Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder)

27:27It starts super good in the beginning and that it gets stuck. What we did was to painstakeingly identify places where it goes stuck. And there is a different approaches but address, like different ways, how we do it, but address the places where it gets stuck. Tune the entire system quantitatively and having a very fast feedback loop to improve it in the area where it got stuck. The most important areas. It still does get stuck sometimes, but that's the scaling law and we're still early in that scaling law, I would say. And so when you talk about things getting stuck, it's like the AI agent just saying, like, I don't know what to do from this point or like they introduce some kind of bug.

28:11Is that an example getting stuck? It introduces some kind of bug and then it's not smart enough to figure out how to get out of that bug. I see. And this is a common problem people have with tools like this is they like get to a certain point and then it's like, well, I don't know what to do. I'm not an engineer. Like, here's a bug. It's running into where the infrastructure is built the wrong way. And so it sounds like one of the paths to solving that is what you're describing as you make the AI smarter to get to avoid more and more of these places they get stuck. Another is people just learning how to get AI unstuck.

28:50This is something when we had Omjad on the podcast from Repolate, he said that this is like the main skill that he thinks people need to learn is how to unstuck AI when it runs into a problem. Just thoughts there. I don't know anything along those lines come up as they say that. I mean, this is something that is a problem today. And the frontier of where this is a problem is very rapidly like receiving back. So what we did was to identify the most important areas. Like, oh, so specifically adding login, creating data persistence, adding payment with Stripe. Those are the things that we make sure it doesn't get stuck on, for example.

29:33And the places where it gets stuck today is currently something that you can use being very good at understanding and getting unstuck. But in the future, it won't be so important. This is just going to not get stuck. And I know you're not talking super in depth about this because this is one of your unfair advantages. This kind of stuff you figured out. So I'm not going to push too far. I don't know, I know you want not everyone to do exactly the same stuff. So I want to zoom back to the pace of growth that you guys have seen. One of the big stories, everyone's always looking at you guys of like 15 people, 10 million ARR in two months.

30:10It's absurd. It's something. I don't know if it's ever been done in history. If so, it's maybe a couple other AI startups recently. How have you been able to do this? What have you done that has allowed you to grow this fast with so few people? I'd like to take credit of having done everything end to end in the product. But what we were building on top of the oil here, which we have discovered oil, which is are the foundation models. And then what you've done is that we've obsessed about what's the right way to present this to a user, what's the interface for the human to get as much out of this as possible, packaging together.

30:52I showed you in the demo that how you can add authentication and making this work seamlessly together as a whole. That's what we've done. And then people love the product. That's what that's the driver of the growth. For getting awareness, we mainly been posting what we've shipped on social media. That's how people know about us. So building in public is how people usually describe that. So it's like, I think it's like, you guys have the advantage of the demos are just like, holy shit, you can do that. And then you guys share the numbers that you guys are growing at. So it's innately interesting and shareable.

31:31But I imagine most people have something interesting to share. I guess is there anything that you think you did that other companies maybe haven't done that make the product so lovable? I mean, the team is everything in building a great product. So I just give a big shout out to the notice within the code. I had recently, I would say, and you want people who have a cheap really fast and have good taste for what is simple, what's the right abstractions. And I think that's what we've done differently. Have this obsession for me just making it better and better and better. This episode is brought to you by the Fund Rise flagship fund.

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32:57See, boring. That's the point. You can start investing in minutes and with as little as $10 by visiting fundrise .com slash Lenny. Carefully consider the investment objectives, risks, charges and expenses of the Fund Rise flagship fund before investing. Find this information and more in the Funds perspective at fundrise .com slash flagship. This is a paid ad. Okay, I want to come back to the team because I know you have a lot of thoughts there. In terms of writing code, how much do you guys actually use AI to write the code that is building loveable? How do you how does that work on your team?

