From Copilots to Agents: Rebuilding the Company Around AI

When you're building AI, the first thing that you need to build is the brakes of the system. It's the understanding on where you're going to deploy it and how you're going to deploy it. We had thousands and millions of information lines about our users. And the first thing that we did was we just built the system that allowed us to understand everything about every user. We built these copilot tools and we realized very quickly they didn't adopt them. So we went funnel by funnel, putting agents in front of, like, critical aspects of the business. We put the agents in front of our users really quickly. It was very painful. If you see the best companies out there, 97% of their value gets created after year 15 through year 1 5, 97% of their value.

0:00

40% of used car transactions in Latin America end in fraud. Not the lemon problem you find in the United States. Kidnappings, forged documents, stolen vehicles. And In Mexico, only 5% of the used car market is financed, compared to 90% in the US. Carlos Garcia Otati founded Kavac after being defrauded twice trying to buy and sell cars in the region. The company he built handles buying, reconditioning, selling, financing, warranties and logistics. Four separate businesses underneath one consumer experience, operating across Latin America and the Middle East. By 2021, Kovac had 10,000 employees and was growing at 300%. Then capital disappeared and the company had to rethink everything. Instead of retreating, Carlos bet on AI replacing copilot tools that employees wouldn't adopt with agents that now handle more than 90% of customer interactions. The transition took a full year of flat growth. A16Zs. Angela Strange and Gabriel Vasquez speak with Carlos Garcia Otati, founder and CEO of kavak.

0:44

Carlos, for those who aren't familiar with Kavak, can you introduce the company and tell us a little bit about the scale of where you're at?

1:52

Yeah, sure. Well, first of all, thanks for having me here. It's amazing. Kavak is an all in one marketplace to do anything related to your car. So we work out of Latin America, we work in Mexico, Brazil, Chile, Argentina. We also have operations in the Middle East. And what we essentially do is we manage the lifetime of our users from the moment that they want to sell their car to the moment that they want to buy a car. If their car breaks down, we're there as well. So we manage the end to end process of a user's journey while they own their car. And we do everything. We buy these cars, we recondition them, we Then sell them online. We provide the financing to our users as well. We manage their warranties, their services throughout the process. We pay their tickets for them if they want us to do that. And we just make sure that we're just building that relationship with our user as they go along. In terms of scale, well, the business is probably the biggest E commerce auto business in Latin America. We do around 10,000 transactions every month, growing very fast. We have around 3,500 people. Yeah.

1:59

Fantastic. I wish I had a service that would also pay my parking tickets.

2:58

Yeah.

3:02

Well, Carlos, when we first met, like, there was this particular intensity that you brought to the table immediately. And I think we'll see that across the interview. But I think there's something unique about your background. Having been born in Caracas, Venezuela, moving a lot, I think you did 14 schools, is that right?

3:03

That's right, yeah.

3:21

And we're just curious how that early upbringing kind of shape Carlos now.

3:21

Wow. It's a good question. Let me try to unpack that. Right? There's like a lot of the learnings and a lot of what I am today come from those years and from my family. So, yeah, you know, I lived in up until I was like 17, 18, I've lived in Venezuela, in the US, moved a lot. And I think three things sort of like came out of that that still stay with me. The first thing is getting used to change, right? And changing 14 different schools meant that sometimes in the same city, I would go to a different school. You're always moving. My parents were always trying to find the best things for me. So the first thing that I learned, I think, about change was how can life be at a certain point in time, really great, and then all of a sudden it could stop being great because you were in a school, you had great friends, like you were enjoying everything, and that you had to just move and start all over again. And I started to see sort of like that pattern of everything could be great one day, and then all of a sudden, not great. And the same way, the other way, right? You get to a certain place where you're not having fun, it's not good. But all of a sudden you move and you get an opportunity to reinvent yourself. And this is something that I've been unpacking over the years, right? Because when you're building a startup, when you're building a business, it's exactly like that. You sometimes are on the top of the world, but the next day you're in the bottom of the world and vice versa, learning that and having gone through that so many times, change the way I see things. And I think that shaped my ability to build companies and build them. With all of these changes that happen as you do it, I think that's one. The second thing, when you're changing, you always have to have something that doesn't change. And that was, for me, my family, in the Inception movie, you know, that he had his totem to understand whether he was in reality or not or in a dream. For me, that totem was my family. It was my mom, my dad, and my sister. Throughout all of those moves, up until the time I was 17, that remained constant. And that allowed me to value what was important. My dad was in the military, so we had everything that we needed. Growing up as kids, the basic things, my dad and my mom just gave us so much love. And they put ourselves, me and my sisters first on everything that they did. But I think the biggest thing that sort of, like, shaped me back then was just watching them, like, every time we changed from a place to another place, they were excited about it. They were very optimistic about it, and they were always excited about what's next. They were always dreaming. We were always talking about all of these dreams of the things that we wanted to do and how we want to spend our time together. Everything that we did, my parents sort of, like, took it upon them to just make it great and fun. And that continued. Right. You know, in 2002, my dad was an admiral in the Navy and didn't want to be a part of what was happening in the country. And he was against the government, and he decided just state his position there, and that it got him prosecuted. It took his freedom away. He lost his job, and he eventually had to move from Venezuela. And I saw him as well and my mom do the right thing every single time, even if it wasn't convenient for them. And I stayed in Venezuela. They had to leave the country. And the next chapter of my life came without that constant on a physical constant. We still had the fortune that we could see each other every year. But I saw that, right? I saw them just do the right thing no matter what, and be optimistic about the world that they wanted to live in no matter what. And the third thing about those years is the pattern recognition that you develop. You know, like, I have the advantage and the privilege that I went to public schools in Venezuela and to Oxford. So I lived in. And I had a life where I've seen different socioeconomic ecosystems, and that sort of, like, provides a level of empathy that few have. But on the other hand, you develop when you're changing so much. The only thing that's constant is human beings, is people. You start to learn how to read people, and you start to see the common threats around your world. And I've developed sort of like it would probably would have been a defense mechanism, but I developed a formula on how to make sure to create win win scenarios with everybody around me, right. Like how to go that formula of building relations where one plus one equals four and not two. And as I got older, I became really good at making that formula work. So I started to take more and more control of the narrative than I thought I had.

