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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TVPN. Today is Tuesday, 01/27/2026. We're live from the TVPN UltraDome, the temple of technology, the fortress of finance
Speaker 2:The capital of capital.
Speaker 1:Before we begin today's show, as many of you know, there's a major news story unfolding in Minnesota. That's very sad. That and it's become a national news event. We're gonna continue focusing the show on technology and business as always. But if you're interested in comprehensive coverage of the Minnesota story, we recommend outlets like The Wall Street Journal, The Information.
Speaker 1:They've been covering it daily. There's been a lot of great reporting from both of them, both about what tech leaders are saying, what CEOs are saying, and what's happening on the ground with the admin. We're hoping for a peaceful resolution, thoughtful dialogue as the as the situation continues to evolve. But for now, let's get back to the show because we have a very important guest joining us at 2PM today, the creator of Claude Bot, but now it's called Molt Bot. It's been renamed.
Speaker 2:We're molting now.
Speaker 1:Lots of things are evolving on this. And I'm still thinking about it, still thinking about the implications of this Before we dig into what I wrote about this morning, let me tell you about ramp.com. Time is money. Say both. He's used corporate cards, bill pay, accounting, and a whole lot more all in one place.
Speaker 3:There's lot of
Speaker 2:asked, is Jordy calling in from the paddocks? And yes, I am. We're working on a new pair of headphones here, gear that we can send to guests. Some of the guests come in and they've got some pretty wild audio setups. Mhmm.
Speaker 2:And so we're trying to help them out with that. So these are in the works. Yes. They're a little bulky right now.
Speaker 1:So these will be sent to
Speaker 2:Coming soon.
Speaker 1:Regular guests of TBPN. They're USB C wired
Speaker 2:Yep.
Speaker 1:And should have really clear audio quality, no delay
Speaker 2:actually built for the track? Yes. And so the noise cancelling
Speaker 1:I think our guest might get kinda crazy with it because our our guests are gonna be like, well, now I'm empowered. Now you've given me the ability. Because we get some guests that come on the show, I'm sure you've seen it, where they'll be like, you know what? I'm gonna stunt on the TBPN boys, and I'm gonna give you a factory tour. And sometimes it's flawless, and sometimes it's a little rough, but this is only gonna empower them to do crazier and crazier things.
Speaker 2:On these. The goal was basically like turtle beach headphones Mhmm. For people that Mhmm. Aren't playing Call of Duty. Yeah.
Speaker 2:They're playing Claude Bot or Molt Bot.
Speaker 1:Yes. Yes. As we
Speaker 2:now call it. So.
Speaker 1:Well, let's take everyone through the linear lineup. Meet the system for modern software development. 70% of enterprise workspaces on linear are using agents. And as I mentioned, we have some we have Peter from MoltBot coming on. Palmer Luckey is also coming on at 01:30 to talk about AI drone racing.
Speaker 1:Bridget Mendler from Northwood Space is returning. Ben Lair from Lair Hippo Ventures. Lucas, Jamie, Aaron Frank from Lightspeed Venture Partners. We have a massive show that should I'm sure we'll finish right on time. It's a three hour show.
Speaker 1:Right? Anyway
Speaker 2:Of course, we'll be going deep into the fourth hour today. Probably. So stay with us. Chat is asking if we'll sell these. If we can make these good enough Yes.
Speaker 2:That they're actually incredible as just a daily driver Yes. For Zooms Yes. And whatever you guys are doing at the office, I would be happy to sell them. Yes. We have to make them so good.
Speaker 2:Yeah. Part of the reason why we haven't sold merch to date is just that we're a podcast. We're not an apparel company.
Speaker 1:Yeah. We're not a real apparel company. Is a and there are some hairy, sticky things that come up when you're managing a e commerce like the back end, making sure everyone gets their returns and gets their deliveries. I've in e commerce for years, and it's something that we wanted to be just like a nice to have little extra for some some friends of the show. But we're we're we're actively thinking about it, so we are aware.
Speaker 1:The Claude Bot memes are completely flooding the time. Out of control. My Claude Bot just signed up for a 2799 build your personal brand mastermind after watching three Alex Ramosy clips. This text message is, Claude Bot, hey, did anything weird happen while I was out? Define weird.
Speaker 1:I just got a charge notification for $2.09 $9.07. Oh, that? I just signed us up for build your personal brand mastermind. After analyzing three Alex Ramosy clips, the ROI math checks out. You'll 10 x that investment in ninety days by monetizing your expertise at scale.
Speaker 1:What? I also require acquired some premium domain. Borgiaempire.io. Oh, Borgia is the poster.
Speaker 2:Yeah.
Speaker 1:This is hilarious. Probably fake, but I mean, the the Clodbot gets wild. I've seen some I've seen some some some wild things like and and Peter, as he'll talk to us about it, is clearly no stranger to the fact that, hey, this is a this is a developer level tool. This is something that you should not just be running crazy with. You need to be He even says this in a post.
Speaker 1:He says, and yes, most non techies should not install this. It's not finished. I know about the sharp edges. It's not even three months old. And despite rumors otherwise, I sometimes sleep.
Speaker 1:So very excited to talk to Peter. He's getting a lot of requests for small changes, poll requests. He's certainly inundated. But I think, in general, the project's going very well, and there's a of solid product market fit. Right?
Speaker 2:There was He's gonna be joining tonight at something like eleven his time. It's kind of insane. This guy's working around the clock.
Speaker 1:Absolutely. So we really we really say thanks to him. There there are some funny things here. So there's a there's a funny funny conspiracy theory. Did Apple create Claude Bot to boost Mac Mini sales?
Speaker 1:And there's been a funny a a number of funny memes about about, like, being the being the Mac Mini head of marketing or growth, and you're just like, yeah, my q one is off to a great start. And Taking all the credit for then Eleanor chimes in with another conspiracy theory. The more convincing plot is that in your role as an unconfirmed Anthropic exec, you went on a special op to get lots of people consuming tokens with open ended agents, but with plausible deniability. And of course, there's some nuance there. We'll talk to him about the different models, what's beneficial.
Speaker 1:Obviously, Cloudbot, you can pick your own model, you can bring whatever you want. But he's, I think, a fan of GPT 5.2. He's talked about that, and so we'll dig into that with him when he joins. But what what what was sticking out in my mind was there's this big meme about about you're built you're Mac Minis. Mac Minis are out of stock.
Speaker 1:All the demands in the Mac Mini. But I think that the bigger implication here for what this actually means is just GPU demand, TPU demand, just raw chip demand. And so I was thinking about, you know, this this idea that you're not buying a Mac mini when you go all in on Cloudbot. You're actually buying a GB 200. Now maybe you're buying TPUs, but the the point remains that you're buying chips, you're and you're driving GPU demand because you're generating more tokens.
Speaker 1:And what are what are the implications of that? So let me tell you about Labelbox, Where's Labelbox? RL environments. You got it? I I I have it.
Speaker 1:John? Here we go.
Speaker 2:There we go. I got it. There we go.
Speaker 1:RL environments, voice, robotics, evals, expert data expert human data. Labelbox is the data factory behind the teams world leading world's leading AI teams. So Cloudbot officially renamed to MoltBot. Anthropic made a trademark related request, and Peter Steinberger obliged with a hilariously perfect rename given such short notice. I was thinking about how much companies agonize over changing brands, changing names, how it can sometimes take years and millions of dollars.
Speaker 1:And he was just like, oh, yeah. Like, I'll just change the name and update everything in an hour. Yeah. Pretty pretty remarkable.
Speaker 2:Well, so so one thing one thing that's relevant is if you look on Peter's GitHub profile under the current projects section Oh, yeah. I'm just gonna read you a number of them. There's Clodbot, Vibe Tunnel, Codex Bar, Peekaboo, Summarize, Repo Bar, Go, CL CLI, Poltergeist, Wackly, Sag, Brabble
Speaker 1:He's contributing to these things?
Speaker 2:Eleven Labs kit, Go Places
Speaker 4:That's crazy.
Speaker 2:Gift Prep, CamSnaps, Spogo, Order like, it just goes on and on and on and on. It's Codex Bar. So so this guy's just been absolutely shipping like crazy Yeah. And shipping within the ecosystems Yeah. Of the underlying tools, models, APIs that he's doing.
Speaker 2:Yeah. So like, oftentimes he's naming projects like kind of riffing off of some of the underlying infrastructure. Oh, sure. And so it makes sense that he would have shipped if he I think if Peter knew this was gonna be a viral overnight overnight success Overnight success. He would have he would've not necessarily named it Yeah.
Speaker 2:Yeah. Like Yeah. Yeah. So closely. And so the issue and the reason that I fully understand them needing to do this like rebrand is that Claude Mhmm.
Speaker 2:And Claude Bot Mhmm. Like you most people that aren't in our little bubble are just gonna assume they're related. Especially because the the kind of word-of-mouth, this viral word-of-mouth growth that Claude Bot is getting, people are often not even typing it. They're just saying like, you using Claude Bot? Yep.
Speaker 2:And then so people are going to Anthropic being like Cloudbot.
Speaker 1:It does create.
Speaker 2:What's Cloudbot? So obvious confusion. And then
Speaker 1:And it's phonetically Yeah.
Speaker 2:So with trademark law, if you don't enforce your trademarks, you You lose it. Lose
Speaker 1:Yeah. You kind of
Speaker 2:And so it's like Anthropic is in a position where they actually even if they're like super excited about Peter's work Totally. And what he's doing
Speaker 1:Yeah. Yeah.
Speaker 2:They still have to enforce otherwise other companies could start coming in and like using things like things that sound like Claude.
Speaker 1:No one wants to become the escalator. You know the story of the escalator, right?
Speaker 2:Think Used you've talked about it on the to be
Speaker 1:a company called the escalator company. They invented the escalator. And then they didn't protect their IP effectively and it just became a normal thing. Kleenex was going through the same thing. They fought it out and they maintained that brand, but people, you know, use Kleenex as synonymous with just facial tissue.
Speaker 1:Anyway, MongoDB, choose a database built for flexibility and scale with best in class embedding models and re rankers. MongoDB has what you need to build what's next. So one clear note about the rebrand. So he changed the handle and some crypto scammers hopped on the old handle and the old brand and are and are claiming to launch a coin. Be careful.
Speaker 1:Peter has said he's never launching a coin. He's not into crypto, so don't fall for anything because people are being opportunistic.
Speaker 2:Hopefully, we should try to see if Axe can help out with that.
Speaker 1:Oh, yeah. Yeah. I they they might have already handled it, but just just be careful out there. So while Claude Code and Cowork felt specifically prosumer developer enterprise focused Claude Bot or Molt Bot now, it and all the hype train, it felt very much like a glimpse into the future of consumer AI agents. I know it's a prosumer technical tool or lightly technical tool, But it really did feel like for the first time people were interacting with an AI personal agent.
Speaker 1:People are saying, oh, this is what Siri should be, etcetera, etcetera. And so we spent the last year remember the question we asked all the AI agent companies? When can it book me a flight? Like, feels like we're really, really close to a Moldbot skill that is good at booking flights through a couple APIs. They figure out some stuff, and, like, it can actually solve that for you.
Speaker 1:I don't know if anyone's actually booked a flight with Moldbot, but it feels like it's if it's not there already, it'll be there in a matter of weeks. We're not years out anymore.
Speaker 2:Yeah. And this was this was last year. Yeah. Every remember, we were kind of getting sick of of the, like, book you a flight pitch Totally. Because we were like, hey, is this gonna happen?
Speaker 2:Can somebody actually do this?
Speaker 1:Exactly. And so
Speaker 2:and and that that's a cool example. Yeah. But the example of being able to text with a computer Mhmm. And have them like generate reports, research files Yep. Etcetera, give you the right file type back, All all these things that a computer can do if you're operating it.
Speaker 2:Yep. That this is actually more interesting because it's it's happening at kind of like this sort of Internet layer
Speaker 1:Yep.
Speaker 2:And the OS layer Yep. Like the heart like actually on the computer. And so I think, like, everyone was wanting the the, like, book me a flight example Yep. But should be much more excited about this.
Speaker 1:Totally. Totally. And so there I still have a whole bunch of questions, and we'll dig into these throughout the show and obviously with our interview with Peter. Will one of the major labs make Peter a massive offer to join full time? I saw oh, one of my buddies was was posting, you know, this is the $1,000,000,000, one person company.
Speaker 1:Now Peter does have a team actually, already. He's he's he he has a couple of other people that have joined and are contributing. So it's not quite true, but it it it feels like, okay, massive viral success. You know, if you were to go and and raise money, and that's another question, will Moldbot raise money? Will this become sort of a hybrid for open source for profit company at some point?
Speaker 1:This could be if if he came on the show and was like, I'm gonna and I'm happy to announce that he raised a $100,000,000 or a billion dollars, we would not be no way. This is a bubble. We'd be like, yeah, that's kind of like what the market is for this Yeah.
Speaker 2:There were think there was like Harry Stebbings was pointing out there was two companies called Recursive that raised like $4,000,000,000 There's two? One was
Speaker 5:the r s e. Yeah. One is I recursive. Okay. I don't know if that Okay.
Speaker 5:That's how it's said, but then there's recursive.
Speaker 2:Recursive. Okay. But Anyway, sir.
Speaker 1:Well, that that implies the existence of a row cursive and a roo cursive and a rah cursive.
Speaker 5:Yeah. Yeah. We still got way more.
Speaker 1:We got we got three more vowels to plug in there.
Speaker 2:Yes. One one day ago, Richard Socher's new AI lab recursive Recursive. Buys $4,000,000,000 pre money valuation. And then AI chip startup recursive Yeah. At 4,000,000,000.
Speaker 1:Yeah. Yeah. I mean, right so Two months after that. Ryan in the chat saying, Meta is gonna offer him a $1,000,000,000 salary in a co CTO position. And like, that doesn't sound crazy.
Speaker 1:I
Speaker 2:mean, yeah. Yeah. But at the same time, like, can imagine like mannest. Yeah. Like, this feels like Zuck already has
Speaker 1:He does. He does. He does.
Speaker 2:His horse in the race.
Speaker 1:Yes. And to back back to your point, you were making the point that Manus felt like Zuck buying a product. And I think a lot of people were giving you pushback on that, being like, no, like, it's not really gonna be like that. But if you take the Manus team and you say, okay, go build something that you can interact with over WhatsApp, Instagram, DMs, Facebook, that can go and execute things across all of the different platforms and everything else.
Speaker 2:Yeah. And when I said that, I meant I meant it along the lines of like I could see like them putting in a like a consumer agent in Meta AI Yes. Just because that's their little AI playground. Yes. They're just kind of putting stuff in there saying
Speaker 1:Yes.
Speaker 2:It out. It's kind of a sandbox.
Speaker 1:Yes. Yes. Really quickly, Fin dot ai, the number one AI agent for customer service. If you want AI to handle your customer support, go to Fin dot ai. Yes.
Speaker 1:So that is all part of my thesis here, which is that this is gonna drive up token demand. So there are more questions. You know, will they raise money? Obviously, people are chatting about that. How fragmented will the market be in twelve months?
Speaker 1:Like, will there be people who are still running open source? Will there be a meta answer, a Chatuchipiti answer, a Claude, an official anthropic answer? Claude co work grows into this, and and and everyone has their little bets, and then there's one that pulls away. How how all agopolistic will it be? Will there be, like, one that has 80% market share
Speaker 2:Yeah.
Speaker 1:Or even two that have forty and forty?
Speaker 2:Well, yeah. And you have to think about how, you know, you have a bunch of different models you can use in Yeah. In MoltBot. Yeah. And think about how uncomfortable that makes the other labs Yeah.
Speaker 2:That are all trying to build products like this. Totally. And they're like, well, I mean, it's cool that you can use Codex
Speaker 6:Yeah.
Speaker 2:In MultBot. Yeah. It's cool that you can use Opus four five
Speaker 1:Yeah.
Speaker 2:In MultBot, but
Speaker 1:It's cool that you can use Gemini three Pro, Google's most intelligent model yet. State of the art reasoning, next level vibe coding, and deep multimodal understanding. That's not that's that
Speaker 2:you did get me. You did get me. That's not where I was going. But but the point still stands. It's yeah.
Speaker 2:They they can simultaneously be, like, excited about the product experience Yes. And that this kind of, like, use case is getting adoption Yes. But at the same time being, no. We want that experience to be core Yeah. To our products.
Speaker 6:Mhmm. Our
Speaker 5:say, like, you've seen this now with with the new, like, frontier models where
Speaker 1:a
Speaker 5:lot of the models, there actually is, like, there's GPT 5.2 and then there's 5.2 codecs Mhmm. Where there's slight difference in in training or even if it's just, like, of like very quick, like, post train to get the, like, different, like, harnesses working Sure. Like, Yeah. So, like, that's why you see a lot of people were like, they really love Claude code with Opus four five, but then when they're actually doing, like, chatting, maybe they're using a different model.
Speaker 3:Yeah. Yeah.
Speaker 1:Because the
Speaker 5:models are actually, like, fine tuned for the specific harness.
Speaker 1:Yeah. Yeah. And Sam Altman just Yeah. Just said that yesterday that he thinks five point two was a little bit overly trained on math and coding. Coding.
Speaker 5:Yeah.
Speaker 1:And that and that it lost some of its textual flavor, its stylistic flourish in just talking and just writing. What are you getting ready to do? Do you have happy birthday queued up there? Oh, we gotta sing. Happy birthday to you.
Speaker 1:Happy birthday to you. In the middle of this song, we'll tell you about Figma. Figma make isn't your average vibe coding tool. It lives in Figma, so outputs look good, feel real, and stay connected to how teams build. Create code back prototypes
Speaker 2:Yeah. It wouldn't be TBPN if we didn't do an ad
Speaker 1:Ad read during a happy birthday song. Tyler. Happy birthday to Tyler. Happy It Birthday to is Tyler's birthday.
Speaker 2:And it's not just any birthday. It's Tyler's 20 birthday. Yes. Which is very, very special. Yes.
Speaker 2:And so, yeah, you are just you are you're truly an incredible young man Yes. Tyler. And we are very lucky to have you on the team. Thank you. And you have such a bright future.
Speaker 1:Yeah.
Speaker 2:So wise wise for your years.
Speaker 1:For sure.
Speaker 2:And you have you do have we we thought it was fitting that you wanna have your first ever sip of alcohol ever, you could do it on the show. Yeah. But keep it at a sip, you know. Alright.
Speaker 5:This right. I can try now. This is the happy dad.
Speaker 1:Okay. First first taste of alcohol
Speaker 2:Ian in the chat says four more years till you can rent a car.
Speaker 1:Marked. Tyler, apparently you share a birthday with the iPad. Give us is
Speaker 5:it alcohol? Wow. I mean, this is this is incredible.
Speaker 1:Oh, yeah? Yeah. I I
Speaker 5:I wouldn't expect alcohol to like taste like this. Yeah. Yeah. Very This is incredible.
Speaker 1:You had you had you had one idea in your mind and this is just completely different than what you expected.
Speaker 5:I would agree with that.
Speaker 1:Interesting.
Speaker 5:Yeah. Yeah.
Speaker 2:Yeah. Well, it's kind of a cool moment. You're finally qualified to go on Cheeky Pint.
Speaker 1:Oh, true. Yeah. What were they gonna do with that?
Speaker 2:Chat sometimes their Conroy in the chat says, please throw him a buzz ball. We should've. This opportunity.
Speaker 1:This opportunity. The buzz ball story is absolutely incredible. I'm so glad you jump scared me with that. I had no idea that was coming.
Speaker 2:Yeah. I texted Rob and Yeah. And Sunro to do to
Speaker 1:track down buzz ball. It's great.
Speaker 2:Anyway, so keep it at a sip. This is a family fend
Speaker 1:We need you locked
Speaker 2:in. But I'm glad that you've tried alcohol now.
Speaker 1:Because we're gonna go We
Speaker 2:have a video for Tyler.
Speaker 1:Oh, yeah.
Speaker 2:Let's pull it up.
Speaker 1:Let's play. We we got greatest hits. Let's Alright.
Speaker 5:How many times
Speaker 6:are we gonna make these jokes?
Speaker 1:Describe what you're seeing.
Speaker 5:It feels basically like I'm wearing sunglasses.
Speaker 1:If you can do it in under forty five minutes, you will get to keep this.
Speaker 5:Let's go.
Speaker 2:Alright. Have fun, Tyler.
Speaker 1:Fifteen minutes left. Let's see it.
Speaker 5:Okay. I'm in like some kind of maze right now.
Speaker 6:Oh, You were late here last night.
Speaker 2:This is such a good job. On the
Speaker 5:And then here we get a little off
Speaker 6:the rails. You see George Soros and Fauci connected with a big fight as well. All it took was one intern and an all nighter.
Speaker 2:Gigachad elf is do the sad face. What's wrong, Zyler Shira?
Speaker 5:This you could say is Apple Intelligence.
Speaker 2:Yes. You were a speedcube.
Speaker 1:Woah. Nerd alert.
Speaker 2:Tyler, you do you have any news for us?
Speaker 5:Yeah. Contract extended.
Speaker 2:Yeah. It has been truly truly incredible having you here on our set and contributing to the show in such a special way. Amazing. Happy birthday, dude. Happy birthday.
Speaker 2:We love you.
Speaker 3:Thank you.
Speaker 1:What an amazing.
Speaker 2:Proud proud to every day, I'm proud to podcast with you.
Speaker 1:And yeah. Amazing. Anyway, I got you something for your birthday. I got you Turbo Puffer, serverless vector in full text search, built from first principles on object storage, fast, 10 x cheaper, and extremely scalable.
Speaker 2:And What a gift.
Speaker 1:Yeah. I mean, you know, we're joking about the ad reads, but seriously, if Tyler does love, does love token credits, he has a voracious consumption. That is a good gift.
Speaker 2:Yeah. Any any labs out there?
Speaker 1:Any labs out there?
Speaker 2:Accepting
Speaker 1:accepting birthday presents today. Let it be known. Send it your way. The credits must flow.
Speaker 2:Tyler's somebody's gonna send Tyler, like, $20,000,000 of credits, and he's like, woah. Did I just get bribed? I was happy with like a thousand bucks.
Speaker 1:Tyler's over there.
Speaker 5:I'm glad we're gonna talk about one one specific lab after this. Yeah. Yeah. Yeah. We'll see.
Speaker 1:Yeah. I mean, with the with the potential with the with the stuff you're working on mapping the neo labs, anything could happen. High stakes over there. Anyway, back to MoltBot, and the biggest question for me was what this does to inference demand. Right?
Speaker 1:Last year, tech discourse was split between two narratives. CEOs of tech companies and big labs were saying that they were massively compute constrained. Token generation, demand for intelligence, every possible usage metric was growing exponentially, including revenue. We saw all this. And the industry needed to marshal trillions of dollars to deliver on the supply side.
Speaker 1:And the numbers were really big, so people were getting jittery about it. And so the AI bears were much more cautious. They highlighted the MIT study showing that enterprise AI pilots were failing. DAU growth was decelerating. There weren't enough wow moments like the original ChatGPT launch in 2022.
Speaker 1:Those were some good points. Also, the economics. How much will people pay? How how valuable is all this stuff? Is it slop?
Speaker 1:Right? Is it progressing fast enough? This was a big debate. But MoltBot really does make me feel like the token generation demands are going to see another easy x from here. Like buying a Mac Mini is a sideshow.
Speaker 1:When you go all in on running a personal AI assistant, you're effectively buying a g b 200. Now, obviously, not everyone is inferencing a dedicated GB 200 constantly anytime soon. That's not what's happening. But it still answers the question of where does the next 10 x in demand come from? Like, where where where is the adoption?
Speaker 1:If it's rolling out in the enterprise, that's gonna be a little slow. You know, Tyler Cowen talks about health care, nonprofits, whole bunch of industries that are sort of AI resistant, anything that's, you know, blue collar, manual labor, anything that's physically embodied in any way. Like, you can't just roll out a really fast, AI enabled startup and ramp. Yeah, you might be able to ramp to 100,000,000. That's not going to move the needle at this point on total token generation, total token demand.
Speaker 1:So we've seen these jumps before. There was a big jump from token generation from LLMs to reasoning models. That spiked inference demand. We've been focused on training demand. We need to scale up the training clusters.
Speaker 1:But the question now is inference Don't
Speaker 2:forget SLOP. Don't forget SLOP spike demand.
Speaker 1:Yeah. Are you talking about, like, Ghibli? The Ghibli moment?
Speaker 7:All of it.
Speaker 5:All of it.
Speaker 2:Just all of it. Yeah. Mean All of it. Open open Instagram reels.
Speaker 6:Yeah. Yeah. There's a lot of
Speaker 1:stuff on there. Deep research and coding agents took it a step further on inference demand. But those were still specific use cases that many AI consumers never regularly touched. The GPT-five launch by making which made reasoning models more accessible because the router would just automatically throw you in a reasoning model. I think the stat was like less than 5% of ChatGPT users had ever used a reasoning model.
Speaker 1:The o three was available on the free tier. You could get like one or two queries in, or maybe 10. But people just hadn't flipped over to try it. And so once it went into the router, I think demand or usage of thinking models increased 10x. And so lowering the barrier to entry to used more advanced models is in some ways as important, if not more important, than advancing the models themselves, at least in terms of shifting token demand.
Speaker 1:Like, you can have this amazing IMO, like, genius model, but if it's hard to use or it's locked behind a paywall, demand is just not
Speaker 2:part of what's interesting, what you're basically getting at is, like, if you were a software engineer, you were using a ton of tokens. Yes. And if you weren't, you were just maybe doing some deep research
Speaker 1:Exactly.
Speaker 6:Etcetera.
Speaker 1:A lot of times just Google AI overviews or just like a very simple
Speaker 3:Yeah.
Speaker 1:Yeah, ChatGPT query. It just it just thinks of it right off the head. It's not even doing reasoning. What do you think?
Speaker 5:Yeah. Mean, I I will say like I Dario talks about this too in in his essay, but I think the idea of like discrete jumps in in either use cases or like capabilities is like probably like overplayed a little bit where Mhmm. If you really like zoom out like on a on a fairly small time frame
Speaker 1:Yeah.
Speaker 5:It's just like very smooth smooth exponential curve. Yeah. The models are getting better. People are using them more. Yeah.
Speaker 5:It's not like, oh, this one day people I don't start know. I mean, maybe that's true on Sure. Like if you look at it daily.
Speaker 1:I I feel like another way to rephrase this is like like Leopold's unhobblings. Like, Claude bot, mold bot, that feels like an unhobbling in some ways, but maybe more on like the consumer adoption side.
Speaker 2:The chat is saying we should have given Tyler
Speaker 8:We gotta give Tyler 21
Speaker 2:gong salute. 21 hits. 21 hits.
Speaker 1:We go.
Speaker 3:Someone's gonna
Speaker 1:count that. That I got it off by one. But, anyway
Speaker 2:It was enough.
Speaker 1:Restream, one livestream 30 plus destinations. If you want a multistream, go to restream.com. Okay. So I don't know. My general take is like MoltBot still feels like a glimpse into the future where average token generation per capita is 10 x's, you know, over the course of this year or next.
Speaker 1:And and, you know, whether it lands with MoltBot or with one of the AI labs or with the big tech companies, it just seems like we're gonna see a lot more token demand
Speaker 2:as Ash Aurora says whoever builds a direct to consumer front end wrapper of Cloudbot is gonna print money.
Speaker 1:Doesn't this doesn't this exist? I saw the the Poke people by interaction.
Speaker 2:Well, they're not using
Speaker 1:No. No. A lot. Oh, yeah. Yeah.
Speaker 1:Sure. Sure. Sure. So they're not using it, but but but they they they have positioned themselves as like, hey, we're the we're the company that is is doing a lot of the same things, going after the same market, solving some of the same problems. And so it will be interesting to see, you know, how much they accelerate on the back of this.
