ClickHouse CEO: AI Margins Need to Improve | Revenue Concentration Should be a Concern Transcript, AI Summary & Key Points

00:00 We're just getting started. This seems to be accelerating at an unprecedented pace. We haven't seen revenue growth like this in our lifetime. We went 0 1250 200 and we'll finish this year north of 500. Our guest today just got front of shirt sponsorship for Craven Cottage and for Fulham. Most importantly, welcome Aaron Cass, founder and CEO of Clickhouse, industryleading online analytical processing database management system.

00:24 Try saying that after a couple of tequilas. But they've just crossed 350 million in AR. And Aaron is incredible. He was one of the leading execs at Elastic for years. Before that, he spent 12 years working with the one and only Benny off at Salesforce. Now he's obviously the co-founder of ClickHouse, which is worth over 15 billion. We need to get to a billion dollars of ARR as quickly as possible.

00:50 I'd put the overunder at December 2027, and I would take the under. We could take the company public next year if we wanted to. >> Ready to go. >> Aaron, dude, I've done over a thousand shows. I've never had a setting quite like this for a show. So, thank you so much for for hosting at Fulham and Football Club. >> Yeah, total joy. Now, I want to start with just a little explainer on what is ClickHouse and what does ClickHouse become in a 5-year period just to set the scene there.

01:30 >> Yeah. Well, as one of our more recent investors, uh, I think you understand the thesis behind it, which is it's the world's most popular open source database, and it satisfies a very broad array of use cases, and it's used by nearly every AI native company, Anthropic, OpenAI, Weights and Biases. Um it's known for its lightning fast query execution and uh extreme resource efficiency in terms of storing vast volumes of data.

01:53 >> When we look at bluntly the fastest growing AI companies, I think the single biggest question that I have right now is where are we in the cycle? You know, I'm really good friends with very smart people and they go, Harry, I've seen this before. The levels of debt that we're seeing is insane. The the prices and the valuations are so exuberant. And then I also look at adoption and revenue scaling.

02:13 And I have these two paradoxical data points. >> We're just getting started. You know, one of the few benefits of age is experience. And so I've been through a few of these before in terms of the internet and mobile and social. >> How does it actually compare as a builder? Cuz we hear a lot of pontifications from venture investors. How does it compare for you?

02:32 >> Those cycles in my experience were much more gradual. This seems to be accelerating at an unprecedented pace in terms of how quickly these agentic experiences are maturing and how quickly these companies are growing. I mean, we haven't seen revenue growth like this in our lifetime. And so, and the demands for on the systems of these agentic applications is unlike anything we've ever seen.

02:55 >> Totally agree with you there. In terms of the revenue scaling, a lot of people always look to pick holes. One of the holes they often pick in the revenue scaling is the gross margin profile. Do we just see a new world of lower gross margins? We look at you companies like Fireworks. Lim was on the show and she was like, "Yeah, we're 30 35%. We hope to be more over time."

03:12 Do we just have a lower gross margin world or do we actually scale into traditional SAS margins over time? >> You know, a lot of these companies just seem to have unlimited access to capital right now. So they and they're growing so quickly that I think they can operate with gross margins that most public company investors would not be satisfied with.

03:31 I think as as long as they can demonstrate a path to margin expansion over the course of the next few years while still growing at these unprecedented levels with very healthy balance sheets, I worry less about gross margins like we did 5 years ago in traditional enterprise software. >> What should I worry about then as an investor as I think about navigating this new world?

03:53 Again, you have the best customer base that you could almost ask for. I was talking about, you know, some of the fastest growing companies on our wall the other day and you're like, well, they're both customers and it was just universal. The best companies were using Click House. What should I be concerned about worry about when I'm investing today looking at these names?

04:12 >> If you were to come down to one, if you were to say this, what's the single biggest risk? >> Yeah. >> Would be durability of revenue because the switching costs that you and I talked about are very high for infrastructure software. the switching costs can be very low for agentic applications. Um, and we're seeing that with these model providers that are leaprogging one another what seems like every other week.

04:38 And I would call into question the durability of some of the revenue for some of these AI applications. When I look at like an anthropic IPO at 2 trillion and you look at claw code being the kind of dominant Trojan horse behind that would that not fall into the low switching cost. >> I would put it in that category. Now it's that's not showing up in our use of cloud code because our anthropic spend is up 100 times from what it was at the beginning of the year.

05:06 >> Can how much do you spend on anthropic? >> A significant amount. You know we I we weren't doing enough at the turn of the calendar year. So I sent an email to the company and the subject was the AI awakening and I said I think we're moving too slowly and I'm not seeing the adoption of these uh coding applications for example that I would expect to see for a leading database provider like click house >> and the company rallied uh to the call and we've seen just this explosive growth in terms of our use of these of

05:36 these applications um and we're now looking at adopting more open weights models whereas just the traditional frontier labs, but I think anthropic specifically and open have the benefit of being both the model provider and the harness provider that the open weights models right now are behind in. >> Do you think that is the right approach though? Do you not think it's better to be independent because then you can actually do optimal model routing for different tasks versus being tied into one model provider because

06:02 they are your harness also. >> Yeah. I mean for example some of these open weights models we'll use for code review but we won't necessarily use to ship production code >> because we have concerns about the output inference. >> Totally get it. You said there about I love this the AI awakening. The challenge then becomes and we had the president of Uber on the show who was much more skeptical of the ROI that it generated internally.

06:26 Um, how do do you think about token budgeting cost when suddenly you're incentivizing this, hey, run free and then the bill might come at the end of the quarter? >> Well, the primary measure that we care about, as you know, is revenue growth. And if we see the sustained revenue growth that we've experienced over the last 3 years and we're a very efficient company as you know um some would argue we're too efficient then I worry less about the expense that we're incurring on coding agents for example because we're

07:00 covering a very broad surface area and our road map is accelerating at a pace that we've never seen before and as long as we can continue to ship features that satisfy this very broad set of use cases then I can always rein in token consumption and the cost of tokens as we know is going down not up and so they're becoming more efficient not less efficient but our revenue is growing faster than it ever has so I'll take that trade any day of the week >> you said that you're too efficient in some people's eyes where

07:27 should you have spent where you didn't spend and how do you reflect on that >> so we've got about a 100 quota caring salespeople for example and I think you know our revenue scale is significantly more than 100 million And so our average uh rep productivity is quite high relative to the industry average. Our competitors that we're going up against, some of these very large data warehousing companies, some of these very large observability companies have thousands of salespeople.

07:55 They wake up every morning thinking about one specific use case. Our sales people wake up every morning thinking about 10 different use cases and there's only a hundred of them going up against an army of 2,000 3,000 sellers for some of these very large data warehousing companies. So I think the one thing and if I look back over the last 2 years that I wish I had done differently was increasing sales capacity.

