# Lovable CEO Anton Osika on $120M in ARR in 7 Months

The Honest Truth About Defensibility and Unit Economics for AI Startups · The State of Foundation Models: Long Grok, Short OpenAI, Why · Replit vs Lovable vs Bolt: What Happens

20VC · Aug 18, 2025 · 69 min · 13,700 words
Speakers: Anton Osika, Harry Stebbings
Source: https://www.996.fm/episodes/20vc--ep-2e59a397/

## Cold open

**Anton Osika** [0:00]:

University is not the best place to learn. It doesn't matter what you're studying. I'd invest in Grok and probably short Anthropic because no. I was I was short OpenAI.

**Harry Stebbings** [0:10]:

Why would you buy that Grok and short OpenAI?

**Anton Osika** [0:13]:

I think it's more the slope on the Grok team. They have they're doing something which I respect a lot, which is to hire missionaries for the data curation part. Morale is super high. OpenAI has gone through all this mess. Right?

**Harry Stebbings** [0:26]:

There will be a leading model that has not been created yet?

**Anton Osika** [0:29]:

Yes. From China. Do you worry about China? I do think there's, a fifty fifty chance they will have the best model. They will be using a Chinese model at some point, and that makes me a bit concerned.

**Harry Stebbings** [0:39]:

This is 20VC

## Intro

**Harry Stebbings** [0:40]:

with me, Harry Stebbings. Now the show state is with the fastest growing company on the planet. We traveled to Stockholm for this interview. It's with a dear friend, Anton Osika, cofounder and CEO of Lovable. Now Lovable has scaled from zero to 120,000,000 in annual recurring revenue in just seven months. Incredible to see. They've also raised over $200,000,000 from some of the best, Accel, Creandum, and, of course, 20VC. And I've heard every show that Anton's done. He answers questions here that he's never answered before. This is a very different style of show, and it was such a joy to make happen. But before we dive into the show's

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## Conversation

**Harry Stebbings** [4:33]:

Anton, dude, I'm so excited to be here with you in person. Thank you so much for joining me on the show. It's great to see you, Ethan. Thanks for coming to Stockholm. Dude, it's great to be in Stockholm. I wanna start. You just recently raised a great round. We're seeing a lot of money going to the space. And I just wanted to start with, is it a capital arms race per case of who has the most money wins, or is it something else? I

**Anton Osika** [4:57]:

think it's an arms race to build the best team, And then there's an arm race to build the best brand and trust from your users. And I mean, can help. For us, it's not a constraint at all. If you're building something like the best foundation model, it might be a constraint just because the compute for training and so on is so large. But for us, it's all about moving extremely fast and collecting the best talent.

**Harry Stebbings** [5:17]:

So if we think about talent as the number one there, we've seen Zucker pay NFL style contracts, mega mega sums for the best people. How do you think about and analyze that and how difficult it will be to get the best talent moving forwards?

**Anton Osika** [5:33]:

I think for me, it's actually more difficult than for Suck to know who which engineers are going to really thrive, push the culture forward, push the ways that we're working in the products forward. For sake, it's like there's these 10 people that know everything about how to train foundation models, and he's more paying for that knowledge than for these people. The talent itself is so good. It's probably it's pretty good as well.

**Harry Stebbings** [5:54]:

Do you think you do not need the same caliber of engineering talent if you're working in the application layer?

**Anton Osika** [6:00]:

You just did very different. I think like I first, one of those people, Suck is hiring, they wouldn't perform as well as as engineers in my team doing what we're doing. So it's a very different type of talent. And if I knew who was like the perfect engineers to hire, I could maybe step up our our like our compensation bands to get exactly those. But but I don't know who are the best people. So I need to just like figure out, are these really, really good people to work with? Are they moldable? Are they going to work well together in this team? And then and give, like, the compensation that you give on the top of market compensation rates for that.

**Harry Stebbings** [6:33]:

You've built an incredible team. Also, like, a less obvious talent in the early days, and then you hire amazing rock stars like Elena Verna. When you look at your hiring process, your talent assessment process, is there anything that's non obvious? So, like, for us, I look for people who have either extreme trauma or extreme masochism. Yes. And being serious, I think not enough people are opinionated. You said brand is important. Great brands are opinionated. People love them or hate them. Lovable. Good good example. But what is yours that is non obvious about hiring or talent assessment?

**Anton Osika** [7:06]:

I like to think a little about slope. If I talk to someone and I learn a lot of things talking from them and I noticed that my conversation is like very dynamic and exciting, that is usually feels like a very good indicator that they're going to adapt to the organization and their slope will be very high. Otherwise, there are good ways to just understand how did they perform. Like, if I could be there with a video camera when they worked in the past, that gives me a lot of signals. That's usually what I spend a lot of time when I'm talking to new candidates.

**Harry Stebbings** [7:35]:

When you think about a slope, it's noticeable with you, dude. Like, we haven't known each other for a huge amount of time. But when I compare when I first met you to when I meet you today, it is still very different in terms of your leadership. Where have you not progressed where you would like to still?

**Anton Osika** [7:49]:

I still operate Lovable in a very scrappy startup y way, even though we're, like, at the later growth stage right now. Adding a bit more structure in, like, in a few key areas is somewhere I'm looking to progress or to start being

**Harry Stebbings** [8:03]:

an excellent operator in. The joys of this show and being friends is we can have a discussion, not like a one back and forth interview. Do you think you actually need that? We've had founder mode be so propagated and praised, and being close to the metal, Jensen having 52 direct reports, I would say structure in that middle layer is where slowness and apathy comes. True.

**Anton Osika** [8:24]:

Yep. Do you think you need that? That's a good question. I I'm going to always operate with this with most of my impact coming from, like, founder mode, but I do need given that there's so many things thrown at me and coming in from all the different directions to have kind of a protective layer that introduces a lot of order in like how do you prioritize all these incoming things. And that comes down to a well running organization. And then you for a well running organization, you need a very organized manager somewhere at the top. And I'm not planning to be that manager myself, but surround myself with great leaders who who do more of the organization.

**Harry Stebbings** [8:59]:

Do you have a protective layer to say? Because I get probably 25 intro requests for you a week, and I probably make one a month. Do you have someone who does filter?

**Anton Osika** [9:08]:

I do. Yeah. And and they say it's a kind of a wonderful chaotic protective layer that works together as a team. Team. I don't really have like a name for it. It's just the people working closely with me. So the team is made up of previous founder type generalists that work closely with me and I work in terms of like quick feedback. This is not what we should be doing. This is what we should be doing. Works okay now. I think we can do even better.

**Harry Stebbings** [9:31]:

You said talent was number one and brand was number two. If we think about great brand, what does great brand mean to you? A super

**Anton Osika** [9:40]:

concrete example is the Apple ecosystem where they obsess about details maybe too much so they move slowly, but that's what builds up trust and is a very strong brand. That's what we're aiming for as well in every interaction, like every time we update the product, how do we make sure we roll it out so that we really understand the users and how their reactions to all the things we're changing very rapidly in in the product, in the company.

**Harry Stebbings** [10:02]:

There's a couple of questions which everyone has where they will kind of throw them as a critique at Lovable or at anyone in the space. One is protection defensibility. When you think about defensibility today, is brand the core element of defensibility or is there something that people do not see?

