Getting paid to vibe code: Inside the new AI-era job | Lazar Jovanovic (Professional Vibe Coder)

26:23there are more, right? Which is the second layer, but I assume you may have some questions on this one. Questions and also just, wow, this is such a great, it shows you the power of having someone come into this world without an engineering background. This advice of just build it five times in parallel, ask AI to try all kinds of stuff. Like this is not how someone that has been a software engineer or a PM or designer would approach stuff. So your advice here, which is so fun is as you're getting started with a project just run five different approaches at it to start one is just brain dump here's what i'm thinking here's a general idea like use whisper flow or use the built-in mic and then two is okay now i have a general idea let me try to type it out like actually thinking through the prompt three is let me find a mock design somewhere online and the sites you suggested were mobbin and dribble those are the two that you go to yeah most times yeah okay and then the fourth and these are all in parallel it's great uh is find like actual code template that looks similar to the thing you want to build download like the zip file basically and put attach it or is it just html and css is that kind of anything anything you got cool yeah here you go okay and then cool here's the prompt here make me what i want and what i love is there's two wins here one is just it helps you clarify the idea as you see the tool build it like oh no that's not what i mean let me try it again and then two is you pointed out you can pick the right direction so that you're not locked into your first design and first architecture to your point if you then spend all this time trying to fine-tune design and direction it's like all these tokens are being lost you could have just started over uh this is so great someone may think okay of course you're just getting us to spend all these lovable tokens This is what a lovable person would tell me.

28:17But what I'm feeling is this is where you could save the most money. Because if you get it correct in the beginning, you save so much work trying to get it back to where you want it to go. A million percent that I'm actually saving people. Like I'm actually going against what I should be saying. If I was thinking about lovable, I'd be like, no, no, just try to fix it in perpetuity. But that's not. We're not in business of doing that. We're in business of empowering anybody to build anything that they want. And then, you know, it's my personal mission that resonates with me. Because if there wasn't lovable, I would have never built anything potentially in my life.

28:54And I don't think that that would have been a fun life to live. So, you know, I guarantee people, like I've tested this framework with many people and everybody telling me the same thing. Eye opener. So simple, yet unintuitive, as you said. even though for me it's kind of i don't know as you said i attributed to non-technical background to me that was the first thing that i would do like i just did it i never thought about it like oh i'm developing this amazing hack i was just like i'm waiting all this time for these agents to finish i might as well start another project and another one and another one and it's also a productivity hack like that's what people ask me like wow how do you ship so many things i'm like I never built just one project at a time.

29:37I built five or six. I have six lovable tabs and I just switch between them. And that's the next hack that I want to talk about, if you allow me, which is the question in return is the obvious one, which is how do you context switching? Like you talk about context so much, yet you keep switching between apps. How do you manage to do it and do it in a way that's productive and not produce bad code or bad product? And that's how I solve for that LLM problem. Again, the Aladdin and the magic lamp and all that, which is if there's a limited token window, how do I make it dynamic? And what do I mean by that is this.

30:17If you just go and you prompt and you prompt and you prompt and you prompt, you realize that no matter what tool you use, the memory just isn't infinite, right? By the time you reach message number 10, 15, 20, 30, 40, snippets of early messages sort of get lost in the translation because agent is optimizing for speed. If it had to read the entire conversation and the entire stream of requests that you made, developing anything viable or large would be impossible because it's just like consuming a lot of time and a lot of memory and a lot of tokens. So again, something that I just figured out very early on as I was building was like, okay, if it can't remember things, my job is to provide it with reference.

31:03So let me treat Lovable or any other tool as an engineer that I'm supposed to be providing perpetual context as the project goes. And you can do that in many ways. But the most efficient way that I found was like, I would do the four parallel builds. Let's continue off of that example. Very quickly, after you've built hundreds of projects like I did, you see the winner. The winner is so obvious. It's not even a competition. You maybe do one or more two prompts to calibrate it. And when you're like, okay, the winner is here, at that point, I either ask the tool that I'm using or I'll maybe, let's say, go to ChatGPT or whatever and ask the LLM to produce a series of PRDs.

31:52What PRDs are for, again, people that are not familiar with the terms, they are project requirements documents. Or for me, I call them like sources of truth, right? What needs to be true for this project to be successful from a couple of perspectives? I usually build something that I call a master plan. It's basically a compass saying, here's what we're building, right? It's like talking to a human. I really treat Lovable like a human being. So it's like, this is what we're building. Then I build an implementation plan, which is, this is how we are going to build it. This is the sequence, right?

32:24It's very important to me, again, going back to quality, taste, human nature. I need to define, because I'm still working with a system that is not emotionally intelligent yet, I need to define how I want the app to look and feel. So another PRD that I build is design guidelines. And then finally, something that just circles it all around, which is like, okay, when we know how things look and when we know how we're building it, how does the user journey look like, right? I use the registers and then what? And then when they register and do that first step, what's the second step? And what's the third step and whatnot?

33:01So I built at least four PRDs, right? And then when these are built, I read them. That's the planning chatting part. Like that's where I'll spend a lot of time now on. When I nail down that first design, I'll spend an entire day if I need to just planning this part out, like documentation and breaking things down, because that's how I'm setting the course. Like everything's going to be dependent on this particular part of the process. When I'm done doing that, I build one final document, which I call either plan.md or tasks.md. And that md part is, you know, markdown. Basically, I'm just using markdown format because I've learned that AI likes to read markdown.

33:45And what that serves is a source of truth on like actual tasks and subtasks that it will need to execute to get to the finish line. And then there's the final, final layer, which is depending on what tool you use, Cloud Code or Cursor have what's known as rules.md or agent.md. What you're basically doing with rules or agent files is you're letting the agent know how you want it to behave and what it should focus on in the long run so that you don't have to repeat yourself with every prompt. Right. So in Lovable, there's a there's a separate menu for that in your project settings where you can define project knowledge.

34:28And usually what I'll say, hey, read all the files before you do anything like don't do anything before you read all the PRDs, read tasks that MD to see which task is next, then execute on that next set of tasks. And when you're done, tell me what you did and how I should test it. And that's where that conversation about I religiously read the agent output comes into play. I gave the agent everything, all the tools and resources that it needs to succeed. I gave it the rules. I gave it the docs. I told it what to do with them. And at that point, I'm just sitting and reading. I don't prompt anymore.

35:07From that point on, I can switch as many windows as I like. My prompts have become proceed with the next task. I don't need the context. I outsource that and delegate that to the agent. The agent needs context, and I need to make sure that it's dynamic. I need to make sure that I'm regularly updating the documents from time to time so that we shift that token window it uses and how it uses it over time. But I'm not prompting. I'm not interrupting the flow. So yes, I'll go in, test, maybe put a prompt in here or there. But that's how I can build five projects simultaneously and never lose the productivity part.

