00:00:00 · Jaimin Rangwalla, Molly O'Shea
[00:00:00] S0: You now have private companies that are breaking into pretty much the top 25 in the world before they even go public. It's an unprecedented time. The biggest of the mag seven was Meta in 2012. Facebook IPO. The largest IPO filing. Everybody wanted in on the most hyped up IPO in history. IPO ed around a 100,000,000,000. But today, look, OpenAI's most recent round was 800 plus billion dollars. Anthropics last round was high 3 hundreds of billions. SpaceX was $1,250,000,000,000. [00:00:28] S1: They're reaching 25,000,000,000 in annualized revenue at a third, if not half, the speed of the hyperscalers and the mega mag sevens. [00:00:36] S0: Yeah. They're adding 10,000,000,000 plus or minus a month, almost 2 and a half billion dollars a week. Most of the companies in the SAS universe don't even have 2 and a half billion dollars ARR annually. Like, they're adding that in a week. [00:00:56] S1: Jaemin, welcome to Sorcery. [00:00:58] S0: Thank you. Thanks for having me. [00:00:59] S1: So we're in the new, beautifully built out Kotu office. How does it feel?
00:00:59 · Molly O'Shea, Jaimin Rangwalla
[00:00:59] S1: So we're in the new, beautifully built out Kotu office. How does it feel? [00:01:05] S0: You know, it's almost like the first day of school again. You know, all came in Monday morning. We didn't know what to expect. Our team here had done a great job of getting everything set up while we were all still just doing our normal jobs downstairs. We came in. The difference is mostly we're much more of an open format, bullpen style, where everyone is sitting next to each other. We have AI folks, data scientists, analysts, all kind of sitting next to each other. So we're really trying to push the deep insights and collaboration. It's really exciting now just being able to yell from one end to the other, say, What does this mean? What's happening here? It reminds me of my investment banking days a little bit. [00:01:44] S1: I heard Philippe has a desk in the middle of the bullpen. Is that correct? [00:01:48] S0: He does. He does. He has a desk. He came in the first day. He put his jacket on it, and he said, Wow, why am I so far from where the center of the action is? We might have to move it back in a little bit closer to the middle. [00:01:59] S1: That's great. I was also walking around the office talking to some people, and they mentioned to me that you have a secret soccer group that goes to the pier at 06:30AM twice a week?
00:01:59 · Molly O'Shea, Jaimin Rangwalla
[00:01:59] S1: That's great. I was also walking around the office talking to some people, and they mentioned to me that you have a secret soccer group that goes to the pier at 06:30AM twice a week? [00:02:11] S0: Yeah, it's not secret. It's selective. I mean, it's a selective group. But yeah, we've been playing soccer for maybe eight years ago we started, and it started with us playing like two on two in our gym, and then we moved it out. And now we're playing eight or nine of us against 8 or 90 bucks, and it's super exciting. We keep score, we have a ranking every week, we count people's goals, the grades move up and down on who's doing well and who's not, and it drives not that we need any more competitive fuel to drive us, but it drives a little extra, in the culture. [00:02:47] S1: Oh, that's so fun. Okay, so we're here today to talk about your spring CO2 investor update. You just got off of it. There's lots of data. I've had a couple conversations with leaders at CO2 previously, Michael Barton, Thomas Lafont, and we've walked through all the different stages of the tech cycles. So we walked through internet, mobile cloud, we're now in the AI era. What is going on here? I feel like every six weeks we need an update at this point. It's just moving so fast, so what are you seeing?
00:03:19 · Jaimin Rangwalla
[00:03:19] S0: Yeah, I mean, honestly, you said is the reality, that AI is big and everyone can make these grand statements about how big it is, and we've also tried to do that a little bit in our slides about trying to size the TAM, But the most exciting part is the pace of the innovation, and you can look at that across how quickly companies have reached $10,000,000,000 $30,000,000,000 $50,000,000,000 of ARR, which we talk about quite a bit, how OpenAI reached almost a billion users in the fastest time in history. Like all of the curves are so much steeper and faster of adoption, whether it's at the consumer level, the enterprise level, revenue level, like however you think about it. And so to us, we always think about rate of change. Like that's how you really define technology and how quickly it's catching on and how big it can be. And a lot of times you see quick rate of change and then flattening, right? A lot of times when we look at apps that used to be popular, there was an app that might've done something, it gets to like 10,000,000 users, and then it all of a sudden flatlines. But the fact that you're hitting these metrics, whether it's top down metrics or user metrics that just continue to go and continue to grow at such hyper rates, and sometimes they actually are seeing almost like a little bit of a slowdown, and then another level a leg up, which just tells us one, we're still early in that adoption, and then the market is bigger than anyone is. Even the biggest bulls, I think, aren't capturing the size of the markets.
00:04:35 · Molly O'Shea
[00:04:35] S1: As CIO of the public sector, how do you map out all the different categories within this era?
00:04:41 · Jaimin Rangwalla
[00:04:41] S0: Yeah. So I think that we are constantly rethinking how we're covering stocks, how we're covering themes, how we're covering subsectors, within the theme. Two or three years ago when we first started investing in NVIDIA, we thought about, oh, now we have to follow the GPU. Like, we we bet on NVIDIA early, but that's usually not enough. Like, what we really characterize a big theme being that there's many ideas across a theme because there's so many companies that are gonna be benefiting and impacting the the forward kind of future of a theme. And so we said that we had to follow the GPU, and so we were thinking about, okay, what does it mean if you're gonna sell, you know, billions and billions of dollars of GPUs? What are what's all the infrastructure that needs to support it? And now I think we've even hit a little bit of a different slice where we're thinking about follow the gigawatts. And really, the gigawatt is almost the the atomic unit of where the growth in AI is coming from, and it's one of the biggest shortages as well that's out there. And I think that we're now identifying, okay, well, what are all the inputs to the gigawatts? What are all the things that are helping reduce the lead times of gigawatts? Who are all the buyers of gigawatts? Who are all the users of output of tokens from the gigawatts? And so we're almost slicing it very differently than we have historically, where it may have just been, okay, semiconductors and internet and aerospace and defense, just kind of sector level, we're almost thinking what slice of the AI supply chain, and then who are the people we're going have covering those slices.