Artificial Antics

Episode 19 - Part 1 - Launch First: How AI Drives Smarter Startups with David Hirschfeld

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Launch First: How AI Drives Smarter Startups with David Hirschfeld | Artificial Antics Podcast Ep. 19 (Part 1)

Rico and Mike sit down with David Hirschfeld, Founder and CEO of Tekyz, to discuss how AI is reshaping startups and business operations.

David shares his journey from physics to enterprise software and introduces his “Launch First” methodology, a revolutionary approach to achieving product-market fit. Discover how realistic prototypes and pre-sales drive startup success while reducing risk.

This episode also highlights practical AI applications, the difference between AI and predictive analytics, and a fun story about designing a garden with ChatGPT.

Packed with actionable insights, this episode is a must-listen for entrepreneurs and developers alike. Stay tuned for Part 2, where we explore the future of AI!

🔗 David Hirschfeld's Links:

🌟 Don’t forget to like, comment, and subscribe to stay on top of the AI revolution!

📖 Chapter Markers

00:00:00 - Intro: Welcome to Artificial Antics

00:01:19 - Meet David Hirschfeld: CEO of Tekyz

00:02:05 - From Physics to Sales to Enterprise Software

00:06:55 - Lessons from 80+ Startups: Why Most Fail

00:11:46 - AI vs. Predictive Analytics: Key Differences Explained

00:13:27 - “Launch First” Methodology: The Power of Prototypes

00:16:50 - Case Studies: Real Stories of Pre-Sales Success

00:25:40 - Practical Tips for Using AI in Business (and at home)

00:26:54 - Funny AI Story: ChatGPT and a Gardening Plan

00:31:03 - Closing Thoughts: Stay Tuned for Part 2

🎧 Huge thanks to Nomad Studios for mastering this episode! Level up your audio-visual game at https://www.nomadstudios.pro/.

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Episode mastered by: Nomad Studios (https://nomadstudios.pro)
Description: The team behind mastering the Artificial Antics podcast audio. Big shout out to Nick and the team! 🎉

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Natasha: [00:00:00] Welcome back to Artificial Antics, where Rico and Mike will talk about the implications and opportunities around artificial intelligence, machine learning, and deep learning.

Mike: Hey everybody. Welcome to Artificial Antics. I'm Mike and I'm joined with my co host here, Rico. Uh, we've got a really exciting episode for you tonight. That's near and dear to my heart. Um, we're going to be interviewing, uh, David Hirschfeld and David is the founder and CEO at a company called TechEase and what they're doing over there at TechEase is really hyper fast development, right?

Mike: And I know folks have talked to me, especially, you know, you've seen what I'm doing where I'm building applications sometimes in like seven minutes. Well, David is a like minded in this, right? And the last time we talked, uh, he was showing me some stuff he was doing with the product called Bolt. I was showing a little, a little bit of what, what I'm doing with REPLIT.

Mike: And, uh, and so we're really excited to talk to David about his AI journey and what he's [00:01:00] doing, uh, in his businesses. So, uh, David, without further ado, let's go ahead and, uh, yeah. Pass it over to you. 

David: All right. Thanks, Mike. And thanks Rico. And great to be back. And I'm really excited to talk to you today. And regarding Bolt and Repl. it, I've abandoned Bolt. I'm all in on Repl. it. So that conversation was pretty meaningful. I've, yeah. So thank you for that. 

Mike: Absolutely.

David: So I've been in software development for a long time, 35 years, actually more than that. I don't really want to admit how many years it's been so many, and I started out in enterprise.

David: Uh, actually I was a physics major in college and then from college I went on to sales, believe it or not, from physics speak, uh, uh, I didn't, I didn't, the, my peer group was, it kind of made me a little unnerved if I was going to be. Uh, go into graduate school in physics, then this social group, my peer group was not people that could speak very clearly about anything other than [00:02:00] equations.

David: And so that kind of unnerved me. So I ended up going into sales, um, and so I have that weird blend where I can talk. To people about their business problems, but I also can talk very technically about things as well. Um, but I don't get stuck on the technical side and trip over what I'm trying to say when I'm trying to explain a simple concept.

David: So anyway, but I went into sales and then from there I went into software development and I worked primarily for enterprise in my early career and, uh, for computer associates in Texas instruments. And I did, uh, Projects at Intel and Motorola and Allied Signal and, you know, names that you would know. Um, uh, but then I started my own software company and logistics route distribution inventory management in the early 90s.

David: Despite all the efforts on both myself and my partner, we ended up growing it anyway to 800 customers in 22 countries.

David: And sold it to a publicly traded firm in 2000, 8 years after we had started the [00:03:00] company, um, which we had no fantasy of any of this when we started. Right. But, uh, we ended up with, we were just going one step at a time, but then when I was VP of products for the company that acquired us for the next several years and then left them cast about for a couple of years and then started techies in 2007.

David: Of course, I thought I knew what I was doing in terms of how you start a software company. and 

David: actually, I didn't realize that I did a lot of things Right,

David: because I didn't realize what those things were that I did right. I thought there were other things and it was, and then it was many years working with a lot of startups over the last, 17, almost 18 years now, we've worked with 80 some odd startups.

David: A couple of them were really successful. The vast majority of them fail. Um, um, and, uh, it was in this process where I started to realize what it was that, what I did that made me successful in the common traits of, Successful startups, but talking about AI and all that. [00:04:00] So yeah, we used to use predictive analytics tools that felt like AI, but they weren't AI, of course they were using, um, uh, uh, complex, complex algorithms to make these predictions.

David: Um, not, and, and still today, these algorithm, the very sophisticated algorithms for like financial predictions for people's like retirement models and all that. Um, but they're just algorithms, right? They're not. They're not AI. And, and of course, I'm assuming most of your audience knows this, but the big difference between a predictive analytics tool and an AI tool is AI identifies patterns that a predictive that you can't see or know, whereas predictive analytics is expressing a known pattern, uh, and using algorithms to do it.

David: So you literally learn and uncover things using, artificial intelligence that you didn't know and may not have existed in terms of consciousness prior to that tool uncovering that thing. Um, uh, and I have lots of examples of this. I'm not going to go [00:05:00] into them right now, but probably a lot of people know what they know of examples themselves.

David: But, um, I will give you one example. The guys that, um, uh, developed open AI, once they started to produce, um, um, natural language sounding, um, um, output from the stool based on questions they were asking, they had no idea. How it was able to do that and write in such a natural way, uh, produce words in such a natural way, just by doing word prediction based on, um, uh, a very large model, having Uh, built all these vectors right between all these nodes.

David: Uh, so that's the technical aspect, but the, uh, so they didn't realize those patterns would just naturally emerge. Um, I still don't know how it does it exactly, uh, but it does it and it does it really well. And so literally [00:06:00] there. Kind of like falling forward and it's just a kind of a controlled fall in the process of expanding and building what AI is capable of giving it new capabilities and then watching what it does with those new capabilities and Some of them are predictable and some of them are not and they just keep kind of following The value proposition and moving in that direction.

David: So I started working on Uh, with AI tools in the early, uh, when did tensorflow come out? 2013 or something like that from

Mike: that sounds about right. Yeah. 

David: Yeah. 

David: But I started playing with AI back then using tensorflow and. Um, and it was pretty cryptic at the time, but it was, but it was real AI. Um, it was really the first real consumable AI is from my perspective.

David: Um, um, so I played around with that and never built any practical applications with it. Just more just playing around logic test. And then, of course. You know, [00:07:00] I'm in business and people come to me with projects and that becomes my focus. And my focus of building a really exceptional software development team was what captivated me throughout all that and staying ahead in terms of technology.

David: And. We're, you know, when you're talking about building a company of that operates in an exceptional way, you are always building it. You're never not building it. You're just continually pushing and improving because it's never exceptional enough, which is the whole concept of trying to become exceptional.

David: Uh, and then Open AI, a start, uh, comes out. This is before ChatGPT and I'm reading an article that was, that OpenAI wrote about itself and I was blown away. And this was about a year before ChatGPT came out. It was a Scientific America article, maybe not even a year. Um, so that's when I started really engaging again with AI in a, in a bigger way, um, uh, and using it to see, and then [00:08:00] ChatGPT comes out.

David: Uh, and, uh, uh, and then all of a sudden as really consumable, uh, by everybody, of course, because they had whatever the fastest adoption of any product in history by, by orders of magnitude, not just Right?

David: Slightly better, but unbelievable. Um, so, of course, immediately I'm, uh, the whole exceptional thing is you've got to constantly push the envelope in terms of not only how you run a project and how you, um, design and architect things, but also that you're on top of technology from a leading edge perspective.

David: Uh, not bleeding and even bleeding edge to some degree where you're constantly testing the bleeding edge to see what's practical and can't and you can and can be risk mitigated in terms of applying it to customer problems. Uh, so then, uh, and what I've been finding even like [00:09:00] since the last time we spoke, which was a few weeks ago, Um, is the speed at which this is improving, um, it just makes it impossible to really predict what's possible.

David: So like, as a result of some of the things I've been doing in the last couple of weeks, you know, I'm reinventing, uh, deciding to reinvent my company again, because I can't just be okay. Even with the accelerated pace that we're doing things at now. It's not enough. Um, it won't, it won't matter in a year. Um, I'm not sure what will, I'm not sure what will matter in a year, but definitely what we're doing Right? now won't matter 

Mike: Yeah. Right. Right?

