The rise of the professional vibe coder (a new AI-era job) | Lazar Jovanovic (Professional Vibe Coder)

0:00 I'm the first official vibe coding engineer at Lovable. You're at the top point one percent elite level of vibe coding. It's a dream job for so many people. It became a job by building in public. You don't need a company to hire you. You can hire yourself as a professional live coder first. You've never coded, you don't wanna look at the code. Coding is gonna be like calligraphy. People like, Oh my god, you wrote that code? That's so amazing. It's gonna be so rare, that it's gonna become An art. These Venn diagrams of engineer design Air PM. Used to be very separate, now they're converging. AI regardless of your background is an amplifier. If you don't know what you're doing, you're just gonna produce garbage faster. Feels like an emerging core skill is learning clarity in the ask of the AI. I like to use the Aladdin and the genie analogy. You rub the lamp, a genie comes out, I'll grant you three wishes. The first wish is I wanna be taller. Genie makes me 13 feet tall because I was Is not specific, eh? I just don't understand what do you mean when you say you know what I mean? So you need to be specific. I'm optimizing a hundred percent of my time today on good judgment.

1:03 Clarity. Quality Taste. Today my guest is Lazar Jovanovich. Lazar is a professional vibe coder.

1:13 He gets paid to vibe code all day. and build internal and external products. This conversation is going to blow your mind in so many ways This is not only a really interesting new career path for people to consider. If you listen to what Lazar shares.

1:28 It's also a really important glimpse into where things are heading for tech roles. I found myself thinking more deeply about the future of product management. and engineering and design during this chat than I have in a long time. We also spent a bunch of time on Lazar's best advice as an elite vibe coder. For getting the most out of AI Tuls.

1:48 He's got a bunch of really interesting and useful frameworks I've not heard anyone else share that will immediately level up your success using all the latest AI tools. This conversation is going to expand your mind in so many ways, I cannot wait for you to hear it. If you enjoy this podcast, don't forget to subscribe. And follow it in your favorite podcasting app or YouTube. It helps tremendously.

2:09 And if you become an insider subscriber of my newsletter, you get over 20 incredible products for free for an entire year. Including a year free of lovable. And Replit, Bolt, Gamma, N8 and Linear Devin, Postalk, Superhuman, Descriptor, Flow Perplexity, War Grenola, Magic Patterns, Drake Catch, IPRD, Mobbed, and Stripe Atlas. Head on over to Lenny's Newsletter.com and click product pass. With that.

2:32 I bring you Wazar Yovanovich, after a short word from our sponsors. This episode is brought to you by Strella, the customer research platform built for the AI era. Here's the truth about user research. It's never been more important or more painful. Teams want to understand why customers do what they do. But recruiting users, running interviews, and analyzing insights takes weeks.

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3:45 Today's episode is brought to you by Some Sorrow. If you listen to this podcast, You know that we spend a lot of time talking about building things that sit on a screen. onboarding funnels, mobile apps, and checkout flows. Samsara is building products for the physical world. First responders racing to emergencies.

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4:23 and answers questions like, did that truck driver break abruptly because they were distracted? Or was that a heroic act? If you want to ground LLMs in messy real-world telemetry or solve edge AI constraints at a planetary scale, Samsara wants to talk to you. If you like playing with enormous data sets, moving fast, and working in small teams, come help build the technology that makes the physical world safer and more efficient. Visit Sumsara.com slash Lenny to learn more. That's S A M S A R A dot com slash Lenny. Lazar, thank you so much for being here and welcome to the podcast.

5:00 Thanks for having me, man. Okay, so I had Elena Verna on the podcast. She's had a growth of lovable. She mentioned that she works with a professional Vib Coder. You I had so many questions. I almost wanted to like go on a tangent with her to try to understand this role. Instead, I asked you to come on the podcast.

5:17 Uh, there's so much I wanna talk about. I wanna talk about just this career path. And just how you got into it, how other people might get into it. Where do you think this is all going, this whole bite coding thing? Also I wanna get into what you've learned about it being successful.

5:31 Using all these AI tools because this is Your job. First I wanna just start with understanding this actual job. Just like what is it that you do day to day. You're basically being paid a full time job to vibe code. Incredible.

5:44 What are you responsible for? What are you doing day to day? Well, as you said it, like it's The it's a dream job, right? I get paid to do what I would have done anyways, right? It's the best job in the world. I get to Use tools like Globable.

5:59 Every day to push projects to production, whether for internal or external use. Those could be ranging anything from like different templates. On

6:09 marketing side, sales side, or whatever, or they can be as deep as like building some internal tools with a lot of integrations and connections and whatnot, right? So The surface area that I cover is pretty wide across all departments, because it's such a flexible role and it complements so many things. Right, it it's it's an idea's role. A lot of people have a lot of great ideas. But they don't know how to build them and or they just don't have the bandwidth to

6:33 And that's where I step in today to make sure that these ideas come to life fast and with quality and security that they should have in order to be available for users in production. And one thing that's really interesting here is it's both internal and external tools. A lot of companies have Someone building a bunch of internal tools using AI.

6:51 you ship stuff that's actually public and and and like sort of a product level products. Yeah, definitely. Like some of the stuff that I've shipped that are public are like when we launched our Shopify integration. most of the if not all the templates that users were remixing were built by me, right? So stuff like that. Or like the merch store,'cause we wanted to obviously prove the concept that hey

7:12 lovable and Shopify just works. It's so simple anybody can do it. I've I coded our merch store. So All the merch, including this shirt that people were buying. Online? uh they would have bought it well from a store

7:24 That was built by me. But then on again on the internal side we We wanna track a lot of things. Like one of the The cool things that we wanna Uh build now, for example, like

7:34 feature adoption matrix. Like if if we Build the feature. How many people are actually using it, adopting it? Like And That's a pretty custom build, right? We have a very custom stack.

7:43 We're building custom features. There's nothing out there. Then I could just pick off the shelf and build Or adopt faster than I would have built it myself. Like at this point. I'm at a stage where like if it takes me An hour or two hours to set up like a

7:59 Big Enterprise account somewhere, I'm just gonna build it myself faster. So you know, I'm uh I'm in that position of like Build versus buy. I I'm I'm in the build. boat, uh, so to speak. Yeah. And then who do you report to? Are you kind of this rover that helps wherever or you would the win a specific team?

8:15 I I'd say probably closer to the former, right? Uh I've started in growth, right? Elena brought me on uh early on and you know, to to c'cause she has so many great ideas and like she just needed somebody with the right type of monst mindset and velocity and ownership to just Take him away. Build them up. Get him into production, whether they're like

8:36 based on education or or or anything go to market or whatever. But then obviously the When you're Able to ship fast. Everybody needs that in an environment that we as a company are now living in, which is where the fastest growing startup in history. So every department needs a Lazar.

8:54 Now or yesterday So now I'm like shifting a little bit, I guess, into Some of the go to market rules and even building some again internal tools for enterprise T, but I'll I'll I'm I'm working on some community tools as well right now as we speak. So I'm a little bit all over the place, but I kinda

9:09 thrive in that environment where like I'm given А роф концеп, а роф ідея, і нам Tasks to bring it to life as soon as possible. Okay. I'm hoping with this chat we create a lot more Lazars. And I wanna get to the career path, how you got to this and what it takes to actually become a full time bike coder. But I wanna start with

9:28 Because you do this full time, you're You're at the top point one percent elite level of vibe coding. You're doing this full time. They hired you to do this as a job. I'm so curious what you've learned. What are some pro tips that you've developed for being successful with AI tools lovable, and also just more broadly.

9:46 What are maybe two or three things you've learned that have That help you be really good at. To this job. The first understanding that I had very early on, even though I just in full transparency before we begin I don't I don't have a technical background. I never

9:59 wrote a single line of code in my life. Almost like I've I've Yeah, written a couple of console logs manually, and that's about it. Right. So like I I'm very much lean on to AI assistance. Let me actually follow that thread because that's such a good point. And something that when we were chatting earlier, you pointed out.

10:15 Your feeling is it's actually an advantage to not have a technical background when you get into this space. Yeah, yes, I I honestly feel that it is because People like me Don't know that they Are not supposed to be building XYZ, and that's how we actually are able to build it.

10:32 Um let me give you an example. Like Six, seven months ago. somebody in our community was like, Oh, I wish Lovable can build Chrome extensions, right? And then folks that are not technical were like, Well

10:43 Why why is that not possible, right? And then people that are technical start explaining to you all well, you know It's a React, it's different stack, it's this you and People like me include myself, we just call in. And like build me a Chrome extension based on this app. And I was able to do that with Lovable.

10:59 There were people that were able to build Desktop. applications on lovable. Again something that Shouldn't be possible. It simply is, right?

11:08 Community manager with me. At one point she was like building this presentation deck for Or something she's like Would it be cool if this was a video? Right.

