a16z Podcast - The Factory of the Future with Chris Power

Episode Date: November 17, 2022

Today, we have an episode with Chris Power, the founder and CEO of Hadrian. Hadrian is a company trying to build the most efficient factories on the planet. In this conversation, we’ll introduce the audience to advanced manufacturing, and expose them to the reality that it’s a remnant of the first space race. We also cover the challenge of manufacturing, the importance of visibility in complex systems, the killer app for space, how simplifying the world of atoms can be done through bits – and ultimately, what kind of experimentation that may unlock.Timestamps: 0:00 - Introduction1:28 - What is advanced manufacturing?4:18 - When a hatch is jammed at the ISS6:11 - What’s happened since Space Race 1?8:56 - A retiring workforce13:20 - What is at stake?21:03 - Onshoring manufacturing24:06 - Is capital enough?24:43 - Fixing the problem with technology28:55 - Convincing the old guard31:20 - Building a new culture34:45 - Experimenting with hardware37:24 - The value of observability41:47 - The cost of timeliness46:09 - Hadrian’s key risks49:22 - Why Hadrian pivoted52:22 - What talent is needed57:31 - Why focus on space first?1:03:38 - The killer app of space1:10:36 - Who inspires Chris? Resources: Hadrian’s website: https://www.hadrian.co/Chris’ Twitter: https://twitter.com/2112Power Stay Updated: Find us on Twitter: https://twitter.com/a16zFind us on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. For more details please see a16z.com/disclosures.

They would have had an extra billion dollars in revenue last quarter, had more of their parts being delivered on time. Today we have on Chris Power. Chris is the founder and CEO of Hadrian. Hadrian is trying to build the factories of the future. And in today's episode, we talk about what advanced manufacturing is, how advanced it really is, what's happened since the first base race, the complexity of onshore manufacturing, the killer app for space, and how simplifying the world of atoms can actually be done through bits. and ultimately what kind of experimentation that might unlock.

If you like this episode, I have a feeling you'll also like our recently published and first ever American Dynamism 50 list, the list of 50 companies building in the national interest that embody the ethos of American Dynamism. And guess who's on that list? Patreon. You can find it at our homepage at A16Z.com or at A16c.com slash American dash dynamism dash 50.

Enjoy. The content here is for informational purposes. only should not be taken as legal business tax or investment advice or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund. For more details, we see A16Z.com slash disclosures. Chris, welcome to the show. Thank you for having me. All right, let's start with a really simple definition.

What is advanced manufacturing? Advanced manufacturing is an industry term that generally covers the complex and high precision side of all industries, which is usually semiconductor, aerospace, defense. Basically, anything that you think of from like the Jetson's flying car future is generally bucketed as an advanced manufacturing. I think it's interesting that this term advanced manufacturing covers an industry which isn't always that advanced or maybe hasn't kept up with the time. So could you give a couple examples of ways that this space of advanced manufacturing

is maybe not the reality that people might expect? On the defense side is a great example. You know, everyone sees defense primes coming out with drone programs or advanced fighter jets and stuff and really flashy products and marketing and things, wow, you're like everything, works perfectly. Under the hood, once you get below the assembly level, you know, someone making a fighter jet, really what they're doing is outsourcing all of the components with the wing, the engine, everything to a tiered layer of 10 mini primes, then 20 tier three suppliers, and then literally 10,000 small suppliers dotted across the country that are doing everything

from a machine component to, I don't know, the circuit board that is one part of the fire control system or whatever. And that entire layer is basically chaos. You know, the B2 bomber, which is one of our most strategic assets in terms of the nuclear program. About a year ago, the government had to issue an RFQ for some of the parts on the B2, not just to replace the parts, but because no one, you know, the guy that designed it or engineered it retired and they didn't have it documented anywhere. Like there's literally no manual or document of how to make that part. So the government had to go out and say, hey, we need someone to come up and reverse it. You need this entire thing. So there's stuff like that that's really scary. And another example is we shipped

the Ukrainians what we thought was three years of inventory of Stinger and Javelin missiles, which are shoulder-mounted, really cheap missiles that can take out a tank or something. So for providing that to a human force in Taiwan or the Ukraine, it's exactly what we want to be sending people to deter invasions. So we shipped them three years worth of inventory. The Ukrainians blew through it in three a week. So then they're a senior and CEO basically came out and said, you know, hey, Biden administration, and you want more stings and javelins, but one, it'll take us a year or two to spin-up manufacturing. Secondly, we don't know how to make some of the components anymore. So basically below that veneer of product, everything else is a complete disaster.

And I think because of the flashy products and, you know, you're making like a really incredible fighter jet or drone, people think it's super advanced under the hood. In reality, it's a bunch of people in garages making components that look like they're out of the fast and furious, too. And it's all duct tape and spit. Yeah, I mean, you use the word insane, but it really does. surprise me to hear that there are these examples. And it also sounds like these examples are not unique. I heard in a couple other interviews you mentioning that 50% of F-16s are grounded because

they don't have the requisite parts. Or I think you gave another example of the International Space Station, something happening to it, a hatch getting jammed, and then a similar phenomena happening where they had to like go and hunt down a piece of paper. Can you tell that story? The F-16 one is the scariest. But basically, if you look at the DOD these stats, more than 50% of the F-16s are grounded. And it's mostly because they can't maintain them. And it's mostly because they can't get parts. And what ends up happening is they end up catalyzing other planes for parts. And that makes the problem worse and worse and worse because of this advanced manufacturing supply chain issue, which is not a COVID issue. It's not an inflation

issue. It's been going on for years. It's just now that it's coming to the forefront as more and more people are realizing how important defense wasn't is. And the space station one is hilarious. So there's So I'm going to get some of the details wrong here. So if anyone from NASA is listening, I apologize. But basically, the hatch at the space station gets jammed. And astronauts want to know how much force they can apply it on jam the hatch. Because if they apply too much force and they snap it, like, you know, it was screwed. So, you know, they ask NASA, what's the spec for this hatch component?

And it takes them several days to figure it out because there's no, there's no record of that part. And eventually they find that the guy that made it 20 years ago or whatever is retired. And as the story goes, you know, they find the drawing at his desk drawer from the paperwork that they managed to save when the business got shut down. And that was how we knew how much force to apply to the bay door to get it open. And for something as advanced and symbolic as it's an actual space station, like, that is the ground floor reality of how the supply chain works, which is, yeah, completely bonkers. That is bonkers. But this, as you mentioned, didn't happen overnight, right? We didn't wake up one day and have everything broken.

So what's happened in the last couple decades? if we trace back all the way to when some of these things were being created decades ago during the first space race, what happened between now and then? You know, in the US really won World War II because of manufacturing and logistics, not because we necessarily had the shiniest missile or whatever. What ended up happening is we had a really good aviation industry. We had a really strong automotive industry, and we had a really couple of strong, like, core manufacturing industries

that we could very quickly retool to missile production or fighter debt production or something like that. After that, through the financialization of everything in the late 70s and the 80s, basically the corporate incentive outsourced everything to lower-cost countries like China, where we basically sacrificed robustness for profit and loss optimization. And through that, we drove a lot of manufacturing out of the country. And what people don't realize is that when you do that, you don't just lose that base layer manufacturing of the cheap stuff. You lose the skill set and the culture that people know how to manufacture things.

when we need to retool it to semiconductor or we need to retool it to defense production or space production, that talent base and that capacity just simply doesn't exist in the system anymore. Part of the reason is cost plus manufacturing, just because everyone's been so fat and happy in defense for a month time, that flows through the supply base and really, if the government can't really do anything about it if you're shipping fighter jets late, then does the supply chain really care about it, but a base layer? So culturally, basically, the entire industry is tooled up around 50,000.