33:32We have set up loveable so that we can change loveable with itself. We have done that. There is a lot of hyper -specific things in terms of running a separate like we spin up a dedicated computer for each user. It doesn't do everything. Loveable doesn't do everything. So we use the tools that are for developers, not for the 99 % most of the time. Everyone uses AI all the time in writing code. It's also in great course for experimentation. And the tools like cursor and stuff like that, like anything you can do. I think cursor is the one that almost everyone uses in the team. Okay, cool. We did a survey recently on tools that my listeners and readers use in cursor.

34:2517 % of all people that read my newsletter use cursor already, which is absurd. And you guys are in there too. Okay, so along these lines, there's obviously other competitors and companies in the space. So everyone's always wondering, you bold, replicate, cursors, a different kind of thing. What's the simplest way to understand maybe how loveable might be different from say, bolt and replicate, which I think are probably the closest? The packaging for non -technical people is what we aim for. And I showed you in the demo that you can edit the text, you can erase the changes in colors and so on instantly without having to go into like a code editor and without having to wait about 30 seconds for the AI to do the full change.

35:11So that's the big way that we think about packaging it. And then for making sure that this can be used as productively as possible in a larger team, something that's different from, I think the other, all the other tools is that it's, it is synchronized with the GitHub. And that means that you can use cursor if you're, or the people in your team that want to be more low level, they can use cursor. And while the people who don't want to mess and set up their local file system and commit to GitHub and so on, they can use loveables. Not getting stuck is, I think the most important thing for people, and that's why we came, we came into the space late, we haven't done the same type of marketing, there's as many others and we're still from the people that I talk to rank as the one that works most reliably.

36:05I love it. Okay, so, so let's point about how you can just use loveable to build a lot of it for you and then get into cursor to edit and tweak. Is a really big point and you're saying other companies aren't as good at that. I don't know if any other dust that, I don't even let you do that. Amazing. Okay. And then I had, what's kind of like the vision for a loveable, like, what's the end state of this? Is this everybody can build anything they want sort of thing? What's the simplest way to understand where you're going in the next, I don't know, five, 10 years? I mean, I have to say, so we're building the last piece of software and it is inherently very hard to predict how the world looks like in five years this day.

36:45It's very hard. But the last piece of software, how I see that is that it's almost instant to go from what you want to change in the product or what you want to build to having it fully working and to integrate it with any of your existing systems or integrate it with kind of a very powerful third -party providers. Already today, you can just ask, add and chat with OpenAI and then you get a chat with OpenAI in your product. But that's like, just working perfectly is something that's coming in the coming two years, I would say. And then after that, there is a lot of things in building a product that is not just engineering sidewriters.

37:34And I think an AI can be very useful in understanding your users. So if you use the analytics tools, you know that there is something quite common which is to see how users are interacting with the product. AI can do that on an absolutely massive scale and propose changes to a human to say, that sounds like a good change to make it a bit more intuitive. And it can also automatically run spin -out A -B tests so that you can see the data or these improvements to the product. So I think that's on the horizon as well. Quite interesting about this in one way is people wonder just what jobs will be more important, what skills will be less important.

38:21Let me share a thought I have and then I want to get your take and see where you go. This, it feels like what is getting more valuable is being good at figuring out what to build and then knowing if the thing you had built is correct and good and ready. So it's like discovery, ideation, idea, part of the step of launching a product. And then it's like cased and and craft. Just like, is this the thing? Is this going to solve people's problems? Because the building now is being done more and more. And it's interesting used to be the reverse engineering was the hardest most valuable skill. And now it's like, figuring out what to build.

38:59You could sit there and you could just tell it what to build. And a lot of people get to your screen, I'm sure. And they're like, I don't know what to build. I don't know what people want. And it's like, that's the thing now. So I just, I've reactions to that and thoughts on what skills will matter more and less. I mean, if you want to, if you're a founder or you want to build something, yeah, I, I totally agree that figuring out what are pin, pin points and seeing like, there are often currently solutions to every, some kind of solution to everything. What is the, in how can you make this? Genics better.

