"Founders can also choose to build new companies, so I call them rebound, revenge, and rebirth. Rebound founders are comfortable with the identity of being a founder, so they move to the next idea as quickly as possible without thinking it through. It is like a rebound relationship right after a breakup. They build a rebound startup because as long as they are doing a startup, they still have an identity and can still fundraise. There are also revenge startups. For example, a founder was fired from a benefits platform by the board and then went on to build a direct competitor. The original company was a unicorn and later collapsed, while the new company became a billion-dollar all-in-one HR platform." - Jeremy Au, Host of BRAVE Southeast Asia Tech Podcast


"All startups are bets. They are bets on the future. They are bets that the future will become reality. They are bets that this company wins the race. They are bets that regulators will not regulate the company out of existence. In each round, investors pay more to find out what the bet really is. The real question is whether the risk taken matches the reward. From both the investor and founder perspective, founders can fail, but they are pioneers of a new world, and they teach us what can work and what cannot work." - Jeremy Au, Host of BRAVE Southeast Asia Tech Podcast



"AI robots are back. They may have been too early for their time because hardware is now cheaper, indoor sensors are more available, facial recognition middleware is more powerful, and language is now powered by ChatGPT. AI robots are back for social robots. Jibo is a great example of this. They failed, but they were also ahead of their time, a pioneer of social robots. Today, we already know there will be AI-powered teddy bears." - Jeremy Au, Host of BRAVE Southeast Asia Tech Podcast

Jeremy Au breaks down why most startups fail even after raising capital and why failure is often misunderstood by founders, investors, and the media. Drawing from venture data and real startup case studies, the discussion unpacks common failure patterns, the role of timing and macro forces, and why economic failure does not always mean bad judgment. The episode reframes failure as part of innovation, while staying honest about incentives, power laws, and investor reality.

01:40 The Brutal Math of Venture Capital: Jeremy explains why only about 1% of startups become unicorns, with high death rates at every funding stage.

03:55 Are Failed Startups Really Failures?: The discussion reframes failure, asking whether founders are failures or pioneers who were simply too early.

06:10 Jibo and Being Too Early: Jeremy shares how a social robot startup failed due to high hardware costs and missing infrastructure years before AI and sensors were ready.

12:30 Six Common Startup Failure Patterns: Jeremy outlines repeatable failure modes, including bad teams, false starts, speed traps, and bad macro luck.

20:10 Bad Macro Luck and Market Cycles: The episode explains how funding winters and external shocks can kill startups that were otherwise doing fine.

We will be talking ~very much~ about failure patterns and value addition of this component. ~And so very much~ we're talking about deals, which is very much that starting process of getting them into the portfolio company.

You can imagine that when as VC brings on a company, one of the first things they have already identified as part of the due diligence is they already identify that this company, for example, we need more salespeople. They may need a new marketing leader and so they may need more connections to more businesses.

And so very much as part of that process they say, look this is a gem in a rough. This is a company that's gonna become a unicorn in the next 10 years. And as part of our due diligence, we have identified that these are things that we need to improve. And so very much how do we help them improve this?

Because if these companies do not improve, what we have talked about is that the default scenario is that these companies will eventually fail and die.

So the other question that we have is then if we talk about this is that they have to generate value. And [00:02:00] so they identify how they have to help these companies because if they don't help these companies that the most likely scenario is that these companies will die. And so we look at this failure rate and yes, you know in this scenario you can see here is that, out of a thousand plus C companies at the top, only half of them effectively raise the next round, which is a Series A, right?

And then if you look at the next stage is that, out of the 500 plus, only about 300 plus. So about 60% of the companies managed to make it the next round. So there's about 40% are free. And out of the 335, only 172, so again, about 40% of those companies died at the next stage. And then out 172, only again, 96, which is about 40% death rate.

And then out 96 out of them, only 96 minute to blah, blah, blah. And so out of this total subset of unicorns, you know, only 1% of these companies became a unicorn, right? Which is 12 companies, which in this subset includes [00:03:00] obviously Stripe, but also Docker, which is a very famous kind of like infrastructure for coding company.

And of course there's a certain set of number of companies that you exit over 50 mil, a hundred mil, 200 mil, 500 mil, and over $1 billion plus, right? And so, I think the crux of it is that, even when you make that investment, there's a very high death rate that's still happening over and over again.

And so you really have to be quite powerful about this. Because we talked about how these investments, most of them don't venture capital, but some of them do have a power law and achieve that. And so when we think about failure, there's always this debate about failure. Are we trying to de-stigmatize failure?

