Replit CEO Amjad Masad on 1 Billion Developers: A Better End State than AGI?

29:10Talk to us a bit about Repplet Agent. Yeah, so every year, we implemented a co -pilot like features. We're actually the first startup to train code models outside of Microsoft and OpenAI. We also have some of them for a small time. There were soda models. There were three billion parameters. and that was really exciting, but the thing that I thought would be transformative is agents. I actually had a thread that went viral at the time in 2022 about how soft operations will change programming and perhaps the economy. And so every year we tried it, I remember we tried it with the GPG3. The context window wrangling that we had to do was insane.

29:56like we had to, every time we generate a class or a function or whatever, we'd have to like summarize it into one sentence and put it back into context to be able to kind of iterate. So that didn't work. 2023, you had auto GPT and things like that come out and you could tell the models getting better at like being coherent a little longer, but it wasn't working very well. October 2023, I gave a talk at TED Talk and I talked about how in the future people make software. In it, I talked about agents. I kind of predicted test times scaling as well where I was saying, there's going to be a trade -off between costs, speed and accuracy.

30:47Sometimes you want to like pour more compute or time into a task. And you're gonna have these plans and the agent will iterate on these plans and build a software and you're gonna be human in the loop where you're that's sort of the creative engine. It was the plan, it was the roadmap for where we're gonna build. And 24, I think around the time for Oak him out, it felt like we're almost there. And so I essentially put the entire company on that. And in fact, we actually did a layoff in May 2024, partly to kind of cut burn and focus. But the other part is like, I knew in my bones that there was the way to go and we were doing a lot of other random things that were unimportant.

31:31So between March, the first time I got a demo from someone on the AI team, Zen on our team, he showed me something and I could immediately feel like we're there. It was like almost like a baby, a baby kind of agent. So we spent seven, eight months working on it. And then it just felt like we were on this treadmill fixing one bug after the other, you know, trying to make it go here. And the transformative thing that happened as like June 24 when Sonnet 3 .5 came out and Sonnet 3 .5 had two important properties. Actually, the main property that people don't treat you talk about all that much is Sonnet was able to generate like thousands of tokens.

32:28I think up to 32 ,000 tokens of code, coherence code. So you almost. Whereas with GPT -40, when you're doing agents, you're writing one function at a time and then testing. If you remember, had they caught ignition demo, as I go, they write one thing, they go to the browser, they write one thing, they go to a browser, and that was like, that was intractable. That was very, very expensive. And we thought that's not going to work. And the thing that Sonnetbro, though, at the time, is like writing high quality code and not being lazy about it. Because the problem with OpenAI's products were lazy.

33:04There's a real the Paul of laziness, where it's a, it like yasset to do something and it's, and at one point, it adds a comment and says the rest of the code here. Bro, I asked you to make that program. Why are you asking me? Slash. It's for the... Get a quick, a human. Yeah.

33:24And so, Susanne, it was this huge unlock and we felt like we're going to be able to ship soon. And there's always this tension, the quality and windio and ship. And so we set that line for my birthday September 5th. And it was so contentious. Actually, at least one person in the team kind of quit because they thought we're not ready. And he was partially right. And we launched an agent. And there was a lot of excitement because it really is the first software agent that works on the market. the very first and people got really excited because, oh, you can try this thing and you can get a glimpse of the future or this thing can bring it in a database and like provision it for you.

34:07It can run a migration, it can like deploy my app. But then as it escaped the kind of early adopters, it was, you know, a lot of people were disappointed because it was actually kind of crappy. And so we sprinted between September and then, December, we had something we were really proud of and we exited the beta. And although we're growing well, then we grew really fast from there and people got a lot of value out of it. Now we have Virgin 2 coming and it's rolled out to some beta users and we've done AB tests and it is anywhere depending on the metric we're looking at between 50 and 500 percent better.

34:51Wow, so it created a 50 % better data retention, a 50 % conversion, a 50 % better engagement. But the metric that was really great was, new users are twice more likely to deploy an app that they made with agents. And power users are five, six times more likely to deploy an app that they made. And deployment of a Repplet is very, very important because that's one of what makes Repplet great. It's that you can go from an idea to a deploy thing and we see people who deploy are 10 times more likely to retain on a Repplet. So that metric we track very well. So now I look at V1, I'm like this crappy thing.

35:36We got to ship V2 as soon as possible and like on the team and so we're starting to roll it out now and it's really good. Can you give us some of the intuition for how you've gotten it so much better? Because I imagine it still saw it 3 .5. That still seems like the Southern model that everyone likes right now under the hood. Maybe it was to be had a scene for how the agent actually works and how you've gotten it to be so much better when the base models are very similar. Yeah, so at the 3 .5 era, we had to build this fairly complicated multi -agent system. and we were talking about LandGraph earlier where there was a state machine component to it.

