Tech Brew Ride Home - (Portfolio Profile) Onix

Episode Date: August 21, 2026

In this episode, we explore Onyx, a platform that enables experts to train their own AI models to help millions with health, wellness, and personal development. Founders Nicholas Nadeau and David Bennahum discuss how their domain-specific, trust-based approach is reshaping AI and expertise sharing.

While I am on the road today, here is a portfolio profile episode. As ever, if you'd like to invest in companies like this one alongside me and your fellow listeners, check out right home fund.com. IT pros can't always be about fun and games until there's a fun game to actually play. Today's sponsor Eaton created an online card-based game called Ace of Uptime, and the whole idea behind it is to give IT pros a sandbox. You can practice problem solving and decision making and have some fun in the process. Each level of the game, you go up against a familiar foe like old processes or silent system failures. Your delta scenario, you choose your solution, and then you see how your decisions play out. Will it resolve the problem? Will it escalate it faster than expected? Start playing and find out.

Head over to Eaton.com slash ace to play ace of uptime. That's eatin.com slash ace. Welcome to another weekend bonus episode of the Tech Brew Ride Home. Brian McCullough, as always. We've got another weekend bonus episode for you, a portfolio profile episode. We're going to be talking to a company that the Right Home Fund has invested in. It is Onyx. It is AI.

It is something that's very exciting. We're talking to the founders today. We've got Nicholas Nato and David Benahum. Nicholas and David, thanks for coming on. Thank you so much, Brian. Nice to be here, Brian. So let's do this first. I always like to start with like a 30 second sort of elevator thing of like what it is that Onix does.

And then let's go into the product a little bit. Oh, you like a little quick pitch, eh? Yeah. Sure. So Onyx is a platform that enables people with meaningful expertise accumulated over a lifetime to train their own custom AI model that we provide that then in turn can be given to the thousands or millions of people. for whom accessing that expertise would otherwise be impossible to help those people with really challenging aspects of their lives in health and wellness. So the focus being wicked problems in areas of health and wellness with world-class experts

in that domain that could change your life. So let's pick one at random from the current slate of experts that you have on there. Like, give me somebody that I might want to talk to and how I would talk to them. Yes, so Dr. Jordan Metzl, who is at the hospital for special surgery in New York City, is a leading sports medicine doctor, also an extraordinary athlete in his own right. He's done, I think 40 marathons, 30 plus Iron Man triathlons. He's written multiple bestselling New York Times books, and he's a legitimately astute, deeply researched and intelligent physician. Again, expertise being recovery from injury in sports, whether you're a performance athlete or aspiring just to do something, he's your gem. And he has blessed us with several decades of his proprietary knowledge, right? The material that has not really gone online, that's his working papers, his memos, his notes, his books. We have trained what we call an onyx.

That's what we call these agents onyxes. The Dr. Metzell Onyx is a world-class onyx in this domain. and I will tell you more, but that's a highlight of an example of the kind of expert we might have on the platform today. So the idea would be, I download the Onyx app,

I pick from the current slate of experts, and I'm chatting with them as if they are them? Well, you're chatting with their expertise. The mechanic you described is correct. We're in early access on iPhone only, Android coming soon. Early access means you need an access code to get in. You can download it, but absent the access code, no can do.

That's intentional because we're really doing a shakedown cruise on some of these elements. Having said that, for your listeners, we do have an access code. It is simply Ride. R-I-D-E with the access code, ride. You will get access to Onyx. So, having said that, yes, if you're coming in, say, as a ride-home listener, you'll be landing into the application with no known reason why you're there, you're not coming in through one of the onyxes directly, which is another path.

You'll be greeted by the onyx advocate. It's essentially the conciergeers that gets to know you. And based on your self-declared reason you're there, like, hey, I broke my leg, I need help, or I'm suffering from long COVID, I need help. You know, it'll triage you, so to speak, and then introduce you to some number of experts, meaning models trained on this knowledge of specifically experts on our platform. And then you will tap and move over to that expert and begin your journey. your wellness journey with that known experts.

So that is the way. And typically if you are coming and say from Dr. Metzell, who we talked about earlier, from his landing page with his code, then Onyx is smart about that and we'll say, oh, okay, this is the Metzell code.

Let's have Dr. Metzell actually welcome you into the application because you're here for him. And from there, of course, you could always discover other experts and so on. But those are the two doors, right? So it is a marketplace in the sense that as you're, and we can get into the business angle of this in a second.

But these experts are able to say, hey, listen, you know, I have my books out there. I have my practice, but, you know, I'm only one person. I can't, you know, help everybody. But in essence, you can, in a supplemental way, interact with my expertise because, what? It's trained on a, like, a private corpus of their writings, their, they're lecturing, all sorts of stuff like that, right? Yeah. There's two pieces. So that's one is the technical piece, which I think you'll explain in a moment how the training actually works.

And the other is just a sort of philosophical one. So philosophically, if you just think about it, every one of us that has knowledge who are in the knowledge industry, you can only see so many people a day a week a year. And that's generally been true, as it is today, as it was a hundred years ago, like you could probably only see. see a couple hundred people, you know, as a doctor or a year, give them meaningful help, right? So what would it mean if your onyx could faithfully render that assistance without you needing to be directly involved? The answer is, well, that's pretty amazing. It could be thousands or hundreds of thousands or millions of people that you could reach.

But here's the key thing. It's the fidelity of that representation does not meet your standards of quality. It's garbage. You do not deserve anybody's business. We don't deserve your business. So this is where Nick, you know, and I think the quality of the trading is so essential, these experts, they don't ultimately believe that the thing that represents their brand equity and their knowledge deserves it, right? Because these experts are in mission to heal the world.

That is their mission. So if this thing is not prepared to do that for them, as them, so to speak, or as their knowledge, we don't deserve their business. We don't deserve your business. We should pack our bags and go home. And that's a tall bar. That's the one we've met. And I'll let you talk about how we got it.

Yeah, no. And it's really fun because when you take a step back and really think about, you know, what does it take to build models and all that? We're probably one of the few companies that don't really have a data bottleneck. We're working and building this trust with these experts, bringing in their public data, bringing in their dark data and really creating a human-in-the-loop effect for, you know, self-improvement with these experts as part of it, the AI, not as a separate, you know, pitch it over a fence or scrape from them.

