Building AI Technology for Distribution with the Human Mind in Mind

Transcript 

Welcome to Distribution Talk with Jason Bader, the show where we dive into the stories,struggles and solutions from business owners and thought leaders in the wholesale distribution market. Hey friends, Jason here. In this episode, I had the opportunity to speak with Jason Sullivan. He's the founder and CEO of a company called Distro, and they focus on AI applications. And I've been talking about AI a lot lately, and I promise I'll have some other subjects to discuss here in the near future. But we're coming up to this conference,this Applied AI for Distribution. So yes, I'm talking a lot about AI because I'm pretty excited about attending this thing next month. First week of June in Chicago, and again, Applied AI for Distribution. What I just found out though is Jason's going to actually be one of the speakers there.

And so I think he's speaking on Tuesday afternoon. And yeah, I'm looking forward to hearing him and seeing him, meeting him face to face. And I think it's kind of funny. I don't get to meet a lot of my guests face to face. And so I always enjoy going to these conferences and shows where I actually get to say hello to them. And yeah, it's something a little different. There's something a little bit special about getting to meet somebody face to face and chat with them. But anyway, a little bit more about Jason. One of the things that really makes it unique is he worked on an application for HARDI, which is one of the trade associations I spent an awful lot of time with. And they're in the HVAC distribution space.

And he worked on a custom application for them or a custom query, really. It's called AskA2L. And we'll speak a little bit more about that in the episode. But it really was a really customized application or AI query that was really designed for the counter associate where they could become this very, very knowledgeable person to that contractor in a short period of time. And I started thinking about all these different applications. Boy, in the beauty space, you have stylists asking questions of wholesale beauty supply distributors. And you have in the green space, you've got landscapers who are trying to get advice from these landscape supply commercial nurseries. And I started thinking about, wow, what if you could create these custom AI queries that were really industry specific and really got down deep. And that's really what Jason can do. He's a technologist at heart, which he'll explain. But it just fascinates me. Again, I totally geek out on AI. But then this is where the broad stroke of possibility now becomes practical application. And it's just, again, a fascinating world that journey that he has gone on. I thoroughly enjoyed speaking with him and asking him questions. And I really hope you all enjoy the interview.

Well, hey, Jason. Welcome to Distribution Talk. Thanks so much for taking the time to be with me today. Hey, Jason. It's great to be here. Thank you. Yep. See, another Jason, man. This is good. You know, it's funny. I've had a couple of Jasons recently. I'm like, oh, I guess we're coming out of the woodwork. So. We're a different breed. We're living that Jason life. Indeed, we are. Indeed, we are. Well, if you wouldn't mind, give us a little background on how you got into your technology world. And yeah, just share with us a little bit of your personal career history. Yeah, absolutely. I'm the founder and CEO of a company called Distro. We'll get into that later. As for me in a nutshell, I'm a technologist with pretty deep AI data and software engineering experience.

And I'm really passionate about using technology to solve problems for the economy in a particular distribution. Nice. So again, you know, you are a tech. What does a technologist really mean? I mean, you know, people say they're in software. People say they dig on technology. What is a technologist, at least in your mind? Yeah, it's funny. It's tough to suss out what the real deal is. Who's the real deal, right? I can say what my background is, which is I'm somebody with an academic background in computer science. So I did my master's degree in computer science at Stanford. I focused on artificial intelligence, as well as data systems, really sort of the core infrastructure behind artificial intelligence. And from a career perspective, I really come from the software world.

That's what I mean when I say technologist. So I've been a software engineer for many years. I've been in the startup world for many years. I've been a founder before. And of course, with Distro, it's just really what I love to do. Yeah. One of the things you mentioned when you and I spoke before that you study cognitive science, what does that mean? Help us understand that. Again, you're talking about some guy who has an undergrad from the University of Oregon. Come on now. Got to bring it down for me, man. Go Ducks. Go Ducks. Well, yeah, look, I've always been really fascinated by the human mind. How do we retrieve information? How do we perceive things? How do we think about things, make decisions?

If you look out there at any Malcolm Gladwell- type literature, that sort of stuff, that just really gets me fired up. I love it. Gotcha. So while I did my master's in computer science, as I mentioned before, I did my undergrad at Yale in cognitive science. And in particular, I focused on behavioral economics and decision making. So really just how do people perceive things? How do people make decisions? And what's the sort of quantitative side of that? Interesting blend there. Taking that background and then applying your computer science to it. And I think ultimately that's what's brought you here. Let's go through the career a little bit. Go ahead, if you wouldn't mind. Yeah, absolutely. I've had an interesting path.

