Accel: The Quiet Firm Behind Facebook, Cursor, Nebius, Lovable, Vercel

[00:04] We initially invested in Facebook in 2005. We led the Series A out of our early stage fund. Microsoft had just invested into Facebook at $15 billion, and we had the chance to invest around, like, a little bit south of $20 billion. Across companies like Cursor, Anthropic, and Debius, 16 months ago, $150 million investment that I think is up 13x today, and the world has now awakened to this company and how special it could potentially be. [00:30] growth team here at Excel, we're about to apparently get $3 trillion IPOs. How do you expect the market to handle that? [00:49] All right, so we have a very special group here today. We have the growth team at Excel. We do. We do. Thanks for being here. How many of you are there? Excel is actually very large. I mean, I was really surprised when we walked in. [01:03] Yeah, I mean, we're seemingly large by strategy in places we dive into, but the reality is, like, as a team, it's quite small. So on the late stage, in terms of investors, we've got about six investors that deploy most of that capital. And we obviously do it in concert with the whole crew around the table. That crew has been together for a very long time. I mean, the three of us have worked together for 15 years. [01:25] a lot of it is grown from within. So a lot of the people you see running around are people that we hope [01:29] add to that list of six over time. [01:31] I was surprised too. I already made this joke in the last interview because we did one with the early stage team. But walking around South Park, the building is very, it's very unassuming. And then you walk in and it's like restoration hardware got hit with some pet ties and it's gorgeous.

[02:01] It's my show. - It's your show, you know everything? - Yeah, I know. The crazy stuff that's happening in Silicon Valley right now, because things are happening really, really fast. You're probably seeing companies come at you at a faster clip than ever before. We did this interview at Ko2 and the CIO over there, [02:16] on public markets, and we were talking about the size of which companies went public. The largest one was Meta, it was Facebook. You guys were a very large part of Facebook. I think you held 10%. So let's go back to the lore and history of Excel. So maybe talk through that Facebook deal. You guys weren't here at the time, but would love to learn more about that. [02:37] Yeah, I think Arun and I like to joke that neither of us is, we're not really old, but I think we're just old enough to have seen a couple of distinct technology cycles and a couple of eras of, you know, Excel. And we joined at the time when Facebook was a private company in the portfolio and it was just reflective of where the technology ecosystem was at the time. The thing that still kind of inspires [02:59] Us, you know, through the Facebook parallel was, it was like the first platform company that we saw. So all the companies as associates that we were building relationships with were figuring out how they could like build their business atop Facebook as a distribution platform. And that parallel has actually repeated itself multiple times. I think today there's a pretty clear parallel in terms of Anthropic and OpenAI and the labs themselves. But that was sort of the ecosystem that we grew up in. [03:27] And, you know, it was, I think we feel today very thankful

[03:31] We're so lucky to work at a place like Excel at a multi-stage, multi-strategy, multi-geo platform, largely because of all the work that went into sourcing investments like Facebook. Not only Facebook, but a number of other great ones from that generation. And we were lucky to have seen the very beginning of it. I remember our early days in our first growth fund. We had an opportunity. So we initially invested in Facebook in 2005. [03:55] We led the Series A out of our early stage fund. [03:57] And we created this growth vehicle in 2008. Miles and I joined in 2008 and 2009. And one of the first opportunities was to buy some Facebook secondary that came up. Microsoft had just invested into Facebook at $15 billion. And we had the chance to invest [04:13] around like a little bit south of $20 billion. And I remember two distinct things in that moment. [04:19] One was, [04:21] In that era, you had investors that invested in the Series A, [04:25] Then you had a separate set of investors that invested in the Series B and a separate set that invested in Series C. It was sort of this structured... [04:32] graduation through the ranks. And so it felt unnatural to say, "Hey, we're a Series A investor, but we're investing in the Series C or Series D." It felt it was very different than what a lot of other firms were doing. [04:44] And secondly, we're investing at $20 billion. [04:47] Like, what was the upside from there? And so I remember that partner meeting around the table saying, we actually think this could be $100 billion business or more that we could generate north of a 5x [04:58] Lo and behold, that was way undershooting what the opportunity and the potential of Facebook was. But I think it just, you know, 16, 17 years ago, I think that was...

[05:07] the foreshadowing of the moment that we're in right now, where technology dominates our entire lives, these companies are growing faster than ever, bigger than ever. But even back then, we felt some of those same [05:18] dynamics and some of those same impulses, I guess, of evaluating a company that was already so dominant, but how big could it actually be? [05:28] What I remember about that moment actually was that [05:30] We had this very strong venture practice, and we were creating this growth practice. And Ryan Sweeney was actually one of the partners that helped lead the beginnings of our growth practice. And he had us showing up to work in pleated khakis and gingham shirts. We looked like total idiots. And he would remind us every day to be humble and to hustle. And all of this came on the backs of people that came before us. [05:50] If anyone's seen Ryan recently, he's wearing a flat rim hat, joggers, Air Jordans. So I think he's done fine and graduated from the apparel side of things. But if you meet anyone inside the walls here, you're going to have that humility and a lot of that hustle as well, which stayed with us. [06:05] Did you guys hold on to that? [06:06] position. [06:08] - To the Facebook position? - Not long enough. - Not long enough. - No, that's not what funded this beautiful-- - There have been a couple of other decent partnerships along the way. - It helped. We should have held longer. - That's awesome. So I wanna go through each one of your portfolios, and we'll make it a cohesive conversation, but [06:26] What I was really surprised about is that you guys are generalists. [06:30] So how did you come up with [06:32] I mean, you all distinctively have different backgrounds and I'm sure networks and that kind of thing. But like, how do you come up with the theses behind the positions and the different companies that you've invested into, whether it's Nebius?