36:17And there was a lot of non -AI state transitions that we're having to make so that the more you put into the eye, the worst decisions it often makes and less go here and it is. So a context window was still very important because there are actually studies showing that although these models are advertising a million tokens, actually after something like 32 ,000 tokens, reasoning in a lot of benchmarks, just like tank, like crazy, right? And so there's a lot of context window wrangling, and so we had a manager, and it had different contacts than the editor, than the debugger, because we had to kind of make sure they're isolated and they have their different memories and things like that.

37:11And the tooling between all these things had to be different. We built our own protocol for the agent to call tools because actually tool calling was not very reliable at the time. It would like hallucinate tools or hallucinate arguments. So there was a lot of engineering behind it to make it work. When computer use from Floppy came out, so that was 3 .5 V2. The moment we laid our eyes on it, we felt that there's something important that wasn't getting marketed, that was a start of a transition, which is, it looks like it actually fine -tuned it for long horizon reasoning. Because if you want something to do computer use, you're You're going to have all these images in context, and it's going to have to kind of continuously like click on things, reason, think about what to do next, click on the other thing.

38:07And so you can actually roll out a long chain of tool calls without that big of a degradation and reasoning. And so we started re -architecting the model of the agent to be, let's call it, less multi -agent and more single -frighted because the models are getting good at it. And that's like a much bigger simplification. It added other challenges, but it's a much bigger simplification over the existing model. And so kind of the lesson to learn is that you have to constantly rewrite the systems because you want to make use of the Next version of the and you want to be able to predict what's coming down the line when 3 .7 came out You know cursor had a big problem with integrating it everyone hated it on cursor I think just they just recently fixed it and the reason is because again 3 .7 is more agentic And so when you try to use it and that it's a composer style request response, it is not very good at that.

39:17It's actually worse at that because it's trying to kind of make decisions that you're not giving it the space to kind of do this looping. And so there's a really kind of tough lesson for engineering and product teams. If you over optimize for the present capabilities, you're going to enter a local maxima that is quite hard to move. There's an innovator's dilemma problem on the order of months. The innovator's dilemma used to be an order of decades where a company has an innovation which is a certain height of success based on a product that they made that people really love. but then there's a disruptive technology and they don't make use of it because it might be destructive for the current business where it cannibalizes their business and so they tend to not pay attention to it and fight it the classic example is like Kodak had a digital camera product, but they didn't actually launch it because I was gonna cannibalize their film business which was the thing that's making the money actually and this kind of thing is happening on the lower ones which is really harder up your head or at.

40:31And so the move fast break thing is actually very, very important today, right? More than ever. And you have to be okay with your, with sometimes like delivering crap experiences. You mentioned cursor. What do you make of the entire lens? It feels like the landscape of coding tools has just exploded in the last six months. And, you know, developers are reaching for new IDs. You know, many more people who didn't consider themselves developers before entering the market. What's your view of the market landscape? And how do you think of as the ideal person that chooses replettes versus one of these other tools?

41:07Yeah, so I think there are incremental innovations and there are more disruptive, clean slate innovations. And I would put replant in the latter category. So So you take VS Code and you build an amazing AI experience on top of it. Really cursors like a fantastic experience. A lot of people on our team use it. The thing is it is by definition, Kermel, you took a business software that Microsoft says we've been building for over a decade and you added this, you're much better experience on top of it, but you're still kind of, it is still literally this additional layer with the ROTLOT agent, we actually took a clean slate approach to that.

41:57And I was like, okay, what do we need to make it that people aren't coding at all? Like, you know, we want to kind of drive towards this vision of no coding, not only no coding, no DevOps, no IT. Like, we don't want you to set up a database. We don't want you to write migrations. Like, writing migrations is the worst thing ever. Like, you know, if people don't talk about this, But one of the worst things about building software is being able to keep your version control, your database schema, and your deployment settings and configuration in constant and lock step. And most actually most outages when you read postmortems from Google Cloud or AWS, it's like a configuration error and usually it's outdated configuration.

42:42The software changes, but they forget an environment firewall configuration. And so when you have an agent to actually do these things, this is actually much better at doing that. And so the system that we built for the agent is this sort of transactional lock -step system that does these transformation one at a time. When you hit Reverts and Replet, it actually reverts the code, but also reverts the database changes. And other environmental things, and environment variables, things like that. So there's all these things that we thought about where you as a developer coming to our outlet, the thing you have to worry about the most is your ideas.

43:29You know, you don't have to worry about where do I get object storage and how do I configure my buckets, right? Whereas when you're sitting in cursor, There's either so many in your company, a back in engineering worrying about these things, and you're basically hooking into these APIs, or you're having to build them from scratch. And it would help you hit those APIs, but you still have to architect the larger system. So I think there's like a fundamental category difference between these things. These products are hooking into existing systems and require a lot of existing support around these systems, Whereas, a replet is trying to be the final tool you have to adopt in order to build a piece of software.

