An Ex-SpaceX Engineer on Elon Musk, Starship, and Building a $1B-Valued Startup (Scott Morton, Founder & CEO of Revel)

Scott Morton https://www.linkedin.com/in/scott-morton-68334a15 is the founder and CEO of Revel https://www.revel.io, a software platform for testing and controlling complex hardware systems. Before founding the company in 2024, Scott spent nearly a decade at SpaceX building control software for Falcon 9 and Starship. That experience helped him recognize a broader problem: while rockets, nuclear systems, supersonic aircraft, and other advanced machines have grown increasingly sophisticated, the software used to test and control them is often fragmented and decades old. Revel was created to close that gap. The company has raised $180 million, was reportedly valued at just over $1 billion, and counts Impulse Space and Radiant Nuclear among its customers. Its platform scales from small benchtop tests to industrial systems with hundreds of thousands of telemetry channels. Revel has also created its own programming language, RevelCode, designed to combine performance and accessibility with the runtime safety required for high-stakes physical systems. In our conversation, we explore: How AI can accelerate high-consequence software teams without replacing rigorous testing and reviewWhy hardware test and industrial-control software still relies on tools created in the 1980s and 1990sWhat Scott took from Elon Musk about betting on teams before you know the answersWhy Revel created its own programming languageThe “runtime safe” philosophy: what it means and why it mattersRevel’s one-to-many model and the hardware frontiers it’s touchingThe strategic case behind Revel’s $150 million Series BHow Revel’s edge showed up in an industrial-control bake-offHow Scott hopes to preserve Revel’s engineering culture as it scales toward 500 peopleRevel’s long-term mission – and what it means for the hardware renaissance— Timestamps (00:00) Intro (02:04) Why no one will vibe-code a nuclear reactor (04:15) Revel’s engineering edge (05:27) What Revel actually does (06:34) Why industrial software has stagnated (07:52) Why previous startups couldn’t crack it (10:26) The limits of building control software in-house at SpaceX (15:20) Lessons from nearly a decade at SpaceX (20:22) Why Revel built RevelCode (24:46) Will Revel open-source the language? (25:25) Scott’s early projects and builder mentality (32:28) Where his drive comes from (33:50) What Scott took from Elon – and what he chose to leave behind (36:02) Scott’s standards as CEO (38:56) Scaling from small tests to industrial systems (43:40) Deploying Revel and the hiring bottleneck (45:23) How Revel finds and assesses talent (46:21) Emerging frontiers in hardware (49:36) Revel’s unusually smooth trajectory (51:05) How AI fits into Revel’s platform (52:42) Revel’s long-term vision (54:18) Final meditations — Follow Scott Morton LinkedIn: https://www.linkedin.com/in/scott-morton-68334a15 X: https://x.com/scottgmorton — Resources and episode mentions: https://www.generalist.com/p/an-ex-spacex-engineer-on-elon-musk — Production and marketing by penname.co https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

• 0:00Speaker 00

  SpaceX, at least when I was there, the product was getting things to orbit. It was not building an incredible software platform. What we did build actually went viral internally at SpaceX. I talked to a number of other companies out there and asked like, what are you guys using? What are you guys doing? And they were like, oh, man, it's awful. I was just thinking about the future and what is the most impact that I could have? Is that at SpaceX or is it leaving SpaceX and delivering this type of platform for all the other companies out there trying to build incredible machines? Today, Revel provides a software platform for controlling hardware systems like nuclear reactors, jet engine test facilities, systems like oil and gas refineries. One of the biggest keys to SpaceX's success is just that Elon is willing to make massive bets on his team. Even though everyone's like, we have no idea how this is going to work. We started building the catch tower before Starship had ever re-flown.

• 0:44Speaker 00

  Everyone at SpaceX was like, this is crazy. And ultimately, it was caught on flight five.

• 0:50Speaker 00

  One of the best parts of being at Revel is that in one day, you can go to a nuclear reactor company, you can go to the most cutting-edge satellite manufacturer, and then you can go to like a hypercar company. It's pretty cool.

• 1:06Speaker 01

  Modern AI systems have made software easier than ever to build, cooling venture capital investment in the category, and hammering public software stocks. That's what makes Revel one of 2026's narrative violations. A software startup thriving amid the chill. Founded in 2024 by SpaceX veteran Scott Morton, Revel makes testing and control software for companies building rockets, supersonic aircraft, nuclear reactors, and other complex machines. In less than two years, it's raised $180 million, won customers like Impulse Space and Radiant Nuclear, and was reportedly valued at just over $1 billion. In today's episode, Scott and I discuss the hardware renaissance,

• 1:51Speaker 01

  why industrial software got stuck in the 1980s, what he learned from Elon Musk, and why Revel decided to create its own programming language. I'm Mario and this is The Generalist. It's great to have you here. I'm really excited to chat and learn more about you and Revel.

• 2:09Speaker 00

  Awesome. Yeah, great to be here.

• 2:10Speaker 01

  I think one of the interesting places to start is maybe noting the the sense of Revel being almost a little bit of a narrative violation. You know, we live in a world in which the dominant narrative is that AI is sort of solving all software and that every company will sort of maybe build their own systems entirely from scratch. And you are building a software company for the most demanding buyers in many ways in the world. Where's the disconnect that people miss in that narrative that leaves the space for Revel to thrive in the way that you have?

• 2:45Speaker 00

  The biggest thing is that I don't think anyone's really going to kind of bet their career on like vibe coding a control system for, let's say, a nuclear reactor or a rocket engine, or something that's very high consequence. A lot of these, I think, kind of shallow web apps that are very easy to code, I think definitely, I think those are maybe in trouble with the new capabilities of AI. But I think fundamentally, a company is like an asymmetric capability. You have a group of people that are really specialized in this space. And at Revel, I mean, we are fully leveraging AI tools as much as we possibly can. But there is a lot more that goes into software that controls these high-stakes systems than just authoring code.

• 3:29Speaker 00

  We have a full CI system. So what that is, is like a bunch of hardware that we control is in a lab. We have every type of hardware or kind of system that our platform supports. And anytime we do a release, it goes through a whole process that takes several days to make sure that it is all correct. When we release it to our customers, it's going to behave as we expect. Also, vibe coding only really helps with the authorship component. So with our stack, everything, every line of code is reviewed by someone that you have the right person at the company to review it. And so we've seen a lot of, I mean, internally, we've seen a lot of kind of acceleration of our authorship, but not necessarily.

• 4:12Speaker 00

  But there's a lot more that goes into releasing correct software to control physical systems.

• 4:17Speaker 01

  Is there a version of the future where you think, hey, if these models get so good at this trajectory, maybe there's something we have to do very differently? Or will it always just be the case that, hey, yes, those models can keep getting better? That'll just help us deliver an increasingly better system?

• 4:33Speaker 00

  I think so far, what we're seeing, it's only just enabling us to move a lot faster. And then again, we have this, the kind of specialization in the area, like we have people. We're a pretty tenured group so far, actually. We're pretty light on junior engineers. We do want to hire more junior engineers in the next few months. But it's kind of mostly kind of former SpaceX senior engineers. We have several from Palantir and Andro as well. But arming these people with AI, where they really know what they're doing, they know what the correct solution really looks like, just kind of through their experience, has been a huge accelerant for us. And I think it'll kind of continue in that direction.