[06:43] Cursor, Lovable, all those types of companies. - I think we've always been generalists, but we definitely all have areas of focus and comfort, and then we go really deep in different categories [06:56] over time. Like Arun has always spent a lot of time around infrastructure and cybersecurity. Matt spends a lot of time around infrastructure. I've done a lot of application software and developer tooling. But I think that the way the technology landscape is evolving, I mean, these categories, especially these applied AI categories, can just [07:15] sort of come out of nowhere and grow so quickly that you have to have some mental plasticity to wrap your head around these new categories as they evolve. So we are generalists, but we definitely have areas of focus and we're constantly trying to hone new ideas. And the same premise applies today as always has at Excel in the way that we've just sort of practiced the job. I mean, you really have to show up prepared, especially in today's market [07:45] on which company is going to win before you even get the first meeting. And then you have to really show up and add some value and, you know, [07:54] convince this entrepreneur that there's a compelling reason to work with you. And so we are generalists, but we try to be micro prepared in certain categories. [08:02] One of the best enterprise software investors in the last two decades, I believe, is Andrew Bracha. [08:07] whose background he spent over a decade at Yahoo. [08:10] He was a consumer internet guy. He joined Excel with the explicit mandate of

[08:14] investing in consumer internet companies, [08:16] But when the advent of PLG started and consumerized enterprise software started, he was actually super well positioned to invest in those companies. He led our seed investment into Slack early on. Samir Gandhi has been a prolific consumer investor, but he's actually one of our leading cybersecurity investors as well. And so I think we believe areas of focus, domain knowledge, that's super important. [08:46] perspective relative to all the people that spend time in that category that might be interesting and unique and actually right. And so we encourage that exploration and, [08:56] And it's an important part of the way that we function, because I think all ideas are welcome. You should focus, but at the same time, you should be open to new perspectives and new ideas. [09:06] Excel is more of a quiet story and like a quiet... [09:10] I don't know. Silent Killer? Is that what it is? Maybe? I'll take it. Silent Partner. How about that? All right. Excel is more of a silent partner than some of the flashier names, even on this road or down the block. So I'm really curious from your standpoint, how are you winning these deals against like [09:29] the flurry of [09:31] marketing and blah, blah, blah and hype that's going on in here. [09:35] Okay. [09:35] I mean, I think, first of all, we approach it with humility. Like, this is a very humbling job in ecosystem. There are a lot of talented investors out there, and we have a lot of professional respect for our peers. With that said, I think our style has always just been a little bit to stand behind our founders.

[09:50] And really, the equation is very simple. If we do good work, [09:54] over time that will be reflected in results and returns. And if we're good humans and good partners and pleasant to work with and good backers of our founders, [10:02] they'll say nice things about us over time. So I think that shows up in scenarios where, for example, [10:08] When we were able to work with Michael Truel in Cursor, you know, we were like really humbled to get the opportunity because it was a pretty competitive situation. And I asked him after, I said, [10:19] I'm really honored that you picked us. Can I ask you why? You had so many choices. [10:25] He just said in a very simple Michael way, he said, I asked around and people said really nice things about Excel. [10:31] And I think that is sort of the brand that we've tried to stand behind over the years. It should never be about us. It should always be about the founders. And that has been true for 42 years of Excel. [10:42] - Okay. [10:43] I think the other component of that is just that up until maybe only-- and we're going to talk, I imagine, a lot about consensus and some of these consensus investments that are driving outsized returns in the private markets. [10:54] Up until about five to seven years ago, [10:56] It was almost a religion here to be the first institutional investor into a company. And as a result, you're almost [11:03] organizationally introverted. You're spending your time going and finding something that someone hasn't been spending time with or crafting a relationship that can be in some way, shape, or form proprietary to the firm. And I think internally, we still view that as the most amazing demonstration of the craft, if you're able to do it. Now, we're not oblivious to the fact that there are consensus names where you need to lean into some of the experience and the work that you've done in the past to get access to those and to be a part of some of those phenomenal

[11:33] at the social media posts about a founder raising a round and a VC making it about themselves is pretty cringew. Like, don't throw your shoulder out patting yourself on the back type of situation. And so we were always just like, take a step back. It'll be about the founders. I say all this now, maybe our comms team has done something related to patting ourselves on the back. But, you know, generally, that's just the vibe of the office and the vibe of the firm and kind of how we just think about [11:57] practicing the craft adventure. - How has funding actually changed over time? We're in a ridiculously chaotic, a little bit schizophrenic, [12:07] era where it is like land grab time, logo grab, talent grab. [12:12] How are you thinking and like what are you seeing of the different types of funding and how that's changed? Yeah. [12:18] - Okay. [12:19] I think one way that we think about it [12:21] And this is where, again, we're incredibly lucky to work at a place like Excel that allows us to prosecute what we all agree is this generational technology change holistically across every imaginable dimension. And what do I mean by that? We're prosecuting the AI opportunity across every layer of the technology stack. So literally from the chips to the neoclouds to the labs to the applications down to the systems integrators. [12:51] the growth stage. So at the early stage, we've been the early initiating investor in companies like Lovable, Decagon, Scale, Gamma. At the growth stage, we've reflected our conviction in some of the iconic breakout AI companies in terms of some really sizable investments. So just as an example, across companies like Cursor, Anthropic, and Nebius. And then also importantly, because it's a hallmark of how Excel functions,

[13:16] we've prosecuted this AI opportunity globally. So not only from our office here in Silicon Valley, but across our team in London, across our team in Bangalore, [13:24] So, holistically, when we reflect on our work over the last couple of years, I think what we see is a $7 billion portfolio of really thoughtful, nuanced investments that we've selected very carefully. We don't believe in a blanket strategy and just spraying and praying and blanketing an entire category where we're going to do every single Neolab, every single application category. We pick with subtlety and nuance and hopefully wisdom, and I think that's why our LPs pick good managers. [13:53] And so I think we've tried to do it very holistically in a way that really there's only a couple of firms in the world that are structurally able to do. [14:01] How have check sizes changed? I mean, even in Q1 we saw like [14:05] nearly $200 billion go into [14:08] like maybe two or three companies. Yeah. [14:11] There's definitely been an unmistakable concentration of capital and maybe interest around a handful of late-stage private companies. [14:19] We're very fortunate to be a part of a lot of those companies. [14:22] But the rest of the ecosystem is also growing exponentially and really, really excited to us. I think of our ability to reflect our conviction in two ways. The first is just earliness of investment. So ideally we are initiating the investment, writing the first check. The other way is just size of investment. [14:39] So companies that we really feel like are the definitional companies of this era, you know, we're able to invest [14:46] four or five hundred, six hundred million dollars at a time.

