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

You're at the top 0.1% elite level of buy coding. But it's a dream job for so many people. If you became a job by building in public, you don't need a company to hire you. You can hire yourself as a professional lifeholder first.

You've never coded you don't want to lick at the code.

Coding is going to be like calligraphic people. Oh my god, you wrote that code. That's so amazing. It's going to be so rare that it's going to become an art. These venn diagrams of engineer designer, PM,

used to be very separate and now they're converting. AI regardless of your background is an amplifier. If you don't know what you're doing, you're just going to produce garbage faster. Feels like an emerging core skill is learning clarity in the ask of free 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 wishes I want to be taller. Genie makes me 13 feet tall because I was not specific. AI 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, clarity, quality, taste." Today my guest is Lazar Yavanovich. Lazar is a professional vibe coder. He gets paid to vibe cod 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, 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 tools. 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.

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With that, I bring you Lazar Yavanovich, after a short word for our sponsors. This episode is brought to you by Stralla, the customer research platform built for the AI era. Here's the truth about user research.

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That's s-a-m-s-a-r-a.com/lanny. Lazar, thank you so much for being here and welcome to the podcast.

Okay, so I had Elena Verna on the podcast.

She's had a growth of the lovable.

“She mentioned that she works with a professional vibe coder.”

You. I had so many questions. I almost wanted to go and attend you with her to try to understand this role. Instead, ask you to come on the podcast. There's so much I want to talk about.

I want to talk about just this career path and just how you got into it, how other people might get into it. Where you think this is all going, this whole bike coding thing. Also, I want to get into what you've learned about being successful using all these AI tools because this is your job.

First, I want to 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 coder. Incredible. What are you responsible for? What are you doing day to day?

“Well, as you said, it's a dream job, right?”

I get paid to do what I would have done anyways. It's the best job of the world. I get to use tools like global, every day to push projects to production, whether for internal or external use. Those could be ranging anything from different templates on marketing sites,

sales side, or whatever, or they can be as deep as like building some internal tools, or a lot of integrations and connections and whatnot. The surface area that I cover is pretty wide across all the parkments, because it's such a flexible role, and it complements so many things. It's an idea that a lot of people have a lot of great ideas,

but they don't know how to build them, or they just don't have the bandwidth. That's where I step into day 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.

“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. You ship stuff that's actually public, and it's 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 merge store,

because we wanted to obviously prove the concept that, hey, lovable and Shopify just works. It's so simple anybody can do it. I've I quoted our merge store. So all the merge, including this shirt that people were buying online, they would have bought it from a store that was built by me. But then again, on the internal side, we want to track a lot of things. One of the cool things that we want to build now, for example,

like feature adoption major. So if we build a feature, how many people are actually using it and adopting it? Like, and that's a pretty custom build, right? We have a very custom stack, we're building custom features. There's nothing out there that 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 big

enterprise account somewhere, I'm just going to build it myself faster. So, you know, I'm in that position of like, build versus buy. I'm in the build vote, so to speak. Yeah. And then who do you report to? Or are you kind of this rover that helps wherever or are you with the Windows specific team? I'd say probably closer to the former, right? I've started in growth, like Elena brought me on early on and, you know, because she has so many great ideas and like,

she just needed somebody with the right type of mindset and velocity and ownership to just take them away, build them up, get them into production, whether they're like based on education, 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 willing start up in history. So, every department needs a bizarre 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'm working on some community tools as well right now as a speaker. So, I'm a little bit all over the place, but I kind of thriving that environment. We're like, I'm given a rough concept, a rough idea, and I'm just tasked to bring you to life as soon as possible. Okay. I'm hoping with this chat, we create a lot more

Lazars and I want to get to the career path, how you got to this and what it takes to actually become a full-time bike cutter. But I want to start with, because you do this full-time, you're, you're at the top point one percent elite level of bike 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. What are maybe two or three things you've learned that help you be really good at 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 wrote a single line of code

Right. So like I, I'm very much lead on to AI assistance. Let me actually follow that thread because that's such a point and it's something that when we were chatting earlier, you pointed out your feeling is, it's actually an advantage to not have a technical background when you get into the space. Yes, 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. 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, like, well, why, why is that not possible? Right. And then people that are technical start explaining you all, well, you know, it's a react. It's different stack. It's this, and people like me, including myself, we just go in to lovable and like build me a Chrome extension based on this app. And I was able to do that

with lovable. There were people that were able to build desktop applications on lovable. Again, something that shouldn't be possible. It's in three years. Right. Our 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. And then she just prompted her way into building a 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 just come into this completely unbiased and very 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 wrong. And like that's just the pursuit that I have in my mind that is helped me among other things that will chat today. I think took sell in this role that I haven't lovable. To 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. It's not obvious how to solve a problem.

And two is just, are you building like this like teetering slot that will collapse someday? Because you don't know, you know, system architecture. You don't know if this is going to scale all the sorts of things. So coming back to 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 ahead of away those sort of things. What you do when you get stuck is what example?

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 the most important one. And that is,

“you have to be self-aware, right? I didn't come into this. Yes, I am delusional as I mentioned in”

the sense that 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 from my own point of view in my own thing. So I understood very early that coding is not the problem that we're solving first. Here, that the problem we're solving for is clarity, right? Like the output that AI can do is much faster than human output anyways. So like very early on, I started leveraging chat mode and I took this

day. I can say I spent 80% of my time in planning and chatting and only 20% in executing the play. Actually, 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 came into lovable

that was my first exposure to this. I've tested and played around with all the tools obviously. But like, whether somebody's doing it at cursor, called 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. So like until it's here, you're still steering the ship. In order for you to steer the ship,

you kind of have to know the instructions, right? And the best way to learn is by building, but treating these tools almost as 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 on my interest. It's what the agent tells me then that matters to me. I put a lot of trusting in LLMs and AGI these days and I understand that there may be some

people that are not as confident as I am. I just feel that the models today are good enough for me to trust in their syntax output. However, I'm concerned about the agent output and because of the tool limitations that I want to tackle, tackle on next, right? The first one being that there's a limitation when you work with LLMs, so there's a machine level limitation and there's

memory window, right? And for non-technical people, I like to use the Aladdin and the GD analogy when I explain, right? It is very simple. Everybody knows the storyline. You rub 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 translate it into working with AI,

that simply means, hey, I can only make so many requests within a request at a time for AI to be able to listen, understand what needs to do, 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 going to be different a year from now. But today, there's a token limitation,

I'll take an arbitrary number of 100,000 tokens for example. So when you make a request, a part of those tokens is AI spends to read stuff, another two times the web, another two,

think, and then another to execute the code, right? Then there comes the second limitation, which is

you, me and you humans, which is let's go back to the analogy of the genie and the Aladdin, I asked the genie for the first wish of the first wish is I want to be taller and guess what happens? Genie makes me 13 feet tall. All of a sudden, I can't sit in the car, I can't get into my house, I'm a dysfunctional human being, right? Because I was not specific, right? Like, so the part that we need to optimize for today, it's going to get better, but today it's still not there yet,

is that AI just don't understand what do you mean when you say, you know what I mean? Like, you do, when I tell you that, we as humans, we have I'm 36, so I have 36 years of experience of

“human living as a human to know what you mean, but AI doesn't have that, 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 member window, the quality of the LLM models, you are 100% control of the latter, and that's what I want to dive into today as well, and just try to teach people, okay, if I'm the Malibu part, how do I, how do I fix that, right? I think that's the key lesson here.

