Tech Titans: Navigating the Digital Transformation w/ Gregg Carman

In this episode of The Human Code, host Don Finley engages with tech innovator Greg Carman in a wide-ranging discussion that explores the intersection of technology, leadership, and personal growth. Carman shares his journey from a developer to an entrepreneur with multiple successful exits, emphasizing the importance of continuous learning, recognizing one’s strengths, and surrounding oneself with expert collaborators. The conversation delves into the transformative impact of AI on businesses and personal lives, predicting significant advancements in AI's pragmatic applications in decision-making and efficiency by 2024. Carman and Finley discuss the evolution of startup fundraising, the changing job market due to AI advancements, and the potential for AI to democratize data analysis for businesses of all sizes. This episode offers insightful perspectives on leveraging technology for human and business betterment while highlighting the indispensable role of human ingenuity in navigating the future tech landscape.

00:00 Welcome to The Human Code: Unveiling the Intersection of Tech and Humanity 

00:50 Introducing Greg Carman: A Tech Visionary's Journey 

01:26 The Evolution of a Tech Entrepreneur: From Developer to CEO 

04:07 Embracing Challenges and the Power of Continuous Learning 

06:04 The Transformative Impact of AI on Business and Personal Growth 

09:39 Predicting the Future: The Expanding Role of AI in 2024 and Beyond 

27:14 The Philosophy of Startup Funding and the Future of Work 

32:50 Wrapping Up: Insights on AI's Role in Shaping the Future

Sponsored by FINdustries
Hosted by Don Finley

Transcript

Don Finley: 0:00

Welcome to The Human Code, the podcast where technology meets humanity, and the future is shaped by the leaders and innovators of today. I'm your host, Don Finley, inviting you on a journey through the fascinating world of tech, leadership, and personal growth. Here, we delve into the stories of visionary minds who are not only driving technological advancement, but also embodying the personal journeys and insights that inspire us all. Each episode, we explore the intersections where human ingenuity meets the cutting edge of technology, unpacking the experiences, challenges, and triumphs that define our era. So, whether you're a tech enthusiast, an inspiring entrepreneur, or simply curious about the human narratives behind the digital revolution, you're in the right place. Welcome to The Human Code. I have with me, Greg Carman. The man is a legend. Just going off of his bio, he has seven exits. He's focused on V. E. P. E. growth. The man has a new startup as well that is leveraging A. I. that will help to bridge the gap between taking actionable actionable results and insights from the information that already exists in your business. Greg, I know that I'm not giving anything that you've done any justice. So I'm just going to open it up and ask you like, how did you get to be the person that you are today?

Gregg Carman: 1:24

Thanks, Don. It's nice to be here. I think like a lot of us, there are, I've been in technology for 30 years. And I think there's often this view that there's a straight line, it was, Early success, continued success. And you just go and that certainly isn't my journey. There are the highest of highs, the lowest of lows, an average trend up, but it's a journey that you're on. It started 30 years ago as a developer. We were working on some really cool technology at the time, but you think about it, it was rather basic. We were migrating data and systems from mainframes to server based systems. And we were creating graphical user interfaces that were otherwise being done on green screen terminals. So it was a real breakthrough in technology. And from there, I was okay at it, but from there I started dabbling in a little bit of sales work. I was involved in a startup. I was like employee number 126, but I was also, in my early 20s, but they needed help with sales and that sort of became my calling and I had a really successful early career in enterprise sales, was fortunate enough to, you Have some people who believed in me and promoted me into enterprise sales in my mid late twenties, when all my peers were in their forties and fifties and sixties and I had a lot of success there. And then I had the opportunity for about. 17 years to work with a core group of people at a variety of different businesses, but these are real luminaries and innovators in the world of tech. And they taught me a lot of what to do and a lot of what to avoid. And and I was blessed with that experience. And then over the last 10 years, I've, I found myself in key leadership roles, go to market leadership roles in early stage businesses. And how I got here is, there, there were seven good exits, couple failure, couple, complete failures and a couple middlings that just never really took off, but still exist. And I decided that it was time to actually, be the founder and the CEO and to actually be responsible for the opportunity, the vision, the culture, and the overall direction of the company. So that's how I got here. 30 years is a heck of a long time. And, I hope I have, another couple of decades to go by, impacting this industry.

Don Finley: 3:51

I hope you do as well. Now, making that transition from developer to enterprise sales and now to CEO as well. And I appreciate that you brought up not just the success, but the failures in this latest revision. And then this world that we have today, what has been refreshing? What has been a challenge for you? Where have you grown?