08:18 >> That's so interesting. And so you should have invested more in sales team sales leaders earlier. >> Well, I really wanted the pressure for the first few years to be on product and engineering because I looked at the two most popular infrastructure software companies over the last 10 years and I distill that down to Data Dog and Snowflake. They were both successful but through very different avenues.

08:35 Data Dog had this PLG self-service developer motion so you could get started, deploy an agent, instrument your application, never talk to anybody in sales. Snowflake went heavy after the enterprise through, you know, very expensive sales and marketing. I just thought it was going to be a lot easier to follow the data dog playbook than the Snowflake playbook.

08:54 And it it proved to be the case, but at some point you need to layer in an enterprise sales motion on top of some sort of PLG distribution. What do you know now about layering on that enterprise sales motion that you wish you had known before you started? >> You know, I spent 12 years at Salesforce and so I was kind of a a student of of Mark Beni off's playbook and so many lessons learned through that experience and this was a long time ago.

09:17 I joined that company 24 years ago. >> What was your biggest lesson from working with him? If there was one takeaway >> that you can overestimate what you can achieve in one year and underestimate what you can achieve in five. When I started, it was a three-year-old startup and it was basically a glorified contact manager, you know, Salesforce automation.

09:36 Um, we essentially said what you're traditionally using ACT or gold mine or using a spreadsheet, you can use Salesforce for. But Mark had this bigger vision and he said we're going after Sei, SAP, Oracle, Microsoft. We didn't have the product set to go after those competitors. But he was such an incredible marketer that he created this perception in the industry that some of the largest companies in the world could adopt this technology and that we would deliver on a roadmap that would satisfy the requirements over

10:02 time and he did. >> You said the word road map multiple times in different contexts there but um I do a show every week with Jason Lapkin and Mario Driscoll. It's very successful and popular which is fun but Jason said last week that if you are not well into your 2027 road map already you are behind. Are you seeing dev acceleration because of AI tooling?

10:22 And how do you measure actual ROI internally when attribution is really difficult? >> Yeah, we're shipping products faster than we ever have. We're entering new product categories um two years ahead of where we thought we would. >> Really? >> Yeah. Both organically and inorganically. Um we've made six acquisitions over the last four years that have propelled us into new use case areas.

10:44 and our organic road map shipping features like stateless workers which is essentially infinite compute we've shipped those faster than we ever thought possible how do you think Nikash Palato is a very good friend of mine he's a very brilliant M&A machine how do you think about the buy versus build versus distraction what's that internal decision maker for you when you think about those six acquisitions >> if I think that our product and engineering teams can uh innovate in a specific area that we're not in today, then

11:14 I'll let that play out organically. If I see uh a founder or group of founders that are building on top of Clickhouse that are getting into a category that I think is going to be, you know, a future component of what we build as an ultimate data platform, then I think about doing something inorganically. And we partnered again with six different founders, uh actually more than that.

11:38 Some of these companies have multiple founders. Our most recent one earlier this year was Langfuse. Yeah. Out of Berlin. >> Um which is three incredible founders entering agent observability. Every enterprise in the world is going to need this technology. >> In terms of like the agentic future that we face. How does software and product decisions change when you no longer cater to humans but you cater to agents?

12:02 Well, even four or five years ago, software applications were designed for a specific persona that had a role within an organization and their query patterns were very predictable and whether or not you ran a report or you looked at a dashboard, agents don't have personas. And so while you would traditionally use a specific application for observability or data warehousing or CRM, agents expect that they're going to traverse across all these applications and they're not going to be constrained by access.

12:34 They're not going to be constrained by latency. And the experience is going to be defined by the slowest point in that chain. And so what's the number one requirement for agent query patterns? low latency because they're executing dozens of SQL queries simultaneously across all these different systems and the most important requirement is the unpredictability of those query patterns, the responsiveness and the fact that they're much more exploratory than a traditional human, you know, report or query.

13:07 Sure. Can I ask you when you see the explosion of agent queries in this way you'll also see the increasing awareness from agents to be more costefficient to what extent do you think you see a race to the bottom on pricing with the awareness from agents that they can't have an explosion of queries and cost being the same? >> Well, I don't see agents necessarily being costefficient.

13:26 Uh I don't see them thinking about consumption and budget like humans do. Um >> and my mother have that in common. But the but the volume of queries is exploding at a rate that we've never seen. And so it's requiring these systems to completely rethink, you know, their pricing models, their consumption patterns, access patterns, and not only are agents hammering these services in an unprecedented way, but they're actually now selecting the underlying infrastructure.

13:57 And so, you know, while you could go to claude or you could go to chat GPT and say, you know, what technology should I use for this specific use case, I'm thinking about a future where the agents actually select the infrastructure stack behind the application and positioning Click House to be the default database for the next generation of applications that agents are building, not humans.

14:19 And just so I understand, when we fast forward to that threeyear preference stack for agents, it's number one latency. It's number two >> efficiency. >> Efficiency. >> Yeah. I mean, Tesla, for example, is ingesting a billion events per second into ClickHose. Like that throughput is unprecedented. And so you need the ability to both ingest that efficiently, store it efficiently, and then be able to query that efficiently at a a fraction of the cost of traditional database technologies.

14:47 There just isn't another technology in the world other than Clickhouse that can satisfy those requirements. >> When you think about that agent buying process, trust and security are so important. Everyone is saying that we're at this golden age in terms of cyber security and we see more and more security hacks. How do you feel about the security vulnerabilities that come with the agentic future that you are planning for in three years out?

15:10 More on the enterprise side. We obviously see it on the personal side, but more on the enterprise side. Well, I think it's going to require multiple deployment models. So, you need to be able to consume services via a cloud offering through any one of the three major hyperscalers. You're going to need the ability to manage that data on prem behind your VPC in your firewall.

15:29 So, you're going to need to have the flexibility to deploy these applications as you best see fit, especially in the indust in the enterprise where you've got highly regulated industries, a lot of data privacy concerns, a lot of compliance requirements. And so as a supplier to these customers, we think about how do we support them dependent on their deployment preference.

15:51 And you know that's a tricky road map to maintain because most companies pick one of those avenues. You know I mentioned Snowflake and Data Dog. They're primarily cloud services. You know you look at more traditional technologies that run on prem and so if you force your customer into a specific lane you know you're limiting the addressable market that you can go after.

16:11 When you look at the agantic future of the 3 to 5 years that you're planning, what seems insane today that you think will be quite common place in 3 to 5 years? >> We can talk about the fact that agents will need to have an identity. >> Love that. >> that they don't have today. They'll need to have a budget. And how do you authorize an agent to >> what you mean?

16:30 Agents need to have an identity and a budget. You know, if you ask Anthropic how they chose to use Clickhouse, they'll tell you they asked Claude, "What technology should we use for this specific observability use case?" And Claude suggested Clickhouse. I'm thinking about a future where they say, "Hey, we need to build an application, provision the underlying stack."