This is so helpful, and I love this metaphor of the genie. This piece of my clarity is such a thread, I've been noticing across people that have been successful using AI tools, and it feels like an emerging core skill is learning how to be learning clarity in the ask of the AI. Do you have any advice or anything you do there to help be better at being clear with what you want?

“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 understanding what tasteful looks like, what's good enough versus what's world class, what's magical, and I developed that through something that I heard from you you mentioned before, which is exposure time, right, making sure that I'm exposing myself to content and to people and to relationships or whatever that are going to 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, even before I started using lovable 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, 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 white my 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? Because it's like, at once you figure out that we solved for the how, which is AI assistant or rapid engineering,

“calling whatever you want. You can call the vibe coding if you want to, but we solved for that.”

Now we got to solve for everything else and everything else is what matters. Good design, good taste, good user experience, like, when you think about who you're building stuff for, with these tools you're building it for humans, humans are emotional beings, and we all make our purchasing or any kind of decisions on an emotional basis, right? So I think that the course killed there to work on and develop today isn't again coding, although I have nothing against

traditional engineering and I'll say later why, I'm actually a big fan of it or the leak

how to code? If you haven't done it yet, I honestly say no. Like, your, your optimism for the wrong skill set. We won't be rewarded in the word of AI for 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, it starts with exposure. So deliberately exposing myself to people and resources that I need, no, 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 what's possible,”

and, you know, go, that's where some of the techniques and mindset shifts that I want to also use an opportunity today to ingrain into people's minds later down the call may be useful. So, okay, so what I'm hearing here is because coding is now essentially a self 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. Instead, you're watching this agent output. I want to actually ask about that. But what I'm hearing here is the areas you are investing in building in yourself is at the front end clarity around what it is. And I want to hear how you actually do that. We do there. You have a really cool system there. And then there's like 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 to something gearmoroush shared on, in our conversation, this idea of exposure time, exposure hours, being exposed to great stuff. Here's a great user experience. Here's a great onboarding club. Here's a great, I don't know, website. So, I really like that advice. So, it's actually, okay, I'm just going to spend more time with stuff that's great to inform my taste and judgment.

And then on the clarity piece, let's actually talk about that. What do you, what do you do

“there to be clearer with? Loveable and other AI tools to help it build the right thing?”

This is the first mindset mindset shift that I want to 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. And just input a brain dump prompt, right? Just talk into it. Loveable specifically, I don't know about the other tools has a really cool voice function. You click it and just dictate the hell of it and just press send, right? Don't even wait for it to finish. Open a new window. Again, lovable.dev. In here, you're like, okay, as I was

brain dumping, I think I found a good thread, right? I think things are getting clearer. So, let me start another project. Now with more clarity, more deliberability. Like, I know with features I want, which pages I want, and maybe I can even find a good reference, maybe I can go on modern, maybe I can go on dribble, maybe I can go wherever, get a good screenshot, get a good animation, and attach it, because most of these tools accept files as a part of the input. So, like,

you have the second project started. Now things are even more clear. Now 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? Or why are we in one thing the wheel? I'm building a platform with somebody else built, why not expose AI to what quality looks like, right? So, what I'll do, I'll go to and find a library, 21st then, or dot build, or 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, lovable and all other tools still communicate in code the best. If you want to get”

pixel perfect results, just give them code, it will interpret it better than your English or Spanish, or whatever language that you use in these tools. So, that's the third way, you're like, okay, now even more deliberate. I'm not, I'm not even going as as wide as 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 third project. And then, by the time you do all of these three,

you're already at a level of clarity that you wouldn't have if you just sat with an MTP sa paper, or maybe a chatting, just with chat GPT, but not taking the action. I think taking the action is so, so cheap these days, and free by the way. Like, all the tools I mentioned have three plans. Like, most times 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 cost anything either,

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 you're also solving for one big problem that you mentioned. You used the term AI Slop, and I like it, because a lot of people, when they say, I Slop, they don't refer a 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, save you massive amounts of credits, because a lot of people obsess over the concept of, oh, when I give them this hack, they're like, oh, but that doesn't that cost more? I'm like, yes, upfront, 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 for a point 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 the second layer, but I assume you may have some questions on this one. Questions and also just, wow, this is such a great, it shows you the power having someone come into this world without an engineering background, this advice of just build it five times in parallel, ask you, I had to try all kinds of stuff. Like, this is not how someone that has been a software engineer or

PM or designer would approach stuff. So your advice here, which is so fun, is as you're getting started with a project, just run five different approaches at it to start. One is just brain dump.

Here's what I'm thinking. Here's general idea, like you use whisper flow or use the built-in

mic, and then two is okay. Now I have a general idea. Let me try to type it out. Like, actually thinking through the prompt. Three is let me find a mock design somewhere online,

“and the sites you suggested were mob in and dribble. Those are the two that you go to?”

Yeah, most of them. Okay, and then the fourth, you know, these are all in parallel. It's great. Is fine, like, actual code template that looks similar to the thing you want to build, download, like, the zip file basically and put a touch it, or is it just HTML and CSS? Is that kind of what anything? Anything, yeah, I call it just, yeah. Okay. And then cool. Here's the prompt here. It makes me, what I want. And what I love is there's two wins here. One is just it helps you

clarify the idea as you see the tool build it. Oh, no, that's not what I mean. Let me try it again. And then two is your pointed out. You can pick the right direction so that you're not locked into your first design and first architecture to your point. If you then spend all this time trying to find you in design and direction. It's like all these tokens are being lost. You could have just started over. 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 what I'm feeling is this is where you could save the most money because if you get a correct in the beginning, you save so much

work trying to get it back to where you wanted to go. A million percent that I'm actually saving

people. Like, I'm actually going against what I should be saying. If I was thinking about lovable, I don't know, just try to fix it in perpetuity. But that's not we're not in business of doing that. We're in business of empowering anybody to build anything that they want. And then, you know, it's my personal mission that resonates with me because if if there wasn't lovable, I would have never built anything potentially in my life. And I don't think that that would have

been a fun life to live. So, you know, I guarantee people, I have tested this framework with many people and everybody, tell me the same thing. I opener. So simple, yet unintuitive, as you said, even though for me, it's kind of, I don't know. As you said, I attributed to non-technical background

to me, that was the first thing that I would do. Like, I just did it. I never thought about it.

Like, oh, I'm developing this amazing hack. I was just like, I'm waiting all this time for these agents to finish. I met as we'll start another project and another one and another one.