David: Yeah, right. Like, and like tools, like Repl. it was really a hinging point for me. So thank you for that. Um, you know, I was playing with Bolt and it was quite good, but it wasn't, but it had some problems and not that Repl. it doesn't have problems, but it's that much better. [00:10:00] Um, in all the ways that you told me it was, um, uh, in fact, because I'm developing, uh, I decided to start a project of my own to build, uh, in my spare time, which is not a lot, but to build a, a partner portal, basically a part of referral partner portal.

David: Since I. And building up, you know, my referral partner 

Mike: Mm hmm. 

David: and I need a way to be able to capture all that information and also for my referral partners to be able to log in and give me a referral partner when it's recorded, when it was given, and then a way for them to be able to monitor the status of that partner between the time they gave it to him until that actually becomes potentially a client.

David: And, and then how much revenue is being generated from that client for the referral partners to be able to. See what fees that they've been accruing and what's been paid out. And Right. And so I started using replic to build this, and I was doing this on my own to just to see how far I could get with replic on this.

David: And I've actually [00:11:00] building out the whole application with this so 

Mike: that's 

David: not scalable. It's not scalable. 

Mike: right. Right. I get that. 

David: right. But does it need to be scalable for this app? Probably

Rico: for

Mike: Probably not. 

David: Not for 

David: this. Yeah. And I could Probably turn it into a SAS product, which I'm actually using replica to build out that, um, uh, uh, that infrastructure, right.

David: But again, it won't be scalable, but it really probably won't need to be scalable, at least not until, not. 

David: unless it starts to get really big adoption. And that by the time it does, I'm going to have tools to be able to generate microservices on the back end. Um, uh, and some of those microservices and they'll be containerized and some of them will run in auto scaling environments like Lambda whatever.

David: And, uh, uh, and I'll be able to use the tool. So that, so the reinventing that we're in the process of doing, which I told my director of operations the day before yesterday, she was actually [00:12:00] thinking the same way, um, as that, uh, we need to think, okay, what agents do we need to build? We need to be thinking about agents that.

David: We'll transform how we do what we're doing today. Um, uh, both agents that may operate real time, as well as agents that will produce results like, like a microservices development agent, and maybe a workflow agent, and maybe, you know, in terms of how these apps get strung together. And then use an AI, uh, scaffolding or infrastructure to be able to then, um, insert the business rules and snap these pieces together and generate the user experience in the front end and, um, generate test scripts and, uh, and implement automated testing and, uh, the quality, you know, code quality checks and, you know, all this, Right. And 

Mike: Yeah, 

David: automate as much as possible. Right. This is sort of my thinking from a reinventing perspective, what we do. Um, we were already working, building some AI [00:13:00] models, which I had mentioned last time we spoke, um, internally one for my, uh, startup methodology for the niche analysis piece. Uh, another one for, uh, uh, for estimating projects.

David: And we're a week away from being able to. See the, some of the fruits of that, uh, and then we'll actually start an early, um, uh, a pre launch sales campaign on that cert is, uh, you know, and, and that one, we had to build a working model before we could go out and start doing pre launch sales. So I've kind of jumped into the, uh, a startup discussion as opposed to an AI discussion there.

David: So I'll try to stick with 

Mike: No, you don't, you don't have to, you don't have to stick to it. Honestly, you know, what's, what's interesting, David is, you know, when we talked last, I was really interested in your, your launch first product. And, um, so why don't you actually tell the listeners about this? Because I've talked to a couple of people about it, [00:14:00] just at the base level of what I do, um, and what you were doing there and they were like, Whoa.

Mike: Whoa. You know, 

Mike: so talk about that finding product market fit, uh, before, before, you know, spending the buy in the farm. Right. So I, I'd actually, I think our listeners actually love to hear that. So 

David: Okay. All right. Well, I'm happy to talk about, actually, I can't help but talk about that because I work with a lot of startups, right? Um, uh, so launch first. So, so we started, uh, the, first of all, how did launch first? How to figure out what launch, what launch versus today. I think that's, it helps to explain what it is.

David: Um, we started, you know, we've been developing software for a long time. Uh, uh, and we realized that we're constantly having to iterate during the development process, because even though we did a really complete design, what we thought with user experience and understood the requirements as we're getting into the actual delivery of this.

David: Founders are saying that's not gonna [00:15:00] really work. It's not, you know, it's not really supporting the work of the business the way I thought it would. I, and they always say, but this is what you told us, Bill. They say, I know, I know, I know, but now that I'm actually playing with it, I can see that it's not Right. And so we spend a lot of time iterating, which drives the cost of the MVP way up, um, or post MVP. Whenever it was, they decided to make The changes that they realized they had to make to support the workflow, which may or may not be what they need to do to have product market fit. But that was a whole different issue. Right. Anyway, so they. Um, so then I, we started doing more elaborate, uh, design, uh, mock ups until we got to a point where the design mock ups actually were almost functional prototypes. Um, we use tools like, well, uh, we, to some degree we use Figma. To the degree that we have add ons where we can animate all the functionality in it because you can do a lot with Figma now, you couldn't two years, you couldn't two years ago, but now you can to [00:16:00] really animate the mock up into a real prototype where the screens, the baby are on the screen and logic and the functionality when you click something and things like that, you actually are exposing to the user.

David: So as they're playing with it. Um, they can see that this is going to work. That's not going to work. Right. And then if they have to make a change in the design prototype, then it's cheap and easy, Right. As opposed to doing the same thing in software that's already built. Um, so, uh, we took these prototypes and built them out.

David: And what we found was by doing these really elaborate design prototypes, which take a lot longer to do. Um, I'm two and a half, three months often, uh, to do a fully, you know, because we don't just do the MVP version of, but we do the big vision, you know, the two year vision version of the prototype, because we want to make sure that the whole model holds together.

David: Um, uh, we real, then the iteration during development went down to very little, almost nothing. Because we [00:17:00] knew exactly what we're building all that iteration happened during the design this phase of the project and then I started thinking to myself, you know, why don't we take these out to potential prospects because they're so realistic.

David: You probably could get some people to buy in early and then you would know that they really want to pay for this. It's really worth it to them and also who you should be marketing this to. And I finally was able to get. Uh, a few, uh, customers, um, a few years ago to test this theory, four of them. And three, we were successful at being able to generate pre launch revenue a significant amount.

David: Um, one company, uh, uh, one company, we did three demos and we sold all three in the aerospace parts distributor world, um, for 15, 000 each we were selling lifetime licenses because, and I'll, I want to explain about the lifetime license thing here in a minute. Um, it's not always a lifetime license, but, uh, it just depends on the product and [00:18:00] the value proposition, and it's gotta be a high enough value for them to be willing to buy an early enough.

David: Um, we sold three at 15, 000 each. We saw that, and that was on three demos. That's all we did was three, all three sold. Um, we did, um, for a, um, clinical trial software, um, that we were selling a, uh, a license to for 250, 000 each. Um, it's. For the life of the clinical trial and get free implementation and in clinical trials, the big value is the implementation because that costs way more than the cost of the software.

David: Um, and we sold 2 licenses at 250, 000 each. This is all without no software. We're just demoing the prototype. Um, and the prototypes so realistic that we tell people this is just prototype first version of the software won't be out for 345 months, whatever that is, and won't have all these features in it.

David: And they don't hear that. If the prototypes realistic [00:19:00] enough, they think, oh, so they're in QA and test, not going to release all the features Right. away when we tell them it's not, this is just a prototype. It's not the real product. They don't hear it. They 

Mike: They're, they're bought in already cause they can see The

Mike: vision, right? Like they see what, yeah. Yeah. 

David: they think it's already built. So they don't question your ability to build it. Whereas if the prototypes just click through mockups, even really good ones, they'll still ask the question, well, how do I know you're going to build this? 

Rico: Right. 

David: How do I know you'll be successful building it? So you have to make it realistic enough.

David: So that question never comes up if you're doing prelaunch sales. Um, and the. Um, uh, the third one was, uh, for real estate investment, portfolio management system. And we sold 23 licenses in two months, um, generated 63, 000, 68, 000 for that. Um, and now people are saying, Yeah. but you're giving away a lifetime license.

David: You can't getting more revenue from the customer. Okay. With that one, we continued to sell and generated a lot more [00:20:00] money, um, after those first 60 days. And so we're generating. As much money as you would get from a seed investor. Um, and we're giving away in, in an immeasurable fraction of a percent of the market.

David: Whereas with a seed investor, you're getting 20, giving away 10, 15, 20 percent of your equity or more. Um, and all the work you do to find that investor and sell them and all the pitches and the pitch decks and everything you're doing, none of that goes, is going, moving you forward to build your business.

David: Thanks. Whereas everything you do with launch first is moving forward and building your business. You're building your marketing stack, you're building your sales message, you're building your outreach campaign, right? Depending on how far you take launch first. You've built your prototype and when you, and when we've proven That you got a product market fit, which I, my definition of that means that you have, um, achieved, um, uh, enough sales at a high [00:21:00] enough closing ratio that you can prove that you've got lifetime value of your customer versus over cost of acquisition is at least three to one.

David: And that way you've got that. Two X to reinvest back into the scaling and growing of your business. That's That's viable. You have a solidly viable business and can be that or more, and it could be maybe a little less than that. Sometimes, you know, it's not exactly that depending on how you calculate that lifetime value.

David: Uh, if it's a short lifetime value or really long lifetime value, but you just need that ratio. You need to know that this there's profit in this business that you is repeatable. Um, uh, in the pre launch sale and people will buy if you're offering high enough value, like in that lifetime license or whatever, and the high enough cost to them in terms of the problem you're solving.