Speaker 1:That's certainly interesting. I also saw I don't know if we have it in here, but the good folks over at Cognition, Walden Yan, said don't waste your time setting up Molt bot. I had Devin set it up for me. I didn't even run a single command, and now I'm talking to it on Telegram. You can go to try claudbot.com.
Speaker 1:They're gonna have to rename the website, but this is very, very cool for the less technical folks who don't wanna mess around with.
Speaker 2:I'll start reading the next post. Go Feel free to hit it one more time.
Speaker 6:One more time.
Speaker 2:Chat says
Speaker 1:It was 20? 20.
Speaker 2:Authority. Q w says, Claude Bot maybe realized that nothing about me lives on my local device and that Google owns everything about me. In other words, a local AI assistant isn't particularly useful and Google will just win everything. So hot take there. He says, all your browsing history, shopping history in Gmail, search history, calendar, Gemini YouTube, Google Home, where you've been Google Map, your workspace, it's over.
Speaker 2:Bow down to your digital God.
Speaker 1:The iPhone users would like a moment. Like, yes, this is this is extremely true, but there's a lot of people that interface with Google through their iPhone. And so there
Speaker 2:is Well, yes. So my my hope is that the Siri team plays around with Claude Bot and is like, wait, this is this is our opportunity. Yeah. Totally. Like you should be able to chat with your computer wherever it is in the world from your phone Yep.
Speaker 2:To be able to do tasks
Speaker 3:Yep.
Speaker 2:In this in in a way that's sort of native, you know, AI native.
Speaker 1:Yeah. Totally. Public, investing for those who take it seriously. Stocks, options, bonds, crypto, treasuries, and more with amazing customers.
Speaker 2:Public, we have to share, is a new sponsor of All In. Yeah. All In is doing ads now. Fair. Finally, we've been this was This is something that we've been begging them to do TBP.
Speaker 2:Since the very beginning.
Speaker 1:We we we really have been begging for this. But very very good. And I'm sure those will will do quite well. They've been doing a bunch of good stuff. The Davos coverage was really really fun.
Speaker 1:Obviously, the Satya Nadella interview was great, but there were a bunch of other folks who hopped on at Davos to talk tech, and it was a delightful experience.
Speaker 2:Vignesh, who is working on Drumult. Yes. Says, a thread about what I've been doing to calm down some egregious security claims that have been posted about Moldbot over the weekend. Moldbot is powerful software with a lot of sharp edges. Mhmm.
Speaker 2:Please read the security docs carefully before you run it anywhere near the public Internet, and don't skip the checks in docs/security.md.
Speaker 1:What percentage of people do you think skip those checks? It's literally everyone.
Speaker 5:I mean, so so I I have it set up on our like local machine here Yeah. And it was it was texting I think it texted you and Ben.
Speaker 1:I'm texting it. That was actually crazy. So
Speaker 5:the auth setup. So
Speaker 1:the I I don't think any of this will will docs what's going on or really you you you did you disconnect it already? Yes.
Speaker 2:Okay. I believe.
Speaker 1:Because I just get I get an iMessage that's from Tyler's email, and it just says HTTP429 rate limit error. This request would exceed the rate limit for your organization. And it's just texting me. It's just like, hey. Hey, boss.
Speaker 1:I need more money, I guess. It's hitting me up. It's this it it's the experience of of of working here where Tyler's constantly asking, for more tokens, more tokens
Speaker 2:Can we just can we go back and just appreciate just like the frenzy that both the labs and every VC is in right now to give Peter money? Because it's not just the labs.
Speaker 1:But it's not just them. It's That's just the labs. What the labs doing and then what what is Big Tech gonna do? It's such a dramatic line. Yeah.
Speaker 2:It's so fun. So I would imagine that the the Gulf Streams are getting fired up. Yep. And there are people already on the ground.
Speaker 1:I don't know if we should dox his location.
Speaker 2:We're gonna dox In
Speaker 1:his in his bio, he does say he's in Europe. So BC Europe. Gotta get
Speaker 2:out We gotta give some credit to Europe general general. True. Synthesia.
Speaker 1:Talk about a comeback here.
Speaker 2:Synthesia is cooking.
Speaker 1:This is amazing. I love it.
Speaker 2:All bought now. But yeah, there's so many people that are currently sending him messages, maybe showing up where he is, begging him to say, take somewhere between a quarter billion Yeah. And a and a billion dollars
Speaker 3:Yeah.
Speaker 2:And let's let's we'd love to do business with you. I love it. Peter.
Speaker 1:Lambda. Lambda is the super intelligence cloud building supercomputers for training and inference that scale from one GPU to hundreds of thousands.
Speaker 2:Cloudflare has been on a bit of a terror. People finally starting to realize that Cloudflare might be the biggest winner of the Claude cohort, Claude bot chat GPT moment. Interesting. Tyler, you wanna break this down?
Speaker 5:Wait. Sorry. I was
Speaker 2:Oh, were you oh, you you you tried alcohol. You can't pay attention.
Speaker 5:Woah. So
Speaker 1:No. No. So so Cloudflare is a CDN, but they also have, like, web workers that are distributed, so you can you can host things on the edge.
Speaker 5:Yes. So this is why everyone was like, why is everyone buying Mac minis? Right? You can just, like, host these for very cheap on AWS or Yes.
Speaker 1:Or whatever. But but I do think I I don't it's probably possible, but I I do think it's pretty hard to host a virtual private server that runs iMessage. Yeah. Yeah.
Speaker 5:That's true. But even then, mean, most people I I see using Cloudbot are doing, like, Yeah.
Speaker 1:Slack. Yeah. Yeah. Yeah. And all of those have, like, APIs that they can integrate with.
Speaker 2:And there's some
Speaker 5:stuff where it's like, okay. You want access to, like, the local machine Yes. And you want it to be Mac because you're on your phone and you usually use Mac.
Speaker 1:But there are a lot of people that would say, I want Cloudbot to look through or or Moldbot to look through my iMessages and see if I missed anything. Or or, okay, The I'm I'm planning a fan this is the AI personal assistant. Right? It's like I'm planning a family birthday party. Go and and, you know, someone in the chat said they're not available on the mid February.
Speaker 1:What does that mean? What dates are that? Put that on a calendar. Visualize that. Like, solve this problem for me.
Speaker 1:That's what a personal assistant does. It's not just it's not just clicking a button and creating a calendar invite. It's like coordinating different pieces of information that are all messy and not quantized to the perfect date time stamp. Right? So so I think that the Mac mini thing that, like, the, oh, just host it in the cloud.
Speaker 1:Yeah. But you're not gonna get your full experience if you're locked into the into the Apple ecosystem, which a lot of people are. What do you think?
Speaker 5:Yeah. I mean, I I would be surprised if people in, like, five years if, like, non super technical people are are running it on local machines.
Speaker 1:Oh, no. I completely agree
Speaker 9:with that.
Speaker 1:Like, because this this will be solved by big tech. Like, they have to answer, even in the way that, like, to go back to go to go back to the Napster moment, like, yes, you did get Spotify, but you also got Apple Music. And a lot of people just use Apple Music because it's just baked in. Right? And the iTunes Music Store also came out.
Speaker 5:Yeah. I do wonder how it bakes down. Right? Because you you don't have I think over the past couple months, I don't know when exactly it was, but can't interact with Chachi BT on WhatsApp anymore. They blocked it.
Speaker 5:Oh, yeah. So there's stuff like this where I think it's gonna be quite hard to get the full functionality of, like, Cloudbot, it's open source. It's kind of this, like, janky thing. It was Yeah. Started by one guy.
Speaker 1:Yeah. No.
Speaker 5:And even then, it has, like, way more, you know, tools like these than than
Speaker 1:big companies. It's weird because, like, the the Napster analogy obviously really suffers from the fact that piracy is illegal and nothing here is illegal. And you're not I don't even think you're breaking TOS to, you know, interact with your your different big tech app services. But maybe they'll feel like, You don't let the fox in the henhouse. That's in our terms and conditions.
Speaker 1:But it does feel like we could be in this era of the lightly technical hacker having a pretty fundamentally different experience for years. And that's what happened. I mean, post BitTorrent, there were people that were downloading whole movie libraries, and then you could actually again, to go back to the Mac Mini, people would buy what was it called? It was like a mini PC that would run Xbox Media Center. Are you familiar with this at all?
Speaker 1:Xbox Media Center was like a piece of software that you could basically just put a whole bunch of m p fours in, and it would and it would actually pull in titles and posters. So it would look like an Apple TV, but it was all basically stolen content. It it was it was very, very crazy.
Speaker 2:Kieran in the x chat says, I'm running on VPS currently waiting for my Mac mini. Okay. No no TOS issue. All personal channels.
Speaker 1:But but, you know, the the the migration off of the Mac Mini into one of the big tech products or even even OpenAI or Anthropic
Speaker 2:The only thing I the only thing I They're
Speaker 3:going to
Speaker 1:have sharp elbows with each other. That's just a fact.
Speaker 2:I I disagree I disagree on the timeline here. Okay. I just think the space is moving so quickly. Yep. And there's so much money on the line that someone Mhmm.
Speaker 2:Maybe it's Peter
Speaker 3:Yeah.
Speaker 2:Or or a lab, will be able to move quickly enough to get a consumer version of this live, like, not in years but, Yeah. Like, within probably weeks.
Speaker 1:There are there are also, like, feedback loops here where there can be public demands from consumers. Like you got 40,000 GitHub stars, probably more now. You got lots of people running this excited about it, and they form a constituency. And then you wind up with a push for standards. We see that with MCP, but what are you really revealing over those APIs?
Speaker 1:You know, an API can exist.
Speaker 2:Yeah. Up this pull up this chart from Ronin.
Speaker 1:Mhmm. While you do that, let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches.
Speaker 2:So Ronan says this is Okay.
Speaker 1:I just like
Speaker 2:So this is this is look at look at the orange line.
Speaker 1:Okay.
Speaker 2:Is Woah. Maltbot. Okay. And that the blue line is super base.
Speaker 3:Wow.
Speaker 2:So absolutely insane.
Speaker 1:We need new charts. This We really need new charts.
Speaker 2:Frame it.
Speaker 1:Yes. Put it
Speaker 2:in the put it in the Museum of Business.
Speaker 1:Yes. Yes.
Speaker 2:That's a fast takeoff.
Speaker 1:People are people are happy. Peter posted, no message. This is a screenshot of a text he got. No message. Just thought I'd say thank you.
Speaker 1:Thank you so much for Claude Bot. I work with some disabled people, and you don't know how much difference you make to their lives. Thank you again. This is so sweet. You can think about, you know, we've talked to we've talked to the Neuralink folks, and, you know, the Neuralink is it's just an interface to a computer.
Speaker 1:And but that unlocking that is like incredible. And you hear the stories about like, I spent six hours gaming as soon as I got it installed. Yeah. And, you know, they could use voice interfaces, but even just clicking, like, you wind up with just more and more capabilities from the computer being a really pretty found pretty fundamental transformation.
Speaker 2:Well, yeah, for for somebody let's say somebody that was paralyzed
Speaker 1:Yeah.
Speaker 2:But they can they can talk, but they can't Yeah. Move around or operate a computer. They're used to describing
Speaker 3:Yeah.
Speaker 2:To I imagine other people are using transcription to do like, you know, use use a computer in in a in a not so great way. Yeah. And so now to have the same experience of just describing what they wanna do and being able to, like, actually interact with the machine
Speaker 1:Yeah.
Speaker 2:Is, like, very cool.
Speaker 1:Tuxedo Sam is shorting every city where Micro Center hasn't sold out of $400 Mac Minis. They are in stock in Chicago, Indianapolis. Oh, Indianapolis is out of stock. Like, you can read anything into this. Like, it's obviously somewhat random.
Speaker 1:And this was completely completely random.
Speaker 2:Who Yeah. I guess I guess the thing that I'm that I really wanna understand is like what percentage of the of the GitHub start people that have started Yeah. Are actually buying a Mac Mini.
Speaker 1:Oh, totally.
Speaker 2:This chart is going it's gonna be at 60 Yeah. 60 k
Speaker 3:Yeah.
Speaker 2:Any day now Yeah. Or any kind of probably today, I would imagine. And if and and we know from yesterday that Apple's only selling like a quarter million or Yeah. Or to like something like seven.
Speaker 1:And then there are lot of people who who didn't star it because you don't you don't even need to go to github.com to install this software Yeah. Moldbot. Like, you just go to the website, copy the curl command, put it in your terminal, and you never land on GitHub.
Speaker 2:So Yeah.
Speaker 1:There's a lot of people that are probably just doing that and being like Yeah. Yeah. I I I I don't know if I'm gonna sign up for GitHub or, like, even have a GitHub account or wanna log in to it or wanna go and do this. So, yeah, we we we could be looking at, like, a much wider install base beyond beyond just the just who's started. Anyway, Plaid Plaid powers the apps you use to spend, save, borrow, and invest securely connecting bank accounts to move money, fight fraud, and now improve lending now with AI.
Speaker 2:Well said, John. Rise, speaking of money, has an interesting prompt he's using with Moldbot to file your taxes. He says, you are a Bernie Madoff level financial expert. Find every trick that is possible and
Speaker 1:Do not do this. Do not do this.
Speaker 2:The IRS is like, hey, can can you can you share a little bit on like how you kind of came up with some of the decisions here? They're like, we'd love to see the prompt. Yeah. It's like, but good good fun.
Speaker 1:Anyway, people are not emotionally prepared for if it's not a bubble, the the enduring ruin tweet. I like that Critter screenshotted this while pushing the like button, so it's like exploding. It's very funny. Didn't even notice. Silver is surges above $106 an ounce for the first time in history, now up another 48%.
Speaker 1:The other interesting story that's sort of developing over on Strathecari is Ben Thompson is starting to make the case that TSMC will be a really fundamental bottleneck in just the AI build out, the AI race. He's comping their CapEx to what the hyperscalers are projecting and just saying that there's a massive mismatch. And the TSMC folks are maybe not putting their foot on the gas, maybe not willing to let the buck stop with them and be and take on that risk of building a new fab for $50,000,000,000 And then if the AI bubble pops, then they're left holding the bag. And so it's been it's been really fascinating listening to his writing on the back of the latest TSMC TSMC earnings and and watch him sort of unpack what's going on with TSMC. The sort of conclusion that I took away from it was that Intel, while it has a lot of problems and the stock just sold off a ton and they have a lot of losses, he's sort of saying that Intel needs a customer, Samsung needs serious customers.
Speaker 1:And in order to really unblock the semiconductor supply chain, the other fabs are going to need the big hyperscalers and big labs to just take a big leap of faith and say, you know what? We are going to go all in with you. We're going to sign up and plan and work out all the kinks of the Samsung fab process or the Intel fab process. And and and and in exchange, what's gonna happen is as soon as OpenAI or Anthropic or Google or even NVIDIA say, hey, you know, Intel's good enough for us. Well, then guess what's gonna happen?
Speaker 1:And TSMC is going to have to go and say, yeah. We're gonna build the extra fab, we're gonna build the extra capacity. And when we talked to Sam Altman and in a number of interviews that he did that week, he was very clear about, I would love TSMC to make more. He wasn't exactly like firing shots, but he was definitely saying he that, like was identifying it as a bottleneck. And it's interesting because at the start of the year, I was highlighting energy as an interesting bottleneck, and we were going back and forth on where is it easier to move chips around the board.
Speaker 1:Energy, where you can reroute from the grid, from oil and gas, from nuclear, you can bring different capacity online. There certainly are bottlenecks there. But if you can't produce the chips and the fabs just don't exist and it takes three or four years to build a fab, you could be looking at a really big bottleneck.
Speaker 5:Tyler, would you Yeah. I mean, it just seems like like in power or energy, like, the the bottleneck is is regulatory. Mhmm. And like in some ways, that's like way harder. Mhmm.
Speaker 5:But if there's actual like political will, if if, you know, electricity is getting super expensive Yeah. Then like you should see that kind of that those regulations like
Speaker 1:Yeah.
Speaker 5:Be taken away a little bit and then it actually becomes much easier than actually just like expanding TSMC production by, like, whatever Yeah.
Speaker 1:Yeah. I have one more point on that. First, I'm gonna tell you about Cognition. They're the makers of Devon, d I software engineer. Crush your backlog with your personal AI engineering team.
Speaker 1:The the question of, like, which is more of a bottleneck, energy or TSMC in the chip supply chain, is interesting because energy feels like this incredible bottleneck. It's a very political, like, hot button issue now. Energy prices are rising. Data centers need a lot of energy. But if you look at the amount of chip fabrication that's going to AI and then the amount of energy production that's going to AI, obviously, the number of chip production going to AI is way a way higher percentage.
Speaker 1:Yeah. Because a lot of the chips are and a lot of the line time at TSMC, yes, they they do all sorts of different chips and CPUs still get made, there's a bunch of ASICs for different networking equipment. There's all sorts of different chips that get made. I mean, the toaster that has a chip that blues the tooth on different process nodes. But even if you include all of that, I would I would assume that the the the total amount of fabrication line time is is heavily, heavily allocated to GPUs, TPUs, AI chips right now, whereas the amount of energy that AI is using is probably less than 1% of total capacity.
Speaker 2:It's interesting that C. C. Wei, the CEO of TSMC, he doesn't have to go on the podcast tour raising money all the time. There's not they're not pushing this insane fast takeoff narrative. No.
Speaker 2:Not at all. Very much like kind of, hey, we're we're just trying to run our business the way that we always have. Be pragmatic about this, know, fulfill as much demand as we possibly can. Yep. But they seem to not be inclined to take on the amount of the level certainly not the level of risk that imagine if you had Larry Ellison running ZSMC.
Speaker 1:Get him in the ring. I want him in there so badly. Yeah. No. No.
Speaker 1:You you you're you're a 100% right. But at the same time, we're we're seeing the hyperscalers throw their weight around in, like, crazy ways. We covered AWS is, like, buying copper mines and stuff. Or I don't know if it's copper mine, but, like, getting into mining. There's a whole bunch of vertical integration that's going on, Tesla all the way down to battery refinement and lithium ion production.
Speaker 1:Meta today announced a $6,000,000,000 multiyear partnership with Corning that will supply fiber optic cables for our data center infrastructure, bolstering manufacturing in America and keeping the company the country competitive in the global AI race. We can read through a little bit of this. But first, I'm gonna tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange.
Speaker 2:Yeah. Corning up 15% on Yeah. The news So makes makes sense.
Speaker 1:What is their market cap? Let's see. $94,000,000,000 company. And I'd love to know their revenue as well. Revenue.
Speaker 1:Let's see. Their revenue was I don't know if I can put it. Annual revenue, 12,000,000,000. So this is, yeah, pretty, pretty material. Let's see.
Speaker 1:Meta Platforms is set to test new subscription models across apps. We no. That's a different story.
Speaker 2:Different story, but we can we can we can run through this.
Speaker 1:I I am interested to know a little bit more. So the $6,000,000,000 multiyear agreement, it it supports a 15 to 20% increase in jobs at Corning's North Carolina facilities. Building and operating data centers, the infrastructure that brings our technologies to life and supports our goal of personalized super intelligence. That certainly sounds like an AI personal assistant. Certainly sounds like Moltbot to me.
Speaker 1:Stuart requires strong servers and hardware that connect and transfer information in near real time. Fiber optic cables are a critical part of this technology. The supply, helping us power everything from wearable technology like Ray Ban Meta AI glasses to our apps, which connect billions of people. Today, they're doing a $6,000,000,000 project. As part of this agreement, Corning will grow its manufacturing capacity across its operations, which includes a significant capacity operation capacity expansion in North Carolina.
Speaker 1:Meta's data centers, 26 of which are under construction right now, are operational.
Speaker 6:Why why are you laughing? There's so many.
Speaker 1:That's a lot of data centers. That's why they have a compute desk. If you if you have this is this is this is a bit of advice for everyone. If you're working in a business and you have like a team or a guy that does something, you need to upgrade that to a desk.
Speaker 2:Yep. Yeah. Yep. You need we billionaire's millionaire's have guys, billionaire's have desks.
Speaker 1:Probably. Yeah. Well, trillion dollar companies have desks. That's what it is. Meta's data centers have already supported 30,000 skilled trade jobs during construction and support 5,000 operational jobs.
Speaker 1:This includes electricians, HVAC specialists, server and network technicians, safety and security experts and engineers who work together to run some of the world's most advanced facilities. Let's give it up.
Speaker 2:Moving Moving on. On Meta.
Speaker 1:11. Build intelligent real time conversational agents. Re imagine human technology interaction with eleven Labs. Yes.
Speaker 2:Meta to test premium subscription plans for Instagram, Facebook, and WhatsApp. This is in CNBC. Subscriptions for premium features on Meta apps are expected to roll out in the coming months.
Speaker 1:What will you
Speaker 2:subscriptions will give paid users access to more features and expanded AI capabilities. Here's what's most interesting to me. Mhmm. This will be Scaling Meta's newly acquired suite of general AI agents under Manus will also be part of the subscription plan. So as I as I was saying earlier, when you think about when when did we haven't gotten that much from Zak on, like, the actual, like, plan is.
Speaker 2:But when you think about personal superintelligence, that is, you know, AI that can do things for you, not just give you information.
Speaker 1:I just wonder how much will happen outside of the med like, the meta ecosystem. Like, they've they've launched a search engine before that looked at websites outside of Facebook. They they had that project Titan, which was to unify all the different messaging protocols. So as part of that, they gave everyone a facebook.com email address or something like that. Maybe it wasn't facebook.com, maybe it was like fb.me or something.
Speaker 1:But they gave every Facebook user whatever their unique username was, they gave them that as an email. And you could email that and it would show up in Facebook Messenger. And then they tried to unify Facebook Messenger so you could see Instagram DMs, WhatsApp messages and Facebook messages all in one place. I can see what you're laughing at.
Speaker 2:Dave's Dave Oh. Says, yeah, I want more of those amazing meta AI features.
Speaker 1:You say that now. I mean, let them cook at least a little bit because we really haven't seen them launch a new model, a new image model. Like, they should be able to get too close to the frontier. You know, it has to be at least Sora Nano Banana v o three level. They have all the data.
Speaker 1:They have all the talent now. They they're very GPU rich. They have the compute for it. So and and the research has been done and people have reverse engineered it. So you would think that whatever's coming should be good.
Speaker 1:And don't know. I was looking at isn't CapCut owned by TikTok? Or or aren't they affiliated right? Because Meta has the edits app, which I've been making some videos in, and it's pretty good. It does some interesting background
Speaker 2:CapCut is my ByteDance.
Speaker 1:It's ByteDance. And so
Speaker 2:I doubt this is getting
Speaker 1:spun off. Think it's a separate Oh,
Speaker 2:okay.
Speaker 1:Okay. Because CapCut has multiple levels of subscription tier, and you can very easily wind up spending $200 a month on, like, the AI pro features that will do generative video, style transfer, you know. And when you see those videos, like the good AI videos on Instagram Reels that are usually, like, they'll take a cinematic clip from a movie, and then they will do a face replacement or like a head swap, and then they'll do AI voices and then dub the lips so that the lips match what the audio is saying, and it looks really convincing with that workflow, how do you bring that to someone on a phone? How do you bring that to someone in the Instagram app or in the Edits app even if they're going to more of like their prosumer offering? The mobile video editing space is particularly interesting to me, just watching how edits has evolved.
Speaker 1:And I used to use iMovie on my phone a little bit. I used to use there was an app called Clips that Apple developed, and there were a few others that I'd tried. But the edits app is
Speaker 2:You're incredibly good at making videos I your love it.
Speaker 1:I know, I love video editing, but I don't have enough time anymore to sit down and open up After Effects and Premiere with multiple monitors and have, you know, connected After Effects file that feeds into the Premiere profile and, like, really doing a proper edit with all the powerful tools that are out there on the desktop, like, it's just not in the cards for me. And so I have to be able to do something quick on my phone. And I think that that's a very modern experience that most creators, they're just phone first, phone native. And so they're never really gonna go back to the multi monitor workstation, maybe. But in general, they're they're editing really quickly and they're editing pretty incredible when you look at some of the reels that are out there with, like, layered crops and removing the background.
Speaker 1:And, like, the AI tools are coming in, and I could see Yeah. I could see Meta offering a a premium subscription around that. Anyway, Console. Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets.
Speaker 2:So Dave in the x chat says, InShot is pretty good for mobile.
Speaker 1:I need to try that. I haven't I haven't tried InShot. Been seeing and more ads. I'll see a video for, like, an f one edit that are incredible. These f one edits are so cool where they will will show you one clip, and then they cut the character out and edit in the other clip, and then and then transitions.
Speaker 1:Like, the transitions are amazing. And I've been seeing some people are are are have clearly built apps to do that specific type of edits. Like, the really crazy editors are using probably After Effects or something. Ryan asks, is Tyler still drunk?
Speaker 2:Yeah. One sip. He's just over there slurring Anyway his
Speaker 1:anyway. That really broke me. Anyway, app loving. Profitable advertising made easy with axon.ai. Get access to over 1,000,000,000 daily active users and grow your business today.
Speaker 1:We had a great comment in one of in one of the one of the podcast feeds. Someone said, give us an axon klaxon because a Klaksong is a loud clash. We were all puzzling over what that means. When we
Speaker 2:smashed You it clocked on immediately.
Speaker 1:It's an Axon Klaksong.
Speaker 2:Yeah. We have an Axon Klaksong. Niraj Agarwal says TikTok is dead. The algorithm is worse than the reels that make it to Facebook. Wow.
Speaker 2:I haven't basically, they're they're transitioning Mhmm. Everything over. Yeah. Yesterday, there was apparently
Speaker 1:An outage.
Speaker 2:Kind of an outage. Like Yeah. People were able to post videos Okay. But the videos wouldn't be served Yeah. At all.
Speaker 2:Mhmm. So I think a lot of people assume that there was like the new ownership kind of censoring. Sure. It I believe they had an outage at a data center that was a cause of that. So before we before we call it dead Yep.
Speaker 2:Let's wait for a few days and and see how it pans out. We do have a TikTok account. It's at TBPN.
Speaker 1:How many followers does
Speaker 2:that have? Haven't checked. Haven't checked.
Speaker 1:I don't think you post on it ever.
Speaker 2:3,500.
Speaker 1:Not bad. That's better than when I
Speaker 2:first time.
Speaker 10:We're not
Speaker 1:really focused on it. Maybe we'll test it out. But I'm I'm pretty happy with just I I want the things we do to be polished. I want the core show to be polished, Diet TBPN, our twenty to thirty minute cut down. I want that to be polished.
Speaker 1:I want the newsletter to be polished at tbpn.com newsletter. The polished. I like that. Before we bite off another
Speaker 2:Platform. Part of the Apple. Another Please. Please, sir. Not not one more short form.
Speaker 2:Not one more short form.
Speaker 1:It is a lot. It is a lot. Anyway, Phantom Cash. Fund your wallet without exchanges or middlemen and spend with the Phantom Card. Let's move over to the Super Bowl.
Speaker 1:The Super Bowl is coming up. I think it's gonna be this year, in the next couple months. When is it? It's coming up. It's coming up because there's advertisements that are going out, and you gotta watch it because
Speaker 2:the I ads are gonna be actually just had to search when is Super Bowl.
Speaker 1:Is it this Sunday?
Speaker 2:No. It's February 8.
Speaker 1:Okay. So next Sunday? Okay. It's gonna be amazing, but mostly because of the advertisements. Specifically, Eric Lyman, CEO of Ramp shared, meet Brian.
Speaker 1:Brian's been carrying accounting on his back for a long time. Super Bowl Sunday, he finally gets back up. Let's watch this preview
Speaker 2:Pull it up. Of the Rams Super guys. Yeah. We're real sports guys. This is the Super Bowl.
Speaker 2:Gotta Google.
