79. Roman Stanek: "Assume the worst scenario and then double it, and then double it again"

Jonathan: Welcome to The Difference Engine, the show for tech founders, investors, and innovators. Paul: This is an episode we've been waiting to record for quite some time. Uh, we've got an extraordinary European entrepreneur, founder of three companies, Mr. Roman Stanek.

He's the CEO of Good Data. Jonathan: Although born in Prague, is now resident in Marin County in California with three successful companies built under his belt, and he's a man that has a s- incredibly good grip on what is happening in the world of AI and what it means for your company. Paul: Absolutely. Listen up to learn how to scale a business in today's crazy AI environment, how to keep people focused, and the truth about 996 and what it takes to succeed in software today.

Hey, Roman. We've been waiting to do this for a long time. Welcome to The Difference Engine. How are you?

Roman: Good, good. Good morning. Good morning from California. Paul: A- an afternoon, uh, over here in London.

Um, we thought we'd get you on because there aren't that many people we know who are European, an engineer, and have started, uh, and successfully grown three companies. Um, and as you said, you've washed up in northern California, not Silicon Valley. Can you take us through a little bit of that journey, please? Roman: A- absolutely.

I, um, I actually started my first company in Prague and completely built it in Prague in, uh, in the late '90s in the first, uh, uh, internet bubble, and it was absolutely crazy. It was absolutely crazy, you know. It's, uh, it is actually, you know, that's probably the closest to the AI bubble today, and I was able to build it, um, on, on almost no funding in, in again, in Prague. Paul: Yeah, so good cost of engineers.

Roman: Yeah, yeah, and it, it, it was kind of different. It was everything was kind of, um, super cheap and we, you know, raised very little money, sold the company to Sun Microsystems. The company was Java development tools called NetBeans. I still people- I still meet people today who tell me that they actually grew up on, on NetBeans and they use NetBeans and, you know, sometimes I get...

I, I, I, I meet people and they ask me, like, "What's the future of NetBeans?" And so on. So it feels, um, that's, that feels, um, really good. And, and about a year into, into NetBeans, I got a call from Sun Microsystems in the US from the head of, uh, M&A, and they asked me if I would like to talk to them about selling the company.

So I sold the company, uh, which was super difficult process, you know, stories around that. And then, um, and then I moved to, you know, I worked for Sun for about a year. Um, they came to me and said, "You, you did well." You know, they accelerated everything.

They let, they kind of, um, they, they knew I wanted to start another company, and I started another company in 20- uh, 2001 and moved to Boston for that one and, you know, sold that one in 2006. Paul: And, and people may forget, but Sun was an absolute leviathan in terms of, like, software engineering. It was the place to be, right? Roman: Sun was, Sun was so...

It was the dot in dotcom, um, if you remember that, you know. So it was, uh, they were selling - They actually, they were, they were actually discussing in 2000, um, getting rid of their sales force because there was so much de- there was so much demand for their servers. They actually wanted to auction servers on eBay. Uh, which lasted about six months, and then everything crashed, and they sold the company to Oracle for peanuts, and so on.

Um, but, but it's actually very interesting. There are two, two, two things interesting, um- Sun is like OpenAI and Anthropic today Paul: Exactly Roman: Everything what they did was unbelievable. They scaled, they didn't need to sell. Everyone came to them.

They were, like, in middle of everything. And the second thing is that The culture of Sun, um, if you look at it, Eric Schmidt, who was the CEO of Sun, became the, the, the, the CEO of Google. So the culture of Sun essentially became the culture of Google. So that culture still kind of lives on.

Um, but yeah, it, it was, it was absolutely crazy. And so, so going back to kind of, you know, my, my story, so first company was in, in, in, in Prague. The second company, second company I started and, and sold in Boston, which was not, it was up suboptimal and, and, um, you know, uh, the difference between East Coast and West Coast in US, like people still, you know... I think that everyone would like to see like a Silicon Valley in Boston, and it's not there.

Um, and so I actually, I was, uh, it was kind of impractical. I was, you know, everything what I wanted to do was in Silicon Valley, so I had to get on plane from Boston. So when we sold the company, I actually moved here and I started a third one, you know, straight here. And I, I don't live far.

You, you position it like Silicon Valley is not Northern California. I'm like, uh, you know, 50 miles away from Silicon Valley. And I actually believe that, uh, in today's world, San Francisco is kind of the epicenter of, of Silicon Valley as much as, um, you know, San Jose. Paul: Good.