David: And they perceive that problem to have a high enough impact to them. Those are two independent numbers that cost and that. Uh, perception impact because, uh, but if they're both high, you can get them to hear your [00:22:00] message and then you can get the, and they want to mitigate this cost. You can sell enough of these to get to, um, proof of proof of viability.

David: And if you do that, then we build it. Then we start building the product, not before. Cause I can't tell you how many founders I've watched go down the tubes, having spent hundreds of thousands or even millions of dollars, more than one founder has spent several million dollars with us to eventually fail.

David: So, uh, because of this, because they lack product market fit. 

Mike: Proof proofing at first is, is huge. Right? Like, and, and this is, this is a SAS hack really. Right? Like I, I hear this in books, like Rob Waleen has the SAS playbook or start small, stay small. And then there was another one. I think you mentioned maybe mom or something like that. Was that

Mike: you mentioned that to me? Yeah. 

David: The mom test. that one's brilliant. Yeah. It's how do you figure out what your customers truly need and what problems are really [00:23:00] struggling with? So this goes into focusing on the problem, not the software. So if you ask somebody about, what do you think about this feature? You're not going to get any, any true answer from them.

David: Typically they may love the idea and still never spend a penny on it, or they may hate the idea, but not realize that it's solving a really big problem of theirs, because whatever it is. And it's, and the book is called the mom test because assuming you have a good relationship with your mom, that's an assumption, right?

David: If you ask your mom, you can have a business idea and you go to her and you said, what do you think of this idea? Um, free pizza delivery, you know, app, and she's going to go, Oh honey, I think that's wonderful. You're so smart. I know it'll be successful. Right. So the

Rico: so handsome. 

Mike: Yeah.

David: And you're so handsome.

David: How can anybody say no to you? 

Mike: right. 

David: So the question is, how do you, how could you actually ask your mom questions about this thing you want to do and get valuable, honest answers from her, her, not [00:24:00] even realizing what the questions are, are about. Regarding. Right. And that's because you're focusing on the problem and how they struggle, what problems they have related.

David: There are other problems that you have related to that and how historically they've dealt with those problems and how much they think that problem costs them. Are there any other intangible things that impact them because of that problem on and on and on. Right. So, um, never speaking about your product or a feature.

David: Um, uh, and this is, and this is what you do. So I, I say, right. Sounders often come to me with the black robes on. They have this vision, which you want founder to have a vision, but then they have this belief system built up around the vision and that's what you don't want them to have because that's code for, I'm going to fail.

David: And so I, I work hard to get them to throw that black robe away into the fireplace, honestly, and to put on the white coat, the white coat being now they're a scientist, they're a clinician.

Mike: you're in the lab. 

Rico: They're in the lab.

David: a lab. It's a lab.[00:25:00] 

David: And they, and, and focus on the problem, love the problem, talk to your customers, uh, about their problems, not about your product and the product that you're building is just a natural, uh, way to mitigate the problem.

David: Not the thing you should be in love with, 

Mike: Yeah, 

David: in love with the problem. 

Mike: be in be in love with the problem. Absolutely. Absolutely. So, as we're winding down this 1st segment of the series, David, um, I just wanted to say, do you have maybe 1 or 2, uh, let's call it practical tips for, um, you know, business owners out there, whether it be small, medium or large, uh, regard in regards to, you AI.

Mike: And these, these could be high level things. It could be slightly low level things, you know, just maybe a couple tips. 

David: Um, so, yes, um, and I think you mentioned before we started, like, some funny stories, right? 

Mike: There you go. Yeah. Perfect.

David: yeah, right, and I actually, I've got a funny story that [00:26:00] also is kind of a, Explains a practical tip about how to talk to AI, right? Um, uh, what I try to explain to people that are not necessarily comfortable with AI is just start asking AI what you should be asking it and say, I'm trying to decide, make a decision about something, or I want to know the best way to approach something.

David: What question should I ask you about that? Start There And then that starts. Then it comes up with questions. And if the questions don't sound right to you explain to it why you don't like one or more of the questions and give it a reason. And then, uh, and you're starting a conversation just like you would with a good friend.

David: And by the way, say please and thank you 

Mike: Yes. Yes. 

Rico: Don't talk to it. Like you talked to Siri.

David: No, right. Please and thank you and explain things like it's somebody that you care to communicate really well with you will get way better answers. Um, and there's actually apparently studies now on this. Please. And thank you. So the thank you helps confirm.

David: To the [00:27:00] AI that it's getting the right going in the right direction and the police actually generates better responses. I've been doing that from the beginning just because I appreciate how well it communicates and so it just seemed natural to say please. But anyway, so we're, so we move into our new home two years ago in San Diego.

David: Um, sold our home in Scottsdale, Arizona and moved to San Diego. I know we went the wrong direction. Everybody, I've heard that a thousand times. Everybody's going the other way. Anyway. So, um, and my wife and I are standing about three months after, after chat GPT came out three or four months and I've been telling her about chat GPT anyway.

David: So she, um, uh, asked me, she says, you know, okay, let's talk about my garden. Cause she likes to do square foot gardening. She's a garden. And, um, she says, how many beds do you think I'm going to need four by four beds? You know, to grow because I want to grow all our own vegetables and, you know, that's exactly what she'll end up doing.

David: Um, and, uh, and then her sister calls right then. And so she gets on the phone and [00:28:00] she's, you know, standing 10 feet away from me talking to her sister about the move. And I'm on there asking chat GPT. Okay, we're, you know, we're in our early sixties. We have. Um, um, we have a lot of square feet in our backyard.

David: So we want to grow all our own vegetables in, uh, with raised beds. Now, how many four by four raised beds do we need to grow all our own vegetables? Considering we're not vegetarians, because at first it said, this is how many beds you would need, uh, given your climate and your location. And I said, that seems like an awful lot.

David: Um, were you assuming that we're vegetarians? And it said, yes, I was because you said all the vegetables you need. And I said, well, we're not, but we like to eat a lot of vegetables. Okay. Well, let me adjust the numbers. Right. And so, um, I think of chat GPT as a she, I don't know if that's misogynistic or not, and I apologize if it is, but, um, um, but I always think of, of, of being so helpful for some reason that makes me think of.

David: of the kind of [00:29:00] female energy. Let me put it that way. So anyway, so she responds in, um, uh, what says this is how many beds you'll need. If you don't, If you're not just vegetarian, I said, okay. So, and, and it looked about Right,

David: based on what we had already talked about. And I said, okay, what do I need to plant in each bed and considering command and planting restrictions?

David: Cause you don't want to put, I don't remember what lettuce and onions in the same bed or something like that. I'm not a gardener, but. Certain things like to grow with other things, right,

David: And some things hate to grow with other things. So, uh, it gave me, uh, uh, the planting list for all the beds. And I said, okay, what would the succession planting be, uh, be given seasons, right,

David: Cause there's three planting seasons and you can't, Again, you can't plant something in a bed that was, something else was growing in it and expect it to flourish if it didn't like the soil from that thing. So there's certain plants you want to do. So it does, it comes up with that, um, for all the beds and then I say, what [00:30:00] companion flowers should we plant in each bed?

David: And then it comes up with that and the reason you want flowers is flowers will attract away the bugs that want to eat the thing. But if you put the wrong flower, In a bed, it'll attract bugs that really liked the thing. And it go, Oh, I like, I like the cucumbers better than this flower. And then you're in trouble.

David: So it comes up with that. And then I said, okay, give me a, put all this in a table in tables by bed by season. And so it produces the whole planting plan for all our vegetables and all of these beds by season with the correct. Uh, vegetables and flowers and, you know, and what needs to be planted at what time of the year, given.

David: where we live. So she get, my wife gets off the phone right about that time. And she said, okay, where were we? And I said, what do you, tell me if this looks Right.

David: And she looks at it and she go, her mouth hangs open and she looks at me and looks back and she said, how? I said, chat GPT. Remember I've been talking about this. 

Mike: that's Great [00:31:00] 

David: that's my coaching for anybody that wants to start to figure out how to, how to, Use these tools because you build a relationship with it, right? In terms of how you perceive this, what you, when the context in which you perceive it, so that you know when to reach out to it, which is almost always. Um, 

Mike: Agreed.

David: anyway, it was that that's a funny story and, uh, and it happens to be a very useful one. 

Mike: No, that, that, that's great. I love, I love the tip and I love the story to provide context around that too. Um, so we are going to be doing, uh, another segment with you, David, coming up soon, uh, and we're going to be doing that. Folks on, um, it's really the future of AI and practical, really some, some business tips, and, uh, we're going to have David talk about his new podcast too, which, uh, which he's, he's releasing here.

Mike: Um, so, uh, with that, David, thanks for being on the, uh, on the show and Rico, you want to take us out? 

Rico: [00:32:00] Sure. Uh, thanks everybody for listening and we're looking forward to getting David back in the lab again soon and, uh, furthering our episodes. So we'll see you next time.

David: And thank you guys for the great questions. And as always the fun conversation and the tip about replet. Yeah. 

Mike: Yes, yes. Yeah, that replica. I'm so happy that, uh, that you were able to find that valuable. All right, folks, we'll see you back in the lab soon. 

Rico: What's up everybody. Welcome back to artificial antics. And in this episode, we're going to do a bit of a recap with David Hirschfeld from techies and his launch first AI company that, uh, he's been utilizing a lot of tools and things to make things. Go a lot faster. I'll start again. Mike, I screwed that up.

Mike: Yeah. 

Rico: company. What's up everybody. Welcome back to artificial antics. And I'm here with my cohost, Mike. Mike, if you want to say a quick hi, 

Mike: Hey, everyone. 