11:17 And then she just prompted her way into building a v generating an actual video inside Lovable before that was available. Now that's a feature. Now you can prompt Lovable to do it, but back in the day when she did it. Even I thought it was impossible. I never tried it. So I think that's the advantage that we have over people that are technical. We we're just coming to this Completely unbiased. And very

11:40 Positively delusional. Which I think you have to have. When working with AI tools, you have to come with this delusion. That Absolutely everything is possible until proven

11:51 Wrong? And like That's just the the pursuit that I have in my mind, uh that is helped me. Among other things that we'll chat today. I think to excel in this role that that I have at La.

12:02 Two of the I think concerns maybe traps people that don't have a technical background fall to in theory is One is If you get blocked.

12:11 It's not obvious how to solve a problem. And two is just are you building like uh this like teetering slop that will collapse someday'cause you don't know. You know, system architecture, you don't know if this is gonna scale, the sorts of things. So

12:25 Coming back to ha what you've learned about how to be successful and build successful products. Talk us through just things you've done and things you've learned for how to avoid those sort of things and what you do when you get stuck is is one example. I I'm happy that you mentioned like those those limitations. I have some other ones that I want to bring in, but let's address this one first, which is of the most important one, and that is You have to be self aware.

12:46 Right, I I didn't come into this Yes, I am delusional, as I mentioned, in the sense that I I just don't want to accept something's not possible, but I'm also well aware that I need to be better. In order for it to become a reality.

13:01 From my own point of view, in my own sake. So I understood very early That Coding is not the problem that we're solving for here, that the problem we're solving for is clarity, right? Like

13:12 The output that AI can do is much faster than human output anyway. So like Very early on, I started leveraging chat mode and uh to this day I can say I spent Eighty percent of my time in planning and chatting and only twenty percent executing the plan.

13:30 Actually, right. I'm optimizing for the right kind of speed. Most people optimize for the wrong one. That's the first lesson that I learned. Literally on day two because I just I came into Lovable. That was my first exposure.

13:43 to to to this, I've tested and and played around with all the tools, obviously, but like Whether somebody's doing it cursed or clawed code, doesn't matter where you are. the problem remains the same. You need to be clear on what you want to do and you need to know what you're doing. Because These are still just tools. Yes, AGI is coming, but it's not there yet.

14:03 So like until it's here You're still steering the ship. In order for you to steer the ship, you kinda have to know The instructions, right? And The best way to learn is by building, but treating these tools almost as

14:17 technical co-founders and educators and learning while doing And religiously reading the agent output, not the code output. I don't care about the code. Like the syntax is not of my interest. It's what the agent tells me did that matters to me.

14:33 I put a lot of trust in in in LLMs and AI these days. And I I understand that there meet may be some people that that are not as confident as I am. I just feel that the models to date R Good enough. For me to trust in their

14:48 syntax output. However I'm concerned about the agent output and because of the Two limitations that I want to tackle. Tac along next, right? The first one being Yeah.

15:00 The the there's a limitation when you work with LLMs. So that's there's a machine level limitation and there's a human level limitation, right? The first one is There's something that that is known as the context memory window, right? And for non technical people, I like to use the Uh Aladdin and the Genie analogy when I explained, right? It's it's very simple. Everybody knows the storyline.

15:21 You you rub the the lamp, a genie comes out and tells you, Okay, I'll grant you Three wishes, not three thousand wishes, not three million, just three. At a time, right? to me when I translated into working with AI That simply means hey

15:36 I can only make so many requests. with in a request at a time for AI to be able to Listen? Understand what needs to do.

15:47 scope it, do the research, read, like take all the actions, all the inputs and ingredients that it needs to produce a high quality output. Right. So that's the first part. Understanding that there's a limit. And it's denominated in tokens. Maybe that's gonna be different. A year from now.

16:03 But today There's a token limitation, I'll take an arbitrary number of one hundred thousand tokens, for example. So when you make a request A part of those tokens is A I spend to read stuff.

16:13 Another two print, the web. Another two. Uh think And then another to execute the call. Right.

16:21 Then there comes the second limitation, which is you. Me and you humans. Which is Let's go back to the uh analogy of the GD and the Aladdin. I asked the GD for the first wish and the first wishes

16:32 I want to be taller, and guess what happens? Jeanie makes me Thirteen feet tall. All of a sudden. I can't sit in the car. I can't get into my house. I'm a I'm a dysfunctional human being. Right.

16:43 Right. Because I was not specific. Right? Like So the part that we need to optimize for today It's gonna get better, but today it's still not there yet. Is that A I just don't understand

16:56 What do you mean when you say You know what I mean? Like you do when I tell you that we as humans don't We have I'm thirty six, so I have thirty six years of experience of human Uh living as a human to know what you mean, but AI doesn't have that.

17:10 Right, so you need to be specific, you need to provide references, you need to provide the right context. So what I've learned Is how to combat that part. And I think You know, because I can't control the first part, which is the token memory window, the quality of the LLM models.

17:27 You are A hundred percent control of the ladder. And that's what I I want to dive into. uh today as well and just try to teach people, okay If I'm

17:36 The malleable part. How do I how do I fix that? Right. I think that's the the key lesson here. This is so helpful and I love this metaphor of the genie. The this piece about clarity is such a thread I've been noticing across People that have been successful using AI tools.

17:52 And if Feels like an emerging Core skill. is learning how to be Learning clarity in the ask of

17:59 The AI. Do you have any advice or anything you do there to help? B. Better at Being clear with what you want.

18:07 Yeah. So first of all, you need to be, as you said, yourself right now. You need to be good at understanding what clarity means and how to translate it. In my terms, Clarity means

18:20 Um Understanding What Tasteful looks like. What's

18:26 Good. Enough versus what's world class, what's magical. And I developed that through something that I heard from you. You you mentioned before, which is exposure time, right? Making sure

18:38 That I'm exposing myself to content and to people and to relationships or whatever that are gonna help me to level up in that domain. Again, it goes back to self awareness. Like I knew When even before I joined Lovable, I was like, Okay.

18:53 Even before I started using loanable or any I tools, first thing that I knew was like I don't know how to code, right. So My first thing was like Oh I can build.

19:01 Wow, amazing. But a week later it was like Oh, I can build, but I'm not fast enough. So I optimized for speed. So I was like, Oh, I can build and I can build so fast. And then two weeks later I

19:13 White development cycle that I'm in. began and it's still ongoing, which is Wait a minute, should I have I even built this in the first place?'Cause like Uh

19:24 Once you figure out that we solved For the how which is Use AI assistant or rapid engineering, call it whatever you want. You can call it vibe coding if you want to. But like We solved for that. Now we we gotta solve for everything else. And everything else is what matters. Good design.

19:40 Good taste. Good user experience. Like P. W when you think about who you're building stuff for with these tools, you're building it for humans. Humans are emotional

19:49 Beings. And we all make our purchasing Or any kind of decisions. on an emotional basis. Right, side.

19:56 I think that the the core skill there. Today isn't again. coding, although I have nothing against traditional engineering and and I'll and I'll say later why.

20:07 I'm actually a big fan of it. Of the leak engineering, but like People like me, people watching that are like Should I Start learning how to code.

20:16 If you haven't done it yet. I I'd honestly say no. Like You you're you're optimizing for the wrong skill set. We won't be rewarded in the word of AI. For

20:29 Faster raw output. We will be rewarded for better judgment. So I think that better judgment comes with again to go back to your question, like How are you solving for that? How are you solving for this? Well

20:41 It starts with exposure, so deliberately exposing myself. to people and resources that I n know I need to consume. To level up. And then A lot of it just comes from building as well. You know, if we're honest, like it's a muscle. Everything is a muscle. You need to practice, you need to see.

20:57 What's possible and you know Though that's where some of the techniques and mindset shifts that I wanna also use an opportunity today to ingrain into people's minds. Later down the call may be uh useful. Uh okay, so what I'm hearing here is

21:12 Uh, because coding is now essentially a solved problem, I love that you don't look at the code. You don't even Like you've you've never coded, you don't want to look at the code, you don't care about what's happening there. the instead you're watching this age now but I wanna actually ask about that. But what I'm hearing here is the Areas you are

21:29 Investing. In building in yourself. is at the front end clarity around what It is, and we're and I wanna hear how you actually do that. What you do there? You have a really cool system there. And then there's like

21:40 the taste and judgment of knowing is this the thing I want? It feels like those are the two sides now that are more and more important. And on the taste judgment side you share this concept. This is something Gier Maraush uh shared on in in our conversation, this idea of exposure time, exposure hours. being exposed to great stuff.

21:57 Here's a great user experience. Here's a great onboarding club. Uh, I don't know, website. So I li I like I I really like that advice because ac it's so actionable. Okay. I'm just gonna I'm gonna spend more time with stuff that's great to inform my My taste and judgment.