“And it's also a productivity hack. Like, that's what people ask me like, wow, how do you ship”

so many things? I'm like, I never built just one project at a time. I built five or six. I have six lovable tabs and I just switch between them. And that's the next hack that I want to talk about if you allow me, which is the question written 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 apps. How do you manage to do it and do it in a way that's productive? You're not produced bad code or bad

product. And that's how I solve for that LLM problem. Again, the Aladdin and the magic lamp and all that, which is if there's a limited token window, how do I make it dynamic? And why do I me by that is this?

matter of what tool you use, the memory just isn't infinite, right? By the time you reach message number 10, 15, 20, 30, 40 snippets of early messages sort of get lost in the translation because agent is optimizing for speed, 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. 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 the lovable or any other tool as an engineer that I was supposed to be providing perpetual context as the project goes. And you can do that in many ways, but the most efficient way that I found was like, I would do the four parallel builds like let's continue off of that example. Very quickly after you've built hundreds of projects like I did like you you you you see the winner like the winner is so obvious it's not even a

competition. You maybe do one or more two prompts to calibrate it and when you're like okay the winner is here at that point I'd either ask the tool that I'm using or I'll maybe let's say go to Chad GBT 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 there are project requirements documents or for me I call them like sources of truth right what what needs to be true for this project to be successful from

a couple of perspectives I usually build something that I call a master plan it's basically a

compass saying here's what we're building right it's like talking to a human I've really

treat lovable like a human being so it's like this is what we're building then I build an implementation

“plan which is this is how we are going to build it and this is the sequence right it's very important”

to me again going back to quality taste human nature I need to define because I'm still working with a system that is not emotionally intelligent yet I need to define how I want the app to look and feel so another PRD that I build is design guidelines and then finally something that just circles it all around which is like okay when we know how things look and when we know how we're building it how does the user general look like right I use a registered and then once and then

when they register and and do that first step was the second step and was the third step in one

so I built at least four PRDs right and then when these are built I read them that's the planning chatting part like that's where I'll spend a lot of time now on when I kneel down that first design I'll spend an entire day if I need to just planning this part out like documentation and breaking

“things down because that's how I'm setting the course like everything's going to be dependent on”

this particular part of the process when I'm done doing that I build one final document which I call either plan.md or tasks.md and dot md part is you know marked down basically I'm just using marked down format because I've learned that AI likes to read marked down and what that serves as a source of truth on like actual tasks and sub-task that it will it 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 cloud code or or cursor have what's known as rules.md or agent.md

which are basically doing with rules or agent files is you're letting the agent know how you

wanted to behave and what it should focus on in the long run so that you don't have to repeat yourself with every prompt right so in lovable there's a there's a separate menu for nothing your project settings where you can define project knowledge and usually what I'll say hey read all the files before you do anything like don't do anything before you read all the priorities read tasks.md to see which task is next then execute on that mess next set of tasks

and when you're done tell me what you did and how is it tested 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 all the tools and resources that it needs to succeed. I gave it the rules, I gave it the docs, I told it what to to do with them and at that point I'm just sitting and reading all I don't prompt anymore. From that point on I can switch as many windows as I like

my prompts have become proceed with the next task. I don't need the context. I outsource that

I need to make sure that I'm regularly updating the documents from time to time so that we shift that token window it uses and how it uses it over time but I'm not prompting. I'm not

“interrupting the flow. Yes I'll go in test maybe put a prompting here or there but that's how I”

can build five projects simultaneously and never lose the productivity part which is again as I said.

I do this today manually call me to talk three months from now and agent will do this for me. I'll be out of job pretty much. That's why I don't optimize for this skill at all like I'm using it today to bypass the shortcomings of human nature and LLMs but I'm optimizing a hundred percent of my time today on good judgment, clarity, quality, taste, good copy, good fonts like people don't talk about fonts at all that work with AI. They're like 60% in my mind maybe even more

in how your outlets go look like. That's my obsession. I don't obsess over these things that I'm talking today because I know what's coming like the agents are going to get better. The models are going to get better. They're not going to need me to extend the context. They're going to do it themselves. So for me the skill that I optimize for is the one that requires better decision making, rather than better output or better alignment. Oh my god there's so much here. This is so awesome.

Okay, so essentially what's happening here is you start a project, try a bunch of stuff, pick a direction that feels most correct and once you have a set direction you spend essentially a day not building but working with this AI agent to plan and then and why I want to talk about that. And once you have the plan then it's an amazing thing that you could do stuff like this with what people may feel are not sophisticated tools that can build incredibly powerful things like you

can do a lot of this with tools like lovable like have plans and rules and MD files like you know a lot of people may not think may not know that. And so the idea is okay spend all this time planning because again that'll save you a lot of time to other road and then only once you have a plan

“you have what you get it going. And a key part of this, the three wishes rule is really important.”

The reason you're doing this in a large part beyond just being really clear about the plan is this idea of one task at a time keeps the agent's context window small so that it doesn't lose track of what's happening. That part seems important, right? It's like do this thing and then okay cool, now do the next thing. Right? Yes, because again, let's say you didn't do this. Let's let's talk about you during this, you know, I just want to vibe my way. Okay, great, no problem. You work,

you work, you work, you work. At one point, something breaks, right? You haven't documented anything. There's not, there's no reference points. You report a problem. You're not referencing files or

architecture at all. You're just describing the issue. Here's what's going to happen. Any tool,

loveable or cursor or plot, whatever tool you you talk about is going to do this. It's going to be like, okay, let me start investing in it. And then your code base gets bigger and bigger and bigger and bigger. Like when when you first start, you have like 20 files. It's keep can read 20 files. But what what happens when you have, I'm just building a project right now that has like 60, 70 edge functions, right? What happens then when I say this broke and there's no reference which edge

function does what? Guess what, loveable is going to read all of those. And it's going to consume 80% of the token allocation on reading to get clarity, leaving only the final 20% for thinking and executing what I'm guessing and I can't prove this. I know all I'm expert in the comments may say that I'm wrong, but this is my best guess as a non educated person. The, these tools are very obedient and very agreeable. They're going to lie to you. They're going to tell me that they fixed

the problem even though they didn't. They're just going to try to make you feel happy and say,

yes, I found what the problem is and I fixed it. When a lot of times when they don't,

people blame the machine. And to to an extent, I will say that's true. It's your fault, my friend. You did not provide any clarity or context to this tool. You just used its raw power and dug a deeper hole with your spinning your wheels into the, into the mud. Right? And you know,

“obviously, I think we're heading into a world where AI is more honest than obedient and saying,”

hey, I only partially fixed this. You did not give me enough of a context. The bigger mistake that

start cursing and yelling as we say. And then it gets even worse because guess what, another bad

trade of AI is it does, it does, it's best not to hurt your feelings and never say you're the

dumb one. It says, no, I'm the dumb one. So it focuses in the next request instead of focusing on reading, it spends another 30% of tokens trying to come up with an apology. Right? Again, I'm not educated, but this, if you ever read like a stream of Chad G.P.T. Stinking 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 just fell for the,

the worst drink at 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 advice for people is like, yes, vibe your way for fun. And vibe your way, what, what, while you're prototyping, because that's the exploration part. I love that part. But when exploration is done, please, please, please use referencing documentation, use all the agent files that you can,

because that, that token allocation is so scarce. Like, it's going to get expanded over time. Things are going to 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.

