Inspire AI: Transforming RVA Through Technology and Automation
Our mission is to cultivate AI literacy in the Greater Richmond Region through awareness, community engagement, education, and advocacy. In this podcast, we spotlight companies and individuals in the region who are pioneering the development and use of AI.
Inspire AI: Transforming RVA Through Technology and Automation
Ep 22 - Beyond the Code: Reimagining the Human-AI Partnership w/ Kyle Johnson
From protecting billions of people against online terrorism at Meta to founding tech startup Ara, Kyle Johnson is pioneering new ways for humans and machines to collaborate. His vision goes beyond building AI-powered tools—he's creating systems that empower everyday people to harness artificial intelligence without a technical background.
Kyle introduces us to the revolutionary concept of "vibe coding," where anyone can create sophisticated applications simply by describing what they want in natural language. Unlike previous technological waves that required specialized knowledge, today's AI interfaces through conversation, making it uniquely accessible. As Kyle demonstrates, someone with no coding experience can build everything from educational flashcards to custom games just by having a dialogue with AI tools like Claude.
What makes Kyle's perspective particularly valuable is his focus on the invisible ROI of artificial intelligence. While many companies chase flashy AI features, Kyle reveals how backend implementations often deliver far greater business value. Drawing from his experience with counterterrorism and integrity systems at Meta, he shares practical strategies for identifying repetitive business processes ripe for AI enhancement—where a single implementation can save hundreds of hours while improving employee satisfaction.
The conversation takes a fascinating turn when Kyle explores the future of human-AI collaboration. He envisions a world where the code itself becomes increasingly invisible, where interior designers might transform spaces through natural language in VR, or data analysts might investigate patterns through conversation rather than queries. His advice for aspiring founders cuts to the heart of successful innovation: fall in love with problems rather than solutions, embrace uncertainty as a sign you're on the right track, and remember that both AI and human expertise have essential roles to play.
Ready to start your own AI journey? Connect with Kyle on LinkedIn at linkedin.com/in/gkjohns or find him on Twitter @kyledotai to learn how you might transform your creative process through the power of AI collaboration.
Welcome RVA to Inspire AI, where we spotlight companies and individuals in the region who are pioneering the development and use of artificial intelligence. I'm Jason McGinty from AI Ready RVA. At AI Ready RVA, our mission is to cultivate AI literacy in the greater Richmond region through awareness, community engagement, education and advocacy. Today's episode is made possible by Modern Ancients driving innovation with purpose. Modern Ancients uses AI and strategic insight to help businesses create lasting, positive change with their unique journey consulting practice. Find out more about how your business can grow at modernagentscom. And thanks to our listeners for tuning in today. If you or your company would like to be featured in the Inspire AI Richmond episode, please drop us a message. Don't forget to like, share or follow our content and stay up to date on the latest events for AI Ready RVA. Welcome back to Inspire AI, the podcast where we dive into the minds shaping the future of artificial intelligence. Today's guest is someone who's not just building with AI. He's rethinking how humans and machines collaborate.
Speaker 1:Kyle Johnson is a tech entrepreneur, data scientist and writer based in Richmond, virginia. He spent six years at Meta working on machine translation, digital trust and complex systems that shape how billions of people experience the Internet. That shape how billions of people experience the internet. But these days, kyle is focused on something much more personal helping everyday people harness the power of AI. He's the founder of Aura, a platform that helps teams turn raw data into visual stories that actually drive action, and the founder of Tidewater Research, where he helps enterprises navigate the messy reality of AI adoption. Beyond the products he's building, kyle is emerging as one of the most thoughtful voices around how AI is quietly transforming the way we think, create and work. In his recent article, the Quickening, he argues that transhumanism isn't coming someday. It's already here for those who choose to collaborate with AI. Today, we'll explore Kyle's journey from big tech startups, how non-technical folks can start experimenting with AI and what it means to vibe code your way into the future. It is my pleasure to welcome.
Speaker 2:Kyle Johnson to Inspire AI. Hey, thank you so much, Jason. Really appreciate it. Happy to be here.
Speaker 1:Kyle, thanks for joining us today. Can you start out by telling our audience a little bit about yourself, your business and your interest in AI?
Speaker 2:Yeah, absolutely so. I'm an ex-marine and former metadata scientist that's kind of where I got my start in tech and I currently run an AI consulting firm and, as you mentioned, my other company, aura. It's Aurasocial, and Aura is kind of like GitHub for storytellers that's what we call it. It provides infrastructure for data scientists and data analysts who need a place to generate, store and share their insights, not just data, so it's very insight driven, as opposed to just piping data to more places, which is where a lot of data startups are going now.
Speaker 2:My interest in AI is very much on the technical side, but it's very applied, which I think has a lot to do with just the teams that I chose to work on on Meta, to do with just the teams that I chose to work on on Meta. I'm a tinkerer at heart. I like actually playing with things, actually trying new things and finding opportunities to just make entities and organizations more efficient with this new technology. I just love doing it. But I don't just focus on the technical side and technical implementations of things. I'm also really interested in just how people are using AI to make their lives easier, and usually that just means chatbots, I think a lot of people see them as a bit of a gimmick. Right, they're like, okay, this thing isn't really smart. But in the article you spoke about, I mentioned folks who I've seen with my own eyes while I was consulting really make themselves smarter with chatbots. They found these new ways of working with them.
Speaker 1:So I'm really interested in just all aspects of how AI is changing our lives. Absolutely, the concept of AI making people smarter that definitely resonates with me. It's almost like there's this new digital literacy, but it's not about learning code. It's about learning to think with AI. Right? It's not about learning code, it's about learning to think with AI, right? That's a pretty powerful shift, absolutely, yeah, all right, so tell us a little bit about how would you describe the journey that's led you from meta to founder life.
Speaker 2:That's a good question. So when I was working at meta as a data scientist, I really just chose to work on teams that had high stakes or high impact missions. I didn't like I didn't want to be on like the newsfeed team right, which had just been around for a long time. It had been optimized to hell and back right. There was just wasn't a lot of like high impact work to do. So I chose teams like counterterrorism, child safety, ai, language, research at FAIR and impersonation. So I think that that had a huge impact on me in that I chose teams where the outcome really mattered right. And, as you know, like when you work at a big tech company, there are teams where it doesn't really matter and you can just kind of get along by doing the work. But I always stayed on very mission-focused teams. But when Lama 2 dropped in 2023, I want to say I started almost exclusively just incorporating AI into my own work and some of the tools that our teams were using and I just took into brand with it. There were a lot of data scientists at the company. I felt very confident that data science analytics would continue without me. I risked getting fired and just really went all in on this AI implementation kick. I was on and it went surprisingly well.
