Why Great Founders Think Like Engineers | Qasar Younis, Applied Intuition
In a Nutshell
Great founders treat company-building as a repeatable craft and adopt an engineering mindset—measuring outcomes, staying radically pragmatic, and intentionally designing both product and business model from day one. Applied Intuition succeeded by rejecting costly vertical integration in autonomous vehicles; instead it built a horizontal platform that adds intelligence across many machine types, letting customers focus on their core value. Product-market fit is treated as a fragile, ongoing state that must be re-earned daily through continuous customer contact, not assumed after initial traction.
These notes were generated by AI and may contain inaccuracies.
First-time founders tend to believe that building a company is a one-time thing. In fact, building a company is similar to the work of a craftsman or honing a skill. Adopting a mindset that this will be done for many years, and maybe repeated two, three, or four times, leads to approaching company formation differently. Success on the first company is great, but often it doesn't happen. Spending 3 years in a first company that was not successful provided the biggest lessons that made Applied Intuition so much more successful, with those lessons coming from a company started 20 years ago.
The biggest mistake made in terms of setting up companies was the name Anthony Younes. The company founded is Applied Intuition. Prior to that, the role was Chief Operating Officer at Y Combinator, and before that a company was founded that was acquired by Google. At the beginning of the career, work was done as an engineer at General Motors and Bosch. Applied Intuition is a physical artificial intelligence company. Many people often think that physical artificial intelligence is limited to humanoid robots, but cars, trucks, and industrial equipment can be made smarter and have a greater impact in a shorter time.
The mission is to add intelligence to a billion machines. The only way to do this is to take the same platform and apply it to a lot of different machines. The reason to add intelligence to those machines is because those machines are very stupid at the moment. It requires humans to operate them. If intelligence can be added to machines, they can work on their own, and that offers much greater value. The company employs more than a thousand engineers or approximately 1,500 employees. The company is valued at $15 billion. Products are distributed in dozens of countries around the world by numerous manufacturers in various sectors.
Grew up in the context of the decline of the American automotive industry from its position as the best industry in the world. As an engineer, entered an industry that was in a very volatile situation. The thinking at the time was that staying in this industry if it shrank could be very bad for an engineer. Therefore, part of the ambition to become a founder was to control destiny. Left really great jobs at General Motors and Bosch, which are excellent companies, to start a company. It may have seemed like a big risk, but after 20 years it turned out to be the right thing to do.
Cars that can drive themselves still sounds like science fiction, but it has become a reality. The industry was very different when Applied was founded in 2017. At that time, it was not clear to people how self-driving would be built. It was unclear whether self-driving would be achieved. It seemed to be heavily geared towards scientific research. Many AI breakthroughs had yet to occur. The Transformer technology and this new architecture, which has benefited from large language models, also has a significant impact on self-driving. Almost all of these basic building blocks were not present. Perhaps the most important point was that it was not sure if self-driving would ever happen.
Many of the self-driving car companies at that time, many of which no longer exist, were actually doing what some AI companies are doing today. They were trying to work in a fully integrated, vertical way. They try to build everything: the tools, the information, everything, the data engine, and sometimes even the vehicles themselves. Whether they will build automated taxis or trucks. That becomes extremely expensive. At that time, the feeling was strongly that it was not clear which vertical path would work, and it was not clear that being a vertically integrated self-driving car company was actually worthwhile. Often, companies spend a lot of their resources and energy on things that the end customer doesn't really care about.
The interior of a car using the platform has far fewer components compared to a classic vehicle interior design. While making the vehicle smart, the platform it operates on is also changed. Traditional platforms are not really designed for independence. They are not really designed for intelligence. Each component is separate from the other. In newer vehicle versions, much of that can be reduced and integrated into a single computing unit. Then intelligence can be added to it, and all those other non-intelligent tasks like raising the window, playing music, and things like that can be done. The direct effect on the final result is the presence of a much smaller number of components.