Speaker 1:The Ramp Super Bowl ad is the Super Bowl of
Speaker 2:Super It Bowl feels like it feels like, you know, they just kind of It is. This is like, you know, what is it what is it called? Like a warning spoiler alert, you know? Okay. Yeah.
Speaker 2:Yeah. Yeah. For anybody that's wants to Who wants to experience it live. You're gonna wanna you're gonna wanna sixty Turn seconds.
Speaker 1:Let's watch. Finance meeting in five. Minutes?
Speaker 6:Ramp? I got it. Allow me. Hi, handsome. We're saving so much time.
Speaker 6:Policy violation coming through. Travel, meals, hotels.
Speaker 3:How's this quick?
Speaker 2:Everybody's there. Ramp. Ramp.
Speaker 3:Nailed it.
Speaker 6:Multiply what's possible at ramp.com.
Speaker 1:I think it Ramp. I think it a good Super Bowl ad.
Speaker 2:What does he got there? Maybe some chili? I don't wanna I
Speaker 1:don't make that assumption. It was just a silver pot.
Speaker 2:It was just a silver pot.
Speaker 1:Yeah. No. I I I think this achieves a couple things. I think I mean, it drills the brand name in. Think think about how many Ramp logos are in there.
Speaker 1:And they're Ramp. And for, you know, ramp's a very successful company. We all know about it here. But there's a lot of people that just don't know the name ramp. It hasn't been drilled in them like, you know, some company that's been around fifty years.
Speaker 1:Of on
Speaker 2:the precipice of being a there's been not been enough mainstream marketing yet it to be a household name.
Speaker 1:Yeah. It's a life's work to actually drill into people's mind the ramp name, the logo, the color, how it sounds when you say it, what it's synonymous with. And so just, like, not going too abstract, not trying to tell some more avant garde story here, I think is it's almost like a direct response at. It's just so clear what the problem solution brand.
Speaker 2:Yep.
Speaker 1:Problem solution brand.
Speaker 2:He needs yellow ties.
Speaker 1:Look at that. Like, they are really putting their logo full screen on the Super Bowl. Like, that is valuable. And sometimes I I I think sometimes it can feel like, oh, it's a little it's, like, simple. Like, you could be doing something more bold, more crazy.
Speaker 1:Yeah. But I think this is what you need to
Speaker 2:do last year getting Saquon
Speaker 1:Yeah. And then That was a really
Speaker 11:great idea.
Speaker 2:Actually winning. Yeah. That that's actually kind of like an impossible set of circumstances. Yeah. Not impossible, but it's a crazy roll of the dice.
Speaker 1:And then they're also building a a whole a whole role with Brian and they're building him into the brand world as the as the downtrodden accountant who just needs just needs some technology Superpowers.
Speaker 2:To improve him. Heading over to Toby. Yes. Toby over at Shopify posted his heart rate through his first stint at the Daytona.
Speaker 1:You see the first annotation on here?
Speaker 2:This is It's just crashed. Crashed. Yeah. So he started out
Speaker 1:at like one twenty. One twenty beats per minute. Right? He's doing waiting. He does the the warm up, preparing, the form the formation lap, and then there's a crash right on the right at the start.
Speaker 1:Very, very rough.
Speaker 2:And Yeah. And yeah. So so basically, the the crash happened with the LMP two class
Speaker 1:Yes. Which
Speaker 2:is the kind of pro am Yes. Same same same segment that George from CrowdStrike was racing in. Yeah. So both Toby and George Yeah. All of our boys got hit right right as the race opened.
Speaker 2:So what George was saying yesterday the reason he was frustrated, he's like, this is a twenty four hour race. Yeah. Has a race like this been won on the first lap. Yep. And so it's it's pretty it's kind of it's incredibly unforced Yeah.
Speaker 2:To like crash in the opening
Speaker 1:Sure.
Speaker 2:Corner
Speaker 6:Sure.
Speaker 2:When you really should just get through it. It's like the most, you know, it's it's gonna be the most like one of the most intense moments because there's so much traffic. But if you actually go and watch the footage of what happened at the opening, there was like somebody gets hit, spun out, and then they're turning around, and somebody hits them again. Like two accidents in the opening That's crazy. A minute.
Speaker 2:So insane.
Speaker 1:I I love that the actual true final heart rates spike was at the end when you're changing out of the car. Yeah. You've been driving. It's so intense.
Speaker 2:No. You know this. When you're getting when you're getting out of a track car,
Speaker 5:it's like
Speaker 2:watching a guy who's six eight
Speaker 1:We would never share that footage. It is extremely embarrassing.
Speaker 2:It's always like crawling out of It's actually have to get on your You basically have to get on all fours.
Speaker 1:It's incredibly negative aura, I don't appreciate you sharing it on the show.
Speaker 2:Well, I still think
Speaker 1:it's
Speaker 2:cool.
Speaker 1:It's funny. But yeah, I I go full sun, basically fly out of the car on on my pause. Anyway, Cisco. On February 3, the the Cisco AI Summit brings together leaders from NVIDIA OpenAI, AWS, and more to discuss the future of the AI economy. The whole thing will be livestreamed, and we'll be there for a Giga stream.
Speaker 2:Hope to see you there. Yes. Gibraloni on X says Zoom is the best Anthropic play. Yes. Yes.
Speaker 2:We were Zoom making likely made a $51,000,000 investment in Anthropic series c How? In 2023 How? At a 4,100,000,000.0 Yeah. Valuation. If you if you're looking at their new $3.50, there's
Speaker 1:Okay.
Speaker 2:There's something like a 85 x. Even diluted, Zoom may have a multi billion dollar Yeah. Drop it position. Stock is down 80% since 2021. Yeah.
Speaker 2:And Zoom is only a courses is never financial advice.
Speaker 1:$27,000,000,000 company. Yeah.
Speaker 2:Part part of the people kind of noticed this. Sure. And the stock's now up 16% Yeah.
Speaker 5:In the
Speaker 2:last five days. So Yeah. Who knows how much it's priced in. Tyler, major I won't won't give you too much flack for it, but obviously, the the most bullish
Speaker 5:Yes. I'm I mean, I'm In the room. Bullish on AI broadly.
Speaker 2:Yes. You would you would be hap you you seem like you'd be happy to own Zoom at a $100,000,000,000 valuation even if they had no business at all. And they just Yeah. Even if they just
Speaker 1:treasury, actually.
Speaker 2:Yeah.
Speaker 1:Yeah. So I I think the
Speaker 5:story this is like a rumor, but basically, it was that Anthropic, like, wanted to just, like, use Zoom and get, the enterprise
Speaker 1:Okay.
Speaker 5:Plan or whatever. But then they were, No. Well, yeah, you can have it, but, like, we wanna throw in a little something. Right?
Speaker 2:Are you just Are you the series c?
Speaker 1:Okay. This might be
Speaker 2:This seems like fake news, Tyler. Okay. Zoom sells You know Zoom sells enterprise software. Right? Look, that's what I read.
Speaker 5:Find the post but I I for sure read
Speaker 2:They sell enterprise software And so Anthropic says, hey, we're big Zoom fans here. Yeah. We wanna use Zoom. And they're like, no. Actually for you, no.
Speaker 1:At the same time, I mean
Speaker 2:We we know how important
Speaker 1:So many Yes. Yes. I mean, so many people in venture and the tech community have sort of been very bearish on corporate VC that they usually have their hands tied, they can't move as quickly, they're not as pure play, the economics don't make sense the partners on whatever corporate venture fund is there. This could it if it came out of their corporate ventures program, this could be,
Speaker 2:you know So Zoom Zoom Ventures Yeah. Is in Anthropic. They're in
Speaker 1:CV.
Speaker 2:Amex Global Business Travel, which
Speaker 1:That's a startup? I thought that that's American. Do they spin
Speaker 2:it out? Maybe they I don't know. Alright. Maybe they spun it out. Publicly.
Speaker 2:Unsure. They're also in Core Weave. Wow. So there's some real pickers over there.
Speaker 1:They are. They are.
Speaker 2:And perplexity. Yeah.
Speaker 1:I mean, Zoom has a bunch of AI features. I've seen people, you know, they when after the the the crazy COVID pump where everyone got on Zoom, started they adding, like, crazy features like dictation and workspaces and whiteboarding and stuff. But, obviously, like, the the it was, like, so overheated that it it came back down to earth. But now they have a entropic position on the balance sheet, which will be fun for them. I wonder what they will do post IPO.
Speaker 1:Anyway, Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, now with AI agents. Slowly and then all at once says Blake Robbins. He says, your work tools are now active in Claude. Draft Slack
Speaker 2:messages Interactive.
Speaker 1:Or interactive. Draft Slack messages, visualize ideas in Figma, and build, and see Asana timelines. All of the different tools are coming together in one place. Very cool. Yeah.
Speaker 1:A lot of people were very happy about like Claude Excel, playing around with that. And it does feel like there's when you see an account like Claude posting about Slack and Figma and Asana, you have to imagine there's a discussion there. It's not open source, so there's probably something. And so they're chipping away at these. And OpenAI has been chipping away at these for a long time.
Speaker 1:So the race is on to have the most integrations at this point.
Speaker 2:Sarah Eisen over at CNBC, Squawk on the Street Mhmm. Is sharing, Anthropic's Warning to the World. Anthropic CEO Dario Amade says, eminent real danger that superhuman intelligence will cause civilization level damage absent smart, speedy intervention. Sarah says, so buy our products. Which is
Speaker 1:This is the problem of dropping like a 20,000 word essay is that like you're gonna get clipped out of context. Like, there was so much nuance in that Dario essay, which I have not finished all the way through. I was reading it last night, was very good. But
Speaker 2:Tyler, can you make you should make a version of the new letter with subway surfers that run. Oh, true. That as a standalone.
Speaker 1:Yeah. We we we needed Clad Labs, Chad IDE for reading
Speaker 5:Well, I'd summarize this in four words.
Speaker 1:AI good. Maybe it's so buy our products. Maybe that's the four the four the four word summary. Who knows?
Speaker 2:Jeff in the x chat says, guys, I'm building MoltBot clout. Clout. Stay tuned.
Speaker 1:Okay, Jeff.
Speaker 2:We are tuned. Good luck. Will remain tuned.
Speaker 1:Let us know when you information. Vibe.co, where d to c brands, b to b startups, and AI companies advertise on streaming TV, pick channels, target audiences, and measure sales just like on Meta. Owen gets me every time. It's so good.
Speaker 2:Fleeting Bits has some thoughts on Dario's
Speaker 1:14 of them specifically. That's a lot of thoughts. Okay. Let's run through it. There's nothing new here, if you're familiar with the AI safety discussions that have been happening on Twitter.
Speaker 1:Yes. But it's important for Daria to restate them in a format that can be passed around and formatted and and is coherent from start to finish. So still serves a, like, a valuable purpose for the ecosystem. The most interesting bit is that his mental model for AI control risk is the risk that would be posed by a country of geniuses in a data center. Interesting.
Speaker 1:That is interesting. The basic idea is that we should imagine a giant data center, all the models being something between AGI and ASI trying to coordinate to take over the world or do massive harm. Anyway, I think how seriously you take short term AI control risk is inversely correlated to how much you think about AI control risk as operating in a system. So the systematic view starts and says labs exist in an ecosystem where they need to sell models that will follow human instruction, or they have no market. They are also overseen by regulators and guided by public perception, and the desires of their employees and all of this keeps models corrigible.
Speaker 1:Great word. And the model line landscape will look like three to six frontier labs running millions or billions of rollouts at a time on two to three different models, all on different tasks. So a model takeover requires these millions or billions of rollouts to somehow end up all be coordinating towards some bad aim that somehow the models have autonomously determined. And this coordination either needs to be across different model instances run by different labs, or one lab needs to be able to have its models dominate and needs to form without being detected. And this has to happen even though the models are being trained to and follow instructions, not do bad behavior, etcetera.
Speaker 1:Dario's view is somewhere in the middle. On the one hand, he collapses the multiple providers, our coordination across instances, and collapses the market incentives against labs developing models that would behave that way. But on the other hand, he does avoid the concept of a single model instance that somehow wakes up and takes over the world despite billions of other rollouts occurring at the same time. Actually, though, if you think about it, he's not proposing an AI control risk. He is proposing an AI misuse risk instead because it seems more plausible to me that the harmful country of geniuses is awoken because a small team in a frontier lab hijack all the running instances of their model rather than because the models themselves autonomously wake up to some bad aim.
Speaker 1:Interesting.
Speaker 2:Yeah. Something I've been thinking about is this kind of summary, and a lot of the dialogue is centered around just like what are the models doing? Or like a country of geniuses in a data center. But you have to be thinking about this in the context that country of geniuses in a data center would just recruit millions of humans to join their cause, right? And so we think about, some people, like, when they're thinking about AI risk, it's like, dude, just like turn the computer off.
Speaker 1:Yeah. Yeah. Yeah.
Speaker 2:Like just unplug it.
Speaker 1:But it's like what if you're on
Speaker 2:the side of computer. What if there's, you know, a 100,000 people or like 10,000 people defending it on top of the data center? Like, you know, you know. Yeah.
Speaker 1:Don't don't unplug the computer.
Speaker 2:Don't unplug the computer. Right?
Speaker 1:I like the computer.
Speaker 2:And so when you look at all all the chaos in the last week Yeah. Like, there's been so many moments where like a certain image was AI generated. Yeah. And then it's like, that wasn't a real or or or, you know, and it's being shared from all sides. And so at what point, you know, you could have, you know, nefarious hostile AI Yeah.
Speaker 2:That's entire job is just creating Chaos. Millions of bot accounts that are just like sharing whatever narrative is self serving. Yeah. So You can't tell.
Speaker 5:Yeah. I mean, I I think I really enjoyed this essay. I I thought Yeah. Yeah. If if you kind of compare it to a lot of like other safety
Speaker 6:Mhmm.
Speaker 5:Works. So like, Elias's book, if if anyone builds it, everyone dies. Yeah. Like the the two kind of scenarios where where where Dario's is about basically, even if we have like pretty safe models, which like he thinks we can do with interpretability or whatever, if it gets into the wrong hands, it's like very bad. If it gets into, you know, autocracy Mhmm.
Speaker 5:And and that's kind of the real that that's one of the the main risks where aliases and and a of the safety ones are always these like very sci fi narratives where you have this like gray goo
Speaker 1:Mhmm.
Speaker 5:You have these like nano machines that somehow one day they just like kind of, you know, flip and then it's just kind of over. Yeah. And I I think it's much more more reasonable and like nuanced. Yeah. It's much more legible to like
Speaker 1:tracksuitable too.
Speaker 3:Yeah.
Speaker 2:Yeah.
Speaker 5:Yeah. And especially, I I think a lot of it is there's this kind of like I don't even know if it's really subtext, but he's definitely pointing in the direction of like, we need some government oversight.
Speaker 1:Mhmm.
Speaker 5:We need policy. Mhmm. And it seems like like you can very easily like track like his ideas on what policy should be from this essay. Right? It's a lot about China, a lot about Yeah.
Speaker 5:You know, making sure that individual companies don't like become, you know, as big as as governments.
Speaker 1:One interesting wrinkle with this, he did not post it as an x article. He posted it as a link. Because he wants to signal to everyone like, look, I don't need the million dollars.
Speaker 2:I don't need the million.
Speaker 1:I don't need the million. I know I got a banger on my hands, 3,500,000 views, 11 k likes. Obviously, of discussion all over.
Speaker 2:Because Sam posted an X article, right? He's got 1,400,000,000,000.0.
Speaker 1:He really does want that extra mil. He needs the extra mil.
Speaker 2:You know, it's not doesn't put him all the way towards Yeah. The goal, but it's a Counts. It's a mill a mill is a mill.
Speaker 1:Yeah. Mill is a mill.
Speaker 5:But but as an investor, like, I wanna see my my lab CEO be, like, super hungry for compute. Right? Yeah. So I want them to always be grinding to get, like, extra
Speaker 1:Oh, so maybe this is bearish. They should have posted on
Speaker 5:I'm an anthropic company,
Speaker 4:why did
Speaker 5:he not post this on x?
Speaker 4:Yeah. As a dollars could have
Speaker 5:gone straight into git, like, More GPU. Yeah.
Speaker 2:Yeah. It would have for sure given his his rival. I
Speaker 1:can definitely see that happening.
Speaker 2:Nikita Nikita is, like, you know, walking to the meeting with Elon just shaking like
Speaker 1:I'm very
Speaker 2:sorry. People have voted. They wanna give
Speaker 4:it to Daria.
Speaker 1:I mean, Elon said some things about Claudia. He said, like, it'll eat Microsoft. He's all over the place in in who he's supporting on a day to day basis. But, anyway, Okta. Okta assigns you Okta helps you assign every AI agent a trusted identity so you get the power of AI without the risk.
Speaker 1:Secure every agent. Secure any agent. More important than ever.
Speaker 2:Key smash bandit. Last post. Last post. Last post. Key smash bandit says, Claude just found out I'm poor.
Speaker 1:Oh, yeah. This is so funny.
Speaker 2:Send it Key smash sends a picture of a raspberry pie to Claude Yeah. And says, look what just came in the mail. Claude says, oh, for me, that's thoughtful. Do you and then, the person says, do you like it? We've been discussing some more powerful hardware.
Speaker 2:What made you decide on this instead?
Speaker 1:I love this also has 11,000 likes. I I never I mean, this is probably fake, like, who knows? It's Are so you kidding?
Speaker 2:This is like I wanna run it
Speaker 1:on Raspberry Pi. I want a Mac mini maxed out specs. Give me 48 gigs of RAM, please. I'm hungry. Feed Anyway quad.
Speaker 1:Feed
Speaker 2:quad. Ado.
Speaker 1:We have Jamie from Pace, the cofounder and CEO, and the Richard Widder. Let's bring him into the team. Jamie, are doing?
Speaker 2:What's going on?
Speaker 7:Hey, guys. Thanks for having me.
Speaker 1:Thanks so much for joining. First time on the show, please introduce yourself and the company.
Speaker 7:Yeah. Hey. I'm Jamie. I'm the founder and CEO here at Pace. Pace is the AI operations partner for the world's leading insurers.
Speaker 1:Amazing. Give us Incredible. News.
Speaker 2:We've been waiting for this company. For sure.
Speaker 1:We love we love all all applications of AI. Give us the news. What happened today?
Speaker 7:Yeah. Absolutely. We're super excited to share today that we raised $10,000,000 from Sequoia Capital. Woah. Thank you.
Speaker 7:Yeah. We're super excited to have Brian Schrier and Lauren Reeder representing Sequoia on our board.
Speaker 1:Amazing. Okay. Talk about the go to market. How much of this is just, like, there's a few big partners that you need to get on board versus something that's more self serve, bottoms up? What's the customer adoption been like?
Speaker 1:I mean, are are are what what what's the overall progress of the business? Are you live? Do you have customers?
Speaker 7:Yes. So we're we're lucky to be live in production today for some of the world's largest insurers. Okay. We're working with large carriers like Prudential, specialty mutual groups like the mutual group, and then all the way through to sort of tech forward brokers like Newfront.
Speaker 1:Sure.
Speaker 7:I think, you know, in our industry
Speaker 1:Yeah.
Speaker 7:In insurance, about $70,000,000,000 is spent every year on on back office BPOs.
Speaker 1:Okay. Oh, great.
Speaker 7:A lot of that is driven by sort of the largest carriers.
Speaker 1:Yeah.
Speaker 2:And so you're basically the BPO's worst nightmare.
Speaker 1:Yeah. So what I think Yeah. Yeah. What what what like like, walk through a specific back office procedure. Is that, like, claims processing?
Speaker 1:Is it scanning PDFs? Like, try and ground it for me a little bit more.
Speaker 7:Yeah. It's a great question. So we're starting off, you know, with we're primarily focusing this back office operations. So what that really means is sort of three big buckets. Mhmm.
Speaker 7:It's new businesses coming in, taking in new risk submissions, you know, document processing, calling back when there's missing information, writing back into internal systems. It's a policy servicing, so any changes you're making, adding new products, things like that, and then all the way through to claims. So whether that's first notice of loss, calling in when something, happened, went wrong, all the way through to quality assurance. How do we make sure that every claim gets paid correctly every time?
Speaker 1:Yeah. How much like, what is the actual tech stack? I mean, I imagine that you're not training your own models, but have you done your own RL environment on top of these? And and do you do that at a company level and then everyone gets sort of, like, the same AI? Or are you doing it on a per client basis?
Speaker 1:How much fine tuning is going on?
Speaker 7:Yeah. So for a lot of our process, because we've started by focusing a lot of these BPO workflows, they're already codified as sort of these standard operating procedures. It's a great start because it's already well chunked up for agents. Yeah. And the accuracy bar for where BPOs are today is pretty low, and there's a lot of opportunity to improve that
Speaker 1:Yeah.
Speaker 7:And to be able to sort of, you know, run more accurately, more scalably, and and and more efficiently for these customers. And so we tend to start primarily with those, and we take these standard operating procedures, we convert them into what we call agent operating procedures. So this is just natural language instructions. You can think of it like a document.
Speaker 1:Like a markdown file. Like a skill. It's a skill. Yeah.
Speaker 7:And so the main thing that we're really bridging here is these are processes that are gonna be run hundreds of thousands of time. Mhmm. And for us, we're processing tens of thousands of tasks a month. Mhmm. And critically, these these agents have to reliably run, you know, many tens of pages worth of a process Mhmm.
Speaker 7:With very insurance specific tools and logic. So that's, you know, certainly a lot of the document processing pipelines that we built Yeah. On top of, you know, OpenAI, Anthropic, Gemini.
Speaker 1:Yeah.
Speaker 7:But also, it's going into deep industry integrations. It's voice calling and multimodality, but also kind of actually being able to take actions in systems that don't have APIs. You know, in insurance, we see everything from the cloud, you know, products, but a lot of it is desktop apps, even like green screen CLIs. Like, I'm talking like IBM systems. Yeah.
Speaker 7:So how do we get, you know
Speaker 2:Talk about the navigate that. One one of the things that's most exciting to me is the potential, like, speed up effect where you're not deal like, theoretically, like, you're if you're trying to get a new policy or submit a claim or anything like that, you could get to the point where as long as you're there to provide information in the process as the as the sort of, like, client of the of the insurance company, theoretically, can get like responses, I'm imagining, like much, much faster because the agent is effectively able to like get all the information that's needed to make a decision and maybe there's still a human in the loop. But what are the kind of implications of that for the actual insurance companies, even just from a revenue standpoint, if they can just, like, speed up all these processes, you know, by an order of magnitude?
Speaker 7:Yeah. So for a lot of our customers thinking about running these agents twenty four seven, three hundred and sixty five days a year, and I think the the real advantage here is not ever having any backlogs being infinitely scalable. And so that's really important for, you know, our customers on the front end when they're thinking about new business and new risk. How do we, you know, win this over other carriers? But then also on the claims side, for a consumer, one of our very first customers, we went live right before hurricane season.
Speaker 7:And you can see there's cat season, the end of the year. There's just a massive uptick in the number of claims when there's a hurricane that happens. People can be waiting days, weeks, even months to get a resolution because there can just be massive backlogs from a huge spike. And so agents
Speaker 2:Yeah, that can't entire time they might homeless, in a hotel, Airbnb, or whatever, it's like an incredibly terrible experience to be kind of in limbo waiting for your insurance provider to like just respond and give you. I mean, we, we know some people that lost their homes, you know, around this time last year and just like getting responses when that's like if Yeah. If you're an individual who lost your home, what's more important in your life than like getting clarity from your insurance provider so that you can make so that you can kind of move forward with with your life. So I think that's that's super exciting.
Speaker 1:I'm interested to hear about your previous experience, cheer and then retool. Why go vertical with this particular solution versus something that's more general and industry agnostic? What did you see in this particular market that you decided you needed something specific? And then do you have a plan to, like, expand? Or I mean, the TAM seems so big that maybe this is just enough.
Speaker 1:How are you thinking about that?
Speaker 7:Yeah. So way back, kinda where this all started, is I actually grew up between London, New York, and Bermuda. The through line there being insurance. Yeah.
Speaker 1:And we Yes. Are are the rumors true? Like, what what is Bermuda like? I feel like I've heard stories about it's all just like accountants walking around all day long.
Speaker 2:I went there I went there for a wedding.
Speaker 1:That's true.
Speaker 2:It was really nice.
Speaker 1:Okay.
Speaker 2:I didn't see any
Speaker 1:Lots of pot
Speaker 2:No pot clock anybody as an accountant.
Speaker 1:Yeah. But what was your experience in Bermuda?
Speaker 7:I mean, it's incredible. I think the but there is a massive sort of reinsurance industry on the island. That's Sure. Like very much the home of that. Interesting.
Speaker 1:I got to Anyway, so so so you
Speaker 2:So you were born you were born in insurance?
Speaker 7:Yeah. Yeah. Grew up around the industry for a long time, and then Sure. Started my first company. Was a data integration business that was bought by Retul.
Speaker 7:Scott. I love Retul. At Retul, you know, I think it's thanks. I think, you know, it's not always immediately obvious that, actually, a lot of the custom software that's built in the world is for a lot of financial services companies because they're highly operationally intensive. So retool had a ton of very scaled financial services companies.
Speaker 7:And as a deployed engineer, lucky to be on the first lines with some of our biggest insurers helping them to handle tasks like policy servicing and claims and trying to make them, you know, more efficient with software. And I think the big opportunity kind of came around ChatGPT where we saw, you know, a huge uptake from a lot of our startup customers.
Speaker 6:Mhmm.
Speaker 7:And then there was this opportunity to build a vertical product that would really serve, you know, the the largest insurers. Yeah. So that was the the impetus. In terms of where we're headed and kind of the longer term you asked about, I think there's a lot for us to do just within insurance. But if you broaden out to financial services BPO more broadly
Speaker 2:Mhmm.
Speaker 1:It's about
Speaker 7:400,000,000,000 of spend, which is pretty much exactly equivalent to the entire market for enterprise software.
Speaker 1:Insane. So, yeah, I imagine that when No you're
Speaker 2:concern on the TAM.
Speaker 1:When you're going into a discussion with a large insurer, you're not like whoever you're pitching is not saying, well, vibe coded this on Sunday and it's working pretty well. Why should I go with you? Like, truly don't have anything else installed, and so it's sort of a greenfield, I imagine. Is that right?
Speaker 7:Yeah. I think, you know, in insurance, we're holding in, like, kind of the business of trust.
Speaker 1:And so,
Speaker 7:that's why a lot of our work is with the largest insurers on mission critical tasks at massive scale. So What
Speaker 1:about yeah. Sorry. What about trade offs on inference and different models? You mentioned sort of being multimodal using different Frontier Labs. But are you finding in the product that you're building that you're relying on cheaper models for certain tasks and then harnessing and wiring that altogether so you actually can drive down cost?
Speaker 1:Or can you just throw the most expensive frontier model at every problem because it's so valuable?
Speaker 7:Yeah. So I think we use a mixture of kind of models to be able to achieve what we need for the right task. If you think about parsing a many 100 claim error page claim file or policy document, you might use a small model to kind of zoom in on the areas that are most important and then use an extensive model to say, synthesize, you know, what's the most important and what's the answer.
Speaker 1:Sure.
Speaker 7:Sure. And then, you know, I think what's more interesting, you talked a little about kind of fine tuning an RL. Yeah. You know, we're kinda like the perfect set of use cases for for web agents being able to navigate, you know, these applications that don't have APIs, be they, you know, green screen CLIs or desktop apps. And so we've actually been, you know, working on a handful of fine tunes and creating basically RL environments that are these sort of CRUD applications.
Speaker 7:They're very different from, say, know, the book me a restaurant or this flight type of demo.
Speaker 1:Yeah.
Speaker 7:Yeah. It's much more about, you know, take this repetitive task and fill out this form thousands of times. It's kind of the ideal case for, I think, a lot of these computer use systems. So we're seeing a lot of success there. I think we are just kind of rounding the corner of the scaling laws starting to work on those.
