A

All right, everybody, welcome back. Number one podcast in the world. It's July all in episode 280. Freeberg is on a little vacay. We'll leave it at that. And yeah, bestie Brad is here. How you doing, Brad?

B

I'm doing great. Vacay in maybe Idaho or somewhere. J. Cal. Who knows?

A

Who knows? Who knows? It could be anywhere. It could be anywhere. I mean, there's lots of things. He could be in plenty of places. And looks like you are. Yeah. Somewhere in the northeast. I'll leave it at that. You having a little vacay for yourself this week?

B

I'm in my flag room. Very patriotic room here.

A

Very nice.

B

You know where I work on the east coast in the summertime and spent some time in D.C. this week and it's been a great week. Been a Great week. Celebrating America 250.

A

Great. And you're going to be out of there by the second week of August. Yeah. So I have it August 10th through the 30th. I'm good.

B

Exactly. Exactly.

A

Jason.

C

Jason.

A

Oh, absolutely. You don't know the half of it, man. I am on a summer bender. I'm like, where's your vacation, by the way?

B

Where are you? Where are you right now?

A

I am in Paris. I did about eight interviews at the raise conference. They'll be coming out in the all in feed and of course, cackling from the factory. Look at him. You're working in the factory. Chamath Palihapitiya. It's gonna be a hot software summer for Chamath. How's your hot software summer going?

C

It's good. Selling enterprise software is hard, but it's good.

A

Jamal's like, man, I was such a dick to all my CEOs. Hey, the SaaS period.

C

And now, you know, I went to Geneva. Shout out to Mark Benioff. I went to Geneva. He works out of Europe, sees all his European customers, and he had a dinner in Geneva, which I joined. And then me, Jensen, Brad Smith, Anthony Tan from GRAB and a bunch of other folks were put on this UN commission for AI that Mark is the co chairman of. When you see Marc Benioff in action, man, this guy is a master.

B

Holy shit.

A

He is the impresario of impresarios.

C

Yeah. You see how he's built such a ginormous business? It's impressive. It's impressive.

B

What is a commission by the United nations for AI? What is their calling?

C

Open source.

B

No, but, no, I mean, it's like the United nations actually do anything. They actually.

C

It's so funny. Yeah, I mean, Anthropic was there too. One of the co founders, Tom Brown I think was his name.

B

Yeah, that's good.

A

Was the Anthropic guy running around saying it's the end of the world, it's the end of the world?

B

No, no, no.

A

He was very.

B

Tom's awesome. Tom's awesome.

C

In fairness to him, he wears it on his sleeve which is like, hey, we really believe we're doing the right thing.

A

Right.

C

And just trust us. And I think the future is open source for all these countries.

A

Well, we're going to get into that. That's on the docket for sure. But let's start with the IPO update. You know, there's a trillion dollar IPO rush to the exits and you know, this was a big topic of discussion, Brad, at the liquidity Summit last month and we'd never seen a trillion dollar IPO. We had one this year already. SpaceX trading right about where it went public. So it was priced, I guess, to perfection and theoretically gonna see two more. Brad has the inside information, so I'll try to get it out of him. OpenAI and Anthropic are slated to go out. Let's just go quickly over what happened with SpaceX. It ran up to $200 a share. It's been down a bit. It's at $150 a share, as I said, that's right at the IPO price. So it's trading at that $2 trillion market cap, currently seventh largest company in the world. And Anthropic confidentially filed on June 1st.

B

I don't know why they call this

A

confidential filing when it immediately comes out, but I guess the information is confidential. Polymarket says 65% chance Anthropic's IPO will happen this year on light volume, 360K. And two weeks ago, Gavin Baker, another bestie, said he thinks they're going to end 2026 with over $100 billion in revenue and very profitable. He said a couple of us guests on the program that he thinks it would trade at 3 trillion right now if it went public. Chamath, you made a great call on the pod. You said, hey, good idea for Elon to get out first. What are the chances here, Chamath, that these other two get out this year or maybe in like, you know, say nine months in the, in the first quarter of next year, we'll start there.

C

Well, I think that these are all great businesses. I think the question is what is the market clearing price? And I think that's more of a function of how much appetite the markets have to absorb new issues and at what scale. That's number one. And I think that's mostly determined by price. So I think Anthropic and OpenAI are probably in two different places. The last time we heard from OpenAI, their cash burn was still quite high just because of the diffuse nature of their business and more reliance on consumer than enterprise. I think Brad mentioned it in one of the pods that Anthropic may actually be accidentally profitable. I think he said something like that.

A

Yeah.

C

Let me tell you something really interesting. I sat down with my CTO today and I said, how are we doing on token spend? And he said the most incredible thing. He said, write down our token costs are doubling every 45 days.

A

Okay.

C

And I was like, ugh. And he said, yeah. And I said, well, what is the downstream productivity? And he said, maybe 5% max.

A

Okay.

C

And I said, okay, so my costs are doubling every 45 days. My upside is essentially flat. And he said, basically. And I said, well, explain why that is. And he said, honestly, what we're finding out is that you need to use a lot more tokens to get to this next iteration of improvement because we've effectively already asymptoted. And I said, so what should we do? And he said, honestly, we have to figure this out. And so we're going to take a step back and try to figure out what to do. I don't know how many other companies will actually go through this reckoning now, but the point is everybody in the next three or four years will for sure go through it. So I suspect that if you can get out now, you should get out now before all of that starts to seep into the water table. Because I think that's probably what allows you to get out at a huge price and raise a huge amount of money.

A

All right, Brad, you are well invested and well known for being invested in these two next IPOs, so you probably have some good insights since you talk to them on a regular basis. Chances they get out in the next six to nine months, both of them, you'd say 100% chance. Unless there's some outside event, blockade of Taiwan, some black swan event that we're not anticipating. What do you think the chances are they're public when we're sitting here and I'm skiing in Hokkaido?

B

Yeah, I think it's very high. But let me first say the SpaceX IPO, where we were also investors and we also bought in the ipo. I mean, it was textbook. It was a hugely successful IPO. They raised $75 billion at 1.75 trillion. Okay, so it went out below where we are today. It's up 25%, you know, and let's call it on 35 billion of forward revenue. So if you think about that revenue multiple, it's trading at 2 trillion on roughly 35 billion of forward revenue. It's an incredible achievement. I think it was textbook. I think Anthropic and OpenAI were watching very closely because, frankly, we had not had an IPO of that size. And to Elon's credit and to the team's credit, Brett and Gwen, they really pioneered some really smart and interesting things as part of that ipo. So, you know, you heard from Gavin Anthropics rumored to be, you know, trending over 100 billion in revenue compared to the 35. Right. If they exit the year at 100, that means their gap revenue next year could be well over 100. So based on the SpaceX success, I think it would be a blockbuster IPO. And I think SpaceX has shown them the way on things like the total raise, pricing, liquidity, inclusion into the indexes, how to do the lockup. Like, I think they've gone to school.

A

It was a staged release. In terms of getting out of the lockup, it has to hit certain milestones, and some of those are time.

B

Early inclusion in the index raised $75 billion.

A

Like, you know, early inclusion in the index. Let me have you unpack that for a second. Because people said, hey, may, maybe this feels unfair that they should be forced to buy it. What's your take on that? Is that just like haters gonna hate, or is there something to that?

B

I think there was legitimate concern.

D

Right.

A

This would never be legitimate concern.

C

Yeah.

B

The legitimate concern is that a company that had not been through the process of being vetted post ipo, there's a lot of volatility. You've seen that chart, Jason.

A

Sure.

B

That the peak to trough drawdown in the six months post IPO is 50%. We've seen a pretty big drawdown here from the peak to trough as well. So you don't want to jam it into an index at the peak and then have a 30% drawdown on top of people, which often happens in IPOs, because people get excited, it runs ahead of itself. But they didn't do that here. There was fear that that was going to happen. So both the exchanges and the indexes, they looked at this and they made some modifications because the other side of the argument is it's so damn big and important important that it needs to be part of the index. Right, Right. And so the reason the rules had previously existed is because most companies coming public were younger earlier, less tested, less revenues, less profitable. All the things weren't as important in the overall scheme of things. So I think that they pioneered some really smart things. It's worked well, it's traded well. And so I think that that provides a bit of a blueprint for Anthropic. But just in terms of the enthusiasm is an altimeter, is a fidelity, is a T. Rowe an enthusiastic buyer of Anthropic. Based upon the things we know today around profitability and model improvement and revenue growth, et cetera, yes, everybody would be pig piling in. Everybody would be trying to get into the top of the book. And the last I heard again rumored that they would like to get out this year on OpenAI. Everybody knows that anthropic kind of passed OpenAI on a revenue trajectory. But I will tell you, OpenAI has kind of got its swagger and mojo back. It's coming out just today with a whole new set of models. We know GPT6. There's a lot of talk of that coming out within the next 30 days. A whole new generation of models. I think their revenue has really ticked back up. The most recent kind of rumors I see on Twitter is around $70 billion stacks at the year. So just as a reminder, 70 billion may not be over 100 billion that's rumored and anthropic, but it's still twice, you know, where, where the revenue of SpaceX is at. So can they get out at over a trillion on that type of revenue growth? Being one of the two frontier premier labs, I think the answer to that is yes. I'm not sure. There's a huge race between the two of them to get out first. I think they'll both go out when it's, when it's time. I think OpenAI has a little bit more complexity just associated with the corporate restructuring that they have to go through, et cetera. So I would be surprised if they go out before Anthropic. But the fact of the matter is, I don't know. But today, as I sit here today, Altimeter would be a buyer at scale and at size in both of those

A

IPOs at 3 trillion. Are you a buyer or are you, hey, it's obviously going to trade up and down and I. There's no rush because you, I think were the one who said on the pod or Might have been at Liquidity Live when I asked you point blank, hey, should retail get involved in SpaceX? What's your thoughts?