[14:49] and then we can scale all the way in between. [14:51] But I think we've been growing and learning with the market too. [14:54] You know, I think [14:55] All of us have been surprised, at least myself, about [14:59] the amount of capital that has been raised in quick succession and how quickly these companies are growing from a talent perspective, from a scale perspective, [15:07] Our first growth fund was $480 million. [15:09] when we first join. [15:10] It is not unusual for us to invest $500 million into a company. [15:14] actually to invest over a billion dollars into a company. And so the nature and the scale of the game have changed dramatically. [15:20] but so has the opportunity on the other side. [15:23] And so if we believe that these companies can be trillion, multi-trillion dollar companies, [15:28] within a very short hold period, [15:30] We should reflect that in check size. So I actually think the market is totally rational. [15:35] on this. I think if anything, a lot of us have underestimated the potential of AI and the value creation that it offers. And so we're constantly pushing ourselves about [15:45] to our bounds and to our comfort level about our ability to invest and how much should we invest and when should we invest? What are the points of conviction that we're seeing? We could talk through a couple examples of that, but [15:57] You know, we are-- [15:58] It's [15:59] It's uncomfortable and we're pushing ourselves to be uncomfortable because the market is changing. The frontier is moving so quickly. And if you just look at the data for it, it's [16:07] never been harder to be in the early stage business. The barrier to entry to start a company is incredibly low. And as you think about how many companies are started and how many opportunities are out there, I think when I joined the firm, we probably had 90% coverage over every seed in Series A.

[16:22] We're nowhere close to that today. And it's just not practically possible to have that level of coverage at kind of seed in series A. But what we still have is we still have a very small cohort of companies that are the outliers that run into the late stage. And everyone's talked about the private market getting larger, but the returns in the private market at the late stage are actually going to start matching the returns at the early stage. If you look at top quartile performance of early stage funds versus late stage funds, I think they're going to be pretty close to each other throughout this cycle. [16:52] story in the early stage business, but top quartile for sure. And we're seeing it as you see the scale of the anthropics and cursors and nebviuses of the market. [17:01] I was just talking to Brian Singerman about that. I mean, he did a lot of huge growth deals at Founders Fund and is now investing into managers. But he was even talking about like, yeah, okay, you can get later into the company, park a bunch of money in it and still outperform all the other investors. 100%. Yeah. Yeah. And I think that opportunity will only grow. I mean, if you think about it, 10 years ago, there were zero publicly traded companies worth a trillion dollars. [17:24] Five years ago, there were five companies worth a trillion dollars. [17:27] As of today, there's 14 with probably three or four private companies that are pre-IPO that we could all point to. And I think it's fair to expect there will be $10 trillion companies and beyond over the next cycle. [17:39] Damn. [17:41] - Fingers crossed. - We hope so. - That was a good sound bite you got there. - Let's go. - Preparation over there. - Preptides is what that was. Someone had his gluten water this morning. - What is that water? - Commercial break. - Yeah, commercial break. - Commercial break, what is this, what are you drinking? - We have to still have one shot. - Still and Sparkle. - Okay. - No, but seriously, that is like the zero plastic water?

[18:02] No, there's no plastic in it. It's amazing. Would you like some? Here, take the bottle. [18:08] - This is too funny. - It needs like a little sound. - Well I have to finish my sparkling water first. A little interlude with Lunen. - Yeah. - I gotta get a kickback for this. - Yeah we better get some free equity in Lunen. - It's all I've been hearing about once I got into the office. They're like, "There's no more Lunen in the fridge!" - We have some other stuff we can sell you. We got some CrowdStrike downstairs. We got some-- - Those are the priorities here at Excel. - We're running out of Lunen. - Pushing her water. [18:32] I'll try it. [18:35] - Oh my God. - Right? - Mind blown. - Wow. - It smells itself. - Mind blown. - Total placebo. - Total placebo? - Don't ruin this for us. [18:47] This episode is brought to you by Brex, my favorite. You become what you spend on. And I refuse to spend my time on work that shouldn't exist. Expense reports, receipt chasing, and manual closes. The companies building what's next from Vercel, OpenAI, Anthropic, Granola, and Deepgram. [19:07] all made the same call they all run on brex brex is the intelligent finance platform that combines cards expenses and banking into a single stack with agentic finance built in ai agents that handle expenses automatically [19:22] Enforce policy before spend happens and close your books in minutes. That's why Sorcery runs on Brex, so I can spend time on building and not busy work. It's time to get Brex AF. Learn more at brex.com slash sorcery. That's b-r-e-x dot com slash s-o-u-r-c-e-r-y.

[19:44] Bye! [19:45] Turing is training the next generation of AI with tasks that require real expertise and real world judgment. That's why companies like NVIDIA, Anthropic, Salesforce, and Gemini partner with Turing. Turing builds realistic reinforcement learning environments and data systems based on real operational traces, the kind of infrastructure Frontier Labs need to train superintelligence. Visit Turing.com slash S-O-U-R-C-E-R-Y. [20:15] You have a public market company, Nebius. Let's talk through that because that is like a really hot company right now. They just had a huge deal. What was it like $26 billion? Yeah, we announced a big deal with Meta. Mm-hmm. [20:28] Yeah, first and foremost, as a venture investor, I wouldn't wish it on anyone to own a public stock. I mean, having the stock apps be like the major app that I use on my phone now, it's very stressful having to mark to market every day. You know, that's an amazing story of an entrepreneur, Arkady, who actually built Yandex, which was built to about a $30 billion market cap on the NASDAQ. And then the war broke out in Russia, and many of the engineers followed Arkady out of Russia, and he basically... [20:57] collected where he was and was thinking about what he was going to do next with all these engineers that followed him. And it was actually one of the founders of Excel, Jim Schwartz, who introduced me to Arkady and basically said, he's trying to think through what's next. He's got a few balls in the air. You should talk to him. [21:11] And so for a couple of years, Arkady and I went back and forth on what would eventually become Nebius. And actually, the early innings of that was me trying to convince Arkady to sell me his 30% stake of ClickHouse, which he rightfully refused to do. But as I got into that negotiation with him, I got to know him as an individual. And he is the most quietly humble killer I've ever met. He is truly, truly special and out of one entrepreneur.