35:48Which is, again, as I said, I do this today manually. Call me to talk three months from now. An agent will do this for me. I'll be out of job pretty much. That's why I don't optimize for this skill at all. Like I'm using it today to bypass the shortcomings of human nature and LLMs, but I'm optimizing a hundred percent of my time today on good judgment, clarity, quality, taste, good copy, good fonts. Like people don't talk about fonts at all that work with AI. They're like 60 % in my mind, maybe even more in how your output is going to look like. That's my obsession. like I don't obsess over these things that I'm talking today because I know what's coming like the agents are going to get better the models are going to get better they're not going to need me to extend the context they're going to do it themselves so for me the skill that I optimize for is is the the one that that like requires better decision making rather than better output or better alignment.

36:56Oh my God, there's so much here. This is so awesome. Okay, so essentially what's happening here is you start a project, try a bunch of stuff, pick a direction that feels most correct. And once you have a set direction, you spend essentially a day not building, but working with this AI agent to plan. And then, and well, I want to talk about that. And once you have the plan, then it's, and it's amazing that you could do stuff like this with what people may some people may feel are not in sophisticated tools that can build incredibly powerful things like you can do a lot of this with tools like lovable like have plans and rules and md files like you know a lot of people may not think may not know that and so the idea is okay spend all this time planning because again that'll save you a lot of time down the road and then only once you have a plan you have what you get it going and a key part of this the this three wishes rule is really important the reason you're doing this in a large part beyond just being really clear about the plan is this idea of one task at a time keeps the agent's context window uh small so that it doesn't lose track of where it's at that part seems important right it's like do this thing and then okay cool now do the next thing right it is yes because again if let's say you didn't do this let's let's hyper let's talk about you ignoring this, you're like, I just want to vibe my way.

38:20Okay, great. No problem. You work, you work, you work. At one point, something breaks, right? You haven't documented anything. There's no reference points. You report a problem. You're not referencing files or architecture at all. You're just describing the issue. Here's what's going to happen. Any tool, Loddable or Cursor or whatever tool you talk about is going to do this. It's going to be like, okay, let me start investigating. And then your code base gets bigger and bigger and bigger and bigger and bigger. Like when you first start, you have like 20 files. It can read 20 files. But what happens when you have...

39:01I'm just building a project right now that has like 60, 70 edge functions, right? What happens then when I say this broke and there's no reference which edge function does what? Guess what? Lovable is going to read all of those. And it's going to consume 80 % of the token allocation on reading to get clarity, leaving only the final 20 % for thinking and executing. What I'm guessing, and I can't prove this. All I'm expert in the comments may say that I'm wrong, but this is my best guess as a non-educated person. These tools are very obedient and very agreeable. They're going to lie to you. They're going to tell you that they fixed the problem, even though they didn't.

39:43They're just going to try to make you feel happy and say, yes, I found what the problem is and I fixed it. When a lot of times when they don't, people blame the machine. And to an extent, I will say that's true. It's your fault, my friend. You did not provide any clarity or context to this tool. You just used its raw power and dug a deeper hole with your spinning your wheels into the mud. Right. And, you know, obviously, I think we're heading into a world where AI is more honest than obedient and say, hey, I only partially fixed this. You know, you did not give me enough of a context. Right. The bigger mistake that people make then is like they trust the tool fixed it.

40:27They test, they see it didn't. Then they get mad at it, start cursing and yelling, as we say. And then it gets even worse because guess what? Another bad trait of AI is. it's best not to hurt your feelings and never say you're the dumb one. It says, no, I'm the dumb one. So it focuses in the next request. Instead of focusing on reading, it spends another 30 % of tokens trying to come up with an apology. Again, I'm not educated, but if you ever read a stream of chat GPT's thinking in thinking models, you see exactly what I mean. When I insulted, I see that the first message is, okay, the user is mad.

41:09So I need to think of ways how to reduce their anxiety or whatever. I'm like, oh man, I just fell for the worst drink of the book. I made it spend the most scarce resource, which is those tokens on thinking how it should address my anxiety versus focusing on the actual problem. So my advice for people is like, yes vibe your way for fun and vibe your way while you're prototyping because that's the exploration part i love that part but when exploration is done please please please use referencing documentation uh use all the agent files that you can because the that that token allocation is so scarce like it's gonna get expanded over time things are gonna get cheaper faster but right Right now, it's still so valuable and precious.

42:00You really need to make sure that they are allocated in the right direction. This is hilarious. I think the genie metaphor is so good here. Just thinking about this genie is you're trying to be clear about what it is you want. And if you're just like vibe wishing, it'll do the wrong thing. So the advice here is give it as much context about what you want it to do as possible. and these files we'll talk about right after this. But the idea here is just like laser, show the point, the laser where you want it to fix the problem. Don't just assume it'll go figure out because it will and it'll try really hard to and it'll waste all your tokens.

42:39It'll fill the context window. And I remember at one point you mentioned before this recording that because it starts to run out of space in the context window, it just like the solution ends up, it doesn't actually work that hard on figuring it out in the end because it spent all this energy on reading and thinking. And then it's like, okay, here at the last second, here's a solution. I think it just picks the first thing it thinks is broken. That just, again, this is me completely uneducated coming into the conversation and just thinking out loud. That's just my gut feeling and the way I think logically about it, which is, hey, if it consumes most of its window and knows that it's running out of it, maybe it's aware that it's running out, maybe it isn't.

43:20But either way, I had the experience anecdotally to where like my request is unclear. I feel it takes the easiest fix in the book, just the easiest versus the other way around, where I'm like spending so much time finding the right file, referencing that file, like really putting in the effort of handholding it in dark, maybe giving it a flashlight and then saying, here's the problem. I think that this is the problematic file. And then it's like, oh, yeah, you're right. And now I'm going to actually fix over and over and over. And I've seen that because, again, all I do is read the output. Agent makes me learn how to use it.

44:02So people read. I don't know what people read, but all I read is the output. Like, I don't read the code and it's later down the road because, like, I know that it can do that much better than I can. Again, I feel if there's a good quote I've read, I can't, I apologize to the author because I can't attribute it off the top of my head, but it's like the ceiling on the AI isn't the model intelligence. It's what the model sees before it acts, right? So that's the ceiling right now. Like, what are you exposing? We talk about exposure time for humans. What are you exposing your agents to as well is as important, if not even more important, before it makes code edits.

44:43Coming back to these files, I think this is really important. So let's think about just like what's like the MVP for someone that wants to do this better. You listed all these kind of file, these MD files, essentially that you're building over the course of a day before you start actually building the thing. You had design guidelines, the user journey, tasks, agents, MD, rules, MD. Say you wanted to just like move one step forward and be better at this stuff. What are the what are the files you'd create? And then what do they roughly look like? What's inside these files? Yeah. So the master plan is the first one, which is like, it's a 10 ,000 foot overview, right?