39:31So somehow like figuring that out is super important. What you have an existing product, then I think taste and like, if I had to taste in what is, what is good is even more of the important part, take like the engineer's skill set is still going to be important because that helps you understand what are the constraints. So what you can build. And I just think a lot of software engineers are probably a bit scared now. Like, okay, I'm out of a job. What's going to happen? But they should see themselves as the people who translate the problems that are stated by a human probably to a technical solutions.

40:13And, but they do have to abstract themselves up a few steps, not just by looking at the in their text stack like, oh, I can just do the front and genius. They engineers or technical people are very good at understanding what are the constraints technically and they should see themselves as that translators. Is there like a, like, is it almost like you want to be learn the end manager skill of overseeing engineers versus like the actual engineering skill or do you think it's still going to be really important to learn how to code and be really good at that? I mean, doing a bit of everything being in general is, I think, much more important than it used to be.

40:50And if I'm putting together a product team today, I will re -obsess about getting as much of as as many skill sets as possible for each person I hire. They should know how architecting a system works perfectly. They should know the sign. They should know they should have product taste. They should know how to talk to users. I think everyone should be able to know a bit of what of that preferably. Easier said than done. It's hard to find people that know all these things. So let's segue to hiring and how you hire. How many people do you have at this point? Is that, some you sure? Yeah, no, we're at 18.

41:2918. Wow. I love that you, it sounded like you're about to say, oh, we have a hundred people now. No, 18. Okay. So you went from 15 to 18. Okay, great. So, what do you look for when you're hiring people? The way I saw you describe it on Twitter is you look for cracked engineers, the best cracked team in Europe, things like that. I guess just specifically, what are you looking for when you're hiring? I think the most important thing is that people care a lot and they're not just like, oh, I'm here for a job. I'm here for being a just a passenger on this journey. But everyone should really care about the product, the users and care a ton about the team, how the team works together and that you're always contributing to making the team work more productively together.

42:17And that's like care or preferably obsession gets you a very long way. And then you do often want to have like absolute super power in some dimension to be able to understand and do as many things as possible. Like have these generalist brain that quickly learns any skill, but we're super, super good in one dimension. And that's for us, that's mostly cramming as much out of AI, out of the large language models, some understanding the entire perimeter space of what you can change to make this their product perform better. So how do you actually test for these things? You know, like some of these things describe everything everyone's looking for, like they care about the user, they want to collaborate well.

43:06Just like when you're, because like you have 18 people building in the company that's growing more than a millionaire every week, like that's an absurd scale. And the people you've found are clearly world class. And I think a lot of people are going to like want to hire the type of people you're hiring. So when you're actually interviewing, how do you suss out some of these things like their AI cramming skills, their team building collaboration, what do you actually do? I always ask people what they've done before. And these people that I'm describing, they have often done something where they care a lot about what they've done before.

43:43And digging into details about the technical things that they did. And then I mean, we do the normal thing of giving it, showing a very hard problem that is a bit unorthodox that someone hasn't seen before, preferably, and see how they think through the thinking region through that. Then something that I think is more uncommon is that we do, I pretty much always have people join, the work simulation for at least a day or for no full week. Awesome. Okay. So work trial, that's awesome. So basically they work with the team for at least a day. You said, I like, sometimes a week. Yep. And I love this point.

44:23You made about, they show, they cared deeply about something they previously worked on. And you look for just like obsession with the thing that they built last or something they worked on. Like what percentage are engineers of these 18? So 12 at least right, coding at least part times. 12 at 18. Okay. Cool. When we were setting up, you're like, oh, our engineers creating content now. I think that's a cool example of how people do a lot of different things. Yep. Also, okay. So I have your job posting that you shared once of like one of the actual job description. I'm going to read a few lines from it.

