This Machine Makes Custom Car Bodies in Days | Machina

I was talking with some of my friends in Tesla. A full set of dies for one of the first cars they made was $120 million. With our process, we realized, okay, we can get these robot sheet formers to form sheet metal without any need for dye. Two robots come from two sides. Start pinching the sheet. As you expand, one of the robots starts giving it shape. I would love to live in a world where any great idea can become real. I'm a car guy, so I used to make cars panels with hand. We announced a collaborative work that we're doing with Toyota, enabling people to design a car that's uniquely. They want it to look like. If we make a company that enables freedom of expression in physical world, that's going to be a massive company.

0:00

Today I have the pleasure of sitting down with Ed Mehr, and he is the co founder and CEO of Machina. And Machina is basically building these robots that allow you to form metal in a very unique way. We're sitting next to the, I think, third or fourth iteration of the Franz von Holzhausen. I don't know how you describe that, but anyway, Franzolo. Yeah, Franz Zolo. How did that happen?

0:40

Yeah, no, so we were going to a conference and the organizers of the conference say, hey, in this conference, we want to really honor Franz for all the contribution he has had to the auto industry.

1:02

Chief designer of Tesla.

1:14

Chief designer of Tesla.

1:15

Yeah.

1:16

And he's a great guy, fantastic human being. And it's like we want to come up with something that really captures him in something that's permanent and, you know, it matches his contribution into industry. Obviously he's built all these amazing metal machines. Right. And I was talking to him at the time, to the organizer, I was like, hey, you know, like we've been doing a lot of sculptures, so maybe we can do something around that. And then it was like, yeah, that's a great idea. And then we chat a little bit and the idea of Han Solo and Franz Solo came about. So it shows Franz being, you know, kind of memorialized in a, in a, in a, in a medal. And there's a picture of us giving it to him as a gift. And I think he looked happy about it. I know he was being nice, but, you know, it's a pretty, pretty massive, basically sculpture.

1:16

When you decided to do this in the first place, like, what does that process actually look like from just scanning someone's face or body to actually having it, you know, made in metal?

2:08

Yeah, this is kind of the. Comes down to the core thesis Of Makita. Can you turn ideas into physical reality as fast as possible in the most automated way? Right. So it starts from a design. We feed the design to our software system. Our software comes up with a rough set of instructions for the robots to manufacture the part. Then we send those instructions to the robot. The robot looks at the sensor data every 4 millisecond and I make adjustments. So you have the rough instructions, but online, the robots are constantly make adjustments to make sensor apart in real time. So there's both like an offline component and a real time component. And then at the end, once you're done, the robot scans it so we can look at the final result and compare it to what the design was, make any adjustments we need to do or not. The robot can come up actually a set of adjustments to make the part more accurate. But the whole kind of tool chain, from design and idea all the way to the final physical product is part of our technology stack.

2:16

You mentioned when we were just walking around that it used to take like more than 25 attempts before you got a part or, you know, that was made correctly. How is that, how did that start and how is that kind of evolved over time?

3:15

Yeah. So what we're doing is something pretty chaotic. Right. You know, we call these systems robo craftsmen because the idea is that they can operate like a human blacksmith or a craftsman, a set of robots. They can pick up different tools, then come up with a set of process parameters and sequence of operations to turn an idea, a design, a cat, into a final product. But a lot goes into that. As a human, we're constantly looking at the piece, making adjustments, changing our course of action. So it's a pretty chaotic, high variability kind of process. So we needed to tame that. Right. So early on, we didn't have any data to figure out how we're going to tame this process. Right. That's one of the challenges going from scratch, exactly, in robotic application is that there's not a whole lot of real data out there for you to use to be like, okay, how am I going to find form sheet metal like humans would with a hammer? So we first built a machine and the idea was like, a human will guide it, right. So we come up with some kind of heuristic set of parameters, let the robot do its thing, we look at the results, we make adjustments, go another trial, another trial. So basically it was just human in the loop, but instead of human picking up a hammer himself, the robot was picking up the hammer and doing the work. And we constantly Would look at the data, make adjustments. So early on, you know, one of our early parts we got was from SpaceX. You know, it was a shroud for a rocket engine. And it took us 25 different trials to even get it right. Right. Even ballpark of.

3:27

Right. And what were all the like, issues during those 25 trials?

4:55

You know, like one trial it comes in and depart tears. You know, we just apply too much force in one area and depart tears another. You know, you're going through and suddenly the part in the middle of the forming buckles because of the stresses, another one, you start getting really bad surface quality. It digs into the material and it just doesn't look good. And then even if you get the part roughly correct, then it's just inches off of cad. Because the sheet moves in all kinds of unpredictable way as we're forming it. So a whole bunch of challenges there. So we slowly start adding more and more tool so that the human operator can kind of like, you know, make adjustments that are necessary in a more direct way. Um, and now we are like averaging around four or five trials. The goal is, you know, with enough data, we can build accurate models that like, you know, zero shot it the first time. The robot figures out how to form the part accurately without having to like, do any kind of iteration.

4:58

I think this is like a very novel way of forming a part. Yeah. Can you talk about how the process actually works from just taking a flat piece of sheet metal to actually having a form part?

5:56

So forming is our core operation. Right. Actually, the robots do more than form. They do trimming, they do bending, hemming. Those are some of the things we're working on. Heat treatment. Did you just start with forming was a core operation? Right. But the goal is that the system can do, you know, anything a human craftsman can do. Because once you have that, then you set up a facility of like 20, 30, 100 of these. And now you can program that facility to do all kinds of operations to make all kinds of different, different parts. But we thought really hard about, okay, this is a platform that eventually can do any parts. But where do we want to start with? Forming is, is one of the, I think is the largest metal process sector. Most of the metal parts you see around you are formed sheet metal parts. So and the, the, the traditional way of making formed parts is that you have to make a die. Giant stamping presses. These are sometimes like four story, bu, you know, building size stamping presses. You put two matching D sheet in between them. You apply pressure with the, with the stamping press and you get your part. So and the bottleneck over there is just those dies. You know, a, you know, I was talking with some of my friends in Tesla while back, you know, a full set of dies for a, for one of the first cars they made was $120 million. Right. So you're spending significant amount of dollars to, to get your first batch of die sets, to get your first batch of parts. So with our process we realized, okay, we can get these robot sheet formers to form sheet metal without any need for dye. And the way they work is similar how to a potter form forms a clay bowl. Two robots, they have two stylus finger looking things that are super accurate, very highly rigid, can apply a lot of force. They come and start from a flat sheet that's kind of fixtured in between them. The two robots come from two sides, start pinching the sheet and expanding the sheet. As they pinch it, you know, the same way, you know, you get a, you get a little, you know, play doh and you, you push it from two sides, it expands. And then as you expand, one of the robots starts giving it shape. So it deforms it expands it and gives it shape. And then incrementally over time you, you get to a shape that is defined through software, just instructions sent to a robot. And there's no static die that is required. So complete gets rid of the die matter of hours after your design is done, you can start getting the first.

6:07

Physical part for something like this. When you are doing scaled production of a single car, let's say like the Model S, it makes total sense to invest in that die and buy the four story building thing. But for most iterative working on things and just iterating on a design or process that does not make sense to make a die for. So what kind of initial products did you guys work on?

8:33

Yeah, so yeah, the natural fit is where the design constantly changing. Right. You know, everybody thinks of our application, oh, maybe it's a good prototyping. You know, kind of tool prototyping is great, but I think, you know, we always thought that this could be even go to early production volumes. So we look at applications where you know, they're making few thousand of each design a year, not a million like you would do model Y or some, you know, Ford F150, few thousand a year. But then you want to constantly change your designs after like, you know, you manufacture a few thousand. So aerospace became a very good fit. You know, the number of airplanes that you know, total Being manufactured is a few thousand a year, you know, at best, you know, rockets defense systems. So those became early, early customers. So Department of War become, became one of our early customers to repair their current systems, their fleet. Right. You know, an aircraft gets damaged in mission, how fast can we make a replacement part for a skin of an aircraft, a landing gear door for an aircraft. Instead of waiting four years going making dies, you know, can we get it? A matter of hours. So that was the first application, expanded to more defense applications. Missiles, hypersonics, those are one of our biggest applications today. But then on the commercial world there's a whole bunch of applications as well. You know, we have France Solo here, so we had a lot of art entertainment architecture applications. But my favorite application is actually, you know, I'm a car guy, so I used to make cars panels with hand. So I always wanted to use these machines to make custom cars, to make expressive cars. We announced recently a collaborative work that we're doing with Toyota being enabling people to design a car that's uniquely expressive of what they want and you know, how they want it to look like. You know, being even able going to a website and say, hey, I want a Toyota Tacoma, but I don't want it to look like everybody else's cars. I want the door to look like this. I want my favorite sports team to be formed on the back of the tail again. And I want this unique vehicle. And I think that's another very interesting application we recently started working on and I'm excited for it.

