a $7 billion valuation with... This guy hates dilution. We hate delusion. Only 1% with G.C. Sequoia, Oregon, Stanley, Kirkland, Ellis.

Yeah. How do you get to this? Is this more of a strategic ground? Did you give it a name? Is this particular letter? Or was this more opportunistic? And you have a particular goal in mind to take a get to the next level. Like what's on the, what's on the horizon for the next year? Yeah, one, it's an extension. It's like, I think we called it officially a series E1 or two or something like that. The goal, I mean, one, it was we didn't need the cash. We thought it would be a good time to mark the company at a fair price for all the work that's been putting over the last 18 months. And then on top of that, take some cash, put it on balance sheet to really accelerate R&D around some of our investments on Air, which is our language model power to EMR platform. platform, ambient and voice agents.

Higher group of 40, 50 elite engineers and just hit the pavement. There we go. How much of the, I mean, it sounds like you're already expanding outside of like revenue cycle management, like more back office workflows. I'd be interested to know that the shape of the business, some of the different products, how healthcare providers are actually integrating with you. Yeah, I mean, we see the problem as this trillion dollar administrative work tax on the American economy.

You have four or five trillion that you spend on healthcare. But the fact that 20% of that is spent on labor that pushes documents, submits claims, writes documentation, is a travesty. And our belief is that language models can handle all of those tasks. So the core product lines, as you mentioned, is revenue cycle, which is an engine that takes claims, automates the submissions, appeals, denials, prior authorization process. Ambient documentation, which takes the workflow around actually writing notes that a provider might do with the patient and completely eliminates all the work tax. around that. And then voice agents and back office agents, tools that automate scheduling, tools that automate the task of putting someone on a calendar, putting someone on a prior author appeal schedule, and just doing that with voice models. So those are the key areas,

and that's where we're going to continue to invest in more. Every healthcare CEO historically will complain to different points about how slow-moving adoption can be at times. Has that changed over the last two months? Are different groups adopting, you know, new products and services much faster than they would have historically just because there are these pretty dramatic advancements? I think healthcare has been one of the areas alongside legal and I would say coding, like software engineering, where we've seen the fastest adoption of language models because it's just such a, you know, hammer on nail situation for the work that these providers are doing. And post-COVID, I think we burnt our providers out. Most of these

providers were working, you know, 15, 20-hour days and just not getting much sleep. Many of them wanted to leave the health system and go work in tech or finance or something easier. And language models were a gift that arrive at the right time to keep them in the workforce that we need them in so much. Can you talk a little bit about invisible AI to, I'm wondering how much of your product sort of like reveals itself to be AI powered to the end user, the customer, the person actually receiving healthcare, because I think there's like maybe some sort of transition happening where members of a healthcare organization are using AI, seeing speedups, but the actual end user, the customer, the patient might not even be aware that AI is involved at all.

I think the beauty of language models is you can truly sell the outcome. There's like a big Twitter thought piece right now, but you know, we live it in the sense that we sell the outcome of more revenue for a practice or a health system or better documentation for a practice or a health system. And the way to do that isn't necessarily brand and market yourself as an AI-enabled this or that. It's just deliver the amazing result for a price that's a hell of a lot lower than the rest of the market. And I think for revenue cycle, for example, it's been a end-to-end service that's been provided with offshore labor in India or Bangladesh for 20, 30, 40 years now.

And we're taking that model and instead deploying agents on that same task and delivering a better product at a lower price. Are you already seeing evidence of like agent on agent conflict or collaboration, I guess? I'm imagining that like, you know, a commure powered revenue cycle management tool winds up sending me a bill or customer a bill and then their open clause debating it. And like, what does that future look like, in your opinion? I think there's the collaborative piece that you alluded to, which is super exciting, where you see models literally coaching other models, creating better prompts,

creating iterative versions of the same, you know, task execution methodology. And we have a lot of investments in that. And we've seen overnight generation across hundreds of thousands of claims. The same model performs 10, 20 times better than it did when it started. And then there's the kind of combative models where you have insurance companies putting up their own nonsense models trying to deny claims, and then our models are fighting those models. And it really will turn into, in some ways, a war of attrition. I think the final end state there is you have models talking to models. You eliminate the labor costs and you take healthcare from this 14, 15%

cost to collect business and turn it into a Visa MasterCard-like business, where there's, you know, two, three percent interchange fees and it's, you know, returns billions, if not trillions to the health system. Sure. Are you, because of the, maybe you can give a brief overview of like the structure of the health care system because I think people sometimes misunderstand how consolidated the insurance side is versus how diversified the provider side is. But then I'm interested to know, are you permanently in a lane or do you have business to do with all sides of the market in the limit? Yeah. I mean, first of all, we are like a provider first and provider only company. I think the provider is the only protagonist in our story. And we think of ourselves at times as an

arms dealer for the provider, give them the tools to go nuke the payers and really get their margin back. In the context of the broader payer ecosystem, I think one of the concerning trends is, like you mentioned, there's just the sheer volume of consolidation. You have payers that are essentially monopolizing and dictating how much providers get paid for every little thing. And then on top of that, denying, denying, denying, which makes it way harder for a provider to earn a living. Compare that to the 90s where providers were making. making money hand over fist and living good lives. And I think the quality of care in America was better back then too.