• 5:15Speaker 01

  Yeah, I think it's part of the reason I was excited to have this conversation is that I think it's Revel feels like an example of what an amazing next-gen software company could look like that you don't want to, you don't want to outsource this capability in. Maybe to take another beat and give folks a better sense of what it is exactly that Revel does, can you sort of, yeah, give folks a little bit of the texture there?

• 5:38Speaker 00

  Yeah, so Revel provides a software platform for controlling hardware systems. Hardware systems being like nuclear reactors. We do rocket engine test sites, jet engine test facilities, and then also kind of industrial-scale systems like oil and gas refineries. And what's really exciting right now is we're kind of moving more in that direction. And the fundamental problem that we're solving is that these, the software in this space really hasn't made any kind of material improvement since the 1980s and 90s. I saw this problem firsthand at SpaceX. To have something great at SpaceX, we had to build it all ourselves. And I was part of the team that did that. And then I was just thinking about the future and like, what is the most impact that I could have

• 6:24Speaker 00

  in this space? Is that at SpaceX or is it leaving SpaceX and delivering this type of platform for all the other companies out there trying to build incredible machines?

• 6:34Speaker 01

  I've heard you mention that, you know, the fact that this the sort of state of play has been stuck in the 80s and 90s before. Like, why do you think that's been the case? And when you think about what's been stuck, has it been truly the underlying capabilities that are stuck there? Or is it more just the interface layer that is, you know, incredibly web 1.0 and just not what people are used to in terms of polish? Or is it both of those things?

• 6:59Speaker 00

  I think just all the software engineering talent got very excited about the internet technologies. You can really just see, it's like these tools that are available really do date back to, it's like 1986 is when one of the major platforms used in test was invented and really hasn't changed much since then. And then 1993 is when the platform that's generally used in industrials was created. And then you can see then 1998, nothing, and then all the way through 2000s. And I think it's really just all the software engineering talent went and worked on the internet. And this space just kind of languished. There weren't really any startups focused on this. There was no real pressure on the incumbents to really innovate.

• 7:40Speaker 00

  And so I think then companies like SpaceX came along and proved that you could do interesting things in hardware. And I think, you know, this definitely Revel is kind of part of a couple of companies now that are really focused on this.

• 7:52Speaker 01

  And presumably, it's also just a testament to how sticky these solutions are, that once they're ingrained, it's very hard to rip them out such that, you know, you mentioned there haven't been many startups in the space. But looking over the last five, 10 years, I've seen a few folks try and take a chip at it. And it feels really hard for folks to make the sort of progress that you guys actually have done. What's that disconnect there?

• 8:14Speaker 00

  Yeah, I had this question. And also, kind of, could Revel have been invented anytime in the last decade?

• 8:19Speaker 01

  Yeah, what's different?

• 8:20Speaker 00

  I think it could have. I really do. And also, I think a lot of the companies that are in our space are similar in that they are actually looking to what SpaceX did. And they're kind of modeling after this.

• 8:29Speaker 01

  This lighthouse finally.

• 8:31Speaker 00

  And I think SpaceX really is, it's like the ultimate proving ground for software, for hardware. They're trying to move as fast as they possibly can. They will make big investments to move really quickly. I was fortunate to, you know, write a ton of control software at SpaceX and then also work on how are we going to do this in the future? And so I think there was just a kind of accumulation of a lot of experience. And then it's that experience what we are taking forward to Revel. It's kind of, it's pretty simple. You need to have this kind of incubator to figure out what the next generation of systems look like. And then, you know, those people can then go and take that experience outside, outside the company.

• 9:10Speaker 01

  So if I have to synthesize it a little bit, it feels like the old set of software, you know, didn't develop because there was this massive talent problem where everyone just moves to the internet. Plus, it's super sticky, so there's, you know, not an incentive to rip it out. Then the few newcomers that come in don't have this experience where they get to see exactly how to build this from the inside of somewhere like SpaceX and learn, okay, here are all these edge cases, and it's tough to get these companies to adopt it unless it's perfect anyway. Do you kind of have a bit of a chicken and egg issue there? Is that sort of a decent distillation of some of the dynamics that Revel was walking into?

• 9:48Speaker 00

  Yeah, yeah, I would add also that SpaceX is this, this pressure cooker. And we were extremely motivated to think very hard about this. And then we had Elon's backing to go and try a few things. And we also had, you know, accumulated like decades of experience elsewhere inside the company. The system has to work. It has to also have evidence that it's, it's accelerating the team. Uh, and I think the combination of those things, uh, is what kind of results in greatness. You need to have the pressure. You need to have, I think, the high stakes situation. And, uh, and then that's how you, I think, discover new approaches.

• 10:27Speaker 01

  Yeah, you, you'll know about this much better than I do because of your time at SpaceX. But reading about the company and about sort of Elon's management style, it feels like, you know, there's sort of maybe a preference to in-house as much as possible, but also a lot of pragmatism where it's like, hey, if we can get, you know, the, the lock from the bathroom door, that's 30 bucks to work on, you know, one of our engines, we'll do that too. What was it about the old software systems that just clearly did not work for what SpaceX was doing? And it such that this kind of an investment was, was actually worthwhile?

• 11:01Speaker 00

  Yeah, I, I actually want to add to what you just said there. I think there's a, this big notion that SpaceX vertically integrates everything. And I, I think it's actually, it's not, I mean, I was involved in a lot of these decisions. Totally not what I, what I saw there. If you were to say, you know, in a meeting where you're trying to decide what to do, like, we should vertically integrate this. Like, you would just be like, like, no one would know what you're talking about. Like, what do you, that's not why you build in-house.

• 11:27Speaker 01

  Yeah.

• 11:28Speaker 00

  You build it.

• 11:28Speaker 01

  It's not axiomatic.

• 11:29Speaker 00

  You build in-house when you look at, and we did a huge survey of all the options when we're trying to figure out what to do for Starship.

• 11:35Speaker 01

  Yes.

• 11:36Speaker 00

  We looked in test. It was like exhaustive.

• 11:39Speaker 01

  Yes.

• 11:39Speaker 00

  Uh, and we came to the conclusion that these were not a good fit for what we needed for Starship. And we, we looked at, we had the massive trade internally. And then, then we started kind of looking at prototyping a few approaches that based on our experience on Dragon and Falcon. What, you know, if we could just go first principles and dream up something. And, uh, and those kind of started to gain momentum. And then finally, we kind of got it across the kind of hump of showing it to other people and getting a lot of consensus. And then it was like, we should go try this. And even then, there were still a lot of like, why don't we just take forward what we did for Falcon? Even then, it was actually very hard, a hard sell internally to actually build it ourselves.

• 12:21Speaker 01

  To zoom into a little bit there and, and, you know, I don't, I don't expect you to go so, so granular. But when you say it wasn't a good fit for, for Starship, like, what exactly were the old systems just like? Too slow to, you know, not capable of doing the kind of testing you need to do it for this type of machinery? Like, yeah, what, what didn't work?