44:14One thing I've heard from users when I talked to them about Replet agent and deploying on Replet. One of the things that people love is that you can go straight to deployment and that Replet does the whole thing. You start from nothing and you end up with a fully deployed system. Can you talk a little about that? How do you think the deployment space plays into this? You guys in some ways are not comparable to a lot of these other companies in the sense that you can go all the way on Replet. But how do you think about that last mile? Who cares about that and how does that play into the long conversion?

44:41Yeah. So, in the same way that I can say that cursor helps you with coding, doesn't help you with the other stuff for cell, helps you with hosting, doesn't help you with the other stuff, right? And again, it's like this back to the cathedral and the bizarre, sort of like a bizarre, or you need to kind of find all these tools and configure them and figure out, whereas sort of, wrap it. I mean, another sushi analogy, there's ala card and there's al macasse, a wraplet is al macasse, we're going to make, we think we have great taste, or we're going to make the design choices for you. And it's not for a lot of people.

45:14If you want to make all these choices, don't come to a wraplet. I mean, there's a lot of other products out there. So in terms of like the deployment system, the if you want to reach a billion people, eventually like making software. At priority most of them will not know how to set up a deployment environment and therefore the replica product needs to have deployment environment. Basically that's how we approach product in general you know. In the early days of Repplet there was always this narrative of it's students, it's young people, it's people learning how to code. It feels like in recent years that's really changed in maybe AI's enabled that.

45:54I was talking to a Netflix engineer who's telling me about He's using Repplet. Paul Graham has obviously always been a big advocate of Repplet and one of the early believers in the company. How do you think the user persona has changed and how will it continue to evolve over time? How amazing of a visionary is Paul? Like how can you look at a crappy Toy -like Repplet and just see that oh that this one day could could be really big or the idea that people are leaving You know are sleeping on mattresses and other people's homes. That's gonna be like a hundred million dollar company It's incredible.

46:26Yeah, it is fascinating. He's also incredibly good at human. He's been very supportive during very difficult times in the company when all those were weren't. It was frustrating for a long time that like, oh, replete as a toy, hobby toy, students, kids, teenagers. On the one hand, I was excited by it because we had a group of users that are willing to experiment, that are willing to kind of try to find a future of software, the future what we just talked about of being able to have an economy built into the software infrastructure. And we tried a lot of that and I think it's going to work. We still have, like the main missing thing was the agent, but all these things are going to work.

47:10And there's this call of illusion that happened with these users that was very important. The other thing that that perception was important because sort of competitors were paying attention. They looked at replacements like, oh, that's a toy thing. Well, I would have paid attention to it. A very close friend of mine and someone who's looked up to in the end industry, visitors the other day, and visit a lot of our friends. And he was selling him, he was using replic to kind of post -op ideas for a new company. And everyone was like, well, isn't that like the toy thing that I'm just working on?

47:48was like, well, no, it's very useful for me. And that's how I'm able to rate on these ideas very quickly. So now, yeah, the perception is changing. And partly look, I mean, we took explicit decisions to make the product more premium. Actually, what's fascinating now is the product, a replica is the most expensive product in the market, with the cursor composer, I think one request is four cents, with a replica one request is 25 cents. in the reason we did that is like we just really want to build an agent. We don't want to build co -gen tool. And if you want to build an agent, it's going to be expensive.

48:26It's going to iterate and it's going to call a bunch of tools with every request. And so it did eliminate some users. That partly also shifted the perception and kind of more professionals, got them bored. But if we're going to reach a billion people, we need to go down market again. But I think we started in one end and now we're starting in another end. We'll meet in the middle, I guess at some point. But I guess that replete is the more roaster now. And as we drive costs down by perhaps using more open -source models and things like that it's going to become more and more acceptable to people.

49:12What do you think of vibes coding? I don't really like the term. I think you shouldn't fight it because I actually didn't like Jenny. I either. It's just I don't know. Same. Yeah. I just like cheapens the possibilities. Yeah. It's like, oh, this thing that generates things. Well, actually, you can build agents and not just generate things. we can actually reason. In vibe coding is make sense if you're sort of a starting form position of coder and your Andre Carpathy and you don't want to kind of worry too much about the code and you keep heading into whatever. But if you're starting with Rocklet, you're actually not starting for a position of code.