3:26

Carlos, so how did you get into entrepreneurship? When was your first business? What were you thinking and what got you excited?

7:51

Yeah, well, this zero, like no technology into the mix.

7:59

Right.

8:04

But it was actually at 12, my dad had been sent to Newport, Rhode Island. And I remember in the US when, like, if you wanted to work at McDonald's or Walmart packing bags, you need to be 14 years old. I wanted to have some money to buy some Michael Jordan cards. This is 1996, so you have to remember the whole Chicago Bulls phenomenon. And you're going through that. And I remember that the house that we moved into had a lawnmower. And I just went and just knocked on the door, asked the person that owned the house that if I can mow their lawn, and she said, y I started to do that, and at a certain point in time, I didn't have enough time to lo all the loans that I was getting. And I was getting paid like 20 bucks to do this. So I went back to my house and asked for my dad to dad, I need you to loan me some money so I can buy a few more lawnmowers. And I needed to recruit a team to do this. So I went back to the basketball court, I convinced a bunch of kids to mow some lawns. And for me, the business there wasn't mowing the lawn, was just knocking on doors and asking people to mow their lawns and just getting a big enough demand and figuring out how to fulfill that demand. And I think that was very early learning. But what really hit me was that most of these kids didn't show up at the time that they needed to mow that lawn. So I was always under delivering to my users, to my customers. And I ended up like changing the whole system to becoming sort of like a subscription system where I would tell the owner that their lawn would get covered every month for a 20 buck fee and that I will just get there and mow it and every month it will be in the right sort of condition. And that allowed me to think about it very differently and it ended up becoming something really big for me at the time. So, you know, it started there. I went back to Venezuela like at 14 and I had like $20,000 in my pocket. And that sort of like it was crazy, you know, 14 year olds, it's a lot of money, right? Yeah, I don't know if it was 14, like I don't the exact amount, but it was a lot like it was a lot of money that I just seeded it into the next business and so on, so forth. Some of that capital actually came into Quebec. Right. It just, I never stopped building after that. I just, I learned that, you know, you need to put that money to work. And that was the same year that I also, like, this was 1996, I opened up my first email. It was magic, you know, like I went to my father's office, I'm moving a lot, so I'm writing letters to my grandmother, to my cousins and all of a sudden, you know, you go from letters to email. That was a magical moment for me as well. That also like seeded another obsession that was Internet. And I think I was really early for a Venezuelan guy into seeing how magic worked. And like the combination of those two things of, you know, operational intense understanding what your product actually is, which is not mowing lawns, it was just making sure that people were satisfied with how their garden looked and having the workforce incentives in a place where it would go, it led, it continued to compound and to work out into what we're doing today.

8:04

Thank you for that background. You could have done many things with this background. What was the moment that you decided, ah, I'm going to start Kabak?

11:22

Yeah. Well, it all built up to sort of like that moment, you know, I left Venezuela first, went to Italy, ended up doing an MBA in Oxford, worked at Amazon for a while in the UK and I think that this is the first time that I see a digital business at scale and how it's impacting the users. And I returned to Latin America obsessed with Amazon. I went to work for McKinsey for a while because I needed to pay for my mba. But I ended up leaving to join Lineo and build the marketplace side of Lineo, which was, it's a business very similar to what Amazon had, where you had retail and your marketplace business. And we launched it out of eight countries in Latin America. And while I was. And we can unpack that and talk about that in that journey, but while I was doing that, I was moving from Colombia to Mexico and I needed to sell a car. When I go out and try to sell my car, there was no place where I can just go and sell my car. It was very informal market. So I had to join a classified, put my car online, and then meet up with a bunch of people to get that transaction done. I ended up settling something with a person there. We sold the car to that person, and I got defrauded in that process. It was a nightmare. And I lost the car and I moved to Mexico to launch Linio. And that sort of like, it was in the back of my mind, you know, like I, I just been through, through, through this terrible process and I started to work on a solution to, to sell my car in a, in a, in a different way. So when you think about the market in Latam, you have. It's very informal. 90% of the market is informal. It doesn't happen in dealers, it doesn't happen in a formal space. All transactions happen between peers, people like you and me that don't know what they're doing and have no information. The problem with this informality is that 40% of every single transaction ends up in fraud of one way or another. And this is not the lemon issue that you find in the us this is literally getting kidnapped, killed, being defrauded. The way that I was buying a car that has forged documents, that is stolen. So you have all this fraud that exists in the system that make it very unsafe for like normal users to go out and just transact among each other. And I was part of that, trying to sell my car. But the interesting part was that when I landed in Mexico and after a year, I was probably the worst type of citizen in Mexico, you know, a Venezuelan, an entrepreneur. So no bank wanted to give me access.