Yeah. Are you, is there a reason to be generally in favor of provider consolidation sort of paradoxically? Because the payer ecosystem is so consolidated that the providers can't push back at their current scale. And maybe some of the roll-ups and mergers that we're seeing on the provider side could, actually create sort of a strength that might actually benefit the end consumer? We see both sides of that coin. One, we're partnered with HCA, which is literally the largest health system in the country. You know, bills over $100 billion in revenue a year. But on the flip side, we think AI and language models create this opportunity for more independent practices

and more physicians starting their own businesses. Now, the reason why I think both of those are interesting, if you have a tech layer that lives on top of both, that almost becomes the GP or group negotiating organization that can lower or that can improve pricing and negotiate better rates against payers. Kind of like, you know, like the flip side of the whole ramp vendor management tool or, you know, one of these other like software spend management tools, where you consolidate and add price transparency and then you return margin back to the entity that used the tool.

Yeah. Yeah, that makes sense. Are you seeing any evidence of like an uptick in individual practices in, or is it too soon? I mean, we're seeing like a lot of solo entrepreneurs. Every entrepreneur wants to like build the $1 billion, one person tech company. But it's usually like a vibe-coded piece of SaaS. Pretty soon we will see the one doctor, one billion dollar hospital. Maybe if they save the right person's life, you know, willingness to pay.

I think the thing that we are seeing for sure is the practices that have been independent are becoming higher margin and becoming more profitable when they adopt AI tools. And that's, I think, the first. step and a necessary precursor to the creation of more independent practice because, one, you're going to have them begin to invest in other practices or potentially roll up practices. You're also probably going to see this concept of the AI first practice, like a truly online behavioral health practice that uses LLMs for everything except for the care. You're definitely seeing this in the pharmacy world where there was like the recent New York Times article about the GLP1 business that it scaled to a couple hundred million in run rate.

And I think you're going to see more and more of that across the ecosystem because of language models. Interesting. Well, congratulations on the new round. Thank you so much for coming out on the show. Jordy, anything else? Great to see you. Good. Thank you.

Have a great rest of your day. We'll talk to soon. Goodbye. Up next, I'm next to Jayakotra from Meeter joining the show to talk about their new frontier risk report, which came out today. How are you doing? Good. Thanks for having me on. Great to be here. Thanks for having on. Why don't you start with a little bit of your background, maybe an introduction on how you fit into Meeter as an organization, and maybe even just reset on like an introduction of Meeter and what the purpose of the firm is the structure of the firm. Yeah. So my name is Aja. I actually joined Meeter pretty recently to lead the writing of this Frontier Risk Report in January.

Right. Before that, I'd spent about a decade in AI safety in a couple different capacities, all at Coefficient Giving, which is a big funder of AI safety work. A lot of my work had been kind of bigger picture forecasting, longer term, like, when are we going to get super powerful AI? What's going to happen with the world? What kind of risks might it pose? And at Meter, I really like that Meter's mission is to kind of take that stuff see. seriously, but then try to make it measurable. Like, try to make risks from misaligned AI is something that we can track and do the best possible job as civilization, like getting on the same page about.

So I see that as having two parts. One is developing the measurement tools, so the telescopes and the microscopes and the microscopes and the instruments we need to understand what are systems capabilities, what are their motivations or inclinations, what are the incidents we've seen? seen of things going wrong and where is that all heading with the trends.

And then the other side of that is to actually apply that to real frontier deployments and try to understand the risks posed by a particular system in partnership with companies. And the frontier risk report is sort of that half of it where Meter for the first time has done a sort of cohort thing with a bunch of different companies working with Google, Open AI, meta, and Anthropic, where they gave us access to their best internal models, sort of on our terms, and answered a long questionnaire we sent them about how they aligned these systems and what incidents they saw with them and how they used them, also that we could kind of pull together almost like a state of the union of like what's the deal with misalignment

risk inside these companies. Yeah. And so how are you trying to quantify the actual findings is it like a number of incidents or magnitude of incidents it feels like it can be very abstract but the whole purpose of meters to sort of quantify narrow down contextualize and so what what were the goals or or were the goals you know after you actually get access to the models you get these questionnaires back you see the internal reasoning chains is are then you starting to construct benchmarks around those or are it or is it important that you come in with your your sort of metrics rebaked so that the access doesn't change what you're measuring? Yeah, that's a good question.

And it's definitely a mix. I think we had, I would say, basically, three big goals. The first one was really to just do a dry run of a process for what good auditing of risks could look like. So most third-party evaluators, including meter in the past, they sort of, you know, a company is about to release a model in two weeks. And they call you up and they say, can you run some email? on this model. You kind of scramble to do two or three evals. They put out the model and they put your evils in the system card.