22:10 And then on the clarity piece, uh I want to get let's actually talk about that just What do you What do you do there to be clearer with lovable and other AI tools to help? It build the right thing.

22:22 This is the first mindset mindset shift that I wanna Put into people's minds. Right. If you just have a vague idea, let that be your first version of the project. Open Cursor, lovable, whatever it is that you're using.

22:35 And just input a brain dump prompt. Right. Yeah. Talk into it. lovable specifically, I don't know about the other tools, has a really cool voice function. You click it.

22:45 Just dictate The hell of it and just Press ten, right. Don't even wait for it to finish. Open a new window. Again. Lullable.dev.

22:53 In here, you're like, okay. Yeah. As I was brain dumping I think I found a good thread. Right.

23:00 I think things are getting clearer. So let me start another project. Now with more clarity, more deliberability. Like I know Which features I want, which pages I want. Maybe I can even find a good reference. Maybe I can go

23:14 on Mobbin, maybe I can go on Dribbble, maybe I can go wherever Get a good screenshot, get a good animation. And attach it'cause most of these tools accept files as a part of the input. So like You have the second project started.

23:29 Now things are even more clear. Now you you you expose yourself to quality and now you're like Well What if I What if I found a template? that actually is already out there. Why reinventing the wheel? I'm building a platform that somebody else built.

23:43 Why not expose AI to what quality looks like, right? So what I'll do is I'll I'll go to and find a library. When he first is them. Or Uh um

23:53 Or a dot build, or like whatever places which Allow me not to export Screenshots but export code snippets because Guess what? Even though English is The number one programming language.

24:06 lovable and all other tools still communicate in code the best. If you wanna get Pixel perfect results. Just give them code. It will it will interpret it better than your English or Spanish or whatever an language that you use. Uh in these tools.

24:21 So that's the third way. You're like, okay. Now I'm even more deliberate. I'm not I'm not even uh going as as Why this like giving it vague concepts. I'm giving it code snippets. Like I want this exact design. I want this exact type of functionality. So that's your

24:37 Third project and then By the time. Ю Do all of these three. You're already at a level of clarity that you wouldn't have if you just sat

24:47 We're Uh an MT piece of paper or Maybe I maybe chatting just with Chad GPT but not taking action. I think Taking action is so so cheap these days.

25:00 And free, by the way. Like all the tools I mentioned have free plans. Like most times you you would be able to do this without spending any money at all. Just by starting multiple projects because Guess what, that doesn't also call cost anything either? Uh or doesn't incur additional cost except for builder credits. You're gonna get three

25:20 four, five, six different concepts that you can compare. As you're comparing them. Clarity just keeps coming. Like And things get better and better to understand and

25:30 You're also solving for one big problem that you mentioned. You used I the term AI slob And I like it'cause a lot of people when they say yeah, I slop, they don't refer Yeah.

25:40 a c uh beautifying the code, but beautifying the design. Right. This process that I just mentioned actually gives you four or five different design options. And In the long run.

25:52 Save you massive amounts of credits. Because a lot of people obsess over The concept of oh When I give them this This hack they're like

26:01 Oh, but that doesn't that cost more? I'm like Yes, up front. It may cost a little bit more. In the long run, if you really want to finish this project, you're actually saving hundreds of credits and maybe even hundreds of dollars. Not to mention the amount of days simply because you started from a point.

26:16 of better clarity. And better refinement process. Right. So like That's the first step of solving for clarity. There are more. Right, which is the s the the the second layer, but I I assume you may have some questions on this one.

26:34 Uh, it shows you the power of having someone come into this world without an engineering background. Build it five times in parallel. You ask AI to try all kinds of stuff. Like this is not How someone that has been a software engineer or a PM

26:49 Or designer would approach though. So your advice here, which is so fun. Is As you're getting started with a project. Just run five different approaches at it.

26:59 To start. One is just brain dump. Here's what I'm thinking. Here's a general idea. Like you use Whisperflow or use the built-in. Uh Mike. 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 out.

27:14 mock design somewhere online. The sites you suggested were Maubin and Dribble. Those are the two that you go to? Yeah, most times, yeah. Okay. And then the Fourth. These are all in parallel. It's great.

27:25 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 kinda what anything you got, yeah. Here you go. Okay. And then cool. Here's the prompt here. Make me s what I want. And

27:43 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's like Oh no that's not what I mean. Let me Try it again. And then two, as you're pointed out. You can pick the right direction.

27:56 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.

28:08 Uh This 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. But I what I'm feeling is this is where you could save the most money because if you get a Correct. In the beginning.

28:23 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 I'm actually going against what I should be saying. If I was thinking about lovables, 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 they want and then you you know it it's my personal mission that resonates with me'cause if

28:50 If there wasn't lovable Um I would have never built anything. potentially in my life, and I don't I don't think that that would have been a fun life. To live.

28:58 So um You know, I I guarantee people, like I've tested this framework with many people and everybody's telling me the same thing. Eye opener. So simple yet. Unintuitive as you said. Even though for me it's kinda

29:11 I don't know. Yeah, as you said, I I attribute it to a 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. It I was just like I'm waiting all this time for these agents to finish. I might as well start another project.

29:29 And another one, and another one. And it's also a productivity hack. Like that's when people ask me like Wow, how do you ship so many things? I'm like, I never built just one project at a time. I built five or six. I have six. Lovable tabs. Just switch between them.

29:42 And that's the next hack that I want to talk about, if you allow me, which is Then the question in return is the obvious one, which is How do you context switching? Like you talk about context so much yet You're a keep switching between Fs. How do you manage To do it.

29:57 And do it in a way that's productive. You're and not produce. Bad code or bad product. That's How I solve for that L M problem. Again. the Aladdin and the magic lamp and all that.

30:09 Which is If there's a limited token window. How do I make it dynamic? And what do I mean by that is this. If you just go and you prompt and you prompt and you prompt and you prompt, you'll realize that no matter what tool you use.

30:24 The memory just isn't infinite. Right. By the time you reach message number ten, fifteen, twenty, thirty, forty Snippets of early messages. sort of get lost in the translation because

30:37 Agent is optimizing for speed. Right. 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.

30:53 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, so let me treat Lovable or any other tool.

31:07 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

31:18 Like I would do the four parallel builds, like let's continue off of that example. very quickly after you've you've built hundreds of projects like I did, like you you you see the winner like the winner is so obvious it's not even a 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

31:40 I either ask the tool that I'm using Or I'll maybe let's say go to Chad GPT or whatever. And ask the LLM to produce a series of PRDs. What PRDs are for again people that are not familiar with the terms, they're a project Requirements documents or for me.

31:58 I call them like sources of truth, right? What sh 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.

32:12 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

32:21 how we are gonna build it in this is the sequence, right? It's very important to me again going back to Quality. Taste. human nature

32:30 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.

32:43 And then finally something that just circles it all around, which is like Okay. Well we know how things look. And when we know how we're building it. How does the user journal look like, right?

32:53 I use the right 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. So I built At least four PRDs.

33:04 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

33:18 planning this part out. Like Documentation. And breaking things down. Because That's how I'm setting the course. Like everything's gonna be dependent on on this particular part of the process.

33:29 When I'm done doing that, I build one final document. Which I call either plan. Or tasks that Md and dot Md part is um Uh you know, uh Markdown basically I'm just

33:41 using markdown format because I've learned that AI likes to read markdown. And what that serves as a s it serves as a source of truth on like actual tasks and sub tasks that it will need to execute to get to the finish line. Right. And then there's the final final layer, which is depending on what tool you use.

34:00 Cloud code or or or cursor have what's known as rules.md or agent.md. What you're basically doing with rules or agent files. Is Your 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.

34:20 Right. So in Lovable there's a there's a m s separate menu for that in your project settings where you can define project uh uh knowledge. And usually when I'll say hey Read all the files before you do anything. Like don't do anything before you read all the PRDs.

34:36 Read tasks.md. To see which task is next. Then execute on that next next set of tasks. And when you're done, tell me what you did and how I should test. And that's where that conversation about I religiously read the agent output comes into play. I've told the a I gave the agent everything.

34:54 All the tools and resources that it needs to succeed. I give it the rules, I give it the docs, I told it what to to do with them. And at that point, I'm just sitting. And reading.

35:06 Oh I don't prompt anymore. And from that point on, I can switch as many windows as I like. My prompts have become Proceed with the next next task. I don't need the context. I outsource that.

35:17 And delegated that to to the agent. The agent need c 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.

35:30 So that We shift that token window it it uses and how it uses it over time. But I'm not From thing. I'm not Interrupting the flow. Yes, I'll go in, test, maybe put a prompt in here or there, but that's how I can build five projects

35:45 Simultaneously. And never lose the productivity part. Which is again. As I said. I do this today manual.

