AI Copilots Are a Dead End. Here's What Actually Works | Kavak CEO

Most of the feedback and learnings I got is that every week you should make your business 1% better. Making your business 1% better is taking a friction away from your user and making their experience 1% better. Every year or so, I fire myself. Your business, if you do well, is going to grow faster than you can ever grow as a human. You know, if you're going to hire a CEO to build that vision that you laid out, what would you hire for? And I spent a couple of weeks just thinking about that. Then I asked myself, can I hire myself back to do that?

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. 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 hold their car. And we do everything, you know, 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, you know, we're just building that relationship with our user as they go along. And in terms of scale, we're 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.

Wow. It's a good question. Let me try to unpack that. There's a lot of the learnings and a lot of what I am today come from those years and from my family. So yeah, I lived in Venezuela and the US up until I was like 17, 18. Moved a lot. And I think three things sort of came out of that that still stay with me. The first thing is getting used to change. When you change so much, 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, and that didn't necessarily come in the form of the best schools. We could end up in a public school in Venezuela which is very different than a public school in the US. The best private schools in Venezuela rival the public schools in the US. So the first thing that I learned 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, you were enjoying everything, and then you had to just move and start all over again. And I started to see that pattern of everything could be great one day and then all of a sudden not great, and the same way in the other way. 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. 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 changed the way I see things. I'm never stuck when everything is going really good. I'm like, it's going really good, or when it's going really bad, being depressed about it. I know that it's just going to change again. And I see how this takes a toll on a lot of people. Everybody thinks that all these mental health issues, every time that you see so many swings, people get disoriented. For me, that's my nature and I think that shaped my ability to build companies and build them with all 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 you know doesn't change, and that was for me my family. In the Inception movie, he had his totem to understand whether he was in reality or not, or in a dream. For me, that totem was my family, 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. And I think this was the most important thing because 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 gave us so much love and they put me and my sister first on everything that they did. But I think the biggest thing that shaped me back then was just watching them. 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 these dreams of the things that we wanted to do and how we want to spend our time together. And I remember there was a point in our life when I was just coming back from the US. I was 13 years old. One of those changes and they sent my dad to the middle of nowhere. It literally took like 12 hours in Venezuela by car to get there. Then you had to get in a boat for two hours. Then you got to this village where Christopher Columbus got to when he discovered America. It was like a thousand people living there. And we were just coming back from Newport, Rhode Island, which was amazing. And my father gets stationed there and we're going there and I had to be homeschooled by my mom. And when we get there, there was one car, only one car in the whole village that was assigned to my dad. He was going to be the commander of that station and the car only went in reverse. Seriously. And this is a great story because me and my sister, my mom, and they were getting there and they're just laughing about it. They're just like, 'Oh, oh shit,' just laughing about us getting home in reverse. And seeing that level of optimism, it sort of shaped everything for me. And that was everywhere we went, everything that we did. My parents sort of took it upon them to just make it great and fun. And they always gave it all. That was a town that they rebuilt. And I saw them rebuild that. And I saw them do like everywhere they went, they just gave it all. And just seeing them just showing up and loving the work, making sure that we stay united, and being optimistic around all those changes was critical. And that continued. In 2002, my dad was an admiral in the Navy and he didn't want to be a part of what was happening in the country and he was against the government and he decided to just state his position there and that 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 that was a moment where that constant, that totem, changed for me and my sister because it was the first time in our lives where we were not in the constant. I stayed in Venezuela, they had to leave the country, and the next chapter of my life came without that physical constant. We still had the fortune that we could see each other every year. But 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. So that would be the second thing. And the third thing about those years is the pattern recognition that you develop. I have the advantage and the privilege that I went to public schools in Venezuela and to Oxford. So I lived a life where I've seen different socioeconomic ecosystems and that provides a level of empathy that few have. But on the other hand, when you're changing so much, the only thing that's constant is human beings, is people. And after a certain point, probably like school 10, you don't want to get hit in the face anymore and you start to learn how to read people and you start to see the common threads around your world. And I developed a formula on how to make sure to create win-win scenarios with everybody around me. How to build relationships where 1 plus 1 equals 4. And not 2. And as I got older, I became really good at making that formula work. And every time I moved, my situation changed, but I could faster make it a great situation for myself and for my family. So I started to take more and more control of the narrative than I thought I had.

Yeah, well, it all built up to that moment. 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 was the first time that I see, this is 2009, 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 Linio and build the marketplace side of Linio, which was 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 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's a 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. Literally, it was a nightmare and I lost a car. And I moved to Mexico to launch Linio and that sort of was in the back of my mind. I had just been through this terrible process and I started to work on a solution to sell my car in a different way. And I just, at night, I just built an algorithm to price every single car out there.

So when you think about the market in Latam, it's very informal. 90% of the market is informal. It doesn't happen in dealers, doesn't happen in a formal space, and 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 like 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 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 entrepreneur. So no bank wanted to give me access.

Yeah. Nobody was going to underwrite me. So, but I still needed a car. In Latin America, you need cars. If not, you're using public transportation, which...