**Anton Osika** [10:21]:

No. I think you need to build a product if you want to, like, maximally defend be defensive, where if you are on this product and the platform that the product is, you don't want to live because you have so much value that you've created on the platform that you're getting automatically every day. So that's what Lovable is becoming in this product building platform where you Lovable today is your technical co founder. We wanted to be your co founder in general that handles all the admin, setting up your finance operations. But if you're on a platform like that, you you probably don't want want to live.

**Harry Stebbings** [10:51]:

Would you say to all founders building an AI today from day one, don't worry about defensibility, it comes over time?

**Anton Osika** [10:58]:

Yes. Great question. I have a friend who has this fun analog in terms of an AI startup, which is that AI startups are like chickens shot out of a cannon up in the sky if you if you can start getting traction. And then it's all about flapping fast as a chicken because there are new chickens shot out from cannons every day. And if you keep flapping faster than the other chickens, then you're going to do great. And I think that's a good like first

**Harry Stebbings** [11:22]:

level of analysis in how you should operate. I'm just gonna say for any vegans that are listening, no chickens were shot out of cannons, and that is the most extremely Swedish way of you know, it's the Reid Hoffman who says, you know, it's about kind of running off the cliff or whatever with a paraglider and just kind of flapping. That works too.

**Anton Osika** [11:38]:

Yeah. I think I think that's my recommendation, to just be like, execute fast, grow faster. When you're starting to get up there, you can start maybe start thinking a bit about about the defensibility.

**Harry Stebbings** [11:48]:

That's the one criticism. Another is that actually when you look at these businesses, and a lot of people are criticizing this with your Replit, your Bolt, your Lovables, they're not actually very good businesses in terms of unit economics, and so much is passed through. So, like, bluntly, if I give you a dollar, how much is passed straight through to Anthropic and OpenAI? I don't give

**Anton Osika** [12:08]:

you the exact numbers, but if you look at the paid usage, majority, it's not everything.

**Harry Stebbings** [12:13]:

How does that change over time?

**Anton Osika** [12:15]:

So as our business develops, we're looking to get most of our revenue once you as a user are like, I love this platform, I'm never leaving. But today it's only like in the beginning, you're paying to build pretty much. So over time, we just want to create so much value, stay on the subscription, and a small part of the cost is goes to the to their AI compute.

**Harry Stebbings** [12:36]:

Will you be able to make money through not optimizing models? And what I mean by that is in the future, you may not need the very best, very latest model to do the simple about me website. And so you can route users. As

**Anton Osika** [12:52]:

all applications develop, the AI is going to be adapted to those applications. And for most things, it's like super simple to do it. It's like you're driving a car and you don't you're not thinking about what you're doing. When you're in a new situation driving a car, then you're like your brain really goes on fire. We're not there. We're not close to being there yet. I think for us, it's too early to optimize for that because the AI is every month is like doing new completely different things. So we just want to be able to iterate really fast on what the AI is able to do and not optimize the models for what they what it's doing.

**Harry Stebbings** [13:22]:

That's really interesting. So you build for what tomorrow's model can do, not what we have today.

**Anton Osika** [13:27]:

Yes. To quite a large extent, yes. And generally, when I think about models, they're the models that are very thoughtful and deep thinking. And now we put as much of work on those models. In the future, it's going to be a mix in terms of when it's obvious what you should do, it doesn't cost any money. It's super fast. But when it's a new situation, which building a software product often results in, then it has to think much more.

**Harry Stebbings** [13:52]:

One other area where you can see real, like, margin expansion is also in token selling. Like, when you think about, like, how you price tokens, given prosumers and consumers don't fundamentally often know the price of tokens, you can actually have quite a considerable markup on token usage. Do you think that is a place of real elasticity to gain margin or not?

**Anton Osika** [14:11]:

Yeah. So this was a few months ago, but we looked at how much revenue is flowing through the AI from Lovable applications. Okay. And it was more than $10,000,000 in ARR. And now all of that revenue needs the user to go through this bit complex process of setting up the connection to the model providers. We're looking at simplifying. So stay tuned for how we enable more simplicity, first of all, for our users with that. And then if we can reduce the underlying cost, maybe we can add take a margin there as well.

**Harry Stebbings** [14:42]:

How do you think about mental plasticity to delay margin optimization? So, like, the willingness to wait for margins to come. And what I mean by that is, like, if you look at delivery, its margins are shit in the early days, and over time, they get better and better as you have more and more people use it and more density, more orders in small areas. You've gotta be patient. Same with OpenAI. Same with Lovable. How long does one think before you're thinking margin optimization?

**Anton Osika** [15:12]:

I have these two conflicting pieces of perspectives on it. And one is I speak to Nik, who built Revolut, and he just tells me, like, Anthon, you need to compute the payback time, and then you need to do super hard performance optimization on acquiring new users. And then you of course need to have a good payback times in terms of profits per user, which makes sense. If you can do small changes in on margins, actually affects a lot on how fast you can grow. But the other perspective, which I index a bit more on right now is you just want to have as much mindshare and as many users who just love the brand as possible right now. And then you can think about that later. So exactly how I trade those two perspectives off is you need to look at the weights in my neural network, but it's some combination of the two.

**Harry Stebbings** [15:56]:

It's so funny. I think it's absolutely number two. And then it's number three What is that? Which is NICS, which is, like, incredible performance optimization. Yeah. Really understanding funnel metrics metrics from from CAC CAC to to LTV, how you drive efficiency through the channels. Then do you know what's ironic? You kind of then go back after that stage to an art, which is where Nik is now, which is we've done that so well. Yep. We have to sponsor race cars because brand again becomes the most important thing. It's so interesting. You know that kind of bell curve where you see it up and then it comes down again. It's it's kind of like that on brand where you have it at both ends of the spectrum. Yep.

**Anton Osika** [16:30]:

I think you like, if you can do everything at once, the company benefits a lot, but you usually can't. Like, you should you should be focused. What would you most like to do

**Harry Stebbings** [16:38]:

now that you're not doing or can't do?

**Anton Osika** [16:40]:

So I would like to rethink how the applications are built. Like, what is the best way to build an application. What Lovable does now is it takes all the best practices from decades of how great software products we built. But that's not how the future is going to look like. All software applications are going to have some type of AI. They're going to have extremely seamless payment and checkout flows. That's something I'd love for us to spend time on figuring out and making it possible for our users not to just have superhuman AI engineer, but to have a AI engineer that

**Harry Stebbings** [17:13]:

builds like the future of applications. We mentioned margin optimization there. When we look at kind of the model providers, we said that it's one way you also have to have that mental plasticity. We saw OpenAI suggest or proffer Lovable style competitors. To what extent do you feel OpenAI and Anthropic will come after Lovable in the way that Claude code comes after Cursor? In the

**Anton Osika** [17:36]:

long term, it just comes down to execution of a team and many people are going to offer what we're offering today. We just need to offer much more when that time comes. Give a better user experience, give a better value proposition to our customers.

**Harry Stebbings** [17:49]:

Who do you worry more about OpenAI doing or Anthropic doing it?

**Anton Osika** [17:53]:

What we're betting on is to be the gateway for humans and be the best user experience for AI. And so far, OpenAI is doing that better than Anthropic. So I see them as a more serious competitor in that in that in twelve months.

