A (4:52)

I think that's a really good insight that you had seen it all. You've worked at a Lot of different companies, a lot of advisory. And so you do start to just see the same sort of problems and patterns and you also see the same way of working and the things that kind of become like really draining.

B (5:07)

Yeah.

A (5:08)

Because they're the same kind of friction points. What has been some of the most eye opening ways and that company. So Anton, I had spoke to him a couple of times and what's really amazing is I think they were like 35 people when they got to over a hundred million in revenue or near 75 million in revenue. And so they were a pretty small team. And so they must be doing things like very differently than normal companies. So considering you've seen like some of the best run B2C or B2B companies, what are things do you think they're doing much, much differently that have kind of surprised you?

B (5:41)

There's a couple of them. The first one, which I find the most interesting one is the level of autonomy every single employee has at Lovable, meaning that they can make really big decisions on a what are they going to be working on, how is it going to get done, how is it going to get shown to customers, what are the interaction points? And that level of autonomy, meaning that there's no cross functional dependencies in order to complete really any project creates so much agency people and create so much passion behind what they're doing. Because it's not just something that a product manager wrote and then just hands off to engineering. And when engineering done it's just like gets handed off to marketing. Everybody's doing the full development life cycle, even to some GTM pieces. Honestly almost all of the GTM pieces a lot of the times completely within a singular person. And that is scary for larger companies because they don't believe that people, let's say engineers on the ground, have the level of understanding to be able to make those choices. However, if you empower them with that information, the beauty of what comes out on the other side, in terms of the velocity, in terms of the quality, in terms of not having a scope creep, but actually the output comes out better than the initial thought or initial like discussion of what it came out with, generates this incredible ability for every single employee to have really big impact in overall experience of the company, but also not having to hire a lot of employees that are just coordinating matrix between people that are actually doing jobs. So there's a couple of rules, so to speak, cultural rules that we have at Lovable, which is number one, everybody is responsible from end to end on everything that they touches They're a full owner. There's no such thing of like oh, I need this person to do this part. That person. No, you try to do it all by yourself and only involve other people if it's absolutely necessary. You are responsible for making all of your own decisions. If you don't have information, you go ask for inputs but nobody's gonna digest it for you to you to just do your little piece. You have to full level sense of ownership. We have more generalists than specialists because of that and we do contract specialists quite a bit. So I'm not going to lie that 35 people is the only human capital that lovable has. You probably have 20 to 30 contractors too that are working side by side. Those full time employees that are providing the specialty and where we are lacking in some of the generalistic hires and then just Velocity above all, we understand that velocity is one of our biggest moats. So we optimize for it. And obviously it's not something that we're going to continuously pressuring on. We don't want to create a bloated software as well by continuously shipping into it. But velocity of hey, from idea to where customers are feeling it should be at most weeks, definitely not months, most definitely not years. And we follow those principles pretty passionately.

A (8:38)

Yeah, autonomy, I kind of heard that was a big part of it. Yes, the end to end is super experienced. I want to come back to that which is in growing organizations, as you said, you have this person does a little part, they hand it off to another person who has specialized knowledge, they do another part and then there's a lot of comms because all these people are handing work off to each other and then the velocity of execution is just very different. Probably because you have people who can be autonomous, work end to end and so they can ship much faster and that's an expectation of them.

B (9:04)

Yes.

A (9:04)

On the kind of end to end portion of it like so you have these folks, they can be much more autonomous and end to end. Do you think that that is going to drastically change how you think about functions? So you've stood up many a growth team, you understand marketing pretty well. In these teams you have somewhat specialist teams. You have a growth team that does onboard and a growth team that does monetization. In marketing you have even many more specialist teams. You have product marketing, brand, all these different niche teams. Do you think differently that there's just going to be a marketer, a growth person and they can do it all?