35:53 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.

36:04 To bypass the shortcomings. Of Human nature. And LLMs. But I'm optimizing a hundred percent of my time today on

36:13 Good judgment. Clarity. quality Taste. Good copy.

36:18 Good fonts. Like P people don't talk about fonts at all that that work with AI. They're like sixty percent in my mind, maybe even more. in how your output's gonna look like. That's my obsession.

36:31 Like I don't obsess over these things that I'm talking today because I know what's coming. Like The agents are gonna get better, the models are gonna get better. They're not gonna need me. to extend the context. They're gonna do it themselves. So for me

36:45 The skill that I optimise for is Is the the one that that like Requires better Decision making. Rather than

36:53 better output or better uh alignment. Oh my God, there's so much here. This is so awesome. Okay, so Essentially what it what's happening here is

37:04 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

37:15 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

37:26 What people fe may some people may feel are not. Thank you sophisticated tools that can build incredibly powerful things. Like you can do all a lot of this with tools like Lovable, like have plans and rules and

37:37 M D 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.

37:49 And A key part of this that you This three wishes rule is really important. The reason you're doing this in a in large part beyond just being really clear about the plan is

37:58 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 step.

38:11 Right. It is, yes. Because again, if Let's say you didn't do this. Let's let's hypot let's talk about you ignoring this and like I I just wanna buy my way. Okay, great, no problem. You work, you work, you work.

38:23 At one point. Something breaks, right? You haven't documented anything. There's not there's no reference points. You report a problem.

38:33 You're not e referencing files or architecture at all, you're just describing the issue. Here's what's gonna happen. Any tool. Lovable or

38:43 Cursor or plot, whatever tool you y you talk about is gonna do this. It's gonna 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 when you first start, you have like twenty files.

38:56 It's it can read twenty files, but what what happens when you have I I'm just building a project right now that has like sixty, seventy edge function functions, right? What happens then when I say this broke and there's no reference which edge function does what? Guess what? Lovell is gonna read all of those.

39:14 And it's gonna consume eighty percent of the token allocation on rating. To get clarity. Leaving only the final twenty percent for thinking and executing. What I'm guessing, and I can't prove this, an LM expert in the comments may say that I'm wrong, but this is my

39:30 Best Guess as a non educated person. The f These tools are very obedient and very agreeable. They're gonna lie to you.

39:40 They're gonna tell you that they fixed the problem. Even though they didn't. They're just gonna try to ha 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

39:52 People blame the machine. To to an extent, I I 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 into the mud, right?

40:10 And and you know, obviously I think we're heading into a world where AI's more honest than obedient and saying, Hey I only partially fixed this. You know, I You did not give me Enough of a context.

40:22 Right. The bigger mistake that people make then is like They trust the tool fixed it. They test, they see it, then they get mad at it. Start cursing and yelling, as we say.

40:34 And then it gets even worse because guess what? Another Bad trade of AI is. E D that's it it's best not to hurt your feelings.

40:43 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 thirty percent of tokens trying to come up with an apology. Right. Again. I'm not educated. But that's if you ever read like a stream

40:59 of Chad GPT's thinking. We in thinking models, you see exactly what I mean. Like When I insulted I see that the first message is okay, the user is mad, so I need to think of ways how to reduce their anxiety or whatever. I'm like oh man, I I just fell for the

41:15 the the worst thrink of the book. I 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 my advice for people is like

41:29 Yes, vibe your way for fun and vibe your way w while you're prototyping,'cause that's the exploration part. I love that part. But when exploration is done. Please, please, please. use referencing documentation Uh uh use

41:45 All the agent files that you can. Because the that That Tolkien. Allocation is so scarce. Like

41:53 It's gonna get expanded over time. Things are gonna get cheaper, faster, but right now it's still so Valuable and precious you really need to make sure that they are allocated in the right direction. This is hilarious.

42:05 I think the uh 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 You know, by wishing. Uh

42:17 It'll do the wrong thing. B as give it as much context about what you want it to do as possible. And these files we'll talk about Broke. Uh

42:26 Right after this. But uh The idea here is just like laser Show the point the laser at 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

42:39 Tokens that'll fill the context window. And I remember at one point you mentioned before this recording that it because it starts to run out of space in the in the context window, it start it just like the solution ends up it doesn't actually work that hard on figuring it out in the end, because it's spent all this energy on Reading and thinking and then it's like okay, here I'll at the last second, here's the solution.

42:59 I think it just picks the first thing and it thinks it's broken. That just again. This is uh me completely uneducated coming in 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.

43:18 Maybe it's aware that it's running out, maybe it isn't, but either way I've 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

43:33 The other way around where I'm like Spending so much time. Finding a right file. Referencing that file. Like really?

43:40 Putting in the effort Of hand holding 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.

43:51 And now I'm gonna actually fix over and over and over and I've seen that because Again. All I do is read the the output. Agent makes me learn how to use it.

44:02 Bye. Then so people read I don't know what people read, but I all I read Is the output. Like I don't read the code and it's later down the road,'cause like I I know that it can do that much better than I can. Again, I feel

44:15 If There's a good quote I've read. I can't I I'm I apologize to the author'cause I can't attribute it off the top of my head, but it's like The ceiling on The AI.

44:24 Isn't the model intelligence it's what the model sees Before it acts. Right. So that's the ceiling right now. Like what do you 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.

44:41 Before it makes score edits. Yeah. Coming 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 list it all these kind of file these M D files essentially that you're building over the course of a day before you start

44:57 Actually building the thing you had. Design guidelines, the user journey, tasks. uh agents M D, rules M D. So you wanted to just like move one step forward. and be better at this stuff. What are the n what are the files you'd create and then What do they roughly look like? What's inside these files?

45:12 Yeah. So the master plan is the first one, which is like it's it's a ten thousand foot overview, right? It it it really high level explains The intent. uh that I have with this app.md is that what you call it or 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 him to to you feel. And a lot of times in the master plan I will reference the other PRDs. I'll be like

45:38 The design needs to feel modern and slick, but for a exact You know. Parameters consult and read design guidelines. Dar M D.

45:47 Right. So I'm using just the master plan as like This high level overview. Right. to to get the agent into Oh, okay, yeah. We are building

45:56 X Y Z. Right. Um Then there's the implementation plan because you know, there needs to be some order. Yeah, yeah.

46:04 If you just like dump stuff on top of each other without any order. Um you're never gonna get to the finish line. And this is tasks.md, is that what you call this? No, that that's the implementation plan. Yeah. Okay. An implementation plan is kind of s uh In service of the future tasks.md?

46:21 If that pay 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.

46:32 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 it just goes into the

46:44 Uh explaining of like oh well. If we're building this, I think We should start with the back end. And we should start with tables and then later authentication, and then after that, we're gonna bring in the API, and then after that, we're gonna do this. It's like again just. Think of it as having got

47:00 I'm an ideas guy. I'm sitting with a technical guy. It's me and you. We're building our startup. You I know you're a software engineer by background. And I'm telling you my idea. I I'm giving you the master plan and you come to me back and you're like Okay. If you wanna do this, it's doable. Here's how I would order it. Like you have

47:15 A roadmap? You're not You didn't open your linear and started writing features and and uh RFCs and whatever. You're just high level talking about the the order of things. And then Me and you again as two co founders, we talk and say, Okay, well

47:29 If we agree on this, like how 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 like I I like to see

47:41 uh um lovable or any other tool. Chat GPT is good at it. I even have my I built like custom GPT, so if people wanna start somewhere before they even get into any tool. Uh they can go to Chad GPT store. And For GPTs and just type lovable

47:57 base prom 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? So I like to see some elements of CSS.

48:12 in in design guidelines'cause you know you With design is a little bit it's a little bit tricky. A I Yeah. sometimes over creative. So I uh that's where I'm doing a little bit more Technical steering, right?

48:23 Um and then finally it's just the user journeys. Just like if we know how things look like, if we know how uh they feel if we know what we're building high level like high level, just very high level again. How do people navigate? What what are some of the the features in there, you know, and stuff like that. And then tasks.md get into the nitty grade, like oh If you want these user journeys and you want the back end built first, here's a set of tasks that I need to do. Like it just takes that.

48:51 as an input. I'm just making the tool Do the Do that, you know. That Gritty work that

48:58 humans used to spend so much time on like I feel like with With these tools, we're all becoming product managers on steroids. You know, like we're just leveraging AI, but like good product managers, I think are not compensated for writing good PRDs, they're compensated again for good judgment.