B

Correct.

A

And you were like, hey, listen, it's a 4% float, 5% float, it's going to trade up and down. But you know, a year from now it might be trading at the same basic price. It's going to be priced not to perfection, which it seems to have been, but I think your position was it's going to be priced reasonably. There'll be plenty of time to get in. You don't have to like, you know, panic about getting your shares.

B

Yeah, yeah. Once a company's valued at over a trillion dollars, like the get rich quick schemes are over. Right? Like that. You and I share a deep passion, Jason. We gotta get retail investors, we gotta get the citizens of the United States in on these value creating opportunities earlier. Right. The accredited investor laws are insane that we have in this country and keeps people from participating in these things. But it is what it is, right? So they're coming public at over a trillion dollars. I still think there's a lot of meat on the bone on SpaceX, on Anthropic, on OpenAI. But you're not going to have things that are. I don't expect that they're going to be priced in a way where you're going to get a 50 to 100% durable bounce out of the IPOs. If so, that would mean they were probably mispriced right into the ipo. But I do think that these things can be compounders. They're going to compound at the rate they compound revenue. And I think all of these companies are going to compound revenue at well over 30% for the next many years

A

and 30% a year for just so people understand that this is high growth in public markets on very large revenue numbers already, you know, growing 30% when you have 100 million revenues, one thing growing 30%, you know, when you got 10 billion or 100 billion, you know, this is, this becomes a different task. So let's talk a little bit about these two companies, Chamath and what the public's going to perceive them as. ChatGPT seemed to be the public brand, the consumer brand for large language models. It's the AI for people who are doing their homework or mom and dad are trying to fix the dishwasher, whatever. And then Claude took the lane of hey, we're going to be the one for corporate. And it did seem like OpenAI got very distracted with Sora and Disney relationship. We're going to make a puck with Johnny. I've everything consumer. Then they realize, oh wow, the revenue seems to be an enterprise first. Is that going to wind up being the big mistake when we look at it? They kind of gave the Google position, the high growth position to Claude and Anthropic and they took the Yahoo position. Or do you think they'll catch up on the enterprise or maybe they should just go back to trying to be the consumer version. How are these going to be positioned a year from now? How's the public going to look at them?

C

The problem with enterprise revenue is at some point the person that's spending it has to see an ROI.

A

I asked Fable 5 High Anthropic's new model.

C

Yeah, Anthropic's new model. I first asked it, what is the lift of the S&P 500 earnings per share growth since 2024 from AI? And they answered, oh, it's 50%. So then I looked through it and I said, well, no, you're including the money that Nvidia makes from selling chips. So I said, okay. I asked a different question, which is then what was the EPS growth of the S&P493? And the answer was 9%. And I said, okay, well that's different. And I said, unpack that. And the overwhelming majority of that was from pricing power sitting on top of inflation. And then the other 3% was from buybacks. And so the answer as far as all publicly available data was that the actual ROI was somewhere between 0 and 2%. So I don't know. I mean, I think that enterprise looks really good. The problem is that very smart investors like Brad and Gavin and others at some point will start asking companies, what's your roi? What's the actual EPS lift? And if the answer is, well, I don't really know or I'm not sure, and you don't necessarily have the pricing power to continue to raise prices. Enterprise is probably a little bit more brittle because there are fewer buyers and they're more demanding. Consumer, on the other hand, then all of a sudden becomes an incredible safe harbor because you have tens of millions of buyers. And having those two orders of magnitude more buyers at a much smaller price point inoculates you from the vicissitudes of an ROI discussion. So it all really depends on what the actual ROI is of this money being spent. I think that we're in the phase of just being astonished, as Brad said, about the scale of the revenue growth. But at some point you'd have to be an idiot not to ask, well, who is paying you this and can they sustain paying it to you? I just don't know what the answer to that question is. And at some point it may not be now. At some point people will have to answer that question.

A

And interesting.

C

Million dollars a year on tokens. And that million dollars a year is doubling and tripling and quadrupling. At some point you're going to have to show an ROI that's above the risk free rate of return. Otherwise you're going to have some angry investors on your hands.

A

And our discussion here for the last couple of weeks on the pod has centered around that and the industry has responded on the place where all the CTO, CEOs and capital allocators hang out, which is X.com, formerly known as Twitter. Here's Praveen, the CTO of Uber. And so when you ask like how are they getting, how are they getting the ROI out of this? People are now bringing that conversation front and center and they're explaining it on X. And he talked, remember Uber was also the one that ran through all their tokens in the first quarter. So then on the other side of the business, which is legal, operations, marketing, customer support, HR and procurement, which he lists here, he says in this, you know, today 99% of our engineers use AI tools. Okay, great, right. It's everybody's, you know, doing vibe coding and has coding assistance. More than 70% of pull requests are attributed to local or cloud agents. Our engineers have built 2,500 agentic skills. So how are we bringing agentic AI beyond engineering? And what they've decided to do is essentially he talks about these agentic pods and this to me seems directionally how this should be done, which is you find engineers and you as we talked about forward deployed engineers, fancy way of saying put an engineer, put them into departments and have them work with the department heads who understand systems thinking, how their process is done. And he, he says it's making basically long and short of it is they're making massive, massive progress on the operational side of the business. So Brad, you're pretty familiar with Uber and have been a long supporter of that. This is a company that knows how to deploy technology pretty well and they're an operations machine run by an operations machine.

C

Dara, they should report the EPS gains attributable to AI.

A

Yeah, well, I mean this first step seems like they're really being thoughtful about this. First, hey, this token spend got out of control with the developers. We're going to need to pause this and look at it. And then second, here's how it's going to lower costs and create more efficiency. So, Brad, let's talk about that side of it. Not just token maxing with the developers hitting the slot machine of like, okay, let's see if this pull request and

B

let's see if this produces the right

A

code or not to these departments in a more strategic way. It's not just the person who works in hr, you know, using Claude code or perplexity or whatever and trying to vibe code something. This is, hey, we're sending engineering in to work with your top systems architect and we're going to, you know, try to find that roi. Yeah.

B

Yes. You know, first I would say Chamath is right. The only question is on what time frame. There's no doubt that there is a lot of money being spent today that is in the experimental bucket. Right where I think there probably isn't direct roi. Chamath, to your point, but I think we're so early, nobody cares. I think we're so early in terms of enterprise adoption. Remember, the total addressable market here is every single small, medium large company on the planet. And so we've never seen revenue growth like this because we've never seen a TAM like this. And if you look at the distribution of revenues across these businesses, it's not like it's concentrated with four or five customers. There are millions of customers independently, economically making the decision that is rational for them every day that it makes sense, like Praveen at Uber. And of course they're trying to find things on both right now, mostly the cost side, cost takeouts to justify the investments that they're making in tokens. But I think we're on the verge of, of breakthroughs in intelligence that's going to dramatically change the revenue side of the equation for a lot of these businesses. Breakthroughs in life sciences, breakthroughs in product innovation, et cetera, where they could not divorce themselves from this even if they wanted to. For example, Jensen Huang has talked many times that all of his design work, all of his design work now at Nvidia is using AI to design the next generation chip. The machine is building the machine. So you can't get rid of that even if you wanted to. And tiny intelligence advantages at the frontier where he sits are required. Like there's no way. I don't think that Jensen is going to use anything but the best models that he can to build out those capabilities. So I just think that we're not going to see that in the next few years, you're going to see it under the hood, of course. And. But that occurred at Snowflake. There was tons of optimization that occurred at Snowflake, but their revenue continued unabated. Their revenue growth continued unabated because they further penetrate, penetrated use cases, further penetrated the enterprise. So let me be provocative here. If these guys end the year over 100 billion, I think that they're on a revenue trajectory that they could 3-5x again next year. We've never seen anything like this.

A

You're saying 100 to 300? 100, I'm saying.

B

And Jason, like you and I have talked about this, our minds were blown. If a company could go from 100 million to 300 million, we're talking from 100 billion to 300 billion, 200 billion of incremental revenue is incomprehensible in the history of Silicon Valley. Okay. And just the fact that we're even.

C

In the history of the world.

B

Yeah, in the history of the world. So the fact that we're even talking anywhere close to this tells us something different is going on here. I think the thing that's different is that intelligence is the largest TAM we've ever seen in the history of the world. These guys are penetrating it. So, yes, the super sophisticated companies, the 8090 and Chamath, are helping optimize their token spend that are early adopters. 100% that's occurring, but it's not really changing the trajectory that the frontier laps are on. Yeah.

A

And one of the interesting things about this technology that's really unique, we talk about intelligence on demand. When you would make a piece of software or you had some technological innovation, it would typically accrue to, I don't know, one group of people in an organization, you know, maybe two groups of people. Right. Excel comes out. Okay.

B

Yeah.

A

The accounting department's having a field day with it, but it's not really affecting human resources or marketing. Okay. Yeah. Maybe it trickles down eventually. Every single person in every single organization is playing with these tools. So if everybody's playing with it, everybody's trying to apply it all at the same time. It's kind of like, you know, you got a thousand person organization. People are spending 200amonth. Okay. Yeah. Chamath, they double it every, you know, X number of months. Okay. Yeah. Now they're spending $400 a month per person. Okay. They're spending $5,000. Well, if the average salary is 100, 150K at this organization, it's only an incremental 3, 4, 5% on top of their salary. So the way I look at it is did it make that person 3, 4, 5 times more effective at their job? And I think the answer is yes. So that's why there's so much token maxing going on. And it's also a bottom up type product. You can just get into this product for 20 bucks a month. And you know, no CIO or CTO is like, oh no, you can't spend 20 bucks a month on your corporate card for this technology. So when a bottom up technology hits everybody at the same time, that's what would explain this revenue ramp that we're all having a hard time adjusting to. It applies to every single person. Like who is it impacted by the technology? Is my question to you Chamath, like in what organization you're working with, with 8090 is there a department that says yeah, the intelligence on demand, not for us, we don't need it.