Speaker 2:I was working at Reality Labs at the time on a team called Trust and I built a system that monitored what users were saying on external social media platforms about the products that launched. So we launched a new headset. I was building apps that would look at all the comment sections on Twitter, all the what else. We looked at Reddit posts. We didn't use Facebook posts, but I was basically ingesting all that and using AI to make sense of it, and that was something that a lot of people weren't doing.
Speaker 2:And when people thought of AI at the time, it was very focused on some external facing chat bot, right, some external facing use case or feature where the user's directly interacting with the bot or with the AI. And I'm like man, I'm getting a lot of mileage out of just having the AI understand things on the backend and write me a little report. And I think that that paradigm, that like way of seeing AI adoption and AI implementation, was unique. And at a certain point I was like, okay, I don't see many people doing this. I see the market opportunity and that was all the confidence I needed. So I spoke to Mari, my wife and co-founder now co-founder and she was like yeah, that sounds like a good idea and we opened up Aura.
Speaker 1:There it is. Yeah, that definitely sticks with me too. Data is not valuable until you turn it into action, right? Yep, so R is helping people bridge that last hardest mile of telling a story in a way that actually moves someone to do something.
Speaker 2:yeah, yeah, yeah, it's funny. You say like the hardest mile, because I call it the last mile delivery of, like the data value chain. Right, you actually have to get it into someone's hands. Who is going to make a decision? Right, a lot of data scientists and data analysts.
Speaker 2:This is probably the number one mistake that data scientists make in their first like five years of their career. They make these awesome analyses, but they don't think about that last mile delivery. They don't think about who they're going to even deliver this thing to. They don't think about what decision it's going to support. They don't think about, you know, at the end of it, I always tell, like, my mentees to like make a recommendation for what to do next, but they would a lot of the time they would make a recommendation that was like completely out of touch with where the business was, and you know you can do a lot of work and not get much for it. So, yeah, that last mile delivery is very important and at Aura, I think it's. You know, I think that's where, if you think of the value chain as a funnel, that's where a lot of the value drops off, right, just getting that insight into the right people's hands. So that's what we're focused on.
Speaker 1:Yeah, awesome. Yeah, it's really good to know your customer and to be able to articulate the problem you're trying to solve with the technology before you go dive into just experimentation mode. I think that's one of the reasons why, like 90% of all data science, experimentation doesn't make it to production, you know you know?
Speaker 2:yeah, totally agree. I think that having um it's funny because data science it's it's, it's firmly in like the tech, the tech world. Like you would sit on a product team with, like engineering managers, ux researchers, data engineers, but I think it really straddles the line. Sometimes it's like almost a business function in a lot of ways and I think that knowing how to be a translator between the two worlds it's totally a business function, yeah, yeah absolutely, and um that, knowing how to be a translator, between the two worlds.
Speaker 2:It's totally a business function. Yeah, yeah, absolutely, and just knowing how to translate between those two worlds is super important, but it's not really spoken about. Everyone's worried about the newest models or being super stats rigorous, which you should right. That's good, but you need to really be thinking about why we're even doing this, right? It's?
Speaker 1:not tech for the sake of tech, for sure. Yeah, absolutely All right. So let's double click on Aura. What problem are you solving and what makes it different than other data tools?
Speaker 2:Yeah. So the way I like to pitch Aura is it's GitHub for data storytellers, right? Software engineers have this platform for those who don't know called GitHub, where you can kind of share your code with everyone else and it acts like a central repository where you can work on code together. You can take someone's project and fork it, which means kind of creating a new project out of that one, and it's kind of the one central place where your code can live and be shared right, and in some cases, be even like deployed from right If you're using something like Vercel. But there's nothing like that.
Speaker 2:For people who are telling data stories, right. For folks who need to create analysis, they need a central place to create the analysis, to store it and to share it from. There's nothing right now, and I'd argue that in most organizations, google Docs is doing the hard work. People are doing an analysis in a Jupyter notebook, right, or an R Markdown notebook. They're screenshotting their charts, they're pasting them into a Google Doc and they're saving it as a PDF right, and that's where all the data analysis is happening. There are very unique challenges of doing a data analysis and no one's really tackling them, no one's really facing them. So that's what R is doing, and I think that one part of one concept that hasn't really that isn't really spoken about is again what I call like the data value chain.
Speaker 2:Right, so you start with raw data, which is just observations of things that happened. Right From there you have to turn that into insights. Those insights need to be fed into decisions. The decisions need to drive action and then from the action there's impact, right, so in a way it's a funnel, right. There are drop-off points between each one.
Speaker 2:Sometimes you don't have the data to make the insights, sometimes the decisions, for whatever reason, don't become actions. We're really focused on that insight to decisions transition, right, data scientists know how to turn data into insights. But from going from insight to decision, having what I like to call a storefront for your insights, right, if the data science, if the data science team or data analysis team, was a business within a business, which it is right you're kind of selling the insights, they need to be timely, they need to be related to the context of what's going on in the business and they need to be actionable, right, but that's what you're selling, that's what a data team is selling. So we're kind of building infrastructure for those data teams who need to sell their wares, as it were.
Speaker 1:Okay, so help me visualize this a little bit more. You're selling infrastructure. What does that mean? In like something that they're trying to deliver. So they have this concept. It's data driven. They want to get their concept and the richness of their analysis out of a Google Doc. What does it look like to them in their final product?
Speaker 2:Yeah, so it'll look like something close to medium is how I would describe it. Medium is great because they really put a lot of effort and I respect them for this a lot of effort into what the articles that you write look like. Like you can tell, they put a lot of design into, a lot of design effort into it. They made it very easy to comment on specific parts of it and highlight certain parts of it, right, and I really, really, really, was kind of inspired by that experience. So what we want to have is, for every data team, a nice little repository of analyses that have, you know, interactive charts on them, right? That's something that is that should be standard, you know, for folks doing data analysis. Like, if you make a chart, why are we still screenshotting? Like, why are we screenshotting anything?