B (9:36)

I think that we're going to walk Away from full time employees being highly specialized. However, I'm not going to walk away from the fact that specialization knowledge is needed still very much for every single company. So I think that we're going to be in a space where these AI native companies will have smaller full time workforce and that full time workforce is going to be a lot more generalistic in nature with obviously some specialties will still exist potentially but then there's going to be a lot more contract to hire fractional interim advisor specialties that augmented in the areas that that generalist doesn't have a really big detail. But there's also a difference in the product lifecycle to me too because if you're at the beginning where you truly building things, generalists are the best at just putting the building blocks in place and this is where lovable is at. And then there is a product lifecycle where it just goes into pure optimization portion of what has been built as a scaling before it goes into the next horizon of innovation. We're not at optimization and that's why the specialties here like not as important for us to have in full time positions in the company because we're still putting this big building blocks in place and we're just focusing on people that understand what those blocks are going to be and giving them full freedom to do whatever they want to do in the future. This might change but I think that we have taken the notion of just having only generalist and very small employee force to a completely new level compared to any other tech SaaS company that has reached 100 plus million. And by the way, I mean we are already like well over 130. So like we're growing still really quickly. It's not like we've doubled our workforce either. So I think we may be like a 45 people right now overall NFT. So I just think that the companies will be able to maintain a smaller headcount for much longer during their building stage and optimization stage. I don't even know if like companies will be able to have it for a really extended period of time the way that they have it right now because the categories in AI are evolving so much faster. You constantly need to start built. And even at lovable, the way that I think about us in the market, we are at 130 million in AR. I don't think that we have product market fit secured. I feel like we have to regain it every single month because things are changing so quickly. So it's build, build, build before category more plateaus and how much it's changing and then maybe things will shift, but there's no end in sight at this point to that shift.

A (12:12)

Yeah, it's such a fast moving space. Hey, if you want Elena's playbook, make sure you click on the link in the description. And also we're going to put Elena's incredible promotion for all of you to start to use Lovable and get value from it straight away. Click the link in the comments to go get that promo offer today. One other thing then I heard is, well, it's pretty evident, right that Lovable is a much smaller company than you would typically see at the revenue you're at. And so one of the things that happens is teams are much smaller and so they would bring in someone of your experience and your caliber who's a growth leader and is used to hiring standing up teams, instrument and practices. And do you think people who have done leadership in the past when they go join these companies are going to be actually thrown into can you still do the work? Right. I'm kind of going down the path of like there's a lot of people who have got themselves into a tough position where they really are pseudo move around the budget and move around people and they don't really understand how to practice the craft anymore. Do you think they're in for a tough time when we start to see more and more of these small companies do much, much better?

B (13:22)

I think that role of a pure manager is going to die. I see the writing on the wall and honestly think it's going to be better for all of us because they just create additional layers and friction and they hold information from other people and they just sit in meetings all day long. They lost, like I said, all of their vertical expertise. They only have horizontal oversight. And I think anybody who has lost their vertical expertise and be able to do things hands on because they're get so caught up in the meetings and just like high level tasks are going to be obsolete in the next five years and that is not going to make me any friends. But at the same time, if a person has lost the ability to change altitudes, I call it like changing altitudes as you're working to where you can get into the nitty gritty details and do things yourself as well as then escalate and then think also strategically, then your role is on the line. If you want to go into AI native world. I still think that there is going to be plenty need for these types of people in the legacy tech and in other industries as well. They're not Going to be moving in this direction as fast, maybe eventually. But if you're talking about AI native companies, that vertical expertise becomes absolute necessity in what to do. And even for myself, I've always missed IC work. And anytime I get into a larger company, I end up doing almost none of it. So I almost look like I'm micromanaging team because I get into all of their workflows, provide the feedback, do some designs and they're like, get out of here. What are you doing? You're a vp. Go isolate over there. And I'm like, I just can't. Like, that's not who I am. So it works for me very well because I feel like I have this really nice balance and it's actually accepted by the company. But I know that a lot of companies reject that from their leaders. They don't want them to be in the vertical IC level expertise because they want them to be strategic. So anyway, all that is to say is I think the true manager job is on the chopping block in the AI native world.

A (15:30)

Yeah. Number one piece of feedback I always get is like, hey, why is Kieran in doing the work? He shouldn't be doing that. And I kind of set my teams up and say, I actually prefer to do the work than do people management. So you probably have to tell me of all the people problems and not have to tell me about any of the actual work problems because I'll be in the work. And it's just how I've always believed. Like, you should never lose touch with doing the work.

B (15:52)

No. Because then you don't understand what your team is doing.

A (15:55)

Yeah.

B (15:56)

Like, how can you actually manage them? Yeah.