percent of our promises we break all the time. And once that sets in and that becomes like the accepted norm, then it's really hard to turn that needle another way, both culturally and systematically. And then over the last 30 years, because we haven't really had to fight a great power competitor, we've only been really going up against a bunch of people in the hills or some really small countries or, you know, basically warlord bans. Now that system has really been tested because we can just show up and look scary and people run for the hills. So none of the stresses in the system have been revealed until now where it's really starting to break down rapidly. And it's a bit like, you know, if you don't maintain your personal health

for like 10 years, you might seem fine on the surface, but until you go try and play like a game of touch football or something with your college buddies and you realize that your knee is completely bucked, you know, it's the same type of situation where we think we're fine and it takes 10 years to find out we're not fine. But by that point, the rust is kind of set into the system and we're in a really dangerous strategic position because of that. Yeah, I think the fitness analogy is a great one because everyone can relate to that idea where they're like, oh, I'm totally in shape and they try sprinting 100 meters. And even that is like shock to the system. So it sounds like we haven't kept up. But I think there's also something you've talked about, which is that the people who were involved several decades ago are also starting to retire. So what does that look like? How many companies are actually involved in this space of advanced manufacturing? And what are we seeing there in terms of that almost lapsing? Yeah, so there's something like 20 to 30,000 small businesses that make up the majority of the defense industrial base. And I think just to frame this before I go into the detail, basically if you're making a fighter jet, you're actually outsourcing most of the assemblies like a wing or an engine to another company like Pratt and Whitney.

And then Pratt and Whitney has a network of 2,000 suppliers that give them the components and they might do some engineering. And then so what these companies are actually doing is taking the Lego kits and assembling them and then throwing the assembly up another layer. and Locky finally stitches the whole thing to give an example. So there's about 30,000 or so of these small manufacturers that in aggregate make up the entire defense industrial base, but individually are like small businesses where maybe they have 10 to 20 million in revenue max, and there's maybe 15 or 20 employees. And the danger there is because we outsource manufacturing

and because we culturally decided that if you don't have a college degree, you're worthless to society. there's been no new entrance to the manufacturing workforce because it's not sexy and that's not rewarded in the culture. And because we've had no shocks to the system, no one's realized what a big problem it is. So basically that entire band of owner operators at that $20,000 and $30,000 small business level,

average age of a worker is like 55, average age of an owner operator who's a small business owner that is actually needed to function in the business is 62. So basically, if you switch back to the first space race, or the Cold War, there's a bunch of 30-year-olds that went inside of businesses, and now 30 years later, they're 60s, 62. And because we're not rewarding culturally being in manufacturing, all those people were relatively successful,

so the sons and daughters got a college degree. So they didn't want to take over the business. So basically we have this problem with the entire defense and space and semiconductor industrial base is on this House of Cards of 62-year-olds that through no fault of their own are retiring, there's no one to take over those businesses and also the knowledge that is used to make those parts is not like in some GitHub or something

where they can pass it onto Lockheed and say, hey, someone else can go make this part. It may or may not be written down or recorded in their business. It's mostly in some two or three people's heads that have been making that thing for 10 years and it is complete art. So, you know, regardless of capital or talent, the IP or the knowledge of how to make that component

is not even fungible or transferable. So you have the situation where it's not just a matter of throwing a billion dollars at the problem and going out and scaling some new factories. It's like, no, literally there's two guys in the country that know how to make this turbine blade for this engine component. And they're all retiring. And once they retire, you know, good luck. Now there's six months of reverse engineering just to figure it out. And often this is on like specialized equipment. One of the Northrop suppliers, this is a couple of years ago.

There are many, many examples of this. We're trying to move the production of one part from one facility to another. and it was in a different state, right? And part of making this part is to code it with, code it with a coding that makes the component work, how it's meant to work. So it's like a chemical process. And did all the manufacturing engineering,

rehoused it in this new facility in a different state, and they couldn't get it to work for like a year. And they finally figured out that there was a mineral content of the water in the different state that was slightly different and undocumented. So the water as part of the process was different, and they literally couldn't figure it out because you've got these minute differences. in, you know, whatever, like the localized environment, which can all be controlled for it is not

that scary on an individual basis, but in an aggregate, when you think, when you realize it's like $100 billion a year of these parts being produced and it's all kind of crazy, like, duct tape accidents that it works at all, that's kind of like the situation that we're in as a country. Yeah, I mean, it almost reminds me of those memes that are like expectations versus reality. And expectations are like, you have this image of, let's say, like a SpaceX rocket taking off. And you're like, oh, my gosh, look how far we've come. And then the reality behind it is these people about to retire with desktop drawings in their drawers or in this case, like a specific mineral content in the water that's changing their ability to produce these products.

So I've actually heard you use the term dangerous when you speak to the point that we're at in terms of this pipeline and this particular space of advanced manufacturing. And if someone's listening, they might be like, okay, a bunch of people are retiring. some people are not very keen on the idea of us continuing to pursue space. But what would you say to the average person? Like, what's at stake here? What are we going to lose if these people retire? And we don't have these things documented. Unless we solve this problem, I think the country and, you know,

our way of life is at essential risk. I mean, knowledge I give to people is if you're living in a small town or something like that, you know, we've built up 200 layers of abstractions in society. so that, like, you can be an artist or you can be a painter or you can be in finance or in crypto or making video games or whatever happens to be. And the reality of the world is that 200 years ago, you know, we were killing each other over food and it's a miracle in the first place that we're here and that society is relatively stable and, like, the roads get paid. People forget because they grow up in America that it's so successful that, like, they don't

have to worry about having a bulletproof car. Otherwise, if you have more than like a $100,000 net worth, someone in the gang might try and steal your daughter, which for the rest of the world is like a reality, right? But because America is so isolated culturally, you know, most Americans' view of geopolitics is Russia bad. You don't learn those lessons. And as a younger person, you don't realize that unless we, quote, quote, keep the rose paved, like this can all fall over very, very quickly. So if you run the scenario of saying, okay, right now, basically, we are successful because, you know, we are the world's police and whether we should play that role or not, is obviously up for debate,

but the reality is that we are fine culturally because everyone understands that if you fuck with America, we will put a missile over your head and you're dead. Or have we gone to a great power conflict, we have enough logistics and infrastructure to go and win that conflict or release. Be scary enough of that conflict never exists in the first place. And the analogy I like to tell people is,

you know, bar fights happen when both people mispredict their ability to win the fight. And bar fights don't happen for two reasons. one is there's two UFC fighters staring down each other and they both know the cost of a conflict and both the other person is scary so that fight never happens or there's a bunch of morons but there's a bouncer and like he's big and scary

enough that the conflict never happens in the first place but that construct of a bar fight relies on impressions and kind of social trade-offs that like hey enough people have seen their friend getting beaten up by a bouncer so I'm probably not going to even test that assumption that this is a real

thing. Now the reality of course that most police officers and most bounces, you know, are probably incompetent, can probably get taken out by someone relatively competent as a civilian, but, you know, we have enough social construct around the concept that is a really dumb idea that no one wants to take the risk. And it's what I describe it in defense land is a lethality mirage. And a lethality mirage is basically everyone else's impression of you is that you are a 10 out of 10 lethal, so they absolutely are not going to fuck with you.