[21:41] And most people would have hung the cleats up and said, I've had a great run. [21:46] billions of dollars from my experience with Yandex and I'm gonna retire and he was thinking, how can I plow this all into infrastructure? Because I have this unfairly advantaged team to go take it take take that market by storm. [22:00] And he wanted to do it in a nuanced way. At the time, there were other NeoClouds. At the time, obviously, we had the hyperscalers coming into the GPU market. And his view was way, way larger-- his vision was way larger than what others were talking about in the market. He fundamentally believed that infrastructure would be delivered in a different way. It wasn't about giving a very large cluster to Meta, even though they're a customer of ours and we're incredibly happy about that. [22:26] It was about thinking about a world where [22:28] developers that have domain experience working on backend, infra, GCP, AWS specific experience, we're going to fundamentally change to be [22:38] operations, founders, people outside of those orgs that maybe didn't have that domain experience, provisioning agents to go interface with infrastructure. And what do all the primitives mean in a world like that, where you don't have to understand the massive AWS catalog, but you just interface differently with infrastructure? And some of the areas that we talk a lot about now in the private markets, you see a massive growth on areas like inference, were always part of the scope of what he wanted to build. And so now you have this engineering culture, which is very unique, [23:08] into what I think is a much more durable vision for a next-generation hyperscaler for the AI era.

[23:15] - And for those who don't know what Nebius is, could you just give like a brief, quick line on that? And then also where does it fit? [23:23] for inference people [23:24] This will be a wide-ranging audience, but in terms of inference, why is that becoming so important now? Obviously, we're seeing it with agents and more different types of compute that they need and all the data that they're creating. But could you just share that? Yeah, absolutely. So at its most base level, Nebius is intending to build a next-generation hyperscaler. So they want to own everything from the data center itself through to designing the server racks. [23:54] So we talk a lot about how many data centers need to be built, how many GPUs need to be delivered to handle the demands of AI, both training as well as inference, which we'll get into in a second. These guys are one of the most aggressive teams to scale that infrastructure and meet the moment. And they want to own all of it vertically integrated. And that's really important when you think about delivering inference. So inference is we've now trained all these models and we need to get value out of them. [24:24] against the chat GPT, against OpenAI's model. But as you allude to, agents start using inference in an exponential way. The demand curve goes way up for what we're going to need from an inference perspective. And when you control capacity by owning the data centers and the GPUs, and you control the software, you're in an advantageous position to be able to meet the moment and deliver inference for a market that we fundamentally believe is going to grow exponentially.

[24:54] planning across the entire ecosystem. And we're consistently every quarter waking up [24:59] being surprised by some new announcement. Google announcing that they're going to do their first equity raise. [25:04] over a decade for $80 billion to go spend even more than all of their cash flow on infrastructure. [25:10] I still view it as we're eating one and we're just getting going. And there's going to be a lot of scaling that needs to happen to deliver the infrastructure for AI. And Nebius is going to play a small and hopefully growing part of that. [25:21] I went to one day of GTC. [25:24] and they dominated. Their marketing was everywhere, it was on like [25:31] 500 cars and all over the place. And then I was like, [25:34] I'll check it out. Okay. Next to SK or SK Hynix. Yeah. Um, those two had really good marketing there, which was very strategic. Um, okay. So we talked about that. I do want to go into the agentic layer a bit more. I'm sure you're definitely seeing it and you're seeing it too. Um, but so. [25:54] that is creating like a firestorm of new products for companies, new use cases, and just extreme growth for these companies. So what is your current view on where that lands in the next like [26:09] I don't know, by the end of the year, do you think we're starting to, like, kind of see inklings of, like, actual agent adoption and, like... [26:17] It's definitely banging around a bit and it's a little bit messy, but like, how do you see this playing out? [26:22] Can I do something super controversial before we get to this very important topic? Can I brag on Matt for a second because he's not going to brag on himself? Do it.

[26:31] What Matt won't say about Nebius is that today it seems [26:35] fairly obvious and it's a very buzzy company. 16 months ago when Matt led a pipe investment into Nebius, that was not the case. [26:42] And I think it is like very emblematic of original thinking and how we try to function at Excel. If we're passionate about a category, and especially if we're passionate about a founder, we will find a way to structure the right investment. And so whether we are making [26:57] you know, writing the first check into scale, [27:00] or doing a growth investment in a company like Cursor, or finding a way to make a public investment in a company like Nebius, I think that just reflects our ability to express conviction in a bunch of different ways. And so, you know, again, I'm bragging on Matt's behalf 'cause he won't do it, it's not sort of who he is, but this was [27:18] 16 months ago, $150 million investment that I think is up 13x today, and the world is now awakened to this company and how special it could potentially be. I think Matt gets a lot of credit for having acknowledged that. [27:31] year and a half ago. [27:33] in a really good retail community. [27:35] - And a really good retail company. - It's the branding though, you know? [27:38] Great branding. [27:39] We need more merch. Okay. Keep rolling on agents. No, you. You go. I think... [27:44] to Matt's earlier point, [27:46] We might not even be in the first inning of this. [27:49] The level of adoption and growth that we're seeing on agentic workflow is phenomenal. So we can take Superbase, for example, which is the backend database to a lot of agent workflows and agent applications.