49:15 Right. Somebody else can do the the writing. You As a as somebody who directs and builds this product product you need to know Again, what what

49:25 What's gonna be useful, what's gonna be tasteful, what's gonna be Something that actually moves The Neil. I will say one thing though. Just because I put so much emphasis on like oh

49:37 You need to acquire taste. Oh you 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

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50:53 Go to workows dot 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

51:13 A I build this thing that would have taken Somebody weeks. Months right. Like The amount of investment to achieve this thing is absurd. RY

51:24 Also, this shows you just what professional vibe coding looks like. You know, everyone imagines by 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 girls' problems that lasts that, you know, scales. This is this is how you do it. If you really want to do this as a

51:44 As a real 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 there's obviously a ton of value in prototyping. Like There are a lot of people maybe watching this that are like okay, I wanna use Lovable at work, but I I can't or whatever, you know, there's

52:00 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 prose, I think. is the one of the best use cases. We

52:14 Uh our motto for twenty twenty five was uh 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.

52:29 Go into Lovable and build the prototype in thirty minutes. And just hand it over. Like and I have a real like job that I held before Lovable. That's exactly what happened. Like this time. Last year I needed something built.

52:42 Enterprise great, really. And lovable. And myself were not there yet to build it at that point. But I have I had a team of engineers that I worked with.

52:53 I built the prototype in four hours. And they actually were able to replicate it six to seven months later into production with with connecting all the Pipes and everything, but like If I had to describe it I would say took me it would take me at least a week or two just to get the words out there.

53:10 I just sat and built it in four hours, and that's like Lovable January of last year. This lovable today, January twenty twenty six, is like Ages ages ahead.

53:22 with functionalities. Like it it's so much better. It's not even a contest, right? So I think now When our stage where like, for instance, there's I'd say at least To best of my knowledge.

53:34 At least half of SP five hundred companies have people working in them that are using Lovable. To some extent. Right. And we have a lot of

53:43 Enterprise companies that are actually on enterprise plans with lovable that are creating super meaningful projects like Uh I'm not gonna name names, but like uh leading ride share companies of the world, reading telecommunications companies of the world, leading

53:58 Leading companies of the world in many many aspects healthcare, finance, like are Actively With their teams using lovable And It's always the same feedback, which is

54:08 Yes, we may not be able to push to prod, but like Our marketers are no longer waiting for engineers. Our uh you know, people in g in go to market or or sales or uh HR or whatever roles are now just confidently building internal stuff for us to

54:25 Manage our expenses. or manage employee onboarding or like there's so many use cases like that. Where like you're seeing lovable uh and and other tools for that matter being used to to push things into production. Yeah.

54:39 To help people do this. workflow that you're describing with all these MD files. Do you think you could share? Uh after we record this, just templates, like simple templates of what these files look like for people just to look at and copy. I would literally go to Chat GPT as I said and brain dump into it in my

54:55 Just type lovable GPT uh lovable a PRD generator. You'll see my name there, right? And and 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

55:12 And upload those. Amazing. Cool. We'll link to that. So So it's not it's not just here's a bunch of files, it's go talk to this thing and it'll generate the right files for you and then you plug that into Lovable or other tools. Yeah, it's trained on it's trained to think like I do. So yeah. Oh amazing. Okay.

55:26 That is perfect. By the way, I want to talk about like how you unblock yourself'cause there's a whole other series of Tips you have there. But I just wanna reflect on it's so interesting how One, you're kind of from first principles.

55:40 Under s learning how to build product as a PM, as an engineer, as a designer. 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 your D design. So I think that's so interesting just to do it.

55:56 This it's interesting that these are the things that we've got. Functions. still work and are necessary. Now it's U and A I Help.

56:05 create all this basically this triad that's always existed, product manager engineering. And design And something I've always thought Is that

56:15 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.

56:29 clarify. Be really clear about the requirements. Figure out what success looks like. It feels like That's Where the skill is most needed.

56:38 There's also a design component of like make this look awesome. And I feel like that's gonna be an emerging Uh The the value of that. being really good at design and taste and judgment is only gonna go up.

56:50 Uh Before we get to Things you've learned about unblock yourself.'Cause 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?

57:03 If we measure success in the right terms, again, um AI as you pointed out. regardless of your background is an amplifier. So You know, if if you don't know

57:15 Mm-hmm. what you're doing, you're just gonna produce garbage faster. One thing again I just want to double down on is Um good enough was good enough.

57:27 Right. Because Even producing good enough was not easy. Right, ten years, fifteen years ago. Just producing was more than plenty, more than good enough. You you built the SAS

57:39 Who cares how it looks like it works, it it does stuff like you oh my god, I'm so much more productive. Today. Like if if good enough was here, let's say like let's let's visualize it for people. Like If this was like Pretty pretty bad, could be better.

57:54 mediocre. Good enough. World class If this was the gap between good enough and world class, well guess what? The gap is now this. 'Cause everybody produces good enough with AI. Absolutely everyone does it.

58:09 So now learning and optimizing for How do I produce world class and magic? Is the the key lesson to take away today. As you pointed out, I think

58:21 PMs are the winners of AI today. Because they bring clarity. If I was A a a betting man, as they say.

58:30 I I'd bet that The next class that wins our designers. Because We're training these tools. To be more clear.

58:39 To be better. To make better Technical decisions. I don't think we will train them just yet to be make better emotional decisions. And I think design is all about emotion. And that's where like

58:52 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 figure out when you join Lovable? Like what's the biggest personal upskill. Let's say like working with Felix Nad Abbey.

59:06 All of the people that are designers Just really what moved. You shifted the needle. For me I'm like Oh

59:13 So this is how world class looks like and this is what it takes, right? I I you always use the analogy of like I I wanted to steal one of their designs and bring it into my lovable project. So I went into Figma and I was like Let me just take this background like and just

59:30 Put it in there. I went in. And realised that what could be Uh uh. you know, interpret it as a pretty simple or rather simple gradient.

59:40 Chuck. fifty different layers to produce. So I clicked on that component and I was like Oh my God, this is not Three colors, this is fifty colors. And not just fifty colours.

59:52 fifty covers with different gradients of levels of opacity. So Oh, okay. Well that and that's the big disconnect that I've had all along. So like Um Again.

1:00:04 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 a an amazing newsletter. Like

1:00:20 Oh and To teach you how to and learn how to prompt for good design. Learn about design styles. I didn't know what Bauha Bauhaus meant or glass morphism, had no idea. So I I built an app as well for that and lovable. I was like I needed to build an app to learn these styles, so now it's public. Anybody can see it. It's like

1:00:38 Some UI style dot laap. I don't know what it is. Like It has like eighteen 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.

1:00:49 Uh is probably uh w what I would what I would optimize for um at 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 thinking? Do you feel like that goes away based on your experience.

1:01:05 It it never goes away. We will need elite engineering more than ever. Like'cause let me tell you this, in a world where everybody builds and everybody's building everything Who's doing the maintenance? Right. Maintaining code bases, uh scaling code bases, maintaining projects, um

1:01:24 You they're still gonna be a thing, uh uh definitely. And obviously AI is gonna 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 when everybody's building.

1:01:41 Infrastructure suffers. Right? Like We know and experienced like Cloudflare went down two or three times in the last two or three months, the whole internet goes down. Elite engineers are the ones fixing this. lovable experiences

1:01:56 Massive amount of influx of new юзер. infrastructure there suffers. Elite engineers are the ones building The infrastructure to hold the fort, right? So like I think we're gonna need a lot of people.

1:02:09 With really good skills of like hey who actually builds the world that needs to support billions of builders now because everybody's gonna want to learn how to build stuff. Like How do we teach them? How do we maintain everything that they need? the hostings, the the security, the

1:02:26 Email, the connectors, the APIs the whatnots like So I think there's gonna be room for it. But I I'm also on the boat of people like

1:02:35 If I had an eighteen year old brother and if he asked me what should I do, I would tell him, Hey, go become a plumber. You know, not don't don't go and get a CS degree. You learn uh learn a good trade, you know,'cause uh The new generation of millionaires in the US are actually electricians and plumbers and whatnot, right? So it's like Uh you know.

1:02:54 Yeah. It's a balancing act, I'd say. I don't know. Like I I do still think that Good engineers. With with good sense of like Um

1:03:04 Understanding where the future is going are always gonna be needed and and scarce. Such an interesting thing. Question. I think to your point. There's definitely gonna be people need to keep building the machines.

1:03:15 That power all this stuff. Well we need engineers to build the actual Products. The the the application layer. That's the that's the question. Like, is everyone gonna be like you? Is everyone gonna be Or designer is just gonna be all we need.

1:03:27 Everybody's gonna become a 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 re I'll refer to myself as I as a rapid engineer in in a year from now because VIP coding is just coding in twelve months from now. And even today We spoke about this before, like

1:03:47 How many elite elite engineers Are Public admitting. They're no longer hand coding or manually coding, whatever you want to call it.

1:03:57 Day AI writes all the code. I I I use the analogy here of like Coding is gonna be like calligraphy. You writing code is gonna be the equivalent of like You write you fine printing like on a canvas and people like, Oh my God, you wrote that code? That's so amazing. It's gonna be so rare.