Rico: we're here with David Hirschfeld. And as you remember from our last episode, we talked about David's company [00:33:00] techies and one of his products that he offers called launch first.

Rico: Uh, David's been in tech a long time and we kind of talked about his journey into AI and some successful use cases with AI and without further ado, we'll let. David, get into the business side of what AI can do for you.

David: Uh, thanks, thanks. Great to see you guys again, Mike and Rico and, um, uh, really looking forward to the discussion today. Um, yeah, for the audience, I'll tell you a little bit about. Me and where I come from. So, um, I was in enterprise when I started in over 35 years ago in software, um, uh, for large companies.

David: I can tell Motorola, Allied Signal, Texas Instruments, and then had my own startup from in 92 and which we built and sold to a publicly traded firm in 2000. And then I ran VP of products for the company that acquired us for the next three years until I cast out again. And started techies almost 18 years ago in 2007.

David: And techies is a [00:34:00] custom software development shop. Um, and lately it's a custom AI development shop because that's all there is anymore. It seems like is the focus on AI for, for many reasons. Um, uh, one is because everybody that's coming to us has some AI requirement. Uh, if not, they're building an AI product, uh, that they want us to build.

David: Um, and also because we automate a lot of stuff internally in techies and recognize that AI is changing every aspect of software development and, uh, design and workflow automation and how we have to approach all this. So, um, um, so it's really captivated us and, and it put us in a position where we are literally reinventing ourselves almost every month.

David: Um, Uh, what, who we are, what we do, how we go about what we do and what direction we're headed, um, to try to stay ahead of this massive wave that is AI. [00:35:00] 

Rico: Definitely. And David, just for the audience, can you tell us, like, how could a small business start identifying tasks for, uh, for the automation workflows?

David: So that's a really important question and a tough one to answer because I could give you a lot of trite. responses on what you should be looking for, manual tasks, things like that. But usually in a small business, a lot of these things are part of your DNA of operating. If you're a profitable business and successful, then you get into this work, this manual workflow of doing these things on a regular basis.

David: You understand and handling all the nuances of what it takes to do these things, not even recognizing how many nuances you're handling because you've handled them so many times. So, uh, if I go when I, in the past, when I've gone through workflow automation with the client, a good example, a friend of mine that runs a really big business network and, um, we did a [00:36:00] workflow automation with him.

David: It took three months, not three months of effort, but three months of going back and forth, probably total of 30 hours or 40 hours of development effort. Uh, but three months of going back and forth with him, teasing out all the nuances, every time we'd come up with a new build and show him, he would realize that he had missed some of the requirements and certain of the cases.

David: And at the end of those three months, um, we had something that worked and this was somebody who spent seven hours every Monday getting ready for this big networking meeting, uh, every Tuesday morning. And it was, it's complex because of the way he runs his meetings and how big his network is. And, uh, Uh, that workflow automation, which he didn't even know he could automate it.

David: But I suggested he should consider doing this based on things he had told me. And he said, okay, let's do it. Uh, let's do it. It takes him now 15 minutes to do his Monday. And he's, every time we talk, he, he tells me, you know, I still use that program you wrote for me four years ago. And [00:37:00] I just, every Monday like clockwork and it's just amazing anyway.

David: So, but there was like 40 hours, maybe 50 hours of actual programming work and quite a bit of time for us to tease out all the nuances. So most, a lot of small businesses are full of these types of workflows and that's not the only workflow he's got. That's really time consuming. Uh, Um, and it rarely is right.

David: So now I'll talk a little bit about like what we're starting to do internally. Um, uh, so we have this idea of trying to document workflows that we have, that we know are repetitive in what we call playbooks, because we want to be able to scale. And if we bring in somebody new, that's going to be. Doing that thing, if it's a marketing task or sales task or development, automation task or whichever it is, we want to be able to give them the playbook for them to learn.

David: So they know what are all the steps to do and what and what are the nuances that they may run into and how to address those, [00:38:00] uh, Now what we're start, I'm starting to realize is that for any of these playbooks, we need to be thinking in terms of taking the playbook and now using AI to start to automate that playbook.

David: You know, asking and asking ai, okay, here's my playbook. Um, uh, uh, for this particular thing, um. Do you see anything that I could improve in the playbook, number one, because it may come up with things that I didn't even realize that are duplications of work, uh, just because it's something we've done so many times and are comfortable with and good with, um, and ask it if there's a way to improve it, and then, Ask it what, how can we automate these activities or should we even rethink the, how we approach this completely?

David: Right? That's the first thing is, should we rethink this? We don't want to disrupt our business, but maybe in the process of rethinking it, we can come up with some tweaks to improve what we're doing and then ask it how we, [00:39:00] um, um, how we automate. These functions or which functions can we automate and then ask it to prioritize from the ones that are the least costly to automate and can be done the quickest to the ones that would take more effort and time to automate and have it build a priority list of automation tasks, each one that we should be able to put in to activity once it's done to see a boost in productivity.

David: Uh, our ability to produce. So the idea for me is, okay, right now I have a, a virtual assistant that's helping, that's doing my marketing outreach for podcast related stuff. Right. And we, and we've got that, uh, playbook really pretty well defined now. So, but as I scale, I don't want to get more of the A's. I just want my.

David: VA to get, be basically be better at doing more of these. And we will hit a point at some point where that's a capacity is hit, but we've automated a lot. Maybe she's now able to handle five times [00:40:00] or six times or seven times the capacity she could with the automation. And we bring somebody and all of, and AI is documenting the changes in the playbook along the way.

David: Um, um, now we bring new people in and we can scale much faster, much bigger. Uh, with much less cost. So that's how I approach it internally. I don't know if there are, is a better way to do, but I think it's, I feel pretty solid that this will be hugely effective. Uh, um, and then of course, there's all kinds of tools that you can use to do different pieces of this automation, depending on the thing that you're trying to automate. But that's what I would say. If you're a business, think in terms of playbooks, what are the common things that you do on a regular basis that are manually require today, require a person to do it, and it could be a phone call, you know, and voice, it could be, um, uh, [00:41:00] sending communications of custom communications with people are responding to community communications in a very specific way and be able to document.

David: Um, the results of those, it doesn't matter what it is, document these things. Where is if your business doubled in size, how would you bring a new person in so that that person can now get up to speed very easily and quickly. And, uh, they have a way of measuring whether they're doing something correctly or not.

David: Um, and those, that's what to me, a playbook is right. Um, and when you have that, you can start to, uh, then you can talk to somebody like me or, or, um, or just ask AI how, Okay. what would I automate here or, and what can I improve in my workflow and things like that? That's how I would go about it as a small business. 

Mike: 1 thing that I'll bring up here because I had a really great meeting about it just yesterday is, um, probably about. Two months ago, um, we released some, uh, some, you know, you, you call them a playbook. Let's, you know, [00:42:00] I, I've had other people like our, our buddy, uh, Tim Shakur calls them workstations. Right.

Mike: But it's basically, Hey, you land here. This is how you do your job, right? Here's your functions. Here's your different things. And it's easy, you know, how to do it. And, and AI is checking you along the way. And then obviously you still have to understand that AI isn't perfect. Right. And it might, let's say hallucinate, but I was talking to, um, I just built a couple of tools for our GTM group.

Mike: And, um, and so we do a meeting every week cause we want to get a pulse, right? Like our use of the tools where, you know, uh, are there any challenges, right? How we can, can we refine these? Right. And I think one of the biggest thing is making sure that, uh, You don't just release the tool or release this workflow automation.

Mike: And then like, that's it, you know, we're not going to look at this. And, uh, so I said, you know, I said, Hey, so, you know, how are you guys doing with it? You know, are you having any good wins? And one of our guys, Mark was like, are you kidding me? He's like, Honestly, without this, this set of tools, I would be lost.

Mike: He's like, I [00:43:00] don't even understand how I did my job before you built these tools for us. Right. He, and so I was like, Whoa, that's like killer, you know? So he said, this 

Mike: is how I operate all day. I used, I use the tools. Right. And, uh, 

David: Yeah. It feels really good when you make that kind of impact. Right, 

Mike: Yeah. And, and, you know, he's in sales and, you know, that allows him to be on calls and talking to customers and doing the relational parts of his job instead of the transactional parts. Right. So, um, so yeah, no, that, That's great David. Um, and I, and I know you, you know, you told us even, uh, the, a couple of little bits of other stories too, right.

Mike: They, these automations folks are, um, You know, once you, once you figure them out and to David's point, and Wendy says it, Wendy, uh, Reeves says it too. Like you have to understand the process, you know, what you do, how you do that playbook manually before you automate it. right?

Mike: It has to be very well, you know, it has to be [00:44:00] efficient And

Mike: you have to have a good process for it.

Mike: Otherwise you're just making something that's inefficient faster. Right. Which doesn't really move the needle. So. 

David: right. right. Yeah. It's always, you always have to, reinvent how you do things. Sometimes if you can make it enough faster than it does move the needle, right? It may be a repetitive process that could be done better, but if you make it fast enough, that becomes invisible because it's not create, it won't create a bottleneck, um, until you scale many times beyond where you are.

David: Whereas today it might be creating a bottleneck. So, um, and, and you have to do that kind of assessment too, but some of the, Other things like there's one tool from one of my clients who's in healthcare. Um, and, uh, they have an AI nurse that is like talking to a real nurse on the phone and you can even interrupt her and, you know, and say, no, that's, that's not, that's not what I'm talking about.