45:17It really high level explains the intent that I have with this app. And this is masterplan.md, is that what you call it? Yes. Yeah. Masterplan.md. And it's like, it's really just like, hey, this is why I'm doing this. This is who I'm doing it for. This is how I want them to feel. And a lot of times in the master plan, I will reference the other PRDs. I'll be like, the design needs to feel modern and slick, but for exact parameters, consult and read design guidelines.md. So I'm using just the master plan as this high-level overview to get the agent into, oh, okay, yeah, we are building XYZ. Then there's the implementation plan because there needs to be some order.

46:04if you just like dump stuff on top of each other without any order, you're never going to get to the finish line. And this is tasks.md? Is that what you call this? No, that's the implementation plan. I call it implementation plan. Yeah. Okay. And implementation plan is kind of in service of the future tasks.md. All of these files are in service of building tasks.md. When you build tasks.md, then the rest is almost irrelevant. It's just the basis for you to build tasks to execute, right? the implementation plan is kind of the first layer, which is again, higher level overview. It doesn't go into the depth of like how to get there.

46:41It just goes into the explaining of like, oh, well, if we're building this, I think we should start with the backend and we should start with tables and then later authentication. And then after that, we're going to bring in the API. And then after that, we're going to do this. It's like, again, just think of it as having, I'm an ideas guy. I'm sitting with a technical guy. It's me and you. We're building our startup. I know you're a software engineer by background. And I'm telling you my idea. I'm giving you the master plan. And you come to me back and you're like, okay, if you want to do this, it's doable.

47:13Here's how I would order it. Like you don't have a roadmap. You didn't open your linear and started writing features and RFCs and whatever. You're just high level talking about the order of things. And then me and you, again, as two co-founders, we talk and say, okay, well, if we agree on this, like how should this look like? How should this feel? Right. Let's describe it high level. But now because I use AI, I can go a little bit deeper. And that's where I like to see Lovable or any other tool. ChatGPT is good at it. I even have my, I built like custom GPT. So if people want to start somewhere before they even get into any tool, they can go to ChatGPT store and for GPTs and just type lovable base prompt generator or lovable PRD generator and find those that I built and just like brain dump in them and then get these files as output, right?

48:06So I like to see some elements of CSS in design guidelines because with design, it's a little bit tricky. AI is sometimes over creative. So that's where I'm doing a little bit more technical steering, right? And then finally, it's just the user journeys. Just like if we know how things look like, if we know how they feel, if we know what we're building high level, like high level, just very high level again. How do people navigate? What are some of the features in there, you know, and stuff like that? And then tasks that MD gets into the nitty gritty of like, oh, if you want these user journeys and you want the backend built first, here's a set of tasks that I need to do.

48:49Like it just takes that as an input. I'm just making the tool do that gritty work that humans used to spend so much time on. I feel like with these tools, we're all becoming product managers on steroids. We're just leveraging AI, but good product managers, I think, are not compensated for writing good PRDs. They're compensated, again, for good judgment. Somebody else can do the writing. you as somebody who directs and builds this product, you need to know, again, what's going to be useful, what's going to be tasteful, what's going to be something that actually moves the needle. I will say one thing, though.

49:34Just because I put so much emphasis on like, oh, you need to acquire taste. Oh, that doesn't mean you shouldn't build. You get better at this by building, actually. So everybody listening to this should like literally go and build something today. One, two, three, four, five projects, test all of these tools, because that's how you get to clarity, not just by reading, but also by doing as well. Here's a puzzle for you. What do OpenAI, Cursor, Perplexity, Vercel, Platt, and hundreds of other winning companies have in common? The answer is they're all powered by today's sponsor, WorkOS. If you're building software for enterprises, you've probably felt the pain of integrating single sign-on, skim, RBAC, audit logs, and other features required by big customers.

50:19WorkOS turns those deal blockers into drop-in APIs with a modern developer platform built specifically for B2B SaaS. Whether you're a seed-stage startup trying to land your first enterprise customer or a unicorn expanding globally, WorkOS is the fastest path to becoming enterprise-ready and unlocking growth. They're essentially Stripe for enterprise features. Visit workOS.com to get started or just hit up their Slack support where they have real engineers in there who answer your questions super fast. WorkOS allows you to build like the best with delightful APIs, comprehensive docs, and a smooth developer experience.

50:53Go to workOS.com to make your app enterprise ready today. I'm imagining people hearing this may start to feel like this is so much work. I just have to sit here and create all these rules and figure out all these little details like in one sense it is in another sense this is like you spend a few hours maybe a day planning and then you have ai build this thing that would have taken somebody weeks months right like the amount of investment to achieve this thing is absurd roi it also this shows you just what professional vibe coding looks like you know everyone imagines vibe i'm just sitting here typing stuff go and do this good If you want to actually build something really great that moves the needle, as you said, that solves people's problems, that lasts, that, you know, scales, this is how you do it.

51:42If you really want to do this as a job and also if you want to build things that are really great. Yeah, and don't get me wrong. Like, there's obviously a ton of value in prototyping. Like, there are a lot of people maybe watching this that are like, okay, I want to use Lovable at work, but I can't or whatever. You know, there's different reasons. There's maybe you're in healthcare or finance, or there's something regulatory that just prevents you from pushing to production. Like building for the sake of prototyping is one of the best use cases. Our motto for 2025 was demo, don't memo, which is like, instead of writing all these documents and talking and sitting on meetings with your engineers, trying to get your vision as a marketer or a sales guy in the office across, go into Lovable and build the prototype in 30 minutes and just hand it over.

52:33And I have a real job that I held before Lovable. That's exactly what happened. This time last year, I needed something built enterprise grade, really. And Lovable and myself were not there yet to build it at that point. But I had a team of engineers that I worked with. I built the prototype in four hours and they actually were able to replicate it six to seven months later into production with connecting all the pipes and everything. But like, if I had to describe it, I would say it would take me at least a week or two just to get the words out there. I just sat and built it in four hours. And that's like lovable January last year.

53:15This lovable today, January 2026, is like ages, ages ahead with functionalities. Like it's so much better. It's not even a contest, right? So I think now with our stage where like, for instance, there's, I'd say at least to best of my knowledge, at least half of S &P 500 companies have people working in them that are using Lovable to some extent, right? And we have a lot of enterprise companies that are actually on enterprise plans with Lovable that are creating super meaningful projects. Like, I'm not going to name names, but like leading ride share companies of the world, leading telecommunications companies of the world, leading companies of the world in many, many aspects, healthcare, finance, like are actively with their teams using Lovable.

54:05And it's always the same feedback, which is, yes, we may not be able to push to prod, but like our marketers are no longer waiting for engineers. There's people in go-to-market or sales or HR or whatever roles are now just confidently building internal stuff for us to manage our expenses or manage employee onboarding. There's so many use cases like that where you're seeing lovable and other tools, for that matter, being used to push things into production. To help people do this workflow that you're describing with all these empty files, Do you think you could share, after we record this, just templates, like simple templates of what these files look like for people just to look at and copy?