11:31

Nobody was gonna underwrite you.

14:15

Yeah, nobody was gonna underwrite me. So. But I still needed a car. Like in Latin America, you need cars. So when I landed and after a year, I bought a car, I went into one of these classifieds, got a car that I liked, it was a used car, bought it, and after two months, the police stopped me and they were to throw me into prison because all the documents were forged. So the whole process of discovering Kabak was just by me, you know, being probably the most naive person in Latam. And that's sort of like the thing that I needed to figure out at that point, whether I was an idiot and I got defrauded twice or there was a bigger problem. And that's when I learned sort of like those stats, that level of informality, that level of fraud. But the most interesting piece about it was, yeah, imagine a world where you can solve that fraud, where you can figure out how to get the information, make sure that people don't have to go through this fraud. And imagine a world where you can also back the lemon issue. You know, if a car breaks down, and one thing that's true about used cars that I've learned after the years is that they're gonna break down. There's no way around it, right? Like, it's like humans. We're just, at a certain point, we're gonna break down. The real question is, how do you show up for your users when that happens? Right. I don't. I don't make these cars. I just provide the proper warranties for somebody when, when they buy them, I can, I can be there when it fails. But imagine in that world, you're able to also solve that. The biggest thing that we saw was that nobody was financing this asset. So to put it in perspective, in Mexico particularly, only 5% of the market is financed. Of the used car market, that when you Compare to the U.S. the U.S. is closer to 90%. So this means that in the U.S. out of 10 people, seven have a car. In Latin America, out of 10 people around, two have a car. And that was the real sort of like, opportunity that I saw that I could relate to as well. When you live in Latin America and you use public transportation, you take two hours to go into work, two hours to get back. You're using this really unsafe public transportation system, that the moment that you get yourself in a car, you change the life of your family forever. And I went through that myself. I bought my first car in my 20s. And the biggest, you know, I've built Kabak, I've built all of these companies. And the biggest change that I saw in my life was when I, when I got myself in that, into that first car, my business started to do better, my social life started to do better. And in Latam, when you're thinking about these economies that are so polarized, and, you know, there's no middle class, there's just people that are struggling, people that are doing really well, and very few people in the middle class. When you think about what's that one thing that gets you into the middle class or that separates you is a car. Yeah.

14:16

And so you've described, or I've heard you describe recently, Kazakh, as Spotify meets Amazon meets Toyota meets Citibank. Was that always the original vision of Kavak or how did that evolve? Maybe unpack that analogy a little bit.

17:03

When I saw this opportunity. The opportunity was not to just go and try to solve the buy and sell process of it. Solve the sort of like the lemon or the warranty coverage part of it. It was very importantly, find ways to get people into cars. And to get people into cars, you needed to make sure that the transaction was safe, that you could, you could, you could provide the proper coverages and that you can get financing for your users to be able to buy this car. You know, my, my whole goal became how can I get people into the middle class through the car. And, and having built Leanio, I learned this. This is a business that started in Latam in 2012. Right. This was very back in the day.

17:18

Where it was the first marketplace.

17:59

Yeah. So when you're building, when we went out to build that, we were very young, we were in our 20s. I was one of the oldest one, or the oldest one I don't like. And we went out to build Amazon. And what we realized very early on that if you're going to build a business in Latin America, you need to build like 10 different businesses to make your business work. And I'll give you some examples. Right. We needed to buy these products and sell them online. But to do that, you needed to have payment rails and you didn't have stripe back then. So we had to build our own sort of like payment systems to be able to transact. And you had like 30, 70%, you know, rejection rate. And you needed to take that to where it is today. Right. Half of the people didn't have credit cards, so they wanted to pay cash. So we needed to build cash on delivery options, which meant getting to people's homes with a product, getting the cash and getting that cash back into the system, which was very tough. You didn't have trucks, you didn't have DHL, FedEx in this market. So we needed to buy our trucks, build the software, build the systems to be able to do this. We basically didn't have anything. Right. So we spend a lot of our time building the basic infrastructure to do that last mile thing that's selling online. And when you're in the US you're not facing that issue. You're just trying to make one process that doesn't work 15 times better. I learned through that experience that you need to build whole infrastructure behind it. And when I was thinking about Kabak, I was a little bit older. I have gone through that experience and I knew that in order for me to solve this fundamental issue, that is, how can I get more people in my lifetime into the middle class and sort of like be a part of their life through their car? The biggest question that I had back in 2016 when I started the business was what do I need to build? What are those pillars that I need to build to make this business work? Right. And I didn't want to do what we did in our previous company. That was figure it out as we go. I needed to strategize really well because this time, where the Uber without cars slide is out there, Airbnb without hotels, and I'm telling the ecosystem, hey, I'm going to have infrastructure. It wasn't popular back then, and still it isn't really popular. But in Latin America, it was needed. So for us to sort of like solve that issue, we needed to build four different businesses below our business to make our business work. You know, the first thing is we needed to build that E commerce platform so people can come sell their car and buy a car. We needed to build their operational or factory reconditioning warranty machine where, you know, we could come at scale and really fix these cars or recondition them, get them into hand of another user and when it fails, make sure that we were there. And this was a big undertaking. You know, used cars is usually anywhere between three to seven times bigger than new car sales. So if you're successful, your factories are going to be three to seven times bigger than all the OEMs combined. And you're dealing with edge cases. Right. You're not dealing with a linear manufacturing process. So we needed to figure out how to build, you know, a machinery that could do that at scale for hundreds of thousands of cars. You know, the regular mom and shop, you know, does 20 cars in a given month. Right. We needed to build the financing engine. How are we going to underwrite these clients? How are we going to get the capital to finance them? How are we going to collect? How are we going to do this all online? So we needed to build a financing business and we needed to build a logistic business. When you think about cars is that they move, like all of them, very.