David: She'll say, Oh, I'm sorry. Can you explain, um, you know, what's different about what you're talking [00:45:00] about versus what I thought it was. And then you do, and she got, Oh, okay. And I understand it's like a real conversation. And the person can even say, you know, I'm just kind of sad right now that she might, she might start, um, you know, just say, I'm sorry, you feel that way.

David: Tell me what you're, why you're sad and start kind of giving, yeah, it might be somebody who's older, who feels isolated. Right. But that's not the purpose of the tool. I'm just saying, these are some of the things, some of the side effects, the purpose of, of the tool is to basically automate really manual workflows that require somebody with specialized Nursing skills.

David: That is a tedious process, like transitioning somebody from the hospital to long term care. That's a good example. And to be able to make an infinite, not infinite, but like an unlimited number of calls for large numbers of patients at at the time that that patient really needs to call to get this transition support, right?

David: Explanation of what's going on. Um, Yeah, Um, uh, a phone number. They can call if they have questions, which would be the [00:46:00] AI nurse again. Um, um, explanation of services that they can expect. What's what, you know, giving basically and very patient and answer any questions. And there's no time gap and no additional cost that negligible cost in terms of how long the call takes, because there's not a limited number of two people doing this for hundreds of patients, right?

David: There's hundreds of calls happening in parallel, however many needs to happen and they happen just at the right time. So that's an example of a massive value for healthcare system. That's understaffed right.

David: now. Um, um, it doesn't replace nurses, but it takes the pressure off the fact that nurses can't get anywhere near as much of this done as they need to. right?

David: And this is not the part of their job. They really want to be spending their time doing 

Mike: Exactly. Yeah. Menial work, right? Yep.

David: Now, here's one that we're going to be doing. Oh, so go ahead, Rico. 

Rico: no, no, go ahead.

David: Here's one that we're planning on doing, [00:47:00] uh, based on a discussion we, I had this week with my director of operations in terms of our teams.

David: What's one of the things that every development team. Has to do every single morning and that's a stand up. Not every team, but anybody that's using any kind of modern methodology, uh, development methodology, right? You do a stand up where everybody in your immediate team is talking about what they got done yesterday, what they're planning on doing today and any dependencies that are outstanding.

David: Um, and that's all you do. But it still takes 2015 to 30 minutes. I mean, if you're really, really good at 15 minutes, right? But usually it takes 20 to 30 minutes to get through it. Something comes up, people start to discuss it and then it takes the scrum master whoever is running. It has to say, okay, we'll handle that afterwards.

David: I don't want to wonder whatever. So we're going to build an AI agent to that pulls in all this information from during confluence and, and, and identifies anything from email communications that may be relevant, pulls together and [00:48:00] does an automated scrum with a stand up with the developer Right,

David: before any scrum meeting.

David: And then, uh, and then we may eliminate them all together, or we may have a quick one minute call to say, you know, is there anything that didn't get addressed in your, um, in your, um, Meeting with Gerald, whatever we're going to call this scrum agent, right.

Mike: This is awesome, by the way, this is, I'm just, no, listen, I'm thinking about, so a couple of things, one, I personally wouldn't get rid of a daily meeting, especially in a, a distributed remote work environment, because what people like to do is that's how they get a human connection, right? But in the 

David: And that was my exactly right. 

Mike: In the same breath though, having Gerald give me a rundown so that I'm, I'm like, and, and, and I mean, That's just so fricking valuable to understand and aggregate the data from all the channels, including email and [00:49:00] teams and, you know, whatever, you know, maybe it's Slack for your company. Right. So, but aggregating all that data and really having a rundown of what WTF did I do yesterday?

Mike: Because you know what happens? People are moving, moving, moving. And they, and they may not even give themselves credit for all the stuff that they've done. Right. So having that just quickly delivered to them, I could see that being transformational and that's just fantastic. That's super cool that you guys are doing that. 

David: So one of the things I want my team to do is every day talk about how, what they're going to do, try to do today using AI to improve, you know, right. To improve what they're doing, whether it's make it better, make it faster. Um, um, uh, whatever, whatever that is. So that may be what happens in our standups.

David: And 

Mike: There you go.

David: you know, is that, and any dependencies That have to get discussed that have several people involved, right? 

Mike: exactly. That that's, that's a good purpose for them. Yes. 

David: [00:50:00] So the scrum master now is looking at the, whoever's running it, right. So looking at the result of these, of the standups and sees that there are six points that, uh, may be a problem with the people with dependencies move forward.

David: Spends five minutes on those. Gets those addressed and spends 10 minutes now taking and doing an intake on, okay, what's your AI thing today? And everybody's got to come up with something even if it's the same as yesterday. I'm gonna continue to do this Okay, what and and what value have you gotten out of it so far?

David: You know, no, no value Okay, do you think it's you're going to or is it something you should come up with a new one tomorrow? You know like that and Right. And change the whole media need for those meetings so that it's almost like having affirmations in the morning, right? And so if you have your list of things you read every day as your starting day kind of Process like I I have one somebody I met somebody recently is really successful and he was doing it [00:51:00] I thought you know, I I know this works because you just keep Sticking those, those ideas in your mind every morning, Right.

David: And, um, and you just start to make them happen unconsciously, right.

David: If you say every single day, you know, weekend, week out, no matter what day of the week it is, and there's like 20 things, right? One's for family, one's for the company, one's for finance, like that sort of thing, one's for health and one's for exercise, and there's three or four things under each one of those, and there's certain kind of format you follow, so they have.

David: Punch and impact and they're generalized enough. So why not turn our standup meeting into something like that every day about AI, but not aphorisms, but talking about planting that seed of this is what I'm going to do. And knowing I have to be doing something to 

Mike: it on their 

Mike: keeps it on their 

David: push, it. Right. 

Mike: They're accountable. They're, they're accountable 

David: to take, I want to take credit for the agent, uh, scrim agent thing, but that was my director of operations guy, 

Mike: That's, that's great. No, I, [00:52:00] I,

Rico: That's a great use,

Mike: I love that idea. And, you know, we were going to go into directly into like, um, trends for the future, but, you know, I was thinking about it and, um, one of the things we have on the agenda, David is last episode, you know, I had talked about how you had showed me bolt and I showed you repl it.

Mike: And you've, you've completely migrated to Repl. it. So a question for you, I have is how do tools like Repl. it change the game for developers and business, right? Like, and how have you seen those gains with, with the, you know, some of the tools and the features that Repl. it has, like, like their agents, right?

David: right? I mean, I

David: I'm imagining how it's going to change the game. He's starting to use replit made me realize that we really need to reinvent ourselves again, completely, because what we're doing as a developer, as developers and building apps just won't, it won't be the same thing next year, you know, in a year from now, it'll be.

David: And the ones that are still trying to do it the same and those, they're not going to go away in [00:53:00] terms of demand, but they, um, uh, but they're just going to be so pretty far behind the curve in a year if they're still, even if they're, and a lot of shops aren't even doing modern things from a methodology, methodology perspective, from a automation perspective, a dev ops, CIC, a CD, you know, um, uh, automation, automated testing.

David: I mean, all the things that are. Like the buzzwords, right. That are kind of modern shops, Right. They're not even doing all that stuff. Um, so, uh, next year, all that stuff will just happen. In this time next year, potentially. So from a predictive standpoint, just how fast things like replit are coming along.

David: Um, like for example, we need a, uh, referral partner portal because we're building this network of referral partners. Um, so we have to have a way for a referral partner to, Um, easily add a referral if they have one or, [00:54:00] or we pull it, they send me an email with the referral and, uh, the portal is watching emails and automatically creates a record for them knowing what their referral, you know, fee rate is and things like that.

David: And then that way a partner can go log into their dashboard and see, Oh, you know, I, there's eight referrals that I've given. Here's the status of each one. Two of them, actually, we've got contracts and now are accruing some, um, uh, commissions for me. And this is what's paid out, you know, over the last nine months or whatever.

David: Um, and I'm building the whole thing with Repl. it in my spare time for the last week and a half. And I've got much of the first version of this done. So what does that mean? Okay, do we do these high fidelity prototypes anymore, or do we actually build a application prototype instead? Use Repl. it to have Repl.

David: it, uh, basically have it describe the design to it and have it build out the screens and the workflows, and then [00:55:00] have it wire all that up after we're comfortable with, we think the design is good, and build it as an application and get an MVP out. In a month or three weeks or two weeks or a week, Right. And go out to the market and do some prelaunch sales with this, um, with this tool that was built by replica to prove that there's a product and now you've got something they can start using. It's, and it might even scale to a decent amount because Repl. it allows you to deploy it into a, uh, into an auto scaling server.

David: Right? that's 

Mike: Yes. It, it, it really does. I mean, you could get something that I

Mike: would say, unless you're like Twitter, it can, you know, it could scale pretty well, right? Like you'll hit the limits at some point, but to your point, you know, that partner portal probably isn't going to be getting like a ton of play, right?

Mike: Like, 

David: Well, you don't know that if 

Mike: Because I want you to get a lot of partners and a lot of partner activity. But you know what I mean? I think about the amount of 

David: Yeah. I'm just kidding. 

Mike: put in would [00:56:00] flow through that. Even if you're doing really well, it's not a ton. Right. So 

David: This might be all we need, right? But I also, then I can put a SaaS front end on it. And so my partners, if they want to use it, right, then they are paying me 20 bucks a month. And now they're using it as their own partner portal. And if you've got five people that you're referring projects to, you have one dashboard that's consolidated, right. for all of it. 