Well, well, as soon as they clean that city up, I'll be right back there. But, um, three companies, uh, and, um, you know, a move successively west. We'll come back to that because we wanna talk about, um, the difference between European and American entrepreneurs in a, in a bit. Um, so Czech, uh, or Czechia, I do get confused, Slovakia.

Um, I think I've got them in the World Cup, uh, in the World Cup ballot, so, so hopefully good luck there. Um, but this country, I don't think enough people know about it. Could you give us a sense of what it's like growing up there and the engineering ethos, et cetera? Roman: It, it is a very industrial, like a engineering philos- philosc- culture, mathematics engineering philos- culture.

I would say to the point where, um, the, the sales and marketing somehow kind of atrophied. So, so you, you, you, you know, we have good, good, uh, engineers, uh, in, in Prague and Czech Rep- Czechia, you know, Czech Republic, but, um, not enough, um, salespeople and marketing people and, and product managers. We are building that and, and training that, kind of that muscle. That muscle was not, was not there historically.

And, you know, it's, it's, um, it's interesting because, you know, I, I had a chance to meet with, uh, Roberta Metsola, the President of European, uh, Parliament, uh, the other day. And, and she asked like, you know, the audience, like how, what they could actually do better. And I said, "Look, you know, the Czechs are producing cars. You know, we are really good at it.

You know, Škoda makes more money than Porsche. Uh, the politicians shouldn't try to build Silicon Valley in Europe. That's impossible. Again, no one can build Silicon Valley in Boston."

They should just stop kind of being the problem. And I told her that, you know, the, the European Parliament should do only three things, you know, deregulate, deregulate, and deregulate because, uh, that's problem for, uh, for good data, AI, as it is for Skoda, you know, regulation. Paul: Christina Cafaro, uh, was on this pod recently, and I think she would violently agree with you. Um, so, and you're right about, you know, we, we, Jono and I are petrolheads.

We love, uh, Tatra, uh, a name from the, from the, from the past. Uh, as you mentioned, Skoda. What about the software side of things? I mean, there are a couple of players, and you obviously employ a lot of people in Prague, right?

Roman: It, it's kind of a, it's, it's a little bit of puzzle, um, uh, because, you know, if you look at, if you look at, let's say, Poland, you know, they have 11 labs. You know, they have real big visible AI success and so on. Um, the same in France and in Germany. The Czechs, again, the Czech culture is much more like a engineering culture, so I think that we have plenty of engineers, but not, not, not, they have not that many kind of large in- uh, internet, uh, um, or AI, AI, um, uh, big success stories, so they are not that visible or we are not that visible.

But, um, th- things are changing, and I think that, you know, uh, there are more and more people who can actually build companies. Jonathan: Yeah, and, uh, isn't it, isn't it true that, um, with this engineering background, um, somewhere along the line you created some software which is now on Mars. Is that true? Roman: Yeah, yeah, it i- it is.

It's actually Ne- again, NetBeans, you know, was very kind of, uh, uh, innovative company. Um, and in a way, when we started NetBeans in 1997, um, it was very similar to today. There were no rules. There was nothing kind of, there was nothing to guide us.

There was no TechCrunch, you know? People couldn't, people couldn't, um, Google NetBeans because Google didn't exist. Jonathan: Not even on AltaVista? Roman: Yeah, exactly.

People had AltaVista NetBeans. You know, I was kind of right out of college and so on. But my point is that today it's the same People assume that they know how to do AI. People assume that they know what AI is and how it's actually gonna work and so on.

Um, internet was, you know, I, I, I sold, you know, I worked for a US company for l- you know, couple months in, in '90- '95, '96. And we had, like, a, um, internal communication channel, and I told the CEO we should actually put it on internet. And he said he would never put, like, internal communication, you know, up internet with all the porn and so on. So they s- everyone saw internet like it's just a place that will be used by a bunch of, like, crazy people and so on.

And it's the same with AI today. Still I meet people who believe that AI is just some sort of a, some sort of a template, you know, for computers to replicate our job and so on. I, I don't think that people understand, uh, you know, kind of the impact and, uh, the kind of... It's gonna be the more disruptive.