The most exciting part is taking the same platform and putting it into so many different vehicles. If building this type of platform or intelligence for only one sector, it may never see the light of day because it is too expensive. In most industries, horizontal companies actually achieve great success. Take, for example, data classification. Each company can create its own data classification product to help classify the data it collects from its fleets. But the end customer who buys the self-driving system doesn't really care who classified the data, whether they bought it or made it. Fast-forwarding to the present time, there will be a lot of trending towards horizontality. Therefore, many parts of the technology package can be bought, allowing an autonomous driving company to focus only on the most valuable and important part of the autonomous driving problem.
The effect of the 2017 approach was that it required a great deal of capital. If building everything yourself in a very specific sector, both capital risks and market risks are taken on when moving into a vertical sector. This is why the vast majority of companies have not managed to survive to this day. The decision was made to provide the tools and let everyone try to figure out self-driving. That was a very good step. Primarily because manufacturers, not in the field of autonomous driving, but on the manufacturing side, have always been interested in building much of this technology themselves.
One of the first engineering managers worked with had a sign in his office that said: "No problem can withstand persistent thinking." AI companies today are spending a lot of money. This does not necessarily mean that it will be successful. This does not mean that it will automatically fail, but it does involve greater risks. The best founders are those who think about the problem as a whole. Part of the problem is related to engineering and technology, but the other part is related to business. Both things need to work together. A reasonable focus on commercial marketing is important. Automotive original equipment manufacturers (OEMs) operate in a highly competitive industry. Studied at the General Motors Institute. Grew up in this highly competitive industry. When in a highly competitive industry, thinking carefully about how money is spent is necessary. Therefore, there must be a very clear value. For this reason, it affected the need to build products with very clear value.
No other company on the planet is developing physical artificial intelligence on the scale that is being done. As a horizontal company, this layer of intelligence is provided to all these other companies. The biggest opposing view is that a business model should be built within the technology, and the technology should be built around a business model. It cannot be added later. It is very difficult to install plumbing after the house has been built. The biggest recommendation is to start seriously considering commercial marketing earlier than thought necessary.
Previous experience working as an engineer involved spending a lot of time in factories. The enormous impact that anyone who has worked in factories knows is that it is an area subject to intensive processing operations. Doing "X" results in the quality of the parts being "Y". If something different is done, the quality of the parts will be different. Productivity and efficiency, everything can be measured. Think of it like "McDonald's" but multiplied by a million. The factory is just all these little things that have to work together. That reinforced the concept that the company itself is almost a system. Essentially transferring the engineering mindset to business. That was very valuable to the company.
An engineering mindset is one where measuring things is important. It is a mindset in which honesty is important. If talking about art, sometimes it comes down to someone's taste. They like this band, and they don't like that band; they like this painting, and they don't like that painting. Physics isn't like that. Materials science is not like that. The product either works the way it was designed to work or it doesn't. If designing something simple, a door, hinges, handles, and heat transfer between rooms are things that can be measured. If one person makes a door and another makes a door, one of these two doors will be better. If one person paints a picture and another paints a picture, it's not really black and white. Once that engineering mindset is taken into business and a company is started, the same kind of deep, difficult questions are asked as one tries to answer objectively: will this be a better product strategy? Is this a better job? Is this a better investor? Why are we doing this?
All values can be summed up in two words: radical pragmatism. Radical pragmatism is another way of saying to be intentional in actions. Who becomes an investor is intentional about that. The product that should be included is intentional about that. Whether to open an office in Korea is intentional about that. Therefore, there is no contentment with simply opening an office and hoping that one day business will be accomplished there. A product must be built because it will be in demand by customers. What do they want? What do they need? What are they good at? What are their weaknesses? Why would they buy this? How much will they pay for it? All of these things are documented. Intentionally doing things and writing them down are kind of the same thing. Even if the wrong decision was made, it is possible to go back and understand where the mistake was in the logic.
Y Combinator taught many things that would not have been learned just as a founder. Many, many companies were seen, thousands of companies during time there. If in a relationship, only that experience exists. But if a couples therapist, a lot of relationships are seen. So, "Y Combinator" is somewhat like couples therapy. That's how patterns of successful partnership relationships among founding partners begin to be seen. A good co-founder relationship is one where the two or three really complement each other very well. Never recommend starting a company with four or more people. There are a very large number of people who will try to lead the company. There are simple logistics involved, because four or five people will have to be brought together to make a decision. Also strongly do not recommend doing this alone, as having several people together increases the likelihood that all the necessary skills will be present.
