The One Mindset That Built a $15B Company | Qasar Younis, Applied Intuition

1. 0:00 – 1:16

   Intro

   1. QYQasar Younis0:00

      First-time founders tend to think that building a company is a one-time thing, and really actually building a company is like being an artisan or honing a craft. I think if you have the mental perspective that you're gonna do this for many, many years, and you might do it two or three or four times, then you actually approach starting a company slightly differently. And it's great if the first company works, but oftentimes it doesn't work. My first company I spent three years on, and it wasn't successful. Some of the biggest lessons I learned that make Applied Intuition, you know, much more successful came from that company 20 years ago. So what makes a company succeed versus a company fail? The biggest mistake I've made in terms of starting companies is... [gentle music] My name is Qasar Younis. I built Applied Intuition. Before this, I was the COO at Y Combinator, and before then I founded a company which was acquired by Google, and at the beginning of my career, I worked as an engineer at General Motors and Bosch.

2. 1:16 – 8:04

   When Everyone Went Vertical, I Went Horizontal

   1. QYQasar Younis1:19

      Applied Intuition is a physical AI company. A lot of times people think physical AI is just humanoids, and humanoids is a very interesting form factor of physical AI. But I actually think cars and trucks and industrial equipment is something that can be made more intelligent and have a bigger impact sooner. This is the Giga truck. It has, uh, some self-driving hardware on there. These trucks are running live on Japanese roads right now autonomously. Our mission is to put intelligence on a billion machines. The only way you do that is you take the same platform and you put it on lots of different machines. And why do you wanna put intelligence in those machines? 'Cause those machines right now are pretty dumb. They require human beings to operate them. If you can put intelligence into those machines, they can function themselves, and if they can function themselves, they provide a lot more value. The company is over 1,000 engineers. We're almost 1,500 people. The company's valued at $15 billion. Our products are deployed in dozens of countries around the world, in lots of manufacturers, in many verticals. Now, it's more famous as the place where the industry has already started to die. I grew up very much in the shadow of the American car industry losing its position as the best in the world. So I'm entering as an engineer, an industry which was in a very volatile situation. My reflection on that was if I stay in this industry and the industry shrinks, that could be very bad for me as an engineer. So part of my ambition to become a founder was to control my own destiny. I left really great jobs at General Motors and at Bosch with really great companies to make my own company. It seems like a pretty risky thing, but 20 years later it was, it was the right thing. Cars that can drive themselves. It still sounds like science fiction. But guess what? It is here. The industry was very different when we founded Applied in 2017. Self-driving, it wasn't... People were not clear how self-driving would be built. It wasn't clear if self-driving would happen. It seemed like it was very research-oriented. A lot of the AI breakthroughs hadn't happened, and th- this is really important. The transformer and this new architecture, which the large language models have really benefited from, also has a lot of impact in self-driving. All of these almost building blocks didn't exist, and maybe the biggest point was we weren't sure if self-driving would ever happen. I think at that time, lots of self-driving car companies, many that don't exist anymore, were doing actually what some of the AI companies today are doing. One thing is they would try to go vertical. They would try to build everything, the tools, the in- all, everything, the data engine. Sometimes even, you know, the vehicles themselves. They're gonna do robotaxi or they're gonna do trucks. That becomes very, very expensive. At that time, we felt pretty strongly it's not obvious which vertical is gonna work, and it's not obvious that being a vertical self-driving car company is actually valuable. A lot of times companies will spend a lot of their resources and energies on things that actually the end customer doesn't really care about. This is the inside of a car. This is kind of a classic inside of a vehicle, and this is using some of our, uh, platform, and the big difference between these two is there's a lot fewer components here. As you make a vehicle intelligent, you also wanna change the platform that it's on. The traditional platforms are not really made for autonomy. Uh, they're not really made for intelligence. Each of the components are separate. The newer version vehicles, we can reduce a lot of that onto individual compute, and then you can put intelligence on there, and you can do all these other like non-intelligent things like rolling up the window and playing your music and things like that. The downstream impact is just a lot fewer components. I think the most exciting part is taking the same platform and putting it on so many different vehicles. If you're building this type of platform or intelligence just for one vertical, it might never happen because it's too expensive. Most industries, the horizontal companies actually do really well. Take, for example, data labeling. Every company can make a data labeling product for themselves to help label the data that they're collecting from their fleet. But the end customer who buys the self-driving system doesn't really care about who... Did they buy the data labeler or did they make the data labeler? If you fast-forward today, there's a lot more horiz- horizontalization, so you can go and you can buy a lot of the parts of the stack, allowing you as the self-driving company to focus on just the most valuable and most important part of the self-driving problem. The downstream impact of the 2017 approach is it required lots and lots of capital if you're building everything yourself. In a very specific vertical. So you're taking the risk, capital risk, and you're taking the market risk of going into a vertical, and that's why vast majority of the companies have not made it to today. And we said, "Okay, actually, we should just provide the tools and let everybody try to figure out self-driving." And, uh, that was a very, very good move predominantly because on the manufacturer side, so not on self-driving, but on the m- manufacturer side, they were always gonna be interested in building a lot of this technology themselves. One of my first, uh, earliest engineering managers, in his office he had a sign that said, "No problem can withstand the constant onslaught of thought." You see AI companies today spending a lot of money. That doesn't necessarily mean that they will be successful. It doesn't mean they're automatically gonna be unsuccessful, but it's more risk. So I think the best founders are thinking about the whole problem. Some of the problem is the engineering and the technology, but the other problem is the business, and you wanna make sure both of those things are working together. Having a fair amount of focus on commercialization, I think is, is important. Automotive OEMs, they work in a very competitive industry. You know, I went to the General Motors Institute. I grew up in this extremely competitive industry. When you're in a very competitive industry, you're very thoughtful about how you spend your money, and therefore there has to be very clear value. And so the way that it impacted us is we have to build products that have very, very clear value. There's no company on the planet that does physical AI in this breadth that we do it, as a horizontal company providing that intelligence layer to all these other companies. My biggest contrarian view is that you have to build the business model into the technology and the technology to be built around a business model. You can't add it on afterwards. It's very hard to put in plumbing after the house is built. I think my biggest recommendation is really think about commercialization earlier than you think you should be thinking about it.