Speaker 2:So I really want to make the experience of reading an analysis and sharing an analysis good, and I think that, like, when it comes to sharing, too, like a lot of the you know, there's this concept of, like, open graph information where there's, you know, when you share something on social media, you see like a little preview, right, why shouldn't you, why shouldn't that shared preview be highly tailored to the analysis that it's related to, right and it's, you know, little features like that can really go a long way and they're not like I've even gotten to like the AI features, right, but there are just little things that would make the product or make the experience of folks doing data analysis and sharing it a little bit sweeter. So we're kind of just like hyper-focused on this one area of data analysis and data science.
Speaker 1:Cool, all right. So you've worked on everything from machine translation to integrity systems at Meta, and I just love the fact that you've worked on counterterrorism and all of that. That's amazing. I would love to hear some stories about that sometime, but tell us, how has that shaped, how you think about AI today?
Speaker 2:Yeah, I actually love this question because it's one I hadn't thought of and I'm so glad we're talking about it. So I think the primary and this is kind of a different answer that a lot of folks might expect I think the primary way that it affected you know that working on these very unique teams affected. My view on AI is that I spent a lot of my time working with decisions made by humans, right. So imagine content review. You know Meta is not just going to delete someone's account because a machine said to do it Right, at the end of the day, you need what we call ground truth or a human to look at and be like yeah, this really is an account impersonating Elon Musk, right, which was a very common thing at the time. So, you know, when humans are making those decisions, it forms a kind of data. It forms a kind of data, right, like they might have. We might have sampled 1000 accounts, right, label them whether or not they're spam, whether or not they're impersonation, and then we have some estimate of the prevalence of this problem, right. And you know that experience of working with humans to make these decisions with semi small data, and you know having a policy that the humans were reviewing against. I didn't know it at the time, right? But that is the perfect mental model for how I like to leverage AI on the back end, right? So the reason we used humans on the back end was because, at the time, they were the only ones who could say you know, yes, this post is alluding to some terrorist organization. It was actually really hard to build classifiers to do that back in the day, but now you know, an AI can easily do that, and they can do it with images too, right? So the game has completely changed, and what I realized, you know, when AI started to get really good, was that I can take that exact same process and use it for whatever we want, right?
Speaker 2:So a good example is the product or the feature that I spoke about a little bit earlier, where you can kind of ingest all the social media chatter about your product or something that happened at your company and use AI to evaluate it. Say, hey, is this, is the user here or the poster praising our company or no? Are they mentioning a specific product? Are they mentioning what might be a bug? What's the sentiment? Positive or negative? Are they mentioning a specific person who works at the company, because they did that a lot with Facebook, right, and you can take all of that, aggregate it and then just do data science on it, right, you can just chart it over time Is it going up, is it going down and that was a really, really, really powerful perspective.
Speaker 2:And I think that you know, while a lot of folks are focused on these again, these like user-facing AI features I've always been very concerned with using AI to become more efficient in a lot of ways right, to do things more quickly, to do things with less friction, to do things with a huge cost reduction. So, you know, the flashy AI feature, everyone wants to do it. But the value sometimes it's hard to communicate because you don't really know how it's going to land, right, you don't really. Until you test it, you don't know what it's going to do to your daily active users or whatnot. But with this approach, you know, using on the backend, we can say, hey, here are five processes that we're going to automate and we can. You know, if we do this correctly, you know, within, with this tolerance for accuracy, you can expect about an 80% cost reduction. And that resonates with with CEOs and leadership, because it's just so tangible.
Speaker 1:Most definitely. Yeah, it's a great reminder that some of the highest ROI is invisible. Yeah, we all want to make the machine run smarter in the background, right.
Speaker 2:Yeah, no, that's a great way to say it. The best ROI I might steal that, actually the best ROI is invisible, and I think that that's again. Ai is just like any hype train in tech. You see the flashiest parts of it, you see folks getting $100 million valuation off of something that looks very visually impressive, but at the end of the day, it's a technology that needs to be leveraged for your own purposes, and I see no shortage of opportunity in just making things more efficient on the back end.
Speaker 1:Yeah, all right. Okay, so we have a fairly large, I would say, professional audience that needs to hear how they can take these concepts and do something with them. So what's the biggest misconception non-technical folks tend to have about AI?
Speaker 2:Yeah, I love this question. I think the biggest misconception non-technical folks tend to have about AI yeah, I love this question. I think the biggest misconception they have is that they can't participate in this new wave of tech. So, if you think of the last few waves, they were a little bit less accessible, right, I think of, like the big data wave about 10 years ago. Right, that was inherently technical. You needed not only like to understand on the data engineering side how to even manage all this data, but you also needed some stats knowledge to process it correctly and to extract the insights and whatnot.
Speaker 2:This is different. Ai is different because of the medium that it happens in. Right, ai, you know, god bless the engineers who created it this way it operates off of natural language, right, the whole point is that you can just talk to it like a human right, and they've kind of tweaked it to make it even more human right, to make it like respond to you as if it were in this conversational way. And I think a lot of non-technical folks, you know, when you hear artificial intelligence, you're like, oh my God, this is like the final boss of things that I should not be talking about. Right, it sounds. It's almost scary, scary sounding, but at the end of the day, you can kind of leverage your intuition about how you would interact with a human ways to use it. But I think this thought partner approach, you know, that we kind of spoke of a little bit earlier is by far the most effective way to get started with it.
Speaker 2:So, in the article we mentioned, you know there are complex situations like real estate negotiation or like working with doctors to advocate for a family member's medical care. Medical care those are situations where you should be bringing the context to the AI, storing it in a project or just dumping it into the window and hitting enter and then kind of using it to reason back and forth. And that is so effective. And we're at the point you might see a video from me soon. We're at the point where, with the same context, I would argue that in my experience, the chatbot is giving me better responses than I can get myself. Right, I'm just going to say it Right, yeah, they're very good at reasoning and I think you know, being non-technical, you might think, ok, I'm not going to be able to like really leverage these things. It's like no, you can, you can go really far with the chatbot no-transcript.
Speaker 1:That's pretty wild. Yeah, I feel like maybe the gap is between technical and non-technical people. It's not really that. It's more like those that use AI like Google versus those that use AI like a collaborator, and that's where the reasoning comes into play. Double check my know. I saw one of your recent posts about you know what was it. I think you wrote it up here.
Speaker 2:I use this all the time. I think I use it almost every five chats. I like make a point to do it. It's what about this situation is clear to you? That doesn't seem clear to me. Ah, yes, that question is so good because it will. It makes you take a step back and you'll usually and you're usually kind of shocked at the result when you first see it, you're like, oh my God, like you are spot on, right, yep. So, yeah, I like to ask that all the time, and what I say it's doing is it's kind of like filling in your mental blind spots in a lot of ways.