18:02

Very easy things to do.

21:52

Yeah, well, back I was very naive. Right. Like when we started this, like we.

21:53

Now we call that defensibility when you're starting. Yes.

21:58

But we knew that we needed to do that to really provide that amazing solution for the end user. And we knew that our life was going to be living hell for the first few years because nobody was going to appreciate the infrastructure piece of it.

22:02

And this is a great segue because obviously Kavak is a very complex business if you think about one country. But you've been very intentional since the beginning of saying that Kavak is going to be a global company. And there's very few examples of companies in Latin America that have expanded successfully across, across the region, but also abroad. Like, you know, you guys have operations in the Middle east as well. So like, talk to us a little bit about that. Like, what, what is that? You know, what does that mean to build Quebec as a global company? And how do you translate this, you know, kind of complexities that you find in one market across different markets as well? Because you can imagine that that requires a lot of effort.

22:19

Yeah, well, the whole logic was the complete opposite, right? Like on how we think about sort of like expanding how we think about markets. So first we're not thinking about markets, we're thinking about the problem that we're solving. You know, we wanted to like, make sure that we could provide as much impact as fast as possible for our users. So the way that we, we think about markets and why we launched in Mexico City is because Mexico City is the largest city in North America. The market size of Mexico was huge. And in Latin America, people concentrate around the biggest cities. So 60% of the opportunity of Mexico was in one city. So when you're starting a business, the last thing that you want to do as you're going for that product market fit, as you're building all this infrastructure is go to broad too quick. So we actually, when we started the business, we went, no, let's go into the place where we can just spend a lot of time trying to understand the problem without expanding and just building everything. And that was Mexico City for the first four or five years. And we didn't have a lot of money to begin with as well. So we couldn't build all of that infrastructure that I mentioned that I was going to build out. We just had to put all of our time in building sort of like the data capabilities to be able to scale that. So at the beginning we actually just spent a lot of time in Mexico building this, building a product that had product, market fit, profitable product, you know, in the first four years and growing. And then we realized, you know, was that for us to launch this in any other Market and do it well. It takes you four years of just building the basic little things, so then you can think to start to scale them. So, like, when we started to expand, we expanded under, under the same philosophy is, okay, our home ground and what we're building and what's getting big, it's. It's Mexico. But then, you know, we saw cities like Sao Paulo, cities like Buenos Aires.

23:03

And how do you, I guess when you think about expanding, like, what, what led to those? You know, like it was the density of the cities or like, how, how do you guys picked, you know, the cities that you guys were going to expand?

25:04

It's, you know, one thing that was really relevant for us is the size of the overall, overall market. So we were looking for cities that, you know, it was, you know, bigger than a 20, a $40 billion opportunity as a city as its own in terms of transactions to how deep the problem is that we were solving. You know, whether it had what was the fraud rate, what was the financing penetration. You know, the more problems that it had, the more frauds, the less financing availability, the better for us and for what we were building. And also the size of the ticket of the car. Right. Like economics play a big. It's really important at the beginning that you have the right unit economics to sort of be able to continue to fund your growth. So any ticket size that was below $10,000 didn't make sense for us as an expansion city at the beginning. So when we mapped out those cities, you have very few cities left that are going through all these things. And that's how we mapped out the cities that we're in. Sometimes we went in really not aggressive. We just went in slow and learned. Other times we went in a little bit more aggressive. And we got the learnings through sort of like just doing this in several cities throughout the past years. But it's always been about not just establishing a global presence, it's about getting investing and seeding these markets for the first four years. Follow the data and try to make sure that you build the right data capabilities to scale those markets. And what we see in every single one of them is that after a certain amount of years that you build all of this infrastructure below it, that scalability becomes a lot easier and replicates what we saw in Mexico. So it's never been the ambition to build a global company. The ambition is to solve this global issue. And we're trying to pace ourselves into that.

25:15

All right, I want to jump back to 2017, and you put out a Company wide memo, which started with, I'd like to start complementing our people pipeline with a robot pipeline. And just to ground all of us, 2017, the transformer paper had just come out. It was still five plus years until there was chatgpt. And then you were pretty specific. You're like, we're gonna have Robot 1, the VP of Sourcing, Robot 2, Customer Satisfaction, Robot 3, Cross Selling and so on. And so today many companies are starting to implement that in 2017. That was not something that was top of mind for most. Like, bring us back to your thinking there. And what drove that?