And then maybe you lose one small conflict and someone, goes well hold on like maybe these guys aren't so scary as we thought they were and in reality i think we're about a three out of ten and the real danger comes when you know a great power competitor finds out before you find out that you're actually a three out of ten so the problem with everyone thinking advanced manufacturing is in a really good place is that we don't go fix the problem because culturally everyone thinks it's fine the roads are getting paved fighter jets get made, you know, if we go into a conflict, we're fine. In reality, we're probably so far away from doing that, but if we have one conflict with China where we expend most of our ballistics

inventory, we might not be able to remake it for like five years, then we're basically standing around, you know, with our hands tied behind our backs. And when there is not one or two great powers in the globe kind of keeping the peace, that's when you get fragmentations and you get despots and dictators pushing the boundaries of what can be done in their country. And then also they see weakness and then they start moving into invasions of other countries and we get back to this kind of multipolar fragmented world. So it really is quite serious. And to go from the state that we are currently in where it's the tail end of Pax Americana and Peace Through Strength to a highly conflicted world is a really scary position. And it's not going to be a matter of like,

oh, we go to war. It's like, oh, we go to war and we lose. And also like, we don't have food. And the American consumer can't buy an iPhone for less than $10,000. or have laptops at all, you know, imagine if GPS went down. Imagine if we just didn't have GPS, right? So there are obvious impacts of that in terms of being able to drive or whatever. But all of the airlines run on GPS, all the train systems run on GPS, our ability to coordinate military conflict relies on GPS. But there are like less than 50 GPS satellites,

and all of those can be shot out of the air pretty easily. And all that's preventing, you know, some adversary doing that and basically collapsing Western civilization in one fell swoop, taking out less than 10 satellites for the cost of maybe $200 million in lasers or hypersonic missiles is the fear that the response from America is so great that we will win any conflict that's put ahead of us. And what our adversaries are starting to realize, faster than we are realizing, is that our lethality is more like a 3 out of 10 versus an 8 or 10 out of 10. As VCs know, risk happens slowly and then all at once. And by the time you realize the risk and it starts

cascading, it's kind of too late to respond. The difference between this time around and last time around was, yes, risk happened slowly and then very quickly in World War II, but at least we had the fundamental culture and infrastructure of a defense industrial base to be able to go, we're making great cars, so let's shift that to making fighter jet chassis and we're kind of okay, and the response time might be 18 months to two years. When you don't have that fundamental infrastructure, you know, the response time can be 10 years and you're in a really serious position where you're caught with your hands behind your back and you can't respond and everyone knows you can't respond and then basically everyone can run around doing whatever they want

and that's how you get the collapse of society as soon as someone realizes the police force were incompetent you get a bunch of bad actors that creep through the system and that's basically a mistake that we're at but not just kind of a localized barfire level but how the globe operates in general so yeah it's incredibly scary and I think people are going to get a really hard wake-up call in the next two years I think he brought up a lot of good points there one of them is this idea of space that many people think is a frivolous endeavor. But what happens in space directly impacts what happens on Earth. You mentioned GPS, but it's also weather. It's also agriculture. It's us understanding climate change. All of this happens within space. But I think you've also brought up the

defense side. And then even if people aren't interested in either of those, there is the direct relationship to manufacturing that happens with, as you mentioned iPhones, but also medical devices, semiconductors, which are in so many of the devices that we use, this is all part of advanced manufacturing. And so I think it's important for people to realize that, you know, even if they don't believe in this idea of American dynamism, which we obviously do, there are direct correlations to their everyday life that will happen if we don't have this infrastructure. Even if you're an EA type of person or, you know, you're a pacifist or whatever, or if you're into climate change or like, you know, pick any industry that you think is important.

Like, good luck running compute on GPT3. If there are no chips or China takes Taiwan and then the only chips you can buy have like a bug in them. You know, like it's it's not that hard to take a line to draw and it's like very serious. I want to understand this idea of onshoreing or bringing some of this technology back to the system in the United States. And what I want to understand here is it sounds like there is a delta between where we are and where we want to be. And how much of that delta is broken down into the investment in the space versus the talent available or the technology that we have available, or even is it just a matter of time for us to catch up? Obviously, it's a multivariate equation. But what would you say are most important drivers or maybe the things

that are underrated by people? Because I'd imagine that some folks might just say, okay, let's just pour a trillion dollars into this. That'll fix the problem. But will it? It won't. And the most important bit is talent. So if you think about software engineering and you want to solve the problem of how can we produce more data scientists or people that are capable of working at open AI or something like that, which is arguably like the top tier of software engineering. The way that you get more of those people is having this base layer of application developers and then front and back end engineers and then more hardcore backer engineers and then SREs and data scientists and maybe you have a million people.

You produce like a thousand really incredible people in these like domain spaces. Like science, knowledge stacks on each other. You have this talent competition. You produce amazing people in these features. fields. Like, US doesn't have the track team that goes and wins the Olympics unless we have, you know, thousands of colleges that are really competitive for track and field. That's how it goes. And to take that sports example, you can't just start from a cult start and say, well, we want to be competitive. We want to go blow a trillion dollars and with the Olympics. It doesn't work like that.

That takes years and years of training. You need to get people when they're 14. You need to train them up. Like, it's a cultural thing. Like, why would a kid want to go do sports in the first place? And in America, we have that problem solved because America loves sports like the Romans did, and it makes sense. So if you think about that from manufacturing talent level, you know, you want to go solve rocketry or defense or hypersonics or semiconductor. It's not a capital problem. It's a, where are the people that are going to go engineer that system and then run that system? And the reality is they don't exist. So what the impact of that is is time.

So, you know, you look at the semiconductor problem and go, how fast can we reach those semifference? conductor. The reality is, you know, the Biden administration gives Intel $50 million. That's arguably the hardest. You know, that's the heavy work division of manufacturing and the talent doesn't exist. You can't go and hire 20,000 people or even 1,000 people that know how to go and execute that construction, how to go engineer that factory, how to go run that factory. They just simply don't exist. And you cannot simply go and train someone up in even three years to go from like junior college, you know, track and field to like winning the Olympics. It doesn't work like that.

You need the coaches, you need the entire cultural infrastructure. So that's really what we lost when we outsource manufacturing in the 80s is there is no talent base that is generative of the genius types of people that can actually go and do all these advanced things. And that is the thing that people don't realize is, yeah, it's not a capital problem. It's a time and investment problem. And you have to have the base layers there to be able to execute the hunt stuff. Yeah, using the fitness analogy, it's like taking the Olympians from 30 years ago

and saying, we're just going to toss them back in and compete in the next Olympics. And it's like, it doesn't really work that way. Or like, hey, we've got these kids and they kind of fit. And by the way, we've got this training program. And in two years, they'll be winning the Olympics. Like, it doesn't work like that. Right. Definitely.

Okay, so it sounds like what Hadrian is doing to solve this problem is a mix between fixing the talent pipeline and also using technology. So let's return to the talent. But how are you using technology to fix this problem? So the way we look at it is there's like five or six core parts of high precision machining. Some are lower skilled than others, but they're all pretty highly skilled. So what we are doing is basically at each part of the factory, developing software, basically grabbing the last smart people in each of those domains that exist and pairing them

with the best software engineers that we can find saying go automate as much as possible that part of the skill. And in reality, you can only ever automate, you know, 60 to 80% of that. Some of it is just like the technology curve doesn't exist. You know, you're like waiting for 10 years of machine vision to catch up. So the job of a startup is to industrialize research or existing technology and apply to a new domain. It's not good. It's not sit there with 40 PhDs and, you know, try and create something that's like high risk. That is like the science pipeline. So we grab, we grab it into great whatever we can and build software around those talent basis to remove the boring stuff, automate what we can, and then the last 20 or 30% where

it's impossible to want to make, we build software that is highly processed driven where we can throw someone new to that role in there. Within 30 to 90 days, depending on the role, they can be trained up into that and have enough scaffolding that if they just kind of follow the instructions, they will like get 90% of the way there. For some parts of high precision machining that is way harder than others, basically we're using technology to solve. the talent problem. And then when we can't use technology, we have to simplify it so that you could hire in someone who has had no aerospace experience and they're making flight hardware for a rocket program in 30 to 60 days. Because for us to scale out to replace the 50 billion,

so let's argue that we can get to 10 billion, you know, we can't go and hire a million machinists. We have to automate our way so that we can go train 100,000. And that is like barely doable, but it has to be a combination of, yeah, solving the talent pipeline. Using automation to basically lower the burden of that talent pipeline problem and then focusing on the areas where calendar scarce or a hundred come by, as well as attracting as much as possible entrance to the new workforce, which is why branding and marketing is so important and speaking about this problem over and over again

because people don't know what's a problem and they realize like, oh, I'm a software engineer at Google, I can actually contribute here. Or I work in hospitality and I can actually get in the fight and help solve this problem is really important from that aspect as well. And that's why the cultural reward system where, like, manufacturing is not really sexy is a huge problem because, you know, unless it is going to sound dumb, but like unless some 19 year old from like UCLA can go basically like

convince some hot girl at a bar that like manufacturing is cool, then like why would they ever go shoot for manufacturing versus going to work for Google at Goldman Sachs, you know? Just as like kick her back to the cultural challenge because unless it's awesome and celebrated, you know, that's a really, really hard problem. Yeah, I actually met one of your, newly trained or currently trained machinists who used to be a copywriter, Everest. I think last week at LA Tech Week. Yeah, Everest is awesome. Yeah, and so it is a fascinating process that you guys are

undertaking to take people who aren't within this sphere and training them up to be machinist. And something I've heard you talk about before is this maybe counterintuitive idea that to actually take the existing systems, you need to simplify them in order to enable these new jobs, right? because you can't train a previous copywriter to be the machinist from 30 years ago that can do everything that that person did. But if you do simplify those processes, that opens up the job pipeline for many of these people to become that machinist. Totally.