1:04:15 But it's gonna become An art. Right? It's not gonna be It's gonna be commoditized completely. Like it it already is, in a sense. Most elite vibe coders.

1:04:25 Rely on AI again, it's an amplifier. Right. So I think um Everybody becomes an engineer. in in the in the world of the future. A designer, a PM uh uh everybody is

1:04:38 Uh uh. an a forward deployed engineer or an air assistant engineer or an LM engineer or a vibe coder. The term is irrelevant. We're all Using Limbs. For raw output based on good judgment.

1:04:53 Or bad judgment. No man. Essentially these Venn diagrams of engineer designer PM. They're all used to be very separate. Now they're converging and people with a specific with deeper PM engineering design background are gonna

1:05:05 Like they can all do the same thing essentially. All the roles are converging. What a what a time to be alive. And it's so hard to predict exactly how this all goes, but But it's fun to plantificate. I wanna get back to When you get blocked. Speaking of elite engineers.

1:05:18 Uh Thing that there's like in there. In reality, you're still writing code. Using these tools. Sometimes code.

1:05:26 It was Things go wrong. Bugs are introduced. There's a weird database thing, there's like some um network issue. What do you do when you get stuck? Do you have kind of a workflow you go through of unblocking yourself?

1:05:37 Yes, great question and absolutely true. Like no matter how good of a plan you have in place, you're gonna run into problems eventually. And I have like a small little framework that I call four by four, just again, analogies. Right.

1:05:51 Four by four. If you if you have it on your car, you're gonna get yourself out of the mud. Much easier than than Uh the other way around. So Um in that sense.

1:06:00 Four different ways to debug. Attempt one of each. Only once and I'll explain why. In the end. Um

1:06:09 First one is again Every tool is different. I'll I'll reference Lovables workflow. Um, which is when something breaks

1:06:17 Lovable agent is smart enough to say, Hey, I made a mistake. It will label that message in orange. And uh have this little button usually which is uh called try to fix. So your agent basically admits it made a mistake.

1:06:32 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

1:06:42 Problem is a little bit deeper then. Right. You click to try to fix, but The the problem persists. And sometimes even the problem persists. But

1:06:52 Lovable agents are aware that it persisted. So there's no more try to fix button. And the The culprit there is usually You're using a third party integration. You did not give enough context to global where what to observe and what to see.

1:07:09 So I can see that the problem exists because Lovable cursor, cloth code, you name it, all these tools are good enough today to fix any problem they're aware of. Again, awareness is the key. Yeah, right. So when they're unaware of it There comes the second part, which is

1:07:24 Okay, I need to bring the awareness layer. And what I do there is I go in very simply. Open the preview sandbox dev environment of my app, whatever. Try to run the The the function that's broken.

1:07:38 Right click, read the console log. Right. Every browser allows you to just go and read the console login. Lotta times It will record.

1:07:48 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.

1:08:07 Let 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.

1:08:18 You copy that. You paste it inside. Your chat Ninety nine percent of the time. That's enough. That's that's already enough. I was like, Okay, got it.

1:08:28 Found it, fixed it. Right. But then There are situations when even that's not sufficient. So like okay, I need to go even deeper.

1:08:37 And that's where like code reviews and evaluations come into play. My go to tool today for that is Codex, Open AI, right? What I do is like Any any build that I do, I will export it to GitHub. Like

1:08:50 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. So I I

1:09:02 you know, youth codex since beta, like Important. In there? And then I'm using an external tool, so I'm I'm like

1:09:11 In the first try, as if you remember, like I used the tool and I was like Total vibes, I'm I'm relying on the tool, right? In the second try. I use my save. as the awareness

1:09:24 Uh uh a facility. In the third one, I'm using an external tool. A as a facilitator, which is like I'll either connect to codecs. And chaff with codex.

1:09:34 to then fix the problem in lovable. Right. I don't allow codex to make code changes for me. A lot of people will say, Why don't you? Like it's a good good model. I just don't know its agent well enough. Like I don't wanna go and and And use a tool that I don't know how to steer.

1:09:48 So I use it only for diagnostic purposes. And I'll also do it manually. It's an old Uh workflow that I had before Codex and before Cloud Code, which is There's a tool called Repo Mix.

1:10:01 Which allows you to like Compress? Every all your entire code base into a single file. You download it and then I upload it to Claude, just cla regular Claude or Chad GPT, and I'm like This is what I'm building. Read it and and this is the problem that I have.

1:10:16 These are the console logs again. It's almost like having an external consultant at that point. Like you're hiring help. Elsewhere'cause your team just can't handle it. Right. And then the fourth one is is usually the best one because Of the time when there are problems, it's my fault.

1:10:31 Like, no matter how your ego is big, guys that you're watching this, it's your fault, trust me. You you had a bad prompt, you premised your request. in the wrong way. You just don't wanna admit it. Or you can't remember that you did. But it's your fault. So

1:10:46 Again, illovable and in the 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 gonna take three steps back. And I'm gonna think about my prompt a little bit more.

1:11:02 Take a couple of breaths, go for a walk. Have some coffee. Come back. With a clear mind. And

1:11:07 Try again. Cause guess what? AI's just writing code very fast and sometimes it stumbles on a very small rock. And It only happens then and never again. So you just gotta make the same request again in Usually that just fixes the problem.

1:11:24 It's just a snack. It's a syntax error. It's it's something s minute. Right. And then I do the final thing. Which is.

1:11:32 This. And this is the key one. Sure. When the problem gets fixed I go into the chat mode and I and I ask Lola, I say, Okay. I needed to do four different things to fix this.

1:11:44 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. Ninety nine percent of the time I get such a great answer.

1:11:54 Yeah. I don't have the problem of not knowing what to do next time. Right. Like Again, you need we all need to be aware and realistic. These tools are so good at at doing things the right way, if they are used the right way.

1:12:09 It's always our fault. It's a har I say ninety percent, but honestly, it's a hundred percent our fault. Right,'cause 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

1:12:27 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'm um I struggle with prompts a lot of times I use chat mode to help me craft a good prompts.

1:12:41 Anybody can do this too. If you Are just stuck it's ten PM. And you don't know what to ask, switch to chat mode. Brain dump. And be like

1:12:50 Help me draft a better prompt. Help me prompt you better. And let the tool. effectively prompt itself. A lot of times you're gonna solve Your problems by not introducing them at all.

1:13:01 With with bad inputs. So Oh my God. Everything you share is so interesting. Yeah. I just wanna

1:13:10 I wanna keep digging. So just to reflect back the the sequence and then I wanna follow up with another question. The sequence you go through when you get stuck. Which is gonna happen to everyone. One is Just Ask the tool to try to fix it.

1:13:24 And oftentimes it's telling you something is wrong. Can 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.

1:13:35 And this advice I love of just ask it to add more Debugging. Lines to its own consolog. to help.

1:13:43 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.

1:13:52 Find the problem. And then step three is go to codex, which is which is so funny. And uh and I hear this a lot. That codex is like the The most elite engineer as an AI. Karpathi tweeted this once that

1:14:06 And we had the head of codecs on the podcast too, by the way. Uh that he's like Anytime I have the most gnarly bug I just go to codecs, let it run for half an hour, and it solves it, unlike any other tool author. And so it makes sense that that's where you go. So the idea here is you

1:14:20 Point codex to your code. You showed all the console all output logs. What the problem isn't just Have it go figure it out.

1:14:27 Sweet. And then this final step is so great and this is where I want to go. They which Use this as a learning opportunity. So that next time You solve the problem more quickly or avoid it completely.

1:14:39 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?

1:14:52 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. 'Cause I won't remember to prompt you better two days from now.

1:15:05 Put this into rules. Put this what we just learned into rules.md'cause I I'm making you read the rules every time anyways. So you might as well just record it there. So I'm not gonna prompt you better. You're just gonna learn that I'm stupid.

1:15:19 And you're gonna prompt yourself better. Right. Again. Just eliminate yourself. And and and move the context, you solve ninety nine percent of the problems with AI today. So idea here is uh help it

1:15:31 build its own brain and and rules and way of thinking. Based on problems you're into. So great. Okay. So I'm gonna come back to this point you've made a couple of times, which is so interesting. This idea that you watch the output of the agent. to learn what is going on. Something I've seen other people, Ben Tossel who I think is at Factory now share this recently. He's also

1:15:51 Basically by coding all the time. He was really into no code tools before and now he's all about vibe coding. 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 C of cursor when he was on the podcast.

1:16:08 Yeah, this vision of cursor becoming Basically what comes after code. What's the layer that we are adding on top of code? Where people don't need to worry about code anymore. And

1:16:19 At that point, it was like a year ago that we chatted and it feels like this is the lair. is the agent conversation. of what it is what it's thinking and then what you tell it back. So it's essentially it's English in a conversation which is Like it's not even pseudocode. It's interesting that that's

1:16:34 Where feel it feels like things are heading. The layer overcoat is just It's thinking and your conversation with it. Yeah, yeah, exactly. I mean, um Again in a in a way.