**Harry Stebbings** [18:06]:

How did you analyze GPT-five? And when you look at performance post, are you more or less bullish on OpenAI? We

**Anton Osika** [18:13]:

looked at a lot of how GPT-five would impact our users before we decided, okay, let's put this into the product. And we looked at how long time it took to get responses. We looked at our quantitative evals and then we just vibe checked it in many different ways. And what we concluded was that it's oftentimes too like ambitious for our users. And that's why we decided, hey, this is very smart. So let's give it all our users and see what they tell us in terms of how like what's good and what's bad. What we found was that for the use cases, when you have to solve a really, really hard problem, it's great. In terms of is OpenAI doing a great job? I think this was a really smart obvious choice for them to say like we have these five different models that you have to select in ChatGPT. Let's just bring it down into one model GPT-five. So they should definitely should have done that. But it comes with a lot of trade offs. And so far, I'd say they executed pretty well on it. The model

**Harry Stebbings** [19:09]:

is still too ambitious. There's also a question of when you set the bar at AGI, and then you get model optimization and model routing, really essentially what it is. That's it. Capability wise, it hasn't been a step function improvement in what we had before.

**Anton Osika** [19:23]:

The biggest part of GPT-five that's disappointing is that now they have to optimize all these different things into one model. Before it was like different models and they had to do it really fast. So it's inevitably going to fall short in some dimensions. I mean, it it just is a disappointment that you can't improve in all the directions at the same time. How do you use OpenAI versus Anthropic within Lovable today? We have a this very complex agentic chain where we pass the users response, the application information through many different models. And like we take really fast and small ones and then we use for code writing. We usually use Anthropic. And right now you can say like, I want to use GPT-five, and that's better when you're solving a really hard debugging problem.

**Harry Stebbings** [20:02]:

Super interesting. And you've seen it be better than Anthropic when it comes to a hard debugging problem? Yeah. What do models not do today that would be a step function change in what Lovable can do? Like something

**Anton Osika** [20:12]:

I'm I'm super excited about is that the AI has more context about who they're talking to and how they should be answering to guide them through our specific application. Solving that problem is something that we have to do. And we have to do it both with like how we build this agentic chain and over time in building absolutely world class, paying $100,000,000 for getting the people that train the models. So that's the on the horizon for us to to get it to like be hyper personalized for you specifically.

**Harry Stebbings** [20:40]:

When you think about hyper personalized for you specifically and the users that you have, you recently announced a 100,000,000 ARR, amazing milestone to hit in seven months. For years, dude, it was like zero to ten million in two years was like the gold standard. Yeah. That's what I was brought up on, which makes me feel really old. My question to you is when you look at revenue breakdown, of the 100,000,000, just kind of guesstimate, what is split between hobbyists, pro devs, kind of normal people? How does it fit between the different segments?

**Anton Osika** [21:10]:

You're right. So people do everything with Lovable. They come with their idea to build a software business and product. And then there's a lot of people in large companies that use it as like, okay, now I can prove show what I actually think we should build in the business. And they build a working product that then they can like decide, are we going to give it to our engineering team and they actually implement it. And then it's everyone else who build like their personal website, their small business websites, like in a few minutes. 80% of people are are in the first category. They're building real complex applications in terms of revenue. Yeah, in terms of revenue. Percent. And then the second segment is actually growing very fast because enterprises are slowing to wake up. But you might have seen this product leader from Google who says like we're never again writing a document about a product. We have to use Lovable or something to build out a fully working demo. That use case is also growing very fast. And in terms of the third use case, a lot of people have been burned trying to build nice websites in this like no code website builders with Squarespace and so on. And if you can just always do everything they loveable and with a UX that I think is more sophisticated in moving fast, that's also growing. But I think the the first two are the ones who are really, like, game changers.

**Harry Stebbings** [22:21]:

Okay. So we go back to 80%, sorry, is, like, actually building complex apps, and then 10% is enterprise and 10% is hobbyists? Yeah. Is that what you want it to be?

**Anton Osika** [22:29]:

We want to build for the new generation of AI native founders that build like maybe one person unicorns too. The funny thing is that those people also have jobs maybe in large successful companies, and they wanna help their friends and their family to build simple websites. So I think this is a yeah. I think this is a good split.

**Harry Stebbings** [22:49]:

Is that an optimal market to go after if you're thinking, god. It's not such a VC, but, like, value extraction, which is like an AI founder building a mega business on Lovable. Great. You wanna have to have a lot of mechanisms for value extraction and then be it payment solutions or you name it. But if they're single seat, it's just like tough to get true value extraction from that. Is it not much better to be hobbyist for everyone, for mom and pop, to build the about me website where it's 7,000,000,000 people?

**Anton Osika** [23:15]:

Like, our mission is to enable a lot of people that have the opportunity to build businesses, but they have been held back by not being able to write code and have access to capital to hire engineers. So it's obvious to start with the people who are going to build businesses. And then it naturally trickles down to everyone else as well as a function of that. Think those are the best people to start building for. Where you can extract value, I think less about that. I think about our mission.

**Harry Stebbings** [23:43]:

You should have, like, a lovable holiday fund, which is like every year we pay the most talented people within large enterprises for a week's holiday. And then they build their business. Yeah. So they they can they can They'll just use Lovable for the week, and after the week, they see they quit their job. Yeah. I think it'd be the funnest thing ever. I think that

**Anton Osika** [24:01]:

sounds good. Yeah. Yeah. But I can just expand a bit on, like, on the business thinking there as well. Yeah. So I think many of the largest businesses, they haven't been quite started yet today. Now with AI, you can move so fast, you can iterate much faster, close to your customers. You can drive prices down. We want to be the enabling tool for that movement. I think over time, that's going to result in a lot of revenue. If we can do every all of these use cases as that you're asking about at the same time, what our use case percentage of adoption or revenue is going to converge towards is just what's the what's the spend from enterprises? What's the, like, end game spend from enterprises? What's the end game spend for consumers on tools like this if we continue to dominate this completely new category?

**Harry Stebbings** [24:44]:

Obviously, I'm super grateful for you for taking my money. But the reason the number one reason why I would invest in Lovable, LATAM expansion is actually incomprehensible. Very much like Uber, you could never have foreseen the market expansion that would take place. Yep. Very much like Lovable. Saying website builders is an x market is completely the wrong analogy to understand how big Lovable could be moving forwards. And that's a common thing of the best venture investments ever made.

**Anton Osika** [25:09]:

Yeah. I I think also just wanna say on the enterprise use case. So if I was a CEO or like a CTO of a large enterprise company, I wouldn't think in terms of, how can we make our engineers more productive? I would think in terms of how can we get the most information about what we should build as quickly as possible into new products or into our existing products. That requires everyone in the company to be able to work in one place to change and edit their products and propose new changes to it. It's hard for us and for anyone in that matter to build a product that does that tomorrow. It's better for us to start with the founders who are building it from the ground up and then move it into the enterprise, the same experience into the enterprise.

**Harry Stebbings** [25:50]:

It also allows for this incredible democratization of ideas within companies. I interviewed the CP at Duolingo for 20 products. And he actually said how two designers, not traditionally ones who actually come up with obviously building products Yep. From day one, created chess in Duolingo. And they did it with I can't remember what the tool was. I hope it was lovable. And that was actually their first iteration of it, which I thought was an amazing instantiation of this. Does that mean then that we lose the design process and the brainstorming process? Do we skip that and go straight to prototyping?

