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Ryan Aytay: We like to say we're doing the work of consequence, and, of course, the work the the consequence of failure, of course, in this world is pretty significant.Jordan Metzner: Built this week, breaking it down. Built this week, we show you how. A fresh idea, a clever tweak, you locked in true.Sam Nadler: Hey, everyone, and welcome to Built This Week, the podcast where we share what we're building, how we're building it, and what it means for the world of AI and startups. I'm Sam Nadler, cofounder here at Ryze Labs. And each and every week, I'm joined by my friend, business partner, and cohost, Jordan Metzner. How you doing today, Jordan?Jordan Metzner: Hey, Sam. Happy to be back. Exciting week in AI world. So much going on. Lots to talk about.And obviously, really excited to have a have a great guest this week as well.Sam Nadler: Yes. Super excited to introduce our guests. But before I do, please don't forget to like and subscribe. We're 500 subscribers away from 30,000 subscribers on YouTube, a big milestone for us in under one year. New episodes out every Friday.So if you're into AI and startups, please give us a listen. And with that, I'd like to introduce the COO of CodeMetal, Ryan. I'm super excited to dive into your business today. But if you don't mind, give us a a quick intro of who you are, and let's jump into high level what CodeMetal does.Ryan Aytay: Yeah. Well, Sam and Jordan, great to be here with you today. And yeah. So I am very excited to be here. I'm about, I think, five and a half months here in at CodeMetal as president and COO, and it's been an amazing journey.Kind of like you said with AI, there's a lot of things happening, and that's ultimately why I'm here. Before this, I spent about four years running the Tableau business. If you've heard of Tableau, you know, great analytics company as part of Salesforce since I was the CEO of that for about three to four years. And then prior to that, spent, you know, roughly fifteen years at Salesforce sort of from the early days in 2006 and 2007 doing a number of different things across the business. And so, yeah, that was it's been a it's been a great journey, and, you know, we moved on from that into this new world.And, a lot to talk about, a lot to unpack, and I'm, of course, still learning in in my own right.Sam Nadler: So my understanding, and I wanna hear from you because I'm I'm I'm not gonna do it justice, but CodeMetal's real value proposition is its ability to translate code from, you know, one language base to another, but using formal methods. So, you know, institutions, large enterprises can really trust that that translation will work. Is that the core functionality? And I'm sure there's millions of things I'm missing here, but how would you describe it in one sense?Ryan Aytay: You know, and I have a few slides I could pull up and kinda walk you guys through kind of how we look at the world. But I think what you know, when I think about what we do, we're really trying to lower the barrier, if you will, from code to metal. And that's, you know, from software to hardware. That's really where that kind of comes together. And it's really from any code to really any hardware, but I think what you said formal methods, which is a form of verification and using the right, you know, mathematical proofs and the right type of testing to ensure that whatever the source is, wherever that code comes from that it behaves, that it has the same intent, that it is optimized and that is running of course in this new capacity on any hardware just like you would expect it to.And I think, you know, provably correct are the two words that I like to use because it has to work. You know, we're not we focus on mission critical companies that have, you know, a lot of different things and and if you don't mind, maybe I'll just see if I can pull up a couple slides. Yeah. Let's do it. So, you know, because who doesn't love slides ultimately.Right? So we gotta have some broad centered conversations. So, you know, as I was mentioning, you know, our goal is really to lower the barrier, you know, as you think about kind of code moving into, you know, from code to hardware environment, that's where the name CodeMetal comes from. We talk about provably correct and I think the really important thing to talk about here is like pretty much everything we depend on, at least I know I depend on in my life, like there's code somewhere. Right?Whether it's, you know, your phone, you depend on that, but that's not as perhaps mission critical, but, like, you know, the military that protects us or the car that you drive in or the, you know, think about, you know, aerospace or the power grid or go down the list of the medical devices that you, you know, if you are dealing with like an MRI machine or like things that you need to make sure that, you know, you can operate in a daily scenario. Like, those systems all depend on code. And so that's great, but it's also a little bit scary because a lot of that code is legacy. Maybe it's, you know, been written years ago, and it's hard to change it. Right?Especially in an AI world, we've all, you know, heard of Tesla and an over the air update. And when you get an over the air update, you know, things change. The