The real AI revolution isn’t software. It’s farms, mines, and trucks. | Qasar Younis

[00:00] You decided to join Twitter recently, put out your first tweet. Marc Andreessen quote tweeted it and said, this is the best AI CEO nobody knows. Our best work is done alone and quietly. Every minute you're writing something for public consumption, you're not focusing your very limited time that you have on your customers and your product. You're building a lot of the future that we're going to be living in. What does the next couple of years look like? Us solving some of these impossible problems like cancer are directly going to be related to this AI boom.

[00:30] overall should go down significantly. A thread that has emerged on this podcast is that AI is coming just in time to save us. The real impact of AI in the next five to 10 years really is going to be in farming, mining, construction. These industries, they need autonomy and it couldn't come soon enough. If you look at farmers, the average age of a farmer is in their late 50s. What does that mean in 10 years from now? There's a lot of anxiety about what AI is going to do to [01:00] home are very anxious about AI.

The best thing that you can do is spend time to understand and you will quickly see the limitations. Get to know it, then actively make the technology be used for good. [01:15] Today my guest is Kasser Yunus, co-founder and CEO of Applied Intuition. You've probably never heard of Kasser or Applied Intuition. This is the most important under the radar AI company and CEO that I've ever come across. It's a $15 billion company that has been growing quietly over the last decade. [01:33] What they do is they add AI to vehicles, like cars, tractors, planes, submarines, mining rigs, and a lot more.

18 out of the top 20 automakers are customers, as well as the biggest global construction, mining, and trucking companies. [01:47] also the Department of Defense, [01:49] They're basically Waymo or Tesla, but without the hardware. Kasser himself was born on a farm in Pakistan, grew up in Detroit, started his career as an engineer at GM and then at Bosch. He then went on to start a couple companies before starting Applied Intuition. I love everything about this episode and I am so excited to bring it to you. [02:08] Don't forget to check out Lenny's Product

com for an incredible set of deals available exclusively to Lenny's newsletter subscribers, [02:15] Let's get into it after a short word from our wonderful sponsors. [02:19] This episode is brought to you by Omni. Many product teams today are in the process of debating how to ship AI analytics. The hard part is obvious. Having an LLM guess at SQL in production is a huge mess and just a bad idea. Omni takes a different approach. They have a semantic layer built in so that when you embed their analytics, the AI actually knows your business definitions, not just your raw tables.

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You're basically building a lot of the future that we're going to be living in, and people may not even realize this. [04:16] And there's two sides to this. On the one side, let me ask you this question. [04:19] If things go really well, [04:21] What does the next couple of years look like for people with the emergence of AI, with physical AI? [04:26] What's a vision of the future? Let me take the broader AI perspective. [04:30] point and then the micro, the more specific one on physical AI. Macro, I think, think about this like the Industrial Revolution, right?

So if you're sitting, let's say, in the late 1800s, there's a lot of, you know, we can focus on a lot of bad things that happen because of the Industrial Revolution, right? You have child labor and you have monopolies emerging and you have abuse of, you know, wars end up happening. But there's also, it's an almost... [04:57] almost unimaginable [04:58] present without the [05:00] and without the kind of benefits we got out of the Industrial Revolution, which is broader access to healthcare like we've never seen before. [05:10] Access to goods, material goods, things like we take for granted, like heating and cooling your home.

There's this great YouTube kind of channel that focuses on POW letters from Germans. [05:25] who are seeing America in the early 40s, and they're writing letters back to Germany about what they're seeing as they're basically prisoners of war. And they're kind of blown away that the towns that they roll by in these trains as they're going to their POW camps are all lit up. [05:42] or that there's cars everywhere. 80% of German towns in World War II did not have electricity. And that's kind of a mind bending kind of thing, because we just assume all this stuff, all this technology is, you know, equally distributed.

So the positive version is these things that we [05:59] let's say folks who are [06:01] wealthy or folks who have access to technology. [06:06] These things everybody has access to. The fact like simply having somebody who's a coach to you and having that – [06:13] Coach, very specifically to you, not a generic question. [06:16] you know, chat GPT that's giving fairly generic answers. This is a very powerful thing. I think us solving some of these impossible problems like cancer, [06:26] are directly going to be related to this AI boom. So I think net suffering in humanity, I think just like the industrial revolution, overall should go down and should go down significantly.

And I'm a fundamental optimist in that view, that technology will bring that positivity. In physical AI specifically, again, when you have things like your... [06:49] You have your own car and you have the ability, you have your limbs and you have your senses and you can drive. [06:55] You take these kind of things for granted. You jump in your car and you go to the store. For somebody who maybe is disabled or somebody who doesn't have the money to afford a vehicle, access to mobility that's nearly free or is free is a big deal.

And that simple example of making self-driving cars free for everybody and how that would change everything. [07:16] The planet... [07:17] You live in Rwanda and you are... [07:20] two hours from the nearest hospital, [07:23] That matters in a very, very true way. And so I think a lot of, let's say that... [07:28] negativity around AI comes from people [07:31] who frankly speaking are living in a very, very good existence. And when you live on the other edge of society, [07:39] Yes, and I'm not... [07:40] like some naive person who thinks that there's no downsides of technology.