C

Well, it's less, it's less about being dismissive that way. It's more that regulators and other people won't necessarily allow to use it the way you want.

A

Okay, so finance hipaa. Yeah, there's HR data. You're not allowed to put that to work just yet. What I'm finding is once you start using this and getting some gains, it's very addictive. And we were sitting here, Brad, I don't know, maybe in January and I got that open claw bug and then I started playing with this Hermes agent which is not a French company by the way, they just use French names. It's nouveau research or whatever it is. I started playing with that. It's a very peculiar piece of software, but it's a very open piece of software. So I went to open router, I got my own keys, I've been playing with glm. Then I talked a little bit about bit sensor on the program known as tao dollar sign tao. It's a, it's a crypto project. Somebody who is creating a subnet that is putting GLM 5.2 and other models available at really cheap prices. So I all of a sudden experienced because they gave me an API key having my token costs go down 95% and when you have unlimited tokens as an exercise which is going to come to everybody eventually everybody's going to learn how to drop the price by 95% and it's going to happen as well. Because people like Grok with inference. This is all inference, right? This is what people are using. They're Using inference to do this. Well, inference is being impacted like three or four different ways. The software is getting better open source at the same time. You're going to have distributed networks like Tao and you're going to have better, you know, chipsets from Groq and Cerebras, et cetera. All that's happening at the same time. Once I got down to 95% cheaper, I started setting my agents instead of doing daily runs to doing hourly runs. Then I took my agents from doing one task and I broke them up into three agents and have them doing three different things on the hour. And when you start doing hourly tasks and then you wake up in the morning and like 14 jobs have been done, you're like, wait a second, this is completely different. As one example I have, it has all the all in episodes, all the this week in startups episodes. And we set these cron jobs to go find what the new trends are in technology. I have a trend spotting agent running every hour informing me of the top three or four trends. And I just give it words. Really does change your thinking. When costs go down, what do you think tokens are going to cost, Brad? And you know, next year?

B

Yeah, we've seen, we've seen 90% reductions in the price of tokens for each of the last two and a half years. We've talked a lot about Jevons Paradox, which I think you're referencing here, which is you're going to use a hell of a lot more when it happens. I think the central debate right now in AI is the one that Chamath keeps pointing us back in the direction of, which is for 18 months since the deep seek moment, right when the deep seek moment happened, the markets fell 40%. And there was a reason for that. Many started arguing that the frontier models were screwed, that open source was going to kill them, that they were closing the intelligence gap, that model routing was going to make it easier and easier to route these tasks to cheap tokens. But despite all of those arguments, and now we're 18 months into this and I had this back and forth with Gurley a lot. I love open source. I want all the competition in the world. Let's be very clear. But despite all of those arguments, the facts on the field are just the opposite. The share of economic value, right? There's this quote, there's this tweet this week from Jesse Zhang that we ought to pull up here. The economic value, the share of wallet, is actually increasing to the frontier labs, while the share of tokens these Commodity tokens is obviously going up, you know, to the other guys. And I had a little back and forth this week with Nikesh on this, kind of trying to suss out why is that the case. Right? Because what people would have thought is, oh, cheaper, pretty damn good. 90% is good enough to do all these tasks that you're talking about, Jason. So nobody's going to use the anthropics and the open AIs of the world. But despite that, it looks like their share of wallet has gone up.

C

I think it's not that. I think it's more that when the iPhone was a novelty, everybody would keep upgrading because you expected that the new price was worth it. And then at some point, there's a moment you can debate when it happened, where people said, you know what, I'm just going to keep the old phone because it's good enough. And I just don't see the difference. And I think that there's going to be a moment like that. Like when I use Fable 5, the problem is that it's nerfed on a bunch of things that I would normally research. You know, I was with somebody this weekend and he was telling me about some health thing and I put it into Fable and it's like, won't answer you. And I'm like, okay. So I think that everybody will get to a point, they'll get to it at different times where they just say, you know what? Like, it shouldn't really matter what model I'm using. If I get an answer that I think is reasonable and I can kind of go about my day separately, I think when the corporate CFO gets involved, that'll be an entirely different conversation altogether. I think that what I can tell you after this UN commission that I joined with Benioff and Jensen and Brad Smith, there is not a single country in the world that is not trying to figure out its own sovereign AI strategy. And I don't think they believe using a closed source American model is the answer. And so I think we have to keep in mind there's trends. One is just geographic penetration of humans, and there are still many, many, many more people that don't use it than do, which is an upside and an opportunity for everybody. And then the second is there is going to be the experimentation, as you said, that needs to transition to ongoing, repeatable usage. And then the third is that all of that then needs to plug into the existing regulatory infrastructure that we use as societies to run the world. And I think when you put all of these Things together. It's not clear to me who wins, except that you're going to have a lot of diversity of choice. Certain countries, I can tell you after this week, have no desire to subjugate themselves to any technical risk. And so they're willing to spend the money to have their own. Now we can argue and debate whether that country has any chance, but they would rather take an open source model like Nvidia's actually and stand up their own stack soup to nuts for their own people and their own companies inside of their own country. And if the models are 99% as good or 95% as good, there's going to be a claim that some countries make which is it's just good enough.

B

That's the question. That's the question.

C

And then separately there are companies who will not have the earnings growth to justify this without going on some long protracted carve out of cost. And not most companies, you know this, they just don't do it. They don't have the nerve to do it. They're not capable of it. You know, you wrote that famous essay to Zuck. He was pressured into finally doing it. Absent a very few companies, most people just allow the problems to compound. So I just don't see a world where when you get clobbered over the head, you don't look at other ways of just displacing costs. And if it's like Coke, Pepsi kind of a thing and Pepsi is 11000 the cost of Coke, I don't know, I just think it's a, it's a risk that I think has to be managed in the perception of the market participants and the underwriters.

A

To add to that, Brad, just open source is very hard to implement when compared to just firing up Claude and having Claude already approved in your organization. The number of steps it took me in order to, and I'm pretty familiar with technology, it took me hours to configure my new setup to get onto this bittensor network to get openrouter going. And to your point, Chamath, it does dynamically route now. So I'm dynamically routing and I'm, you know, GLM 5.2 and then if I fall back to Claude, but which quad am I going to fall back to? And here's another piece of evidence to your point Chamath, there are some organizations that just are incapable of this. They don't have the, the team that, you know, does this naturally. We just talked about the CTO of Uber. Now let's talk about Another cto, Andy Fang, is the CTO of Doordash Shout out to Stanley. And so he, as you can see here in this tweet, a lot of people listening to all in over the last couple of weeks are coming out and as I said, explaining what they're doing to address this exact issue. He says, hey, with our internal coding benchmarks, we're able to confidently introduce open weight models into our AI code review without degrading code quality. Have the Frontier model Fable from Anthropic to do the hardest work, delegate lower level work to Kimi 2.6 and they are now releasing their benchmarks. So another group releasing their benchmarks and saying, hey, we know this is an issue. The CTO has been charged. To your point, Chamath, again, CFO says, hey, make sure this is profitable. We get the roi. They put that on the cto. Here's another CTO from another leading tech organization that knows how to implement this.

C

Yeah, the really interesting thing we have to forecast right now is what happens in an earnings miss. And I think what happens in a, in a moment where for whatever reason, maybe there's just an externality, that there are a series of earnings misses, where are people going to look? And I just think that people find it very difficult to lay off other people. I think it's much, much easier to cut other costs. And I think that the more successful these companies get in a very quick amount of time without really proving the roi. I just think the bigger the risk is. It's complicated. The game on the field when you're working with these enterprises and just trying to explain it to them is I think that they're getting smarter quickly is what I would say.

B

I would just say I think that Chamath Sack's absolutely right about the sovereign stacks that are going to get built around the world. This is not either or we are going to have open source and we are going to have Frontier Intelligence. The preponderance of the tokens today are already shifting toward cheaper, lower lagging models out of OpenAI or lagging models out of Anthropic or the other Frontier Labs that are out there. Obviously we talk about those two. SpaceX has released an incredible model, you know, in the last two days. Meta's out with, you know, a terrific model today. So Gemini is still in the hunt. So there are lots of choice.

C

The Meta thing was really intense because I thought, okay, you know, we talked about the game theory which was Mark should scorch the earth with open source. I think they flubbed that play. But then I think he is now said he's going to create a price war. And so if you look at the tweet or the quote, there was a post. Jason. I don't know, Nick, if you can find it, I got it. Announcing it, he was basically like, hey guys, I'm going to give you the same quality at like 1/100th of the cost. Now, again, there's a lot between here and there. There's a lot of enterprise distribution that's required. And you know, there's been a couple of misfires before, but I thought it was interesting that the vector of challenge was on cost.

A

Yeah, here's the Mark Zuckerberg, just so I queue it up for you there, Brad. And he's inkd that was his old handle back when he was in college. F I N K D. And he's done more tweets today over this Muse Spark announcement than he's done in his history. So he's getting into the X.com conversation quote. Today we're releasing Newspark 1.1, a strong agentic encoding model at a very low price. It's available through our new META model API and in Meta AI. So he's coming out saying, hey, we got the strongest agentic tool here, please come use it. He also wants to have his own essentially, you know, he wants to jump into not the hosting space, but he wants to provide tokens as well.

B

So again, I think we're going to have a tremendous amount of selection. The competition is great for America, but I think if you look at the things people are doing. Let me give you an example. The premium workload. Jason, you talked about summarizing a document may take 20,000 cheap tokens to do. Of course, shoot that to a lagging model or an open source model. But if you're talking about replacing a software engineer for two hours, that may take 2 million expensive tokens. And the consequence of using something that's 95% as good is really high, right? Because you have a long running task and if the task breaks early or it breaks in the middle or breaks at the end, there's a huge cost to that.

