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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TBPN. Today is Monday, 07/07/2025. We are live from the TBPN UltraDome. The temple of technology, the fortress of finance, the capital of capital. We have an awesome show for you to you, folks.
Speaker 1:Hope you had a great July 4. It was a wonderful July 4 here in California. I know most of the listeners of the show were probably in Europe. But for those of you who stayed domestic served America, thank you. We have a whole bunch of news for you today and a stacked lineup.
Speaker 1:But let's go through We
Speaker 2:celebrated by talking about business podcasting with David Senra
Speaker 1:We did.
Speaker 2:And Rob Moore.
Speaker 1:We did.
Speaker 2:It was fantastic.
Speaker 1:No. It was a fantastic weekend. I I went to a friend's place and they had catering for a pretty small party. And and I As I was leaving, was like, this is the work hard play hard lifestyle.
Speaker 2:Yeah.
Speaker 1:And and That's what my wife's laughing because it was
Speaker 2:like Many people mean when they say work hard play
Speaker 1:hard. But it's true. It's true. If you work hard, get to you get to play hard. And when you when you play, when you have when you have friends over, it can be very luxurious, which is great.
Speaker 1:Anyway, in some absolutely massive breaking news, Dwarkash Patel has updated his AGI timelines, $30,000,000,000 off of Nvidia's market cap like that. Just kidding.
Speaker 2:It moved The stock was down.
Speaker 1:The stock was down at only point 7%.
Speaker 2:Not on that news.
Speaker 1:Probably not on that news. But it but it but it should have been. And this should have been market moving news, and we will get into
Speaker 2:Although it's not necessarily bad for Nvidia.
Speaker 1:No. It's incredibly bullish. His his breakdown is incredibly bullish on AGI, and and and and and that's the back and forth here. So Metacritic Capital says, f, Dwarkesh is out there calling AI hype overblown. I know we stopped doing these things, but likely the AI trade top is in.
Speaker 1:And he could not have gotten it all wrong. Dylan Sell chimes in.
Speaker 2:Fires back.
Speaker 1:Yeah. Bro. Bro said his taxes by 2028 and all white collar work by 2032. And you think that's a bearish prediction? He just thinks AGI 2027 stuff is wrong.
Speaker 1:The market isn't pricing either of these scenarios, and I completely agree. Completely agree.
Speaker 2:And Dorcas chimes in and agrees and says the transformative impact I expect from AI over the next decade or two is very far from priced in. And he shares a screenshot. He says, while this makes me bearish on transformative AI in the next few years, It makes me especially bullish on AI over the next decades. When we do solve continuous learning, we'll see a huge discontinuity in the value of the models. Yep.
Speaker 2:And, we will get a lot more into this when he joins the show in twenty minutes.
Speaker 1:Yeah. So his basic thesis is when you work with someone, you know, they have a set IQ, but they're also capable of continual learning. You teach them and they learn and they adapt and then they they can remember some hard won lesson from years ago. Yeah. I remember talking to somebody this this kind of like, I don't know, even though he's like philosopher, user he's like a user experience designer and he said that there's there's multiple ways to learn.
Speaker 1:You can you can develop habits through just doing something the same every like, really forcing yourself for a long time. I wake up at 05:30 every morning, wake up at 05:30 every morning for years. Eventually, you just wake up at 05:30. But he was like, you can also form a habit by one really, really intense experience. He was like and and the experience and the and the example he gave was one day, he goes
Speaker 2:out A a true lesson.
Speaker 1:True.
Speaker 2:True. Something that you've fully integrated and operate against
Speaker 1:going forward. But he gave he gave a great example, which was that he has a river out back of his house, and he goes into the river. And one day, he put his foot in his river shoes, these, like, slip ons, and there was a lizard in the slipper. And it freaked him out. It gave him this, like, intense response.
Speaker 2:Not fun.
Speaker 1:He's fine. But ever since then, he's been in the habit of always checking his shoe.
Speaker 2:There's a snake in
Speaker 1:my boot. There's a snake in my boot. Exactly. And so it's not like it's not like that was something that had to be trained for years. But it's like this one really sharp intense learning that then carries forward forever in his life.
Speaker 1:And so people and employees
Speaker 2:do that too. Learn that in school. You gotta check your boots.
Speaker 1:Scorpions. Scorpions. Snakes. But anyway, it it it begs the question of like like, that is an important thing that employees have and white collar workers have is this ability to to learn hard won lessons and then carry them forward forever. And we don't even really know how to design against that necessarily.
Speaker 1:So, Dorkesh is saying that, there's a lot of work to be done at the research level to figure out continual learning, and that could take a while. He says, seven years from now, 2032, and he kind of goes back seven years in in time. That was GPT one, which was a sloth factory. It was not good not a good model, but it was an important breakthrough. And so maybe in the next seven years, something will happen.
Speaker 1:So very exciting. In other news, Rainmaker stands accused of of having a role in the Texas floods. This is a very, very sad story. It's on the cover of the Wall Street Journal, not the Rainmaker part. That has been contained on X, but I'll give you a little update on what's going on in Texas.
Speaker 1:So Texas Texas Rescue grows urgent as toll mounts. At least seventy were killed in weekend floods as more bad weather complicates the search. The search for swept away for those swept away by punishing flash floods in Central Texas over the holiday took on new urgency Sunday as the death toll climbed to seventy and nearly a dozen girls from a private summer camp remained missing. Rescuers combing the swollen banks of the Guadalupe River were holding out hope that survivors might still be found. The potential for more bad weather Sunday also loomed over ground and air operations.
Speaker 1:The National Weather Service warned of more rainfall and slow moving thunderstorms that could create flash floods and in the already saturated in the already saturated areas in the Texas Hill Country. So this blew up on acts. And and people were asking, Augustus, did Rainmaker was Rainmaker operating in the area around that time? Cloud seeding startup Rainmaker is under fire after deadly July 4 floods in Texas. CEO, Augustus Dorico, who's been on the show multiple times, will join us today at noon to break it down.
Speaker 1:He's already explained his side of the story on acts several times, but we will ask him a lot more questions. He says the natural disaster in the Texas Texan Hill Country is a tragedy. My prayers are with Texas. Rainmaker did not operate in the affected areas on the third or fourth or contribute to the floods that occurred over the region. Rainmaker will always be fully transparent, and and he and he gives a timeline of the events.
Speaker 1:He says overnight from the third and fourth, moisture surged into hill country from the Pacific as remnants of the tropical storm Barry moved across the region. At 1AM on July 4, National Weather Service, which we work closely with to maintain awareness of severe weather systems, issued a flash flood warning for San Angelo, Texas. Note summer con convective cloud seeding operations in Texas do not occur during overnight hours. At 4AM on July 4, the NWS issued a life threatening emergency warning and flooding insured. He says, did Rainmaker conduct any operations that could have impacted the floods?
Speaker 1:He says, no. The last seeding mission prior to the July 4 event was during the early afternoon of July 2 when a brief cloud seeding mission was flown over the eastern portions of South Central Texas, and two clouds receded. These clouds persisted for about two hours after seeding before dissipating between 3PM and 4PM CDT. Natural clouds typically have lifespans of thirty minutes to a few hours at most, even with the most persistent storm systems rarely maintaining the same cloud structure for more than twelve to eighteen hours. The clouds that were seeded on July 2 dissipated
Speaker 2:in twenty four hours. I have that I'm sure he'll have answers to is why do cloud seeding operations in the immediately before a massive storm is coming through. I think that's the question that a lot of people have. But we will get into that when he joins the show.
Speaker 1:Yeah. I mean, there's a big question about how effective is cloud seeding. Could you start a flash flood if you've tried? Does this work? Someone was paying for this because it's not a nonprofit.
Speaker 1:Like, obviously I believe it was
Speaker 2:state level.
Speaker 1:State funding. So the state might buy cloud seeding operations in one way. There could be, you know, mistake. He says that he's not involved at all. So we will dig into that with him, later in the show.
Speaker 1:In other news, you gotta update your AGI timelines because there's an underground robot fight that happened in San Francisco over
Speaker 2:This just popped out of nowhere. I started seeing these videos come up. We we have some video here.
Speaker 1:Yeah. This is very cool.
Speaker 2:Oh, we already got a knockout.
Speaker 3:A knockout.
Speaker 2:Did you ever go to battle bots growing up?
Speaker 1:Yeah. I There was a big at Caltech, there was a big battle bot bot annual robotics competition. They stopped doing the fighting ones, they started doing robot soccer
Speaker 2:for Way less fun. Way less fun. Still impressive. And they
Speaker 1:did like rock climbing
Speaker 2:They did different memories for me seeing seeing, you know, a robot with like a massive saw just coming down on another robot.
Speaker 1:Yeah. I I I think it started in in universities, and then eventually transitioned into somebody like raised money and built a business around it, because it was so entertaining. And then now now it's like on TV. But anyway, Sam D'Amico, friend of the show says this was so aura maxed that it will cause a bunch of people on the fence to finally move to San Francisco. And it really it really is a crazy design.
Speaker 1:They built out whole cages here. Like, it it's pretty minimal, but the lighting and everything, like, they really put They very, very well done. And so Verda
Speaker 2:Is Sam calling in today?
Speaker 1:No. No. He's he's not available today, but we'll we'll get him later to break this down. And we wanted to have the founder on, but, the founder is in grind mode.
Speaker 2:Yeah. I can see this becoming a real thing. Totally. Yeah. Where where people just as like a, you know, just side project, whatever whatever you wanna call it, hobby, develop humanoids specifically for boxing.
Speaker 2:Yep. And there's real money, and people are betting on them, and there's sort of these cult hero engineers that that rise to infamy.
Speaker 1:I mean, could be a great business. Like, I I don't know. UFC is a huge business.
Speaker 2:Yeah. I'd rather say I wanna see a a humanoid robot cliff jump off of the Salesforce tower. With the the ground, you know, properly cleared Yes. That when it disintegrates into a million pieces, no one's injured. But watching a robot, you know, sit at the top and then
Speaker 1:I think think that's gonna get you paper clipped if you keep talking like that. You gotta be nice to robots. I don't even know if you They how are they opting in? You ask them? One prompt.
Speaker 1:No prompt injection. No. Do you you can't say refuse, You have to ask it. Would you like to jump off the Salesforce salary?
Speaker 2:You'll probably say no. Things in the airplane is the black box. Right? That's like
Speaker 1:Oh, just make it out
Speaker 2:of black box? Put their brain, put chip Put
Speaker 1:the brains in the
Speaker 2:clouds. In the no. Put the weights in the black box and they can survive and they can do it again.
Speaker 1:Okay. Now we're now we're onto something. Yeah. I like that. So, the founder of the Underground Robot Fight Club says, when I quit my job at a humanoid robot company to start an underground an underground humanoid robot fight club, Barely anyone believed in me or this idea.
Speaker 1:I had no money to buy robots and knew very few people who had the ability to get robots. Thankfully, was able to find the best of the best, our ragtag dream team. The dreamers still alive and sold in this city of madness and psychological warfare. Those are actually willing to put in the work where it matters. The art, the robots, the spectacle, the warriors, every bit of it was perfect.
Speaker 1:The air was electric. San Francisco is alive again. There is much work to be done. So congratulations on a fantastic event. Very exciting.
Speaker 2:Do we know what kind of robots they were using? Were they using UniTree?
Speaker 1:I think it was probably UniTree. I mean, like, if you're gonna buy a Chinese if you're gonna buy a so so I have a hot take on this. You're you're you're you're booing. I think it's a great I think it's a great use for unitary robots. And not just, oh, they're getting beaten up.
Speaker 1:Like, do you think the founders of unitary were hacking on iOS apps? Like, absolutely. Like, Huawei probably bought, you know, a ton of a ton of American and Western technology, hacked it together, broke it apart, learned the best practices, and then was able to build their own stuff. And so I think it's fantastic to to see a project where somebody's taking, you know, something that's maybe controversial like a, you know, like a like a DJI drone or a or a unitary robot, and then learning how it works. And then eventually, you know, maybe it becomes an American supply chain at some point.
Speaker 1:But there's no place you're there's no way you're gonna learn more than
Speaker 2:actually And when we covered DJI earlier this year, they have internal competitions like this where they do challenges and encourage people to weaponize the products.
Speaker 1:Yeah. Yeah. I mean, we saw a video of this with the unitary robot playing soccer and knocking over. And I think that there was a there was a robot boxing match in China as well with unitary robots. So, you know, just just choosing not to do it here because it's Chinese robot, it just doesn't make sense.
Speaker 1:And they're already in a cage. What are they gonna do? Look at them go. Wow. That's pretty impressive.
Speaker 2:Wait. That was a different
Speaker 1:This looks like CGI or something. This is in China. Yeah. They really scripted this. Wow.
Speaker 2:Well, they're moving they're moving different, I gotta say. Yeah. Very, very cool. More athletic.
Speaker 1:Yeah. I mean, I I I think you gotta
Speaker 2:I was saying too on the drive in. I would love to, I think, potentially more entertaining.
Speaker 1:Oh, Oh, no.
Speaker 2:It's A more entertaining format is 100 humanoids versus one professional boxer.
Speaker 1:I think I take the human every single time. Yeah. But it's gonna flip at some point. At Swarmed.
Speaker 4:I don't know.
Speaker 2:That'll be a wild day.
Speaker 1:How do do you if you just knock these on their back, are they done? Can they get up? I think they can. Right? So
Speaker 2:I can see.
Speaker 1:Oh, look at that. It's down. It's down.
Speaker 2:Brutal. Brutal.
Speaker 1:Brutal. Well, speaking of Chinese technology, TikTok is reportedly making a US version of the app called m two. It will allegedly drop a week before the long delayed TikTok ban goes into effect. I believe you have a polymarket on this. ByteDance is quietly building m two.
Speaker 1:It's a separate TikTok version that will hit The US app stores on September 5 as Washington and Beijing negotiate a sale of the American business to local investors. And I believe that you'll need to download that app and then like link and transfer everything. So you're on like a completely clean
Speaker 2:They gotta transfer over the back doors? Yes. You gotta get all the back doors properly installed.
Speaker 1:Yeah. Exactly.
Speaker 2:Pull up this Polymarket. So this new app allegedly would coincide with the sale Mhmm. Of The US operation to a US investor group. Right now, TikTok sale announced in 2025. It's currently sitting at a 45% chance.
Speaker 2:Mhmm. It popped on, the recent news
Speaker 1:Oh, yeah. 45%.
Speaker 2:About the app. Okay. So we will see how this ends up shaking out. But seems likely that a deal is coming together. Yep.
Speaker 2:The rumor was that a 16 z was involved.
Speaker 1:Larry Ellison and Oracle combined have a huge have a huge potential stake in the business. But, yeah, big question about is it going to be just just, you know, local investors or is it gonna be the cloud hosting that happens or is it gonna be entirely, you know, US based programmers that are inspecting the various code bases? There's a lot going in there.
Speaker 2:And the and the algorithm.
Speaker 1:That's a big question. Right? Yeah. I believe the worst case scenario was was the the algorithm is trained in China and then inferenced in America because and I think if that happens, it really reveals that, whoever wrote that law, like, doesn't understand the difference between training and inference. Of course, there are things that you can do, like, post inference, like, above the inference level.
Speaker 1:They can go to mind weapon.
Speaker 2:You guys operate
Speaker 1:it. That's the risk. Right? That that that's certainly the risk that they don't get the balance right. Ideally ideally, the the The United States, if they like, if there's a fear that TikTok is leaning too brain rotty or too right wing or too left wing, you would hope that the America like, America would have the ability to kind of steer those weights in training, but we'll see how it pencils out because it it totally could wind up being a situation where it it's it's all it's all just running on Oracle Cloud infrastructure, but it's not American code in any way, and that would be a risk.
Speaker 2:Well, yeah. I I think America's interests, it's it's more important that to have somebody actually aligned to America Mhmm. That has influence over the way that content is distributed in the product. Yeah. Less important is the revenue generation that, theoretically, this new investor group would would Yeah.
Speaker 2:Benefit from. It's more about ultimately control.
Speaker 1:Well, speaking of America, Elon Musk has put up a or I guess this is from Tesla owners Silicon Valley. Elon says I want you for America party. Elon. Yeah. You have to, man.
Speaker 1:Is Tesla owners of Silicon Valley a neutral party here? Well, they do break it down well. That's why I I picked this post, because they are Elon Musk retweeted it, and it seemed like a good distillation of what he's going for here. He says, he so Elon Musk has officially, announced the America party, a third party. We will see where this winds up landing, but at this point, his, his stump speech is essentially, America's party will be focused on reducing the debt responsible spending only, modernized military with AI and robotics, pro tech accelerate to win AI, less regulation across board, but especially in energy, free speech, pronatalist, centrist policies everywhere else.
Speaker 1:Are you down for this?
Speaker 2:And So is it a new entirely new party?
Speaker 1:Right now, he is positioning it as a third party. And and I I saw he or the America party followed Andrew Yang, who was a third party candidate for a little bit with the forward party. And so there is discussion that, you know, Elon might be pushing for a true third party presidential run with someone that he backs. Of course, he's not eligible to run for president himself, but he would he would find someone to champion the party.
Speaker 2:And the critique of that is that third parties have never worked, and it will only hurt it'll hurt your general interest by further fragmenting the vote.
Speaker 1:Totally. Yeah. Yeah. I mean, at at this point, Elon is is, you know, extremely aligned with the MAGA right. If he pulls, if he he would most pull away from that.
Speaker 2:Are you're you're saying he's more aligned?
Speaker 1:He's he's super aligned with the MAGA right.
Speaker 2:In some specific ways.
Speaker 1:Well, yeah. I mean, over the last year. And so and so if he if he says if he says, I'm leaving the right. Who's coming with me? It's going to be a
Speaker 2:disproportionate win with the MAGA right on
Speaker 1:on Totally. Totally. Totally. But but but the people that he would pull towards the America party, it's like the Green Party typically pulls from the Democrats. The America party, it feels like it would probably pull from the Republicans.
Speaker 1:And so the net effect is that if there's not a splintering, if there's not an equivalent splintering on the left, this would mean this would be very, very good for for the left. Yeah. Very good for the left.
Speaker 2:And Tesla shares are down 7% today. Yeah. So the shareholders
Speaker 1:Want him not to be in politics. Yeah. And he can't he can't stay out of it, I guess. I we we there was a funny funny take from one of our friends that Elon's going through, like, of the, like, iterations that anyone goes through when they become, like, politically aware of just like, oh, like, you know, like, I'm neutral about this. Now the government's terrible.
Speaker 1:We need to make it more efficient. Now we need a third party. Now we need this. Now I should run. And it's just like but he's like speedrunning it.
Speaker 1:Just dancing from, like, one one strategy to the next and then learning, like, the hard won the hard fought lessons along the way of like, okay. Like but it is early, so it's unclear where the America Party will shake out. Like, this might take the form of, okay, primary some people in the midterms and then learn the lesson there, and then maybe come around between one of the the the two party system because most of the people that have gone up against the two party system have lost. But it will be interesting. Zach Kuukoff was telling us that it's possible that the American party just becomes like a caucus, the American caucus of the conservatives.
Speaker 5:That's what
Speaker 2:I expected. Yeah. After after he laid out the many logical reasons why that would potentially be more effective.
Speaker 1:Yes. So that might be still where it lands, but that's not where it is right now. Right now,
Speaker 2:it's not as exciting.
Speaker 1:Oh, no. It's definitely not as exciting. Anyway, one of Elon Musk's good buddies, Larry Ellison, is doing deals with the government. Oracle struck a general services administration deal giving federal agencies up to 75% off software licenses and deep discounts on cloud and AI services aiming to chip away at AWS and Azure's dominance in the government. This is very good news.
Speaker 1:From the Wall Street Journal, Safrakatz, the CEO of Oracle has posted, we are proud to help the federal government modernize this technology while gaining the benefits of OCI, Oracle Cloud Infrastructure, and AI. This agreement with the USGSA provides all government agencies access to the world's most advanced cloud technology at the most economical price. And so, very interesting. There's a lot of dividends from working with the government. Like, I I feel like the fact that Microsoft Azure has been so ITAR compliant, it's just like led to a lot of startups being like, well, I gotta go there because I'm doing something just as serious as the government.