We can discuss that, but I just see there's a lot more positive. So when you ask that question, [07:49] What's the next? [07:50] forget three to five years, what's the next 20 years? These things that we take for granted that are bad, [07:56] suddenly or not [07:58] there. And I think certain diseases, certain accessibility to [08:04] basic services suddenly start going away. One last example that is [08:11] You take just the fact that you can message people basically for free, you know, for people old enough. Like this is not the norm.

We came from Pakistan. [08:21] We couldn't even communicate back to Pakistan because the long distance... [08:24] you know, was so expensive. And so it was handwritten letters. Today, you can basically contact anybody on the planet basically for free. [08:31] There's obvious downsides for that. But there's lots of upsides for that, which is being in touch with people that you care about and you love. [08:39] basically for free. And so I think AI has the ability to bring this abundance [08:44] to many, many more people at a near free cost. [08:50] On the flip side of this, as you pointed out, [08:52] There's a lot of anxiety about what AI is going to do to the world, to jobs, robots.

There are these videos coming out of China with these robots with nunchucks, like the stock market. I feel, you know what, I feel the nunchuck union is up at arms. [09:10] How dare they? Yeah, but it's scary. And the market's reacting more and more to just like, oh, wow, these companies are maybe not going to survive long term. [09:20] Again, being at the center of this and building a lot of the stuff that will get us there, how do you envision the next couple of years playing out? Are you optimistic?

What keeps you optimistic? Any advice to people to help them kind of stay... [09:34] calm through this period. [09:36] Those are the two separate things, anxiety around technical shift and then the... [09:41] Public investors reacting to specific stocks they've held. We have to separate those things. Let's talk about them separately. The first one, the core root of fear is misunderstanding. I think if you at home are very anxious about the impact of [09:59] AI in some variant on your own job, the best thing that you can do is spend time to understand it and you will quickly see the limitations.

There's some great videos on YouTube which are like, you know, trying to get Gemini to understand what a cup is by just holding it upside down and it like really strutting to do it with, you know, chat GBT. [10:21] So it's like if the revolution is coming, you know, [10:25] The AI overlords have to first understand like the top and bottom of a cup. And so you realize that you can see the video of nunchuck wielding humanoids, which are pre-programmed and that cost $15 million to do that video. Um, [10:40] Yeah, that is true.

It's not fake. I'm not implying it's fake. But it's also not what your brain kind of fills in the gaps. You see nunchuck robots and you just feel like, well, these are sentient beings that are at their own volition rather than it's a bunch of motors have been programmed to do a certain thing. If you really want to be impressed, you go to a car factory. [11:02] And we've been doing that for 25 years. We have very, very advanced robots moving extremely fast to build things. And why are we don't we have anxiety about the car factory, but we have anxiety about the nunchuck robots is because the human being doesn't like that gap.

We understand the gap of, you know, of a welding robot. You say, OK, that's a robot. It's been programmed to make this weld. But we don't know the technology. We isn't just as an individual human being living in the world. [11:32] do that nunchuck thing and so you substitute that with anxiety and fear [11:37] And so I would really implore you to. [11:40] you know, kind of learn more about the technology and you start seeing the edges. Now, does that take away from the most fundamental thing that you're getting at the string that you're pulling at, which is, [11:50] Like is society going to be fundamentally harmed?

And is this net net bad for society? I think in any technical shift, [12:00] The emergence of WhatsApp. [12:02] Just as an example, there are people who are damaged by that, literally companies that go away, but also humans who are damaged by the advent of that technology. [12:13] as members of society and as leaders in society, [12:17] We can [12:19] we can kind of move that funnel in whichever way. Technology first, remove the word AI. AI is such a emotional word because it's wrapped in these things you don't know. [12:31] And so that fear then kind of deforms.

So let's just say [12:35] technology. [12:36] So it's up to us to recognize this technology can be used for good and technology can be used for bad. [12:44] And I think that's where really the focus is. So get to know it. [12:47] And then [12:49] actively make the technology be used for good. [12:52] as a participant, whether it's a founder or all the way as an individual, you know, employee or citizen of a large company. Then on the second part of the question about, you know, public investors and stuff, this is my, I don't have any, you know, particular research on this, but this is what my guess is what's actually happened.

Beyond being an engineer, which is my core identity, for lack of a better word, I was also, I did an MBA at Harvard. And so that was the first time that this, [13:19] let's say, I didn't come from very wealthy upbringings. This is the first time when I went to Harvard I saw [13:29] Like... [13:30] you know that world that world of people having like private jets and stuff is a really eye-opening experience for me but the real world i was exposed to was high finance and how high finance works and you might think [13:42] as I did, [13:43] from far away that folks at hedge funds or at large [13:48] public equities funds are extremely nuanced and thoughtful.

And they are like, you know, on whiteboards with, you know, extremely deep and, oh, maybe even theoretical math to figure out should they buy or sell. [14:05] you know, Figma. [14:06] And that's not actually how it works. I mean, really what these folks are is in this specific case, I think what's happening is they buy and sell stock. They are smart people and they do work hard. It's not to take that away. But they don't have a fundamental edge that you would assume. [14:22] that somebody who sits in Skyscraper in New York has.