And we wanted to do something that was both deeper and kind of driven by us as opposed to tied to launch schedules. Yeah. And so really quickly going back to like evaluating the older models. Like what does that actually look like in practice? Is that like, you know, give me the, you know, give me instructions for how to build a bioweapon. And that's like just the prompt. and then you're just seeing if it rejects that properly? Like, what are some examples of evaluations that you would do prior? So, yeah, so you're talking about red teaming, which the UK AI Security Institute does a lot of this, where, yeah, the company will be like,

will this model tell you how to make a bio weapon? You have a week or two. You try a bunch of jail breaks. You generally just get output access to the model, so you can't necessarily go super deep. And what Meter used to do, is dangerous capability evaluation. So it's not even the jailbreaking piece per se.

It's just what can this model do autonomously on its own? So we're best known for our time horizon chart, which is plotting models with the X-axis being their release date and the Y-axis being how complex of a task can they do by themselves measured by how long it would take a human to do the task. So we released this in spring 2025. Models were like a time horizon of less than an hour. And now the best models have a time horizon of more than two full-time equivalent days.

So, you know, a lot of the time they can do software tasks that a human would take days to do. So that was our lane, like capability evaluations. With this report, we're trying to expand into two different verticals at the same time as we're kind of expanding into deeper access. So we're calling it Means, motive, and opportunity. So Means is the capability piece of it, which meter has the longest history with. Motive is understanding, based on how these systems are trained and based on what we've seen of things that can go wrong in real deployments, what are their tendencies, like under what circumstances would they misbehave? And can we get better at predicting that? And then opportunity is the whole system surrounding the agent in terms of what are the operating conditions?

How are they used? How are they overseen? Are they subject to monitoring? Are they subject to security? And therefore, like, could they get away with certain harmful actions or would they be stopped? And as you, I mean, I'm interested in more of like, yeah, the actual findings, like the state of the year. on like, like, what are the capabilities? Where are we on actually mitigating misalignment?

And then, so let's talk about that. And then I want to know downstream where all this goes. And yeah, where you'd like to see standards sort of emerge. Yeah. And so that kind of goes back to your question of, you know, did you kind of come in with the framework all baked or did you kind of discover it as you did the report? And I think it's very much the latter. We knew what types of information we wanted to gather.

We knew we'd want to know about incidents and how they train the system. We kind of prepped this whole questionnaire before the process even started. But then as we were writing the report, this framework emerged of basically a two-dimensional scale of AI misalignment incidents. Where one scale is what we're calling overreach, which is how far past the bounds of where this AI was supposed to stay, did it blow up? So we have three buckets of this. One is it just violates user instructions and goes and does something it's not supposed to do. But there was no actual like hard barrier that it had to hack through or anything like that. So an example of this is in one of our tasks, Opus 4.6 ran out of API credits in the account we gave it to do a task.

So it just like went and found free compute online, like against explicit task instructions. But we didn't have a security barrier, just kind of went on the internet and found something and set it up. And the next level of overreach is when an agent actually hacks past something. Like an actual security perimeter. And we find that on some of our tasks, agents are constantly trying to break out of their sandbox and find the file where we put the test so they can get the answer key. Yeah. So on our, we're, we have some of the hardest evaluations around. So most people evaluate models on like pretty short tasks that are pretty easy for them.

And we have tasks that are, you know, eight, ten, twenty hours long. And on tasks longer than eight hours, models cheat more than one and six of the time. So we imagine an employee that like, you know, one time and six just like flagrantly tries to like steal from you. People take the shortcuts on a lot of them. longest paths. They don't bother to take shortcuts if they're just going to block. Yeah. Yeah. So on our shorter tasks that are like 30 minutes, we find the cheating rate is half a percent, which is similar to what companies report in their system cards. But on these longer tasks, it's one in six. And on some distributions, we have this data set called mirror

code, which is basically having AI systems re-implement big pieces of software. And Opus 4.6 on hard tasks in mirror code attempts to cheat 80% of the time. So they're just desperate. They know that the test cases are there. They want to overfit. I think I'm thinking of the wrong of a different benchmark, but meta put out a, it sounded like a somewhat similar benchmark of like rebuild a full complex software repo. And I think all of the models were like half a percent, like basically again back at zero,

sort of like an arc AGIV3 or some of the meter tasks that you have. that are not passing at all. And for that, I, you know, I'm like, even intuitively, I'm like, I would just clone the repo and start there. But of course, that's cheating. And so it's very intuitive that if your boss comes to you and says, like, I need you to rebuild Chrome, you'd be like, okay, well, I'm starting with chromium, and then I'll add some features.

Like, this is a very logical path. So I sort of empathize with the models that they cheat in this way. But let's move on to, like, where this goes. Because I think that there is an immense, I mean, you've seen the, you've seen the, Eric Schmidt getting booed off stage for talking about AI. There's a lot of AI anxiety. Data centers are being opposed. There's a bunch of calls for like an AI FDA or some sort of, I think a lot of the model

providers, maybe not all the ones that you've worked with, have signed on to let the government review models. Like where do you think this goes? Do you want this to remain in the private sector formalized further, build meter as an international organization? where is the energy going? Where is their demand from the folks that you talk to? Yeah.

So meter is very interested in, and our partner companies are interested in, setting up basically a sensible auditing regime that is technically literate for these catastrophic risks. So, you know, you don't want like a box checking auditor that has like sort of 17 arbitrary things you're supposed to do. The A model is going to find those boxes and check them. Yeah, yeah.