9:00

How did you kind of come up with this idea in particular? Because my understanding is that no one is really doing something similar to this.

11:11

Yeah, so you know, I come from aerospace background, right. I actually have like a unique kind of thick mix of aerospace and software. You know, academically I was on the software and AI side, but I ended up going, you know, more than a decade ago to SpaceX. And that's where I started getting more familiar with the manufacturing. And kind of very early on I kind of realized that like the biggest bottleneck for hardware world is not that we don't have ideas, it's not that people don't want to make all kinds of great products, is that every time you have to build something, you have to build a factory for it. So once I was at SpaceX, I really saw this tangibly, you know, that every factory is custom built for the product you're trying to make. You know, you look at SpaceX's history, you know, now they're a 20 something year old company was founded 2001, 2002. There is two rocket families that has been manufactured. One of them is like halfway there Starship, right? And both of them are building two different facilities, two different sets of tooling, because you have to build a factory every time to try to make a product. So the seed of my career kind of started at SpaceX is like, hey, can we build factories that can make car parts in the morning and then rockets in the afternoon? Right. They're not custom specific. So I got a lot of excitement about 3D printing. So after SpaceX, I spent some time at Relativity, focused on 3D printing. But 3D printing was just, was amazing. But it could only enable certain type of parts in an agile way. And then I started Machina in 2019, really focused on, okay, what is the underlying platform we can make that can do all kinds of manufacturing processes. And to give credit to the people who have been working on this, I mean people have been thinking about this for decades, right? There are people who have been thinking about using robots in an incremental way to do different types of manufacturing operations in universities since 70. Some of those folks, you know, I give credit to, like Jian Chow, Professor Jian Chao at Northwestern, you know, that me thinking about these since 90s and writing papers around them. The key was how can you do it accurately? How can you do it cheaply, right? Consistently, you know, consistently cheap in a cost effective way and accurately. And I think the missing pieces was like cost effective robotics, but then artificial intelligence to come up with the right set of process parameters as a human mind would do. And I think those were the pieces that didn't exist till today. But we certainly standing on the shoulders of a lot of researchers and folks that have been working on this for.

11:17

A long time, working at SpaceX and kind of seeing Elon work firsthand. What do you think is the limiting factor to basically making more Elons?

13:48

I think, you know, it's a good question and I think it's a billion dollar question, right? If a society could make billion elons, I mean like we're gonna, we're gonna be in completely different world. From my perspective, there's two components. One is Elon is extremely multidisciplinary. Right. You know, I think if you have a common knowledge in one discipline, could be extremely useful and revolutionary in another discipline. You have some idea in automotive that everybody knows about it, it's commonplace, and you go to aerospace and be like, oh my God, why haven't we think of that? So thought of that same thing. With software. I think he started in the software world and he captured all these ideas around agile manufacturing, rapid iteration, rapid testing. And then he brought in the hardware world, which was very risk averse world, right? You know, like waterfall planning for years. Nobody wants to take risks, you know, and he kind of combined those things. I remember there were days, you know, in one of the last few months that I was at SpaceX, you know, they wanted to test a Rapture engine, which is the engine that became the Starship's engine. And people were like, this engine is not ready for testing. You know, we're not going to do it. And he was like, just do it, it's going to be my birthday. Worst case is going to blow up fireworks, right? So he also, you know, brought this idea from software world, like rapid iteration, do it really fast. I think that helped a lot. And then I think it also, it was, it was just significant amount of courage that probably got reinforced through successes in the past where like he was just like positive optimist. He was like, okay, you know what, we're going to do this, it's going to be fine. It's going to cost millions of dollars, but it's going to be fine. We're going to figure it out. So there's like that courage of like trying new things and not be scared. I think those two, like multidisciplinary and significant amount of courage to try things. It just became significantly useful in the areas he went into.

13:56

I think some of the ex co founders of PayPal, when he was first starting Space X, they like made a video, a compilation of all the rockets exploding to like try to deter him from, from basically incinerating his 100 million that he had just made.

15:58

I was like, that's fantastic.

16:12

Yeah, yeah. And he just kind of decided to do it anyway.

16:14

Yeah, yeah.

16:17

We were, you know, talking earlier and you said before you basically made your first, first prototype, it cost like a total of roughly $300,000 and you basically got the parts required to build your first prototype with just through very unique ways. Um, and I definitely like to kind of go over what are those? How do you do that?

16:18

Yeah, yeah, you know, it's, I think that's one thing I learned from SpaceX is that make things working as soon as possible. Like don't, don't get stuck in analysis paralysis. Get something out there, try it and see how it works. So when we started the company, you know, we had relatively small seed round at the time. I think we raised like $2.3 million so we certainly didn't have a lot of money to do a lot of experimentation and, you know, a lot of like, kind of thinking through things before we get started. So we were like, okay, you know, we need to in matter of month get some parts forming. And you know, we went to some of our vendors that we use today and everybody has like six to one year lead times before they can even sell us any new equipment. So we're like, this is not going to work out.

16:38

So I try to move at startup speeds. This doesn't work.

17:28

Exactly. So I was like, okay, you know what, I'm going to go to Detroit and try to see if we can buy some used equipment, used robots, used sensors. I was like, okay, Detroit has all these auto companies that use a lot of robots scanning sensors. And I remember I went to this, it's like, I would say like, you know, kind of cemetery of robots. It was like this giant robot and the outskirts of Detroit, giant warehouse and the outskirts of Detroit. And it was actually pretty eerie. You enter and it's this like giant room of dead robots, failure sitting there. And this guy is buying these, these from, you know, from OEMs, automotive OEMs, to just scrap them, right, and sell them for parts. So we went through that warehouse and found like couple that was working. And I think we bought those at the 10th of the price of a new set of robots. And it was immediately available. Just put them on a backup flatbed, send it to California.

17:31

What would normally cost like millions of dollars, cost like a couple?

18:28

Yeah, I think so. I mean, like, you know, we bought the robots itself at the time were, you know, new was like maybe 200k each. And then we bought them for like 20k so like, like 10th of that price. And you know, I ended up also, at the time I wanted to be very cost effective. So we had a very good landlord that was very into robots and he was constantly bringing his friends to show the facility that we were working in. And I'm like, hey, you know, you know what would be cool to have in your facility is a couple of robots. And he was like, yeah, that would be great. I was like, hey, if you want to chip in, you know, for half of the price of the robots, I can kind of like give you more equity. And I was paying rent with equity at the time.

18:30

And how did you negotiate that deal?

19:09

We just had a good landlord. I think that he was, you know, he, he and his family, they had a defense company as well. They had a defense industrial company. And he Was really excited about what we were doing.

19:12

So they kind of had some history of like understanding that this stuff typically in the early days of like, especially a hardware company, you need space, but you know, you're ton of cash.

19:25

Yeah. And he. And they were a huge supporter. I was like, this is cool. I want to be part of this, this next generation of manufacturing. So they were early believers and I think, you know, you know, so that they bought it, you know, they were like, okay, you know, the first year you can pay with equity, buy some of your equipment with equity. But then, you know, the catch was like, you know, I want to be able to bring some of, some of the friends and people that I know to see this. I'm like, that's totally fine. It works out. Yeah. So we were pretty scrappy, you know, a matter of three, four months, I think we put together for her system together and formed part for our first customer, which at the time was Air Force and NASA.

19:33

How'd you end up getting that first customer?