16:49 So you've got a database, you've got networking, you've got compute, you've got storage, and the agents actually making that selection process, but they need to have authorization, they need an identity, they need to have a budget, right, to be able to consume those services. We're not there yet today. So if I were in your shoes, I'd be thinking about what companies are best positioned to give that agent everything they need to build a software application.

17:16 >> I'm sorry, help me understand that. Where should I be looking then? And why is that not included in the harness? Like, why is that not in the settings and preferences of the harness and the model provider? >> Because most companies aren't just going to let their agents run wild and build whatever they want and consume as many resources as the agent deems fit.

17:32 There's going to need to be some sort of governance and oversight with that consumption. And we're not there yet today. There's some human that is observing that consumption. They're monitoring the agentic spend. They're putting controls in place uh to make sure that things don't get out of hand, that they don't access enterprise data that they shouldn't, that they don't spend a certain amount of money that they're not authorized to.

17:54 If you look out 3 to 5 years, those agents are going to be fully autonomous. When we think about I I said one that I think is very clear is also like specialized models. You know, we both know Linet Fireworks. I think every company will have their own model, you know, trained on their own data. They'll supplement their own data with you, additional data.

18:12 But I very much see that being common. Do you see a world of millions of specialized models? Do you think you actually have your anthropics and your open AIs take the large majority of enterprise and only very specific cases have specialized models? How do you foresee that given the access point you have? >> I think we're going to have both. I think you're going to have specialized models for specific use case like legal tech.

18:33 If you look at Harvey for example, I know they're I think leading the category in terms of specialization, but I think the large frontier labs are still going to be the dominant providers in the space. Can you help me out here? I'm an investor in Lagora. Why is that a better approach than Loras who obviously have not decided to dedicate their resources to building out specialized models?

18:51 >> They they consume less clicks is the short answer to the to the question. We're an infrastructure provider. So like we're picks and shovels clickous. So we're not like picking winners in these categories. Lorra could be a bigger company than Harvey a year from now. I I can't predict the outcome of these specialized providers. I don't know their revenue scale.

19:08 What's the average customer spend on Click House? >> Uh, it's a good question. So, you know, we define a customer once they hit a certain uh revenue scale. We've got a long tale of customers that that consume some of our services, but once they actually are in production at scale, we count them as a production customer. And uh there's a chart that you can see with our our revenue growth and our and our customer growth.

19:32 And you can see they're growing at a at a at a similar rate, but revenue is actually growing a little bit faster because our customers are growing faster than new customer acquisition, which is the most important function for a company of our size is how many new customers can we onboard in any certain period because we've seen the expansion characteristics of these services are unlike anything I've seen in my career.

19:56 You know, we had over 130% net dollar retention uh at previous companies. We're over 200%. Because these use cases expand. You could be using us for data warehousing. Then you use us for real-time analytics. Again, these historically were like siloed applications inside of an enterprise. People are now saying, "We want to put all of this in one data repository.

20:14 We want to build applications against it. We want to expose it to our customers. We want to expose it to our partners." And so, we're just seeing this rapid growth. Average customer spend. I mean, we've got customers that spend tens of millions of dollars with us every year. We've got customers that spend thousands of dollars with us every month and everything in between.

20:32 So averages can be a little bit misleading. If I were to look at the midpoint, probably around $100,000. >> When they are making that buying decision, which competitor do you fear the most? >> The one that isn't in the market yet. >> Huh. >> Like our competitors are right in front of me. I can see them. I know their strengths. I know their weaknesses.

20:49 And what I worry about is the technology coming from the rearview mirror. I worry about the next click house. like people really didn't see this technology coming. It was open source 10 years ago. That's when I first discovered it. It burst on the scene. Thousands of companies adopted it, but there was no company behind it. And so people dismissed it as just another popular open- source database.

21:11 There's been a lot before it. There will be a lot more after it. So I worry about what's the company that's going to disrupt us in the same way that we're disrupting the competitors in front of us. >> You mentioned obviously Clickcast being an open project and you know the amazing early traction that you had. When we look at the percent of tokens that are now going through open models, it is increasing exponentially almost it seems and it is removing from frontier models.

21:36 What percent of tokens will go through open in 3 years versus Frontier? >> Well, the easy answer is 50/50 in the same way that what percentage of enterprise software today is open source versus proprietary. >> I think it's a pretty even distribution. Look at the big two. >> That would be a controversial prediction though. >> I don't Look at the big two data warehousing providers, Snowflake and Data Bricks, >> right?

21:58 Snowflake is primarily a closed ecosystem. Data Bricks is built around open source. Like would you argue which one's going to be bigger? >> Data bricks >> perhaps, right? But then you add Data Dog. Data Dog's primarily proprietary, right? Other open source observability tools are open. Which one's going to be bigger? >> Data bricks. >> In observability, I would argue data dog over data bricks.

22:23 >> Data. Well, you never know. 3 to 5 years is a long time. >> Underestimate data bricks. It's a great company. >> You know what's shocking when you say that? It's like 5 years ago, Chat GPT wasn't out. >> Maybe >> that that's the stark wow. >> I mean, are they going to get into infrastructure? Will they be offering databases as a service? I wouldn't dismiss Anthropic and OpenAI as core infrastructure providers.

22:44 >> Really? >> Correct. Yeah. Not at all. I don't see them as competition today, but you see how they're entering new categories so quickly. Just imagine the surface area they're going to cover in three years. >> They're building their own chips. This would not be extraneous. Totally get that. But the conventional wisdom would be that you see 90% through open, 10% through frontier.

23:04 You know, in the conversations that I have today, everyone basically says frontier models will be useful cancer, climate change, extremely valuable but very few to us and then the rest of everything will go through open. You don't agree with that? I I don't because I think it especially in the enterprise they want provisions and protections that potentially openweight models especially those that come out of China cannot provide around indemnification for example and output inference and it's going to limit the use

23:45 cases that those openweight models are adopted for. Now again it's very important that we distinguish between openweight models and open-source software. Okay, we're in the latter category. >> Can we >> my predictions on enterprise adoption around open weights models is very different. >> Totally get that for those that do not know and I'd like to be not just for kind of Silicon Valley inner engineers open weight versus open source in a minute.

24:16 >> Let's focus on open source. So open source is essentially where anybody can inspect the source code. Anybody can modify it depending on the license that it's governed by. You can deploy it with no attribution to the authors of the software. You can modify it. You can monetize it without any relationship of the people that are actually developing it.

