Billion Dollar Moves™ with Sarah Chen-Spellings | Global Venture Capital
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.
00:18:21 · Sarah Chen-Spellings, Michael Anders, Sarah Chen-Spellings
[00:18:21] S1: How do you differentiate between hype and substance here? [00:18:23] S0: When you're looking at investing in a company, an AI business, you wanna really dive deep, avoid the hype, and get into the substance of what's the adoption of their product. How are they growing? And of the many, many, many AI businesses that they may be competing with, how are they stacking up in terms of usability and use case and adoption relative to their peers? And I think it's very easy to put money into AI right now. It'll be just as easy to lose money in AI. And I think what you really have to do is navigate through that hype because there is an enormous amount of hype that is not gonna translate into success, and yet there's going to be enormous wealth creation and business productivity created through AI. [00:19:09] S3: In a space clouded by noise, Mike and his team are focused on substance, not slash. They aren't chasing trends. They're backing builders. So I asked him, what separates the companies that actually make it? [00:19:21] S1: What is, like, the common thread among, you know, some of the big names that you've invested in from Figma to Adyen?
00:19:21 · Sarah Chen-Spellings, Michael Anders, Sarah Chen-Spellings
[00:19:21] S1: What is, like, the common thread among, you know, some of the big names that you've invested in from Figma to Adyen? [00:19:26] S0: What we're really looking for is customer adoption and then a lot of diligence calls around users of this software, this this business. How are they using it? How are they finding it? What's, you know, helping their business? So there's an enormous amount of work that goes into validating the product, the efficacy of the product, the likelihood of continued growth of the product. And then also too, you know, we have a network beyond just the immediate iconic client base of some of the largest single family offices around the planet and sovereign wealth funds around the planet. And so when we invest in a company, you also get the ICONIQ network behind you. And so when we look at investing in a business, one question we always ask is, can we really add value here? We don't wanna just be a capital provider. We wanna be a partner to their business. We wanna help them think about growing their board. We wanna help them think about key executive hires, and we certainly wanna be very active in making customer introductions and helping generate ARR and inject more energy behind the growth that they were already seeing. [00:20:28] S3: Mike and his team have built a front row seat to the evolving tech economy. And today, that vantage point has never been more critical. From macro uncertainty and market cycles to the AI gold rush to the question of values in corporate culture, Mike has seen it all. So what does he make of this very moment?
00:20:28 · Sarah Chen-Spellings, Michael Anders, Michael Anders
[00:20:28] S3: Mike and his team have built a front row seat to the evolving tech economy. And today, that vantage point has never been more critical. From macro uncertainty and market cycles to the AI gold rush to the question of values in corporate culture, Mike has seen it all. So what does he make of this very moment? [00:20:48] S0: I had twenty years less gray hair than I do today. And so winning that trust early on was certainly one of the hardest things we had to do. Starting ICONIQ since then has had less friction because we had the trust of clients. We had a track record of delivering for them, and we had really this network that we had begun to use for this information edge, this access edge. And so day one of ICONIQ, while it was not without bumps, certainly didn't have the early stage hardship that comes with any, you know, startup business, if you will. But of course, along the way, even with an ICONIQ, there were bad hires we made. There was a couple businesses we started and didn't work out. And as long as you take a step back and have an honest assessment of what went wrong, Why did things not work out like they did for our growth business? [00:21:44] S4: Copy shot. [00:21:45] S0: Then you get better. Then you get smarter. [00:21:47] S3: So what was the hardest moment in the ICONIQ journey that you can speak to?