20:11

Yeah, so I think, well, one of the benefits of our team was that we came from aerospace. So, you know, and I spend one year after Relativity Space talking with a lot of people in the industry. So by the time I started the company, you know, we already knew who the customers were. You know, they were like, hey, there's no doubt. We need complex formed sheet metal assemblies.

20:13

Someone's hair is on fire and you can see it and they know it. It's just, it costs so fucking much and the lead times are ridiculous.

20:36

Exactly. And they're like, if you can do it, if you can make it with robots, you can do it faster. We'll buy it. So we had the customers even before we started the company. So it was our own initial network. So we didn't have a huge challenge with the customers. Early on it was mostly about just like, can you actually deliver a product? Which was a big if at the.

20:41

Time when you kind of set out, you know that you have customers and you're going to start this thing, you've got the space and you've got your first or essence of a plan. How did you kind of think through going from nothing in an empty warehouse to actually manufacturing parts for customers?

21:05

It's kind of. Well, now I'm thinking about it, honestly, it was just like one step at a time, you know, it's like, okay, we need to buy robots. Okay, we need to buy robots. We need to put together and weld things together and put stuff in the ground. You really. It was, it was like you know, a thousand steps and start taking the first step and then do it as fast as you can. I think I was lucky that I was able to kind of work with some of the folks that I knew from previous companies of relativity and SpaceX, you know, kind of joined me early on. My interns at Relativity joined me and you know, we were all too, too naive to know that this is not going to work. We're like okay, let's just, or, or it works or not going to work. And we just, we just took the first step and then the second and the third. I just did, you know, do it as fast as you can. So we, it wasn't really, it was just general is like do it as fast as you can, get to the forming part and then just figure stuff out as it comes up. Beyond that really it was just, just tenacity and just figuring problem solving. Right.

21:21

Were there any big like hurdles before, you know, you were able to ship like going into, you know, it's nice to say in like Hindsight it took 25 different attempts to make the first part. But I imagine that at the time, you know, that kind of sucks. You know, you make the first version and you' like holy, everything broke. Make the 2nd, 10th, even 15th and you're like it's still not there.

22:22

Yeah, no. It's kind of funny you mentioned that, but we were just having fun. I remember the first part we made. We gave some instructions to robot formed a part and we were like excited that roughly the shape is there. We're like oh my God. We never thought this is going to work. But it kind of looks like the ghost of the part we wanted to make and that's good enough for us to get all excited. So I think we're just excited to get any result. I remember in early days we didn't even have a full on software to control the robot based on the sensor inputs. So we will actually take turns. I would literally sit or some of the other team members will sit at the robot. And sometimes these builds are multiple hours, right. And we will look at the sensor data and play like we are the controller. We would actually make adjustments to the, to the location of the robots and.

22:43

To make manually, just, just vibrobotting manually.

23:32

And it was just, it was just exciting to go and see how these parts come out. You know, we're not even thinking about oh, it's a failure. It was like, okay, just I would rather, I wouldn't do it. I wouldn't want to do anything else. This sounds fun. We have giant robots that are forming complex shapes out of sheet and we're here to, to play with it. Yeah, to some extent it was just naivete of like not caring about the end results and just pushing through and do the cool thing with the robo. It works, right? And then we will work as much as we could and then we'll get tired and we'll go to sleep and then come back the next day and just keep doing it. Right. We just felt kind of lucky that we have the resources and the time to do this and we don't have to worry about a lot of other things. Right.

23:35

Did you have a similar experience at SpaceX? Because I think you were working there. Like wasn't it 2012 is time frame that was like before they actually landed the first rocket?

24:17

Yeah, right.

24:25

What kind of experience did you take from that to this company?

24:26

Yeah, I remember. You know, one thing was probably very formative for me in SpaceX was we had to do way more things that we had the expertise for in those days.

24:30

What's an example of that?

24:46

Like for example, you know, you know, we might have to do a physics based simulation of a certain thing, certain manufacturing phenomenon, and we don't have the PhD in physics simulation that can do it. And the idea was like, well, who's going to learn it when? Who's going to make a first attempt? And that was a pretty complicated concept for me to wrap my head around because I came from grad school. Before that I left my grad school to go to the industry. And my previous thinking was like, you need to go become expert in one field and that's what you would know and you go try another expert to figure out their things. And to some extent that's true. I mean there is, there's a value in becoming an expert in a field. But when you're working in such a multidisciplinary field, you know, the coordination between the experts is also a whole other set of challenges where a lot of time it makes sense for the first early iterations for people to gain more breath. Yeah, right. And I think that was the unlock for me at SpaceX is like, hey, you can. Anybody can go much outside of their field and learn a lot of other skill sets and start putting the early version of things together. At some point you need experts to come in, but you cannot start with all the experts present in the room. Right. And that was actually like not something I learned in school, not something that was taught to me when I was like a Kid. It was like, I thought like, yeah, you know, you go through school, you become expert in one thing and that's going to be your contribution. But SpaceX kind of broke that for me. I was like, no, no, no, like you can go learn those other things. Right?

24:47

Yeah, there's, there's definitely an advantage and kind of arbit, you know, on purpose keeping the team small and giving like latitude to people to just go own an entire part or process and figure it out. Because then, you know, it's not like playing telephone with three different parties. It's just one person focused on that thing 24 7.

26:24

Yeah. And then you were just thinking about, you know, I mean, not to. I think again there's a huge value in being an expert, but when you're setting something early on up, you know, what is, who is an expert? Somebody who spent four years maybe of their PhD figuring something out. Okay, if I can fast track that, can I learn that in two years if I'm really excited about it? I think that was the mentality I developed a little bit at SpaceX. And I think it's hugely important for these like multidisciplinary startups where you need to know enough to get things going. At some point you need the experts and they need to come into play. But you know, getting over that fear of. Right. You know, like you could learn these other very advanced fields enough to get started.

26:41

I imagine if you're, you're creating something from scratch, you want people that are just like self starters and they're, they're figuring things out. Did you look for kind of track record of having built things in the past or what were you looking for?

27:24

Yeah, I think, you know, bias for action is huge. You to your point, like people who have done things in the past are not scared of trying things and building the whole stack to some extent. Also I remember in early days I would go talk to experts in robotics and they would be like, this is not possible. You know, you're applying a lot of force with these robots. They're going to deflect, they're not going to be accurate. Robots are non known not to be accurate. You know, this is not going to work. And so I started trying to kind of get a little bit disappointed. Okay. These experts maybe are not the good fit to start with. So I think early days, you know, I went back to my interns even like in previous companies, I was like, hey, you guys are about to graduate from school, do you do something? And these guys are smart. High bias for action. But almost all of us were a little bit naive and, you know, to criticize it too much. We were like, okay, this would be cool, let's try it and figure out what's going on. And then that early team came in and then they tried it. They didn't know what the outcome is going to be and it kind of worked. And then afterwards, you know, some of the experts looked at it and I was like, oh, I guess, I guess it could work. Yeah, you know, and now we can, you know, you know, now we can develop it further. But yeah, I think those early days you want really biased reaction. You want really smart people that have a lot of biased reaction and again, to some extent naive enough to try things and not immediately dismiss as, oh, it's not possible.

27:37

Did you have to screen out anyone that kind of had, you know, a huge amount of expertise and looked good on paper, but just didn't. It wouldn't make sense in a real world scenario?

29:05

Oh yeah, I mean, we sometimes screened them and sometimes didn't screen them and they came and, you know, and then later on realize maybe they're not, it's not a good fit for them. Right. You know, it's a double edged sword, you know, you know a lot about certain topic. You know, obviously you can do a lot, but also like, it just kind of cripples you. It puts you in the analysis paralysis mode. Right. Where you constantly double, you know, checking yourself, you know, putting doubts. So we certainly had to screen for it. And sometimes, you know, we hired some folks that ended up realizing, okay, maybe this person was, you know, smart, smartest guy ever, but maybe not the best fit for where we are with as a company.

29:15

I really love Travis Kalnick and he had this thing where whenever Uber entered a new city, he would try to celebrate the city in some way. And I think a lot of what you guys have done is kind of similar to that, where you find some customer and you kind of celebrate the customer. Even with Franz, you know, he's this like amazing designer and has designed cars that millions of people use every single day. And you kind of celebrated him by creating this.