By the way, that's why retail investors have become such an active and significant part of the market. Those folks have gone to [14:35] AI consultants and have gone to people who are literally developers at these firms and they'll do something like, hey, why don't you build me this app? [14:44] in a week and then you know this like consultancy will come back with an app which kind of looks like [14:49] maybe a Figma or another, some web app and said hedge fund manager, they're like, well, and then if the company was sitting there, they would say, no, no, this just looks like my app, but this is actually not my app.

It's not as deep. It doesn't have all these things. There's integrations with all these other systems. [15:07] But for the public investor by there, like, yeah, but it only took like a few weeks or a month to build this. It took you 500 engineers a couple of years. [15:16] Thank you. [15:16] This AI thing could be real and the things I'm reading on X about like just vibe coding your way to replace, you know, billion dollar companies. That might be the case and the market immediately prices in that risk. [15:29] And that's where that sell off comes from.

That doesn't necessarily mean [15:33] All of those. I mean, I just within the last 24 hours, I had a I can't say, but it's like a very, let's say, calibrated investor who said this is the time to buy because these companies are not actually going away. And so. [15:48] I think those are two anxiety within society and the sell off are two very different things. They're motivated by different things. They're part of the larger narrative, but I wouldn't conflate those two things. It's not that the hedge fund investors like I'm worried about society self service now.

[16:04] Like it's it's there's it's different than that. At least that's my impression. This is the alpha we've been talking about. Time to buy. This is not investment advice. [16:14] Well, that's really good advice. I think the real advice is. [16:17] to fight fear. [16:19] And I feel that anxiety, especially when I go to Michigan and outside of people in the Silicon Valley bubble. It's like just try to learn a little bit. [16:27] about the technology that you're afraid of and you'll start seeing some of the [16:31] I love your point about how self-driving cars are essentially robots.

We don't call them that, but they're robots. Absolutely. [16:39] You see a nunchuck-wielding robot, a self-driving car doing bad things is... [16:42] could be very dangerous already. And so that's a really good reframe that if you just think of it, it's just another robot and it's been really good for us. And by the way, the self-driving thing, as an example, you know, whichever way you slice the statistics that are available from self-driving companies, they're supremely, supremely more safe than human drivers. And I do believe in 20 or 30 years, not that much longer, we'll look back and we'll kind of be like, [17:12] you [17:13] In the post-Industrial Revolution, that was a normal thing.

[17:17] You would send kids who are in middle school to go work. [17:19] It happens in third world countries today. There isn't a lot of emotion behind it. It is not considered to be exploitative because you have no choice. [17:27] You know, everyone just... [17:28] And I think we'll look back in 25, 30 years and we're like, people would just like... [17:32] tired, [17:33] Under the influence, you know, after like extremely stressed. [17:39] going through a traumatic life cycle, [17:40] experience and then they jump in into a car. Like that.

It is crazy. Everyone should really emotionally think about it. Just in the United States, over 30,000 people will die. [17:55] In the next year. [17:57] from these accidents. [17:59] Like the old Stalin line, it's like, you know, one death is a tragedy, a million is a statistic. And we just let the statistic kind of go over our head like, oh, it's 30,000 people. But if you ever have talked to a family of somebody who went through a tragedy like a car accident, it's unbelievable. [18:17] And, you know, you suddenly all the fear of, [18:21] AI robots goes away and you really see that human impact and you realize like actually us driving doesn't make sense.

And it's not for any other reason. [18:30] then literally people die. I've become a huge, I have a Tesla, and I just use self-driving all the time now. [18:36] Just like a few months ago, it got very good. And it used to be nerve-wracking. And now it's like, wow, this is much better than I am. And you're not doing driving as a job. [18:46] Imagine if you're a [18:47] commercial truck driver or you work in a mine or you work, you know, like they're [18:54] A little bit of intelligence, a helping hand.

[18:57] in that very dangerous task, it's incredible. And I think there's something about the human... [19:03] brain where [19:05] When you bring up that reality of self-driving trucks, the immediate people are like, well, what about the trucking jobs? Now, needless to say, we don't have enough people who want to do that job. So leave that fact to the side. [19:19] I think the fact that you really focus on is the fact that people die from trucking accidents. [19:25] Like we can't, you know, throw out the baby with the bathwater. And so I think I implore everybody, you know, who thinks about AI broadly.

[19:34] and physical AI specifically to always recognize that your monkey brain is programmed [19:42] Because of thousands of years of being in, you know, hundreds of thousands of years of living out in the wild and being in the cave that when you hear the rustle in the bush. [19:49] that is, you think it's a snake, because that's what our ancestors were programmed. So now when something new enters our [19:56] psyche, your view isn't [20:00] Well, [20:01] If mining, if mines became autonomous, well, wouldn't that lose jobs? It's like, [20:06] Those are awful jobs that people die in.

And the best evidence is that people don't want to work in them. [20:12] Like that's the best evidence. Like no, nobody's clamoring to go work in a, in a, [20:17] mine in a remote area and so intelligence can help make that you know make that reality much much better people are seeing ai advance in all these different ways on the software side you know they see all these models being releasing it's driving 100 of people's code now what's really cool about you is you see the hardware side of this [20:34] And I think one of the biggest changes to our lives will probably be robots walking around doing things for us.

