All-In with Chamath, Jason, Sacks & Friedberg
00:15:09 · Jason Calacanis, Chamath Palihapitiya, David Sacks
So I I just thought, like, to me, was so striking how early we are, but also how incredibly profitable everyone is, which indicates there's quite a bit of productivity being produced across the whole value stack. Those are my biggest takeaways kind of from the s one. I don't know if you guys agree with this, but, you know, it all felt pretty remarkable to me. I'd be curious to know if you guys think I'm I'm I'm a little loopy on being too exuberant in my reading of this stuff. [00:15:39] S2: I think the thing that that is probably the most important is the last box that you said where it... You wrote in assumption, where you said assumption. [00:15:48] S0: Right. Yeah. Totally. [00:15:49] S1: Well, how do they measure that? But by the way, I agree with you.
00:15:49 · David Sacks, Jason Calacanis
[00:15:49] S1: Well, how do they measure that? But by the way, I agree with you. [00:15:51] S0: But The last box I made up. I said assume two to 10 x. So I'm just I have no idea. But I'm a user of Claude. I think we get a lot of value for Claude. I think our people are able to do more because of Claude than they would otherwise be able to do. So our business grows faster. We can get more done in a shorter period of time. I think I tangibly experience that pretty regularly. I've talked a lot about moving to open source, and we have our own cluster installed with our own kind of open source now. But I think what Claude is showing is that they they have such a high margin. They actually have good elasticity on pricing. So they could push price down, and you could start to see them start to segment the market a little bit where they could start to be more competitive perhaps with cheaper tokens for cheaper, easier tasks. And then premium tasks charge a higher price for intelligence and start to stratify the value of the intelligence that they're providing by changing the price points. And I'm... I envision that's where everyone's gonna go.
00:16:44 · Chamath Palihapitiya, Jason Calacanis
[00:16:44] S2: Nick, I'm gonna show you... This is to Friedberg's point about what is the potential downstream productivity gains that everybody can have theoretically with AI. Just put that on the screen. This is from Microsoft's earnings. My research team put this together. It's really quite incredible. What this shows you is that Microsoft's revenue went from 198,000,000,000 to 332,000,000,000 in the last four years while staff only increased by 2,000 people. I mean, isn't that stunning? Like, you would have thought before AI that if somebody said, great, we're gonna, you know, get close to doubling revenues at this kind of scale. [00:17:29] S0: Right.
00:17:29 · Chamath Palihapitiya
[00:17:29] S2: You probably would have thought that headcount would have doubled too. And the reality is headcount stayed flat, and we don't know how many people will take this offer that Microsoft just gave for, you know, to to leave because I think they offered it up to 60,000 people, but this number could be under 200,000 depending on how many take it. And so just the scale and the impact on the productivity, to your point, this idea that it creates job loss, don't think it's true. It's more that you're seeing productivity gains at the same number of human input, and I think that's interesting. I went through the s one. You want me to give you my little s one breakdown? Mhmm. This is the most incredible business I've ever seen. I hope that they go public after November 11 because it will force them to update with q three, and then we'll get even more insight into... This is like some contraption that I've never seen before. I've never seen a business like this. It's really, really, really incredible. So let's cross our fingers because post November 11, you'll see q three drop. What people have been whispering is that the revenue growth kind of moderated to sort of like the 50% range. Q4 is TBD, but let's break this down in a bunch of charts because I think it's interesting. Okay, so Nick, start with chart number one and we'll just go through them one by one. Okay, so the first thing that I always read in an S1 is what are the risk factors? And what I had my team do is I said go put together a word cloud. This is great, is cool. First tell me what are they afraid of, okay? And when you look at it, the share of words in the risk factors that are allocated to different risks are very important, and what this tells you is the single biggest risk to the ant business is compute. They mention it more than anything else. And specifically inside of compute they talk about data centers, power, chips, grid, electricity, hardware, etcetera. Then a close second but still second is regulation. Okay? They care about government policy. They care about sanctions. They care about export controls. Then it's this idea of zero data retention and privacy and IP. Then it's AI safety. Then it's just making money. Then there's their competitors. Then there's governance. What you notice is what are they not afraid of?
00:19:50 · Chamath Palihapitiya
They're not afraid of customer traction because they they rarely mention it. They're not really afraid of employees leaving because you'd be an idiot to leave if you were inside, and they don't really care about taxes and any of these other things. So this is a business that is very much on the forward foot that understands the binding constraint. So now if you know that the the compute is their biggest risk factor, then you double click into that. And I had my team run a further analysis, which is to say, okay, how do they describe these risks, right? How many times do they mention them? How many words are you spilling talking about this? And what you find is that inside of the compute problem, their biggest issue is really data centers. And then further, it's the financing commitments that they have and it's the power. All of these are really important because, again, it helps us highlight what the binding constraint is to this business. So as goes data centers, as goes power, and by the way, this is a great setup for the politicians because it's very obvious if you're a Democrat as you read this, and I'll speak about it in a second, what you should be trying to do to win in '28 versus what Republicans have to do in '28. Right? Basically, the takeaway from all of this is I think antisemblematic of the entire AI complex, which is to say it's all about data centers, which means it's all about power. If you're a Democrat, the best thing you wanna do is slow all of this down so that there's a recession going into '28. The only thing you need to do is slow down power and slow down data centers. On the other side, if you're a Republican and you wanna have the best chance of winning in '28, this is the one thing that must be done right. You must get the power, electricity, data center thing right.
00:21:40 · Jason Calacanis
[00:21:40] S0: Okay. So based on this, your premise is they need data centers. If they don't get data centers, it can't keep growing. However, Sacks, the truth is these are the liberal of all liberals in Silicon Valley. It is the largest amount of money that has ever been made by founders outside of Elon Musk. It would make sense to me perhaps the opposite of what Chamath saying. Shouldn't the Democrats come in and say, we are pro data center and energy because this is gonna help society because they wanna see Dario and his group win because they are gonna be the equivalent on the left of Elon Musk on the right. Wouldn't it be better for them to steal the the data center charge and make Anthropic even more profitable so that that 51% of all of their... Or 80% of all their money just flows into democratic super PACs?