Speaker 2:There are a lot of times when you, when we are so immersed in a problem that we can't take a step back and be like, hey, maybe we're focused on the wrong thing. Or one that I got from ChatGPT recently was I was talking about my startup and it was like you know, you're probably farther along than you think you are, you know, when it comes to the branding of this thing, and I was like, whoa, thank you, that's a great compliment, right For sure. But yeah, little things like that. It'll really just illuminate parts of the problem or parts of your thinking that weren't super clear to you. Very useful.
Speaker 1:Yeah, I'm going to set that one to memory. What's clear about this situation to you that doesn't seem clear to me? Awesome, yeah, all right. So if I'm a business leader who doesn't code, what's the first thing I should do to start leveraging AI effectively?
Speaker 2:That's another great question. It's something that I end up speaking to a lot of business leaders about, and they asked a very similar question to this. I'd say the first thing is to try it yourself, right, really get used to using the chatbot yourself. There are a lot of business leaders who, rightly, are skeptical, and I understand why they'd be skeptical, because you know, outsourcing any kind of thinking to a machine is risky, right, I can understand where they would see where they'd be hesitant, but I would, I'd encourage them to view it almost like a combination of a mentor and an employee. Right, when it comes to your employees, they're going to make mistakes, right, you expect them to make mistakes and you have a process for managing, for catching and managing the mistakes that they make. You got to view AI the same way, right, every once in a while. Yes, it might. It might hallucinate, as they say. Right, it might give you an answer that you're like is that really true? Then you go to Google and search and you find out it's not true. That's fine, right, it's going to happen, you know. Be vigilant. So, again, number one is to really try it yourself, right, and get in the habit of using it again as a thought partner right, using it to talk through problems and talk through dilemmas and to just gain clarity. That'll give you a surprisingly good idea of AI's capabilities too.
Speaker 2:I think a lot of folks are kind of out of touch with how good or bad AI is, and I think those daily interactions of just talking through problems with it will show you exactly where the limit is right. You'll start talking about something and you'll see it's like you exactly where the limit is right. You'll start talking about something and you'll see it's like okay, this thing is not. You know, understanding what I'm saying right now. That's the limit, right, and that the experience of hitting that boundary is good for you right. It'll teach you a lot of like what AI is capable of.
Speaker 2:And secondly and this is something that I do to start out, pretty much every consulting gig is have your team leaders you know, however, your business is structured conduct a really quick audit of just the repetitive processes that their departments are doing Right and there will be many of them Right. So the customer service team is a great example. This is where I'd argue that most of the best processes come from in terms of like automation, their ability to be automated. So you would go into the customer service department and say you know what are our reps doing every single day. That takes a long time, right?
Speaker 2:One example I found recently with a client was she was working, she was leading a call center, right, and it turned out that her reps, what she would do every single week was she would sample some number of calls, read through the transcripts and evaluate them against some rubric and then write up a little report and do an evaluation. And that is a textbook AI implementation case, right, because again, when it comes to AI for understanding, it's so good, right? So what we ended up doing was building a little pipeline that took the audio transcribed, it fed that to a chat bot next to the rubric, said you know, generate some evaluation, you know, using structured output, and from there we had basically a checklist of what the rep did or didn't do and then a little report for what they could do better. And doing that kind of unit by unit in your business. That will take you a long way.
Speaker 2:If they can say hey, here are the five steps to what I do, you can hand that to an engineer who knows how to build AI pipelines. And that is the program flow of what they're going to build. So that process of just going through finding the repetitive processes, naming them, outlining the steps and then just passing that to a team of engineers who know what they're doing with AI is powerful and I think that that alone can. You'll see crazy cost reductions. Like you'll see, like you're, if you can do this in a week and save like hundreds, hundreds of man hours, it's ridiculous, it's a crazy time to be doing AI implementation.
Speaker 1:Plus employee satisfaction. Personally, like nobody really wants to be doing those repetitive things. Exactly, exactly, exactly, yeah, yeah, right. So your advice is to personally sharpen your thinking, your AI access and leveraging it on the daily, and then upping your business operations by sharpening your tools in automating the repetitive things out of the business. That's great, right.
Speaker 2:Yeah, and I think I start with the personal part, too, where I'm like, hey, you yourself should be trying this thing right, Because I think it deals with the skepticism very well. And I've yet to meet a business leader who actually committed to using it to make decisions and didn't like it. I have yet to meet one. I've done a bunch of consulting and I haven't met a single one who, after giving it a real try, has been like ah, this isn't useful. And I think once they see it for themselves, once they're like, oh my God, this thing taught me something, that's when they're open to AI proliferating through the company.
Speaker 1:Yeah. So with the inverse in mind, do you think there'll be a time when people need to be concerned about how much the AI is doing for them and how little they're using their brain functions? Have you considered that at all? Crawling through the minefield of figuring things out on our own, it's now all abstracted away. What's the future of human thought if AI is doing all of that grunt work for us?
Speaker 2:That's a good question. Yeah, I worry about that sometimes, especially with creative writing. Oh, yeah, exactly, I used to write. If you go through my Medium account, I used about that sometimes, especially with like creative writing Like oh yeah, exactly.
Speaker 2:I used to write. If you go through my, like my medium account, I used to write a lot, you know, but now it's all so AI assisted that like I'm probably not as good of a writer, like I got to admit that and I don't know, you know, maybe maybe in the future, you know, everyone will adapt to AI writing most of the code, just like no one has to really do computation by hand anymore. But that's a really good question. I don't know.
Speaker 1:We'll keep thinking about it then.
Speaker 2:Yes, yeah, we definitely will. It's going to come up again.
Speaker 1:All right. So tell us in your experience, how can individuals without a coding background leverage vibe coding to bring their ideas to life?
Speaker 2:I love this question too. So start with a chat bot, right, and start small. That's definitely the approach you want to is like daunting, right, like a lot of like. There's just so much and you're never going to feel like you're really like good at it because problems are always popping up. So I would say start really small and start with a chatbot just making a single HTML, css JavaScript file right, a html file, so you don't have a coding background. Right. Get used to building little tools. Right, a dot HTML file, so you don't have a coding background. Right, get used to building little tools, right.