[20:40] Do you have a sense of just how close we are to just robots around us day to day? [20:45] So I would think about the framing here matters again on a spectrum. [20:51] So there are robots around us like Zumbas, you know, like they clean your carpet while you're sleeping. There's robots around you when you make a coffee. That's an automated machine that is taking an input and doing a bunch of things based on what you need. So what you're really talking about is… [21:09] how fast can you go up that spectrum to where you have a robot that can take on lots of tasks with little guidance?

And the way that I would think about this is, let's say we're sitting in, this podcast is happening not in 2026, but 2006. And you're asking me the same question about mobile. And you say, well, mobile is coming. This is, remember, pre-iPhone, which comes out in 07. Everyone has got those flip phones. So we have some [21:35] We have mobile. It's not like a completely, you know, so we have some robots around us already. [21:41] But like it's like, OK, so what when are we going to and you asked me in 2006, [21:44] When are we going to get that Star Trek phone that can do everything?

And I think at that time I would say, because I don't even know the iPhone is coming a year later, I would say, well, Lenny, I don't I don't know. [21:55] Maybe it's one to five years. And if it's not five years later that Uber is, [22:01] WhatsApp, [22:02] Instagram, Snapchat are all products and they're being consumed by many, many, many millions of people. So what happens when you think about sitting in 2006 and why can't your brain figure out that Instagram is coming? Instagram is very hard to even conceive.

[22:18] without phones that have an app store. [22:20] have cameras on both sides are available, generally available, that lots of people have it. And the fact that people are comfortable being on social networks in 2006 is still an early thing. This is pre-Twitter and Facebook is not that big. And MySpace is, but it's not the same type of private kind of community. And so the point I'm making is... [22:41] I think it can come... [22:42] pretty fast. [22:44] But the way and the form factor will come is hard to pick, just like it's hard to figure out Instagram is going to happen because the intelligence in that particular type of hardware, which will be...

[22:56] generally available, that's a key word, generally available, is really going to impact the use cases. So I think like [23:02] The most obvious use cases that will come early are going to be use cases where you get the most amount of bang for buck. [23:10] And the bang for buck is... [23:12] a car that drives itself. [23:13] or a mining robot which is a mining vehicle which is now intelligent. And the reason is, [23:19] All that, you know, [23:20] let's say engineering required to make this giant [23:24] you know, machine that moves dirt has already been done.

It's been done over the last, you know, 50, 60 years. So then you're just putting a little bit of intelligence into it and leveraging everything else that that that the companies and kind of people have developed. So I think I mean, and I'm not just pitching my own book or a physical AI company. I continue to believe that. [23:45] I think our brain emotionally loves the humanoid concept. [23:49] because we're monkeys and but actually just like more pragmatically [23:55] it's actually just putting intelligence into things that already exist all around us.

And then once that happens, then new applications will emerge, which I think we'll talk about in five to seven years, which we'll start seeing. So let's just move forward five to seven years and let's see what reality exists. And then maybe we can try to jump into the future from there. I think generally speaking, every single car company on the planet right now is working on a product that's like a Tesla FSD product. Every single car company there without exception. [24:25] many companies are working in versions of that that will become fully autonomous within a cheap sensor suite.

So the fundamental difference, just to simplify it all, the Tesla approach versus the Waymo approach, just to really keep it simple, is the Waymo approach is lots of sensors and lots of compute and maps. [24:41] And the Tesla version is very few sensors, no maps, no high fidelity maps. I'm just generalizing here and cheaper compete for the lack of better word. And the Tesla version. [24:53] version of a product. This is in the industry is called an L2++ product, is going to be available everywhere because it's literally cheaper. [25:02] and it doesn't require like HD maps, the Waymo product functions better in a geographically constrained area.

So you fast forward five years, both of these types. [25:13] of technologies will be much more ubiquitous l2 plus plus and l4 will be much more ubiquitous not only in the bay area or in parts of china but really globally there are companies working on this globally so now [25:27] I don't know if you remember, but nav systems used to be a big deal in cars. You would pay thousands of dollars, and nav systems were kind of the thing that everybody wanted. We're at that moment for... [25:36] L2 plus plus systems where like people are willing to pay thousands of dollars for a semi automated vehicle.

It will not be a long time. You're already seeing this happen in China where the downward pricing pressure for that autonomous product for the lack of better word will become close to free. [25:52] So now you fast forward five to seven years in every car. [25:56] has some level of autonomy. So now you have to like mentally think [26:00] Live in that reality that everybody who's buying a car [26:02] They just get FSD with it. [26:05] Now you start seeing a different world because now the average person isn't wondering is self-driving in a company.

They use it all the time. They don't wonder are nasty. And so. [26:14] What you have in nav systems is, [26:17] a carplay emerges in Android auto emerges and it's very natural. People like, oh, I have my phone, I just plug it in and it wasn't a big revolution. But the car plane and your auto revolution is actually huge. [26:27] It brings free navigation and free applications to your car, and it's fairly ubiquitous. And so I think the next thing that happens in five to seven years is then full autonomy becomes the thing that everyone expects.