49:59You're starting from an idea, you're starting and then you go in and the agent is unfolding this code in front of you. Actually, when you're using Rapplet agent, you don't have the luxury to look at the code. So we have another protocol assistant, and assistant is for more advanced people. And that you can do more by coding there, because it's like a request response, and you kind of like kind of refute the code and do all that. But if I were to explain a replica, it's just vibe. Like don't call it vibe. And not vibe coding, just vibe. You've always been a bit of a contrarian. One idea that's very popular now in Silicon Valley is EGI.

50:45There's this idea that there's gonna be no software engineers. And you sort of have the opposite view. There's gonna be a billion software engineers. Talk to, how do you think about EGI? What is EGI in your view? And what would you say to all the people who say, I talked to a lot of software engineers and they're like, well, I'm not gonna have a job. I'm worried about not having a job. when we're worried about no one's gonna have a job. We're all just gonna be on universal basic income and all this stuff. Replytics in some ways, the opposite vision, right? Of like, we're actually all gonna have jobs.

51:10They're just gonna be very powerful and we're gonna be able to do all these amazing things. I think it's like a fundamental, it's philosophical difference.

51:22What is special about humans and what's replicable in the machines and at least in the near term? My view is that AI is going to get really good at sort of two things. Things that are highly represented in the data and things that you can construct a very good RLN environment for. So what can you construct a great RLN environment for? Like obviously with Alpha Zero games, right? Games are famous for, you can have these self -play sort of algorithms that of time. Now with reasoning models, you know, math is an environment that especially with lean, it's like a code, almost like an expression of math that can be executed.

52:14That's like a great, you know, RL environment, I think code execution as well. So running the code and then, you know, doing your reinforcement learning on that. And things that are already represented that don't get hub and things like that. But there's a lot of other domains where we actually still don't know what we're how we're gonna make them better. Like new fundamental and new ideas, new knowledge. It's not entirely clear how we're gonna get there. Can you use RL for these more software things? Perhaps you create a reward model, you can approximate these things, but I feel like the sort of the ideas is in the creativity and the sense of like coming up with really novel things and understanding the world and very complicated, intractable way and you know coming up with an idea that could fundamentally change how things work or change the world.

53:12I think we'll still have be the domain of the human. And AGI will have AGI but it would be a functional AGI meaning it would do the jobs that a lot of humans are doing today by virtue of the training data being available and by virtue of some of these jobs having like ground truth that you can train on. And the reason I call it functional AGI is because it's fundamentally not general in that you can throw it in a super novel environment and for it to efficiently learn things especially when they're, you know, when there's not explicit feedback and be able to be successful in that environment, which you have the definition of the universal AI, which doesn't feel like we're trending that way, but I do think that you can reach something.

54:08So the definition of a AI at a lot of these companies is doing economically useful activities in front of a computer, right? I mean, But if I have a remote worker, I'm going to create a hundred more workers and implement all my ideas. And still, it's a tool. It's useful for me. Is it going to replace me? Well, if I am like a code monkey, it's going to replace me. But if I see my place in the world as someone who can generate ideas and create products and services, because I understand what people want and how the economy works and all of that. I think that's still irreplaceable. I want to talk to you a little bit about your life story.

54:52You touched on coming to the US, the ONV's growing up in Jordan. Maybe you started the beginning for people who don't know your story, because it's a really inspiring story. And in some ways, your whole life has built up to a repilate. It's not just a company. I mean, your wife works at the company. Your cousin works at the... Like, this is like your whole life and your whole mission. All in. Bring us to the beginning. Like, how did this all come together? How did you get to the US? How did you get into Silicon Valley? Yeah, yeah, so it might one of my first memories Just as a child. I don't know if you remember your first memory, but I remember very vividly that my father Kind of getting this this machine and like opening this this box and like putting it together And I was fascinated by it even before I knew what it does and I walk walk over him and I kind of look over this shoulder were him sitting at the keyboard and sort of finger sort of typing.

55:50He had like a big manual like you know you throw it at someone who could really hurt them. And he would he was reading into it but one by one he was like finger typing, CD, MKD IR you know these docks commands. And remember, feeling that it's just, wow, this is a machine that you can talk to. What is a DOS? It is like a Rappl. This is where the Rapplit name comes from, ReadYval print loop. You can essentially have a conversation with this machine. So my father would like go in like attend classes to learn computer computers. And he would like, you know, every night he would come in with all these notebooks.

56:39He's like such a such a big nerd. Apple doesn't fall far from the tree. I'm different than my father. My father's a Palestinian refugee crew up with like this intense focus on education. Like if we're gonna make it, we're gonna have to be like the best educated, we're gonna have to be better than anyone else We're gonna so there's like a a students and working really hard My mom is sort of the the opposite my mom is like a sort of a free spirit She was a Interpol tree she taught me a lot of poetry When I was kid and I was actually able to So it was like there's an art to telling an Arabic poetry.