We need to make our kids be okay with failure. Oh, he's a failure. The startup is a failure. So I think for us, when you think about startups quite interestingly and quite carefully, right? Which was that, you know, are they failures or pioneers? So for example Jibo was the world's first social robot. They raised $73 million.

Starting from [00:04:00] 2013, and then he died at 2018. So they raised about a $3 million in five years and they created this beautiful robot that basically looks like Pixar, right? And basically could talk to kids and talk about their day and so forth. And what was interesting was that they failed because they have this vision which was that everybody will be able to interact with their own social robot.

And at this point of time they learned, for example, that there's certain vision. But they learned that the hardware was actually a lot more expensive. 'Cause all of the components they wanted to build wasn't really at scale, right? At that point of time, especially 2013 to 2018, today of course a lot of these hardware components are cheaper. Thanks to Shenzhen and China and so forth.

By that time, it was very expensive for them to build. And more importantly, they thought that they could use sensors, for example, that already existed. But what they realized was that there was no middleware, they had to code. Because the sensors that they were using, cameras that they were using were primarily used for example, for outdoor, et cetera, but we're not doing well indoors, where, you know, indoors the light is much more dim,

right? And then they have to use [00:05:00] middleware to translate that signal to say, if a kid is looking at me and smiling, that means something. What is a smile? What is anger? What is that? And so there's a lot of code they had to do. And basically it was just much more expensive to build this robot, even though the end vision of a Pixar like robot Wall-E talking to you was the end vision, right?

Also some bad things happened along the way. The CEO is diagnosed with leukemia, so he had to take a step back. The CTO stepped up for a year as interim CEO and then suddenly out the blue at a time in around 2017 , 2018, I don't remember. But Amazon launched with Amazon Echo, which was basically saying a smart speaker, right?

And so at that point in time, there was no such thing as smart speakers. And it turns out that they had this big vision of building a social robot, but it turns out that Amazon was willing to build smart speakers, which turned out to be hot. And also Amazon was willing to basically produce them for effectively no margin, right?

Because they felt like they wanted an Alexa in [00:06:00] everybody's home. Now after that, we had Siri obviously it was also started competing. We saw Google Home competing as well. So basically what they realized was that their market died because people were like, okay, social robots are out actually, but people want smart speakers, right?

But it turns out in 2023, AI robots are back, right? You know? So they were maybe too early for their time because now hardware is cheaper, indoor sensors have become more available. Facial recognition software middleware has become more powerful. And people now have ChatGPT to power the language.

And so AI robots are back for social robots. So I think Jibo is a great example of, hey, you know, they were a failure, but also you can say that they were ahead of his time, right? A pioneer of social robots. And today, I think we all believe, and we already know, that there are going to be AI powered teddy bears, right?

Imagine you read Calvin Hobbes, you know, the tiger, his stuffed [00:07:00] toy talks to him and has adventures of him and talks to him and everything. You can totally imagine that you can make using ChatGPT a stuffed tiger and the power of Shenzhen, you can probably create your own Calvin Hobbes sidekick to give to your kid, right?

And so, I wanna talk about how to define failure. And for the purposes of this conversation, we'll define failure from an economic perspective, right? Because we're talking about it from the VC perspective, and what we're saying is that the early investors did not, or never will get back more money than they put in.

They didn't receive a reward for taking on that risk. Maybe they lost all the money, maybe they recovered some of the money. Maybe they recovered the principle, but they didn't get that reward right? From a VC perspective.

Just because it's an economic failure doesn't mean that it's a dumb.

All startups are bets that are bets on the future. It's the bet that the future come to reality is a bet that this is the company that wins that race is a bet that regulators will [00:08:00] not regulate our existence. But these are all bets, and so VCs like to play poker a lot, right? Because they feel about it that from their perspective is,

when they make an investment, they're flipping a card. They get to pay more into each round to figure out what it is, and the question is, did you take on the right amount of risk for the right amount of reward? So from our perspective and from the founder perspective is these founders can fail, but they very much are pioneers for renewal

and they teach us what can work and what cannot work, right? And so the awkward reality is that it can be very difficult to understand startup failures. And the reason why it is difficult to understand startup failures objectively, is because of three things. First of all, is the single cause fallacy. We want to believe that there's only one reason why the startup failed.

