20VC：AI 泡沫论错了｜AI 毛利率需要改善｜收入集中度值得警惕｜为什么人们高估了开放模型，但企业仍然害怕前沿模型——与 ClickHouse 的 Aaron Katz 对谈

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 from 0 to 12, 50, and 200, and we'll finish this year north of 500. We need to get to $1 billion of ARR as quickly as possible. I'd put the over-under at December 2027, and I would take the under. We could take the company public next year if we wanted to.

This is a very special 20VC with me, Harry Stebbings. The show you're about to listen to, oh, it was not filmed in the usual recording studio. No, no. We went to Craven Cottage, the home of Fulham Football. Why? Well, our guest today just got front of shirt sponsorship for Craven Cottage and for Fulham, most importantly, the team that play there. Welcome Aaron Kass, founder and CEO of ClickHouse, industry-leading online analytical processing database management system. Try saying that after a couple of tequilas. But they've just crossed 350 million in ARR. They have customers like Microsoft, Anthropic, OpenAI, Tesla, Netflix. If you're a great company, you kinda use ClickHouse. 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 Benioff at Salesforce. Now, he's obviously the co-founder of ClickHouse, which is worth over $15 billion. I cannot wait for you to hear this discussion. It was so much fun for me to sit down with a dear friend in Aaron.

You have now arrived at your destination.

Aaron, dude, I've done over 1,000 shows. I've never had a setting quite like this for a show, so thank you so much for hosting at Fulham Football Club.

Yeah, total joy.

Now, I want to start with just a little explainer on what ClickHouse is and what ClickHouse becomes in a 5-year period, just to set the scene there.

1. ClickHouse Powers AI Applications

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

When we look at, bluntly, the fastest-growing AI companies, I think the single biggest question I have right now is: where are we in the cycle? 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 are insane. The prices and the valuations are so exuberant.” And then I also look at adoption and revenue scaling, and I have these 2 paradoxical data points.

2. AI Growth Defies Historical Cycles

We're just getting started. 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, mobile, and social.

How does it actually compare as a builder? Because we hear a lot of pontifications from venture investors. How does that compare for you?

In 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. We haven't seen revenue growth like this in our lifetime, and the demands on the systems of these agentic applications are unlike anything we've ever seen.

Totally agree with you there in terms of the revenue scaling. A lot of people always like 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 when we look at companies like FireEye, where Slim was on the show and she was like, “Yeah, we're at 30–35%. We hope to be more over time”? Do we just have a lower-gross-margin world, or do we actually scale into traditional SaaS margins over time?

A lot of these companies just seem to have unlimited access to capital right now. They're growing so quickly that I think they can operate with gross margins that most public-company investors would not be satisfied with. I think 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 than 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, you have the best customer base that you could almost ask for. I was talking about some of the fast-growing companies on our wall the other day, and you're like, “Well, they're both customers.” It was just universal: the best companies were using ClickHouse. What should I be concerned about or worry about when I'm investing today and looking at these names?

3. AI Revenue Faces Durability Risks

If you were to say, “What's the single biggest risk?” it 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, and we're seeing that with these model providers that are leapfrogging one another what seems like every other week. I would call into question the durability of some of the revenue for some of these AI applications.

When I look at an Anthropic IPO at $2 trillion and at Claude Code being the dominant Trojan horse behind that, would that not fall into the low-switching-cost category?

I would put it in that category. That's not showing up in our use of Claude Code, because our Anthropic spend is up 100 times from what it was at the beginning of the year.

Can I ask how much you spend on Anthropic?

A significant amount. 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.” I said, “I think we're moving too slowly, and I'm not seeing the adoption of these coding applications, for example, that I would expect to see for a leading database provider like ClickHouse.”

The company rallied to the call, and we've seen this explosive growth in terms of our use of these applications. We're now looking at adopting more open-weights models rather than just the traditional frontier labs, but I think Anthropic specifically and OpenAI have the benefit of being both a model provider and a harness provider, something that the open-weights models are behind on right now.

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 they're your harness too?

For example, we'll use some of these open-weights models for code review, but we won't necessarily use them to ship production code because we have concerns about the inference output.

Totally, yeah. You said, “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—how do you think about token budgeting and cost when suddenly you're incentivizing this: “Hey, run free,” and then the bill might come at the end of the quarter?

The primary measure that we care about, as you know, is revenue growth. 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; 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 covering a very broad surface area, and our roadmap 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. 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's 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 should you have spent where you didn't spend, and how do you reflect on that?

4. Sales Capacity Unlocks Growth

We've got about 100 quota-carrying salespeople, for example, and I think you know our revenue scale is significantly more than $100 million.

Yeah.

Our average 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. They wake up every morning thinking about one specific use case. Our salespeople wake up every morning thinking about 10 different use cases, and there's only 100 of them going up against an army of 2,000 or 3,000 sellers for some of these very large data warehousing companies. So I think the one thing, if I look back over the last 2 years, that I wish I had done differently was increasing sales capacity.