[28:02] That's growing. [28:04] 350% [28:05] at hundreds of million dollars of scale. [28:08] And they have virtually no salespeople. [28:11] it's all inbound. That's crazy. Which, you know, and I think we're just now scratching the surface. There's a bunch of orchestration and product development [28:21] to allow the product to scale to some of the applications that we're seeing. But most of the usage that we're seeing is actually coming from inside the enterprise. [28:29] And so what started as a vibe coding backend, so if you're building on Lovable or Bolt or V0, you would attach a Supabase database to it. [28:39] Now we're seeing people in enterprises that are building an application using Claude, [28:44] co-work or Claude Code. [28:46] or even Codex, and on the back end, it's using Supabase. And so we actually have pretty good insight into this. [28:53] And the level of adoption that we're seeing in the enterprise for people, for agents, for the workflows that they're doing, and the importance of those workflows, it's growing exponentially. And so I think that gives me... [29:04] Confidence, if we look at some of our other portfolio companies, just in terms of where they are in agent adoption and AI adoption as a whole, [29:11] we're still so, so early and have so much more to go. - I'm so curious. So how are people discovering that? Is it just built in to like, I don't know, spin up a new website for me or spin up a new feature or something like that? I ask this because [29:24] There's a little tangent. My dad just started vibe coding. Oh. And guess what he vibe coded, guys? Golf handicap app. No. Pickleback. Captain's log. Whoa, wow. Yes, he's a boater. Is he a sailor? Shout out Steve. Come on, Steve. Good word. Get that guy some loon and water. I know. But he, it was really interesting. I was like, he was showing it to me. He was so excited. And it like has tide charts. It has temperature. It's like, here's this route you can take. Here's when the sea's going to be like a little bit more choppy than it's not.

[29:54] Here you can log your trip. It was really cute. But so he was, I was like, dad, how did you do that? Like really, how did you do that? And he was like, oh, I just did it on Claude. I like asked it to do this. It told me I could pick from these three products and that one, and I can add this database and blah, blah, blah, blah. And it just kind of did it for him. So [30:12] Is it... [30:13] in the workflows? Is there something strategic underneath or what's going on there? Everyone help him. Steve needs a database. I do think Claude or Codex or all these tools are now recommending a lot of products on the backend. So Supabase is- Is that a paid thing or is it just preference-wise? No. I think the [30:32] In the last era, it was search engine optimization. In this era, it's AI optimization. And so these products are now the distribution mechanism for all the downstream products and services that you can use. [30:44] And they tend to prioritize the tools that have the best developer and user experience. [30:48] And so this was actually the early bet of the Supabase team, which is [30:52] Everyone has, there's a bunch of database products that are out there. It's built on top of Postgres, which is the most widely used database language and framework that's out there. But it's just an incredibly easy tool to use. And so their first adopter was the YC batch they were in. So 60% of YC companies now choose Supabase. They just made it incredibly easy to use. [31:14] Turns out, if you have that sort of framework and methodology, it makes it really easy for AI to use. It's actually the same reason why we're seeing a ton of growth [31:22] from Vercel, which is another one of our developer-first companies. And so I think it's just a lot of experimentation, people trying using AI

[31:32] and then falling down the rabbit hole and discovering the power of AI. [31:36] So, I mean, I guess on the agentic adoption side of things, these companies are getting another... [31:43] breath of life that they probably had no idea they would reach the scale in the amount of time that they have. Kotu put out a super-based chart not too long ago that they got like 80 or 90% of their... [31:54] growth and their customers within, it was a really short period of time. It was like 12 months or something like that. I'll find it. [32:00] They just crossed 9 million developers [32:04] you know, last week, when we first invested, it had under a million developers. And that was at the beginning of last year. That's crazy. So most of their growth has happened actually in just the last three or four months. With the launch of Opus 4.5, [32:16] and long-running agent execution [32:19] that's driven a ton of growth. - And this is where also being thematically focused and tight knit as a group, you see the interconnectedness of the momentum of each of these companies. There was a week a year ago, and I remember Arun and I were talking debriefing after having been in a couple of board meetings, and I think you were seeing through Supabase this [32:37] you know, atmospheric chart that was up and to the right in terms of new developers on the platform. I had been in a linear board meeting the week before, and we saw this spike in workspaces being created. And we sort of, like, between the two of us, this didn't catch on, but we started talking about this concept of, like, agentic influence. And it was, like, all of a sudden, these... [32:56] Agents are making decisions about downstream workflows and downstream tool creation. And we just sort of said we have to invest in every single company that is going to be in this flow and every single company. More importantly, that is like the choke point that's metering out these decisions. So that gave us the conviction with our partners Ben Fletcher and Genia to go after a lovable.

[33:16] And when you're sitting in a room of tight-knit investors that are all working on similar companies, seeing the same trends in their adoption curves, [33:27] It gives us a more holistic view on like, where else should we go be really aggressive? And these curves all happen at the same time. [33:34] That's crazy. What were the main categories that you were looking after? Fortunately, we were already early investors in Vercel. So at that time, it had been a huge beneficiary. And we've continued to [33:44] invest over and over again in Brassell. [33:46] Um, [33:47] We were investors in cursor at the time, but we certainly saw a lot of you know cursor as a choke point for downstream workflow creation and downstream tool recommendation [33:57] That probably emboldened us to make our second investment in Cursor. [34:01] We certainly saw the benefit that would accrue to Anthropic and other labs as well. [34:06] But, um, [34:07] I think it emboldened us to make [34:09] not only initiating investments, but also, you know, double down and triple down investments on companies that we were already a part of. [34:17] Yeah, and it took us way deeper into infrastructure too. I mean, we were admittedly slower than our peers on the application layer for AI because we were very worried about [34:27] how fickle they were when the weights of the models were getting wider and wider. And we spent a lot of time in infrastructure and we're continuing to spend a lot of time in infrastructure. So we talked about Nebius, but we are investing in chip layer. We are investing in data labeling like we were with scale. We are investing in pure play inference software providers like Ying and the team at Radix Arc that just came out of XAI. They're the inference team there. So we're going to continue to