[26:38] And so I think in all of that, and you will see a clear decrease in injuries and death. [26:44] Because of that, because you have some intelligence helping you help. Now, again, I'm using the consumer vehicle analogies just so people can understand it. [26:54] But this is the same construction, the same in mining, it's the same in defense. It's in every one of these verticals, there's these big physical machines that humans are interacting with. That teaming up with that machine, [27:06] is the future, the productivity unlock from just you [27:10] Looking at a machine, [27:12] not like a sentient being, but almost like a physical agent.

[27:16] of something you're trying to accomplish unlocks things that I think are very hard [27:20] to think about. So I, I love, you know, [27:23] You know, things like Motebook and I love the, let's say, open claw revolution that's happening for the lack of a better word. But I think the big impact that's still that's still such a small part of society. [27:34] My barometer of impact is like you go to the Detroit airport and you sit in a gate and you look around and you're like, how many people are using open cloth?

And it's like, you might be the only person who knows what that is. And, and. [27:50] Whereas everybody, they're living their lives. And so it's like to them, actually, the impact of AI is going to be in this physical world. I see you also have a... Check it out. I'm a convert. There you go. Perfect. Peter's coming on the pot soon, so I got some lobster claws. [28:07] Yes, I think the real impact of AI in the next... [28:11] five to ten years really is going to be in farming, in mining, in construction, in self-driving trucks.

That's where you're going to have a real impact, though I think [28:22] I mean, I love the stuff that's happening on these platforms, but it's still segregated to, like, frankly, developers and a small, very, very small part of society. [28:32] I wasn't planning to spend so much time here, but this is extremely interesting. And I think it's important for people to hear from folks like you about where things are heading. Because as I said, everyone's just like, what is happening? What is going to be my future? [28:45] The jobs piece is really interesting.

And you have a thread that has emerged on this podcast recently. [28:50] is that people are afraid AI will take their jobs, but in reality, AI is coming just in time to save us. [28:57] because populations are declining, people are aging, and we need something to help us there. I know this is something you and like this is something Mark talked about and you're really close with him. Help us feel better about just how AI isn't going to take our jobs and actually going to, [29:11] save save us [29:12] Yeah, I think honestly speaking, these industries, [29:17] like they need autonomy.

I mean, and it couldn't come soon enough, frankly speaking. This is not like people are not fighting for those trucking jobs. [29:29] If you look at farmers, the average age of a farmer is in their late 50s, 58 or so. [29:34] What does that mean in 10 years from now? That means many of those farmers are going to be retiring if they're not already retired. And 20 years, we have even a bigger problem. That, by the way, is every vertical is like that. And my hypothesis here, but unlike, sometimes people say like, [29:52] you know, McDonald's can hire or like, you know, the mind local query can hire and where all the people.

[29:59] The people are still here. [30:01] I think they just the trade off is just not worth it anymore. [30:04] In the 1980s and the 1990s, doing the long-haul trucking job was what the family has to sacrifice, the father not being there for days and weeks on end. And today, that same working-class family is... [30:18] can make that decision and say, you know what, I will drive for Uber or DoorDash. [30:22] And I'm willing to do that because I can turn that app off and pick up my kid and I've [30:26] prioritize that.

That is where I think this kind of intelligence kind of revolution in the real world is really, I think, is going to fill those gaps in. [30:39] rather than like [30:40] an entire industry is suddenly gone and it's just automated. This is, this is, this is, this is, I don't believe that future, mainly because the realities of actually, you know, replacing an entire industry with robots is, is, is still, you know, [30:53] That's too complex. [30:55] One day it will happen. [30:56] but it's not happening anytime soon. But the entire society will be different by that point.

And I think, again, use the Industrial Revolution as a good version of that. You know, the earlier question, [31:07] if I'm somebody who is not in the AI ecosystem, [31:11] And I have this anxiety. And how would I do it? [31:14] Reading history books is a great way to really understand history. [31:19] how society deals with this. And there's a lot of literature, because Industrial Revolution doesn't happen like, you know, in the dawn of Christianity, where not many people are writing and not many people are reading. Lots of people are writing, lots of people are reading in the last 150 years.

And you can read [31:36] both the people who are impacted by the Industrial Revolution, people who are benefiting. And writ large, it's a very positive experience. And that doesn't mean there, again, there are downsides. [31:47] We should mitigate the downsides. But the thing that we can't do, and this is maybe specifically as America or society as as the global population as a whole. [31:56] There's this impetus... [31:58] to say like, we got to pump this brake on, again, don't say AI, say technology. Pump this brake on technology. The issue then is the American economy.

[32:06] really ends up stuttering. And that impacts... [32:10] the lowest end of the labor market way more than anybody else. And so in the attempt, [32:17] to help the people who are the most marginalized we actually hurt them the most and the the you know the the statistics between europe and america are you know been have been have been are pretty explicit but in the last decade basically the american economy is is now you know growing at a much higher pace and that growth hasn't come from you know [32:39] Detroit, Michigan.