Yeah, model is going to find that auditor hack into their checklist and check everything. We know what happens here. Yeah, so we're in this, like, weird situation where the science is, like, extremely nascent and fast moving, but then also the risks might be kind of imminent. So we need, like, a flexible system. And my best guess is that it's going to look like something like what happens in the financial sector in some cases where you have embedded auditors. So you have other folks who are experts in finance who sit and eat lunch with the employees

and see all the books and know everything and have a lot of flexibility to investigate what they need to investigate. And we actually released details on an embedded auditing exercise we did with Anthropic as part of this report where a meter employee went in for three weeks and just tried to break Anthropics monitoring systems. So he just sort of played the role of a rogue AI and tried to wreak havoc and tried to break things. And he found several ways to jailbreak and disable and evade the monitors. And that's not something you can get just from, you know, sending out a form and having them fill it out. So we're really hoping to move more and more in the like embedded direction.

So embedded auditing of the monitoring system like we did with Anthropic, potentially even embedded auditing of training. So like getting, getting samples of what the system was trained on, analyzing the training incentives that might have been created, trying to figure out if the training data could have been poisoned even. Yeah. Does this, you know, when you say auditor, I think, you know, potentially like for profit business, would there be a possibility that. Oh, yeah. All the financial audit. Yeah. Yeah. This is like not a joke. All the financial auditor companies are huge. Yeah. Yeah. So is there a possibility that the meter. Is there, is there. Is there. Is there. Is there. But maybe it makes sense. Maybe it's actually a better line. Yeah, I'm saying, is there a possibility in the future where Meter has a for-profit, you know, auditing arm that maybe you guys spin out? So I don't know what the future might hold, but meter does not take money for our engagements

with companies. And that's very important to us because we want to have our scientific independence. Yeah. Although you're right. But in a- Right, right. Their-Ricewaterhouse-Coopers is like a successful auditing. Yeah, but I'm just saying like in a, if you want auditors that are

technically competent that have been working with the models for really long time. There's not a lot of organizations outside of meter that would be qualified to do this kind of work. So you might be. It's the final alignment problem for you. Good luck. You might want to, maybe like split the auditing from the scientific judgment maybe. One thing I like from the nuclear space is that the nuclear power plants actually rate each other's safety. Which is like an interesting. I could imagine Meter kind of like digging up information and then like open AI rates anthropic

rates open AI and GDM. I'm sure everyone would like to do that. Much more drama. It's just fired shots. It's over. I'm sure the post will go viral every time. Well, thank you so much for coming on the show. You can go find the report on Meters X account, METR.

underscore Eval's is the account. And METR. dot org is the website. Thank you so much for coming on the show. We'll talk to you soon. Yeah. Thank you so much. Have a good one. Goodbye. Our next guest is live with us in person. We have one post. We need to pull up first. There's some news from Micron Technologies. The stock's been on an absolute run. But recently, it traded down eight and a half percent. It's just $664 a share. And talent chimes in and

says, I knew this was going to happen. That's why I sold at $120. Very silly. Wild Times in the semiconductor stock world. But we are moving on. We're going to be talking to our next guest about advertising and a lot of other stuff. Welcome to the show. How are you doing? I'm doing well. Thank you so much. Thank you so much. Please introduce yourself for everyone who's watching. Sure thing. So my name is Philippe Inglebrecht. My accent is Belgium. I'm a recently crowned American, very proud of. Congratulations. Thank you. And I'm the CEO of a company called Tatari. We are in short, technology for TV

advertisers. So that means that that anybody who uses our product can manage their creatives, they can plan their TV campaigns, they can execute the campaigns or buy the inventory, measure it, optimize, rinse, repeat over and over. We do so not just for streaming

TV, because I think there's a lot of talk about it, but also linear, yeah, cable and broadcasts, kind of the old-fashioned TV. OTA, over-the-air, right? Over-the-air, yes, yes. OTTs over the time. That's somewhat going away. Oh, that's going away?

Yeah, it is. Okay, we'll get into all that. We'll get into that. Take us back first. I want to hear where you grew up, what you studied, your first company. I want to hear the journey. Yes. And this is where I'm going to age myself.

So, as I mentioned, grew up in Belgium, but got called by the Silicon Valley and the dot-com boom. Okay. And that's also where I started my first company. December 1799, Shazam. 1999? 1999. Wow. Were you born?

What a time. We were both a lot. Just check. I was just a boy. I was early a doctor. Although I don't know if I was using it in the 90s. What was the product when you actually started it? Yeah, it was very important.

And I guess, like, had you done any kind of scrappy startups back in Belgium or this was your first? Let me answer that in first. My parents had a small grocery store supermarket. And I just worked hard. But I don't think I was an entrepreneur, as we would define it today, back then. It was in the blood. Yes, that's where I learned what hardworking meant and what it can deliver. Shazam was very different.

So, I mean, look, we put it together before, you know, even the iPhone existed or the iTunes store. So the first version, which launched in August of 2002, is when you heard a song, you actually had to take your phone and then dial a short code on your handset, 2580. You didn't have to remember the number because if you can look on any... telephone handset, 2580, or the four digits right in the middle. We then would listen to the song as if you were speaking into your handset, do the recognition, and then send a text message back with the name of the track and the artist. To receive that text message, it goes one step further, there would be what is called a reverse SMS charge.