Speaker 2:So a good example is flashcards for your kids. You know, your kid has a test coming up on something simple like I don't even know, like multiplication tables right, go to Claude. Claude is good, because it lets you see, lets you build things and see the actual output, like the web page that you built in the UI, which is amazing. Go to Claude and say, hey, my child is studying this. Maybe even take a picture of one of their homework assignments. Here's what my child is studying. Can you make me some flashcards that they could use in an HTML file and it'll just do it my god, that's a.
Speaker 1:That is such a great suggestion, man, I'm gonna check that out sorry.
Speaker 2:Yeah, keep going no, no, no, yeah, I do this all the time. Uh, so, like, that's an example that, um, I used with my brother, right, but it took. No, I, I didn't look at the code that it wrote, right, I don't even know. I don't know if I use any frameworks. I don't know what the code that it wrote, right, I don't even know. I don't know if it used any frameworks. I don't know what the code looked like. I just said, hey, create the flashcards. And the flashcards appeared, right, you save it as an HTML file. It's magic, it's magic, it's crazy. You save it as an HTML file. And I was like, hey, just double click this, right, put this on your desktop, double click this, and it appears and it works, right.
Speaker 2:Another example is my wife and I, right, we were trying to like what were we playing? We were playing some like relationship card game, right, that was like asking deep questions and I was like I bet I can make one of these. It's a little more tailored to us, right? So I just gave it some context, I gave Claude some context about me, some context about her, and I said, hey, generate like a relationship card game where we can like. It was another, yeah, it was another card game Demonstrate excuse me, generate a relationship card game that's tailored to us, that'll like bring us closer or something like that, and it did it, and it did it so well and the game was actually fun, right, but but again, for new people without a coding background, that's something you can do without even having to look at the code. Right, it's like this interesting new way of doing things called vibe coding right, where you almost forget the code is there. Right, there's a carpathy tweet about that and, uh, he was the head I believe he's the head of ai andrew carpathy.
Speaker 2:Yeah, right, right, and this guy's like he's been doing, you know, like language-based AI for a long time. I remember reading his articles in like 2014. But, yeah, you almost forget. The code is there, right? You're literally just speaking or typing and the app appears and then you say, hey, change this thing right. And then it tweaks it right, and if you're a non-technical person, you can get pretty far with just this, like html, uh, with just html files and tweaking them through natural language.
Speaker 2:From there, you just copy it, save it in a text file, uh, and we can, like I'll maybe leave some instructions in the comments, right, for how to do that save it in a text file and then just double click it and the app you built appears in your browser. So I would say, start there, start with Cloud, because you can even see it as you're typing, and just use language to kind of sculpt this app Like the way I described. It is build by reacting. I think that's a great way to view. You know how to get into vibe coding if you don't have a background.
Speaker 1:Totally, you, you know how to get into vibe coding if you don't have a background. Totally, this was. This is a little off the cuff and I've never done this with any of my guests, but I I did take your suggestion and I created this app this morning with claude and I'd never used claude before and I wanted to share it with you real quick yeah, absolutely so so this is this is the game.
Speaker 1:Uh, I just died. Wow, it's good. This is the game that I created this morning with one prompt. The prompt is on the left hand side and basically it's space invaders with blocks of cheese, like I said, and I'm just blasting them away. And I do have lives. I just lost one. You know this.
Speaker 1:I shaped in two prompts. Right, I said I would like you to create a video game set in the year 2121. Make it like the game Space Invaders, but with one noticeable difference the invaders are blocks of cheese. And he came up with this concept of Space Gutas Dairy Invasion of 2121. And it spit out all this code and I was like I wonder if this thing's going to work. And then all of a sudden it's presenting this UI and gives me the storyline gameplay, in case I wasn't familiar with how Space Invaders works. It's got all of these types of invaders with descriptions Mind-boggling, honestly, to see this could come out and be perfect.
Speaker 1:I mean, not like ideal necessarily, but it worked with one shot. And then, you know, I was in my first pass, I was losing a lot, so I said, okay, what was my second prompt? I said let's make it two times as hard to kill the player. I think the cheese shoots too often and too accurately, and so it slowed it down and it allowed me to win my levels. Incredible. That's where we are and, honestly, man, I published it and I didn't know I could publish this and I copied the link to the Discord channel for AI Ready RVA and I made it available to anybody to play. I don't know that anybody's reacted to it just yet, but I'm definitely looking forward to their reactions.
Speaker 2:Yeah, it's so crazy Because, like, I think of like how long this would take, like, take me to code up, right, if I was trying my hardest, if I was totally focused, had nothing else to do, it would take a while and I would get the physics wrong, right, I would like, I'd be like thinking of like there'd be so much to manage, right, you'd have to design it. And the fact that an AI could just spit this out, you know, literally word by like, token by token, is it blows my mind. Like things like this never cease to amaze me, yeah.
Speaker 1:Yeah, Crazy. It's awesome. I'm going to continue working with Claude and see what else it can do. I love that you made vibe coding approachable with just a few statements of you know, start small. You know, break down your tasks and see what it can do. I think that's, that's totally approachable advice.
Speaker 2:Yeah, yeah, absolutely. I think it's also a good way to get into coding, like. One thing that I never liked was how everyone's saying like, oh, it's not a good time to major in computer science or learning to code is dead right, even though I use it to generate a lot of code. I totally disagree. Right, because code is the medium between natural language and everything. Now, right, if something can be controlled with code, now you can control it with your voice or by typing words in natural language. If you have any kind of understanding of code, you're so much more empowered to build things with AI. Now, anything that you can hook up to any kind of code now is AI controllable. So, yeah, I think there's never been a better time and I think it's a great way to get started, absolutely.
Speaker 1:So what tools or platforms would you recommend for non-technical folks eager to experiment with vibe coding?
Speaker 2:Yeah, I would say definitely, Claude, just because, again, it has that UI that we just talked about and you can kind of talk through things with the webpage next to you, right. So it's almost like you and the chatbot are looking at. I think of it as sculpting in a lot of ways, right. It's like you and this assistant are just looking at the statue and you're saying, oh, the arm looks a little funny, can you like take a little bit off the shoulder right, and it just chisels a little bit off the shoulder. I really think of it like that. So definitely, claude.
Speaker 2:If you want to get a little bit more down and dirty, I would say Cursor. You know, i't know, cursor is what's called a text editor, right, which is where you actually write the code out, and it has AI integrated in really, really, really nice ways. So everything is kind of right there. And you know, if you want to extend you know the game you built or the flashcards you built you would dump that text into cursor and then just chat over it there and it can kind of make, make more edits. So it's really good and things are. You know the cursor team. I think they went from like a hundred million annual recurring revenue to 200 in like a month or something like that, something crazy. And these guys are one of the one of my favorite companies like they're. They're really good. So I would say follow what's happening in that space with Cursor, but those two tools will get you really far.