AI will be more disruptive than internet ever was. Jonathan: And is, is there anything in particular you, you, given your experience over the last couple of years, you see happening with AI and the economy in general? Roman: The problem with, with AI is that we all have our kind of experience. Our lived experience with computers tells us something.

You, you worked with PC your whole life, you know. You know what computers can do, you know. You, you, you s- you go to ChatGPT, and there is a little screen. You talk to it, and you assume that this is kind of it, you know.

And you don't understand that on the other side, there is a giant data center with NVIDIAs that, you know, are so powerful and so kind of, um, so, uh, th- so much compute power that no one ever experienced that. So we are dealing with a beast that we have no idea how to deal with it. And, and, and it looks very innocent. It looks like a ChatGPT, ChatGPT, like a screen.

Um, but, but I think that people who actually know the full potential are people, like, who code with, uh, with, uh, AI. I'm trying to code with AI. Sometimes I spend a whole weekend coding with AI and getting advice on that. And I, at some point, I'm like, I'm almost building like a, like a personal relationship with my coding assistant because there's such so much like going on.

It's like you, you work with someone for the whole weekend, you know, you kind of become friends. So, um, it's not, a- again, it, it is, it is kind of a, um, incredible. And then you read all these kind of mathematical proofs that Anthropic and Codex are now discovering and so on, and you can start to see kind of the full potential, and we are just two, three years into it. Imagine being like 50 years into it.

Jonathan: So I mean, given that this sort of we are right at the beginning of something we, we really can't even hope to understand because it's so big, you know, what advice would you give business leaders at the moment to, to make sure that AI is working for them? Because, you know, there is a danger that AI doesn't work for us, it works for it, it works for its owners. Roman: I, I, I would say that AI will work for OpenAI and Anthropic. Um, you know, I think that you see, you see the Anthropic just raised boatloads of money yesterday.

Um, when I, when I meet with clients, I see essentially two types of companies. I see companies that, or business leaders who take it very seriously. I have a very large customer in US, a major, major, you know, company that you read about in the news every day. They just did a, you know, a two-week offsite, uh, where the whole management was kind of sitting and, and strategizing how to actually compete with Anthropic.

Now, that company is not in, in, it's a financial services company. It's not, it's not company in AI, but they s- they absolutely understand that, um, Anthropic is, is kind of existential, existential threat. And then I see companies that don't do anything and believe that this is just, you know, again, it's like a, it's, uh, it's, uh, it's, uh Not- nothing major that, you know, we have some new templates for Word and people will be able to write emails better and so on. And I think that those two, you know, the, the companies that underestimate AI, there's probably more of them, and, uh, it's gonna be very dangerous.

Jonathan: Yeah. It's inter- it's interesting that the FT Today has a piece, uh, th- on the back page that says, "Suddenly the software apocalypse was over." And I suspect people in that latter group are breathing what they think is a huge sigh of relief that maybe AI isn't as impactful as everybody's saying it is. Roman: I don't think that that's what they actually mean.

I don't think that that's what they actually mean. What they actually mean is that SaaS can actually leverage AI to transform itself, you know, the SaaS industry. It doesn't mean it's not gonna be impactful. And we are talking about SaaS industry.

We are not talking about, uh, anyone else, anybody else. So, so the Saas- SaaS industry, you know, for the last six months was like, um, you know, it looked like everyone will replace CRM, you know, Salesforce with Anthropic and, you know, Workday with, you know, Anthropic and, and Open- and OpenAI and so on. And there is some hope. So I, I would say, I would see it as like hope not as, uh, you know, the judgment is still out.

Paul: Yeah. It's the first quarter of the, of the ice hockey game. Uh, I know you like ice hockey, so, uh, maybe. Um, I want to take you back a little bit to the like the pre-SaaSpocalypse when you were scaling up the, the companies and obviously, you know, Boston, Czech, then the Valley.

Um, could you give us a sense of the difference between those early days of sta- scaling a company up and making big deals like the financial services company you mentioned. I know you've got some good stuff going on in Europe soon as well. Um, y- you know, what's the... what, what advice would you give people who are, who have something hot, maybe it's an AI product, and they wanna scale it to the next level?

Roman: You have to, you have to appreciate complexity if you deal with big companies. There is no shortcut. There is no, um- Product-led growth, you know, trial, people will pick it up and somehow magically the whole company will use it and they will pay you, um, uh, they will pay you mi- millions of dollars. It's, it's large companies, um, they have, they have antibodies against new vendors.