[34:54] you know, lean into this view that we're in the early days of supporting the infrastructure to scale all the things that we want to do to the right of that. And to the right of it, there's a lot of conversations around durability when you get into applications that everyone has hit on over time. But [35:08] I think [35:09] Probably at this point a pretty consensus view is that we're rate limited on infrastructure and we need to figure out ways to scale that and [35:16] I think the three categories that we've seen just a dramatic [35:19] Um... [35:20] tailwind behind are one developer first companies [35:25] Um... [35:26] that are particularly impacted by AI, [35:29] Two is just AI infrastructure, all the things that Matt was talking about. And then three is security. [35:34] especially with mythos. The last six weeks for our security companies have been [35:39] Tremendous. And it's counterintuitive. When Mythos first came out, [35:44] I think the stock market thought that Mythos was going to kill a bunch of our security companies. Just look at CrowdStrike's stock price over the last six weeks. It actually is such a tailwind behind a lot of these companies, especially if you can be the platform that incorporates Mythos and AI security into your native platform. [36:00] That's one that we're really excited to and see a bunch of different benefits across many different companies. I want to get to that in a second and we can talk about Sayara. [36:08] How do you pronounce Radixarc? Radixarc? Radixarc. Radixarc? You guys said totally different things. You're going to have to ask the Indian team. I mean, I was reading it a couple of times. I'm like, nope, I didn't say it right. We have issues internally, obviously. And so who did that one? Who did that investment? That was Ivan actually. Okay. Oh yeah. Well, that's why I read about it

[36:38] conversation with Gilly Ronan not too long ago, prolific. [36:43] He's on a run. He's an incredible investor. Truly. I'm going to be talking to Syaira in a couple of weeks. We're going to be doing an interview with Yotim and Doug at Sequoia. He's very excited about that deal. So I'm curious from your standpoint. So how did you get into Syaira for people that aren't aware? We have to give some background for some of these things, but just break down that deal for us and how important they are right now. [37:13] its life as a data security company. [37:15] And, um, [37:17] We were initially investors in the first data security business called Varonis that was started in Israel. [37:22] Our partner, Kevin Camoli, is actually still on the board of Varonis. And so we knew something about the category. It's always been a good category, maybe not a great category, but Varonis is a super impressive business. And so... [37:35] The credit for Sayer actually goes to our partner, Philippe, that sits in our London office. [37:40] He does a biannual trip to Israel and meets all the interesting security companies that are there. And he intersected Yotam. And there are just these moments where you meet these compelling founders... [37:51] And... [37:52] There's just something about them. [37:54] With Yotam specifically, he came out of AD200. He had all the background of being a great security professional. [38:01] But he's also an incredible salesperson. You're going to see this in a couple weeks. So compelling. You sit with him for 15 minutes. He can convince you to buy something.

[38:09] or sell anything, you know, he's just one of those founders and he has this natural [38:15] grit you walk away from that meeting feeling like he's just going to build something amazing [38:19] And so we ended up co-leading the Series A with Doug [38:23] Um, [38:24] And Philippe led that out of our London office. [38:27] And that company had a really great trajectory, but you know, there was this moment [38:32] I remember it back in 2022. [38:35] where [38:36] Thank you. [38:36] One quarter didn't go as well as we were expecting. And we had a conversation with Yotam. [38:43] And we just believed in him and the opportunity. We leaned in in that moment and we actually led the series be. [38:49] out of our growth fund here. [38:50] And that was a moment where the category wasn't totally clear. AI had not taken off. I don't think ChatGPT had even come on the scene at that point. And the company... [39:00] was doing well from a product perspective, but it wasn't reflected in the go-to-market and the ARR ramp. And so that was-- [39:07] You know, that was an interesting investment, and that was also led by our partner, Philippe, and his conviction in the company and the founder. [39:14] And a year later, we ended up leading the Series D as well. And so it's one of our largest investments overall. As AI has taken off, data security has evolved into AI security because AI [39:25] Data is the fuel for AI. And so they're actually one of the, I think they're the highest valued private security company on the market. [39:34] And right in the tailwinds of everything that we're seeing around AI,

[39:39] It's a really, really impressive business. - It was while even talking to Gilly, he's like, "I think we sold too low for Wiz." - Yeah, look at CrowdStrike. - Wow. - Right? - Yeah. - Yeah, but in terms of the cybersecurity standpoints of AI and what's happening with agents, you're just creating like, [39:55] infinite [39:57] opportunities for breaches of all types. People are connecting. We did this interview with Merge and it's like, [40:04] they know because they see this firsthand, they're helping companies [40:07] integrate and connect with any tool they want. And interns can join teams. And all of a sudden, they're trying out these new tools, and they're compromised, and there's infinite amounts of potential threats. So you're partnered with some of the fastest growing companies on the market. How are they thinking about cybersecurity when they're [40:25] implementing more agents and they're thinking about scaling even faster? Well, it's a bit of an unknown frontier. I mean, the data exhaust from AI [40:34] is [40:35] unquantifiable. [40:37] the amount we talked about falling down the rabbit hole and creating stuff on AI. The amount of creation. AI has democratized [40:45] creation. [40:46] in effect. There are 10 million developers [40:49] Actually, there are more than 10 million developers in the world. 30 million developers in the world? You know, you're the cursor guy. More than that. But there are probably 500 to a billion people, or maybe even more, that are building on AI that couldn't do that before. And so... [41:04] I just think the surface area of what needs to be protected by security in general has grown so massively and is continuing to grow.