45:04It's very inspired by Shackleton, right? Would you agree? Cool. I love it. By the way, did you write this or did you have AI write this job description where you like create an engineering job description? In fact, let me read it to you. I don't even know. You may not know what I'm referring to. I'll read a few lines here. Long hours, high pace candidates must thrive under a high urgency under AGI timelines approaching. Difficult mission ahead, honor and recognition in case of success, those seeking comfortable work need not apply. And then there's a few other things, collaboration, other exceptional minds, purpose larger than any normal engineer role, generous share and venture success.

45:42Amazing. I think thoughts. Yeah. So I did, I didn't get some up with the formatting of this, but then I was mostly me doing the exact tracing of the different front lists. So yes. And I love that. You know, some people is giving like holy shit. I'm not signing after this, but a lot of people, the people you want is like, yes, this is exactly what I wanted to be doing. Great. Amazing. Okay. Cool. So so it feels like one of the elements of hiring here is create a really good filter to be clear about just how intense this is so that the people that want that are the ones drawn to you. Okay. And then you're also you're in Sweden.

46:26Fastest growing startup in Europe ever. Thoughts on building in Europe, slash Sweden versus the US slash San Francisco. Yeah. So this ambition level that you're talking about in the job, it's more uncommon in Sweden. And I think that is the like the biggest unlock that someone like me, you work with. She's that this is the like the time in human history when you have the most impact for our work, our and that's why we have to be super ambitious, like just up to ambition level. And then we can maybe retire and have AI take care of most things in society. And and and bring inspiring people to be this ambitious in the place where the average ambition is lower.

47:16But the talent, the the role talent is much more available is is a great recipe. I think that's a great recipe. So then and that's what's I think it's some kind of advantage there. And it's it's a bit of a double edged sword, but but it's some kind of advantage. So I'm hearing is like there's there's incredible people in Europe. They're just not they're harder to find in what I'm hearing is like the key is how do you sus them out and get them to want to talk to you. Yeah, most people in Europe, they haven't thought that oh, do going on an extremely ambitious mission is what I want to do. So that's figuring out who those are is a big part of it.

48:01Awesome. Okay. I want to talk about peritization. I imagine all these things that I just shared about just like how ambitious this mission is how much you're doing the last piece of software. You must have a bazillion things that people ask you to build that you want to build. What's your approach to deciding what to purchase and actually build? I just top line, I think identifying what is the biggest bottleneck was the biggest product problem and iterating or fast. I'm saying, okay, this is the biggest problem. Let's really resolve that problem. And then picking the next one and not overthinking, not like dreaming out the long -world map.

48:40That's my side of the fault. There's a very, very simple algorithm. Understanding what is the biggest problem is not always a simple problem. I think yeah, so we spend time, once you're talking to users, reading up for what people are writing, we have a feature board for people to do a lot of requests as you say. And then when we pick one of the problems, we're quite engineering -led. For a product like ours, it's hard to have product managers that are not engineering -nears say, oh, this is what we should do now because the right solution to the problem might be entangled in things that are technical details.

49:32They might be entangled in technical details. So like, okay, yes, this is the biggest problem, but we should have this larger technical initiative that's going to solve all of these problems. So it's quite engineering -led compared to many other product companies. As a true, I'd be worried if you guys had a product manager at this point and make so that would not make no sense right now. I imagine the answer is it's chaos and there's no actual defined process. But just like, what does it look like generally? What's kind of the cadence you guys operate on? How do you take an idea to build it, speck it, launch it, just like, what does that look like if you have something?

50:10If you look back, like three months, we mainly said, okay, let's do this weekly planning. We have a big jam board where we have all the main problems, and then we have a rank them, which I'll do, we focus the one we're focused on next, or this week. And then we have a demo of where we say, okay, are the things we ship this week, so to get everyone on the same page. We do have a bit more of a roadmap now, and where we say, here we're going to make so sure you can support custom domains, next, we're going to add collaboration after that. And the biggest problem now, or the biggest initiative now that solves the biggest problem is making the system more agentic.