A

So you still the tokens, right? You. And back to this analogy. And they're pulling the slot machine and

B

you lose and the time and the compute. So if an AI agent is replacing a $200 an hour consultant, right? Take that as an example. So three consulting firms, they're competing, they need the smartest consultant. They're charging 200 bucks an hour. The difference between spending 3 bucks on a cheap model or 15 bucks on an expensive model to replace a $200 an hour consultant, it's just irrelevant. That inference cost difference is irrelevant if you're getting something that's bulletproof for 15 bucks. And so I think that's what we're seeing play out. The best evidence for all of this is just revenue growth.

A

Right.

B

We can sit here and speculate all day long as to revenue not from

A

anthropic and opening I but from their customers.

B

I know, I'm talking about what is anthropics revenue growth compared to OpenAI compared to the open source models, compared to millions of independent actors are choosing every single day. The open source companies are growing. Right, but they're growing, selling something that is really, really cheap. And there's a, there's room in every single market for premium products, for mid tier products and for commodity products. And I think we see a lot of this token growth. People are speculating that the intelligence gap between that commodity stuff and the frontier stuff is going to collapse to the point that people won't pay for the frontier stuff. There is no evidence of that on the field today. It may develop over the course of next couple years, but it's not on the field today.

A

Yeah, and just to give people an idea, we keep mentioning what sovereigns are doing to give you the specifics on that. The UAE very famously has their own Abu Dhabi Technology Innovation Institute Shipping falcon. You probably have heard about that. The Saudis have humane and they're doing their own models that are Arabic LLMs. And then this week Japan is investing $6 billion in a consortium. It's called the Neoterra. Neoterra N E O T R A consortium. And they're doing that and skipping ahead to physical AI, that is robotics. Okay, joining the conversation here, the one, the only Saxypoo Sax bringing you into the discussion. Talking a little bit here about the debate that we started here on the podcast, getting ROI from tokens. Where are the tokens going to accrue to open source versus the frontier models? Bunch of ctos chiming in on X this week, in the last couple days, in fact, talking about how they're managing intelligent routing first to open source models, then falling back to Fable and the frontier models. How do you think this is playing out? And if you're an investor in the space, how do you think about the frontier models and their growth when you have CFOs coming in and saying, hey, justify this cost and do you have a cheaper solution and what Is that cheaper solution?

D

Well, look, I think that enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that that would be more efficient. And they are seeing their compute costs or their token costs just skyrocketing right now. So everyone's trying to figure out how do we put the brakes on this or at least control it, make sure we're getting roi. You also have the AI sovereignty issue that we discussed last week that Alex Karp talked about, where they're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. So there's no question that enterprises would like to diversify. They would like to get off of these frontier models when they can. The problem is, I think in most cases they don't have the technical ability to do it. I mean, Coinbase figured out how to do it, Doordash figured out how to do it, which is to say they built a token routing system, a layer of middleware that allows them to sort of send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that. So I think this is a case of the spirit is willing, but the flesh is weak. I mean, they are willing, they would like to diversify off of these close models, but they are unable to do it. And so this is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing. Now, I don't think that means that usage is decreasing. I think usage is skyrocketing in both these categories. It also may be the case that because the whole point of using an open model is you just pay for the compute cost, you don't have to pay a lab. So it may be the case that it's hard to measure that usage in terms of spending, but nonetheless, I mean, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data. Like Brad's saying, the revenue is skyrocketing. And I think the most you can say is that enterprises that are technically capable would like to gravitate towards hybrid architectures, but at the same time, it takes technical expertise and it is just phenomenally convenient, whether you're a developer or an enterprise, just to go with the frontier labs, and that's why their revenue is skyrocketing.

A

It is the easiest choice. It's the most refined. Yeah. Most refined products.

D

Yeah. And there's one other thing here as well, and this was discussed in a really interesting blog post by the founder of Decagon, which is enabling AI powered customer support for enterprises. And what the founder said is, look, open models are great when you know exactly what you're trying to do, why they're smaller, cheaper models. But you have to do post training, you have to have the data set and you have to know exactly what you're going to use them for.

B

Totally.

D

But if you don't know exactly what you're going to use them for, you want the most powerful general intelligence that you can get. Right. So what he said is that for mature use cases, yeah, you want to go open, but for immature use cases, which are all the new things people are discovering right now, you're just going to want to use the most capable general model that you can. And then once you figure out what the workflow is and what the workload is going to be and exactly what you're trying to accomplish, then you can use a small, highly trained model. And I think he said something optimize

A

in the post to get the gains for customer support.

D

Your model doesn't need to know physics, for example, and so you don't need that capability. But enterprises are still trying to figure out exactly what all these workflows are going to do. So I think that's another factor, which is to say that it depends on the use case and how mature that use case is. And you really want the most powerful frontier models that you can at the discovery of all the potential for the technology.

B

Yeah.

D

And then we just wrap up then there's one other interesting post that I saw was by Nikesh Arora who also said that what he's seeing is, yeah, enterprises would like to diversify. They would like what he called model fungibility. They would love to commoditize these models. Right. And just hot swap them.

A

Yeah, Headless is the term being used, right?

D

Yeah, yeah, that'd be ideal for enterprises as you sort of swap out the model for the cheapest one that gets your task done. But then what do you do about memory? What do you do about context? What do you do about history? And what he said is no one's really figured out a way to abstract that stuff away from the model yet. And again, this goes to the technical challenge of creating this middleware layer that would do the most efficient token routing. It's. Well, you know, it doesn't work unless you can make all of that context and memory and history fully portable to the cheaper model that you want to basically hot swap to, which means you

A

have to have some technical ability. Sax and the people with technical ability, the tip of the spear, the 1% of people deploying this technology are starting to figure that out. Here's another proof point and some more evidence. This is Ali, the founder of Databricks, I think a company you're very familiar with, Brad, and what he realized when you start taking apart the harness and you start looking at the skills, you look at the memory and all this accoutrement that you put around your tasks. He said, we find that the same model, using the same model not using open source versus OpenAI or Claude, we found that for the same model, the choice of harness can significantly save costs by about 2x. So they found with GLM5.2 that this performs extremely well and that their tasks literally are getting cut in half using the same model but with a different harness. And that rings true to me. Once you've built one of these agents, and I was talking about one earlier, I'm running every hour on the hour to find trends. I asked it to please start optimizing it and when I optimized it, it was like 80% less token use. And now in these apps you can go to your analytics stacks and you can actually see your token use by hour, by job and across which models you're using. This is really sophisticated and hard for a consumer to do of the technology, but it's definitely a trend.

D

So with that harness that he was using, is that something they built in house?

B

Yes, I think.

A

Yeah.

D

Okay, got it. So they basically created their own application,

A

Omnigent in front of these and that it can multiplex different harnesses and models for different tasks. So he's not only routing to the right LLM, he's routing to the right harness. And people don't even know what skills are. People don't even know what the memory is at this point. They're. That's all abstracted into the Claude product or the Perplexity product, et cetera.

B

Yeah, there'll be a massive business. There already is all these inference clouds, you know, the base 10s of the world, the fireworks of the world. Every single hyperscaler in the world is going to do this. They're all going to provide, you know, tools that allow you to achieve some level of model fungibility. The big question is, at the end of the day, we're going to have it's going to be very heterogeneous. But what is the mix between these two? I again think the TAM is so damn big here that you're going to have huge open source use cases, sovereign use cases, et cetera. You're going to have plenty of room for the Frontier Labs. Let me throw something out I'd like to get your opinion on. To a certain extent there's this implied assumption in the world that there's going to be this convergence of intelligence. If you look at the benchmarks today, seems like everybody on the benchmarks, they are converging. But yet if you look at the revenue distribution, it's not converging at all. One of the questions I have, will the model router itself be smart enough to overcome David, the inherent intelligence advantages of the generalized of the Frontier Labs? The non consensus argument might be that intelligence is not converging at all. That superintelligence becomes fully self, you know, recursive. And as it becomes recursive, you actually extend the lead because the smarter your model gets, the more revenue you get, the more compute you can buy. The more compute you can buy, the better the model is that you can build. So I think there's a chance that over the course of the next two to three years, as we take on much more complex agentic tasks, that the distance between the Frontier and everybody else doesn't converge. It actually extends. We shall see. But I think there's this implicit assumption in all the arguments today that that everything's converging. I'm not, I'm not sure that we've really run that to ground.

A

Another piece of evidence to put in to this mix. I interviewed Anton, the CEO of Lovable. Lovable is an app that or as a service that allows you to vibe code, you know, different pieces of software. They've got a really interesting take on that. They went from 100 to 600 million in revenue over the last two years. They went from 0 to 350 in the first two years of the company. Product's been out, I think roughly for like 30 months. Then I also spoke to the CEO of ElevenLabs, Matti and I asked both of them point blank, are you guys, you know, your major customers of, you know, the, the Frontier models? Yes. They're spending tens of millions of dollars with those Frontier models. I asked them, hey, are you concerned about data leakage and them competing, you know, releasing competing products? Eleven Labs is doing voice and obviously Claude code, you know, an obvious competitor, lovable. Are you going to make your own models Both of them said that they're working essentially on their own models. Those are major customers of the Frontier Labs who they want to get off of the Frontier models and they want to have their own proprietary model. The ability to create verticalized models is getting easier and easier every six months or so. So that's going to be another trend to look for is these verticalized models for voice, verticalized models for building code. And we're going to see people stop using the Frontier Labs. And these are major, major eight and nine figure customers. I think they're going to just run for the hills and only use the Frontier models that they're using.

B

The counterpoint, there is 11 labs. I love Matty. Do you really think he's going to use an inferior model? He's got to have the best voice agent in the world. And if the best voice agent in the world is, is given to him by using the Frontier Labs, can he afford in a competitive marketplace to say, I'm going to use the cheaper version, the thing that I built for myself, even though it's not as good as the other thing. If he builds something better, I totally agree with you.