3. 8:04 – 10:27

   The Engineering Mindset

   1. QYQasar Younis8:05

      Previous experiences working as an engineer, and I spent a lot of time in factories. The huge impact within, for anybody who's worked in factories knows, is it's a heavily, uh, processed area. You do X and the quality of the parts is Y. If you do a different thing, the quality of the parts is different. And throughput and efficiency, everything can be measured. Think about like a McDonald's, but times a million. Like, a factory is just all these little things that have to work together. I think that reinforced in my brain this concept that even a company is almost a system. So I take the m- almost like the engineering mindset into business, and I think that's been very valuable for the company. The engineering mindset is one where measuring things is important. It's one being truthful is important. Let's say if we're talking about art, sometimes up to somebody's taste. They like this band. They don't like this band. They like this painting. They don't like this painting. Physics is not like that. Material science is not like that, and it's absolute. Product that functions in the way that you designed it, or it doesn't function. Let's say you're designing something simple, a door, and the hinge and the knobs and then the heat transfer between rooms, those are things you can measure. If you make a door and I make a door, there will be one of those doors will be better. If you make a painting and I make a painting, it's not actually black and white. So once you take that engineering mindset to business and starting a company, then you come up with the same types of, like, deep hard questions where you try to objectively answer, "Is this gonna be a better product strategy? Is this a better hire? Is this a better investor? Why are we doing this? This is the reason we're doing it." You can kinda boil all of our values down to two words, radical pragmatism. Radical pragmatism, another way of say, saying that is being intentional. Who's becomes an investor of ours? We're intentional about it. Product we should get into, we're intentional about it. Should we open an office in Korea? We're intentional about it. And so we don't just open an office and hope some- there'll be some business there. We should build this product because it's gonna be demanded by our customers. What do they want? What do they need? What are they good at? What are they weak at? Why would they buy this from us? How much would they pay for it? Do we write all those things down? Intentionality and writing things down are kind of the same thing. Even if you make the wrong decision, then you can go back and you can kind of understand where was the mistake in your logic.