1:16:46 I really Optimised for for good judgment and part of good judgment is i comes from Again. learning how these tools work. You need to know what's possible. We talked about it and I I know I may sound sound contradictory sometimes, right? But it it it's because, as you said, it's so interesting the world we live in.

1:17:05 That things contradict to each other. It's an advantage not to know what's possible, but then at the same time You cannot B. Completely.

1:17:13 uh oblivious to uh uh something that's like a a a factual thing. So let me talk about a failure of mine that came from being delusional. Um back in the day when open AI um

1:17:26 Uh started uh uh or better said released image generation natively in the app, right? So you could go to Chat GPT and be like gener generate an image of XYZ. the whole world exploded. Like that was like the biggest thing ever. Obviously first thing that comes to my mind is like I wanna build a lovable app. I just wanna build a wrapper.

1:17:46 And I wanna build an image gen. With lullable. Without thinking that OpenAI did not release an API for that. Just yet.

1:17:55 Sorry. I spent At least a week? Trying to brute my force. Uh brute force my way into

1:18:03 Making this work instead of just waiting for another week, because a week later, they had an API and I built this up in 30 seconds. The problem was that. Like I try to do it when it was impossible impossible. Like so Um I think again, you know, uh uh

1:18:20 I 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, they can browse the web, they can read files.

1:18:35 They they have reasoning And thinking capabilities. So that's why I'm so invested into that conversation'cause a lot of times it will tell me, hey What you're trying to do is just

1:18:48 And do At the moment because of XYZ. So like I always use those uh uh as a learning opportunity and I just level up

1:18:56 Most buy. Being in chat mode. for planning and learning purposes. And and'cause it just again develops your clarity Your judgment capabilities Uh rather than coding capable.

1:19:08 Yeah. The other point you made here, uh that I think is really important is that over time these tools will do more and more of what you do manually. I've heard this from other people that are Doing this

1:19:20 Full time basically vibe coding is just they had all these workflows. All these files and then Cursor adds them, level blads them and Yeah. 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 differences. A year ago, a year ago, if we had an interview, your mind would be blown. Stuff that I had to do as workarounds to for to to address shortcomings, like I've built a very successful course on that with starter story, like

1:19:44 For a year people were like just, Oh my God, you're the only guy in the world that knows this secret. Now lovable natively addresses ninety nine percent of it. I can almost say Most of the stuff that I I was teaching people like I have a YouTube channel a little bit appreciate, but like There's a

1:20:02 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 it just works, right?

1:20:23 So Um that's why as I say like Um Yeah. It's the it's the horse's analogy.

1:20:30 I don't know if you heard of it, like a lot of people are tweeting about it, which is like We started Building the steam machine in seventeen hundreds, right? Took us about two hundred years. To build it?

1:20:40 When it got to when when engines got built and put Cars were put on the roads. I I think that ninety percent of horse population was got eradicated in the US within twenty years. The person that tweeted this works at Claude Code, right? So he was like

1:20:55 Now when I translated it into AI I was hired to do a job. Technical job, technical writer, whatever. I became obsolete. Six months later.

1:21:06 Like humans did not get the twenty years that horses did. The guy. that that is was hired to do a thing is like six months later I need to reinvent my my role. I need to involve it. Into

1:21:19 into something else, right? So you know, I 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.

1:21:37 Right. Sitting in meetings. Taking notes. Doing spreadsheets. Like

1:21:43 Nobody may maybe there are people that like that, but like most people don't. We're just getting it to a place where we're rewarded for what really matters, like Clarity Judgment. Thinking

1:21:54 We're actually gonna be paid to think longer. And ponder longer because The longer idea simmers and gets broken down, the better. Because building it is gonna be an instant, right? It's gonna be

1:22:09 Like this. It's just a matter of few having so much clarity around it because Guess what? If a tool is superpowerful. And you're given a wrong input.

1:22:18 the alcohol's gonna suck as well. That's why like I've never become good enough at Claude 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

1:22:34 This is not what I wanted to do. So that's why I I still s see myself being good at Like using tools that are Uh

1:22:42 Uh a little bit on The exploratory prototyping path. Um uh more than like And

1:22:48 The path that Yeah, uh elite engineers will use, for example. I love your optimism and excitement about this stuff. I think for a lot of people. Say they're current software engineers, PM designers.

1:23:00 There's a lot of fear about the future of their careers. Are they gonna be relevant? Will I will my software engineering skills disappear? So to follow the story 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

1:23:21 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.

1:23:32 Yeah. Emotional intelligence for sure, just understanding human nature, real life stuff. I think we're all gonna get So Tired.

1:23:42 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

1:23:52 Craving humans naturally. Are gonna wanna do live. stuff more. So anything human to human. Is gonna be a big thing to skill up on, understand the dynamics.

1:24:04 Anything regarding math. If it's a math problem, I think P Peter is it's the said it recently. People that just do math stuff, you know, AI is gonna come for you. Like anything that's very deterministic, meaning X input equals Y output and it's pretty clear the The line's pretty clear.

1:24:23 AI AI's got got you eaten eaten for lunch, right? But If you understand how X to Y goes in human dynamic human relationship layer. I think that's where

1:24:33 Things are gonna become good. So if we translate it again to a s specific skill I'll say it again, good design, really good design, great design, like How how And when I say design, that's Images.

1:24:45 fonts as well. Copy. Copy's a big one. Like we all now. We're like Two years into AI? I'll bet you me and you if people put

1:24:55 Ten 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 gonna be a very good skill to have'cause people are just gonna know F or three.

1:25:08 That it's AI written and even I don't read AI output anymore. I I don't like to s seeing it. I want raw that raw human experience. So I think human skills. I I don't even know how to describe it because I don't I don't think we're doing a awesome job. Well.

1:25:27 putting g labels onto what humans are good at natively. But I think we will. I think we will describe job descriptions better. Um We we will have like uh uh human first engineers, I don't know, or human designers, or I don't know how to describe those roles same way.

1:25:43 How A Karpathi. A coined vibe coding? I was vibe coded before he did it. I didn't know how to call it. Like

1:25:50 I started vibe coding. In July of twenty twenty four. And I think he uh he coined it sometime in early twenty twenty five. So I was like doing it for seven months. And I was teaching people how to do it for about three or four with courses

1:26:05 And I didn't even know how to call it. Like'cause there was no name. It was like Oh I'm just using AI to to to do this for me. I don't know, whatever. So yeah, I think we're gonna reinvent some of the the terms, rules and whatnot, but um

1:26:19 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 mid you're a middle manager, you're a middleware person that's just translating stuff. Um

1:26:31 And I can use that analogy again. Translators. are gonna die of people writing jokes, comedians are not. AI's never gonna be able to write a good joke. Never, never, never. Just doesn't have that layer that just doesn't understand what's funny.

1:26:46 Like if you ever try to use AI to write jokes, like they're awful. They're always gonna be awful. But if you use AI to translate things from one language to another. It's very good at it. Like It has gonna replace translators, it's gonna replace most journalists because it does good research, it can write good copy, whatever. Not not elite journalism.

1:27:05 It's not gonna be able to replace all the writers. It's gonna amplify great writers that can train AI on how to write books. So like Somebody who's a Amazing writer is gonna all of a sudden write seven books a year instead of one. Right. So that's that's dangerous. If you're an average writer.

1:27:21 Be careful. There's zero comedians, me. Zero. And that's just my personal belief. Like AI's never gonna write good comedy. It's impossible. And like So

1:27:33 Try to find your analogy in your industry. Like I just gave you one for Um writing skills, so to speak. So writing jokes. Super good skill to have. Um translating

1:27:46 I'm sorry to say, but like But You're not gonna have a job for much longer. Like Uh You better find something else to do. Um

1:27:54 But yeah, that's that's how I look at it. The the comedy piece is interesting. I had one of the founders of a the data labeling company, I don't know if it was Mercore or maybe Surge. And he said that um I think it was Anthropic hired a bunch of national lampoon Comedy writers.

1:28:10 Uh to help them. Train. Models. And so they're working on it. And so I I love this strong prediction you 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.

1:28:23 I'll be wrong on ninety five percent 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 speaking of career, so one interesting career option is to do what you're doing.

1:28:37 As you said, this is a dream job for you. It's a dream job for so many people. What What is the 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 I've done so many things in l in in life, like um

1:28:57 Blue collar jobs. looked at even at Subway while I was studying and stuff like that, like Um I'm 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.

1:29:13 Uh I waited tables a long time, so you develop some human skills, you understand what people like, what they don't like. 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 slum dog 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 quite the questions in the in the quiz better.