A (15:58)

And it's not that much fun being an expert in like just comms and horizontal people management. I just don't think it's advice.

B (16:04)

People have a lot of fun with that.

A (16:06)

I know. I guess some people.

B (16:07)

Some people love it.

A (16:08)

Yeah. That is true. I think the other part of that is like, so there's like those kind of folks, I always call them kingdom builders. They see their whole worth in a company is like the size of their team. I've got a big team. I'm really important. I quote, my big team. Yeah. And I have lots of budgets. So how do you see people kind of equating their worth in these AI companies? Like, maybe you're going to be a pretty senior person with a team of three or a team of four. How do you think about that in these kind of companies?

B (16:36)

Yeah. So I think that first of all, my leadership Principle which thankfully aligns with this AI native world is that the best leaders are the ones that have best work on a team happen without them. If you need a leader to actually produce something in the team, I feel like you're a shit leader because then you didn't lead, you created a bunch of dependencies on yourself. And that like dependency is what helps people feel job security, especially if they have no vertical expertise and they actually don't produce anything themselves.

A (17:11)

Yeah.

B (17:11)

So it helps them feel that this is why they earn the spot or why they get paid, how much that they get paid or why their title matters. So I think that it's just a very flawed mindset that we've created in hierarchies and titles that is just like holding our society as an industry behind. I actually think that the team sizes per manager can increase quite drastically. You know how we usually say like oh, seven direct reports or so is like should be an average of the person to manage. Because you're assuming that you're resolving a ton of cross functional dependencies for those people. You're assuming that you have to give them a lot of direction in terms of what needs to be done. I think that the team size is actually in AI native companies can go much higher for who like your manager is per se because you can have 10, 15 people team and they can just run independently. And yes, there's mistakes that happen. There's actually like the biggest objection that I get was like, but oh my gosh, what if they go into like this wrong direction? And I'm like, who cares? Because we can really quickly go into a different direction. Like the cost of mistakes is not so big anymore. So you don't need that coordination matrix and like that supervision as much like okay, we up, let's go this way, like no big deal. So I actually think the team size is going to grow, not necessarily shrink. And I think that there's going to be fewer management layers. I think the org charts I hope will collapse. I hope that we're just going to have ICs leads and heads and that's it. There's not manager, senior manager, director, senior director, junior VP, senior VP, regular VP, chief officer. So all of this is unnecessary and it's created by this matrix approach that we think about building software and building teams. And when that falls off, and again, I don't know how far it can scale, nor do I even know how existing companies that have that really high matrix approach can pivot in this direction and whether it makes sense for them. To pivot. But the ones that get started with it, it just makes so much more sense to remove that management layer for as long as humanly possible. But that also requires very different types of leadership that comes in into the companies.

A (19:16)

Yeah, 100%. If you can have people that can be much more autonomous, you can break the kind of friction points where you have to create all of these roles that are really just semi comms roles like I get information and I pass on information, then I pass that information on and then I pass that information down and then there's the person who actually does the work and they do the work and then I pass the information back and it goes all the way across. For every person doing the work, there's like four people passing the information of that work being done around a company. And it's trying to get back to having people who are mostly doing the work and to be able to do that. I think if you can have people who are autonomous and I think the end to end part is a big part because in bigger orgs you've worked in them. It is a lot of like everything gets broken down into more and more specialized knowledge, which means it creates more and more comms lines.

B (20:05)

It's a game of telephone. The end result is just completely different than the initial idea too. So it's just like everything along the line ends up being disappointing output. So I think that we have an opportunity with AI nativeness to reinvent some of this org structure and titling and what it means to build companies. And I hope Lovable is going to be one of those companies that helps reinvent and write the new playbook too.

A (20:29)

And so one of the things I wanted to get into is has AI made you rethink the role of growth? And so for our listeners, growth typically help kind of the self serve product led businesses acquire users get users to activate on a product which means they've done something of value in that product, they've used it in a meaningful way. Then they actually figure out hey, how can I get people to use this product more often? And how can I get people to upgrade to the next package of this product? And you've done that and you've instrumented that so many times for so many companies. Do you think any differently about that now as you go into Lovable?