And this is something that software engineering has done really well where there's like a clear delineation between SRE, DevOps, data science, front and back end, and different tiers within that. And traditionally machining has often been there's one guy. that does 90% of that whole pipeline themselves. So there's no clear snap-off points where there's a degradation of skill where you can put someone here

and then they learn the next run. It's all one person's sole operating the entire thing, which just doesn't scale. How do you convince the existing machinist to transfer this knowledge? I'd imagine there's some sort of incentive that you need to put into place because, I mean, maybe I'm wrong about this,

but I imagine they might feel like their jobs are being automated. way or that they're being replaced in some way. And of course, some of them, it sounds like they're planning to retire. But how do you actually convince the person who has all this knowledge to want to share it and be part of this new system? I think there's a couple of things. The first one is the smartest and best people know that the industry is due for a transformation and that it's inevitable that someone's going to come along and do this and they want to be part of the winning team not left behind. So that's a big part of it. Yeah, incentives really matter.

And I think culturally in manufacturing, you don't get many opportunities for growth. And there's a bunch of really smart people out there who've been kind of siloed and not given the opportunity to stretch and grow. And I think culturally, they understand that if we're automating one part of the factory, we're not going to suddenly like fire 20 people. Like, no, no, no, go pick whatever else you want to do, you know, manufacturing engineering or CMM or a higher skill level of CAM programming. And I think the other thing is, yeah, incentives really,

matter. And I think we're probably the only factory on the planet outside of SpaceX that is giving everyone in these roles, you know, the same tier of equity as the best software engineers have. Every technician and Hadrian, whether you're packing boxes or whether you're an absolute master of your trade and maybe you're one of the only 20 people left that can do it is being given the opportunity to have probably the only opportunity they've ever had to create generational wealth for them and their families. And with that, you're an honor of the company. And then you're highly incentivized to contribute to the system instead of being like, well, I'm on $40 an hour, and this guy's on $20 an hour, and I'm on $40 an hour because I have this tribal knowledge.

Why would I go and share it? Because that's what, you know, that's the incentive. And that's why, like, oddly, there is no, like, stack overflow for a machining. Because I think it's basically a function of the fact that manufacturing has been an hourly workforce for such a long time, even the highest skilled positions. because then you get this weird, localized competitive set where even within your facility, you're not really wanting to train or contribute to people

because you're putting your own job at risk. Whereas in software engineering, you're in salary, you're in high demand. It's more about sharing knowledge and going as fast as possible. And I think, yeah, that all comes down to culture, but I think that actually gets driven off, like, historical being an hourly position for such a long time with no meaningful equity upside. Because then why would you share your knowledge if, you know, you're just going to train someone up to replace you

or the owner of the crappy factory that yells at you every day of why the pot is like is no longer incentivized to give you an higher, higher, an hourly wage, you know? Yeah, totally. And obviously there's positives and negatives to each of those cultures, but something I've heard you talk about before is you have all of those different roles sit together at lunch or actually meld together in a way

so that there isn't like the software engineers here and then the new machine is here and the old machine is elsewhere. And so can you speak a little bit to that and what you're seeing in terms of what aspects of each culture are being brought together and highlighted? Yeah, I think, and again, we're not perfect.

We're probably the only one's doing it at all, but many, many, many challenges. I think the first one is making sure that the software engineering team understands that the person that's operating is the golden goose and they are the customer and changing that mindset from, oh, there's this internal team that does some function.

And, you know, it's like the customer service team at a SaaS startup, like, who cares, you know, whatever. But if the customers, if it's SaaS customer screens and says we need this feature like everyone knows to go and jump. So making sure we understand that our internal team is the customer of what we're building. And, you know, if they have one hour of downtime, it's a really serious problem. And also their happiness as a user is like a really serious problem. And that creates this interesting dynamic where, yeah, you've got like technicians that are on hourly wage or whatever. And they're the software engineer from Stripe, running around being like, oh shit, this guy thinks my product is terrible. Like, this is a really

serious issue. And that means a lot. The big problem to solve is continually reinforcing it. Everyone's working hard and there are, you know, there are different challenges. And I think people not from the software domain are like, why are you building this feature? And it's like, six months of two software engineers. And yes, I understand it's painful. But continually like melding those communication streams together and letting people, you know, understand each other's worlds is really important. I mean, the ultimate Hadrian employee would be like a person filling out quality paperwork who was also always a software engineer so that like the localized pain they would just go and fix or vice versa. So yeah, there are many, many challenges to getting

that right. But the important thing is to like have some shared pain in both ways and then make sure that the interaction is like operating gives feedback, software engineer picks it up. But the really difficult part is like, this is really painful for you, but it's also six months of software engineering so it's getting deprioritized but like how do you make sure that is actually understood and communicated throughout a rapidly growing organization is an incredibly hard problem and even really simple things like making sure software engineers are out on the factory floor as much as you're really possible sitting behind operators and even doing their jobs where possible is incredibly important culturally and also just for like decentralizing the product learning

I mean there's this classic trap of like you think the product's good and it's not and then whatever feedback mechanism you got is imperfect. So trying to get it down to single-threaded, like the person that's building the automation for this part of the product is capable of actually doing that job and is forced to do that job every couple of weeks and relearn the real user pain is an enormous challenge, but it's probably the most important thing

that we can be doing to maintain that culture at scale as we're rapidly growing. Yeah. I mean, you hear of some companies doing this, like if you work at Airbnb, you're encouraged to stay at Airbnb's and understand the product, but this is obviously a different level of that. Something that stood out to me, though, is you speaking to, obviously, this is a really hard problem to solve.

And I think, you know, people say that anything that integrates into some form of hardware, not just software and bytes, is like playing on hard mode. And I can speak to that as in I've mostly worked in the arena of bytes and even within the marketing sphere. And so within that sphere, you can just kind of A-B-test the shit out of everything. If you're unsure, you test it, right? if you have the right amount of traffic. With hardware, you can't really do that.

And so I'm curious to know, as you're building this company, how are you deciding what bets to take? And also, what signals are you looking for to make sure that you're on the right track because you don't have millions of page views that you can just test to get the signal from that noise? Yeah, that's a really good question. So there are like very obvious projects

that from the outset, everyone knows, are the biggest points of pain, whether it's time or annoyance or whatever it is. And then you can't sit in a room for three years and try and build an automated factory is because you only really know what actually matters and what doesn't matter at all is by running the factory and then being very prepared to rip up half your roadmap and realize that what you've been doing for the last year was an assumption and not reality. So yeah, you can observe a lot of pain. You can observe where bottlenecks appear that you didn't expect them to.