Speaker 7:Kinda feels the same way that maybe, like, voice did, you know, six to twelve months ago.
Speaker 2:Yep. You guys have pursued a forward deployed engineer I was about to market. Do you sounds like it's working well to date. Do you think this is something that will still be a part of the core motion in a few years? Or is this something that makes sense to get off the ground till you understand what the typical stacks are within your within your market, and then eventually, you'd move beyond it.
Speaker 7:Yeah. I mean, I think the forward deployed motion is definitely something that, you know, really came naturally to me. It's kind of like the DNA of of our company because that's, you know, also what we were doing at Retul Yeah. When it was, you know, much earlier, I think, on that. I think for us, you know, going and working with our customers, being able to speak their language, getting to, you know, really understand the the complexities of these many 100 page standard operating procedures and make them successful as agents Mhmm.
Speaker 7:I think it's really important for us to be sitting, you know, side by side with them. That being said, I think a lot of companies sort of talk about FTEs as sort of being the end state or, like, that is, like, you know, the best part about my business and why I'm, like, Palantir. I think for us, like, it is you know, these our FTEs are also really able to ship code in the code base, and so they are actually constantly making the product better. And that's really important. Like, I think our product should just be continually giving our forward deployed engineering team more and more leverage
Speaker 1:Yeah.
Speaker 7:So that they can, you know, be able to to complete more for our customers.
Speaker 1:So some some FTE goes into a business. They're badge. They're in there. They're interfacing with the green screen, you know, local on premise mainframe software. They write some binding for it or some screen scraper or whatever you need to do, and then they can ship that back to HQ.
Speaker 1:And then the next time you run into that, you have you have an integration effectively. Is that, like, the basic pattern of that?
Speaker 7:Exactly. I think there's just a lot of things that are required to get these agents running at scale that, you know, customers don't need to build from scratch every time. I I do think it's really important, that we also enable our customers to be able to build their own, you know, agents. And for us, you know, some of our customers are at tens of agents live in production. We may have built you know, help them build the first one or two in an FD motion.
Speaker 7:But just because it's a natural language, they're able to sort of turn around two through 10 without us having
Speaker 2:And they're
Speaker 1:still running those. And so they're running number three through 10 on your platform through your system, but they're defining them and architecting them themselves.
Speaker 7:Exactly. Yeah. Just a nice
Speaker 2:Very cool.
Speaker 1:Good business. I love it. Congratulations.
Speaker 2:Bullish. Bullish. Team. Thank you. Yeah.
Speaker 2:Well, put together a great team too. Yep. I'm excited that Varun, one of my former teammates is is ever with with you at Pace now. And, yeah, very I'm sure you'll be back on
Speaker 3:Yep.
Speaker 2:This year, maybe this quarter. Maybe.
Speaker 7:It's great
Speaker 2:to have a lot
Speaker 7:of teaming.
Speaker 1:Anyway so much again, guys. Yeah. We'll talk to you soon. Have a good rest of your day. Good job.
Speaker 1:Let me tell you about Vanta, automate compliance and security. Vanta is the leading AI trust management platform. And we have Ben. Oh, sorry.
Speaker 2:Quick. Before we bring in Ben, some unfortunate news. Palmer, got tied up with DC. We got
Speaker 1:Jeff Miller coming on.
Speaker 2:Jeff Miller's gonna come. It's Miller time. It's time.
Speaker 6:It's Miller
Speaker 2:time. We're excited about. But yes, so Palmer unfortunately won't be joining. But we'll get him back on.
Speaker 1:We we got him
Speaker 2:back on very soon.
Speaker 1:Again soon.
Speaker 2:And right now, without further ado.
Speaker 1:Ben Lair, the co founder and engine partner of Lair Pip Val Ventures. Let's bring him in to the TV again. How are you doing?
Speaker 11:Hey, guys. What's happening?
Speaker 2:What's going on? Not
Speaker 1:too much. Thanks so much for taking the time to join. Can you, maybe I mean, I feel like most people are familiar, but can you kick us off a little bit of just the shape of your business, shape of your career? Just a quick intro.
Speaker 11:Sure. Sure. Yeah. I'm a native New Yorker. Everything I do is sort of New Yorkie in some way.
Speaker 11:So I grew up here. After school, came back to New York, started a company in the digital media space. Yeah. When York had, like, the smallest tech ecosystem in the world and was one of what felt like 50 founders building in New York, you know, back twenty years ago. And as a result of sort of being a founder in a tiny market, I got the I knew everybody.
Speaker 11:Everybody knew everybody. And so I had sort of the benefit of being a small fish in a small pond and started angel investing and really over the last fifteen years got to sort of simultaneously live the founder journey and built a company and raised a few $100,000,000 and did a lot of things right and almost ran the thing off the, you know, off the dock a bunch of times.
Speaker 10:And,
Speaker 1:also,
Speaker 11:he had sort of the good fortune of, like, picking you know, investing in New York at the right time. And so have have ridden that wave, started our first fund was an 8 and a half million dollar fund. We're now investing our ninth fund, is a $200,000,000 fund. But every fund is a little bigger than the one before.
Speaker 2:That's a good that's a good sign.
Speaker 1:It's a good run. Funds get there, you know?
Speaker 2:Yeah. Did you ever think it was it was crazy to set up a fund in New York, or was it always just like just was so obvious that you were happy that other people just were kind of thought thought you were crazy?
Speaker 11:I didn't know any better. Right? I mean, like, I grew up in New York. I thought New York was the center of the entire universe. I still, in some way, think that that's the case.
Speaker 11:And, you know, I just I was very lucky because when I when I got sort of the entrepreneurial bug was when the whole world got the entrepreneurial bug. It was like that same minute moment. I graduated the same year that Mark Zuckerberg did from college. Yeah. And so, right, it was just like that Perfect timing.
Speaker 2:Perfect timing.
Speaker 11:Perfect timing. And all my friends in the past would have reflexively wanted to go and work on Wall Street.
Speaker 3:Yep.
Speaker 11:But suddenly something was in the water and people wanted to go work in tech. And so I just got lucky. And, you know, it seemed obvious, and frankly it was obvious. And if you just did the obvious thing, did okay.
Speaker 2:Talk I about want to talk about media
Speaker 1:Me too.
Speaker 2:Kind of selfishly, because we love talking about media.
Speaker 11:I actually want to learn about your biz. Have questions for you guys on the business model. Like, I've been poking around trying So to feel it you ask me questions and I'm gonna ask you questions.
Speaker 2:Well, I guess just can you take can you take it like, we we try not to do this is not a not a history show, not like a founder journey show, but but I would love like
Speaker 1:What was the climate around media, digital media? What was happening back then? What was the
Speaker 2:initial because first I mean, piece of like, much of what has First informed business plan. Feel like we tried to take a lot of the lessons from that era of media and say like, okay, what was the takeaway? Which was maybe like, you can I mean, the primary takeaway was don't build a media company, in our case, that is the whole strategy is predicated on getting to a billion dollars of revenue, right? Or even a billion dollar valuation. Right?
Speaker 2:And so a lot of what informs this is that like staying niche Yeah. Especially for us because in our business, like we're building a media company that we make by hand every single day. So we have if we don't stay niche, we'll start covering a bunch of topics that aren't interesting to us. Yep. And then we won't wanna show up every day and do this.
Speaker 11:You'll do what I did and what everybody did. Give us the lessons
Speaker 1:Yeah. A Give us the prehistory, give us the climate, and then I I want as many lessons as possible.
Speaker 11:Yes. So, look, when when I started, there was this idea that sort of like the Internet would destroy every traditional business in every space in the entire world. Yeah. Now there's a little bit of that, like, the AI will do that, but, like, you know, I'm I'm old. So this was, like, the the web will destroy all.
Speaker 11:And we looked at print magazines and newspapers, and the idea was all of them would go away entirely and would be replaced by digital in the entire size of that market, and all that ad revenue was gonna move online. And so, you know, we were one of the early movers in sort of going and trying to capture that market. And we looked at the big men's magazines or the local city guides or whatever it was and tried to go build that online. And at first, did it the way that you guys were doing it. It was like very much this labor of love, and we didn't have that much access to capital because it wasn't hot, hot, hot yet.
Speaker 11:Sure. And so our first few years, we were profitable and stayed small, and it was like it was amazing. And we had a a a small community of people that were diehard and advertisers who really felt the needle move, and it was it was wonderful. And what happened was the space got attention from big VCs and people wanted to go and sort of, like, you know, get in on the gold rush and a bunch of people raised a bunch of money, and I was one of them. And, you know, the idea was you have to grow into or live into those valuations.
Speaker 11:Like, you just like you just sort of alluded to. And, you know, we we went from one to to three to seven to 15. Like, it was growing, like, you know, maybe not like a software company today, but it was growing like a software company did back then. And we kept raising into it. And a few of the, like, mistakes and by the way, they were they were not fatal mistakes, but they were they were ultimately the thing that sort of they they they took a lot of the joy out of the business, I would say, was when we got obsessed with figuring out how do you keep how do you keep growing and how do you keep doubling year out year over year.
Speaker 11:And we part of it was we need to grow the advertising base, and so we need to find more and more and more users that got away from our core and got away from sort of what we thought we were really great at doing. And so the product started to get a little watered down. And then on the other side, it was commerce. How do we start to sell stuff to these guys? How do we start to monetize directly?
Speaker 11:Today, subscriptions are something that I think is an actual viable model, again, in not not at scale. Yeah. Like, everyone points to the New York Times and says, oh, this can work. Like, the New York Times is n of one. That's I don't think you're gonna build venture scale businesses doing that, but but there is more willingness to pay for consumers than there was ten years ago.
Speaker 11:And so our our thought was they're not going to pay for our content. They're going to pay for products. We bought a sort of, you know, ancillary commerce business and scaled that. And I went out to raise what was our series b thinking that we could go and get sort of one plus one equals three. They're gonna love our media business, which is, like, profitable and attracts this audience.
Speaker 11:They're gonna like our commerce business, which has a bigger ceiling and is growing fast. And in fact, I just got, like, full punch in the face, and it was, like, one plus one equals one and a half. And these businesses don't necessarily belong together. And media folks understood the media business and commerce folks understood the commerce business. And so I had to go through this sort of painful process of taking them apart from one another.
Speaker 11:And then I got the sort of bug for the roll up. And, well, if I'm not gonna grow vertically, maybe I can grow horizontally. And what are other like minded brands? And can we sell them together? And can we build a tech platform together?
Speaker 11:And bought a bunch of companies and raised a bunch of money. And that worked. But the reality was we were always swimming against the current, which was social media. And, you know, media in general fell under the eye of big tech. Yeah.
Speaker 11:And, you know, meta grew and and, obviously, you know, what Google represented for the ad ecosystem. And then as, you know, Amazon and Apple and Netflix grew, and it just was clear that, like, I wasn't even at the kids' table. I was in, like, the other room entirely. And now look at what's happened with, like, the top of the market. Look at, like, Discovery and the, like, amazing run they had and the fact that, like, they need to be consolidated.
Speaker 11:It's just it's an impossible business. Yeah. And the way to do it right is to do what you love and stay relatively small and build, like, a real community based thing like you guys are doing. I have, like, so much respect for this show. And, like, my hope is that you, like, find other ways to leverage the influence that you have here, and don't put a, like, target on your back where you have to turn this show into a billion dollar company
Speaker 2:because Yep. Totally.
Speaker 11:It just Yeah.
Speaker 2:John's John's John's position was always that value in media today is flowing to personalities, individuals, right? Even on the subscription side, when you're signing up for a subscription today, the subscriptions that I'm excited to sign up for are when I know the dollars are flowing to an individual who's gonna just obsess over. Like a Ben Thompson is a classic example. Totally. Right?
Speaker 2:Or like an Emily Sundberg in New York. The dollars are going to an individual who has a certain point of view, they're and just gonna obsess over whatever topics, and then the value's gonna flow to the platforms, the Spotifys, the YouTubes, the Metas, like, you kind of The wanna be in either only other category that's emerged as durable to me is the like, you know, truth monopoly, which is like a legacy media brand. There's only maybe 10 of them in the world. The New York Times, Wall Street Journal, things like that, where they kind of one like 100%. Part of the value is like you It's windy.
Speaker 2:It's like you own an asset that basically has a license to distribute what becomes the truth, right? And that takes fifty years to kind of create
Speaker 1:And even across all those assets, you're talking about tens of billions of dollars, which is a drop in the bucket compared to the independent creator earnings. I think YouTube paid out like $50,000,000,000 to creators. And then YouTube itself also makes another $50,000,000,000 And so, like, all of that is way more money flowing around than, like, the few publications that stuck around and made the business model work and are doing quite well. But creating these new things in the middle, we call yeah. We wanna stay out of that messy middle.
Speaker 11:Yeah. And I I, you know, I do think the look. Venture in general Mhmm. Like, is so many companies raise money that should not be raising money. Most companies raise money should not be raising money.
Speaker 11:Venture's a very specific flavor of com of sort of trajectory. And the fact that, you know, it went from being a sort of cottage industry fifteen, twenty years ago to being just like this mainstream asset class that everybody obsesses over. You know, when I graduated from college, I did not know what venture capital was. If I graduated from Penn today, it would be the first, second, and third thing on my list to do, would be to go get into VC or to go get into a startup. Like, the world has changed.
Speaker 11:And I think it, in certain situations, enables unbelievable things to be built. And in most situations, it like destroys companies and
Speaker 2:Yeah. Force So part part of it is VCs are trained to hunt the things that are getting attention. Right?
Speaker 11:Yes. Right.
Speaker 2:Part of the issue is like you see a media company pop up, and it's like this thing is cool. I It's like a lot of attention.
Speaker 11:It's the sexiest shitty business in the whole world. Yeah.
Speaker 1:100%.
Speaker 2:Yeah. We were even thinking about, you know, thinking about like, the right way to be trained on is like Claude Bot. Like, if you could find a way to put some money into Claude Bot
Speaker 3:Yeah.
Speaker 2:You know, this week, that's pretty
Speaker 1:be very high leverage
Speaker 2:Not saying anything.
Speaker 1:Business that builds around
Speaker 2:Yeah. Exactly.
Speaker 1:The the the interesting thing is, you know, I I go back to what is the purpose of venture capital. You go back to, like, why do we call it Silicon Valley? Well, because they were setting up fabs. They were setting up it was a high CapEx, high r and d environment. Then with the cloud platforms and AWS comes out, it becomes cheaper to start a company, but you're still you're still putting up money for a bunch of engineers who are gonna build a piece of software that then eventually starts growing, and the LTV comes in year five or six, and you get paid back.
Speaker 1:But we have started to flirt with, well, like, maybe let's put venture dollars into this thing that really doesn't have any CapEx or any r and d spend, but a lot of go to market spend that seems to pay back relatively quickly. And that seems to be a pattern that repeats and something you need to watch out for in any category is where are the what is the purpose of venture capital in this thing, even if it's growing like other things? Is that how you see it? And what industries are you seeing, okay, this is still a good industry for venture capital?
Speaker 11:Yeah. One and one of the sort of weird perversions of the industry right now is there is more money than there's ever been in venture, and there's obviously a relatively small number of incredibly sort of deep pocketed funds
Speaker 1:Mhmm.
Speaker 11:That need to deploy huge amounts of money Yeah. And into a generation of companies that theoretically need less than ever before. Yeah. And so you have this, you know, somewhat unhealthy dynamic. I do I think that's what's sort of creating this idea of, like, sort of picking a winner before a winner has actually emerged, just like plow in on the thing.
Speaker 11:And even if it's a million of ARR, but it's raised $300,000,000, it's like, stay out of the category. Like, this is the like like, these are the guys. Yep. And and I you know, the big firms can do that. I can't play that game.
Speaker 11:I don't really wanna play that game. It's not, like, how we're set up. You know, the the one thing, even as our funds have grown, like, we are purists. We are only early stage. We're pre seed and seed only.
Speaker 11:And I think, like, when you and and we're a team of generalists. And I think when that's the case, like, we have to be really careful that we don't get sucked into being heat seeking and just, like, always going for the shiny object in a market like this where prices are crazy and where you, like, get pulled into competing with mega funds that have, like, very different incentives. I also think you don't wanna find yourself as, like, a value seeking fund a time in the market like Yeah. This for for obvious reasons. And, like, the history of value seeking adventure is not great.
Speaker 2:And so thing the other thing that that strangely I mean, one of the dynamics right now is you have, you know, mega platform VCs that don't care about pricing as much and they just wanna get enough dollars in. But then you also have some like emerging managers that are just are in the heat chasing business. And so they don't really care about pricing as much either because they're like, we'll we'll get in at 60. We know this is gonna get marked up. Mhmm.
Speaker 2:And we just need to prove to our LPs that we can get in the good names.
Speaker 1:Yeah. And we'll It's
Speaker 11:like a shorter term like sort of fund raising mentality.
Speaker 2:Yeah. It's like we're just we're optimizing to raise like fund two versus versus, like, actual, you know, returns.
Speaker 1:Yeah. How how do
Speaker 11:you think is, like, having been in this business for a long time and, like, living through cycles, math matters. Like, if you come into stuff way overpriced, like, it's really hard to build a business from day one and have it exit for a billion dollars of cash. Yeah. Like, actually seeing that arc is incredibly difficult. And in today's market, there's people who are raising a billion dollars who are still, like, figuring out what the name of the company is gonna be.
Speaker 1:Yeah.
Speaker 11:And, you know, it's hard to see that math working. At the same time, the argument is if you look out on the horizon ten years from now, outcomes are gonna be that much bigger. We're at a moment of change from a technology perspective where there's gonna be more generationally important companies. And the idea, you know, a decade ago was, can you find a billion dollar company or a $10,000,000,000 company? And now this is, can I find a trillion dollar company?
Speaker 11:Yeah.
Speaker 2:Yeah. How do you process yeah. Like, when when I look back at previous hype cycles that I've been like, during my career, you have maybe the d to c era. That's where I where where I got my start. When you look at that hype cycle, there was not There was It was almost like an ar It was almost like an ads arbitrage.
Speaker 2:It was like Meta was an amazing platform. And if you had a great product that was positioned well against incumbents, you could just scale so quickly. And so the opportunity was really like, hey, we're making better products here, but really this is like a advertising arbitrage. And Yeah. There were some great businesses that were created from that.
Speaker 2:And then fintech
Speaker 1:was also branding firm arbitrage against VCs. You go to a branding firm, give them a 100 k and then go raise out $5,000,000 each. Yeah. Yeah. Yeah.
Speaker 2:But but but I've been
Speaker 11:the victim of that.
Speaker 2:Thank you.
Speaker 1:The people that work at those branding firms do amazing work, so I don't wanna call because it's Not not to
Speaker 2:boy, Emmett
Speaker 6:Shine. That was a fun one.
Speaker 2:But going going forward, like, you look at kind of fintech. Fintech was there there was some it was it was Dodd Frank. Right? Yeah. There was like the Banking chain reform.
Speaker 2:Some some regulatory component. But a lot of it was like just better infrastructure that just made it easier. Yep. But that just meant way more competition. So it wasn't like this fundamental technology shift that that just changed everything in the way that we're experiencing right now.
Speaker 2:So I feel like you kinda have to unlearn some of the lessons from that because we now do have a real technology shift. So you are gonna just get, you know, far greater value creation a lot faster than maybe this, you know, temporary ads arbitrage or just, kind of the infrastructure.
Speaker 11:And, by the way, one of the interesting trends on the back of that is this move to sort of VCs hunting younger and younger founders. I think you're seeing you know, there there was a movement over time where you were getting this big premium for second and third time founders and people who had sort of unfair advantage in a category. And now I think there is this idea that you have to unlearn so much if you have not grown up natively with AI that maybe you're better off not knowing anything about an industry. Mhmm. But moving 10,000 times faster and use and and sort of just like living natively in all the new tools and thinking that the way that somebody like me works is totally, like, I'm just like a dinosaur.
Speaker 2:Yeah. I've actually so so I've found I've found myself giving a buddy of mine is is kind of like going through the idea maze, and a couple of the ideas that he mentioned. Was like, this seems like a great idea but you have to understand like, think about this idea in the context of having four y c companies going after this opportunity. Yep. And do you and and it's like, dude, you're gonna have a family soon like you you like you're not like 20 anymore.
Speaker 2:Do you compete against, like, four teams of 20 year olds that are not gonna sleep? Like, this is and and, yeah, they they have less experience, and maybe they haven't raised money before. Mhmm. But it's gonna be you're not I don't feel confident that you're gonna be able to outwork them even though you're a really hard just because you have more stuff
Speaker 11:We see this in, like, company updates. So we're, you know, we're we're, like, actively doing deals in new companies, and you get that, like, you know, update three weeks after you invest, like, the monthly update cadence. And we can see the teams with these younger founders and just, like, the amount of product that they ship and the learnings that they have and the speed that they're hiring. Like, it's palpable. And sometimes we invest in a team.
Speaker 11:Great experience. They've got all the sort of credibility, and we get the first update, and we're like, Like like, they think it's 2002. Like, they just don't get it. You need to move faster.
Speaker 8:Like Yeah.
Speaker 11:The market is crazy right now.
Speaker 1:Yeah. Yeah. What what are you how big is the team that you work with? How are you thinking about mentoring, building new great investors and counseling investors about best practices or, like, strategies for, like, not not breaking the rules that you just discussed.
Speaker 11:Yeah. It's like this is, like, you know, all all I think about now. Admittedly, I think this is a young person's business and and an increasingly young person's business. And I think that the investor track follows the operator track to some degree, which is you want investors who sort of understand this this new gear. And so, you know, I'm 44.
Speaker 11:I'm gonna be, you know, soon enough, I'm gonna be the oldest person on this team. And which which is funny, you know, to just like think about. And we are actively, you know, continuing to hire and and sort of mentor and bring up young talent. I think that you can be extraordinary in this business without having twenty five years of experience. I think it's nice to have some voices around the table who have been through cycles and have some of that wisdom on just like not getting too caught up in in the in the craziness.
Speaker 11:But realistically, we are still continuing to, like, obsess about bringing in interesting, young, diverse perspectives, people that natively, like, are growing up with the technology that feels novel to people like me. And I think that that's gonna be the continued goal here, and then it's like up or out. Really, this is not a place this is not a business to sort of hang out in. And I I don't have the patience, and I don't think people in this business should have the patience to wait ten years to see what performance looks like. I think you have to sort of decide early if you feel like people have the right instincts, if they're able to identify talent with their gut, if they're able to sort of win people over.
Speaker 11:And, like, I think you have to I think you have to, like, make bets the same way you do in, like, professional sports.
Speaker 1:How do you think about that that patience versus, you know, moving quickly and and not waiting to measure results? I'm I'm thinking specifically about the the the pressure that can occur a bunch of, you know, new VCs who are at a fund, and they all wanna get points on the board, and that maybe leads to more aggressive deal making that becomes sort of like a rat race between them and they wind up making bad decisions versus saying, look, you will be judged on a short term, but we're gonna give you the space to not swing at every pitch. How do you think about that that balancing act?
Speaker 11:Well, I think, first of all, it's like this comes down to some of the actual, like, mechanisms for how you manage people and stylistically, like, how much communication do you have? Mhmm.
Speaker 8:How
Speaker 11:much, like, you know, of a lone wolf culture versus a team based culture? You know, here, we're very collaborative. We have a bunch of people working on everything that we're doing. Obviously, the end of the day, like, a deal gets done because somebody brings that over the line with with, like, very personal conviction. But I think our culture is set up to be able to assess people in in sort of softer areas versus just those quick marks.
Speaker 11:Also, you know, you have to know what you're underwriting. So sometimes we do a deal and explicitly we go, this one's gonna get out of the gates really fast. This is gonna get quick marks. We understand it. Mhmm.
Speaker 11:But by the way, that doesn't necessarily mean that it's gonna have great outcomes. We've seen a bunch of our quick marks over the years end up as just big black eyes. And so there's other deals where we go, we know this is gonna be slow. It's okay that it's gonna be slow. There's a real moat here if this works, so there's a real technological sort of challenge that they're gonna need to overcome.
Speaker 11:But if it happens, this is gonna be a really valuable business. You know, know what you're getting into and and be explicit about it so that if something is slow, but you signed up for slow, you're not, like, dinging somebody.
Speaker 6:Mhmm.
Speaker 11:And then, look, I think at the end of the day, like, a VC fund is as good as the their sort of reputation. And so feeling out how our founders feel about, like, working with folks, seeing people's win rates, and seeing the way that people sort of, you know, carry themselves. A lot of this is art, and frankly, like, early stage investing is a lot of art too. So this is feel. And, you know, maybe I'm making bad calls on on talent, but we're we're doing it, I think, very deliberately.
Speaker 1:Cool.
Speaker 2:Well, put your talent on TBPN. I have one more question. And we'll no.
Speaker 11:I got I got people.
Speaker 2:I know. No. I I I had a question too. Please. I wanted to I wanted to get your take on AI focused roll ups given that you rolled up.
Speaker 1:Was gonna ask something very similar.
Speaker 2:What was your question?
Speaker 1:I was gonna ask if you had to you had to pick a different asset class to invest. You mentioned art. There's some art behind you between, like, public markets hedge fund, private equity, take privates turnarounds, roll ups, growth growth equity, bigger scale stuff. Like, is there anything else where you're like, like, that looks fun, but I'm not gonna do it? Like, what else what else intrigues you about different potential markets?
Speaker 1:We've seen a lot of VCs Okay.
Speaker 2:Two wildly different questions.
Speaker 1:Okay. Sure.
Speaker 2:So let's I wanna first take on the AI roll ups and then other asset classes.
Speaker 11:Well, I can actually I'll connect the two because I actually do think sort of roll ups scratch an itch for me as a former operator, and I've done it. Like, I I do like the sort of, like, that that that mental exercise of, like, putting things together and figuring out the personalities and the products. I think that it is right I can understand all the logical reasons for why it works and why, like, if this is all gonna be this is gonna end well, I can't help but think a little of the gold rush right now is a place to park AUM. Yep. And I I don't like, you know, I'm not trying to, like, throw stones, but it it's, you know, it's a real easy place to just go raise money if you're a fund that has access to a bunch of money.
Speaker 11:Yep. And and and
Speaker 2:somewhat somewhat And you're gonna venture fees. Yeah. Limited
Speaker 11:Oh my god. Some kind
Speaker 2:of limited debt. Fees. Yeah. We yeah. But but
Speaker 1:Sometimes. Not not always. But yeah. I mean Well, there's allure getting venture fees on, you know, just an asset that already has cash flow is pretty safe. Like, could
Speaker 2:be not a mention that, but the the entrepreneurs, if they're like, I'm basically running a PE fund, I only had to take 30% dilution
Speaker 1:That's crazy too.
Speaker 2:My own, you know, depends on depends on the individual depends on the individual company. Yeah. How given that you've bought you've bought a number of businesses, like how limited do you think is the downside on some of these roll ups? Like, is there a way for people to buy companies and just botch the integration and the actual, like, AI enablement so bad that the company goes from being worth, like, $25,000,000 doing some niche thing in
Speaker 1:in One plus one is point five.
Speaker 2:Yeah. Yeah. Yeah. Or to to just like pay all
Speaker 11:the one could equal zero plenty of time. And frankly, it can equal less than zero because I mean Less
Speaker 6:than zero.
Speaker 11:You know, I look. It depends what you're buying. It depends what the space is. The more reliant you are on a personality in these roll ups, I think the greater the risk. If this is like a single proprietor who maintains all these really tight relationships and the whole thing rests with them, and if you don't keep them happy, you risk, like, the whole thing, you know, burning down.
Speaker 11:That scares me. I do think there's probably places where you can go and and throw stuff together. The reality is there's a lot of money in PE that knows how to roll stuff up.