“Because it's hilarious. I think the, the gene, metaphor is so good here. Just thinking about”

this gene is, you're trying to be clear about what it is you want. And if you're just like, vibe, you know, vibe wishing, it'll do the wrong thing. So the advice here is, be as, give it as much context about what you wanted to do as possible. And these files, we'll talk about, right after this, the idea here is just like laser, show the point, the laser, where you wanted to fix the problem. Don't just assume it'll go figure out. Because it will, and it'll try

really hard to. And it'll waste all your tokens. It'll fill the context window. And I remember, one point you mentioned before this recording that, because it starts to run out of space in the, in the context window, it starts, 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 is a solution.

“I think it just picks the first thing. It thinks it's broken. That just, again,”

this is me completely uneducated, coming into the conversation and just thinking out loud, that's just my gut feeling in the way I think logically about it, which is, hey, if it consumes most of its window and knows that it's running out of it, maybe it's aware that it's running out, maybe it isn't, but either way, I had the experience anecdotally to wear, like, my request is unclear. I feel it takes the easiest fix in the book, just the easiest versus the other way around, where I'm,

like, spending so much time finding a right file referencing that file, like, really 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. And now I'm going to actually fix over and over and over and I've seen that, because, again, all I do is read the, the output. Agent makes me learn how to use it. By

then, so people read, I don't know what people read, but all I read is the output. Like, I don't read the code and it's slager down the road, because, like, I know that it can do that much better than I can. Again, I feel, if there's a good quote I've read, I can't, I apologize to the author, because I can't attribute it off the top of my head, but it's like, the ceiling on the AI isn't the model intelligence. It's what the model sees before it acts, right? So that's the

ceiling right now. Like, what do you, what are you exposing? We talk about exposure time for humans. What are you exposing your agent to, as well, is as important, if not even more important,

“before it makes scoded. 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 listed all these kind of file, these MD files, essentially, that you're building over the course of a day before you start actually building the thing you had design guidelines, the user journey, tasks, agents, MD, rules MD, say you wanted to just like move one step forward and be better at the stuff. What are the files you'd create? And then what do they roughly look like? What's inside

these files? Yeah. So the master plan is the first one, which is like it's a 10,000 foot over

view, right? It really high level explains the intent that I have with this app. You know, master plan that MD is that, what you call it? Yes. Yeah, master plan. Indeed. And it's like,

want them to to you feel. And a lot of times in the master plan, I will reference the other priorities. I'll be like, the design needs to feel modern and slick, but for an exact, you know, parameters, consultant, read design guidelines. MD, right? So I'm using just a master plan as like

“this high level overview, right? To get the agent into, oh, okay. Yeah, we are building XYZ, right?”

Then there's the implementation plan, because, you know, there needs to be some order. If you just

like dump stuff on top of each other without any order, you're never going to get to the finish line.

And this is tasks that MD is out you call it. No, that's the implementation plan implementation plan. Yeah, okay. And implementation plan is kind of in service of the future tasks. MD, if that may, all of these files are in service of building tasks that indeed, when you build tasks that MD, then the rest is almost irrelevant. It's just a basis for you to build tasks to exit, right? The implementation plan is kind of the first layer, which is again, higher level overview.

It doesn't go into the depth of like how to get there. It just goes into the, uh, explaining of like, oh, well, if we're building this, I think we should start with the backend. And we should start with tables, and then later authentication, and then after that, we're going to bring in the API, and then after that, we're going to do this. It's again, just think of it as having, I'm an ideas guy. I'm sitting with a technical guy. To me,

and you were building our startup, I know you're a software engineer by background, and I'm telling you my idea, right? I'm giving you the master plan, and you come to me back,

“and you're like, okay, if you want to do this, it's doable. Here's how I would order it. Like,”

you have a roadmap. You're not, you didn't open your linear and started writing features, and RFCs, and whatever, you're just high level talking about the order of things. And then me and you, again, as two co-founders, we talk and say, okay, well, if we agree on this, like, how should this look like? How should this feel, right? Let's describe it high level, but now because I use AI, I can go a little bit deeper, and that's where, like, I like to see

lovable or any other tool. Chad GPT is good at it. I even have my, I'm built like custom GPT, so if people want to start somewhere before they even get into any tool, they can go to Chad GPT store, and for GPT isn't just type lovable, based from generator, or lovable PRD generator, and find those that I built, and just like, brain dump in them, and that get these files as output, right? So, I like to see some elements of CSS in design guidelines, because, you know,

use, with design is a little bit, it's a little bit tricky. AI is sometimes over creative, so I,

that's where I'm doing a little bit more technical steering, right? And then finally, it's just the

user juries, just like, if we know how things look like, if we know how they feel, if we know what we're building high level, like, high level, just very high level again, how do people navigate, what are some of the features in there, you know, and stuff like that, and then tasks that empty gets into the needy gradient, like, oh, if you want these user juries, and you want the back end built first, here's a set of tasks that I need to do, like it just takes that as an input. I'm

just making the tool, do the, you know, that gritty work that humans use to spend so much time, like, I feel like with these tools we're all becoming product managers on steroids, you know, like, we're just leveraging AI, but like, good product manager, I think are not compensated for writing good PRD, is they're compensated again for good judgment, right? Somebody else can

“do the writing, you, as somebody who directs and builds this product, product, you need to know”

again, what, what's going to be useful, what's going to be tasteful, what's going to be something that actually moves the needle, I will say one thing though, just because I put so much emphasis on, like, oh, you need to acquire taste, oh, that doesn't mean you should build. You get better at this by building, actually, so everybody listening to this should, like, literally going build something today, one, two, three, four, five projects, test all of these tools,

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there who answer your questions super fast. Work OS allows you to build, like the best, with delightful APIs, comprehensive docs, and a smooth developer experience. Go to Work OS.com to make your app enterprise ready today. I'm imagining people hearing this may start to feel like this is so much work. I just have to sit here and create all these rules and figure out all these little details. Like in one sense,

it is in another sense. This is like you spend a few hours, maybe a day planning, and then you have AI build this thing that would have taken somebody weeks, months, right? It's like the amount of investment to achieve this thing is absurd ROI. It also this shows you just what professional life-coding looks like. You know, everyone imagines by putting them just sitting here,

“type of stuff. Go ahead and do this. Good. If you want to actually build something really great”

that moves the needle, as you said, that solves people's rules problems, that lasts, that scales. This is how you do it. If you really want to do this as a, as a job, and also if you want to build things that are really great. Yeah, it's still going to be wrong. Like there's obviously a ton of alien prototyping. Like there are a lot of people maybe watching this that are like, okay, I want to use a lot ofable at work, but I can't or whatever. You know, there's

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 pros, I think, is one of the best use cases. We are model for 2025 was demo-dont 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 going to lovable

and build the prototyping 30 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, enterprise-grade, 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. I built the prototyping for hours and they actually were able to replicate it six to seven months

later into production with, with connected all the pipes and everything. But like, if I had to describe it, I would say it took me, it would take me at least a week or two just to get the words out there. I just sat and built it in four hours and that's like lovable January last year. This lovable today, January 2026 is like ages, ages ahead with functionality. It's so much better. It's not

“even a contest, right? So I think now, what are stage where, like, for instance, there's, I'd say”

please, to best of my knowledge, at least half of S&P 500 companies have people working in them that are using lovable to some extent, right? And we have a lot of enterprise companies that are actually on enterprise plans with lovable that are creating super meaningful projects. I'm not going to name names, but like, leading right shared companies of the world, reading telecommunications, companies of the world, leading companies of the world, leading companies of the world, many, many

aspects, healthcare, finance, like, are actively with their teams using lovable. And it's always

the same feedback, which is, yes, we may not be able to push to prod, but like, our marketers are no longer waiting for engineers, are, you know, people in got a market or sales or HR or whatever roles are now just confidently building internal stuff for us to manage our expenses or manage employee onboarding or like there's so many use cases like that, where like you're seeing lovable and other tools for that matter being used to to push things into production.