57:30And so I was just a mix of two things because I can be very intuitive. I can be, I can go on purely an intuition and take a lot of risk based on some kind of idea or vision or something that I feel good about. And I also have this very analytical mind and I can sit and be such a You know pin in the butt about about being so rigorous about certain things and that's that's really my father's inspiration and and so You know, you know one day my father comes home and I'm sitting in front of the computer and he was he was mad He put all the savings into this machine and and I was like, you know, opened a computer apart, took the parts out, put them back in, and I was like, you know, doing it in an angry, I know exactly how to use it, I know exactly how it works, and I showed him how to use it.

58:27I showed him essentially how to create things, how to open applications that he's been studying the whole time, and I was like, okay, this is fascinating, you know. All right, it's yours. And the first program that I wrote, I think I mentioned earlier, was to teach my younger brother math and I thought, okay, I can use this thing, this conversational machine, which I still think about it that way. Obviously with AI, that really happened. Yeah. And this idea that you consider front of it, learn something, play games, do something fun. And so that was the first program that I built. And then when I was a teenager, I was really obsessed and Counter -Strike, so I would go to these Internet and Land Gaming cafes, and I would like, you know, Whatever money scraps of money I have, I would like Put it into that and just play a lot of Counter -Strike And strategy games and things like that.

59:25I got very good at them. To the point that it was like a source of income. I was actually winning tournaments and things like that. It's good to go to eSports early on. So that's another bench of my life. But one of the things I noticed about those businesses, is they were running on a pen and paper, I'm like, you have all these computers. You can just write software for it. So I did write this client server software that did accounting, that get people accounts and username and password and manage their time on the system and they're also did security so that people can't format the computers or do install malware and start selling that and it made a lot of money on that.

1:00:12I mean, I sold it to a lot of businesses in Jordan. By the time I got to college, I had this idea that AI is going to get so good, we're not going to have to write software. It just felt like software is this like pedestrian thing that you do. It's like not that interesting. It's just like you just do it to like make things. And at the time like these wizards of code generations were coming out from Microsoft. So when I went to school, I actually studied more on the electrocure engineering side, especially because my father thought that computer science was not a real field, because the engineering association of Jordan would not admit you into that as an engineer, if you don't have like you know electric going gearing and by the way my father is the vice president of the so organization.

1:01:04I didn't know that. I learned so. He really loves that engineering organization. But throughout my college experience I got really into program languages. I started reading programs, started reading hack and news, program wrote a lot on on list. He actually has a book called OnList and programs view of program languages is more of an art rather than science. Like these artifacts are aesthetic artifacts and not just functional artifacts. And that also played into the reason to create Repplin because I wanted to try all these program of languages. And it wasn't a place I learned to intern at to be able to try all these program of languages.

1:01:48And after I created Repplin, had that breakthrough that I talked about earlier, it went viral in the US, a bunch of attack companies started adopting it. If you remember 2010 -11, there was the MOOC kind of hype. We have AI hype now. There's a blip period where there's the massive online courses. Audacity came out of that period. Coursera came out, code academy. And I got a bunch of, they all started using Repplet by the way. And I got a bunch of offers. I eventually decided to come to the US, got an O1 visa, because a lot of my work was published in the news and everywhere else. and so it was possible to go know when Visa landed in New York early 2011.

1:02:33The only money that I had was taking from me at the airport. And the reason is in the airport in a month, I had like perhaps $700 dollars. There's the money that I'm going to the US with. And the folks at the airport did not know what an all -one visa is. I apparently like no one in Jordan had ever gotten no one visa to get to the US. And they didn't think it was like a resident visa. They thought it was like a visitor visa and that I needed a ticket back. And I was like, no, it's like I can go there, I can work, it's a work visa. And they didn't believe me. I was like, go look it up there. They didn't believe me.

1:03:14And they made me buy a ticket back. And that was something like 500, 600 ,000 dollars. So I arrived there with like about a hundred bucks. And my salary was $80 ,000, $70 ,000 or $80 ,000 in New York City. That's pretty big. Yeah. Well, not in New York City. When your rent is like $2 ,000. I think at some point you had someone offered to buy the company for a lot of money. How did you decide to turn that down? That seems like that was a pretty big decision. Coming from this background, you grew up, you made it to the US, you got this job, then you have an offer by your company for life changing amount of money.

1:03:46In seeing amount of money, we were like six people at the time. And you know, the numbers that were thrown around is between 500 million to a billion dollars or six people. And so it would have made me insanely rich, right? So And it was a tough time. I Wasn't really happy about the culture then like we grew to six seven people or something like that from from the three that are our families essentially and And we hired people that I didn't like very much and the culture was changing and I kind of wanted to do a reset. And at the same time, my mom was diagnosed with cancer back in Jordan and I had to go back.