24:36 You can contribute to it. You can fork it. Now open source licensing has evolved significantly over the last 5 years. That affects some of those implementations. I'm pleased that you said there that you don't agree with that and that actually there will be more concern around using open weight models and potentially Chinese models. Um when you when I speak to people on the show they actually say that the biggest enterprises say I'm more scared to work with frontier providers than they are open source Chinese models

25:06 because people don't trust the statement zero data retention. It's basically you saying just trust me like I got you. You know, some people will take you at your word, many will not. And so I think a lot of companies worry about sending their source code, for example, to a frontier lab. >> Do you see that? >> I do. I see it every day. I mean, we have our own concern internally, right?

25:29 Because you worry about the output from that code generation. You worry about, you know, third party indemnification if you were to consume code that's being derived from another repository. So what do you do in that case? You then go to an open model. >> You limit the use cases. You know, you can use it for code review for example, but maybe not to push production code into an environment that your customers are using.

25:54 >> But then what do you trust? You trust an open Chinese model with the more sensitive data. >> It depends on the use case >> cuz again this is what someone said it on the show the other day and I was like, "No, you put it wrong." like you must have got that confused cuz they said for all like kind of less sensitive things we use you know anthropic and then for everything more sensitive we use an open source Chinese model and I was like you mean the other way around and they were like no no no that's the right way

26:18 around. >> I think when you when you need the the legal protection that most enterprises do you're going to want to work with one of the frontier lab providers. I think there's too much security concern around some of these openweight models. >> Is it justified >> today? I think it is. If I look out a year or two from now, I think a lot of these concerns will be addressed.

26:43 >> You don't buy the back door to the CCP or >> you know, I personally don't like to speculate that, you know, by using some of this software you're somehow going to be engaging in some nefarious >> Chinese espionage. >> Yeah, exactly. I mean I I it's quite fantastic to go there. >> Listen, you're a CEO of one of the kind of most prominent open companies in the world in terms of Clickhouse.

27:08 When we look at the American open models, we significantly lag behind. If I were to say, Aaron, I want you to spearhead open American models. What would you do to encourage incentivize us to dramatically leaprog China now in our open ecosystem? Well, obviously I'm a huge fan of open source and open weights models. So, I don't think that any sort of government intervention uh is uh is wise um in terms of limiting the adoption of these technologies, the distribution of these technologies because I do think you know open

27:45 source and open weights models are the future and the future is defined I don't know 3 to 5 years. It's really hard to look out further than that. Um, I personally wouldn't take your capital and say I'm going to deploy it to develop an openweight model. >> Do you see more and more enterprises want to go back on prem in this day and age? >> We do. >> Yeah.

28:07 And even companies that I thought would never be going back on prem are talking about going back on prem. like some of the most innovative digital native companies in Silicon Valley are now thinking about moving their stack from you know one of the hyperscalers to an on-prem environment. >> When we think about agentic workflows a lot of what we've said kind of agent identity um how sophisticated are traditional enterprises when you speak to the CEOs when you sell to them what you see and what's the chasm between what

28:38 you see and what they know >> narrow >> it is. Yeah, I mean I was at Canary Warf yesterday meeting with some of the largest financial services companies in the world. They are leading the way in terms of they're adopting new technologies in a way that I've never seen in the past. A lot of the times historically the sales cycles into these big firms would be measured in years, not quarters, right?

28:57 They're now adopting technologies much faster than they ever have before. >> So you're seeing sales cycle compression in this day. >> Yeah. Um, I mean, open source aids in that because you can get started without any sort of vendor relationship. Uh, PLG products like data dog and click house aid in the fact that you can just spin up an environment without ever talking to anybody in the sales organization.

29:21 You can have this frictionless experience to where you can evaluate, deploy, scale the product without a traditional enterprise sales process. >> I think people just fundamentally misunderstand the GTM and the business behind it. What do investors get most wrong when analyzing your business? >> Investors often say like where's where's the moat? Like how difficult would it be for me to simply redistribute ClickHouse?

29:45 Uh what's the risk about one of the hyperscalers offering click as a managed service? You know, it's been done before where AWS or Google or Microsoft takes your open source and they redistribute it as a managed service. So now you're almost like competing against your core database. uh that has been an issue in the past. I think if you can maintain a competitive advantage with your cloud offering or your proprietary features that are very very difficult to replicate then you can maintain that moat and I think very few

30:18 open source companies get that right. I do want to weird transition back but when we said about kind of agent preferences and agent you know anthropic using anthropic to choose click house does that mean like developer relations developer community becomes less important and how does the future of brand change when agents become decision makers? So I talked about you're building an application like let's you're building a dating app right so you can build it over the weekend you can vibe code it right and in theory

30:48 that agent can select the stack right it can select a managed Postgress service because you want to support transactions it can a managed click house service because you've got analytics uh and everything in between. You still have an enterprise buyer. You still have a huge data warehousing project at a top bank or a telco that's going to be driven by an engineer or a developer and there's still going to be a human that's making that architectural decision on are they going to use ClickHose?

31:18 Are they going to use Snowflake? Are they going to use Data Bricks? You've got an observability workload, are they going to use something off the shelf like Splunk or Data Dog? Or are they going to embrace open source and use something like Clickhouse? There's for the next decade there will still be a human involved in that decision loop. >> Totally get that.

31:34 So it doesn't change the investment and commitment that you have towards brand. >> Not at all. Yeah. Because budgets are still controlled by people, right? And budgets correlate to technology decisions. And so a few years ago, I started doing things around awareness. Like for example, for AWS reinvent, Amazon's big cloud conference in Las Vegas or Google Next, I partnered with the Chain Smokers and I had them perform because I said there's not one party that everybody at reinvent wants to go to.

32:03 It's a bunch of like shitty restaurant buyouts and happy hours. I want one party that 60,000 software engineers are, you know, jumping over themselves to get access to. So I partnered with Alex and Drew and we started performing these concerts and they started performing these concerts and in support of ClickHouse. Um so then I thought about how can we even drive broader awareness and so a sports sponsorship came to light.

32:26 I'm not the first person to do this as you know you know a lot of other companies that are sponsoring Premier League teams. >> Sure. And so we we did a financing earlier this year and then we extended it and brought in some strategic investors like yourself and David Sachs and Michael Dell and JP Morgan. We didn't need the capital. We had a billion dollars on the balance sheet.

32:46 Uh >> I quite like the affiliation to those names. So thank you very much for including me. David Sachs and JP Morgan and very helpful. >> Happy to. So I thought what better way to spend this new investor money than to sponsor an English Premier Football Club in London. >> Why football? Why English Premier League? You can sponsor F1, you can sponsor Lagora, do golf as well.

33:05 Why football? >> Well, I love the sport, but let's put that to the side for a minute. I think the value of these sponsorships obviously come in two forms. The first is awareness. And as we saw last night against Chelsea, this is a game that's being televised globally. So, you've got millions of viewers that are looking at your brand. You're getting impressions obviously.

33:25 The second, which is obviously easier to quantify, is hospitality. And we're sitting here at Craraven Cottage along the tempames. I think this is arguably the best sports experience in the world and I've been to many. We had 20 executives last night attend an intimate Michelin grade dinner. We had, you know, the Seale executive come from Paris, one of the largest banks in Europe just to experience that.