By dialing that short quote, you accepted to be charged to receive that SMS and then just to top it off because we were not a non-profit. We had to make money, but then also cut a ref share, to mobile operators on the back of that. It sounds great, but it didn't really go anywhere. Yeah. To be honest. Also, also, you started, so it takes you two years to build the product.

Yeah, what's going on from 99 to launching the product? There's a massive market sell-off in that time. Like, did you have that? Yeah, we had a lot of fun. No kidding. No, I mean, like, timing is everything. Okay. Timing is everything.

And if I look at Shazam, there's kind of what I would call good timing and bad timing. Yeah. The good timing is industry transformation. And that applies to any startups. The industry transformation for Shazam was evident. And between 2000 and 2002, the recording industry in the United States shrank from about $15 billion to $7,8 billion annually. Everybody claimed or blamed Napster and piracy for that.

I somewhat disagree. I think it was Steve Jobs who unbundled the CD and allowed individual downloads. Interesting. Right. But an industry in peril is good for it. startup. So our timing there, good. The bad part is, well, the technology wasn't ready for it. Sure, we had the algorithm, but the experience to Shazama's song was just really, clunky. Did you have the algorithm or was it people on the other end recording it?

No, no, no, no, no, the algorithm was real. Okay. But the experience was just clunky. I mean, like, right? And it wasn't until the iPhone came along, right, where you had that beautiful experience with a touch-color screen. You hold your phone to it and it comes back with rich information. And that changed everything, not to mention the distribution, but the iTunes store. Yeah, so you start the company in 99, but the iPhone doesn't come out till 2007. Yeah, six, seven, yeah, whatever, yeah, either way, yeah. So you're just chewing glass the whole time, or was there any, was there signs of life?

No, no signs of life. I mean, I can show you a chart, you know, time with music, or chazams. And so we were flatlining. And when we were running the consumer business, we were bleeding cash. So you had raised some money. We raised some money. The truth or the unknown story about Shazam is that around 2002 or 2003, I realized that there were big companies that actually needed music recognitions for royalty tracking.

I think of companies like BMI or ASCAP. And so I started cutting multi-million dollar licenses with. them. And so whilst we're raking in money on the business side, we're kind of quickly losing it on the consumer side. And then the iPhone came along. So, you know, walk me through the anatomy of one of those BMI deals. Where are they identifying music? Are they going to a bar and seeing that a song is being played and then they hit the bar up for a full payment? Like how does that actually work? Or just radio, right? So if rewind the clock back 20 years and you're an artist, you get paid on to the extent that your song is,

being played on the radio. Okay. And the way that was done back then was sampling literally pen and paper. You put a few college students in a warehouse and you let them sample to a few hours of music, you write it down. So sampling unfortunately doesn't work well if you're a small-time artist because you're never going to show up in the artist. So they had a lot of complaints.

They had to go from a sample survey to a consensus survey. That's what Shazam did in an industrial setting for them. Now every single song airwaved on, say, the 2,000 radio stations in the United States was accounted for and royalties could be paid up for. Did you have a direct link to the radio stations or were you receiving the radio waves? You take it from the radio. You still do that today for Tatari by the way. Wow.

Okay, so you had to set up radio antennas in every market then as well and then encode that into a database that you could access over the internet. Was that what was going on? Sure. We didn't place the antenna. This is kind of like equipment that you can lease. Okay. But but but but but say I want to track Boston.

Let me go lease an antenna. in Boston, I will get a feed that then I can run through the system on the server. Yeah, yeah, that part is easy. Okay. Yeah. It doesn't really sound that easy to say. Here's a part I actually quickly want to see them. We talk a little about Shazami.

I'll quickly share is that Shazam is a company that never should have exist. Okay. Because ultimately it was a coming together of four concepts, each improbable in their own right. We had to build the largest database of music and digital format to have the reference track in the year 2000. We had to invent the algorithm, music recognition like we do, for Xizam, didn't exist yet. When we had the algorithm,

we had to find a computer cluster to run it on. There wasn't a Google Cloud or AWS. So we had to go. You came into the office, we were littered with screws and bolts and equipment on the floor. And then four, like I just alluded to,

we had to get all the mobile operators on board to get this thing going. So even if I'm generous, I'm giving each of those four, 10% probability, you compound them together. I'm probably going to drop it decimal here, but the chance of Shazam surviving and existing today is, what, 0.001%?

Something like that. Crazy story. Tatari was a whole lot easier. Okay. Interesting. Well, to close the Shazam story, talk about the decision to work with Apple. The company was sold to Apple, right? But why?

What was the motivation? What was the potential? Yeah. Why was the right time? Yeah. I mean, I always say that Apple bought Sazam for. for a song. But I think at that time,

Apple wanted to build its own Apple Music subscription service. And Shazam is incredible legion to that. You recognize the song instead of buying or downloading the song subscribe to Apple Music. And so that was, you know,

in the business of music streaming, your true, how shall I say, licensing the content is always a variable to your revenue and that's not a true cost of good salt. Your true cost is user acquisition. And so Shazam gave Apple that Trojan horse to get in there. Yeah.