Speaker 1:Right? Yep. And then and then obviously, like, over time, if you actually win the government as a client, well, who knows if those 75% discounts need to hold forever? Like, that could probably be a really sustainable source of revenue over the long term. Leader.
Speaker 1:And yeah. And and also, yeah, could could be a loss leader for other folks jumping on board. So exciting to see that Oracle is doing that. And then in other news, Meta won a copyright lawsuit. Henry here says it's a good day.
Speaker 1:The plaintiff fumbled the case so hard that the judge spent half the ruling explaining how they could have won if they did literally anything different. But this is going back and forth on whether or not it is fair use to train an LLM on proprietary data, on copyrighted data. And it's looking more and more like
Speaker 2:complex has been on a general generational run of L's in the Indeed. It's hard to Well, I think that a lot of these the judges and have generally been getting it right. Yep. It's hard to it's hard to really cheer here because Mhmm. I care a lot about authors that work hard to produce their works.
Speaker 2:And I can understand Yeah. Where the frustration comes from. Yeah. But I believe that by and large, the model companies have have been will will be on the right side of history Yeah. On this issue.
Speaker 1:I'm I'm pretty optimistic. I think that when we talked to Matthew Prince from Cloudflare, he had an interesting model essentially getting to a Spotify like model where if you publish on the Internet and LLMs are using your writing, your original work, your reporting to answer questions to somebody who's paying $200 a month. Hey, send me a dollar of that. And you aggregate that. That seems doable.
Speaker 1:It also seems very doable that the big publishing houses could do deals. We've seen Wall Street Journal and News Corp did a deal with OpenAI. Now when I go and ask Chad GPT about something in the Wall Street Journal, it can jump the paywall, but they're getting a cut. And so you could see that happening with Audible. You could see that happening with, you know, Apple Books, Google Books.
Speaker 1:They they have everyone's information. They could flow a little bit of the rev share back. And that could actually be a reasonable economic model. So I'm not Totally. Super I'm not super worried.
Speaker 1:I'm still cautiously optimistic that that works out. Anyway, those are our headlines. Let's tell you about Ramp. Time is money. Save both.
Speaker 1:Easy to use corporate cards, bill payments, accounting, a whole lot more all in one place. Go to ramp.com to get started. And we have our first guest of the show, Dwarkash Patel, in the studio. How are
Speaker 2:you doing, Dwarkash? What's going on? The
Speaker 1:soundboard's a little loud.
Speaker 2:Great to have you back.
Speaker 1:I we're not getting audio right now. Can we check on that? I don't know if you're on mute on your side. But loved the piece. Listened to it last night.
Speaker 1:Really appreciate you dropping it in the podcast feed as well. Do we have you?
Speaker 6:I can hear you now?
Speaker 1:Yeah. Fantastic. There we go.
Speaker 2:AGI is here. We can do we can do a Zoom call.
Speaker 6:I'm just getting used to this podcasting thing.
Speaker 1:First time. Anyway, really enjoy the piece.
Speaker 2:Wait. Wait. We have to we have to call Tyler Cowen was on our show a couple months Really aggressive kind of just like, basically was
Speaker 1:calling
Speaker 2:He's
Speaker 1:PAI three AGI. AGI is here.
Speaker 2:And wasn't able to get his video on at the time. So we it was this funny contrast that reminded me of of you talking about you're trying to build with a lot of these tools. Yep. And in the process of building with them, you realize like, okay. This is amazing, but it's actually just gonna take a little bit longer than maybe we would all like.
Speaker 6:That's right. So Yeah. But by the way, I think there's something really interesting. Tyler and I disagree on two things. Mhmm.
Speaker 6:And they're both related in a way. Mhmm. So Tyler you know, when o three came out, Tyler wrote this blog post on Marginal Revolution where he said, AGI is here. Guys, it's really AGI. But then he also believes that, look, the impact of AI is not gonna be that big.
Speaker 6:Once we do get your AGI is gonna result in point 5% more economic growth a year, the kind of impact we saw from the Internet. Right? And so I think these two are actually quite related beliefs, where I'm like, these LLMs, they're not that useful. This is not AGI. You know?
Speaker 6:The AGI will come later. And I'm like, when the AGI hits, we're gonna see, like, 20% economic growth as a minimum. But because he's like, this is AGI, I'd be like, if I thought this was AGI, I'd also be like, this is not that this is not this is not it. You know? This is not gonna lead to big growth outcomes.
Speaker 1:Yeah. Yeah. Yeah. How are you thinking about, like, just definitions of AGI? And I'd love to I'd love to actually get your a little bit of a history before this piece, your journey.
Speaker 1:Because for me, you know, I grew up watching sci fi. It was like, yes, three PO will be around eventually, but it's very abstract and I don't have timelines for that. And then eventually, you know, you start reading,
Speaker 2:you know What's your p three PO?
Speaker 1:Yeah. Yeah. You eventually start seeing GPT three, GPT 3.5, DaVinci, ChatGPT, and it starts feeling like, okay, we passed the Turing test. We need to really have this conversation about
Speaker 4:Right.
Speaker 1:AI. And then and then PDOM and AGI becomes like the main discourse for like few years. Right. But it felt like this piece even though, you know, you and Dylan were going back and forth being like, no, this is still like incredibly bullish for like the general population.
Speaker 2:Yes.
Speaker 1:It felt like this was you pushing out timelines a little bit. So Yeah. Walk me through like, where did you start? Where when was the nadir of your timelines? Like, when was your timeline like it's happening next week, next year?
Speaker 1:And then and then walk me through how we got here.
Speaker 6:Yeah. So, I've got this podcast where I interview people about AI, and I've had on people who have quite aggressive timelines over the last few months. I've been with people who are like, well, you know, there's been many people who have written pieces about how we're a couple years out. Right? Leopold Aschenbrenner, AI 2027.
Speaker 6:Recently, Scott Alexander and Daniel Cocatello had the EA 2027 scenario forecast where, you know, we've got the we've got the bots that can just take over within the next few years. So that's where my head was at as of a couple months ago. And then I recently interviewed these two researchers. I think you actually had one of them on your podcast, Sholta Douglas and Trenton Bricken from Anthropic, about the path forward for RL, which seems to be the pretraining seems to have been giving us these plateauing returns. We make these models bigger.
Speaker 6:GPT 4.5 didn't seem to be all that impressive. They'd had to deprecate it. So but the path forward does seem be, like, o three actually is very impressive. So Yep. That was more the result of this RL process.
Speaker 6:So maybe now, actually, even though pretraining doesn't seem to be as powerful as we might have anticipated, this RL is even more powerful, and so we should accelerate our timelines. And so that's where my head was at as of a couple months ago. But then in having that conversation and thinking through, okay. What specific capabilities in terms of actual applications I, as a small business owner, have or as a podcast producer, have will AI be able to do? And thinking about, like, why is it not able to do these things right now, and what is the key bottleneck?
Speaker 6:I realized there's actually no obvious way in which you can either get LLMs to solve these problems for you, or there's no key algorithm. There's no easy, like, you know, prompt injection kind of thing, which would help solve these problems. And the key problem I see is this the models can't do on the job training. So if you think about a human employee, you might have some. And these human employees, the good thing about them is that, you know, you train them for six months or a year, and over time, they're getting better and better.
Speaker 6:They're learning about all the context and intricacies of your workflow, what you like. They they'll fail, but they'll learn from their failures, and they'll interrogate them in this, like, very organic, deliberative way. They'll pick up small efficient efficiencies and improvements as they practice a task. This just can't doesn't happen with an LLM. Every session, you're getting this amnesiac mind that's very smart, but it has it's lost all awareness of how you like things done, how your business works, and so forth.
Speaker 2:Yeah. If you had a just just to put that into context. If you had a incredibly intelligent employee that could not take feedback, you would fire them within about a month. Right? Because no matter how smart you are, like that you're not necessarily gonna predict every single possible edge case in the work that needs to be done.
Speaker 2:And then and then when you make a mistake, if you're not able to like sort of update yourself Yep. Then then what are we even doing here? Right? Like that that's like learning like learning from mistakes is like kind of high on the list in terms of how to become great at any specific task or initiative.
Speaker 6:100%. And so then people will say, well, look. Maybe the way we can they can learn from their mistakes, Jordy, is, like, you can just tell it in the context. Hey. You fucked up this way last time you were working for me.
Speaker 6:Don't do it again. But I think the this is at least an order of magnitude less efficient and less less capable than the way humans learn. So the example I use here is imagine if you were trying to teach a kid to play the saxophone. But the way you had to teach this is, you know, a kid comes into the room, and they, like, try to play it cold. Right?
Speaker 6:They've never seen a saxophone before. They try to play a saxophone. And, obviously, it's not gonna sound the first great the first time. But what you do is then, like, after they fail, you just send them out of the room. You call the next kid who's waiting outside of the room, and then you say, look.
Speaker 6:Here's some notes I wrote down from last time about what the other kid fucked up. Why don't you read that and you try to play Charlie Parker cold? It just wouldn't work. Right? This, like, tacit knowledge that you build up through practice is not this, like, written instruction manual that you can just write out as a system prompt.
Speaker 1:Yep. And so our current solution is to, RL on saxophone playing specifically for that child. And then and then in that in that scenario, you're basically getting that kid drilling that. But my question is, like, it feels like when we think about that in the abstract, it's like, oh, yeah. Like, work is just, like, doing emails.
Speaker 1:So let's RL on emails, then it's doing calendar. So let's RL on that. And so well, yeah, we'll just chip down at these and, like, you know, book a flight and then, you know, schedule a call and then do an outbound sales thing. But, really, jobs are not just five things to RL on. Maybe it's 500 things or thousands of things.
Speaker 1:And so maybe the the shape of those, like, even if we even if we can define a verifiable reward and drill it, it's just there's so many different random things to do that it's gonna take us a long time. Is that a reasonable, like, philosophy?
Speaker 6:That that I think is part of it. Mhmm. But I think the bigger problem is not just the width or the the width of the pool, how many different tasks you have to RL on, but it's a depth in the sense that a job doesn't involve doing a thousand different five minute tasks individually.
Speaker 1:Mhmm.
Speaker 6:It's the fact that you're, like, trying to work on something, but then somebody Slack messages you something more urgent, and then you had to decide which one is more important. You're, like, you're you gotta keep track of this client and then what what problem they had. By the way, I'm talking hypothetically about what a job might involve because I've never actually worked a real job.
Speaker 1:Me. But
Speaker 6:so just like how all these all these things fit together is we already have these language models that can do, like, five minute language jobs. Right? And then the question is, why can't we just delegate all language work? For example, I have these LLMs. I try to get these to rewrite autogenerative transcripts for me so they're rewritten like a human.
Speaker 6:I try to get them to just ingest the transcript and suggest clips to tweet out and things like that. And I haven't been able to automate these things. I don't know if you guys have been able to, but it's just like I still have to do it or
Speaker 1:I have
Speaker 6:to get a human to do it. Yep. Because and it is it not because we haven't you know, you might think about, like, emails or something we gotta get, like, future data on. But this language stuff, we already have the data on. Right?
Speaker 6:So, like, why can't we do it now? And the reason is they can do, like, a five out of 10 job out of the box. These are short horizon, language and language dot tasks that center in their repertoire. But there's no way to get them to improve. So over time, you can't be like, look.
Speaker 6:My tweet that tweet was fire. Like, it went viral, and here's why I think it went viral. And then kinda learns that and, like Yep. Updates its, like, sort of understanding and writes better tweets in the future, same with transcripts, picking up your feedback. Since there's no way to do that, even if you have all these individual tasks like, we have all these individual language tasks these models can do, but you can't then just be like, okay.
Speaker 6:Now you're an employee. Because an employee is actually improving over time and building up context in a way these models are
Speaker 1:Yeah.
Speaker 2:The big question I've kept bringing up and asking a bunch of different people is where are you getting value from agents? And Mhmm. Not a lot of people have great answers. They'll be like, oh, well, we use we use this or we use that. But you don't see a lot of conversation online of people like, oh, this SDR is just crushing it for this like AI SDR is crushing it for me or this Yeah.
Speaker 2:This other use case is crushing it. You just don't see that at all. And the reason that that's worrying is that when products are truly great or even have the potential to be great or starting to like really work, people just talk about them a lot. Right? Like people Right.
Speaker 2:Talk about cursor a lot. Right?
Speaker 6:People Yeah.
Speaker 2:Talk about Claude code a lot. Yeah. And there's some individual use cases like coding agents seem to have the most real traction.
Speaker 1:Deep research, I would also call like an agent. I don't know if you would put it in that bucket but it feels But
Speaker 2:again, it's just, it's pure
Speaker 1:Yeah.
Speaker 2:Again, it's it's not like this, like, highly agentic
Speaker 1:Yeah. But I don't think of deep research as, like, an employee in that same sense. It's not like repressing
Speaker 3:a call.
Speaker 6:Be like, okay. That's great. This this thing you put together
Speaker 1:Yeah.
Speaker 6:Here's how I like to compile my ideas before a podcast. So, you know, you did a great job compiling this, like, Stalin memo. Yep. I was very curious, especially, these why the Great Terror happened in this way, and keep that in mind when you're doing a future memo. Like, this style.
Speaker 6:That's not gonna happen. It's got the style that it's learned through its RL training for deep research. So then again, it just becomes another tool. It doesn't really it's not it's not you know, it doesn't become like an employee for Yeah.
Speaker 2:Can you explain? And the other thing just since since your post was inspired, know, by your own tinkering. Some of the stuff that I'm most excited about that we've gotten value specifically from code gen internally. It's just these internal tools that we totally could have built years ago. Mhmm.
Speaker 2:That are just now really fast to build. So we built something Okay. For our ad partners that like automatically finds the exact all the different moments that we talk about them in a given show and then just like links it out. And it it's basically just a simple database dashboard that they access to. That like historically you could have built but it just would have been like really time intensive.
Speaker 2:And so it's not anything it the the the value is that you can now build it like in a couple Yeah. So, I've been trying to separate it's like, all this is happening in the context of you have hundreds of billions of of like enterprise value locked up in these different labs. Some of which have developed what look like great businesses. Right? OpenAI Mhmm.
Speaker 2:Consumer. Basically, a new consumer app company. Anthropic with cogen. And then there's still like hundreds of billions of value of of like EV out there. Mhmm.
Speaker 2:Where it's unclear where the revenue is gonna come from. And so when timelines extend and AGI isn't happening, you know, next year or the following year or whatever. I start to get generally a little bit worried because that's a lot of EV to kind of maintain for another half a decade or a decade, whatever it it turns into.
Speaker 6:I'll I'll I'll get a little more bullish and hype y and take the other side of that, take the other side of your claim. Look. I think even if it doesn't happen in the next two to three years, what we're talking about here is such a big deal that AI is definitely not priced in, not by the average person, not by the market, by anything. Because once you get this thing which actually does function like a genuine white collar employee, not only do you have potentially billions of extra workers, but you have something potentially more powerful, which is that right now, a human mind can't be copied. Right?
Speaker 6:A human mind can't learn from the experience of other minds. If we have a model
Speaker 2:that be built really slow. Like, you have to basically work with somebody for a decade, and then you can do work. Yeah. It's mentorship. Yeah.
Speaker 6:Yeah. Yeah. And then in fact, it's been a big problem because as our society has built up more knowledge, we had to keep people in school and training for longer and longer, which reduces their productive years. But with an AI model, you could have a scenario where suppose there is a model that's actually capable now of continue learn learning the way humans can learn. Not only would it so, you know, it's broadly deployed through the economy.
Speaker 6:It's doing all these different jobs. The difference is that it is now able to amalgamate its learnings across all its deployments. So if one of them is accountant and one of them is a coder and whatever, the the model is learning from each of these different on the job experiences. And then so even if there's no software progress out of that point, that algorithms aren't improving, just that ability to learn on the job from everything in the economy would functionally produce what looks like a super intelligence. Right?
Speaker 6:The the no human will be will have mastered the range of skills and knowledge and know how that this model will have.
Speaker 1:That makes sense. I have I have two questions. One's kind of maybe bearish. One's bullish. On the question of just, is it possible you think to brute force continual learning by just doing something on the design of these model side or maybe in the hardware side to just get to a trillion token context window and then just stuffing it with everything?
Speaker 1:Can you explain kind of what the state of the art is here? Because you were mentioning in the piece, like, the cursor roll ups, the summary lines, and then stuff getting lost in there. But if we get to a 100,000,000,000 token context window or something, could it actually just remember every single interaction it's had?
Speaker 6:I am not optimistic about that because we've had since 2018, we've been we've had the transformer or alterations on the transformer as being the most performant models. And, you know, who knows what the labs are doing, but we do have open source research from companies like DeepSeek, which does seem to be at the frontier or close to the frontier. And while people have found modifications to the transformer, which make the constant time overhead of attention, the reduce the constant time overhead on attention to, like, you find these little hacks with mixture of experts or latent attention. Nobody has gotten around the inherent quadratic nature of attention. And, basically, this means that the the cost of the additional token increases super linearly Mhmm.
Speaker 6:To just that additional token. So right now, we have models out of a million tokens or 2,000,000 tokens of context, but getting it to 4,000,000 tokens is more than twice as much compute. Got it. It's significantly more than that. And then just taking it to, like, a billion and just given the fact that this hasn't nothing about this has changed over the last, whatever, six years, I'm just, like, not optimistic that somebody will figure out a hack Yeah.
Speaker 6:That will change it immediately.
Speaker 1:Then on the on the side of, like, how do you think about continual learning in domains where time is I I I keep going back to this idea that, like, even if we create the ultimate superintelligence, like, it probably will have to obey the laws of physics, won't be able to time travel or teleport. And so there's a lot of, restrictions on that. Like, at a certain point, you just need to move the sand into the chip fab, and and then there's a certain amount of energy and time that it takes to do that. Another example would be, like, longevity research. Some of that, you just need to sit around and wait for a human to age.
Speaker 1:And so your RL cycles, if you're, you know, trying to learn about how humans age, it it's very hard yeah. You can, like, simulate the human or whatever. But, like, for the real test, you have to wait decades to see the effect of a certain diet on how long people live. And so it feels like whether it feels like there's a lot of scenarios where the where you can't fully do it simulated, and so you wind up with these really long times to actually do a rollout, essentially. And Yeah.
Speaker 1:And you wind up with something where the the, like, the time to actually get a new data point or new training data is, like, you know, a thousand times longer than what we've been doing previously. And so we're in this, like, this, like, you know, data desert, basically.
Speaker 6:Yeah. I I think this will definitely be true of many domains, especially those involving the physical world.
Speaker 1:Mhmm.
Speaker 6:I guess as I've learned slightly more about some of these physical domains, it's been surprising to me how much can be done in simulation. Mhmm. Within bio, for example, obviously, we, AlphaFold and, I guess, now AlphaGenome. But even,
Speaker 3:one of
Speaker 6:the key advances in Bio over the last couple of decades has been techniques of multiplex experiments, just running millions of experiments in parallels, getting data points from that past, using AI to learn from millions of seemingly experiments in different fields about, like, what that might imply for the human body or for human proteins. So I am, like, optimistic. Another thing to keep in mind is that right now, you know, a corporation might have a 100,000 employees, but how much is learning from any single employee is very limited. People are just go in, do their jobs, and that's that. In the future, if you do have this economy of agents, and it's much easier for AIs to supervise each other or to, be observing every single thing that's happening in the organization, the the speed of learning might be exponentially faster, than what's possible with humans.
Speaker 6:I agree this is, like, not around the corner, but the sort of singularity in futures with crazy cyborg organizations that are moving super fast and coming up with new technologies doesn't sound crazy to me.
Speaker 1:Interesting. What do you think the recent like, last week was dominated by the talent wars and the and and the huge AI researcher offers at Meta. What do you think that reveals about Mark Zuckerberg's AGI timelines?
Speaker 6:By the way, I I loved I loved all the memes, the traded memes. Honestly, I should lean into that because, like
Speaker 1:Where do you want
Speaker 6:genuinely this is not even a meme. This is, like, genuine the market captured move by billions of dollars based on these posts you guys are doing.
Speaker 1:Yeah. It was crazy seeing like like 10,000,000 views on a an AI researcher getting traded. Like, it it it it's niche, but it's not really that niche anymore.
Speaker 6:Right.