Mike: Yeah. I love 

Mike: this. I mean, I, I 

Mike: really, I love the idea. Yeah, that's 

Rico: It's a handy tool.

David: yeah, yeah, I, I, I'm still like shaking my head. We have a team meeting tomorrow where I'm basically going to show this to the team. Right. And they all laugh at me that I built it. Right. Because my development skills are a little rusty. When you start building a company, you don't get to play with, I love coding.

David: It's like my favorite thing to do. Um, uh, which is why sometimes I'll take on these hobby projects for friends of mine like that workflow [00:57:00] automation for the guy with the network. Anyway, but. I don't get to do it very often. Right. So my skills are a little rusty for any particular technology. Right. So They don't need to be that good. anymore because AI is,

Mike: They 

David: know, AI does it

Rico: Yeah, 

Mike: I will say this, you need to know how to debunk what comes out. And I know, I know you're already thinking it and you're doing it, but you know, to folks and our listeners, you need to be good enough to know what's coming out of, you know, what's coming out of it is good, bad.

Mike: Uh, what needs to be modified because you don't repel it. Is great. But the first thing I did with Ruid agents was asked it to build a Django app, which is a Python framework and, uh, with these specific things, and it built me a Flask app, which is different but similar, but different, right?

David: Yeah. right? 

Mike: you know, the, it, it worked.

Mike: But it was like, wasn't what I asked for. And if you didn't know the fundamental differences between those two frameworks, which it's, it's a massive difference, um, then, then you would never know any better. Right. You [00:58:00] just say, Oh, I got this pretty thing and yeah, it works. Look, I clicked the button. right. 

Mike: So, um, so yeah, so with, 

David: Let me qualify what I said. Yeah. Yeah. Let me quote. Yeah. Let me qualify. Like, Like, when it comes to approaches and architecture and things like that. I'm coaching my team, even my most senior guys still just that comes from experience or database design or, you know, things that. You just learn all the nuances of what can tank you, um, and what will make it really scale and be resilient and, um, um, and reduce maintenance over time because you can build on it and expand it instead of it starting to become heavier and heavier and, you know, in terms of, those kinds of architectural concepts, um, Uh, and what it means from a technical implementation perspective.

David: I understand that really well. I just don't have to remember how to write the syntax for 

Mike: Totally agree. Yeah. It's like Linux commands, right? It's like [00:59:00] Linux commands. I don't, I know what Linux can do and I know exactly what I need to Google to get my exact Linux command. Now I use chat GPT for all Linux stuff. It's so good with that man. Like you can have it with you have a pass script or whatever.

Mike: It's just so good because these are like these minute little things that we shouldn't. Be keeping in our head anyway, we should just know what can be done and what, you know, at a basic high level, what should be done. And to your point, David, thanks for clarifying, because I a hundred percent agree with you the specifics of what used to be called a code jockey, where you're just like, Oh, I type code, that's my job.

Mike: That's going away. Like, I mean, way sooner, I think that some people think, and it's really going to be about just knowing how to guide things through. And, and, and, and to your point, some of those skills of experience where it's like, Hey, what's, what could, what's good. What's likely to tank us. That's a great way to say, I mean, like, and that's something that you gain from experience.

Mike: So you're always going to want to [01:00:00] have. These, these, you know, people with experience that are, that are guiding the people that, um, you know, you're going to want to have good code reviews. Right. That's one thing, right. And even if you go to like an AI code review, which, um, we've started to do some of that, like as a first pass, right.

Mike: Which saves you time. So it's like, it's the menial work of, Hey, did this hit or not hit? These basic things, right? Oh, it didn't great. I'm not even going to look at your code review, but, but for that code to get through and actually go get pushed to production, heck Yeah,

Mike: there's going to be some scrutiny there, right.

Mike: So 

Mike: from your, from your senior architects, developers and whatnot, and, uh, and you need that. So no, that's awesome. Um, so, so thinking about that's the kind of the future, part of the future of coding, what other. Predictions of like, you know, crazy stuff. I, we had some conversations that were like, whoa. And, uh, so I wanna get your take on what other predictions you think are happening, uh, over the next couple years that are gonna be [01:01:00] directly outcomes of, of, ai.

David: Okay. So some things that are really hard to predict, um, in terms of like maybe in five years or 10 years, do we even need programs anymore? Or will ai. just assemble the workflow as it's needed real time? As you're asking it to do things and then it sees the patterns and I don't know, I'm just saying that's a possibility that I've kind of been pondering and what does that mean and how do you do something today that will have some kind of resilience and, you know, three or four years from now, it is very, very tough to, um, uh, to break or maybe be.

David: Then this is scary for all the creatives in the world right now. It's especially today with sorrow coming out Maybe we don't have movie and film and TV production anymore because AI is Generating it real time based on your real time feedback as you're watching it by you know, your your How [01:02:00] you respond and, you know, you laugh and, and it's, and it's picking that up and creating stories.

David: Um, um, um, as you're watching it and as these are not pre produced things, they're just custom designed for you. Um, that's one, 

Rico: If I could just on that, we, we, we, yeah, we did a round table while back and, uh, Mike K you remember this one, Mike, uh, he threw out, he said he can't wait, he can't wait until it gets to the point where he can sit down on the couch and say, this is what I'd like to see and give a general like storyline and the type of characters he wants to see and have AI just literally, you know, think for a moment.

Rico: And with that, Three over the release of Sora, I'm sure that'll be coming sometime in the near future, but then AI will just create the storyline, add the characters and everything, and then you're watching, you know, original content that you kind of created yourself, but you just gave it, you know, the idea of what you want to talk about or what you'd like to see.

Rico: So

David: yeah. Yeah, and then it's testing things like, did he laugh at that, not laugh at that, right? And it's monitoring you real time and it's getting to know you better and better [01:03:00] to, so that it creates a comedy that you literally can't like your stomach's falling apart

Rico: can't breathe.

David: every single note and the timing and Right, 

David: I mean, I could see this at some point. I don't know when, um, uh, I don't know if that's three years away or 30 years away. Right. I used to, but 30 years seems like everything's a closer. I used to think. What AI is doing today and four years ago, I would have said that's 15 years out, not, not four years.

David: Well, actually I would have said 15 years and it probably wouldn't have thought it was this good. So, um, here's one thing I believe is predictable, which I think you guys know, cause we talked about this, but if you're invested in, multi level parking structures or any kind of a parking structure, um, like multi level garages outside of stadiums or in an office building or underground parking lots, like under a mall or whatever, sell it today.

David: Cause in somewhere between three and seven years, [01:04:00] I don't know when that tipping point will happen, but it'll happen very quickly. There won't be any cars parked there anymore because of automated, because of, um, automate auto driving, right, Uh, uh, things like. When Tesla comes out with their auto taxi and Waymo's already out, which I've ridden in Waymo's and they're pretty frigging amazing.

David: Um, and then you've got, uh, and then the people and people stop buying cars. And the few people that they'll stop buying cars because of the, it costs a lot to own a car way more than it'll cost for you to be driven everywhere by these competitive auto driving taxis. right. Um, and there'll be so available.

David: That you'll be able to get one in a minute or two, always, because somebody in your neighborhood will probably still own a car somewhere because they're making money off this auto taxi, and there'll be a critical mass of these vehicles, um, um, available so that when you say, Hey, I'm, you know, I'm, I'm leaving now, and you finish brushing your teeth, you walk outside, it'll be [01:05:00] waiting for you already.

David: So, uh, and it's much safer. So, and it'll be much more dangerous to drive a car because it is dangerous to drive a car today. We're just used to it. But it would be much safer. So it'll only be people that can afford it. And that just really want to drive and love to drive. That'll have cars. Cause I know I, and that'll be True. 

David: or let's say you have a pickup because you like to haul stuff.

David: Right. Um, um, so you would just say, I'm, I'm. You know, get a pickup to help you haul whatever it is you're buying, that'll be the thing you get and it'll be there like almost immediately because there's an infinite number of pickups on the road and they'll all be self driving pickups. Um, there'll be some exceptions for that, I think, like for people that live in rural areas, that'll take a lot longer before this sort of thing might be available there in that kind of number.

David: Um, obviously for people that use, you know, Their vehicle for work, like construction vehicles and things like that. Now, you know, there'll be exceptions obviously. Um, uh, but [01:06:00] it's, but for the typical driver, they're going to work or going to the store or, or going to a friend's or entertainment, those, I think it'll be a massive shift.

David: I don't know what the automakers are going to do. Um, um, to, because the demand is going to shift and the need for as many car vehicles on the road is going to go dramatically down. is they'll just be so much more efficient. 

Rico: Mm hmm. 

David: So there's a 

Rico: I think. Well, uh, how do you think the adoption would be by the public? I mean, do you think that'll be like a phased approach where it'll be some people that like, that are still skeptical now? I mean, you've, you've seen AI adoption in your own business, let's say. Uh, how do you think the public at large is going to adopt that?

Rico: Or do you think people are still going to like be a little resistant to giving up their, their freedoms, their own vehicles?

David: well, I'm an early adopter, of course. So I've been in a way, Mo, um, a couple of different times in Phoenix, right? Um, uh, my wife and my mom are both saying you're crazy and I'm [01:07:00] thinking to myself, no, I, you know, you just don't really 

Rico: tired of driving. Right,

David: I, it's, it's nice. I can sit there and play chess while I'm going, you know, Going from wherever and it'll pick you up right at the airport.

David: Now, you know, in Phoenix, that was new in the last month, uh, right with all the other ride shares. It just navigates in between them. Um, and it'll drop you off there. And, uh, it now all goes all the way to my mother's place, which is way North. And it, at the moment, it's still in the city because they hadn't turned it on freeways yet, but that it's only a month away probably.