Exactly. Exactly. Yeah. Well, I would rather just go in reverse than not have a car at all. But yeah, 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 Kavak was just by me being probably the most naive person in Latam. And that's 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 those stats, that level of informality, that level of fraud. But the most interesting piece about it was, 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, 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 going to break down. There's no way around it. It's like humans, we're just at a certain point we're going to break down. The real question is how do you show up for your user when that happens. I don't make these cars. I just provide the proper warranties for somebody when they buy them. 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 these assets.

So, to put it in perspective, in Mexico particularly, only 5% of the market is financed, of the used car market. When you compare to the US, the US is closer to 90%. So this means that in the US 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 opportunity that I saw that I could relate to as well. When you go deeper on that and you think about Latin America, not having a car gives you a different life than having a car. 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 change that I saw in my life was when I got myself 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 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.

So it comes from what I'm describing. When I saw this opportunity, the opportunity was not to just go and try to solve the buy and sell process, solve the lemon or the warranty coverage part. It was very important to 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 provide the proper coverages and that you can get financing for your users to be able to buy this car. My whole goal became how can I get people into the middle class through the car. And having built Linio, I learned this is a business that started in Latam in 2012. This was very back in the day where it was the first marketplace. So when we went out to build that, we were very young. We're in our 20s. I was one of the oldest one. 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. 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 payment systems to be able to transact. And you had like 70% rejection rate and you needed to take that to where it is today. 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 the 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. So we spent a lot of our time building the basic infrastructure to do that last mile thing, that 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 a whole infrastructure behind it. And when I was thinking about Kavak, I was a little bit older. I had 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 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? 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 is a 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 solve that issue, we needed to build four different businesses below our business to make our business work. 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 the operational or factory reconditioning warranty machine where we could come at scale and really fix these cars or recondition them, get them into the hand of another user and when it fails make sure that we were there. And this was a big undertaking. 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. You're not dealing with a linear manufacturing process. So we needed to figure out how to build a machinery that could do that at scale for hundreds of thousands of cars. The regular mom and pop shop does 20 cars in a given month. 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, they move.

Yeah. Well, back then I was very naive. Like when we started this...

Yes. 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.

Yeah. Well the whole logic was the complete opposite on how we think about expanding, how we think about markets. So first we're not thinking about markets, we're thinking about the problem that we're solving. We wanted to make sure that we could provide as much impact as fast as possible for our users. So the way that 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 too 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 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 in the first four years and growing. And then we realized 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 when we started to expand, we expanded under the same philosophy is okay, our home ground and what we're building and what's getting big is Mexico. But then we saw cities like Sao Paulo, cities like Buenos Aires.

It's one thing that was really relevant for us is the size of the overall market. So we were looking for cities that were bigger than a $20 billion opportunity as a city on its own in terms of transactions. Two, how deep the problem is that we were solving. Whether it had, what was the fraud rate, what was the financing penetration. 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. Economics play a big, it's really important at the beginning that you have the right unit economics to 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. And we went 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 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 investing and sitting in 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 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.

So when we started Kavak, 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 is going to 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. 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 it 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. And that's the moment where I sent out that memo and that communication was just projecting ourselves into the future that this was what we're going to be feeling at, 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. 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 how are we going to create this highway of information where we can talk to everybody. And I think there's a show that I just watched a couple of episodes last week that can help me land this, but it's a show on Apple called Pluribus. It's this show about a virus hits humanity and what the virus does is that it connects us all in hive thinking. 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. And AI is a lot about that. 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 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 basis 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 this 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 these decisions. And in Kavak, 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 environment around you. So we knew that we needed to put AI and 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 could learn about a car was when it failed. And this was something that was not popular back in the day because everybody was like, 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 from that failure and every day just making the inspection, the reconditioning and servicing the post sale of it better just by learning that process. And that's a daily decision that you face that you needed to replace with data. Underwriting is the same thing.

Yeah.

So there were different places where it worked more or less. Pricing worked pretty well, reconditioning worked pretty well, underwriting 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 thinking about this and building the ontology and our systems together in 2017. So by the time ChatGPT came out, we were ready from an ontology perspective. We had all our systems connected. We had the systems in the right place to extract information and start to build agents. And we needed to make a decision on how we viewed our organization going forward with this technology. We knew that we couldn't scale the way that we were scaling. We had too many people. The highway of information was not optimal. So we were not delivering a great customer experience for the customer service 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. We started talking about, every time we had a friction or 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. This was three years ago. 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, of what they were navigating, how they were chatting with us, where we were failing them, where we were succeeding. And the first thing that we did was we just built this system that allowed us to understand everything about every user.

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 extract and automatically contextualize it. And we made the typical mistake that everybody's making, which is we built these co-pilot tools to give them to our teams so they could just use them and provide a better customer experience or just have the information to provide a better solution to our customers. And we did just that. In 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 find out what they needed, they were not going to do it.

So we went funnel by funnel, putting agents in front of critical aspects of the business. So it started by, we didn't, like most people attacked it back then, just trying to solve customer service. 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 at that moment. So 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 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 complexity. And we had an orchestrator in the mix that was 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 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 to 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.

No, we had a year.