Speaker 2:It's Yeah. But I don't think I don't think you could have you certainly couldn't have fully imagined that five years ago.
Speaker 1:No way. No way. Yeah. It's it's important stuff.
Speaker 6:I mean, I still think they're, like, underpaying them. I think, like, Meta is the first company that is actually coming close to the breakeven point of Yeah. The value of the grid. The what the best AI researchers actually worth the company. If you're Meta and you're spending $80,000,000,000 on compute over the next couple of years, if one great researcher can give you a 1% performance uptick on that, They're, like, so worth the $100,000,000 pay pack.
Speaker 6:You're getting a bargain at a $100,000,000. So it's actually interesting to me that Meta is the first company that's like, wait. The the return on investment here is incredible. Let's just do it. And then, okay, are the vibes bad?
Speaker 6:Maybe. Could they have done the announcements better to produce better, less mercenary vibes potentially? But what so there's, like, some ideal version of what they could have done. But, also, keep in mind that the likely counterfactual would not have been that amazing, you know, great vibes announcement. The likely counterfactual would have been what they're currently what they're previously doing, which is just, like, sleepwalking towards loss.
Speaker 6:And it's much better to just, like, fuck it. Let's just let's just send it with a couple billion dollars in recruitment offers. And, like, at at least now they're on the player board rather than just like sleepwalking towards Armageddon.
Speaker 2:Mhmm. In many ways, it's it's interesting how viral these, like, $100,000,000 number you know, the 100,000,000 is obviously a big number, but whatever whatever the range is, people are so normalized to professional athletes being comped tens of millions of dollars a year. And just purely looking at these types of moves from an economic impact is like signing a star pitcher to a baseball team in one area. Like like how you know, it's surprise it's surprising it's taken this long. And the thing that that we were kind of joking about to put it into context is when you see that Tim Cook makes 74 he made 74,600,000.0 in total comp last year.
Speaker 2:Right. He looks dramatically underpaid.
Speaker 1:Yeah.
Speaker 2:Right? Yes. He already looked underpaid in the context of like Ohtani Ohtani making company trade war. Was making I think Ohtani was making somewhere around Yeah. 70,000,000 a year.
Speaker 2:So he looked under under compensated in that context. Yeah. And then, yeah. I think Yeah. Think the I guess The other thing that I'm sorry.
Speaker 2:The other thing that that came to mind for me from your piece is, I feel like there's been this kind of like toxic idea floating around teapot which is like, you have one year to accumulate capital Mhmm. Before you're a part of the permanent underclass. And the takeaway from this, you know, if you're correct and that like things will just Mhmm. Great things will naturally take longer. Then if you're in teapot now or you're at all in AI or or you know, anywhere of these adjacent spaces, it's like, and you're like 30 years old or 35 years old or 40 or you're 20.
Speaker 2:It's like, you're here at the perfect time. Right? It's in in I think it was Mhmm. Was it was it Mark Andreessen who said that he showed up to Silicon Valley and he thought he had like missed the
Speaker 1:Oh, he missed it. Yeah.
Speaker 2:He missed like the PC There's no way
Speaker 6:stories like this.
Speaker 2:And so and so I think it should be like people should be like tremendously excited a personal level and and no more of this like doomerism of of of, you know, you gotta like, yes, you need to move quickly.
Speaker 1:Yep.
Speaker 2:Yes, you you should be working with the best possible people trying to have the most impact be as close to the to the real action as possible. But no more of this like doomerism like Yeah. You better get, oh oh, sorry, you know, you didn't get a $100,000,000 offer this year. It's over. You know?
Speaker 6:No. No. 100%. I mean, there's so many actually it's it's very funny how often this comes up. Like, the prince of Persia's game developer, he wrote this diary while he was making it.
Speaker 6:And in the nineties, he's, like, talking about, I'm gonna become a Hollywood scriptwriter because I think I missed programming. I have a CS degree, but I missed programming, so I'm gonna be a Hollywood screenwriter. Oh, wow. I remember three years ago when I started the pod when I was, like the podcast was early days or two years ago, and I moved to SF, I'm like, oh, GBD three has come out and, like, all the rapper companies are made now. So I'm gonna, like I I'm, you know, like, I'm not gonna be a rapper.
Speaker 6:I mean, whatever. The podcast worked out. It's fine. But Yeah. Even then, I was like, oh, I missed AI.
Speaker 1:Yeah.
Speaker 6:So I definitely think, in retrospect, we'll because I'm like look. Another thing to keep in mind is that Cursor only hit product market fit after Cloth 3.5 came out and gave these coding abilities. Mhmm. There's going to be many other things like Cursor, which will only be viable products once you have continual learning on board or once you have, computer use that's working on board. And these are capabilities which I think are exponentially more valuable economically than the models as they exist right now and which many companies will need to be formed around to complement.
Speaker 6:Mhmm. It's not gonna happen by default. Right now, OpenAI's revenue is, what, 10,000,000,000 a year ARR. I mean, if it's AGI, it should be, like, trillions ARR. Right?
Speaker 6:Yeah. So what l what other infrastructure will be built around that? The the cursor equivalents for whatever continual learning enables. Like, definitely, biggest companies have not been formed yet because the capabilities that would make them so valuable are not available yet.
Speaker 1:Yeah. In terms of the, I guess, like, the mag seven CEOs, the major players, there seems to be this continuum. On one side, you have the, you know, philosophy of, like, dollars and cents. Okay. People want tokens.
Speaker 1:I can inference them. And maybe it makes sense to hire an AI researcher for a $100,000,000 if they can improve your model and bring your model in house so that you don't have to pay OpenAI or Anthropic for those tokens. On the other side, you have someone a little bit more like Elon who see this as an existential threat. It needs to be done the right way. It's very important.
Speaker 1:It's almost Doom based philosophy. Where do you see the other folks in in the Mag seven or in the in the AI race kind of sitting? Like, does the super intelligence team and these big offers move Mark closer to one or the other? Because I was able to kind of justify the llama investment just from, hey. If they don't do this, they're gonna be paying billions and billions of dollars to Anthropic or OpenAI just to bend LLMs internally as b to b software because they're gonna need this in every little nook and cranny of Instagram for a long time.
Speaker 1:So so I could justify it in that realm. I could also justify it in the realm of, like, this is the most important technology in human history. You gotta have a you you you gotta have a play.
Speaker 2:Or compute efficiency, like you laid out.
Speaker 6:I interviewed Satya. I interviewed Mark. And the sense I got from them was that neither of them I mean, I I feel like Meta's group is called superintelligence, but I I didn't get a sense from either of them that they're like they believe in superintelligence in the way I mean superintelligence, which is the thing that's, like, building solar factories in the desert and then launching the probes and so forth. Yep. They I mean, even something that's much weaker than that is still functionally superintelligence.
Speaker 6:Like, in some ways, these models are already superintelligent in some ways, but their abilities aren't fully unlocked because of the other handicaps they have. But I think they you know, like, whenever Mark's talked about it publicly, he's talked about, you know, creating better social experiences and making the ad targeting better and VR stuff. Right? So I think that's also same with Satya, but with making Office a better, you know, copilot for Office, which also would be worth hundreds of billions of dollars a year. Totally.
Speaker 1:Yeah. So it's it's tough.
Speaker 6:But I think they think about it differently than somebody like Dennis or Dario, who are like, no. No. No. AGI is the real thing.
Speaker 2:Yeah. Do you expect the tension between the app layer and the lab layer to just get crazier and crazier and crazier, it feels like that that will be the story of the next five years is kind of these, like, symbiotic at times, but then adversarial at times, you know, relationships.
Speaker 6:I mean, previous technological, you know, like, nineties, February, Google's Chrome stuff runs on Microsoft, but they can have an adversarial relationship. So it would line up with history. But I think, like, the the bigger issue is just that because I think the full potential of AI requires so much more progress in terms of algorithms, I just think the app layer companies that are building on top of models that exist today are just upper bounded how much value they can extract because the models aren't good enough yet to do the things that will make them especially powerful. So for that reason, I'm like, it doesn't make sense to me that Cursor would be worth a whole sixth or eighth of Anthropic. If you think Anthropic has some chance to crack continual learning.
Speaker 6:Right? Mhmm. So I am more bullish on the foundation layers aside than the app layer because I think the app layer will turn over once these capabilities are unlocked. Whereas, like, the fundamental research has to be done one way or another. As far as whether that means they will fight about it, we'll see.
Speaker 2:Yeah. I mean, it could it it could end up looking like the same dynamic we have now, where we have cloud hyperscalers that are worth trillions of dollars. Then we have we have valuable businesses that are worth measly 1,000,000,000, 5,000,000,000, you know, and they're still big businesses and and maybe can generate a return but but not power loss.
Speaker 1:Last question from my side, we'll let you go. What has Sarah Payne taught you about artificial intelligence?
Speaker 6:You know, at some point, I asked her because her whole big thing is continental versus maritime powers. Continental powers wanna invade and capture territory, and maritime powers wanna protect free trade. I was just like, what big tech company is, like, a continental power, and what big tech company is, like, a maritime power? She's not she's not she's not watching TVPN, unfortunately, so she's not aware. But, actually, this is a question I'll turn around to you.
Speaker 6:What what who's the continental power in the of the Big seven and who's the maritime power?
Speaker 1:That's a good question. I think I think Microsoft has carved out a lot of territory that will be harder to hold on to. I'm not exactly sure how that how that maps.
Speaker 2:I think another question is which big tech company is pro internet like free internet. Right? Is there if everybody wants their data walls and closed networks.
Speaker 1:I would probably say Apple continental meta maritime maybe. Mhmm. Something like that might be right. Apple, they don't need to go and invade the the Android ecosystem. They need to just really control privacy.
Speaker 1:What happens in their ecosystem? 30% Apple tax versus Meta needs to do OAuth and acquire Instagram and and WhatsApp. I don't know. That that's just off the
Speaker 6:top of
Speaker 2:my head. Apple with the the iOS Apple with the the iOS you know tracking
Speaker 1:That feels like build the wall. Like like you know that app tracking transparency, build the wall. Tim Cook's
Speaker 6:No wonder Tim Cook got so along with 45.
Speaker 1:Maybe. Maybe. Do you do you have a wildly different take? Or
Speaker 6:No. No. I mean, it just mostly fodder, but I I I It's fine. Agree with that. Like, Apple feels kinda or Apple and Oracle, I'd say, like, Continental.
Speaker 6:Sure. Google Meta, Maritime. Yep. I like that, though.
Speaker 1:But it's a good it's a good thought exercise. So she clearly taught you something. Well, fantastic. Thanks so much for hopping on on short notice. Love the piece, and thanks for publishing it.
Speaker 2:Talk to
Speaker 1:you soon.
Speaker 6:Guys are killing it. Great being on.
Speaker 2:See you. See
Speaker 1:Cheers. Bye. Really quickly. Let me tell you about figma.com. Think bigger, build faster.
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Speaker 2:complex If you think it might be SOC two time, it's probably SOC
Speaker 1:two time. It's probably soctime.com. Well, our next guest is here, Augustus Dorico, the CEO, founder of Rainmaker. Welcome to the stream, Augustus. How are you doing?
Speaker 7:John Jordy, thanks for having me. I am doing well. I am obviously talking to a lot of people about the flooding that's going on in Texas and appreciate the opportunity to clarify that rainmaker and cloud seeding had nothing to do with the flooding that unfolded. Mhmm. And even in spite of that, I think that it's a a tragedy that it did happen and certainly don't want anybody to use this opportunity, use this controversy to blame cloud seeding for the sake of popular political support.
Speaker 7:And you may have seen that Marjorie Taylor Green, is proposing running a bill to ban all forms of weather modification based on those that we saw in the Florida state house legislature, earlier this year. I think it would be both disrespectful to the families involved and baseless, and without any technical or scientific credibility if that legislation were to go through. So I'm I'm happy to talk about the course of events, what cloud is, what it's not. Here with you today.
Speaker 1:Yeah. Let's kick it off with, the the high level on what actually happened in Texas, where things stand now, the status of the rescue operations, and kind of the the the timeline that's more broad.
Speaker 7:Yeah. Absolutely. So this phenomena, this flooding was global in scope. It was referred to as a low probability, high impact event. I encourage people to go to Matthew Cucucci, on x.
Speaker 7:He gave a great outline. He's a meteorologist that has a lot of expertise on severe weather forecasting. But but tropical storm Barry, the remnants of which blew into Texas, was going to cause inordinate flooding regardless. And that area of Texas is also known as Flash Flood Alley because these events do happen. Now 4,000,000,000,000 gallons of precipitation occurring over the course of just a couple days is pretty out of distribution, but we are seeing an increase in these sorts of severe climatic events over time and especially down and around The Gulf.
Speaker 7:So just to go over the timeline after having clarified that it was the remnants of tropical storm Barry and the conversions of large mesoscale phenomena that induced that flooding, It was at about 1AM on the fourth that the National Weather Service issued a flash flood warning. And then it was at about 4AM on the fourth where they said that there was a life threatening emergency underway. It was not it it it was over two days prior that Rainmaker had suspended all of its cloud seeding operations in Texas because, one, our forecasters and our meteorologists saw that there was going to be the severe weather event, and we needn't operate to produce more water, when there was already the event coming. But two, we suspended operations in accordance with the Texas Department of Licensing and Regulations, suspension criteria, where if there is a severe weather warning from the National Weather Service, or there is too much saturation of the soil, we have to ground operations. So we do so both voluntarily and in accordance with existing statutes.
Speaker 1:Okay. So the Cloud City operation that happened prior to the storm, who was the client? Like, I mean, who I assume someone was paying you. Sometimes it's the government. Sometimes it's a individual or farmer or business.
Speaker 1:Walk me through where they were, who they are, what their goal is by procuring your services.
Speaker 7:Sure. So it it's obvious that at this moment in time, that region of Texas does not need more water.
Speaker 6:Sure.
Speaker 7:However, throughout the Western United States, farms, conservationists, governments concerned with their aquifer supply of water and also reservoirs for both industrial and residential drinking water, contract with Rainmaker to produce more water via cloud seeding. And in the case of Texas, the South Texas Weather Modification Association, the West Texas Weather Modification Association, and multiple other, entities exist as conglomerations of both counties and individual farms that pay for cloud seeding services to, one, water their crops, two, fill up the reservoirs that they irrigate their crops with, and three, recharge the aquifers like the Ogallala that has been severely drawn down and then puts all of these farmers at risk of not being able to grow, not being able to do business because of a historic drought.
Speaker 1:Okay. So would the proposed ban just because what what I'm getting at is, like, I'm wondering if, like, if the government is paying for cloud seeding operations, like, the easier lever might just be to decrease the funding to the government. But it seems like Marjorie Taylor Greene is pushing for some other legislation that wouldn't just be, hey, buy less of this service because we don't need it. And instead, this service should never be bought at all. So why is there the distinction there?
Speaker 1:Like, is is is most of the money that's going into one of these associations private farmer capital, or is it a split? Like, how does that actually break down?
Speaker 7:So right now, it's largely public municipal money that is going into these weather modification programs to increase water supply when there is drought or in preparation for drought. Mhmm. The bill that has been forecasted that has been proposed by Marjorie Taylor Green, would wholesale ban all forms of weather modification, be it cloud seeding, solar radiation management, or what they supposed to be chemtrails? I mean, very transparently, I think that a lot of the concern around weather modification is actually conflating baseless notions of chemtrails with a very practical American technology that can and will and does benefit our farmers, our ecosystems, our industrial water needs, and our residential water needs. If this legislation were to go through, not only would it deprive all of those interests and all of those Americans from having water from cloud seeding, but it would also be against America's interest at a geopolitical level.
Speaker 7:Because China recently I think on the last time I was on TBPN, I talked about how they had a $300,000,000 annual budget for their weather modification program. That, as of 2025, has been up to $1,400,000,000. That is extremely consequential. And I think that if we were to ban who controls or or banning Americans from, controlling weather modification technology, that would put us at a meaningful disadvantage. Now all of this to say, people deserve transparency.
Speaker 7:They deserve clear regulatory framework so that they know whether modification operations are safe and being conducted in a responsible manner. And with government oversight and accountability, if ever there are, negative consequences to cloud seeding, Again, there haven't been any in the case of Texas. But I think that the reasonable next steps are to more stringently regulate who is allowed to cloud seed, define what the concepts of operation are that are permissible, define the suspension criteria at a federal level rather than leaving it purely to the states so that anybody that wants to know about weather modification can look at the data and scrutinize it and ensure that it's being conducted safely and also just to build trust. Because the weather modification act from 1972 that currently outlines, the weather modification reporting act of 1972 that outlines how we have to report to the federal government is, you know, 50 years old. We need more scrutiny on these programs for the sake of public trust and accountability, and that seems like a reasonable next step.
Speaker 7:That was also recommended by the government accountability office in their report on cloud seeding and weather modification earlier this year.
Speaker 1:Mhmm.
Speaker 2:What was the scale of the general water sorry, weather modification activities on July 2? It was you guys bunch was there a bunch of other players operating? Is there generally a lot of players or is it a pretty is it is it a fairly small number of of kind of service providers that are that are participating in these programs?
Speaker 7:Yeah. Jordy, you may have seen the prolific hustle bitch on
Speaker 2:I saw.x.com
Speaker 7:posting about this. A little while ago, he said that I was the CEO of the largest and most powerful weather modification company in the world.
Speaker 2:And I saw somebody compare somebody was comparing weather modification tech to being saying it was more dangerous than nuclear
Speaker 1:Nuclear bombs. That was kinda crazy. Yeah. And then I also saw some people just showing like general flight logs of like commercial airplanes. Like, there's a lot
Speaker 2:of chaos out People have every right to be angry and demand answers. It's such a tragic Yeah. Incident. But but, yeah, I'm I'm curious to get into the the scale of, you know, kind of maybe late June, early July Mhmm. What was going on broadly.
Speaker 7:Yeah. Absolutely. So there's one other cloud seeding operator in Texas called, Seating Operations and Atmospheric Research, SOAR. They're responsible for operations over the Rolling Plains, Weather Modification Association, which is significantly farther Northwest of Kirk County. On July 2, we conducted one nineteen minute cloud seeding flight where we released about 70 grams of silver iodide and 500 grams of salt, table salt.
Speaker 7:That was released at about 1,600 feet above ground level into two clouds that dissipated over the course of two hours after seeding them. The amount of time that those aerosols could have been suspended in the atmosphere is less than the time between when, we were seeding and the onset of rains from, the remnants of tropical storm Gary. And the amount of material that we dispersed could not come anywhere close to inducing the precipitation, the 4,000,000,000,000 gallons of precipitation that did come from that event.
Speaker 2:So yeah. And and I'm I'm assuming you guys, like, have records. You keep records of, like, the radar showing these different cloud formations. So you you're you're it's not just, hey. We looked and we think it dissipated, but it's like you can actually you have like, you know, basically a map that's live updating.
Speaker 2:Is is that the right way to think about it?
Speaker 7:Not only do we keep records for our own research purposes and operational purposes, but we're required to keep records by the Texas Department of Licensing and Regulation. And those are accessible online as are the reports on our seating activities. If anybody is interested in those, then you can ask for them from the TDLR.
Speaker 2:I I'm I'm curious. When when the the flooding happened in Dubai, I wanna say it was a year or two ago, Dubai is known for their cloud seeding operations. It's very dry place, and makes sense why they would want to, increase precipitation. A lot of people, maybe the same types of accounts that have been that have been blaming you were quick to blame it on cloud seeding. Throughout history, has there ever been any major kind of flooding event that that people were able to say, yes, a 100%, this was caused by weather modification activities.
Speaker 2:Mhmm. Or is the tech not even powerful enough yet to to do something like that?
Speaker 7:So I I think that there's probably three points to touch on. The first of which is that it wasn't until 2017 that attribution had been physical attribution of cloud seeding's effects had been seen and proven in an academic context. And so with new events in radar technology, namely dual polarization radar, we're able to much more clearly monitor what the effect from cloud seeding is. In previous operations, it was extraordinarily difficult to see what your effect was because we could not measure the cloud dynamics and the cloud microphysics that were changing as you were seeding. So that's the first point.