And, you know, you create these alignment gaps. You create these actual, you know, fidelity gaps in their, expertise, how it's presented, and how it, you know, behaves to their intent. And so there's really three layers of data that will bring in. And, you know, one of the few companies are probably asked permission to use the data of these experts, you know, unlike big AI in a lot of ways. And so we'll bring in, you know, when we start working on experts, we'll bring in your public data, all the books, your podcast, your substack, your blog posts, and a lot of these top experts in the world, special health and wellness, they have big public presences. Most of our

experts, you know, millions of followers, YouTube followers, subsacques, subscribers, books sold, you name it. They have a lot of data and missions already out there in the ecosystem. And it's the same type of data that, you know, all the big AI companies have already scraped up and gobbled up. And so instead of merging all their data with the 4chan and Reddit and Wikipedia and God knows what else data, that is the statistically average vanilla response that you get from the frontier model providers, what if we actually built models based on just this corpus based on just this vertical with a focus? And that's one reason why we chose like the SLM route, my background in robotics and whatnot really focus on building these domain-specific models

that can say no, that's stay in their lane. And that's why having an array of multiple experts, hey, the nutritionist model reaches the limits that's trying to go out of the band. Let me introduce you to the sports medicine expert. Hey, let me introduce you to the psychology, I give you psychiatry, whatnot. You can actually bounce around these experts instead of them guessing and reaching to areas that's not in their domain. And so once we get past, you know, the public data, which we've put out some technical

reports, we already passed the frontier models on expert fidelity, accuracy, and ground in this just off the public data, we start to bring in their dark data. What is the data that you've written down but you've never published? The manuscript, the memos, the notes and rough drafts that went into that book or went into that podcast. Not the polished pristine stuff that sort of loses some of your personality when it's put on the internet, but really the rough drafts that show me your thinking, show me how your ideas come together.

I love that kind of stuff. And then we get into the really dark data, the stuff that's never even, you know, exited your head until with our system, with us in the loop, with working together, we discover things that, hey, you've never made this explicit. It's always been an implicit part of your practice. And so one example is, I guess it's a couple months ago now,

we put out a blog post, but one of our experts, Dr. Dave Rabin, he's a psychiatrist and neuroscientists, you know, big in terms of stress and recovery. And, you know, one of the pioneers of, of psychedelic and PTSD and things like that and recovery around that. Really awesome guy. And we noticed that, you know, all the generic models and the baseline, if you prompt to say,

hey, you're Dr. Dave Rabin. Tell me what you think about this. It'll reach towards like, you know, psychology 101, polyvagal theory and things like that. Because that's a statistically average response because there's nothing in the corpus to say otherwise. But when you start to, you know, talk to Dave, he's like, well, I personally don't subscribe to that. That's not part of my practice.

And wait, let me say specifically what, because when I read the piece, whatever polyvagal is, even though what you're saying is a generic model would say, would get into polyvagal stuff as whatever. But what Dave told you was, well, but actually I wouldn't. I wouldn't as a person, as an expert. But he's never explicitly wrote that down anywhere. Like, I hate polyvagel theory. Never say that.

He's never had to because it's always been his personal practice and he's, his approach the problem. Working with us, human the loop, making sure our experts are part of our, you know, the active learning of this system, we bring in this dark data that's always been implicit in their practice to make sure that the models we put out there on our platform best represent them not only from an accuracy point, a groundness point, a fidelity point, but also a judgment point. How would they navigate this workspace, this problem space with the user? And that's where, you know, if you think architecturally of how we've built this, it looks much closer to, you know, ClaudeCode, cursor, windsor, there's a workspace we're

working together on with the users in a health and wellness journey. And we're trying to get to some point B. And it's through iterations, through judgment, through, you know, this process and not just a transactional chit chat. So to really be explicit about this, what we're not describing here is Dave Rabin as a digital twin that will tell his jokes or whatever, but it is Dave Rabin who, as opposed to, even if you go to one of the generic models and they've scraped all of his data, and as you're talking to him, it's bringing up polyvagal theory or whatever, he's saying to you, but if you were in the room with me in a session or whatever, I would never bring that up. I would never bring that up.

And so essentially, that's the difference here. It's not, again, a digital twin, but it is more of a, what would you describe it as? like an avatar of their expertise. It is a true representation of them expertise personified, if you will. And that's our core belief is that, you know, expertise, there's two parts to it. There is the factual components, you know, all the textbooks and papers you've ever read and written and whatnot. And there's the personality, judgment perspective point of view, that taste, that, you know, David likes to say terroir and provenance, whatnot, bring those together.

That's what expertise is. Whereas all the other models out there, what they put on is a facsimile of that. There's a mask that they pretend to be these people. They're just basing it off of statistically average data they've scraped and collected. So each expert has worked with you to refine this and be like testing it out and being like, well, I would never do this or I would never say that. And it's interesting because your model is, again, not just a marketplace where we're selling these avatars of these people.

But it is they're able to go out and say, hey, this is me, and if you want to plug in and interact with me. So they have an incentive for it to be accurate because they're also, in a sense, putting this out there as a representation of their thinking. They're setting a price. I mean, just to be clear, on the business model, you subscribe to these models, right? In some elements similar to aspects of substack, like, oh, you have a paid newsletter or free newsletter. Well, paid newsletter is what it is.

my paid model is what it is. And I set that price as an expert. And I keep 70% as an expert. And Onyx gets 30% for the effort of just everything we're talking about here. And if the expert doesn't make money, we don't make money.

And we don't charge them anything else. Like we're not going to charge them on a set of fee and yada, yada, yada, yada. Like it's basically, if you're invited on the platform and we agree to work with you, we're investing in you. We believe in you as talent. And we're business partners. You're not our client. We're not your vendor.