That is so interesting. So you should have invested more in the sales team and sales leaders earlier?

I really wanted the pressure for the first few years to be on product and engineering because I looked at the 2 most popular infrastructure software companies over the last 10 years, and I distilled that down to Datadog and Snowflake. They were both successful, but through very different avenues. Datadog had this PLG, self-service, developer-led motion, so you could get started, deploy an agent, instrument your application, and never talk to anybody in sales.

Snowflake went heavy after the enterprise through very expensive sales and marketing. I just thought it was going to be a lot easier to follow the Datadog playbook than the Snowflake playbook, and 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'd known before you started?

I spent 12 years at Salesforce, and so I was a student of Marc Benioff's playbook. There were so many lessons learned through that experience, and this was a long time ago. I joined that company 24 years ago.

What was your biggest lesson from working with him, if there was one takeaway?

You can overestimate what you can achieve in 1 year and underestimate what you can achieve in 5. When I started, it was a 3-year-old startup, and it was basically a glorified contact manager—salesforce automation. We essentially said, what you're traditionally using ACT! or GoldMine for, or using a spreadsheet for, you can use Salesforce for.

But Marc had this bigger vision, and he said, "We're going after Siebel, 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 time. And he did.

You said the word roadmap multiple times in different contexts there, but I do a show every week with Jason Lemkin and Maria Driscoll. It's very successful and popular, which is fun, but Jason said last week that if you are not well into your 2027 roadmap already, you are behind. Are you seeing development acceleration because of AI tooling, 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 2 years ahead of where we thought we would.

Really?

Yeah, both organically and inorganically. We've made 6 acquisitions over the last 4 years that have propelled us into new use case areas, and our organic roadmap is shipping features like stateless workers, which is essentially infinite compute. We've shipped those faster than we ever thought possible.

How do you think—and Nikesh Arora is a very good friend of mine and 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 6 acquisitions?

If I think that our product and engineering teams can innovate in a specific area that we're not in today, then I'll let that play out organically. If I see a founder or a group of founders that are building on top of ClickHouse, that are getting into a category that I think is going to be a future component of what we build as an ultimate data platform, then I think about doing something inorganically.

We partnered again with 6 different founders—actually more than that. Some of these companies have multiple founders. Our most recent one earlier this year was Langfuse—

Yeah.

—out of Berlin, which is 3 incredible founders entering agent observability. Every enterprise in the world is going to need this technology.

In terms of the agentic future that we face, how do software and product decisions change when you no longer cater to humans but you cater to agents?

5. Agents Choose the Infrastructure

Even 4 or 5 years ago, software applications were designed for a specific persona that had a role within an organization, and their query patterns were very predictable, whether or not you ran a report or looked at a dashboard. Agents don't have personas, and so while you would traditionally use a specific application for observability, data warehousing, or CRM, agents expect that they're going to traverse across all these applications.

They're not going to be constrained by access, and they're not going to be constrained by latency. The experience is going to be defined by the slowest point in that chain. So what's the number 1 requirement for agentic query patterns? Low latency, because they're executing dozens of SQL queries simultaneously across all these different systems. The most important requirements are the unpredictability of those query patterns, the responsiveness, and the fact that they're much more exploratory than a traditional human report or query.

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 cost-efficient. 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 costs staying the same?

Well, I don't see agents necessarily being cost-efficient. I don't see them thinking about consumption and budget like humans do, but—

Pepe and my mother have that in common.

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 their pricing models, their consumption patterns, and their access patterns.

Not only are agents hammering these services in an unprecedented way, but they're actually now selecting the underlying infrastructure. So while you could go to Claude or you could go to ChatGPT and say, "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 ClickHouse to be the default database for the next generation of applications that agents are building, not humans.

And just so I understand, when we fast-forward to that 3-year preference stack for agents, it's number 1, latency. It's number 2—

Efficiency.

Efficiency.

Yeah. I mean, Tesla, for example, is ingesting 1 billion events per second into ClickHouse. 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 fraction of the cost of traditional database technologies. 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 cybersecurity, 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 3 years out, more on the enterprise side? We obviously see it on the personal side, but more on the enterprise side.

I think it's going to require multiple deployment models. You need to be able to consume services via a cloud offering through any one of the 3 major hyperscalers. You're going to need the ability to manage that data on-premises, behind your VPC and in your firewall. So you're going to need to have the flexibility to deploy these applications as you best see fit, especially in the enterprise, where you've got highly regulated industries, a lot of data privacy concerns, and a lot of compliance requirements.

As a supplier to these customers, we think about, "How do we support them depending on their deployment preference?" And that's a tricky roadmap to maintain, because most companies pick 1 of those avenues. I mentioned Snowflake and Datadog. They're primarily cloud services. You look at more traditional technologies that run on-premises, and so if you force your customer into a specific lane, you're limiting the addressable market that you can go after.