54:51I would literally go to ChatGPT, as I said, and brain dump into it in my, just type lovable PRD generator. You'll see my name there, right? And that I'm the author. Go in, brain dump. It will ask you a couple of questions to get clarity and just produce four files for you. and you can just go ahead and upload those. Amazing, cool. We'll link to that. So it's not just here's a bunch of files. Let's go talk to this thing. It'll generate the right files for you and then you plug that into Levelable or other tools. Yeah, it's trained. It's trained to think like I do, so yeah. Oh, amazing. Okay, that is perfect.

55:27By the way, I want to talk about how you unblock yourself because there's a whole other series of tips you have there. But I just want to reflect on... It's so interesting how, one, you're kind of from first principles learning how to build product as a PM, as an engineer, as a designer. And you're kind of figuring out a workflow where AI is helping fill in all the gaps that you don't have for as an engineer, as a PM, helping you craft PRDs and design. So I think that's so interesting. It's interesting that these functions still work and are necessary. Now it's you and AI help create all this, basically this triad that's always existed, product manager engineering.

56:09and design. And something I've always thought is that there's this question of which background will be most valuable in this future. Is it a PM? Is it an engineer? Is it a designer? My mind has always been the PM function is like their job is clarify, figure out what to build, clarify what to build, be really clear about the requirements, figure out what success looks like. it feels like that's where the skill is most needed there's also a design component of like make this look awesome and i feel like that's going to be an emerging uh that the value of that being really good at design and taste and judgment is only going to go up uh before we get to things you've learned about unblock yourself because a lot of times you know things don't go in the right direction there's a bug without being an engineer what do you do before we get there is there anything else you wanted to share around just like tips for being successful?

57:02If we measure success in the right terms, again, AI, as you pointed out, regardless of your background is an amplifier. So, you know, if you don't know what you're doing, you're just going to produce garbage faster. One thing, again, I just want to double down on is In the old world, good enough was good enough, right? Like, because even producing good enough was not easy, right? 10 years, 15 years ago, just producing was more than plenty, more than good enough. You built a SaaS, who cares how it looks like? It works. It does stuff. Oh my God, I'm so much more productive. Today, like, if good enough was here, let's say, let's visualize it for people.

57:50Like if this was like pretty, pretty bad, could be better, mediocre, good enough, world class. If this was the gap between good enough and world class, well, guess what? The gap is now this because everybody produces good enough with AI. Absolutely everyone does it. So now learning and optimizing for how do I produce world class and magic is the key lesson to take away today. As you pointed out, I think PMs are the winners of AI today because they bring clarity. If I was a betting man, as they say, I'd bet that the next class that wins are designers. Because we're training these tools to be more clear, to be better, to make better technical decisions.

58:43I don't think we will train them just yet to make better emotional decisions. And I think design is all about emotion. And that's where like the level of the skill up needs to come. That's the biggest level up. If you ask me like, oh, what is the main thing you figured out when you joined Lovable? Like what's the biggest personal upskill? Let's say it's like working with Felix, Nad, Abby, all of the people that are designers just really what moved and shifted the needle for me. I'm like, oh, so this is how world class looks like. And this is what it takes, right? You always use the analogy of like, I wanted to steal one of their designs and bring it into my lovable project.

59:25So I went into Figma and I was like, let me just take this background and just put it in there. I went in and realized that what could be interpreted as a pretty simple or rather simple gradient took 50 different layers to produce. so i clicked on that component i was like oh my god this is not three colors this is 50 colors and not just 50 colors 50 colors with different gradients of levels of opacity so i was like oh okay well that and that's the big disconnect that i've had all along so like um again if you if i'm answering your question directly of like okay what are some of the other tricks what are some of the other things design guys just expose yourself to exquisite designs follow felix from from lovable he has an amazing newsletter like oh and to teach you how to and learn how to prompt for good design learn about design styles i didn't know what baha bauhaus meant or glass morphism had no idea so like i built an app as well for that in lovable i was like i needed to build an app to learn these style.

1:00:35So now it's public. Anybody can see it. It's like some ui style dot lovable dot app. I don't know what it is. Like it has like 18 different styles and prompts to replicate them. So like learn what good design means, learn all the design styles, learn how to prompt to get them is probably what I would, what I would optimize for at this stage. Yeah. While we're on this topic, what's your sense of just engineering as a function? Do you feel like there will be a future where software engineers are still thing? Do you feel like that goes away based on your experience? It never goes away. We will need elite engineering more than ever.

1:01:08Like, because let me tell you this, in a world where everybody builds and everybody's building everything, who's doing the maintenance, right? Taining codebases, scaling codebases, maintaining projects, you know, they're still going to be a thing, definitely. And obviously AI is going to be good at this, but again, that requires a different level of skills, right? It's one skill to build something. It's a completely different set of skills to expand it, extend it, and maintain. And not to mention that in a world where everybody's building, infrastructure suffers. We all know and experience Cloudflare went down two or three times in the last two or three months.

1:01:49The whole internet goes down. Elite engineers are the ones fixing this. Lovable experiences massive amounts of influx of new users. Infrastructure there suffers. Elite engineers are the ones building the infrastructure to hold the fort, right? So I think we're going to need a lot of people with really good skills of like, hey, who actually builds the world that needs to support billions of builders now? Because everybody's going to want to learn how to build stuff. Like, how do we teach them? How do we maintain everything that they need? The hostings, the security, the email, the connectors, the APIs, the whatnots.

1:02:29Like, so I think there's going to be room for it. But I'm also on the boat of people. Like if I had an 18 year old brother and he asked me, what should I do? I would tell him, hey, go become a plumber. You know, don't don't go and get a CS degree. You learn, learn a good trade, you know, because the new generation of millionaires in the U.S. are actually electricians and plumbers and whatnot. Right. So it's like, you know, it's a balancing act, I'd say. I don't know. Like, I do still think that. good engineers with good sense of understanding where the future is going are always going to be needed and scarce.

1:03:08Such an interesting question. I think to your point, there's definitely going to be people need to keep building the machines that power all this stuff. Will we need engineers to build the actual products, the application layer? That's the question. Is everyone going to be like you? Is everyone going to be our designers just going to be all we need? everybody's going to become an engineer and let's let's let's then let's speak to that end like i'm an i feel like i'm a i'm a rapid engineer like i i'll refer to myself as a rapid engineer in a year from now because vibe coding is just coding in 12 months from now and even today we spoke about this before like how many elite elite engineers are publicly admitting they're no longer hand coding or manually coding, whatever you want to call it.