B (21:02)

I do. So I define growth specifically for me in product led growth lens is that I try to look at product and see how can product answer questions of how do we acquire customers through virality or user generated content? How do we activate customers, how do we monetize them and how do we retain them? That is like at the core of what I'm trying to accomplish in every single company. The interesting piece here is acquisition piece. I still very much feel is there like you need to think about how can you stand up any viral loops, any user generated content, how you can utilize it across all of the other channels. So that piece I still feel very connected to and very focused on. Especially since a lot of marketing distribution channels are collapsing or not performing well at the moment and product is still becoming like one of the biggest defensible moats of how you can acquire customers if you can lean on product to do the acquisition. So it becomes like almost the biggest marketing channel if you can make it. So obviously not every single product can be made into marketing acquisition channel itself. Activation to me has been very interesting topic because I've been a huge proponent of activation. I've written so much about activation and how companies treat activation incorrectly. However, with AI, the problem statement of activation changes quite a bit. With AI you don't have a bunch of screens, a bunch of options, a bunch of things to do. There's just the prompt box. And everything in activation just happens with your interaction with that prompt. And that is part of core product experience. It is no longer like very little things that you can do in growth of like of making it right because there is very little real estate to even touch when you're having a truly AI native product that you're working with. So it's like the. The real estate that growth can touch has collapsed quite a bit from many, many screens and many many options and all of the awareness that you needed to build and all of the from good friction to bad friction. The more screens, less screens. Like none of that exists. All of a sudden it's just a box. So it's very different mentality because now you just need to use your AI to get to that aha moment as fast as possible. And then still what growth does still focus on a lot is how to monetize. Because we don't really know how to monetize AI properly. And AI LLM costs are changing very rapidly. Everybody's going between usage model to outcome model. But then you still have packages with feature different. There's just like so many still unknowns of what is the stable and scalable and profitable models for us to monetize on AI and how do we educate customers and our potential users on what those options are and how should they think about it. Because it's quite different from margin profile to the actual usage patterns compared to traditional SaaS. So I still think so. Acquisition, yes. Activation. I'm not like, I'm not even sure what's happening there. Monetization? Heck yes. There's like so much work to do on monetization and innovation, honestly that we can introduce with AI and then retention too. I think retention is always going to be a growth problem, but the retention here is more not necessarily like in product again experiences. It's all about all of that communication and rapid that you can drive through both AI getting to the point where retention is a given because they've built or done something meaningful as well as all of the vehicles around it that growth can layer on making sure that any resurrection, reactivation or communication paths are clear.

A (24:34)

Yeah, and I was thinking that because I'm a pretty active, lovable user, actually I use it every single week, built in a couple of apps, one pretty big app. And like, yeah, like it's. I know how you would even consider activation because it is really just like me coding away with my assistant and then like, how do I know I got value from it? It's like, did I build the app? Did I get a page build? Like what. What is like that initial thing of value and for the most part that is the product experience and the things I love that lovable have added is I can now basically just connect. Buy a domain. I can just buy a domain in the app. I can connect it to the app. I did that recently, actually. I bought a domain, I connected it to the domain and it was hosted in like under five minutes. It was like crazy. That helps my retention. Is that a product thing? Is that a growth thing? So these things do start to blur.

B (25:19)

Yeah. But I do see it as a product thing because it's a core product experience and functionality. We do define activation at lovable is you publishing an app. So we say like, okay, you finished prompting. So we're not just going to optimize a number of prompts that you do because that's almost an anti metric once you start going past a certain point. And then we're also pushing our activation definition. So that's like an ultimate that you not just didn't click the button, but you actually started to either yourself use the app that you've built, somebody else internally in your company is using it, or you actually published it as a product and you started to get customers to it as well.

A (25:52)

So one of the core growth things as well is trying to figure out those Metrics for your core power users. Like trying to split users into power users, medium users, not your core user base. I can imagine one of the problems is maybe you have too many users because how do you even start to wrangle who is your user? Right. One of the interesting things, I had a conversation with someone very recently about all of these AI coding assistants and there was a couple of interesting things they brought up with Lovable, which is, hey, Lovable has this whole other Persona type, which is a person who used to play video games, which I never even thought about. Now go off and they see the same kind of thing and they're building apps. I don't even know what that Persona is. The student is a Persona like all these kind of young kids are building cool stuff for themselves. Personal software basically is a Persona. Have you even thought about who are we building for and we should just build for anyone who wants to build apps? Or do you start to think about who is my course user group?