I started my career actually on Wall Street as a quantitative trader and investment analyst. It was a heck of an experience. I learned it's a very fast- paced environment and it's pretty exciting. But ultimately, I sort of learned it wasn't really for me. And when I got a job offer to work at a financial technology startup as a software engineer, that was really a life- changing experience for me. It really just sort of turned my mind on to what was possible. Tell me, what sparked you? What changed for you? Yeah, you're absolutely right. You look at the quantitative trade in the hedge fund world, there's no shortage of people with AI backgrounds or PhDs and things of that nature. For me, while the quantitative side of investing is really interesting, it still remains interesting.

What really got me fired up about going into the startup world was the idea of building products, building something that people can use, rather than just leveraging math to make money in the markets. And once you get to that place where you can put pen to paper, so to speak, write code and build something from the ground up and see users use it and be delighted by it and excited by it and have it make their lives better and easier, it's addictive. You really can't turn back from that. That's more of a noble calling. I'm not trying to be too grandiose with that suggestion, but it is more noble than just going out and making more money.

I guess you could argue the other point that you are on hedge funds, you are working with retirement accounts and you're people that way. But I think that really building this to figure out how I can make people's lives better today, that's got to be appealing. Yeah, absolutely. And you don't necessarily often see folks with that pure technology, academic background and the human development, behavioral psychology type of background. That's really what I'm all about, is marrying those two together. How can I build technology with the human mind in mind and use that to make people's lives better? And that's really what we're focused on here. It's a great point. As you know, I've interviewed several people who are founders and startup people, and they do tend to be from other disciplines, maybe the law or different behavioral backgrounds.

But being a pure technologist, maybe it gives you a leg up at least in understanding what's possible. I think there's a lot of challenges out there. There's a lot of hype in terms of AI and what it can do for space. And that hype is largely warranted. There's a lot of noise too, right? Yeah. And you really have to pick your spots and speak to the right people and have the right perspective on what AI can and can't do. Yeah, I think that's a great point. As I've shared in this podcast, I'm still in the off phase where I'm like, man, it can do all kinds of stuff. I don't know what I want to do, but I can do all kinds of stuff. And I think it's difficult to really narrow that down.

As you said, cut out the noise, narrow it down to, well, what do I want to make it do today? Yeah, exactly. And look, there's also fear. It's not just noise. There's fear. What's it going to do for us? What's it going to do to us? Is it going to come and take people's jobs? Is it going to make people's lives more difficult, right? It can be a scary thing. And so that's a big part of what I like to do in terms of thought leadership is I want to be that steady rock to help you shepherd your way through some of this uncertainty and better understand what's possible and what's not. Yeah. I had a great conversation this morning, actually, with a good friend of mine, Rakoffi.

He's in the video game business and he's been in this for a long time. And he's seeing leaps and bounds of opportunity with AI inside of that video game design business. And for guys his age and my age, there's a little bit of fear, you know, the things that his experience has been able to achieve and to where he's been relevant because of his experience. Now, AI supplants some of that. And, you know, again, as you said, how do you overcome that fear, you know, overcoming fear, but also then saying, all right, well, how can I use this as a tool to not only make my designers, you know, the people that I'm charged to oversee, but how do I help them acquire different skills?

And we actually talked a lot about training paths and things like that, that could be created through AI. First of all, I'll say your buddy has a really cool job if he's working in video games. Oh, he has one of the greatest jobs. No, it's cool. I don't think he really knows how cool it is, but. That's often the case. I would say if you look at that space, video games, right, there's generative AI can do a lot. Yeah. And especially, you know, in the design and development of a game. But at its core, what it's doing is essentially what it's for the distribution space or other spaces, which is that it puts a lot more power in the hands of a given person in the space to have the leverage to do a lot more.

Right. So you can build a game of a smaller dev team, right. And build that out to a much larger game and start competing against the bigger players. That's one of the ways that we think about how we're helping distributors, especially sort of midsize and smaller distributors. How can you use a team you have and compete with some of the bigger folks? For sure. So kind of a good segue there. What was interesting about distribution for you? I mean, why this space? Why us? It's a great question. I didn't come from space originally. I mean, the closest thing I had is I've got an uncle who's been a general contractor for many, many years, but I don't have a situation where I've got a parent in distribution or anything like that.