27:11

We knew that we were building this really complex business. We were building, as we mentioned before, a business that was vertically integrated had many different businesses layered into it. And we were dealing with real edge cases. When you're trying to solve lifetime value for customers related to their car, you're always dealing with an edge case. It's not a straightforward solution for any given problem. It's the most important purchase a user's gonna do. They're probably financing themselves for the first time. It's probably their first car. And their car is going to break down at some point and it's going to break down in places where you don't want it to break down. So you're always dealing with different situations. You know, we're the master of edge cases. And when you're dealing with an edge case, what happens is that it requires a lot of information and communication from the company to be able to solve that in a way that the user is satisfied. And what I started to see in 2017 in our company was that that highway of information, it worked really well when we were really small because we were all in a room when something like this happened. And we can make decisions really quickly and we had all of the information and we were able to develop an amazing experience. But what was really clear to me at that point in time that if we scaled and if we became a company that's doing hundreds of thousands of transactions every year, or millions of transactions every year, that was not going to be true anymore. That's the moment where we sort of like when I sent out that memo and that communication was just projecting ourselves into the future, that this was what we were going to be trying to solve at scale. So for me, it was all about building from day one the right ontology around all of our different businesses or business lines for them to be able to communicate together. And you see it today, right? Like when you scale a business, what's the issue when you scale a business is you have many people everywhere, right. And they cannot communicate in the way that they communicated before. So if you're in the invoicing team and you need to invoice a car for a customer and you have a doubt with the auto parts piece of the invoice, you have no way to know who to call. If you have a doubt with the price of the car, you have no way to know who to call. And that was the challenge that I was seeing at that time was like, how are we going to create this highway of information where we can sort of like talk to everybody? And, and I think that there's. There's a show that I just watched a couple of episodes last week that that can help me land this. But it's a show called in Apple called Pluto, right? This is a show about a virus hits humanity. And what the virus does is that it connects us all in hive thinking, you know, like I have all the knowledge that you have, I have all the knowledge that Gabriel has. So everybody is sort of everybody. And in real time, they can connect all of the information of humanity and just deliver an output or a communication or an innovation. Right. And AI is a lot about that. Right. And building a business is around like the best businesses will communicate really well within their organizations to solve a determined issue. It could be a, an operational issue, it could be an innovation issue. But if you manage to get that communication flowing, the velocity that you can innovate, the level of service that you can deliver was huge. And we saw that because it was hitting us in the face every day. I don't think there's many companies out there that have to manage so many edge cases. So I wouldn't give myself too much credit. It was just about facing that problem on a daily business and then just pushing towards building the ontology. Because the only thing that I knew that was going to get us on the other side was the data piece of it and how we connected all of these business. That's where, when you think about my business particularly, I only learn through trial and error. That's my way of learning. And everybody has their different ways of learning. And I think that you need to make a lot of bad micro decisions every day and show up to see what happened, to have a great macro outcome after compounding sort of like this decisions. And in Quebec, we have what we call the four places where a business will succeed and fail every day if we do it well or we do it bad. One place is pricing. If I buy a car and I buy it at the wrong price or I buy the wrong car, I'm going to lose money. That's a fact. So we knew that. We knew that in order for us to do pricing well, we needed to be able to learn every day and each car that we bought to make sure that we bought the next car better. And you have 60,000 unique SKUs with unique features that you need to price any given time with a macro happening around you. So we knew that we needed to put AI in data in terms of how we thought about pricing. And we knew that we needed to do that on a daily basis. Humans cannot scale that decision. We also knew that cars will fail. And I didn't know anything about cars back then. So the only way for me to learn about cars was not about how I inspected them and then sold them, reconditioned and sold them. The only place where you can learn about a car was when it failed. And this was something that was not popular back in the day because everybody was, well, why are you going to own the warranty? There's no sense in it. And on one end there wasn't an infrastructure in the markets that we serve to delegate it. So we needed to own it just to be able to solve the problem. But the most important thing is that by owning the warranty, you own the data at moment of failure. And we built all of our systems just learning sort of like from that failure. And every day just making the inspection, the reconditioning and servicing the post sale of it better just by sort of like learning that process. And that's a daily decision that you face that you, you needed to replace with it with, with data. Underwriting is the same thing. Yeah.

27:49

Which is notoriously difficult in this industry. So then if we take to your, to your microdecision point, you started like many companies, like, all right, we will have AI tools, we will give them to our smart employees. It's going to make everything more efficient. But as you talk about, that actually did not work. And so you pivoted more towards AI is just going to have to do this. And there might have been two strategies tested a little bit here and there, but you guys pretty famously went all in just assuming it was going to work and then working really hard to get it up to human level and then past human level. How did you manage to move the organization in that direction? Because it's not just technology, it's also the people challenges, as you point out.