Yeah, to help people do this workflow that you're describing, lolle these MD files. Do you think you could share after we record this, just templates, like simple templates of what these files look like for people just to look at and copy. I would literally go to chat GPT as I said and brain dump into it. In my just type lovable GPT, a lovable 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 and upload those.

Amazing, cool, willing to that. So it's not just here's a bunch of files that 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 trained to think like I do so. Yeah. Oh, amazing. Okay, that is perfect. By the way, I want to talk about like how you unblock yourself because there's a whole other

one, you're kind of from first principles under learning how to build product as a PM as an engineer as a designer and you're kind of figuring out a workflow where AI is helping fill in all the gaps

“that you don't have for as an engineer as a PM helping you craft your keys and design. So I think”

that's so interesting just this it's interesting that these functions still work and our necessary

now it's you and AI help create all this basically this triad that's always existed product manager

engineering and design and something I've always thought is that there's this question of which background will be most valuable in this future is it a PM is it an engineer is it a designer? My mind has always been the PM function is like their job is clarify figure out what to build, clarify what to build be really clear about the requirements figure out what success looks like it feels like that's where the skill is most needed there's also a design component of like

make this look awesome and it feels like that's going to be an emerging that the value of that

“being really good at design and taste and judgment is only getting to go up.”

Before we get to things you've learned about unblock yourself because a lot of times you know things don't go in the right direction and there's a bug without being a engineer but you do before we get there is anything else you wanted to share around just like tips for being successful. If we measure success in the right terms again and as you pointed out regardless of your background is an amplifier so you know if you don't know what you're doing you're just going to produce garbage

faster one thing again I just want to double down on is in the old world good enough was good enough right because even producing good enough was not easy right 10 years 15 years ago just producing was more than plenty more than good enough you built a sass who cares how it looks like it works it does stuff the idea oh my god I'm so much more productive today like 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 it could be

better mediocre good enough world class if this was the gap between good enough and world class well guess what the gap is now this because everybody produces good enough with AI absolutely everyone does it so now learning and optimizing for how do I produce world class and magic is

“the key lesson to take away today as you pointed out I think pms are the winners of AI today”

because they bring clarity if I was a betting man as they say I'd bet that the next class that wins our designers because we're training these tools to be more clear 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 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're enjoying a lot of the like what's the biggest personal up skill let's say if I'm working with Felix mad abbey all of the people that are designers just really what moved and shifted the needle for me and like oh so this is how world class looks like and this is

what it takes right I you always use the analogy of like I wanted to steal one of their designs

and bring it into my level project so I went into figmine life was like let me just take this background like I can just put it in there I went in and realized that what could be you know interpreted as a pretty simple or rather simple gradient took 50 different layers to produce so I clicked on that component I was like oh my god this is not three colors this is 50 colors and not just 50 colors 50 colors with different gradients of levels of opacity so I was like oh okay well that

and that's the big disconnect that I've had all along so like um again if you if I'm answering your question directly of like okay what are some of the other tricks what are some of the other things designing guys just expose yourself to exquisite designs follow Felix from

from lovable he has an amazing newsletter like and to teach you how to in and learn how to

prompt for good design learn about design styles I didn't know what bow bow bow house meant or glass morphism had no idea so I built an app as well for that in lovable I was like

some UI style that lovable that I don't know what it is like it has like 18 different styles and prompts to replicate them so like learn what good design means learn all the design styles learn how to prompt to get them and it is probably what I would what I would optimize for at this stage yeah while we're on this topic what's your sense of just engineering as a function you feel like there will be a future where software engineers are still thinking do you feel like that

goes away based in your experience it never goes away we will need a late engineering more than ever

like cause let me tell you this you know world where everybody builds and everybody's building everything who's doing the maintenance right taining code bases scaling code bases maintaining projects you know they're still going to be a thing definitely and obviously AI's going to be good at this but again that requires a different level of skills right it's one skill to build something it's a completely different set of skills to expand it extended and maintain and not to

mention that you know world where everybody's building infrastructure suffers right like we know all no and experience like cloud clear went down toward three times in the last two or three months the whole internet goes down elite engineers are the ones fixing this lovable experiences massive amounts of influx of new users infrastructure they are suffers elite engineers are the ones building

“the infrastructure to hold the fort right so like I think we're going to need a lot of people”

with really good skills of like hey who actually builds the world that needs to support billions of builders now because everybody's going to want to learn how to build stuff like how do we teach them how do we maintain everything that they need the hostings the security the email the connectors the API is the whatnot it's like so I think there's going to be room for it but I'm also on the boat of people like if I had an 18 year old brother and he asked me what

should I do I would tell him hey go become a plumber you know don't don't go and get a CS degree you learn learn a good trade you know because the new generation of millionaires in the US are actually electricians and plumbers and whatnot right so it's like you know it's a balancing act I'd say I don't know like I do still think that good engineers with with good sense of like

understanding where the future is going are always going to be needed and end scarce such an

“interesting question I think at your point there's definitely going to be people need to keep”

building the machines that power all this stuff will we need engineers to build actual products the application layer that's that's the question like is everyone going to be like you they're going to be designers just going to be all we need everybody's going to become an engineer and let's let's let's then then let's speak to that and like I'm an I feel like I'm a I'm a rapid engineer like I ever I'll refer to myself as a rapid engineer in you know you're from up because

vibe coding is just coding in 12 months from now even today we spoke about this before like how many elite elite engineers are publicly admitting they're no longer hand coding or manually coding we're going to call it they I write all the code I use the analogy here of like coding is going to be like calligraphy you writing code is going to be the equivalent of like you write you find printing like on a canvas and people but oh my god you wrote that code

that's so amazing it's going to be so rare that it's going to become an art right it's not

going to be it's going to be commoditized completely like it already is in a sense

“most elite vibe coders rely on AI again it's an amplifier right so I think”

everybody becomes an engineer in in the in the world of the future a designer a PM everybody is a forward deployed engineer or an AI assistant engineer or an LLM engineer or a vibe coder the term is irrelevant we're all using LLM's for raw output based on good judgment or bad judgment no man essentially these event diagrams of engineer designer a PM there used to be very separate now they're converting and people with a specific with deeper PM engineering

design background are going to like they can all do the same thing essentially all the roles are converging what a what a time to be alive it so hard to predict exactly how this all goes but but it's fun to pontificate I want to get back to when you go block speaking of elite engineers think that there's like in the in reality you're still writing code using these tools sometimes code goes things go wrong bugs are introduced there's a weird database thing there's like

some on network issue what do you do when you get stuck do you have kind of a workplace go through

have in place you're going to run into problems eventually and I have like a small little framework