• 12:40Speaker 00

  We saw a number of issues. Some of them were just that, uh, software engineers cannot work well with hardware engineers. I'm like, it's kind of a, a format that both of them could share. That's another problem, I think, in some of these commercially available options. Uh, we also, there's a very big difference between the software that ran on the launch pad and the software that ran on the vehicle. Uh, and so we really wanted to try to take the best of both worlds, the best of all the approaches and build someone that would work for both. We kind of had this objective list, uh, that we wanted, you know, if, if you could just write in like a, you know, one sheet of paper, all the things that you'd like about your, your software. And then you take that list and you try to map it to these different solutions. And then what we, we thought we could build in-house.

• 13:21Speaker 01

  And so you had sort of built some version of these systems for Falcon and Dragon. Uh, and this was sort of like, hey, take these, these pieces maybe, and, and maybe a different order of magnitude or a different level of depth, uh, that we can run on in a very different way?

• 13:37Speaker 00

  Yep.

• 13:38Speaker 01

  How, how long did that take as a, as a project to build something where really it worked in the way that you wanted to?

• 13:45Speaker 00

  I mean, I think this is actually part of why I ended up leaving to go build Rebel is it was very, very hard to build in-house. And I actually felt like we never really took it all the way to what we could. We could see, you know, we, we rolled out a, a version of the system. But SpaceX, at least when I was there, you know, the, the product was getting things to orbit. It was not building an incredible software platform.

• 14:07Speaker 01

  Yes.

• 14:07Speaker 00

  And so, uh, yeah, I think it worked quite well. What we did build actually went viral internally at SpaceX, which was actually very rare because all the, all the programs are actually very siloed and isolated. Kind of by design, because you want them to move as fast as they can without being kind of, you know, Dragon be like, oh, you can't, you can't do that on Starship because this is how we do it. You're just fully kind of unencumbered. You can just do what's right for the program. But what we did build actually did spread throughout the company. Based on a lot of our experience deploying it and then scaling it up to orbital class, I guess the largest rocket in the world. You know, I thought there were, there was experience there that I thought could help build something for the future for the rest of the world. And that's kind of why I wanted to, uh, leave.

• 14:49Speaker 00

  And I think I also, you know, I talked to a number of other companies out there outside of SpaceX that were, you know, startups trying to go as fast as they could. And I asked like, what are you guys using? What are you guys doing? And they were like, oh man, it's awful. Like, we are using either these commercial tools and we're just like, it's, it just doesn't feel like it's helping us out. Or we're trying to build it in-house and, and similar to SpaceX, I'd say at a different order of magnitude. But they're like, this is just not going to get anywhere soon. Like, this is going to take forever. It's going to be actually extremely costly to make this great.

• 15:21Speaker 01

  You, you were there for almost 10 years, right? Um, difficult thing to do, but if you had to sort of try and distill down the most important lesson that you took from that time, is there something sort of actually quite clean that maybe almost fits in your brain as a mantra? I imagine, I imagine there might be.

• 15:37Speaker 00

  One of the biggest keys to SpaceX's success is just that Elon is one to make massive bets on, and on, and on his team. Uh, that we can do this. And even I was at certain points, a little skeptical, like, could we, especially, I think, specifically the, the catch tower. I mean, we started building the catch tower before Starship had ever even flown. And originally, we were going to try to catch it on the first flight.

• 16:01Speaker 01

  For folks that don't know, could you tell them what the catch tower is?

• 16:04Speaker 00

  Sure, sure, yeah. So Starship, um, was designed from the beginning to be, or the booster, and then also the ship to be caught by, you know, caught by a tower. It has these arms that come out from the tower and then basically the booster and ship kind of hover in between the arms and they, they basically catch, catch the vehicle.

• 16:24Speaker 01

  Which is this crazy idea.

• 16:25Speaker 00

  It's incredible. It's actually, I mean, it saves an incredible amount of mass in the vehicles. You don't have to have these heavy legs down at the bottom and all the structure to support the booster in that way. It's much easier to hold it from the top, kind of in tension. You think about kind of a string holding something up versus trying to hold it up from the bottom. And, uh, that's, uh, a much more efficient way to hold the structure. And so it has massive benefits. And that's, I think, what Elon was so, he was like, no matter how hard this is, this is the right solution long-term. And he was, he just made a huge bet on the team. We were, I mean, everyone at SpaceX on the search for her was like, this is crazy. Can we actually do, we don't even have a flying vehicle yet. Can we actually go directly to catching it?

• 17:05Speaker 00

  Like on top of building the largest vehicle that is designed from the beginning for reuse, you know, full reuse, both the, the ship and the booster. And ultimately, I mean, it was caught on flight five and just, he was right. So, but it was him, I think, making that bet very early on in the program, uh, that got us there so quickly. If we had waited till it flew and then tried to retrofit everything and change the vehicle, it'd be a huge change to how, how the vehicle is designed. And so making that bet at the very beginning in hindsight was clearly, uh, like a stroke of genius.

• 17:41Speaker 01

  Where does that fit into your sort of mental model on a day to day? Are you just trying to make your decisions with, you know, a greater speed than if you hadn't seen that? With sort of greater conviction than, than if you hadn't seen that?

• 17:53Speaker 00

  I think the most tangible thing is, there's, there's two. I think one is, at Rebel, we've made some bets very early on that seemed, they were, they seemed like pretty big and difficult things to sign up for initially, but they're paying off massively now.

• 18:10Speaker 01

  For example?

• 18:11Speaker 00

  For example, we're using the compiler tool chain. So we have our own programming language.

• 18:15Speaker 01

  Yeah.

• 18:15Speaker 00

  That enables a lot of what we, we talk about, uh, all the improvements. And we are using LVM as the backend of that, which is the, it's the compiler tool chain for Rust and the Klang compiler for C++. It was a totally foreign thing to the team. No one ever used it before, but ultimately it was clearly the right solution long-term.

• 18:36Speaker 01

  Why was that?

• 18:38Speaker 00

  It's kind of just becoming the standard. It's clearly the future, the future-proof compiler tool chain. I think everything is going to converge on using that.

• 18:45Speaker 01

  I see.

• 18:46Speaker 00

  And it was a huge bet on my team's ability at that point. You know, we were like three people that we would be able to go and figure it out. And then ultimately, you know, this is what 20 something months later. It's awesome.

• 18:59Speaker 01

  Yes.

• 19:00Speaker 00

  Like the, the language is incredible. It's, it's, it's super performant. The tool chain has a lot that we can leverage to make sure it's correct. So that's one example for sure. I think the other big thing from Elon is just, I think that teams are, when you do that, like when you sign the team up or you say, we're going to go try this. Engineering teams are inherently often just conservative and they can't imagine what they will come up with down the road. This, this like the catch tower seems incredibly hard.

• 19:32Speaker 01

  Yes.

• 19:32Speaker 00

  Have no idea how we're going to solve those, all the problems that we need to, to make that happen. And so engineers, I think are just, just conservative by nature. But, and they can't see kind of around the corner of what they will come up with along the way. And so I think Elon was just, would always make bets on the team and continue to make bets, even though when everyone's like, we have no idea how this is going to work. Like this isn't looking good. He like, let's spend another month on it and then keep doing that. And then people have breakthroughs that they did not foresee.

• 20:01Speaker 01

  Yes.

• 20:01Speaker 00

  And so I think a lot of teams are just much more capable than they even, than they even imagined. I can, I can picture like a traditional corporation, they come to engineers like, hey, can we make a catch tower?

• 20:11Speaker 01

  Yes.