33:56

So there were different places where it worked more or less like Pricing, it worked pretty well. Reconditioning, it worked pretty well. Underwriting, it worked pretty well. But the biggest challenge that we were facing was customer interactions, right? Like those edge cases. The beautiful thing that happened was we started this in 2000, thinking about this and building the ontology and building of our Systems together in 2017. So by the time that ChatGPT came out, you know, we were ready. We were really ready from an ontology perspective. We had all our systems connect like that. It was really, we had the systems in the right place to sort of like, extract information, to start to build agents. And we needed to make a decision on how we viewed our organization going forward with this technology. Right? And we knew that we couldn't scale the way that we were scaling. We had too many people. The highway of information, of things, was not optimal. So we were not delivering a great customer experience for that customer experience that we wanted to deliver on these edge cases. And we knew that if we wanted to scale, we needed to change that immediately. So we started to think about more of that architecture, of how can we make sure to build agents and build them in a way that they can communicate with each other. And it started from the recruiting process. Every time we had a friction or we had a need, we started to think about, well, can this be solved with humans that have blood, or can this be solved with agents that have electricity going through their veins? And we started slowly just thinking about, where do we need to put an agent? Where do we need to put a human? But the first thing that we built out was that operating system that allowed us to know what to do next. And when you're building AI, the first thing that you need to build is the brakes of the system. It's the understanding on where you're going to deploy it and how you're going to deploy it. We had thousands and millions of information lines about our users, what they were navigating, how they were chatting with us, where we were failing them, where were we succeeding. And the first thing that we did was we just built this system that allowed us to understand everything about every user. Right? And that's something that you couldn't do prior to that ChatGPT era, where you had the information, but you couldn't sort of like extract and automatically know, you know, contextualize it. Right? And we made the typical mistake that everybody's making, that is, you know, we build this copilot tools to give them to our teams so they could just use them and just provide a better customer experience or just have the information to provide, you know, a better solution to our customers. And we did just that, you know, in 2000, you know, late 2022, early 2023, we spent a lot of time building these tools for everybody in our organization, and we gave them to them. And we realized very quickly they didn't adopt them. And when we saw that, we knew that even if you had the right information, even if you had the correct highway or database for people to, like, find out what they needed, they were not going to do it. So we went funnel by funnel, putting agents in front of, like, critical aspects of the business. So it started by. We didn't, like, every. Most people attacked it back then, just trying to, like, solve customer service. We didn't like. We. For us, the issue was not customer service. For us, the issue was underwriting your loan. It was, if your car broke down, what do we do then? And at that moment. So we. We went and tried to solve the hardest thing first. That was those edge issues that our customers were having. We had all of the information of our users. We just needed to build sort of like the right skill sets to solve that. And we created this process where we built agents working symbiotically with humans in the organization. And some things humans solved, some things agents solved, depending on a complexity. And we had an orchestrator in the mix that was sort of like guiding who was going to solve which. And we started very slowly with one funnel, one process, created a skill set, and we started to see how agents could perform better than humans on certain tasks and started to scale it from then. And for the past three years, we've just been creating all of these skill sets that have been able to empower a lot of our AI agents and build the architecture that allows them to communicate with each other for us, ultimately be able to orchestrate something simple for our user. But we put the agents in front of our users really quickly. It was very painful. Yeah.

34:37

No, that I think, is what is unique is you had weeks or maybe even a couple of months where various functions were underperforming the humans, and you just had the sort of confidence that you were going to get there and resisted the temptation to hire more humans back or give up on certain tasks.

39:34

No, we had a year.

39:51

Yeah.

39:52

So we were growing, like, the business was growing 300%. Like 2022 was growing 100%, and 2023, we were flat. So the reason behind that was we were just restructuring everything below the line. And when you start to put these systems in, what typically happens is Your customer experience starts to deteriorate at the beginning because you're not delivering at the same level that a human could deliver. Your sales is dropping because we're not doing customer service, we're doing sales, we're doing purchases, we're doing financing. So you've seen all your output. KPIs just deteriorate. I think that the resilience that we had at that moment was, you know, we didn't have for a certain funnel, not for the whole company, we didn't have a plan B. The plan A was we need to make this work. And we got our engineers, our teams and everybody just making sure that these agents could perform at least parity to what we were performing before. And it was in a certain funnel, you see a drop up until it doesn't, and then you start to, it starts to go back up. And we got to a place in the first funnel that, you know, we were like, like 1.5 times better than our best human. And in a certain place. And at that point we said, okay, let's not focus on making it seven times better because the models will get there. And we have an amazing philosophy in the company that is we don't build for ChatGPT for. We built for ChatGPT 7, right? Or we built. We know that the models are going to, are going to move faster than what we can move. So we try to like, anticipate what needs to be done. So like, when that, when that technology is there, our infrastructure and architecture sort of like can actually take advantage of it. And we started to work on market share of these interactions with our customers. So when we saw a funnel like delivering parity or a little bit better than parity than human, we went to the next friction, so on and so forth. And it was always the same pattern. It goes down before it goes back up. And we slowly started to sort of become more confident about that strategy. And up until a point where we decided, well, you know what, we need to burn all the ships and just do this for the whole organization, right? Which is different. Today we manage like 90%, 95% of every human, every interaction with our users, with an AI agent in the middle. But that's not a reality for all of our backend, right, Pricing, invoicing, all of these things. We have ML, you know, we have all of these, of these systems now we're building sort of like the agents to manage these systems so they can also converse with all of our other agents. And it's just, you just have to have the patience of it. But it took us, you know, like it was a year of flat. A lot of. Under a lot of pressure, you know.

39:53

How did you manage, I guess, that pressure with the culture within the organization for such a long period of time?

42:43

It comes ultimately to what we believe the world is going to look like in a few years. Right. You know, we think that this is the biggest technological shift that's ever happened to humanity. And our responsibility as leaders in this time and for our company is to make sure that we're not only on the other side of the shift, but we're thriving. And I like to go back a lot to Netflix. I love Netflix because they started out as a videotape company. Right. And then they went to streaming. Well, let's unpack that. You have Blockbuster, then these guys innovated and you had videotapes delivered to your house. So assortment wasn't an issue anymore. And then you had streaming. The way that I like to think about Kabak is that incumbents or Blockbuster. Kawak was videotapes sending to your user. And that's probably traditional software.

42:52

Yeah.