A

That is what he believes he's doing. He believes he's making a better version.

B

Yeah. So that's the question that I just, you know, put on the table. Whether or not you're going to see this convergence, whether it in fact is that easy. I don't think it's that easy, but we shall see.

A

Okay.

D

It may come down to how discreet and sort of predictive the use is. So like Decagon, the customer support AI company, they said that 90% of their usage now is being sent to open models. But those are open models that they've had the opportunity to post, train on and do a huge amount of customization based on all of their learnings and all of the data that they've gotten. So again, it comes back to maturity of the use case. If you know exactly what you're trying to do, it's probably easier. But you know, I don't think that's most enterprises though. And maybe there's going to be a pattern where you know all the immature use cases, which is to say all the things you're figuring out, you're just going to want to use the most powerful model possible. And then once it gets really well defined, maybe you start moving some of those workloads to post trained open models.

A

Purpose built models.

D

Yeah, yeah, purpose built. Yeah. It could be something like that.

A

That's kind of what's Happening with the people who are the tip of the spear. They're working on the routing of the jobs, they're working on the harness and they want to be independent and have that AI sovereignty we talked about last week. Speaking.

D

Well, but just to take on Brad's point for a second, I actually agree with what I think you're saying. Brad, which is the market today seems to be pushing towards duopoly or it has become a duopoly, certainly measured in terms of revenue. If you were to look at market share based on token revenue, there's only two companies making meaningful revenue. Anthropic's at what, 60 something billion ARR. OpenAI at 40 something billion ARR. I don't know if anybody else even registers. And it may be the case that the more tokens that Anthropic and OpenAI produce, I mean we've got to remember every token that they're serving up is on behalf of a use case. Right. So they themselves are learning from that. That and they're getting better at then providing whatever offering that is. And so who knows, the gap may be growing. A year ago it seemed like we had five major labs. Now it seems like there's a top two and then everybody else. So I mean, look, I could see AI easily becoming another tech market that becomes a duopoly, which by the way is the trend. The historical trend is like monopoly or duopoly in most tech categories, for better or worse.

B

Yeah.

A

In this case though, however, we're using revenue as the metric to determine the winner. Keep in mind, when you're doing open source, those are dark tokens, those don't come up as revenue. So we don't know the utilization that's occurring at Doordash when they're using an open source model. We do know their fable and their anthropic spend. Right. And because we see that in the anthropic revenue ramp, the more they deploy these things on their own hardware, using commoditized hardware, using the Neo clouds, and you don't see that it doesn't come up as revenue, it comes up as free. The only thing you're paying for there is the hosting cost, you know, and that's. That will come up on Nvidia's balance sheet. So the gains you'll see there will be cerebras, Neo clouds, Caruso cloud, et cetera. So just keep that in mind when we're having this discussion. Let's talk a little bit back to sovereignty here. The CCP said that they might or there's a report out, according to Reuters. Reuters generally does a good job of this. They dropped a couple of anonymously sourced reports about AI in China and these were published about 15 minutes apart. The big scoop that CCP officials, Chinese Communist Party are reportedly considering restricting overseas access to China's top models. So two Chinese regulators met with Alibaba, ByteDance and Z AI. They're the ones who are doing GLM 5.2 that we keep referencing. They're discussing limiting access to the top open and closed models outside of China. Why are they doing this? Well, they're making any theft or leaks of AI research a national security offense. And they want to control who can fund Chinese AI labs. And we saw this with Manus, which was a Chinese company, tried to go to Singapore. The CCP pulled those employees from Singapore back to China. And so here is their main concern, the quote is that they're concerned about Mythos. Chinese authorities are deeply worried about the potential for Mythos to exploit software vulnerabilities and that Washington might deploy a model against Chinese interest. Sachs, last week I proposed the reverse. To you in your previous position as czar of AI, do you think the United States should be banning those models? Now we have the opposite China saying potentially, according to these reports, allegedly that they might restrict them. So explain the game on the field here. If you're going to look into what China's thinking, why would they want us to not have those open source models? And how is this chessboard developing?

D

Well, last week I explained why it would be harmful to the US to ban open models. So if you're China and you want to harm the U.S. maybe you would want to. I mean, it does kind of make sense because our companies are benefiting a lot from all this R and D that they're doing. Now, at the end of the day, I think the story is probably a little bit overstated. I think there are a few Chinese models that were open source that have gone closed source, but I don't think they're all. I'd be surprised, let's put it that way, if they all went close. So, for example, the number one model in China, as I understand it, is ByteDance's model, which is already closed. That's kind of like their ChatGPT equivalent and it's always been closed. Then you've got Alibaba's Kwen, which was open and now I think is going closed, and Zhipu, which has GLM 5.2, which we've talked about a couple weeks ago because it seemed to be catching up to what was then commercially available as the American frontier. At certain tasks, they I think are going close too, after having been open. And so this is, I think the tactic is you stay open until you catch the frontier or you get close to it and then there's a really compelling incentive to go close because you want to capture all the value for yourself.

A

Which by the way, is exactly what Sam Altman did famously at OpenAI. Not only did they go from a nonprofit to a for profit, they went from open models to closed models. So it's exactly paralleling what Sam realized three years ago.

D

Yeah, I mean, in a way that was what I think Meta's original strategy was, was that Llama was going to be open, but then they actually, they've sort of backed away from open a little bit. But is this kind of an obvious strategy? Right? Is, is that if you want to catch up, you go open because by the way, you're not going to make any meaningful revenue on, on closed anyway because you're not close enough to the frontier. So why would anyone buy your product? But if you go open, you get the developer community on your side and you get utilization.

A

More people use it, which in AI gives you reinforcement learning. Yeah, thanks.

B

Well, having. Having spent some time in D.C. this week, I and talking with put the White House and Treasury, et cetera, on this topic, what I can tell you is while there may be some debates about regulation of US models, the one thing there's absolute agreement on is doing everything to stay ahead of China and the President. All the way up to the President. Very interested. How far are we ahead of China? What are the things we need to do to stay ahead of China? It is a unifying force in Washington. And the idea that we were going to kind of take our Frontier labs off the field, off the playing field, while letting Chinese open source models run free, you know, and on top of that, distilling our models, I will tell you, GLM 5.2 has watermarks from Mythos all over it. Right. So we know they were distilling, et cetera. And I think the US Government's gonna take steps against distillation, which they should do. So I think that, you know, China doing this, in some ways, I don't think it hurts the United States. The United States can spin up open source models. We've got reflection spinning one up. Obviously we've got the good work going on at Nvidia with their open source models, the labs. I've talked to a couple of the Frontier labs About open source models. I said, why aren't you guys making open source models? There's not a lot of demand for it. If there was a lot of demand for it, we would make it. And so I think the US is in a good position. I think this is probably more chess playing by China than actual threats because it would hurt them a lot more than it would hurt us.

A

Yeah. And then to just back up your point Sax, about when you're behind, go open and then once you catch up, start tightening things up. That's exactly what they did with Android, Right. Google released Android. At a certain point they were like, in order to use Android in the license, you have to include Google search. You gotta use Google Drive, you gotta use Chrome. And they started tightening it up. So it's not really an open source project at this point.

D

Just by the way, I think the absolute best thing that could happen for America in terms of winning the AI race against China is if China somehow sprouted their own doomer community. Yes, we need like a Chinese yud over there.

A

We gotta get their p doom up. We gotta get their p doom up.

D

Yeah, exactly. We need a lot more people over there freaking out about, you know, job loss or RSI or whatever. Yeah, that'd be the best thing that could ever happen to us is if they start cracking down on their labs in the same way that the doomers want to do over here.

B

Yeah.

D

Brad, let me just say just one comment. I mean, look, I agree with you that from the present on down everyone wants to win the AI race. And in fact, that was in the big AI policy speech the President gave about one year ago. That was the whole thrust of the speech was declaring that we were in an AI race and America had to win it. I think the big risk is more that. And this would not be at like the top level. You know, I think if the President could make every single decision, it'd be perfect. The issue is at a lower level in the bureaucracy, do people somehow do things that are counterproductive? Maybe they think it's gonna help us in the race against China, but they end up doing something that's ham fisted. They just like ban something or without, you know, really truly understanding all the implications of it. So I think there's no question that the administration wants to win the AI race. The president definitely does. And at the top levels they will all make smart decisions. The question is whether at lower levels of the bureaucracy you can get mistakes being made and then you have the influence of Congress and whatever they want to do those guys, they're more responsive, I think in a way to the doomer community. That's creating a lot of political pressure right now.

A

Well, and the throttle, you know, paradoxically to all of this might not be the software, might not be the chips, it might be energy. Yeah, Chamath. I mean, when you look at your data center projects and the other ones that are going out there, if we need more tokens, if people need more inference, we have a gating factor in the United States, which is, which is energy.

C

There's an analysis that my team put together which I think is quite staggering. If you just look at the load growth that's expected between now and 2050, we are about three entire California's worth of energy short. And that's just assuming regular consumption of devices and cars, fridges and televisions and computers. So we have an enormous problem in the United States with respect to electrons.

B

Yeah.

A

And if you put Taiwan into the mix here, where the chips are coming out of. I had a really big wake up call. There was a Wall Street Journal article about this. The amount of lng, which is what Taiwan runs on, is like they have two or three weeks of it. China decides to blockade Taiwan, they're going to run out of energy immediately. So this is energy both in China and Taiwan and in the United States. It's all dependent on that. We have to get nuclear running, more solar running more batteries, more of everything. And that is obviously a regulatory challenge here in the United States. All right, let's talk about your time in D.C. brad Gerstner went to D.C. everybody, and huge congrats, Brad. You've been harping on about this accounts now called Trump Accounts, the Invest America accounts. And tell us what happened in D.C. this week because I think you finally have the number one app in the world. Trump Accounts is the number one app in the world. Congratulations. And a bunch of announcements. So what's the contours of the announcement? And maybe you could take us behind the scenes. There it is. Trump Accounts, the official app number one in top downloads your kids can invest in the future.

