00:21:53 · Ethan Thornton
And so Rev two, whatever you want to call it, we have internal nomenclature type two aircraft, will generally be super flexible manufacturing processes that don't scale so well, but you'll get to a full performed mission. And usually, we'll do, like, one or two blocks during this process. So cascade, learn, learn, learn, collapse, cascade, learn, learn, learn. And then a type three vehicle is when you really truly start to optimize the thing for rate. And that... When you understand the system deeply, like, very, very, very deeply, the level of DFM you can do with that thing at the end of the day is so much higher. I mean, for Glide right now, in this factory, we're bringing up a machine that would be able to make 40,000 Glide airframes a month for, like, $7 a piece at an airframe level. Now I'll be clear that product will be a lot more expensive than that because of warheads, because of amniotic, because of different things. You want to do that on the airframe. You want to do that on the the solid rocket motor. You want to do that on the jet engine, but you want to do it in due time. Because at any given point, you only want to be optimizing around one thing in the engineering process. And then your job is to collapse that cycle as much as possible. Because in a lot of companies, that style of execution could take five years. Like, are plenty of companies where whiteboard sketch to first flight is like twelve to eighteen months. And so for us, it's like, how do I get that down to two, three months? I'd say for us right now, that full process for us on average for a product, a year ago, it probably took us on average two years. Right now, we're at about a year. I wanna get that whole process down to, like, two months. And also, along the way, you earn the right to cut out steps of that process, but right now, we gotta, like, eat our vegetables on actually taking the steps. But, yeah, right now, if if we can get it down to a few months over the next eighteen months, we'll be in a good spot. And I'm happy to talk about why that matters. Like, product iteration specifically in defense is the thing that matters more than cost or performance. Go me
00:23:45 · Ty Morse
[00:23:45] S0: to Yeah.
00:23:45 · Ethan Thornton
[00:23:45] S1: Go off on that? So... Yeah. Look. Generally, I think the optimization for The US needs to be asymmetry. I think product performance is great. Scalability is necessary. But, really, what we need to be doing is running math on dollar to dollar, more importantly, CNC machine to CNC machine, technician to technician. How do we stack up in a scaled conflict against Russia, China, Iran? Like, that is the way things will look in this incoming future. And so as we look at China specifically, and your playbook here changes depending on the adversary. And I'll say, I I don't expect us to go to war with China. I think there are plenty of people who work in defense that are super, super hawkish on this conflict happening. I don't think it'll happen, but if we don't deter it, it will happen. And so the reason to do this is you need deterrence, but to achieve deterrence, you have to be able to win a war. And so winning a war does become sort of the optimization function. As you look at this, China, especially in this sort of thing in consumer electronics, has somewhere between three times and two orders of magnitude more of this sort of manufacturing skill. And so what that means is if you're manufacturing the same thing as China, they will win. They will just outproduce you. And so for us, I think the style of winning really comes down to shipping products that for some period of time on the battlefield before China can copy them or engineer a solution against them, can do a specific mission set that creates asymmetry. So if... Let's... Actually, good example, pike. So China right now outbuilds us on shipping tonnage by roughly 232 times. Right? There's a world where we could try to increase the number of ships we build 232 x in the next three years, I would love to see that world. And I think anyone working on that world is fighting the good fight that needs to be fought on some time horizon. I don't think it will close in time. That's where you start to look at something like Pike. One one shipping container can deploy a good number of Pikes from a very decentralized fashion in theater, and I will be able to make many, many thousands of pikes a month. Well, if each pike can take out a small ship and a three pikes can take out a big ship, suddenly, have created asymmetry against China's advantage of building more ships than us.
00:25:49 · Ethan Thornton
Now the issue there is that China will both copy Pike and build a countermeasure to Pike. We're actually working on our own countermeasure to something like Pike, Bing Dart, and I'll talk more about closing both ends of that loop. But then in the process, we'll also be releasing the product that comes after Pike that gets through the Chinese countermeasure. And that is a cat and mouse game, and it's not linear. It's not like you look at, like, one mission set. The mission sets are always changing, and that's the weird thing about defense is in space, you have, like, one optimization, generally, and it's, like, dollars per kilogram to orbit. For us, it's kind of this indimensional chess game of, like, thousands of different mission sets. Are you sensing? Are you talking? Are you shooting? Are you doing logistics? And you're basically trying to sample that space and find specific points where you can create asymmetry. But that asymmetry, depending on how fast China moves, it might last two years, but it might last six months. And the gaps in that asymmetry will continue to decrease as China gets better at building products like this. And so my goal is to build a machine that can just iterate on these products and then have flexibility and vertical integration on the supply chain to actually produce them. I don't care if you have one pike. You need, like, a 100,000 pikes, but manufacturing alone won't get you there either. So you need to be able to iterate faster than your adversary to create that asymmetry in the cat and mouse game while maintaining, and this is the harder part than even engineering, while maintaining the ability to rapidly switch out your production to, within weeks, retool a factory to make the next new thing that is coming down the pipe.
00:27:22 · Ty Morse
[00:27:22] S0: One of the things that you talked about when we were just walking around the factory is you would much rather have a lot of OpEx versus a lot of CapEx. And I think part of that is, like, if you have a bunch of CapEx, you kinda, like, lock yourself into some future. Whereas if you have a lot of OpEx, maybe you can, like, swap things out faster. How do you think about that?
00:27:40 · Ethan Thornton
[00:27:40] S1: Yeah. It's a great great question. So one, I think too many people think of manufacturing as a maximization. Like, there are three manufacturing organizations that are probably all three just as excellent, but almost couldn't look more distinct. Like, if you look at, like, Tesla, SpaceX, and Apple, wildly different approach to CapEx, wildly different approach to supply chain, completely different levels of vertical integration. It's not that one's better than the other. They're just like custom fit for the problem they need to solve. And so for us, it's actually how do you pull the best lessons from each of those three. In defense, specifically, at this period of defense, I think it is nice to have a CapEx light, OpEx heavy business. And the reason for that is for starters, you're constantly in this chicken and egg scenario where you can't win a program until you have the production class, which means you have to pre invest in the CapEx before you have before you have the contract, which is a really, really difficult thing to create a, like, capital stack for the business to do. And so the more... Yeah. The more you can actually take away from CapEx and put on OpEx, you can you can wait for OpEx until you win the contract. Similar, it rhymes. Similar is for the government. If the government is buying a capability and let's say the CapEx is super, super cheap, but I have the same amount I can spend on CapEx. If I'm flexing on OpEx, the product might actually be a bit more expensive, but I can go and afford to build many times the CapEx I would need to deliver on that contract, and that gives me surge capacity. The the hard dynamic in defense across the country right now is how much do you how much do you preposition for a conflict? And this is super, super, super hard. Like, how do you afford as a country to have factories that if a war starts can make hundreds of thousands of things, but the war hopefully never starts? And so how do you minimize the amount you're paying for that along the way? And putting more on CapEx and OpEx here being cutting POs on the supply chain side or more often, frankly, operator hours, provided you can simplify the operator hours. This principle doesn't work if your OpEx cost is, like, highly specific composite technicians.