Billion Dollar Moves™ with Sarah Chen-Spellings | Global Venture Capital
00:09:37 · Sarah Chen-Spellings
[00:09:37] S1: You really were ahead of the curve compared to... I mean, Lightspeed is now RIA, General Catalyst stopped calling themselves a venture firm and even bought a hospital. You almost did what they are now doing, where you've built the family office relationships, managed the money, built the growth firm, Impact. I mean, now you have the data centers, all of that. Talk to us a little bit about the strategy, the through line here. Did you see it then 2011, you know, the writing on the wall that this is the direction that wealth is going to dictate in some way?
00:10:08 · Michael Anders
[00:10:08] S0: I don't think we could have started ICONIQ in any other geography in the world, and I'm not sure we could have started it at any other time in the world. I think there was something in kind of the mid two thousand where collaboration, social, partnership were emerging themes that actually meant something. Silos were a bad thing, and community was a good thing. And obviously, Facebook was kind of a pillar of promoting community. And so there was something about the timing and the location that allowed ICONIQ to become ICONIQ. And I think there was something humble in the earliest of days about ICONIQ that understood collectively a group is gonna be smarter than any one individual. And if we can get a collective group of exceptional founders and CEOs, and not just Silicon Valley, but consumer, energy, transportation, US, non US, old, young, that diversity of thought was gonna help us become smarter as long as we were better listeners than we were talkers. And so, that DNA, I think, is what ultimately drove ICONIQ. And then, of course, who would have thought the Facebook would become Facebook? Who would have thought that, you know, we would have just been at the epicenter of these businesses starting from one day and then the next there, tens of billions of dollars of value, hundreds of billions of dollars of market cap. So the relevancy of the ICONIQ ecosystem just became more and more of a juggernaut in driving interesting deal flow and also helping us build internally the team to source and vet that deal flow in a really intelligent way. And then I think too, as you start listening more and more and that becomes core to who you are, you start picking up patterns, you start picking up themes. So one of the early themes that we picked up on was we had done a few one off consumer direct investments, Alibaba, JD dot com. There was a number of these. And one, we realized that as our clients became public company CEOs, they were no longer allowed to opt in to a direct investment that they wanted to do whether ICONIQ sourced it or someone else in the ecosystem sourced it. And so we raised the fund, and we brought in my partner Will Griffith to drive that... The building of that fund. And that now is... We're in our seventh vintage. There's a 100 people at ICONIQ dedicated just to our, you know, venture growth equity, tech investing.
00:12:54 · Michael Anders, Sarah Chen-Spellings
But we saw early on from the consumer that it was a a very interesting opportunity to migrate to sort of enterprise software. And so that was a really interesting shift in 2013 where the vast majority of our investing over the last ten years has not been in consumer where we had done a few deals, but now is in enterprise software. Yeah. And that just was, again, really great timing. It allowed us to find companies like Adyen, ServiceTitan, Procore, Snowflake, Datadog. The list goes on and on and on. And so, again, it was sort of listening to the ecosystem, listening to the client base, seeing these patterns, and in this case, making a pretty bold and deliberate move into investing in enterprise software. And as we began investing more capital into enterprise software, we began seeing the migration of the cloud, and we were living this every day. [00:13:54] S1: Yeah.
00:13:54 · Sarah Chen-Spellings, Michael Anders
[00:13:54] S1: Yeah. [00:13:55] S0: And so as we began spending time again with more of our clients, for example, a couple of the CEOs of the hyperscale players, we saw the migration of the cloud, and we were hearing from them that there was no way they could keep up with the demand on storage. And so as innovative, thoughtful, sort of business creators and allocators, our first impulse was who do we allocate capital to that's investing heavily in the data center space? And there wasn't anyone at the time. There was large, you know, infrastructure funds where a percentage of the fund was dedicated to data centers and the rest was toll roads. But there wasn't anyone dedicated to investing just in data centers. And we saw this again from this client base and from the investing we had done in enterprise software that the cloud was going to be a huge place to invest and that data centers would be those railroads. And so we began building data centers, and we raised our first fund dedicated just to the building of data centers. And we really decided early on that we were gonna focus almost entirely on the hyperscalers. [00:15:09] S1: You've seen the mobile wave. You've seen also the different crashes, 2016 high of, SaaS enterprise and more. Now we're on to the next wave of AI. What are your thoughts?
00:15:09 · Sarah Chen-Spellings, Michael Anders
[00:15:09] S1: You've seen the mobile wave. You've seen also the different crashes, 2016 high of, SaaS enterprise and more. Now we're on to the next wave of AI. What are your thoughts? [00:15:21] S0: First of all, it's no secret, but AI has become top of mind for, I think, most everybody at this point and for good reason. If it was even a year ago where people were skeptical of how real it was and what would the implications be, I think there's a very little debate about how real AI is, how disruptive it is going to be. Just taking that seriously, I think is is important. There's lots of ways to look at AA. There's the foundational models, LLM, you know, small language models. Our focus has really been, and no surprise for ICONIQ, has really been on sort of the application layer. Where is AI creating product that has a use case in business? Either creating efficiency, allowing for employee productivity, you know, margin expansion. These are the areas where we've looked at. And so we've spent a significant amount of our time over the last two years diving deep into AI, but not so much from the foundational standpoint and more from the application layer. [00:16:24] S1: I guess you're you're speaking to sort of the picks and shovels approach really of taking, you know, what's going to be AI as a horizontal application in many ways. You've invested into category leaders like BetterUp, Calendly, right, Canva. How do you see AI being core to these category leaders?
00:16:42 · Michael Anders
[00:16:42] S0: Around the time we started ICONIQ, there was a lot of folks that believed investing in technology was a vertical. Some point between then and now feels like most people agree it's no longer a vertical. It's a horizontal. It really doesn't matter what business you started. You founded a widget company. It's now a technology company that sells widget. And so there's this horizontal layer that makes every single company, like it or not, a tech company. And we see AI as being another layer in that horizontal tech stack. And so we think every company will be an AI company. And what's been fascinating for us is of the 150 or so companies we've invested in over the course of the last ten years, most of them were not AI companies. But now every single one of them is transitioning to become an AI company. And as we sit and meet with these companies on a regular basis, we have an AI scorecard. How quickly are you embracing AI? Show us how you're adopting AI tools into your traditional business. If you look at a company like Figma, which was not an AI business Yeah. But now Dylan will talk openly about the fact that AI is raising the ceiling and lowering the floor for developers to come in and effectively use Figma in ways that they weren't able to do just a couple years ago. And then we look at companies like Ryder or ElevenLabs. These are pure AI native businesses, but, again, businesses that are solving a real problem, creating real productivity in the workplace, efficient workflows, allowing for margin expansion. And soon, we see this as even, like, new product development ideas are gonna come from AI. This is the future in our opinion.