They hate new vendors. You know, onboarding, we, we had a, we had an example where it took us, um, about 18 months to be onboarded by a large company. Just, just being onboarded by their procurement and so on, because no one wants to do it. No one wants to have a new vendor.

They, they would much rather work with existing partners than to, to rely on someone new. And so, so there's, there is this kind of a, um, there's this kind of a difficulty to get in that, you know, can be only overcome if you're actually super focused on complexity. Solve that one complex problem, deal with it, don't get distracted by anything else. That's kind of, that's my advice because, um, there's, again, there's no shortcut.

Unless you, unless you, you know, um, unless again, you, you, you like Sun or Anthropic and people come to you and ask you, you know, all the big companies are essentially coming to you. So, so that's kind of where I see the, the, the analogy between OpenAI, Anthropic and Sun, is that every large company now understand that they have to work with them. And for anyone else, you know, you have to kind of work hard to, to get in. Paul: Yeah, we're calling it the, we've, we're coming up with a term called the vibe chasm to describe the, the problem that you won't be able to leap it now that those guys have taken all the, the, uh, low-hanging fruit.

So love to talk to you about that at some point. Um, y- you've been, you have also a unique perspective in that you know the US and you know Europe very well. Um, we've talked about this personally m- many times, but how would you characterize the tech adoption attitudes and, uh, maybe this leaches over into economics a bit, the difference between US and, and European approaches to tech and tech entrepreneurship? Roman: In, in, in the US, it's still kind of, um, there are still, there are still pioneers, you know?

I, I had customer who, um, bought a million dollars of, of software, and they wrote it off about two months later because they changed the strategy, and no one was complaining about it. It was their problem, and they just wrote off a million dollars. Imagine someone in Europe buying a million dollars worth of software and then writing it off. They would be, they would be unemployable.

Paul: Unless they were government, but yeah, yeah, okay, I take your point. Roman: Yeah, yeah, exactly. But then, you know, that, then we are talking about billions of dollars, you know? Yeah.

Paul: Exactly. Exactly. Roman: But, um, and I, I think that's the problem. Like, you know, like when I moved to US in, um, in 2001, uh, it was right after September 11th, right after September 11th.

And, and we were building software for integration, um, integration, um, of, of systems, which was a big problem of, of, of 9/11 And, and like six months into it, a Czech company, I just moved there, you know, I, I had like, you know, some, some, uh, cheap visa and so on, and then a fax machine started printing orders from Department of Defense. They wanted to buy our software to integrate their systems, and we actually built half of the company on that. That's not, you cannot imagine that happening in Europe.

That would never happen, you know? And then that's one example. And the second example is that when we actually meet with clients, um, and we have advisory boards, you know, like large companies, they come, they share their ideas, they kind of wanna talk about it, they wanna show everything else. If I do the same in Europe, everyone will have me sign NDAs, and it will be like, "You cannot talk about me.

You cannot mention my name. I'm not gonna tell anyone what we do." So it's, it's much more secretive. It's much more kind of, uh, closed.

And again, um, failure is, is difficult, so, so the, the European, European trials take, you know, 18 months because people wanna check every single box, and they never do, but that- that's, that's a different problem because the technology is changing so quickly. So yeah, it's, it's a, it's a fundamentally different environment. And, and now in, with kind of the speed of AI, this is becoming almost impossible, you know, for European companies to actually compete and understand.

Paul: Yeah, right. I, I was watching a, there was a debate on television last night, and they had some supposed experts, one CEO who knew what he was talking about, another guy directly contradicting him, and uh, the, uh, guy from the government was just nodding at everything, even when they said, "What we should not do is let a certain company in," and that certain company, who you can guess who it is, is all over government. Uh, so the guy was nodding like we should stop them, but it's already, he doesn't know what's in, what's out.

Jonathan: But that's, you know, because very few politicians have any background in business, let alone technology, so they're ill-equipped to make decisions. Roman: Not only that, but they also want to kind of regulate it, so they wanna be, they wanna be behind the, the, the steering wheel, huh? Like, this is where AI will go under, you know, our leadership. So that's, uh, that's a, that's a problem.