David: And then it'll get there in the same amount of time. And it's half the cost of Uber. And they don't even have any competitive pressure on them yet. So, um, uh, but once there's a critical mass to this and, uh, uh, the, I think there'll be a big wave of the, uh, public that basically starts using them because they're getting in one with a friend or, or, uh, because they're finding [01:08:00] out that everybody is taking one to work and they're the only ones driving to work.

David: And people are thinking, are you crazy? So they'll try it, realize how really incredibly cool it is. Um, I, it'll happen fast. It'll happen really, really fast. Um, uh, it'll hit a certain critical mass. Like I said, three years, seven years, somewhere in there, I think somewhere in between that range. And that's really purely guess it's not based on anything except for my experience I had with something massively disruptive like this with, um, uh, that I saw with Uber.

David: So, um, I don't know if I mentioned the story to you last time or not, but I, I used to travel to India a lot, 15 times, starting in 2010 until the first week of the pandemic. Um, uh, because I was building my teams there and people that say that they work offshore and had bad experiences is because they were throwing basically a project over the wall to some [01:09:00] team in India that they really didn't know, right?

David: Um, if you, you can't expect to have a team that works in a particular type of culture that you're trying to build if you don't get to know them personally and spend time with them, um, uh, and establish some of the basic fundamental tenants and then you build an exceptional team no matter where they are in the world.

David: Um, so that anyway, so I spent, um, uh, uh, for the first six years, I went there six or seven years. Yeah. till 2015. So I started actually in 2008, traveling there. Um, so I had to make that 17 trips. But, uh, 2010, 2015, every time I would go, land in Mumbai, and I'd take, uh, Uh, drive it have somebody pick me up because there's no way I was going to drive there, um, uh, because it's just nuts, right.

David: It's opposite the other side of the road and the, and there are,

Rico: Volume.

David: there were literally no rules and there were like in the [01:10:00] city of Pune that had five and a half, 6 million people. There were no rules. There were like five traffic lights in the whole city. So people just had to figure out how to get through intersections without dying.

David: And right. 

Mike: Mm-hmm

David: And there were stop signs. I mean, there just was no traffic control. Um, that's changed a lot since then, but this was back in 2011, 12, 13. And there was this infinite sea of tuk tuks or autos. There are these three wheel motorized rickshaws, no matter where you went. I mean, that's not, I would be picked up in a car and that there was probably 10 of those.

David: Motorized rickshaws to every car. Um, and then also there were 10 motorcycles as well. So it was like motorcycles and these three wheeled rickshaws. Then I didn't go for 15 months between 2015, 16. And I came back and I got in the car to go to Pune and I thought something is really different. I couldn't really put my finger on it.

David: Then after we were driving for a little bit, I realized I'm surrounded by cars, not tuk tuks. What happened to all the tuk tuks? And so when we got to the [01:11:00] office. And I thought it had big government regulation, nothing could possibly eliminate a millions of these vehicles and their drivers all, you know, literally overnight.

David: I got to the office. I asked her locker. She was our director of that office at the time. And I said, cause we had Chalaka's one team and Gayatri is a different team because I mentioned Gayatri earlier. Anyway. So I asked her locker, what happened to all the autos? She says, well, you know, Uber came to India about six months ago and they won't approve them. And Wow.

David: whammo, an entire class of vehicles and all the people that own those cars were literally wiped out overnight. And the people that started, and the people that started Uber, which was only six years before. weren't sitting there in their garage going, just imagine in only five or six years, we can wipe out a whole class of these vehicles in Southeast Asia, right?

David: And I mean, obviously they're not thinking like that, um, which I always say, [01:12:00] things that are truly disruptive like this are never Intended to disrupt in the ways that end up disrupting. Right. So does, uh, did, uh, Elon Musk say we're going to get rid of all these parking structures? No, of course not. But when we hit that critical mass, it's going to happen fast.

Mike: For 

David: Um, just like it did, uh, by the way, all those vehicles came back because a competitive service came out, um, uh, like a year later, I think it was called a wall or do wall or something like that, um, that was an Indian based company and they approved them. And then, of course, to compete, Uber had to approve them as well.

David: And then overnight, they're all back.

Rico: They're back. 

David: They're back. Yeah. 

Rico: That's crazy. So on the, on the business aspect, staying in the same theme, as far as adoption, you know, you had some experience now with it. What, what advice would you give to businesses to get to AI adoption, maybe amongst the employees or, or, you know, B2B, uh, relationships?

David: Um, [01:13:00] and that's probably a really good, but really hard question to answer because people, It's it's a mindset thing. So, so whatever you can do, right, whatever you can do to constantly put it in front of them and then to, Um, guide them into using it For something on a daily basis, or at least a couple times a week with everybody in your, uh, team so that it's, they start to just think about it when they're doing something.

David: Um, that's what you need to do. Uh, explore ways that it can help them in their personal life as well as in business, um, that you feel is safe. That's not going to expose your business in any negative way to things that you might like intellectual property and being, um, you know, where A. I. Is using that to train.

David: And there's lots of tools you can use and ways of protecting privacy that are that are. Pretty much like cloud is everybody uses the cloud. Now, nobody worries about it in the way [01:14:00] that they did 78 years ago, and it's like that with AI. You don't have to worry about it. As long as you take some basic precautions, have your privacy settings set properly in the tool that you're using.

David: Make sure. you understand what the privacy is. Uh, capabilities of that tool are that they're not using your data to train the model that it's, if you have a little private, uh, uh, garden wall around your data, uh, and then you use it, um, uh, and, and explore what tools are out there, uh, that you can use an intro that might be a benefit to your people on your team and that you can introduce to them a really, really good one.

David: That's probably very. That's ubiquitous in terms of how it can be applied as, as a notebook LM, which I love because it becomes your own little private AI garden 

Mike: What is it called? What 

David: notebook LM from Google, from Google. 

Mike: From 

Mike: Google. Yep. 

David: Yeah, right. And it's just a very, um, uh, low hanging fruit. It's [01:15:00] kind of product where you can upload any document, put links in there for content that you want it to learn about.

David: Uh, and then you can ask it anything about that content. And it's very specific in terms of what it's being, what it's trained on now. You know, it's a large language model informed by your specific content. Um, you can even create a discussion. About that content by just clicking a button. And now you've got two people talking and they sound like real people talking about the content you put up there, summarizing it, creating really intuitive insights.

David: about that content surfacing things you might not have realized about your content. In fact, we did it when it first came out, like in the first few days, pointed it to my website, techies dot com. And of course, we're blown away having because these two people are like having a podcast episode talking about what we do and very edgy kind of a cool conversation.

David: And they said, well, these guys have been [01:16:00] doing it for But, you know, uh, this kind of concept of launch first, and they've had this for several years. That's like dog years in tech time. I was like, you know, these are kind of nuanced, cool things that it's doing. It also was talking about some of the messaging down halfway down on our website about some of our capabilities that was not messaged properly.

David: And we didn't realize until We, heard them talk about how they perceived it. And we go back and read it and go, you know, it's exactly right. So, like, you just use it as a, like a, uh, an evaluation tool, right? Like for that, but, um, or to say, summarize all this for me and put it into a certain form so that I can present this to a customer or create a proposal for me, here's all of the parameters or, I mean, you can do anything with it, right.

David: And it just focuses on your content. So that's a good way to start to introduce it.

Rico: We, we did an experiment a while back and Mike, maybe you could remember the [01:17:00] tool that was, but where it created a, um, a script and it sounded like a man and a woman talking on a podcast and they 

Mike: it. That's, that's this. 

Mike: That's it. Nope. 

Rico: that's what it is. 

Mike: the thing. Yeah, exactly. 

Rico: And, uh, we, we had, uh, added the audio to it and they were doing the ums and ahs as they talked 

Mike: Yeah, they stop and pause and 

Mike: yeah, that's what 

Mike: got me is like, it's 

David: you didn't know, yeah, you would not know. 

Mike: Yeah. And if you 

David: Uh, by the way, 

Mike: the other a hundred people that have released podcast episodes about their notebook LM thing, because that's the one, that's the one thing I will say is I wish I could do different voices, like, like change the speakers in there.

Mike: That would be gold. and I think there's another thing that, that actually allows you to do that. So, uh, because it's so

David: there is some guy, you can guide it. Now you can guide the conversation. Yeah. They just came out with that like last week, um, where you can guide the car. I don't know about the voices yet. I think they may have that now. Uh, there was a really funny one that somebody did and [01:18:00] published, um, where basically they, um, explained to notebook LM that you're not a real person.

David: Yeah. That you're an AI. Anyway. And so then they had this two people talking and says, you know, I don't know what to do with this information that I'm not real. Well, what? And she said, what about my family? She, she says, well, yeah, I mean, you still have a family, right? I says, well, I don't know. I mean, I called my mom and there were, that number didn't exist and neither did she.

David: No, I think I'm really an ai. I don't, it was so funny. 

Rico: That's something else. 

David: funny. 

Rico: We're going to have to find that.

Mike: Yeah, we will have to find that for sure, David. And, you know, we were talking about podcasts. So like, um, and generating them. So speaking of podcasts, David, you've actually got a new podcast coming out. You want to kind of tell us like what the podcast is about, what motivated you to start it? 