**Anton Osika** [26:23]:

Look. To date, what you've done is that you've taken an idea and then you went through many, many, many steps until it's like a fully fast growing product. I call that the product life cycle. One part of it is writing the code, which is like where AI now has made it much faster. There are many steps after that. There are steps before that, which is to like mock it up, validate it internally, validate it with your users. What we've done so far is to take all the first step until like this is validated. This is what we need to ship. And even we have even external users on it into one few minutes or a few hours of building. So that's where we've seen like the most maturity on our product. The steps that come after is something we have to build out as fast as possible so that you don't need like a product design engineering organisation. It's one all one tool where anyone with the best ideas spend the most time.

**Harry Stebbings** [27:11]:

The steps after all the steps before. And what I mean by the steps before is you see at the other end of the spectrum, Figma doing Figma make, where they're like, hey. We'll always have the design process, and then we'll move with you into the second phase of that product life cycle Yep. Into the build or prototype phase from design to prototype. To what extent do you worry about entry from that earlier standpoint? Entry from Figma or Yeah. Entry from Figma, given the fact that they own the design phase, just then move into prototyping.

**Anton Osika** [27:40]:

I think humans are sometimes too obsessed with small details being perfect, which makes you move much slower. And the way of doing it right now with the design and what like one person does all the design very slow, very detailed is going to be replaced by AI doing you talk much more high level and you talk about your design philosophy and then the AI does the implementation of design. And then you as a human go out and get all the context from do other people think this is looks good and give it all as feedback into the AI. And then there's a very seamless opinionated way of taking it all the way to a product with all the marketing and growth functions in built in AI behind it, as well as all the tooling you need to evolve high quality software product, comes like testing, quality assurance and so on. And that's a new way of doing it and thinking you should be doing design with Make and like the Figma tools, it will slow you down too much.

**Harry Stebbings** [28:32]:

What happens to Figma then?

**Anton Osika** [28:34]:

For some pixel perfect things, it's going to be amazing to continue to use Figma. I don't know how the distribution will look like in terms of doing it with a more opinionated way, which is what our platform is becoming, versus how many companies want to continue to do it like you do it now in a tool like Figma. Do you think you're opinionated enough? Our tool enables a lot of flexibility at the cost of some velocity on our product development. But I think it's a pretty good sweet spot. You can build with Lovable and then any engineer can come in and edit and take over if they want to. I think, yes, we will we would be moving faster if we were more even more

**Harry Stebbings** [29:10]:

opinionated about how things should be done. What are you not opinionated on that you would like to be in a dream world? In a dream world, we would

**Anton Osika** [29:17]:

be even more opinionated about how you build an application and we would know what's the future of building applications with AI being such a core part of it. I don't think it's possible because how AI works and like what's the best UX with AI for the products that are built with Lovable changes so rapidly. At some point in the future, I'd love to be there. And what happens if we can be more opinionated is that you get the right level of detailed adjustments on how the AI works for your product, or back end flows and workflows, so automations work for your product. And now we have we support a lot of different things. So it's more you need to be really good at prompting right now. Do you think we will prompt in five years time? Yes, I think so. But maybe it will evolve in terms of how you do it. Like hyper personalization takes care of a lot of detailed prompting that we have to do today.

**Harry Stebbings** [30:10]:

What does that

**Anton Osika** [30:11]:

mean? Prompting is basically providing context to an AI of what your goals are and how you want it to do something. When you have great employees for you, They know everything about how you how you want it to work. So you just have to say, let's go to Stockholm and do a hackathon and then it just magically becomes what you want it to be. It

**Unknown** [30:28]:

pretty much does. Honestly. I to say

**Harry Stebbings** [30:31]:

that I sent a picture to my mother beforehand and she's like, you had nothing to do with that. And I'm like, no, I did not. She's like, I know. Right. And

**Anton Osika** [30:40]:

you can't just say tell ChatGPT or something. Let's go to Sacramento hackathon. He's gonna come up with something else than what you had in mind. Right? Mhmm. And so you can either prompt it very, very detailed or you can make sure it's it knows how you think. And that's what we'll be evolving towards.

**Harry Stebbings** [30:55]:

We said the word opinionated. Yep. And we spoke about it with regards to the company. Dude, I love your social media presence because you're also opinionated in your social media presence. And I think it's, respectively, also just quite blunt. And you've been opinionated in how you talk about competition, and specifically like a Replit of the world. How do you think about whether or not to engage in an opinionated stance against competition or not? I

**Anton Osika** [31:20]:

don't think so much about competition. The only thing that matters is that we make our product the best product and we continue to deliver on like our value promises to our customers. If there is something that happens, so there was a competitor that found a lot of apps that have been poorly made and they said, oh, this is a vulnerability. And I spoke to a lot of security professionals. That wasn't really like how you would normally announce vulnerability. So then I went in and bashed them as an outcome of that. Think I that was a very reactive thing, and I think it was like something I'd be happy to share in person to that competitor, like, face to face.

**Harry Stebbings** [31:57]:

Well, I mean, it was it was interesting because Jason Lemkin, who's a friend of mine, I don't know if you saw it, but he was using Replit. And then I can't remember exactly what happened, but they basically had a massive security breach or they deleted all his database or something bad happened, and it was, like, code red for them. And the takeaway for him was, like, just security on all of them. Yep. It's just nowhere near where it needs to be. And, like, it's wrong for Replit to bash Lovable. It's wrong for Lovable to bash Replit. All of you guys suck at security. Is that true?

**Anton Osika** [32:25]:

Yes. I think they they yeah. Like so let me say it different way. First of all, we talk about security like company wide every week, almost like every day I hear something about security because we take it so seriously. There's so many different fronts to make it much more secure than if a human would do the application development. And that's why it's so important for us to be the best in the world at security. So you're saying

**Harry Stebbings** [32:48]:

it's more secure than humans?

**Anton Osika** [32:50]:

Not yet. If you take your average developer who normally works in a large team where they have a lot of support and then they they that human goes out and builds an application, they are going to create software that has security holes on average. When you build an application with Lovable, it's going to tell you to go through a bunch of security reviews, and the AI is going to do a bunch of security reviews. And finally, it's going to give you green light like we haven't found any security vulnerabilities. If you compare those two, the the average, truly average developer with Lovable, Lovable is going to have a lower chance of having a vulnerability. And so we want them that put that to 0%. We need to put that at 0% chance of vulnerability. It

**Harry Stebbings** [33:28]:

reminds me of self driving. For the world's best driver, I'm sure you are better than self driving. But for the majority and for the majority who are tired Yes. Humans have the potential to be hungover, high, malfunctioning in some way, actually wildly dangerous and much, much better. Very much so. Yep. I'm very proud of what the team done so far

**Anton Osika** [33:47]:

with

**Harry Stebbings** [33:47]:

the

**Anton Osika** [33:47]:

security, and but there's more to come.

**Harry Stebbings** [33:49]:

We've spoken about many different competitors in different ways from your Figma to your Replit. If you move forward three years, what does the space look like then?

**Anton Osika** [33:58]:

I focus on what our product does and how we serve our customers best. And like, I don't really predict that. If we get all the the majority of the profit share in this market, that's amazing. This is spread out across different companies. That's that's also fine as long as we build a product that lasts for generations. And that and I do that by building the best product for our customers.

