The Exchanges

Q What are you not opinionated on that you would like to be in a dream world?

A Like in a dream world, we would 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. So at some point in the future, I'd love to be there. And when what happens if we can be more opinionated is that you get the, um, the right level of detailed adjustments on how the AI works for your product. How the backend flows and workflows, automations work for your product, and now we have, we support a lot of different things, so it's more, um, you need to be really good at prompting right now.

AI assessment note: “in a dream world we would be even more opinionated about how you build an application”

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

A You just did very different. I think, like, I, one of those people, Saki's hiring, they wouldn't perform as well as engineers in my team doing what we're doing. So it's, it's very different type of talent. Um, and like, I, if I knew who was like the perfect engineers to hire, I could maybe step up our, like our compensation bands to get exactly those, but, but I don't know who are the best people. So I, um, 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? Um, and then, and give like the compensation that you give on the top of market compensation rates for that.

AI assessment note: “So it's, it's very different type of talent.”

Q How does it change the structure of Teams? When you look at Teams today, you have obviously software engineers, you have designers, you have developers, you have front-end, you have back-end. How does it change The structure of teams themselves.

A Harry, if you want to create a personal website for you, it's super productive. You can do it. You don't have a team. It's just you. You just create it with AI. Hey, if you want to ship the first version of your SaaS and start making money, it's all you. It's not a team. Like a team just slows you down. Maybe you get some input from a designer. Like how does this, how do you think it should look? And so on. Uh, but once you have existing software, With users, and then you want to iterate and change that software, AI might absolutely bring down, kind of mess up your entire codebase. AI might mess up your codebase. So then you would want to work with a software engineer that knows how to bring, have quality and consistently Keep quality in the product.

AI assessment note: “You don't have a team. It's just you. You just create it with AI.”

Q they did it with, I can't remember what the tool was. I hope it was lovable. Please say it was lovable. Um, and that was actually their first iteration of it, which I thought was an amazing instantiation of this. So I totally get you there. Does that mean then that we lose the design process and the brainstorming process? Do we skip that and go straight to prototyping? Yeah.

A Look, so, uh, to, to date, what you've done is that you've Take in an idea, and then you went through many, many, many steps until it's like a fully fast growing product. And all of the, 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. Um, 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. And, uh, 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, and even we have even external users on it into one few minutes or a few hours of building. Uh, so that's where we've seen like the most, there's 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 organization. It's one, all one tool where anyone with the best ideas spend the most time.

AI assessment note: “take all the first step until like, this is validated... into one few minutes”

Q was like zero to ten million in two years. Was like the gold standard. That's what I was brought up on, which makes me feel really old, which is amazing to see. My question to you is, when you look at revenue breakdown, of the hundred million, just kind of guesstimate, what is split between hobbyists, pro devs, Kind of normal people. How does it fit between the different segments?

A You're right. So, uh, 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, that use it as like, okay, now I can prove, show what I actually think we should build in the business. And they, they build a working, uh, product that then they can like decide, are we going to put this, this into our, uh, give it to our, our engineering team and they actually implement it. Um, and then it's everyone else who build, like, their personal website, their small business websites, like, in a few minutes, and 80% of people are, are in the first category. They're building real complex applications.

AI assessment note: “80% of people are in the first category. They're building real complex applications.”

Q Do you worry about job displacement at scale in a 10 year time period?

A So I worry about us humans globally, not even understanding what we want to achieve on this planet. And if, um, there's a lot of rapid change with, like, white collar workers being out of a job, and, like, humans, we get super worried and concerned and scared, we're gonna, all hell is going to break loose. So that, that's what I'm worried about. But if we're a bit more thoughtful in terms of like, okay, if there would be insane amount of job displacement, this is kind of what we think we should do. This is what we want to achieve. Um, this is how we make sure people, like, have, can make some made up job in the interim. Um, then, then we would a hundred percent solve that.

AI assessment note: “if there's a lot of rapid change with, like, white collar workers being out of a job”

Q 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 10 years?

A So you mean 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 a bank is a software company, right? It's all about software systems and the old banks are moving much slower. I think, yes, there is going to be some companies that are like built ground up for an AI to change their, their systems. Uh, 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. Um, so yes, I, I imagine there are also some, um, benefits of being, having been around for a long time in the enterprise, in, in like banking, there's a certain element of trust and so on. Um, so I don't know how large the shift is going to be in, in the, in like across different segments of the enterprise market. But, um, many companies will get disrupted by cheaper, much, much better alternatives.

AI assessment note: “many companies will get disrupted by cheaper, much, much better alternatives.”

Q When you do the user interviews and user feedback sessions, what are your big lessons or piece of advice on how to do them well? What questions are good? What questions are bad? Any lessons?

A Uh, so they, they, I think for us, there are two different types of user interviews. We, we have this, this type where we just see them use the product and see, like, where do they, do they understand the product? And so that's more of a user experience interview. Um, and the other one is, uh, to understand, like, if they have just tried the product a bit, we ask them, okay, so you try the product a bit, what's, uh, why are you even interested in this? And ask them, like, what problems they're facing in their business. Try to identify What's the biggest pain point that you, that they're actually looking to solve? It might be, oh, I want to get more customers, and I think I can get more customers if I can show to my customers that I can get the first version out with AI more quickly. So those are the questions.

AI assessment note: “ask them, like, what problems they're facing in their business.”

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

A You just did very different. I think, like, I, one of those people, Saki's hiring, they wouldn't perform as well as engineers in my team doing what we're doing. So it's, it's very different type of talent. Um, and like, I, if I knew who was like the perfect engineers to hire, I could maybe step up our, like our compensation bands to get exactly those, but, but I don't know who are the best people. So I, um, 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? Um, and then, and give like the compensation that you give on the top of market compensation rates for that.

AI assessment note: “So it's, it's very different type of talent.”

Q I don't, I don't really respectfully agree or get you because like you give prompts under the prompt box. So you say like, build me a SaaS app or build me a dog website or whatever the prompt is. Dude, all you need to do is click it and you see the code being written and then you see it being created. Like the aha moment is pretty obvious, no?

A So there are many aha moments for, or like education moments to get the most value, get the full value out of using it. And the, the most important of those are with regards to when the, when you feel like you're getting stuck and the AI doesn't understand you. And there's a, there are many things in how to get around, around that, that you can pick up as a user. It is how you, about how you prompt It's about how to understand what doesn't work and explain or explain clearly what, what the, what the problems you're seeing, what, what you find could be the problem when you're building a more complex feature. And it's about that you can actually onboard an engineer to do small changes to the code base. Like those are things our users should know and not everyone knows them.

AI assessment note: “So there are many aha moments for, or like education moments to get the most value”

Q 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.

A Yeah. Yeah. I think, um, as 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. So when you're in a new situation, driving a car, then you're like, your brain really goes on fire and 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 the, what it's doing.

AI assessment note: “for us, it's too early to optimize for that because the AI is every month”