1:29:37 I have 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

1:29:47 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

1:29:57 consumers in the world. How do you get in front of the The eyeballs, right? Like and At get attention. Which is gonna

1:30:05 Is this more scarce resource and it will be even more scarce, but like Going back to the Bite Court of Rule. If somebody's like saying, Okay, well, I have I have a pretty diverse background too, and I'm babe coding and like how I how does this become a job? Well For me, I feel like it became a job by building in public. I didn't

1:30:23 Chat with Elena once, only once, and like Why me? There are so many good vibequarters I did how did you Pick me. out of the crowd. And

1:30:31 I think you know, obviously You she gave me a couple of reasons, but like To translate it into like a uh uh was one concept it was like I was building in public and sharing. I

1:30:42 As I said, I made a YouTube channel and I I should have 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'cause I I just have that type of Caters.

1:30:55 All my years are very long. And X doesn't doesn't cut it for that. Like you need very you know, you need to be very Uh to on on on point? To be successful at X, so I'm not.

1:31:07 So I guess you know, it's just like Build them public, share your knowledge. Give away all the secrets. Like there are no secrets whatsoever. Uh, if you're sitting on a good concept, you're missing out. I just share it immediately if you figure something out. That I recognize that um very early on. And you know, just like

1:31:24 I think a lot of people participate in hackathons these days. I want to encourage people to do them, like find those those opportunities locally to connect with other builders. Lovable is hiring across the board. Check out our op open positions. It's as easy as that, right? Like Just apply really find companies that that are hiring and and hiring in in different roles. And I've seen people do something. I'm gonna give people a a secret away. Couple of hires. Stood up by

1:31:50 Not sending resumes, but sending lovable apps. They built lovable apps to show what they're why they're good. Fit for a role. And 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 what you want from me or how do you see us collaborating and working together. Right. So there's people

1:32:13 Finding creative ways to get in front of Eyeballs of Decision makers like Elena, right? And um

1:32:20 I I mean Skill wise, again. w we're just re uh repeating ourselves here, but I think it's important to repeat it as many times as possible. Really? Develop.

1:32:31 Good judgment. Right. uh understand in a diper sense How Uh

1:32:38 how things translate when wive coding comes into play, right? There's a company out there. I I I'm not gonna name them, but like um That uses lovable religiously is gonna be one of our main case studies actually where like They a actually hired vibe quarters before Lovable. Like I'm the first official

1:32:57 Vive coding engineer at levelable, like with that title. But I've met people In companies where they hired them before us, people that are just five quarters, people that just understand that speed matters right it still matters a a lot to be fast and like there's a company out there with three biquorders full time all they do is like translating the old uh code base into

1:33:20 Uh uh on to lovable. This is bringing everything. They're CRM, CMS, everything. They're all the tool sets that they have and they need it. s there are people now actively just migrating everything. Everything over there's S P five hundred companies that are like putting lovable in in job descriptions too, like saying, Hey

1:33:37 lovable skills uh skills are You know, um recommended in in the recommended tab, right? So yeah, to to to to Go back to the

1:33:47 How to become vibequarter professionally. Well You don't need a company to hire you. You can hire yourself as a professional life order first. I think The reason why It I clicked with.

1:33:59 Anton and Elena and everyone else because I was already doing it. Like All all I did I just changed the the the the vehicle. But I was already doing it. professionally before I got hired.

1:34:11 So that's kind of the The the Key like Uh do the job you you you would have done anyways. What a mind expanding conversation.

1:34:20 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, I don't know, disillusioned, scared. And you're the opposite of that. You're just leaning into this, just taking advantage. Taking not sure where it's gonna go, but

1:34:37 Following the path. Yeah, and I don't want to interrupt you, but like it's it's it's because like look, um Lovable specifically isn't a company. You can talk about it as a company. I don't see it as a company. It's a і це найдія It's a mission. It's it's it's

1:34:53 Something More powerful than the internet in my mind. Because like Uh In turn allows us to consume Lovable allows us to build and en in our nature in human nature.

1:35:05 is to build to create Right and and The fact that there's a tool today that you can go into And dump an idea in. And and something comes out of it and somebody uses it and finds it useful to me, it's just

1:35:20 It's the craziest concept ever. It's my my only life's dream. I had my first computer when I was six. And I was convinced My whole life that I'm gonna be a software engineer or that I'm gonna beat building but like life wasn't As simple as that for me. Like uh you

1:35:39 It was very, very uh Complicated and honestly, the last five to ten years I gave up on that dream almost. I I thought I'm never gonna Build anything? Like I tried I

1:35:49 I I've tried to build with technical, like I just couldn't find alignment. I was I just gave up. And I Now like at thirty six, like Thirty years later.

1:36:00 I feel like Again like that, that's kid. Like I dream Every day. Like I it's it's amazing what this enabled us to do. And I Anybody that's scared, like just try it.

1:36:11 Mm. It it switches from fear to excitement immediately because then you see what's possible. First hand. Just coin. Build something, build anything.

1:36:21 And the the fear goes away. You 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. It's as big as

1:36:40 You come in. And you just say What's on your mind? And And just ship.

1:36:45 I think a big part of this is just stop listening to this podcast go just do stuff. You actually try try to right. Ideally people stop right now. They've heard enough. I gave them what I I gave them the best that I could. Just start listening and just go. All right, bye everyone. Okay, I'm just joking. But let's but let's we we'll we shall wrap it up. Um

1:37:04 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 we'll let you go. Yeah. Uh.

1:37:16 Text tag doesn't matter anymore. Right, it doesn't matter. Like people obsess over Oh, is this Right. In HTML is this written in React, is it doesn't matter. Like

1:37:27 It never mattered, but now matters even less. The end user. Just Once A stellar experience.

1:37:35 We live in a world Where anybody can produce good enough, so you you better start learning how to produce magic,'cause otherwise you're just gonna End up in a crowd with millions and millions of others. But at the same time

1:37:48 If you don't know what magical looks like, don't be discouraged to start building anything. And start Start from good enough. and level up. The best way to level up?

1:37:58 Exposure time. Set aside more time. On learning than building. Look read the agent output. Learn how it's thinking so that you know what's possible.

1:38:09 But then also Go and get inspired. Follow Good designers on X. Find tools.

1:38:16 Where great designs are produced. And follow their creators. There's a tool where w w where I'm following just the the actual person that built it'cause he H publishes videos almost daily, forty, fifty minutes long.

1:38:30 Of him designing. I wanna see how a world class designer does it. I wanna see him talk to the tool, I wanna see him prompt. And that's how I learn. To become better at it. So again Exposure time.

1:38:43 Just deliberately set more time aside. So learning than coding because You can code fast, but you can call garbage fast. As well as magic fast. It's the same amount of time.

1:38:54 It's you and your input that matters. Forget about decisions on Tech stack, forget about which back end are you using, which front end are you using. That doesn't matter.

1:39:05 Quality Taste. Design. That's all you need to optimize for. In the future.

1:39:11 That's ahead of us. Well Zara, this uh I think we're gonna leave a lot of line a lot of minds buzzing after this conversation. 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.

1:39:26 Where things are And revisiting this conversation. I really appreciate you coming on, sharing all of this. You're awesome. 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? Awesome, yeah, um so

1:39:41 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 a a lot of cool

1:39:55 Tips and tricks that I that I wanna share and teach people how to um use lovable and and just vibe code in general. And level up. And on how people can Uh be useful.

1:40:07 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 in. I envy the person.

1:40:19 that is gonna try lovable for the first time after watching this episode'cause the feeling is just unmatched. Oh of you going from a consumer to a builder. But in that process there's gonna be Some Battles to fight.

1:40:31 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 watched this. And you're like I'm gonna do it. I was on the fence and I'm gonna do it.

1:40:45 If something breaks, if something doesn't connect and relate. I need to know what that is. My job is a hundred percent to empower you. To build the best Work of your life.

1:40:56 Right. Um and uh you know, and I need to say this too. 'Cause a lot of people may be inspired. Uh.

1:41:03 Not by Building Or using lovable but But rather building lovable. Come join our team.

1:41:12 Again, we're hiring across so many things. I think a lot of people should feel inspired because I h 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 Верно би акцент. І цнат а коинцідент. The best people are gathering

1:41:35 And we we want you to be a part of it too. So if Yeah. the energy and the conversation resonates with you, or if you heard a pr about a problem today. And you you're like, Man, I I think I can solve it. Come, join us.

1:41:48 Help us build. And shape the future of software development. Incredible. And uh what's the site that I imagine is just a link on Lovable's website to find the the open roles. Link folks there. Yeah. Incredible. Wellazar, thank you so much for being here.

1:42:02 Appreciate the opportunity. Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review, as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show.

1:42:23 at Lenny's podcast dot com. See you in the next episode.

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