When you look at the agentic future over the 3–5 years that you're planning, what seems insane today that you think will be quite commonplace in 3–5 years?

We can talk about the fact that agents will need to have an identity that they don't have today. They'll need to have a budget, and how do you authorize an agent to consume services?

But wouldn't the agents need to have an identity and a budget?

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.”

So you've got a database, networking, compute, and storage, and the agent's actually making that selection process. But they need to have authorization. They need an identity. They need to have a budget 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.

I'm sorry, help me understand. Where should I be looking then, and why is that not included in the harness? 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. 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 who is observing that consumption. They're monitoring the agentic spend. They're putting controls in place to make sure that things don't get out of hand, that they don't access enterprise data that they shouldn't, and that they don't spend a certain amount of money that they're not authorized to. If you look out 3–5 years, those agents are going to be fully autonomous.

One that I think is very clear is specialized models. We both know Leonard FireWorks. I think every company will have their own model, trained on their own data. They'll supplement their own data with additional data, but I very much see that being common.

Do you see a world of millions of specialized models? Do you think you'll actually have Anthropic and OpenAI take the large majority of enterprise, with only very specific cases having 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 a specific use case, like legal tech. If you look at Harvey, for example, I think they're 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 Lagoras who obviously have not decided to dedicate their resources to building out specialized models?

They consume less ClickHouse. That's the short answer to the question. We're an infrastructure provider, so we're picks and shovels at ClickHouse. We're not picking winners in these categories. Lagora could be a bigger company than Harvey a year from now. I can't predict the outcome of these specialized providers. I don't know their revenue scale.

What's the average customer spend on ClickHouse?

It's a good question. We define a customer once they hit a certain revenue scale. We've got a long tail of customers that consume some of our services, but once they're actually in production at scale, we count them as a production customer.

There's a chart that you can see with our revenue growth and our customer growth, and you can see they're growing at a similar rate. Revenue is actually growing a little bit faster because our customers are growing faster than new customer acquisition. The most important function for a company of our size is how many new customers we can onboard in any given period.

We've seen that the expansion characteristics of these services are unlike anything I've seen in my career. We had over 130% net dollar retention at previous companies. We're over 200% because these use cases expand.

You could be using us for data warehousing, then using us for real-time analytics. Historically, these were siloed applications inside of an enterprise. People are now saying, “We want to put all of this in one data repository. 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. So averages can be a little bit misleading. If I were to look at the midpoint, it's probably around $100,000.

When they're making that buying decision, which competitor do you fear the most?

The one that isn't in the market yet. Our competitors are right in front of me. I can see them. I know their strengths. I know their weaknesses. And what I worry about is the technology coming from the rearview mirror.

I worry about the next ClickHouse. People really didn't see this technology coming. It was open source 10 years ago. That's when I first discovered it. It burst onto the scene, and thousands of companies adopted it, but there was no company behind it. And so people dismissed it as just another popular open-source database.

There have been a lot before it. There will be a lot more after it. So I worry about what company is going to disrupt us in the same way that we're disrupting the competitors in front of us.

You mentioned, obviously, ClickHouse being an open-source project and the amazing early traction that you had. When we look at the percentage of tokens that are now going through open models, it is increasing exponentially, it seems, and it is taking away from frontier models. What percentage of tokens will go through open models in 3 years versus frontier models?

6. Open Models Face Enterprise Constraints

The easy answer is 50/50. In the same way that you ask what percentage of enterprise software today is open source versus proprietary, I think it's a pretty even distribution.

That would be a controversial prediction, then.

I don't know. Look at the big 2 data warehousing providers, Snowflake and Databricks. Snowflake is primarily a closed ecosystem. Databricks is built around open source. Would you argue which one's going to be bigger?

Databricks.

Perhaps. But then you add Datadog. Datadog is primarily proprietary. Other open-source observability tools are open. Which one's going to be bigger?

Databricks.

In observability, I would argue Datadog over Databricks. Well, you never know. 3–5 years is a long time.

It's a very long time.

And I don't want to underestimate Databricks. It's a great company.

Do you know what's shocking when you say that? 5 years ago, ChatGPT wasn't out. That's—

Yeah.

—such a stark wow.

I mean, are they going to get into infrastructure? Will they be offering databases as a service? I don't know. I wouldn't dismiss Anthropic and OpenAI as core infrastructure providers.

Really?

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 3 years.

They're building their own chips. This would not be—

Right.

—extraneous.

Yeah.

Totally get that. But the conventional wisdom would be that you see 90% going through open models and 10% through frontier models. In the conversations that I have today, everyone basically says frontier models will be used for cancer, climate change, and extremely valuable applications, but very few for us, and then the rest of everything will go through open models. You don't agree with that?

I don't, especially in the enterprise. They want provisions and protections that potentially open-weight 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 cases that those open-weight models are adopted for.