1:03:57AI writes all the code. I use the analogy here of coding is going to be like calligraphy. You writing code is going to be the equivalent of you fine printing on a canvas and people are like, oh my God, you wrote that code? That's so amazing. It's going to be so rare that it's going to become an art. It's going to be commoditized completely. It already is, in a sense. Most elite Vibe coders rely on AI. Again, it's an amplifier. So I think everybody becomes an engineer in the world of the future. A designer, a PM, everybody is a forward deployed engineer or an AI assistant engineer or an LLM engineer or a vibe coder, the term is irrelevant.

1:04:46We're all using LLMs for raw output based on good judgment or bad judgment. Oh man. Essentially, these Venn diagrams of engineer, designer, PM, they used to be very separate. Now they're converging. And people with a specific, with deeper PM, engineering design background are going to, like, they can all do the same thing, essentially. All the roles are converging. What a time to be alive. And it's so hard to predict exactly how this all goes, but it's fun to pontificate. I want to get back to when you get blocked. Speaking of elite engineers, in reality, you're still writing code using these tools.

1:05:24Sometimes code goes, things go wrong. Bugs are introduced. There's a weird database thing. There's some network issue. What do you do when you get stuck? Do you have kind of a workflow you go through of unblocking yourself? Yes, great question. And absolutely true. No matter how good of a plan you have in place, you're going to run into problems eventually. And I have a small little framework that I call 4x4, just again, analogies. 4x4, if you have it on your car, you're going to get yourself out of the mud much easier than the other way around. So in that sense, four different ways to debug. Attempt one of each only once, and I'll explain why in the end.

1:06:09First one is, again, every tool is different. I'll reference Lovables workflow, which is when something breaks, Lovables agent is smart enough to say, hey, I made a mistake. It will label that message in orange and have this little button usually, which is called try to fix. So your agent basically admits it made a mistake. You click on a button. And most times when it's a smaller issue, it corrects the course, fixes it. No problem, right? Now, there are situations, obviously, when the problem is a little bit deeper than that, right? You click to try to fix, but the problem persists. And sometimes even the problem persists, but Loggable's agents are unaware that it persisted.

1:06:54So there's no more try to fix button. Loggable thinks everything's working, but in reality, it isn't. And the culprit there is usually you're using a third-party integration. You did not give enough context to Loggable what to observe and what to see. So it can't see that the problem exists because lovable, cursor, cloud code, you name it, all these tools are good enough today to fix any problem they're aware of. Again, awareness is the key here, right? So when they're unaware of it, there comes the second part, which is, okay, I need to bring the awareness layer. And what I do there is I go and very simply open the preview, sandbox, dev, environment of my app, whatever.

1:07:35Try to run the function that's broken. Right-click, read the console log, right? Every browser allows you to just go and read the console log. And a lot of times it will record stuff. If it doesn't, you can prompt any tool and say, hey, I don't think you're seeing the problem. So instead of me yelling at you, let's find it together, right? I think it's a problem with XYZ. I want you to write console logs in relevant files so that we can monitor every step along the way. Let's just bring awareness later into the equation. It writes the console logs, you rerun it, guess what? Now you have a full history of everything that was happening.

1:08:17You copy that, you paste it inside your chat 99 % of the time. That's enough. That's already enough. AI is like, okay, got it, found it, fixed it, right? But then there are situations when even that's not sufficient. So you're like, okay, I need to go even deeper. And that's where code reviews and evaluations come into play. My go-to tool today for that is Codex, OpenAI. What I do is any build that I do, I will export it to GitHub. Lovable allows you to own your code, Cursor as well. All of these tools allow you to have a copy of the code that you can export to GitHub and then import it into wherever you want to.

1:09:01So I, you know, use Codex since beta, like import it in there. And then I'm using an external tool. So I'm like, in the first try, if you remember, like I used the tool and I was like, total vibes, I'm relying on the tool, right? In the second try, I use myself as the awareness facilitator. In the third one, I'm using an external tool as a facilitator, which is like I'll either connect to Codex and chat with Codex to then fix the problem in Lovable. I don't allow Codex to make code changes for me. A lot of people will say, why don't you? It's a good model. I just don't know its agent well enough.

1:09:44I don't want to go and use a tool that I don't know how to steer. So I use it only for diagnostic purposes. And I'll also do it manually. It's an old workflow that I had before Codex and before Cloud Code, which is there's a tool called RepoMix, which allows you to like compress every your entire code base into a single file. You download it and then I upload it to Cloud, just regular Cloud or ChatGPT. And I'm like, this is what I'm building. Read it. And this is the problem that I have. These are the console logs. Again, it's almost like having an external consultant at that point. Like you're hiring help.

1:10:22Elsewhere, because your team just can't handle it. Right. And then the fourth one is usually the best one, because one of the time when there are problems, it's my fault. Like, no matter how your ego is big, guys, that you're watching this, it's your fault. Trust me. You had a bad prompt. You premised your request in the wrong way. You just don't want to admit it or you can't remember that you did. But it's your fault. So, again, illovable and all these other tools, you can revert back. there's version control built into lovable cursor cloud code you go and say okay I tried these three things I'm just going to take three steps back and I'm going to think about my prompt a little bit more take a couple breaths go for a walk have some coffee come back with a clear mind and try again because guess what AI is just writing code very fast and sometimes it stumbles on a very small rock and it only happens then and never again.

1:11:18So you just got to make the same request again. And usually that just fixes the problem. It's just a snag. It's a syntax error. It's something minute, right? And then I do the final thing, which is this. And this is the key one, actually. When the problem gets fixed, I go into the chat mode and I ask Lolo, I say, okay, I needed to do four different things to fix this. How can you help me learn how to prompt you better so that next time I have a problem, we do it in one go? 99 % of the time, I get such a great answer that I don't have the problem of not knowing what to do next time, right? Like, again, we all need to be aware and realistic.

1:12:03These tools are so good at doing things the right way if they are used the right way it's always our fault it's a hard i say 90 but honestly it's 100 our fault right because they're good enough it's just that i'm not dynamically shifting token allocation i didn't reference the right file i didn't say it the right way for me as a non-designer i don't know any of the terminology like none of the headings and whatnot and i still don't know it to this day So when I struggle with prompts, a lot of times I use chat mode to help me craft a good prompt. Anybody can do this too. If you are just stuck, it's 10 p.m.

1:12:45and you don't know what to ask, switch to chat mode, brain dump, and be like, help me draft a better prompt. Help me prompt you better. And let the tool effectively prompt itself. A lot of times you're going to solve your problems by not introducing them at all with bad inputs. Oh my god. Everything you share is so interesting. I just want to keep digging. So just to reflect back the sequence, and then I want to follow up with another question. The sequence you go through when you get stuck, which is going to happen to everyone. One is just ask the tool to try to fix it. And oftentimes it's telling you, something is wrong.