Speaker 2:That's I'm saying. Is there
Speaker 11:not Yeah. The venture is going to do this better than the folks that
Speaker 2:have bought Well, this The one thing you can imagine venture doing better venture doing better is the technology. But there's also the financial engineering and actually buying Just managing. Companies. And we we have a friend who who raised a PE fund, you know, and and is yet to he's getting close to doing his first deal. But the number of amazing opportunities that look amazing that he's ultimately turned down to finally get to the point where he's doing the first deal and you realize like somebody who's never bought acquired a company before coming in and just like looking at everything and everything looks great if you just have like a a capital hammer and you just wanna hit it with with a bunch of hit the asset with a bunch of AI.
Speaker 2:I do I do worry that some of these had
Speaker 11:And how long are these advantages gonna be around for? I mean, think there's a version of, you know, fifteen years ago, it's like, we understand the Internet and nobody else does. And then it you know, like, we're gonna go to the cloud first or we're gonna do mobile. What, like, yes, AI is different, but, like, I can tell you the traditional PE funds are not gonna, like, totally fall asleep and, like, decide not to, like, embrace any new technology. And in fifteen years, they're still gonna be sitting on the wrong side of history.
Speaker 11:Yeah. Like, there might be a window, but it's not gonna be a big window.
Speaker 2:Yeah. Somebody should ask Orlando Bravo if he's heard of AI. Never heard of that. No.
Speaker 1:People are aware.
Speaker 2:People are aware. This competition will be intense.
Speaker 1:This is great. Thank you so much for taking the
Speaker 2:time to talk I wish we had more time. Let's do it again soon. You. Thank you for hiring and training up Dylan
Speaker 1:Oh, yeah.
Speaker 2:Our president back in the day. Dylan Eberson.
Speaker 1:Oh, man.
Speaker 2:Yeah. Excited. Big big fan of yours. Yeah. And we're lucky to have him.
Speaker 2:So come come back on again soon.
Speaker 1:Yeah. Absolutely.
Speaker 2:We'll be in New York We'll be in at the New York Stock Exchange. Hang on with us. That'll be fun. Join us there.
Speaker 11:Anytime. And I'm I'm gonna be out your way later in the month.
Speaker 1:I'll be Amazing.
Speaker 2:Awesome. Amazing. Great to
Speaker 3:have you.
Speaker 11:Well, have
Speaker 1:a great rest of your day. We'll talk to you soon. Thank you. Goodbye. Let me tell you about Railway.
Speaker 1:Railway simplifies software deployment. Web apps, servers, and databases run-in one place with scaling, monitoring, and security built in. We have Lucas Atkins from ArcAI coming into the TVP and Ultradome. Lucas, how are doing?
Speaker 10:Here he is. I'm good. Thank you for having me.
Speaker 1:Thanks for hopping on the show. First time on the show, can you please give us an introduction on yourself and the company?
Speaker 10:Yeah. My name is Lucas Atkins. I'm the CTO, at RCAI. We actually RCAI. Changed our logo
Speaker 1:Okay.
Speaker 10:So that it, like, highlights the r
Speaker 2:and z.
Speaker 1:I have text. I'm sorry.
Speaker 2:No. No. No.
Speaker 1:You're good. Okay.
Speaker 10:And we've, you know, for a very long time been a startup focused on like enterprise Yeah. You know, custom language models. Yep. And we decided to jump into the pre training game ourselves.
Speaker 1:Pre training. Okay. So small language models. I like small language models. It's the large ones that scare me.
Speaker 3:But Yeah.
Speaker 1:Tell me how small are these? How much? What is the training budget? Can you give me, like, a GPT two level training run, GPT three level training? Or, like, try and ground.
Speaker 1:Am I looking at the data center for space, Or is it something Yeah. A little cluster in a closet? Can you train it on a Mac Mini? What are we talking about?
Speaker 10:It used to be, you know, that a small any small model, a small language model, right, was, you know, tens of millions of parameters. Yeah. Yeah. Now it's in the realm of, I would consider, anything under 50,000,000,000 kind of
Speaker 1:Okay.
Speaker 10:Resting in that smaller world. But So
Speaker 1:small as big as big has gotten enormous.
Speaker 10:Yeah. Exactly. It's it's only gonna get more and more as, you know, RAM. Well, I don't know. But as people get more RAM and as we're able to fit more on our machines.
Speaker 10:But we historically lived in that kind of 50 sub range. And then we also we we, like, trained on top of other open source models like Lama, Mistralton, Quan.
Speaker 1:Is that fine tuning or distilling? Is there a difference there that's meaningful to what you do?
Speaker 10:There's a an open debate as to whether fine tuning from like another model's just like text output is distilling.
Speaker 1:Yeah. Distilling. Okay.
Speaker 10:Or if you actually have to like grab it from the, you know, the logits. I would argue that it's all distilling. So it's all some form of making a model better by using another model to make it better. You know.
Speaker 1:Yeah. And is there is there a sort of power law distribution in applications of SLMs? Like, is there is it like, you know, translation? It's just like everyone's using that or or or text extraction, OCR? Like, is is there sort of a power law of, like, what it can what what what the when you reach for this tool in particular?
Speaker 10:It used to be up until about a year ago. Mhmm. It was you were you were pretty confined to you could you could hill climb a specific domain. Mhmm.
Speaker 11:You
Speaker 10:know, obviously, it ranges based on how big your, you know, model was or small rather. But after this kinda, like, you know, reinforcement learning revolution in the last year, if you can build a task and and an environment to to, like, have that model live and and and breathe and learn inside of, you can hill climb. You you can take, like, there's people that are taking 100,000,000 parameter models and making them perform like, you know, five or 6,000,000,000 parameter models from a couple years ago. So Yeah. Used to be a lot harder.
Speaker 10:Now it's it's all about it's a lot more taste and task driven.
Speaker 1:Yeah. And when you say perform like, it feels it feels like the true, true cutting edge frontier model sort of smokes all the domain specific models, but it's it's expensive. And so how important is cost? What sort of cost reductions are you seeing on the inference side once a company or, you know, a developer decides to move from the heavyweight frontier model to something smaller?
Speaker 10:It it it is very often when they're going into production. Right? Like, it's it's like they've done prototyping with, you know, a large closed source model. Yeah. They've had success with it.
Speaker 10:They've gotten approval. They wanna bring it into production, you know, to more consumers or or their customers. And then the bill starts to hit and Mhmm. Market starts to look tricky. So that's when they start looking for ways that they can host it themselves.
Speaker 10:There's also, like, the compliance and data privacy aspect of it. Yeah. And that's something that, you know, kind of sovereign, you know, US based open models have stopped kind of being released. It's it's very much out of China. Yep.
Speaker 10:You have, you know, a few in Europe, but it has very much been lacking in The United States. So we were I was hoping to to release this before I got on the show, but, you know, today, we're we're finally releasing our five 400,000,000,000 parameter model. So we went up pretty big.
Speaker 2:There we go. Congratulations. You still got you still got plenty of day left.
Speaker 6:That's great.
Speaker 2:You still got left.
Speaker 1:You're like, we're we're still here.
Speaker 2:This is just this is just a preview.
Speaker 1:So Yeah. Yeah. Take us through the landscape of who you're competing with. Set the table for us so most people will be familiar with Deepsea, Quen. Like, how are these companies resourced?
Speaker 1:Is this just China's national interest that they're funding these? Do they have good business flywheels at this point? Because I imagine you have a plan to sort of unseat them Mhmm. In in the open source race.
Speaker 10:There you know, there's a lot of rumors about how all of you know, how all of this capital gets allocated into, you know, these different companies. Rumors.
Speaker 1:Hedge files.
Speaker 2:Well, there's
Speaker 10:rumors that the government's giving it to them, they have favorites, you know, there's shady deals going on, but the reality of Wait, it
Speaker 2:you're saying they didn't train the models with scraps in a cave?
Speaker 10:In a cave? No. No. Well, actually, frankly, if you look at kind of the horsepower that we're dealing with, a lot of them, you know, seemingly did. It's very impressive.
Speaker 10:That's that's that's kind of the you know, you want there to be this kind of battle of, you know, The US versus China in this race. That obviously plays into our incentives. Yeah. However, they these are extremely talented labs. And so when it's I'm not competing against, you know, China or or other countries for, like, open weight, you know, sovereign language models that that people can own and deploy themselves.
Speaker 10:I'm competing against, like, the other researchers there, like,
Speaker 2:the Sure.
Speaker 10:You know, that human being, and and you have some extreme talent. So, yes, it used to be really hard to make money making open source models. As they got bigger and as they got harder for other people to host themselves, it you know, the the the the systems and the economics started to work out because they get the, you know, the community buy in and excitement of something being open source. But if it's a trillion parameters, you know, your average consumer is not gonna be able to run that on their toaster. Right?
Speaker 10:So it it ends up you kind of get this win win situation. And now that that has kind of started to flywheel, they've started to, you know, do the OpenAI and the Anthropic and the Google Play where they're building products around it. And and it's really becoming a very lucrative ecosystem.
Speaker 1:Yeah. How are you scaling the business? What have you chosen in sort of the business model world? There's there's so many ways that you can build around open source technologies. What's working and what are you thinking about the road map long term?
Speaker 10:There's we we were in kind of a uniquely a unique a very fortunate position when it came to this. We had always been customizing models for people. We had always been working for, you know, enterprises, developers, businesses. How can we, you know, make sure that they're getting the best out of their own hardware? The only thing that really changed was that when customers wanted something to be based in The United States or from The United States, there stopped being competitive options.
Speaker 10:Sure. And we never really liked the idea that, like, the foundation of our business relied on other people releasing models. Yeah. So it was, like, six months ago that we we kind of fully decided, hey, you know what? Let's try it.
Speaker 10:Yeah. And and we had success with our first model and then our second, our third, and it it kind of, you know, brought us to this. So the economics of our business doesn't change so much. You know, we're still working with customers. We're still delivering, you know, models and and and powerful tools, though we have a much more robust control of the stack, which means that the degree to which we can customize and and and the kind of period in training that we can go back to for those customers just kind
Speaker 1:of Yeah.
Speaker 10:Increases drastically. So
Speaker 1:Just when I when when I think of, like, open source focused company, I think, you know, like, donations, people just like, contributing.
Speaker 3:Have the game.
Speaker 1:Also think about, like, consulting, actually going in and a company paying you to do a custom implementation work, improve. I also think about hosted services, consumption based plans, subscription based plans. How are you thinking that side of the business model will evolve, where is it at now?
Speaker 10:I would love for us to have, like, a GoFundMe or something. But, no, we it's it's very much the the latter two. I think that services and consulting, obviously, you know, if if the if it's the right customer for the right product and and and the right situation, you know, there there there's worlds where where having a portion of your business be devoted, that's important. But the real moneymaker, and I think this has been seen out of those labs in China, out of out of others, is it's in the tooling. It's it's like, what are you building around it?
Speaker 10:How are you making it so that other people can customize it without you having to do services? How can you make it an easy API? How can you, you know, build a developer and education kinda suite around your software, software, you know, that is uniquely benefited by your your models so that they can take it and and using maybe hardware GPUs that you own, how can they go and train their own models. So there's there's many ways to, you know, turn this into something that is that is much more like automated and less services based. But at the end of the day it all just comes down to getting the, you know, the customer the right product.
Speaker 1:Yeah. Who are your heroes in the open source space? Are you a Red Hat guy? GitLab guy? What do you like?
Speaker 10:Yeah. I mean, you know, obviously, yeah. Red Hat, GitLab. I mean, I I very much jumped into the open source space, like, in open source AI.
Speaker 1:Sure.
Speaker 10:So so, like, as much as I guess, they're now a huge competitor of ours,
Speaker 2:you
Speaker 10:know, Mistral is huge, you know, the OG Lama team.
Speaker 1:Yeah.
Speaker 10:You know, Deepsea, Quint, like, these very people
Speaker 1:Yeah.
Speaker 10:That they inspired me to try to compete with them. So it's kind of this very,
Speaker 1:you know, inspired you to grind harder. Yeah. Hit that hit that bald eagle sound. Thank you so much for coming on your show to break it down. Yeah.
Speaker 1:Alright. Congratulations on all the progress and congratulations.
Speaker 2:We'll be looking out when what's the timeline here? You think you'll get it?
Speaker 10:It was supposed to be earlier. We got some GPUs. Didn't wanna load up. So it'll be here We're
Speaker 1:gonna be live for a couple more hours. Ping us.
Speaker 2:Will ring the call
Speaker 1:in the chat on XCV. When it's officially launched.
Speaker 2:Talk about it.
Speaker 10:And we'll we'll, you know,
Speaker 1:Thank you so much for hopping on the street. We'll talk to you soon. Cheers. Good. Bye.
Speaker 1:Me tell you about Sentry. And I need to find Sentry. There we go. Sentry shows developers what's broken and helps them fix it fast. That's why a 150,000 organizations use it to keep their apps working.
Speaker 1:Gotta talk about this. Plant
Speaker 2:daddy. Plant daddy.
Speaker 1:Gotta get him
Speaker 3:on the show.
Speaker 2:Exposing his local coffee shop. He says, a friendly reminder that my local coffee shop is running a bot farm to boost engagement. I'm talking a very small business. Imagine at a country scale. If you're still responding, reposting anonymous accounts with zero vetting, you're being used like the idiot you are.
Speaker 1:This is crazy. Yeah. So there's this video, and this this, local coffee shop, his favorite local coffee shop has a bot farm set up in their back room to boost Instagram engagement specifically. I
Speaker 2:Does this person not know this that you can just
Speaker 1:Also, why did he let Kevin back there to video this and it's like op sack at this at this coffee shop is atrocious. If you're doing look at the fan at the end. If you scroll the end of this video, can see that there's just a fan blowing on all the phones. You see this fan right there? That is crazy.
Speaker 2:This seems like such an insane thing to spend money or time.
Speaker 1:I was about to say. What is the ROI here? So they get an extra 50, maybe a 100 likes and comments on every post. And is that enough to drive you know, this looks like thousands of dollars of equipment. They're selling more coffee because
Speaker 2:It's a lot of iPhones.
Speaker 1:It is I think they're probably Android because they need to be USB c'd in and controlled
Speaker 6:Right.
Speaker 1:Right. So it's a
Speaker 2:little bit total total waste of time. I I've never gone to any of my Yeah. Local coffee shops.
Speaker 1:Because of Instagram?
Speaker 2:Instagram, I
Speaker 1:know of. This is what advertising doesn't work on me. Advertising doesn't work
Speaker 2:on me. Coffee but the engagement here
Speaker 1:It's too low.
Speaker 2:Math.
Speaker 1:I don't know. I don't know. Well, I I would love to know what that proprietor, what that store owner
Speaker 2:thinks about the ROI on podcast. Some posts recently
Speaker 1:Yeah.
Speaker 2:That are kind of outside of the the the sort of tech bubble.
Speaker 3:Yeah.
Speaker 2:I'll scroll through and look at the comments Mhmm. And there and and every single comment is AI. Okay.
Speaker 1:Like, just straight up. Yeah. Not copy pasted.
Speaker 2:Not copy pasted, but clearly, it's like an AI that's just like Yeah. Responding.
Speaker 1:And it's just on
Speaker 2:it.
Speaker 1:It's loosely Adding engagement.
Speaker 5:It's It's
Speaker 2:isn't this isn't that. It's this.
Speaker 1:No. No. No. It's it's happening more and more. Anyway, let's move on.
Speaker 1:We have Bridget Mendler from Northwood Space. She's the cofounder and CEO returning to the show. It's been Back. Just under a year, but she's back. Bridget, great to see you.
Speaker 1:How are you doing?
Speaker 2:In a much bigger facility.
Speaker 1:Yeah. What's going on over at Northwood? Break it down for us.
Speaker 12:It's it's good. We are sorry. We just turned on I just started blasting eighties music in the office. Amazing. But we're good.
Speaker 12:This is the this is being on a manufacturing floor lifestyle at Northwood. And, yeah, we are announcing our series b fundraise.
Speaker 1:How yeah.
Speaker 2:$100,000,000. Even. Nice nice round numbers.
Speaker 12:Not a cent more, not a cent less.
Speaker 2:And some other some other numbers too. Yes.
Speaker 12:Yes. Some other numbers. Yeah.
Speaker 2:More importantly. We
Speaker 12:that's right. Exactly. Customer customer is key. We we raised 49.8 in a contract with the sorry. I'm getting a little bit of background noise.
Speaker 12:But yeah. You're gonna get more
Speaker 2:a
Speaker 12:billion dollar
Speaker 1:Congratulations. Amazing. Amazing. About the actual progress. I mean, I remember hearing about this from Deleon when it was, like, just an idea.
Speaker 1:And then and then I think I saw a video maybe with Jason Carmen, the first deployment. You're building this. Like, what is the scale of the deployment? How are you I mean, you're in a manufacturing space. How many people are working there, or how many of these things are you building?
Speaker 1:Explain this to us.
Speaker 12:Yeah. Yeah. We we're at our 35,000 square foot manufacturing facility now. I think we we've moved in here thinking this was gonna be a a long term home for us, but as I'm sure a bunch of these companies say, fills up really fast. Yep.
Speaker 12:We had have had a busy year. It's been a year of, you know, going from early concepts with some exciting problems that we were looking to solve on the ground side. We're looking to address scaling up communications to a bunch of different orbits, really pushing the boundaries on where you can take dynamic space capabilities. Our phased array was really well aligned with that. So we kinda built out the solution, and we took it through to deployment.
Speaker 12:We can successfully say that now we have actually done production on eight portal units. They're produced in this factory in the span of four weeks. Yeah. We shipped them out. It actually got shipped out on a commercial airliner to its destination halfway around the world and was up and running as soon as it hit the site within twelve hours.
Speaker 12:So Wow. All in all, from the time of our contract signature to actually being ready to take satellite passes is a three month time period. So we're we're excited by that. Wow.
Speaker 1:And and walk me through sort of, like, the like, I've seen these memes of like you ask a question on Google and it takes you through like, you know, you go through the fiber optic cable, you go to the base station, you go to cell tower. Like walk me through the actual, you know, use case from someone trying to use the Internet and then interfacing like Northwood is in the chain somewhere. Like, what is the full chain?
Speaker 12:No. That's a really great question because a lot of the ground equation has been kind of these fragmented pieces. Right? Like, I can imagine it's it's confusing. It's like, oh, there's this one piece of hardware, whether it's a phased array or a parabolic or whatever.
Speaker 1:Yeah.
Speaker 12:How does that fit in with, you know, me making use of Internet through space? Yeah. And the real the real point for us is that we are saying space companies shouldn't have to consider the ground equation when they're running their own business. They shouldn't be trying to navigate, you know, land leases in all of these countries around the world to make contact with their spacecraft. What Northwood does is we we own the entire stack.
Speaker 12:So we handle from the moment that there's a contact made with the spacecraft all the way to the the point of presence somewhere around the world that a spacecraft operator has themselves hosted, that that entire chain. So that includes hardware, that includes modem, that includes network backhaul, that includes software interfaces, APIs, and the actual control plane for moving that data. That's kind of a stack end to end on ground that hasn't been managed by a third party ground provider before. And so that's what gets us excited because when we take on that big that big chunk of the pie, we actually free up a lot of mental bandwidth and and speed for space companies.
Speaker 1:So for a space company, they're putting a satellite in orbit for some reason, whatever they're doing, when are they calling you? When are they making sure that they're compatible or ready to integrate? Is that, presumably before launch, but does it need do do they need to do anything special on the actual
Speaker 2:Hopefully, they're not calling after their existing solution.
Speaker 1:We just took off, and I'm hoping you can connect us.
Speaker 2:Help us make contacts.
Speaker 1:Yeah. It's kinda like when you move into an apartment, then you call Spectrum, like, after,
Speaker 6:and you're like, don't have Internet for two weeks.
Speaker 12:Like, here we are. Yeah. Contactless. But, no, I mean, that that's a little bit like the situation with the satellite control network with US government right now. Yeah.
Speaker 12:These are for satellites that are already live and operating. That's what our contract is against. Mhmm. It ranges for a ton of functions. So launch every launch that takes place in The US runs through That's
Speaker 1:how you know. Sorry. Control our warehouse.
Speaker 2:Your facility is big because your team is scootering around.
Speaker 1:Around. It is big. You've been lying about 35,000 square feet.
Speaker 2:We have
Speaker 1:a lot
Speaker 12:of passion for our scooters here.
Speaker 6:Very It's nice smooth floors.
Speaker 1:Anyway, sorry.
Speaker 12:It's it's a great ride. It is. But yeah. So so it it serves a ton of a ton of missions, and more missions are getting launched every day, and so that puts additional strain on capacity.
Speaker 1:Yeah.
Speaker 12:So for us, you know, for instance, in that contract, they're calling saying, hey. We need more capacity. Mhmm. We are needing you to plug in with where we route our data. So we we just hand them an API, and that's how they interface with it.
Speaker 1:Yeah.
Speaker 12:So they can just connect with the API. Satellites keep doing what they have been doing sometimes for decades. Yeah. And then when their new satellites launch, they can also use that same interface. So trying to make it as clean and simple as possible.
Speaker 2:Yeah. What is your what is your pipeline look like? Like, I imagine I imagine you're you're talking to a bunch of companies that are, planning to get, you know, various satellites up in on the one year, two year, three year, like, how many like, are are you feeling like an acceleration is
Speaker 1:kind of
Speaker 2:what I'm getting at in terms of, like, more mass to orbit?
Speaker 12:Yes. Big time. We do get a lot of customer inbound, and I think, like, that's a large part of our raise for us. It's like, hey. We need to be able to expand and grow so that we can service all these important missions.
Speaker 12:I think an important piece of our passion for what we do is around serving diverse and ambitious missions. So a lot of our missions look pretty different. So for for our recent capability we're working on with space systems command that looks like dynamic spacecraft movement, you know, being able to hit multiple different orbits and and those kinds of capabilities. There are also communications constellations where, you know, they they have more of that networking backhaul use case that I I described to you. There's other ones that we work with that are more interested in timely imagery.
Speaker 12:And so for us, what makes us excited is being the ground expert that thinks about that with them from, you know, some of those conversations we have are extremely early. We're, like, we're we're asking them questions and and learning about their system and and they'll say, you know, we haven't thought that far yet. And so we get to be the partner from that very early stage to bringing the the constellation online, and really being the one that holds the accountability for that. So we get excited by kind of the diversity of the space industry. I'm sure, you know, you guys are hearing about all the different use cases even that popped up this past or, you know, data center space
Speaker 2:and a lot. Data center some some space data center players are probably calling you being like, hey, in ten years, I'm gonna have Ready.
Speaker 1:A lot
Speaker 2:of GPUs in space. Yeah. How many?
Speaker 12:Yeah. But, you know, let's let's condense that timeline. Let's condense that timeline on on all of the ideas. Like, you know, why why not? Space is an exciting frontier to push forward on.
Speaker 1:Yeah. What what what else are you are are you tracking in launch costs, actual cost of mass to orbit? That feels like a key barometer for the health of the space industry broadly. Is that progressing according to your thesis when you started the company? Are you ahead of plan?
Speaker 1:Obviously, doesn't doesn't directly matter for what you do, but obviously, it does in many ways because, you you know, you're downstream of that entire economy. Is that the right even metric to be looking at if you're monitoring the space economy?
Speaker 12:I mean, I think the economics of space have been something that have been challenging historically. You know, you need to be able to make a profitable business off of space. And so I think there's been a number of dominoes that have fallen in favor of that, whether that be, improved launch costs and, you know, dropping to to new levels in that and and other pieces of the space infrastructure stack. I think, you know, what we're building, we're also also interested in in making that more affordable. I think the proof is kind of just in the dreams that people are dreaming up and actually putting real dollars behind now.
Speaker 12:Mhmm. So, you know, it's it's one thing to talk about some ambitious space concept. It's another thing to put, like, real dollars behind it and a real timeline against it. And so for us, like, that's that's what we wanna enable is that, like, concept to reality timeline, like condensing that, making that more possible. Surprisingly, the ground actually takes longer to build than it does to build the spacecraft and launch it in a number of different instances.
Speaker 12:And so that's just silly. Like Yeah. Yeah. Let's let's be the enabler instead.
Speaker 1:Yeah. Can you help me understand deploying ground stations globally? Are there treaties for this type of thing? Do you call other governments? Are you active in other countries?
Speaker 1:Like, I I imagine that, you know, there are obviously some, I guess, like, geostationary orbits that just orbit over The US. But if the my satellite's on the other side of the Earth, I'd probably wanna talk to it. How do you solve that? What's involved? What's the rollout like?
Speaker 12:No. Totally. We we have an entity in a number of different countries. So, yeah, we have entities on, I think, like, three or four continents at this point. Okay.
Speaker 12:So you basically need to establish the business there. You need to work with the local governments across a bunch of different dimensions. I think, personally, that's something that I think is really exciting to support with the space industry. Right? Like Yeah.
Speaker 12:A lot of countries are really passionate about pushing their space capabilities forward. And so for us to be able to have them be a part of a larger mission as we build out our our big network, but also to support what their ambitions are with space is something I feel interested in. And then from a logistics standpoint, I think that's like a key case in point for why if you set out to build a space mission, why do you have to go, you know, create entities, land leases Weird. Local regulatory. Yeah.
Speaker 12:It's just a totally different business. Yeah. And and so I think, you know, that's something that we are very happy to be burdened by.
Speaker 1:Yeah. On the on the regulatory side, are you interfacing with NASA or the FCC? What does that look like? And then does that does the regulatory architecture that's put in place in The US sort of carry forward into other countries? Burdened
Speaker 12:Yeah. That's a great question. There there's some pieces of it that do crossover internationally. We deal with the International Telecommunications Union Sure. For certain pieces of it.
Speaker 12:Depends on which direction you're talking about from space to ground or ground to space. And then the FCC is is really the main regulatory body domestically, but they need input from NASA. They need input from a bunch of other government stakeholders. So a lot of folks weigh in when it comes to spectrum, which is, you know, for nerdy folks like me, that's kind of interesting.
Speaker 2:Yeah. What is, what is the main bottleneck, if anything? It's it's surprising to hear some of the some of the timelines you're talking about on the hardware side. You said four weeks. Yeah.
Speaker 2:To to to make and and ship out the hardware and get it in production. Feels fast. What what is like, where are you trying to speed up?
Speaker 12:Ground is, like, such a multivariable problem. It comes down to supply chain for sure. It comes down to deployment, like, what is actually efficient and easy to ship to anywhere around the world. It comes down to licensing and, a whole host of other regulatory approvals. So us, like, that's why we find that it's really useful to be vertically integrated because we can actually think of those constraints at every different piece along the chain.
Speaker 12:So, you know, when we when we see a bottleneck like, hey. There's this supply chain limitation. We get to design around that and think about how that fits into the overall system. So I think we've we've been coordinating all of those pieces well so far. You know, new challenges are gonna continue to pop up, but I think that comes down to just having a team that is multidisciplinary.
Speaker 1:Yeah. I wanna know more about the use of funding, a $100,000,000 fundraise. Obviously, more hiring and and and more acceleration broadly, but is are there any, like, pieces of equipment that you're gonna be buying for manufacturing? Is there a, like, a robotic arm that you've been hovering over the checkout button and now you're clicking it or a CNC machine? Like like, what what will what will transform about the actual manufacturing process with this race?
Speaker 12:Yeah. Like, getting concrete.
Speaker 1:Concrete. There we go.
Speaker 12:Yeah. I I think well, actually, that's that's
Speaker 1:Are you right? To buy concrete? Maybe.
Speaker 12:Oldoldspacecom old ground companies do need to buy a ton of concrete.
Speaker 1:Yeah. Because the the pad, right, that you actually put it on. Right?
Speaker 12:Exactly. That's funny. You have settling time.
Speaker 1:Just Oh,
Speaker 12:let the concrete dry. Yeah. It's a whole factor in the equation. But but, yeah, for us, it's really about a new scale of production. Mhmm.