Theranos failed because Elizabeth Holmes was a crook. And that's it. But we also know there were multiple factors in it as well. The board of Theranos could have dug into it. The employees could have whistle blown [00:09:00] earlier, right? VCs could have and investors could due diligence earlier or more thoroughly. So there are multiple points of failure to it, but it's much easier for us too often simplify for both good outcomes and outcomes.

And so we say meta succeeded because of Mark Zuckerberg, but there could be also be other reasons for many other reasons. And so I think it's gonna be quite difficult to do about it. Two is in failure, we often have something called the fundamental attribution error, which is that when we observe others, we tend to say that it's their personality skills so forth, while downplaying the environment of bad luck, right?

So for example, WeWork obviously collapse, but also you must remember that the pandemic also happened, right? And so a lot of people say if you watch the movies and everything, it's very much about Adam Newman and how he's a bad founder. And he had a reality discussion feel but also there was a pandemic, which crashed the office workspace market, right?

Not just for him, but [00:10:00] for many other players in parallel. And because Zoom became super viral and now everybody became hybrid and offshore, so coworking spaces structurally had much less demand, right? And so that's something to be thoughtful about is that it seems to be easier to say, is Adam Newman's fault than to talk about all the other factors?

And lastly, of course, is it's very hard to figure out the truth because when a new venture fails, the investors, the teammates, the media often blame the founder, for example. And the founder often blames the industry, external circumstances or other parties, the board director et cetera.

And it takes time to figure out, people are covered by NDAs, people have reputational risks. People don't wanna be sued by one another. So it takes time for the truth to come out. So just because the company fails to the short term doesn't mean that you often takes five or 10 years for the truth to come out for us to really understand what really happened behind the scenes,

right? And so when we think about startup failure, there are about six common clusters. And there's this book that I recommend, which is [00:11:00] called why Startups Fail by Harvard, MBA Professor Tom Eisenmann. And I was at my point of view to classify this, but those are the six clusters of failure.

And you have to understand these six clusters because again, when the VC is meeting them, they're thinking about this from the selection side. But also thinking about it when they are part of the portfolio company, how do we avoid these failure patterns, right? How do we get 'em to the next stage? So the six failure patterns are good idea bid follows.

The second one is false starts. The third is false positives. Fourth is speed trap. Fifth is bad macro luck. And six is cascading miracles. So those are six approaches, and I'm gonna explain each one of them. The first one is relatively straightforward which is there's some form of dysfunctional performance across the early founding team or the early investors or stakeholders, right?

So a common problem is who's the boss? I just on LinkedIn saw a interesting post where somebody raised [00:12:00] about I think $80 million in capital. But what caught my eye was that the person announcing it on his LinkedIn title said that he was the co CEO of the company. in my head, I was like, wow congratulations on raising this tremendous amount of money for your AI company.

But straight away my sensation was sooner or later there's gonna be a fight about who is the actual CEO. And that's gonna be very destructive in that scenario. And the board, I'm sure the VCs who invested there are thinking about it and thinking to themselves, who would be the better CEO if which come to shove. A decision has to be made about which CEO is the real CEO, for example.

So who's the boss? The founders don't have industry experience. Maybe they're not entrepreneurial, actually. They think they're entrepreneurs, but they're not entrepreneurial and flexible. Maybe the investors are not a good fit in the early stage, or maybe they just can't work with their customers or early suppliers,

right? So for Quincy Apparel they raised $1 million seed capital. So they were inspired by Love Vulnerables, Run the Runway, and Love, Bonito by basically the concept of direct consumer [00:13:00] apparel. These were both Harvard MBA students and it turns out none of them had any fashion experience. They were both co-CEOs equivalent and they for example acknowledged that.

And so they felt like they brought, build together and SOP on how to discuss and agree and so forth. And, you know, were all collaborative and, you know, trust us, we still make the good decisions even though we are co-CEOs, right? And I think the tricky part for Quincy Apparel, and in this case, like their book as well, was that they knew they didn't have experience in the apparel industry.

So they brought in an investor, they had invested in Bonobos But it turns out that the investor in Bonobos didn't really know much about Bonobos either. They just put money in. So there was no value add from the investor perspective. And then, so as a result, when you're making the apparel, they were just making mistakes like the sleeves are too short, right?

And basic stuff that basically made it, that datas were very inefficient. And basically as they learned these mistakes they ran out money [00:14:00] 'cause they ran out time and money to make those mistakes. And so other raising a million dollars, they failed to make direct to consumer work fashion for women fail.