Don't think of this that way. business partners and we're going to build an amazing business for you, scaling your expertise to the world. And if we don't believe in your expertise or believe you're going to have the Moxie to promote your expertise, it's on us to say, well, why did we bring you into this platform? That doesn't make any sense. So there's a real alignment of interest here, right, which is to get a massive audience to your knowledge. Yeah. So this is coincidental, but offline, um, you both know that, um, we had some, uh, health issues with, uh, one of my children this summer. And so like one of the things, one of the experts that you have on there is like in

pediatrics and things like that. So in essence, I'm going to imagine that when I was having this health issue with my child and it was a rough couple months, if I felt like there was an expert there that lined up with what I was going through, educating myself with this new health issue that popped up and how maybe we would have to deal with it, how our lives might have to change, to deal with it and things like that, I could subscribe to that expert. And as opposed to going to chat, GBT or Claude, and, you know, hoping for the best,

you're saying it's a more targeted sort of that. It's a more precise tool. First of all, I'm sorry to hear all of this, Brian, and I'm glad that you've gotten through. In your context, not only would you have had the opportunity to be with potentially the right pediatrician for your child, but the other thing we would say you could have done

is you could have invited your spouse into the chat with the same AI pediatrician, and we do support group chats where you can have multiple human beings who are a care team together, like your parents care deeply about your child, and what does it mean then to have both of you in a conversation with that AI

working on your child together? Those are like brand new modalities that start to make a lot of sense. In our model, we also offer that you could say, hmm, there's a pediatrician in this chance, at, but I'm actually, let's just say, suffering as a parent in terms of grief. And is there a person who can help me with my guilt? Which is not a pediatrician, by the way, it's someone who's good at that. And I might say, well, geez, I actually want to be in a chat with the pediatrician and that person

who can help me with my grief as a dad because somehow the synchronicity of the two points of you will help me care for my child better. You know, we need to nurture the caregiver as much as the person receiving a care. And now you've got this ability to do. do a group chat with two or more of these agents together. And again, it wouldn't make any sense. Oh, at the same time? You're saying? Yeah, precisely.

Yeah. And we think that elevates, you don't have a care team, especially assembling around you. You have a world-class team of people who could be a nutritionist, a fitness person, and a pediatrician, all coming together, three points of you, working as a team for you and your son. That is what we unlock. And it would make no sense to do that with open AI.

Like, what would it mean to have a group chat conversation with open AI, open AI and open AI almost had open AI let's have like that means focused now when you have something trained on a specific

body of knowledge as Nick was talking about and something is really interesting and you could see how not as interesting it would be if you munged together the therapist and the pediatrician's knowledge to do one blobby thing

welcome to open AI that is why they have so many problems they've not just munged in those two things they've munged in a billion things or more. And welcome to hallucinations. Welcome to the average answer. Welcome to the shit show. And as we all use AI more and more,

we're kind of like, huh, man, there's a lot of noise and not a lot of signal and responses. What is going on? And so there's a crispness to that type of group chatting that we don't know any other product actually today that offers that type of agentic group chat. Yeah. Well, I want to give one more use case

because I kind of was going with a more stressful use case, but like, there's nutritionists on there. So let's imagine that you're going through, you know, a weight loss journey or, you know, like a New Year's resolution sort of thing. And, like, you can do things to, you know, help coach yourself through eating better through exercise, that sort of stuff. Ever woken up and needed a cup of coffee just to feel like a person? If you're thinking, yes, daily, then listen up. Ultra pouches partnered with leading neuroscientists to design these pouches. They use clinically proven neutropics and adaptogens to help deliver immediate focus and smooth energy that lasts one to two hours with zero nicotine and zero caffeine. Yep, it's

possible to feel energized and focused with zero nicotine or caffeine. So don't sleep on ultra pouches literally. New customers can use code TBRH to get 15% off at take ultra.com. That's take ultra.com for 15% off with code TBRH. threats are like a hydra that learned how to type, cut one head down, and two more pop right back up, which means the old way we've been handling cybersecurity just won't cut it anymore. That's where Rubrik comes in. They've engineered a platform that secures your data, controls your AI, and protects your identity.

See how Rubrik helps you stay ahead of threats at rubric.com slash mb. That's rubr-i-k.com slash mb. Yeah, yeah. So I'll go almost personal. Like nutrition is a great example. Like, you know, there's a baseline of facts. Calories in, calories out, eat well, don't eat too much. Like I think all nutrition can basically, you know, agree on that.

But then like what's a vegan nutritionist versus a paleo carnivore? Like they're not wrong, but they're semantically different. And what the right nutrition advice for me depends on me, my, you know, if you will, my world model, who I am and all the context around me. And that relationship essentially that you build with these. you know, experts to go through that journey together on. And so personally, like I use onyx for my maraths for partner race training, my nutrition. I'll bring in Mark Sisson, primal nutrition, you know, organic, a little paleo, if you

will, and like Jordan Metzell for sports and recovery, them together are working with me. And then I'm in this grocery store, you know, what am I buying right now to help match my plans? Let me get into discussion in situ and not like what, sift through blog posts or Google searches or whatnot to trying to figure that out, I can bounce ideas off of and better prepare. We have a lot of our people who are using Onyx right now, even just, you know, power users love it for just preparing them for their upcoming primary care appointment,

empowering them and just sending them up for success to ask the questions they should be asking and getting rid of all that low-hanging fruit stuff that often, you know, takes up so much, you know, time. Looking at the roster of experts, again, and we're very early days that you've launched with. It is sort of health-related and sleep, nutrition, things like that. Number one, two-parter.

Number one, why pick that as like sort of the first vertical, if you will? But then second of all, what have you seen in terms of the people, the experts that are responding to this and why they seem to be interested in it and giving it a try? Yeah. Great question, Brian. And so you're right that, you know, a year ago, we would have been like, well, you know, we could do many, many different categories, right? You could potentially build something like this for self-improvement, for legal finance.

Right. Weightless. Dressing better. Dressing better. Lifestyle, restaurant advice, you name it. Like travel. So we kind of adhere to this notion of a sacrifice strategy that when you really want to prove something out, you can't be all things to all people.

You should really zero into what you think you can do really well. And then when you have a set of competing categories to do really well in, whether it's, as you just put it, fashion advice or health and wellness or personal finance, like what are the components as entrepreneurs we have to ask ourselves that we think is our moat and our edge? Like what are the things that is about what is it about this product that's special that when applied to a certain category really unlocks value for that category? Because if you look at it that way, it helps you essentially score the categories against essentially what you're trying to prove here. So let's just go with the first kind of thing we really deeply believed in, which is that we are really good at solving multifaceted challenges that defy easy answers, where the stakes are high. Right. And the reason why we want to be good at that is if things don't meet that criteria, then things like the Internet, the Google, the Claude might be really great places to go. Yeah.

But as you elevate the stakes, we want to be there. And so then you're like, okay, of these categories, which of these feel really high stakes? And much as I love fashion, you know, with a passion, I don't think the stakes are that high. Like, I don't think it's like quite the same level. Much as I love restaurants, I'm not clear the stakes are like changing whether my meal was two or five stars. However, things like personal finance, that's actually pretty high stakes and health and wellness is pretty high stakes. And in some domains you could argue legal is pretty high stakes. So right there, you've got three interesting categories, right?