B (26:48)

Yeah. So there's a couple of thresholds that we've thought through of how we go down into definition without restricting the horizontal aspect of the platform where anybody can come in and build an app with us. So the first decision that we thought is, are we building for technical or not non technical users? That was like a really polarizing decision because if we're building for engineers, it would just require, as we're coding up, we would just require very different treatment. We decided to build for non technical group, but we don't want to piss off engineers too. So it's like very much our adjacent Persona of do no harm there and make them not have an allergic reaction to Lovable, but at the same time they have amazing tools like Cursor that they can go to. And we're not going to try to compete with Cursor on owning engineering Persona. The next level is actually, okay, non technical. What are the use cases that they're going to be doing? We've identified two that we're focusing on right now, which is one is the solopreneur that are coming in and building a product versus the other one is a team player. So it's an engineering adjacent Persona within the corporation, Product manager, marketer, designer, sales, finance, ops, like you name it. And they're doing it for prototyping or internal tooling and whatnot. The only reason that we separated the two is because one is trying to build a business on Lovable, the other one is trying to improve their productivity on Lovable. So. So there is quite a different output of what they're trying to get. But the building product on Lovable is much more complicated portion of the use case compared to just internal tooling. So our vision is to enable more solopreneurs to build products on Lovable. But on the path there, the team player use case just is like, it makes sense for us to tackle that as well. So we can help people with productivity and just learning AI in their workspace as well. And we felt a really big market pull from that direction as well. But then on top of it, then you can also start talking about specific jobs to be done. And for example, for building products, we said, okay, we don't want to compete with Shopify on E commerce use case. Like, we don't want to redo Shopify. Shopify is fantastic, they're doing good and we rather integrate and partner with them to create a vibe coding option for their storefront. As opposed to going into direct competition versus some other apps like B2B apps or even some B2C apps. There is no really clear competition. So we're like, okay, yeah, this is something that we want to do you from end to end ourselves. So we kind of went down that waterfall decision tree of where is it that we want to focus, who is it that we don't want to piss off, that we think is a really important Persona for us versus where is it that we're just not going to play at the beginning, but every single decision that we make is also, don't alienate anybody. Just have a very good focus on where you can add additional value for specific user set that we want to focus on.

A (29:28)

Yeah, that makes sense. But when you say when you're trying to delineate between those users in terms of the experience, I assume the coding assistant is just tuned to be a great coding assistant. And all of the way you do the delineation of features is in all the additional features built around the assistant. I guess what I'm getting at is when I go in and I start coding with my assistant, it's not categorizing me as a novice coder. And then the model, the assistant has actually changed the way it's the model. Like working with me, it's like everyone gets the same sort of code and experience and all the functionality around it is the things that are more projected for the different user types.

B (30:03)

Yes. Because our mission fundamentally is to make it just work so you don't have to know all of the details around it. But if you know the details, you can look under the hood. And you can go into all of it. So this is why we have dev mode, this is why we have GitHub integration. So if you want to go into those details, feel free. But fundamentally we want to build an experience that is seamless from a customer perspective, from end to end and things that have not even felt possible before. Pushing further past just like a beautiful landing page or the beautiful prototype that you can create on lovable to something that is actually functional. Yeah, okay, so that's the not an alienation piece. We're not holding the code hostage. You can go look at the code, you can go adjust the code, you can go the take code out if you so wish. So that is the piece of where it's an adjacent use case that is very important to us, but it's not something that we are actively focusing most of our time in creating new functionality for.

A (31:03)

Yeah, okay. Just staying on the topic of growth for non AI native companies, for companies that are trying to figure out how to apply AI to their go to market. Do you think companies should start not replacing but thinking of their growth team as more of an AI innovation team? And I can give you a quick example. Let's say one of your companies that is a PLG and human company. So like product company again for our listeners, they usually have a self serve model. You can go in, you can buy something and then they have higher valued plans and you would talk to humans to do that and they would still have humans for customer support success. And so the use case I use that kind of breaks the tyranny of like we do things to make the humans more efficient and then growth are doing things to make the self serve model more efficient. Is I think most of these are all going to want to converge on this AI multimodal agent. Right? So if you go to a website, you have an avatar, the avatar can speak you through the product, it can sell you, it can get you on board and then you go in, the avatar can use the product on your behalf. I've been talking to founders and they've been showing me how to do that. It can actually onboard you. And then when you have a support issue, you talk to the same avatar and the avatar is basically saying, hey, I can support you, I can do this thing for you. So in that case really the entire growth journey is really just an AI version of a human. And I think that is starting to maybe break the ways that we've traditionally thought about growth versus what is not growth. And I'm wondering is it a better Way to think about it that companies should just have a AI innovation squad which could be the growth team but like they serve both the human and the self serve components.