[41:11] at an exponential pace. But as Mythos showed, [41:15] six weeks ago, [41:17] Vulnerabilities have also [41:18] grown tremendously and exponentially as well. The capabilities of attackers have grown as well. And so I think the need for security products has only increased. Now, the question is where the value is going to accrue. And... [41:32] just like we're seeing in other categories. I don't think there are going to be a thousand different companies. I think it's going to be a few platforms. [41:39] that accrue most of the value in this market. [41:42] They're the ones that companies actually trust. [41:44] And so I think Sayre is one of those. CrowdStrike is one of those. Palo Alto is one of those. But the opportunity set has definitely gotten way bigger. [41:51] We haven't talked about token maxing yet. LAUGHTER [41:56] Why are you laughing? [41:57] We talk about token maxing a lot, but I'm like, hit us with it. Big fans. Yeah. Call him token map. [42:03] I'm just going to try that one. I don't think that one landed. Cut. Oh my god. You're drinking too much lumen. Yeah, what's in that stuff? No plastics. Yeah, I spiked mine. Oh my god. [42:17] - So on the topic of token maxing and people just cashing out ridiculously, or crashing out maybe is the right term, on token usage, I mean I know I do this for myself because I'm like take out all the N hyphens, like I'm doing ridiculously inefficient things over and over again. Have your teams, have your companies at all talked about like their token bills and how they're going to bring them down, like what are the best, like you can't rate limit.

[42:42] Right. [42:43] - It's actually interesting. There is definitely some, [42:47] episodic overconsumption happening out there, and that's grabbed a lot of the headlines. [42:52] I think my view and probably the house view though is that the overall trend is dramatically the opposite. Like we are just scratching the surface of token consumption globally, even though we do need and you know companies will weed out certain examples of token waxing. So we did this survey of developers and we asked them how many of them had [43:14] A CFO who was telling them to spend less on consumption versus more, and we actually found that seven times more companies are being told to let it rip and spend more. So I think the overall trend is towards a lot more consumption. [43:29] But yeah, I mean, the examples of overconsumption out there are a little bit ridiculous, and those will be curtailed. I think the overall trend, though, is a wave to the positive. I... [43:37] I think part of the dynamic is that the capability frontier is advancing so rapidly. [43:43] week to week, month to month. [43:45] You can do way more today [43:47] on AI, leveraging AI than you could even like three months ago. [43:51] And so, [43:52] I think it's a hard thing to say [43:55] We're still in the early phase of people discovering the power of AI. [44:00] And there's so much more upside to people [44:03] Um, [44:03] building on AI and standardizing on AI and like incorporating that deeply into their workflows, then like saving on the edges in terms of optimization.

[44:12] I think we'll get to that point, but I think we'll see that when the capability of Frontier starts to plateau a little bit and we enter a more mature phase of the game. [44:22] bullish or bearish on half a [44:24] billion dollars in token spend a month. [44:27] So [44:28] I'm very bullish that we're going to go well above that. - Very bullish. - Really? - Yeah. [44:34] Wow. [44:35] Very. [44:36] I think there's a reality of this that like the amount of indigestion we're gonna have related to token maxing is purely predicated upon the capability frontier as a rune set. And so if we stop [44:50] If you believe that we're going to at some point asymptote intelligence against these models, then we're going to have a lot of indigestion and 500 billion isn't going to happen. I don't think there's a lot of data out there that shows that capability improvement is slowing. I think... [45:03] The adoption is very early days. There are people that are on the extreme end of that in token maxing for sure. But it's buoyed by the fact that the capability frontier is rapidly expanding. And when you expand outside of what I would say is probably a very, very, very small percent of companies that are truly consuming tokens and truly leveraging AI for what it can do today, and you expand. [45:26] broaden that across the ecosystem of enterprises, prosumers and consumers, the token side of things is going to be [45:32] I think it's going to be just like every underestimated infrastructure forecast. [45:38] We're going to spend X and we always spend X plus some multiple of that every single quarter. Everyone revises up. And you're going to see revisions up on tokens for sure.

[45:47] Do you think it'll ever get to a tipping point? [45:50] You know, it's a philosophical point because like at some point, you know, if you go so far, you're talking about machines running a lot of things. And, you know, you can go as far as the Elon point of view where we need to harness the sun's energy to be able to create as much possible infrastructures to support this token consumption. [46:07] Maybe that's too far, but it's only going as far as the value [46:11] it receives back, right? And so there is going to be a governor against it if we don't see value back from it. Now, extremely far is where AI runs a lot in our lives and much, much further and much more penetrated than what we see today. [46:24] Today's episode is sponsored by VCX by Fundrise, the public ticker for private tech, allowing investors of all sizes to invest in venture capital. [46:34] Learn more at GetVCX.com. [46:38] Some of you may not have heard this yet, but our sponsor Public just launched something called Generated Assets, and it brings AI into investing in a way I've honestly never seen before. Here's how it works. You type in an idea like AI-powered supply chain companies with positive free cash flow or defense tech companies growing revenue over 25% year over year. Public's AI then dispatches a swarm of agents that scan every single US stock, evaluates them, and instantly builds a custom [47:08] why each stock is included. And before you invest, you can even backtest your idea against the S&P 500. So you're making decisions with real context, not just guessing. And beyond generated assets, Public lets you invest in stocks, bonds, options, crypto, all in one place. They'll even give you an uncapped 1% match when you transfer your investments over from another platform. If you want to build a portfolio that actually reflects your thesis, visit public.com slash sorcery.

[47:34] Paid for by Public Investing. Full disclosures in the description. [47:37] Founders scale faster on Deal. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit deal.com slash sorcery. That's D-E-E-L dot com slash sorcery. [47:53] Okay, well, you talked about Elon, so I want to talk about SpaceX. I'm just kidding. But you guys, you are the growth team here at Excel. We're about to... [48:04] apparently get $3 trillion IPOs [48:08] which is insane. How do you expect the market to handle that? Is it going to absorb that? Are we going to get a shift? What are the different scenarios that we could walk through? [48:18] I mean, I think it was a huge win for Elon to lead the charge and get SpaceX into indices early. [48:27] Whether or not you believe that's right or wrong, it was a huge win to be able to help buoy some of the float that's going to hit the market. And that to me is far more important than what happens in the next six months. And maybe that's us wearing our long term investor hat and thinking about things over many horizons rather than some sort of near term return threshold. So could it be rocky in the early days? Possibly. But I don't think what I don't think is rocky is the business models that are behind those companies. And I do think that if anything. [48:53] I would want to be long-term holders of that basket over many generations. [48:58] Well, first of all, I think... [49:01] It's a really good thing these companies are going public. [49:03] And there's a bit of a race to get out. If you look at the retail...