And then you go a little further and you're like, okay, where does privacy and trust really matter? And again, you're left with just a handful of categories. Why do we say this? Because we do not read the chats. We do not, you know, use the chats to train other AIs. And this is all part of our principle, right? And so where are the domains in life where that privacy really, really matters. Again, you're down to just a handful of categories.

In fact, the ones I mentioned kind of bubble back up again, right? Now, when you get to the expert side, which of these categories might be really mission-driven where the experts themselves can bring like a very legitimate and unique body of work? And if you sort of look at it that way, it gets a little more complicated. I'm not clear personal finance is as mission driven, as health and wellness, right? I'm also not clear of the differentiation in personal finance. There's some granularity there, but I don't know if it's like that broad.

Are you a value investor or different? Yeah, I mean, there's stuff there. And certainly legal, you get into a real rabbit hole with legal. You know, it's very complicated. And I'm not even clear it's about individual expertise as much it is about the law, full stop. it's very complex and also very smaller, like how many people really need legal advice, et cetera, people, but the scale is quite there. So long story short, Brian, health and wellness started to really bubble to the top. And I think the big unlock with health and wellness was the

realization that we are a mission-driven company. We believe AI should be a tool for human flourishing, not a tool for surveillance, not a tool for extraction, not part of the attention economy, etc. And when you really line that up, the people who, practice health and wellness. A lot of people who woke up at the age of 14 and said, geez, I actually want to be a doctor. There are different people than the ones at 14 said, I actually want to be a venture capitalist. Like, I'm sorry. Like, it's reality. Like, I think the guy who wakes up at 14 or the gal and says, I want to be a doctor, that's a mission-driven person. Right? And so that gets us to, I want to work with those people because ultimately, if they have a higher commitment than just

making money, their commitment is to heal the world. Let's be clear. That's what these people are in market to do. The whole vibe of how we're going to go out there and change the world completely shifts away from a transaction. Like, how much money did you make me to how many lives that would impact? And that's an X more interesting. And you sort of underline it there. So I want to underline it a little bit that this is another sort of differentiator is central to your pitch to an end user is that it's encrypted on device, there's HIPAA compliance, all sorts of stuff. Like essentially, like, you don't know for sure

that Sam Altman might be reading your health, they say they don't, you know, etc. But you're saying that from day one, our point is this is all just for you. We're not going to train on it and all that stuff. We don't need to. We're building small language models where the data comes from the experts directly.

As I said, we don't have a data bottleneck the same way a lot of other companies see their data bottom. And not only like the Sam Altman point, they keep the records, all these things. So these things are subpoenaed, brought into court and now, you know, now your stuff is out on the open web through discovery and whatnot. Our goal is to have as much to, as close to zero in any database, even encrypted as possible. I just have emails in my database so I could authenticate people. We didn't even do passwords. We do OTP because I want the least amount as possible. Keep it all at the edge. Like this is my robotics thinking is, you know, as as this grows, my cost

of compute basically goes to zero because this all goes to the edge where we can deploy our small language models on the more and more powerful phones. And so that your safest space, your vault of your personal life is already on your phone, keep it there. We don't want it. But we want to provide you the value. And that's why like from a business model and how we architected the company, if we build our technology this way, if we build our business model where we rev share with experts and we subscription with users, our incentives are aligned. We're not trying to resell data or do weird, sketchy stuff,

we're trying to just provide value both sides. If we don't provide value to users, they churn. If we don't provide values to experts,

they leave. We are incentivized to do good by both sides of that marketplace. Let's go to the other side then. Let's imagine

that it's 18 months down the road, two years down the road, and I, Brian, let's assume that we buy into the fact that I know what it takes for 30 years

to do a startup. And I am a technology historian, and that's part of what being an investor is, is, you know, hey, here's the lessons I've learned when you're starting a company. Or my investing partner, Chris Messina, here's what I've learned for 30 years of designing products, right? Yeah. And I sign up and I, you know, give you, you, my public stuff, you know, you've got 3,000 podcast episodes you could go through. But, you know, like you said, the stuff that maybe I haven't published my, you know, what, what? what do I get out of it? You're saying that I get 70% of the revenue. So this is a new sort of product that I can offer. But also, what about ownership? What do I take away? What do you take away if we part ways all that good stuff? So in our agreement together, you have the ownership over all your intellectual property. So everything that's put into your model belongs to you. And we explicitly say we have no right to use that to do anything other than train your mom.

That's number one. We also say to you, this is completely non-exclusive. Meaning if at the same time that you're with us, there's somebody else doing something similar and you want to try them too, not a problem. We don't deserve your business if we're not the best. Number three, if you're not happy, you can leave for any reason or no reason at any time without a breakup fee or any sort. at all. We would just say to you, let your existing paying subscribers finish their firms, at which point we will delete your data, delete your model. We have no right to maintain your model either. We've been very, very rigorous about these points because ultimately we're here

to support you and being successful. And we don't think there should be any other aspect of this relationship other than you being successful through our partnership. It's, I'm sure you've thought of this, but, you know, I thought of this. This morning was like, you know, someone that does what I do, like a early stage investor. I could put myself out there and someone could work with Brian, Brian's Onyx for a couple months, asking questions as they're developing their startup idea and their product. And they're like, you know what, Brian? I like working with Brian.

Brian has good ideas. Like, I'm just thinking of this through an investor lens. Like that could be a way to be like onboarding people to be like maybe I want to work with Brian. So any walk of life, I could see that somewhat down the road. Yeah. Okay, let me back up and ask about y'all. And let's do Nick first because I've known you longer, Nick. You come from AI in robotics and things like that, right?

Yeah, no, in French, we say, Dorset, too, a person who touches everything, started my career off spent a decade and actually in biomedical. I was a mechanical biomedical engineer major. Right. And built surgical robots, brain implants, cognitive neuroscience, imaging, simulation, things like that. That's where I really cut my teeth. Did class one, class two medical devices. Never want to do that again.