• 20:12Speaker 00

  And they're like, absolutely not.

• 20:13Speaker 01

  Yeah.

• 20:13Speaker 00

  And the CEO is like, let's do something more conservative. But Elon knows how to, I think, yeah, get the best out of his team. And this is, I think a big way that he does it.

• 20:22Speaker 01

  Yes. I was interested in that, the fact that you guys have, you know, built your own programming language, use your own programming language. Why is that necessary or valuable for what you do?

• 20:33Speaker 00

  There's a few reasons. I mean, just like the kind of software platforms, there's been no new programming language designed for controlling hardware systems. Also in three or four decades. And it's kind of the central component of a lot of these platforms is how you actually write what you want to do down in the form of a programming language. Meanwhile, in the last three decades, there's been incredible progress in, I think, just the software world, learning about how humans can write code well. Like Python wasn't even in use back then. And so I think, you know, we've taken a lot of cues from Python in our programming language. And I think Python has been so successful, not because it's interpreted

• 21:16Speaker 00

  or other aspects of the language, just that it's very accessible, very easy to get started with. And so we've built this language to try to be just, it's kind of, it has several aspects. It's highly performant, it's highly accessible, and it's what we call runtime safe. So if it compiles, it cannot crash. And there's just no language out there that does all those three.

• 21:35Speaker 01

  How extensible is it? Does it work sort of across, you know, any possible piece of hardware that you could imagine? How do you sort of wrangle that?

• 21:45Speaker 00

  Yeah, I mean fundamentally, what you're doing in these hardware control systems is you are taking a bunch of inputs that are coming from the hardware system, like picture like a temperature measurement or a pressure measurement. And then you're going to do math and then you're going to write a bunch of outputs in the code. And those outputs are like turning a valve or turning on a pump or, or something like that. And fundamentally with the, so the language is designed to do that middle part extremely well.

• 22:11Speaker 01

  I see.

• 22:11Speaker 00

  Do the math on the inputs to determine what the output should be. So it is very much designed for that problem set. And that's what's made it so, so great for users. It is specifically designed for this problem. You know, the performance is really important for determinism, which is that every time you run it, it's going to behave in the same way. And then it will finish what it needs to, to, you know, to write the outputs at the right time. Second, accessibility, this is actually a big problem in this space. That a lot of these teams are a lot of hardware engineers and they design the hardware systems, they know it the best. They know it better than we, they've physically been in the field.

• 22:47Speaker 01

  Yes.

• 22:47Speaker 00

  Building them, but they can't, but then it comes time to tell it what to do in the form of a language and they have to go at someone else. They have to tag someone else in.

• 22:58Speaker 01

  Yes.

• 22:59Speaker 00

  And then there's a massive interface there. So this person's coming in, they don't know the design at all. And then the hardware engineer has to explain in excruciating detail what they want to have done. And then there's a lot of iteration cycles with that. It takes a lot of time. It's, it's always wrong. I was, I actually, I mean, this is exactly what I went through at SpaceX early on is that. So I wrote the repellent load sequence for Falcon nine and I had to explain to someone else exactly how I want it to work. And it took extremely long time.

• 23:26Speaker 01

  Extremely long being how long?

• 23:27Speaker 00

  Six months.

• 23:27Speaker 01

  Wow, really? Okay. I would, I would have guessed when you say extremely long, like, I don't know, three weeks. It's a six months for that.

• 23:34Speaker 00

  And it was, obviously there was a lot of other things going on and I had to, but there's a lot of iteration cycles with that person. And then with Revel today, you could do it in literally an hour.

• 23:43Speaker 01

  Wow.

• 23:44Speaker 00

  So it is extreme. I feel like when we tell people we're able to program in language, it sounds like a cool software, software engineering project, hobby project. And I think probably the first three or four months that Revel's like, oh, is this really going to work? This seems kind of insane, but what we're seeing today, I mean, this is like, this question has been totally put to bed at the company. Like it is doing exactly what we had hoped. The hardware engineers are out there using the language day to day. There's probably people writing it right now, running it on test stands. And we've even seen, we've actually had technicians at these companies, like reading the code and even writing it. And that is what I was always, I was kind of always envisioning the hardware engineers.

• 24:22Speaker 01

  Yes.

• 24:23Speaker 00

  Which I have deep understanding in it. I was actually a mechanical engineer turned software engineer. And so, but it's, it's awesome that it's doing exactly what we had hoped. And then it's, I think it's even going beyond what we had imagined, which is that people that typically at companies never get access to this type of thing. These are the people that typically run the tests and they are actually interacting and even updating the code.

• 24:46Speaker 01

  Do you open source the code? Why, why, why not?

• 24:49Speaker 00

  I think that is probably what we'll do long-term.

• 24:51Speaker 01

  Yeah.

• 24:52Speaker 00

  I would like to do that. I think, you know, we have to, I think in this stage, it's, we're obviously still building it. So I think there will be a, a point in time where it's the right thing to do.

• 25:01Speaker 01

  Because at a certain point, you could imagine that becoming just such a powerful standard and in the end being extremely useful. But I, yeah, I imagine there's, yeah, lots to figure out in, in, in getting things right.

• 25:11Speaker 00

  Yeah, I think we, we want to get it to a mature state. I think also it is, you know, kind of a key part of the platform. And so I think we want to make sure Revel gets into a good spot before we start to open source things.

• 25:23Speaker 01

  Yes, that makes sense. You mentioned that you, you sort of had this transition from mechanical to software engineer. But going even, even further back, what's the first thing that you remember building?

• 25:35Speaker 00

  Oh, growing up?

• 25:35Speaker 01

  Yeah.

• 25:36Speaker 00

  Yeah. Wow, yeah, I, I build all kinds of things with my, uh, my, my dad. So I grew up in Wisconsin. He had a workshop and we would just, I got really into RC cars and we would, I would build these like off-roading RC like Mad Max creations.

• 25:52Speaker 01

  Wow.

• 25:53Speaker 00

  I really wanted to fully automate them, but you know, we didn't have Revel back then.

• 25:56Speaker 01

  Yes.

• 25:57Speaker 00

  But yeah.

• 25:59Speaker 01

  Was he an engineer, your father?

• 26:00Speaker 00

  No, he wasn't. He worked in, he worked for the state.

• 26:04Speaker 01

  Ah, but he just was into this sort of stuff?

• 26:06Speaker 00

  Yeah, he, he did all kinds of like woodworking and things like that in his spare time. So yeah, built a lot of things growing up. Obviously, yeah, I had Legos. I built like an entire city, even a space station in the basement of our house. And yeah, I, I think there is, there's something really, it's actually what we look for in a lot of the people we were trying to hire at Revel is people that are fundamentally builders. I think how you can look for that is, is do they have side projects? Are they so into what they're doing that they're, especially in college? Like, are they also building things on the side?

• 26:40Speaker 01

  Yes.

• 26:40Speaker 00

  And, and that's kind of a key, a key, a key thing that if people love what they're doing, they're going to, I think, just do a much better job at it. They're going to really care about the outcome. It's also, I think, just a key to like early startups. You need people that are really passionate about what they're building and see it as really kind of their life's work and their craft.

• 27:02Speaker 01

  I love these proxies, different founders use to find like who, who is, you know, fit for their mission. I like the side project idea. What is the, the, the history of your side projects? Like if you think about the sort of formative ones, what, what helped you level up bit by bit?