Now, again, it's very important that we distinguish between open-weight models and open-source software, okay? We're in the latter category. My predictions on enterprise adoption around open-weight models are very different.

For those who do not know—and I'd like this to be not just for Silicon Valley engineers—can you explain open weight versus open source?

Let's focus on open source.

Yeah.

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 with the people who are actually developing it. 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.

Okay. I'm pleased that you said that—that you don't agree with that, and that there will actually be more concern around using open-weight models and potentially Chinese models.

When I speak to people on the show, they actually say that the biggest enterprises are more scared to work with frontier providers than they are with open-source Chinese models.

Because people don't trust the statement "zero data retention." It's basically you saying, "Just trust me. I got you." 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. We have that same concern internally because you worry about the output from that code generation. You worry about 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 can use it for code review, for example, but maybe not to push production code into an environment that your customers are using.

But then what do you trust? You trust an open Chinese model with the more sensitive data? Because, again, this is what someone said on the show the other day, and I was like, "No, you must have gotten that confused." They said, "For all less-sensitive things, we use 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 around."

I think when you need 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 open-weight models.

Is it justified?

Today, I think it is. If I look out 1 or 2 years from now, I think a lot of these concerns will be addressed.

You don't buy the backdoor to the CCP or—

I personally don't like to speculate that, by using some of the software, you're somehow going to be engaging in some nefarious—

Chinese espionage?

Yeah, exactly.

Yeah, yeah.

It's quite fantastic to go there.

Listen, you're CEO of one of the most prominent open-source companies in the world, in terms of ClickHouse. 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 and incentivize us to dramatically leapfrog China now in our open ecosystem?

Obviously, I'm a huge fan of open-source and open-weight models, so I don't think any sort of government intervention is wise in terms of limiting the adoption or distribution of these technologies. I do think open-source and open-weight 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. I personally wouldn't take your capital and say, "I'm going to deploy it to develop an open-weight model."

Do you see more and more enterprises wanting to go back on-premises in this day and age?

We do, yeah. Even companies that I thought would never go back on-premises are talking about going back on-premises. Some of the most innovative digital-native companies in Silicon Valley are now thinking about moving their stack from one of the hyperscalers to an on-premises environment.

When we think about agentic workflows, a lot of what we've said—agent identity, 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 you see and what they know?

Narrow.

It is?

Yeah. I was at Canary Wharf yesterday meeting with some of the largest financial services companies in the world. They are leading the way in terms of adopting new technologies in a way that I've never seen in the past. A lot of the time, historically, the sales cycles into these big firms would be measured in years, not quarters. They're now adopting technologies much faster than they ever have before.

So you're seeing sales-cycle compression these days?

Yeah. Open source aids in that because you can get started without any sort of vendor relationship. PLG products like Datadog and ClickHouse aid in that because you can just spin up an environment without ever talking to anybody in the sales organization. You can have this frictionless experience where you can evaluate, deploy, and scale the product without a traditional enterprise sales process.

I think people just fundamentally misunderstand the go-to-market and the business behind it. What do investors get most wrong when analyzing your business?

Investors often say, "Where's the moat?" How difficult would it be for me to simply redistribute ClickHouse? What's the risk of one of the hyperscalers offering ClickHouse as a managed service? It's been done before, where AWS, Google, or Microsoft takes your open source and redistributes it as a managed service. So now you're almost competing against your core database. 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 difficult to replicate, then you can maintain that moat, and I think very few open-source companies get that right.

I do want to make a weird transition back. When we talked about agent preferences and agents—Anthropic using Claude to choose ClickHouse—does that mean developer relations and the developer community become less important? And how does the future of the brand change when agents become decision-makers?

So, say you're building an application. Let's say you're building a dating app, right? You can build it over the weekend. You can vibe-code it, right? In theory, that agent can select the stack. It can select a managed Postgres service because you want to support transactions, a managed ClickHouse service because you've got analytics, 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 who's making that architectural decision: Are they going to use ClickHouse? Are they going to use Snowflake? Are they going to use Databricks? You've got an observability workload. Are they going to use something off the shelf like Splunk or Datadog, or are they going to embrace open source and use something like ClickHouse? For the next decade, there will still be a human involved in that decision loop.

So it doesn't change the investment and commitment that you have toward the brand?

Not at all, because budgets are still controlled by people, right? And budgets correlate with technology decisions. A few years ago, I started doing things around awareness. For example, for AWS re:Invent, Amazon's big cloud conference in Las Vegas, or Google Cloud Next, I partnered with The Chainsmokers and had them perform because I said, "There's not one party that everybody at re:Invent wants to go to. It's a bunch of shitty restaurant buyouts and happy hours. I want one party that 60,000 software engineers are falling over themselves to get access to."