Clearly why we're saying health and wellness and not medical. But then I caught the Sarah bug. Joined as head of engineering of Aon 3D, YC, Winter 17. You know, built 3D printers that have parts on the space station, the moon now. Then became the founding CT over at 1X, X, scaling humanoid robots before the chat of before all that, and that's when you and I first started chatting a bit. Really interesting time to be in the robots ecosystem. You know, before physical intelligence was even a term,

we were doing end-to-end learning, you know, essentially small models on these, you know, embedded devices. It's really awesome when the first Jetsons came about from the Nvidia. Like, oh, we can actually have compute now at the edge. We can actually do things where you have a multi-orchestrated system with smart things running around at the edge. And then maybe like cloud or things on the edge. the back end, you're going to have your computer and redeploying that to the fleet and seeing that

that closed loop ecosystem, which inspires a lot of the architecture we have now, essentially. For me, whether it be robots or AI, it's all the same thing. It's their agents, whether they have arms or they don't have arms. These are all action-oriented systems that are trying to, you know, achieve a purpose. In parallel to that, did one of the first PhDs in physical human robot interaction, right, the Cobot Revolution and the first neural networks in like the early, you know, 2010's late aughts where we said, hey, can we, you know, control robots with these new things called neural networks is when ImageNet and AlexNet and all that started coming out. Like really interesting to see physical human interaction, social interaction, just collaboration

between human and intelligent systems. Had my exit from 1X, went to become the global CTO, well, started a services company that got acquired by one of the largest data labeling companies. So I got to see inside how the sausage was made of all the big AI models, how all the major enterprises transformed, annotated their data, built some of the human data factories in like Madagascar and Africa and whatnot. So we really got to see, okay, what did it take to build the data machine? And then when I exited from there, you know, I was putting around the ecosystem,

looking for my next thing. And that's when, you know, through founder dating, essentially met David. I thought he was crazy at first. but, you know, lo and behold, here we are. Well, before I get to David, your bio, Nick, says that you're building the opposite of that. I'm really trying to build the opposite of that. You know, I saw, transform, sold whatnot,

a lot of the internet data, found some of my, like, cringe posts from when I was 14 in some of these data sets. And I said, you know, I'm not getting compensated by this. I didn't give anybody permission for this. Once you see inside what it takes, and you realize, like, from the robotics world, there could be a different way

if we just bring some of those paradigms over, we don't have to default to like the Web 2.0 extraction exploitation economy. The attention economy is just a default way because it's worked for so long. Can we build something different? And that's where like when I met David, the thesis was, you know, we're an interesting time. Can trust in privacy actually make the product better and not, you know, be a hamstring? And that's really been the core thesis of everything we've done at Onyx since then. David, I could have a whole hour more long conversation with you about the fact that you were like a founding writer at Wired and stuff like that.

But is this your first jump into a startup? No. Okay. No, I've had the privilege of, as you alluded to, being in this industry for a while. Yeah. I think we all kind of have our origin points. for me it was being 13, getting my first home computer when that was like a really new thing

in the words not a large popular. You got a, you got an for this audience, you have to name the computer. Atari 800, 48K of RAM, two dual bay drives with 512K max on the floppy and a 1200 board modem. See, that's how you do it.

Yes. And so by the way, that device, that Atari is about 40 feet away from us right now. I saved it. It still runs. Except now what we've done is I connected the serial bus to a Wi-Fi sort of repeater that is weirdly some dude makes these things to go into 8-bit computers. Wow. And now my Atari is connected to the internet. And then from there we connected it to Claude.

So now I've got Clod in there. And then I had Clot build, among other things, Tetris recently. Because Tetris didn't exist. We're vibe coding Atari games at the office. And running them on an 8-bit machine. It's really awesome to see the continuity of the joy, right? Because for me, this industry and tech is just a source of joy. It's play, it's fun.

It's discovery, it's exploration. I bring a humanist point of view. And I think part of what connects us next is we both share this very strong humanist perspective in what we're building and what motivates us. So everything I've done in my career has been around this, like, how does technology make a difference in the world, improve our lives? I've always just felt that strongly. And I was part of the first wave of kids to take the first AP computer science exam.

That's a weird fun fact. I was paid the program at the time I was 15, which was kind of weird and cool at the time. And then to your point, I came out of university knowing how to write, which was interesting. And it coincided with the onset of Wired Magazine. And in life sometimes you're in the right place at the right time. And I was in that right place at the right time. And so I found myself part of the earliest team at Wired. I ultimately ran the New York Bureau for WIRED covering Internet 1.0 and had the real privilege of being with so many of the folks that essentially built this thing we now use.

And it just never stopped. So reading the writing on the wall a little bit as a journalist, I ultimately in the late 90s exited out of WIRE and went to work for one of the largest ad agencies in the world running digital strategy. Amirati Purist was what it was called. 7,000 employees. I was like, what the frick am I doing in this ginormous thing? I'm an executive vice president. I don't even know what that means. It just means that I'm like really senior.

And I had this big job, which is doing all the digital strategy, all the storytelling. And we worked with things at Unilever and Burger King and all this stuff, but critically, Dell computer. So I was part of the team at Amaradi that got Dell as a client, which was probably one of the biggest deals of the year for any company anywhere on earth. It was a billion dollars of media spending. For those of you who know the ad industry, the commissions are massive, et cetera. And we created the Delph for Me identity,

which came out of my group, right? So literally the notion of mass customization at scale, creating those narratives, and that's what won the deal ultimately. And that was their brand identity up until two or three years ago, right? Delphor me, you guys may remember that. Now, why do I bring all this up? Because one of the things that I love to do is create meaning

in the companies I work on. And essentially, you're creating a narrative, right? Because if you're really innovating something new, you're kind of ahead of where people are, you need to create that story. And so I think of it as narrative infrastructure and the things that I work on. So I also had sort of post-the-agency time.

I worked in New York City for kind of an early seed fund. We invested in a bunch of companies, some of which did rather well at the time, things like Media Bistro and Daily Candy, These were like early companies, et cetera. Now to go all the way through my whole bio, but just simply put, after 9-11, I was like, huh, you know, again, I was like,

is this really making a difference in the world? And I wound up creating one of the largest civic tech plays. This is, you know, back when it was rather novel. I essentially looked at blogging and said, hey, we could create replacements for the loss of newspapers across the United States, the belief being that news is good for healthy civil society. And given the absence of, a coherent business model, I'll just raise the money as a nonprofit. And I basically pioneered

the onset of nonprofit newsrooms. We ultimately had 150 writers. It's called the American Independent News Network. Probably raised like 15 million plus. It's still around to this day. I'm still the chairman of that board. And I think we've done $200 million of funding for this thing over the years. It's kind of extraordinary. Worked from there in gaming. I came back to New York at one point and basically started working in the gaming industry. I'd say the most recent thing I did was in blockchain. And I would say coming out of blockchain, I was pretty exhausted by that culture.