Speaker 1:Yeah, that was. My first step into vibe coding was with an IDE like Cursor, and I use VS Code at work and I've used various other IDEs. But cursor was like VS code on steroids, and when I started mucking around with that thing I ran into the occasional error Maybe I was asking for some code updates that I didn't have some of the packages built into my system already and so I would have to troubleshoot my way through that. But it was a profound shift for me. Just experimenting with that, I did get some of the most basic apps working. I don't know that it's ready for something as easily accessible as what I just did with Claude this morning. Right, but you're right, if you want to do some enhancements and get your hands in the code and really leverage different libraries and be more intentional as a software developer, you'd have to get into the IDE, and that's where the real power can happen. I think, yeah, absolutely. So what common hurdles do you think non-technical individuals face when diving into vibe coding and how can they overcome them?
Speaker 2:Yeah, so I think you know there are a few different kinds of ways that you can build.
Speaker 2:You know, when it comes to vibe coding, one is just building like kind of like one off apps that you might send to a few people and that are useful, right? I think, honestly, there's going to be a lot of folks in the future who are building little tools for their teams. They just need to share them. I think that's going to be a lot of code now and you, as an EM, know it would be insane to be like, hey, can you build a tool for us that we need later today? Like that would never happen nowadays. But I think with the way things are going, it's going to right. So, in terms of hurdles, I think that the hurdles that you'll start seeing really occur when you start building things that are closer to being used for like mass adoption. Right, and obviously you would never vibe code something like into production, right, you want to get like real engineers to handle like the just the necessary, like plumbing that comes with, like building something that's in production. But I think there is a middle ground, right, and I find myself building a lot of like prototypes and MVPs, both for companies or just to like show folks, or just for like to show my, like co founder, like and like my team, and sometimes they incorporate expected functionality, right, it's kind of what I call it right, where people want to be able to log in, right, people want to be able to change their profile. People need you might want to have billing enabled, right, you might want to have you know authorization or with a data like database with authorization right, and those things are not something that you want to be coding yourself, right, like you do not want to code up and like I learned this the hard way you don't want to code up like an email registration flow right, it sucks, no one wants to do it right?
Speaker 2:So I think a huge hurdle for non-technical folks is when they encounter that, when they encounter having to build some kind of expected functionality and a lot of them will be like, okay, I'm already vibe coding, why don't I just vibe code this? Right? And I would say, don't, do not vibe code these like standard things, right, yeah, so I would say, like, the way to overcome that hurdle of these expected things that everyone expects to be fast and smooth is to use frameworks and templates as much as you can when you get to like the bigger stuff. So there are JavaScript frameworks. One is nextjs. I like viewjs, so thumbs up, nice, I like viewjs, which is I think yeah, it's called Nuxt with a framework, and I would say leverage those as much as you can, because they have a lot of that stuff built in Right and on top of that, the AI knows how to incorporate it Right. The AI knows Nextjs, it knows Nuxtjs. Going another level higher, can we just like?
Speaker 1:yeah, go ahead going another level higher. Use a framework. Can we just talk through that one a little bit? So giving a prompt, a natural language prompt, to the AI and say go build this Space Invaders clone is one thing, but how do you incorporate Nextjs into a prompting system like that? Can you give me an example?
Speaker 2:Yeah, and this takes a little bit more experience and it might be a little bit down the road for a lot of non-technical folks, but eventually you want to learn how to kind of spin up like these full stack apps, right. So this is where I think the vibe coding gets fun right, Because you can build such complete systems really quickly. So I would encourage anyone to go to like just Google Nextjs and you'll see what I'm talking about, right. But it's a framework with kind of like that's kind of batteries built in. So what you would essentially do is you would start a project with Next and then you'd open it up in Cursor right and then you talk to the chat in Cursor right and then you talk to the chat in cursor right and it has access to all the files in there. It knows how to use the framework and you can get a lot built out really quickly. So I'd even take it a step further than that and say you know what? Don't start from scratch with these frameworks.
Speaker 2:Use a template, right and templates. You know, if you'd asked me, like three years ago, I would have said I would have been like too proud to use a template. I'd be like, no, I'm gonna code it up myself, right, but, uh, the templates have a lot of functionality already built for you and you can test them right. As an example, like a lot of apps like have like a sidebar right where you can click like the different views you want to view yep, uh, you need that to be smooth, you need the routing to work, you need the URL to change correctly, Right, and that needs to feel smooth if you're going to have other people test it out, Right. And I would argue that if you start with a template where it already feels smooth and then just use, you know, kind of open that in cursor and kind of make your changes to make it your app, that's a lot easier and a lot. You'll get a much more stable product than if you were to just vibe code the whole thing from scratch.
Speaker 2:So if I had to kind of like, take a step back and, you know, give a high level view of what I'm saying, I'm basically saying you know, stand on the shoulders of giants, right, Don't try to vibe code everything from scratch, just so you can say it's your own right. I used to have this complex in my head about that. Even if you're non-technical, try to find projects that are close to what you're doing, but just need a little bit of customization and start there and that's where these templates come in. So, yeah, I would say again stand on the shoulders of giants, leverage the work that's already been done and use templates and kind of edit those. So it's a little bit down the road, right. A lot of you can get a lot done just vibe coding from scratch in Claude, right. But if you start building like prototypes of your apps which you probably will if you get good at vibe coding you apps which you probably will if you get good- at vibe coding, you're going to start thinking hey, I can build this app right.
Speaker 1:Start with templates, where a lot of the flows already optimized for you. Yeah, totally so. Don't fight the complexity, right? Yeah, learn from others. At my office, we always say don't reinvent the wheel, right? So if the scaffolding already exists, use it so that you can focus on creativity, right? Exactly, make your idea different than what the template was and better, right?
Speaker 2:I think that makes a lot of sense.
Speaker 1:Great advice, okay. So looking ahead, how do you see vibe coding evolving, especially in making technology creation more inclusive?