So I partnered with Alex and Drew, and we started performing these concerts in support of ClickHouse. Then I thought about how we could drive even broader awareness, and a sports sponsorship came to light. I'm not the first person to do this, as you know. A lot of other companies are sponsoring Premier League teams.

Sure.

We did a financing earlier this year, and then we extended it and brought in some strategic investors like yourself, David Sacks, Michael Dell, and JPMorgan. We didn't need the capital. We had $1 billion on the balance sheet.

I quite like the affiliation with those names, so thank you very much for including me alongside David Sacks and JPMorgan. Very helpful.

Happy to. So I thought, what better way to spend this new investor money than to sponsor an English Premier League football club in London?

Why football? Why the English Premier League? You can sponsor F1, you can sponsor, you know, Lacroix do golf as well. Why football?

I love the sport, but let's put that to the side for a minute. I think the value of these sponsorships obviously comes in 2 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 looking at your brand; you're getting impressions, obviously.

The second, which is obviously easier to quantify, is hospitality. We're sitting here at Craven Cottage along the Thames. 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. A C-level executive came from Paris, from one of the largest banks in Europe, just to experience that. Those types of relationships are extremely important, especially as we move upmarket.

Do you think we will see the price of sports assets increase dramatically even further? We had, obviously, the Rohn Koslo buy. I always get it wrong, but I'm a Brit, so forgive me. It's not the Seagulls; it's the Seahawks.

The Seahawks. Yeah.

Seahawks.

Yeah, which obviously I didn't love to see, considering both Koslo's an investor in ClickHouse, but he was a minority owner in the 49ers.

Why is that bad? Why didn't you want to see it?

Because I'm a San Francisco 49ers lifelong faithful.

Dude, I'm from Fulham. I don't have a clue. I thought it was the Seagulls.

Well, it would be like 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.

Right?

No. Unless there was significant monetary gain, in which case I'll do it in a second.

Well, that was a very savvy businessman, so I'm sure it's going to be a good investment for him.

And then Josh buys the Lakers for $12.5 billion, and I'm like, to the point of underestimating where value accrues: do you think we'll see $20 billion sports teams?

I do. We just saw that with the Lakers. I think it was the most expensive sports transaction—

Twelve and a half.

—in history. $12.5 billion. It was reported that the Seahawks sold for $9.6 billion.

Yeah.

It's all obviously well reported what the English Premier League clubs trade for. I do think that. It's an experience you simply can't replicate through technology or anything else. There's something very visceral about it. We felt it last night: to be there at the pitch, with 28,000 rabid fans on their feet to launch the Premier League season—a southwest London derby, Chelsea versus Fulham, 3–2, 5 goals. What more could you ask for?

I totally agree, and I think also, in the world of AI, you actually crave those experiences more.

I agree.

That and music, in particular, I think will be two of the most blossoming. I totally get you there. How do you think about spend for it? I'm not asking you how much you paid for it, but how do you think about ROI effectiveness on share? We're going to commit a lot of budget to being in front of share.

We had 20 guests last night, budget owners from some of the largest companies in the world. Half of those are customers, and half of those are prospective customers. So I can very easily measure the spend that I can gather from that basket of accounts over the next 12 months. 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 and 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.

Dude, I was talking to your investors, and many of them said, “Every round, I've wanted to invest more in Aaron and ClickHouse, and he always cuts me back.” What do you know now about fundraising that you wish you'd known when you started?

The credit really goes to Yuri and Alexei. They're my 2 co-founders, and they're spectacular—the best engineers I've worked with in my career by a very wide margin. 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.

In terms of cutting back investors, 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, and 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.

I reference them like you would in any other relationship. 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 has he helped with awareness from his social presence? Has he helped with recruiting? How does he work with other investors? Do people perceive it as a positive to have him on the cap table?”

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 of capital. It's more and more remote in a lot of cases.

7. Durable Growth Beats Fast Fundraising

I'm trying to build a generational company that outlives me. 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. 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. 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 $1 billion of ARR as quickly as possible.

The most important metric for the company is new customer acquisition. We add hundreds every month. 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 $1 billion in ARR?

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. I'd put the over-under at December 2027, and I would take the under.

Do you think you'll get that before? I do. I'm going to go for February 2028. I think that's more than 18 months. Yeah, it's 18 months.

I would definitely take the under on that timeframe.

What do you mean?

Oh, yeah.

We're at $250 million now?

We're well north of that.

Oh, well, that's unfair. You said a bit 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. OpenAI and Anthropic simply pay, and they go to the frontier model providers.” Is that true, or was I being glib?

I think it's true, depending on the category that you're in. If you're a digital-native AI startup in San Francisco, it's a very difficult employment environment because you're competing against OpenAI, Anthropic, and others that are extremely well capitalized and are putting offers that are extraordinarily aggressive into the market.

If you're an infrastructure provider like ClickHouse, we look for a slightly different profile. We're looking for database engineers—people that have experience with distributed systems—slightly different from what the frontier labs are hiring for. We employ people in 27 different countries, which gives us a competitive advantage. So I can hire engineers in Portugal, Germany, and Singapore.