Jonathan: So the, the point is, is that those, those of us that exist in the, the technology environment are constantly evolving what we do and the technologies that we do it with. And I think you've got a good instance of that because, you know, you've, you've sort of evolved good data from BI to AI And, and can you talk us, talk us through that? Because, you know, that's always an exercise in evolving a company to survive and go to the next stage. Roman: And, and survival is the right word.

You know, I think that, uh, um, as, as many or, or most SaaS companies are dealing with, with this kind of notion that anyone can wipe code anything. It's, it's anyone can build, you know, features overnight. Um, uh, the, the AI models are much more, you know, more and more capable. Like the AI models double their kind of cognitive functions every 200 days.

So when we, you know, every time we talk, you know, things double. Um, and, and, and, and so, so, so for us and for not just for Good Data, but for everyone, you, you have to look at it and say, "Well, you know, if I don't do anything, you know, we will be out of business in 18 months. This is, this is really, really dangerous." So, and yet, you know, you deal with, you deal with, you know- You deal with engineers who don't want to change.

You deal with engineers who have certain, like, you know, experience, and they believe that they actually know what, what, what we should be doing, and so on. So getting kind of sense of urgency, getting that alignment, um, all the signals are against you. You know, everyone's saying, "Oh, the, I don't see that. I don't see that problem.

Nothing is happening. Customers are still buying. Customers are still telling us, you know, we don't need this," and so on. So it actually takes, like, real, um, um, real effort to, um, to, um, to actually change the company.

And, and you know, I, I don't like ice hockey. I actually like, uh, American football much more. Um, and but my, my, my, uh, kids played soccer, and one thing I learned from soccer from my, my, uh, the best, uh, the best coach on the local, local team, uh, he called it one voice. Um, he always, you know, when the parents were actually screaming from the sidelines, he kind of in- invited them and, and, and, and, and he was screaming at parents and everyone like, "The, I'm the coach here.

I'm telling everyone what to do. No one else will actually... It is one voice." So I think that every company in this environment needs one voice, uh, as the CEO voice, and everything everyone else needs to follow.

Paul: Yeah, I totally agree. So we, we are constantly saying this to clients and, you know, we, we could probably name some very big AI names where, um, you know, they've boasted to us, "We're gonna be the OpenAI of Europe." They've talked about 500 million euros as a fund, and we've just literally told them straight, "That ain't gonna be enough, and you ain't gonna win." But unless you've got someone at the top who sees it, you can't go.

Roman: Yeah, exactly. And then there's always some dissenters. Uh, always people who wanna go in different direction, who don't believe that the change is necessary, and so on. Yeah, that's, that's life.

That's like the... Most people don't like change. That's what makes entrepreneurs entrepreneurs. We like change.

Um, most people don't like it. Most people don't like being in that kind of in the gray zone when the, the old doesn't work and new doesn't work yet, and so on. So that's, like, uh, very uncomfortable for most people, and that's kinda what I living, where I live my life, you know, in that gray zone. Paul: Now, speaking of gray zones, um, recently we had a very nice, uh, dinner with you and some esteemed guests from oil companies and, um, large investment funds, et cetera, et cetera.

Fabulous, uh, meeting of minds. Um, one of the things that, that m- that we discussed was AI adoption and, uh, the speed of it, whether it's, it's going to be, um, carrying on at the pace it is, whether it accelerates, whether some people will not adopt and therefore die. What, what do you wanna see, see out there from when you're selling your Good Data AI products? W- how does that all work?

What's the... What happens when the rubber hits the road? Roman: It... And, and, and again, it's, it's different in the US, and it's different in Europe.

Um- Uh, the, the, the stakes are much higher in US. Com- you know, like the competitive environment is much stronger. You know, there's always new company being funded and so on. So there is, uh, with a few exceptions, there is, you know, and government is obviously one of them.

But with few exceptions, uh, there is, there is a real sense of like, again, existential threat. In Europe it's not the same. You know, you have national like monopolies and, and, and companies with guaranteed business, and they own the, the national markets, and they don't need to move and so on. So I would say it's gonna be I, you know, I'm actually, I'm actually getting to the point where I believe that, like Europe didn't wanna go into, into tech full speed, you know, like 10 years ago.

I, I actually think now it's maybe too late. Maybe it's actually too late. Maybe it's impossible. I mean, all the, all the national interest and, and kind of, uh, competi- competing priorities and so on, may- maybe it's too late.

