Anton (00:00):
When I thought about what's the best thing to build in this AI race, it was something that can take all the fantastic ideas that I want to create and a lot of founders out there want to create and just supercharge that.
VO (00:14):
Welcome to Spotlight on a podcast about how companies are built from the people doing the building one messy, exhilarating decision at a time.
Ben (00:23):
Welcome to Spotlight On, I'm Ben Fletcher, accompanied by Genia ov, and we are really excited to be with Anton Osika from Lovable and we are excited to have him to chat through the journey of lovable and how we are today.
Anton (00:36):
Thank you. Great to be here.
Ben (00:37):
Well, today's really exciting. We are announcing your series A, the largest ever series A in Stockholm. We're in your beautiful new offices in Stockholm. Why don't we start and rewind a little bit and tell us a little bit what is lovable and how would you describe it to somebody that's not familiar?
Anton (00:53):
Yeah, lovable is an AI software engineer and you ask it to build something like you would with a human software engineer and it'll sometimes ask you questions, but it will usually just build the frontend, the UI and it will add the backend capabilities so that you have a fully working application or just a website. It will guide you through adding payments or adding AI capabilities in the application you're building. So it is something an AI software engineer that's used by everyone
Ben (01:25):
Really. Awesome. Maybe we rewind and learn a little bit more about Anton and when things were getting started. You are very technical founder in the sense that you have been a founding engineer in the past. You've been a CTO and co-founder in the past and you started by doing research. Maybe start from the beginning and tell us about your journey, your journey with AI and then how that culminated in building lovable.
Anton (01:48):
I mean, I was always this kid that loved to pick apart technology at home and then at some point I understood that you can build things with computers. So I started coding computer games when I was very young and then I went into university and I was curious about how the world works. So I decided I want to do physics. That's the ultimate, get the questions answered to how the universe works, and that was mostly super fun. I had this huge interest about what is intelligence and the human brain and took a lot of the machine learning courses as well. It came to me that if you want to have impact in the world, which I care a lot about and changing, putting a mark, then you have to be building something and the best place to do that is to build a startup. So I went out into the industry after that and I've been building AI products basically throughout my career. And now I think the even more exciting thing is to build the teams that work really, really well together to make those products and the entire company that brings it out to the world, the do that the best possible way.
Ben (03:02):
You've always been at the center of ai, whether in academia or with your startups or when you were building. Why did you decide to build lovable to unlock for not just technical users but for everyone?
Anton (03:14):
So I actually started playing around with what are the new capabilities a bit more than two years ago when they started to be able to reason basically, and I had built these tools, open source that thousands of people were using, but they were all engineers. And after thinking about like, okay, a lot of people are making engineers more productive with ai, it's super cool. I love it. As an engineer,
(03:42):
I did realize that the long-term outcome here is that anyone will be able to build software thanks to ai and going from zero to one for so many more people, it's going to have much more impact. And I think often many of the unique ideas, some of the best ideas, they don't come from engineers. So if you can really short circuit their ability to take their creativity and put it out in the world, it's going to just be so much more impactful. And that was the idea of let's create a completely new type of interface where you can do everything that a human software engineer can do, but it's used by your mom and anyone on the street.
Zhenya (04:26):
Your team started with just you and Fabian. How did you two meet and how did you decide to start the company with him?
Anton (04:31):
Yeah, so Fabian is my co-founder. He's been CTO and been building companies since he was a teenager and sold companies in the past. And he was actually a team lead at the company I built before. And then when I thought, okay, there's something humongous that you can do with how fast core AI capabilities are advancing, I thought about what type of personalities do I want in the founding team? And from working with Fabian, I know he's this extremely pragmatic, high urgency focused on just building and doing that as fast as possible. He had actually left the company where we worked together, so I ended up at summer on my bicycle outside of where he lived and I called him up and said, Fabian, let's go want to walk. And then I explained what was the big idea of figuring out the interface of the future to build software products and we decided to go ahead and build lovable.
Ben (05:34):
You've always had a big vision of empowering everyone, technical and non-technical users. How did you land on that and is there one thing that always drove you to make sure that it was inclusive and building for everyone?
Anton (05:48):
I think we're working on the most exciting product that someone like me can work on. It's like taking all the hard learned lessons of building products and then putting that into an intelligent system that can do that for anyone out there who has a great idea, who wants to build a company or just wants to accelerate what they're doing day to day. If you've been talking to people in the startup space, you've noticed that everyone who wants to build a company, they're desperate for people who can actually build the product. So my mom even comes to me and she asks me, Anton, I need to get this software here. I want to be able to help my where she, her workplace use AI more. And she's just bottlenecked by this very, very specialized skillset of software engineering. And when I thought about what's the best thing to build in this AI race, this transition that humanity is going to go through, it was something that can take all the fantastic ideas that I want to create.