Speaker 2:Yeah, I love this question because this is something I wrote another Medium article about earlier, where I predicted that data analysis would happen in natural language at some point. Right, I didn't know, it would be like 2025. I thought it was going to be like 2035, to be honest, but it happened so quickly. So, to answer your question, I think at some point the AI will become so reliable that even people with a technical background will just stop looking at the code, kind of like, jason, like the app that you built, right. Like you say, hey, build this feature for me or build this thing for me, and you're not. Maybe you looked at the code, I don't know, right, but you're looking at the final product, right. You're typing out what you want and you're looking at the product and you're reacting to that, and then you're going back to the natural language prompt, right, and you're tweaking it, then looking back at the final product. In the middle of that is code, but you're confident that that code is correct, so you don't have to look at it that much. I think that that will be how vibe coding evolves for the better, and that's going to make it more inclusive, where a person who doesn't have a technical background. Who doesn't necessarily speak JavaScript? They can say, hey. Who doesn't necessarily, you know, speak JavaScript, they can say, hey, you know, I need to review a bunch of tax forms. Right, just build me a UI where I can quickly skim through this section. For each one, and I hit the right arrow key and the next one pops up, and if I hit the space bar then it deletes something. Right? That kind of useful vibe coding software, I think, is going to be able to be built really quickly and I think that you won't have to worry about the code, right? So that's going to really really make adoption much faster. When I say adoption, I don't just mean of chatbots, I mean the adoption of people interacting with code, people building things, right. So, yeah, I think you know, the first thing that's going to change is that the actual code will just kind of fall away, just like a lot of the computation that happens on our like. Right now we're both using laptops, right, but you don't have to think about anything memory related, you don't think about any computation, right? It's just happening, I think. Secondly, there will be a lot more and I don't know the best way to say this, but there'll be a lot more forms of creating that will also start to occur in natural language.
Speaker 2:So data analysis is an example I just used where, let's say, you're investigating bank fraud right, you have some system that's hooked up to a huge database, right, and maybe you're just talking, you know, maybe you're saying, okay, I'm suspicious about you, know Tim Smith's transactions last month, show me the last 10 transactions. Then on a screen, the transactions show up, right. Or maybe you're wearing a VR headset, I don't know, make this even more futuristic. And then you're like, okay, of these transactions, how many were outside the US? And then those pop up. Or the answer pops up and you say, okay, show me who they were to, right, and then you see, like a few different names, how many of them were over $100,000? And then you know, you see a bunch of transactions and one name pops up and the analyst is like, ah, found it right, I found the fraud.
Speaker 2:I think that kind of thing is going to become much more common, as right now, again, there's this intermediate code step right, where I have to take myself out of my investigation mode and write code, right, that's what my job was when I was working on integrity, right, I would be. What I wanted to do was kind of be an investigator, right, was to be asking questions, kind of interrogating the data, right. But I would have to take myself out of that loop and use my brain to write code which kind of completely snaps you out of anything else you're doing. So I think that you know, for this data analysis example, you can stay in the investigative mode, right, the medium is just natural language which we're used to. So the code will kind of fall away and it'll become much more, much more easy to just do the thing you want to do, right?
Speaker 2:I think that that's that kind of thing, is going to extend to many different domains that I probably can't even think of now. Right, I'd imagine like wearing a VR headset. Let's say I'm an interior designer, you walk into an empty house, you're wearing a headset and you say you know, style this with like art deco. Give this an art deco theme, put the couch right there. Okay, move the couch over here. Actually, let's imagine that there's a house party happening right now and all the people appear around you Right, and these things will be happening again On the back end.
Speaker 1:There's code being written, there's some kind of config or something being generated that's changing the thing for you, but you are just thinking in natural language and reacting to what you see, and I think that pattern is going to really expand to lots of different creative endeavors and forms of building. Wow, I believe it. An hour ago I probably would have been way more skeptical, but the way you described it, I totally believe it, and it's not about obsessing over the code or learning to code really anymore, although you did say something that I believe to be true we need coders, we need people that understand the code. You have to be able to elevate your vibed output to something extensible, something production-ready, scalable all of that. That's super important for running businesses with software. That has to still exist, and I don't think AI is there yet.
Speaker 1:I am cautiously saying those words, but here we're all in the vibe coding setting and letting our curiosity take the hard parts out of the work, which is amazing.
Speaker 2:Yeah, it is, man. It's a crazy time to be alive.
Speaker 1:Yes, it is. I'm excited, man. All right, so what's one piece of advice you'd give to someone working inside a big company today who dreams of launching their own AI-powered startup?
Speaker 2:Yeah, that's a good question. I'm going to give you three, because there's just so many things I wish people had told me when I was starting this.
Speaker 2:The first is to focus on yeah yeah, the first is focus on problems, not solutions. Ai is a solution to many problems, but you will get much further by focusing deeply on a problem, preferably one that you experience yourself, right, which is kind of how I started Aura. It requires a mentality shift, right? You know, before I was a founder, I would kind of shy away from people who were talking about their problems. I'm like, okay, here we go, right, let's be positive. Right, but you want to start being obsessed with that, like, when someone starts talking about their problem and you're a founder, you should kind of hone in on that, you know, and be like, yeah, well, actually, what's going wrong? Right, a lot of time you'll find out that they're like man, I have all these customer service interviews that happened and I can't, I don't have enough time to process them. You know, my boss is pressuring me to hit these KPIs and I just can't seem to get it done.
Speaker 2:As a founder, you're like, boom, that's my startup idea, right, you go home, you vibe code out a prototype, right, which is exactly what I've done before. You vibe code a prototype. You hit that person up like, hey, you wanna check this out really quickly. Maybe you send them the published quad link, right, and you're like, would something like this help you out? And if they say, oh my God, yes, I can't, oh, this would be a godsend, right, you have validated that idea, right, you validated that someone will pay you for this, right, because you just solved their problem.
Speaker 2:So I would say, firstly, focus on problems and kind of match them to solutions. It's a mentality shift that is kind of counterintuitive, but it will get you really far. Like, the best startup founders are obsessed with problems. They look for problems, they join, they go networking, just so they can hear people's problems. So that's number one. Number two leverage AI to the hilt, leverage it as much as you can, but also leverage experts in your network. So I have a rule that if there's a concept or something that I just cannot figure out or something I can't crack, I reach out to somebody on Upwork or I reach out to through my network, Right? A good example is when I started, I was using, like the raw Azure cloud, right, just to like launch my prototypes. It's a pain. I mean, you know how, you know how cloud goes, right, like they don't try to make it easy for you, and I was like, okay, I don't know how to do this, so I reached out to know everything in order to do anything.