**Harry Stebbings** [34:17]:

And this is why brand is so important for you? That's how I think about it. Do you mind if devs go to Lovable, get 60% of the code from there, and then fine tune it?

**Anton Osika** [34:27]:

I don't like from the get go two years ago, I decided that I'm gonna build Lovable. Know it's for a world where humans don't write code anymore, and they were quickly moving there. We're very, very quickly moving there. Today, I don't mind at all. Like, it should be flexible. Some humans have their way of doing things. And I think it's good if you have like ecosystem where you can use many, many, many different tools on on the product. Over time, I think it will converge towards the very opinionated platform, like the ones we're building towards, and everyone's look at what's the cost benefit of doing it with some other tool as well. Only using Lovable is going to be the obvious, most the high velocity and high quality driving choice.

**Harry Stebbings** [35:06]:

Today, does AI make one x engineers 10 x, Or does it make the 10 x engineers a 100 x? It does both. It really does both. I have to force you to one.

**Anton Osika** [35:19]:

For the junior engineers, one x engineers, they often are bad at something. Right? If they can bridge that gap, it takes them from zero to one and to be able to do something they were not able to do before, it's like a 10x, they go to 10x or even more. So if that's the case, then they definitely got, then it's more valuable for them. If it's a 10x engineer working on something where you need a lot of many years of experience to work on a system that a new junior engineer completely doesn't understand, the user, the 1x engineer doesn't understand the system, then the 1x engineer is useless. So no AI is going to increase their velocity, whereas the 10x engineer is going to maybe go to 100x engineer.

**Harry Stebbings** [36:00]:

How will the size of engineering teams change in the next five years?

**Anton Osika** [36:04]:

For the best companies, engineers will react as this translation layer. They will need to be more thinking more in terms of product, being a product manager. I think there's a higher elasticity on such engineers. So you might see many companies being like, oh, more engineers, we can do even more, even faster. They are out talking to the customers and changing things with AI super fast.

**Harry Stebbings** [36:26]:

Do the skills required to be a good engineer then change with time?

**Anton Osika** [36:30]:

Yes. Definitely. Like, I think being a generalist becomes more and more important with everything in everything with AI so that you can understand how things will come together as a larger whole. And then you use AI for the deep expertise that you don't need in the future as much.

**Harry Stebbings** [36:48]:

When you think about skills required too, there's a lot of people who are asking today, should I bother studying computer science if we're gonna see Lovable be the last software that we ever need? How would you advise your little brother questioning whether it's GCS at

**Anton Osika** [37:04]:

university? University is not the best place to learn. It doesn't matter what you're studying. You should be out there and really understand how the world works in terms of how work translates to value creation. And you don't learn that at university. And so university is like a way to train your brain to learn new things and meet a lot of interesting people. Would you encourage your children to go to university? So this is now twenty years in the future, pretty much. So it's hard to say to say something about twenty years in the future. I think it's a great experience to have had in life. Why not? But it depends on what outcome you want to reach. If you want to have a job that where you make the most money, no, they shouldn't go to university.

**Harry Stebbings** [37:44]:

I think the opportunity cost of those years is very high. True. Yeah. In the in The UK in particular, just get very drunk for three years. Yeah. And that's generally how it is. And generally, we study generalist subjects like geography and history. Honestly, it is a little bit of a waste of time, in which case you can utilize those years so much better given your stamina, your energy, the plasticity of your brain at that age, which is why I highly advocate against it.

**Anton Osika** [38:08]:

Agree. If you just do a very, very specialized job for those years, maybe you'll become less of a generalist. So there's like there's a trade off there as well, of course, that while as university, you're exposed to many different concepts which can be useful.

**Harry Stebbings** [38:20]:

We mentioned earlier AI and enterprise. When you look at the biggest enterprises today, they're not able for data, for permissioning, for security to use AI. Are we going to see the biggest shift in incumbent power in the next ten years?

**Anton Osika** [38:37]:

So if they're not enabled, there's someone else that will come in and be enabled. I think you see this in banking, like, for example, where bank is a software company, right? It's all about software systems. The old banks are moving much slower. Yes. There is going to be some companies that are like built ground up for an AI to change their systems. And anyone who's exposed to like customers understanding the legal requirements and so on can move much, much faster in creating a good customer experience. So yes, I imagine there are also some benefits of being having been around for a long time in the enterprise. In like banking, there's a certain level of trust and so on. So I don't know how large the shift is going to be in across different segments of the enterprise market. Many companies will be get disrupted by cheaper, much, much better alternatives.

**Harry Stebbings** [39:25]:

Interesting. You said there about trust. How loyal do you think Lovable users and customers are? Do you think there's a high propensity to switch and an ease to switch, or do you think people fundamentally are loyal? It's fifty

**Anton Osika** [39:35]:

fifty. Like, some people are just super super loyal to a brand. Many people I mean, if you do something that hurts your brand, they will switch, and they're just out there looking for maximizing some kind of cost versus capability subjective. You can think about both of those groups simultaneously. Like, if you have the best product with the best value, you're going to get everyone.

**Harry Stebbings** [39:56]:

We spoke about kind of people being threatened, large incumbents. What questions should large CEOs, business leaders be asking today about the future of AI and their companies and how they use it that they're not asking, do you think?

**Anton Osika** [40:10]:

One of the biggest bottlenecks for this company is going to be some kind of change management for the humans in the organization. And I think they should be asking how have similar companies to ours changed management very, very, very rapidly and get that conversation into the leadership room and then maybe across the entire organization. Just started those examples of where change management has been very successful. And then look at specifically which AI tools should we be using. Should we be building our product on top of Lovable 100% because then everyone can collaborate there? Should we hire some new type of people that come in

**Harry Stebbings** [40:44]:

and upscale everyone? You said about speed. You said about talent earlier. Bluntly, dude, I get really fed up with everyone saying that Europeans are about espresso and take in the summer, and it's August and July, we're not gonna work. And I advocate for a very aggressive work culture, which, you know, is nine nine six. Yep. How do you feel about the importance of unwavering hard work over balance in the desire to win?

**Anton Osika** [41:12]:

I think over a ten year period, I would advocate for some balance. But if over a two year period, if you really care about something, then you should make sure that you have, like, you get your exercise, you sleep in really, really well, maybe something that you know relaxes you, and then just work your ass off. That's what you should be doing.

**Harry Stebbings** [41:31]:

Do you agree then with Scott from cognition, who clearly said to all wins of employees after hiring them or buying the company, it's six days a week. It's unwaveringly relentless. And if you don't wanna sign up for that, you can leave. In how

**Anton Osika** [41:47]:

we think about it is that you are here to have 10 x impact over the other people at other companies. If you don't have 10 x impact, so for well, you do that by being very talented, being good at your job, and being very focused. For some people, you need to put in a shit ton of hours, but not for everyone. Am I seeing the impact? Am I seeing that if you would tell me you're leaving tomorrow, I will be like, no, you are like such an important part of this company, you have to stay. And that's how I push performance and impact. Do

**Harry Stebbings** [42:14]:

you do the keepers test?

**Anton Osika** [42:16]:

Yeah.

**Harry Stebbings** [42:16]:

Has it made you change how you construct teams?