We did a lot of work around player identity, player ownership of game assets. It was really interesting technology, but I was really fatigued by the culture, which was extremely about financial speculation to be blunt. And I think it really hurt and undermined. What's good about the technology? So part of the purge and the cleanse

honestly was I thought with AI we've got to build something that can make a difference in the world that doesn't get sucked back into these negative values and to Nick's point earlier when you build something with the foundation of trust and privacy and have that actually be better in terms of delivering a product

in a highly competitive market called AI that is a fantastic place to be standing in so this is by far one of the most challenging and interesting projects I've ever worked on and I think our partnership is probably the finest one I've ever had in company building.

So I'm very grateful for that. Oh, that's ways to thank you. Yeah. If Bitcoin hasn't peaked your interest yet, then it might be time to get peaking. Cash app makes it easy. You can set up automatic purchases with zero fees or buy larger amounts, also with zero fees, start small or go bigger. It's designed to be simple either way.

For a limited time, new customers can get $10 added to their balance. Just use code Bitcoin 10. When you sign up, and don't forget this part, send at least $5 to a friend in the first two weeks. Terms apply. Cash app is a financial services platform, not a bank, banking services provided by Cash App's bank partners. Bitcoin services provided by Block Inc. brand. For additional information, see the Bitcoin Disclosures at Cash.com. With this summer's record-breaking heat, it's hard to cool down enough to get a good night's sleep.

That's where the pod comes in. by 8th sleep is a smart mattress cover that goes over your existing mattress and actively heats or cools each side of your bed independently. It connects to your wearable, analyzing your daily activity. Then it predicts how you'll sleep and adjusts the pods temperature automatically. What I love about the 8th sleep is the simplest of things, the ability to be cool when it's time to go to sleep and warm when it's time to wake up. And my side is entirely under my control. My wife can be whatever temperature she wants on her side of the bed too. Use code ride home at 8Sleep.com

slash ride home for up to $350 off. That's code ride home at 8Sleep.com slash ride home. And when you say founder dating, how did you get hooked up? So I mentor at like half the accelerators here on the East Coast from tech stars to like credit destruction lot of things like that.

Why I say where we actually are? We're physically in Montreal. We are building this in Canada in Montreal, you know, beautiful offices in old Montreal. come visit. And so, you know, Founder dating, yes. One of the fellow mentors that I work with,

she had worked with David previously in the blockchain side. And so when David had exited his last company, he was also like, I guess, putz in the ecosystem working up a coffee shop and said, you know, who should I meet in Montreal in the AI space? And so, you know, shout out to Mary Chantal. She's like, you know, you should meet Nick.

I think you guys would connect. And so, you know, mutual introductions started having coffee dates together over pre-Christmas holidays 24-ish, I guess. And then by the time, you know, January rolled around, I said, you know what, let's do it. Let's just start a company. We've talked enough. We've bounced ideas. We were adversarial.

You had some indurgial ideas. I shot them down. We came up with new ideas. And, you know, what converge is really like, there's something here. And if we don't act on it, like, it's going to pass by. Yeah. How did you, like, settle on this as an idea? because when we first spoke, there were different things in the mix.

But why did you settle here? Well, I mean, a lot of thoughts that are, Brian. So we definitely had some core principles that remain true today. And I think one of them is this notion of data sovereignty, right? That whether you're an expert or consumer, your data is yours. And it's an asset. And the more we empower people to value that asset through their use of AI and working with us, the more will be successful as a company.

So don't try to siphon away their asset. Data is hard work or not really matters. There's a bit of blockchain philosophy in there, too, as I'm sure you picked up the implications. So I do think that was kind of a bit of a north stuff, right, to begin with. Which is what Nicholas sold me on was that was, I was in just because, yeah, can we monitor, can I get a piece of my data that everyone else is getting rich? We had a notion around a building a gig economy around your data, right?

This is when we talked to you, Brian, way, way back in the earliest, the earliest of days. Now, I have folks I've known for many, many years. So when it came time to raise some money, like very early, I said, I want to go to my folks that I know at a particular fund, Alpha Edison, which is some of you may know about it. It's in Westwood, Los Angeles, about a billion dollar fund. And the two principles there are Nate Redmond and Nick Roth, Nick Roth in particular, I've known for many, many years. And I've never worked with him professionally, but I've always really admired his acumen.

He's built numerous multi-billion-dollar companies and has been just one of the most active. He was one of the first in agenic technology. He built something called Firefly in the mid to late 90s that was old to Microsoft. Like so early, literally the phrase intelligent agents, that's what they were doing. He built something called People PC,

which had an IPO and was basically giving people free personal computers that were ad-supported, pretty wild stuff. Really a great thing about consumer market, financial markets, and just the challenges of building technology. And so I called Nick. And I basically said, Nick, this is what Nick Nadeau and I are thinking of doing.

And he said to me, David, Dana Sovereignty is interesting. We don't think it's going to be necessarily monumental, but given our relationship and we wanted to work together, like I'll potentially do something, we'll give you a small little C check. But, but hear me out here, there's something we have been thinking about

around decentralized, distributed, agentic AI. And if you're interested in hearing us out on this, it's something we're really keen on. it's something we could work together on. And that was the beginning of where Onyx now are up to, because both Nick and his partner, Nate Redmond, really challenged a lot of our assumptions. And once they challenged it,

they put forward their assumptions. And we wound up going out to their offices in L.A. and having like a three-day working session with them. That was one of the most creative, I think. We had a few of those. Yeah, but just from the beginning, the first one. Yeah. And it was like, okay, you guys are not going to be investors.

you're going to be co-founders in this company with us. This is way more than putting capital to work. It's putting real knowledge to work, and it's de-risking a lot of our assumptions. So we brought them in as co-founders, and they're, of course, investors too. And I'll have to say to you that it's been one of the most critically valuable pieces in appreciating that less is more and making hard choices,

but doing it with people around the table who brings such a diversity of viewpoints and real experience. And I think, at least for me, having built successfully, unsuccessfully over many years and you as well, having done what you've done,

I'm kind of done with, like doing everything on my own. It's not interesting. This stuff is too hard. You need a brain trust. And what does it mean to trust people? Again, we're back to trust as a core value. Trust people early to bring them in

because you believe that they will help you de-risk, absent their knowledge. Yeah, maybe you could try to do it on your own. But actually it's going to be way harder, way more lonely, and probably not successful in the way this can be. So some deep life lessons there, you know, and that's some of the origins. I would even put an extra spit on that. Like, I've taken a lot of dumb money in my career. And, you know, there are times I just need cash, you know, come in, a follow investor, whatever, just fill in there on.