Gregg Carman: 4:15

I think what's refreshing is your, the ability for To start from being a lay person in a particular subject or capability to being a skilled person. The tools that are available out there to to find the subject matter, to find the content, to become capable and eventually, a novice and then an expert in it. The tools are just out there. So much better than they were 10 years ago and certainly better than they were 30 years ago. 30 years ago, we were still going to the library to actually do a lot of research. The actual library. It's amazing. Um, the thing I learned though, is you have to constant, you have to have an innate interest in learning. You just do. You may not have it right now in your career, but at some point, you may. You must possess it. All right. You must possess that innate interest in learning more about the profession that you're in. And the other thing is trying to understand some pattern recognition in what am I good at a macro level, a real high level, and how does that relate to specific job functions? And is there a path? For me to apply what I'm really good at to those specific job functions. And the last, most important thing is surrounding yourself with people that believe in you, but also are experts in their field. People that are better, stronger, faster, smarter. Then you, and if you can accomplish that, at least in my experience, then you're going to be able to get through this journey.

Don Finley: 5:54

I really do like the continued learning that you talked about. I think it's one of those skill sets that I can also say has helped me in my career. A lot of people we talk to as well. Do you see that this is with really the explosion of AI and AI's explosion has been going on for 10 plus years now, but really in the last like year and a half, people are starting to see that usability impacts on a more personal level. Do you see the skill sets needing to change? Along with that, or is it more just you're going to end up learning a lot more, a lot faster, or it's going to be a, actually, I'm just going to turn it over to

Gregg Carman: 6:33

I subscribe to the idea, don't know if it's right or wrong, but this is the notion I subscribe to that AI for most of us in most businesses, in combination with human cognitive ability, Will result in better, faster, stronger, will result in less risk being taken, more reliable outcomes could be for your personal life, could be for your professional life, could be for the company's direction. So with that in mind, that in combination with our cognitive abilities I think that AI is. Bigger than, but of the same magnitude as the breakthrough of the Mosaic browser in 1994 from the University of Illinois. I really do. It's of that level. It's, and the reason is because it's ability to be a part of everything to make us more productive, more efficient. More accurate, more effective is pretty much evident to me and to a lot of the people that I surround myself with. But I think that means that we have to become well versed in how we can apply it to our business, to our life. And that's where we, one set of education. But the other thing that I've learned along the way, and it goes with all these setbacks in career, ups and downs that come with career. And that is, it's. Expertise comes with the combination of repetitions and time. And early in my career, I didn't respect the importance of the time dimension. And I believe every type A energetic professional in the first decade of their career falls victim to that. But you. have to have the repetitions and the time in order to develop the expertise and that expertise coupled with AI. results in a very good combination.

Don Finley: 8:30

I can completely buy into that. And along the lines of the way that I teach my team now is for our developers, we all have coding assistants, right? That AI is more like your, it's your partner, but it's more along the lines of like your intern. And so you're going to give it tasks. That sit along the lines of I need to stub out this code. Go ahead and take care of it. But you're always giving that cognitive review. of that work. Whereas like for me personally, marketing hasn't been one of my strong suits. And so when I'm working with an LLM and asking questions like let's say perplexity AI, I'm looking for it more to guide the discussion and take more of a leadership role. Where I can help to fill in the gaps and then also add contextual information to whatever we're working on. But it is that partnership that you're going after in which it's not just the delegation or, push it aside, but the real lift that we've seen from creativity and also from even productivity has been that collaborative approach to both sides. What do you, I think 2023 was really the year of the LLM. What do you see 2024 shaping out to be?

Gregg Carman: 9:48

I think 2024 becomes one of the first mass adoptions of the combination of these LLMs with pragmatic day to day capabilities in businesses and in our personal consumer lifestyles. So going beyond just help us write a better email or help us write a better article or help us write a better piece of code, but actually getting into better decision making, better next course of action, better risk mitigation behavior. And I think that's really where we're headed. Imagine if we go from this capability that, that we've seen, help us write better code, better articles, better emails and we translate that into, better decision making at a small, medium sized business, that the business using large language models can scour all of its data analytics capabilities. All of its insights, usually to the tune of about 1300 recommendations a month. It's insane. And then to be able to like, identify precisely, here are the areas that you can take action on next. Because the large language models went through all of it and recognize the best patterns for you that matched your business circumstances. And now you can spend less money and incur lower risk to try to get the outcomes you're achieving. I think that's what 2024, we'll start to see the first big breakthroughs in that. It'll be that ability to apply it to a pragmatic, scenario that results in better outcomes. And again, you can translate that into diet and weight loss in your personal life. You can translate that to travel and itinerary in your personal life. The same thing, massive large language models applied to pragmatic scenarios. Resulting in better outcomes

Don Finley: 11:45

I love that. And also you are taking a rather not, I don't want to call it completely unique, but there is a very unique approach that you're looking at to really agenic solutions. And it's about the reasoning and the logic that can come about from a tool that can look at, something that is 1300 recommendations and help you decide what are the three that I can implement today or implement in the