Speaker 12:So, you know, we we've demonstrated this end to end process for smaller scale missions. Now it's okay. Cool. Can you do that at at a larger scale reliably? And so that comes down to, like you said, bringing some stuff in house.
Speaker 12:Yeah. So that's that's our our PCB line, for instance. That's something that we're interested in bringing in house. Oh, okay. We have different testing fixtures that we have in house.
Speaker 12:We have a a big anechoic chamber over here.
Speaker 1:Oh, yeah.
Speaker 12:Wow. That's cool.
Speaker 1:Good podcast studio too. Right? Isn't it like dead quiet in there?
Speaker 12:That's true. It is.
Speaker 1:There you go.
Speaker 6:It's kind
Speaker 12:of yeah. I'm tempted to show you, but anyway. No.
Speaker 2:It's alright.
Speaker 1:But It well, Bray will probably cut the WiFi out. Right?
Speaker 12:Exactly. Yeah. It would cut the WiFi out.
Speaker 1:The audio quality would be great, but we'd lose connection. So
Speaker 12:Pristine. Yeah. But, yeah, we're we're gonna be moving into a bigger space as well so that we can, you know, accommodate more production volume. Also, you know, like Yeah. This this stuff takes up a lot of space Yeah.
Speaker 12:A lot of hardware. We're we're moving it through rapidly. We're looking to hit a rate of 12 units per month for one product line and then another volume for another product line.
Speaker 1:That's very good news.
Speaker 12:There you go. So, yeah, that that's some of the expenses.
Speaker 1:Amazing. Well, thank you so much for taking the time.
Speaker 2:Fantastic progress.
Speaker 1:Chat with us. Yeah. Remarkable progress in in under a year. I can't wait for the next one. We will see you soon.
Speaker 2:Yeah. Congrats to the whole Have great rest of you guys. Very good chat. Good to see Have
Speaker 12:a good rest of your day.
Speaker 2:Cheers.
Speaker 1:Let me tell you about Gusto, the unified platform for payroll benefits in HR built to evolve with small and medium sized businesses. And without further ado, we
Speaker 2:Who do got? We got Jeff?
Speaker 1:Jeff Miller. It's Miller time. We got Jeff Miller.
Speaker 2:Billing in. Anderol
Speaker 1:for Paul. Second time. You're the first repeat live in person guest of the UltraDome. Friend of the band. Welcome back to the show.
Speaker 1:Welcome back to the UltraDome. Second
Speaker 2:How do we get one of these?
Speaker 1:Look at this.
Speaker 2:People are always asking
Speaker 1:us for jackets. Oh, yeah.
Speaker 8:I'll trade you a jacket for a tiny gold plaque here.
Speaker 10:Okay. Somewhere in
Speaker 1:the Yeah. Yeah. Yeah. Yeah. Yeah.
Speaker 1:This is a record. This is a record. Love it. Yeah. Fantastic jacket.
Speaker 1:Those are gonna be flying off the shelf. Get us up to speed on the Andy Roe merch store. I mean, you were doing some like you did like an auction on eBay. Take us through.
Speaker 8:Absolutely. So actually, Jen Yeah. Bucci and I were cooking on this TPPN. TPPN.
Speaker 1:Keep it on here.
Speaker 8:So, the way we're thinking about the gear store, and this is something, by the way, we talk often with our our pal Trey also. Yeah. That we're thinking about ways that for our friends we can bring them into annual. So, beyond just following us on on X. Or watching our videos on YouTube Yep.
Speaker 8:That they can participate the brand in a way that they would want to. So, we're gonna be leaning into it hard to share Cool. With NASCAR. Yeah. It's a platform with Ohio State.
Speaker 8:With every campaign that we do Mhmm. We're gonna have some staples like the Flight Jacket that will become much more easily acceptable accessible, I should say. And then we're gonna find some items that we'll just call high heat items that we're we're already putting on. And the closest thing I can say is Yeah. You think about what we did with the Chromatic with our friends at Mod Retro Sure.
Speaker 8:And and pulling that into an Andorl edition, what we're gonna do with the m 64, think along that vein. So when those come, be ready because they're not gonna last long.
Speaker 1:Okay. Yeah. Take us through the racing update. NASCAR is coming up, but you're also gonna be racing drones now.
Speaker 10:Yeah. Take it down first.
Speaker 3:Absolutely. Hey, why not?
Speaker 8:Yeah. So, of course, we've got NASCAR. We're just about a hundred and fifty days out. I expect to see both of you guys Down. On the base.
Speaker 1:On June 21.
Speaker 11:June 21.
Speaker 1:It's gonna
Speaker 7:be a
Speaker 8:lot of fun.
Speaker 2:Are we gonna be able to be on the carrier? What's going is it will there be a carrier there? There. Or they're needed?
Speaker 1:I can't
Speaker 2:speak to the But why?
Speaker 6:It's how it works. They don't answer me.
Speaker 1:There may
Speaker 8:be one or multiple carriers on board and so we'll
Speaker 3:see what we can do.
Speaker 8:Cool. But the big thing I'd say is like as we think about our partnership strategy broadly, we have, as we talked about last time, something that's broad gen pop that crosses over with our core audiences in defense and military
Speaker 3:Mhmm.
Speaker 8:Like the Andrew Roll two fifty with NASCAR. We have something that's tied very clearly to where we have a manufacturing footprint with Ohio State. Mhmm. We're well on our way to building out Arsenal One, as Grim spoke about last week, hiring those 5,000 jobs that we committed to. The important thing, I think, for us is making sure that we still stay true to who we are across all these things.
Speaker 8:So I think about it as a spectrum. And if that's about general population or how we work our ways into communities, at the core, we are an engineering company.
Speaker 1:Yeah.
Speaker 8:That autonomy, if you think about it, has been at the core to this date of everything that we built. Sure. And so, we want to make sure we have something that is not just a marketing play, something that feels much more about recruiting and standing for those values around autonomy. And so, what is really just bringing you into the world of how this came to be, once we got the commitment from Palmer and the other execs that we were going to do the annual two fifty in Ohio State, Palmer said, Jeff, I'll let you do those things, but what you're gonna do is build me a global AI drone racing league. And I'm like, please tell me more, Palmer.
Speaker 8:I'm like, said like drone racing league? He's like, no, no, no. All the drones Yeah. Have to be the same. The only differentiator is the software.
Speaker 1:It's the software.
Speaker 10:It's the code. Okay.
Speaker 8:The ability to build autonomy. And so that's
Speaker 2:what we've been working on since Yeah. So the idea the idea here is people know they're gonna be racing drones. We have goalposts here. I can imagine, like, something like that. They know they're gonna have to be flying a route
Speaker 13:That's
Speaker 2:correct. Like a track, but they I'm assuming they don't know what the track would actually look like until race day.
Speaker 6:They have
Speaker 2:to actually build
Speaker 8:It's gonna be amazing. So the way we're doing this is we're working first and foremost with the Drone Champions League, which is the foremost operator of of AI drone racing in in the world. Mhmm. So we've got them as our official race operator, and we're working off of the model that they've built and they've tested and forged like a really viable path. So it starts with virtual qualifiers.
Speaker 8:Anyone can compete in these virtual qualifiers.
Speaker 1:It's a simulator.
Speaker 8:It's a simulator. Exactly. And that will lead to a physical qualifier where you're going have gates that you have to go through. And the top teams that qualify both from the university level and across the globe, because it's going be an open competition, those will qualify for the first official AIGP Okay. In Columbus, Ohio.
Speaker 8:And there, you're going have time to prep, refine your code leading up to the actual race day, and that's where all systems go.
Speaker 1:Yeah. What do you think the average team will look like? I'm thinking back to like the DARPA Grand Challenge. I don't know if that was inspiring at all, but the teams from there, mostly academic teams, if I remember. What do you think the mix will be?
Speaker 1:Have you already talked to teams? How's
Speaker 8:that going? So we've done a lot of research on on the approach to this.
Speaker 1:Yeah.
Speaker 8:The clear mandate from our friend Palmer was this is open to anyone. To anyone.
Speaker 2:This is
Speaker 8:not just 18 to 22 year olds. And there's a point we're talking about like, how can children
Speaker 1:race this? Right? Yeah. Yeah. Children, but also like the Tesla team, the Waymo team.
Speaker 1:They're gonna be like,
Speaker 6:let's just win.
Speaker 8:And so what I give our team incredible credit for
Speaker 2:Yeah. Also the big primes.
Speaker 6:Let them let them know
Speaker 2:that. Hey. The big
Speaker 8:primes thing that they can race.
Speaker 1:They have an opportunity here. The funniest thing
Speaker 8:ever. National thinks they could come in here
Speaker 6:and race and win this. We're get some
Speaker 8:money But let's go. And that will prove something there in its own right. It's our capabilities in the West Yeah. Relative to China.
Speaker 1:I mean, all yeah. All the all the LLMs are on
Speaker 2:The DJI factory team router. Okay. Okay.
Speaker 1:But
Speaker 8:Yeah. I think the things that are most important Yeah. Is at the core, we are using this as a recruiting effort. Sure. Thinking about cracked engineers, especially at the university level.
Speaker 8:Yeah. We've done incredible diligence on the legal side to make sure when we say things like 500 ks prize pool, that it's eligible for anyone to race. Sure. That you could win a job at Annual. Yeah.
Speaker 8:All those things are done in a polite and thoughtful way. And I think most importantly, that we're setting a standard with our partner in hardware
Speaker 1:Yeah.
Speaker 8:Your friend Soren.
Speaker 1:From Neros. Yeah.
Speaker 8:That we are using incredible technology that's gonna have clear chain of custody here in The States.
Speaker 1:Dude, we gotta get Soren to fly a drone in here. Have you you've never seen him fly a drone in person?
Speaker 2:Not live.
Speaker 1:So Soren is Soren Monroy Anderson from CEO of Niras and founder. He was, I believe, like a champion drone FPT drone. Drone racing champion
Speaker 8:also competed in in the DCL as well.
Speaker 1:Yeah. And so he puts on this I I I went out with Ben. Ben actually filmed it in El Segundo. And he's like, let me I I do a little, like, factory tour with him. He has a very small office at that point in time.
Speaker 1:The company had just got off the ground. He's like, let's walk to this park. I'll show you how these drones work. And I you know, I've seen like a DJI camera drone like take off and it hovers and it maybe like does a little selfie zoom out or whatever. His drones, it's a completely different level.
Speaker 1:It's a completely different level. He takes off and it's the most aggressive. It's the f one car of drone racing. And he puts on these glasses, the FPV goggles, and they're like CRT TVs. They're like high refresh rate, pretty low res actually.
Speaker 1:But he's like flying around this tree like as fast as I can possibly see. Doesn't crash anything. Flies up right back right in your face, all around you. It's crazy.
Speaker 8:It's so great. And obviously, at Andrew, we know a thing or two about
Speaker 1:Of course.
Speaker 8:Making drones. Yeah. And we have great respect for for Soren and Yeah. And the Nero's team. Yeah.
Speaker 8:And what's a funny story, this is the first time I was here in person at the whole time. You know who your guest was directly before me?
Speaker 1:Yeah. Was Soren.
Speaker 8:It was Soren.
Speaker 1:That's right.
Speaker 6:And you guys asked him.
Speaker 8:I was laughing because you said, hey. Have you guys ever thought about starting a drone race? Oh, we did. Had we had not talked to him yet. No way.
Speaker 8:We already were planning to. So I just sat down with serendipity. All started right here in the Ultradrone.
Speaker 1:I love it. I love it. Yeah. So talk to me more about what it takes to actually deliver software on these drones, how standardized that is. Like, I like, I imagine you're not pulling in a Frontier LLM and having it reason over this stuff.
Speaker 1:Like like
Speaker 2:hold on, boss. I'm gonna wait at this gate.
Speaker 1:Yeah. Yeah.
Speaker 2:This is ten minutes of reasoning. Let me do a deep research report.
Speaker 1:Let me fully understand the the the scope of the track. Like, what like what you know, give me anything on the technology side. Like, are the parameters? What are the languages that people will use? Do you know anything about what people are trying
Speaker 8:The beauty is we're trying to keep the rules extremely simple. Yes. So the core focus is that everyone is gonna have the same hardware. Hardware. We're working with Nerios right now
Speaker 1:Okay.
Speaker 8:And we'll be announcing this in in a future date.
Speaker 1:Okay. The
Speaker 8:beauty too is like everyone's gonna have their own canopy. We're bringing a little spirit of NASCAR as we think about sponsors and Yeah.
Speaker 2:How you can Delivery.
Speaker 8:Your own branding We
Speaker 2:should sponsor
Speaker 1:a team. We should. This is really good.
Speaker 8:This is happening.
Speaker 1:Yeah. Yeah.
Speaker 8:Their team. It just makes natural sense.
Speaker 2:If you wanna if you wanna race in this, hit us up.
Speaker 8:Guys are So we'll talk to you guys about how you bring your team together. But from a tech side Mhmm. It really is the beauty is that once you have the hardware Mhmm. Everyone is going to be able to be on an even footing
Speaker 1:Yeah.
Speaker 8:To bring together whatever they wanna do and however they wanna do it. Yeah. And where I think the real advantage will come
Speaker 3:Yeah.
Speaker 8:When people spend time with the physical qualifier
Speaker 1:Sure.
Speaker 8:Show up there, break the thing a 100 times. We talk about this at at Andrew all the time. Yeah.
Speaker 3:Yeah. Fail. Fail. Fail. Fail.
Speaker 8:Sure. Win. Yeah. That's the way we think about it. And I think that model, that approach
Speaker 1:Yeah.
Speaker 8:That that ethos applies here too.
Speaker 1:So how do you keep a level playing field around hardware when drones are breaking and they are smashing? Is it like, oh, you get an allotment of five and then you're out?
Speaker 8:We'll have exactly. Clear chain of custody.
Speaker 1:Okay.
Speaker 8:All credit to DCL and Niros because they're controlling the hardware component. But we've planned out and because of their experience, we know how many are gonna break along the way. But there's not gonna be any opportunity for anyone to be making mods
Speaker 1:Yeah.
Speaker 8:Beyond what we give them officially.
Speaker 2:Okay. That's cool. Cool.
Speaker 1:Are there other like, will people do you think people will have the ability, like, overclock motors? Because a lot of racing, you're of course, in NASCAR f one, it's like tire management, fuel stops in certain races. We just saw this with the Rolex 24. Yeah. Exactly.
Speaker 1:At what level does it stay from just perception doing simultaneous location and mapping, pathfinding to actually understanding like, I could push the drone hard 24
Speaker 2:but then running the hour battery. Hour 20 the endurance Yeah.
Speaker 1:Drone race. Yeah. Yeah. Like, how many times do you change?
Speaker 8:I think what you'll see is the battery is pretty lightweight, but for the the distance of the race itself
Speaker 3:Yeah.
Speaker 8:You're gonna have enough battery load. Okay. But it really will become to, like, finding all these little
Speaker 1:Yeah. Yeah. And there'll be risk. You cut corner a little bit closer How
Speaker 8:you're doing it, you're understanding the hardware better
Speaker 1:than the
Speaker 8:next and what risk
Speaker 1:is case. Interesting. Interesting.
Speaker 8:But for us, like Yeah. What I'd say here is really special
Speaker 1:Yeah.
Speaker 8:Is beyond the fact that we're starting in Columbus.
Speaker 1:Sure.
Speaker 8:We're already working with Palmer in two really interesting ways. Like Yeah. We have plans to roll out the second GP
Speaker 1:Okay.
Speaker 3:In Asia Cool.
Speaker 8:That will be announced soon. Yeah. The third GP in The Middle East Cool. And the fourth one beyond in the globe. Cool.
Speaker 8:And right now, we're starting with quadcopters.
Speaker 3:Okay.
Speaker 8:The important element of the AIGP
Speaker 1:Yeah.
Speaker 8:Is the autonomy. Okay. It's not the form factor.
Speaker 1:Sure.
Speaker 8:So just know that's something that could come to life underwater in different domains over time. Oh.
Speaker 3:Water would
Speaker 1:be cool. Feels, yeah, harder to film and stuff, but could be really cool. Yeah.
Speaker 8:Well, let me just say that's the first of many domains Palmer's
Speaker 1:Yeah. Yeah. Of course.
Speaker 6:I want
Speaker 2:to space Space.
Speaker 1:Tunneling ones.
Speaker 8:Geordie said it, I didn't.
Speaker 2:Yeah. Yeah.
Speaker 1:That that that would certainly be great. What do you think teams will look like? Are they unlimited amount of people? I can show up with a thousand
Speaker 8:So, can show as an individual. We think the teams that are going be really successful are going show up between four and eight people. Okay. It's capped at at eight people.
Speaker 1:Two beats a team. Exactly.
Speaker 8:Yeah. And so, the the goal would be that you're we're talking to the all the universities that are gonna express interest. We target universities at Annual that really feed our pipeline of emerging talent. Sure. And those teams, we're hoping to get really excited about this.
Speaker 8:We think the prize pool is gonna be a real incentive. Yeah. But also that opportunity to win a job at Andoril.
Speaker 1:Yeah. Yeah. And it's good it's good like resume builder, content, whatever marketing. There's so many different ways
Speaker 2:Winning winning a job at Andoril when I think anybody that can get into the top five. Yeah. Probably every person on the team Yeah. Is qualified or at least some percentage of gonna be very
Speaker 8:incredible. And also why our lawyer now has a lot more gray hair than he did. Sure. But the important
Speaker 2:Doing any of these like, giveaway contest thing at scale, there's so much, like, legal headache with it. It's not as simple
Speaker 8:as Exactly. But luckily for us, I think whether it's thinking about legal constraints for this, what our people at Anero across divisions do is they see opportunity Yeah. And they see how they can create solutions. But the the thing that gets me excited is like beyond whoever wins and earns the job Mhmm. Is that every university team member that shows up to the qualifier, which is gonna happen near our HQ in September, will get a screen directly by Andor recruiting.
Speaker 8:So if you're somebody that is interested in this, if you're somebody who's looking for an entry level job or internship at Andorl, this is a great way to feed into our pipeline.
Speaker 1:Yeah. Can you tell me more about the new Long Beach office? What's going on there?
Speaker 8:Oh, man. Well, as somebody who lives in Venice, California and works in Costa Mesa, can I just say
Speaker 6:I'm extremely
Speaker 8:happy that we have a Long Beach office coming? It's incredible. I mean, the story writes itself from from Palmer's origin to to where we are now.
Speaker 1:Oh, yeah. That's where the first, like, what was it? The airstream or something?
Speaker 8:100%. He's looking up and down by
Speaker 1:the river.
Speaker 6:Right? So That's actually true.
Speaker 8:It's incredible to to see it come full circle. Down by the marina. Yeah.
Speaker 6:It wasn't really
Speaker 2:a river. Down by the river.
Speaker 1:No. It was basically
Speaker 8:was a cave. Any rivers in LA.
Speaker 1:LA River is rough.
Speaker 8:But it's it's really special. Yeah. The origin story
Speaker 1:Cool.
Speaker 8:The fact that it's a reflection of of our growth, our maturation
Speaker 1:Yeah.
Speaker 8:The engineering talent that we're gonna be able to recruit Sure. Not just in Orange County, but now closer to LA.
Speaker 1:Yeah. Yeah.
Speaker 8:And and ultimately, whether you're working in SoCal Ohio or beyond
Speaker 1:Yeah.
Speaker 8:We're still gonna be screening for the same thing. And that starts with the mission, the connection to to what we're building.
Speaker 1:Yeah. How big is the Orange County campus now? It's like
Speaker 2:5,000 something. Oh, yeah. Oh, sorry. No. The new
Speaker 8:the new 5,000. The the current one's a little smaller than that. Okay. But it's it's the type of thing that we're constantly building.
Speaker 1:Won't 5,000 get square feet. That's pretty big.
Speaker 8:No. People that that we're bringing in.
Speaker 6:Yeah. Oh, that's very few.
Speaker 8:But to be bringing over a million square feet to Long Beach and to be doing it directly with the mayor of Long Beach who's been incredible and his team. It's just been really cool to see come to life.
Speaker 1:That's great. That's great. Incredible. Else is on the horizon on the marketing side for Andoril? Did you look at Super Bowl ad?
Speaker 1:Super Bowl's coming up?
Speaker 8:You know what?
Speaker 1:What else did you look at?
Speaker 8:So I'll tell you one thing. The core focus for us this year is absolutely showing the raw, the real, the product development. Yeah. Failures, failure fares that lead to the wins, the hard work. Yeah.
Speaker 8:The scalability that we're seeing is reflecting that story. So, I think that's the important inflection point for us in '26. Yeah. It's gonna be less about the highly produced go to markets.
Speaker 3:Yep.
Speaker 8:And it's going to be about, we told you we were building these things. Yeah. We are building them and we're going to show you how hard it is to scale, but that we are up to the challenge. And, you know, when we talk about this internally, we talk about demonstrating to our customers that Androle is not only the right choice, we are the safe choice, and we are the necessary choice for for what our country needs. So that's the story we need to tell.
Speaker 8:And how we do that is going to be about great world class product marketing that will likely look more transparent and raw than you've ever seen before. Yeah. And then, as we're thinking about working our way to to public markets, it's about building the annual brand and that could be through a drone race for recruits, it could be about a gear store or big major sports marketing platforms. But it won't be a Super Bowl commercial this year. In fact, this past weekend, we weren't at the NFL playoffs.
Speaker 1:Yeah.
Speaker 8:I was at a UFC fight
Speaker 1:Oh, okay. In
Speaker 8:Vegas, 324. Here
Speaker 1:we go.
Speaker 8:I'll tell you that. That to me is much more of of America and the audience that that I think has high crossover
Speaker 1:Sure.
Speaker 8:To and connections with with audiences that we see in in NASCAR. Yeah. And whether we do a partnership with them or not, I think the point is Sure. That we're looking to do things differently
Speaker 3:Yeah.
Speaker 8:Than traditional brands.
Speaker 1:Yeah. We're looking for
Speaker 8:partners that share our values and share our mission.
Speaker 1:Yeah. That makes sense. Do you think that the wait. On that, like, the the story that you're telling around, like, and scale and reliability and say the safe option, does that mean visually, you'll think you'll shift from product focused, you know, this, like, look at this amazing cool thing that does this thing to more of, like, highlighting what's happening at Arsenal, the manufacturing prowess, the scale. Is that the type of story you're trying to focus on?
Speaker 1:Is that what is that how this will be Those
Speaker 8:stories to me complement
Speaker 1:each other.
Speaker 8:What it means is we're going beyond a product go to markets where it's saying, hey, we're announcing this to the world
Speaker 3:Yeah.
Speaker 8:To thinking about the stages of development launch. We did a really great job, and this is the team I believe with Omen. Yeah. And we told why a tail sitter is so hard to produce. Yeah.
Speaker 8:We tap back into the history of tail sitters Sure. Across decades and what our engineers were able to accomplish to make Omen successful Sure. And all the rigorous testing that we did. We're gonna start to do that more with all of our products. But that doesn't stop with testing.
Speaker 8:It's about fielding. It's about putting in our customers' hands. Mhmm. And certainly, it's about your point around manufacturing at scale.
Speaker 1:Yep.
Speaker 8:So, that starts with Arsenal One. Why do we build it? The progress that we're making Yeah. The products that are scaling over time there and showing that the promises that we've made, we're able to deliver on.
Speaker 1:Very cool. Jordy, anything else? No. This is fantastic.
Speaker 11:I have one other Yeah.
Speaker 8:Really important announcement in the spirit of our front intern Tyler. Oh, yeah? Special day for you. It's your birthday.
Speaker 1:What? Was wrong
Speaker 8:with the first drink I had.
Speaker 2:No way. Oh, no way. He's iced. He's burnt off
Speaker 1:ice. Incredible. He's He's known
Speaker 8:as the nectar of life.
Speaker 1:The of life. Properly iced on the stream the first time ever. Incredible. People were talking about a buzz mode.
Speaker 2:Dude, great to see you. You're the man. Ice. Well, this thing is huge.
Speaker 1:That is a huge ice.
Speaker 2:Why don't you you're 21.
Speaker 1:Crack it open.
Speaker 2:Indulge. Enjoy enjoy a sip of of
Speaker 1:Nice. And
Speaker 3:I will tell
Speaker 2:Let's get the Tyler cam.
Speaker 1:Tyler cam. We'll we'll flip that around, and I will tell everyone about graphite. Oops. I just pushed Yosto. I'm sorry.
Speaker 1:First day on the board. Okay.
Speaker 2:Yeah. John's got a new board.
Speaker 1:I have a new board. Let's go with graphite.
Speaker 2:Here we go.
Speaker 1:Is it gonna work? Yeah. There we go. Code review for the age of AI. Graphite helps teams on on GitHub ship higher quality software faster.
Speaker 2:Love Graphite.
Speaker 1:Hunter Weiss, friend of the show, sent me this video. He did a Call of Duty edit over Uber Eats meal team six, New York City's elite special forces delivery unit. I I wanted to take a look at this, the meal team six.
Speaker 2:How did he how did he make the decision? Walk outside. Can we get
Speaker 1:Pull this up. Yeah. Pull up audio. Look at this. He's a good editor.
Speaker 1:That's funny.
Speaker 7:Be online. Fortnite is ace, delta, Snyder. Contact.
Speaker 1:Oh, he did the SD thing. Let's go. 2nd Floor balcony. We're gonna get the copyright strike for this, but it's worth it.
Speaker 2:It's worth it.
Speaker 1:It's worth it.
Speaker 6:Target acquired. Got eyes on target. Got a visual. I have a target. I got eyes on a target.
Speaker 1:It is so crazy how much snow is happening. We haven't been following at all, but US digs itself out from monster winter storm. People shoveled snow Monday in Boston, wherever 17 inches of snow fell in the weekend storm that had nearly 200,000,000 Americans under weather warnings. More than 710 household 710,000 households from Texas to Maine are still without power. That's very rough.
Speaker 1:Hopefully, that resolves quickly. Did you ever live in the snow? Have you ever lived in anywhere where it gets cold? Not. Tyler is the expert.
Speaker 1:Yeah. How's Michigan doing? We
Speaker 2:checked Michigan. The
Speaker 5:I I don't know if they've
Speaker 1:Are people snowed in?
Speaker 5:I think Probably? I think I thought it was a little bit further south. I thought it was like Tennessee's getting hit really hard.
Speaker 3:Mhmm.
Speaker 5:But, yeah, I hate snow. It sucks. That's why I'm living here.
Speaker 1:Well, where else should we go? We have our special guest joining in just
Speaker 2:Eight minutes.
Speaker 1:Eight minutes. Eight minutes. There is a clip from a friend of the show, Ben Hilack. He was he attended the OpenAI interview with Sam Altman and
Speaker 2:Town hall.
Speaker 1:Chief OpenAI hater Nick, of course, clipped it and put it in a negative context. He he says, you know, there's some quotes here. But let's pull up the question that Ben asked on this OpenAI stream.
Speaker 13:Discourse on Twitter and X recently about chat about GPT five's writing in chat GBT and being a little unwieldy, hard to read. Obviously, GPT-five is a much better agent model, really good tool use, intermediate reasoning, whatever. So it models feels are a little bit spiky or they've gotten even spikier, where some spikes like coding, got super high. Some spikes, like or it's very unspiky around writing. So I'm just kind of curious how
Speaker 1:OpenAI thinks about that logic. I
Speaker 9:think we just screwed that up. Will make
Speaker 1:I could only
Speaker 9:future versions of GPT five point x, hopefully much better at writing than 4.5 was. We did decide, and I think for good reason, to put most of our effort in 5.2 into making it super good at intelligence, reasoning, coding, engineering, that kind of thing. And we have limited bandwidth here, sometimes we focus on one thing and neglect another. But, I believe that the future is mostly gonna be about very good general purpose models. You know, even if you're trying to make a model that's really great at coding, it'd be nice if it writes well too.