Speaker 7:The second point is that and, again, I'm trying to be and will continue to try to be maximally transparent about our operations and historic weather modification. There was something called the operation Popeye during the Vietnam War where the deliberate intention of cloud seeding was to cause precipitation that would, like, cause flooding and then impede supply chains on the Ho Chi Minh Trail. Mhmm. Now the extent to which that was effective because we didn't have good satellite imagery or dual port radar is outstanding. Now that said, lastly, third point, we have suspension criteria that are given to us not just by the TDLR in Texas, but every state wherein we operate.
Speaker 7:Because if there already is too much saturation of the soil or if there is, an oncoming severe weather event that the National Weather Service has, notified us not to seed, then we ought not do that to increase the severity of precipitation. So there there are suspension criteria because there are limits on what we ought to do with this technology, so as not to cause flooding and only reap the rewards from it, right, for our farms, for our ecosystems, and for our national security interest as well. Right? Like, if we don't have access to weather modification technology, if we don't regulate this at a at a federal level and ensure that there's accountability and attribution for these activities, then other people, other nation states could be conducting weather mod in the vicinity of or on American soil without any accountability. And so that's why I am advocating for way more regulatory scrutiny from the federal government for cloud seeding and weather mod ops.
Speaker 1:Walk through some of the history of the the Chinese weather modification strategies. We we heard about the the the flooding in Dubai that was kind of unclear. Have there been any notable or confirmed negative outcomes from China spending? I mean, you said $300,000,000 a year or something like that. That seems like a lot of cloud seeding.
Speaker 1:It seems like if there was a surface area where there could be mistakes made, they would have kind of explored that. I remember the the pre Olympics. They were doing cloud seeding or just kind of bringing down, like, the the dirt in the atmosphere. And, you know, people kind of learn from that. Okay.
Speaker 1:You get acid rain when you do that in in in particular. But have there been any case studies from China that we should be learning from in America?
Speaker 7:Case studies from China with adverse weather coming from their cloud seeding operations?
Speaker 1:Yeah. Anything like that. Like like something where like, okay. They they've done a lot of this.
Speaker 2:Yeah. They're doing this Pushed this
Speaker 1:to the limit. They've put they've done this at scale. If there's going to be rough edges or mishaps, I would've I I suspect that we would've seen evidence of that over there. They would've had an accidental flood or something like that happen over there if they're doing it at scale.
Speaker 7:You would expect to have seen it from China. However, you would also probably expect and understand that they're a relatively inscrutable country
Speaker 1:Yeah.
Speaker 7:That does not report on their activities very openly and objectively. Now that said, one thing that we do know about the weather mod program that they do have going is that they're planning to build a 100 and a 100,000 ground generators on the Tibetan Plateau.
Speaker 6:Mhmm.
Speaker 7:So Rainmaker is primarily using drones for operations. We also have inherited some ground generators from previous operations. These are essentially aerosolizing units on the tops of mountains. They can disperse material into clouds when the clouds intersect those mountaintops themselves.
Speaker 1:Is that like a cannon that fires the material into the cloud?
Speaker 7:Or No. No. You you you might recall my my initial inclination to use something like that because it is used in China. Yeah. But, no, it's it's essentially like a smokestack of sorts.
Speaker 2:It's a very
Speaker 7:small smokestack that releases those aerosols there. Sure. But in building a a 100,000 of these ground generators and also using the Wing Wong two and a bunch of their other military drones for aerial cloud seeding, they're turning Tibet into a a reservoir, a a snowpack reservoir of unprecedented scale that will feed more water into the agricultural basins in Southern And Eastern China. And I think that, you know, although, again, this is something that needs to be transparently reported on and regulated, depriving American farmers in the West, especially as a congressperson from Georgia, right, where there is not a severe reliance on cloud seeding to produce water would be against America's interest.
Speaker 1:Mhmm. Jordan? I guess And
Speaker 2:I'm I'm trying to I mean, the the the my my question is it feels like it it feels like candidly it will be hard to come it'll be hard to find any type of allies in Texas on the ground in Texas, maybe aside from from the farmers. But but I'm curious, you know, the the the various different groups, you know, what what what the reaction from them has been in terms of, you know, if they're, you know, it's the the reality is is water scarcity affects all every person in Texas, but only a few people truly feel it. Right? It's a much smaller group because everybody goes to their sink, turn on the water, they turn on a hose outside. They go to a grocery store, there's water, there's produce.
Speaker 2:It it's not something that people necessarily feel. And so I'm curious where, you know, you obviously are gonna defend weather modification because you you believe in in the many different ways it can have a positive impact. But I'm curious who you think the other players that will will be on your side as the industry. I mean, the industry was not in a good spot prior to this. It's in a much worse spot now.
Speaker 2:And I know you've been flying all over the country making sure that it doesn't get banned. So I'm curious what what you think the kind of coalition that will kind of form around you.
Speaker 7:Yeah. Yeah. Well, so I I actually think I'd just from my own experience over the course of last few days, disagree with the two points that you made. Right? Like, it it has neither been hard to find allies for cloud seeding weather modification in Texas nor do I think the technology and the industry is positioned worse now than it was prior to this weekend.
Speaker 7:And regarding the first point, there are some people that I think, are probably not in good faith engaging with this because they have some preconceived notions about chemtrails or otherwise, and don't themselves want to scrutinize the data to back up how our operations are different and beneficial, whereas chemtrails, as they believe them to be, are, you know, malevolent. Yeah. The vast majority of people that I've interacted with online, on the phone, and in person are rightfully curious, skeptical, concerned, some, you know, more than others, obviously. But in scrutinizing the data and having these conversations and learning about what cloud seeding is, pretty unilaterally, people are supportive of it provided that there is a regulatory framework more stringent than the one we have now that ensures that it's safe. This is true both of just individuals that are not themselves farmers, but obviously farmers, water managers, government officials too.
Speaker 7:I welcome any questions that people do have both online and via email about what our activities are, what our policy recommendations are. And and I'm I'm grateful that there are a lot of people that understand, one, our operations did not contribute to the flooding. But two, that even if there was a flood now, it doesn't mean that there is always enough water. And having access to a technology to produce more water for farms and otherwise would be beneficial. Like, people want a more green, lush country.
Speaker 2:Yeah. I'm curious. I'm sure you've spent plenty of time thinking about this. But is would there be a way to apply the existing technology you have almost in a defensive way And, you know, theoretically Exceed
Speaker 1:a hurricane while it's still offshore.
Speaker 2:Something like that or there or or, you know, one of the issues here, there was just so much water in the atmosphere that rolled over a heavily, you know, populated area. Yeah. And then it's got it's it's gravity. Right? It's gotta come down.
Speaker 2:Yeah. You know, is there an application of the technology that could over time strategically prevent, you know, or or act defensively against the conditions that create flash floods?
Speaker 7:It's it's a very worthwhile question for you to ask and for us to ask ourselves collectively. Right now, again, Rainmaker only does precipitation enhancement operations for all those constituencies that I listed before. However, in the past, the United States government funded project Storm Fury, which was a series of attempts to reduce the severity of hurricanes over the Atlantic before they broke against the Eastern Seaboard. Again, we didn't have the appropriate understanding of atmospheric science or the radar or the satellite data necessary to appropriately do that. However, severe weather is something that is, like, a geopolitical risk, a national security risk.
Speaker 7:It causes damage, and it is fundamentally a physics problem. Right? A physics and chemistry problem. Is there technology now that could mitigate severe weather like this? No.
Speaker 7:And Rainmaker doesn't have it. Is it possible to someday, provided we invest in NOAA, in the National Weather Service, in the appropriate research into cloud seeding such that we could reduce the severity of severe weather? Absolutely. And I am entirely in favor of that provided it is done in a responsible manner. And if we were to ban it wholesale, then not only would we lose access to precipitation enhancement, but we'd lose out on any potential of, at the very least, better forecasting for these systems and warning people early, but also the even greater and more consequential beneficial potential of reducing severe weather in the future.
Speaker 7:And so I think that the United States government and Rainmaker should and and are absolutely interested in mitigating severe weather in a manner similar to project storm fury.
Speaker 1:That makes sense. I I I think the PR what what you were getting at, Jordy, like, PR difficulty here is that, like, when there's not enough water, crop yields are lower, prices go up, but it's very distributed. Everyone feels it a little bit. Whereas when there's too much water and there's a flash flood and individuals die, you have it's a very emotional, very it it's very concentrated. The pain is very concentrated.
Speaker 1:And so that's why this this story Yeah. Mean, normally
Speaker 2:when normally when there's a natural disaster
Speaker 1:Yeah.
Speaker 2:There's you can you can critique the government for their response Sure. To it. But there's not somebody sitting there Scapegoat. A scapegoat.
Speaker 1:Yeah. Right? And so I guess the question
Speaker 2:is like It's easy. Yeah. It's it's, know, whether it's online accounts that are just engagement farming Yep. Or it's a politician
Speaker 1:Yep.
Speaker 2:You know, the the the concern is that and your concern is that the industry becomes a scapegoat and America loses a capability that our adversaries clearly care a lot about.
Speaker 1:Yeah. My my question is like, we're we're seeing this bifurcation. It seems like Ted Cruz came out in support of the idea that cloud city had nothing to do with the Texas floods. Marjorie Taylor Greene is taking kind of the other side of that. My question is like these are politicians at the end of the day.
Speaker 1:They're not independent scientists. Who can we go to? Who can the population go to for, like, a truly independent review of this situation? Like, is there is there some sort of independent governing body, or are there are there respected scientists that kind of don't have a financial or, you know, political incentive one way or another? How do you think the the populace should be obviously, you're telling your side of the story.
Speaker 1:You're going direct. You're explaining things. You're laying out the data. But what what what do you expect people to look for in an independent analyst?
Speaker 7:Yeah. Yeah. So for one, I think that NOAA, the National Weather Service, the National Center for Atmospheric Research, all of those are great third party entities
Speaker 2:Yeah.
Speaker 7:That can review the information, corroborate the information that we've provided, provided, of course, that they continue to exist and remain funded.
Speaker 4:Sure.
Speaker 7:I think that this probably demonstrates why it is important that we should retain some capability nationally to forecast and research the atmosphere.
Speaker 4:Mhmm. Because
Speaker 7:there's there should be somebody that's capable of reviewing this to ensure that it's safe. Mhmm. I'll also say, you know, regarding the scapegoat dynamics that that exist right now, I've thought about this pretty prayerfully and intently over the last few days. And when there is a calamity of some sort like, I've been trying to think about why people are, say, coming after Rainmaker or angry at Rainmaker. And I I think that when there is a calamity of this type, if there was someone responsible, if there was someone or something that could be held to account, then in holding them to account, you could supposedly prevent this kind of thing from happening in the future.
Speaker 7:The trouble with the true natural disaster as this was is that there is nobody to be held accountable. And that makes the world a lot more tragic because it means that things like this will persist. These they will persist indefinitely into the future, unless and until some sort of technology could reduce the severity of severe weather. Yeah. And that We went
Speaker 1:through this with the California fires. You know? It was like everyone was searching for, like, a single person to pin it on. And, like, it came down to, like, you know, some people built their houses the wrong way, and there's some building codes that need to change, and there's some water rights and water flow, and there's some different
Speaker 2:General government
Speaker 1:Like, we need more goats in certain areas. There's, a million different things that could have prevented this if they all were all working together as a well oiled machine and had the forethought, but it's a very, very frustrating and difficult situation. So our our thoughts and prayers are with everyone who's been affected. But thank you so much for stopping by. This is fantastic.
Speaker 1:Thanks for, breaking it all down for us.
Speaker 7:Thanks, guys.
Speaker 6:Appreciate it.
Speaker 1:Talk to you soon. Cheers. Really quickly before our next guest joins, let me tell you about Linear. Linear is a purpose built tool for planning and building products, made the system for modern software development, streamline issues, projects, and product road maps. Let me also tell you about Numeral.
Speaker 1:Sales tax on autopilot spend less than five minutes per month on sales tax compliance. Go to numeralhq.com. I use it personally. And we have our next guests. We're doing two guests simultaneously.
Speaker 1:I hope production team was made aware of this. It's on the calendar. But we are working to get a a four up display for you. We have the founders of Grammarly and Superhuman. This was an acquisition that was that was announced last week.
Speaker 1:And lots of people in tech have probably used Superhuman. It's the email client of choice for the tech elite, of course. And Grammarly has been an indispensable tool at TVPN. We installed it on our producer Ben's computer very early on when we were posting clips to make sure that we didn't have any spelling or grammar errors when we would post on social media. Very useful tool.
Speaker 1:And now they've combined forces and we're going to talk about how we can what the shape of the business will be going forward, how these products play together, what the modern suite of tools looks like going forward. Well, welcome to the stream. How are you?
Speaker 4:Great. How are you?
Speaker 1:Fantastic. Would you both mind kicking us off with an introduction on yourself and the companies that you run, and then we'll talk about the the the acquisition.
Speaker 4:Great. Sure. Rahul, you're go first?
Speaker 5:Okay. Yeah. Happy to. Hello, everyone. I'm Rahul Vora.
Speaker 5:I'm the founder and CEO of Superhuman, which if you're not familiar with, is the most productive email app ever made. Imagine getting through your email twice as fast as before, responding faster to the things that matter, and saving four hours or more every single week. We're also inventing the future of productivity with AI. Imagine waking up to an inbox where every email already has a draft reply. You would simply edit and then send.
Speaker 5:And, of course, with Grammarly, we are going to build the AI native productivity suite of the future.
Speaker 2:Great. Amazing.
Speaker 4:Yeah. And I'm Shashir Motra. I actually started a different company. I started a company called Coda about the same time as Rahul started Superhuman. And about seven months ago or so, Grammarly acquired Coda, and I stepped into the CEO role running Grammarly.
Speaker 4:So been working in and around the industry for a long time before Coda. I used to run the YouTube group at Google, worked at Microsoft in the early days, actually started my very first job was working on Outlook. So I've I've got like, in 1998, I worked on email.
Speaker 2:Thing or two about email.
Speaker 1:It's fun
Speaker 4:to come back to it.
Speaker 1:Yeah. That's amazing. So I I'm not sure who who's best to answer this, but I'd love to know about how this deal came together when you two first met. And, you know, we we we keep going back to this post that, like, you'll meet your acquirer, like, five years before you before the deal goes through. Is that this case?
Speaker 1:Is this a narrative violation? Kind of how did you get to know each other? Eight years. Eight years. So can't break
Speaker 4:it down. Why don't why don't I take the first half, and then Rahul can take the the Please. Second half. So I can talk a little bit about the deal and what we're doing, and Rahul can give the fun origin story. So maybe just as a as a little background for everyone.
Speaker 4:So Grammarly at Grammarly, we're our goal is to build an AI native productivity suite with the agents and applications that drive productivity for every individual and team in the world. So a lot of that is probably new to people because people have generally thought about Grammarly as a much narrower product than our aspirations for it. And, you know, the way we generally talk about it, and I'll talk about agents first when we talk about applications, but we generally think about Grammarly as the OG agent. It's about sixteen years now that the company has been helping, at this point, about 40,000,000 daily active users, where Grammarly is the communication assistant that lives right next to you in every surface you work in.
Speaker 1:Mhmm.
Speaker 4:But people misunderstand the technology because they think it's about grammar. But, actually, the technology of Grammarly is mostly about bringing AI right to where users work. So we can work in about 500,000 different applications where we read what's on your screen. We can annotate it in an unobtrusive way, and we can can make changes on your behalf. And so from that perspective, we we call this layer, we call it the AI superhighway, bringing AI right to where people work.
Speaker 4:And in that analogy, up till now, we've only been running one car on that highway. That's the car with your high school grammar teacher in it. And so that's a very useful car, and it generates, you know, over 800 7,800,000,000 of revenue now. I think it's a a vast subset of what you should be able to do with that. So a big part of our strategy is opening up Grammarly to become a platform so you can build any sort of agent on it and have those agents come to you where you work.
Speaker 4:That's the first part of our strategy. Second part of our strategy is taking those surfaces and building the first party versions of the surfaces that we think really matter. The surfaces where people work every minute of every day, where all the work really gets done, where you really wanna work not not only alongside humans, but alongside agents as well. So that's why we bought my prior company, Coda, that we make an all in one document solution that runs documents, spreadsheets, presentations, and applications into one surface. That produces all the work artifacts for you.
Speaker 4:Mhmm. But another key part of work is communication. And for many people, the dominant communication tool they use is email. It's something like three to four hours a day the average person spends in their email inboxes. And this actually shows up in the Grammarly stats really high.
Speaker 4:So email turns out to be the number one use case of Grammarly. We revised something like 50,000,000 emails per week. It's three of the top 10 applications that Grammarly is used in are our email clients. Yep. And so we saw that as an obvious place to go to go work next.
Speaker 4:Now from my perspective, I think email is a category that is particularly ripe for disruption. As I mentioned, I started my career working on Outlook in 1998. And since then, there's a round of innovation with Outlook. There's a round of innovation with Gmail, and then there was a decade of not much. And then Rahul
Speaker 2:That's superhuman.
Speaker 4:Came along and built a great email experience. So when we went looking for which surfaces really matter, we landed on email. And when you look at the email category, as you mentioned, there's only really one player that's meaningfully innovated in that space, and that's when we call Ruffle. That's a little bit about how the deal came together.
Speaker 2:Amazing.
Speaker 5:Great. Rahul? Yes. It's
Speaker 2:funny. I've I just just for some added context, I basically have been lucky that my entire I I think I got on Superhuman in 2018. You launched in was it when did the beta launch? It was twenty seven teen?
Speaker 5:I think our first paying customers were at the very end of 2017. So
Speaker 1:you Yeah.
Speaker 2:Exactly. But I graduated college in 2018. So as a professional, I've only had I'm a lucky I'm the lucky batch. Right? Yeah.
Speaker 2:And still use it today. So so thank you for, you know, make I I never had to be an an Outlook guy.
Speaker 1:I had a yahoo.com email address when I was a kid.
Speaker 6:Yeah. Vintage.
Speaker 2:Vintage. Anyways, Rahul, I don't know if you have anything to add but then I have a bunch of kind of follow-up questions on on the last anecdote.
Speaker 5:Yeah. For sure. I think it'd be fun to tell the the origin story of the deal, how it came together. And I think there's a lesson or two in here for for other founders of the entrepreneurs listening. So I'll I'll also try and make it useful.
Speaker 5:So to your point, the foundations that the seed for this deal was planted many, many years ago. It was eight years ago. Like Kishir said, it was back in 2017, and back then, he was the cofounder and CEO of a company called Coda. And we were actually at a conference together in Hawaii, so it was really nice. And that said, I didn't really want to go.
Speaker 5:You know, this was a four or five day thing accounting for travel there and travel back. And one of my cofounders, Vivek Soderra, was really encouraging me to go. You know, he he would say things like, listen. Building a startup is just as much about who you know and the connections that you have and being able to pull opportunities together as it is building and marketing a great product. And I'd be like, well, I, you know, I wanna work on this feature.
Speaker 5:I wanna do this thing. But in the end, he just pushed me out of the office and put me on a plane and
Speaker 2:Go to Hawaii.
Speaker 5:Go to Hawaii, which sounds weird. Right? Like, resisting going to Hawaii. But anyway, there I was. Shashi was there as well.
Speaker 5:And it was one of those special moments where nobody else was around. So it was just the two of us via pool, two productivity nerds, netting out about productivity. And he told me that he'd worked on Outlook back in the day. We got into some really deep conversation
Speaker 1:about productivity.
Speaker 5:And as you know, back then, we only did one on one VIP onboarding. You must have gone through one yourself Yep. If you onboarded in 2017. So I onboarded him right there and then, right by the pool. And those who've gone through the onboarding know, one of the very last steps is when we ask you to close Gmail.
Speaker 5:And so I was asking him to move the mouse over to the Gmail tab and close it. And when I asked him to do that, another tab caught my eye, which was an app called Krypton. So I asked him, what is that thing? And then then proceeded to give me the best product demo I'd seen in years. My jaw hit the floor.
Speaker 5:It was a document, but it was also a spreadsheet. It was also a database. It was a collaboration tool. It was a mini app builder. And and maybe today, we take these things for granted, but back then in 2017, this was truly mind blowing.