But lots of other companies succeeded, right? So Bonobos, Love, Bonito, Run the Runway and all those have quite interesting biographies actually, if you wanna check it out online as well. Bonobos is actually really interesting. Again, their co-founder conflict. I listen to this biography. And then the founder has a very interesting

experience because he was suffering from mental illness during this timeframe. So he talks about a quite interesting story about him having a mental breakdown and being arrested by the police while also fundraising and so forth. So, quite interesting story about how he has to go through rehab and rehabilitation.

So, yeah, but for Bonobos, they made it but Quincy Apparel did not. Obviously there are other companies that made it as well in the direct consumer or fashion space. Secondly is false starts. So, sometimes founders can be very persuaded or very convicted about their vision [00:15:00] of the world.

So they don't really talk to customers and they neglect to research customer needs before doing all the engineering building, the product launching and very much is driven by founders who believe in a certain way of the world, right? And so they often build the wrong product that customers don't really need.

So for the founder of Triangulate, his perspective was that with the launch of Facebook and the social graph, he felt that dating could be a lot more efficient because as an engineer, his perspective was that dating and compatibility should be data driven. So he said, using a social graph, you plug in and connect and social graph, we will match you with the people who truly a compatible review.

I think he was proven wrong by the market because what it turns out that the way he shared builds dating app was focused on the pictures, right? Which was Tinder was just one picture and swipe. You know, left or right effectively, right? Yes or no. So in this case, his vision of the world, which is that humans should use data to match with their loved one [00:16:00] failed, but he felt very convicted about it.

And the incredible part is that people gave him $1.5 million to build a product based on data-driven dating, right? Now false positives are people who have survived those two things and they have achieved some level of product market fit, but they incorrectly extrapolate that early adopter enthusiasm for the mainstream.

And they step on the gas too early. So very much what happens is that they have that early success signal. So they start to expand ' cause the investors want them accelerate and then they end up scaling the product from the correct customers to the wrong customers, and then they die because they run out money.

So Baroo as a founder Lindsay Hyde, she's also a Harvard MBA she raised $2.6 million for past services. So basically the concept was that if you are a condominium in, say for example, Boston as a concierge, is that you have to walk your dog and so your concierge and your condo can walk all the [00:17:00] dogs in a building, right?

So it's almost like a B to B to C approach, right? So instead of like, another company called Rover, which was basically this is consumer allows people to book a dog walker because I'm lazy to walk the dog next week or I'm away, you know, from home for the week.

Instead of booking directly a dog sitter,

Speaker 20: Their

Speaker 19: approach was to partner the condo, your property management, and basically create that value added benefit. For you to be able to access dog walking services, dog feeding services you know, watch out for your dog sitting services or so forth. The issue that they had was that they have a lot of success in the early days in Boston.

But it turns out that there was certain issues that she didn't really understand at that point of time was that first of all, when they launched it during autumn and winter. So that's mistake number one, because in winter nobody wanted to walk the dogs. So there was very high enthusiasm because nobody wanted to walk the dogs in winter, you know, in Boston, right?

Another problem they had was that the condos they had actually turned [00:18:00] out in retrospect to have a movie production crew. So this crew that came into town, brought their pets and basically were busy shooting a movie, and so they didn't have time to walk the dogs.

And so there were very big users of it. So they had very high usage rates, very high utilization rates. And so investors were very excited by this demand signal. And then they expanded the new cities. And then unfortunately, summer came, new apartments, new cities, and basically the company didn't have as much demand as they thought.

And then the company ran out money and it died. So, this is a real experience. And I remember talking to her and getting advice from her and she very much was saying that, Hey, you know, my lesson I learned was that when you expand, you gotta expand slowly and it be very thoughtful about which this best match your customer profile, right?

Because her reflection was that she has succeeded in Boston and so maybe she should have gone, for example, to expand to DC instead of expanding to New York because New York is a different type of city from [00:19:00] Boston is more suburbian. Then the next category is called speed trap. This is when you achieve product market fit and you saturate that original target market and then you keep expanding because you try to keep pushing and grow to more categories.

But as you expand to more categories you end up losing product market fit in those new categories. This is often driven by what I mentioned before by the concept of network effects, which is a winner takes all. So you're the first mover. There are multiple competitors. It is time for you to kill your competitors and accelerate quickly because it's a land grab and you better eat that space before your competitors eat it.