But I had the opportunity to meet some folks in the space. And I would say, you know, I came for the market opportunity and there's a real opportunity here. I'll get into how I think about that, but stayed really for the people. I love folks in and around the trades. And if you think about it, hanging with counter staff, it's a very different thing for hanging with software engineers, right? Oh yeah. Yeah. Yeah. Get to be a little bit of a different side of myself, but I also say, look at the opportunity, look at the technology side of things, look at the problems that folks are facing. It's really the perfect time for an AI powered solution, like what we bring to the market.

We talked about this before, tons of excitement, a little bit of fear, a little bit of noise out there. If you can come to a space and provide that clarity and be that long- term AI partner, then you can do a lot of good. And that's really what we're focused on. Yeah. And, you know, there are a lot of gaps inside distribution, I think. And there's also a lot of inherent inefficiencies that, you know, in distribution, we tend to throw labor at things that we don't understand. We don't know how to, you know, how to streamline. And so, well, hey, let's just throw more bodies at it. And, you know, let's face it, distribution is an expensive business to operate. You know, the net profit is not, it's not very big.

It's actually pretty thin. And so, the more labor we throw at things, just the tougher it is to make money and to profitably or keep your doors open. And so, I think that there's a tremendous opportunity, to your point, to look for ways to leverage technology tools. And, you know, specifically, as we talk about AI, to find ways to actually be able to compete and make a nickel at the end of the day. Yeah, I agree with you completely. And I'll say one of the things that really drew me in from a tech perspective is I come from that data background. At its core, what we're focused on is data. That's what I do. So, anywhere that there are challenges with data, I get really excited. What do those challenges look like?

Well, is there a lot of data? Is that data potentially kind of messy? Is it hard to get a hold of? Is it hard to connect one area of data to another area of data, right? And the more, you know entering the space, the more I got into it with folks at distributors, executives, as well as at the counter and all the way between, what I realized is data is a problem. I mean, you've just got so much data out there, so many SKUs. You've got just constant model super session happening. It's expensive to maintain a solid data set. And you've got a lot of distributors who are otherwise really sophisticated, but they've got data in their ERP that's just a challenge to work with. And that is.Messy Exactly.

Super messy. Super messy. And sparse, too. It's like, you're not necessarily getting a ton of information with one entry for a product in the ERP. So again, that's really where I come from. That's really where we excel and what excites me. Yeah. It's funny, as you were talking about data there, is it messy? Is there a lot of SKUs? And I'm like, yes, yes, yes, yes, yes. I mean, absolutely. All of those things, again, for a data guy. Look, I'm a data junkie as well. I love it. I think any way that we can harness that and put it into a format where people can do something with it, now we're starting to cook with grease. Now we're moving. But that's really where people like you come in to try to make sense of all of this.

Because I can dream about it, but I just can't do it. I don't know what the heck to do with it. Well, yeah. And I'll say, it's not just the data itself that's the problem in a vacuum. It's who's interacting with it and how are they interacting with it. And look at folks at the counter, counter staff or inside sales. They've got to interact with the data a lot. They need to retrieve product information. They need to construct quotes. They need to do cross- referencing. They might need to do a little help as far as providing a contractor with an install guide or some other technical guidance. You have to be really nimble with this stuff. And sometimes it's really hard to get a hold of the right information or even know if the information you've got is right.

Yeah. Well, especially in distribution, we have a pretty fast progression, meaning that people who within two years could easily be in that position where the customer is facing and hoping to give advice. And that's a pretty short window for all of the background and experience that a good counter associate would have. And so compressing that knowledge base and somehow making this person appear knowledgeable and really be serving to that customer community, especially that contractor community that we talk about, that is a challenge. I mean, that is tough. And often poor advice is given or, hold on a second, I better check on that or even worse. Here, I'm just going to give you what I think is right and I hope it doesn't blow up your application and things like that.

Yeah. There's a lot of risks there. I mean, time to quote is a really important thing. And if you can't get a contractor, an answer, especially someone who's more experienced, they're going to go right across the industrial park to a competitor. And that's one of the many challenges these counter staff counter folks are facing. As you mentioned, lots of different distributors have different ways of training these people up. I've done a ton of site visits, I've spoken to countless distributors. And it's a pretty common paradigm. You want to train somebody up from the ground up and maybe they drive a truck or they work the warehouse for a while and then they move to the counter. And that's a good way of getting familiar with the product catalog and it seems to work.