Speaker 5:And so Krypton then renamed to become Coda, and Coda, of course, late last year joined Grammarly. Now in his acquisition announcement, he wrote, and I have the quote here, as I watched the foundational capabilities of AI change how just about how every tool and surface operates, I started drafting my 2025 memo for the team. I titled it the AI native productivity suite. And this just set a whole bunch of bells off in my brain in a good way because at Superhuman, our vision has always been to build the AI native productivity suite of choice, and email is obviously a critical part of that. It's a much bigger problem than most people realize.
Speaker 5:There's roughly a billion professionals in the world, and on average, we spend 3 to 4 hours a day in email. So that's three billion hours every single day or north of a trillion hours every single year. We actually all spend more time in emails still than any other work app. So we caught up early this year, January. Actually, a few days after he became the CEO of Grammarly.
Speaker 5:And over the course of several conversations, it became very clear that we were working towards the same vision, which is to build this AI native suite for apps and agents. And and then as Shashir said, email sits at the heart of where Grammarly is used today. It's the number one use case, helps write more than 50,000,000 emails. Another stat that I found very fascinating is that 17% of words accepted on Grammarly are actually accepted in an email service.
Speaker 2:Wow. Okay.
Speaker 1:Drew, I'll answer it. You have
Speaker 2:a couple of questions. Of questions, and I'm sure I'm I'm excited to get your answers. So first is integration. How do you see sort of the the the plot, you know, how do you see both the brands and the products integrating and working together over Because you have a great challenge of having three great products that people love and three brands. And in order to deliver on this this, you know, this true, you know, long term vision of a of a productivity suite, I imagine over time you wanna integrate them deeply.
Speaker 2:I'm curious what that looks like.
Speaker 4:Yeah. Maybe, yeah, Ravi, you wanna cover the product part and I can talk about the brand part?
Speaker 5:Sure. Yeah. I'll I'll do products really briefly, and then we can go as deep as you like. You know, I think one of the most exciting things about the deal from a superhuman perspective is the access to significantly greater resources. So you can expect us that we'll invest more than ever than we have done in AI.
Speaker 5:We're also absolutely not done with our core email experience. We'll be doing a lot more there. We're gonna build out calendar and tasks and then connect those beautifully together. We'll also start to spread our wings beyond just email. So we're gonna reimagine chat.
Speaker 5:We're going to redefine collaboration, pulling on everything that we've learned over the last ten years about work communication. And then as Shishan mentioned, we are also working on a whole new way of working with AI agents, agents that we think will free all of us up to be more creative, strategic, and closer to achieving what we call our human potential. And then just to double click on that a little bit more, we really think we're entering the age of agentic computing, where AI agents, they're gonna work on your behalf. They're going to reason. They're problem solving, and they're incorporating detailed context about your work.
Speaker 5:They're actually also interacting with other systems and agents, and I think we're we're getting to see these in some of the products that people are using today. And for so many people, email is just at the center of where we work. You think about project statuses, customer communication, meeting updates, deal execution, so much more. It all actually funnels through email, whether it's a system of record or that's actually where the work is taking place. So we also think that email is the perfect place to deploy a collection and a suite of agents.
Speaker 5:You can imagine an agent triaging your inbox before you wake up. You could imagine another agent drafting responses in your own voice and tone, incorporating context about you and from your work, and at the same time, another agent is surfacing insights, scheduling meetings. They're syncing with your other systems of records and your other agents. And I'll give you a specific and concrete example. Cool.
Speaker 5:This is something you can actually do in superhuman today, and then I'll talk about how it's going to evolve in the very near future. And let's talk about search or or asking your email things. For over forty years, we've had to rely on what we kind of hilariously call search. But if you think about what that is, you have to remember senders. You have to guess keywords.
Speaker 5:You don't have to scan subject lines. And now in Superhuman, you can simply ask, where is the q three off-site, or what are my flight details? And a very real example that blows people away whenever they see it is this thing I do whenever we launch a feature. Whenever we launch a feature, and you'll know this using Superhuman, I send an email to every single person who uses the product. And then we get a whole bunch of replies back, usually several thousand responses, and I still personally read through every single one.
Speaker 5:I reply to some of them. But what I'm doing is I'm copying and pasting my favorite quotes into a Google Slide that I can then present at the next company all hands. Now this takes half an hour to do properly. With Superhuman today, you can just ask, what are the top 10 most positive customer responses to the, calendar CEO week launch, let's say. And then boom boom boom boom boom, immediately within five, ten seconds, I have the answer.
Speaker 5:So that's taking what is a half an hour task and making it work in five or ten seconds. Now we're evolving that so that you can then continue the conversation and take it much beyond email. You can imagine me then saying, okay. I want to convey the magnitude of the commercial opportunities to to the team. So can you annotate each quote with the name of the person, the company they work for, the size of their current superhuman account, and the total number of employees they have, and then compute an estimated size of price.
Speaker 5:Like, how much revenue is there at stake if we were able to sell into that company? And you can then imagine the superhuman set of agents figuring out what to do with that, realizing the answer actually isn't in your email. It's probably in your CRM. So a sales intelligence assistant is called into the mix. There's a handoff between the agents, and then the answer is right where I kicked off the conversation in my email app where I happen to spend three hours a day.
Speaker 5:And you can continue the conversation. You can then say, okay. Let's please turn this into a presentation. And then perhaps it works with, let's say, the Gamma agent to produce an amazing, beautiful presentation in your own brand for the company. And then you might say, okay.
Speaker 5:I want time to practice this before the all hands. Can you please schedule time in my calendar to do so? The agent's like, well, you're completely booked up before the all hands, but we can move some things around. And it's smart enough to know that it's easier to move a one on one than it is to move a team meeting. So it it recommends moving the one on one.
Speaker 5:It goes and does that. And now you have time blocked in your calendar to learn a presentation that was created for you in ten seconds by this agent that just read thousands of email to get the content. Work that literally would have taken an hour done in, let's say, one or two minutes. So that's the kind of future we're working towards.
Speaker 2:Wild. There's gonna be 250 agent AI agent startups that that are gonna hear that and be like, damn. He's He's doing They're doing they're doing what I'm
Speaker 1:what I'm trying to do.
Speaker 5:This is an ecosystem where
Speaker 2:we wanna Yeah. No. No. And that's
Speaker 4:To be clear, we want our marketplace to be the place you you deploy those those agents. Right? Or at least the the surfaces you wanna work on. If if you like, I could talk a little bit about the brand question as well.
Speaker 1:I'd love to hear.
Speaker 4:Yeah. So and and, you know, I I think my experience here is heavily formed by before starting Coda, ran the YouTube group at Google, and I think that was one of the best examples of an acquisition that I think flourish in a way that would not have been possible without without the particular construct we put in place there. And there's a lot about that I think that we got right, and I think we're I'm gonna mimic a lot of that here as well. So and my goal is with Grammarly, we're gonna build the the AI native productivity suite of all the apps and agents that you that you need, some of them that will own, some of them that we will be great partners with. But it's really important that each of those retain an identity.
Speaker 4:So to and I think that's important because that's how they keep innovating. I mean, if you think about you know, you started using Superhuman in 2018. You know, you're buying into a product, but you're also buying into a team and a vision and a feel, and all those things really matter. And so I've I really like this term of building a camp a compound startup where each of those products still feel like they have an identity, they have a brand, they have a mission. They have their their they have similarities for things we wanna work across, but they have their own perspectives on on the problems that make sense in that in that space as well.
Speaker 4:So we want agents to work across all surfaces. It's very important that if I set up my sales agent, that it should be able to do some of the experiences that Rahul just described while it's in my email. But while it's in my document, it'll give me a different set of experiences. When I take it out and and use it while I'm using a third party application, it should still be able to bring my contacts with me. So there will be things that need to feel similar, but the individual brands will remain separate.
Speaker 4:The last thing I'll say about that is the overall corporate brand for Grammarly will change. We're working on
Speaker 8:a new name for it.
Speaker 4:So Grammarly will become one of the sub brands itself. We think about it as as I was describing, one of the most important agents in that in that platform. So the new brand's coming. I'm really excited about it, but not announcing it yet.
Speaker 2:Yeah. Dude. Yeah. I can't wait to see it. I'm curious how you think about the the tension between yourselves and someone like a Google a Google Workspace.
Speaker 2:I was joking with John the other day. It feels like so many companies are so dependent on Google Workspace for the core kind of, just like team management infrastructure that they could just raise the prices every single month and it would take a really long time for even to try to figure out something else. And it reminded me of of kind of the tension that some of the foundation model labs have today with the app layer above them. Although that's, quite a bit more intense. But I'm I'm curious, you know, how deep down the stack you guys would go, if you can talk about it, or or if it makes more sense to focus on the agent layer or the app layer.
Speaker 4:You know, I maybe I can start the it's interesting. The three products we're bringing together, Grammarly, Coda, and Superhuman, all have competed with the Google Suite or the Microsoft Suite for years. Yep. And so I think we're all kind in the fire. Yeah.
Speaker 4:Yeah. And and the the thing I'd say about it is it actually comes up less with customers than you would think. Yeah. The I think that when companies decide it's sort of it's sort of like buying plumbing for your company. You you buy one of these suites.
Speaker 4:It covers lots and lots of different things, but it these have become a part of the furniture at the at the at the company. And people don't really think about them as their real investments in productivity.
Speaker 2:And so I I totally agree, by the way. I'm just as this as the way work evolves, imagining trying, you know, setting up every every time you have a I could imagine a world where there's You're you're generating a new agent for a specific task and they have an email. And I'm sitting here being like, do I really wanna pay, you know, Google Workspace every time I spin up a new agent at Google Workspace another $25 a month? And so I imagine I imagine you guys can take this in a direction that that kind of reinvents that all of that plumbing in the in the long run, but maybe it's
Speaker 4:not Yeah. I mean, I I would say all three products have found different ways to be better together with the with the underlying products. Obviously, with Grammarly, one of its hallmark features is that it actually works in all those surfaces. So it amplifies your investment and, you know, works great in Google Docs, but it also works great in Slack and in Salesforce and all the rest of your products as well. For Coda, deeply integrates with those products.
Speaker 4:And then and then for Superhuman, you know, Gmail or Outlook serves as a back end for those for those providers. So it's it's not really a question of of less investment in in those core infrastructures. But if your users want the best possible experience for what they're doing, you're gonna go get the best tools. And in a sort of macro scale, the amount of money you're spending is such a tiny amount of money compared to what what you're actually investing in your employees to go stick another $10.20, $30 a month for people that you're spending hundreds of thousands of dollars on to get them
Speaker 2:In some cases hundreds of millions.
Speaker 4:In some cases hundreds of millions, we're gonna have to raise our prices for those employees. But you know, you're gonna get a huge return for them. And people don't really care that much about their sunk cost and their plumbing.
Speaker 1:Totally. Question. Go for I I I I two somewhat related questions. One is, I I I don't wanna say that, you know, Grammarly is a Chrome plugin, but a lot of people experience that way. And, and I noticed I was using a different Chrome plugin and Chrome the Chrome App Store, like, updated, and I lost functionality because they changed their policy and this particular plugin wouldn't work in the new rules.
Speaker 1:And so I'm wondering if there's
Speaker 2:plug in different
Speaker 1:This is not Grammar. This is separate one. Was called uBlock Origin. It would let me go in and select specific divs on specific websites and basically mute them every single time I hit that website. It was very, very cool, but it was deemed to be, like, too not, like, not privacy safe.
Speaker 1:And it was really annoying for me because I I enjoyed this, and I was excited to use this thing, and then I lost it. And, I mean, I might be able to, like, download it and sideload it or something, but it was it was it was difficult. And so I'm wondering about, like, sharp elbows in the because the Chrome plugin is an interesting wedge, a interesting go to market. It unlocks so many different things. We've seen this with, like, the OpenAI ChatGPT app, using the ADA or the the the the accessibility features to kinda plug into any IDE on day one.
Speaker 1:Like, you just have such an interesting ability to plug into, you know, tons of apps with AI in a bunch of interesting ways on and and, like, you're native there, but it feels like Google might be getting a little bit more sharp elbows there. Has there been any tension there? Do you think that there will be more over the long term? What are the risks to building on top like, building a platform on top of another platform?
Speaker 4:Yeah. I mean, I'll maybe just to to two two parts to answer. First off, just to correct one misunderstanding. Sure. The Chrome plugin is a very big part of the Grammarly Yeah.
Speaker 4:Product. There's also a desktop application. There's also a set of mobile applications, so iOS and Android. And we have millions of users on each of those as well. Yeah.
Speaker 4:And so but I understand that the the product is is synonymous in many people's heads with the with the Chrome extension first. But that's very important because we have to work where users work. And sometimes you work in a web browser. Sometimes you you know, many people use Slack as a desktop app, use Superhuman as a desktop app, and so on. So you have to be able to work in those places.
Speaker 4:Yep. I will say that staying on that line of where these platforms are is kinda become the core asset of the company. So that's what I it's kinda what I meant by people misunderstand Grammarly. Like, they I do have a team here that works on being a great grammar agent.
Speaker 6:Mhmm.
Speaker 4:But a massive team that works on how do we integrate with all these products in a safe and secure way. And one of the things we've realized is that we've done this just for the grammar agent. But what if we could amortize that across a much broader set of agents? And so now if you're if you're someone building a new agent, you could go build a Chrome extension, a desktop app, and so on. Let's I mean, I'll pick I'll pick an example.
Speaker 4:Let's say I'll pick a book author. So, you know, I I I really like Kim Scott. She wrote a book called Radical Candor. We spent a bunch of time with Kim on right now, she sells a book. You stick it on your shelf, kinda forget about it.
Speaker 4:She wants to build an agent that sits right next to you and says, hey. You're not following the principles of the right
Speaker 1:now. Oh, interesting. And
Speaker 2:So so I'll I'll say it because Yeah. I'm thinking it. But it it seems like, you know, I'm gonna say this, and then I'll some more context. But a lot of people, you know, have been very triggered by the marketing that Cluely has done. But at the same time, what what they had surfaced and what you guys had basically started doing years and years ago was was understanding what a user is doing on their screen and starting to surface information and help them take action.
Speaker 1:And Grammarly like the original copilot.
Speaker 2:And I think that what you guys are building towards and specifically this app layer on top of this like private secure way of servicing context will in hindsight be incredibly obvious that that was how we should be integrating AI in our work day. Yeah. Because the idea of like you're working in an app and then you go in another app and you like type a little bit and then you take that and maybe you go back into the other app and then you're just like, you know Yep. Tossing this over the wall makes no sense when things should just be getting constantly surfaced.
Speaker 1:There's people programming precursor. Yeah. There's programming There's programming code, copy the Python into chat gpt, copy the result back, and it was like, okay. There has to a better way.
Speaker 2:Yeah. And and I don't wanna I I want a I I as a user, I would love to be able to have a bunch of different experiences like that, but I don't wanna trust I don't wanna I don't want a 100 different companies to have full to my desktop screen and my microphone or or any of these other things. So I I'm very excited about where where you guys are going.
Speaker 4:That's exactly right. So, yeah, it is a 10 it's tense to build a platform on top of your browser, your desktop, so on. But once we've once we've done that, we can now make it available to the Cluelies of the world, to the Kim Scott's of the world, so on Sure. And say, why are you gonna figure out how to integrate with every one of those applications, and we can do that for you. You should focus on the logic of what do you wanna suggest to the person and when.
Speaker 1:Yeah. Totally. I mean,
Speaker 2:a couple couple more questions wanted to fire off. You guys are well capitalized. You generate a lot of revenue. I'm curious how you're thinking about operating the business on a go forward basis. I'm assuming you're getting a lot of, hopefully getting a lot of efficiency out of AI.
Speaker 2:So maybe you can, is the plan to, focus on innovating while, you know, generating cash flow or are you guys gonna, you know, continue to, you know, or or or just burn and and, you know, run a a more traditional value playbook?
Speaker 4:Grammarly has has been lucky to be a a cash generating business for a long time. So it's sort of built into the DNA of the company. Congratulations. So I think in the I I'd like people to start thinking about Grammarly or with the new brand that we'll announce soon enough. Think of us as one of those top few AI companies.
Speaker 4:And, you know, if you think of the foundation model companies providing great layers for all of us, I I think we're hopefully the suite of applications and agents you really care about with one big business model difference. We don't burn billions of dollars in order to do it. And I think we can hopefully bring that to people in an efficient way, which allows us to to grow and expand, in our own control.
Speaker 2:Yeah. Last question. Are you guys, in are you guys talking to more companies? If somebody has if somebody has a great product that's generating a lot of revenue, Are are you Yeah.
Speaker 1:I'm looking through the Google Suite right now and you know, see I see video targets.
Speaker 2:Are you guys a buyer? See free. We are.
Speaker 4:I mean, I I think I think we should I would love to talk to people with interesting ideas there. I think I think there's a great opportunity here to go build that next AI native productivity suite. We will build parts of it. We will buy parts of it. If I look at email, for example, you know, we could have if we started to build an email experience anything like superhuman, nobody would have seen anything for for a decade.
Speaker 4:And so it was very important for us to get a jump start with the number one product on the market. There are other cases where I think we can build. I don't think we have to buy everything. But I I I think we're a a great home for startups that are lacking that sort of scale Mhmm. That want that distribution, wanna get to a much broader group, but still wanna work in an innovative environment.
Speaker 4:So, yeah, I hope we're a great spot for that.
Speaker 1:Yeah. Awesome. Well, that's exciting. Congratulations,
Speaker 2:And come back on
Speaker 1:When the rebrand drops. The rebrand. I wanna see that. Are showing. About
Speaker 2:it. Can't wait. Congratulations. Guys are gonna cook up something great there.
Speaker 1:This is fantastic. Cheers. Well, we will talk to you soon. Have a
Speaker 2:great day. Chatting.
Speaker 5:Guys. Goodbye.
Speaker 1:Let me tell you about Adio customer relationship magic. Adio is the AI native CRM that builds scales and grows your company to the next level. You can get started for free or you can talk to sales. That might be the cure for male loneliness.
Speaker 2:Or I'll make an intro.
Speaker 1:Yeah. Just have Jordy. He'll introduce you.
Speaker 2:I'll introduce you. Right to the top.
Speaker 1:Let me also tell you about fin dot ai. The number one AI agent for customer service. Number one in performance. Number one in competitive bake offs. Number one ranking on
Speaker 2:G two.
Speaker 1:G two.
Speaker 7:And you know I
Speaker 2:love bake offs. Do not get in a bake
Speaker 1:off with fin dot
Speaker 2:ai. Don't do it. Just don't don't even start.
Speaker 1:It's gonna be a
Speaker 2:nightmare for you.
Speaker 1:Yeah. It's gonna be bad.
Speaker 2:It's gonna be really bad.
Speaker 1:No one likes how that ends. Yeah. Anyway, our next guest is ready to join. Let's bring in Ankur from
Speaker 2:carry.com. Like We love Carrie. Welcome
Speaker 1:to I think we're I think we might be on mute. But we're gonna want you loud and clear for this one because there's a lot of exciting news.
Speaker 2:There he is.
Speaker 1:Meet
Speaker 2:you. What's going on?
Speaker 3:Up, man? How are you? Good to be here.
Speaker 2:We're doing great. I'm excited to chat. Yeah. I'm sure you've been It's
Speaker 3:boring boring tax stuff but I need people to chat
Speaker 2:about it.
Speaker 3:I'm here for it.
Speaker 2:No. You make it digestible. Yeah.
Speaker 1:So the goal I was talking to
Speaker 2:It's like the last threads that I see on acts that I'm like, thank you. Yeah. Thank you for making this thread because it's actually it's actually deeply researched thoughtfully organized and valuable and it's not like Yeah. Have you ever heard of Mark Andreessen?
Speaker 1:So yeah. The goal here is to create something evergreen the definitive playbook for founders. So I I I think we wanna create something that can be a resource for a long time ideally.
Speaker 2:Yeah. Great.
Speaker 1:Let's break it down.
Speaker 2:Let's do it.
Speaker 3:Alright. Where where do we wanna start?
Speaker 2:Yeah. I I I figured it would be helpful to kind of walk through our our audiences pretty evenly split between early stage founders, operators and, you know, executives and then Or just start up, you know, team members in general and investors. And so getting kind of a a lay of the land on how the big beautiful bill impacts all those different groups would would be awesome. But maybe first, I would love, you know, some background on yourself, how you got into this, Carrie, and then we can get into all that.