B

This has been a four year mission in the making thanks to you guys. You were early supporters, backers. We talked about it on here and you know, founders are crazy. And you guys probably looked at what I was working on and, and, and thought you're nuts. You're wasting your time on this. And so, you know, when it got signed into law last year, that's a huge moment in a founder journey that it's like getting your first Round of funding, maybe like, okay, we actually this thing is going to happen. But on July 4th of this year, the app went live. Right? So that means millions of accounts got created, the accounts got funded. And to celebrate that and to really kind of take the next step forward, you know, we designed a joint bell ringing first in history between the NYSE and NASDAQ from the Oval Office. That was incredible. We had 100 CEOs there, kids there, families that were impacted. And the president really, you know, kind of laid out that this is much bigger than just a program to give a few people some accounts. This is really about making every child a capitalist. In fact, the President suggested that we're going to auto create accounts for all 50 million kids, or upwards of 70 million kids under the age of 18. So he called on us to get the accounts open faster, for more people to have more impact, to make sure no child is left behind.

C

Brad, just slow down. Because a lot of people don't even know what a Trump account is. Just explain what it is. And then you should contrast it to like a 529 account and some of these other things.

B

Great. So, as you guys know, the idea was very simple. $1,000 for every child at birth. That could compound for their life in a privately owned investment account. So you're born, you get a Social Security number, and you get an investment account. And if you do that, and you start with $1,000 and somebody matches that and you save 10 bucks a week, that's $50,000 at age 18. And the idea.

C

And that's invested in the S&P 500.

B

S&P 500. So when these accounts are created, all that money goes into the S and P 500. There's no cost. It's a free account for the lifetime of the recipient. And that was packaged into the Invest America act, which was passed into law a year ago as part of the reconciliation bill. So that's what actually occurred on July 4th of this year. All those accounts were created for all of these kids. That's the reason the Trump account app is number one in the App Store, because parents started hearing about this and saying, whoa, I need to go download and get this set up for my child. We had over a million and a half counts created in the first, first 24 hours after the launch of this. We had over a billion dollars of deposits. So I was contributing money into the accounts of my nieces, my nephews, my kids, friends, kids. Every account app has a QR code, Jason. So somebody can just send you the QR code for your kid, you double you Apple pay on your phone, double click and you send them 25 or 50 bucks. So that is kind of the most essential part of it. But we also had a bunch of announcements around Philanthropist, just to be clear.

A

You can get access to that when you're 18, 19, 20 years old and start putting it towards school. Or you can roll it into your Ira Roth. Ira, I guess your retirement account. Obviously. Michael and Susan Dell were the anchors here. Over $6 billion, $250 for each of 25 million children, primarily lower and middle income kids. SpaceX's president, Gwen Shotwell, she joined the party, put 350 million in her SpaceX shares and for children of lower income communities. So with this there's a device or some way to do it so you can target specific communities by geo or by I guess their net worth.

B

It's just zip code and age. Zip code, zip code and age.

A

Okay. And then Micron put in 250 million up to 1,000 per employee. So that seems to be a really interesting way to do this. Like you can do an employee, I'm sorry, an employer contribution.

C

And Brad, Brad did it for all kids in Indiana, I think, right?

B

Correct. All kids in Brazil.

A

Brad, this is a big number here. This is a big announcement. Brad, the guy who complains when we make him buy in for 10k after 10pm at the poker game and who like rage, quits the game when he loses $6,000 somehow Brad dropped $100 million. I mean, oh my God. Let's get a round of applause and a golf clap. Brad, this is, I mean I've never heard of you doing any philanthropy. Like sometimes you show up with a bottle of wine to the game. But this is a big number. This is a big decision for you, huh?

B

Well, I think this will become the largest direct philanthropic platform in the history of the country. We told the president we think we can raise $100 billion in the first 12 months. And so the scale of the philanthropy, the nature of the philanthropy, directly to America's kids without a charitable middle band that's directing who gets what and how it's distributed. So you think about the people who now are, you know, we're 10 billion or 100 billion. How do they give that money away at scale, effectively. Now we have a platform they can do that with. It goes directly into the accounts. The money can't be taken out until the kids are 18. It compounds for.

C

There was a bunch of noise about how some people won't do it. Because it's called Trump accounts. And that some people said, you know, this is going to create this weird class divide by people who had TDS and refused to give their kids. Because I think your website or something said something like 13 million bucks by the time they're 50. And, you know, I tweeted something to the effect of that is an irresponsible amount of money to not give a kid. Because you don't like the fact that it's called a Trump account. It's. It's patently insane.

A

If you go on Blue sky, which is like the open source lib, TDS social network, people are like, just put one. You know, y' all trust those Trump accounts? I sure as hell so. And so there's a bunch of people.

C

Yeah. Speak to that for one second.

B

Like, so I would say this. You know, it was the enabling legislation is the Invest America Act. A lot of people, a lot of Democrats call them Invest America accounts. They're officially Trump accounts. And the facts on the ground are that parents aren't listening to that noise. The parents who are signing up for this are across the income spectrum, across the economic spectrum. They're across the political spectrum. They know and understand that their first responsibility is making sure their kids have a connection to the American dream, have savings for their life. But yes, they are called Trump accounts. And I've read some of that blowback. But the President himself. Let me just make this case very strongly. There's nobody who I've talked to about this over the last two years who cares more about every child getting an account than the President himself. In fact, that occupied a lot of our conversation over lunch. He said, how do we get more people auto enrolled in this faster? I want every kid to have the shot to have this. I don't want anybody being left out and left behind because their parents are too busy working two jobs or because their parents may have an issue with it being called a Trump account. So the President is pushing us very hard. And the Treasury Secretary, and he told me, you need to brag.

A

He gave you instructions. He gave you an order that he wants you to auto create the accounts. This is a brilliant move. We know the Social Security numbers of people who are under 18. He told you, get to work and automatically create the accounts. Are you gonna do what President Trump has commanded you to do, Brad? Are you gonna auto create them, Brad? Are you gonna disobey the President?

B

Our intention is to get all 50 to 70 million accounts created over the course of the next 90 days using all of this data. But you know, listen, we got to work through treasury, the White house, Social Security, etc. They're definitely hurdles.

A

Warren and Bernie Sanders and Ro Khanna, who are going to try to stop you. Are they going to try to stop you from doing this? Are they giving you blowback because they don't want to give Trump the win, which is totally retarded.

B

But no, listen, I'll give credit where credit is due. You know, Cory Booker's come out and supported these and Gavin Newsom, Governor West Moore, you know, John Fetterman, Senator from Pennsylvania. So there are plenty of Democrats who are able to get over that hurdle. But you bring up a good point. And I said this on CNBC yesterday. On the one hand, you have Bernie and Mondami. They want to take and tax all these corporations. They want to control all that money in Washington and decide who gets it right. It's a very dependent on Washington model. On the other side, you have the president and this administration and frankly, a lot of Democrats who are more in the orthodoxy, closer to the center, who say, no, let's set up a private account for every kid in America. Let's fund them. Let's not make them dependent. Let's make them independent of the government to build wealth on their own, financial literacy on their own, more likely to graduate from high school, start a business, buy a home. Those are two very different worldviews for America. And I think the antidote to more socialism is more capitalism. And as I told the president, this is more capitalism.

A

Sachs, if this succeeds and Brad does as he's been instructed by the president, we're gonna go from 50% of people owning equities in the country to as much as 70, maybe even 75% of the country having access to and for the first time, being part of Equity Nation. What's your thoughts on this, Sacks?

D

Look, I think that's a great thing, and I think that this is a tremendous new philanthropic platform. And that's really important, especially in this time of growing anger and backlash and populism against billionaires and people questioning whether the system is rigged and whether they can be successful in America, whether they will be able to be part of it. This is a really important antidote to that. But I almost think that the philanthropic aspect maybe has gotten almost too much attention because people are naturally attracted to the freebies. And the part that I think hasn't gotten enough attention are all the comments I saw on CPA Twitter where all these accountants were talking about what an unbelievable, I guess you could say estate planning strategy, this is. Or basically tax advantaged, like a wealth management technique, whatever you want to call, like planning for the future. And there's never been anything like this before. They were basically saying this is like in the top three. You know, there's certain things that you just have to do. Like if your employer offers a matching 401k, you have to do it because otherwise it's just you're losing out on free money. And if you don't do a health savings account or you don't max out your Roth ira, there's just certain things you have to do because they're so tax advantaged or you're getting free money, right? And in this case you're getting both. There is the opportunity for, frankly, the free money for your kids, Right. But also the tax advantage is huge. So let's just go through this. And Brad, correct me if I get any of this wrong. So you can donate up to $5,000 a year to your kid as long as they're under 18. And it's not just you, it's any friends and family or others can contribute as well, which is new. And then they get tax free compounding until they're 18. And your employer can contribute up to $2,500 tax free. So at a minimum, you should go to your employer and say, sign up for this. And if you have to take $2,500 out of my salary and make it a donation to my kid's Trump account, because then that's a huge tax savings, right? Neither side has to pay tax on it. So like Brad said, this is basically like an ira. You get tax free compounding, then when the kid turns 18, they can get access to it and they can do a rollover into an IRA or into a Roth ira, which is even better, because when the Roth IRA matures, you don't pay tax on the money that gets distributed out of it. Whereas with a traditional ira, all the taxes get deferred until the end. The difference is that when you do a IRA to a Roth IRA conversion, you're supposed to pay taxes at that point. And I saw one really clever CPA say that, well, the best way to do this is wait till your kid is actually not a dependent anymore. Like, so maybe they're in college or they just graduated from college and they're in like the 0% tax bracket because they're not making any money. And then do the conversion. And so you'll be able to convert the Trump account very cheaply into a Roth ira. And now they're going to have two to three hundred thousand dollars potentially in that account that they can then do tax free investing for the rest of their life or they could potentially start a company with that. Other things you can do with an IRA is you can use part of the money on a down payment for the first home purchase, or if you get into a health emergency, you can use money for that. So there's all these things. You're allowed to distribute money out of an IRA without incurring a penalty. But generally speaking, the point of an IRA is to save for retirement. And this is where I think it gets really amazing is because if you start with 2 to $300,000 at age 18, you'll be at $10 million plus by age 60 if you just let it compound. I mean, there's ranges, a lot of

A

Nepo babies we're creating here. We're going to have a lot of rich kids with trust funds.