29:56

Yeah.

30:20

What type of philosophy are you taking to that when you're, when you're just making something like a Toyota truck or, you know, Franz statue.

30:21

Yeah, no, no, you're absolutely right. I think, you know, you know, we're. Our long term goal is you have a system that can do all kinds of metal structures autonomously. Right. And that's a huge market. It's a trillion dollar Market, but almost that can become the impediment to actually, like, grow fast. Because now you have too many markets that you can go after. Yeah, right. It's just too many applications. Like, okay, am I going to work in heavy machinery, in agricultural machinery, in automotive, in aerospace, in defense, in architecture, in entertainment? Everywhere needs metal. So to some extent, we were like, okay, we need to make few applications very happy. And what we chose in those few applications were things that we were also excited about ourselves. You know, I loved custom cars. I used to make custom cars. So I was like, okay, this is an application. We're going to go. I know enough where I can have a very good, intimate conversation with our customers. You know, one of the things we did with Toyota, I remember early on in the conversations, the Toyota manager that we worked with, you know, we went into a meeting with other Toyota execs and he was like, like, ed is one of us. Like, you know, he knows cars and he's putting his mouth, you know, his money where his mouth is, and he just wants to love to build cars. And he already built a car for, you know, themselves without any customer. They already have a. That's amazing. It's fantastic, right? So, you know, and the same thing, when we came from aerospace, you know, we were, we were in that industry. We're excited about the application. We could become thought partners. We're not just the supplier, right? We're not like, you call us and then we'll build whatever you want to build. I'm going to give you opinions. I'm going to be like, hey, this is how you should build it. This is, this is how it's going to get better. You know, I've been thinking about it over the weekend, and here's my ideas and my thoughts. And then the customer feels like, okay, you're not just a supplier. You are. You're excited about what I'm doing and you want to be a thought partner into it. And that was a key principle for us to choosing applications we're going into to have a significant amount of knowledge and interest in that application, and then slowly. And each of those applications could become hundreds of million dollars in revenue for us, right? So they're not small applications. But instead of going abroad and just selling to everybody and being kind of this dumb, uninterested customer that just want to sell you a machine or sell you a product, we really wanted to partner.

30:28

Did you do anything that was just purely for your own curiosity and excitement, like making any part that wasn't for a Customer, but just because you wanted it to exist and wanted to see if. If the machine could actually make it happen.

32:48

I think if you. If I asked me, I would always be like, no, there's always a rationale behind everything we. Did. You ask our team, they're probably going to be a lot of times like. And was like, why are we making this? And it's probably what. What he wanted to do. I think, you know, the building the truck was one of that. Right. And then later on end up becoming, you know, help us close deals. But I think that's. That's part of the situation, like part of the, you know, if you're not excited about it, then you can't sell it either. Right. You know, if I just purely making decisions based on logic, then I'm out there and nobody connects with that, you.

33:02

Know, So I think a lot a big part of this is you kind of have to. You have to create a story that other people want to believe in. And the best. The best stories are something that they haven't heard before, and you kind of come up with it in your own head and you just show it in the real world and then they're surprised by it and it resets their own expectations of what's possible.

33:39

Yeah, we made it. Exactly. We made this showpiece. It's SR71. It's the. To me, it's the best plane ever made. And it's very complex shape. You know, it's one of the fat. Is. It is at the time, the fastest plane made. And, you know, I just purely. We purely did it because we were just fan of that plane. The moment we made it, it was just, mark, we want to take to a show. Half of my customers, a lot of them would start calling me. I was like, hey, can I get a version of that and have it in my facility? Because, yeah, you do something authentic, I think people just connect with it and be like, okay, these guys are not here to just make money. These are not here to just make machines. They're excited about this industry. Right. And we are.

33:56

I know there's different kind of schools of thought where some founders want to basically build a company in order to integrate with some other business and then sell that. And I think most of the best founders are basically just trying to build something that will just keep on evolving over time and grow into a massive company. How do you think about that when you're first deciding to start it?

34:35

I don't think I ever joined any company where my end goal was to sell it, you know, at Relativity Space, you know, I drew part of the founding team. That was not the end goal. Same thing with Market Up. You know, I honestly, we didn't even start this company to be like, oh, let's make a profitable business.

34:53

I kind of love that.

35:13

It wasn't really that, right? I mean, I had this kind of remote trust that like if you build something that's cool and useful, you will make money. Right. While we started, I really, what I wanted to do was like, you know, I was really interested in building physical things. And I was like, you know, as a college graduated, in order for me to build physical things, I have to join giant companies. SpaceXes of the world, Hondas of the world, Toyotas of the world. And they're great companies, but I need to be part of this larger whole that has enough resources, can build factories to can turn my ideas into reality. So really at the core of this was like, can we enable expression for people with great ideas, starting with ourselves, with the people who started the company. If I want to build a Franz Solo, how easy can I make it? Right? And I think that was something that.

35:14

You can do at your own company. But you can't necessarily just go inside of a big company and say, I want to make this cool thing and I want to use one of our machines to do it.

36:08

Yes. And I think, and even if you want to do it in those large companies, that means huge investment in tooling and a lot of custom specific machinery and equipment that you have to build to make it possible and just economically not feasible to just do whatever you need to do. So I think, or you want to do. So I think the core really inspiration was, and it still is for this company is like, I would love to live in a world where any great idea can become real. You know, I walk around, I mean, you walk around in the streets, all cars look the same, all buildings roughly look the same. You know, there's not really design diversity in our physical world. So really the core thought was if we, and we make a company that enables a freedom of expression in physical world, that's going to be a massive company. That's a company that's, you know, that's going to define the future. You know, if tomorrow, I mean, any sci fi movie that I watch, there's bajillion cars and hovercrafts and rockets and satellites and bajillion designs of buildings on multiple planets. I'm like, okay, the factories we have today are not going to make that happen. Right. So we need something that's flexible and can do all of these things. So that was really the initial motivation. And, you know, and we loved building things. And then our customers are great. You know, they come in and was like, yeah, we're, we're on the same page. Let's make this h happen. And then the rest becomes, you know, what is your path? You know, in technical terms, we call it go to market. Okay, who's your initial customer and then your second customer and your third customer that sees this benefit until you build that world. So our long term goal is, I think, you know, Machina could be a very large company. A company where, you know, you can, you have some ideas. You go on a portal, you start turning your intention into a design by even speaking to it or working with it through neural network, sorry, neural lace, transferring your intent into a design and be like, hey, I want 300 of that in Hawthorne, California, in Los Angeles, California. And then the right facility gets programmed to make that part and ship it to you. Right. And anybody in the world can do that. I think that's. And that's a, that's a trillion dollar company.

36:14

John Collison has this line, I think he tweeted it a while back where he said, if you just look around in the world around you, everything is so extraordinarily difficult to actually make reality. Even like a bench, like a park bench, is so complex to get, you know, deal with all the regulation, all these, these hurdles. That is effectively just like a universe. You look around and it's just a universe of passion projects.

38:42

Yeah.

39:03

And I think it's very, very positive for any company if they basically lower the barrier to enabling people to make those passion projects.

39:04

Yeah, Yeah. I think, you know, I mean, if you think about, you know, humans, I always think about what does it mean to be human. Especially now. It's becoming, you know, kind of like a more pertinent question with AI and everything else. I think for me, being a human is, you know, we're here to express ourselves in each of us in our unique ways. You know, you're expressing yourself with this amazing podcast that you're making, you know, and that's how you want to define the world. And that's your contribution to the world. That's your expression.

39:12

That's my leverage point.

39:44

Yeah, exactly. And I think, you know, if you can make expression for people easier and easier, it's very easy to put your thoughts now in words, in computer screens, in apps. The physical world still very hard to be expressive in it. It's very hard to have a car that's uniquely expresses you. It's very hard to have a home that uniquely expresses you. It's very expensive, very time consuming to do that. So I think that's. That's a frontier for me. I mean, like, if you think about philosophical frontier is expansion of the boundary of expression. And I think that's what I'm hoping we're doing here at marketing.