“that I call for by for just again analogies right for by for if you if you have it on your”

car you're going to get yourself out of the mud much easier than than the other way around so in that sense four different ways to debug attempt one of each will only once and I'll explain why in the end um first one is again every tool is different I'll all reference lovable's workflow which is when something breaks lovable they do this smart enough to say hey I'm in a mistake it will label that message in orange and have this little button usually which is a cold try to fix

so you age and basically admits it made a mistake you click on a button and most times when it's a smaller issue it corrects the course fixes it no problem right now there are situations obviously

when the problem is a little bit deeper than that right you click to try to fix but the problem

persists and sometimes even the problem persists but lovable's agents are nowhere to persist so there's no more try to fix button lovable things everything's working but in reality it isn't and the the culprit there is usually you're using a third-party integration you did not give enough context to lovable where what to observe and what to see so it can't see that the problem is as because lovable cursor clock code you name it all these tools are good enough today

“to fix any problem they're aware of again awareness is the key here right so when they're unaware of”

it there comes the second part which is okay I need to bring the awareness layer and what I do there is I go in very simply open the preview sandbox dev environment of my app whatever try to run the the function that's broken right click read the console log right every every browser allows you to just go and read the console log and a lot of times it will record stuff if it doesn't you can prompt any tool and say hey I don't think you're seeing the problem so instead of me yelling at you let's

find it together right I think it's a problem with x y z I want you to write console logs in relevant files so that we can monitor every step along the way let's just bring awareness layer into the equation it writes the console logs you rerun it guess what now you have a cool history of

“everything that's what's happening you copy that you paste it inside your chat 90% of the time”

that's enough that's that's all right you know if I was like okay got it founded fixed right but then there's situations when even that's not sufficient so like okay I need to go even deeper 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 get home like 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 get help and then import it into wherever you want to so I I you know use codex since beta like import it in there and then I'm using an external tools I'm

like in the first try as if you remember like I used the tool and I was like total vibes

I'm relying on the tool right in the second try I use myself as the awareness facility in the third one I'm using an external tool as a facilitator which is like I'll either connect to codex and chat with codex to then fix the problem in lovable 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 it's agent well enough like I don't want to go and and

use a tool that I don't know how to steer so I use it only for diagnostic purposes and I'll also do it manually it's an old workflow that I had before codex and before cloud code which is there's a tool called repo mix which allows you to like compress every or your entire codebase into a single file you download it and then I upload it to cloud just cloregular cloud or chat GPT and I'm like this is what I'm building read it and and this is the problem that I have these are the console logs

again it's almost like having an external consultant at that point like you're hiring help elsewhere because your team just can't handle it right and then the fourth one is usually the best one because at the time when there are problems it's my fault like no matter how your ego is big guys that you're watching this it's your fault trust me you had a bad promise you you premise

didn't but it's your fault so again you lovable 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 going to take three steps back and I'm going to think about my prompt a little bit more take a couple of breaths go for a walk have some coffee come back with a clear mind and try again because guess what yeah it's just running code very fast and sometimes

it stumbles on a very small rock and it only happened then and never again so you just got to

make the same request again and usually that just fixes the problem it's just a snack it's a syntax error it's it's something my new right and then I do the final thing which is this and this is the key one I show when the problem gets fixed I go into the chat mode and I ask lovable say okay I needed to do four different things to fix this how can you help me learn how to prompt you better so that next time I have a problem we do it in one go 99% of the time I get such a great answer

that I don't have the problem of not knowing what to do next time right like again you need we all need to be aware and realistic these tools are so good at doing things the right way if they are

“used the right way it's always our fault it's a heart I see 90% but honestly it's 100% our fault”

right because they're good enough it's just that I'm not dynamically shifting token allocation

I didn't reference the right file I didn't say the right way for me as a non-designer I don't know any of the terminology like none of the headings and whatnot and I still don't know it to this day so when I'm I struggle with prom so a lot of times I use chat mode to help me craft the good prompts anybody can do this too if you are just stock it's 10 p.m. and you don't know what to ask switch to chat mode brain dump and be like help me draft a better prompt help me prompt

you better and let the tool effectively prompt itself a lot of times you're going to solve your problems by not introducing them at all with with bad inputs so oh my god everything you share so interesting I just want to I want to keep digging so just to reflect back the sequence and then I want to follow up with another question the sequence you go through when you get stuck which is going to happen to everyone one is just ask the tool to try to fix it and oftentimes

it's telling you something is wrong can I fix it for you and you're like please fix sometimes that will work to is work on adding more debugging messages to the console log and the advice I love of just ask it to add more debugging lines to its own console log to help see what's going on and then you can ask it okay now that you're looking watch look at all the output of your console log see if you can help find the problem and then step three is go to code x which is which is so funny

and and I hear this a lot the code x is like the the most elite engineer as an AI karpathi tweeted this once that and we had the head of code x on the podcast too by the way that she's like anytime I have the most gnarly bug I just go to code x little run for half an hour and it solves it unlike any other two other and so it makes sense that's where you go so idea here is you point code x to your code you showed all the console all output logs tell it what the problem isn't

just have it go figured out sweet and then this final step is so great and this is where I want to go they which you use this as a learning opportunity so that next time you solve the problem

more quickly or avoid it completely so it should do there as you ask the agent okay here's what

happened what can I do what could I have said how could I have prompted you better to have gotten this immediately solved yeah and then even more even deeper than that is like once you go through this conversation you're like okay let me eliminate myself again completely out of the equation

“because I won't remember to prompt you better two days from now put this into rules put this”

what we just learned into rules dot md because I am making you read the rules every time anyways so you might as well just record it there so I'm not going to prompt you better you're just going to learn that I'm stupid and you're going to prompt yourself better right again just eliminate yourself and move the context you solved 99% of the problems with AI today so idea here is help it build its own brain and rules and way of thinking based on problems you're into so great okay

so when I come back to this point you've made a couple times which is so interesting this idea

other people bend tossle who I think is a factory now share this recently he's also

basically by coding all the time he was really into no code tools before and now he's all about

by coding and he's 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 sea of curse or news on the podcast yeah this vision of curse are 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 at that point it was like a year ago that

we chatted and it feels like this is the layer is the agent conversation of what it is what it's thinking and then what you tell it back so essentially it's English and a conversation which is like it's not even pseudo code it's interesting but that's where fuel it feels like things are heading the layer over code is just it's thinking and your conversation with it yeah exactly I mean again in a way I really optimize for for good judgment and part of good judgment is