51:00And that has a bit of a longer roadmap, but we still do the cadence of weekly planning. These are the things we're focusing on this week. It's mostly, there's a good word for this that you, I would want you help with, but Polish, fixing the bags and Polish this week, and that was the planning on Monday. That was actually this week was Polish, Polish week. I love that. How far is this roadmap that you're now having? I mean, it's clear over the coming month, and by the stretches out three months, and then, but within one month, it's probably going to look a bit different. Okay, and then what are the tools used just for folks that want to understand, like, the latest tools?

51:43So you said, FIG Jam, what else is in that stack of tools? I mean, we do so many things in our company in linear, because it's just an amazing product. So we do talent application tracking in linear. Oh, I have to go through and this thing a little bit made custom made tools for that, linear and then FIG Jam. So simple. How soon until one of your engineers is an agent engineer? Any engineer, do you think? Do you have a sense? I love to dig into what does that question actually mean. I think we've been talking about like, oh, AI, that would require more something playing chess. That's AI. Like, if you get even AI, if a computer can play chess, that's AI, and now that's like, oh, no, that's a chess program.

52:34And we always shifting this forward and forward. I think anything that a human doesn't do is just a smart computer system. Right? So what is, when is a software engineer and agent, I think it's always going to be just, we're building in, loveable is just an interface that humans interact with to create the software that they want. And then how we solve that, if we set going to be an agent under some definition, yeah, sure, I think so. But that's less important to me. Okay. I like that. Let me ask this. You guys are moving super fast, scaling like crazy. You just grabbed a little bit about your process, weekly planning, FIG Jam board of ideas, and now there's a roadmap that you're kind of thinking out in the future.

53:29Is there anything else that you found or helps you move this fast that gives you a lot of leverage over the small team you have to ship quickly and move fast? That you haven't already mentioned. We worked from the office most of the time. I think it's pretty nice. Then you can say, like, hey, I think we're thinking wrong about this thing or like, shouldn't we actually do this other thing? And especially, I think lunch, eating lunch together is a pretty productive hour where you cross pollinating. I mean, people are constantly thinking subconsciously as well about how to solve this different problems and which the most important ones are.

54:07And then being in office has this like focus or most of the time you should be focused, but you also have this like high bandwidth where everyone has a bit unstructured communication. I love that. The answer to the CEO of a company that's one of the most advanced AI tools in the world is one of your answers to how to move fast is like lunch together. I love that. That's so human. And so it makes all the sense in the world, but I love that that's still a part of this. Yeah. Okay. You talked about this kind of on the same thread. You talked about if you were to start a team, like a new product team today, say you were head of product somewhere or head of RPM VP of product somewhere, building a new product team, scaling a product team.

54:51And what would you do going forward that's different from what people have done in the past in terms of who you're hiring, how you're structuring them, that kind of thing. Just like what do you think people should be thinking as they build product teams going forward, knowing tools like lovable exist and all the other stuff that's going on? I mean, everyone should be excited about using AI. I think that's a pretty big one. And then the team working well together is the body like the launch you have to like to sit down and solve problems together. You should at the bottleneck for most products this day, it's not going to be as much on the engineering, but having good taste, good intuition about your users and that's, I mean, engineers and everyone preferably in the team should have that willingness at least to want to go through that motion and listen to the users and truly understand what they care about.

56:00What's kind of like the background of most of the engineers and people you've heard, are they like, is there anything like in common, are they just like super impressive humans generally, like champions of programming contest stuff like that? And I know like what are some attributes of the folks you've hired so far? I think rural cognitive capabilities that's strongest, like diamond, the strongest correlate of being at lovable, but there is this start -up mindset that I think is also we're very strong. Being a bit more, being much more interested in moving very fast and iterating fast than having a lot of structure, a lot of process and thinking about the business as a whole, more than thinking about my specific profession, my specific craft that I'm seeing myself like wanting to dig in into on me.