39:45

When you first start a company, there's million constraints. Like you said, you raised a little bit of money, like 2 million bucks, and that might be enough money to start, but it's not necessarily enough money to scale to massive facilities that cost hundreds of millions of dollars and deploying huge amounts of robots. So how have you kind of thought about at any given point in time, what are my constraints and then what can I do, like, with maximum leverage on. On the resources that I have available in order to get to the next stage where you have less constraints or different constraints?

40:22

Yeah, it's like, you know, almost. It's like a running list of what is the highest risk to the company. You know, you might have 200 risks to the company. And when we say risk to the company, risk to the company's revenue and survival, right? Like how, how long you can do this and how reliably you can do this. What are the risks to that? What are the dangers to that? And then you kind of create a list and then your job, I think as a CEO or founder is like, rank that list from the most imminent danger to the least imminent danger and then go after that list like, okay, how can I resolve number one? And like, you, literally, you have to be like, almost dogmatic about it. Not care about anything until number one is resolved. Or usually like number one to three because like, you know, there's some fluidity between which one is number one.

40:49

You stack rank the list of fires and you say that one will burn down the building.

41:36

Yes, exactly. And actually I have like, you know, it's on my phone. Like, you know, if you look like it's like they have there, there's like three, four things on the, on the background of my phone that are just the highest risks for the company at each.

41:39

What are those?

41:52

Right now, number one is we need to learn a new forming policy in SIM using AI. I want to make sure finally be able to fully, just in simulation, learn a policy to form a sheet of metal. That's like number one risk for the company that I put on there. Number two is actually talent. Right? Like there's a lot of stuff around hiring, hiring the right people. And then, and then number three is our largest customer that's coming up. That deal needs to close. So those are my top three today. And I think that's just what it comes down to. Right. And be very realistic about what are the solutions to those top three. And constantly iterate until they're resolved.

41:53

I kind of love that because people spend a huge amount of time on their phones and having. It's really useful to know exactly what the biggest problem is at any given time and be like, basically have a constant reminder of. This is the thing I need to be focused on. When you, when you open your phone and you're like going to check Twitter or LinkedIn, the first thing that you see is, holy shit, this customer needs to fucking close or else we're dead.

42:39

Exactly. And I think it's kind of funny because, you know, in a startup you're constantly being pulled in multiple directions. Especially like, you know, as a CEO or as a founder or even executives or even like, you know, high performing engineer. In a startup, there are a million things you need to work on and people are going to tap on your shoulder, right and left and be like, can I do this? And every once in a while I have this. I look at it and be like, okay, I can just not respond to that right now. I don't need to respond to that. I shouldn't. If I'm responding to that, I'm wasting time and it's not fair actually not doing the right thing for the people in the company and the company, even though they might want me to respond to that, I need to let it go. But yeah, I think that constant reminder, it's a go up start to brutally get rid of noise. Right. And focus on the top three most important things.

43:00

So going from you build the first version of the machine and you start making parts with it. How did you kind of go from deciding to just use that first machine versus like making a V2 and starting to scale up and make new iterations on that? Like, what was that process like?

43:44

Yeah, I think it's a combination of, you know, some of this stuff was some of the stuff that just doesn't work. Yeah, right. You look at it and be like, okay, this did not work, so we need to change that. And then. And the vision that you have for the machine long term. Right. So like you're making compromises between the two. You know, for example, you know, again, it goes back to that list of risks should be like you be the first machine you built. You de risk the most important things.

44:00

Yeah, just straight up, will we even build the first thing?

44:25

Can I even form a part with it? Right.

44:28

Was that a question mark in the back of your mind when you first started the first one? Yeah.

44:31

I mean, amazing. It's like, can we put this together and form a part that kind of. Does it even look like a design of a part that we want to form? So that was the first. And if you go to the. We went to the other building that was the first cells. Right. And then once you remove those risks, then becomes risk number two, number three, number four, and start, you know, kind of going through that. So, you know, our first iterations was all about feasibility. Then I think at our second iteration, we started thinking about, okay, if the system works and you can actually form parts and make metal parts in a fast way, the next biggest risk is how fast can we set up factories that can do these things, deploy the system itself, Second iteration was like, it needs to be deployable. Right. So we went from grounded, connected to the concrete, rooted in concrete systems to build out of a container platform that can easily be deployed, because that was a second risk. You can make parts fast, but if the factories take forever to build, then that's the biggest risk. So let's make a system that's portable.

44:34

You've basically got the system now that it can basically fold up and fit on the back of a semi truck. Did you kind of come in with that idea and say, if we're able to put it on the back of a semi truck from day one, like, it will make it very easy to move around, or did you come up with that later on?

45:35

Yeah. No. So I think we always knew. We always knew that the system needs to be easily set up. Yeah, but what was that form factor? Was it like, oh, you can put in the back of truck, Is it a container? Is it modular system that can be easily kind of connected together? I think that was not fully fleshed out.

45:49

What were your other initial, like, ideas of what that looks like?

46:08

I think the other idea was, like, basically the stuff that I said, I think, you know, we did one iteration that was not a container. You could just put it on a flatbed. And then we saw some challenges with it, and it was like, we dropped that design. The other iteration was like, can we make a modular design that can easily be assembled? You put it in a, you know, in ship sets, but then it's kind of like ikea. You go to the other side and in a matter of day you can put it together. And then we realized the system is so complex that's not even possible. So we landed on this container idea. And to some extent, you know, it's, you know, philosophically that was always in the back of our mind, is that any technology that stays with us gotta move with us, right? You know, we are no match species, right? You know, we, we have been constantly on the move. You know, even on Earth, we've been on the move and now we're going to other planets. So any technology is too static, is never going to be able to survive long term. And container was this like unit of mobility. So it kind of made sense afterwards. It's like, oh, you just got to be.

46:11

In hindsight, it made sense, but obviously you can't just know. Looking forward.

47:20

We're trying a whole bunch of different things.

47:24

Going from the first prototypes and starting to make parts. Were there any like directions that you went down where you later realized that just makes no fucking sense and we got to kind of go backwards and retry.

47:25

It's kind of funny, I think it's hard for me to fully pinpoint that because I feel like, you know, we made a lot of mistakes, but I think we tried to immediately fix them like this in designer things, you know, to begin with. For example, when we first started to build our software stack, we were hell bent on, okay, this needs to be really automatable, almost like an API kind of software where it's all command line. It doesn't require to have any kind of an interface, you just feed in geometry into it and the robots get going. And then we soon realized that it's like, oh no, everybody in this space needs to have visual feedback, right? And we build our first iteration of software to be fully command line based. And then we soon realize, okay, this doesn't scale. Among other than a few of us who are nerds about command line, it's just not going to easily scale beyond us. So with the next version, we went more toward like a visual paradigm. So same thing happened in our business development, right. You know, we first, I think, remember in 2023, we, you know, now we're talking about three applications that we are focused on. But 2023, we worked with 30 different brands. 30 different brands, and out of that work, you know, and each contract was like 50, 100k value. So very small values. But we just didn't know who would be the right customer to begin with. So we tried a whole bunch of things and a lot of it just painful and we wanted to deliver on those contracts. Painful industries that were not a good fit for our application. You could make middle structures for them, but we're not touching the real enough pain point. That was like, okay, this is an industry that we can grow into. And the key was like, you know, do it, deliver it, make true on your promises, but then, you know, make an adjustment immediately. So there's a lot of those painful moments, but I think I would like to think of them as learning moments. Right. Less so as like, you know, kind of full on failures.

47:36

Yeah. Jim Balozik from Sing Ascend, which we interview. We both know he didn't read a bunch of business books. He hasn't watched a bunch of lectures or talks. But he kind of intuited the right way to, to run businesses. Or at least for him, like his model of running a business, he's got all these interesting things like when he recycles aluminum and sheet metal, he gets paid in cash by one of his, you know, the person that picks it up. And then he basically like lubricates his business by whenever someone, you know, a FedEx driver shows up a little bit earlier, stays a little bit late, or someone on this, you know, in his factory is, is working a little extra hard and he notices it, he just gives him 100 bucks.

49:50

Yeah.

50:25

And there's these interesting little ways to make the business run better and make people happier day to day. Do you have anything interesting like that?