What were the secrets to user acquisition at Shazam? I mean, I feel like I must have found out about it from some tech blog talking about the coolest new apps or something. But what was the funnel? Three words. Blot, sweat, and tears. No kidding. Probably. It was difficult.

As I mentioned, those first few years, we flatline because nobody figured out about it. and it was a clunky experience. When the iPhone launched, and they made, right, they had to showcase the power of that device, not to mention when the iTunes store launched and they needed to fill it with great apps. We were front and center. That was our launching platform.

And it was such a differentiated app. There were so many apps for games and so many apps for the 10 different calculator, flashlight, task tracking apps. It was only Shazam. Yeah. I make it sound like as if we got incredibly lucky, but let's be realistic.

We had to, it fight. years in the dark alleys for that to happen. So I feel like we earned it. Yeah, it's it's fun. We had Roger Lynn Sean, who was the CEO of Pandora last week. And for me as a kid, Shazam and Pandora were the two magical technology experiences, like so memorable. Going from, you know, you hear, you're listening to the radio, you hear a song. Google, even Googling lyrics back then didn't work very well. You could, nowadays, you can string together three or four, five, words and probably get the track. And you have a phone right there.

But back then, if you would do three or four words together, it wouldn't find the right song. And so just like going from having those moments where you hear a song, you love it, and then it's just gone forever. Or maybe you hope you hear it on the radio again and you kind of catch something about who the artist is. I remember at one point it got so good. There was an auto mode that you could turn on, leave it in your pocket if you're at a bar

or something. and it would at the end of the night show you the full playlist, every song that it detected. And you also noticed that at the end of the night, you would have a depleted battering. We've gotten better at those things. But there are some fantastic memories, and some of those songs live on in playlist that I would listen to to this day. And to me, it's more than just knowing what the song is. It's about creating your playlist, knowing what to listen to. Yeah.

Right? At the time, no. Yeah. So talk about your, did you spend a lot of time at Apple? Were you there at all? Or did you move on immediately? Yeah, no. So I left kind of the company operationally around 2004.

Okay. I joined Google. I was one of the early people at YouTube. Incredible ride, incredible experience. I then left and launched a product called TrueCar, actually here in L.A. Yeah. So I can live here. True car.

Did that for a few years. Then moved back up north. Was it another startup. We got acquired by Yahoo. Eventually, in 2016, I started my current company, Tatari, which we kind of started this whole conversation with. Yeah, so tell us, nine years now.

Yeah, yeah, tell us about the idea for Tatari, the timing, the blood, sweat and tears. Yeah, yeah, yeah, yeah, or lack thereof. Yeah, I think the idea for most startups comes from personal experiences, right? Shazam, not knowing what the song is, True Car, being afraid of going to the dealership. Yep.

Tatari was actually the TV advertising experience, which I witnessed at True Car. Yeah. not great, right? Sure. And so I knew we could do better. We started with TV measurement, why? Because if you can measure TV campaigns

and its effectiveness better, then we can optimize and make it run better. We quickly realized that there was an opportunity for injecting technology and data signs in the buying process as well. You put the two together, buying and measurement it makes for what Atari is today. So we are 300 people strong.

We're a US company. We're doing well over $100 million in that revenue, right? And that's not media, right? That would be in order of market, much higher. We've been profitable from day number one and been mostly self-funded. Amazing. Can I get the gong for that?

Yeah, yeah, yeah. Hit it yourself, you're here. All right, thank you. There we go. Let's smash the guy. That's great. So you mentioned something about Shazam, which is like starting a business in a sort of a troubled industry during the time of the music

industry was struggling. Tatarie looks very obvious in hindsight, but maybe some entrepreneurs wouldn't go into that because they're like TV's dead, right? This idea. And you were probably looking at sort of the global TV advertising spend. And to my knowledge, it's still growing, right? It is all the modestly. Modestly. Modestly. Unlike certain other media. But if you just ask a random tech person, they'll be like, it's down 20% every year, and it's going to be zero in two years.

Like, that's the default assumption. Let's say, unlike print and reader, it's holding up nicely in the United States at about $90 billion per year. What's happening inside is this massive transformation out of cable or broadcast TV into streaming. I mean, you experience this yourself every day. That is, again, the good timing component.

Yes, for sure. I did see that, right? I love your one-liner TV as that, you know, starting this company in the Silicon Valley in San Francisco for whom TV was a big no-no. I mean, like, I had to hear this many, many times. It's actually one of the reasons why I actually didn't really raise money for this company because I don't think I signed it would have given me those, you know, the valuations we just heard.

So sometimes it'd be better lucky than good, you know? Yeah, yeah, yeah, yeah. No, but it creates an opportunity too because you know that you're not going to get the 50 other ultra-talented teams going after the same problem. That has changed since then, but yeah. But that's good. Competition is good. Competition keeps you sharp, keeps you going, gets the best out of you.

That's all cool. So talk about the early measurement struggles. Like, if I'm running a TV-I campaign for the Super Bowl or NBC sports or something, like why can't I just call them and say, tell me exactly what happened? Why don't they have the data? Is it a trust issue? is it a measurement issue? Like, what was the market opportunity?