B (32:43)

It's an interesting thought. I do believe that in the future once more products will get sucked in into AI first way of doing things and different products will be on a different velocity of getting to that destination. But I do think in next decade that is how we went from on prem to cloud. This is going to go from like traditional tech to AI shift and we're just starting, we're just seeing the cusp of it at the moment. And I do think that a lot of growth teams and honestly like most of the other teams are going to almost create their own agents in the company that is going to run autonomously. Like why do you need a really sophisticated growth team to do conversion rate optimizations on landing pages? Why do you need growth teams to go do lifecycle email marketing optimizations? No, like you, you should either buy an agent that does this for you or you should build your own agent that does this internally. So it's, this is like the portion of automating, like the one on one things that yeah, we know what needs to be done there. Let's educate an agent and let it go run. I do think that there's still a path here for growth teams and really any other teams to really lean on the some of the human creativity and some more of innovation portion of your job where you're actually thinking outside of the box as opposed to having to settle things that AI can do for you for the most part. So that's why I don't think people's jobs in vertical expertise are going away. I think they're just going to be lifted in the type of work that you're doing. But in terms of introducing AI nativeness to companies. So I've seen so far two things happen to businesses. Number one, they create like an AI innovation team that is central, that is sit somewhere with office of CEO or sit somewhere with the operations and they try to buy AI tools and they try to like have people use the tools and that doesn't really work because it gets really hard to pull your head out of the sand out of like everything that is going on and all of the priorities that you have and say like now I need to go and learn something new. So like it has a pretty big rejection rate and people fundamentally think about it as a burden and something new that they reject out of their system as opposed to an opportunity to do something Differently and better because there's still a learning curve. It's not like it's magically just happens. You still have to spend additional cycles of implementing it even if there's something better on the other side that is waiting for you. And then the other way is that they hire these AI native employees and just plop them into organization. And those AI native employees that think about it just like I said and lovable like end to end, everything is solved with AI tools from coding. They spend 80% of the code written in AI and they just like do the final 20 to whether it's marketing, they create creatives in AI copy and AI they like, they go use so many AI tools to get a lot of the job done and they get completely suffocated in the organization because they just become a regular employee and they're not able to really showcase the capabilities of what they do because they immediately start overstepping some bounds and cross functional roles and responsibilities that exist. So I actually don't know how existing companies can do this. Maybe Intercom is the only case study that I would be interested in right now that have really shifted themselves and said hey, we're going to be AI first and like we're blowing everything externally and internally. But it's like a company wide thing because I haven't seen a data point of successfully introducing it from one department and spreading it into the others. But I hope that I'm wrong and I hope that somebody figures it out because I'm in like an advantageous situation that we're starting from scratch so I don't have to deal with that tech debt and organizational debt which is just not fair to then go and say this is how you do it because. Because I actually have no idea.

A (36:34)

Yeah. Are there any no brainer growth use cases for AI? You probably get asked by many different growth leaders and growth teams what are some ways I should start to use AI in what I'm doing? Is there any kind of no brainer things that they should start doing?