Emotional compatibility is very important, such as how leadership happens, how feedback is given, and how talking to each other occurs. Similar ambitions are also important. One co-founder cannot work hard and diligently while another doesn't want to work hard. A partner who wants to build a company for generations should not be paired with another who just wants to get rich quick. Agreement needs to be ensured. Also, choosing the right market. Many smart people who work hard and have good relationships with partners have been seen, but they were in the wrong market. Imagine trying to sell ice. A very simple product, just ice. If ice is tried to be sold in a cold region, not many people will buy it. But if ice is sold on a hot day, many people will buy it. This simple analogy is indeed true. Sell ice in hot weather.
The mistake that first-time founders make regarding product suitability for the market is believing that it is a final destination. Product suitability for the market is actually more like a case. It can disappear. When trying to determine if product fit in the market exists, the indicators are: Are people willing to give their time? Are they willing to pay money? However, being very skeptical and assuming that product-market fit does not exist is necessary. Even when revenues reached 10 million, it wasn't entirely sure if product-market fit was being achieved. The product is located in a dynamic market. There are other products, companies, and technologies, and it can be easily replaced. Therefore, there is always a constant state of striving to re-establish product suitability for the market. A good example of this is Coca-Cola. Everyone knows Coca-Cola, but it spends a lot of money on marketing. So why is this? Because convenience, i.e., consumers' desire to drink a certain beverage, is a temporary state. If they forget about it, they will stop buying Coca-Cola. Therefore, product suitability to the market is gained every day.
The way product-market fit is stayed within the scope of—perhaps this is a better way of putting it than having fit—is that customers are talked to constantly. Do they use the products? Does it have an impact on their programs? Will success be achieved in bringing the products into the production stage? In the world of apps, when the iPhone was gaining popularity, there were many apps that people downloaded but never used again. Founders used to say, "I have product relevance to the market because we have one million downloads." However, a million downloads is not an indicator, because if no one uses it again, then it is not a product fit for the market. Therefore, being very honest as a founder is necessary. Are you within the product's market suitability range, or not?
It is not thought that very successful outcomes can happen without reading a lot. Currently reading a book called "I Am That". It is actually a book about Indian spirituality and talks more about Hindu philosophy about detaching from the world around you and how that allows seeing things more clearly. There is something special about reading a book that consists of hundreds of pages and requires sustained concentration. A list of books is maintained on the website which are actually favorite books and those that have influenced the most. Sam Walton's "Made in America" is a truly wonderful book. Mahatma Gandhi's autobiography is very good. It is called "The Story of My Experiments with Truth". Nelson Mandela's book "Long Walk to Freedom" is a very good book. When reading it, it makes those other books look like a disposable chocolate bar.
The root of ambition is to control one's own destiny. It is not known for sure why that is wanted. Perhaps because moving from Pakistan to America as a child created a lot of stress in the mind at the time. But a large part of personality stems from being an immigrant, and from experience in a working-class family. Thus, fear never left lives. Living in a constant state of fear already occurs. It is always around. Sometimes there is not enough money to pay the bills and meet the obligations, so almost getting used to being afraid has happened. There is a high tolerance for fear.
One way to tell if a successful founder or a good employee is how annoyed one is by having a boss. When working for a large company like "Bosch", the daily challenge lies in feeling frustrated. Does the manager appreciate the work? Can work happen on the things wanted? Is the company moving in the direction wanted? What are the disadvantages of being a company founder? The price is not paid with frustration. As a founder, the price is paid with fear. Because it is not known what will happen to the company. So there's no frustration, the founder is the boss. But all this fear remains. When working for a large company, fear is not felt because being part of an entity that will take care of the person, pay the salary and things like that. Discovering what really bothers is important. Is frustration easy, or is fear easy? If frustration is easy, entrepreneurship might be right. If fear is easy, then perhaps staying in the job is best.
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