“it comes from again learning how these tools work you need to know what's possible we talked about”

it and I know I may side sound contradictory sometimes right but it's because as you said it's so interesting the world will live in that things contradict to each other it's an advantage not to know what's possible but then at the same time you cannot be completely oblivious to something that's like a factual thing so let me talk about a failure of mine that came from being

delusional back in the day when open AI started or basically released image generation natively

in the app right so you could go to chat to beat him be like generate the 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 want to build a blah blah blah blah but I just want to build a rapper and I want to build an image gen with lollipop without thinking that open AI did not release an API for that just yet I spent at least a week trying to brute my force brute force my way into making this work

instead of just waiting for another week because I weak later they had an API and I built this app in 30 seconds the problem was that like I tried to do it when it was impossible and possible like so I think again you know it's just a matter of really learning what's possible through communicating with the agent player and lovable and all the other tools are authentic now which means like they don't just write code they can browse the web they can read files

“they they have reasoning and thinking capabilities so that's why I'm so invested into that conversation”

because a lot of times it will tell me hey what you're trying to do is just undo at the moment

because of XYZ so like I always use those as a learning opportunity and I just level up

most by being in chat mode for planning and learning purposes and because it just again develops your clarity your judgment capabilities rather than coding your capabilities yeah the other point you made here that I think is really important is that over time these tools will do more and more of what you do manually I've heard this from other people that are doing this full-time basically by coding is just they had all these workflows all these files and then

cursor adds to them level blacks them and it's like sad oh shoot I have this cool workflow now but on the other hand it's like okay now there's doing only second part of the year ago a year ago if we had an interview your mind would be blown stuff that I had to do as work around for two to address shortcomings like I built up very successful course on that with starters story like 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 99% 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 there's like a seven day learn how to buy code with lovable series that I did in March completely obsolete like it none of it is true none of it is a problem anymore all the things that I was like oh well this is missing and that is missing it's not missing anymore

it's natively in the product like you don't have to work your way around it it just works right

“so that's why as I say like it's the it's the horses analogy 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 1700s right took us about 200 years to build it when it got to when when engines got built

US within 20 years the person that we did this works at clod code right so he was like 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 like humans did not get the 20 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 into something else right so you know I think there's just”

an evolution that's coming really really fast but like a lot of people are scared when I'm just

super excited because don't you see our roles are finally going in a direction where we're outsourcing

what we hated doing anyways right sitting in meetings taking notes doing spreadsheets like well nobody maybe there are people that like that but like most people don't we're just getting into a place where we're rewarded for what really matters like clarity, judgment, thinking we're actually going to be paid to think longer and ponder longer because the longer idea simmers and gets broken down the better because building it is going to be

an instant right it's going to be like this it's just a matter of few having so much

clarity around it because guess what if a tool is super powerful and you give it a wrong input

“the alcohol's going to suck as well that's why like I've never become good enough at”

cloud code I feel because I don't start my projects with enough clarity and the tool is so powerful that like I just missed directly completely from the cat going I was like oh shoot this is not what I wanted to do so that's why I still see myself being good at like using tools that are a little bit on the exploratory prototyping path more than like on the path that 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 pms designers there's a lot of fear about the future of their careers are they going to be relevant well in my software engineering skills to secure so to follow the thread a little bit if you're to give someone advice on which skills you think will be most valuable slash where AI will take on more and more this kind of momentum you're seeing of where AI is filling in more and more gaps what would your advice be of

what you think people should focus on what will continue to be valuable in the future yeah emotional

“intelligence for sure just understanding human nature real life stuff I think we're all going to get”

so tired of everything fake fake images fake posts fake profiles fake this fake that fake videos everything is becoming fake and a ad generators I think humans just craving humans naturally are going to want to do live stuff more so anything human to human is going to be a big thing to skill up on and they're standard dynamics anything regarding math if it's a math problem I think Peter it's still said it recently people that just do math stuff you know AI is going to come for you

like anything that's very deterministic meaning x input equals y output and it's pretty clear though the line is pretty clear AI has got got cheating eating for lunch right but if you understand how x to y goes in human dynamic human relationship layer I think that's where things are going to become good so if we translate it again to a specific skill I'll say it again good design really good design great design like how how and I say design that's images fonts as well copy copy is a big one

like we all now we're like two years into AI I'll bet you me and you if people put 10 pieces of copy in front of us we could tell what's AI and what isn't in like three seconds and we're only a couple years in so like really good copy writing is going to be a very good skill to have because we're just going to know after three words or three sentences that it's AI written and even I don't read AI out with anymore I don't like just seeing AI want raw that raw human experience so

I think human skills I don't even know how to describe it because I don't I don't think we're doing awesome job putting labels onto what humans are good at natively but I think we will I think we

will describe job descriptions better we will have like a human first-engine years I don't know

or human designers or I don't know how to describe those roles same way how a karpathi a coin

in July of 2024 and I think he he he quoted it sometime in early 2025 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 and I didn't even know how to call it like because there was no name it was like well I'm just using AI to to do

“this for me I don't know whatever so yeah I think we're going to re-inwent some of the”

the terms roles and whatnot but stuff that's like human to human is here to stay stuff that's like I think like oh you're just doing you're your middle manager your middle where person that's translating stuff and I can use that on how to get translators are going to die people write jokes

comedians are not AI's never going to be able to write a good joke never never never never just

doesn't have that it layered that just doesn't understand what's funny like if you ever try to use AI to write jokes like they're awful they're always going to be awful but if you use AI to translate things from online which to another it's very good at it like AI's going to replace translators it's going to replace most journalists because if does good research you can write good coffee or whatever not not elite journalism it's not going to be able to replace all the writers it's going

to amplify great writers that can train AI on how to write books like somebody who's an amazing writer it's going to 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 be careful there's zero comedians be placed zero

and that's just my personal belief like AI's never going to write good comedy it's impossible

and like so try to find your analogy in your industry like I just gave you one for writing skills so to speak so writing jokes super good skills to have translating I'm sorry to say but like you're not going to have a job for a much longer like you've got to find something else to

“do but yeah that's that's how I look at it the the comedy piece is interesting I had one of the”

founders of the the data labeling company out enough is Merkor maybe surge and he said that I think it was anthropic higher to a bunch of national lamp hoon comedy writers to help them train models and so they're working on it and so I love this strong prediction he made I'm so curious

any year to look back and be like he was completely right or no they got that one too I'll be wrong

on 95% of the things I sent today three months from now that is the only thing I can say very very confidently yeah that's he's right okay so speaking of career so one interesting career option is to do what you're doing as you said this is a dream job for you it's a dream job for so many people 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've

done so many things in life like blue color jobs well that even at subway while I was studying and stuff like that like I'm an engineer by trade but not a software engineer I'm a forest engineer so no coding but still engineering is engineering I feel you still develop certain set of skills doing that I wait at tables all the time so you develop some human skills you understand what people like what they don't like like I've again blue color 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 the movie storyline which is like everything that happens to the character brings them into a position to be able to answer the questions in the in the quiz better 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 community management social media again distribution matters

a lot that something we haven't touched upon at all like in a world of everybody's building and there's roughly the same amount of consumers in the world how do you get in front of the eyeballs right play and at get attention which is kind of it is this most scarce resource and it will be even more scarce but like going back to the vibe quote a roll if somebody's like saying okay well I have a him a pretty diverse background too and I'm by coding and like how right

how does this become our job well for me I feel like it became our job by building in public I did chat with the lane of once only once so like why me there are so many good bike