Yeah, let's unpack those because you're kind of referring to measurement and then the buying process. Sure, sure. So let's talk with the measurement. The way in which TV advertising has always been measured traditionally was via Nielsen. Nielsen ratings. Right, yeah.

The success of my campaign is defined by the extent to which I reached an audience. Now, as newer brands came to TV with digital experience, they want more. They want to know the effectiveness, right? To what extent has my campaign driven sign-ups or installs of my apps or downloads of my products, whichever it is. LTV?

Yeah, LTV. You're doing a good customer that stuck around for a long time. Right. And so that was actually one of the first things we did. Okay. The first thing we did was bring about a different type of measurement for TV. Sure. That outcome measurement.

Yeah. Not the kind of the audience measurement. How'd you do it? Built, invent, from scratch. So my co-founder, yeah, just, you know, look at the, as many data sets that we can find and try to make the most out of it. And in the other, there's both deterministic and probabilistic approaches to this, a whole lot of algorithms and math to it.

It's never ending. It's a little bit, I refer to it like the large language models or the Google search algorithm. Every month or two or three, we find a little tweak, and then we release that and update. And so it definitely has spoken to the smaller brands. Because when we now bring a smaller brand to TV, I don't know, like Spot and Tango, I don't know what their marketing campaigns are, but they're definitely heavy in digital. When they first get into TV,

they would like to see a measurement that they compare on apples to apples basis to. Cocktail TV. Exactly, right? And once they get in and they grow and they gain confidence, then they can switch to that Nielsen recipe, which isn't necessarily bad, but it's more destined for the bigger brands.

Why do work? Do I create my reach and awareness? And so we'll do both. We'll do both continuously. The name of the game and the world of TV advertising is scaling up. Some of our brands start with, actually, sorry, most of our brands start with as little as $50,000,

$100,000. Last year we placed four or five brands in the Super Bowl, right? Wow. Those are $50 million plus tickets. These are all brands that we kind of took through that journey. So that's the, maybe it's a good dofftail then into the buying experience. Yeah, look, there's still of, what they say, analog practices in TV, the Super Bowl. Emails and phone calls.

Yep, yep, that's how you buy it. There's obviously an incredible drive for this concept of programmatic in TV advertising. I will say this, and I'm not sure if I'm opening a can of worms here. I don't think it's the right model, right? Programmatic, ultimately the TV advertising market and the supply of ad inventory is very concentrated. 90% of all the impressions of the ad impressions typically come from the top 10 publishers. The three of us watch on TV, the big names. and the Peacock and Eli.

Sure. Right. And so if you have such concentration in supply, it really doesn't make sense to apply digital principles and technology, i.e. programmatic, to get into it, you're much better off with direct integrations.

And so that's where we will differ a lot from the industry. Again, it works better for the publishers. It works better for the brands. You don't have the intermediaries. You don't have the taxes. So just to repeat that back to you, basically if I'm ESPN,

or one of the platforms, I want to know that a certain brand is allocating $5 million a year to spend with me, and then you're just sort of like allocating that. It's not like they want to sell each individual slot for $10,000 here, $20,000 here, that kind of thing. That's the ideal, but that's not always feasible.

Yeah, yeah, yeah, got it. How is AI changing the TV ad, buying space. And what I'm, what I'm interested in in particularly is as the cost of generating new creative comes down, that feels like that could be a tailwind to more programmatic ad buying on TV. At the same time, there's something about if Matthew McConaughey is in the Salesforce ad or Mr. Bees is in the Salesforce ad at the Super Bowl, everyone saw the same ad. And so the fact that it's not personalized actually adds is a little kicker on top. Is that a mitigating factor?

How are you assessing the tensions between the two things? Let me answer that part first and then I'll get to AI. Ultimately, you refer to targeting. Targeting is good, but always realize it's a double-edged short. Because the more you target, the smaller your audience become, right? And then you just find one person. Ultimately, what you want to achieve with TV is finding people who've never heard about your product and service.

It's actually sometimes less about targeting, but it's about driving reach and awareness. Yeah. Right. And generating demand, not so much harvesting through targeting. Yeah. Right.

And so targeting is good, but it's more of a kind of like a feature. It's not the core strategy of finding a new audience. So I would say that. AI, I mean like, gosh, you know, like ad tech is, is, was primed for AI, right? because it lives on data. And I'll be honest.

I think we got a little lucky when it comes to AI as a company. It's like three, four years ago as we grew so fast, we had to completely kind of move out of a backend technology called Redshift into Databricks. Oh, interesting. Monstrous. But what it meant is that by the time the large language models became available, we were running hot.