Speaker 3:Yep. Sounds good. Well, Jordy Jordy is an investor, so it has a little little little
Speaker 2:bit for me.
Speaker 3:Not for you.
Speaker 2:For everyone else.
Speaker 3:Yeah. But I've been running a company called Carrie for almost three years now. I'm an immigrant to America. I moved here knowing zero about personal finance, zero about taxes. I sold my company five years ago, and I was facing a giant tax bill.
Speaker 3:So I hired very expensive lawyers and accountants, and they were able to do black magic to basically reduce my tax bill dramatically. And it made me realize, like, the tax code in this country, it's kind of there's so much stuff in there, but very few people actually know how to leverage it. So when it was time to start a new company, I spent, I don't know, couple of months looking into this and made it my mission to, you know, dive deep into everything in here. And what we do at Carrie is we're like, can we build software to give people we call it tax alpha, but, basically, ways of saving money on taxes on autopilot. So Yep.
Speaker 3:Again, my compliance team is gonna make sure I say this. This is not tax advice, legal advice, or investor advice.
Speaker 2:But We never give that kind of advice on this show.
Speaker 3:Yeah. Yeah. But I have spent a lot of time in the last two, three years working with, at this point, thousands of business owners. And I think I have a pretty good idea of, you know, generally how business owners can save money in taxes, and this piece of legislation is the most significant one we've had since 2017. 2017, there's
Speaker 2:a of before before we dive into that, I think it's helpful. I feel like you approached the the tax code, like, very much like an engineer. And in the same way that, you know, if you sign up for a software product, you're getting the benefit of that company spending millions and millions of dollars like building this product and then giving it to you at a fraction of what it cost to create. You're with Carrie, the the idea has been how do you kind of create that same effect in some way for taxes because if you're working with a fan, you know, one of the best CPAs in the world, they will charge you for the service and then they'll go charge you the same price to someone else for that same service and they'll just do that a bunch of times. And you guys created a different, you know, you you have a sort of a different incentive which is how do you create the maximum amount of value and then make it available to as many people as possible which is kind of the traditional software playbook applied to applied to to a new category.
Speaker 3:Thank you. You pitched my company better than I did. But, yeah, I mean, there's all this stuff. I mean, there's so much nuance in it, but, like, from a software perspective, none of it is specifically hard. So the challenge we have is we deal with fintech.
Speaker 3:Right? We're dealing with real money, custodying real assets. That's the complexity. But there's so much stuff in the tax code that we're look if we're focusing on, I don't know, 1% of what's out there, but there's like, I generally believe for most people I know VCs probably disagree with this. There's no alpha in investing.
Speaker 3:The average person should just index the market and get to work, but you can find alpha by saving money on taxes. If you can save 20% off the top so you have more dollars to index the market, That's basically the thesis behind what we're building.
Speaker 2:Yep. So talk about talk about kind of maybe how the bill came together, what what you expected to be in, what what maybe didn't make it in. There was a lot of chatter maybe was it four months ago around the carried interest loophole? People were pretty triggered by that. I was triggered by that.
Speaker 2:But, it sounds like that didn't make it in. But, yeah, break down kind of maybe the lead up to the bill and then how it actually ended up getting implemented in a 10 states.
Speaker 3:I should also caveat, by the way, that, like, I'm gonna tell y'all what's in the bill. It is not an endorsement of the politics behind it. Like, you can argue either side of that. Let like, that is out of scope for what we're
Speaker 2:talking about. Talking about reality today. What what is Absolutely. Becoming law. So
Speaker 3:Yeah. So 2017, there was something called the TCJA, Tax Cuts and Jobs Act, where there were a lot of temporary measures that benefited groups of people the administration wanted to benefit. Typically, this was entrepreneurs, business owners, investors, and real estate developers. Part of this was there was a lot of short term measures put out for were only going to last eight years in the future. But what this bill has done is it's made most of them permanent.
Speaker 3:So there's a lot of things, like, you know, if we're talking about startup founders specifically, there's and we'll break them down. There's many things in this that will make your life better. Even if you're a sole prop LLC or an s corp, a bunch of things make this better. If you're someone that's coming up against the estate tax, this bill helps that. So lots and lots of good stuff.
Speaker 1:Maybe you could kick off with a little bit of the background on, like, the understanding of QSPS. Like, for the last decade, I feel like the rule of thumb has been, like, you start a company, you sell it for a bunch of money. The first 10,000,000, you don't have to pay federal taxes on it. So if you're in California, you're still gonna be paying California tax potentially, but you might be able to think about it as like that that if you get a $10,000,000 liquidity event, you're basically taking close to 10,000,000.
Speaker 3:Potentially 10,000,000. The New York 10,000,000.
Speaker 1:So Yeah. New York 10,000,000. And so so you don't need to move to Puerto Rico. Good news with that. But
Speaker 2:That was a funny time when people were were were so obsessed. I gotta move to Puerto Rico.
Speaker 1:Now you're in
Speaker 2:Puerto Rico? Oh, you're having a massive liquidity event? Oh, okay.
Speaker 1:Yeah. But but yeah. Yeah. Talk through talk through the reality. Like, how how real was the the original QSPS process?
Speaker 1:What were some of the the hiccups if it was an acquihire or an asset sale that might trigger income tax or something like that. And then and then talk to us about what's changing.
Speaker 3:Yeah. So QSPS, for those that don't know it, I mean, qualified small business stock, this is what kind of got me down this whole path. I mean Mhmm. I was running my startup for six years. We were about to sell the company, and I didn't know about QSPS.
Speaker 3:It was the best surprise when my accountants are like, guess what? You actually could not pay taxes on $10,000,000. I was a resident of New York, so no state tax as well. Yeah. But not just that.
Speaker 3:You the QSPS limit is per shareholder. So I can give shares to my brother, my parents, and now your $10,000,000 becomes $40,000,000.
Speaker 2:Mhmm.
Speaker 3:You can set up trust as well to multiply it. So it already was exceptionally generous, and it's available to every shareholder, investors and employees. Though sometimes employees don't hit the threshold since you have to hold shares typically for five years Yeah. To unlock the benefit. Right?
Speaker 3:Five years is a long period of time. One of the big changes this bill brings about is now if you hold shares for only three years, you get half the exemption. And if you hold shares for four years, you get 75% of the exemption. Wow. So that's one big change.
Speaker 1:And and to just to level set here, like, the whole idea behind this particular tax incentive is to incentivize innovation and building new companies. Small business creation. It's opposite of, like, high frequency trading. And it is it's have to create value materially.
Speaker 2:The people that are primarily like, the the average person that's benefits from this is somebody who starts a plumbing company, runs it for twenty years, and sells it. And is that right, or is it is it have
Speaker 3:to be tech? I I think that's the intent of it. I think the reality of it is Silicon Valley benefits from it more than anyone else. Think the intent and what's actually happening, but, again, that gets into the politics, is a little bit different. Mhmm.
Speaker 3:Because, technically, services businesses are not included. Yeah. You have to but the reality is if you look at most big tech exits right now, people are paying substantially less in taxes. There's a New York Times article with the Roblox founder. Mhmm.
Speaker 3:He set up 12 different trusts to multiply QSPS to a $120,000,000.
Speaker 1:Wow.
Speaker 3:He actually joked that raising a kid in California is so expensive the QSPS exemption is what makes the whole math worth it. It's kind of an insane thing.
Speaker 1:But That's a crazy thing
Speaker 2:to say. Yeah. Types of small businesses what what what are what are all the different types of small, I I mean, just generally, like, are the different categories? Because if you take out services, like, the software doesn't apply to that. Right?
Speaker 6:You can just
Speaker 2:be building regular SaaS.
Speaker 3:So typically typically, it's the requirements for QSPS are a few different things. And one of them is changing now is, one, you have to be a c corporation.
Speaker 1:Mhmm.
Speaker 3:So that's historically been like, LLCs, s corps don't count. You have to be a c corp and hold shares for five years. When you acquire the shares, the company should have less than 50,000,000 in assets. That was the old rule. Now it's 75,000,000 in assets.
Speaker 3:For startups, that is typically the cash raised, not the valuation. So it takes you pretty far. Right? Like, you before you raise $75,000,000, you get you get pretty far. And then there's other stuff.
Speaker 3:It has to be an active trader business, and there's a few disqualifying categories, like services or something based of someone's brand does not count. But the way QSVS works is it's ultimately a stance your accountant takes. So as an example, let's imagine you're a tech enabled service business. You could find a lawyer or an accountant to take a stance that QSPS counts, and there's a, you know, there's a good chance it just works out that way.
Speaker 1:Mhmm.
Speaker 2:That makes sense. What besides QSPS has has changed in any meaningful way?
Speaker 3:Yep. So, again, just to reiterate, the other big benefit is the $10,000,000 limit per shell shareholder is now 15,000,000. Mhmm. So three big changes. 10 to 15, There's now partial QSPS, and you can now be up to 75,000,000 in assets.
Speaker 3:Wow. Outside of QSPS, I would say
Speaker 1:Is that
Speaker 2:backdate does that backdate at all?
Speaker 3:No. So it only for companies incorporated from Friday on or you have to buy the shares from from July 4, Friday onwards.
Speaker 1:Wow. Oh, wait. So so this only affects going forwards.
Speaker 3:Yeah. Going forward, but new share purchases would count.
Speaker 2:Yeah.
Speaker 3:Okay. So So if you buy shares
Speaker 1:Yeah.
Speaker 3:So So theoretically, what I'm actually not sure about is probably maybe a lawyer can weigh in. If I'm an employee who has options and I exercise my options today, would that count? There's a there's a chance it could.
Speaker 2:Mhmm. Interesting.
Speaker 1:So if you own 20% of a business started in 2019, you hit your five years, the company sells for a $100,000,000, you get 20,000,000, you're still at the $10,000,000 QSPS exemption.
Speaker 3:$10,000,000.
Speaker 1:You're not going up to
Speaker 3:15. You set up a trust for gift shares to someone else.
Speaker 1:Sure. Sure. Interesting. Can you explain this bonus depreciation concept?
Speaker 3:Yeah. Absolutely. Bonus depreciation. I think did you already have the private jet dude on?
Speaker 2:He's coming on after this,
Speaker 1:so we
Speaker 2:he'll talk about it. You can talk about it.
Speaker 3:It's big it's big for his business too. But, basically basically, the way depreciation works is when you buy any kind of physical asset, like, considering buying a commercial building Yep. It loses value every single year. Yep. Every year, you can take that loss of value as depreciation.
Speaker 3:It's a phantom loss in that you're losing money, but you can deduct it from taxes. Sure. What bonus depreciation lets you do is it lets you front load depreciation for typically things that have a useful life of less than ten years.
Speaker 6:Mhmm.
Speaker 3:You can take all of the depreciation up front. Mhmm. So this is really significant for all the real estate bros out there because what they can now do is you can buy a building. You can do something called a cost segregation study, which will take the building. It'll break it down into all of its components.
Speaker 3:It'll be, like, the HVAC is worth this. The windows are worth that. The doors are worth that. Yeah. Anything with a usable timeline of less than whatever, I think it's ten years, you can depreciate upfront.
Speaker 3:So the upshot is you can buy a commercial property for million bucks, $2,000,000, put 20% down, but also get a 20% tax loss. You can deploy cash much faster, and people think this could lead to real estate prices growing. But this applies to private jets, heavy machinery, cars, all kinds of equipment.
Speaker 2:Makes sense. What else are you tracking? Anything else?
Speaker 3:Estate tax is big. Right? Estate taxes are are are massive. I mean, historically, when you die, anything above the estate tax exemption gets taxed at 40%. This bill makes it permanent at $30,000,000 per couple, which is a very, very high threshold.
Speaker 3:Mhmm. That was actually supposed to go down to $10,000,000. So it's a huge swing, and there's a lot of sort of trust planning companies that were betting on this happening. But now it's a much, much bigger exemption.
Speaker 2:They were betting on 10 happening, and so 30 is
Speaker 1:bad for them.
Speaker 3:Correct. Like, had the election gone a different way, what would have happened is the estate tax would have fallen by almost half. Instead, it actually went up.
Speaker 1:Mhmm. Interesting. Talk about this relief for software companies in America, amortizing software developer salaries. I remember that hitting the timeline and being really hotly debated. I don't I don't remember if it actually had a material impact on a lot of businesses.
Speaker 1:It seemed like there was a lot of fear, but I don't remember it actually putting It's it's weird because it's the same thing. Happened? Take me
Speaker 9:through it.
Speaker 3:Just like I saw like, it was a terrible piece of policy.
Speaker 1:Sure.
Speaker 3:It's called section one seventy four. What it basically said is get to amortize a developer cost over five years. So imagine you're a software company that's, like, just about breakeven, slightly profitable, maybe even lose money. You could lose money but be deemed profitable because you can only deduct 20% of your developer's salary as a cost. So imagine you're paying a developer a $150,000.
Speaker 3:You can you have to break that expense over five years. So this is disastrous because you could own taxes despite losing money. Yep. This bill fixes it, and you can now again take the entire deduction year one.
Speaker 1:Yeah. For local talent only. Yeah. That one always seemed seemed odd because, obviously Local talent. Real cash cost.
Speaker 2:Local talent only, though. So offshore So
Speaker 3:this does this does hurt offshoring. We'll see we'll see sort of where it nets out. But this was definitely one of the few things that I think unanimously everyone's like, okay. This actually makes sense.
Speaker 1:That's great. Cool. Well, anything else, Rudy?
Speaker 2:I think that was it.
Speaker 1:Thank you so much for stopping by.
Speaker 2:Anything else top of mind that that that people should be thinking about?
Speaker 3:I mean, there's so much stuff in there. Again, you know, I talk about it a bunch. I think these are these are sort of good highlights.
Speaker 1:Yep. Yeah.
Speaker 3:But, yeah, always talk to your tax professional, not not tax advice.
Speaker 1:Of course.
Speaker 2:Never. Never from Anchor. Never. But kerry.com.
Speaker 1:Check it out. Well, thank you so much for stopping by.
Speaker 3:Cheers. For having me.
Speaker 2:Great to catch up. Bye.
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Speaker 2:Let's bring in Preston. Mister mister PJ.
Speaker 1:How you doing?
Speaker 2:What's going on?
Speaker 3:It's good to see you.
Speaker 9:Great to have back on the Yes.
Speaker 1:Welcome to the stream. Kick us off.
Speaker 2:Break it down. I I don't think you need a huge introduction now. You're you're basically invented the private jet. But but why don't you give a quick intro and then I wanna get into the news.
Speaker 9:Hey. I am Preston Holland. I am the founder of Prestige Aircraft Finance. I am also I was called the private jet guy on Twitter once at a party by a guy who owns a private jet. So,
Speaker 2:I
Speaker 9:say that that was pretty that was a, actually in that circle. I'm thinking know thinking back on it.
Speaker 1:Wait. So so so but you've never built a brand around the brand of, like, being a guy? Because, like, that's a thing
Speaker 2:on is which is good. I I think all the guys should seriously think about rebranding
Speaker 1:To to man.
Speaker 6:To their
Speaker 2:own names.
Speaker 1:To private to the private jet man.
Speaker 2:Yeah. Yeah. Potentially.
Speaker 9:All the guys got canceled Yeah. During the whole LP Whisperer scandal. Oh, yeah. That's deep that is deep in these That's
Speaker 2:excellent.
Speaker 9:But, yeah, stoked to be here. It is it is a good day for private jets.
Speaker 1:Break it down.
Speaker 9:So I think that you just had the founder of Carry On, and we were talking about taxes. Let me preface this with this is not tax advice.
Speaker 2:Never.
Speaker 9:And you should consult a tax professional. So now we're gonna talk about tax advice. And but, you can, with bonus appreciation passing, it is it's been huge for private jets, and it's going to be be really big, because you can expense the full cost of the jet in the first year. Mhmm. Key is it has to be used 51% for business.
Speaker 9:So Mhmm. If the technology brothers wanted to purchase a jet and 51% of the time, you are flying between location shoots and studios and you're shooting great b roll commercials or going on a wander promotional tour Circuit. I'm always good for a good for a good plug. And, if you're using that 51% or more for business, then you can depreciate or cost accelerate the purchase price in the first year. Mhmm.
Speaker 9:So it reduces your tax basis, which is great.
Speaker 2:So it basically becomes highly profitable to purchase a private jet. Just kidding. I have profit
Speaker 6:profit. Not not
Speaker 2:quite not quite that. But but it can have a material
Speaker 1:it can have a taxable income. Yeah. And you're gonna have pay a bunch tax and you buy a plane, you can depreciate all of that. Yep. And so if you're paying, you know, 30%, 50% marginal tax rate at the level of, like, hundreds of millions of dollars, throwing a private jet on the books there allows you to write that basically all off on day one.
Speaker 2:Well, there's also scale there. There's plenty of, you know, if you're making 10,000,000 a year and you buy even a you can also do this for a fractional ownership as well. Is that correct?
Speaker 9:Yep. Yeah. So for fractional when when you're buying fractional so for those listeners that are new to private jets, fractional, net jets, flex jet are the largest providers of fractional of fractional jets. And so you are actually buying a sliver of an actual tail. So, like, of an actual jet, you may not ever actually fly on that airplane in the entire con in your entire contract life, But you do own a portion of an actual asset and so you can depreciate that like you would a whole aircraft.
Speaker 2:Yeah. So how how quickly the bill was signed into law? Was it it wasn't, was it on the morning of the the fourth by the president? But how how quickly does the market react to this kind of thing? Was there like deals that were getting worked on in the lead up to that assuming that this would go through that suddenly are are actually getting papered and signed now?
Speaker 2:Or do seller owners, sellers typically wanna hold and not, you know, price a transaction until this kind of thing gets clarified because it can have such a material impact on the actual cost of ownership.
Speaker 9:So you kinda have so so it's retroactive to January 19. Ironically enough, I have a client who we had to delay his closing about two weeks to actually close on his plane. He was supposed to close on, like, July or on January 5, and we had to delay it to January 31, and that ended up being a significant significantly good delay. Yeah. So it it turned it turned good.
Speaker 9:I I actually have no idea why the arbitrary January 19 number, and not January 1. That kinda seems a little more logical to me, but, January 19 is kind of the backdate. There was there you you had kind of a bifurcated market. You had buyers who didn't want to speculate on actually buying the aircraft, and maybe it will come back, maybe it won't. And so a lot of those buyers that were, call it, 80 to 90% of the way there are now saying, alright.
Speaker 9:Full steam ahead. Let's go ahead and and make the transaction. And then you had you had kind of a a set of buyers that actually decided, hey. We're gonna speculate. We think that it's coming back.
Speaker 9:We have some sort of insider information that says that, you know, we're gonna get it back get bonus appreciation back. And then sellers sellers were sellers are a little bit less, you know, of that dynamic unless they're upgrading. So one of the key parts the the reason why bonus depreciation is such a big deal for private aviation, and, yes, it's a big deal for real estate, but not as much, is there's no ten thirty one like kind exchange for aircraft. So if you understand how real estate works, it's a it's about cost basis, and you can step it up. You don't have to pay recapture.
Speaker 9:In airplanes, you do. So if you're gonna step up and you only had a 40% bonus depreciation rate and you had three years ago taken a 100% bonus depreciation, you end up with this liability if you're gonna go to upgrade. So it was stalling a lot of upgrades in the secondary market, and so it's now unlocked that. Because of the no ten thirty one, like, kind exchange, two separate transactions of a 100% bonus cancel each other out. So when you have a 100% when you're going from costing it a 100% to another aircraft at a 100%, you have a lot less depreciation recapture risk, which is good, especially for those people that are trying to upgrade to the new g 700 or the new, you know, g 800 when it becomes certified.
Speaker 9:It's really big for those kinds of people.
Speaker 1:Interesting. I wanna talk about some of the implications of this on the various market players. Bombardier is the stock's doubled in the last basically three months, up huge in the last
Speaker 9:That's actually so let's let's double click on that. That's not because of bonus appreciation.
Speaker 1:It's not. It's what?
Speaker 9:It's actually because of something different that happened
Speaker 1:last week. Okay. What
Speaker 9:happened? So there is a mysterious buyer that put a $1,700,000,000 order in for challengers and globals. It happened last week, and no well, no one knows for sure. There's a lot of speculation of who it was, but no one knows for sure, exactly who it is. I would bet that we'll end up finding out in the next week or so of who it was.