C

Yeah. So this is like, this is all

D

you have to do to make sure. Sure that your kid is protected for retirement is if you and your family and your friends and your employer can just contribute to their Trump accounts. Like that's like way better than Social Security.

C

Brad, I have an idea. I have to go sell some enterprise software, so I have to leave. But I'm really proud of you. I think this is incredible. You should convince OpenAI and Anthropic to give the equity of those companies. If this is going to be as big as you say, 100 billion, 300 billion, zillion trillion, put it into the accounts of every kid.

D

Can you just explain how that works against the $5,000?

C

I got to go. Love you guys. See you later.

D

All right.

A

Good luck on the sales call.

B

Yeah.

A

So always be closing Chamath Always be Chamath closing abc Chamath always be close.

B

You know, again, David and Chamath as we build out the platform at scale. So imagine now you have 50 million accounts that are opened. We do. We. I've said on cnbc, you know, I've obviously talked with Dario and Sam and Elon and others about making those donations. I don't like this idea of shaking down our companies, taking their shares and then putting them in some government slush fund that perhaps Bernie or AOC or somebody's going to control in the future. I've said it's got to be voluntary. And number two, it should go into citizen accounts. Right. Privately held in citizen accounts. A compound for their life. And so you asked the question, David how does that happen, given the limits that you have, you know, the $5,000 per child. That's why you have to have so, you know, 50 million accounts open. Right. Because then you can take dollars in at scale. But we can also set up a pooled account, David, where it can be distributed over time. So you distribute it to all the kids subject to the limits that you have today, and then any remainder you can distribute to the three and a half million kids that are going to be born next year, or the three and a half million kids born the year after that, or the three and a half million kids born after that. We are on a trajectory now that we're going to have over 100 million of these counts set up over the next decade. Okay, so we could have 70 million today, and then you're going to add 3.7 million a year. So you're going to be at 100 million private individual accounts that are compounding for people's lives that anybody can donate money into the people themselves. I think one of the things that gets lost is moms and dads or somebody working their summer job. Put in 10 bucks, put in 100 bucks, put it, you know, into these accounts. They get to see it on their phone. You know, this is when we started this. My sons and I designed this app, and it's basically what we ended up with. It's a, you know, Joe, shout out

A

to Vlad at Robinhood helped you with it.

B

Yeah, Vlad and and Joe have implemented a more elegant version of this. But every kid owns a little bit of Nvidia, a little bit of Microsoft, a little bit of Apple. Imagining opening up that account, David, in middle school or high school to the Money page. And now you're getting excited that you're seeing, oh, man, I'm in the game. I have ownership. And while you reference what it could be for families who can contribute $5,000, obviously Michael Dell and I and Gwen and everybody else were focused on the 50% of Americans who feel left out and left behind who would otherwise have zero. If you do the math on this, over the course of the next 15 years, you could have somewhere between 2 and $4 trillion added to the accounts of families and kids who would have otherwise had zero.

A

Go ahead.

B

We talk a lot about that.

D

See the philanthropy piece? Basically, the way the philanthropic aspect works is that other people, philanthropists, can contribute towards that $5,000 per kid. Right. So when Gwynne Shotwell contributes 2 million shares of SpaceX to 2 million kids, each kid's getting a share of stock.

B

150 bucks.

D

150 bucks. So now that's counting against their $5,000 limit. But so that's what makes it compelling is. Okay, look, every family that can afford to do the 5,000 should because it's just so compelling from a tax and saving standpoint. But then even for families who can't, there are going to be beneficiaries of philanthropists who just want to give this type of direct giving. And it seems to me this is so much more efficient and so much better than the whole NGO industrial complex where absolutely.

A

Where they take 40% for their offices and their.

D

Yeah, they're just grifting. One of the numbers I saw was kind of amazing is again, it just goes back to the power of compounding is that if a Trump account had been maxed out and you have the standard market rate of return that we've had for, say, the past 30 years, then by age 28, that kid will be a millionaire.

A

Incredible.

B

That's right. All the numbers you hear me quote, the $50,000 and the $200,000, it doesn't assume maxing, you know, that just assumes people are adding $50 a month. Because I've been focused, as Michael and others have, really on the families who don't have the capacity to save today. We're getting all of them into the game. And the president directed us, he said, Listen, we have 529 accounts that already helped the top 10%. That's not who we're focused on. This is about the Main street agenda. This is about all the families that he ran for to feel left out and left behind. And we're reconnecting them to the American dream through universal ownership. They all have their own account. They all have a private account on their phone. It's a game changer for the country. It's the largest change to our Social Contract since 1935 and Social Security. And importantly, I think it couldn't come at a better time. You know, we have this, we have this fight also.

D

Just every employer should be signed up to be, you know, an employer that can contribute because again, you could take that $2,500 and hopefully, look, it's additive and it's not just a substitute. But even if it's just a substitute and JCal, your employer takes 2,500 bucks out of your salary and puts it in your kid's Trump account, then it's reducing your taxable income. So it's a no brainer.

A

If you're a profitable company, your employees are Going to love you.

D

Yeah. But I think every employee is going to want to. And every employer should do it because it's a tax savings for both. Right. So the tax savings here is huge.

A

Yeah. So just off of the mechanics of it, I just want to maybe level up here for a second.

C

Yeah.

A

I have been often critical. I call balls and strikes and I can tell you in detail the things that I have a problem with this administration and their actions they've done. And I have done it here on the podcast. I wanna address the people who are nagging this and specifically nagging it, because it has the name Trump Accounts on it, which I told you at the poker game, call them Trump Accounts. I don't know if that was like an obvious thing or I was the person who told you to do it. I'm not taking any credit here, but I remember that conversation where I was like, just call them Trump Accounts. Like, if whatever criticism you have of Trump, however valid you may feel it is, this has nothing to do with Donald Trump and how you feel about him. Put your TDS on the side. Put your valid criticisms on the side. In this country, we have a K shaped recovery going on. We have immense tension between the haves and the have nots, to the point at which people actually believe that socialism and communism is a better operating system than the best operating system humanity has ever created, which is called democracy plus capitalism. Right. And kids love, love capitalism. They love building businesses. But we are in an existential moment right now. If these kids believe, young kids, and there's a couple of generations of them right now who do not believe in America anymore. While we're sitting Here on the 250Fiftieth Anniversary of this amazing experiment known as America, this is the most American thing you can do. So put aside your tds, put aside your valid criticisms and embrace this. And give the flowers to Brad, to the people donating, like Michael and Susan, Dell and Gwen. This is beautiful. This is the most beautiful gift I've ever seen to a country. And this could be something that's a unifying principle that brings us back together as a country, that everybody gets to participate in capitalism. And this is the number one way to do it, which is to let kids on their smartphone instead of saying, you know what? Mondavi's right. I should get a free bus ride, I should get free pizza, and we should take Ken Griffin's and seize his penthouse. It's a pied a terre, all that. And we have CEOs getting shot and their homes Firebombed. Well, you know what? If you're one of those CEOs, you've done incredibly well. There was something called the Giving Pledge where they pushed, you know, affluent people at the TED conference for decades. Bill Gates and everybody, Warren Buffett, everybody was pushing for this. This is like the perfect version of the Giving Pledge because you're not just saying, I'm giving away my wealth by the time I die. You're very strategically saying, every single person in America gets to be part of the best part of America, which is entrepreneurship, and everybody will be part of the equity nation. And my final point is, one of the happiest countries in the world is Australia. If you've ever gone to Australia. Everybody feels safe. And we have a large number of people in this country who do not feel safe. And the reason they don't feel safe is because they don't think their kids are safe to the point at which people do not want to have kids in this country because they feel the system is just too hard. This could change that. If people feel, hey, kids, have a shot, and I don't have to worry about my kids. I worry about my kids, and I'm affluent. I. I can't imagine being a single parent and what anxiety you must have as a single mother or father. And you're making minimum wage and you're behind the eight ball for your entire life, and now your kids are set. That's all people want. That's the only thing a parent wants, is to make sure their kids have a better future. That was the promise of this country, and somehow it went off the rails for the last two generations. This puts it back on the rails. This is superannuation funds in Australia. In Australia, people are extremely happy. The reason they're happy is they're forced to put 14k a year, or whatever it is, 12 or 14%, I think, of their income into essentially a 401k that they get to direct. To a certain extent, it's forced savings. This does the same thing at a very basic level. This could replace Social Security. This replaces the Giving Pledge. And I just want to say, Brad, a lot of my friends got involved in politics, some of them on this very program. A lot of people. It's very divisive. You threaded the needle here. It was a masterclass in balancing these two crazy parties and the divisiveness in this country. I just want to give you, as your friend, your flowers. This is just absolutely outstanding, what you did. And you have been incredibly humble in your approach to this, this would not have happened without you, Brad. This is your legacy of everything you've done in your life, lots of success. And I've seen it up close and personal. This is a million times X. Everything you've done in your whole life, you'll be remembered for this. This is architecture.

D

This should be as big as Social Security. I mean, it's a new platform.

A

It's bigger, it's an entirely new platform.