We've got single-digit attrition, so we've got extraordinarily high retention. We have done some structured secondaries, and we'll continue to do so over time, but not with the frequency that I think some of the younger companies are doing.

I'm controversial in many ways. One of them is because of my vocal views about remote work. Why am I wrong?

I don't think you're missing anything. I'm of 2 minds, and I contradict myself constantly about this topic. I spent 12 years at Salesforce, so I was in the office every single day—5 or 6 days a week, 10 to 12 hours a day—and it was during this extremely formative time in my career.

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

We started the company, grew very quickly, and found engineers that had a very unique skill set. 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 1,000 by the end of the year. We are introducing 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 offices here in London, New York, and the Bay Area.

Is that specialized around different functions?

Not at all.

Really?

Yeah, both engineering and go-to-market. We're seeing increased participation across the employee base and increased demand for office space. If I look out a year from now, we're not going to have 6 or 7 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 6 or 7. 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 the office in some way?

I wouldn't, and I'll explain why. We're a very international company by almost every measure. Over half of our revenue comes from outside of the US: 40% here in EMEA, 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 and in a variety of different time zones.

I mentioned we're live in 36 different regions around the world across all 3 hyperscalers. There's no way that you can centrally manage that from 1 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, Google Cloud, and Azure. I flew to China to launch a partnership with Alibaba. You’re going to need local-language speakers to maintain those partnerships, and you can’t do it from 1 or 2 or 3 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. It was at the exact same time ChatGPT launched, and these database services are different from consumer services. They take time for companies to evaluate and adopt. It’s not like you’re just going to use ChatGPT overnight and get to 100 million users in 2 months.

So there was this 6-month period, and it shows up on that bar chart of revenue growth, where revenue was slow out of the gate. Now we’ve hit this inflection point, and revenue is surging now that we have over 4,000 customers. But those first 6 months, I raised $300 million at a valuation that was hard to justify because we had no revenue and no product.

Your prices were quite chunky. At around $50 million in revenue, you were priced at around $6 billion.

Again, just a point in time. You don’t get credit for where you are. Venture investing is—

I’m going to tell that to my LPs when my LPs are like, “Dude, but your DPI is not what Gili Raanan’s is.” I’m like, “It’s a point in time.”

Right.

Yeah.

Well, you’re giving credit for the next year, right?

100%.

And that’s how venture investing works, in my experience, on the other side of the table. 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. If you have a track record of execution and a track record of overachieving against your targets, then you can garner a multiple that is disconnected from the public markets.

Which round felt most expensive, and which round felt cheapest?

The Series B that Coatue and Altimeter jointly led at $2 billion felt expensive. We had no revenue, no product, control of an open-source database, no customers, and 15 employees. So I felt like that one put a pretty big target on our back, and that’s when the pressure really started to mount on building this differentiated product. It took us a year.

Those were some long days, 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 3.5 years later.

So you didn’t know that the AI wave was coming in the way and at the speed that it has, which has been the propulsion of all generations?

This was 5 years ago.

Yeah.

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. In the database world, it comes down to price and performance. There are a lot of other attributes in terms of feature completeness, et cetera, but that’s really what it boils down to, and I knew that ClickHouse had an advantage on both.

Which one was the cheapest round?

Probably the current one.

Yeah, I felt this, too, and I know it’s obviously 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. Does that make sense?

It does.

I totally get that. Can I ask you something I struggle with, and another thing that I get chastised for? You said that the infrastructure slope on revenue, or the slope on revenue, was slightly slower because it’s an infrastructure play. I often say that triple, triple, double, double is dead. The 1-to-3-to-9-to-… progression is dead. We need to be 0 to $100 million in a year now. Am I glib and wrong, and does that not take into account infrastructure plays, or is that actually just the new world that we’re in?

As I mentioned previously, I think the durability of revenue is the most underestimated attribute of these companies. How high are the switching costs when somebody is using your product? For any category that goes from 0 to $100 million in a year, I worry: what’s the competitive moat they have to preserve that $100 million from that customer going to something else?

Ours was a bit more gradual. We went from $0 to $12 million, $50 million, and $200 million, and we’ll finish this year north of $500 million, 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 3 years of revenue growth. It’s over a very broad customer base, so we’ve got very little concentration risk.

The basket of AI companies using us—which includes nearly every AI company built on ClickHouse, from Harvey, Sierra, and Decagon to Anthropic and OpenAI—represents less than 12% of revenue. 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 see a lot of people say, “Oh, yeah, I’m an investor in McCaw. McCaw’s 90% of their revenue comes from foundation model products.” And so does Nvidia’s. It seems to be working for Jansen.