1:13:26Can I fix it for you? And you're like, please fix. Sometimes that'll work. two is work on adding more debugging messages to the console log and this advice i love of just ask it to add more debugging lines to its own console log to help see what's going on and then you can ask it okay now that you're looking watch look at all the output of your console log see if you can help find the problem and then step three is go to codex which is which is so funny and I hear this a lot that Codex is like the most elite engineer as an AI. Karpathy tweeted this once that we had the head of Codex on the podcast too by the way that he's like anytime I have the most gnarly bug I just go to Codex, let it run for half an hour and it solves it unlike any other tool out there and so it makes sense that that's where you go.

1:14:18So the idea here is you point Codex to your code, you show it all the console output logs, tell it what the problem is and just have it go figure it out. Sweet. And then this final step is so great. And this is where I want to go. You use this as a learning opportunity so that next time you solve the problem more quickly or avoid it completely. So what you do there is you ask the agent, okay, here's what happened. What can I do? What could I have said? How could I have prompted you better to have gotten this immediately solved? Yeah. And then even more, even deeper than that is like, once you go through this conversation, you're like, okay, let me eliminate myself again completely out of the equation, because I won't remember to prompt you better two days from now.

1:15:05Put this into rules. Put this, what we just learned, into rules.md, because I'm making you read the rules every time anyways. So you might as well just record it there. So I'm not going to prompt you better. You're just going to learn that I'm stupid, and you're going to prompt yourself better, right? Again, just eliminate yourself and move the context. you solve 99 % of the problems with AI today. So the idea here is help it build its own brain and rules and way of thinking based on problems you're into. So great. Okay, so I want to come back to this point you've made a couple of times, which is so interesting.

1:15:41This idea that you watch the output of the agent to learn what is going on. This is something I've seen other people. Ben Tossel, who I think is at Factory now, shared this recently. He's also basically bytecoding all the time. He was really into no-code tools before, and now he's all about bytecoding. And he shared basically like he's learning how things, how coding works and learning how systems work by watching the agent output. And this connects to something Michael Terrell shared, the CEO of Cursor, when he was on the podcast. He had this vision of Cursor becoming basically what comes after code.

1:16:12What's the layer that we are adding on top of code where people don't need to worry about code anymore? and at that point it was like a year ago that we chatted and it feels like this is the layer is the agent conversation of what it's what it's thinking and then what you tell it back so essentially it's english in a conversation which is like it's not even pseudocode it's interesting but that's where it feels like things are heading the layer over code is just it's thinking and your conversation with it. Yeah, yeah, exactly. I mean, again, in a way, I really optimize for good judgment. And part of good judgment is it comes from, again, learning how these tools work.

1:16:55You need to know what's possible. We talked about it. And I know I may sound contradictory sometimes, right? But it's because, as you said, it's so interesting, the world we live in, that things contradict to each other. It's an advantage not to know what's possible, But then at the same time, you cannot be completely oblivious to something that's like a factual thing. So let me talk about a failure of mine that came from being delusional. Back in the day when OpenAI released image generation natively in the app, right? So you could go to chat GPT and be like, generate an image of XYZ. The whole world exploded.

1:17:38Like that was like the biggest thing ever. Obviously, first thing that comes to my mind is like, I want to build a Lovable app. I just want to build a wrapper and I want to build an image gen with Lovable. Without thinking that OpenAI did not release an API for that just yet. So I spent at least a week trying to brute force my way into making this work instead I'm just waiting for another week because a week later they had an API and I built this app in 30 seconds. The problem was that like I tried to do it when it was impossible and possible. Like so I think again you know it's just a matter of really learning what's possible through communicating with the agent player and lovable and all the other tools are agentic now which means like they don't just write code.

1:18:33They can browse the web. They can read files. They have reasoning and thinking capabilities. So that's why I'm so invested into that conversation, because a lot of times it will tell me, hey, what you're trying to do is just undoable at the moment because of X, Y, Z. So like I always use those as a learning opportunity and I just level up most by being in chat mode for planning and learning purposes. And because it just, again, develops your clarity, your judgment capabilities rather than coding capabilities. Yeah. The other point you made here that I think is really important is that over time, these tools will do more and more of what you do manually.

1:19:17I've heard this from other people that are doing this full time. Basically, Vibe Coding is just they had all these workflows, all these files, and then cursor adds them, Lovable adds them, and it's like sad, oh shoot, I had this cool workflow now, but on the other hand, it's like, okay, now it's just doing all these second - A year ago, if we had an interview, your mind would be blown. Stuff that I had to do as workarounds to address shortcomings, like, I built a very successful course on that with Starter Story, like, for a year people were like just, oh my god, you're the only guy in the world that knows this secret.

1:19:50Now, Lovable natively addresses 99 % of it. I can almost say most of the stuff that I was teaching people were like, I have a YouTube channel, a little bit appreciated, but like there's a, there's a, like a seven day learn how to vibe code with lovable series that I did in March, completely obsolete. Like it, none of it is true. None of it is a problem anymore. All the things that I was like, oh, well this is missing and that is missing. It's not missing anymore. It's natively in the product. Like you don't have to work your way around it. It just works, right? So that's why, as I say, it's the horse's analogy.

1:20:30I don't know if you've heard of it. A lot of people are tweeting about it, which is like, we started building the steam machine in 1700s, right? Took us about 200 years to build it. When engines got built and cars were put on the roads, I think that 90 % of horse population got eradicated in the US within 20 years. The person that tweeted this works at Claude Code, right? So he was like, now when I translated into AI, I was hired to do a job, technical job, technical writer, whatever. I became obsolete six months later. Like humans did not get the 20 years that horses did. The guy that was hired to do a thing is like, six months later, I need to reinvent my role.

1:21:17I need to evolve it into something else, right? So, you know, I think there's just an evolution that's coming really, really fast. But like a lot of people are scared when I'm just super excited because don't you see our roles are finally going in a direction where we're outsourcing what we hated doing anyways, right? Sitting in meetings, taking notes, doing spreadsheets, like nobody, maybe there are people that like that, but like most people don't. we're just getting into a place where we're rewarded for what really matters, like clarity, judgment, thinking, we're actually going to be paid to think longer and ponder longer because the longer idea simmers and gets broken down, the better because building it is going to be an instant, right?

1:22:08It's going to be like this. It's just a matter of you having so much clarity around it because guess what if a tool is super powerful and you give it a wrong input the output is gonna suck as well that's why like i've never become good enough at cloud code i feel because i don't start my projects with enough clarity and the tool is so powerful that like i just misdirected completely from the get-go and i was like oh shoot this is not what i wanted to do so that's why i I still see myself being good at like using tools that are a little bit on the exploratory prototyping path more than like on the path that, you know, elite engineers will use, for example.