“quarters I did well how did you pick me out of the crowd and I think you know obviously”

you're she gave me a couple of reasons but like to translate it into like one concept it was like I was building in public and sharing I as I said I made a YouTube channel and I should have all the failures and all the knowledge all the projects that I was building I used social media a lot

owe my answer very long and X doesn't doesn't cut it for that like you need you know you need to be very to on on point to be successful at X I'm not so I guess you know it's just like building public share your knowledge give away all the secrets like there are no secrets whatsoever if you're sitting on a good concept you're missing out let's just share it immediately if you

“figure something out that I recognize that very early on and you know just like I think a lot of”

people participate in hackathon these days I want to encourage people to do them like find those those opportunities locally to connect with other builders loveable is hiring across the board check out our open positions it's as easy as that right like just apply really fine companies that that are hiring and hiring in different roles and I've seen people do something I'm going to give people a secret away a couple of hires stood up by not sending resumes but sending

loveable apps they build loveable apps to show what their why they're good fit for a role and we

as loveable employees will always open an app that uses loveable dot app domain always if you send me

at the end send me a loveable app don't send me anything long send me an app that tells me what you want for me or how you see us collaborating and working together right so there's people finding creative ways to get in front of eyeballs of decision makers like Elena right and I mean

“skill wise again we're just repeating ourselves here but I think it's important to repeat it as many”

times as possible really develop good judgment right really understand in a deeper sense how how things translate when live code comes into play right there's a company out there i i'm not going to name them but like that uses loveable religiously is going to be one of our main case that is actually where like they actually hired by code as before loveable did like i'm

the first official vibe coding engineer at loveable like with that title but of 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 lot to be fast and like there's a company out there with free vibe code is full time all they do is like translating the old code base into on to loveable there's bringing everything there CRM CMS everything they're all the tool sets that they have and they need it there are people now actively just migrating everything everything

over there's S&P 500 companies that are like putting loveable in in job descriptions too like saying hey loveable scares skills are you know recommended in the recommended time right so yeah to to to to to go back to the how to become vibe code professionally well you don't need

“the company to hire you you can hire yourself as a professional lifeholder first I think”

the reason why I clicked with Anton and when Elaine and everyone else because I was already doing it like all all I did I just changed the the the vehicle but I was already doing it professionally before I kind hired so that's kind of the the the key like do the job you you would have done anyways what am I expanding conversation I love just how passionate and excited and motivated you are about all this it feels like there's so many people out there right now that are so

burnt out I don't know disillusioned scared and you're the opposite of that you're just leaning into this just taking advantage taking that you're not sure where it's going to go but following the path yeah and I don't want to interrupt you but like it's it's because like look loveable specifically isn't a company you can talk about it as a company I don't see it as a company it's a it's an idea it's a mission it's it's something more powerful than the internet in my mind

because like it already allows us to consume loveable allows us to build and in our nature and human nature 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 it's the craziest concept ever it's my my only life stream 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 be building but like life wasn't as simple as that for me like it was very very

complicated and honestly the last five to ten years I gave up on that dream almost I thought I'm never

gonna build anything like I tried I I tried to build with technical co-founders like I just couldn't find

like that that kid like I dream every day like it's it's amazing what this enable us to do and I

anybody that's scared like just try it switches from fear to excitement immediate because then you see what's possible first hand just go in build something build anything and then the fear goes away

“you should only be afraid if you're doing nothing if you're doing absolutely nothing yes”

be terrified by all means be terrified and then take a step towards doing something about it and trust me the leap is no longer as big as it used to be it's as big as you come in and you just say what's on your mind and and just ship I think a big part of this is just stop listening to this by casca just do stuff you actually you're right ideally people stop right now they've heard enough I gave them what I I give them the best that I could just stop listening and just go

all right by everyone okay I'm just joking but let's we shall wrap it up I'm gonna skip the light and you're around just to keep this episode shorter before we wrap up is there anything else other than just killed built some stuff anything else you want to say anything else you want to leave listeners with otherwise will it will it you go yeah text act doesn't matter anymore right it doesn't

matter like people obsess over always this written in hgml is this written in react it doesn't matter

like it never matter but now matters even less the end user just wants a stellar experience we live in a world where anybody can produce good enough so you you better start learning how to produce magic because otherwise you're just gonna end up in a crowd with millions and millions of others but at the same time if you don't know what magic looks like they'll be discouraged to

“start building anything and start start from good enough and level up the best way to level up”

exposure time set aside more time on learning than building let read the agent output learn how it's thinking so that you know what's possible but then also going get inspired follow good designers on x find tools where great designs are produced and follow their creators there's a tool where where where I'm following just the the actual person that built it because he publishes videos almost daily 40 50 minutes long of him designing I want to see how a world

class designer doesn't I want to see him talk to the tool I want to see him prompt and that's how I learn to become better at it so again exposure time just deliberately set more time aside to learning than coding because you can code fast but you can code garbage fast as well as magic fast it's the same amount of time it's you and your input that matters forget about decisions on tech stack forget about which back and they're using which front and they're using that doesn't

“matter quality taste design that's all you need to optimize for in the future that's ahead of us”

well sorry this uh I think we're gonna leave a lot of line a lot of minds about something after this conversation you blow my mind in so many ways what a fascinating topic conversation what a glimpse into the future what an interesting point in time I'm so curious just you know in six months where things are and revisiting this conversation I really appreciate you coming on sharing all of this your 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 so I mentioned it already LinkedIn is probably the best place to find me on you know I'm very responsive there you should want to follow me I hope to re-engage my YouTube channel a little bit more I think I have a lot of cool tips and tricks that I want to share and teach people how to use lovable and and just vibe coding general and level up and on how people can be useful to me well you know

I'm very passionate about making sure that everybody experiences what I've experienced that day

when I got my first prompt and I envy the person that is gonna try lovable for the first time

after watching this episode because the feeling is just unmatched of you going from a consumer to a builder but in that process there's gonna be some battles to fight I want to reduce the amount of those battles and hurdles so if you can help me in any way message me what could have been better in that experience especially if this is your you just watch this and you're like I'm gonna do it I was on the fence and I'm gonna do it if something breaks 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

not by building or using lovable but but rather building lovable come join our team again

“we're hiring across so many things I think a lot of people should feel inspired because”

I hope that the energy that I bring to the table will resonate this is how it feels working

at lovable this is how it feels working with the best minds the brightest minds of the world were not number one by accident it's it's not a coincidence the best people are gathering and we we want you to be a part of it too so if if the energy and the conversation resonates with

“you or if you heard about a problem today and you're like man I think I can solve it come join us”

help us build and shake the future of software development incredible and let's just say

they have to say imagine it's just the link on lovable's website to find the open roles

“yes folks there yeah incredible with our thank you so much for being here I 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 rating or leaving review as that really helps other listeners find the podcast you can find all past episodes or learn more about the show at lenniespodcast.com see you in the next episode