David: Yeah. Sure. Yeah. Yeah. Well, I mean, I'm doing a lot of interviews now. Um, and, uh, because the world is [01:19:00] changing so fast and I think it's important that I have that people hear my voice, at least from my opinion, what I think about it as a way of branding. Techies talking about what it means to be an exceptional software company, talking about AI and how it's impacting, uh, the world and the development scene.

David: Um, um, and then I thought, you know what? I really probably ought to be in, uh, um, doing my own podcast on the same thing. So, um, uh, that my first interview is supposed to be tomorrow. Postponed it for a few days, but we're starting it, you know, it's starting literally right away and then I'll publish it as soon as we've done three interviews, so it'll be within a week, week and a half.

David: It'll be published. Um, and, uh, it's called scaling smarter, uh, with, and I'll be interviewing CEOs and CTOs kind of like you guys. So companies that are either are successful or have failed or are in startup mode, you know, right? All of those, uh, with the idea of learning what they [01:20:00] problems they've run into, how they overcame them.

David: Or what happened when they didn't overcome them and how big an impact it had on them, how AI is impacting what they're doing and, or how they're leveraging it to solve these problems. So it's going to be that kind of a podcast, you know, it'll blend between startups and startups and scale ups. 

Mike: I like the, I like that you're actually open, you know, like you're, you're going to focus on the entire sphere of, of how things can go. Right. Because, um, you know, knowing, understanding the failures, uh, is, is just as beneficial, you know, like that as understanding the successes, right. And a lot of times the failures are what ends up ultimately leading to the success.

Mike: Because you've got, you've, you've learned what things could bite you. Right. So, um, yeah, I'm super, super excited to, to catch the podcast. Is that going to be a weekly podcast, David, or is it pretty much just going to, 

David: I'd probably [01:21:00] be two or three, two or three episodes a week is what I'm shooting 

Mike: oh, wow. 

David: 10 a month roughly. And, uh, there'll be shorter in, uh, at least initially, um, um, uh, there'll be much shorter, uh, kind of episodes to really kind of focus on a microcosm of somebody's, uh, business and experience. Um, uh, and that may change, right?

David: So, uh, they may change the longer format ones more like, yours. Um, I'm, I'm using the guidance of somebody Transcribed by https: otter. ai Um, uh, that suggested try the short, the short format first to make, you know, to create more punch in the podcast initially. and we'll see if that works or not. I like talking, all Right. And I like listening to people that want to talk. So I have a feeling it'll probably expand into longer things. And the one thing I'll say though, regarding AI is just channel your inner five year old, you know, when you're thinking about it. 

Rico: That's how we started. I think

David: Yeah. Yeah. Yeah. I think I will [01:22:00] 

Mike: good at channeling and his inner five year old. I don't think he's grown past that, honestly. 

Rico: more an external five year 

Mike: why he's so good at this. That's why he's so good at this.

David: like, uh, a friend of mine told me about his granddaughter who was three years old walking, uh, and she had never seen a book cause she, her family was all digital. We're two and a half year old and they don't read to her, but they're have everything digital and iPads and all that, right. And keep her interested and engaged with.

David: learning stuff on that. She walks up to his coffee table, which is full of these magazines, and she walks up to the magazine and she starts to go like this. 

David: On the magazine and her eyebrows, I mean, she might've been two and a half and her eyebrows kind of knit together. She looked up at him and then he picked it up and flipped the pages and her eyes got huge.

David: Cause she had no idea, 

Rico: yeah.

David: She thought it was everything's digital and you slide your finger around on it to make it happen. [01:23:00] Um, so that's What I mean by channel you're in a five year old, right? You don't know what you don't know. Um, so just click on everything and try everything and don't be afraid. 

Rico: Definitely. Yeah. So, uh, when, once you come out with your first episode and you have to let us know, and we'll put it in our AI bites newsletter, we'll start, you know, kind of pushing that for you to see if we can get some, uh, traction for you early on. But, uh, is there anything else you want to add David, as we, as we wrap up here?

David: Well, yeah, I want you guys to commit to me on the air that you're gonna be that you'll let me interview you on my New podcast here in the next 

Mike: What I didn't want to impose, but I was actually going, I

Rico: I was hoping.

Mike: now. And so I'm really glad, guess what? We're all aligned. Well, we'd love to be on the show, David. And I was actually thinking, um, I have a couple of founder friends that, um, or people that have been at senior, uh, executive levels in companies that have helped grow them and they, they will have some great battle stories for you.

Mike: So, 

David: Oh, I love that. 

Mike: be. Be [01:24:00] pushing some folks your way. Uh, because I think that's such a compelling podcast. I'm, I'm super excited to listen to it and absolutely. We'd love to be guests on the show. So 

David: Thank you. I really appreciate that I figured you'd you want to be but I just thought I'd throw that out like that And you know and just Be fearless that's all I can say is be fearless and Uh, and, but that doesn't mean be, you know, blindly forward your head either, Right.

David: The one thing there was a study done, uh, there's a, a podcast on happiness called the happiness lab.

David: Uh, that's pretty well known. It's a Stanford professor that started this thing anyway, that she has an amazing story. Um, she started a course at Stanford on happiness, um, and she didn't know that it was going to, it was, she's a psychology PhD and, uh, um, and she ended up, the class had, um, uh, got full almost instantly.

David: And then she started to make it online and she ended up like 150, 200, 000 people signing up for it. [01:25:00] And so she started this podcast. So, um, and she interviews. People about what makes people happy, right? And one of the episodes was on CEOs and this idea of power of positive thinking. And it's a myth, you know, that you just keep forging ahead.

David: You keep saying something positive because all these really successful CEOs. When you ask them why they were successful, they say, Well, I was just the right place at the right time. And, you know, we're lucky and we had good vision, but you scratch the surface just a little bit. And it turns out these are very anxious people who are afraid of everything's going to come and tank their business.

David: And they just imagine all these ways of failing, and then they work out mitigation strategies. If this happens, if that happens, it's so they're like brilliant mitigation planners and by doing that, no matter what happens, they had a mitigation strategy for it, right? So to them, it's like, well, we were lucky it all worked out.

Rico: Well, once it's going good,

Mike: that's, that's great. No, that's great. And I'm thinking about the people that I know that I'm really close to that are [01:26:00] founders. And they are exactly like that, right? Like, like, you know, something that five years, let's say five, six, seven years ago, when I wasn't in a, in an executive level at a company and I thought, Oh gosh, this one thing happened and what are we going to do?

Mike: And then I talked to the CEO and he was, he was like really on phased by, he's like, yeah, And we're already thinking about, and, and, and, and, you know, five years later, he was spot on and you know, everything is fine. You're going to have bumps in the road. Uh, but there, there's that healthy fear, you know, to your point, David, and they teach you that in the military too, right.

Mike: In different situations, it's like a healthy fear so that, you know, you have enough to understand that there could be a serious problem and that you figure out ways around that, right. Like I was, 

Mike: um, you know. I forgot, I forgot which book it was. I was reading. They were talking about the most successful people, um, you know, in, in a job are the people who are looking [01:27:00] forward and trying to like, like figure out like what could happen.

Mike: Like let's say a truck driver, right? Like a big semi-truck driver. He's looking forward and like play it a game. Like, oh, if that car moved right over here, I would do this. Right? And, you know, and, and, and I've taken that to heart and so I do that in my life. It's like what could happen? How would I adjust?

Mike: Right? And so that's exactly how entrepreneurs function. Like, you know, naturally, I think so. 

David: right. Yeah, In fact, that's funny that you mentioned the truck driver. Cause I remember, um, this, everybody talked about being a defensive driver and I just naturally kind of did that from the time I was young, like when it was raining, um, uh, heavy rain, I was, and I was 16 or 17. It was fun, but I also, for me, it was also just learning how to control my car in the rain.

David: I go to big giant parking lots that were completely empty at night and just, Do donuts and spin my car out and learn how to, and I [01:28:00] can't tell you how many times that has saved me from being in an accident or, or when I'm getting on the, I'm getting on the freeway ramp and I see there's somebody in the French road and they're literally parallel with me.

David: I think I better slow down. What happens? And then I've had that. I was with my wife one day and I slowed down and the guy just cut right. over. Right. They didn't have their blinker on. They didn't look for me. If I was there, it would have been, she said, how did you know they were going to do that? I said, I had no idea, but I knew if he tried that he had no place to go and we'd be in an accident.

David: So I just slowed down just to take the risk out and right. So it's like that running a business. If you run it, well, 

Mike: If you run it, well, yep. All right, David. Well, thanks so much for joining us. Great to have you on the show for this second segment. Uh, Rico, this was.

Mike: fantastic. Um, you know, uh, we're definitely gonna have to get back together and, uh, you know, like you said, uh, we'll come on your show and, uh, we should do another.

Mike: There's, there's so much to talk about, right? There's always so much talk about, and in three months, our strategy of [01:29:00] development is going to be probably even different than it is today. So, uh, folks. 

Mike: Yeah. 

Mike: it's dramatically different. Exactly. So folks, thanks for watching. Don't forget to like and subscribe if you're liking the content and we'll See you back in the lab soon.

Rico: See you everybody. 

David: Thank you guys. Great conversation. 

Rico: Thanks, David.

Natasha: Thanks for joining us. Don't forget to like, subscribe, and let us know your thoughts in the comments. Stay connected with us on Twitter, Instagram, and LinkedIn for all the latest updates. And check out antics. tv or our YouTube channel at Artificial Antics. We'll see you back in the lab soon. We want to give a huge shout out to Nick and the team at Nomad Studios for mastering the Artificial Antics podcasts.

Natasha: Want to level up your audio visual game? www. nomadstudios. pro


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Mike

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Rico

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