B (36:50)

Some no brainers are fairly straightforward. They're not really big change. I'll just tell them myself. So what is my growth process was before versus now? So my growth process like I would go, I would scout for the idea. Like I would think about something, I would go and I'd write the spec, I'd go review the spec with a lot of people. Then I go to send it to a designer for some sort of inspiration and the vision. Then I go review all of the designs. Then I'd Go to a copy and say, okay, now let's finalize the copy. Then let's go to engineering. Let's talk about what is possible. Engineering scopes it up, scopes it down, whatever it is. Then it gets into the roadmap and then maybe something pops up in the product. Right now, to me, even that cycle is completely collapsed. So I have an idea that still needs to happen. So, so really focus on your idea generation of where it comes from. Then I go to ChatGPT, it writes the initial spec for me. It's 70% there. I take it and then I start just crossing it out. In an hour I'm finished with the spec. I'm not proofing it with anybody. I'm pulling engineer immediately into it and saying, hey, I have an idea, break it down for me because this is the spec. Then I go and I vibe code the prototype so they can react to it too. So there's like an emotional reaction immediately that shortcuts to a solution of what actually needs to be done. And then I hand it off to engineer designer. Sometimes in the more complex things does get involved for sure. I have an incredible designer on the team. It's one designer supporting our entire team right now. And he goes into like more complex things. Otherwise it gets done and then they just ping me when it's live and that's it. Like there is no more of that coordination. So it's just, it's quite shortcutted. But anything from writing specs to designing prototypes, to vibe coding the pages that you're going to be publishing, to even creating small automations on how to do things internally to just help you not have to be sitting with a bunch of Google Docs and Google Sheets constantly everywhere. So it's like a live app that can live for people. It's helpful to just shortcut a lot of these things that take too much time and that decelerate your velocity.

A (38:53)

Yeah, I love that example. One of the ways that I loved using it was we had this off site in San Fran and I was going there to pitch a business strategy and part of that business strategy was a new product. Now in the old world I would have had an idea and then had to get a designer to mock something up and then had to pull in some people to write a memo and then had to pull in an engineer to tell me what is impossible and then had to probably present mockups in a presentation. That usually is what happens. And so what I did in this use case, I kind of built an AI team. So I built a little CTO which is basically using ChatGPT projects and uploaded 20 different docs of all the technical specifications, what are some of the best principles? CTOs. And then I built a UX designer and then I built a CPO and I have my own little team and I basically just presented a fully baked app and it's again, lovable. I built it in lovable and we're going to do that app. And I just feel me and Kip talk about this a lot, is like, I think some people feel disempowered by AI because they are like, I maybe not need it because people are more autonomous. I've never felt more empowered. Maybe it's because I'm an introvert as well. And I just love sitting with my little AI team doing my own stuff. But I actually think it's like the best time to be someone who actually enjoys doing the work and maybe doesn't enjoy when you go to big companies, all of the stuff that has to surround that work and you can just do so many more things and bring your ideas to life so much, much quicker with apps like Lovable. And that's like one of the reasons I actually love what AI is helping people to do.

B (40:28)

Yeah, I agree. AI will automate some portion of our work and if that's the only portion of the work that you can do, then yes, your job is threatened. However, to every single one of our roles, we're only scraping the floor of what actually we can be possible of doing because we held back by things that AI is now all of a sudden automating. So I see it as an unlock block of free time that I can spend on more meaningful things and you just have to look forward with it. Like two people are just afraid that because their entire day is taken up by the things that AI can now do that they're a threat. But I actually think it's exact opposite. It all of a sudden opens up the entire day for you to innovate and for you to actually do something different and more meaningful with your time. So I hope people see it it that way as opposed to in a negative light because I think there's producing much more good to us overall, especially as the dust settles from the initial shock.

A (41:28)

Yeah, yeah, I think this is a great place to end. Like as my good friend Kip says, AI is a bazooka for the creative mind. And I actually think that is very, very true and you should look at this as a way. Well, I can do. To your point, we are held back by all of the things that hold us back as tool and all of these kind of things that hold us back. And so there's probably things that you're capable of that you have never even reached that bar yet. And I think that's the thing AI is going to allow us to do. So thank you so much Elena for coming on, sharing the kind of behind the scenes on the fastest growing AI app on the planet. I'm sure we have a bunch of listeners who are lovable users and we appreciate the kind of walkthrough.

B (42:06)

Yeah, and I want to offer a special offer for people that haven't tried lovable yet. So I'll pop it into a page that will be followed up by this podcast, so check it out to see what it is.

A (42:16)

Awesome. I'll follow up with an episode with some of the best things I've built in Lovable so people can see how I'm using it. And then you should sign up for the page to show how you can do the same things that I'm doing. Thanks so much Elena for coming on.

B (42:27)

Thank you for having me.

A (42:34)

Sam.