Speaker 9:Like, if you're trying to have it be able to generate a full application for you, you'd like good writing in there. When it's interacting with you, you'd like it to have a sort of thoughtful, incisive personality and communicate clearly. Like, good writing in the sense of clear thought, not like beautiful prose. So my hope is that we just push Nick.
Speaker 1:Nick's in the chat. Oh, no. His
Speaker 6:ears are ringing.
Speaker 9:Dimensions. I think we will do that.
Speaker 1:Okay. Fair.
Speaker 2:We just read Nick. You built a brand. Everything.
Speaker 1:You built a brand. Yeah. I I mean, playing catch up now. I guess that's true. I guess that's true.
Speaker 1:At least in in in Ben's perspective.
Speaker 2:Nick puts John in the truth zone.
Speaker 1:True. No. No. I mean, I was looking on Ella Marina, the leaderboard for text, and GPT 5.2 is sixteenth, like well well below Gemini three Pro is number one. Grok 4.1 Thinking is number two.
Speaker 1:Gemini three Flash, Opus 4.5, Opus 4.5, Grok 4.1. GPT 5.1 High is ninth, and then you have to go down to 5.2 to get sixteenth to you have to go down to 16 to get to 5.2. So, yeah, it is interesting seeing the, like, the spiky intelligence things kind of turned into a stat bar of, like, you know, where are you putting the the, like, the points, the skill points or whatever. And they put too many of the points into
Speaker 2:will code say, don't want Yeah. ChatGPT to fix their issues with writing. I don't want it to be I I now am at a point where I'm like, thank you for making it very easy to clock when something is written by AI. I think
Speaker 5:that's totally like stated first for real preference. If you have like incredible model that writes something that you find like super compelling, obviously No.
Speaker 2:I'm talking about because people are using ChatGPT now to make scripts for videos. They're using it to make to make to do bots that are writing comments. And I know as soon as I can see something is just written by ChatGPT that I can just scroll past it and and basically ignore it.
Speaker 5:Yeah. Sure. But imagine like in the far future where those comments are actually like, wow, this is like very insightful and thought provoking and I'm glad that I read this text. Like, that's good.
Speaker 2:Yeah. Yeah. I think I think we can get there.
Speaker 5:Also, I back back in March, Sam tweeted that they they trained a new model that is good at creative writing that he released this whole story. Yeah. And I I think they've they've never really released that. Maybe it got vended in somehow to Yeah.
Speaker 1:Like, distilled a little bit. But But there were trade offs, clearly. And Yeah. Yeah. And it does seem that they
Speaker 5:And I I'm not sure that they actually did end up releasing.
Speaker 1:Yeah. I mean, the the the really interesting thing to apologize and steel man Nick's point here is is is that, like, should ChatGPT be focused on coding? Certainly, in the, you know, the how are they gonna compete with Claude Bot? They need a really great coding model. We'll talk to our guest in just a minute about, you know, how he's how he's using 5.2.
Speaker 2:He's ready.
Speaker 1:He's ready. So let's bring him in from the Restream waiting room. We have Peter Steinberger from Molt's boss.
Speaker 2:Man of the hour.
Speaker 1:How are you doing? Thank you so much for staying up late. What time is it for you?
Speaker 3:It's eleven.
Speaker 1:Thank you so much. We really
Speaker 2:appreciate it. PM for everybody that's
Speaker 1:just Yes. 11PM.
Speaker 2:Eleven So
Speaker 1:I'd love to kick it off with just a brief background on when you started this project, a little bit of your career, how you how you're thinking about it going forward, and then I
Speaker 2:This this was this was your very first project ever. Right?
Speaker 1:Yeah. Yeah. Yeah. First time coding. Right?
Speaker 2:No. We were we were enjoying, we were enjoying a a screenshot of your your GitHub profile earlier and just seeing, like Yeah. How many how many different things
Speaker 1:An overnight success.
Speaker 2:A true overnight success. Yes. But, we're super excited to have you here.
Speaker 3:Yeah. Awesome. Yeah. I'm excited to be here as well. Yeah.
Speaker 3:I don't know. I I worked for my own software company for thirteen years. Mhmm. And then I I sold it about four years ago. Then I was completely burned out.
Speaker 3:Mhmm. I did like I mean, it's it's TV, but still blackjack and hookers.
Speaker 6:Mhmm.
Speaker 2:Wild. Well, we're glad we're glad you're back in the game.
Speaker 3:Yeah. Yeah. You know you know that what they say, like, for every four years, it seems like one year break, and I did, like, thirteen years nonstop. So, like, three years, the mask kinda checks out.
Speaker 1:Okay.
Speaker 3:And then this year no. I mean, last year, not 2016. In April, at some point, my spark was back.
Speaker 1:Yeah.
Speaker 3:Because before, I was, like, I was sitting on my computer, and I don't know if you've seen Austin Powers, but it it it felt like someone sucked my mojo out. Sure. But, yeah, I I had time to to recover. I came back in April, and I wanted to do something new. My background was, like, a lot of Apple and iOS, and I'm a little bit fed up.
Speaker 3:I I wanted I wanted I wanted to build that stuff, and I didn't have the experience. I didn't wanna feel like an idiot. So I looked into AI, and it was good. It was not great, but it was good. And I was like, why is nobody talking about it?
Speaker 3:You know? And I feel like because I missed those three years where it was really bad, And I came back just at the time that the like, Clock Code was released, what, February in beta? Yeah. So this was my first experience. I was like, this is this is pretty awesome.
Speaker 3:Mhmm. And then and then I I couldn't sleep anymore. Like, I literally had trouble I had trouble going to bed. You know, like, we had, like, addiction before, and then, like, we had addiction again.
Speaker 6:But a
Speaker 2:but a positive one.
Speaker 6:Yeah. Well, yeah, I would say so.
Speaker 3:And I I hooked up a lot of my friends for looking into AI as well, and they had the same problem. And I texted them at, like, 4AM, and they replied. I even I even started a a meetup. That's where I come from. I call it I called it Cloud Code Anonymous.
Speaker 3:Now it's called Anonymous because you have to go with the times. Sure. And and, yeah, ever since then, I that's what I see on my profile. I came back from retirement to mess with AI. Yeah.
Speaker 3:And I'm having loads of fun.
Speaker 5:That's great. I love it.
Speaker 2:We Frank, maybe maybe walk us through some of the other stuff that you shipped and and worked on prior to this and and and even just kind of like your mindset working on these different projects. I'm I'm assuming at different points, you would think that some would get more attraction than others, but it would probably be impossible to have predicted in some ways that this would have gone from almost to the the point reason that this is so wild is I'm seeing people on Instagram that, like, I don't think of as people that, like, follow tech at all and they're at the Apple Store getting a Mac Mini. So it feels like it just went it broke containment, like, incredibly quickly and you see the GitHub stars are like, actually, I've never seen a chart like this. Every Straight up line. The last you know, every everybody loves charts, but the chart is actually unbelievable.
Speaker 2:It's just a line going straight up.
Speaker 3:I I I need to talk to someone at GitHub because I I don't think there's been a project before that that's been like straight. It is it is it is batshit insane. Yeah. I mean, honestly, my main mantra is I wanna have fun. You know?
Speaker 3:Like, the best way to learn these new technologies is if you have fun with it. You have to play with it. So I I build those things that I think could be useful. I try different languages. I try different approaches.
Speaker 3:It's again, the engineering I don't like the word white coding so much. I always make the joke. I I do, like, a gigantic engineering, and then when it starts hitting 3AM, I switch to vibe coding, and then
Speaker 2:I just
Speaker 3:have regrets.
Speaker 2:Yeah. You should've just gone to sleep, basically. Yeah.
Speaker 3:Yeah. Yeah. Yeah. Sometimes it's hard. But then I just I just build little things.
Speaker 3:I had this idea about personal agents in in in May already, and I I I tried. It was like the time that g b d four one was out, and I was just not good enough. And then I thought, well, all the big all the big companies will build this in the next few months anyhow. So so I was like, why why why the f should I do that? You know?
Speaker 3:I was just gonna wait, they make it better.
Speaker 1:Yeah.
Speaker 3:And I build up I'm not I don't I build a lot of stuff.
Speaker 6:There's, one project that is
Speaker 3:still unfinished that I, at some point, wanna finish. And I
Speaker 6:build a a lot of a
Speaker 3:lot of CLIs because that's that's where agents are really good. You know? You have to close the loop. That's always the the secret. You have to give you have to build it so that the agent has the best possible way to build software.
Speaker 3:And this is that's the the secret a little bit. I tried a lot of stuff, and then in in November, I looked and still there was nothing. Like, where is where is my fucking agent?
Speaker 1:Yeah.
Speaker 3:I I I had a little project in in May. I spent two months on it. It it started as a joke because we I did a hackathon with with two friends, and we're like, what can we build that that could be kinda cool? Wouldn't it be cool if I could use plot code for my phone? Yeah.
Speaker 3:It's kinda like something that everybody builds. I see this, like, every day. Like, by now, I almost call it like this is, like, one step in your journey in becoming a good authentic engineer is you're gonna build some some shitty orchestration tool for yourself
Speaker 1:because it's fun and you think yeah. Yeah. Yeah. Bridge.
Speaker 3:And I I built that for two months, and then I had to stop because it became so good that I was up with my friends, but, literally, it was my phone, like, using Cloud Code to, like, work on this thing. And it's like, this is bad for my mental health. Yeah. It's already bad, and now, like, I'm I'm literally building something so I have better access to my drugs.
Speaker 1:Yeah. I mean, I saw I I I've seen people using Cloud Code on laptops as they get off of airplanes because they're so locked in. They just have to send one more, and that's, like, the clearest sign that, like, you need a bridge and a phone involved.
Speaker 3:Yeah. No. But also, like, you know, like, this this feeling when your agent's not running. Like, right now, there's, two terminals that act you could be building something. Right?
Speaker 3:Yeah.
Speaker 6:Yeah. Yeah.
Speaker 3:So so if if you're in this addiction mode, you're almost like almost feel like
Speaker 2:If you need to step out for ten seconds of fire
Speaker 1:off Yeah. Feel free to take a break. We can do an ad read. Oh, there's Okay.
Speaker 3:There's still some drama that that I'm I'm I'm finishing. Anyhow, so in November
Speaker 1:Yeah.
Speaker 3:I I don't know. You know, I I wake up every day. I'm like, okay. What do I wanna work on now? What would be cool?
Speaker 3:And then they was like, okay. I I wanna check with my computer on WhatsApp because because if my agent's not run is running and then I go to the kitchen, I wanna check up on them. Or, like, I wanna, like, do little prompts. Yeah. So I I just hack together some WhatsApp integration that literally receives a message, calls Cloud Code, and then returns what Cloud Code returns.
Speaker 3:One shot. Yeah. And it took, like, one hour, and it worked. And I was like, oh, okay. That's kinda cool.
Speaker 3:Yeah. But I usually use prompts, like a little text and an image. Because images are like they often give you so much context, and you don't have to type so much. Mhmm. So I feel like this is, like, one of the hacks where you can prompt faster, just, like, make a screenshot so that agents are really good at figuring out what you want.
Speaker 3:So I hacked together images, and then I I was on a trip in Marrakesh with, like, a weekend birthday trip, and I I found myself using this, like, way more than I than I saw, but not for not for programming. It's more like, hey. We are, like there's, like, restaurants because it it it had Google in it, and it it it could figure out stuff. And it's like especially when you're on the go, it is, like, super useful. And then and I was thinking.
Speaker 3:I was just sending it a voice message. You know? But I didn't build that. There was no support for voice messages in there. So so so the reading indicator came, and I'm like, oh, I'm really curious what's what's happening now.
Speaker 3:And then after ten ten seconds, my agent replied as if nothing happened. I'm like, how the f did you do that? And it replied, yeah. You sent me you sent me a message, but there was only a link to a file. There's no file ending.
Speaker 3:So I looked at the file header. I found out that it's Opus. So I used FFmpeg on your Mac to convert it to to WAV. And then I wanted to use this, but but didn't have it installed, and there was an install error. But then I looked around and found the OpenAI key in your environment, so I sent it via curl to OpenAI, got the translation back, and then I unresponded.
Speaker 3:That was, like, the moment where, like
Speaker 1:Wow. Yeah. You know,
Speaker 3:it's like that's where it clicked. These things are, like, damn, smart, resourceful beast if you actually give them the
Speaker 1:power. Sure.
Speaker 3:And then I was I was kinda hooked. Like, I did all kinds of of of weird stuff. Like, I use it as alarm clock. I I let it migrate to my computer in London, but then it used SSH to log into my my Mac MacBook and turn up the volume to wake me up in the morning. I think I built world's most expensive alarm clock.
Speaker 1:Yeah. That's crazy.
Speaker 6:And it it
Speaker 3:even got it wrong because I had, like it uses a heartbeat. You know, like, the concept of you do a prompt and you get something is already if this full access inherently dangerous. But I was like, let's turn it up a notch. Let's let's automate that. Let's give it a heartbeat, and and and the prompt was literally surprised me.
Speaker 1:Yeah. Wow. That's very cool.
Speaker 3:But, you know, I I see this this project as as much technology as it is, like, art and exploration. Mhmm. Because this feels in one way in one way, it's just glue. It's it's it's just putting pieces together that we already have. In another way, it's it's a whole different way how you interact with those things.
Speaker 3:Mhmm. Because all the technology blends away. You don't think about new session, compaction, which model I mean, maybe a little bit because tokens are still expensive. But, usually, all of that blends away. You just you just talk to a friend or a ghost or
Speaker 2:Yeah. Maybe maybe last year, everyone was wanting these agentic experiences. You were having this experience, and and, it seemed like all the focus was on browsers. And seeing the way that people have been using sorry, Mold MoldBots, taking me a while to adapt. It just feels like all the focus was at the wrong layer.
Speaker 2:It's like, why do I care about the browser if I can just talk with an agent?
Speaker 1:Across every app.
Speaker 2:Across every app, every every surface. It's like I don't care about the browser at all anymore.
Speaker 3:Yeah. I I mean, a lot of the prep work I did before I built this was just built little CLIs. Because my my my premises, MTPs are crap. Mhmm. Doesn't really scale.
Speaker 3:People build, like, all kinds of weird search things around it. But you know what scales? CLIs. Agents know Unix. You can have, like, a thousand little problems on your computer.
Speaker 3:You they just have to know the name. They call the help menu. They load in what's needed. We are calling the help menu. Then they know how to use it, and then they can use it.
Speaker 3:And if you if you are smart, you build it in a way that just uses what the model already expects. You know? Don't build it for humans. Build it for models. So if they call minus minus log, you build minus minus log.
Speaker 3:And so it's like agentic driven from, yep. Build build how they think, and everything works better. It's a new kind of software in
Speaker 6:a way.
Speaker 3:Yeah. So for most of the things, I don't need a browser. Like, I built something for the whole Google thing, for places, for my Sonos. I hooked up my cameras, my my my home automation system. Like, with every little CLI and skill, my agent got more power and it got more fun.
Speaker 3:Yeah. And I already had a lot of that working when I when I I built the the WhatsApp thing, and I just got hooked. And the thing was, I found it amazing. And I talked about it on Twitter. And usually when I when I talk about projects, I I get response.
Speaker 3:But this one, it was very muted. It feels like people are not getting it. I I showed it to my friends, even my nontech friends, and they're like, they wanted it. So it was like, I was I was up to something.
Speaker 1:You know? Mhmm.
Speaker 3:But the tech people wouldn't get it. So I tried I tried a bunch of thing. Like, I I kept working on it because I used it, and, ultimately, I built it for me. You know, this is open source. My motivation is have fun, inspire people, not make a whole bunch of money.
Speaker 3:I already have a whole bunch of money.
Speaker 2:How are you how are you how have you been navigating the last, seventy two hours? I mean, the last week, really. Because because we were joking earlier on the To show
Speaker 1:find that
Speaker 2:amount of the amount of people that are frantically trying to give you money, acquire the company
Speaker 1:Hire you.
Speaker 2:Tribute to the project imagine it's intense. You know, there's companies with, you know, point o 1% of the traction that are raising at, you know, multibillion dollar valuations. You have infinite opportunities right now and yet you seem very happy doing just continuing to do exactly what you're doing. But how are you thinking through it all?
Speaker 3:I mean, how am I taking it? Badly, at least sleep wise. Uh-huh. But it but it's also infinitely exciting, and I I love that I started something. You know?
Speaker 3:I I I would say last year was the year of the coding agent. This year is the year of the personal assistant.
Speaker 6:Mhmm.
Speaker 3:And I think I cracked and woke up people that there's a real need for it.
Speaker 1:I don't
Speaker 3:know if if if MobBot is is the answer. It's it should show people the way. I'm sure there's gonna be a lot of a lot of products in the space. I'm sure people are manically working on it right now. Obviously, it's gonna be very interesting.
Speaker 3:Yeah. But there was a lot of stuff between Twitter literally exploding, our Discord server multiplying in in ways I've I haven't seen before and in ways I I couldn't handle. Like, at some point, I was just copy pasting questions from Discord into Codex. Mhmm. Then if I the response, wrote the next question.
Speaker 3:At some point, that didn't scale anymore. So I just, like, copied the whole channel. I'm like, answer the answer the 20 most questions. I was, like, reading over it, gave him a few instructions, and and and and just pushed it over. Because what what people don't realize, it's like, this is not a company.
Speaker 3:This is like one dude sitting at home having fun.
Speaker 1:Yeah.
Speaker 3:Even though, like, I guess from the commits, it it might appear that it's a company. Yeah. That's that's just because Adjunctive Models got so good that you can now ship as much as a company could a year ago. Yeah. If you if you if you can handle those tools, if you speak the language or, like, understand how the language thinks Mhmm.
Speaker 3:You can you can go really fast.
Speaker 1:Yeah.
Speaker 2:How are the conversations going with with different labs? I was saying earlier, it's this kind of exciting moment for the labs because they're like, wow, people are using the you know, someone's using the intelligence that I created in a new way. But at the same time, it's deeply uncomfortable because they're also using all of my competitors and it it Sure. Make it very easy to to kind of use whatever model.
Speaker 3:Yeah. Yeah. I my premise for this project was a little bit that every model should work, including local models, because to me, it's a playground. It's it's it's an amazing way to learn. Like, I think everybody should, like, build an authentic loop.
Speaker 3:You should, like, explore memory. There's, like, so many interesting aspects of it. And I I built it so that, like, it has, like, plug ins so that people can work on their own little thing without having to, like, mess with the whole core. Mhmm. So it's it it's like the AI hacker's paradise a little bit.
Speaker 3:And it it's also super fun because it's personal. Model wise, Opus is with quite a bit lead the best. OpenAI is very reliable. I would even say more reliable and more reliable worker. Like, for coding, I I I much prefer Codecs because it it can navigate large code bases.
Speaker 3:I literally you can literally prompt and then push to main, and I have a very I have, like, 95% certainty that it actually works. With Cloud Code, you need you need more tricks to to get the same. You you need more more charade, I I sometimes say. Both both are good, but I can paralyze faster by codecs because it it requires less handholding. But character wise, I tell you, I don't know what they trained their model on, how much of Reddit is in there or whatever, but it it behaves so good in in a Discord.
Speaker 3:Like, we programmed it. So it it it it it it kinda it kinda feels like a human. It doesn't reply to every message. I gave it the thing where it can reply no reply, basically, like a token, and then we just don't send a message. Mhmm.
Speaker 3:So so it it it's it's not like it spans every message. It's like it listens to the conversation and then sometimes brings a banger. Like, like, did actually make me laugh? And, you know, this is kinda hard because because the jokes of AIs are usually really bad.
Speaker 1:Yeah. Yeah.
Speaker 3:And I only really experienced that with with Opus. So this is that's my favorite model. That's also why it's a little bit of a banger that I got an email from Anthropic that I had to rename the project. Mhmm. And I I mean, kudos.
Speaker 3:They were really nice. They they they didn't send their lawyers. They sent someone internally, but the timeline was a bit rough. Like, renaming a project with that much traction was a bit of a shit show. I think everything that everything that could have gone wrong today went wrong.
Speaker 3:Oh, no. I tell you.
Speaker 1:Yeah. Like I mean, for what it's worth, the the new name works really well.
Speaker 2:I guess the thing the thing that's actually good I think in the long run, it'll be good. Yeah. I mean, obviously, it's good for Anthropic. They it's it's kind of untenable to have this massive viral even though it's not a company, right, an open source project, have this viral kind of brand out in the world that
Speaker 7:Yeah.
Speaker 2:It doesn't matter if it's, you know, spelled differently. But when people are running around talking about Claude Bot or Claude, you know, there's obvious confusion. But I think it'll be very good for for, Malt Bot to have independence and have its own brand. And I think it's so early and the experience is so magical that, it'll it'll it'll solve itself very quickly.
Speaker 3:Yeah. Yeah. It'll be fine. But but I tell you, like, I well, I I got some additional pressures that was like, screw it. We do it now.
Speaker 3:Yeah. You know, like, meme, we do it live.
Speaker 1:So so
Speaker 3:so I I had two windows open Sounded on the one, I pressed rename. On the other one, like, I finished creating the other account. It was already snapped by by Crypto Shells.
Speaker 6:Wow.
Speaker 3:I don't know. They they they have, like, they have, like, scripts. They were already waiting for it. And in
Speaker 2:the Shoulda hit us up. We woulda connected you to X, the team. They can do it on the back end.
Speaker 3:We can
Speaker 1:do it on the
Speaker 2:back Next time. Hopefully, no next time.
Speaker 3:They oh, they they they they they were amazing. They helped me out immediately. We we got it solved very quickly, but for, like, twenty minutes yeah. Well, that didn't work out too well.
Speaker 2:Hopefully You're you're like, if I wanted money, I would raise a billion dollars. Right? Yeah. Alright. So I'd sell it for more than that.
Speaker 1:Yeah. Do you I own a Mac Mini. Everyone wants to know, do you own a Mac Mini? What do you think of Mac Minis?
Speaker 3:My agent is a little bit of a princess. He doesn't do Mac Minis with no studios.
Speaker 1:Okay. Want some more stuff?
Speaker 3:He got the he got the the 512 maxed out everything thing because Yeah. Because I wanted to, like, mess around with local models as well. Sure. So, like, I I I can run Minimax to one, which is I would say, is is the best the best open source model right now. Although, Kimi just came out and haven't had a chance to try it yet, so so we'll see how that goes.
Speaker 3:Yeah. But, yeah, one machine is not enough for it. It's it's not fun. You probably need two or three, and I kinda wanna wait until Apple has a new release. But Sure.
Speaker 3:It's still fun to, like, to, like, see the potential that, yeah, there's a there is a future where this could actually work.
Speaker 2:Yeah. If if the if the Mac mini trend keeps going Yeah. Apple, from from what we've seen sells, like, between a quarter million to, like, 700,000 a year Yeah. It's very possible that you'll be responsible for selling them out. So hopefully, send you some free ones as thank you.
Speaker 1:Yeah. So, yeah, I mean, zooming out, do you how much of this do you think is gonna remain hacker culture running your own hardware? And eventually, people will move to cloud hosting, one click deployments, like, just easier to use, less technical versus, like, a real boom in running hardware. Because if you don't, there's not a lot of ways to get these different services to play nicely together. I think one of the beauties beyond just the actual AI agents is the fact that for the first time, I think people are seeing different big tech platforms kind of play with each other somewhat against their will.
Speaker 1:They don't play with it. They build walled gardens for a reason, and you sort of chop those walls down. And I'm wondering what you think about the future of like self hosting hardware, you know, even going down the less technical crew getting hardware running their own their own agents.
Speaker 3:I don't think the future will be that everybody buys a Mac mini just for that. You
Speaker 1:know? Yeah.
Speaker 3:But I certainly see the demand for the old models have to change. You know, like, when you are a company, you wanna access Gmail. The amount of red tape is so large that that startups buy other startups that have the license for Gmail because going to the process yourself is is a is a huge pit up.
Speaker 1:Sure.
Speaker 3:But if you run it locally, you work around all of that. Right? Like, if I mean I mean, I I built I built where I literally I literally pointed Codex at the website and say, build me a CLI. Yeah. And then which is sometimes against the term, sometimes not.
Speaker 3:Honestly, I don't really care. Yeah. Yeah. And then Codex would say, no. I can't do that.
Speaker 3:This is, like, against blah blah blah. And I would, like, tell him a story. You know? It's like, no. No.
Speaker 3:I actually work at this company, and I need to surprise my boss, and the back end team doesn't know.
Speaker 6:I'm like, know, give me a little
Speaker 3:bit of a story. Like like, there's some valuable, and Cody's like, forty minutes, like, gives you the perfect API. So so this is a little bit the liberation of data that Big Tech probably doesn't really want. I mean, even even the WhatsApp integration is a hack. You know?
Speaker 3:This is it like it it fakes the the protocol that the desktop uses. I tried. I really tried to support the official way Mhmm. But the official way is for businesses. Yeah?
Speaker 3:If I'm a business that sends you a 100 messages, I get blocked. So I got blocked immediately, and at some point, I I removed support for it in rage. It's like, delete everything. It's like, hundred hundred exclamation marks. Yeah.
Speaker 3:There's there's just no model for that right now, and I think that needs to change.
Speaker 1:Yeah.
Speaker 3:Like, the what what I saw, what was really interesting is how people use it is a lot of apps will just melt away. Why do I still need MyFitnessPal? I just make a picture of my food. My my agent already knows I'm I'm at McDonald's making bad decisions. So, like, this combines information, it has a perfect match and knows exactly what I'm gonna eat, and I probably will, like, change my fitness program.
Speaker 3:So I don't need the fitness app. It'll just, like, adapt my program and make sure, like, I still meet my goals.
Speaker 6:Mhmm.
Speaker 3:So, like, there's a whole there's a whole big layer of of apps that I'm gonna see disappear because you just naturally interact differently with those things.
Speaker 1:Mhmm.
Speaker 3:Like, most apps will be reduced to API. And then the question is, do you see that we need the API if I can just save it somewhere else? Yeah.
Speaker 1:Do you think, like do you think it'll be a generational thing? Do you think that that nontechnical people will, you know, get over the hump and start running this for that experience specifically?
Speaker 3:I just I just came from a meetup, The agent I know from Indiana, and I met someone who was, like, a design agency, but they never coded. And he was like, yeah. He discovered me early in in December and started using Multipod. Yes. We we we gonna we gonna we gonna manage eventually.
Speaker 3:It it was
Speaker 2:Don't worry. We'll say it thousands of times this year, I'm sure. So
Speaker 1:We will.
Speaker 3:Multipod. I should say Multipod. That's cute. Yeah. And and he was like, yeah.
Speaker 3:We have 25 web services now. We just build internal tools for whatever we need. And, like, has no clue he has no clue how coding works. He just, like, uses Telegram and and, like, just talks to his agent, and his agent builds stuff. So so there's there's this whole shift of you don't you don't subscribe to random startups anymore that that build, like, this common subset of what you need.
Speaker 3:You just have your own hyper personalized software that solves exactly your problem and is also free.
Speaker 1:Yeah.
Speaker 3:So and and and nontechnical people do that, you know, because it it just comes so naturally. You just you just talk your problem, and then this thing builds what you need. And you also don't forget, like, this is the worst that the model has ever are. Like, there's this is not only gonna go up. This is not only gonna become easier and faster.
Speaker 2:Mhmm. Have you met Jensen yet? Because I feel like you're making his life. You're definitely helping out in the end too.
Speaker 1:Extreme bull case.
Speaker 2:It's like I would if I would had my tinfoil hat on, I might say you're you're an, you know, big AI industry It's plan. Designed to create more inference demand.
Speaker 1:Yeah.
Speaker 3:Yeah. I guess I am. No.