[32:40] That growth has come from Mountain View and it's come from Sunnyvale, it's come from the Bay Area. And which is another way of saying it's because of new frontier technologies. So putting brakes on frontier technologies because we're afraid of unintended consequences. [32:55] will actually have real intended consequences on people who are trying to help the most. And the reality is very, very fundamental. [33:02] in a future that does not take care of [33:06] the average worker and the average person in America [33:09] we'll have much bigger problems. So we need a solution that takes that into account.

But that solution isn't, [33:15] Just pump the brakes. AI is bad. [33:18] Frontier technology is bad or technology is bad or whatever, you know, whatever thing that you don't like. I think that that'll have really, really bad consequences. One of the reasons that we don't pump the brakes is just fear of China and competition with China. [33:32] The nunchuck robots being a recent example of like, oh, shit. And you have kind of a contrarian take on just how much of a threat China is and how they're approaching things. [33:43] The summary version of this is, I think, the way we recently read as a company.

We read this book, House of Huawei, which is a really great, interesting book. [33:52] Huawei is a really... [33:54] Amazing company. [33:55] for the reason that it makes great technology. [33:58] But, [33:59] The couple hundred thousand people that work at Huawei, about a quarter of them are members of the Communist Party. And Huawei's goal is not to grow profits or shareholders. It's a private company. It's really an extension of the state. So literally the name Huawei means China's ambition. So imagine if you had a company called, you know, MAGA. [34:19] And half of the company or a quarter of the company was a certain political party.

[34:24] And they said our goal isn't to make profits – [34:27] or to be a goal is just the expansion of it's not even a company anymore. It's it's it's something else. Right. And so I think we incorrectly when we specifically speak of Americans, [34:38] we think about China, we impart our [34:42] understanding of markets and companies onto China. So we think Huawei, since they make phones, they must be just like Apple. [34:49] It's like, "No, no, no, actually, that's not like Apple at all." I think the first thing I would implore everybody who thinks about China, especially with anxiety in America, is you're not comparing companies to companies.

This is not apples to apples. This is very, very different. [35:03] Imagine instead of thinking open AI is competing against, you know, DeepSeek. [35:08] you say open as competing against the Chinese government instead of Apple competing against Huawei. Apple's competing against the Chinese government. And you can even remove the word Chinese government is the best word to define what this organization is. But it's not a for profit, privately owned, independent. [35:26] group of people who are working on projects together, build, build products to market. So that's the first very important thing.

You cannot treat China like another America or another Europe or another whatever. Number two is if your goal isn't to make profits, [35:41] you can do incredible research and it can be extremely compelling. But like we've seen, if the system is not... [35:50] sustainable, that's also not a company. That's not sustainable. Let me give a very stark example of that. Chinese EVs are really lauded as being this exceptionally interesting product, right? And you constantly get the streamer of, I would say, fairly shallow analysis, which says, look how good China is, and look how bad Munich, Detroit, Tokyo, Sol are the other epicenters for automotive globally.

There is a Chinese EV-like company in America. It's called Rivian. It makes [36:20] but they lose a lot of money making those products, and therefore the company is not very highly valued. [36:28] I think if you said top 50 or top 100 companies in the Bay Area, I'm not sure Rivian would even make that list. And it's not that the products are bad or the people at Rivian are incompetent or they're not working hard. It's just the business is a tough business. The EV business in automotive is a tough business.

So how can we hold these realities? So we say, look how amazing these Chinese EV companies are. Look how bad the home team is. It's just because the home team is being assessed. [36:52] for being a business. [36:54] It has to make profits. And because it doesn't, it gets hammered by public investors. [36:58] The other thing is not even a company. Now, if we do apples to apples, America just has to build great EVs. [37:06] that means tesla and everybody else combined and we don't care about profits i think america would field some very good products and there would be wow products so it's the the comparisons are really really off and i think that's creates a misunderstanding i think you know

[37:22] Then maybe the most philosophical question, can China succeed – [37:27] And does that mean America has to fail or vice versa? If you believe in open and free markets, you believe everybody can succeed in those markets. And that's been proven for over a hundred years. And I think, [37:39] What we're experiencing right now is how does China play in that ecosystem? Because I said open and free markets and those are not open and free markets. And so but that doesn't necessarily mean that you have to have an antagonistic relationship.

It certainly doesn't mean that China is incompetent and it certainly doesn't mean that it's not doesn't warrant. [37:54] our attention and that our kind of, let's say, focus. [38:00] But it's also not a one-to-one comparison. I think we should be very careful in implying it's a one-to-one comparison. [38:05] And by the way, that like five minute explanation is never going to get to the average person sitting at an airport in Detroit, Michigan, waiting for their flight. [38:14] They just... [38:15] All they consume is China bad. It's not like that. It's not that simple.

It's way more nuanced. [38:22] This episode is brought to you by Lovable. Not only are they the fastest growing company in history, I use it regularly and I could not recommend it more highly. If you've ever had an idea for an app but didn't know where to start, [38:35] Lovable is for you. Lovable lets you build working apps and websites by simply chatting with AI. Then you can customize it, add automations, and deploy it to a live domain. It's perfect for marketers spinning up tools, product managers prototyping new ideas, and founders launching their next business.