I think about it as an operator as a very valid concern. If I’ve got 1 customer, 1 category, or 1 industry that accounts for more than 10% of revenue, I spend a lot of time thinking about it. That seems to be the industry standard—that threshold. If some dimension of your revenue base accounts for more than 10% of your revenue, you’ve got exposure.

I want to limit exposure. The goal is predictability, sustainability, and durable growth. If I’ve got 1 category, sector, or customer that can have such a negative effect if they were to leave the platform, that’s a concern for me.

We spoke about switching costs there, and I think 1 big mistake investors often make is, “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 uses Stripe at the scale that Shopify is at. Most often, you just don’t, because it’s not your core business.

I’m intrigued by how you think about that, especially given your time with Elastic, and whether we do overestimate the idea that, “I’ll just move at scale.”

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—

So TCO?

Total cost of ownership.

Ah.

If you think about how much it costs to run ClickHouse, how much it costs to run a comparable service, you want to have that advantage. Those are the 2 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 worry about creating adversity inside of a company. You have so much adversity outside of your company, right? You have to deal with competitors disparaging you and the company. You’ve got to think about how you stay ahead of the competitive landscape. You’ve got to think about geopolitical concerns. And that’s before you have any sort of personal strife in your life. That’s just work. So why would you want to introduce that into your company?

To create fire in them so that they want to beat someone.

That just comes down to hiring the right people. We only hire people who are insanely competitive.

Has your hiring changed in an AI world—how you determine talent and how you discover it?

I think we’re a little bit unique. The average age of our engineering organization is in the mid-to-late 30s, which is a little bit different, I would imagine, than in a typical venture-backed company that’s only had a product for 3 years. So we typically look for people who have a bit more experience.

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 somebody who’s been building distributed systems for a period of time.

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 2 teenage daughters, and so, as they think about college—

Would you tell them to go?

I would, but I think it’s simply around the life experience. I don’t want to take anything away from the academic output of a 4-year degree—

But with the greatest respect, you should. And I mean that. Again, this is why you’re popular and I’m probably controversial. You should. The process for updating the curriculum 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 neuroscience, then it’s relatively important.

Yeah. If you want to go into medicine, I think we’re going to need doctors. You want that human interaction, right? If you’re studying software engineering, I think you’ll be entering a market that’s very uncertain in 4 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. I use ChatGPT for most of my medical queries now, and it prevents me from seeing a lot of doctors. Doctors are pretty unaffordable to most people. Wait times in the UK for a GP are months.

Yep.

I don't know, dude.

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, and that's not going to change for me personally. Now, I represent a slightly different generation than you do, so that may be different for people behind me in life, 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. We had a family member have a procedure that was done entirely autonomously, with just a doctor overseeing it, but the doctor didn't actually touch an instrument. I think that will be the future.

So listen, we're going to do a quick-fire round. I say a short statement, and you give me your immediate thoughts. Does that sound okay?

Yeah, why not?

What job does not exist today that you think will be extremely common in 5 years?

An AI finance function solely dedicated to AI consumption inside of an organization. That's all they wake up thinking about.

In terms of token resource management?

Correct. And then that job will be made irrelevant 5 years from then because AI agents will govern themselves.

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 aren't going anywhere anytime soon.

In the UK, we have a game, okay? It's called—and forgive the crassness—Shag, Marry, Kill. Shag is short-term buy, marry is long-term buy, and kill is à la poubelle. No, not for me. 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? Well, Meta's a customer, so I don't want to put them in the latter category.

Right.

Microsoft's one of our power users. We power the largest analytical workloads at Microsoft, so I'll probably marry Microsoft. I had the opportunity to meet Satya a couple of months ago. He's quite impressive. We do business with both Nvidia and Cerebras and a lot of the chip manufacturers, so I'd—I mean, I'd like to shag all 3 of them, but 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? You see Etched and a lot of other providers, Cerebras being one of them.

Yeah, absolutely. 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. I'll finish with where I started: we're just getting started. I can't pick the winners and losers, 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 worry about the public exposure to these companies when they're publicly accessible. Right now, it's private capital, and a lot of investors stand to lose money, while a lot of investors stand to make a lot of money.

Totally, but Nvidia represents a huge amount of 401(k)s for a lot of Americans.

Yeah, but Nvidia's a public company.

Sure.

So they've got public disclosures, and that's different from the private markets.

Sure, but if it were to take a hit, you would see mass wealth or monetary impact.

Well, that's the case with any sort of inflated asset. I'm not suggesting Nvidia's inflated.

No, but if you see the concentration of value into a few names in this way, we've never had 85% of the stock market's value predicated on 6 companies.

Yeah, but look at the value creation that's occurred over the last 10 years. Is there going to be some sort of compression? Possibly. Are you going to get back to the levels we were at 10 years ago? Highly unlikely.

What's the biggest lesson from Peter Fenton?

Peter's great. He's on my board. This is the second company I've worked with him at. Peter's very philosophical. I compare and contrast him with Mike Volpi, who's also on my board. Mike was an operator who worked at Cisco for a long time and ran corporate development. I think he did over 100 acquisitions.