So there's very much the reasoning that the management team and investors will be sitting around our board meetings have. What's interesting is that rapid growth in a category often attracts rivals or attracted by that growth sector, right? And so margins will drop as a result and as a result, because of that aggressive expansion,

you can see it as a unsustainable pace. It leads to staffing, bottlenecks, disorganization, complexity, internet [00:20:00] discord and conflict, and also often ethical lapses as well, right? Because people are rushing to hit certain sales targets and quotas, and then because they're growing very aggressively and burning a lot of money, then suddenly the investors get cold feet.

They don't invest. And then the CEO basically runs into a brick wall and then they have to do layoffs and do everything they have to do.

And so a good example would be Fab.com. They were doing at a time, I don't even remember in 2011, they innovated the idea of flash sales. Basically the idea that an item's only available for a few hours or one day, you better buy as much as you can.

And they pioneered that idea of e-commerce in 2011, and it became super hot. They expanded to more categories over time. They reached a billion dollar valuation. What happened was that as they expanded new categories, the new categories, they weren't doing so well, they're losing more money. And then they lost track of the original categories and they were making worse and worse margins.

And eventually the company collapsed. Today the idea of flash sales still exist. If you go on Lazada, you go to anything. The concept of flash [00:21:00] sales still exist. Like the concept of having a promotion, a limited time promotion deal that's counted in hours or is exists as a feature, but it's no longer a full-fledged startup like this.

Now you would think that this is a known problem or people would be smarter than this. But for example, if you look at China today, there's a quick commerce. Wars are happening now, right? They're all killing themselves to death right now. We have massive negative margins right now where customers are having a fantastic time getting bubble tea effectively for free, delivery

for free, everything's for free. And now everybody's killing each other to death. And all the management teams are all locked into this, prisoner's dilemma where nobody wants to say that they're gonna back off or surrender. They all say that they committed millions or hundreds of million dollars to this budget.

And all of them are losing a ton of money right now for effectively no gain. But it's prisonner's dilemma, right? And so now, the Chinese government is starting to talk about, is this over competition? Do we need to regulate? And then, you know, there's all these like [00:22:00] coded signals to be like, you know, what's the right thing to do, et cetera, et cetera.

Plus, in the meantime, consumers benefit in China from this over competition, right? Or speed trap. So it can still happen today. It happens all the time. The next is sometimes you just have bad macro luck, right? So you can build a product market fit, you go to customer base, and sometimes you can have massive financing risk where the entire industry can go through a funding drop, right?

Because everybody just pulls back. So Biotech in the 1990s was hot, then got killed and died. CleanTech in the 2000's, Kleiner Perkins made a big bat on CleanTech, they thought it was the future. It was super hot. And then it turns out that nobody really wanted to buy carbon credits in two thousands, even though the hot thing.

And then CleanTech went through a death cycle in terms of funding 2000's , where Crypto Winter in 2022 because of FTX, right? And so what happens is that a startup may be doing well and so forth, but then they cut the timing very close. Maybe they have three months of runway left, et cetera.

And then Crypto Winter happens, and [00:23:00] then VCs run for the hills. They don't wire their money, they renege on a term sheet, and then a fragile startup basically dies because they get hit at a very unlucky time. So for example, Dot and Bo they had this concept where show was online furniture sales. They raised $20 million.

And then they died because in 2016 there was an e-commerce bust. So there's always a boom and bust cycle that's happening, right? And so you and I know that right now there's Crypto Winter 2022, but. 2025 crypto's back. So you know, lots of companies died in 2002. But if FTX had stayed around and avoid getting caught to 2025, you could imagine that they could have made it, right?

So I think there's some level of luck of the macro perspective as well. And lastly, I think what's very common is something called cascading miracles. And this very much happens when a founder has a very incredible vision, but they seem to die with very low traction. So this is kinda like the [00:24:00] most catastrophic, the most visible failures that happen, right?

So what happens is that these startups often very much have to do multiple things to happen. In order for it to happen, they have to first persuade a critical mass of early adopters to actually adopt it, number one. Number two is they have to build a new technology stack from scratch. Three is they get regulations to work in their favor, and four is they have to to raise a ton of money to make it happen.

Okay, so for example, legendary flops is Iridium. Iridium basically had this vision of creating global satellite cellular connectivity, which is that from anywhere in the world you should be able to call anywhere. So Iridium when bankrupt, but it was bought by a consortium and it still exists today as part of the satellite communications, but the company failed,

right? Segway as gigs mentioned in the past. Was electric mobility, his concept was that people would [00:25:00] walk, you know, use scooters, make it electric, raise a ton of money. Now, obviously, most of us only think about it for your comedy movies, right? Like, Mall Cop or these, you know, comedy movies where people use that ways,

right? And of course, Webvan was a famous company that was in the early two thousands where basically they had a concept of selling groceries online. Of course, the problem was at the time, people were using Dial-up, people were using PCs they didn't have mobile phones and most people didn't have credit cards.