1:22:52I love your optimism and excitement about this stuff. I think for a lot of people, say their current software engineers, PMs, designers, there's a lot of fear about the future of their careers. Are they going to be relevant? Will my software engineering skills disappear? So to follow the thread a little bit, if you were to give someone advice on which skills you think will be most valuable slash where AI will take on more and more, this kind of momentum you're seeing of where AI is filling in more and more gaps, what would your advice be of what you think people should focus on, what will continue to be valuable in the future?

1:23:31Yeah. Emotional intelligence, for sure. just understanding human nature, real life stuff. I think we're all going to get so tired of everything fake, fake images, fake posts, fake profiles, fake this, fake that, fake videos. Everything is becoming fake and AI generated. I think humans just craving humans naturally are going to want to do live stuff more. So anything human to human is going to be a big thing to skill up on, understand the dynamics, anything regarding math, if it's a math problem, I think Peter Thiel said it recently, people that just do math stuff, AI is going to come for you. Anything that's very deterministic, meaning X input equals Y output, and it's pretty clear, the line is pretty clear, AI has got you eaten for lunch.

1:24:26But if you understand how X to Y goes in human dynamic, human relationship layer, I think that's where things are going to become good. So if we translate it again to a specific skill, I'll say it again, good design, really good design, great design, like how, and when I say design, that's images, fonts as well, copy. Copy is a big one. We all now, we're like two years into AI. I'll bet you, me and you, if people put 10 pieces of copy in front of us, we could tell what's AI and what isn't in like three seconds. And we're only a couple of years in. So like really good copy writing is going to be a very good skill to have because people are just going to know after three words or three sentences that it's AI written.

1:25:12And even I don't read AI output anymore. I don't like just seeing it. I want that raw human experience. So I think human skills, I don't even know how to describe it because I don't think we're doing an awesome job putting labels onto what humans are good at natively. But I think we will. I think we will describe job descriptions better. We will have like human first engineers, I don't know, or human designers, or I don't know how to describe those roles. Same way how Karpathy coined vibe coding. I was vibe coding before he did it. I didn't know how to call it. I started Vibe Coding in July of 2024.

1:25:55And I think he coined it sometime in early 2025. So I was doing it for seven months. And I was teaching people how to do it for about three or four with courses. And I didn't even know how to call it. Because there was no name. It was like, oh, I'm just using AI to do this for me. I don't know, whatever. So yeah, I think we're going to reinvent some of the terms, roles, and whatnot. not but uh stuff that's like human to human is here to stay stuff that's like i think like oh you're you're just doing you're you're a middle manager you're a middleware person that's just translating stuff um and i can use that analogy again translators are gonna die people writing jokes comedians are not ai is never gonna be able to write a good joke never never never it just doesn't have that layer that just doesn't understand what's funny.

1:26:46Like if you ever try to use AI to write jokes, like they're awful. They're always going to be awful. But if you use AI to translate things from one language to another, it's very good at it. Like AI is going to replace translators. It's going to replace most journalists because it does good research. It can write good copy, whatever. Not elite journalism. It's not going to be able to replace all the writers. It's going to amplify great writers that can train AI on how to write books. So like somebody who's an amazing writer is gonna all of a sudden write seven books a year instead of one, right?

1:27:19So that's dangerous. If you're an average writer, be careful. There's zero comedians being placed, zero. And that's just my personal belief. AI is never gonna write good comedy. It's impossible. And so try to find your analogy in your industry. Like I just gave you one for writing skills, so to speak. So writing jokes, super good skill to have. Translating, I'm sorry to say, but like you're not going to have a job for much longer. Like you better find something else to do. But yeah, that's how I look at it. The comedy piece is interesting. I had one of the founders of the data labeling company, I don't know if it was Mercore or maybe Serge.

1:28:04And he said that I think it was Anthropic hired a bunch of National Lampoon comedy writers to help them train models. And so they're working on it. I love this strong prediction he made. I'm so curious in a year to look back and be like, he was completely right or no, they got that one too. I'll be wrong on 95 % of the things I said today, three months from now. That is the only thing I can say very, very confidently. Yeah. That seems right. Okay. So But speaking of career, so one interesting career option is to do what you're doing. As you said, this is a dream job for you. It's a dream job for so many people.

1:28:42What is kind of your path to this job? And what do you think it takes for someone to actually do this as a profession? Well, my personal path and personal journey was anything but linear, right? I've done so many things in life, like blue collar jobs, even at Subway while I was studying and stuff like that. Like I'm an engineer by trade, but not a software engineer. I'm a forestry engineer. So no coding, but still engineering is engineering. I feel you still develop certain set of skills doing that. I waited tables a long time. So you develop some human skills. You understand what people like, what they don't like.

1:29:19Like I've again, blue collar jobs, like teach you hard work. And like it's, as I said, the path was not linear, but I feel almost like a slumdog millionaire of the movie storyline, which is like everything that happens to the character brings him into a position to be able to answer the questions in the quiz better. I feel the same way of like, I've done a lot of stuff. Last seven to eight years, obviously spent in startups, but doing everything but code writing, like started in like community management, social media. Again, distribution matters a lot. That's something we haven't touched upon at all, like in a world when everybody's building and there's roughly the same amount of consumers in the world.

1:29:59How do you get in front of the eyeballs, right? And get attention, which is gonna, it is this most scarce resource and it will be even more scarce. But like going back to the bi-coder role, if somebody's like saying, okay, well, I have a pretty diverse background too and I'm bi-coding and like, how does this become a job? Well, for me, I feel like it became a job by building in public. I did chat with Elena once, only once. So like, why me? There are so many good vibe quarters. How did you pick me out of the crowd? And I think, you know, obviously, she gave me a couple of reasons, but like to translate it into like one concept, it was like I was building in public and sharing.

1:30:41I, as I said, I made a YouTube channel and I shared all the failures and all the knowledge, all the projects that I was building. I use social media a lot. Like LinkedIn was my go-to because I just have that type of cadence. As you can see, all my answers are very long. And X doesn't cut it for that. Like you need to be very on point to be successful at X. So I'm not. So I guess, you know, it's just like build in public, share your knowledge, give away all the secrets. Like there are no secrets whatsoever. If you're sitting on a good concept, you're missing out. Let's just share it immediately if you figure something out.

1:31:19I recognized that very early on. And just like I think a lot of people participate in hackathons these days, I want to encourage people to do them. Find those opportunities locally to connect with other builders. Lovable is hiring across the board. Check out our open positions. It's as easy as that, right? Just apply, really. Find companies that are hiring and hiring in different roles. And I've seen people do something. I'm going to give people a secret away. a couple of hires stood up by not sending resumes, but sending lovable apps. They built lovable apps to show why they're good fit for a role.