56:58Amazing. Okay, so smart, like very smart, entrepreneurial, acts like an owner, doesn't just, isn't just like, this isn't just a job, but they feel like they actually have agency. Okay, this is great. There's something you said, kind of along these lines, that I think is important, that one of the things that gets you excited about what you're building is giving people superpowers and especially people that don't add a code, basically 99 % of people, is there anything along those lines that you think is important to share? It's very clear to most people who have been engineers or been founders, that there's so many that have failed in their endeavors because they didn't have someone that know how to solve the technical parts.

57:42Now that we're close to having people know that it's not successful, they solve everything, it's going to be a game -renate explosion of entrepreneurship and better software product. We're not going to settle for all the annoying bad technology that we used today.

58:09Everyone who has an idea is going to say, okay, I'm going to build this thing and show you that this is the best version of the product or what our company should be doing, instead of having low meetings or writing up documents. It's going to be empowering across a lot of different professions and places in the world. What's next for Lovable? What's kind of like the next few things they might launch as this episode comes out? As I mentioned, this agentic behavior. When I say agentic, what it means is that you give more freedom to the system, to decide what happens next. It might want to write a test, run those tests, and see, faster.

59:01Then there are some more obvious things that you want to do to go all the way to easily go all the way to making money with Lovable. How do you set up so that it's hosted on your specific domain? How do you collaborate seamlessly with your team? Making that that is here so that it's all just obvious things. Something we're thinking about is to help just founders succeed after they build their first version. How do they get more users? How do they get feedback? How do they get the word out if they build something useful? I was just going to say that. That's exactly where my mind went. Everyone's going to be building all these things.

59:47No one's ever going to get any traction with these tools because no one knows how to find users, get anyone to basically go to market and growth is a whole different skill. That is so cool that you're thinking about that. How do we run some paid ads for you? How do we think about SEO? How do we think about word amount, the reality referrals? That is very cool. We already have some great books that we have today, people building with how do you do those things that you can find up on a blog? Interestingly, this makes me want to buy some meta -stock because all these apps that everyone's building, they're going to be running paid ads on Facebook and Google.

1:00:23Oh my god. What a good business those other guys get. I want to come back to you said that you can work on your existing code base. This is actually a big question for a lot of people. They see all these tools. They're all amazing for prototypes and concepting. You talked about how you can actually do this within your existing code base. Use -lovable. Let me correct you there. You cannot use it on any existing code base. We have to have a research of importing your code base. What you can do is if you start in -lovable, then you can have engineers editing how in whatever tool they want to use for other things.

1:01:00That's great clarification. Just for people. Most listeners here are not building something brand new. They're working within an existing product. You're saying that that is coming. You can use -lovable in the future in some form with your existing app and product. Great. Wow. That's huge. That's basically the most people. That's going to be a big deal. Final question. We have the segment on this podcast called Failure Corner. Most people come and spot cast the Shelley stories of success and everything's going great. Here's all the things. You guys, this is a good example. Just up and to the right, the fastest curing product ever.

1:01:42What's an example when something totally failed in the course of your career? What did you learn from that? I'm a bit hard -pressed to find something that totally failed. But I think there's a bit of a product lesson where I was the first employee at an AI store appeared in Stockholm called Thonalabs. The premise was just, humans learning different ways. If you personalize, you get two standard deviations, more effective learning. There are a lot of products and education software that helps you learn. That is not personalized. We were building an API to personalize learning. The AI in the song was pretty good.

1:02:34But the thing that we were doing in the end was to say, okay, here's this product. Someone has to build a product or some way to learn where it would be English and things do a lingo. Then the people that have that product have to use this advanced AI APIs to start making it personalized. It's a very hard retrofitting. You have to switch out the engine and put in this AI.

1:03:08The big learning here, it didn't work very well for the company. The company wasn't super successful in this. The big learning is that you have to start with how is this product working end to end? Then, the AI. Where should we add the AI? That was a big learning for me.