1:04:33They entirely had to go back, which is half the team. Well, to spend time with my mother and it was a very stressful time. and the thing that made me, which is like the absolute rational thing to do, is to stick the money to home and live, I guess, happily ever after or something. But I felt two things. One is my dreams, right? I've had the dream of being in Silicon Valley for so long. like the first time I knew about Silicon Valley is through a low -budget movie called The Pirates of Silicon Valley, where it's the dramatized fight between Steve Jobs and Bill Gates. And I was like, wow, this is Silicon Valley places.

1:05:26There must be flying cars and really mass advanced technology. Of course, you come here. It's like the suburbs. But I always wanted to be here. I thought the innovation was really I was reading about all these entrepreneurs. I felt like this is the most important thing in those people are heroes. And I felt like the weight of Silicon Valley also on my shoulders because Paul Graham, you know, Mark and Dreson, and other people that I really respect invested in the company. And like they all have like very high hopes for it. And they're all really excited about it. And I felt like I don't want to let people down.

1:06:11And I felt like if I sold the company, it wouldn't be, I wouldn't have achieved the potential of it. And maybe I would regret it in the future. And it's like, okay, being rich is good. I think money is actually great and improves your lives in many ways. It allows you to focus on the things you love. But, you know, what are you gonna be? You're gonna be another, you know, rich Silicon Valley dude, and there's a lot of them. You know, gonna like write and invest, do angel investing is like your life has gone a little boring and you never kind of want to take the pain again unless you're a Elon Musk to kind of like go start a, start another company and put your life's force and energy into it.

1:07:00And so for all these reasons, we decided to turn it down. Now you have 40 million users? Yes, and we achieved evaluation over what we got sold for. And I think the company is actually underpriced now. It's a lot of grit to get here from six people. I want to talk a bit about your management style. You have a unique management style. I remember seeing one time on the internet. You said, like, I'm now the VP of engineering of Repilit. I feel like over the years, there's always been your hands -on leader. Your leadership style maybe has become more popular. even it wasn't popular six, seven years ago and you were doing this, like, how did you develop your leadership style?

1:07:37What advice do you have for founders as they think about running their companies? In some way it's a deficiency. Jensen now talks talks a lot about him not being sort of a great manager and him having all these reports and only talking to everyone in these big meetings and being, you know, giving feedback publicly, not really doing performance reviews in the traditional way and all of that. And in some way, I would say it is a perhaps lack of skill in terms of like how to do traditional management. The management styles that I have is similar to like how I would like lead an open source project or how I would lead a sports team back home.

1:08:22I've always been a leader and I've always been sort of a hands -on leader where it is this duality of micromanaging and trusting people. It is actually not at odds to do these things. The most inspiring leaders both can go dig into the details and give very precise direction. But then really trust people to deliver on those things. Also trust people have their own innovation, their own ideas. The way I managed the company from the start is I had a text file inside Rapplet, I use it as a set of a notebook, and the text file had everyone's names, and the one thing that I think they should be working on, or the one thing that I expect them to deliver on, and every week when I meet everyone we would go around the table, and I would tell them, did you do this thing?

1:09:15And it's either yes or no, or something, they don't go right or something like that, and then the other question, what are you going to do next week? And so it's like, okay, they did that last week or they didn't do it. Why did they fail? What happened? And here's what you do, what they're going to do the next week. By the way, my execs still write that everyone in the company, every week on Friday, they write, he's what I got done this week. Here's what I'm planning to do next week. And so I can still keep in my head what most so the company can do or is working on. Like I can walk around and tell you this, this guy's working on this, this person's working on this.

1:09:59So partly is I can keep a lot of complexity in my head and I can like really be able to kind of make these, these, you know, very deep decision about how, like a sort of one -button should work inside the product or how certain marketing ideas we should run, and so I can go between all these different departments and be able to go all in into the details and then kind of zoom back out. And also, just having really high expectations. If someone, if we go over week, that person who said they were gonna get that thing done and they couldn't, it's like an obvious reason to let them go. It's like not that complicated.

1:10:46And so, Replet has, and then high attrition rate, especially in the first few months of people joining, 23 % of people are going to either leave or get let go because they're not able to keep pace of the environment or they get confused about how to work in that kind of environment. The other thing I think is unique about your culture. I remember I attended some all -teamed internet and all -you -can -eat barbecue restaurant. I don't know if you remember this. And there's all these young people around the table and some of them didn't even go to college graduate college I mean you seem to recruit for raw talent.

1:11:21Yes, and that's something that a lot of people talk about doing They want to do but it's hard to do. How do you do that? How do you filter people? How do you find these people? How do you give them leeway? How do you train them talk to us a little bit about how that how that happens? Yeah first of all I am You need to be able to work with weirdos and misfits And I was able to do that, whether it's instinctively or whether I relate to them being sort of myself or we're doing misfit. And I can see talents, certain people, like even back in my college years, like finding those people that have hidden talents and being able to harness it somehow.