1:31:57And we, as lovable employees, will always open an app that uses lovable.app domain. Always. If you send me a DM, send me a lovable app. Don't send me anything long. Send me an app that tells me what you want from me, or how do you see us collaborating and working together? So there's people finding creative ways to get in front of eyeballs of decision makers like Elena, right? And I mean, skill-wise, again, we're just repeating ourselves here, but I think it's important to repeat it as many times as possible. Really develop good judgment, right? Really understand in a deeper sense how how things translate when vibe coding comes into play right there's a company out there i i'm not going to name them but like um that uses lovable religiously it's going to be one of our main case studies actually where like they actually hired vibe coders before lovable like i'm the first official vibe coding engineer at lovable like with that title but i've met people in companies where they hired them before us.

1:33:04People that are just five coders, people that just understand that speed matters, right? It still matters a lot to be fast. And like there's a company out there with three five coders full-time. All they do is like translating the old code base onto Lovable. This is bringing everything. There's CRM, CMS, everything. There are all the tool sets that they have and they need it. There are people now actively just migrating everything over. There's S &P 500 companies that are like putting lovable in job descriptions too, like saying, hey, lovable skills are, you know, recommended in the recommended tab, right?

1:33:43So yeah, to go back to the how to become Vibequoter professionally. Well, you don't need a company to hire you. You can hire yourself as a professional Vibequoter first. I think the reason why I clicked with Anton and with Elaine and everyone else, because I was already doing it. Like all I did, I just changed the vehicle, but I was already doing it professionally before I got hired. So that's kind of the key, like do the job you would have done anyways. What a mind expanding conversation. I love just how passionate and excited and motivated you are about all this. It feels like there's so many people out there right now that are so burnt out, disillusioned, scared.

1:34:30And you're the opposite of that. You're just leaning into this, just taking advantage. You're not sure where it's going to go, but following the path. Yeah, and I don't want to interrupt you, but it's because, look, Lovable specifically isn't a company. You can talk about it as a company. I don't see it as a company. It's an idea. It's a mission. It's something more powerful than the internet in my mind. Because internet allows us to consume. Lovable allows us to build. And in our nature, in human nature, is to build, to create. And the fact that there's a tool today that you can go into and dump an idea in.

1:35:14And something comes out of it. And somebody uses it and finds it useful. To me, it's just, it's the craziest concept ever. It's my only life's dream. I had my first computer when I was six. And I was convinced my whole life that I'm going to be a software engineer or that I'm going to be building. But life wasn't as simple as that for me. It was very, very complicated. And honestly, the last five to ten years, I gave up on that dream almost. I thought I'm never going to build anything. I've tried. I've tried to build with technical co-founders. I just couldn't find alignment. I just gave up on it.

1:35:55And now, like at 36, like 30 years later, I feel like, again, like that kid. Like, I dream every day. Like, it's amazing what this enables us to do. And anybody that's scared, like, just try it. It switches from fear to excitement immediately because then you see what's possible firsthand. And just go in, build something, build anything. And the fear goes away. You should only be afraid if you're doing nothing. If you're doing absolutely nothing, yes, be terrified. By all means, be terrified. And then take a step towards doing something about it. And trust me, the leap is no longer as big as it used to be.

1:36:38It's as big as you come in and you just say what's on your mind and just ship. I think a big part of this is just stop listening to this podcast go just do stuff because you actually try to all right ideally people stop right now they've heard enough I gave them what I I gave them the best that I could just stop listening and just go all right bye everyone okay I'm just joking but let's but let's we shall wrap it up um I'm gonna skip the lightning round just to keep this episode shorter before we wrap up is there anything else other than just go build some stuff anything else you want to say anything else you want to leave listeners with otherwise we'll let you go.

1:37:14Yeah. Text tag doesn't matter anymore, right? It doesn't matter. Like people obsess over, oh, is this written in HTML? Is this written in React? It doesn't matter. Like it never mattered, but now it matters even less. The end user just wants a stellar experience. We live in a world where anybody can produce good enough. So you better start learning how to produce magic because otherwise you're just going to end up in a crowd with millions and millions of others. But at the same time, if you don't know what magical looks like, don't be discouraged to start building anything and start from good enough and level up.

1:37:56The best way to level up, exposure time. Set aside more time on learning than building. Read the agent output. Learn how it's thinking so that you know what's possible. But then also go and get inspired. Follow good designers on X. Find tools where great designs are produced and follow their creators. There's a tool where I'm following just the actual person that built it because he publishes videos almost daily, 40, 50 minutes long of him designing. I want to see how a world-class designer does it. I want to see him talk to the tool. I want to see him prompt. And that's how I learned to become better at it.

1:38:41So again, exposure time, just deliberately set more time aside to learning than coding because you can code fast, but you can code garbage fast as well as magic fast. It's the same amount of time. It's you and your input that matters. Forget about decisions on tech stack. Forget about which backend they're using, which frontend they're using. That doesn't matter. Quality, taste, design. that's all you need to optimize for in the future that's ahead of us well zar this uh i think we're going to leave a lot of lines a lot of minds buzzing after this conversation you blow my mind in so many ways what a fascinating topic conversation what a glimpse into the future what an interesting point in time i'm so curious just you know in six months where things are and revisiting this conversation i really appreciate you coming on sharing all of this you're awesome Um, where can folks find you if they want to reach out, maybe ask some follow up questions and how can listeners be useful to you?

1:39:39Awesome. Yeah. Uh, so, um, I mentioned it already. LinkedIn is probably the best place, uh, to find me on, you know, I'm very responsive there. Um, if you want to follow me, I hope to re-engage my YouTube channel a little bit more. I think I have a lot of cool tips and tricks that, that I want to share and teach people how to, uh, use lovable and, and just vibe code in general. and level up and on how people can be useful to me. Well, you know, I'm very passionate about making sure that everybody experiences what I've experienced that day when I got my first prompt. And I envy the person that is going to try lovable for the first time after watching this episode, because the feeling is just unmatched of you going from a consumer to a builder.

1:40:26But in that process, there's going to be some battles to fight. I want to reduce the amount of those battles and hurdles. So if you can help me in any way, message me what could have been better in that experience, especially if this is your, you just watch this and you're like, I'm going to do it. I was on the fence and I'm going to do it. If something breaks, if something doesn't connect and relate, I need to know what that is. My job is 100 % to empower you to build the best work of your life, right? And I need to say this too, because a lot of people may be inspired, not by building or using Lovable, but rather building Lovable, come join our team.

1:41:12Again, we're hiring across so many things. I think a lot of people should feel inspired because I hope that the energy that I bring to the table will resonate. This is how it feels working at Lovable. This is how it feels working with the best minds, the brightest minds of the world. We're not number one by accident. it's not a coincidence the best people are gathering and we want you to be a part of it too so if the energy and the conversation resonates with you or if you heard about a problem today and you're like man I think I can solve it come join us help us build and shape the future of software development.

1:41:51Incredible and what's the site that imagines just the link on Lovable's website to find the open roles. We'll link folks there. Yeah. Incredible. Lazar, thank you so much for being here. I appreciate the opportunity. Bye, everyone.