33:49 And those types of relationships are extremely important, especially as we move up market. Do you think we will see the price of sports assets dramatically increase even further still? We had obviously Ven Kosler by um I always get it wrong but I'm a Brit so forgive me. It's not the Sea Gulls, it's the >> Seahawks. The Seahawks. >> Yeah. Which obviously I didn't love to see considering both Coastal is an investor in Click House, but he was a minority owner in the 49ers.

34:17 >> Why is that bad? Why don't you want to see it? >> Because I'm a San Francisco 49ers lifetime fan. >> I'm from Fulham. I don't have a clue. I thought it was the Seagulls. would be like, well, you know, you turning around and investing in Chelsea, for example, you wouldn't do that obviously as a Fulham supporter. >> I obviously would not do that. No.

34:30 Uh, unless there was significant monetary gain, in which case I'll do it in a second. >> Well, I was a very savvy businessman, so I'm sure Josh buys the Lakers for 12 and a half. And I'm like, to the point of like underestimating where value occurs, do you think we'll see 20 billion sports teams? >> I do. I mean, we just saw that with the Lakers. I think it was the most expensive sports transaction in in history.

34:56 12 a half. >> Uh it was reported that the Seahawks sold for 9.6 billion for example. Um it's obviously it's well reported what the English Premier Clubs trade for. I do think that I mean it's a experience you simply can't replicate through technology or anything else. There's something very visceral about it. We felt it last night like to be there at the pitch, 28,000 rabbid fans on their feet to launch the Premier season, uh, Southwest London derby, Chelsea versus Fulham, 3 to2, five goals.

35:28 Like, what more could you ask for? >> I totally agree. And I think also in a world of AI, you actually crave those experiences more. That and music in particular, I think will be two of the most kind of blossoming. Totally get you that. How do you think about like spend for it? Like I'm not asking you how much you paid for it, but like how do you think about ROI effectiveness on sure?

35:49 We're going to commit a lot of budget to being in front of shirt. >> Well, I can, you know, we had 20 guests last night, uh, budget owners from some of the largest companies in the world. Half of those are customers, half of those are prospective customers. So, I can very easily measure the spend that I can gather from those that basket of accounts over the next 12 months.

36:08 How much of that do you solely attribute to a sports sponsorship? That's very difficult to assess. We could see top of the funnel metrics improve in terms of website visits, new trials that could be a derivative of the awareness that we're driving through the sponsorship. Kind of one of those two ways, if not both. I was talking to your investors and you know, many of them said every round I've wanted to invest more in in Aaron and Click House and he always cuts me back.

36:35 What do you know now about fundraising that you wish you had known when you started? The credit really goes to Yuri and Alexe. Like they're my two co-founders are spectacular. The best engineers I've worked with in my career by a very wide margin. And so I'm happy to be the interface to the investor community and maintain these VC relationships. But really it comes down to how differentiated our engineering culture is.

36:57 In terms of cutting back investors, I mean, as you know, when I evaluate an investor relationship, it really boils down to the value that they're going to bring, the customer introductions that they're going to make, uh, the advocacy that they're going to help with. >> How do you determine that? Everyone sells a good game. VCs, we sell cash. We get good at selling.

37:16 >> I reference them like you would in any other relationship. >> So, I talk to the companies that they've invested in in the past. I say, "What's it like to work with Harry? What customer relationships has he made that have been valuable? How's he helped with awareness from his social presence? Has he helped with recruiting? Has he engaged with your employees?

37:34 How does he work with other investors? Do people perceive it as a positive to have men on the cap table? And those all need to be a unanimous yes before we start working together. >> Do you think you raised aggressively enough? We're seeing a new world by capital. It's more and more remote in a lot of cases. You know, I'm trying to build a generational company that outlives me.

37:55 And I think right now a lot of people look at fundraising as a very short-term exercise. And they want to have this consistent and steady step up in valuation. It's good for your employees. You give them liquidity through tender offers. It's good for recruiting. It minimizes dilution. It bolsters your balance sheet. Uh it lets you forward invest. All of those things are true, but I'm thinking about a company 20 years from now, not 2 years from now.

38:24 So whether or not we raise at 15 billion or 25 billion in 10 years is irrelevant, right? We need to have the right investors involved. We need to build a very durable, long-lasting, sustainable company. We need to get to a billion dollars of ARR as quickly as possible. The most important metric for the company is new customer acquisition. We add hundreds every month.

38:44 Our gross retention is north of 99%. Our net dollar retention is north of 200%. The addressable market we're going after is absolutely enormous. So I think less about valuations perhaps than I should. >> When will we hit a billion an era? >> Within the next 2 years, if not sooner. >> Give me a date. >> We can do a bet. We can both do a bet. All right.

39:08 I'd put the overunder. Yeah. >> At December 2027. And I would take the under. >> You think you'll get that before? >> I do. >> I'm going to go for Feb 28. I think now it's like 18 month. That's more than 18 months. Yeah, it's 18 months. >> I would definitely take the under on that time frame. >> What do you mean? >> Oh, yeah. Yeah. Yeah. Yeah. >> We're at 250 now.

39:32 >> We're well north of that. >> Oh, well that's unfair. You said they're about tenders. We see them more and more for employees. And I think talent acquisition is one of the hardest things today. I actually got in a lot of trouble the other day for this. I said if you are trying to hire a star talent today, you can't. Open AI and anthropics simply pay and they go to the frontier model providers.

39:53 Is that true or was I being glib? >> I think it's true depending on the category that you're in. I think if you're a digital native AI startup in San Francisco, it's a very difficult employment environment because you're competing against open eye and anthropic and others um that are extremely well capitalized and are putting offers that are extraordinarily aggressive >> into the market.

40:15 I think if you're a infrastructure provider like Clickhouse, uh we look for a slightly different um profile, you know, we're looking for database engineers, people that have experience with distributed systems. Um slightly different than what the Frontier Labs are hiring for. We employ people in 27 different countries. Um which gives us a competitive advantage.

40:36 So I can hire engineers in Portugal and Germany and Singapore. Um you know, we've got singledigit uh attrition. So we've got extraordinary high retention. Um we have done some structured secondaries um and we'll continue to do so over time but not with the frequency that I think some of the younger companies are doing. >> So I am you know controversial in many ways.

40:57 Uh one of them is because of my vocal uh expressions about remote work. Why am I wrong? >> I don't think you're missing anything. I'm of two minds and I contradict myself constantly about this topic because I spent 12 years at Salesforce. I was in the office every single day, 5 6 days a week, 10, 12 hours a day. And it was during this extremely formidable time in my career.