43:45

And selling online and underwriting online and everything. And then, you know, moving to AI is like sort of like that streaming transition. And, you know, when you're doing a transition of this shift, you need to make sure that everybody understands that we're going to go streaming or die. Or die. Right. And one of the things that we had going for ourselves is that our market imploded. I don't know if you remember what happened to the autocar. The auto space market in 2020 was down 99.9. A lot of business went under. So it was literally nothing I can do or say to anybody that made them feel comfortable. Right. You know, like when you. When your injuries down 99.9%, you could like, everybody's gonna be uncomfortable.

43:46

So maybe set that backdrop of where you were. Like Kabak, I think, at that time, had 10,000 employees. Like it was a 20, 22. Right. Every was a very high flying time. So 10,000 employees, I think you were burning a million a day. Market implodes.

44:31

We were building this like we were scaling. We were building the infrastructure, a lot of infrastructure to scale. We had more than enough infrastructure to grow four times where we were at that point in time, growing really quickly from going to 200 people to 10,000 people, like in 24 months timeframe.

44:44

Wow.

45:01

The business went from zero to billions in revenue at that same speed with. With a lot of complexity behind how you deliver that Revenue, Right. You know, you're moving cars. So we had everything, you know, just ready to go really quick. And all of a sudden, market's employed and you have to change your strategy. You know, you don't know. And more so if you're building in latam, capital comes in in latam. Well, it never came in at the speed that it came in in 2021, and it never left so fast as well. Right. So you have to just rethink your whole strategy. Right. It's like, you know, capital is not be here forever, and we just need to make sure that we make the shift. But when you're making that shift, remember that it's like, you know, you're at full speed going ahead and say it's like taking off on a plane. Right. Like, that's the worst time to slow down. You need to get yourself to like 10,000ft up in the air before you start to make sane decisions. And we needed to slow down while we were sort of like going through that takeoff process. You were facing so many things, you know, like, should I just push for, for growth? Should I slow down and just buy time? We were in a, in a, in a really interesting pickle because we couldn't just shrink to profitability. We needed to grow while becoming more lean and efficient at the same time. And the company from there, you know, we went on to grow four times to where we were at that place in time. And we went on from burning a lot of money to become profitable in that frame of time. But it was. Everything was very heightening. And when your market down, there's no decisions. When your market goes down 99.9%, there's no decision that's making anybody comfortable. Right. Because for us, we knew that we had something special. You know, we were not just building a business that people wanted, we were building a business that people needed. The, the metric that makes us more proud is that 40% of our customers are buying their car for the first time in their life.

45:01

Yeah.

47:04

This is because that's incredible. We knew that we had something special, and we were also building these AI capabilities in the midst of it that we also saw as very special, especially as operators, because the scalability of it, the thing that we were suffering through the growth phase, that's never ended. We knew that it could probably be easier in the other side. So I would say, like, when. When you have everything coming, coming at you with that level of intensity, expectations all of a sudden lowered. Right. Because there was nothing that I could actually do that would make everybody comfortable more than just get profitable and go through it. And we were definitely working towards that, that, that objective. But the most important objective was not just getting profitable, it was getting significantly profitable on the other side and being able to deliver more impact for our users. So we had that opportunity to make bets.

47:04

And you made a big one.

48:03

And we made a big one. We continued to make it right. But we definitely knew that we needed to do this transition where we were streaming. And I believe that any company right now, any CEO right now, if they're not thinking about it in that way, they're going to be up for a world of slow death and pain. So we're forced into that transition.

48:04

We also have a lot of founders from all around the world that listen to this podcast. Curious if you have any advice that you can share with these founders that are building in emerging markets, let's say Latin America, and how to think about building a business.

48:29

Now, I think first a lot of founders, they go out there and they just want to be founders and build a business. I think that's the wrong take. I think you just need to find a problem that needs to be solved and that you can probably, at the early stages of it, relate to it as much as possible and that you care about. And if you find a problem that needs to be solved and Latam is not about things that just make it better. You're there dealing with. Most of your population is going to be struggling and they're suffering against. They need to feed the table. Basic needs are not covered. So if you're building in Latam, you have to think about building products that people actually need, not that people necessarily want. And if you find a problem, you know, you have to go all in and make sure that you're solving for something that has real impact. I think the purpose behind it will get you through the highs and the lows if you find the right thing. And I, and I also think as a Latam founder, you have to be also agnostic of region. Right. You know, if you see something that can be solved in the US that you're excited about, you know, just go there. Right. One of the things that in Latin America is that nobody tells you that you can think big. No, nobody. No, no. You're not brought up sort of like in that way that you find, you know, when you talk to founders here and when you talk to VCs here, you know, the level of ambition and especially in Silicon Valley, you know, thinking big is the norm. I think that's that's what I think. You know, founders need to understand that they can think big, but they also need to understand that they need to solve something real. Right. Because it's going to take years. If you see the best companies out there, 97% of their value gets created after year 15 through year 1 5, 97% of their value. I've talked and listened to a lot of these founders that have built this generational multi billion dollar companies. And they insight that I get from zooming out and looking at these companies is that when you ask them like, how can you be at year 20 still be growing 30%, what happened to make that happen? And like most of the feedback or the learnings that I got is that Carlos is just about taking frictions away from my users every single day, every week. Making your business 1% better. And making your business 1% better is means taking a friction away from your user and making their friction 1% better. And that compounds over time. And if you do that and you focus on that relentlessly and what you're doing users really value, you're going to figure it out. Right. My job is cleaning cars. At the end of it, we're building all of these AI, we're building all of this, but at the end of the day, it's delivering a car that's clean. So even in the worst day, I could just go and wash a car and feel good about myself, right? So it's making sure that you find that friction and you take it away. Like great people clean the car. Amazing people build systems that can do this scalable for millions of people. Right. So I would say that gets me through a lot of it. Just understanding that we're at year nine so none of our value has been created yet and we just need to take frictions away. And when you do that, scaling is easier. You know, four years ago we didn't have a fintech on in our business. It was very hard to do what we do because a lot of people needed financing and we couldn't control that piece of the business. Now we do and it's thriving and we're helping a lot of users out. And the reality is I make a decision today and I need to factor the fact that I will show up in 24 hours to reassess that decision. Sometimes you make a decision and you let it out there roll for 15 days. And I know when I do that it's wrong. You know, if I make a decision, I need to get on a call the next day and say, how Is this going and reassess and you have to be comfortable with being wrong. So I think enjoying the micro of it is very important. And treat problems as a protein bar. Right. Like our job is literally to solve problems. If you're not excited about solving a problem, if you're not excited about hitting complexity.