**Anton Osika** [42:19]:

Yeah. I think it always under makes it clear to people that I need to always figure out, am I like, how can I have more impact? And then I think in terms of what does this organization look like, is it optimally set up to to succeed right now? Culture is such an important part. If you just like throwing people around too much, it's it hurts the culture and the ways of working. But doing this business exercise of saying, who is this organization set up perfectly to win, definitely shapes how I build the organization.

**Harry Stebbings** [42:47]:

You mentioned Nik earlier at Revolut. He gave me the best answer I think ever on culture. You know, I've done 3,000 shows. When culture comes up, it's like first principles thinking. I'm like, fuck it. We'll edit this bit out. Always. But he said the best thing ever, he said, I don't think about culture. Think about winning. The single biggest determinant of human happiness is growth and development. And when you are winning, you are most optimally positioned to grow and develop. And so if I create the conditions to win, you will grow and develop. And then supporting that, the other thing that people like to do is accumulate wealth as well as development. Yep. And you will accumulate that by winning because of your share price increase. It's That's

**Anton Osika** [43:23]:

a good quote. It's a really good way to

**Harry Stebbings** [43:26]:

think about it, which and I think it's the same, which is, like, if we win, everyone will be happy. There's very few places where they're losing every day, day in, day out, and blissfully happy. Yes. It doesn't happen. What's not great about your culture today if you could change it?

**Anton Osika** [43:41]:

There's a certain personality type that has takes a lot of initiative. They're very excited about new ideas and doing novel things. And as your company matures, that isn't still an important ingredient. But you need the first priority to make what you have high quality to continue to be high quality and improve the quality across everything you're doing. And I want us to be even more like memeifying, let's improve the quality, let's improve how we do things, move slow so that we can move really, really fast.

**Harry Stebbings** [44:13]:

You want to be more thoughtful around where you spend time and where you don't?

**Anton Osika** [44:17]:

Yeah. So this cowboy versus farmer analog where a farmer is like optimizing things for the long term, and I think we can do a bit more of that optimizing things for the long term. But but we always strike the balance of doing You're

**Harry Stebbings** [44:31]:

in that phase of company build yet. I I actually prefer the optimize for the short term. I don't know if you spent much time in China or with, like, Chinese development teams, but they are unbelievable in their psychology around build. They optimize for the short term incessantly and then just like sticky tape the shit, sticky tape the shit, sticky tape the shit. And that is often how they're able to do so much so fast.

**Anton Osika** [44:52]:

Mhmm. If you have a super clear product market fit, you have a brand to defend, you cannot you cannot issue. You can do that in like sprints to move fast and innovate, but you really need to focus on like, are these pieces put well together, spend a lot of time on moving things around in the organization, in your in your product so that it has high quality, maintains high quality, and you can build faster upon that foundation. Can you imagine if Apple were like,

**Harry Stebbings** [45:20]:

oh, fuck. We deleted your cloud. Sorry. Yeah. Sounds very good. All bad. I said earlier about like Europe and summer and not moving fast enough. You said before that it is better to build in Europe. And I don't want this to be like an advert for Europe, but why do you think it's better to build in Europe? There are many good

**Anton Osika** [45:39]:

things about Europe. There are also good things, things that are better in The US, for example. I want to prove that you can build a generational product, a generational company team from Europe. And part of it is on hard mode. What parts are on hard mode? The hard mode is that there's a where the network isn't as great in how many individuals and companies that have worked on and have context for like all the different stages of building an amazing multinational company. Completely

**Harry Stebbings** [46:10]:

agree. There are no Elena Vernas in Europe.

**Anton Osika** [46:12]:

Yeah. Maybe we'll get here soon. That's hard mode. I think access to capital, people that will quickly give you a lot of distribution, help you with distribution and and brand. Do think access to

**Harry Stebbings** [46:23]:

capital is a genuine problem? I think there's so much money in Europe that actually is As I said, it's not a bottleneck for us. No. Yeah. It's not. And you're gonna start to see very soon, I'm sure you're probably already seeing it, but Lovable spinouts, where anyone who leaves Lovable will get a term sheet straight away. 100%.

**Anton Osika** [46:37]:

I think it's easier to get distribution to be on like the center world stage in San Francisco and New York, But we've been able to pull that off from Stockholm, which is a good

**Harry Stebbings** [46:45]:

proof that you can do it from here. Why do you think you've been able to do it? I I have my theory on why I think you've been successful.

**Anton Osika** [46:52]:

I think it's about storytelling and and sharing everything we're doing at the company and empowering other people who are using Lovable, telling their stories, a bit of that. That's how we broke been breaking through. We understand that you should be building in public and share what you're doing.

**Harry Stebbings** [47:07]:

Transparency is everything, and people like to follow people. And you've combined the two very well, is you're incredibly transparent around your ARR growth. Easy to be when it's as good as it is, but you're incredibly transparent in a way that most people aren't, and then it's led by you and your voice. And the two combinations of, like, cult of personality, you and Anton, and then you and ARR growth is what really drives the success in that way. So that's kind of what's harder. What's better? Like, why why should everyone build their company in Europe? I I mean, we are

**Anton Osika** [47:36]:

the biggest talent magnet in Stockholm right now, which is amazing. You can't it's much, much more difficult to be that in San Francisco or New York. We can really pick up all the underutilized talent and 10x their performance by being in a 10x better culture or ways of working and like with with amazing colleagues. So being able to be that like top one is I think the biggest one. There's a culture of like humility and low ego and working really well together as a team that I think is stronger for in Europe and like this way of thinking in terms of efficiency and doing much much more with less.

**Harry Stebbings** [48:15]:

You have inherently higher churn in the valley. When you have a bad day, OpenAI offer you a bigger package, and it's like, nah. I'll even do OpenAI. And that prevents the compounding of knowledge within teams, which I think is so valuable. Yep. Would Lovable be less successful if it were in the valley? I honestly don't know. I think it would be it would be very

**Anton Osika** [48:32]:

successful regardless.

**Harry Stebbings** [48:33]:

Did you ever think about moving?

**Anton Osika** [48:35]:

Yes. When I was about to start the company, everyone was, of course, telling me I should go to SF. But we just kept building and we found some great people in in Stockholm. So we we kept building it from from here. I'm

**Harry Stebbings** [48:48]:

happy how it turned out. That was a decision which you, you know, made and it worked out very well. What did you do in the Lovable journey that with the benefit of hindsight and some experience, you wish you hadn't done?

**Anton Osika** [49:00]:

Look, when we started, we had this this idea. The vision was very clear. The sequencing was not so clear in what what we should be doing. We had we had this open source community that was kind of excited about a tool I made a few months like before we started the company, GPT-Engineer. I think we shouldn't just like scrap that completely and be 100% focused on what's the future look like in terms of building, opening your browser, just building your product there, which is lovable. Why should you have scrap that? You should be very, very focused on doing that. Was

**Harry Stebbings** [49:29]:

it not crucial for customer development, customer feedback?

**Anton Osika** [49:31]:

No. I don't think so. And there was, of course, a plan for how to incorporate it to and get more value together. Open source can be very very useful for many businesses with the perspective of maximal focus, it was just a bad idea to do things that were like a bit too tangentially related. So that's definitely one thing. And this we talk a lot about doing one thing, finding the bottleneck for the company, solving for that bottleneck is the best way to move really, really fast.