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Marc Andreessen [39:27] uh quo tweeted it and said this is the best ai ceo nobody knows follow for the for free alpha [39:34] Elad Gill, famed investor, describes you as the most successful, most quiet company in AI. [39:41] And [39:41] To me, this is really interesting because most founders are told, build in public, build a following, be loud, get out there, talk all the time about what you're doing. [39:50] You did the opposite. You were very into the radar, stayed quiet, build, build, build, and then decided later, okay, now it's time to talk about our story.

[39:57] So I think this counter narrative is really interesting and I think will inspire a lot of founders to not feel like they have to do this. [40:02] What was your justification? [40:03] philosophy of just staying quiet and then starting. Yeah. Yeah. It's a great point. So number one, it was intentional. And I think if it was up to me, we would do that forever. I think we're very much inspired by folks more like a Berkshire Hathaway and less like, you know, let's say a Silicon Valley darling. And I'll tell why I changed the views and then just before I [40:31] Some founders go and take that advice immediately without really thinking about it.

I can do that because I'm known in the ecosystem. [40:40] I know these folks personally, and so I don't need to... [40:45] have a brand out there that is getting a lot to remember me and think about me. If I'm doing my first two companies, we're a lot less known as before I really came to YC. All of our company values can be reduced to these two words of radical pragmatism. Before you take the advice, [41:04] Make sure it applies to your situation. One of the reasons, and Naval, who's one of our investors and a friend, you know, says, you know, fame itself is like a tool and it's, and it's, [41:15] powerful.

Now, if you don't have a network and you can get a following, that's a fantastic way to get, you know, to recruit people to your company, to recruit investors to your mission, and then, of course, you know, the customers. And so, but for us, and I think that wasn't a hard requirement, you know, 10 plus years ago. The other thing is, I think, Peter and I, you know, the old saying about life is kind of like, [41:43] you do things and then you rationalize the thing that you do. [41:47] I think fundamentally, Peter and I, we don't get a lot of my co-founder, Peter, we don't get a lot of emotional satisfaction out of doing very public things.

And I think if I was really to play armchair psychologist and really try to get to the root of why beyond the rational view, which is focus on your customers, focus on the product. [42:17] customers and your product. And ultimately, that's the only thing that's going to produce and yield results. But the reality of the situation today, in 2026, is even a company like us that's known or somebody like me that's known in the ecosystem, you still want to get that broader message out. And that's what I talk a little bit about on X.

So it is definitely contrarian, but it's not just contrarian for contrarian's sake. [42:45] It plays a little bit of our of our own psychology. And then I would say just to just to finish that thought there is. [42:51] I grew up, I'm an immigrant. I came to the US from Pakistan when I was a kid. I have a little bit of a weird name. I grew up in Warren, Michigan specifically for all those at home. When you feel that you're a little bit on the edge of society or you're not maybe in the mainstream, [43:12] And this resonates with some people.

It doesn't resonate with everybody. [43:16] you feel very skeptical of the mainstream because you're just on the outside for so long. And I think you can trace a bunch of founders psychology to this feeling of being an outcast, actually. And so then you find yourself in a situation where you're like the CEO of YC and you're [43:35] The narrative of I'm an outsider is like, I don't know if there's anything more inside than being the YCCO, right? [43:43] I think that reconciliation over my career also has had to happen, which is like maybe that's just kind of a weird kind of thing.

And so when I talked to Mark Andreessen, who really pushed me to go online or Elad or whoever it is, their view is – [43:59] Leave your baggage and your trauma, you know, in the background. And really, let's let's think more pragmatically. [44:07] And the pragmatic thing here is whether I like to do these types of things or not, fundamentally, it helps get the message out. [44:14] And the message can be something very small in myopic, like what's happening in physical AI and machines becoming intelligent. [44:21] or much larger, which is what's happening in society through this fundamental change that we're going through.

I've had the... [44:30] rare privilege or the you know experience of seeing the full [44:35] economic spectrum you know I've really seen the extreme ends of both sides and truly I really mean that and so [44:44] Somebody like Mark, who is close to our company, says, well, that's a [44:48] Those are some ideas that are worth getting out beyond just, you know, you're there promoting whatever some, you know, your company or something like that. And that I actually that I can get behind, which is like the debate and discussion about ideas and what's happening.

[45:01] to our society because of these technical changes. And so, you know, here I am. Amazing. Okay, so there's a few threads I want to follow there. One is you were, as you said, COO at Y Combinator. You saw a lot of startups up close. This is your third startup on your own. [45:20] Something that I hear you talk about is that [45:22] Successful companies almost always show traction very early. [45:27] A lot of founders here are like, no, just keep fighting and maybe we'll be the next Figma Notion four years in.

We'll figure it out. [45:33] What's your experience there and what's your advice to founders who aren't seeing traction early? [45:38] Yeah, nuances. I mean, if I was starting another company, I'd call it nuance, right? So I think what you're saying is correct. I continue to believe that. I think good companies tend to have traction fairly early and then just sustain it for a decade plus. [45:54] To the founders that's toiling, let's say you're listening and you're about two years into your company and you're maybe having a tough time getting money and building that first product that – [46:04] consumers or businesses really love, either through retention or dollars.