[49:08] you know, [49:09] Market in general they haven't had their mom-and-pop investor and [49:13] They haven't had a chance to participate in this incredible part of the cycle till now. [49:18] And so Elon reserving 30% of the SpaceX IPO for retail investors, I think is a really great thing. [49:25] It allows other people to invest in this movement as well. And I think it's a little bit why we're seeing what we're seeing in broader culture, revolt against AI data centers. It's because... [49:37] you know, culturally in our society, we've created this [49:39] haves and have-nots, and now everyone can participate in it. So I think that's a really good thing. I think, too, to Matt's point, there absolutely is value creation here. And so as that becomes more clear, and as these companies go public, and they have to report their financials and their growth, and everyone sees the phenomenal ramp that these companies are on, I think everyone is going to see the power of AI. And so I think that's also a really good thing. And so I think [50:04] This is just the power of the financial markets in the United States specifically. [50:09] I think we can absorb it. I think we will. I think you'll see a number of other countries and investors from all over the world and mom and pop. You know, it's not going to be a smooth up and to the right, but it's a really great thing that I think these companies are going to finally come out and everyone's going to be able to participate. [50:26] Miles. [50:29] - Sorry, those are two tough acts to follow. [50:33] I think there's some, [50:35] Some of the uncertainty around how these companies will price and trade in the early days reminds me a little bit of the

[50:40] 2020, 2021, [50:42] sort of dispute about direct listings versus IPOs. I do think there's a lot of unknowns about what the first 60, 90, 120 days will look like, but I do absolutely agree with Matt's point that [50:53] over the next [50:54] several years, I think this basket of companies will be incredibly valuable. And I agree with Arun's point. [51:00] that it's really good that retail can finally participate. [51:04] Okay, so as we close out, [51:07] I mean, that was a really optimistic... [51:10] place to end, but we're not done yet. What do you guys- How many loonin bottles are these? What are you guys most looking forward to in the next 12 months? [51:18] if you can think that far ahead. [51:21] I personally, and this is kind of piggybacking Arun's point, but I personally am very excited [51:27] to start putting some wins on the board for the world of AI outside of our small little bubble here in the valley. And I totally empathize with the [51:39] indigestion, frustration, concern around what AI is going to do and grasping on to all the negative scenarios that can play out from here. And I think in part it's because, you know, we just talked about token maxing. The reality is, [51:54] Only people on the far far frontier of leveraging AI today are really getting like tangible value out of it and that's changing rapidly. I'm very excited for that to disperse well outside of the valley and I'm very excited to start getting a [52:07] phone calls from friends that don't work in technology, that typically don't talk to me about my day job, aren't mad at me for my day job, to start to say things like,

[52:15] "Wow, this major efficiency unlocked in my life," or "This was fantastic from a health perspective, because I know someone in my family that's affected by this particular condition, and it was untreatable," or "Drugs were struggling to get through trials, and now that's changed." And that's not going to maybe happen in 12 months, but I hope we see green shoots of it, because we really need a narrative shift here around what we see day to day, and where we see this going, and what the public actually views as the risks of AI. [52:45] I'm going to piggyback on that answer because I like it. And it's my wife is an ER doc. She works at San Mateo Medical Center. [52:53] and she [52:54] recently implemented a product that I introduced her to, an AI company. [52:58] that [52:59] takes and optimizes the triage process. [53:02] which is when you check in, how do you rank people in terms of the severity of what they're showing up for and then match them to the proper care? [53:10] There's a ton of slack in that process. And the early results from implementing this is that it made them 100% more effective. [53:18] And when you think about that, when there are lots of people that show up to our ER that don't have health insurance, they show up there for their primary care, they show up there with some emergency. If you can be twice as effective using this in the very early innings before any of this stuff is optimized, just think about the promise. [53:36] That's one specific use case in one specific industry. And you think about this across all the industries that exist. [53:43] retail, manufacturing, you know, some of the frontier categories that we're looking at. That's what gives me confidence about the overall, like, opportunity set that we're about to see. And so I think that'll just become more clear in the next 12 months.

[53:57] I completely agree with this concept of real-world AI applications that make life better for average people. I think that's something to be really excited about. I'm actually going to take your question in a slightly different direction, something that I'm excited about over the next year. [54:12] to bring it back to sort of the Excel viewpoint, [54:15] Watching some of the younger members of this team thrive, you know, the generational continuity here extends from the partner role to the associate role. We have some people that have been here for a decade hustling. [54:27] practicing the craft, getting smarter every day. They've led some really, really exciting investments that aren't quite yet known. And I think we have some rising stars that are going to really, really [54:39] hit their stride and be known to the world in the next couple of months. So [54:43] um, [54:44] Ben Quazzo, Christine Esserman, Gonzo, Josh Fang, Rohan. So many people on the team that are just [54:52] Really really huge important contributors. I'm excited to see them get some get their flowers. I [54:57] Damn, those are all really great answers. What a sentimental one. I know. Oh, my gosh. I'm the sentimentalist. All the associates are going to work for Miles. I'm going to have no chance. There's some of the ones I accidentally left out. Well, Arun, Matt, and Miles, thank you so much. This was so much fun, and hopefully we can do this again soon. Thank you, Molly. Thanks for being here. [55:19] Thanks. Hey, it's Molly. If you enjoy our interviews, check out our newsletter, Sorcery.vc, where we deliver a once a week top deals and tech headlines email and also go deeper on our podcast interviews. Subscribe to Sorcery today. And don't forget to subscribe to the podcast on YouTube, Spotify, Apple or wherever you listen. Link in description to sign up.