41:20 I learned so much from those experiences being in the office amongst my colleagues and peers, learning from people with more experience than I do than I had at the time. When I started this company, it was during co and so we kind of had to be distributed by design. And I started it with some Europeans and so people were in Europe. I was in the Bay Area, my co-founder was in Utah.

41:40 And so, you know, we started the company. We grew very quickly. We found engineers that had a very unique skill set and they weren't all in the Bay Area. They weren't all in London. They weren't all in New York. And so, we built a distributed company. Fast forward to where we are today. We're almost 800 employees. We'll be a thousand by the end of the year.

42:02 We are introducing uh in-person options for our employees. We don't have this draconian return to work mandate or return to the office mandate but we do have offices and we have a huge office in Amsterdam. We have an office here in London, New York, the Bay Area. >> Is that specialized around different functions? >> Not at all. >> Really? >> Yeah. Both engineering and go to market and we're seeing you know increased participation across the employee base and increased demand for office space.

42:29 And if I look at a year from now we're not going to have six or seven hubs. We have an office in Singapore. We have an office in Sydney Australia. We have an office in Tokyo. We're not going to have six or seven. We're going to have 16 to 20 offices around the world within 12 to 18 months. >> If you could have your way, would you not have everyone be in office in some way?

42:48 >> I I wouldn't and I'll explain why. Uh we're a very international company uh by almost every measure. Over half of our revenue comes from outside of the US, 40% here in AMIA, 10% in Asia. Over half of our customers are outside of North America. And so we need to support our customers in a variety of different languages in a variety of different time zones.

43:10 I mentioned we're live in 36 different regions around the world across all three hyperscalers. There's no way that you can centrally manage that from one location. You need to have people in every single time zone. You need to have relationships with the hyperscalers in region. We go to market with AWS. We go to market with Google Cloud. We go to market with Azure.

43:27 I flew to China to launch a partnership with Alibaba. like you're going to have you're going to need local language speakers to maintain those partnerships and you can't do it from one or two or three centralized hubs. >> What phase of company growth was most uncomfortable? When were you the teenager at the wedding? >> The most uncomfortable phase was immediately following our product launch.

43:49 It was at the exact same time chat GPT launched. And these database services are different than consumer services. They take time for companies to evaluate and adopt. It's not like you're just going to use chat GPT overnight. You're going to get to 100 million users in two months. So, there was this six-month period and it it shows up on that bar chart of revenue growth where revenue was slow out of the gate.

44:12 Now, we've hit this inflection point and revenue surging now that we have over 4,000 customers. But those first 6 months, you know, I raised $300 million at a valuation that was hard to justify because we had no revenue. We had no product. >> Your price was quite chunky. I mean at like 50 million in revenue you were priced like $6 billion. >> Again just a point in time like you don't get credit for where you are in my LPs and I do but your DPI is not what you know uh Gilly Ren is.

44:42 I mean it's a point in time >> right? Yeah. Well, but you're giving credit for the next year. And that's how venture investing works in my experience on the other side of the table, which is you're not getting priced for where you are at that point in time. You're getting priced for where you're going to be in 12 to 18 months. And if you have a track record of execution and you have a track record of overachieving against your targets, then you can garner a multiple that is disconnected from the public markets.

45:09 >> Which round felt most expensive and which found felt most cheap? uh the series B that CO2 and altimter jointly led at 2 billion uh felt expensive. We had no revenue. We had no product. We had control of an open source database. We had no customers. We had 15 employees. So that one I felt like put a pretty big target on our back. And that's when the pressure really started to mount uh on building this differentiated product.

45:39 Um, and it took us a year and uh, those were some long days, you know, thinking about when are we going to get this product into the market, what's the customer reception going to be? We knew there was some latent demand. I didn't anticipate there was going to be this much sustainable demand 3 and a half years later. So, that would have been >> also you didn't know that the AI wave was coming in the way and speed that it has done, which has been the propulsion of all generations.

46:07 >> This was 5 years ago. I had no idea. I knew that Clickhouse was the most resource efficient and performant database in the world and so I knew that it would satisfy whatever trend was going to come because in the database world it comes down to price and performance. A lot of other attributes in terms of feature completeness etc. But that's really what it boils down to.

46:28 And I knew that ClickHouse had an advantage on both. >> Which one was the most cheap round? >> Probably the current one. >> Yeah, I I felt this too. And I know it's obviously it's it's a lot of money in terms of $15 billion, but when you look at what you have, the customers, the revenue, the slope, I'd much rather pay more for more than less for less.

46:45 Does that make sense? >> It does. >> Yeah, I totally get that. Can I ask you something I struggle on? Another thing that I get chastised for is you said about the infrastructure slope on revenue or the slope on revenue being slightly slower because it's an infrastructure play. It's very normal. I often say that triple triple double double's dead. You know the one to three to nine to continues is dead and we need to be 0 to 100 million in a year now.

47:13 >> Yeah. >> Am I glib and wrong and that won't take into account infrastructure plays or is that actually just the new world that we're in? >> Well, as I mentioned previously, I think the durability of revenue is the most underestimated attribute of these companies. meaning how high are the switching costs when somebody's using your product and for any category that goes from zero to 100 million in a year I worry what's the competitive moat that they have to preserve that 100 million from that customer going to

47:44 something else so ours was a bit more gradual we went 0 1250 200 and we'll finish this year north of 500 which in the database world is faster growth than we've ever seen including all of the competitive companies that I mentioned earlier today in terms of the first three years of revenue growth and it's over a very broad customer base. So we've got very little concentration risk.

48:07 The basket of AI companies that's using us and nearly every AI companies built on click house from Harvey, Sierra, Decagon, Anthropic, OpenAI etc represents less than 12% of revenue. And so even if half of that goes away the winners are going to offset the loss from the losers. Is concentration risk a valid investor concern? You know, you see a lot of people say like, "Oh, yeah, I'm an investor in Mccor.

48:34 Oh, Mccor's 90% of their revenue comes from frontier model providers." I'm like, "So does Nvidia's seems to be working for Jansen." Is concentration in terms of revenue a valid investor concern anymore? >> I think about it as an operator as a very valid concern. If I've got one customer that or one category or one industry that accounts for more than 10% of revenue, I spend a lot of time thinking about it.

48:59 And that seems to be kind of the industry standard, that threshold that if some dimension of your revenue base accounts for more than 10% of your revenue, you've got exposure. And I want to limit exposure, right? The goal is predictability, sustainability, durable growth. And if I've got one category or sector or customer that can have such a negative effect if they were to leave the platform, that's a concern for me.

49:25 >> We said about switching cost there and I think one big mistake often investors think is ah you know once I get to a certain scale I'm going to move off Elastic and build my own. Once I get to a certain scale I'm going to build my own payments processor. Shopify still use Stripe at the scale that Shopify is at. And actually most often you just don't because it's not your core business.