[46:09] Two years is the difficult time. The heuristic that I would use is if I'm not... [46:16] If the information I'm getting from the market is not informing me on a more and more specific path, [46:22] I would consider resetting. [46:24] And what I mean by reset is oftentimes, and this is wearing my YC hat, seeing hundreds and thousands of companies, is oftentimes it's like the co-founding. [46:33] Like literally the foundation upon which the house is built is not correct. It's like, imagine you built this house and every time you put a cup of water and it slides off the table and it falls on the ground and you're, do you keep adjusting the table?

It's like, maybe the foundation is actually wrong. The whole house is off kilter and the foundation might not only be [46:49] Your co-founders could be the market that you're in. It could be the phase of life that you're in and the amount of effort that you're willing to put into that thing in order to make it successful. There's a bunch of reasons that a company can fail. And you have to be able to. [47:02] Somehow say, I don't know what is the reason. I'm just going to have to hard reset here.

One thing I would tell founders and I tell applied is creating a founder class in itself. People who work at Applied Intuition are now starting their own companies. You know, we have a thousand plus engineers and over time they're starting their own firms. And I say to all of them is. [47:23] Just imagine the first time you're going to do startup for the first three years. [47:27] It's a zero. [47:28] Just rid yourself of the expectation that it's going to be successful and that you're really – you're a craftsperson. If we were – if this was a woodworking podcast and you said – [47:40] You know, the first table that you built was, you know, what was wobbly.

[47:46] You wouldn't say, well... [47:47] Go work at Crate and Barrel. You'd say, that's the first table. We're going to keep at it. Being a founder is its own muscle. [47:55] and you want to exercise that muscle. But I think a lot of founders, especially early in their founding career, put such [48:02] an incredible pressure on themselves to make it great out of the gate that they actually miss the thing that you're getting in that first round, which is learning. [48:10] and building that muscle. [48:12] In the second, third time.

And I think it's not random that my third company is the most successful company. I think you see that more often than not. There are funds which are almost exclusively focused on multi-time founders for this reason. [48:26] What I love about that advice is often the best ideas come from when you're [48:30] You have low expectations. You're just playing around. You're just tinkering. You're not like, I'm going to build the next great. [48:36] I don't know, Google, it's just you having fun. And that's how I found this. [48:42] world that I'm in right now, this path, and OpenClaw is a good example of that.

[48:46] I think why that advice is so difficult is if you hear this and you're in the proverbial war, [48:54] You're like, what the hell are these people talking about having fun? This is hard. And so you have to like hold these like contrasting kind of or conflicting views in your head, which is like it's deeply very, very important. And you should give it your all. And it's also not that important. [49:12] And that's a really hard thing to reconcile and keep in balance. And the way that you approached this company where you stayed quiet like that, I think helps a lot where you're not.

Absolutely. Absolutely. [49:24] Even at YC, when I became COO, I told Sam Altman was a president. And I told Sam, let's not announce this for like a year. Because if the... [49:36] Partners don't want me to be COO. It's not a successful thing. I don't have the pressure of the public scrutiny that why were you COO only for six months or something like that. And I think you have to be very honest with yourself as a founder and as a human being that those things matter. [49:52] What people think about you matter and it impacts yourself and having the spotlight on you.

I always say it's very easy to pivot before you raise money and before you have employees. Nobody cares. The moment you raise money and more importantly, the moment you hire employees, employees join a very specific mission. And you go and you walk into the office and there's 10 of them. You say, guys, turns out this isn't wrong. We're going on a different mission. Imagine if this was war. It's like, what the hell? We're attacking that hill and now we just say that hill is not important. [50:22] important. [50:23] And you as a lead, you lose a lot of credibility.

And it's not only for the superficialness of being a credible leader. It's a practical nature of when you're very, very public, the startup becomes your identity. [50:36] And then suddenly you're [50:38] You're having to reconcile that actually that thing is not correct. So it is one of our – we have these core values in the company. And early in the company, you used to have this line which says, our best work is done alone and quietly. Right? [50:52] And I deeply believe that. And so founders, I would think of it that way.

[50:59] But it's for pragmatic reasons. It's not like some just because it's cool to be under the radar. It just allows you to maybe work in a bit more peaceful ways. [51:09] I love these core values you've shared so far. The last one, the best work is done alone quietly. I'm so on board with that. Radical pragmatism is the other one you shared earlier. Are there a couple more there? These are gems. Yeah, those are, like I would say, the meta values. We have very specific... [51:25] let's say, operating principles.

And this is real [51:29] as tactical as advice I can give to founders. So we can come up with your values when you're getting a little bit of traction. And the reason I say that is early enough where you and the way you come with the values is not like, [51:41] What values should we have like as philosophers? No, no. You should figure out why are we being successful? [51:48] Like literally write down the five to ten things that are the reasons you are being successful. And those become your values.

And you kind of read. And so we did that. And so our first one was going to speed above everything. [51:58] It was like us being fast. The second one is like, never disappoint the customer. [52:03] technical mastery, high output matters, like all the way down to like, you know, ones that are not obvious, like laugh a lot. That's been our core value from at the beginning of the company's history. It's like when you're working in intense things, if you don't have the ability to keep grounded, have perspective, laughter and humor also is a way to get subtle feedback and a slightly different taste than this sucks.

You can say it's not the best. And that is slightly. And so you're you're really creating the.