(06:54):
A lot of founders out there want to create and just supercharge that. And most of the people, 99% of the world population, they don't know how to write code at all. And it's actually even worse than that. Even the people that do know know how to write code, they often have one special set of what they can do, a front end or a backend. With an AI system, you can bring all those skill sets of building the product and even taking the product through the lifecycle of making it useful to users so that anyone can do all of these things.
Zhenya (07:30):
I remember when we met, I think in September and when you had the first version of what became lovable, you talked about having the first early users of the product. Who were those people? How did they find you and what did you learn from those early users?
Anton (07:43):
We had an early access version of the product that we launched on Product Hunt in the beginning. Like, oh, there's a wait list, but if you want to try it, you can talk to us and then we'll see. For us to learn how people use it, we went through a few different core beliefs of what is the ICP, who is it that should start using this? And ultimately it was clear to me that we want to build something that everyone can use that is just the best possible intuitive interface. But the first of those beliefs or hypothesis was it's for rapid prototyping and you want to show what a product could look like, and we got users on that. There wasn't partly because we hadn't built out the product perfectly and the AI wasn't that sufficiently good, it wasn't a super clear, wow, this is really what I want to use. You really have to educate your users to understand. And then another iteration we had was okay, but the system is best for zero to one and one of the places where you go from zero to one is internal tools in businesses.
(08:56):
So we entertained that idea for a while, but I mean ultimately the exciting thing is to build a full product, a full business on top of this. And after we launched and the product just worked really well, we had a lot of things that came together in a way that no one else had something even close, then we didn't have to think about who was using it for what. It was more like, wow, there's this huge capability unlock and users found hundreds of different use cases and that's what we're continue to lean into today and try to help educate for the different use cases at the same time. Yeah.
Zhenya (09:32):
Do you find any particular use cases that either inspire you or are just kind of unexpected for you?
Anton (09:38):
Founders in particular that want to move really fast and people at the larger companies so that want to move faster than being blocked by their existing engineering teams? They use us for hundreds of different of use cases. We have a lot of people in product and that used to do static designs, but also in finance and data and marketing, building small applications and tools that they use or to validate marketing ideas or to just align, Hey, what are we actually building into Spotify is using us and what are they actually building into the core products by socializing different ideas and trying them out with a full ai, they build AI applications on lovable, for example. So that's now a very exciting use case that it's growing very fast.
Ben (10:29):
One of the things that I've noticed as we've been spending time together, you're incredible at focus, blocking out everything around you and making sure you focus on the things that matter, and it really goes all the way into the product that you've built.
Speaker 5 (10:41):
You
Ben (10:42):
All take an incredibly complex product that does a lot on the back end and the front end and distill it down to non-technical users or for everyone to be able to build and create software. What is that within you that allows you to take so much complexity and distill it down so that it's so simple and so elegant in the product as well as how you operate as a
Anton (11:01):
Person? I think I am, I'm super ambitious about all the things I want to do, and the backside of that is that I do want to do too many things at the same time, but if you're smart or if you notice if you work with that over some time, you realize how important focus is. So it's a learned skill to say, no, we have to just pick one thing and do that and remove as many distractions as possible for how we build the product into something simple. And this is just the beginning, right? So we have a long, long way to go. It comes from how the entire team works together. One important piece of that is that every week engineers, they don't just take the plan tasks and do them, but they sit down and through the entire flow of using the product and think about like, Hey, is this actually the best way to do it? And try to polish and simplify and make it as delightful as possible.
Ben (12:03):
We've been really impressed to see that not only the reach and breadth that you get on the consumer side, but now you all have started to go into the enterprise. You talk about Spotify, there are a number of others that have tens, hundreds of licenses and are using lovable within the enterprise. How have you learned and what have you been learning and what's been the experiences you've been moving into the enterprise?
Anton (12:24):
What we've done is we have this product that almost like most people who are very aware of ai, they know about this product, they've tried it. Millions have had some kind of falling in love with this product, so that makes it so that companies come to us with at least one person or usually a team that really wants to use the capabilities that it has unlocked in the company.
Zhenya (12:49):
You talked about the speed of iteration, and I think even in the very fast changing world of AI and AI coding, lovable is moving extremely fast. How do you keep this sort of cadence of product feedback and updating the product extremely tight and fast?