Great. But like, whatever I can do as a founder to de-risk the company, because from day one, venture is a very, risky business and you're more likely to fail than you are purchasing. So every step, every day in this like advice for other founders to find a way to de-risk, de-risk, hiring is de-risking. You know, which investors you work with de-risking.

Let me pause there. A lot of founders don't think about that. They think that the investors are just the money and the check or whatever, but money's a commodity. I can find any other forms of money. No. The de-risking is taking the money from the right people. That is maybe

one of the biggest things to the risk for the success of your company, for paying from the right person yet. And it's hard. Let me just be clear. Let's say not a lot of people with capital can help you do that. They might claim they can. They might think they can.

And I think we've all been to that rodeo where we've taken money from someone you thought could be really helpful. And in the end, it's really play out. So it's hard, Brian. Like, we all know this makes sense,

but actually doing it, it's really hard. Best case scenario, like the bad money is just quiet. Like worst case scenario, they're actually a distraction and pull you off, those rails. One of the biggest pitfalls, I think, as an entrepreneur, is you want to show boat with your investors and you want to spend. And it's like you kind of handle your investor as a

constituent to everything is good. And it's so toxic in the end because you're basically creating a culture of misinformation in a way to yourself, to your investors. And it's a terrible reflection of the relationship with the investor. They must not be very valuable to you, or you might not be able to handle tapping their value if you're doing this. And frankly, so often, and I've been guilty of this in the past, you know, like I'll manage a board meeting, I'll manage a deck, but I'm really dealing with the hard things because to really do with the hard things is to be vulnerable with those people, put yourself on the line and it's hard.

You'd rather just maybe spin it and be like hand wave it. And we're all very good at that. We're all pretty good. If we've managed to raise millions of dollars, we're very good storytellers, one way or the other. And that means you can tell a nice story, whether it's to your board or to whatever other meaning you're doing. And I think it's really a blind spot. And one of the things I learned over the years is stop doing that because it doesn't help in the end. And for me, it comes back to like on that, but unfair advantages. Like back to buying, like,

it's not just money. It's what doors do you unlock to de-risk this more that you can't get anywhere else? And running a startup is guerrilla warfare. I will cheat and find whatever way I can to win. Now, very ruthlessly. And who am I bringing on my team who are willing to get in the mud with me and fight this fight. That's what we're looking for is we surround ourselves with the smart people. I've kept you way longer than I promised. Let me end with three. Two of them are going to be a little poking at things.

Two questions poking at things. And then one specifically for David. So the first poke is we've sort of danced around this, the idea that, that, well, why can a general purpose model do this? But I mean, writ large, that's what everybody's thinking, well, why can't Claude come out with this product tomorrow that will eat your lunch, right? So you mentioned Terwar, which I loved, which I think Nick knows Chris and I, that's been our investment thesis as well. Can you make an argument or underline your argument again for why this sort of distillation, to use that word, of this? This expertise in a narrow field or a targeted sort of thing will beat the, oh, well, we have

all of human knowledge ingested in our model. I'm going to take the qualitative answer. And then I think you can do the quantitative. So here's a qualitative, Ryan. The moat here is trust. But you can't point to something like anthropic and say, oh, there's no way they could, like, technically, technically approach what we're doing. Of course they could.

They have a humongous amount of capital and thousands of talented people. But they don't have as trust. You've got a world of. top-tier knowledge creators, right? The doctors and so on of the world. And if you ask them, how do you feel about Anthropic and Open AI? They're angry as heck.

Why? They stole my work. They scraped it. Then they pretend to be me. And then they give people misinformation that I don't believe in. I'm so mad. I hate them.

So it's hard for those people to go to that community and say, you know what, trust us. We're going to build these small models trained on your knowledge. We're going to create this marketplace. I mean, they could try, but that's tough. I want to point out that what you're trying to set up here is those experts now,

you're giving them a stake. Yeah. So it is their name attached. And so they're incentivized to, there's no incentive for any of the big models to be like, well, this is accurate to X, Y, Z's philosophy or whatever. No. And if I give 30% of the revenue to Ashley Cough or Jordan, that's all. Just to finish on the qualitative side.

We do use this phrase, take back your genius, take back your genius, right? It does tap into a mission-driven anger that they've been stolen from. And then I'll just say, go in a time machine. It's 2000, 2001, Napster, Limewire, have stolen all the world's recorded music. And the industry says, I'm done. I'm never going to be making money as an artist ever again, ever. Because why would you? And the answer was, not through legislation, not their litigation,

company called Apple created something called iTunes. They found a beautiful way to organize music, sell songs simply for 99 cents, high quality, easy discovery, easy management of your library. And that actually broke the cycle. You could still go in pirate music today. Reality is it's no longer an issue. And the break point was 2001 with the onset of a piece of software that created incentives for people to come out of the cold and buy the real deal. We think the same thing will happen for the highest fidelity, AI knowledge. There'll be an incentive to actually put down some money on the table to get Dr.

Dr. Metzell and so forth to be your expert, because the fidelity and quality of that will exceed the bootleg, the bootleg being the version of Dr. Metzell, you can pseudo get clod to vamp and pretend to be, and when that begins to sink in, the highest value consumers in the world will be buying and renting onyxas on our platform.

And so the moat is really trust. It's really, really hard to dry clean yourself from being sullied as a giant thief that pillaged the internet for five years while we were sleeping and say, oops, my bad, come on my platform. It's like, dude, I'm not coming on your platform. You can bribe me, but then I'm a sellout with no integrity. And we'll take the people with integrity.

So that's the first note, right? This is a movement-driven thing. On the technical side, you know, they're trying to do everything all at once. They know the history of Japan, the French language, like a code and Python, and now they're very good at cyber attacks and whatnot. Our models are terrible at all.

that. Our models are really good and better at health and wellness, at nutrition, at sports medicine. And we see it across the domain now. All the papers that are starting come out is domain-specific models and especially harnesses. It's not just the model. It's the entire harness we've built around it. Is critical to higher and better outcomes in specific domains. We're not trying to build a general AGI model. We're trying to create avatars of expertise on the onyx platform that best articulates and represents these world-class experts at what they do on the journeys that is the user. We take a very world-model type approach in this space. There is you, the user, there's the experts in this workspace with you.