But the question is, how do you get them to the next level and how do you get them to the next level more efficiently? Right? Right. Absolutely. I mean, I think that is the holy grail for most distributors. I mean, I think you really hit on it there. It's that transition from the environment to that counter and then ultimately to an inside sales or customer service environment. How do you bridge that gap? That's been, in my experience, that has been the most frustrating things for privately held distributors. There's that huge knowledge, there's this chasm that they have to get across. And yeah, that's a tough one. I'll do one better. It's not just training people up, although it's really important. It's sometimes hiring those people, finding them in the first place.

How do you identify the right people to bring on to the counter? How do you train them up, of course? And then importantly, how do you retain them? How do you get them to a place where you're not at risk of somebody moving to a competitor? You could spend tons and tons of time training somebody up and it could go that way. So your company obviously focuses on and really tries to answer a lot of these questions and a lot of these distributions, not only distribution questions, but other places. But right now, distribution is a great place to play. You got a lot of opportunities in distribution because we are messy people. We are labor- intensive, messy, service- related. We try to do the right thing, but it's not easy.

So tell me a little bit about Distro. How are you attacking this, trying to solve these problems? Yeah, absolutely. So Distro is an AI- forward technology company. We're a team of, say, product- obsessed and AI- obsessed, primarily technologists. And we're here to solve whatever problems we can, leveraging the latest and greatest in AI and the distribution space. And how we position ourselves is we are the all- in- one AI platform for distributors. We're really focused on, if I were to boil it down, helping you get 10 times more out of your reps. Right. That's really the focus. And an important detail to how we position ourselves really is that all- in- one aspect. We have a platform, right? We're not just an individual point solution trying to solve one specific thing.

We're here to attack the problem from multiple different angles. And so we're really this all- inclusive platform. And the Distro platform consists of multiple AI- powered modules that leverage a distributor's data and our dataset as well in a bunch of different ways to help reps, whether it's somebody at the counter or inside sales, or in the field, or somebody who's more of a technical rep, be more effective at serving the customer. So what are a couple of those modules, if you don't mind just rattling off a couple of them? Because, again, you alluded to some of the AI solutions providers out in the market space, they might focus on one aspect, like, for example, CRM. Or then another one might be, we're really good at quoting or whatever it might be.

So could you rattle off a couple other things that you all are as part of your suite of Yeah. I'd say if I were to boil it down to two halves of the Distro platform, there's the intelligence side of things, instantaneous, real- time retrieval of all sorts of information that's helpful to the rep when they've got somebody in front of them, right? Okay. And then there's the flip side, which marries pretty well with that intelligence side, which is the transactional side of things. So how do we then leverage that data and the interfaces we've built to help that rep turn that information into an actionable quote? Gotcha. Okay. What does that look like? I'm being sort of abstract here. Think about the experience of somebody on the counter, right?

A contractor walks in, they might have a question, they might be looking for a particular product, they might have a model number. That's the easiest case, but. That's rare. Yeah, that's the unicorn that comes in the door. Yeah, okay. And maybe second to that, maybe they're doing whatever it might be, a commercial HVAC rooftop replacement, and they have the nameplate for the old thing, and they need something that matches those specs, right? Or maybe even the more difficult case, all they have is a set of and that rep needs to go and translate that into a set of options, and then be able to present it to the contractor in an efficient way, right? That can be a really challenging thing to do, especially for somebody who's a little bit less experienced.

Contractors, they want what they want, and they want to get the information they need in a reasonable amount of time. And oftentimes, that contractor will be aligned to the most experienced person on the counter. And so the less experienced person maybe doesn't even get a chance to get those repetitions in. Right. That's a great point. Yeah. And really train themselves up, right? But if they do get that question, that interaction from the Yeah. They might be going themselves to the alpha dog on the counter and asking a Yep. They might be opening 10 browser tabs to get the answer to a question. They might be sort of rifling through the ERP, and a lot of these ERPs, they can be a challenge to do searches with. They might be looking at physical catalogs.

I mean, it could be a whole research project, really, to get these answers. And they just don't have the time to be able to do that. So where we come in is we've built a whole suite of interactive AI- powered chat interfaces. That makes it super, super easy for that rep to be able to get the answers to any of those questions. Product lookup, part lookup, look for information about a prior set of initiate a quote, compare two products, give me recommendations based on these specs, anything down the list, you name it. And we've done this in a way that leverages core and key industry data so that it's all verifiable, it's all validated, and there's that comfort that the rep is getting the information they need, and it's the right information.