Anton (13:05):
The most important one is that you make sure to have a bit of focus. You take a few opinionated, bold bets on where the product is going for each opinionated bet, you split it up into small chunks of things that you announce and you get feedback on, and then you announce and launch the next thing.
Zhenya (13:24):
I think we've noticed also that a lot of what we see in lovable the product is that it manifests from lovable the company and the culture that you've created, and it's a very special place already. What do you think differentiates, lovable from some of the other companies? What's important to you in building the culture?
Anton (13:40):
The most important thing for building a company that's the generational and category defining is that everyone in the company, they're there because they really care about what we want to build and want to build something big together. So it's caring about everyone in the company cares about who we bring into the team and that they have the shared the same obsession and they care about how we communicate with our customers and our partners. And they care a lot about how the details of the product making the obsessing about it being perfect. I think that's the most important thing. And the second one is part of function of that, how you work together as a team and that you have this team first mentality that even if you know that you have an amazing idea that everyone else should just listen to you, build on top of what everyone is doing so that you can run really fast together in the team. From the beginning, I think we had only some type of founder experience in the team. That's still the majority. And what's people with founder experience often share is this deep care for what you're doing and quite a high agency mentality that if you see something that can be changed, you are not passive, but you take action and translate the opportunities to actually driving through change. So those are some of the things that I value a lot as part of the team today.
Ben (15:16):
And are there things that you look for either when interviewing or when you're building a team to look for those qualities? And one of the things we've noticed is when we spend time together on nights, weekends, holidays, and when we come to the offices, it's full. Everyone's working, everyone's excited, everyone's happy, they want to be here. So how do you test for that and find, because I know a lot of other founders would like to find folks that have the same kind of drive and ambition to their end goal, but you've done a great job of building that and assessing that out early on.
Anton (15:48):
Usually the best predictor is that you've built something yourself because you wanted to build it in the past. And many people who have that mindset, they end up somewhere where they care so much that they are not on the job market at all. So with them, you spend a lot of time to become friends and get them to join. But there are also a lot of people like this who are, they're more junior and they also have, which often means that they have more energy. And we have a mix. We have quite a bunch of very young people, and then we have also a lot of very senior
VO (16:30):
People.
Anton (16:31):
And that mix I think is very good because then if you have a tight feedback loop between people who are young and people are very senior, the young people learn much faster.
Zhenya (16:39):
We noticed you have a strong bias towards hiring either former founders or people who are generalists and have a lot of passion and have very high ceiling. But I think we talked about this a lot, that your view on balancing very untalented generalists and experienced people in particular areas has changed over time from your previous company to early lovable to now.
Anton (17:00):
Can
Zhenya (17:00):
You talk a bit more how it changed and why?
Anton (17:02):
Yes. I've always seen what happens when you have very smart, ambitious people and the benefits of that. In my last company, we, I think hired a bit too senior people like executives too early. And I think in some way they can be more difficult to evaluate because you're so impressed by what they've done and how good they are based on what they've learned. And you're not evaluating some of the core traits of that individual. But now that I think I've just met more people that share those traits that I'm looking for and they have very impressive backgrounds and that I'm more positive towards finding very senior people who just cares as well a lot about the culture and understand the benefits of having a team. That is where young individuals have an ability to have a lot of influence and not just get told what to do and nurturing and are able to nurture that. And so that's made me much more positive than when I started lovable adding select very senior people to also bring up the other people who are more junior, but very, very talented.
Ben (18:35):
Awesome. And then tell us a little bit about building in Stockholm. You are incredibly ambitious from day one. You build a very global business in terms of your user base, how you set up the product and building it here in Stockholm, building out the team, how has it been, how's the journey been? What are the pros, cons, and how have you enjoyed
Anton (18:53):
It? Part of building from Stockholm compared to something like San Francisco is doing it on hard mode, and that's mostly the network is more limited in terms of people who've done it before, especially on tech and culture and how you should hire and manage. I am here because I know you can do something global and that writes history from Stockholm, and that's what we're set out to prove. The other benefits from doing it from here is that there's more just talent is I think equally spread out in the world. Generally, talent is equally spread out. The raw talent, there's more people who are looking for something like lovable, super ambitious and looking for something like lovable in Europe because here there aren't as many other places they would go to. So there is a bit of a larger pool, relatively Speaking of great people,
Zhenya (20:00):
We find that talent is distributed, but we also find that Stockholm actually produced some of the most remarkable European companies such as Spotify or King or Klarna. What do you think makes Stockholm so special that it produces such large companies, and how do you want to contribute to the Stockholm startup ecosystem?