And from there, let's go on a journey. Very different than transactional chit-chat or coding or whatnot, deep research, things like that. This is domain-specific. Not only that. With small language models, you know, as time goes on, everything gets more and more on the phone. as the phones get more powerful, the models get more efficient. So my cost of compute goes zero.

The cost of compute over at Anthropic and OpenAI is very different than our cost of compute. And all of that is, you know, already we're, what, 200 times cheaper than, you know, if you were to try and wrap a big frontier model. So we are profitable at like $9 subscriptions. So the domain-specific architecture, domain-specific unit economics,

that's how we do it. Real quickly, and you don't have to hold to this for, you know, history or whatever, but right now you're being picky. You're turning people down. Like, you're selecting who is going to join the platform. Yes, that's correct. And you seem, you feel like you'll hold for that for the foreseeable, for the near future, let's say. Yes. Okay.

my final one before we wrap up and remind people what to do with what we've been talking about. David, again, my past life is the Internet History podcast and things like that. I've spoken to wired people. I've never spoken to Jane and Lewis. But I'm wondering, two minutes, what do you feel, what are the parallels or differences or whatever you want to say about, was like in 94-95 versus what you're feeling about the AI moment right now? Yeah. Well, there's an odd parallelism, which is very rejuvenating and refreshing. So in that 95 period, everything was possible. It was seen as this hugely disruptive shift in human civilization where communication would be abundant, information would be abundant,

connections between people would grow. And it was a very optimistic moment, right? Where it felt like a lot of the rules were going to get rewritten. And then it felt like there was also like a bunch of incumbents for whom this was extremely challenging and threatening. And these were like the canonical, it could have been the big media companies like Viacom. It could have been Microsoft as a kind of quasi-monopoly. I don't you guys remember back then, but, you know, Microsoft and Monopoly were a big deal.

And this was all about kind of a revolution or a change. And I see that the point we're in now with AI has some of those dimensions to it, right, where it feels incredibly disruptive. There are indeed incumbents in there rapidly that showed up. But those incumbents were the revolutionaries from before. So things like Google, et cetera, right? Some of them are new, like Open AI Anthropic. So it's not an exact parallel.

But there is a sense of rules are getting rewritten. A lot of the conventional wisdom is going out the door. And it creates a lot of anxiety. And in fact, the level of anxiety right now is way higher than it was in Internet 1.5. I agree. Right? The anxiety now is existential. Like somehow AI is going to lead to human extinction.

I, by the way, think it's preposterous. But, but this is a story for another podcast. Well, it's not only that, like, from the inside Silicon Valley angle, it's like, well, this is my last chance to get rich. Yeah. Like, after this, there will be no, the whole game's over. We all become farmers. Right. I'll just say that whenever a bunch of people reach this consensus, you know it's wrong.

You know what the thing might be right. But I guarantee you that this amount of consensus, historically, especially in the world of technology, has always been a signal that just don't do what they're saying. So having said all of that, this is one of the most fertile and creative periods. And a lot of stuff is getting it's set in some sort of concrete over the next couple of years. So there's a fluidity. But I think we all also sense that, yeah, things are going to shake out. And we saw that in previous cycles too. At some point it shakes out.

And then there's future incumbents that show up. No, I even think back to what you like to talk about sometimes, the ebbs and flows, the centralization, decentralization. We're in a great point right now where we're starting to see just like the democratization of technology is incredible, all the open weight models and everything of that. Same thing like personal computers back in the 90s. What I'll say is this, Brian, which I've come to think a lot about, which is capital loves centralization.

because the central place is easy to invest in and easy to forehand and make money off of for an investor. We as human beings love decentralization because decentralization is empowering for each of us individually. We get something out of it. It's in our pocket.

It's in our hands. The personal computer is valuable to us. The mainframe is not valuable to us. At the onset of that revolution, investors really liked IBM. They liked the centralization, right? The colossus is good for capital. And you see that bias

with open AI and a profit. Part of why they're so appealing is it's a single source of truth where I can dump $100 billion as a sovereign wealth fund. I like it. I'm going to clap for it. I don't want to hear about this decentralized distributed stuff because how do I concentrate my capital across a billion models in people's pockets running on their phones? It's not too hard. So that's the tension. It's the same freaking tension, whether it's in 1995 or 2025. It's capital of centralization. Humanity loves decentralization. And there we have it. Let's fight that fight. I was going to, this is really inside baseball, so forgive me, but I was, I was talking to somebody yesterday where they were complaining

about how hard it is to invest in this era of AI. And I was like, well, that's because you came up for the last 15 years investing in SaaS where basically you could plug it into a spreadsheet. No. And like, you just find a category and it's like, well, if it fits this niche, like, I can figure out what the likelihood. And I'm like, yeah, but that's not, that's not historically how it works where you can, you know, plug and play and know what's going to happen, kind of. Okay, so let's wrap by reminding people.

Yeah. Onix.life, you can find out about it. The access code ride will get anyone listening to this in, and you can play around with it. I'm just curious, obviously, if people want to, you know, find out about joining the team or things like that. But also, like, if I'm a dating

coach or like a soccer coach or something like that. Like if I want to get on the waiting list down the road when you open up other verticals, are you ready for that or what? We are taking a waiting list. So if you're an expert and would like to be on the platform, you go to onyx. Life and you'll see an area for the experts. Click on that. There's an obvious link where you can submit essentially like a little about me and why I

think I'd be good for the platform. So we welcome that completely and please come and do that. And we think possibly like self-improvement, self-help is sort of the most adjacent natural next extension in is very close to health laws. So those of you who are coaches and thinking in that domain should consider filling out the form. Yeah. Great. Then as I always say, you know, because listeners, if something you heard today was like,

oh, my God, this is something that could overlap with what I'm doing, get in touch with me, you know how to do that and I'll put you in touch with them. David, Nick, thanks for coming on to tell us about this. and I'm super excited to be involved. All right. I pleasure, Brian. Thanks so much for having us. As they say, Brian, ride or die?

I've never thought of that before. I got to sign up, ride or die. All right, thanks, guys. Thank you, Brian. Thank you.