D

Cause it's philanthropy, but it's also retirement savings. I mean, right. And everything in between.

A

And this is pretty amazing. This is static, this is dynamic. We can add to this. There could be other features.

D

I'm seeing a lot of people in the comments say, why stop at age 18? Why can't you? I mean, you have the Trump account rollover into an IRA or Roth IRA after age 18, but why can't you keep it going? And then people can keep that $5,000 contribution going. And you know, it doesn't mean we take away retirement benefits that are owed to current Social Security recipients.

A

But sun said it.

D

But at a certain point, you could just say that, hey, the next generation's gonna be on this platform rather than the old one, and it would be

A

a lot better, a lot more efficient than government not running it, right, Sacks? Yeah, we don't want the government running this.

D

Let me ask you a question about this, Brad, because I do see one thing that people say, which is, what if Your kid turns 18 and then they just want to blow the money, you know, how do you trust that they're going to put it to good use as opposed to, I don't know, yolo, yolo and whatever.

B

As you know, these things are always political trade offs and balances. And I wanted them to have to compound until they were 30, right, because I figured by 30 you were a little bit more. You had a mature, mentally developed on financial issues. But the argument ultimately came, you're old enough to vote, you're old enough to fight a war if by 18, we don't allow you to have control of your own money. So that's where political consensus was built, David. But the other thing, remember, is they can only take up to 25% out to buy a home, start a business, go to college. The rest rolls into an ira. And there are built in penalties for early withdrawal in an ira. So there are disincentives for people to pull out. But let's be clear, we have to do a much better job in our education, our public education system, leveraging this as the platform, you know, If a kid doesn't have any money, it's hard to get excited about learning about money. But if a kid's in the game and has 12,000 bucks in the seventh grade. Now you got my attention. I own a little bit of Nike, I own a little bit of Apple, I own a little bit of Nvidia. Let's talk about that. How did it get there? How did it compound? If I added 50 bucks a month, what does it turn into? All of these things will now be present on every child's phone in America. 37 states require financial literacy. Every state should build this into the curriculum. We're working with a lot of states on that. You know, we haven't talked about that. We have about 25 states who are going to add money into the accounts of the kids in their states.

A

So you got states are going to do it.

B

States, state action, Oklahoma, West Virginia, you know, Indiana, et cetera. So that's also sweeping the country where the states are looking at programs they already have, where they're spending money for kids that are ineffective. And they're saying, instead of continuing to spend money on these things that aren't working, why not just block, grant the money directly to the kids?

A

Because we take out the middlemen.

B

Yeah, if you give the kids the money, more likely to graduate, more likely to, you know, to buy a home, start a business, et cetera. So I think that we're, as I said in the Oval, this is day one and I am fully committed to the next decade as is my partner in crime on this, Michael and Susan Dell. I appreciate your guys comments on the legacy of this. It has been the most profound work and kind of honor of my life. And standing in the Oval Office with my two sons who are really my two co founders on this. We made the sketch of this at our kitchen table in the fall of 2020. That's where the conversation started. Lincoln's been with me in every single meeting, with every congressman, senator, president, former president, et cetera. The president shouted him out. You know, again when we were there, that journey as a father with my kids has been like, the payback has been really extraordinary.

A

The other thing that's notable here, and again, like you gotta call balls and strikes and give credit where credit is due. Joe Jebbia joined this administration. A lot of people in the tech industry are like, oh, you know, oh, you joined the Trump administration, Whatever.

B

Yes, okay.

A

There's some criticism. He's an incredible world class designer. I was talking to producer Nick, our producer here also happens to show the same last name as me. He signed up for this, right? He's doing well, but his wife signed up for it. The software is fantastic. Let's pause for a second. The American government has made exceptional software and this all got done in Trump's first 18 months. Immense credit for this. This is like of all the challenges this presidency has had and Iran, war and other issues, we make great software. The American government, because of Joe Jebia, makes kick ass software just also major shout out to him, and he could be doing whatever he wants. He's done incredibly well as the co founder of Airbnb, and he's doing this. That's a real patriotic thing to do. I'm just over the moon with this. I think it's fantastic.

B

The dream team you had, like Michael Dell, myself, Vlad Tenev, Joe Gabbia, the Treasury Secretary, Luke Pettit at the treasury, talking basically every day for the last year. And our objective was not we want to build the best thing that the government's ever launched. We wanted to build one of the best consumer products, period, that's ever been launched.

A

Mission accomplished.

B

And any Silicon Valley consumer company would be thrilled with the numbers that we're seeing, the ratings that we're seeing, the engagement that we're seeing. So, you know, it's been fun doing it with that incredible team. And, you know, everybody's in this for the right mission as well. And so I agree with you, Jason. It's rare that government recruits or embraces, you know, that mission. And I think the tent's getting a heck of a lot bigger. It is bipartisan. It's bipartisan in support. You know, this is important. What Governor Moore from Maryland said yesterday, he said Republicans and Democrats have been trying to do something that looks like this, feels like this for 40 years. This guy got it done. Give him credit. This is great for America, great for our kids, and especially on the 250th anniversary, you know, you're standing in the Oval Office looking at the original Declaration of Independence, and you realize what people laid down for this experiment. And then I read this chatter in my feeds about Mandami and others literally wanting to set this great experiment on fire, wanting to burn the place down because they think they have a better formula. No, the answer is evolving and doubling down on the formula that has worked for 250 years. And rather than making all these kids socialists, we get them all into the game. Game of capitalism. They become owners and shareholders in America. So that's what we got accomplished and appreciate the chance to talk about it.

A

Listen. Incredible, Brad, and just amazing to watch you do it. And if you really think about it, the tech industry needs to win. And capitalists and creators and the makers, the people who are build stuff. This is our chance to say, here's an example of something that helps the people at the bottom, right? And I talked a bunch about the minimum wage here. We got $7 minimum wage. Like we need to address that as well. These are the things that if we address what people are scared about, what people who are, who don't have what we all have here, if we have empathy for those people and we actually care about them, and we give them a path to believe in the American dream, they will take that path 100%. We have to give them a better path than these socialist lunatics. And this is so much of a better path. Let's do it again. Let's do another one of these things. Let's keep growing this spirit of getting everybody in the country to have equity in these great companies. That's why the entire world is trying to replicate what we do here. Every single country I go to wants to recreate Silicon Valley.

B

We're not stopping here. And David, to your point, whether it's the AI companies or frankly, whether it's the intel shares or Whether it's the TikTok fee, I now have a place where all of those wins achieved by this administration can go. They ought to go directly to all the citizens of the country into their accounts and compound for a lifetime. And then as far as people over the age of 18, there's certainly a lot of talk about that as well. Not again. As Social Security is a sacred promise by both parties. Nobody's going to change that. But there's a huge opportunity to have a supplement here. Why shouldn't people, you know, between 20 and 30 or 20 and 40 also have a Trump account that they can begin on a supplemental basis adding dollars that they own and control? Remember the big difference between this and Social Security. Social Security takes 12.4% of my W2 income and puts it into something akin to the black hole of government. I don't own it, I don't control it. If I ask a room of 3,000 people how much they've contributed, they have no idea. If I die, I don't have title, it doesn't pass to my heirs, etc. So it's really not mine. But if we created a supplemental ira, it doesn't even require new legislation. I don't think it's just expanding the Age. These. These are IRAs after the age of 18. Right. Then people could start building supplemental wealth and participate in these gains. And so there's a lot of conversations going on about that as well. And so we're not done, but it was a hell of a milestone on the 250th birthday of America to ring the bell in the Oval and to watch all these kids get their accounts lit up. It was pretty special.

D

What I think is really cool about the Trump accounts, I think it's an amazing philanthropic platform, but in addition to that, it's an amazing platform for middle class family planning. That's the point I'm trying to make, is all the CPAs that I'm seeing talking about this are saying, this is like one of the greatest things ever. And if I could only tell my clients to do one thing, this would be the one thing.

A

Finally, something for the middle class. Right. This is what people have been asking for. Hey, let's get something for the middle class. Let's get something for the.

B

You know.

D

Yeah. And I think the market gap, Brad, correct me if I'm wrong, but basically the market gap that was created here is, is that you can't get an ira, which is basically a Tax Advantage savings account, until you have your first job. Right. And get earnings. Correct, Correct. Which would be for most people at age 22 plus. So for that first 22 years, you're

C

not in the game.

D

Your kids can't have an ira.

B

Right, Correct.

D

And you're effectively giving every child at birth ira. You know, it's a Trump account that has certain rules. It's actually better than an IRA.

B

Better than an IRA.

D

It's better than an IRA, because with a. With an IRA, your employer can't contribute 2,500 bucks tax free, can they?

B

I mean, I don't think so. And philanthropists can't contribute to it, and moms and dads and. But the most important thing, you know, like I say this, you know, Buffett's like, the secret is to find a really small snowball on a really long hill. Okay? But the size of the hill in this country, we've cut off the first third of the hill forever. Nobody saves anything until they're 25. Okay. The easiest compounding in the world. The easiest compounding in the world is between 0 and 25.

A

All right, listen, this has been amazing. Yeah.

D

Because they're dependents, frankly, they're still on mom and Dad's.

B

Exactly. So you pick up the first third of life.

A

Incredible.

B

Right. In compounding and so it's a. It's really remarkable. Let's go.

A

I mean, amazing job. All right, we'll see you all next time. Bye. Bye. Let your winners ride Rain Man David Sachs.

D

And instead, we open source it to the fans and they've just gone crazy with it.

C

Love you,

A

Best.

B

These are gone.

C

13.

A

That is my dog taking a notice in your driveway.

B

Oh, man.

C

My habit will meet me at 27. We should all just get a room and just have one big huge orgy.

D

Cuz they're all just useless.

C

It's like this, like, sexual tension that they just need to release somehow.

A

We need to get merch. These are it all in.