Anton (20:18):
Yeah, I mean one of the reasons we want to build it from here is that I know there's going to be a lovable mafia that comes out of lovable, and there's going to be other people who are inspired by the story and go on and create great companies from here. I've been inspired by when I was in university, like, oh wow, there is these entrepreneurs that have built, solved, super hard, found technical problems, and they've really put the mark, and maybe I should do that as well. And in Stockholm, one of the early ones, we had a lot of companies I think during the initial tech boom, and one of the success stories that were part of that was Skype. And that inspired the generation, I think, and maybe inspired Daniel when he started runs Spotify. I think Kloni is another one. And the company where I worked before Asana, I think has inspired a lot of young founders as well. There's this chain of inspiration that I think is the biggest part of it. And then the population here is quite tech native, and I think it's a bit of an introverted culture. And introverted cultures are more tech native, so that could be something as well.
Zhenya (21:31):
Anton, when you launched the company, you scaled to 1 million of a R extremely fast, and then 2 million, 3 million, four, 10 million in two months, and then continued accelerating the growth. And how has the experience been for you? What did you learn? What challenges did you experience with this?
Anton (21:46):
Yeah, so there's been a bit of pain growing so fast. Of course, there's the technical side of things that you have built your system for a certain amount of scale, and then you have to constantly improve things. On the operational side, all your customers or many of them send you messages and ask for things, and you have to be able to graciously find a way to reply, scale the support function. And for me, I think it's of course very distracting that everyone wants to talk to you and want you to speak somewhere or take interviews and so on. So that's also a distraction. The biggest part that takes time is growing the team and spending time on that and ensuring you keep the culture while you're growing the team fast.
Ben (22:37):
Anton, you've been public about building in the open with metrics and what you all are building and you have a lot of fans and you have a lot of supporters and folks that want you to do well. Does it add more pressure for when you're building the company?
Anton (22:51):
No, I think the biggest pressure is our ambitions are so much larger than where we are now, and we have this fantastic opportunity to achieve those ambitions, and that's where I spend my focus on. And then just making sure that we continue to communicate with all our fans and tell them what's happening.
Ben (23:10):
And you've talked a lot about being able to empower everyone. You had that early on in your career where you wanted to have impact and you wanted to make sure that you could unlock that for folks, bring more creativity. Where does that ambition come from within Anton to really go big and to really go for it? For us, you always say you want to dominate, but where does that come from?
Anton (23:31):
When I was a young teenager, I had this, I was very upset about how the world wasn't. It was so many people in conflict with each other and that there should be easy ways to build a better world together. And one of the drivers for me to think like, okay, I'm going to be a founder and build something really big, is that you can, that's one of the better ways to have positive impact in the world. And you see this, I think from, I mean Bill Gates, he's kind of eradicating diseases and so on. Based on what he built that was like a driver. Okay, building an extremely large successful company and being super, super focused on only doing that, not like a philanthropy at the same time is the best way to have impact and mean. It's part of that. It's also part of me just being very competitive, I guess. But me, both me and Fabian, we have a very large founder's pledge, which is about not just buying it like a yacht and using that if we get rich in the future, but to spend our first process to do good in the world, in a world where the AI transition might create a lot of problems as well, which we need great people to make sure that happens in a good way.
Speaker 5 (24:55):
Love
Anton (24:55):
It.
Zhenya (24:56):
Anton, so you just traced the largest series A in Stockholm. You are probably the fastest growing company in Europe, maybe in the history of software. So what's next? Lovable? What are you looking forward to?
Anton (25:06):
The way we talk about our mission is to empower anyone to build, and through that, unlock the human creativity. And that's something we're already doing, but we want to do it at larger scale. And one of the specific personas are using lovable. It's the AI native entrepreneur that comes from any background in the world. They might sit in India or in Poland, and they have good understanding for how do you build a great product and we'll be able to use lovable to translate that into a successful business that helps people. So that's what we want to achieve, and we're going to do that by making lovable, be able to do more things, do everything that it does fully reliably, even though it's ai. And we're going to make sure that we take the community with us in helping them, educating them, and doing many things to make them as successful as possible with support for how do you even build a successful business, for example.
Ben (26:15):
Perfect. Perfect. Well, that was awesome. Thank you. We appreciate it. Thank you for having the conversation with us and we're really excited to work together.
Anton (26:23):
Likewise. I mean, we've been interacting for the full year, it feels like you guys are awesome. Thank you. Thank you, Anton.
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