Yeah. You're not just relying on the resident data inside of that distributor. I think you mentioned it's core information outside of that organization. Absolutely. We pride ourselves on our ability to build and maintain a really sort of sophisticated data mousetrap where we are building and curating an industry data set that's sort of a source of truth. And we marry that with the distributor's data in order to generate answers to these questions, as well as to interface with the ERP to construct quotes, which is the other half of the platform I mentioned. You and I were introduced through a good friend, Talbot G. of you. You did a project for them. Talbot shared with me and hey, man, you got to talk to this guy. You got to interview this guy.

And when Talbot gives me a suggestion like that, I pretty much say, all right, I'll take a listen and see what's going on. So could you tell me a little bit about how that worked with them and what you all were hoping to achieve and then ultimately what came of it? Yeah, absolutely. Talbot's great, HARDI’'s great. It's been an absolute pleasure to work with them on this project. It's a project that we have co- developed. It's something we call AST- A2L. And the genesis of this is looking at some of the recent and regulatory changes coming out of the EPA as they pertain to the HVAC and refrigeration industry. The A2L transition, that is the transition to refrigerants that are more environmentally friendly is important, of course, but also really sort of a thorn in the side of a lot of folks in and around the space.

Because frankly, it's difficult to understand how these changes impact my business. Maybe you're a multi- location, multi- state distributor and different states are adopting different fire codes and changes at different rates. A lot of this information is pretty opaque and it's difficult to come by. And if you look and just do a Google search, or I'd say even worse, use ChatGPT to find information about this stuff, you're often going to get just plain wrong information. And that's going to be really negatively impactful on the business. Yeah, I know when you and I talked a little bit about putting together an interview here, you compared what was the answer from ChatGPT versus what was the answer from AST- A2L. And they were very different. They were vastly different.

And as you said, kind of just plain wrong in some cases. That's the real challenge with these public- facing large language models and chat interfaces. So they have a knowledge cutoff date. They are constrained in a bunch of different ways. It's a challenge because they're dealing with so much data to be able to curate that data in a way that is up- to- date and also correct in every case. So when I tell folks, how do you best use ChatGPT? I mean, it's very useful in a lot of different ways. It's pretty amazing stuff. But would I use it to find out kind of deep, nuanced, industry- specific information? Definitely not. Would I tell my developers to use it to write an entire code base? Absolutely not.

Can I write a little bit of code here and there and kind of help you debug some stuff? Great. But it's got its limitations. And when it comes to retrieving information, really information about the A2L transition, it just falls flat. And again, that was sort of the genesis of this idea, is how can we build an interface for the HVAC and refrigeration industry that is trained on highly, highly curated and fully up- to- date data maintained by the experts at HARDI in a way that is useful to everybody, all participants in the space, whether you're an OEM, you're a distributor, or you're a contractor Okay. So you've put this together. How is it deployed? I mean, what's that? I will say, okay, I got to share with you.

So we played with this at one of my recent training sessions, my HARDI training. I had a bunch of branch managers and I decided, you know what, during lunch, we're going to put this thing up on the screen. Let's see what we can do. We can break it. So I wanted to show these guys actually what was possible. And so we played with it. And one person was pretty funny. They said, can I get a. What is it? I can't remember what piece of equipment it was. Can I get that in purple? And that did mess it up a little bit, but you know, we, for the most part, it was really fascinating, you know, kind of watching these folks' eyes light up and you know I think they can see possibilities that you and I can't see.

Oh, absolutely. You know, that they can see things, uses for that type of technology or that query opportunity that you and I just cannot see because we're not in it every single day. Exactly. You hit the nail on the head and that's really been our approach. We've got our expertise, our specialty, but the real experts in this stuff are boots on the ground. Right. And that's why I and my team have spent so much time, not just with people at the executive leadership team at distributors, but people across the organization making site visits and kind of going deep with folks to really understand what those pain points are. And you Exactly. You hit the nail on the Yeah, it is kind of interesting.