1:03:33What is the big picture of the user? What's the big picture of how do you think the user experience should be? Then add something with AI to solve specific problems. Now some of the labs are doing great, but it's not on top of that product specifically. I think a lot of people hear this. I think it's hard to actually remember this point when you have some cool tech. Everyone needs to try this. They're going to love it. Then you don't realize no one actually cares if it's not solving a problem for them. There's a lot of novelty products that everyone wants to use for a little bit. Then I forget it.

1:04:09I don't actually need this often. What this makes me think about is there's all these product lessons for what is likely to help your product be successful. A tool like Lovable can help you do this. If someone is building something, you can guide them. What's the problem you're solving for somebody? How many people have this problem? Much does this matter to them. Maybe we should add the Lenny modes. She activates in Lovable. She activates this product coach. That would be a question. Hold on. Why are you doing this? Let's take a step back. Everyone's going to be like, what kind of positive? It's hit out of my way.

1:04:58What's your experience? What's your experience? I think there's actually a big opportunity there to say people. There's a play around with this thing. Then there's like, okay, but really is anything people actually want. We call it Lenny mode. Is that a fine with you? 100%. Let's do it. I'll license you no cost. We can't. We made a deal here. Anton, is there anything else that you want to share anything you want to leave listeners with before I let you go and go to sleep? I think again, the world is changing quickly. It's very fun. You should see that it's like, I have fun in all of this change.

1:05:38The best thing you can do for your current profession or if you want to have a new job is to be in the top 1 % in knowing how to use the AI tools. Go out there, use Lovable, use other AI tools and make sure to understand or try to understand as much as possible in how to use them productively. That's something I tell all my friends. In generally, I love the audience to know as well. I've got to make this even more specific for people. How do you know if you're in the top 1 %? What's a heuristic almost? Slash, how do you get there? Is it just use it 100 times a day? What else can you recommend?

1:06:19Yeah, I think if you spend a full week trying to reach an outcome, the best way to learn is I want to do this thing. And then I want to use AI to do that thing. And you spend a full week, you're in the top 1 % in the Lovable population. If you have friends that use around yourself with friends who have this obsession or they also care a lot about this, then you'd be quickly in the top 0 .2%. So what I'm hearing is find a problem that can be solved. Find a problem, a pain point for yourself or someone. And then end to end, fully solve that problem, spend a week getting from idea to a thing that somebody's actually using.

1:07:02And you're in the top 1%. Yeah, I think you said at the top 1 % was just spending a full week and asking AI if you don't understand, so making sure that you can understand. Yeah, that's the thing people forget. You just ask, would you ask the chat feature of Lovable in this case, or would you go to cloud or chat GPT to ask for advice? Yeah, I mean, my recommendation here, if you're a product is to use Lovable to build software and learn that AI tool, if you're, and then you should use chat mode. And chat mode, you have to add, is something you activate in your user profile. It's not launched in the main problem products.

1:07:44So it's in labs. But if you add that flag, then you can use chat mode. If you're, if you want to learn some other AI tool, then you should, I mean, ask that tool or ask, cloud or chat GPT about how that topic, that domain works. Okay, amazing. Where can people find you? Where can they find Lovable and how can listeners be useful to you? Lovable posts, updates and memes on Lovable underscore dev on Twitter. We post things on LinkedIn as well. A lot of things coming out and changing in how we will software. So you can follow Lovable underscore dev and you can follow me at Anton Ossica at Twitter.

1:08:29I'd love more feedback on what people, like where people see this is huge change for them. And we, there are a lot of people posting about that on Twitter. But there's that we have a discordery can share like, this is how I use Lovable and what's the purpose for me. And feedback dot lovable dot dev. You can give, you can ask for new features. You know, there's a lot of people asking about what features you want. So that's the most important thing for us. We just want to solve people's problems. Amazing. Anton, you're doing incredible work. What a journey. I'm excited to have you back some day when we see more chapters of this journey.

1:09:11I love Mojolette. As do we all, that's how people listen to this podcast. Anton, thank you so much for being here. Thank you so much, Lenny. Bye everyone.

1:09:23Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show. At Lenny's podcast .com. See you in the next episode.