hardware gets, you know, it becomes modern. You can bring new technology quickly. And I think that's the type of thing that is really important in this new world.And so, you know, it's great that all these systems depend on code, but the reality is is that, you know, as we go through this world of, like, how do I change things quickly? How do I ship faster? How do I, you know, safety safely translate, you know, old code to new production systems? It's super hard. It's time consuming.It's costly, etcetera. Takes lots of effort, whether it's humans or, you know, AI or whatever it may be to kinda make that happen. And then of course you have to test it. You have to make sure that it's actually something that will work on the said hardware platform that you, you know, that you need to to go through.Jordan Metzner: Resumes don't tell you who someone is. Interviews do. Interviews that captures how someone thinks, how they communicate, how they solve problems at scale.Ryan Aytay: We like to say we're doing the work of consequence, and of course, the work the the consequence of failure, of course, in this world is pretty significant. Like, you can't have your car fail or your plane you know, like, are just catastrophic scenarios. And an example I like to talk about, even if you go back to something as simple as the CrowdStrike thing that, you know, you may remember took down a lot of the air traffic control and many different flights, that was just like one line of code that ultimately kinda broke. And that wasn't even like a very hard thing, it just was an issue. It was a mistake.And so when we think about like, hey, well, but we're in this new world now and like AI solves everything. Right? I can just go out and start like hammering away and doing some code gen, you know, pick your code gen platform, Claude Code, Codex, but on the list of, you know, folks that are out there. And they're all great and we love them all. But the reality is, like, in a production world, AI generated code actually isn't quite safe enough and really never will be for what we'll call a mission critical system at the edge.Right? So what do I mean by at the edge? Well, it's it's basically the hardware side of things. Right? So it's great if I can vibe code an application, you know, a time and expense app or something like that.That's awesome. All of this happens very quickly and that's why we actually really like those environments. But to make sure that it runs safely, accurately, and just like it used to on the with the old code, but in the new world, in this system sort of mission critical system environment, that's really what we do. And so if you think about like, well, why, you know, tell me more. Right?Well, the reason why sometimes it will fail or why it will fail in general is there's a gap. And that gap is really what we try to solve. But, you know, the gap exists because, you know, AI generated code is mostly correct. Right? We know this, and you can actually go in and ask, you know, said AI platform, like, can you do it in an accurate way?Well, pretty much. But we need it it must be correct. Right? It has to be perfect. It has to, you know, it has to consider every requirement.It has to make sure that it tests every possible issue or security scenario or hardware assumption, and then it has to be physically tested. Right? And so this is a lot of, like, what we do at CodeMetal. And what I like to think about it is kinda like a promise. It's like, okay.So we don't just do code generation. That in some ways is getting easier and easier. We are all about, you know, we translate, we verify, and we also optimize to make sure that we're doing it in the most efficient way because we know that in this world, there are certain systems that just can't afford to fail. You know, it's kinda like if I'm trying to, you know, change the electrical in a city, like, can't just do it I I don't want the lights to go out, but I want it to change. Like, these are the scenarios you have to think about.And so, you know, just because it's always fun to show a little bit of, like, you know, what does this look like? You know, this is a a little picture into something that we actually haven't even fully brought out yet, but we will, which is, you know, bit of our own platform, which is, you know, code in, code out. This is a bit of our test generation suite of how things look. And if I think about, you know, like, where do these things go from here, you know, a lot of the things that we talk about at CodeMetal are formal methods, you know, and within that, there's different types of testing. There's, you know, can call it testing and fuzzing and, you know, go down the list of things that we believe are very important to make sure that we're able to look back at what was the intent and the behavior and the origin of the code and how do we use that as a a way to kind of go through and do a proof to say like, is this right?Does this work? Will it run on said hardware? So we have this belief, right, where, you know, generating code actually, the price is going down. It doesn't really cost anything, but if you get it wrong, it's pretty substantial. And so that's a bit of where we are.Sorry. That's a very long answer about like what is CodeMetal, but really I just it's a it's it's a very nuanced