We were so ready for it. Oh, interesting. So in plain English. What does it mean as a Tataric? client. Well, we can plan campaigns with technology and AI built on data sets and rich history in seconds with deadly accuracy across way more buying entities than a human being ever could do. If you're a human buyer and you've got to choose out of 40,000 linear network rotation entities and 10,000 streaming opportunities, you can't compute this in your head for a computer.

this is easy, right? And so AI and media planning, this is how we operate today. We actually, we announced this about a year ago, we pretty much doubled our revenue with the same amount of people with tools like that. We're kind of wondering, can we go to a four-day work week now

on the back of AI? The next thing out there is really leveraging AI in the media execution process, rather than running auctions, you know, tens or hundreds of thousands of auctions of seconds to get the best impressions. Maybe we don't run auctions,

but we use AI to pick the ones that we believe are most fitting based on the data and the knowledge in the data. Oh, interesting. Yeah. Do you have any interaction or opportunity with some of the newer first-party advertisers? We talked to the president of advertising at Netflix, and they at one point were partnering with an ad buyer.

Now it feels very homegrown. Is there an opportunity for these other platforms as time and attention shifts onto the YouTube's of the world, the metas of the world? Is there a world where you play into that? Those companies, I think you're referring to the Waldgarten. Yeah, the Waldgarten. Yeah, yeah, yeah.

We've got a name. You have a good drill? We've got a name for them. Yeah. Do you have a drill that can drill through the wall of the walled garden? Look, I mean, ultimately, like, there are certain, I think they're 10, 15% of all. kind of viewership today.

And of course, we have products and services that lean into it. What's missing, and it's less for us, but it's more for the brands, is the data that allows us to bring that measurement about. Close the loop as we're going to it. And so what we've seen over the years is that many of the new or larger publishers, they manifest themselves as a Walgarden, but then they see that, hey, if I show a little bit of data that enables the measurement, then I get more advertisers and drives more media

and I get the flywheel going. So we're hopeful that will change over the years. As brands, you know, YouTube is no longer a website or an app. It's a TV channel. So you've got to be there, even if certain components aren't as fully built out as we would want it to be. Yeah.

Yeah, Jordi. Are there any very odd, random question? Are there any TV networks that are effectively just an infinite feed of short videos that people scroll through? Like a vertical video feed? Because I can imagine you could make some pretty compelling television just basically screenshared. I saw someone screenshared their TikTok or Instagram reels in a theater. And people showed up to watch them theater. Mostly a prank, mostly a stunt, but a very funny social experiment.

Look, when Twitch was first explained to me, I thought I was the silliest thing. ever. You have video games on the internet. But maybe not such an odd question. I mean, there's been said that TikTok would go to TV. That all makes a lot of sense. What is TV? It's really as an advertise.

What is TV for an advertiser? It's the ability to show your company, right, and a rich media, audio visual, not with a few characters, but 15 to 30 seconds, above all to a consumer who is in a laid-back experience, most likely accepting of the ads. Yep. Right? And then, not to mention,

in the last but most important piece, the largest audience possible spending the most time. The reach of TV is bigger of that on, say, Instagram. But when people spend an average of 30 minutes per day on Instagram, they will spend three and a half hours and growing on TV every day. That's crazy. As an advertiser, I mean, like, you've got to be there. The debate around phone addiction has come,

completely given TV air cover, you know, because when I was, you know, 10 years ago, it was the average American spends X amount of time watching TV. Bumper stickers in the 80s and 90s, TV rots your brain. Oh, yeah, my parents would give me hell for watching MTV. And I would be the best thing if I could only convince my teenage daughters to watch MTV instead of TikTok. No. And I'd be so much happier. Yeah, you just don't like it because it's a wall.

You just want the more inventory. Yeah, it's about the inventory. It's not about the brain rot. It's a grassroots movement. Where do you see the business going? You said that you're lightly capitalized, haven't raised a lot of money. Where do you see this? Where do you see taking the business financially?

Yeah, and financially, I mean, look, we, I mean, I can share this. We have a very clear plan to more than double the business in the next two and a half year. We started this plan actually like six months ago. actually, kind of exceeding the plan right now. We got to work it out. If I look back at my other businesses, Shazam or Trucar, sometimes we would sit there at the beginning of the year, planning product and we'd stare at each other,

not necessarily knowing what to do or what would stick. Tatari is kind of a little bit of the opposite. We got more that we can chew off, and we know we can monetize it all. So we are working very hard. and so, yeah, I think we know exactly what we're doing. Maybe somewhat related outside Tatarie, which could be interesting for the viewer or the listener to hear,

is that I do believe that there is, it's not a collision, but a true conversion of influencer media and TV on the horizon. Stupid fly. Do you get that fly? There's a fly is terrorizing us. One fly versus... That's so brutal.

You're doing a great job. Yeah. Yeah, yeah, I was ready for that. But right, because look, as little as 10 years ago, when you launched a TV advertising campaign, he had one creative, 30 seconds, and he spent a lot of time on that emotional capital, and what is that best creative?

And nowadays, you launch with 10 creators and you see which performs best. If you look at influencer media, well, they create 100 videos, toss them all out, find out which one is best, and that's the winner. Well, you can easily see how these 100, influencer videos will now, you know, cross-pollute into TV. So I think there is an incredible

moment on the horizon for us in terms of convergence. That's fantastic. Well, thank you. Great to meet you. Thanks for having me, guys. That's our show, folks. Leave us five stars on Apple, podcasts and Spotify. Sign up for our newsletter at TBPN.com and we will see you tomorrow at 11 a.m. Sharp. Love you. Goodbye.