50:25

It's hard to be Jim. Be Jim and this kind of ideas. I think, you know, food is pretty important. Food, you know, food. Yeah, good food. I think, you know, you know, one of the very early things that I soon realized is that, you know, people have intimate conversations usually around food, around dinner or lunch. And you know, where one thing we started very early on and still kind of stayed on and at Machina is like, we started with like once a week early dinner that we kind of catered to the company, bring everyone together and yeah, just every come in, you know, just the pressure, the work is off. Let's sit down there on table chat. A lot of good points come out of those conversations that are just people casually bringing it up and, and I, you know, now we have like, you know, launches and, and you know, we do, we do happy hours often. But you know, people think of those kind of like little perks as like perks of work. But I think it's actually around, you know, it's a huge productivity lift. Like, you know, how getting people to just like without the stress of work, just sit down and have conversations. Again, probably not as good as what Jim Jim has. That's, that's a pretty interesting way of like, okay, like let me sell my scrap metal and, and reward people. Not as good. But I think, you know, I realized, you know, just lunch, dinner, conversations around food is always very authentic and helpful.

50:32

Going straight to Toyota might not even be the right model because you can't immediately just scale up to delivering a million truck bodies a year. Like, it just doesn't, you can't just snap your fingers and make that happen. So how did you kind of think through which customers at what, what stage of the company would make sense to have the highest leverage and learnings just internally?

52:03

Yeah, I think early on it comes down to a pain point, right. Who has the biggest pain point? Because the earlier you are, the more risk you have. So the pain point of the customer needs to be so big it's willing to take the risk. Right. I think, you know, even though, you know, our company is not necessarily excited, is not necessarily just a defense company, we're excited a lot of other applications. But defense and aerospace, they had a huge pain point because they have high variety of design and huge cost to change things over. So they're looking for agile technology, technology that can easily go from design, one design to another, one material to another. So they become a very good fit. The other piece was. And then later on we went to auto. Auto became a secondary application for us. The other piece really is about, you know, manufacturing is so tightly coupled with everything our customers do. I mean, think of Toyota, think of an aerospace prime. They are a hardware making company. So manufacturing is just at the core of them. We're not like another supplier, like for example, Microsoft, who sells them like this tool, productivity tool. We are the core of what they do. So any changes in that core, they take it pretty seriously. Right. And almost nobody in the company is willing to take a risk to make a fundamental change in the business just by themselves. So what I soon realized was in order for our customer applications to become successful, we need to get a lot of champions involved. The technical guy might come in and be like, yeah, yeah, you guys are a good fit for application, but you.

52:22

Got to have someone internal at those other companies that want you to be a part of their business and want.

54:08

Them to win 10 tech, 10 guys, 10. Yes, in those companies because it's such a fundamental change. So you get the technical guy in and say, okay, yeah, I like it. That become one champion. You need to get the business guy to come in and be like, oh yeah, this business wise makes sense too. So I'm willing to bet my career on this. And then you need to get the, the investment team at the company coming over like, yeah, yeah, we would love to actually. We see the value enough. They actually want to invest in it and get some of the financial benefit as this company grows. You want the, the CEO and executive team to come in and be like, yeah, this is something I want to talk about in media, you know, and.

54:12

Actually advertise with our brand.

54:46

Yes. And you know, like I said, it's such a fundamental change that like you don't need just one champion like you would do with a lot of other products. You need to get five, six, sometimes 10 different champions across the organization to kind of make the change happen. And so that's, that's one of the learnings we had early on. It's like you're not selling to one person, you're selling to the whole organization.

54:49

Yeah. Do you have a like, kind of a systematic approach? I imagine you don't have this day one, but through this like iter, iterative process where you're talking with lots of companies, what's been the approach that you've kind of adopted over time to make this work? If you have have 10 champions before something works, how do you get those 10 champions?

55:12

Yeah, I don't think it's yet a science since art.

55:29

You're putting a brushstroke on, see what happens.

55:34

No, I think it requires, you know, it requires really just talking to the companies almost like, you know, you know, full court press. Almost a strategy. Right. Reach out to investment team, use your connections to work with the executives, make sure engineering teams are super happy and backing you. You know, make sure the business case is solid, help them even develop the business case. So it's really about having a strategy to just make movement on all four or five fronts at the same time with all the team members. You know, you need to have like alignment across your technical team, your business development team, your investment team, your legal team to really push. And it requires a lot of also like external, like our board members, our investors to be involved and kind of make these connections happen, make these conversations happen. You know, have a good marketing strategy. Just make sure the voice is, hear it out there in the right way. So you know, I would say it's a kind of full court press kind of strategy. Right. And in this sports term, if you look at most of our customers, they're investors in U.S. toyota is an investor, you know, Lockheed Martin is an investor, you know, Yamaha is an investor. So most of our customers that come in and also invest in us and that's what we found works in these fundamental changes in these organizations.

55:37

They need to have a stake in your success. Interesting.

56:58

And the beauty is that like, you know, a single manufacturing is such a large industry that a single customer can make or break. Right. Like, you know, a single customer can become hundreds of millions a year for you. Right. If it's fully adopts your technology when.

57:02

You started to kind of build these partnerships and I don't know, building those relationships inside of those companies. Like you said, you basically screen for talent super early and, and figuring out which, which people are going to be a fit of the company. But it also makes sense on the investor side as well to figure out which companies not only are we going to create products for, but also are going to be like DNA aligned. Because every investor or you know, at least that sort of thing is almost like a organ transplant. And if you, you know, that sort of thing can go bad if DNA doesn't match. So how did you kind of figure out which partners made sense?

57:16

It's a good question. I mean, we don't always get it right.

57:48

Have you had to fire any customers and if so, why?

57:52

Yeah, yeah, I mean, like we went, like I said, like, you know, in 2023 we worked with 30 brands. Now we worked with less than 10. Right. But much deeper partnerships almost. You have to go out there and make an attempt, put your message out there, work with people and then also be honest and be like both sides and be like, hey, this is not a good business case for you. This is not a good business case for me. You know, I'm, you know, I'm sorry, let's, let's move on. Yeah, it's, and it's tough because like you want to make everybody happy. But you know, I think, I guess like the lazy answer to a question is got to try it and got to be honest about how it's going, is it a good fit? And then cut it off if it doesn't work.

57:54

Our last interview was with Mehal from Matic and he talked about basically when he announced in late 2023 that they were going to start shipping robots three months in the future, a bunch of supply chain issues happened and basically they got delayed massively. And then by the time they ended up actually shipping the first units, what they did was they couldn't deliver the product that they thought they could. And so what they did was they just sent emails to everyone and said, this is what our product can do and this is what it can't do. And if you want these, this set of, this set of solutions, then we'll ship it to you right now and if you don't wait three months and we'll, we'll, we'll deliver something that actually works for you. Did you do anything like that with customers on figuring out?

58:36

Absolutely. I think, you know, a lot of these things for us, you know, you know, I wish we could be as preemptive about it. Like, you know, like, like you described a lot of cases was like, you know, we went in, we delivered and then discussion and the next steps. Okay, can we do this? And we're like, okay, maybe we can do that in two years, but not today. Right. And that kind of start filtering out a lot of customers again. I think it needs to be, you always want, you know, customers to be having enough pain point that they don't want you to walk away. Right. You know, and those are the customers you want to keep. Right. So yeah, we have to do that. But a lot of times the conversations like at phase two or phase three or phase four of the engagement.

59:16

So you're going to be scaling up massively. Right now we're in factory two. Factory one. How long did you use? Just factory one.

1:00:02

So we moved in factory one in 2020 and I think we fully deployed. We have 11 manufacturing systems. Two of them we kind of like brought down, but 11 manufacturing systems we had by the end of 2023. So we're at full capacity in 2024. We came into the second facility. I think we're going to be fully operational in this facility by 2027.

1:00:09

So they're looking at all the, everything's.

1:00:36

Rung out three year cycles for the facility to start and get to full, full capacity. And then we're going to our next facility this year.

1:00:38

How are you thinking about scaling up? You know, suddenly it goes from we're just tinkering on how this thing works in the first place and now suddenly you're going to actual units to your next facility, I think starting almost immediately and then you'll just scale up over the course of the next 12 or 24 months. How is the business going to evolve and how are you figuring out how to scale?