thing to talk about, but very important and and most people don't realize, especially I didn't realize before I joined here is how critical this really is. And I think AI helps us, but it doesn't solve every single problem.Jordan Metzner: Okay. Awesome intro. You know, I've been building software and hardware for years and have tried to stay away from mission critical softwares. And that's always been, hey, guys, you know, nothing we're doing here. We're not flying planes, you know.It's always been kind of a safety net for building, you know, web SaaS and mobile apps and things like that. But, you know, when you when you have to pay the brass tax of, you know, human life is on the line, obviously, the the the requirements and the seriousness of the product and software and hardware go to another level, which, you know, historically in my career, I've tried to stay away from because obviously this is a highly risky area and, you know, it takes a lot of a lot of time to make sure it's it's gonna go right. And I think on top of that, you've got a lot of historical systems written in legacy code bases that, you know, many engineers don't even know anymore. Right? And they have to kinda like go back to learn.And probably they'd never, you know, but without AI, they probably would never wouldn't, you know, have the ability to be rewritten and, you know, more efficiently and run on, you know, lower cost hardware and things like that. So tell us a little bit, you know, obviously, we see like, you know, huge major, you know, defense contractors on your website and obviously, we don't wanna discuss anything confidential. But, you know, tell us tell us, like, a good use case of, you know, where where a company came in and, you know, they applied CodeMetal and they were able to kind of, you know, take old legacy systems and and implement, you know, them in in a new way.Ryan Aytay: I think there's maybe two things I would talk about. You know, the first would be, you know, we work with different different types of, you know, we'll call it the Department of Defense or Department of War, you know, pick your pick your term for that. But, you know, in certain cases there are of course a lot of and I have to be a little bit careful so I don't kinda go into too much detail. But you can imagine, you know, like we're trusted by the Air Force, which I think is a fantastic thing. But ultimately, know in these environments there's a lot of different data.There's different data silos that have been set up. There's data that's been around for years. There's newer data. But ultimately, you know, when we're in a world where there is sort of this concept of we'll call modeling and simulation of like what actually happens, you know, if let's say scenario a happens and this other scenario happens, like it's a war gaming effort, right, over time. It's a modeling and simulation effort.And, you know, we have worked closely with the military to basically build what we call a platform. It's called war matrix, which ultimately is something that kinda brings in the different, you know, data modules or or call them call them silos, if you will, and bring that data together. Of course, that brings some of our, you know, code translation, modernization, and integration together and then build a simulation engine on that, of course, which is powered by many different things. But it allows, I think, for a pretty robust experience so that you can go through and do quite accurate and real life scenarios of like, well, you know, and again, don't wanna go too deep, but like, if this happens, then this happens. Right?And again, I can't give you like specific examples quite at this point. You wouldn't want me to anyways. But really that, you know, so modeling and simulation is relevant, of course, for a military environment. It could be relevant for, you know, logistics environment. It could be, you know, relevant for even like a sporting environment, like an f one scenario.There are many different scenarios where modeling and simulation become important, but you can't really do it well if you don't bring the data together and you don't do it in a way that makes it, you know, fully translated and kind of all all in one experience. So that's that's one thing we do. I would say the other thing we do if we go back to like the translation, you know, modernization and optimization component where we verify things using formal methods and a number of the different, you know, test suite functions that we have. And we work with a lot of, you know, call it defense companies. Right?And I won't name them, but they're pretty obvious. There aren't that many of them. They support the the US government. When you think about a company that, you know, let's say does software defined radios or a company that does like, you know, surveillance equipment or a company that does, you know, critical communications equipment out in the field, you know, they are in many cases built with legacy code. Let's say it's c plus plus And that code base ultimately, you know, it's not safe, meaning memory safe.It could be subject to bad actors. It could, you know, a number of different issues. It may not run at the performance level that, you know, the the customer wants it to run at. And so what we do in that case is we can go