49:46 I'm intrigued how you think about that especially given your time with Elastic and whether we do overestimate the I'll just move at scale. >> Yeah. It comes down to customer value, right? You need your customers to continually see value from your service which means you always need to be ahead of your competition in terms of the ROI and the TCO calculation that your customer is going to think about on >> TCO >> total cost of ownership.

50:08 So if you think about how much does it cost to run ClickHouse, how much does it cost to run a comparable service and you want to have that advantage, right? Those are the two primary attributes that you're going to think about in terms of value creation for your customers. >> Do you think it's important to have an internal enemy? >> I don't I I worry about creating uh adversity inside of a company.

50:32 >> Really? >> Well, you have so much adversity outside of your company, right? You got to deal with competitors disparaging yourself and the company. You've got to think about how you stay ahead of the competitive landscape. You got to think about geopolitical concerns. And that's before you have any sort of personal strife in your life. That's just work.

50:49 So why would you want to introduce that into your company? I want to make my employees lives better >> to create them that they want to beat someone. >> Oh, that just comes down to hiring the right people. Like we only hire people that are insanely competitive. Has your hiring changed in an AI world? How you determine talent? How you discover it? >> You know, I think we're a little bit unique.

51:10 The average age of our engineering organization is in the mid to late 30s, which is a little bit different, I would imagine, than a typical venture-backed company that's only had a product for 3 years. So, we typically look for people that have a bit more experience. Um, it's not to say we don't bring people into the company straight out of college, but we want to make sure that they're paired up with, you know, somebody that's been building distributed systems for a period of time.

51:37 >> A lot of people question the value of college today. Do you think that's justified? >> It's something I think a lot about. We've got two teenage daughters and so uh, as they think about college, >> would you tell them to go? >> I would, but I think it's simply around their life experience. you know the and again I don't want to take anything away from like the academic uh output of a four-year degree with the greatest of respect you should and I mean that again this is why you're popular and I'm probably

52:06 controversial like you should like the the curriculum process to update them is so long that by the time it's been updated it's already out of date >> I think it depends on what you want to study >> well if you're studying obviously neuroscience then it's relatively >> if you want to go into medicine I think that we're going to need doctors You want that human interaction, right?

52:22 If you're studying software engineering, I think you're going to be entering a market that's very uncertain in four years time. Do you think this could all get a bit creepy? You said that we're still going to need doctors. Well, I'm not really so sure if I'm totally honest. Like, I use chat GPT for most of my medical queries now, and it prevents me from seeing a lot of doctors.

52:43 Doctors are pretty unaffordable to most people. Wait times in the UK for a GP are months. >> Yeah. I don't know, dude. And and Dario wants to cure cancer. So, I think he'll fix GP appointments, won't he? >> If I've got a serious medical concern or I need some very important legal advice, I want to talk to the best lawyer in the world. I want to talk to the best doctor in the world.

53:09 And that's not going to change for me personally. Now, I represent a slightly different generation uh than you do. So, that may be different for people behind me in life. Uh, but I do think those domains are quite durable. >> Do you think it could get creepy though with the AGI realization coming true? >> I don't I think robotics would be probably more disruptive, frankly, to the medical industry.

53:33 Uh, we had a family member have a procedure that was done entirely autonomously u with just a doctor overseeing it, but didn't actually touch an instrument. Um, and I think that will be the future. >> So, listen, we're going to do a quick fire around. So, I say a short statement. You give me your immediate thoughts. Does that sound okay? >> No, why not?

53:52 >> What job does not exist today that you think will be extremely common in five years? >> An AI finance function >> solely dedicated on AI consumption inside of an organization. That's all they wake up thinking about >> in terms like token resource management. >> Correct. And then that job will be uh made irrelevant 5 years from then because AI agents will govern themselves.

54:17 Which job will never be made irrelevant? VCs like to think it's ours. >> Professional football players. >> Dude, I'm 30. It's too late for me now. >> Professional athletes going anywhere anytime soon. >> Um, in the UK we have a game. Okay, it's called and forgive the crassness. Shag, marry, kill. Um, shag is short-term buy. Uh, mar is long-term buy and kill is you alapel.

54:43 No, not for me. Um, you have Meta, you have Microsoft, and you have Nvidia. What is your shag marry kill on them? >> Which one would I shag? Which one would I marry? And which one would I kill? Meta's a customer, so I don't want to put them in the latter category. Microsoft's one of our power users. We power the largest analytical workloads at Microsoft, so I'll probably marry Microsoft.

55:06 Had the opportunity to meet Satia uh a couple months ago. Is quite impressive. Um, and uh, we do business with both Nvidia and Cerebras and a lot of the chip manufacturers. So, I I mean, I'd like to shag all three of them, but unfortunately, unfortunately, I don't think that's possible. >> Do you think we'll see a much more distributed chip ecosystem in the next few years?

55:28 You see, and you see a lot of other providers. Cerebras being one of them. >> Yep. I think a lot of the hyperscalers and Frontier Labs are going to be very relevant providers in the chip ecosystem. What's one widely held belief about AI that's pretty agreed upon that you think is actually pretty wrong? >> A widely held belief around AI that's generally agreed upon but is wrong is that it's overblown and that we're in a hype cycle that we're in a bubble.

55:54 And I'll kind of finish it with where I started. We're just getting started. Like I, you know, I can't pick the winners and losers. Um but I think the winners are going to far offset the losers. Do you worry about the levels of debt being taken out exceeding any historical norms? I >> I worry about the public exposure to these companies um when they're publicly accessible.

56:17 Uh right now it's private capital um and so you know a lot of investors stand to lose money. A lot of investors stand to make a lot of money. >> Totally. Nvidia represents a huge amount of 40 409s for a lot of Americans. >> Nvidia. Yeah. >> Yeah. But Nvidia is a public company. Sure. So they got public disclosures and that's different than the private markets.

56:39 >> Sure. But if it were to take a hit, you would see mass wealth or kind of monetary uh impact. >> Well, that's the case with any sort of inflated asset. I'm not suggesting Nvidia is inflated. >> No, but if you see concentration of value into a few names in this way, like we've never had 85% of a stock market's value predicated in six companies. >> Yeah.

57:02 Yeah, but look at the value creation that's occurred over the last 10 years. Um, is there going to be some sort of compression? Possibly. You know, are you going to get back to the levels we were at 10 years ago? Highly unlikely. >> What's the biggest lesson from Peter Fanton? >> Peter's great. He's on my board. This is the second company I've worked with him at.

57:21 Um, you know, Peter's very philosophical. Uh, I compare and contrast him to Mike Vulpi, uh, who's also on my board. And uh Mike was an operator, worked at Cisco for a long time, ran corp dev. I think he did over a 100 acquisitions. Um Peter is a career venture capitalist and he's helped shape and form some of the most influential and impactful companies in technology.