48:46

That's a great analogy.

53:23

If you're not excited about doing that, what are you doing then? Every time you solve a problem, you build these barriers, this defense. So you need to enjoy it. That's the job. Look at my story. I come from Carac, from Venezuela. I'm a glitch in the system. I'm not supposed to be here talking to you guys about building this business. I'm so fortunate about having this opportunity. You need to acknowledge that every single day.

53:24

A little on the zoom out. I think one of the things you shared when we were talking before that's unique about you is this annual process that you go through of self introspection, which essentially is you ask, am I still the right CEO for this phase of the company?

53:52

Yeah, I just went through that. Yeah.

54:05

Yeah. Do you want to talk a little bit about that exercise?

54:06

Yep. So you have to balance your role as a founder, stakeholder and as an operator. Right. And, and we do this. I do it myself. We do it with our, with our, with our management team and team members. Every year or so I fire myself, you know, and I go through this exercise that is really painful, you know, firing yourself. It's really painful because your business, if you do well, is going to grow faster and it's going to be than you can. That you can ever grow as a human. So the process that I go through is every certain. Sometimes it happens every three months, sometimes it happens every couple of years. But I definitely go through it a lot. I just fire myself and lay out, you know, if you're going to hire a CEO to build that vision that you laid out, what would you hire for, like what would you ask him or her to do that's relevant? What are the risks that you know that they need to be taking? What are the things that you know that they need to protect and compound? What would you lay out like the job and how would you guide them through the next year of their role to make sure that they're successful? And I spend a couple of weeks just thinking about that and then I go through the next. And this is, this is hard because it puts all of your, you have to put everything, all of your emotions and everything in check. Right. Like you're always, as a founder, you're sometimes doing things that you shouldn't be doing. You're. You're trying to do too many things at once instead of seeing sequencing things. You get impatient. Like, you have all of these things that as a founder and operator, you go through. And this is a time where you can I take a time to, like, take a step back and make sure that I think about it a little bit more coldly, listen more to, like, all of the inner voices of my stakeholders, my users, my employees, my family, and like, all of the things that are. That are out there. And I figure that out first. Then I ask myself, can I hire myself back to do that? Right. And the pros of hiring myself back to do that is, one, there's a huge probability that I'm going to care more than anybody else about it, and caring is important. Two, you have a pattern recognition that nobody else is going to have because you build it from scratch. So you can probably see certain things and solve them quicker than anybody that you're going to bring in. But the most important thing is you're going to have to ask yourself, okay, in order to deliver what you want that CEO to deliver, what do you have to let go of? So you go through that process of letting go of certain initiatives, of letting go of certain pieces of yourself, you know, certain belief. Because in order to build businesses, you have to become a Persona. You're like this. You're always like that. You know, these actors that are always in, like Jared Leto, you know that they're always in character. You sort of have to get into a character, because when you're doing this, this moment in time, you have to get away from that character and realize what's the new Persona that is needed for this new phase, and let go of a lot of the things that make you and build new things, build new skill sets, build new ways of thinking. So I go through that process a lot. So far, I've been hiring myself back to do it. And I really want to do this for the rest of my life. But it doesn't mean that I don't have to go through that process, and it doesn't mean that, you know, the best person needs to be on the field operating. So that's something that I would recommend people to do. And you'll mature through that process. You'll change through that process. But ultimately, you're always that person that you are, you know, that kid or that founder for that certain stage. It's always there, and you're always going to have that as your instant. An incident is really important in decision making, but now it's guided towards a framework of what the company needs from you in this stage, what your employees needs from you, what your family needs from you, what your stakeholders needs from you. For certain, if you talk to my employees, my family, my stakeholders, they definitely want a different Carlos every year, right? And they're excited about past Carlos, afraid of past Carlos as well. My job is to make sure that I get myself, myself in a position where I can continue to deliver, you know, an amazing company for all of us. Well, thank you.

54:09

I think that's actually a great Note. We love 2025 Carlos, are excited to see 2026. Carlos, thank you for joining us.

58:38

Thank you Carlos.

58:45

Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating, or review, and share with your friends and family. For more episodes, go to YouTube, Apple Podcasts and Spotify. Follow us on X16Z and subscribe to our substack@a16z substack.com thanks again for listening and I'll see you in the next episode. As a reminder, the content here is for informational purposes only, should not be taken as legal, business, tax or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see a16z.com disclosures.

58:48