through and say like, you know, hey, we'll modernize, you know, a million lines of c plus plus to Rust just as an example in a very fast way, in a very efficient way, and we'll guarantee that it will work on the device that you actually need it to, like the ones I mentioned before. And so I think that's a, you know, that's also in our sweet spot of what we do.There are many I think what I'm finding in this in this environment is there are many legacy problems that are defined by code similar to that slide I showed, which are mission critical in nature that need, you know, modernization, that needs translation, that need need optimization. Now some are easier than others. Right? So you could say actually c plus plus to Rust may be slightly easier to tackle than let's say like a MATLAB to VHDL type of thing. Those are a little more difficult, but again, we can do these things.It's just a matter of like how does the technology progress. And of course, I also I think it's important to call that we have many great you know, when I think about things like formal methods, we have a team of people almost like a a research department that we've brought brought some of the best people together, folks that come from places like NASA or Stanford or, you know, AWS or, you know, think of some of the great companies out there in great academic institutions. And so we're building an expertise, you know, around formal methods and around verification and validation that I think allow us to make sure that provability is something that we will stand by. And it's really when you think about CodeMetal, you know, we are in many ways focused on safety but also focused on trust. And I think you need in this world to be able to do that.And so lots of use cases. We're just getting started, but so far so good and a lot of great traction.Jordan Metzner: Okay. Awesome. Tell us just maybe one more question on just like kinda how the company got started and found its niche in the space a little bit.Ryan Aytay: So Peter Morales, who's our CEO and founder, you know, worked worked in a number of different places. Started his career with MIT Lincoln Lab, you know, worked in a number of different things, worked on the f 35 and some simulation environments. I believe worked at Microsoft and a couple other scenarios. And I think found himself, you know, doing a lot of academia and, you know, teaching of some of the things that we've talked about here today. And I think really just had a concept and an idea of, like, you know, this concept of mission critical and, you know, how do I make even, like, hardware as programmable as software?It was kind of the original thesis or North Star vision. And I think, you know, CodeMetal was formed from that like roughly two years ago. And so, you know, ever since then, I think he's done a really fantastic job along with the rest of the team and his cofounder Alex to ultimately bring, you know, a lot of these things to life and put them into use with really important, you know, mission critical scenarios like, you know, wargaming. Like, we know that we need to be thinking about these things. It's really just a planning and preparation exercise that, of course, you would want your military to be focused on.And then, you know, it becomes relevant. You know, think about it's relevant automotive, you know, medical device, financial systems, like a lot of these things have become fragile over time. And you can't just assume that, hey, I'm just gonna release, you know, said AI platform to go solve it for me because as we know, sometimes these things have, you know, hallucinations or other problems that occur.Jordan Metzner: Yeah. Awesome background. Great story. I can't believe how, you know, how much progress the company has made with, you know, these types of industries that obviously historically move slow and take a long time to work with that, you know, you've gotten such progress in such a short period of time. So that's that's really impressive.Great little history, Sam. Should we jump into the news?Sam Nadler: Yeah. Let's do it. A lot of news lately. A lot of newsJordan Metzner: in AI. I mean, it's nonstop. I don't know. Where do you wanna go, Sam?Sam Nadler: Well, unfortunately, I didn't choose a very AI themed news. I did choose more of a meta themed news, but I thought it was fun. Meta debuts their new cheaper smart glasses. I don't know if you guys knew this, but about a week ago, Snap unveil Oh,Ryan Aytay: they're they'reSam Nadler: very thick. They're super thick. And they're also, like, $2,000, I think, while these appear to be, you know, $2.02 200, $300. And then just maybe we can wrap this up into one kinda high level thing. You know, Meta also plans to do a prediction market.Sounds like it will be arcade point based, and that if those points translate to dollars, I don't know. Ryan, for context, one of our best episodes was about building a bot for prediction market. Would love to, you know, a, is Meta have the better glass strategy or Snap? And what do you guys think of this prediction market plan?Ryan Aytay: Well, hey. Look. I I'm an optimist generally, but when I think about, you know, I had the early pair of the Meta, like Ray Bans. And I remember I took them to Yosemite, and I kept trying to, like, ask, like, what am I looking at? And