And there are two layers to that. one is like a localized layer like, okay, what is causing this team, this amount of downtime or pain or effort, but then the factory level, what is producing costs outside those localized things? Because in the real world, you can have a highly optimized process over here, but if it's spitting out unclear results or there's some like stochastic variability, then very quickly the factory can go from smooth to chaos and all of a sudden, 30% of the people where the downstream roles are like dealing with the poor outputs of this other thing. So constantly going up and down those layers and making sure kind of each team has the

ability to screen for what they need, but then also having observability of the factory itself and going like, yeah, you guys think the cost is here and it is, but we're not solving it here. We're going to solve it here because that's that that was actually the original root cause of why this issue came across here. And some of that is system. Some of that is just really good foundational operational leadership and, you know, being intellectually honest enough to go like, yeah, yeah, this is not like a paperwork problem. This is because like a customer did this and we need to build a product around here because that's actually what prevents all these downstream issues. I think the other problem that people don't realize

you were talking about marketing data. No factory on the planet has observability. So you can't simply, and maybe like Foxcon does, but you can't simply throw up on a dashboard and go, what is my uptime? Where are the costs for this job? How much labor did we spend on it? It's all kind of swags and like fuzzy mats and people standing around, you know, trying to do time studies, which have their own psychological flaws. So a big part of the technology that we're building is a factory data platform where all of the people and all of the hardware are hooked up to one internal data service so that, and it took us like a year to build this and we're still three months away from having it operationalized so that everyone in the automation team and

operations can look at it and go, oh shit, we actually thought we were really efficient over here, but we're not. And then it becomes much more clear where the costs and the systems are. But even getting to that point is a bunch of software engineering that no one has ever done purely to solve the observability problem. And it becomes much more obvious to everybody where to point resources and where the paint is coming from. Yeah, that's fascinating because again, bringing my experience from marketing, there's so many times where you think something is an issue or some article is going to work or some landing page copy is going to be best and you're wrong all the time. And so if you really don't have that data layer, it's so hard to

tell what's truly going on. And I'm curious to know how that impacts the end customer. So if you're a SpaceX or an Android buying parts through Hadrian, do they get access to that data? And if so, how does that impact that relationship compared to what they're used to experiencing? So those are two good assumptions of potential Adrian customers. Secondly, in terms of the data, What all customers want is transparency and observability. So we had the CEO of a large defense prime in last week. His number one problem for their supply chain team is observability. And there's this metric that they use internally,

which is average number of days before the part is meant to land their shipping and receiving facility that they get notified, it's going to be late. And the average is one. So out of a six to 12-week purchase order or something like that in terms of lead time, the average number of days that they're being notified that something's potentially off track is like basically the day that it's due. And this is a huge cultural problem. It's a huge observability problem. So yeah, what customers want is effectively like

DevOps level visibility that's not muddied by human aggressiveness or, hey, we'll get the job done. Don't worry. We'll pull it out of the fire. So, you know, like the world's best gap chart, basically. To build that, though, you need the entire factory data system to get that data because if you just have, you know, the flex-port strategy in the early days was build the customer portal first and then have a bunch of like analysts just like typing and shipping and receiving data. You can't do that in manufacturing because it's so complicated and you have all these cultural issues of people are always going to say, I'm going to get the job done and that's not because they're lying. It's because like they got white line fever.

They're going to get the job done. We're a couple of weeks-ish away from launching this to customers because it took so long to build that internal scaffolding to give people the data. But yes, Even now we're sending like just Excel spreadsheet summaries of like, hey, here's where we're at in this production one. People are literally responding like this is amazing. No one's ever given this data or whatever, which is from like software land is completely insane. It would be like

AWS not having a dashboard of like what's your SLA up time, which is insane. That's a really hard problem to solve. That's what customers want is like, no, this is the platform. It's the service and we have observability. And then when things do go wrong, you're learning about it an hour after it goes wrong, not six weeks down the track when, like, we have to face up

to the problem when we can't just pass, which seems crazy from around outside the industry, but it's like a, yeah, it's like a magic wand to everybody else in the industry. Yeah, I mean, even extrapolating past advanced manufacturing, I think it's just like a cultural phenomena that we expect these updates, like even if you talk about like ordering from Amazon, people have come to expect my package is going to arrive on this date. And if it's not, I'm going to get a notification and only some small fraction of packages get to And, of course, advanced manufacturing is much more complex. There's many more reasons why you can't have that level of precision.

But it is, I think, like, again, a cultural phenomena that you have come to expect that kind of system. And it's interesting that this is now being implemented within advanced manufacturing. I'm curious to know within the spectrum of Hadrian and your customers, with this implemented, let's say you do get to the point where you have that precision update, what happens you know the obvious thing is like okay a rocket gets shipped on time but how does that actually influence the wider industry does this mean that because things are being shipped on time companies have you know better margins because they operate better and therefore more companies can enter the space or can you speak to like the downstream or you can say like second third

order effects of actually having that system in place yeah so if you if you skip a couple years ahead and like everything's being done through hadrian whether we're building it first party but either everything is being shipped on time or you've got forward warning where something's going wrong. Two big things happen. One is something like 50% of the total cost of a product, like a satellite, for example,

is through delays or inventory levels, which you shouldn't need to have. So as an example, if you think about a Gat chart to build a satellite and it takes 90 days and you do this piece first, that this beats first, and all the parts have to arrive on time. Firstly, because the supply team is super unreliable,

no one is building that Gat chart super tightly. They're building it with about 50% of slack in it because you can't rely on those inputs coming in at the right time. So once we get customers to a point where they know that if we say here is the date, it's reliable, everyone can compress their schedules around that reliability. And because manufacturing time is payroll costs, it's working capital of inventory, It's a build rate.

If you just compress time in manufacturing, you just win on cost. So I think that most of the products will be able to drop their manufacturing costs by like 30 to 50% not because of cheaper parts, but because of the reliability and the ability to compress schedule around that reliability. The second point is Ford notice of errors. So if you have a manufacturing line down because some vendor was giving you a bunch of satellite parts and you expected them on Monday and then you find out on Monday they're not going to come for two weeks.

which happens like 30 to 40% of the purchase orders, that dynamic happens. Then you've literally got people standing around and they can't do anything, which is a huge cost to unto itself. And another CEO was talking to last week, basically, you know, and the way aerospace works is you have an order book

and then you can't book revenue until you actually deliver your satellite or your product or whatever. And they would have had an extra billion dollars in revenue last quarter had more of their parts being delivered on time. Growth is slowing because they can't, meet their order book, not because they're not working hard because the supply chain is a complete mess. The example I would give is like, you know, if you're a back-end software engineer

and you weren't really sure whether you could spin up a new like EC2 instance or not, and like it might take three months, it might take a week, like you don't know. So all of your sprint planning is out the door. All of your like, can I get this product out to the customer compete is out the door and potentially you're sitting around as a back-end software engineer you're like twiddling your thumbs for three weeks because you're blocked on this core piece of infrastructure. So like imagine if, you know, there was no supply chain team and all these smart people could be doing more value added activity versus like calling Bob's machine three times a week being like, Bob, have you put the parts on the machine yet and getting

lied to? Or the aerospace engineers themselves, like not waiting for parts for six weeks and being able to have parts every two weeks and they can like make a test satellite and blow it up and then iterate really, really fast. When I say, like, we can let companies move 10x faster and, you know, lower their cost of manufacturing about 50%. I don't mean because we're cheaper and we are cheaper when we can be. But the main benefit is that you have this high reliability infrastructure layers so you can compress schedule around it. And like, that's the huge win is you can make a fighter jet in six months, not 12 months. And that's what makes it 150 million, not 300 million. I'm coming back to this name of expectations versus reality. And you imagine like

these very, very talented machinists and you picture what their job is from the outside. And really, it's calling Bob's Machine Shop three times a week, being like, where's my part? So I think, yeah, a lot of that is illuminating to realize that the supply chain, of course, is complex. But with the use of technology and training the right people can be simplified. Within Hadrian itself, what would you say the key risks are? So this paints a really, really interesting picture of what we can do to solve the problem. But if Hadrian were to fail, why would that be? Would it be financing? Would it be, you know, a miscalculation on how complex some of these systems are? What do you think, you know, some of the key risks are? Yeah, I think the broad risk of Hadrian is that it's just

unbelievably complicated. And if one piece doesn't work, then the whole thing doesn't work. So the execution, you know, it's a complex coordination problem to take a teal meme. I think the second problem is as the business grows, the reality, the truth-seeking of, like, is this automation possible within X time frame and how we're planning and kind around that is really, really hard? Because you have to make sure that people are being realistic around. Are we actually saving time with this? Or did we just build scaffolding for this process? Which is totally fine. You can't really build automation until you have the scaffolding in the process. But recruiting cycle is someone highly skilled, it might take three months. And as you're growing revenue in an exponential

monthly rate and you're booking customer sales on your ability to deliver that and you're expecting the automation curve to go here and intersect your hiring plan here and the automation curve turns out to be here and you have this gap. It's not as simple as, hey, we're breaking even on this part of the project. Let's just put more labor into it for another 12 months because you can't hire into that gap for three months and then you're behind the April and then customers so the prediction of when projects are going to land and when things may or may not be industrialized as a new piece of automation or process is really, really hard.