• 27:17Speaker 00

  So I was into RC cars and Legos and then I went into trying to build robots and stuff in my, at my house. And then I, I didn't really know what an engineer was, honestly. I knew they built things. And so it was really once I got into college that, and then I was like, I got access to this machine shop and just, I went.

• 27:36Speaker 00

  It was, I had a lot, I built all kinds of things. I was, helped start a few student groups and we had, it was like, one of them was to build a, a wind turbine that would

• 27:47Speaker 00

  go to a community in Nicaragua. That was super cool. And yeah, basically built wind turbines from scratch. It was like, you wanted to build it out of materials that were available in that location. And so you're very much constrained because ultimately we wanted to let them be able to, to build these things.

• 28:04Speaker 01

  Yes.

• 28:05Speaker 00

  And so that was a really interesting design constraint situation of like what materials can they get there?

• 28:09Speaker 01

  What are the trade-offs you have to make for in Nicaragua? It's like engines, certain engines or?

• 28:15Speaker 00

  The magnets are hard to get, so those would have to be sent there. But all the rest, you had to be machine, you know, basically to machine it out of just materials available there. And I mean, it was like, we also made like a, a solar, it was like a solar panel.

• 28:30Speaker 00

  I forget exactly what they're called, but they would basically hold a solar panel and point at the sun continuously throughout the day. And we had to, we built it out of just wood and like junkyard parts. That's fun. And then, and then ultimately I ended up at a robotics lab. I always wanted to work at this robotics, I found that I kind of got into it my junior year. And then I really, really loved that experience. Like I was just, yeah, kind of similar to like building RC cars and stuff in the basement. I was just, but then I had like all these resources available to me. I like actually had funding and I again had the, the machine shop and I was building all kinds. I actually, yeah, published a few of them.

• 29:03Speaker 01

  Did you have any, you know, I'm thinking of sort of the, the PayPal mafia building bombs in high school. Did you have any sort of close, close shaves with things going, going wrong?

• 29:13Speaker 00

  Yeah, we did a little bit of that too. My friends and I, yeah, we made like air guns that would, you know, we were actually like, it would like shoot a pool cue, actually.

• 29:23Speaker 01

  Oh, wow, like a, like a harpoon.

• 29:25Speaker 00

  Well, yeah, we, yeah, all kinds of things like that.

• 29:27Speaker 01

  Yeah. These are, these are somehow fantastically good signals of someone being a good founder in my experience. This sort of, you know, smart, rule-breaking, tinkering, slightly on the edge of danger. Were you thinking about being an entrepreneur in those days? Was that like a concept? You mentioned you didn't have the concept of an engineer really. Was a founder something that you knew about?

• 29:48Speaker 00

  Honestly, not really. I I just knew I wanted to, yeah, I knew I just wanted to build stuff. If I could do it professionally, that would be the best case scenario. And so then I did start following Elon and just what SpaceX was doing back in. It was like sophomore year of college and just thought that was the most insane version of like, that was like the ultimate building things. And I also just imagine they probably, you know, had the best engineers to do it. And so that's really why I was like, okay, I want to, I want to try to get into SpaceX. I mean, sneak into SpaceX is how I was thinking about it. And yeah, I ended up staying at Minnesota a little longer than I expected. I was, I didn't, I wanted to keep taking classes.

• 30:31Speaker 00

  I kind of got into software side. I was good at the robotics lab. I could, you know, build, I could, I could machine everything. I could build the entire rocket, design it, but I actually, I couldn't write the control software for it. And so then I was like, well, I can stay here a little longer and go. And my professor said he'd sponsor me into the computer science department. And so that's actually why I ended up staying a lot longer as an, and then I had to go back and take all the prerequisite classes to take the, the masters, the graduate courses. And so it's kind of funny, there's a full through path there of like, uh, couldn't, couldn't do this in, for the robotics and the robotics lab. Uh, and then also kind of saw the exact same problem, uh, later on at SpaceX and then, and then also at Rebel.

• 31:14Speaker 01

  Yeah. Do you know the, the sort of heuristic of the fox and the hedgehog? The fox is, you know, someone who loves finding many problems and is, you know, sort of believes that no one idea can explain the world. And the hedgehog is like one problem over and over, intensively, obsessively. You've sort of found ways to keep solving the same problem, it sounds like where you're, you know, encountering this limit of, you know, hardware control and, uh, you know, building the language for these systems to work. First in college, then at SpaceX and now, and now with Rebel. It's, uh, yeah, it's fascinating to see that come around.

• 31:50Speaker 00

  Yeah. And I think it's interesting because I think really that experience in college and then switching into, into computer science and being able to really understand, uh, both engineers perspective, the, the hardware engineer, but then also the software engineer. And I think that's, that's really what we've tried to create is something that, uh, the hardware engineer can use, but then the software engineer, uh, can also jump in. And it's, it looks very familiar to them. It's a text-based language compared to, uh, some of the other, other approaches out there that are graphical. I say it's like, it's like programming with crayons.

• 32:20Speaker 01

  Yeah.

• 32:23Speaker 00

  And so, yeah, I think, I think that background is exactly, has really set me up well to, to, to, to found Rebel.

• 32:30Speaker 01

  Where do you think your fuel comes from? When you think about your, your history, like where does the drive emanate?

• 32:36Speaker 00

  I, I think for whatever reason, I mean, I've tended to just go after, it's probably both the hardest thing, but also where I thought I could have the most impact. I mean, I, I joined SpaceX as a, as a 25 year old intern. And I was like, I'm just going to go in and outwork everyone. And that was my mentality. I was like, I, I'm going to sneak in there. I don't, I didn't think I was qualified, uh, but I thought I would learn the most. And I would really kind of see what I was made of, honestly.

• 33:06Speaker 01

  That chip on the shoulder of, hey, I have to outwork everyone. Were you the, I don't know, were you a good student, bad student, you know, the, the last one picked? That impulse comes from somewhere, right?

• 33:16Speaker 00

  I wouldn't say I was the best student in high school. Uh, I was always in like advanced math, but otherwise, uh, somewhat disinterested. I think I had the same mentality going into Minnesota, honestly, as I thought, you know, joining, they actually, I don't know if they do this anymore, but they actually had us, they're like, look to your left, look to your right. Like two of you will not make it to the program.

• 33:36Speaker 01

  Wow.

• 33:36Speaker 00

  They actually said that at the beginning, at the orientation.

• 33:39Speaker 01

  Two of you won't make it through?

• 33:41Speaker 00

  Yeah.

• 33:41Speaker 01

  Gosh.

• 33:41Speaker 00

  It's true. It's, it's, I looked at the statistics on it. It's actually true.

• 33:44Speaker 01

  So there was some of that sense of, okay, uh, I haven't been the best student, so now I'm going to have to prove myself extra.

• 33:50Speaker 00

  Yes, a hundred percent.

• 33:52Speaker 01

  You, you mentioned that, you know, Elon's sort of maybe a superpower, what he really spikes on is this ability to take these big swings and, and, you know, give people the, the confidence to do something a little outlandish, uh, or at least it sounds outlandish. What are the parts of his mode of management that you have chosen not to take with you? That you're like, this didn't work for me, or it's not the way that I want to run my, my company.