this is, like, I think two year roughly two years ago, right when they came out originally.And, you know, for me personally, I've I've always enjoyed the concept of, like, hey. I don't wanna have to be, like, looking down at my phone. I think that's the thing that, you know, glasses like this. It basically gives you a new interface and a new UI to kind of not only look at, you know, what am I seeing, but ask questions and I think get a different perspective. That said, I feel like there's a bit of, you know, there's probably the concern, like privacy concerns that exist out there.Like, am I being watched? Am I being filmed? You know, one of the things I always like at least to tell my kids because I have a 12 year old and a 14 year old is like, you're probably always being watched at this point, and so that's why you need to be very careful about what you do in life. But look, I think the form factor's interesting. I think we're early.You know, the more competition in this space, the better. And I think making these things accessible to other people is great. And, you know, will it be the form factor that, you know, is is vision, you know, a form factor? Probably. In fact, you know, again, I bought them, so I'm I'm an easy test case.But I think there's also voice as another form factor and have, you know, many other companies like OpenAI and things are working on various things to come. So I think it's an exciting time. And, yeah, I think on the prediction market one is like a whole bee's nest of a topic to go through, but I feel like it's exciting and perhaps maybe a way to see, like, more accurate results because it's, you know, less influenced. But I I do I have a a slight concern, like, anything you turn into, like, a gambling scenario or, like, the ability where someone can make a certain amount of money, then that could influence it. But I you know, if there's a way to, like, somehow moderately regulate it I mean, it's obvious why more people are getting into the space because I think, like, the what is it?The Kelshys and the what's the other one? Polymarket. Right? They're everywhere. Right?And and they're, you know, potential good predictors of what's gonna happen in some ways better than, you know, legacy media scenarios. So I think and polls. So I think it's a new world. And I think, you know, being open but being careful is kinda how I look at these things.Jordan Metzner: I think from my perspective, I mean, the Meta Glasses are super interesting. They brought the price point down, obviously, that's really I mean, and then they brought in Kylie, which I think is obviously interesting. I personally think still think like the camera's a little bit creepy. I think if they made like a no camera versionRyan Aytay: two things right here.Jordan Metzner: Well, they're just like, you know, people in certain scenarios don't want a camera on them like that. Well, I agree that like you're being recorded, you know, part of that is kind of the cameras get obfuscated in your normal day to day life, so you try to, like, kind of act normal. But, know, I don't know if you heard, but, you know, they gave away some of these meta glasses to to veterans who have vision problems. And so it seems like, you know, this is like an optimal use case, which is you have vision problems and these glasses can help you. And even if you don't have, you know, like like you're not blind, I can just you know, my parents used to like always have to put on glasses when they go to a restaurant and, they, you know, they show the use case of, like, you know, read the menu for me and see what I like the best.And so it is an interesting, you know, type of new user experience. And obviously, at $300, it makes it pretty accessible. I don't know what they're gonna do with specs at $2,200 plus the, like, cauliflower ear Yeah.Ryan Aytay: The fashion statement.Jordan Metzner: Yeah. Yeah. But but it does seem like early days. And obviously, know Apple's working on it, of course. Joni Ivett, Yucky mentioned at OpenAI.Sam Nadler: Did Joni Ivett confirm he was working on glasses? I thought it was still a mystery what the device I don't know. Was going to be.Jordan Metzner: But I mean, you know, market convergence against like, you know, interfaces. Right? And so, like, it's the same reason why like all the iPhone looks the same as the Samsung phone, you know. I think like we're gonna find convergence on on glasses as well. So anyway, hey, Ryan.It was really great to meet. Thanks for joining us today. That was super cool to learn about CodeMetal and and just like a whole area where, you know, we don't even think about basically, you know, like six five nines of, you know, confidence and making sure systems will work and, you you know, everybody gets back to to their family home at night. So that was that was really awesome.Sam Nadler: Yeah. Ryan, where can people find you?Ryan Aytay: So I we actually just on the website, LinkedIn, you know, I do a lot of posting lately. We've got a couple exciting announcements this week as well, so we'll be we'll be getting those out this week and next week and code metal..ai. So we look forward to to chatting with you guys again. Perfect. Thanks, Ryan.Jordan Metzner: Alright. Thanks, Ryan.Ryan Aytay: Have a nice Alright.Jordan Metzner: See you guys.