57:46 And so he has this amazing pattern recognition to where he can a he's an incredible talent magnet. He's been great for recruiting. >> When you get him on a call with someone, what are you asking him to do? determine if they're good or win them over. >> Well, I typically tell him whether or not he's buying or selling, right? Whether or not he's trying to convince this person to join the company or really evaluating this person critically.

58:08 And that's going to influence, I think, how he approaches that conversation. >> Who do you not have on your board that you would most like to have on your board? >> There really isn't anybody that I would put on that list right now. Um, I'm adding somebody to the board shortly that we're going to announce. I'm really excited about. Uh when I was starting the company, I met with a variety of different investors.

58:28 Mike and Peter were the first two that I called. I met with Martin Casado uh in Andre who's a friend of mine and I would have loved to have him involved because I think he understands what we do uh in a very unique way technically. >> Why is he not involved? >> He was conflicted at the time. >> Ah bugger. >> I know it worked out fine. >> What concerns you today, Aaron?

58:48 >> You know what I mentioned earlier today? Like the competitive landscape I can see is clear as day. it's right in front of us. I know how we're going to execute against them. I worry about the technology that isn't yet in the market and that's going to emerge and how defensible our position is against that. Um because that's what we did. We burst onto the scene.

59:11 Nobody anticipated this was going to be a company that's experienced such success and delivered such customer value. I worry about what that company is going to do that's undefined. And so I go to the company and say we need to constantly think about reinventing ourselves to be that disruptor so that we can basically disrupt ourselves. >> If I could erase one name, Snowflake or Data Bricks, which one would you rather I removed?

59:36 >> Removed from the market. >> Well, I think it's well documented that data bricks is executing extraordinarily well in the market. Uh I've got a ton of respect for Ali and the company. Um, we're going after adjacent markets. Um, these are database technologies, so you squint hard enough, there's going to be competitive overlap with all of them. There's plenty of white space on either side of the ven diagram with us and data bricks.

01:00:02 >> Dude, you're CEO of a, you know, $15 billion company, one of the fastest growing technology and a incredible business. You also have two incredible children. What's the biggest advice on how to be a great CEO, be in London here with me at Fulham and also be a great dad? >> Well, I think the attributes are very similar. You know, you take your job seriously and you commit to it and you think about how you can improve and you ask for advice and you surround yourself with people that have experience doing whether it's

01:00:31 parenting or running a company and you replicate the best attributes of those people and you leave the other ones behind. What do you know about marriage now that you wish you had known when you got married about how what it takes to be successful? >> We've been together for 24 years. Um the the acceptance that it's it's not a straight line and the willingness to um come together with that understanding um and embrace one another's differences.

01:01:00 um celebrate the achievements of the individuals uh in the relationship and realize that you have a shared purpose. Um especially when you have kids um and it's a very powerful shared purpose and that's very similar to running a company. You know, you want all of your employees to be aligned with the objective and what is the purpose? What's the vision?

01:01:21 How are we going to get there? How are we going to execute? >> Final one for you. What are you most excited for when you look forward the next 3 to 5 years? You know, you just met my mother, uh, which is awesome. Uh, she has MS. I'm excited for potential breakthroughs in chronic conditions which have traditionally just always been incurable. I think that's unbelievable that we sit at this time.

01:01:41 What are you most excited for? >> Well, if you'd asked me that question 5 years ago, I don't think anybody would have predicted where we are today, right? I mean, chat GBT launched in November of 2022. >> That's less than four years ago. >> So, looking out 5 years from now is nearly impossible. Um I obviously the same medical advancements is is important.

01:02:00 Um uh I'm looking forward to a Fulham Premiership SP uh championship. Looking for qualification to Champions League, winning the FA Cup. >> I'm looking for the US to uh advance further in the World Cup in four years when it's in Spain and Portugal and Morocco. >> Where will Click House be in five years time? >> I think you know I'd take the under on being a public company.

01:02:23 um we could take the company public next year if we wanted to. Um there's no rush. Why would you not? >> I think if you're looking at the world in, you know, 3 to 5 year time horizon that applies. Again, like I'm hoping this company outlives me and uh in which case whether or not we go public next year in 5 years is pretty irrelevant. Um I mean when Salesforce went public in 2004, it had a billion dollar market cap.

01:02:50 >> What do you think you get by being private? if you're ready to go public next year. Completely agree with you. >> Well, the markets are more irrational now I think than they've been in a long time and so it's pretty rough being a public company and like your stock can trade down 40 50% on a slight miss in a quarter and we know that impact on employee morale and you don't have that in the private markets.

01:03:12 >> It is brutal. Every co is like oh no their head's down. It doesn't matter. It matters. >> Yeah. I've I've come full circle on this. Like I remember having dinner with Ollie a few years ago and I asked him this question. I'm like, it feels like you guys are ready to go public. And he said, I kind of basically run a public company. And he walked me through that.

01:03:28 And I said, well, there's really two dimensions that don't apply. You know, you don't have your employees looking at your stock price every day. And you don't have anybody shorting your company. Those are two material impacts of being a public company versus being a private company. Now, the employee liquidity is more or less gone away because you can do structured tenders and you can give your employees liquidity over time.

01:03:46 The the the bare thesis hasn't gone away. like you don't have people shorting your company when you're a private company and so you don't have to deal with that in you know in your day-to-day course of work and then on top of that a lot of people have traditionally said well the joys of being a public company is you have this kind of tradable currency that you can buy companies with um which is helpful for acquisitions yeah well Stripe is buying PayPal for 50 to 60 billion as a private company >> bit of an outlier but

01:04:14 I get what you're saying >> and Open Rder as well at 8 billion >> god these are two pretty sizable able acquisitions that traditionally would be unthinkable for a private company. So now I'm my question would be why why would anyone go public? >> I mean it's a valid question. I think you want a it increases awareness. It's a financing event. You diversify your investor base.

01:04:34 Uh it's very good for employee morale. Uh I've been through two IPOs. Oh, it's it's it's wonderful. Yeah. You your community celebrates it, your family celebrates it, your friends, your colleagues from university. Like it is not a short-term thing though. again to the point of the the tumultuous journey that comes post you're like great for a week and then at the whims of a volatile stock market.

01:05:00 >> Yeah. But again I believe in the public markets. I believe in the capital markets. I believe that you know in terms of price discovery. Public markets are generally better than private markets in the long term. they behave more rationally than private investors who are willing to pay a premium to get into a company betting on the come. Whereas in the public markets, you're really getting credit for where you are at that point in time.

01:05:22 Maybe there's some speculation built into your stock price, but it's more grounded in the execution and the results that you're delivering. >> Totally get that. Listen, you've delivered incredible results. I have no doubt that you will win the bet that we have in terms of reaching the billionaire era. I look forward to wiring you £1,000 when you do. But thank you so much for hosting us at Fulham. This is incredible. >> Yeah, it's a beautiful setting. Thanks so much for having me.