• 34:16Speaker 00

  I honestly, I think overall Elon's a credible CEO. I don't have a lot, I think extremely intense. I think it, yeah, again, not for everyone. I loved it. I thrived in it. I think being challenged and I, I think I also was very fortunate. I was, you know, one of the first people to join Starship. I think it was his first software engineer down in Boca Chica, Texas. No, no, no, Starbase.

• 34:37Speaker 01

  Yes.

• 34:38Speaker 00

  And, um, and at that point, the program was really kind of this like backwater, kind of like not the, you know, everyone really wanted to work on Falcon at that time. And it was kind of all the crazy ones that would go and want to go work on early Starship, you know, at the very beginning. And I think letting people do that was awesome. I mean, it wasn't, it was kind of a volunteer scenario, but then he got pretty involved and, you know, I, enabling people. I mean, if you fly close to the sun at SpaceX, you know, you're going to have, you're taking a lot of risk for sure. But enabling people to do that and giving them a ton of agency and, um, but also holding people accountable, I think is the right recipe to do great things.

• 35:18Speaker 01

  Flying close to the sun at SpaceX means taking like a big swing on something and putting your name behind it with a lot of resources. And if that doesn't pay off, it's like, hey, then this didn't work. Is that roughly right?

• 35:29Speaker 00

  I mean, Elon says like you, I think he respects people that take big swings, uh, but he also, you know, he tracks the batting average.

• 35:37Speaker 01

  Yeah, that makes sense.

• 35:38Speaker 00

  It's okay to have some, have some misses. I think it's not okay to not like push hard. Well, if you think something is, is the right way to do things, you should, you should say it. And if you, I think kind of hang back and don't, and then it's like, it can't, it's then realize that you knew, you knew the right thing to do, but you didn't push for it. Uh, I think that wouldn't be seen very, uh, well by Elon. But yeah, I think there's, there's high risk reward at SpaceX for sure.

• 36:02Speaker 01

  You're, you're a couple of years in at this point, so I'm sure you're still sort of, you know, the CEO job is like, you have to climb the skill curve every day, it feels like, I imagine. But as you think about the way that you prefer to lead, everyone interprets this, this job very differently. What are the places where you find you're sort of most uncompromising? Or maybe you want to hold the highest possible bar versus, you know, other folks that you've seen? And, and maybe where there are places where you have more flexibility?

• 36:31Speaker 00

  Yeah, I think the product has to be awesome. Has to do exactly what we say it will do. There's no, I have seen kind of in the, in this space, people kind of forward selling capability or saying it can do certain things. And then that doesn't really pan out after a number of months. And that's when Rebel comes, comes in to save the day. But yeah, I think it's extremely important that, uh, we are very transparent with what it, what it can do today, what we, what we plan for it to do in the future. And then I think also, uh, I've definitely pretty involved in making sure the product is what it, it needs to be. And, uh, it's still definitely best idea wins. I mean, I, I change my mind when it, when there's new information all the time.

• 37:12Speaker 00

  Uh, even when if I have like, we just, me and an engineer or someone on the product side disagrees, uh, and then there's new information. It's a clear, like I was wrong, I will admit it right away. I mean, I, I think that's a really, really important, like basically no ego is extremely important to, to make the best decisions possible. And that was, I think, I guess that is another thing I saw in Elon is he would be extremely passionate, but then presented with new information, you'd be like, well, okay.

• 37:38Speaker 01

  That was the quick switch.

• 37:39Speaker 00

  That's it. Let's not go that direction anymore. With the company, we're definitely really trying to run a very tight engineering organization. So I think I've seen, yeah, the proof is kind of clear with SpaceX what has happened. And then you look at how the company was run and, uh, and it's really an, uh, an execution machine. I think we have to adapt some of that for Rebel. It's not, you know, you don't have these launches that are really

• 38:05Speaker 01

  Yes.

• 38:06Speaker 00

  really powerful at kind of aligning everyone. We're going to launch on this day and then everyone kind of backs out, uh, their schedules. And it's, it's also a really nice tool to figure out what are, what's actually the critical path. We don't, it's a little different as a software company where you have a lot of things in motion at the same time. You have a lot of customers as well. But I think having a really strong engineering culture, uh, and then people join and they feel like, wow, I'm with the, the most elite. This is an elite team that has an incredible culture that is also moving really fast, uh, and delivering products. Like the, the best thing is when we, you know, deliver something for a customer and then they go in and have some awesome test.

• 38:46Speaker 00

  Like they, they get through the entire, uh, hot fire on an engine and they always post it in our shared Slack channel. Like we, we get to kind of be part of, part of their success.

• 38:55Speaker 01

  You, you mentioned these launches, you know, that is something that from the outside, at least it feels like Elon does it so, so well. It's like finding these galvanizing moments, these, or, or sort of in some cases, you know, maybe manufacturing even this thing that everyone has to run at. Which feels like just ways of pushing energy into the system in a way. What is the version of that, that, that works for you? Is it doing sort of the Gemba walk down the, you know, the different tables and seeing what everyone's working every day? Is it something else?

• 39:25Speaker 00

  No, I think, I think it's, it's some kind of customer milestone.

• 39:29Speaker 01

  Customer milestones, yeah.

• 39:30Speaker 00

  So, you know, there'd be some large test that a, a customer needs to do. Or maybe we need, there's some new capability that they really need to do it well. So we'll kind of attach it to that timeline. And then I think the new one for us, you know, I think what's extremely exciting about where we're at right now is we've we're very competitive in the small scale testing world. So small scale testing being like a benchtop test setup. And normally with this, these software for testing, as you go from kind of small scale to larger scale, you need different things. Small scale, you want to be really fast, iterate really quickly typically. Larger scale, something like a rocket engine test site, which is a large facility on the desert.

• 40:13Speaker 00

  You want a little kind of more controls, you want more safety. But obviously you still want to move really fast. And I think what we've really struck the right balance in with Revel is we're kind of both very fast to iterate with, but also still very performant and safe. And so what's awesome is we're doing very well in small scale, very well in this kind of large scale facility. And the next phase is industrials, which is large scale systems. And we're also so far, we've, we've seen that we are extremely competitive there as well. And these are all of these different scales, there's probably eight different types of software that are used. And even inside of one company, so at Impulse, they literally had eight different types of software.

• 40:52Speaker 01

  Wow.

• 40:52Speaker 00

  And they have now fully standardized on Revel and they're only using Revel across tiny, even the smallest like kind of circuit board testing system, all the way up to what they're using at this new site called Site 1C, which they're going to use to test their entire stage.

• 41:06Speaker 01

  You mentioned it sort of in these steps of small scale testing, large scale testing, industrial systems. This is a very naive question, but are the industrial systems more complex versus a test? Because it's sort of continuous versus discrete or more inputs? Like what adds the, you know, that is sort of a discrete step in your mind?

• 41:25Speaker 00

  It is just many more, they call them tags, but they're just telemetry channels.

• 41:30Speaker 01

  Okay.

• 41:31Speaker 00

  So.

• 41:31Speaker 01

  Sort of input of some kind or another.

• 41:33Speaker 00

  So we're now, we're actually now deployed at a 250,000 channel system.

• 41:38Speaker 01

  Wow. 250,000 channels.

• 41:41Speaker 00

  Yeah.