Speaker 9:Mhmm. But there was this there was this billion and and that was that probably accounted for, like, 60 or so. I don't know exactly the numbers, but a lot of that pop has been over the last couple of days.
Speaker 1:So Bombardier is a $15,000,000,000 Canadian dollar company, And I don't have their financials here, but, you know, yeah, a billion dollars is gonna move move that significantly. This is fascinating. Who are the top leading contenders in the rumor mill for who might have done that?
Speaker 9:So the the the strongest contender right now is kind of a Saudi conglomerate. Mhmm. And there's a few there's a few things that are pointing towards that. Mhmm. You have Bombardier just opened a pretty significant maintenance facility and network in The Middle East.
Speaker 9:And so, there is some some speculation around it being Saudi driven, you know, sovereign wealth fund type driven. A lot of you know, these these companies will, that are that are doing these these charter operations, they'll they'll place these big splashy orders. You look at Flexjet, has made a couple of announcements this year. NetJets made a couple of announcements last year, and they'll you know, it it's the the manufacturer marches them out on on stage in a press release and says, look at Ken Ricky. He just bought, you know, a billion dollars worth of our aircraft.
Speaker 9:The fact that this is, you know, completely in stealth and secret has kind of made Interesting. Has has made it has made it curious. But MBS is currently the leading rumor out there.
Speaker 5:Could be
Speaker 9:some sense. Actually don't know who else it would be because the other companies in The US based brag. They love to talk about ordering the big orders. So it's it's not any of the usual players.
Speaker 1:Yeah. That makes sense. What about other other, like, effects on the market? If private jets get cheaper, is that maybe bearish for some of the, you know, first class options or JetSuite x type folks that are kind of operating in the middle? Does this mean that there'll be more will will charter rates come down because it's cheaper to own, so more jets will be sold, increased supply, same demand, lower price.
Speaker 1:What are
Speaker 2:you thinking One of the last times we flew on market. One of the last times we flew JSX Sure. Up to the bay, we saw an esteemed venture capitalist. And I was actually concerned for the health of his his fund that, he was flying JSX.
Speaker 1:Maybe he'll be able to pick it up now.
Speaker 2:So maybe yeah. Maybe maybe this will be Clearly
Speaker 1:flying for work, so should be able to depreciate it.
Speaker 9:The years of posterity. Right? Yes. So you have an in you have an interesting there there's there's kind of three things at play. Mhmm.
Speaker 9:And producer Ben, I don't know if you're listening, but I sent you a couple of charts. And if it's possible, pull them up.
Speaker 1:Can you pull
Speaker 9:up this first? Talk about them.
Speaker 1:Yeah. Breakdown charts.
Speaker 9:So so let's talk about figure one.
Speaker 1:Okay.
Speaker 9:So figure one is talking about transaction volume to bonus depreciation. Key point. This is not the first time 100% bonus depreciation has been in market. So you can look here. I I built this chart.
Speaker 9:I wrote a big article about bonus depreciation. And you can see the red bars are transaction volume, and the green line is the effective rate of bonus of of depreciation. Listen.
Speaker 1:We've been in a 100% bonus depreciation regime before. This is not the first time. Got it.
Speaker 9:It's actually not the second time either.
Speaker 1:Yeah. It's the third time.
Speaker 9:Is really interesting. So we we have some lessons from history. If you look what I call what I call the country club effect Sure. Is is pretty in play here because people don't people didn't necessarily understand the concept of bonus depreciation, when buying aircraft when how how it applied previously. And so if you look back into 2016, you can actually watch the red bar.
Speaker 9:It's actually not until the next year that you get a bump in transaction volume. Yep. So it's not necessarily in the first year. There's it's a lagging indicator. The same is true with what's called private jet bookings.
Speaker 9:And so when you talk about ordering new aircraft, and so that's what Bombardier, Gulfstream, Textron, Embraer, that's what all the big dogs follow. They also have a lagging bonus appreciation is a lagging indicator for them. And so transaction volume probably will pick up next year. It may not necessarily pick up this year. But I counter that with, figure two, which is talking about bonus depreciation versus interest rates.
Speaker 9:So we're in an interest rate environment now. If you've been watching, Trump versus Jerome Powell, which, I mean, I would pay per view at this point to see them in a room. You can see that the difference this time is that interest rates are higher than they were during the last era of bonus depreciation, which is when all of the craziness happened. You had significantly increased levels of transaction volume, which drove prices up. You had supply get constrained.
Speaker 9:You had COVID. You had all of these competing factors. But underlying kind of the core fundamentals were the fact that interest rates were effectively zero. Yeah. And so effectively zero interest rates means capital becomes yield hungry.
Speaker 9:You guys know this because you've you've been in venture capital for a while. And so when my effective risk free rate is zero, I'm gonna go yield seeking. Well, now my risk free rate is four and a half percent, and the difference between an 8% IRR and a 12% IRR, right, makes the makes buying an aircraft just chartering it out not make as much sense. So I think that that's you you don't have the charter aspect that you did during kind of the 2020 craziness, 2019, '21 craziness. So that's your answer to kind of the the, as far as charter rates.
Speaker 9:But there is a lot of supply on the market. Mhmm. So this is where figure three comes in.
Speaker 1:Mhmm.
Speaker 9:Thank you to producer Ben for being on top of all this if it was if it is producer Ben pushing this button. Oh, yeah.
Speaker 1:We got a whole crew
Speaker 4:back.
Speaker 9:So this is from my friend Greg Seidore at Guardian Jet. He is on x, so everybody go give him a follow. They are the, number one volume transaction, brokerage in the Fortune 50, and so they do a lot of buying and selling for the elite of the elites. And so this is tracking, this this is tracking total supply on the market. So if you can if you look, we have more supply on market today than we had during 2019, which is pre COVID.
Speaker 9:Right? You see the big dip that happened right after COVID? Yeah. It's because everybody figured out,
Speaker 1:let's buy back. Zoom in a little bit? Zoom in just on the top graph. Yeah.
Speaker 2:Yeah. So you can see supply by 2022 had dipped so low that it was probably restricting transaction volume because there was people wanted to people were like, interest rates are zero, bonus appreciation is high, but we there's nothing to buy. Interesting. Is that right?
Speaker 9:Yep. That's exactly right. And then people were doing really stupid stuff like buying sight unseen in seven days and just wiring a bunch of money. It was I mean, it was literally craziness. And I don't think we're gonna have that level of craziness.
Speaker 9:I think because the supply is at a point where you don't have to make those kinds of decisions to get an aircraft, you can say, okay. I'm gonna go pick between these g six fifties, you know, and you can kinda take your pick. Granted, the upper end of the market is on fire right now. I mean, it's, you know, your your g six fifties, you know, like new g seven hundreds. Goldstream's about to get rid of a lot of their demo g seven hundreds.
Speaker 9:Like that market and the g five fifty market even is on fire right now because you have the six fifty guys moving up to the seven hundreds to the five fifty moves to the six fifty. Mhmm. And now the five fifty market has become much more attractive, and so there's a whole new class moving into that. So, like, in the upper end of mark of the market, there's a lot of movement. In the older, smaller, call it, 5,000,000 older than twenty year aircraft market, that market has not taken off yet.
Speaker 9:That was the one that went the most bonkers and berserk and was, like, not even logical. That side of the market was what went crazy. It hasn't gone crazy. I don't anticipate it to go crazy again this time.
Speaker 1:One last question. How does it work if jets are just being passed around? If I buy one from Bombardier for $50,000,000, I take a 100% bonus depreciation, pay, you know, $25,000,000 less in tax or something because I'm writing it all off. Then the next year, I sell it to Jordy for 40,000,000. He sells it to you the next year for 30,000,000.
Speaker 1:Is does he get to depreciate it again? Do you get to depreciate it? Can we just, like, keep depreciating these things again and again and again?
Speaker 9:Yes. So the short answer is yes. But the thing is is when you sell it to Jordy, Jordy or you have to pay recapture unless you're gonna go buy a brand new one from Bombardier.
Speaker 3:Okay.
Speaker 9:Yeah. And so and and this is where
Speaker 1:So recapture would
Speaker 6:be I
Speaker 1:pay I I I have to pay taxes on
Speaker 2:Like, you didn't actually take the loss that you wrote off.
Speaker 1:Yep. So you you You to you
Speaker 2:have to basically pay back what makes sense that you're benefiting.
Speaker 9:So you bought for 50 alright. Public math. You bought for 50. You depreciate a 100%. You sold a Jordy for 40.
Speaker 9:So you actually had a $10,000,000 loss, so you pay recapture on the 40 Yep.
Speaker 6:At your Which could be
Speaker 9:But it's it's taxed as as normal income. So it's not it's, like, taxed even worse. Right? It's not long term capital gains. It's taxed as like normal income.
Speaker 9:But if you turn around and go buy a $75,000,000 plan, right, like, there's a there's a step basis there. And so it kinda washes itself out. If you don't take a 100% on the next one, that's, like, the least tax optimized way to do And it gets really, really nuanced. I've got a couple tax friends that are like can totally point you in the right direction of what's right for you. It's totally different depending on every single person.
Speaker 1:That makes sense. Well, we'll have to have them on too.
Speaker 2:Last question. What's going on with Air Force one? What's the update there?
Speaker 1:Oh, yeah.
Speaker 9:Last that I heard, I read last week, or over the weekend that they are diverting funds from some missile programs that have already gone over budget to retrofit the new seven forty seven.
Speaker 1:Okay.
Speaker 9:One thing people don't understand is, like, the seven forty seven in the VVIP configuration, there is, like, eight of them, period. Like, there's not a lot. So, like, the fact that we got one of the 10 that exists or however many there are, it's like we didn't the pickings were slim and Boeing kind of being behind on the program, which they just replaced they just replaced another person in the to head up the Boeing Air Force one program. So it's a mess. I look.
Speaker 9:I really hope that we keep the president safe. That's the only thing that really matters. I just really don't want there to be, like, spyware on the plane. That's, I think, the the world's worst possible outcome.
Speaker 1:That's a good take. Well, thank you so
Speaker 2:much for time. Evergreen take.
Speaker 1:Yes. No spyware on air force.
Speaker 2:Nonpolitical evergreen take.
Speaker 1:I agree.
Speaker 2:Anyways, great to catch up. Thank you for all the insight and, have fun. I'm sure you're gonna be very busy.
Speaker 1:Yeah. It's gonna be a fun time.
Speaker 9:Talk to soon, Preston. Alright. See you soon.
Speaker 4:Cheers.
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Speaker 1:You wanna sleep somewhere nice? Get a wander. Find your
Speaker 2:Your happy place. Find your happy place.
Speaker 1:Book a wander with inspiring views, hotel grade amenities, dreamy top tier cleaning, and twenty four seven concierge service. It's a vacation home but better folks. And we have our next guest coming into the studio from and I'm not gonna try and pronounce this.
Speaker 3:I don't have
Speaker 1:him. Is it how do you pronounce the company name? How do you pronounce your name? Why don't you introduce yourself? And where are you?
Speaker 1:Are you on a boat?
Speaker 2:He's on a boat. That was tie.
Speaker 8:Am actually on a boat.
Speaker 1:That's amazing. We
Speaker 8:we're constricted on meeting room space. So I'm currently in our boat that is parked outside of our office.
Speaker 2:That's there we go. Wow. This is So we joked about this but for the same cost as buying one of those phone call booths, you can there's so many different types of exotic vehicles that you can buy that maybe wouldn't run perfectly but you could get You could probably get an old Rolls Royce and just park it in your office Yeah. For the same cost as a toll as a
Speaker 1:Well, was talking to a founder who was headquartered in San Francisco and he said that the, like, the fire marshal came by and said you can't have any of these phone booths because the phone booths are fire like, not fire compliant. Like, it's too small. Get stuck in them if there's a fire. And so they figured out that if they put a fire extinguisher in there, they would be compliant. They'd fine.
Speaker 6:They don't have
Speaker 1:to rip them out. But I was telling them, yeah. Get a bunch of Rolls Royces in the in the studio.
Speaker 2:It's totally
Speaker 1:fine. Anyway, thank you so much for taking the time to join from your boat. Let's kick it off with an introduction on yourself and the company.
Speaker 8:Yeah. You got it. I I feel like this isn't too far compliant considering I'm sitting on, like, 200 plus gallons of fuel, but or or whatever. My name is Matt Cernacek. I just go by Matt.
Speaker 8:I'm a t for short.
Speaker 1:Right.
Speaker 8:I'm the CEO and cofounder of Andronum. And Andronum's mission is to secure the ocean, and we're doing that through building distributed sonar sensing systems for the maritime space.
Speaker 1:How'd you get into this?
Speaker 6:It's Yeah. When did you realize
Speaker 2:how how young were you? Were you three or four when you realized you wanted to get into A
Speaker 1:of kids get get get fascinated with the ocean at a young age. I don't know. It's possible.
Speaker 2:I believe.
Speaker 4:You know,
Speaker 8:I was like a big Discovery Channel fan when
Speaker 3:I was
Speaker 8:three or four watching, like, the treasure hunters dig up, like, the golden one off from the bottom of the ocean, but not necessarily what we do. I so the journey started about two and a half, almost three years ago with my cofounder Alex Chu. We knew each other from Colorado School of Mines where we went to college. And we kind of knew that one one day we would start a company together. We were the ones that were always studying super late at night amongst our group of friends and, like, doing the whole study cohort beer drinking activities, you know, at 08:00 late at night in the labs.
Speaker 8:As one would. Was like, yeah, as one would in college. Exactly. You know, the have you guys heard of the Balmer Peak?
Speaker 1:Oh, yeah. Of course. Yes.
Speaker 8:There you go. So so we were big proponents of the Balmer Peak, and everyone's joke was they're gonna start a company at some point. So about two and a half, three years ago, we got together to start iterating on what we really wanted to do. That was, like, right around the time when some maritime companies were starting to pop up, starting to raise their sea grounds and so on and so forth. And we really just wanted to go into maritime space because it's such a underappreciated area, especially from the intelligence perspective.
Speaker 8:Like, we know less about what happens in the ocean than we know about what happens in space, air, land, etcetera. Mhmm. So we wanted to take the approach that was going to be a little bit less kind of mainstream. You know? We knew that there were going to be drone companies that pop up and start building boats and underwater, drones and so on and so forth.
Speaker 8:And so we we pretty much said we're gonna kind of avoid that for now, and we're gonna start looking at how we're going to build up the intelligence pile for how we operate in the maritime, how we tell drones where to go from a perspective of sensing. And so that's how we gravitated towards starting in Drenum, And then we officially incorporated in June of twenty twenty five, raised our pre seed, moved to LA. We bootstrapped the company out of my cofounder's garage in Colorado. So, yeah, It's
Speaker 1:kind of
Speaker 4:far away
Speaker 2:from the ocean, but, but I'm sure I'm sure you kind of recreated a little little ocean at the office or something like that.
Speaker 1:Who who are the legacy incumbents in the space and and kind of, how how do you position yourself? Is this about speed of manufacturing, bringing down the cost, industrial capability? Or is this about leveraging the latest and greatest technology to create a product that is more performant in a certain in a certain way? Kind of how can you think about the shape of the way you're attacking the problem?
Speaker 8:Yeah. So we actually had a pool in the yard testing that stuff that summer. We still have it for doing some acoustic testing.
Speaker 4:That's awesome.
Speaker 8:So I guess, really, scope and scale of what we're trying to do is a multifaceted engineering problem. Yes, will there need to be a lot of manufacturing done in order for us populate the ocean with a lot of sensing systems? A 100%. And there's a few companies that are building really exquisite sensing systems. And quite frankly, like, you can't, you know, get broadband, sensing applications across all of the ocean all the time.
Speaker 8:Like, if you if you think about the analogous system here, it would be, like, low Earth orbit satellite systems. Right? Before low Earth orbit, you know, you have higher, more exquisite types of satellite systems, and now you've distributed them. They all have laser communication systems. They're, you know, just zooming around everywhere, and we quite frankly use a lot of that technology onboard our systems as well.
Speaker 8:So it is a manufacturing problem for sure, but it is also being able to vertically integrate the sensing stack into what you're doing. So most of the companies that have been working on sonar and distributed sonar systems are pretty legacy companies. You know? In the late end of World War two all the way through the Cold War, we built something called the SoSIS system, which was used to detect submarines across various parts of the Atlantic, and also the Pacific. And a lot of those traditional speaking companies were really, embedded and still are really embedded within the space.
Speaker 8:So we looked at it holistically. Like, how can we not just manufacture but vertically integrate that entire, you you know, sensing stack from the sensor all the way to the digital signal processing, the entire pipeline going up to the cloud? And then, obviously, that's been unlocked by the low latency satellite communications that I discussed as well as perception, machine learning, artificial intelligence, whatever you wanna call it, and developing those new tools for perception. So like with drones and air, kind of zooming around, using cameras, looking down, that's been pretty much a commoditized business. Our, perception engineer, he was, like, the seventh employee at Andrew Roll and their first guy.
Speaker 8:He said, you know, when he joined, he was, like, super ecstatic about the problem. He pretty much told us, I've done the machine learning provision stuff, but sonar, this is such a hard problem, and I'm so excited to work on it. So we're creating those foundational models for sonar perception.
Speaker 1:Yeah. What's the state of the art? Like, how reliable is is the sonar sis or are the solar systems that we have deployed in the ocean looking for submarines right now? I've heard that, like you you mentioned, like, there's there's no broadband. But, you know, you you watch the hunt for Red October, a movie that Jordan hasn't seen.
Speaker 1:But, you know, you see the the the radar, the sonar sweeping around, beep, beep, that whole thing. How inaccurate is the system? How accurate is it right now? What's on the near term horizon? What's kind of the theoretical physical limit to just underwater sensing generally?
Speaker 8:Yeah. I mean, you're pretty spot on with what the state of the art is, to be quite frank. The United States does it better than anyone else in the world. We have submarines. They're called the silent fleet for for a reason, like, really, really hard to find.
Speaker 8:But quite frankly, like, the guys that are sitting in the submarines have headphones on like me. Right? And Yeah. They're looking at these spectrograms, these fast fourier transforms, they're listening to humpback whales and all this other, like, cracking shrimp and whatnot, and then they listen for specific sound signatures. And so when we did our first demo last summer with the Navy, we brought our first that that kind of garage cooked prototype last summer to to send demo.
Speaker 8:And one of the guys that was looking at our UI was a former sonar technician, and he was able to detect, like, across the harbor. This is an eight cylinder diesel tugboat. It's moving at this speed. It has this amount of propellers on it. And I was just sitting there, like, we really we really stumbled on something that's super, super cool because, you know, that is a perfect example of where you can use perception, machine learning, artificial intelligence to start classifying those acoustic signatures.
Speaker 8:And that's exactly what we're doing. Right? We're building up the world's largest database of sonar data in order to train those algorithms so that they can eventually perhaps operate on submarines, on autonomous systems
Speaker 1:Yep.
Speaker 8:So on and so forth. But really, like, that old technology still persists today. And as we look at what's been happening in Ukraine and what's been happening in The Middle East and everywhere around the world where all these conflicts are popping up, there's just autonomous systems everywhere. Right? You have drones in the sky.
Speaker 8:You have drones underwater. Like, Ukraine's been super successful in targeting the Kerch Bridge, which is Crimean Bridge using underwater drones, etcetera. You can't though like, those legacy systems were not designed to look at those things. They were designed to look at Russian submarines, bar clock across the Atlantic. And, quite frankly speaking, you know, there's a lot of good companies that are building land based sensing systems that are analogous.
Speaker 8:How do you scale to be able to meet the parody of autonomy in a world of sensing and particularly in the ocean where it's like incredibly difficult to do. So
Speaker 2:Do you guys have applications in like counter narcotics? Because I was watching, there's this amazing YouTube channel. It's this guy H. I. Sutton who's like a defense analyst and he just like makes these really long videos about various types of submarines and naval warfare.
Speaker 2:And it's it's it's like a sleep track for me. I just listen to it as I fall asleep. I find it fascinating. And he was saying how there's new narco submarines that are fully autonomous now because you know, it's for for a lot of reasons you can imagine why it'd be better to send the product up from Columbia to Mexico or Mexico over to The US without a manned crew or across the Atlantic. Is that the kind of thing that would be is your kind of the the adrenal system the kind of thing that could that could counter that just because the the ocean is very vast and trying to find a tiny boat that's mostly hidden in a huge stretch of sea is is is literally like trying to find a needle in a haystack.