1:00:46

You know, for us, you know, it became, you know, like I said, we started with a lot of customers, narrowed down to few, and then we start seeing some of those few up even within that list. Two or three are now getting to the point where it's like, okay, let's scale or start making production. Like I said, we're lucky enough. We're an industry. That single customer can get you to a few, you know, tens of million dollars in revenue a year. So we can make those decisions based on the customer commitment. Right. If this aerospace prime comes in and says, hey, I want you to make that uav. And now, you know, a lot of that conversation is also like, gives you like five, six years ahead. Kind of like this is what the volumes will be, you know, where things.

1:01:07

Are going to be going and you can kind of plan for it.

1:01:45

And then we can plan it, plan for it. But that also only happens by us keep narrowing and being more intimately involved with each of the customers. So it gives, reduces the risk of expansion. But once we deploy the facilities with our initial customers, then that facility, that's the beauty of our business, is that that same facility can eventually, you know, service multiple customers. Like, you know, you can start making with this prime first and then switch to automotive application the next day. So we almost kind of seed our applications with the first application. It's the first. Our factories with the first application, but easily can switch to other applications down the road and kind of like, you know, serve other customers.

1:01:47

Interesting. At what stage does it make sense? So you've gone from like 30 trials to three really strong customers. At what point does it make sense to kind of expand back outwards and go the other direction and start doing that?

1:02:27

Yeah, that's something we always talk about ourselves. Like, you know, I would love to someday kind of be like what Jim is for, you know, for some of the other metal structures that we do today. Right. Like he does a lot of good, you know, machining, bending, we do complex metal curvatures. I think at some point I will get be. I would like to be in a place where, you know, anybody can log in into our platform, put an order the same way they would do at send content and get their parts at any volume. So that's, that's a long term goal. I would say probably we are like four or five years away from it. You know, we started from very dedicated customers that have, you know, very transparent needs. And I think at the late stage of the business would be where, you know, we go back wide and now anybody can put any order on the portal and then we can kind of fulfill it once we start having three, four, five facilities that are serving our anchor customers and then we can kind of fill the gap with these smaller, smaller orders and smaller customers.

1:02:37

Yeah, Jim. Jim talked about a lot of the things that he does are, like, non traditional. He constantly talks about, like, I don't want to have a CFO because a CFO will tell me not to do things. But I think the way that he's built his company is he's created an environment where he's going to be really happy day to day, and he's just going to be happy waking up in the morning and going back to work and doing that for a very, very long time. How are you kind of thinking, like, from the start? There's different points in the business, and I think over time, if you do it right, you are having more fun every single day.

1:03:36

Yeah.

1:04:08

Because you're basically eliminating all the distractions that aren't fun.

1:04:08

Yeah.

1:04:11

Figuring out which are the fires that, like, I most enjoy putting out. How are you. How are you designing that for your life?

1:04:11

I think it's. It's an interesting, Interesting approach Jim has. I think, honestly, I'm. I'm already there. You know, I think I love problem solving, and I think I'm excited enough about our mission that doesn't matter what problem it is. You know, I'll figure it out. Right. And I'll dive into it. So. So, yeah, I don't. I don't think, you know, I'm necessarily doing things that I don't like today. You know, even fundraising. I mean, people would say I'm being prosperous, not. Not. Not necessarily being honest here, but I enjoy it, you know, like, you know, I think it's part of the. Part of going out there, talking to people, you know, getting feedback, you know, understanding in what ways what I'm saying doesn't make sense. So I. I don't know. Maybe I'm fooling myself, but I think I've gone to a point where I think I can enjoy every piece of the work that I'm doing, or I've learned to enjoy the pieces of work that I'm doing because it's a funny transition. You know, I'm an engineer by the background, you know, and, you know, used to. Used to make cars by hand, car panels by hand. And I was like, okay, I'm gonna make robots that make car panels so I can do the engineering work to some extent. Sometimes I miss that. But I'm as excited to enable. So that our engineers can do it, enable our engineers to be able to do that and kind of vicariously live through them and learn from them. And so, you know, I think you know, not to give you a fake answer, but I do enjoy my day today, even right now. I think it's just every problem is an interesting problem.

1:04:18

Jeff Bezos has this idea of one way doors and two way doors. And I think the biggest example of that for him was when they were first deciding to do super saver shipping with Amazon and they were deciding whether or not they could basically do a monthly subscription or an annual subscription that allowed you to get free unlimited shipping. And the idea, the risk there was basically that if you give free shipping, then the heaviest customers, the people that use the product all the time, are going to immediately adopt it. And so at the beginning it's going to cost an insane amount of money. And then as you kind of scale down the curve of normal customers, people are just going to use the product more or you know, use the service more, but it's not going to cost as much as those early customers. Has there been any moments during the journey where there has been this like one way door that you had to decide like, do we go through, do we not go through?

1:05:52

You know, it's like rule of both is I, Sequoia has a good name for. It's a kind of crucible moment. He calls it crucible moments. Yeah, we had had few, I think, you know, when we started the company, one of the main things we had to decide on was are we going to sell systems, are we going to sell parts or are we going to sell full on assemblies of metal structures? And the easiest route was to just not make a decision and be like, hey, we're open to all three, let's figure out what's going on. And that's basically to some extent what we did. You know, sold parts for a little bit, we sold systems for a little bit. I think came the moment where we like decided that was like, okay, you know, we need to, we cannot be doing all three right. And it's a pretty tough decision because you know, you have customers who are like, okay, if I stop selling cells, those customers are not going to buy from cells for me anymore. And if I don't stop selling parts, those customers will not buy if start selling assemblies. So we had to start kind of thinking about, okay, you know, one of the most important things for us to be clear about what our business model is. And we need to make that decision, otherwise we're going to be spread too thin across too many ways of serving our customers. Because you sell cells, you need to have a support system, you need to have engineers out in the field supporting your customers. You sell parts, you need to make a lot of them before you can kind of make, you know, significant amount of dent in your revenue. Right. So that was one of those moments, right. You know, one of those moments was like deciding okay, what, what is our business model we landed on? We sell assemblies, right. We actually use our systems to manufacture complex products. We sell those products. We're actually operations companies as well as technology company that builds the robotic system. Now for some of our customers in military, we might deploy and operate these cells in the edge. But for the most part there was a day where we're like, you know, and it's a, it's a tough decision because we're selling like, you know, three, three and a half million dollar cells. We're like, oh, some of the customers want that. We're not going to do that anymore. We're not going to sell three and a half million dollar sales. And this big amount of revenue is scary for our board. It's scary for the customers, scary for our employees. It's like, okay, you're never going to sell through it. It was like, well, you know, I.

1:06:42

Got to imagine you have to, you have to like figure out which incentives you want and if you're just, you know, it's kind of like if, if the aircraft manufacturer also had to operate the airliner, then they probably wouldn't design it so that they make all the revenue on, on basically the plane up and failing. It's the same thing with cars. I think for a long time the, the car model was basically the car would be sold at cost and then all the profit would be made up on the parts when it failed.

1:08:54

Yeah. Yep.

1:09:16

And so with, with this sort of thing you through deciding to just sell the finished assembly, you're, you're saying we're just going to make really great machines that do something very, very well and we're going to own the full stack of understanding is it doing it well and like the iteration loop of we just need to output things that people use.

1:09:17

Yes.

1:09:34

Versus just selling the machine.

1:09:34

Yeah. And it's, it's was uniquely the right path in United States because to some extent, you know, we don't have an industrial base anymore. You know, you don't talk to, you know, aerospace and defense primes. They're like, hey, there are these companies that you, can I go buy my, you know, my assemblies from. They're 100 year old companies. These guys, you know, they don't have any margin to invest in new technology. They don't have any strategic capital to employ. So to some extent they were asking us to step in and become new version of, you know, tier one advanced metal structure supplier. Because if you want to sell into that ecosystem and we could have sold it, but long term they're not in a place to buy advanced technology and invest in it. So it was almost like in short term we can sell to these guys, but long term, like we gotta fix this problem fundamentally we gotta actually create a new version of, you know, tier one metal structure supplier and specifically United States that has been eroded. You know, if maybe it was we were a company in China, we would have made a different decision. But in the United States it may just make sense for us to sell assemblies.