Yeah.

Peter is a career venture capitalist, and he's helped shape and form some of the most influential and impactful companies in technology. He has this amazing pattern recognition, and 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, whether or not he's trying to convince this person to join the company or really evaluating this person critically. 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. I'm adding somebody to the board shortly that we're going to announce. I'm really excited about it. When I was starting the company, I met with a variety of different investors. Mike and Peter were the first 2 that I called. I met with Martin Casado at Andreessen, who's a friend of mine, and I would have loved to have him involved because I think he understands what we do in a very unique way technically.

Why was he not involved?

He was conflicted at the time.

Oh, bugger.

Yeah, I know. It worked out fine.

What concerns you today, Aaron?

You know what I mentioned earlier today: 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, because that's what we did. We burst onto the scene. Nobody anticipated this was going to be a company that experienced such success and delivered such customer value. I worry about what that company is going to do that's undefined. 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 Databricks, which one would you rather I removed?

Removed from the market? Well, I think it's well documented that Databricks is executing extraordinarily well in the market. I've got a ton of respect for Ali and the company. We're going after adjacent markets. 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 Venn diagram with us and Databricks.

Dude, you're CEO of a $15 billion company on the forefront of technology and an incredible business. You also have 2 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 take your job seriously and you commit to it, you think about how you can improve, and you ask for advice. You surround yourself with people that have experience doing it, whether it's parenting or running a company, and you replicate the best attributes of those people and leave the other ones behind.

What do you know about marriage now that you wish you'd known when you got married about what it takes to be successful?

We've been together for 24 years. It's the acceptance that it's not a straight line, the willingness to come together with that understanding and embrace one another's differences, celebrate the achievements of the individuals in the relationship, and realize that you have a shared purpose, especially when you have kids. It's a very powerful shared purpose, and that's very similar to running a company. You want all of your employees to be aligned with the objective. What is the purpose? What's the vision? 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 to the next 3 to 5 years? You just met my mother, which is awesome. She has MS. I'm excited for potential breakthroughs in chronic conditions that have traditionally just always been incurable. 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? ChatGPT launched in November of 2022. That's less than 4 years ago. So looking out 5 years from now is nearly impossible.

Obviously, the same medical advancements are important. I'm looking forward to a Fulham championship, qualification for the Champions League, and winning the FA Cup. I'm looking for the US to advance further in the World Cup in 4 years, when it's in Spain, Portugal, and Morocco.

Where will ClickHouse be in 5 years' time?

8. Private Markets Delay the IPO

I think I'd take the under on being a public company. We could take the company public next year if we wanted to. There's no rush.

Why would you not?

I think if you're looking at the world in a 3- to 5-year time horizon, that applies. Again, I'm hoping this company outlives me, in which case whether or not we go public next year or in 5 years is pretty irrelevant. I mean, when Salesforce went public in 2004, it had a $1 billion market cap.

What do you think you get by being private? If you're ready to go public next year, I completely agree with you—

Well, the markets are more irrational now than they've been in a long time, and so it's pretty rough being a public company. Your stock can trade down 40% or 50% on a slight miss in a quarter, and we know the impact that has on employee morale. You don't have that in the private markets.

It is brutal. Every CEO's like, "Oh, no, their heads are down. It doesn't matter." It matters.

I've come full circle on this. I remember having dinner with Oli 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. I said, "Well, there are really 2 dimensions that don't apply. You don't have your employees looking at your stock price every day, and you don't have anybody shorting your company." Those are 2 material impacts of being a public company versus being a private company.

Now, employee liquidity has more or less gone away because you can do structured tenders and give your employees liquidity over time. The bear thesis hasn't gone away. 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 your day-to-day course of work.

And then on top of that, a lot of people would 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, which is helpful for acquisitions."

Yep.

Stripe is buying PayPal for $50 billion to $60 billion as a private company.

Bit of an outlier, but I get what you're saying.

And OpenRueeter as well, at $8 billion.

Yep.

God, these are 2 pretty sizable acquisitions that traditionally would be unthinkable for a private company. So now my question would be: Why would anyone go public?

I mean, it's a valid question. I think, A, it increases awareness. It's a financing event. You diversify your investor base. It's very good for employee morale. I've been through 2 IPOs.

Is it?

It's wonderful. Your community celebrates it, your family celebrates it, your friends, your colleagues from university. It is a big milestone.

And is that not a short-term thing, though, again, to the point of the tumultuous journey that comes post? Great, for a week, and then at the whims of a volatile stock market.

Yeah, but again, I believe in the public markets. I believe in the capital markets. I believe that, 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. 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 $1 billion in ARR. I look forward to wiring you £1,000 when you do. But thank you so much for hosting us at Fulham. This is incredible.

It's a beautiful setting. Thanks so much for having me.