And then I think the third big risk is in manufacturing, if you have a bad process and a bad process, maybe is like something that generates an error more than one out of 100 times, that's not like a mistake. It's like, okay, now this has downstream impacts on schedule or, you know, this machine is down or whatever. If you scale before there is a level of error-proofing that lets you scale, you end up scaling to a point.

something was happening once a week now happens 100 times a week and there's so much negative work in the system that like yes not only do you make no money but then like you're chasing your tail and now you're behind on everything and you stop this like really dangerous kind of like negative spiral of negative work and I think having the discipline to understand what that point is and continually say no to customers even though they really want stuff which is really exciting and like you know I want to grow a massive business so I also want to scale as fast as possible but if you go too fast before you really ready to scale and have that level of error reduction, you can basically blow yourself up and you won't even know what's happening until the last minute. Once you've told customers you're ready to go and you're ready to scale and then you blow up a production order and you break the promise that like, hey, we won't ever have a launch delay because of us. Then you'll lose the magic, right? It can basically survive infinitely as long as you hold the magic. So that is something that I think about a lot is when is the right time to push those buttons and what level of scaling can we do now versus how do we need to be disciplined around error?

reduction versus shooting ourselves on the foot. Yeah. I mean, every company deals with some amount of technical debt, but you're right that hitting that scale button too soon can really exponentially increase that amount. One of the things that I think you explored originally when you discovered this problem was, okay, a bunch of people are retiring. These machine shops may go out of business. Why don't I just acquire them? Why don't I do like a private equity play and just acquire these shops instead of doing what you've done now, which is more so build the technology, train individuals to service them or almost like absorb that intelligence. So can you tell us a little bit more about why you pivoted there

and why you didn't go with that original approach? One of the things that, you know, you don't really learn until you're in the weeds is every piece of hardware variability, whether that's a different machine or a different cutting tool or a different vice or piece of workholding, every new combination of those things that you add on to kind of like the search space of the problem has a non-linear impact on the software engineering complexity that you need to build to get to a level of automation that actually solves a problem versus just, hey, you're 20% better than your competitors, so you have a great private equity roll-up.

It wasn't until I was in the weeds of that problem that I realized that most legacy machine chops have one of every machine ever made, and even within, you know, they have 20 machines, five of them might be the same, but even those five are set up a completely different way. and that adds this enormous non-linear complexity in terms of the software automation that you have to build on top of those systems to the point where it's close enough to impossible that you can call it impossible

and you can squeeze out some margin of improvement, but you would never ever, ever get it to the point where it was a scalable system or it was repeatable enough that it was, you know, going to solve the problem at the kind of multi-billion dollar level that I want to solve the problem at. So that was the core reason why you have to build, you have to build this,

from scratch hardware hand in hand with software hand with processes is so you're making those localized tradeoffs and you can standardize the physical world to be able to abstract it into software to be able to abstract that into process. And now that we have the base of that with clear line of sites, what that looks like at scale, then we're actually going back into acquisitions because then we can reliably say to customers and machine shop owners who want to exit is one, we actually know what we're doing now. Secondly, we have this standardized system. So to transfer a legacy machine shop's parts to Hadrian, there is a process, whether it's a new customer order or whether it's an acquisition, it doesn't matter. There is now a

clean funnel of which this can be done. And then in terms of training and re-skilling, some of these people that we acquire might want to stay on for the journey, and that's great. And now we have this kind of integrated system where we can plug them in and they can learn new skills and they can be like a part of the winning team. But without building all of that from scratch, you never have that core of like, what does great look like? And then how can you, you know, merge people into that. Starting from an incredibly divergent hardware base and process base, it's almost impossible to go in and clean that up both culturally and then just like systematically. You're like, cool, now you're doing 200 hardware integrations instead of three. It's just like,

it's impossible, you know. Yeah, I mean, the complexity is, is hard enough within one, one of those shops. Something that I noticed on your jobs page is that you have around 20 open jobs at the moment. It's always changing, but there are so many different types of jobs as well. So there's data scientists, there's mechatronics engineers, there's security officers, there's salespeople. We talked about the importance of marketing within this space as well. I'm curious to know across the spectrum that you're working in, what talent is most needed right now? Are there specific types of folks that you just wish there was like 10x more of, everyone? Yeah, and the reality is it's everybody.

I think if I had to wave my hand, I would say, give me 100 software engineers that worked at a startup. worked at big tech, but actually have an aerospace engineering degree and did an internship with Boeing. Because where we see people go the fastest is they have high context around what the real problem is, versus having to kind of like learn the ropes on what is manufacturing, what is aerospace engineering. So that would be like the magic wand, which obviously doesn't exist. I was going to say how many people fit that bill? Three. Handfuls. Yeah. Handfuls. The factory talent is, yes, we always need more people, but there's no like one critical talent base where we're really, really struggling.

I think in terms of automation, yeah, we just need all hands on deck. And I think what people don't realize that we struggle with sometimes in recruiting or at least have to overmessage to make sure people understand is that you don't need a hardware manufacturing background to come into a business like Hadrian or SpaceX or Anderil to be able to be a competitive candidate or create value. you know, with your software skills. A lot of what we're building looks and smells like enterprise SaaS, except our customer is internal users, not external users.

And even the deep tech side, it's very close to like, if you're a developer that's been working on like Unity and building video game, you know, geometry engines and stuff like that, that is very close to the software engineering we're doing internally. And even integrating with the hardware, if you're the type of software engineer that is okay with like reverse engineering, some crappy API, you know, which anyone from like a Rippling, for example, is done with like some crappy payroll API from the one vendor that like doesn't have

it fully documented. That's the exact same problem space. And I would say that tons and tons of software engineers need to kind of get it through their head that it's all just regular software engineering problems. Hard software engineering problems. Don't get me wrong, but that you don't need a manufacturing background or a, you know, aerospace background or a space background to kind of get in the mix and start adding a lot of I love that you mentioned Rippling because I think there are so many examples of successful companies that really just did venture into a space that was surprisingly complex and just document it and simplify it. I mean, I'm a Canadian and using a product like Rippling is so nice. Or, you know,

there's other products out there that do the same thing like Workday. But the idea is that I just have to click a bunch of buttons and say, are you an immigrant alien? Are you not? You know, what state are you in, et cetera? And it just outlines the process for you. And I think that's a nice parallel because many people have probably used tools like that before and imagining a parallel within advanced manufacturing of, of course, this stuff is incredibly complex. But if you can simplify it for the end customer to just understand, okay, I'm going to get it exactly on these dates. And then internally, what are the key steps along that way for us to map out and insert automation where possible? That's a great example. Is like, you know, a HR rep to do that

without rippling is 20, 40 hours, and you still need a HR rep to do that job, but it takes them 30 minutes, and, you know, they're not filling out forms for like 40 hours a week and, you know, drinking a bottle of wine at night because they're seeing a filling out 40 hours of forms a week. And it's the same. It's like, we're not replacing the human and machining. We're just like, hey, click three buttons, not click 20 dumb buttons where you do it a a billion times a week and it's, you know, it's painful. And also click buttons in a nice workflow don't have to like go read the paper manual on like what immigration policy is for Canadian, you know, the Z visa holders or whatever. Because it's all like workflow logic. It's

all a process. And yeah, it's very gnarly to wrap your hands around that entire problem simultaneously. But yeah, that's the game of playing. It's good. Yeah. And using that example too, it's like, to your point, you're not the experts from the space. So if I do have a question of like, what the hell does a resident alien mean? I go to my lawyer and ask them, okay, how should I respond to this? But I only involve them when necessary. And it's the same thing with machining, right? You're only bringing in the expert machinist when absolutely necessary and then simplifying the rest.