1:12:02I have this feeling of like, if someone has a talent that is not being put to good use, I feel like a sense of waste. I'm like, you know, this needs to be harnessed somehow. And I think that's sort of a good management skill. But in terms of, so first of all, you shouldn't have allergy to or see people. I remember my wife and co -founder, when we hired Mason, he was like 18 year old kid. He was, you know, a joke that he's a runaway kid from Santa Cruz, which is partly true. He lost Santa Cruz in high school. He wasn't happy. He was happy with his family, with his school. He went up to the city.

1:12:46He went to one of those boot camps. Those boot camps were using, we're using replet all of them. And one of them was sending me bugger parts. I'm like, look, I don't have a lot of people who work on this. Why don't you send me your best engineers? It's like, look, I'm going to send you the sketch. He's really awkward, but he's one of our best. So he came in and I remember high one day, I was like, oh, this kid doesn't keep the door open behind him. He like, a little bit of slams the door on me. He's like, well, he's not really thinking about you. He's like thinking about code as he's walking around, right?

1:13:20So, and still to the state, I see people doing that. But the first thing is, most people, I think, just project these people out right when they can't communicate with them or they can't relate to them. And then the other thing, you know, they're gonna spike on certain things and then they're gonna be not great at some other things, right? And so, but, you know, you can construct a team where it all fits together, where the peaks of someone is the valleys of someone else, right? Someone is really good at, that's shipping thousands of lines of code. And someone else is really good at testing it at a very methodical about code reviews.

1:14:07And if you have one who's like a cowboy slinging code and others like a little more careful, and like meticulous and rigorous, and perhaps a little annoying of how meticulous they are, put these two things together. There's a lot of tension, but then they get a good product. So you want to balance the team in a way. And you want to go to higher from places that other people aren't going to. And that gives you an advantage because everyone's competing over the existing talents on the market. So for us, a lot of it was going to Rapplet. A lot of it was running hackathons, running surprises on Rapplet.

1:14:51and some kids win and we fly them out to us, to work with us. And we've had anywhere from 16, 17, 18, 21 years old join the team and even on the older side, people who haven't had traditional jobs before or were ND game hackers that joined the team. So yeah, I mean, it's sort of a diversity of sources. If I am starting a company today, I would try to find niche communities. This is where you'll find some really underrated talent, whether it's an niche group community around a niche crypto project or a niche program language. That's where I would look first. You mentioned your wife, Haya, a couple of times.

1:15:42What's it been like building a company with your wife? It depends on the day.

1:15:51We've worked together. We met at work back in Jordan. We were working at this company where we recruited actually a foreigner, Kimner Jordan, as part of a job from Belgium. He decided that he loved Jordan a lot. He loved the desert. He wanted to build a company there. So I was the first employee there and I was the second chosen designer. I was an engineer and he pitched us on this idea. We're going to do consulting and then we're going to build a product on the on the side and then we're going to become a product company. By the way, every company that has this idea never becomes a product company.

1:16:27I'm sure you've seen some of them. And so the company was very dysfunctional. He was non -present and so it was like the inmates were running this island. So I and I ended up working a lot of projects together just for fun. And then we started dating, which dating in Jordan is not real dating. Like God for a cup of coffee, she had like a 7 p .m. curfew. And so, and then by the time I started working on the open source, Replet, she actually contributed the logo and a few other designs. She helped with a few other things. And then when I got the VZ to come to US, we got married and we were very young.

1:17:14I was like 24 at the time. And then she joined me in the US. We continued working on projects the whole time. We worked on art projects, working on games, all these other things. And then when the time came to to start the company, I was kind of like looking for co -founders because I'm like, oh yeah, YC says that you need to have co -founders and I guess it's like best to have co -founders and I was like going in these co -founder dates and trying to meet people and all of that. And then she was like, well, I can start the company with you. I was like, it's gonna be really painful. Like it's really, really painful.

1:17:54Like I assure you wanna go through that. And she's like, yeah, yeah, of course. like I saw you, you know, with Code Academy. I can do that three or four months later. She's like, I understand how hard this thing is. But she obviously lived up to the challenge. And I think overall it strengthened our relationship. Because when I was at Code Academy, and I was working you know, 12 hour, 14 hour days, she doesn't really relate. Like what kind of job requires that kind of commitment. And then with Repplet, we were both doing that. So it's not like, you know, your partner is going off in the morning, not returning until midnight.