1:09:36

When you're doing a hardware company, a huge part of the business is basically the factory space and the machines that you're actually doing. And you have to make this huge capital investment. At the start you just have to upfront the cost because no one will give you the money. But then over time you have revenue and you can kind of show that revenue and you know, raise debt off of that revenue. How are you kind of structuring so that you can scale most efficiently?

1:10:40

Yeah, I think, you know, one to your point, one main difference between this hardware company and a software company is that your capital needs going to require a different structure. You know, in a software company, simple, you go to VCs, you get equity dollars and that's it. You know, and you build until you build a high margin product, you know, debatably hard margin product, and then maybe you can kind of like, you know, you can become a very successful company, go public and that's it. One thing you learn very fast with hardware companies is that you need a very complex capital structure. You need equity dollars for R and D investments and engineering. But then you need debt to buy hardware, finance your equipment, finance your purchase orders. You need government potentially grants early on to do some early development work that's high in Capex, you need to work with your customers sometimes because these customers have huge, you know, balance sheets and.

1:11:00

They'Re working with the Toyota, it really fundamentally changes. Yes, a million dollars or $10 million to them.

1:12:06

Exactly. In some ways they can finance certain things better than a private equity firm or a venture capital firm or even a bank can finance it. So you need to bring cost money from your customers. You need to work with foreign governments to do foreign expansion. So you almost get this crash course in 10 million ways to kind of finance your business and all of them are relevant versus in a software company or service company. It's just not irrelevant at all.

1:12:11

When you first started the company, did you realize that you were going to have to spend a lot of your or like a significant chunk of your time thinking about this stuff or was that learning along the way?

1:12:39

No, it was definitely learned along the way. I think I was, I was open to it, I was ready to it. But you know, one of the things you said, you know, like, you know, I never thought I'm going to start and just doing mostly fundraise. I mean I enjoy it now but at the time if you were to ask me, engineer me five years ago, I'd be like, ah, no, that doesn't sound fun.

1:12:48

Well, I mean the thing is now is you've actually got a product that you can show and customers and so it's not necessarily the same slog. Yes, as like here's the technical risk and we haven't even done it yet.

1:13:10

Yeah, yeah, yeah, no, absolutely. I mean it's much better positioned in terms of it's much more straightforward to finance it. But still like you know, you build, you need to build that chops, right? You need to build that chops around. What are all the financial products you can use to build your business?

1:13:19

Yeah, what stories would I just never know to ask but are really interesting.

1:13:33

I think, you know, maybe, you know, a lot of people talk about it, but I don't think people tangibly understand this unless there are people in the startups. Like companies at the end of the day is about is people, company is the people. I mean I truly believe this. You know, people think, oh, it's company, the technology is a company, the customers.

1:13:37

Elon literally has a line where he says an organization is just the vector sum of all the like each human is a vector and it's just they need to be all pointed at the same line.

1:13:58

Exactly, exactly. And it's one of the most, you know, us and humans are highly variable. Like you have a lot of interest in, you know, things that we care about and you know, the way we do things. So I think one thing that's maybe underappreciated in most startups is like for the most part is a human organization endeavor. Right. And I don't think people talk about it as much. You know, you know, technology gets developed, you know, fundraising eventually gets happened. Customers come in if you have a useful product. But what makes company great is the people and how excited about it, how mission aligned they are. You know, the feeling that you get Every day you come to the work. You know, it's not really about the task, at least for me, the tasks that I do, it's about who I'm doing it with. You know, who are the people that are going to sit down around the table? Am I going to get challenged by them? I'm going to have fun working with them. I think those are the stories that are often not talked about. What I think probably the most important.

1:14:06

Stories in the company, were there any examples or do you have any examples of your team because you maybe did this right over time where your team was able to rise to an occasion or make something that you believed wouldn't be possible. Possible.

1:15:15

Yeah, I mean, exactly. You know, we made that truck in three months and we had like two or three systems we can allocate to it. You know, initially it was like 50 paddles. We ended up narrowing down to 13 paddles. We needed it. The designs need to complete. People were working weekends, last minute, making decisions around, okay, what portion of a technology. This portion of the feature. I'm just going to turn off and not work on and do a manual adjustment as opposed to relying on the tech stack. Yeah. I think it was impossible to get a vehicle from design to full body panels manufactured and assembled in three months. And we all did it because we had a party coming up and we wanted to showcase the video. So showcase the vehicle.

1:15:31

No better reason than a party coming up.

1:16:21

We need to make this happen for the party. You know, and those are the moments that I think you're all going to remember. You know, all the. And they were not all pleasant. Right. You know, some of it was pleasant, some of it was fights, some of it was, you know, people, you know, being frustrated. But then at the end, it all comes together. Right?

1:16:24

Yeah. Okay, final question.

1:16:42

Yeah.

1:16:45

What's the hardest thing you've overcome?

1:16:45

You know, maybe I'll give you indirect answer and maybe we can kind of dive deeper a little bit and I'll give you any more examples of it. You know, I think startups are probably, you know, building a startup is definitely one of the hardest things. I mean, I've been involved with three startups and just the third one, first one I'm a CEO in, and it's definitely a hard thing to do. And I think the hard piece is around. It's. It's always internal. Right. It's like something inside it is some resistance. You have a lot of time around things when you're wrong, accepting you're wrong when, when something doesn't Go your way. Start pushing against it and figuring out what you got to do next. I think. I guess long story short is, I think the hardest things are those internal journeys that you go through. At the end of it, you become a better human as a result. But you. You feel a lot of resistance.

1:16:48

What were the biggest moments where you felt that resistance?

1:17:45

There are times where, you know, a business still doesn't come through, regardless of how hard you tried. You know, you have five, six months of Runway, and you really make sure that you need to get to do the next fundraise. Otherwise, you need to let big portion of the team go, and you really don't want to hit that deadline. And kind of you start going through the scenarios in your head, right? To be. To be ready for it, to make all those decisions. I think those are the hard moments. A lot of them don't even happen, but, like, in your mind, you know, you are. You're there. You're like, you're making that decision, and you're like, okay, I need to be comfortable with it, because it might happen in a month, right?

1:17:49

And you're running this like a whole bunch of universes may unfold and trying to figure out which one you're okay with.

1:18:28

You know, it's funny. Like, you know, I did this. I had this professor at university that was teaching science of decision making, and one of the things, you know, he was teaching was, you need to be. Always be positive. Like, you need to be. Always think about the best outcome and be positive and send the positivity out there, and then you'll receive it. I end up. I think that didn't really work for me. So what I do, which is kind of the opposite of that. Like, I'd be like, assume the worst and live through the worst situation.

1:18:34

You've just mentally experienced it, and then afterwards, you're like, well, it's already experienced it.

1:19:10

So, yeah, and anything that happens is going to be a better situation. But those moments of mentally going through the worst case, I think is usually end up being the hardest moment, and nobody else also knows that's what's going on.

1:19:14

It's kind of funny. Like, I. I was thinking about this last night before I went to bed, and I'm like. The number of things that I think about where I'm, like, afraid or worried. I don't even know if afraid is the right word, but it's just like, worried and thinking about it, and I never actually tell anyone else. And then I just figure it out the next morning or a day or two later for it. Yeah, yeah, yeah. It's. It's just ridiculous. And. And I. I think, you know, people have this natural inclination to experience a loss twice as much as a gain. And so we just by definition, kind of have to, like, course correct for that.

1:19:27

Yeah.

1:20:01

Because obviously, you know, we're making progress, like, things are moving forward, and, you know, things aren't actually going to shit.

1:20:02

Yeah, yeah, yeah, yeah. Exactly. And also, at the end of the day, I think, you know, you know, we're so lucky to be living in the United States, you know, gone to, you know, gone through great education, you know, have the opportunity. I mean, like, where else you have, like, venture capital, debt financing, amazing talent, and the culture that, you know, and.

1:20:09

Then you get to, like, you get to, like, own your work and, like, own the reward or part of the.

1:20:33

Reward and culture that appreciates entrepreneurship and taking risk. You know, at the end of the day, I mean, we're pretty lucky. And kind of keeping that in mind, that's like, you know, in the worst cases, probably better than most people in the world, it's pretty empowering thing to think about.

1:20:36