Yes, and then the expert machinist can go learn software engineering or they can go learn, you know, harder and harder and harder levels of machining. Or they can just spend 100% of their time on, like, really knowledge. problems that you need an expert for, not like how to program a threaded hole, which they've done for the last 10 years successfully, you know, four times a week. And like, you don't ever have to do that again. And cool,

go solve this other problem and figure out how to automate that, you know? All right. So there are a bunch of different problems that you can attack within advanced manufacturing. We talked about medical, semiconductors, defense, etc. Sounds like Hadrian is focused at least at the moment

on space. And, And as I mentioned before, there are many people out there. There are many people who disagree with this, but there are many people that think that space or pursuing it is a frivolous industry. I'll just read you one tweet for fun from someone that I saw recently that said, no offense, but I 100% think space colonization is a childish desire. So feel free to respond to that particular tweet, but really what I want to get at is within the sphere of things that you could pursue within Hadrian.

Why specifically space to start? the really short version is like Stripe doesn't get to sell to AT&T until they sell to a bunch of white-commodated startups and there's just a bunch of huge amounts of capital flowing into commercial space which means there's a bunch of net new spend and they're being run by 30-year-olds, not 50-year-olds

which, you know, you want to sell the startups at first and you want to hit that earlier on the spectrum. So commercial space has all of the complexity of every other industry that we would want to serve in the future. So the automation we're building for commercial space is almost completely transferable. But there's a real need because these companies are trying to go super fast

so they will pay for speed. You know, if they are sick of calling Bob's machine shop, but they're young enough from all these rocket and satellite companies that they're willing to take a shot on something new and really work with us to develop the system. So it's just your classic early adoptive problem. Then I think holistically is like, why go to space at all? Like, why put humanity's resources out there?

And I think we could go through this argument of like, you know, spaces of warfighting domain. Like you need observability of the planet to stop nuclear law. launches, so you need satellites, like GPS is a great example. We can go through all like the time-worn arguments that like most of the medical advances on the planet have been downstream of NASA and the ISS and how that flows through society and all that stuff. But all of that is an abstraction of like, why, you know, why Columbus? Like, why go jump on a shitty raft and go look at a new island in Polynesia as like a tribal leader? Like in some

ways it's manifest destiny. Like humans are built to expand and explore and that is just like a core drive of the species. And with that sort of an argument, it just comes down to like growth versus degrowth. That is the eternal cultural fight. And you can call it capitalism or communism or you can call it like the state versus the people or you can call it decentralization versus centralization.

But what it comes down to is like, are we going to use the limited resources on a planet to go get new resources so we can continue this magical species-wide journey of like settling the solar system and finding out what's out there and improving our own lives and like going and getting at it? Or are we going to accept the status quo

and sit there and continue to like shoot in a hole instead of inventing the toilet? And all these people out there who are like by stretching towards the future we need to concentrate on the problems of today and what people don't realize is that historically throughout humanity like you solve poverty by building farms

not by trying to optimize this shitty like hodgepodge hunter-gatherer system that we've got and yes, That rewards people nonlinear, the people who are breaching towards that future and, like, you leave some people behind. But that is what takes the ban from here to here, and everyone's quality of life goes up. And at some point, the Earth's resources are going to die out.

And we have kind of one shot in the next couple of decades to, like, expand so that we can get new resources and make ourselves more efficient and start solving all these problems. But these are all, like, platitudes and economic arguments over the internal cultural problem of humanity, which is like, do you want to go and do cool shit and, like, grow as fast as possible and see what's out there? Or do you want to sit there twirling your thumbs because you're scared? And that is the eternal, like, growth versus degrowth fight. And everything that we see in the media, whether it's legacy media or politics or wars or, you know, communism or, you know, crony capitalism versus true kind of jungle capitalism. You know, it's all a

poor abstraction over growth versus de-growth. And ultimately, like, you've got a big side, and I pick growth. And if we're picking growth, then, yeah, let's go invent new technologies and settle the stars and find out to what's out there and mine asteroids for resources instead of ripping up forests in the Amazon. But, like, basically it comes down to, like, expansion or population control. You know, like, at a certain point, it all comes down to, like, we're going to going to cut down trees or going to mine asteroids. Okay, don't want to cut down trees. That makes sense. So let's go, you know, go do something cooler and more sustainable.

a way to do that. But the third option of restricting resources and, you know, this is like a stupid argument of a nuclear. I mean, you know, like, hey, let's not incur some risk of getting totally clean energy that like net net is way, way, way less morally and economically impactful than solar panels when 90% of the solar panels in the country are being made in China by basically slave labor where millions of minority and immigrant women are being chemically castrated every year and forced into servitude. But, so ultimately, it's like growth versus degrowth. And I think, like, the case for space is it is the last frontier that we have.

And you can think about the moon as the eighth continent. And as a species, we're going to go out and get it and continue to grow and improve things or we're going to stagnate. And if anyone's choosing to stagnate, you're on the wrong side of history and, like, you're going to get blown past by everyone else. And I just wish people would frame the problem correctly. It's, you know, it's growth versus degrowth. There is no, like, economic argument.

like you're the fore humanity is an expansive moral species or you're against it and you know you want to like corral us in this bubble where we're just going to compound the problems i think it's ridiculous yeah i mean one other way you could put it of growth versus degrowth is also kind of like a zero sum versus positive sum mindset right like we can pursue space the technologies will hopefully return back to things on earth but also we can pursue space and pursue improving climate change and pursue AI and pursue insert other exciting thing here, right? It's not one necessarily versus the other, although I do think it's really important to point out what we've talked about already several times is that, you know, there's several advancements from space. I was looking this up because we're doing an episode with privateer, but like whether it's like LASIC to like limb replacements, to tires on your car,

like all of that has been impacted by, you know, unsurprisingly, the very tough engineering challenge, which is to build these things in space, return to Earth because it's much easier to actually apply them here. So without going down too far, that rabbit hole, I do think that one thing that maybe is missing, I might be wrong, but is this idea of like a killer app, right? Something that people can understand within the context of space. And I think some people might argue that like satellites are already the killer application of space that we use on Earth. But do you have any thoughts there in terms of whether we already have this quote unquote killer app within space that people can understand and almost like helps them recognize the value.

I think that's a really, really hard problem because a lot of the benefits of space are not the end product. It's like the infrastructure. It's like GPS. You know, sort of like space invented Google Maps or Apple Maps. It's like it's recognizable by like a consumer and they kind of, they kind of get it very visually. I think I don't think there's a killer app and I don't think there will be because it's like,

you know, does your average consumer? know about AWS. Not really outside of our technology domain, but like, can any of the stuff that they love exist without it? Like, probably not. I think there will be something incredible in terms of not quote-unquote first world countries having access to the internet the first time through things like Starlink, which will be really incredible for those parts of the earth, which will become like a killer app because it's consumer focus. It's clearly linked to space. like it's cool, it has real benefits in terms of education and teaching kids things versus having like crappy internet in the Philippines or something like that.