1:18:38On the weekend, they're wasted and they can't really do anything fun. And so you don't really have this great relationship with them. If you have a startup founder and you have a regular job. But if you're both founders, you're actually going through this together. And I think that ends up being good. And at the time, it was actually working against us because venture capitalists do not like husband, wife, founder. It wasn't a lot of examples at the time. Obviously, the most famous example is Paul Graham and Jessica. But then now there's like they get canvass founders that a bunch of other Companies that that made it work, but there are challenges, too like You know right now we're fully sort of fully committed to the company, but also we have kids And so how do you how do you manage how do you manage this that that's quite a bit of stress and pressure on us?

1:19:38And then the other thing is when something is going wrong in the company Like a lot of people can go home, I can disconnect because they find comforts and talking to their spouse about other things. But when high -end I go home, we're talking about the problems and the problems kind of percolate. And they end up seeming bigger and worse. And so you start to have, you start to need rules around when do you actually talk about work and you're constantly breaking into those rules obviously because you're thinking about something. So I think it is a challenge and I think it is at the same time there's something very Very unique and good about it.

1:20:19Yeah, well, it's impressive. How well you made it worked and you guys have a really great dynamic Mm -hmm. Thank you. All right lightning round. We have some linear on questions. Are scaling a lot is gonna hold Yes, it Scaling different things we're just gonna keep finding things to scale What is the best piece of advice you've gotten? Paul Graham asked me this question. I was stressed at the time and he told me, is this your life's work? Are you going to be working on this 10, 20 years from now? I said, yes. He said, well, why are you worrying too much about the daily tribulations? If they just sell into the fact that even if things are not great today, you're going to be able to fix them and you're going to be able to turn things around.

1:21:07Honestly, as long as you're not dying. And that's why Paul is talking about not dying. It's surviving as a company. What is your favorite new AI app? I'm kind of a lot of died because I make a lot of things myself and I use a replete to make them. I use the basics like, you know, chatroom tea perplexity, but then I spend a piece of software every day to use. I guess Manus is an interesting demo. It's actually pushing on this idea that we talked about of like how long can models work while saying coherence. I think they showed that they can go for an hour with some coherence. Since you brought up Repplet apps, what's a cool Repplet app that you've seen recently?

1:21:55There are a lot of business things that are fascinating. One cool thing that I went to New York. I was meeting a few investors and customers and I met with Sears Home Services. This is a century old company. I didn't know it still existed but I found that the Home Services Department still existed. I met this very cool trendy team. They kind of easily the work I was starting up, they're working at Sears and they told me that six months ago they finished the cobalt migration. And it took them six months. And then I started asking him what kind of other tools to use. He used any SaaS software and they didn't have any ERP software or any of these modern SaaS software.

1:22:42and they leaf -frogged an entire generation of software to start using Rapplet to create agents to manage their business. That's really cool. Yeah, so they have these field workers that every morning they wake up and they're like, oh, how do I optimize my routes to kind of earn the modes and service the most customers? So they build like an AI tool that actually gives them the most optimal route that they He was every day, for example. Yeah. By the way, that team is non technical. They're all operations. Wow. It's insane that you go from cold vault to replet and you skip everything in between.

1:23:22It does, we're talking about this in the beginning of the conversation, but it gives you a sense of the sector to the economy that are going to get transformed by this technology. Favorite book? I am a strange loop. Douglas Hofstadter. I actually disagree with the conclusion slash premise, perhaps, of the book, but it's still one of the best books exploring concepts like AGI, concepts like consciousness and the soul and what it means to be a human, what it means to be a machine intelligence. What is the foundation model that you're, you like most are most impressed by? The Edie -Iman Claude is the best, I mean 3 .7 is really the best at doing agent stuff.

1:24:04Person who's influenced your life. I think my mom had this supernatural belief in me. Like she would talk about all the great things that I was going to do even when I was a very small kid. She gave me this again unwarranted at times confidence in myself. Recommended reading on the eye.

1:24:35I think it's really awesome. I think it got degraded recently, but there's so many papers that you find on Twitter or so many snippets of information, just like go read those papers, skim them, and I think you'll learn about what's coming down the line by just reading the literature. Last question. Who is the most underrated person in AI? I think, Mike Heligatosta, head of AI now, present at a replica. I don't think he's very public, but he was one of the early pioneers of LM's for code. And he's a great leader as well and visionary around where AI for code is how to. Super impressive guy. I love every conversation I have with him.

1:25:24All right, well, thank you for coming on the podcast. I really appreciate our friendship. Thank you for your time. Thank you. I mean, I appreciate your belief in us. And I think you saw something special real long time ago. And like all these things that you notice about with special about Replet, and I really appreciate that. Thank you. We're still 4 % there, 40 million users. We got 960 million to go. Yeah. Exciting times ahead. Thanks, I've done. Thank you.

1:25:57Hmm.

1:26:11Hmm. Hmm. Hmm. Hmm. Hmm. Hmm. Hmm.