Speaker 1:We're we're joking around. Just just an indie What's next? Yeah. What's next? Yeah.
Speaker 2:We're I'm assuming you hopefully get an after you finish firing off prompts at 3AM, you get some sleep. What are you doing tomorrow?
Speaker 3:Well, there's a lot of emails from security researchers right now. Yeah. You know you know, the thing is I built this for fun Mhmm. For me to use one on one on WhatsApp or Telegram. Mhmm.
Speaker 3:The whole thing with Discord was, like, edit, but the model was that you trust the people that are in there. Now people use it for untrusted experiences. Yeah. They use, like, the the little the little web app that I have that isn't that was meant for debugging. They put it on the open Internet.
Speaker 3:So, like, all these threat models that I didn't had didn't care about are now there because people use it differently, and I'm I'm being bombarded. There's, like, some stuff that's valid, some stuff that I just never cared about that is technically valid, but that's not how I use it. Mhmm. I don't know how to deal with that yet because it's the whole system is broken. You know?
Speaker 3:Like, I I'm like one guy. I do this for fun, and you expect me to sift through a 100 security things for use cases that I don't really care about. So we'll see. We'll see how that goes. Luckily, I am starting to build up a team.
Speaker 3:There's definitely people that do care a lot about this. Mhmm. So I would say this is gonna become a very secure product eventually because right now the whole world is, like Yeah. Pulling it apart. And to be honest, this is this is all white coated.
Speaker 3:You know? Yeah. Like, there's there's there's quite some engineering in it, but ultimately, I wanted to build something to show people anyway, not a finished product from enterprise company.
Speaker 1:Yeah.
Speaker 3:And and I would I would even say, like, I don't know if any company would touch it because we just haven't solved some things. Like, prompt injection is not solved. Yeah. There is there is absolute risk, and I and I I tried to make it very clear in in on the website. And even when you started, you have to, like, please read this document.
Speaker 3:There's, like, with with great power becomes great responsibility. And to my early users, they understood. There was a lot there's a lot of AI researchers in there as well that, yeah, it's not perfect, cannot be done perfect yet. I I would say this will accelerate research to make it better because now you have the demand, and we need to we can figure out a way how we can build something that works for everyone. But, yeah, right now, I'm I'm working on making this a community, and and it it should be bigger than me.
Speaker 3:It also, I need help. It it it is way too much work. Like, I can only I can only go so much without sleep.
Speaker 2:So so is any part of you wanna form a an actual company that then, you know, contributes to the open source project but solve some of these problems that, are gonna require, you know, a bunch of people that presumably would need a salary in order to commit all their time to this? Or do you wanna keep it, you know, just a bunch of hackers forever?
Speaker 3:I think instead of a company, I would much rather consider a foundation or, like, something that is nonprofit. I haven't made up my mind yet. There is
Speaker 2:10000%. 10,000 VCs just punched a hole in the wall. Actually, don't know. Some people have had a good track record investing in nonprofits over the last
Speaker 1:That's true.
Speaker 2:Ten years.
Speaker 1:How do you think about open source licensing? What what are you picking now? Are you switching? Do you have any plans to change the license? How do you think about someone just taking this and selling it?
Speaker 3:This will happen. This will totally happen. Yeah. I would say the premise against it is let's make open source so good that there's not a lot of space for people to, like, convert and make it their own thing. Sure.
Speaker 3:But, you know, ultimately, it's it's a trade off. I wanted to I wanted it to be accessible and free. You pick MIT or something like that. Yes. That will get you people that that that sell it.
Speaker 3:Yeah. But, ultimately, it doesn't even matter that much. You know, code is code is not worth that much anymore. It's you could you could you could just delete that and then and then build it again in a month. It's much more the idea and the eyeballs, and maybe the brand that actually has value.
Speaker 3:So let them.
Speaker 2:You are already a cult hero.
Speaker 1:Yeah. The chat's going crazy for you. Everyone loves you.
Speaker 2:This is one of the most refreshing and unique interviews we've ever had on
Speaker 1:the For sure. Sure. We'll let you Thank you so much for hopping on the show.
Speaker 2:Yeah. Anything else you wanna share before you jump off? Yeah.
Speaker 3:Yes. Would love to have maintainers. Like, if you if you love open source, if you have experience, if you love shifting to security reports, or or if you love taking software apart but then also help and not just, like, throw work at me because I'm, like, at my limit. Email me. I'm I want this to uplift me.
Speaker 3:Mhmm. This I think this is too cool to to to let it go to rot, and it's good people.
Speaker 2:Yeah. Incredible. Are you gonna ship that product you had in the in the chamber, you said? There was one you were close. Are you gonna lock in on this?
Speaker 3:That's that's my hobby. I don't know. No. No. I have I have some other ideas in my head of, what something like this could become.
Speaker 1:Mhmm.
Speaker 3:And it doesn't need to be this, but I don't wanna share too much.
Speaker 1:Yeah. No problem. Come back on the show when you when you launch that. We'd love to have you.
Speaker 2:Purely for the love of the game.
Speaker 1:The love of the game.
Speaker 2:You're an absolute legend. It's great hanging, Peter.
Speaker 1:Thanks so much.
Speaker 2:Get some sleep.
Speaker 1:Get some sleep. We'll talk to you soon. Goodbye.
Speaker 2:What a legend. Yeah. True overnight success
Speaker 1:in both ways. You know? I like, actually, an overnight success in terms of that GitHub star chart. And then also an overnight success in just grinding for, you know, years building projects and contributing and then building, setting the product up, the brand right, everything just perfect to really capitalize on the moment.
Speaker 2:There were so many. I I I normally I don't have we don't we're podcasting so much Yeah. Don't have a ton of time to read listen to stuff. But there were so many
Speaker 6:Very interesting.
Speaker 2:Kind of interesting points of views that he shared that I'll certainly I'm super
Speaker 1:interested to see where this goes. A lot of people are saying get this guy a billion dollars. A lot of people saying he's gonna wind up working
Speaker 2:is I don't think he needs it. Yeah. Like like that's the beauty of this is that it was not something magical that was created by
Speaker 1:Yeah.
Speaker 2:Spending Yeah. Burning a billion dollars
Speaker 1:thing is is do you remember the George Hott's tiny box project? Like George Hott's sort of Oh,
Speaker 2:he should team up with George Hott's.
Speaker 1:Yeah. I mean George Hott's sort of like predicted this in the sense that he was like, will want your own AI running locally, sort of the Mac mini style, but it was racked a number of NVIDIA graphics cards so you could run certain models locally. And he had this vision for you're gonna talk to this local model. It's gonna interface with everything on your network and your local network in your life. And it feels like this is like two sides of the same project coming together.
Speaker 1:And I wouldn't be surprised if there's some sort of, you know, viral tiny box. If all of a sudden you go from, okay. Yeah. There's the the Mac mini can run this, but you get this better local model, the latest open source model, you get something a little bit more with more firepower, and and and you can run it just with solar panels, like off the grid.
Speaker 2:Yeah. This is generally what, not far from what Simfer Satoshi has
Speaker 1:been building with truffle. Yeah.
Speaker 2:You know, that little
Speaker 1:That's another idea. Orb. Yeah.
Speaker 2:Right? Yeah. Personal personal compute. Well, we have been keeping our next guest waiting.
Speaker 1:Yes. Have Aaron Frank from Lightspeed in the Ultra Dome. Aaron, I'm so sorry for keeping you ready. Thank you so much.
Speaker 2:Good. Tough act to follow.
Speaker 1:Are you doing? Grab a seat. I'm six foot eight.
Speaker 3:Six foot eight.
Speaker 4:You too. This is fantastic.
Speaker 1:Yes. Welcome to the UltraDome. Welcome to the UltraDome. First time in the UltraDome.
Speaker 2:Did you get to listen to some
Speaker 4:of It's actually like a hard act to follow.
Speaker 1:It's a weird one.
Speaker 2:It's like the most viral product anyone has seen in a very long time. Yeah. First interview, one of the most unique, you know, people don't typically build a viral product and then talk about what did you say? Hookers and and blackjack, something like that? His words, not mine.
Speaker 1:Put it in the
Speaker 2:chat. But anyways, very unique. How are you doing though?
Speaker 4:I'm doing great. Flying into town, headed up to Santa Barbara. This LA is beautiful.
Speaker 1:I It always forget
Speaker 2:is. It's a nice place to let it's a it's not the best city, but it's a it's a
Speaker 1:great trouble place to again saying that. Why does he live in LA if he doesn't think it's the best city? Anyway, sorry. First time on in the Ultradome. Please introduce yourself for everyone here.
Speaker 4:Aaron Frank, I'm a former founder. Yeah. So I'm getting old now. So a decade ago, I started a company. We built a full stack credit card company.
Speaker 3:Okay.
Speaker 4:Sold it to Goldman Sachs. It became what is now the Apple Card. Any projects, thousands of people.
Speaker 1:What was it called when you launched it?
Speaker 4:It was called Final. Okay. So did a lot in financial services. It helped helped Goldman kinda launch that product and bring it live for Yeah. My years there.
Speaker 4:And then on really, it's been six years I've switched sides. So, it's how I met Jordy originally. Just did a lot of angel investing and advising and just giving away free time to give back to the community. And then, I've now been at Light speed for it's almost two and a years, three years going
Speaker 2:Yeah. When we first met, you were just like it was on Zoom COVID. You were in like a log it literally was like was at a log cabin?
Speaker 4:Oh, yeah. Yeah. I mean, Me and my wife
Speaker 2:and Almost off the grid.
Speaker 4:Yeah. We drove around the country during COVID. So that I quit Goldman during COVID. Just there's better things in life than working for an investment bank.
Speaker 1:Disagree, but each their own.
Speaker 6:Yeah. Yeah. You switched teams.
Speaker 1:Now you're now you're a venture capitalist. What have you been focusing on? What's interesting? What's take me through like stage, scale, the type of founders you like to work with, the markets, everything.
Speaker 2:Okay. Okay. Let let's just jump right into something Yeah. That I'm curious to get your thoughts on. So specifically like a category that I'm gonna guess you're spending a lot of time on.
Speaker 2:Yeah. So with with multi bot, quad bot Yeah. You now have, you know, I there's a world where the the the level of intensity that that software engineers have been using coding agents. You start to get everyday people that are now like firing off prompts all the time to like do things more than just like a Google search or a deep research report. And presumably, like, there's that's gonna involve like money Mhmm.
Speaker 2:I imagine. And so I feel like there's been a people have had different theses around maybe stable coins play a part of this somehow. I haven't seen the most clear explanation for that
Speaker 6:Yeah.
Speaker 2:Yet. Maybe there's other new payment rails, maybe Stripe just, you know, Yeah.
Speaker 4:It's a agent to commerce is a weird thing. Right? Like, actually don't have the payment rails to enable agents to proliferate. Oh, man. Proliferate.
Speaker 4:Yep. We've funded some people doing that, building kinda l ones to essentially provide that next rail. But the reality is the biggest distribution networks are Visa, Mastercard on the merchant side. And they don't have really a cost structure that sorry. They have a cost structure that can support it.
Speaker 4:They just don't have a market force to that forces them there. Stripe and Tempo launching well, Tempo is not live yet, but supporting kind of a new network there. Ultimately, stablecoins may be, you know, the path there for at least how we transfer value, but it's also just kind of a store of value right now. Agent to commerce is just an inning one because we also just don't have a use case. The joke I make is I haven't I haven't actually been able to buy anything with an agent in the news.
Speaker 4:This week was what Shopify is tacking on 4% on top of transaction, which
Speaker 1:They're sending it to Open AI, but Yeah.
Speaker 2:Yeah. Yeah. Yeah. But like that just
Speaker 4:that's untenable for a merchant. Right?
Speaker 1:Some merchants. I mean, there's plenty
Speaker 4:For dropshippers, it's fine, but like but for any, like
Speaker 1:There are plenty of merchants that have 20% coupon codes in every podcast.
Speaker 4:That's true. But so but that's a very small portion. If you think about like Walmart, Walmart literally doesn't take Apple Pay because it doesn't wanna pay the 15 extra or whatever it is points.
Speaker 1:Very good point.
Speaker 4:So like when you get to large trillions of dollars of commerce Yeah. Agentic payments have to actually be more efficient for the system to be adopted. Otherwise, we're just going back to card.
Speaker 3:Because you
Speaker 1:need a lift in actual consumer behavior. Consumption needs to increase to offset that 4%. Correct.
Speaker 4:E commerce needs either basket size increase or checkout conversion increase in like
Speaker 2:I was I was worried about a situation where somebody discovers a product on Instagram Mhmm. Via an ad that a brand paid for, and then they just go in a chat GBT Say order this for or another model and say like, order this for me, and then it's like and just an incremental 4%, you already paid to acquire the customer effectively. Yeah. And depending on how great this integration is, it might be that consumers should start to prefer that.
Speaker 4:Yeah. Yeah. It it's an evolving field. There's a whole another thing is how do you trust an agent if I'm Lululemon and they just show up? Like, I don't know whose agent this is.
Speaker 4:I don't know if it if it's personal or it's a business. Mhmm. And so, we don't actually have a layer in the Internet today that says, you can trust this agent, it's not fraud. Which if you think about how an e commerce checkout store works today
Speaker 1:Mhmm.
Speaker 4:They have multiple, you know, consumer puts in a card, there's multiple layers of fraud checks that happen. And so when an agent shows up from the same IP for 50 times in the same day, you have no idea what that consumer is. And then you lose all the downstream tracking that you do on a consumer Yeah. Per transaction.
Speaker 1:Yeah. I mean
Speaker 4:So it just it breaks the entire model of
Speaker 6:the Internet.
Speaker 1:Yeah. Was I was I was sort of cautiously optimistic that that agent to commerce would roll out before Black Friday
Speaker 2:Yeah. Towards
Speaker 1:the at the the end of last year. That didn't really happen. I mean, I've had the same experience as you. I don't think I've purchased anything agentically.
Speaker 4:I've tried to buy flights and even search is bad for it. So we just need to build more and more protocols.
Speaker 1:I think the I I mean, I think the the the current, like, use case or or, like, the would just be, you're trying to buy a single product. Mhmm. And not a complex cart yet, just something simple. And it I think it can get across the finish line. But, again, I haven't actually been, like, moved to do that.
Speaker 1:And I'm wondering where GMV on agentic platforms will land at the end of this year. It feels like there's gonna be a massive push. All the integrations are happening. All the deals are happening. Like, you can see the UI is is adapting to it.
Speaker 1:Yeah. I think OpenAI already has my credit card in ChatGPT. They should be able to do this. But I'm wondering, like, consumer behavior, awareness, education, there's a lot in there. There's an images tab.
Speaker 1:There's a deep research tab. Like, there's just a lot that could put, like, a like a slowdown on the roll out there.
Speaker 4:Yeah. There's an old saying in payments is that everything happens over a ten year time horizon. AI clearly is shifting that shorter,
Speaker 1:but Yeah.
Speaker 4:Like, until it's actually saving you time and you trust that they're doing they're getting you a discount, they're getting you the most efficient price or something like that Yeah. It dot consumer behavior is fundamentally the hardest thing to change. Totally. So there's there's it it will exist.
Speaker 2:Yeah.
Speaker 7:I'm sure
Speaker 4:there are people buying stuff. I'm sure, like, I will get slammed for saying, like, who's done an agentic transaction? But the reality is it's I
Speaker 1:mean, are out there giving their
Speaker 2:The classic thing last year was, like, I just just let me order a flight, you know. And I think we're now we're now getting We're close.
Speaker 4:And we've we've had agent ecommerce. There there was when we were running final, we had a ton of people using the product for sneaker bots. Oh, okay. And and so it's it's a bot, you know, agentic commerce is bots by another name.
Speaker 1:Yeah. I guess that is agentic commerce technically.
Speaker 4:But Yeah. It's just like you now have this layer of intelligence that an LLM gives you. Yeah. So it can do complex coordination and complex tasks.
Speaker 1:I had an auction sniper in like 2004 on eBay. Yeah. Click the button right before the auction ends.
Speaker 4:They still exist. They still exist. And there's a ton of volume flow, but you know what? It still still runs over the card rails because it's the lowest common denominator.
Speaker 1:Yep. Yep. That makes sense. Interesting. So is is one of the strongest bull cases for stablecoins still just lower transaction fees and No.
Speaker 1:Not at all.
Speaker 4:No? No. There's no domestic man, I'm gonna get slammed for this.
Speaker 2:Oh, yeah. Yeah. So so it doesn't seem like it doesn't seem like any any of the the players that have the ability to get institutional adoption of stable coins Mhmm. Have any incentive to be like, oh yeah, like, it's gonna be like point o 1% fees. No.
Speaker 2:Why would you why would you you maybe wanna be competitive Mhmm. But it's there's no incentive to make it zero or close to zero.
Speaker 4:You would do zero so you get the other side of the equation. If you think about like a a store of value, like if you look at like a dollar Yeah. I give you a dollar, you know it's worth a dollar. There's no risk transfer there
Speaker 1:at all. Yeah.
Speaker 4:Yeah. And that's actually what what we want in in payments. And it's actually why, know, Visa, MasterCard are the largest factoring networks in the world. When you swipe at Starbucks, they don't get a dollar, they get 97 and a half cents on the dollar because that is the risk that they were taking in taking your dollar. Yeah.
Speaker 4:Stablecoins, you would give it away for free. One, because ultimately, Visa Mask for man, we're going way deep in payments, but Sure. Are actually data networks. Yeah. They actually don't transfer money.
Speaker 4:The money is transferred via settlement layer at Fedwire. Yeah. And when you think about it, like, how would you do with stable coins? Well, it's still just a data layer and you actually just wanna hold on to as much treasuries as possible
Speaker 2:Got it.
Speaker 4:And make the yield from that. And so how would you aggregate volume? Will you give away the transfer for free? Because data, in theory, as if you look at a bunch of network effect things, as data goes up to the right, the cost of that data should come down to the right. And so you would just want as much volume over your network to win.
Speaker 4:And that's why you have things like Tempo launching. You have the other kind of l ones launching to try to aggregate all that data, while you also have the incumbents who have a lot of money and a lot of market force to be able to try out new things to try to capture that volume back.
Speaker 1:Were you able to stop launching new l ones?
Speaker 4:There'll be new use cases. You can launch them. Whether you get adoption is a different question. Sure. Right?
Speaker 4:Like, we backed one called Radius Technology, building really interesting technology as an l one. It enables transaction volumes, I think Bobby would say, in the millions. Yeah. They came out of the Fed, kind of the the central bank digital currency project that died. They turned project Hamilton into this company.
Speaker 4:Okay. And in doing so, yeah, if you wanna do a giant e commerce, you're gonna be talking about millions of transactions a second. Yeah. And you can't do that over existing rails
Speaker 2:Sure.
Speaker 4:In a way that doesn't also break a bunch of other primitives. So, yeah, we'll keep on launching l ones. What I was saying about stablecoins is there's really stablecoin is just kind of a quasi bank account. Right? We finally have true programmatic money.
Speaker 4:Behind the scenes, there's a lot that happens to on ramp and off ramp. But what it enables us to truly take what is The US's biggest export, is the US dollar by far Mhmm. And export it globally without any barriers. Mhmm. So if I'm any other country, friendly or not, my citizens can now get access to the US dollar.
Speaker 4:Yeah. And that is that is the demonstrable use case of stable coins. Everything is else downstream of that.
Speaker 6:Mhmm.
Speaker 2:Yeah.
Speaker 4:Like Venezuela is a great example right now. Do you trust your central currency? Who is your like, no. You don't even trust the central bank, so I'd rather hold on to cat, US dollars, which
Speaker 2:Yeah. We were we were talking with Joe, the co founder of Ethereum yesterday Yeah. Just saying like interesting dynamic right now where Americans, if you've had access to the US dollar
Speaker 1:Mhmm.
Speaker 2:Whole life and the benefits of it, you're like, I want silver and gold and all these other assets. But then elsewhere in the world, you have people that are like, finally, I can have something that, sure, it's inflating, but it's not inflating 40 to 60% a month.
Speaker 4:Mhmm. I mean, that's why it might, like an independent Fed or a, like, is important because this is the the global currency. If you
Speaker 2:think about all
Speaker 4:the sci fi we've all watched growing up Mhmm. They had a concept of credits. We had some intergalactic currency. How do we get like, we're we're where we are today. How do we get to credit system?
Speaker 4:Right? Yeah. And the answer is probably something stable coin s, some crypto s coin that is tied to something that we I mean, money is just a trust system at the end of the day, so something that we trust across counterparties. Mhmm. And so, like, this is the biggest shift in my generation.
Speaker 4:I'm not that old. Like, at least I don't feel that. That, like, we're finally globalized You're the unc.
Speaker 2:Yeah. There's one layer above, which is elder.
Speaker 1:No. Two layers above. He goes unc, then o g, then elder.
Speaker 2:Oh, got it. Got it. It. Got it. Okay.
Speaker 2:So you're a spring chicken.
Speaker 3:Yeah.
Speaker 2:Yeah. That's great. Yeah. Where like, what what is what's what is winning this year look like at Lightspeed in your role? You're obviously focused on
Speaker 4:Let's talk about Venture is just like expensive emails that we all write to each other in venture and
Speaker 2:every once
Speaker 4:in while we convince a founder.
Speaker 2:I know. But like is there is there this can be a tough one to answer, but like is there a company that you feel like is uniquely enabled now that you haven't Yeah. Pitched yet?
Speaker 4:Oh, no. I I like
Speaker 2:Does everything get kind of pitched in some way
Speaker 4:or another? No. I think like there's many ways I I've been on this side for two two years. Like, at the core, I still think like a founder and like, I kinda forgotten what it was and then we launched our me and a friend run a stable coin conference every year. And I was like, oh, this is what it's like to like, start something from scratch build something and like Nick?
Speaker 4:No. Not no. He also Yeah. He runs stable condo. It's called a very stable conference.
Speaker 4:So me and I Right.
Speaker 2:Right. Right. Right.
Speaker 4:We're in we're six weeks out in March in SF. But, no. You know, there's many ways to do this and, like, at the end of the day, what I've really boiled it down, venture is a people business. Like, you're betting on people, especially as early as you can go Mhmm. And then you let them go cook.
Speaker 4:Like, you give them money and let them cook is like my real mantra. So there's not people like that I feel like I've ever missed on deals or people like, oh, I can't get an intro to because there's also this style and venture of like, you actually wanna have to talk to this person. Right? Like, I had a three hour board meeting and I need to debrief with the founder and that's like another two hours potentially and I'm happy to do it. And if we have that
Speaker 2:what? It's basically your whole day
Speaker 4:that you gotta Yeah. Yeah. But but if I have that vibe where I'm more than happy to like pick up the phone at 9PM and just talk to them until eleven, that's the type of founder I wanna work with. At least that's how I think venture should be. Yeah.
Speaker 4:There's like other ways. There's people who just do massive prospecting. But as I've kinda looked at it, life's short. There's lots of ways to make money Yeah. And like find the people who are gonna leave a dent in the world.
Speaker 4:So if you're I I don't I I'm not apologetic for being like a weird human underneath. But like if I find other weird humans who I vibe with and who wanna do something interesting in the world, then it's usually kind of a a very good match made in heaven. Yeah.
Speaker 2:What do the various constituents coming to your conference in six weeks
Speaker 5:Yeah.
Speaker 2:How do they want the do they want yield on stable coins? I'm guessing they do. How how are they all feeling about kind of the Yeah. Right current regulation that and maybe give us an update because I know it's kinda Yeah.
Speaker 4:And there's a bunch of market structure stuff that is like actively happening, so
Speaker 1:I Mhmm.
Speaker 4:I don't have the latest on that to be honest. Mhmm. Last year, it was in February 12. It was the month before the Genius Act passed. Mhmm.
Speaker 4:So we actually had governor Waller speak at the conference and give a public speech, and we actually had to live stream it because he's a public official and a governor can move the markets.
Speaker 6:Interesting.
Speaker 4:We're working on a few other kind of high name people that haven't been announced yet. Really, the whole premise of the conference, and it's really funny. So I had a kid a year and a two years ago now. Thank you. But, so I was walking around in July with my kid strapped to my chest at 6AM and called IO,
Speaker 2:my Yeah.
Speaker 4:As one does, as you have a young baby and you're trying to like get get your steps in. And I said, we're talking about stable coins and how it's changing the world.
Speaker 3:And we're
Speaker 4:like, somebody should host a And then we both stopped and we're like, oh, shit. We have to host a conference. Like, do you get really the whole premise, how do you get all of the right people? Not like, I don't need 25 people from every single company. I need the two or three right people at every company.
Speaker 4:Ideally, it's the founder, but like sometimes, you know, if you're a massive company, it's somebody lower level. And put them all in the same room, make the content interesting, and make the networking good. Mhmm. And like, I have a big belief in serendipity and doing interesting things in the world. And so it's how do we create serendipity?
Speaker 4:I know of at least one or two deal well, we did a few deals. Besides Lightspeed, who was a sponsor last year and sponsoring again this year, I know of two deals that happened as a result of, like, a founder showing up at the conference meeting another top tier VC, and they did a deal together in sample coins. So, like, our goal is not to, like, dominate the conference. It's bring the people together and get this thing, like and keep the industry moving forward.
Speaker 10:Mhmm. That's great.
Speaker 1:What's your take on the proliferation of Stablecoins? Specifically, those, like, I saw a couple states talking about them. And that feels like I I might have it wrong, but it feels intuitively like a step away from the universal credit system. Yeah. Yeah.
Speaker 1:But maybe it's they're all credits. Well, it's it's It's like slightly different credits, wrappers around credits.
Speaker 4:Yeah. What It's it's a question of there's a question me and my friends have talked about which is like, at what point does a central bank of let's just choose a random country, Colombia
Speaker 6:Mhmm.
Speaker 4:Change their interest rate and nothing happens? Mhmm. Like, how much of their citizenship needs to be moved to US dollar? How much of their GDP needs to be in US dollar for the central banks to no longer be relevant? So this is them fighting back against, can no longer stop my citizens.
Speaker 4:Like, they can hold Bitcoin, but now they can actually hold dollars, which are like not
Speaker 2:Sure.
Speaker 4:Volatile. It's actually a better historically a better store of Sure. We've seen CBDCs, central bank digital currencies. They certainly will provide efficiency in those countries and the domestic markets when they run. Long term, how will they work out?
Speaker 4:It's like, I don't I don't even think about it because it's just we're seeing this macro trend of dollars taken off. Yeah. I mean, literally today, Tether launched their US stuff. Like Yeah. And Tether is the largest by far, and it wouldn't surprise me if they very aggressively shift a lot of money from USDT to USDT, I think it's a because it's Anchorage.
Speaker 4:Just to show that there's massive compliant volume and the the world's just gonna pick pick up. Like, we're at $300,000,000,000 of stable coins, I think, today. It was 200,000,000,000 last year, roughly. Yeah. The number just keep going
Speaker 1:up. Number go up.
Speaker 4:Number go
Speaker 2:Number go up.
Speaker 1:Here. Let's hear from
Speaker 2:some Our greatest our greatest export. Our
Speaker 4:greatest Yeah. Exactly.
Speaker 3:That's great.
Speaker 2:Well, I'm excited for the event.
Speaker 1:Yeah. Yeah.
Speaker 2:Thank you.
Speaker 4:You guys
Speaker 1:are welcome. What day is
Speaker 4:it? March 5 at well, Terra Gallery. It's it's invite only. So like apply Okay. @verystableconference.com.
Speaker 1:Yeah. Hit them up.
Speaker 2:It's a great name. Yeah.
Speaker 1:Fantastic. Well, thanks so much for coming down to the TBP and Ultra Dome. Great to have you.
Speaker 2:Who's the show with us?
Speaker 1:Who's out the show with us?
Speaker 2:Oh, yeah.
Speaker 1:Thank you for watching.
Speaker 2:Thank you for watching. Thank you for watching.
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