And this is where we always have to drive back to, you know, when we look at any kind of tool that we offer, what is the real purpose? And I think in speaking with you earlier, but also experimenting with the AskA2L product and looking at who is going to actually benefit from this tremendously, it's really making these counter people so much more knowledgeable and more confident in what they're sharing, you know, these contractors and ultimately give them, you know, that leg up. You know, those who participate, you know, are going to get the leg up. Yeah. And I'll say, as far as who's using it and how they're using it, I think you have asked how it's deployed. Yeah. Well, there's some exciting things happening there.

We've worked directly with HARDI to host the tool on the HARDI website. We're going to be launching a separate website, AskA2L. com pretty soon. So that's pretty exciting. And what's even more exciting, I think, is we're also working with HARDI to help distributors actually white label the tool and embed that on their internal site or even their e- commerce site. And even further, linking that tool to their internal data. So it's not just informational, right? It's not just, can I get the information I need about this aspect of the A2L transition as it pertains to this location? But also, OK, well, which products do we stock that qualify? And when, at what point will we have to have sold this particular portion of our inventory, right? You link those two things together.

So there's a lot of exciting things happening with this tool. It all boils down to interacting with the distributor and leveraging their data to help them and folks at the distributor better understand this transition. You know, as you talk about this, I'm really thinking about other vertical markets. Where else can this apply? And, you know, just stuff started popping out of my head, like, you know, for example the commercial nursery business you know and I spend a fair amount of time, you know, messing around with, you know, nursery people, you know, the plant people in the landscape and thinking about, all right, well, if you think about the landscapers that they serve and, you know, landscape designers and things like that, you know, imagine having, you know, their version of an AskA2L, you know, it's, you know, AskGreenscape or whatever we want to call it, but gathering information, they could really go crazy with this and really ask those questions.

So, I mean, I think that would be an application that would be really fascinating to look at. Yeah, I think if you look at any industry that has kind of nuanced industry specific information that may be difficult to retrieve or maybe a sort of tribal knowledge, right? Yes. That is a great use case for large language models in particular, but AI more generally. Absolutely. And I'll say even within distribution, you know, we've obviously worked very closely with the folks at HARDI and within the HVAC and refrigeration space, but what we've built and what we are building ports over very well to adjacent industries, whether we're about plumbing or PVF, electrical, MRO, bearings, fasteners, on and on and on. Even beauty supply. I mean, I'm thinking about beauty supply right now.

You know, seriously, I mean, that is a nuanced business. Trust me, hair colors, hair, you know, hair products and things like that. Not that I know much about that, of course, but all of that, all the different variations and what works better. Boy, I can just see tremendous application in different vertical markets. You know, I think we both, you and I both kind of gravitate towards the construction based, you know, because we kind of understand the contractor request of that nature. But I think going beyond that, there's a whole lot of opportunity out there. There's some really interesting opportunities if we start expanding a little bit as well. A hundred percent. Couldn't agree with you more. Yeah. So how does somebody engage with your company if they want to do a custom project?

You know, if they want to do something like you just described with HARDI and maybe this is an association exec listening to this or it's just a large distributor that really is saying, you know what, I want to white label something and I want to be the one. I want to be the first to market here. Yeah. Yeah. So we've got our core distro product suite, our platform that I mentioned. And then in addition to that, we do AI consulting and custom development work like what we've done with HARDI. So anybody that wants to or has interest in engaging with us or at least learning about what we're doing and how it can be helpful, please feel free to reach out so you can check out our website. It's Distro.app. 

And as I mentioned before, to AskA2L specifically, we are going to be launching AskA2L. com in the coming weeks. Yeah. And lastly, please feel free to reach out to me directly by email at jason at distro. app. So I'll definitely put all those in the show notes so that people can link to those. But yeah, I mean, I think, you know, it's how creative do you want to get? How far do you want to go here? And I think, you know, finding a technology partner like yourself is really, you know,one of the first steps to say because you can answer that question you know what is possible? We just don't know what we don't know. Absolutely. That's the name of the game. We don't know what we don't know.

And we're on this journey together. We've got our tool set and you've got your tool set. And, you know, we're just trying to figure things out with the power of AI. Perfect. Hey, Jason, such a pleasure, man. I really appreciate you taking the time to talk through all of this. And, you know, of course, my listeners are going to be like, do you talk about anything besides AI? And I'm going to say right now, man, yeah, this is what I'm digging on. So anyway, hey, thanks again. You know, and I really appreciate the time. Thanks for having me. It's been a real pleasure. All right. You take care. Thank you for listening. If you liked what you heard, consider sharing with your friends and colleagues.

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