That really worked online as well. So Webvan failed at that time. But the reason why I mentioned this is because, in the same breath, actually we know that some companies succeeded in achieving that. SpaceX in 2023, 24, 25. Tesla is also the electric mobility, the same concept for, you know, for electric mobility.

It just turns out to be a car not a two wheel scooter. And obviously Amazon succeeded eventually with online groceries. Right? [00:26:00] And I think they just announced recently that this week that they want to bring some of their grocery line to Singapore to expand to Singapore, right? So a good example would be if you look at Better Place was an Israeli startup.

They raised $850 million. So their concept was that the world would go electric. And so their idea was that they wanted to build a battery swap network, which is a network of places where you could get your car and change your battery instead of fueling your car of gas. And then he partnered with car manufacturers at a time with Ford to create cars

that would fit this battery swap network. Now what's interesting is that they're only able to build and sell 800 cars. So, so one way to think about it is each car costs effectively a million dollars to design, build, and get on the road. And the company failed eventually, right?

But he did a lot of incredible things back then, right? Which was, he created a network of battery swapping [00:27:00] stations. He got the Israeli government to agree to set these things up. $850 million, but it turns out there was just not enough people driving electric cars to use the battery swap network.

You couldn't get that critical mass of consumers to use it. And so the company failed. But of course, today, you and I think about it today and we're like wait, it didn't succeed. Gogoro in Taiwan has battery swap for their electric motorcycles. It's also a unicorn. If you look at Tesla, they have the supercharger network, right? That do charging, but the concept of stations are still there.

So yeah, you know, I think you may argument that better place was just 10 to 15 years too early. Or you can say that executed badly. But again, what I'm trying to say here is that these are often the most famous startups that fail. And so failure is something that happens again to, as we saw 39 out of 40 seed startups.

In the funnel that you saw, they said effectively failure, maybe even up to like 95%. And [00:28:00] so, very much is that the founders can make a decision in terms of how they can move on with life of this failure. I like to say that two approaches. One is to move on. The other one is to build new startups.

So move on. For example Lindsay Hyde, the Baroo founder we mentioned earlier she has now become a professor in the Harvard Business School teaching about entrepreneurial failure. She uses her own case study, explain it as a way to teach founders about how to avoid failure. And yeah, I think she's doing well in life.

Of course, founders can also choose to build new companies as well. So I call them rebound, revenge and rebirth. I think rebound founders are because founders feel like they are comfortable with the identity of a founder, so they just move to the next idea as quickly as possible without really thinking it through.

So it's like a rebound girlfriend right after a breakup. So they have a rebound startup where it's just like as long as I'm doing a startup, I still have identity. I can still fundraise. So I think there's a lot of founders who are like that. There's also revenge startups. So for example, if like Conrad [00:29:00] Parker.

He was fired from Zenefit, which is the benefits platform after the board fired him. As part of his revenge he built Rippling a competitor to Zenefit. And Zenefit was a unicorn. And now is did thanks to Conrad Parker. And Conrad Parker has built a new billion dollar company called Rippling, which is an all-in-one HR platform for HR offices.

And lastly of course, there's rebirth, which is very much founders after you know, he was fired from Oculus after he sold to Facebook and Meta. But after donating to Trump as an early supporter of Trump, he was fired from Meta and then he spent some time thinking about what kind of company he wanted to build.

And in public record after a lot of thinking and processing, he wanted to build two different companies. One company was Anduril, which is a defense tech company that we talked about, which is basically AI and drones and robotics for military defense. But the other company that he had wanted to build at upon a time was a private prison system, right?

So in America, the top three players in private [00:30:00] prisons account for the vast majority of incarceration bids. And so his perspective was that if he could build a tech enabled prison, he'll be able to deliver a better experience, better rehabilitation, and lower cost, and a more humanitarian approach for the private prison industry.

But between these two, he decided that he would work on defense tech because he felt like defense tech would provide a more fair playing field than from his perspective the private prison industry has a lot of regulatory mode. And all of this is something that he has shared on public record about him deciding that it'll be too difficult to enter the private prison industry because of the regulatory mode that the private prisons already have.

But I felt that there was an approach that he could build a much better defense tech company.