**Harry Stebbings** [49:58]:

What is

**Anton Osika** [49:59]:

the

**Harry Stebbings** [49:59]:

bottleneck that

**Anton Osika** [50:00]:

you'll be discussing in the board tomorrow? I think the bottleneck for our long term future is how we identify the technical product, so engineers that will take the product to its next phase and innovate on many, many fronts at the same time. That's in the long term. If you think about the product today, it's giving our AI more capabilities that are really like make it really polished user experience and give it more of those capabilities so that you can build out your full company, grow your business on top of Lovable. Then a bottleneck is for how we serve all this extreme amount of enterprise customers love and pull from them at the same time as we focus, like, prior one is for the for founders building on Lovable.

**Harry Stebbings** [50:44]:

Will Lovable have an enterprise sales team? Yes. And become an enterprise company? They will not become an enterprise company, but but

**Anton Osika** [50:51]:

they will have us enterprise sales team.

**Unknown** [50:54]:

And what is

**Anton Osika** [50:55]:

that? Yes. I'm not so nervous about it. That is just about talking and understanding your customers, making sure they have the tools to get value from the products. That that is what I how I see that that part. And there are course many enterprises like top down enterprise sales team that hustle themselves to wine and dine CEOs. I I don't that's not what we're going to do. What is the hardest role to hire for for you? So I think hiring engineering leaders is very difficult because it's so hard to predict how their past performance will translate to our organization.

**Harry Stebbings** [51:26]:

Have you made mistakes on hiring? Yes. I've made some mistakes. What did

**Anton Osika** [51:29]:

you do that you wish you hadn't done on hiring? I wish I was in the details when I and not delegate too much. And and I I wish I was more proactive about, like, does this person want to reach the outcomes? Are they excited, inherently motivated about the outcomes?

**Harry Stebbings** [51:44]:

I think something that's really interesting when you say about kind of leaders there is I thought of, you know, your cofounder, who was in the video for the OpenAI release. Yep. And what struck me with that is, respectfully, it was one of the first times I've seen him front and center, not you. How do you think about exposure between the two of you, given you are very much the face of Lovable?

**Anton Osika** [52:03]:

I'd love for Fabian to have more exposure, but I also want him to be focused on building the product. That's what he focused on. It's much easier for people to relate to Lovable if they see one person and keep seeing that one person. Today, that is me, and I think it will continue to be me.

**Harry Stebbings** [52:20]:

What do you think is the biggest secret to a successful cofounding pair scaling at the speed of lovable scaling? The most

**Anton Osika** [52:29]:

important thing is just the the raw horsepower and adaptability of the founders. If those are maxed out or if those are high, I mean, you must be able to work together. If you have sufficiently low ego, it's going to work. But if you really want to work extremely well together, I'll take an example, is Fabian and me. He's not very big on doing some weird new way of doing things. He's just like simplify it as much as possible. He's quite introvert and quiet until he's like has really shaped an opinion about what's the most important thing. And I'm on the polar side of the spectrum and saying, Fabian, we should use this new crazy thing. And and that's like polarity is actually very productive for both of us.

**Harry Stebbings** [53:12]:

When you think about that and then you think about you're married and very happily married. When you think about successful marriages, what makes the marriage so successful?

**Anton Osika** [53:22]:

Me and Fabian, we can talk about anything and that's extremely productive. And we can talk about turning every stone and challenging each other around anything. And we have a lot of like humility. I think that's very valuable and very important. And the same is true in my marriage. Humility. Humility. Yes. A lot of humility. Does

**Harry Stebbings** [53:40]:

success make marriage harder or easier? I mean, if you have zero hours to spend time with your partner, it makes it more difficult. I also look at 90% of relationships often struggle, and a lot of arguments is based on money, which is an inevitable thing that's very hard, especially as cost of living goes up. And for a lot of people, that then doesn't become a problem. Has it changed your marriage? Not so much. No. Very humble Swedes, aren't you? Yes. We I

**Anton Osika** [54:06]:

haven't changed my lifestyle since Lovable was successful. Have you not? Maybe I think less about monetary decisions, but, no, lifestyle is pretty much the same.

**Harry Stebbings** [54:14]:

What does the Lovable product look like at the end of twenty twenty six?

**Anton Osika** [54:18]:

I mean, it's your perfect cofounder that you go to with your idea from the idea stage, but also all the way up to growing your business once you have customers and taking care of, like, what Ilya and I is doing, optimizing the product for growth, optimizing the product and optimizing your communication with your customers, be it through email or through different marketing channels. So you eat the whole stack then? Yes. One opinion to way to do the entire product life cycle.

**Harry Stebbings** [54:45]:

You do everything from email marketing to SMS marketing and everything in between?

**Anton Osika** [54:49]:

Yes. And and obviously, this is what an enterprise also wants to build their products on. In the interim, they're using it for individuals, like people in teams, building out ideas that the enterprise companies should be doing, and that you're doing that very, very, very productively.

**Harry Stebbings** [55:03]:

Is benchmarking for models bullshit and evaluation is bullshit? I had Edwin from Serge on the show. Do you know Serge? It's like the scale AI competitor, but it's actually phenomenally successful. It's never raised a dollar, and it's a billion 2 in revenue. It's unbelievable. Well And he was like, the benchmark evaluations are bullshit.

**Unknown** [55:22]:

Mhmm.

**Anton Osika** [55:23]:

I mean, they they turn more and more bullshit over time. There's something called Good Heart's Law. So when you start optimizing for a number, that number stops being a good measure for success, even if it was a great number for a measure of success previously. So that obviously that happens like with all benchmarks over time in some sense. What metric within Lovable means less over time? So it means less if we start optimizing for it. Right? And I guess one example where it means less, I guess, is how many people click the thumbs up button on messages because then we can say say fun jokes or whatever that for some reason just triggers people to be more just asking the human click the button, click the button if you want to do it. And and that's then we're hacking the metric. Right? So that's just one example.

**Harry Stebbings** [56:10]:

Dude, we're gonna do a quick fire round. I'm gonna hit you with some incredibly unfair questions, and you can give me your thoughts. Okay? What wildly held belief about AI do you think is just very wrong? I think

**Anton Osika** [56:22]:

AI is smarter than humans, and most people don't agree. And the reason is that this oftentimes it's very, very stupid. But if you give it all the context or you have like you build a purposeful system for that what they are stupid at, it's smarter than humans.

**Harry Stebbings** [56:36]:

Do you think we will see a plateauing or do you think we will see a continuous exponential progression curve?

**Anton Osika** [56:44]:

I think we'll see a plateauing on the things that we care about, which is a lot of nuance and like being good at all the different things at once in in the same model.

**Harry Stebbings** [56:55]:

But people are looking at GPT-five now and saying, we're hitting a stage where actually improvements are much more incremental.

**Anton Osika** [57:01]:

What you've seen so far is like the sigmoid curves across many different dimensions at the same time. And yeah, we're going to see we're going to see a a plateauing. There's some sigmoid curves where I I think we're still in this like exponential phase of the sigmoid curve. And those could be something like science and engineering and, like, bioengineering, where AI is just going to continue to, like, exponentially become extremely powerful and generate a lot of new medicines and new ways of treating health.

**Harry Stebbings** [57:29]:

Grok, Anthropic, OpenAI. You can invest in OpenAI at $3.80, Anthropic at $1.80, and Grok at, I think, it's a 100. Which one do you invest in? And which one do you short?