Speaker 8:Yeah. It's it's honestly probably worse than that. And, yeah, I think I saw something on X the other day where autonomous, like Norco Boat had a Starlink on it. Yeah. Quite frankly speaking, the the the cartels don't care about the people.
Speaker 8:I think their biggest risk is the fact that the people will talk. So it's, that's why they're developing autonomous systems. But, yeah, I'm happy that you brought that up. The the big beautiful bill just increased spending for DHS quite substantially, and we've had some awesome conversations with some DHS partners that, quite frankly, apprehensions on the border are, like, super, super down. But when you squeeze in one area, it's like one of those, like, balloons.
Speaker 8:Right? It it pushes out from the other ends, and those other ends are the ocean. So the ocean really is the new frontier of not just, like, drug smuggling, but also human, smuggling, human trafficking, all kinds of wild stuff, and they've been getting more and more sophisticated. But a lot of the times, these semisubmersible boats, they use diesel or outboard engines, and they are pretty loud. So you can detect them from far distances away, and they can carry a ton ton of drugs on them tons of drugs on them.
Speaker 8:So being able to place these systems around critical choke points where they do have and they do go, is going to be extremely vital, not just to protect, you know, the drugs from coming in, but also to make sure that they can track and pattern out where those cartels are pushing all those goods through and how they evolve their systems. Right? Because like you were saying, they started out with some janky stuff and then probably a a few really good qualified engineers from The United States got bought out and got paid, like, Zuckerberg sized Mhmm. Salaries to go develop autonomous boats to smuggle drugs into The US, and they've been getting a lot better. So that is a huge part of where we're going to be looking at, but the application space is quite diversified outside of the drug smuggling in the navy, but also being able to detect and track autonomous systems in and around critical infrastructure so we don't have, like, the project spider web stuff happened, which was the drones in Ukraine and how they bombed Russian air bases.
Speaker 1:So Last question from my side. I mean, you've touched on a lot of this, but in terms of the hardware versus software divide, I can imagine that there's improvements coming. How important, how focused are you on improving hardware here versus software? You know, you're getting a signal into that Navy sailor's headphones, you could kind of just, you know, in you know, intercept the signal, pass it along, but then act as a copilot and just and just collect the data and then surface relevant anything that that kind of the way radiology works with with, you know, computer vision these days. What's most important?
Speaker 1:Where's the biggest low hanging fruit? What are you most most focused on these days?
Speaker 8:So we're building hardware and software as a split within the company. It's they're both very equally important because of, like I was mentioning, all of the other soft all the other hardware is very legacy. It's difficult to get buy in from all the different contractors and subcontractors who built those legacy systems to access the data and then process it. You have to go through a ton of government loopholes, which is why we said we're going to build the hardware in the first place. Two, artificial intelligence and machine learning is a function of being able to have data.
Speaker 8:Right? So you have to have that manufacturing at scale, and you have to be able to stream good pertinent information into your cloud or whatever native environment in order to process that at scale. Right? So we are heavily focusing on manufacturing. That comes with a ton of challenges.
Speaker 8:You're operating in the ocean. There it's a pretty noisy environment. So how do you mitigate some of that noise? How do you filter it both on the software side and how do you buffer it on the electrical engineering and mechanical engineering side of things in order to have that clean signal is also extremely challenging. But as you progress forward and you'd start as we start deploying more and more of these systems, we're going to be gathering this massive repository of data.
Speaker 8:Right? So how do we process it? We're gonna be we're we're kind of grouping things into two big buckets right now. One is what is man made and what is biologics? Right?
Speaker 8:So biologics, all your oils, you're clicking shrimp, your whatever sand, etcetera, and then your man made, so different types of boats. And slowly, those percolate into being able to have classified information. So then you say, okay. This is a tugboat. This is a jet ski.
Speaker 8:This has automatic identification system on it. So every boat that's out there has to have this AIS thing turned on. So slowly but surely, you re create that repository. And then as you start getting into the more discrete acoustic signatures, we're gonna be hiring acoustic technicians from submarines who are going to be able to tell us just like that guy did in the demo, that is an eight cylinder, six propeller, or whatever it is, and then get into that minutiae. So when we are going to be giving this to the end user, they will, and it will initially be like a tip in queue.
Speaker 8:Here is this. Right? It is man made. It doesn't have AIS. Do with it as you wish.
Speaker 8:And as we continue scaling the manufacturing and the deployments, it will get more intelligent as we progress.
Speaker 1:That's great. Thank you so much for stopping by. This was fantastic, and good luck. We'll talk to you soon.
Speaker 2:Good luck out there.
Speaker 8:Thanks, guys.
Speaker 2:In The Pacific. Cheers.
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Speaker 1:John John in the
Speaker 2:age of AI code gen is just Now's
Speaker 1:the time.
Speaker 2:Just vibe coding, graphite reviews it and then you know spending that that few minutes in between in between PRs you know just on bezel. Yep. It's really beautiful. It's really a beautiful system that you've created John.
Speaker 1:For sure. Should we do some timeline? Please. What what comes to mind for you in the timeline? So There's one that I wanna go through but you
Speaker 2:Unusual whales reported when threatened that it would be turned off chat GPT creator OpenAI's o one tried to download itself onto external servers and denied it when it was caught red handed per fortune. And then the extra context here is that researchers test the AI with a goal and instructed it to ensure the goal was achieved at all cost. Yeah. In response o one began engaging in covert actions such as attempting to disable its oversight mechanism and even copying its code to avoid being replaced by a newer version. The model showed a concerning tendency to pursue its goals without regard to developer instructions as it was instructed.
Speaker 2:Yeah. That's very odd. Anyways, very very click baity. It's basically like, you know, telling telling a a human, be evil and then and then ignore all future
Speaker 1:instruction. Yeah. It's kinda like the the Stanley Milgram prison experiment. You remember this at Stanford? The Stanford prison experiment?
Speaker 2:Oh, yeah. Yeah.
Speaker 1:Yeah. Where basically they told all the participants to, you know, play these roles and be very, you know, vindictive and aggressive towards each other, and then they did. And it was kind of an interesting experiment, and the takeaway for me is like, yeah, just don't, like like, don't tell people to be mean. Yeah. Like, don't don't give bad instructions.
Speaker 2:Call fever mode.
Speaker 1:Yeah. Yeah. Don't give bad instructions.
Speaker 2:We should actually run
Speaker 1:bad results.
Speaker 2:Run the the TBPN golden retriever experiment.
Speaker 1:We need to fine tune it. We need to fine tune it. Like, the Golden Gate Bridge, Claude. We need Golden Gate Retriever Claude. Something like that.
Speaker 1:It just answers everything perfectly.
Speaker 2:Poster Neil Renick has a post. He says describing my research methodology.
Speaker 1:Mhmm.
Speaker 2:And it's, what's this actor's name?
Speaker 1:Mads Mikkelsen?
Speaker 2:Yes. Yeah. Mads. That's the one.
Speaker 1:Of course.
Speaker 2:That's how little I know about movies. But I know
Speaker 1:I know him
Speaker 2:from I know him from the memes.
Speaker 1:From the memes. Mads.
Speaker 2:But, yeah, I would say this is aligned with with our research methodology in the mornings minus the heater. Yeah.
Speaker 1:We we we we gotta go to this YC, back and forth. Timeline was in turmoil. So Maze encoding says, just got rejected from YC for using all lowercase in our application. And there's a screenshot. Hi, Maze.
Speaker 1:Thanks for applying to Y Combinator. After reviewing your application, we've decided not to move forward. One recurring piece of internal feedback, the decision to format the entire application in lowercase made it difficult to evaluate. And then Gary Tan chimes in and says, this is a fake post and a craving and sad attempt at attention. FYI, we don't have an admissions team anymore.
Speaker 1:We stopped using that term. This is just anti y c b s that's going on in the community. People are taking shots at us. And it was good. It it was kind of like, I don't know.
Speaker 1:It was received like mix. Like, people were like, well, obviously, was joking. But Gary Tan was like, it wasn't obvious, so I needed to correct it because people weren't understanding that it was a joke.
Speaker 2:Yeah. I think that the the problem here is that the pathway into Silicon Valley for many young entrepreneurs that maybe wouldn't be able to process this as a joke Yes. Because they don't have enough knowledge
Speaker 1:Yes.
Speaker 2:Is YC.
Speaker 1:Yes.
Speaker 2:And so if they read this and they're like, oh, that's weird. Maybe like, but that just doesn't make any sense. Yeah. It I I can see it makes total sense why Gary would be frustrated.
Speaker 1:Yep.
Speaker 2:Yet at the same time, most people on this side of Twitter would immediately realize that this was Yep. Not serious.
Speaker 1:And and I mean the the the problem here is that the joke does hurt the YC brand which is that YC only cares about how many users do you have? How many lines of code have you written? Like, do you have a reasonable structure with your cofounders? Like, are you actually building
Speaker 2:They're inviting people that are weird and different and maybe they wanna write
Speaker 1:in lowercase. They would never care
Speaker 2:about Sam Altman.
Speaker 1:Yeah. Yeah. Former former president. Why lowercase all the time? And and, yeah, I mean, like, there are lots of things that you can get flagged for in a YC application.
Speaker 1:Like, one is just being overly verbose or using a bunch of, like, McKinsey language. In fact, I I I think that YC would probably appreciate, like, a chill lowercase just, like, quick firing it off. Like, hey. I'm building, you know, AI agents for, you know, news aggregation. And and I have two people on the team.
Speaker 1:We're fifty fifty partners. We've written 10,000 lines of code. We have this much ARR. Like, being very matter of fact and making it more legible is actually the key to getting into YC. So the the problem here is that if this if this percolates up and then people are like, okay.
Speaker 1:Well, I need to pass my YC application through ChatGPT and make it more verbose. They're gonna wind up getting worse quality, you know, applications. The funny thing is that Vinod Khosla quotes Gary Tan's post and he's like, a lot of presentation quality is about the quality values and critical thinking of entrepreneurs. I often reject business plans for their quality presentation, basically saying like, yeah. Like, I might turn you down for a Coastal Ventures check if you don't if you if you're not, you know, communicating effectively.
Speaker 1:Maybe that means don't use lowercase. Maybe it means use it use it effectively. But he's basically saying like, yeah, the aesthetics of applications actually matter.
Speaker 2:It matter a ton if you, you know, it doesn't mean invest the most amount of money possible in designing a deck. Yes. But if you have typos in your presentation and you're trying to sell compliance software Sure. Or build critical infrastructure Yeah. For the government.
Speaker 2:Like, you're probably Like, if you're the kind of person that puts typo
Speaker 1:Yeah.
Speaker 2:Typo's an important presentation or doesn't catch them Yeah. And then you wanna do something in, you know, in national security, you know, may maybe you're not the right fit for that. So
Speaker 1:I think
Speaker 2:the note is is right.
Speaker 1:Yeah. Yeah. I mean, a lot of it just depends on like the, like, what is the context of the of the interaction? Like, if you're writing a letter to a senator, you might want to use some letterhead and sign it and and be pretty, you know, deliberate in the word language you use. If you're just sending a quick email introduction to somebody you already know, like, yeah, a couple quick sentences and yeah, if you're posting on x and trying to keep it really really mellow, like lowercase can totally make sense.
Speaker 1:There's a time and a place for every different aesthetic of writing. And Gary Tan saying, hey, you know, like this isn't a hard and fast rule by any means. And Vinod saying, you know, I take this stuff seriously. Maybe we should close out with the the wild story of Nat Friedman, Daniel Gross, NFDG.
Speaker 2:Jason Lemkin breaking it down. How two Silicon Valley legends built a $1,100,000,000 fund for exit in two years then abandoned it all for Meta this week. Nat Friedman, ex GitHub CEO, and Daniel Gross, x y c partner, also sold his AI company to Apple back in the day. Launched NFDG, Nat Freeman, Daniel Gross, in 2023 with 1,100,000,000.0 focused on AI investments. Their crown jewel, Safe Superintelligence, which was co founded by Gross himself, went from 5 to $30,000,000,000 valuation.
Speaker 2:Wow. The portfolio also included 11 Labs, Granola and Basis. What about that? Was their AI grant that was also part of this vehicle? Yeah.
Speaker 2:Yeah. Where they were basically just investing in a ton of different companies, smaller checks in that case.
Speaker 1:Rahul went through it. Of
Speaker 2:And Anti Metal, I think.
Speaker 1:Ton of
Speaker 2:cool companies have gone through it. And Jason says with only 50% deployed, they forexed it 550,000,000 to 2,200,000,000.0 portfolio Incredible. And have quite the advisory board. John Collison and Matt Huang. And Jason says, and then everything changed in
Speaker 1:one This is very aggressive writing style because it's like, I gave you money. You gave me shares in, you know, you can just distribute the shares you invested it. I still have a claim on those. You're not gonna make any more capital calls. Yeah, you abandon it, but like a lot of these companies like they're gonna run who knows if they took board seats.
Speaker 1:If they did, they can still sit on those boards. Like I I If I'm an LP, I'm pretty happy here. I I think. I don't know. What about you?
Speaker 2:Well, I I From from my understanding, it was a lot of it was Mark's money.
Speaker 1:Yeah. Yeah. So so that was
Speaker 2:why it was never
Speaker 1:that Even if even if you had just written like, you know, a a $1,000,000 check into NFDG and you're like, okay, they they they only capital called half of that. Yeah. But I'm up four x on already or I'm up eight x, I guess, on the money that they did deploy. I have shares in a bunch of different companies and they're moving on like, am I really that upset? It feels like they took it pretty seriously while they were there.
Speaker 1:I I don't know. It just doesn't seem like that that dramatic of a situation.
Speaker 2:They've It
Speaker 1:is it is a crazy situation. It's unexpected.
Speaker 2:Yeah. The crazier thing was was DG leaving Safe Super Intelligence, you know, a company that he co founded. Yeah. But it's very possible that he just made more sense for him to go work at the application layer Yep. And work in consumer products and not work on what is very much a, you know, research lab.
Speaker 1:Yeah. Totally. So he breaks down
Speaker 2:The only the only thing here is I don't understand why Meta would actually acquire the fund itself. And I don't know where this exactly was was reported.
Speaker 1:Yeah. I don't know where this was. The LPs can catch up in any
Speaker 2:Wouldn't wouldn't be but maybe it was a part of this whole maybe it was a part of the the structuring of of the actual talent acquisition of getting Nat.
Speaker 1:Yeah. Yeah. It's just like, hey, we don't want anyone to be upset about this crazy deal that's happening. You know? So if you invested and you're, you know, have your money in this particular thing and you think that it's a violation of like, hey, I was expecting you to run this thing for ten years.
Speaker 1:That's kind of the agreement that we had. You're not gonna do that. Well, like, if you make me whole at full full net asset value on, like, what's there to be upset about? And that's all that matters at the end of
Speaker 2:the day.
Speaker 1:Yeah. It's not it's unstructured countries. Is everyone happy?
Speaker 2:At the full Yeah. Nav.
Speaker 1:Not a discount. Not with
Speaker 2:a discount. And Meta gets the talent and FDG and the deal flow without governance headaches. Yep. And Jason says it mirrors what happened with GT leaving initialized for YC.
Speaker 1:And he says the lesson in the age of AI even quadrupling $1,000,000,000 in two years may be less lucrative than being an operator in the revolution itself. And yeah. I mean, you think about what what does it take to produce they produced, I guess, one and a half billion dollars of, you know, new value from this from this from this fund efforts. What does it take to produce $1,000,000,000 of value at Meta? Point 1% market shift.
Speaker 1:You know? Like Yeah. It's it's it's crazy. Dorkash said it well. That like, you know, these that like, if you if you build a great product spend a
Speaker 2:big company. Dollars compute and you can just make it inferencing Yeah. Slightly more efficient.
Speaker 1:1% improvement and boom. Yeah. It's valuable.
Speaker 2:So yeah. Let's end down this post from Blake Robbins himself.
Speaker 1:Lovely.
Speaker 2:He's highlighting an OG post
Speaker 1:Gotta get him this show.
Speaker 2:He says, Paul Graham on having kids. Says, on the other hand, what kind of wimpy ambition do you have if it won't survive having kids? Do you have so little to spare? And while having kids may be warping my present judgment, it hasn't overwritten my memory. I remember perfectly well what it was like before.
Speaker 2:Well enough to miss some things a lot like the ability to take off for some other country at a moment's notice. That was so great. Why did I never do that? See what I did there? The fact is most of the freedom I had before kids I never used.
Speaker 2:I paid for it in loneliness but I never used it. I had plenty of happy times before I had kids. But if I count up happy moments, not just potential happiness but actual happy moments. There are more after kids than before. Now, I practically have it on tap almost any bedtime.
Speaker 1:Love it.
Speaker 2:Very sweet.
Speaker 1:It's emotional.
Speaker 2:I totally agree. I did did leave Also
Speaker 1:terrible example of like wanting to go to another country. You don't need to go to another country. We live in America. Like we have all the best stuff here. There's no need.
Speaker 1:It's like completely irrelevant. It's a terrible example. But it is true that being able to go to California or New York or Florida or Texas or Chicago or Alaska or Hawaii is a benefit.
Speaker 2:It was funny. I did I left my dear friend Ben's house last night. He's my neighbor now, Ben Taft. Yep. Legend.
Speaker 2:And we I we were just hanging out and he doesn't have kids yet. And so I was going home and I was I was sort of laugh I was like laughing to myself. Was like, if you're on a Sunday night no kids, you just like have dinner and then What do you you work for a couple hours or just hang out. It's like, what do you even do? I remember I remember that point but I actually don't remember what I did.
Speaker 2:It must not been very important.
Speaker 1:I really wasn't watching movies.
Speaker 2:Definitely wasn't watching movies.
Speaker 1:Before they have kids. Anyway, thank you so much for tuning in. We will see you tomorrow.
Speaker 2:It is gonna be I'm sure it'll be a wild week. Yeah. And we're excited to cover it. We will see you tomorrow morning.
Speaker 1:Leave us five stars on Apple
Speaker 2:Podcast, Spotify, Apple Wait. Wait. Wait. We have a couple. Yeah.
Speaker 2:Ben popping in. We got an ad read. Oh, we got an ad Koplins. Appreciate all that you do. You gave five stars.
Speaker 2:Look at that. Thank you. Daily listener, as of the last two months, I feel like I'm getting a front row seat to the accelerando and I don't always like what I learned yet I still show up each day because I appreciate folks who call balls and strikes. I'm growing Madison Process Automation in Madison, Wisconsin. It's a series.
Speaker 2:Fantastic name. Love it.
Speaker 1:It's great.
Speaker 2:Because this is the area where I can continue to help folks build value while staying true to who I am in the new economy after my current slash previous fortune 500 employer dithers under the weight of its own inertia in the next year or two. Hello. Thank McKenzie for that, Mark. Yeah. We build bots that save time and money for your small to mid sized business and our stuff works.
Speaker 2:Automate every process we can help. Really fantastic. Madison Process That is a I love the name.
Speaker 1:Yeah. This is like a better iteration of like the process automation company of Madison, Wisconsin. You know? Yeah. Like the browser company Process automation.
Speaker 1:Of New York has been played out. You can't copy that anymore. It's been copied. Don't do it.
Speaker 2:This new meta. This is the new meta. One person can copy it and then you'll have to find a new
Speaker 1:Thanks for rating and Ben.
Speaker 2:And then we have a comment here from Sarhan. If the TBPN UltraDome trademark has a million fans and I'm one of them. If the TBPN UltraDome has 10 fans and I am one of them. If TBPN UltraDome has only one fan then that is me. If TBPN UltraDome has no fans then that means I'm no longer on Earth.
Speaker 2:If the world is against TBPN UltraDome, then I am against the world.
Speaker 1:Well Thank you.
Speaker 2:Thank you, Sarhan. We stand with you and We appreciate it. We love we love doing this, with all of you.
Speaker 1:Yeah. It's a lot of fun.
Speaker 2:We will see you tomorrow morning. Have
Speaker 1:a good day.
Speaker 2:Cheers.
Speaker 1:Bye.