4. 10:27 – 13:25

   Hard-Won Lessons From Thousands of Startups

   1. QYQasar Younis10:28

      Y Combinator taught me a lot of things that I don't think I could have learned by just being a founder. I saw lots and lots of companies, thousands of companies in my time there. If you're in a relationship, you only have that experience. But if you're a couples therapist, you see lots of relationships. [laughs] So YC is kinda like couples therapy. And, uh, so then you start seeing the patterns of functioning co-founder relationships. So a good co-founder relationship is one where the two or three, uh, complement each other really well. I would never recommend doing a company with four people or more. There's just too many people who are now, you know, gonna try to lead the company, and there's just simple logistics 'cause then you have to get four or five people together to make a decision. And I would highly recommend against doing it alone as well because having multiple people brings a higher likelihood that you have all of the skills. I think emotional compatibility is really important as in how you lead, how you give feedback, how you talk to each other, and I think similar ambitions. You can't have one co-founder that works really, really hard, another co-founder who doesn't wanna work hard. You can't have one co-founder who wants to build a generational company, another co-founder who just wants to get rich. You have to make sure you're aligned. Also, picking the right market. I saw lots of really hardworking, good co-founder relationships, smart people who are just in the wrong market. Imagine if we're trying to sell ice, something, a very simple product, just ice. If you're trying to sell ice in a cold area, not a lot of people are gonna buy it. You sell ice in a hot day, a lot of people buy it, and that simple analogy is actually really true. So sell ice in hot weather. The mistake first-time founders make about product-market fit is they think it's like a destination, and product-market fit is really more like, like a state. It can go away. When you're trying to wonder if you have product-market fit, the proxies are, are people willing to give you time? Are they willing to give you money? But you should be pretty cynical that you don't have product-market fit. I, I remember for us, even when we had 10 million in revenue, I wasn't quite sure if we had product-market fit. Your product sits in a dynamic market. There's other products and other companies and other technologies, and it can always be substituted, so you're always kind of re-getting product-market fit. A good example of this would be, like, Coca-Cola. Everybody knows Coca-Cola, but Coca-Cola spends a lot of money on marketing. So why is that? It's because the fit, the consumers wanting to drink a beverage is temporary. If they forget about it, they'll stop buying Coca-Cola. So product-market fit is earned every single day. The way that we stay within product-market fit zone, maybe that's the better way to put it rather than have product-market fit, is we're constantly talking to customers. Are they using the products? Is it making an impact on their programs? Are they... Are we getting products into production? If you remember in the app universe when the iPhone, you know, was becoming big, there were many apps that people would download but they would never use again. Founders would say, "I have product-market fit 'cause we have a million downloads." But a million downloads is not an indication because if nobody uses it again, that's not product-market fit. So I think you have to be, uh, very honest as a founder. Are you in the zone of product-market fit or are you

5. 13:25 – 15:57

   Read deeply, think clearly, and aim higher

   1. QYQasar Younis13:25

      not? [upbeat music] I don't believe you can be very successful and not read a lot. I'm reading this book called I Am That. It's actually a Indian spirituality book, and it talks about really more of a Hindu philosophy about detaching from the, the world around you and how that le- lets you see things more clearly. I think there's something about reading a book that takes hundreds of pages and, like, continuous focus. I have a book list on my own website which are actually my favorite books and the ones that impacted me a lot. Uh, Sam Walton's Made in America is a really great book. Mahatma Gandhi's, uh, autobiography is really good. It's called My Experiments With Truth. Nelson Mandela's Long Walk to Freedom, another extremely good book. When you read that, it l- makes these other books look like, you know, like disposable chocolate. [laughs] The root of my ambition is to control my own destiny. Why I want that, I, I'm not sure. Maybe it's because, you know, I moved from Pakistan to America as a child and it was very, really, you know, uh, created a lot of tension in my brain as a child maybe. Uh, but I think a lot of who I am is from my experience of being an immigrant. You know, my experience being in a working class family, and so fear was, uh, you know, was a part of our existence all the time. You're already living in fear. Like, it's our... It's always there. You, you don't have enough money to maybe make the, you know, the things, make the bills and to make the things, so you're always constantly living in fear. So I almost got, like, tolerance of fear. I have a high fear threshold. One way to find out if you're a good founder or if you're a good company person is how much does it bother you to have a boss? [laughs] When you work at a big company like Bosch, the day-to-day difficulty is through frustration. Does my boss acknowledge my work? Can I work on the things I wanna work on? Is the company going in the direction that I want it to go? What's the downside of being a founder? You don't pay with the frustration. As a founder, you pay with it through fear 'cause you don't know what's gonna happen with a company. See, there's no frustration. You're the boss. But you, there's all this fear. You know, when you're at a big company, there isn't fear because you're part of this big company. It's gonna take care of you, it's gonna pay for your salaries and things like that. Find out what bothers you. Are you frustrated easily or are you scared easily? If you're frustrated easily, maybe being a founder. If you're scared easily, maybe stay at the company. [gentle music]

Episode duration: 15:57