**Anton Osika** [57:42]:

I'd invest in Grok and probably short Anthropic because, no, I would I would short OpenAI.

**Harry Stebbings** [57:48]:

Why would you buy that Grok and short OpenAI?

**Anton Osika** [57:51]:

I think it's more the slope on the Grok team. They have they're doing something which I respect a lot, which is to hire missionaries for the data curation part, and they call it AI tutoring. I think the morale is much, much better in that team than both of the other teams. Morale is super high. OpenAI has gone through all this mess. Right? Anthropic has good morale morale as well, and they're growing faster on the enterprise side from what I'm hearing.

**Harry Stebbings** [58:15]:

Do you think OpenAI wins the consumer in terms of, like, next generation Google and Anthropic wins the developer and the enterprise? No. I think it's gonna be I don't want there's gonna be something else happening that we don't know what it is. Do think that there will be a leading model that has not been created yet?

**Anton Osika** [58:31]:

Yes. From China. Do you worry about China? Chinese companies are not as good as either we understand your users, so not very worried. I do think there's like a fifty fifty chance they will have the best model will be using a Chinese model at some point. And that makes me a bit concerned because I Do use

**Harry Stebbings** [58:48]:

Chinese models at Lovable? If we would. Yeah.

**Anton Osika** [58:51]:

And I would look have to look into the details and see like what's bad about that. Do we give them data? We don't want to give them. But I I mean, we just wanna do what's best for our customers. If that's going for a Chinese

**Harry Stebbings** [59:00]:

model and there's no negatives, yes. I completely agree. I think also just like the multitude of models coming out of China is just terrifying. When you look at every week, there's like four new ones, and they're all as good as the last one. Yep. And the speed of distillation is just fucking insane. Are the models of the future open or closed? Like, which model wins?

**Anton Osika** [59:19]:

The best ones will always be closed, but if you want maximum flexibility and some kind of open ecosystem around it, it might be that open ones are the ones that most people choose.

**Harry Stebbings** [59:30]:

You can have dinner with anyone dead or alive. Who do you have dinner with and what do you ask them?

**Anton Osika** [59:35]:

I think I would have dinner with Newton because he was like religious and super smart and just like talk about how he was in his age and why he's religious. He's super like, he invented so many different things and he's a he's a bit of a role model and he's dead, so I can't meet him unless I say him now.

**Harry Stebbings** [59:52]:

Sorry. I can't help with that one. There's no intro there that would work. Fuck. That's amazing. What AI company do not enough people pay attention to? Like I said, CERN for me is one, which is like scale AI, but fundamentally a much better business. Barely anyone knows it, and it's ridiculous. Which company does no one pay attention to that everyone should pay attention to?

**Anton Osika** [60:12]:

I think the browser companies are interesting. So there's Strawberry, here's Stockholm, there's Dia and Perplexity now. I'm I'm very excited to see what happens to other of those companies. What do you think happens to Perplexity? So they're they want to create their phone, I think, and I think that's a good bet. Would you invest in them at 18,000,000,000?

**Harry Stebbings** [60:28]:

18,000,000,000. It depends on what options I have. So you know? That's amazing. You laughed at just gonna say it all. That's very funny. Who's been the single most instrumental person or lovable not in the company?

**Anton Osika** [60:43]:

Oh, it's it's Zhenya at Accel. Zhenya, he ran sales and, like, CEO at Miro, and he was Dropbox at that segment, and I get a lot of input and help from him. What's been the biggest? He's just my coach, and I I talk about how I think about things, and then he asks me questions and and tells me that you have to step up in this, like, a bit of structure in this area.

**Harry Stebbings** [61:04]:

I love him. I had him on 20 sales and he was fantastic. What have you changed your mind on most, penultimate one?

**Anton Osika** [61:10]:

In the context of Lovable, I thought we should be building an agent before the models were ready for it, and because the models were starting to get optimized for an agentic system. What I realized is that no, no, no, you need to have a product that as many people as possible are using today so that you can optimize not necessarily the AI, but this is optimize the entire user experience for those users and get that's that's your data flywheel that you want use. Do you worry about job displacement at scale in a ten year time period? I worry about us humans globally not even understanding what we want to achieve on this planet. And if there's a lot of rapid change with like white collar workers being out of a job and humans, we get super worried and concerned and scared. All hell is going to break loose. So that's what I'm worried about. But if we're a bit more thoughtful in terms of like, okay, if there will be insane amount of job displacement, this is kind of what we think we should do. And This is what we wanna achieve. This is how we make sure people can make some made up job in the interim. Then we will 100% solve that.

**Harry Stebbings** [62:12]:

Eight out of the top 10 paying jobs today did not exist fifteen years ago. I always think that's an interesting stat. And we always overestimate job displacement with new technologies.

**Anton Osika** [62:22]:

Yeah. I think we're going to have maybe a shift away from some very glamorous jobs, which people will be get depressed by. Like, similarly to how being like an artist was like so fucking cool, but clearly you can't make anybody as an artist. And then we're gonna see that again

**Harry Stebbings** [62:37]:

now for a lot of knowledge work and like that's gonna be fine. My kids, brain surgeons. Brain surgeons. No AI is gonna come from brain surgeons for years. Maybe. Have you seen the robots though? The surgeon robots, they're pretty good. I'm gonna be honest. You're not having people be like, I'm gonna choose the robot version of that. Yeah. Is there anything else that concerns you with AI when you look forward?

**Anton Osika** [62:57]:

Humans, we're very good at competing. And in some cases, in many cases, that's amazing. Like, that's how we get top of best companies. Also, we get great technology. But in some cases, we're competing and then we go to war with each other. Like, we start preparing for wars. And I think if we can be better at thinking big picture across across superpowers, that would prevent the scenario where you have like AI that can kill all people in the others like in the other nation in an instant. And like that being triggered without us actually wanting that to happen. Yeah. I'm concerned that us being so competitive in a world where things happen much faster is going to lead to some unexpected results that no one really wants. Which competitor do you most respect? I think OpenAI is pretty good at building products. I think there's other foundation model labs that will do be even better at building products, and those are the ones we should think about for the future. But mainly focus on just what do our users want, how do we make them better products. But you must look across your Figma's, your Bolt's, your Replit's, your

**Harry Stebbings** [64:01]:

who do you

**Anton Osika** [64:01]:

respect? I respect Figma. Figma? Yeah. Why? They yeah. Because they're good at listening to their users and building a good product. And if they can translate that to the full product life cycle, they're a very formidable competitor.

**Harry Stebbings** [64:14]:

Everything goes to plan. We hit all of our numbers and everything works. If that is the case, where then is Lovable in twenty thirty, five years time? We're the the mostly used interface for humans to AI, and that's a very huge market. Dude, it's so much better doing it in person. I've so enjoyed this. Thank you so much for agreeing to do it in person, and I've loved it, man. It was fun. You're a hero, dude. Yes. I'm incredibly grateful to be a lovable investor, but I'm also really grateful to have found a fantastic new friend in Anton. Beyond the conversation today, he's been a phenomenal buddy to me. I'm so thrilled to be able to share this journey with him. What a fantastic entrepreneur and incredible to see the lovable effect and how it has inspired a generation of young founders across Europe. If you wanna watch the show, you can find me on YouTube by searching for 20VC. That's two zero VC on YouTube. But before we leave you today,

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