• 41:41Speaker 01

  And so each of those channels is bringing some form of data from the system, whether that's heat or, you know, pressure, or whatever that might be across oil and gas, or whatever it might be. Is that right?

• 41:52Speaker 00

  Correct. And that's not even, I think some of these will go up to several million channels.

• 41:56Speaker 01

  Okay. I don't have good calibration of what to imagine there, but that sounds extremely hard.

• 42:02Speaker 00

  Football field or several football fields level.

• 42:06Speaker 01

  Yes, but just like complexity wise, like it sounds insane.

• 42:10Speaker 00

  Yeah, it's a lot of systems. It's cool. Yeah, we just had a bake off, which I don't know if you know, it's like you kind of try two systems out. And there were two, two engineers that had, that were very familiar with these platforms. And so they, they kind of gave them the same assignment, one with the traditional approaches that they'd been using at this company, and it took them a week and then completely cold to Revel. Had never even seen the platform. They did it in one day. And they had been using the kind of old, old way of doing things for several years. And so that's when we, that kind of happened a few months ago. And that's where like, okay, we have something in this space as well. We're both competitive, clearly in the test space,

• 42:51Speaker 00

  doing very well there. And then now we, it's clear, we also have something that is extremely compelling in the industrial space as well.

• 42:57Speaker 01

  Do you have to convince some of these large companies that you're going to be around for a while? Because I imagine they're so used to someone, you know, this company's been around 20 plus years. You're around two years, you know, they want to know you're going to be around for 20 years, right?

• 43:11Speaker 00

  Yeah. And that, that was part of the strategy in the latest funding round as well is that clearly we are going to be around for quite a while. You know, there's, there's no way we're going to run out of money. But I think it also comes back to the, the product just needs to be extremely compelling. Like if the, I think that that's another trait is like, the product is compelling enough, they will still at least try it out. And then you move from trying it out. Oh, it is extremely good. And then you move down the stages of.

• 43:35Speaker 01

  Yeah, keep taking more off their plates in a way. Hmm. Very cool. Wow. That's wild to think about. I think you've talked before about your position at Revel, almost like a mini VC, because you have to sort of bet on which companies to sort of resource and dedicate time to, to getting set up. What is the process like of, of taking a company in cold and saying, hey, you know, you're now ready to sort of run your next launch?

• 44:00Speaker 00

  Yeah. I mean, this is something I think has been extremely surprising to me. We essentially can deploy our system in one day.

• 44:08Speaker 01

  Oh, wow.

• 44:09Speaker 00

  We actually have really never, one, actually it was that very large system, it took two days. But otherwise we have done fully same day, or even like a few hours being fully deployed.

• 44:20Speaker 01

  So when you look at Revel, the company as a machine at the moment, where do you see the, the big bottleneck?

• 44:26Speaker 00

  Currently, definitely hiring. We're, I think we have, at least my, my bet on the company is that we need to keep an extremely high bar. And that just propagates all the way, you know, until Revel is, you know, 200, 500 people. If we can maintain that, and which is, I think, another kind of lesson from SpaceX is I think they have, they've done a great job at this. And we need to replicate that at Revel. You want to still be at, at 500 people. Everyone looks around, they're like, wow, this is an incredible company. All these people are, are awesome to work with. That's, you know, maybe harder for us a little bit in that we don't have the, the name brand of SpaceX quite yet.

• 45:07Speaker 00

  But that's essentially the biggest, the biggest bottleneck in that we, I mean, demand has totally outrun the current size that we're at, which is I think a great problem to have.

• 45:16Speaker 01

  Yes.

• 45:18Speaker 00

  Even with the same day deployments, my prime, prime focus right now is hiring and building out the team.

• 45:24Speaker 01

  When you say keep a high bar, every company wants to do that, right? What does that mean for, for Revel specifically? Like what is the, and how do you find those people in a, in a distinctive way? You know, I've heard, you know, the, the largest array of different ways people find a little bit of edge in, in the market. Like, have you found a few pockets where, for whatever reason, we're extremely good at taking Midwestern, you know, tinkerers and, and turning them into, you know, the world's best engineers, or whatever that might be for you? Like what is, what is your playbook?

• 45:54Speaker 00

  We're, we're pretty open to where people are coming from. But I think you just have to have a really good, a really solid process for assessing talent. And I think generally, like you kind of know it when you see it, our process is, I think, quite good at this point. And yeah, we have, the, the best engineers can usually determine if they're, an engineer sitting across the table is going to be a good fit on the team. And so we rely pretty heavily on that.

• 46:20Speaker 01

  Talking about this sort of mini VC role that you have in a way. You get to have a, an interesting front row seat into the amazing pieces of hardware and companies that people are, are building. What do you think the world looks like in five, 10 years from now, when some of these different customers that, you know, Revel is serving flourish? What do you see that maybe others haven't realized fully yet?

• 46:47Speaker 00

  This is one of the best parts of being at Revel, I think, is that you get to,

• 46:52Speaker 00

  in one day, you can go to a nuclear reactor company, you can go to this, like the most cutting edge satellite manufacturer. And then you can go to like a hypercar company. Literally they're all, it's pretty cool. In LA, there's a lot of them there. So I think as an engineer, that is really great. And also I think Revel has a unique position that it's like a, a one to many platform. So if you work in, inside a company and you're a software engineer, you're going to work on just that, that company. Only get exposed to that company's hardware they're building. And then at Revel, you get to be part of all of these missions. But I think what's really exciting, I, you know, I think the small modular reactor space, I think is really cool. I, I think there's definitely going to be, I mean, that's what I'm seeing is they're making great progress.

• 47:34Speaker 00

  And I think the regulations are also kind of clearing the way for them. Obviously I'm very excited about the future space economy. With Starship doing extremely well, and then all the companies betting on, on having low cost access to space. Hypersonics are also really cool. I think that's, yeah, so we're, we're now working with a couple of the best companies there. It's awesome. I mean, one of them was actually very hard to get into. It took, it actually took a year.

• 48:01Speaker 01

  Wow.

• 48:01Speaker 00

  To finally say, okay, we're going to try Revel out. As soon as we, we got into one place, it just spread throughout the company. It was like on the order of a month, it went from one to like 20 systems.

• 48:11Speaker 01

  Wow. What was the hesitation like for, is there, is there something that you learned from that?

• 48:16Speaker 00

  This is a critical part of their operation.

• 48:20Speaker 00

  And they tried one approach before and they were kind of trying to see if that was going to pan out. And then they're like, okay, this, let's, let's give Revel a shot. And we're able to very quickly prove ourselves and then also deliver on the, you know, we say it's five to 10x, it's going to increase your, your cadence of test. And then the first one we did, it did exactly that. They had like, their engineers were, became like application engineers, they had to write a lot of Python. And then they were, had a lot of safety issues with that, where like, you know, if you have Python, a big difference between Revel code and Python is that the runtime safety. So Revel, if it compiles, it will, it cannot crash.

• 49:01Speaker 01

  Yes.

• 49:02Speaker 00

  So you may have these 12 hour long tests. In Python, there's no guarantee of that.

• 49:06Speaker 01

  Yes.

• 49:06Speaker 00

  And so you may have this, the simplest mistake, that's probably most common is like a, a string interpolation error. And that will just kill your runtime system in the middle of a test.