Speaker 2:Yeah, it's a, it's a, it's a thing, man, it's like, uh, there's a lot of coordination necessary. And I reached out to a cloud expert and he was like he's like, you know, honestly, like you can, if you want to, you can go this route, but it seems like you're more product focused and you just want to launch. Why don't you use something like Vercel with Supabase as the backend? Those are two products for those who don't know, and it was the best advice I'd ever gotten. Honestly, it saved me so much time and the AI, for whatever reason, couldn't pick up on that. But this human still had some advantage that the AI didn't and that he could kind of see where I was right and be like hey, this is probably a better path for you and it was some of the best advice I've ever gotten. So always remember that AI can't do everything and when you're really stuck, reach out to humans. It's a great way to network, if nothing else.
Speaker 2:And lastly, is to just get used to uncertainty, and this is the trickiest one, because it feels like. It feels like you're doing something wrong. If you were good at your job, right, if you're good at your job, you know people bring you in when they need certainty, and you usually have seen the problem before and you're like, oh yeah, just do this right. There are only so many things that can be different and you just have this like great pattern recognition for it. When you're a founder, those are the exact kinds of things that you need to be paying someone to do.
Speaker 2:If that makes sense, right. If there's an established way to do it and you feel comfortable doing it, it feels familiar. That's not what you need to be working on, right. You need to be kind of bringing new things into existence and dealing with problems where there isn't certainty yet because you're doing something new, you're building something new. So I would say, getting used to that and understanding that it's not a bad thing, understanding that this constant, you know, not knowing exactly how something's going to pan out is a sign that you're doing something worthwhile, right. It's not a sign that you're dumb. It's not a sign that you're bad at your job. It's a sign that you're kind of on the right track, right. And once you get comfortable, once you're like, okay, I got this, you know this, this, this part of it makes sense, that's when you need to hire somebody let them handle it Right and you kind of like drive on, you know, and find the, find new opportunities.
Speaker 1:So I know that's a lot, but these are things that I wish somebody would have told me much earlier in my career. That's beautiful man, that that's, that's gold. So fall in love with the, with the problem, not the tool. Right, right, and I love the mindset If it feels routine and certain, maybe it's time to delegate. Yeah, right, yeah, yeah absolutely. I love the uncertainty pieces. That's where the real human instinct kicks in. Yeah, and the creative side of us can thrive and build things that no one's ever thought of before.
Speaker 2:Absolutely and also like it kind of brings out a side of you that you might not know was in there. This is getting a little woo right, but like it's um, you know when you're again, when you're doing work that feels that you're, that you're used to, right, you don't have to be like daring, really, you don't really have to be. You're gonna be creative, but not to the extent where, like, you would be creative if you genuinely don't know something's gonna work out right. If you want something to work out and you're not sure, you turn on a part of your brain that's almost like a bit of a maverick right, a bit of a cowboy. You know where you're, like okay, I got to figure this out right. And you approach it confidently. You really don't know if it's going to work out and it turns something on inside of you and I think that a lot of people who experience that like who it turns them into.
Speaker 2:And I think that's what keeps a lot of people as founders when you know, as you know, like if you're, if you have skills to work in tech, you can make a lot of money Right, but to to let that go to do something that's uncertain, I think the reason a lot of founders do it is because of who it, of what it brings out of them.
Speaker 2:I think the reason a lot of founders do it is because of who it, of what it brings out of them. Right, it really lets you. It lets you see what you're like when you're facing a real uncertainty, when you really have to, just like when there's a lot on the line and you like you got to roll a six, you know, and you got to figure it out. So for me, that's kind of what's keeping me keeping me here, cause, like again, as you know, like tech is tech pays really well. But I think that that, uh, a bit that adventurous side that it brings out of you is actually it's a lot of fun, love it so, kyle, where can people follow your journey or get involved with what you're building next?
Speaker 2:yeah, so I think the best place is linkedin. I do a lot of posting there. I try to post a little more video now. Uh, I have a tiktok too. I'll tell you about like it's a linkedincom. Slash in slash. Gkjohns. Like GK Johns. My Twitter is xcom slash Kyle D-O-T-A-I. Like Kyleai, but spell out the dot. And on TikTok, I'm Kyleai like K-Y-L-E-D-O-T-A-I.
Speaker 1:Awesome, All right man Surprise question, but if you follow my podcast you'll know it's coming. If you had any superpower, Kyle, what would it be and why?
Speaker 2:That's a good question. I would say complete control. This could get very deep. It's funny because I was going to say mind reading. I actually thought of this. I was going to say mind reading, right, but I was like I don't know if I could. You know, these like AI as a thought partner.
Speaker 2:With using AI as a thought partner, I've really, really, really had a lot of fun trying to understand like complex social situations that I'm in, right.
Speaker 2:So an example might be you know, I'm working with a company and you know something that I think something fishy is happening.
Speaker 2:You know, and here's an email thread from the CEO and here's a post that this person made and here's some context about what's going on with the stock price and here's this weird thing that my report said to me, right, and I have a lot of fun like dumping it all into chat, gpt in a project and just talking through it and trying to figure out what's going on, trying to get clarity on the situation, if nothing else, just because I think it's a fun thing to do. So I think if I could have a superpower, some kind of like perfect social understanding, where I can immediately kind of clock what's happening and know what people are thinking. I think that'd be a lot of fun, because I've definitely had a blast, you know, using ChatGPT as my like gossip partner, yeah, so yeah, I think it would definitely be some kind of like instant mind reading, social understanding. I walk into a room and I know exactly what's going on between everybody.
Speaker 1:So emotional intelligence basically you know beyond the self awareness, but social awareness and being able to read the room without getting tripped up.
Speaker 2:Yeah, that's really cool. I think I'd have the lamest superhero costume, like emotional intelligence man. Probably isn't the coolest superhero, but I think it'd be fun.
Speaker 1:Yes, awesome, awesome. This has been so much fun, kyle. I know the audience is going to love what you've put down here and there's so much to dig into, so many nuggets of wisdom here. I really appreciate your time and hope you have a wonderful rest of your day and hope to see you on the podcast again soon. Yes, sir.
Speaker 2:Absolutely, man. Thanks for having me on. I really this was fun. I really appreciate it. I like this format. This is good, awesome, well, thank you, awesome Cheers, man format.
Speaker 1:This is good, awesome, well, thank you Awesome. Cheers, man, and thanks to our listeners for tuning in today. If you or your company would like to be featured in the Inspire AI Richmond episode, please drop us a message. Don't forget to like, share or follow our content and stay up to date on the latest events for AI Ready RVA. Thank you again and see you next time.