For the American population, I think we're already buried behind so many layers of abstraction and that's like really, really, really hard. I think that potentially it's something in pharma where so much of the cancer or genetic research can only be performed or can be performed like far, far better in terms of materials or chemical research in space. there, if there's a major farmer breakthrough where it's like, oh, we cure the lupus or like, you know, like leukemia doesn't exist anymore. And it's because of the research that happened on the ISS and it's very publicly done. I think that could be a really killer. But I think

the rest of it's all infrastructure. And yeah, so farmer would be a really amazing one. And I can see like a core kind of consumer link to where they really like viscerally feel the impact. That reminds me of, I think my final question, which is just the idea of painting this future where Hadrian is successful, or rather painting a future where there's, let's say, 10 or 30 Hadrian's that are successful. What does that world look like? Does that enable us to go and cure cancer on a satellite or on the ISS? What are the types of things that we might get? And I say might, because of course, there's no certainty with the success of Hadrian or many of them. Yeah, so the analogy I use is for software engineering, we have so many incredible

software engineers and software products, and that is downstream of companies like Stripe or Twilio or Amazon, because they lowered the barrier to entry for creating new companies and running more experiments on what's a good thing that the world needs, from like a million dollars to like $100. Because that infrastructure exists, you get this candoran explosion of randomness. And firstly, the people that exist in the ecosystem can get 100 more tries at building something incredible, and then new people come into the ecosystem because the cost of entry is so low, the cost of experimentation is so low that you get more flood of talent and randomness. So who knows what comes out of it, but it's obviously true that like if you have this

cheap infrastructure layer that enables rapid iteration and lower barrier cost to do an experiment on to launch a product, you get this cambering explosion of like madness and then amazing things come out of it. And who knows what they are? But, you know, who could have predicted that downstream of Microsoft Azure is like Dolly 2. I don't know, but like, without that compute letter existing, none of that would exist, you know, so who knows? Self-traving cars are all downstream of cloud computing or all downstream of like elastic infrastructure layers.

So what I hope happens with Hadrian is apart from speeding up the current companies making rockets, satellites, jets, and drones, an order of magnitude so they can move faster on the duration pace. We automate this so much that it's basically like flicking the switch on. AWS and spinning up a new, you know, like East Coast instance and starting to tool around with something. And by lowering the barrier to entry of complex manufacturing and making it cheaper and making it accessible through an API, we should see two things, which is the smart people in the space get 100 times more experiments and new entrance to the space don't have

to go and work at SpaceX for 10 years to figure out what the hell is going on and then go start something, they can kind of drop into it straight out of college and have this manufacturing platform that enables them to like rapidly iterate on whatever they want. And all of the sudden we see this, like, ridiculous explosion of, like, who knows what, hopefully so much so the FAA is just chasing their tail, trying to, like, stop kids launching, like, satellites off the roof of their houses, you know? And that's, that's, like, the generative property that would be a real success case for us is we've built this kind of Archimedes leave rover company that by building it, we've, like, generated all these huge second and third

order impacts in the world. And yeah, yeah, I mean, like, apart from helping the defense prime scale and, you know, bunting heads of the CCP, it's going to be amazing and a couple of years to see a bunch of engineering grads tooling around at their garage and like seeing Google style startups happen without $40 million in funding just to get off the ground because they tap a button, pass your off the next day through an API and then they're like experimenting and then who knows what happens after that. But that would be the huge success case for us is that we are the enabler of that like kangrian explosion of talent and randomness that produces all these wild and crazy experiments in the physical world and lowers that barrier to

entry so that we get ourselves closer and closer to the Jetsons flying car future versus, you know, getting stuck where we are out today. I love that because I think maybe it's hard for people to imagine that, you know, Joe Smith in his garage is going to go create a space rocket on his own. But if we actually look back a couple decades ago, the idea of someone publishing online, which now we all do, as long as you have an internet connection, was not democratized, right? I think the first blog was in the 90s and you had to spin up your own server and you had to understand

how to do web development and today it's like you know you pull up your phone you have your Twitter app or your own substack or whatever it might be and we can all participate and it does create this like

infinite ecosystem on both supply and demand and it'll be fascinating to see if we can achieve that on the hardware side and specifically within space so that leads me to my final question which is just I think

this work is really inspiring it inspires me to imagine that future where we have democracy hardware, where people are excited to participate, even if they don't have a doctorate in aerospace engineering. I want to know from you, who is someone that you're inspired by? And what are they working on? Inspired by or like have went from? Could be either. I'll actually share where this question came from. There was an interview that Alex Honnold did on Tim Ferriss years ago. And a lot of people see Alex Honnold as this like superhuman. He's, you know, defied the laws

of gravity or at least fear and he's free soloing up these mountains. And so it's kind of interesting to imagine that there may be someone that Alex looks up to in a similar domain of like, oh my gosh, I can't believe he does this. And his answer was this guy, Mark Andrela Clark. If you've heard of the Alpinus, it's a wonderful movie. I won't spoil the ending. But that was kind of like a fascinating thing to understand that this person who I saw and many other people saw as superhuman saw someone else in a similar light. And so I'm curious to know if there's someone that you are like, wow, I can't believe this person is building something. No one's ever heard of them because in that case,

no one had heard of this guy, Mark, Andreela Clark, at the time. So does that help kind of paint a picture of what we're looking for? Yeah, yeah, yeah. What really inspires me is musicians that tool away by themselves in, you know, bedrooms or caves for like five years and then produce these like works of art that are orders of magnitude better than anything that like, you know, publishing studios get out. And whether that was like Boston in the 70s

where literally everyone thought they were in a real rock band. It was like one guy that not only like wrote the music, wrote the albums, played all the instruments, but then half of the recording equipment he custom built himself. Purely just to like get his work of art out there, stuff like that is inspiring to me, not because it's like a single human, like, you know, I am nothing without the team.

But it's because it's a reminder that these mythical heroes exist. And like people from non-college, educated backgrounds or like completely outside the system are still there are still there toiling away and like humanity is still got it. It's not a like cattle mill of people coming out of education and going in like clicking buttons on computers at Google or open sacks or whatever. Like we've still got this like incredible ability to go off and do random things. Other examples is like I'm obsessed with these random like YouTube building videos where some like nutcase like convinces his wife or whatever. They're going to like build a cabinet

in the woods or whatever and he has no construction experience. and he, like, does it and it's awesome. Those things are what inspires me, not because of the, like, singular genius because of just, like, the doggedness of getting the job done and also, like, the sheer idiocy of being like, yeah, I've never done this before. I didn't even know what the music industry is.

I'm just going to, like, do this album and toil away at it for, like, eight years and hold myself to an incredibly high standard and, like, create something from scratch. And I think why that's important to me is, all of what we're doing is incredibly hard, but it's not that hard. And the way we've built

credentialism into our society is like really bad because it's like most of the barrier to entry to doing something amazing is like psychological. And I try and tell people like constantly as much as I can

like, no, I'm a moron. Trust me. Like this is hard, but most of the trick is being able to take the emotional pain of just hitting the wall with a sledgehammer

until it breaks down, you know? And that's not what we teach people. We teach people you have to have this degree or you have to be born a certain way or whatever. And like 99% of the time except for like advanced maths, that's just not true. You just have to be willing to like get after it and be truthful to yourself and like take good feedback and then like run on it.

So yeah, examples like that are are really inspiring. And those are the people that I look up to versus like, hey, you're this amazing entrepreneur that's had this massive success for one reason or another. Yeah, it's like perseverance instead of getting it right the first time, which is generally what we're taught. like get an A on the test instead of take the test 10 times, but ace it by the end and really understand the material. And it also reminds me of that famous Steve Jobs quote, my favorite one, and I'm totally going to butcher it, but it's something along the lines of

everything that is built around us has been built by people no smarter than you. And so I think that's a wonderful place to end off on. Chris, is there somewhere that you'd like to direct people? How do they find out more about Hadrian, what you're working on, or anything that we've talked about today? Yeah. You can follow me on Twitter, 2112 power. And if you want to come work for us and manufacture the future, you can email us at jobs at hadrian.com. Awesome. Well, thanks for doing this. Oh, appreciate it. It's great. Thanks for listening to the A16Z podcast. If you like this episode, don't forget to subscribe,

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