Maybe tech is not good for Europe. Paul: And in terms of rounding up a little bit where you see the future, and, um, obviously you're on this journey, but an exciting set of products coming out that, that are being adopted, as you say, gray zone, getting there. Um, how do you think business leaders, so the people you sell to, what is your advice for those guys as they think about AI strategy, et cetera? Roman: Don't underestimate it.

Assume like the, the worst scenario, and then double it, and then double it again. Paul: Okay. Cheery. Roman: It, it, it's...

But look at it. Look at it. Like, you know, again, it's doubling the, the cognitive speed is doubling every t- 100 years. And the funny thing is that, um, the, the leaders from Anthropic and OpenAI, they were like, you know, like telling everyone how AI will, um, kill every single job in, in 18 months or 12 months and so on.

Um, and they are not sh- telling that, you know, the story anymore, not because that's not correct, but because their PR, PR advisors told them not to say that. Paul: You're killing the market, guys. Stop it. Roman: You know, exactly.

They said, "Hey, you look, you look, you know, you look unfriendly to the rest of the population. Like, you have to kind of tone it down." But they didn't actually change that message, like, uh, that, uh, that reality, you know. So, so may- maybe we don't hear too much about like every job will be gone in 18 months anymore, uh, but it doesn't mean that, uh, um, uh, that, you know, there's not a threat that all the kind of, uh, you know, simple in-the-office jobs will be gone, especially if you work in like technical support or you do something that is actually highly repli- repetitive and so on.

Um, I would like to see what effect it will have like on the Indian outsourcing industry, you know, people who actually code remotely and, and so on. Um, so, so, you know, I'm not Cassandra. I'm, I'm, I'm actually trying to be realistic, and I'm try- uh, I'm actually, as I said, I'm, I'm, I'm trying to keep up the pace. I code.

I have, you know, all the, you know, GPUs on my desk here. I do a lot of coding. I, you know, I, I evaluate softwares. I have local, local models running on this machine right now, and so on.

So, so, uh, it's the pace and it, the impact I think that, you know, most people just simply underestimate. Jonathan: I think it's also interesting that, you know, how you are absolutely hands-on, because unless you are, you do not understand The rate, you know, the pace of change Roman: Yeah, yeah Jonathan: And, uh, it- it's not good enough anymore if you wanna build a software company to go and get the money and then start assembling the people. You've got to turn it on its head.

You've gotta look at it in a very, very different way, and I think people are yet to appreciate that Roman: Yeah, and I, as I said a couple of minutes ago, the in- our, our intuition, computer intuition is not helping. Like, you use spreadsheet for the last 20 years, it never changed. You know, the version of Excel we used 20 years is more or less the same we- the one we use today. AI is different.

AI doubles... It essentially makes cognitive kind of functions much cheaper, so, uh, it, it, it is a different animal and, and, and, uh, we have to take it very seriously Paul: Some people are tech optimists, some people are tech, uh, AI doomers. It sounds like you're somewhere in between. For sure there's gonna be new roles, right?

Once we've got the cognitive function nailed, th- there's gonna be like, uh, we already see forward deployed engineers, a role that didn't exist, I would call it support back in the day. But there's gonna be, like, lots of opportunities, right? Roman: Yeah, ab- absolutely. And I think that, um, you know, Mark in recent talks about the fact that you will be able to buy a TV, wall-to-wall TV for $100 and your college will cost a million because it will, it will be done by people.

So it's, if it's done by people. So, so I think it will actually make, again, a- anything physical that can be produced will be super cheap. And, and, and all the robots, all the, all the, you know, all the, you know, production that, that can be actually automated and run with, uh, run with AI and so on, I, I think this will change the physical world and how we can actually find the ways how to actually spend our time and contribute and, and build stuff and so on. So, um, again, instead, instead of sitting in, in, in spreadsheets and, and loading spreadsheets, you will be able, we will be able to do something much more productive Paul: Great.

More, more time for us to watch soccer and American football and share a glove. Roman: Yeah, yeah, yeah. Absolutely Paul: This has been very good time spent for us. I think it's been very inspiring to, to listen to your story.

Thanks very much for spending some time with us today Roman: Oh, thank you. Thank you. Jonathan: Thank you for listening. If you wanna learn more about category design, head to becategorical.

com. If you need help designing and dominating your category, then get in touch. Contact details are in the show notes.