• 49:15Speaker 01

  Yeah.

• 49:16Speaker 00

  And then you have your system left in a really, in an unsafe state, may have even broken hardware. And then you also need to go redo your 12 hour test. And then whoever was waiting for the results is also upset. And so that first deployment fully demonstrated all the capability. And then we had people at other sites asking about it, and then it kind of just took off.

• 49:37Speaker 01

  Wow. You know, I feel like it's almost axiomatic that every great company has to have at least one near death moment. Have you had yours yet?

• 49:48Speaker 00

  No, I mean, I, I really can't complain on the trajectory of Revel so far.

• 49:52Speaker 01

  It's, see, that's what it looks like from the outside. I'm like, it looks almost too good.

• 49:56Speaker 00

  23 months in. I think it is, though. Going back to talent, I think it all comes down to that. I mean, we've been very fortunate and we've gotten just an incredible set of engineers and product folks. Jess Wenzinger joined from Palantir, who is, I think, you know, we, at SpaceX, we really knew how to execute on the engineering side. And she just brought a lot of product and kind of customer-facing experience. And so it truly is just getting an incredible group of people together. And a lot of people that have just a lot of experience in the relevant places that we needed.

• 50:31Speaker 01

  What's been the hardest week of running the company?

• 50:34Speaker 00

  I think honestly, the last month has been a little more frustrating in that we have, we just need more engineers on the team. Like, we have an extremely clear vision of the future. It's a very good position that demand is so high. So we've set up an FTE team recently. So that's kind of the biggest bottleneck and we're really focused on, you know, how do we hire great FTEs? Obviously not something that SpaceX had. So it's something that I personally have to learn a lot about. But that frustration, obviously, is just like, it's a great problem to have.

• 51:06Speaker 01

  We talked a little bit about AI building software and the ways in which, you know, you can leverage that. To what extent do you have to build the system to accommodate for agents as almost users? Like, is that something that is already happening at some of these companies? Is that something that you imagine will start to happen more? Or because of the need for precision control, is that sort of less likely?

• 51:31Speaker 00

  I think something very exciting that we're seeing is I think a lot of companies are trying to add AI into their product and kind of pushing on their customers and like, see what's basically just throwing spaghetti at the wall and seeing what sticks with AI. And we have, people are actually already using AI with our product. And I actually think we found that our code is the best possible format to generate, you know, control software from an AI. Because the code had, again, going back to the qualities of it, it's highly performant, highly accessible and runtime safe. And so if you're going to generate code, those are the exact things that you'd want. You want it to maintain accessibility, meaning you can still read it and totally understand it.

• 52:13Speaker 00

  So whatever you generate is still very easy to grok what's happening. And then the runtime safety is also really, if you're going to generate code and you're kind of like, maybe it's less critical. At least you know that if it gets to the compiler stage, it's not going to crash. So those are two asterisks language, I think, are just make it the best possible thing to use with AI. A lot of customers are already doing that.

• 52:34Speaker 01

  Yeah.

• 52:34Speaker 00

  It's not something we're necessarily supporting directly, but they are already, you know, already heavily leveraging AI with the platform.

• 52:43Speaker 01

  When you think sort of like very long-term about what Revel becomes, you know, let's say, five, 10 years from now. If I extrapolate it out, it feels like there's like all these really fascinating things that you can do, whether that's, you know, creating an industry standard around some of these coding language, this coding language you've developed, or, you know, aggregating demand across different industrial companies to sort of help them procure in different ways. Like, there's sort of, feels like a dozen different interesting things. Like, what's your sort of vision for what this might look like?

• 53:17Speaker 00

  The mission of the company is twofold. You know, I've sat in the seat of many of these engineers. And I was a hardware engineer. And then at SpaceX, I wrote a lot of control software, a lot of test software as well. And obviously, that scaled up to Starship. So I feel like I have deep empathy for the engineers that are day-to-day, just trying to get through their testing, write the code they need to write. And so we really want this, you know, today, I'd say the tools they use, they really feel like a bottleneck on their processes. We want to give them something that feels like an accelerant, and it is truly an accelerant. The other side of it is, if we do that at scale, what does that mean for all the companies out there going after these incredibly ambitious missions? Any more of them will be successful, they'll get through their testing campaigns way faster.

• 54:01Speaker 00

  You can test 50 times in a week instead of five times in a week. You're going to ship your product sooner and you're going to ship a much better product. And so that's what I'm extremely excited about long-term, is that we deliver all that kind of twofold mission of, like, for the engineer, but then also, what does that enable across all of these great companies?

• 54:18Speaker 01

  I always like to wrap up with a thought experiment or a question or two. If you had unlimited resources and no operational constraints, what is an experiment that you would like to run?

• 54:29Speaker 00

  I watched so much Star Trek growing up, huge TNG fan, Jean-Luc Picard. And I just want to know if, you know, humans going to be out there, you know, maybe are we going to go to another galaxy someday? I think just, are we going to be propagating around our galaxy? Like, is that actually, you know, is that going to happen?

• 54:48Speaker 01

  Yeah.

• 54:48Speaker 00

  I think, I think we are obviously running the experiment and that's what I was super excited about, working at SpaceX for 10 years.

• 54:56Speaker 00

  But I just really want, I want the answer to that question. Is that like, I thought Star Trek was, I just like, I was watching it as like a, you know, in a middle schooler and it just blew my mind. And it's like, wow, you know, we could be out there exploring all these other solar systems and I would love to know.

• 55:15Speaker 01

  If you could assign a book to everyone on Earth to read, do you have one you'd want everyone to have read once in their life? And you get the assurance that they're going to understand it also?

• 55:28Speaker 00

  I reread this book, it's Our Mathematical Universe.

• 55:36Speaker 01

  I don't know that book. Who wrote it?

• 55:37Speaker 00

  I'm trying to remember it. To get back to you, but.

• 55:40Speaker 01

  No.

• 55:41Speaker 00

  Yeah, it's really interesting. I think it really helps me put things into perspective. It just kind of chronologues the, all the physics discoveries up to today. And it presents this explanation of the universe that it's really just a mathematical model and that's it. And I think, you know, whatever is going on at Revel or in my personal life, it's like, I listen to this and it's just like, I think it really gives you likes, it's like the most zoomed out perspective you could possibly have on everything.

• 56:09Speaker 01

  Yes. And there's something that gives you peace in that, in a sense?

• 56:15Speaker 00

  I think it, yeah, I think it's always like, I think the hard part in running a company is always, I think, seeing the, seeing the forest instead of just looking at the trees and that it's like, I listen to it, you know, usually when I'm trying to fall asleep. And it actually helps a lot just to like, it's like literally the most zoomed out view of the forest you can imagine, like, from the perspective of the universe.

• 56:39Speaker 01

  I love that. Well, that's a great, great place to end. Scott, thank you so much.

• 56:43Speaker 00

  Thank you.

• 56:46Speaker 01

  That's it. Thank you for listening to this episode of The Generalist Podcast. Please subscribe on Apple Podcasts, Spotify, or your preferred podcast app. Ratings and reviews help others discover these discussions. So if you enjoyed the conversation, I'd be grateful if you could take a moment to leave one. For all past episodes and more, visit us at thegeneralist.substack.com. See you next time as we continue to explore the future.