Gregg Carman: 12:11

based on my actual circumstances. So look at, you look at all of the the analytical insights juxtaposed with all of your current circumstances, and then help me recognize the patterns, just a few things. Cause our mind, can accept a handful of patterns at once to make choices from. And, the advances in AI and large language models, I think give us the opportunity to real pragmatic applications to that. You can apply that into, shop floor automation for industry, what is the next best. course of manufactured products that we should run based on the circumstances of our supply chain and our business and in the demand, and again, this is happening at the largest enterprises in the world today, because they have the resources to apply to it and curated bespoke solutions, but to then bring that to the masses on a consumer level and the masses on a small mid market level to level that playing field. I think that's what 2024 has to offer. I think 2025 and 2026 will see massive breakthroughs in that capability. I think you're going to see a hockey stick approach to it in terms of, we'll look back when the clock strikes midnight on January 1st, 2026, we'll look back and say, can you imagine that? It's going to go back to the days of, can you imagine 25 years ago, how We used to wait in line at the airport with our calling card from MCI WorldCom, waiting for our turn to spend 20 minutes on the phone, listening to voicemail and replying. That was it. Can you imagine 25 years ago when we would connect to a 14. 4 dial up modem at a hotel? Start our Lotus Notes to download all of our emails, leave for three hours for dinner, come back hoping that download was done so that we could respond to everything, and then spend three hours uploading when we were falling asleep. Hey we couldn't imagine. I think

Don Finley: 14:07

We did this.

Gregg Carman: 14:07

is what we did. And I believe January 1st, 2026, or sometime sooner, we will look back and say, Hey, that's crazy how we used to do it. It's crazy.

Don Finley: 14:18

And it's one of those, we're of a generation that, we grew up without a phone, right? Like we didn't have tablets. We really only, there was a couple of things on TV. You were recording it live if you were doing anything else. And if you missed it, you

Gregg Carman: 14:32

you missed it.

Don Finley: 14:33

Catching up from somebody else. Yeah, exactly. You missed it. I agree with you. We're in one of those transitionary moments. All right. Thanks. That is going to forever change how we interact with devices and how we actually move forward. You look at what the team at Rabbit is doing and then countless other startups are looking at how you actually interface with the device on a regular basis to give you that extra set of Eyes and ears. And really what you're talking about is from a business component, being able to do the same. And like a business has different senses than an individual person, but they're still there.

Gregg Carman: 15:09

I think what's so exciting is I think we're going to start to turn a corner. And then all of a sudden it'll be there where we will start to be able to ask systems versus just store information in systems. And I, right now we're still at that point where we store information in systems and we automate processes and systems, but to actually seek. Advice from a system using natural language. I think that's that corner we're starting to turn. And then we'll look back and say, can you imagine that? We just used to use, our computer to store information. Can you imagine that? It was just a file repository. Really? Really?

Don Finley: 15:52

that is the impressive thing. I think we are moving forward towards that world that you're describing. And as we look at it from you're creating 10 years ago, and we're still talking about today, the value of data, right? Data being the oil of the business. And we talked to, a few companies every week that they're still at that point where they're just collecting data. They're not turning it into information that they can take action on, but they see the value in gathering the information, but they don't have the resources to go through and find out what's valuable in it. Larger corporations can take the time to take data, turn it into information that then turns into, knowledge and wisdom throughout the organization. But that smaller organization usually is either running too fast on a growth curve. To really take advantage of it or doesn't have the resources necessary to make those decisions. And we're hopefully seeing the democratization of that as well.

Gregg Carman: 16:50

Yeah. I think you're right. I really do. It's where we're headed.

Don Finley: 16:54

Yeah. So we got to share a path that we're going down. I know that you've got some exciting things that you're working on in, and it sounds like that's going to bring us towards that future as well. Where do you see, what excites you about your opportunities ahead of you? And yeah, let's start there.

Gregg Carman: 17:13

What excites me is I think the ability for technology to have a Impact on our client businesses. And I, when I think about clients, I think about businesses. That's just where I've spent my 30 year career is in a business to business setting. But I think our ability to have recurring impact that is more intuitively linked to our technology without debate, I think is where I get most excited. So for example, Over the last, many decades, when when you deliver a solution for a client and they use your product for years there's always this sort of the vendor. We think we, we have a certain amount of value attributed to our product. The client thinks it's something different and various people within the client thinks it's various different levels, but I think that our ability. Either through causation or correlation, either way, I think our ability to actually have a transparent. Linkage that's part of the product use journey about the actual impact that's being made. I think is going to become more and more a part of the products and will become less and less of a debate. So we're, we can all see that. If you were to remove a certain decision making apparatus, from your technology stack that you are going to no longer have visibility to certain levels of impact that have come as a direct result of that, because it's a direct result because you've been making, you've been selecting those choices and you've been tracking their outcomes and monitoring the performance over time. Think it's that sort of thing that I get really excited about. Cause if we can stop. Debating the impact and start to focus with in client interactions, start to focus on what is necessary to be present in your technology, your solution offering for a client to get maximum recurring impact. We can spend more time on that and less time on debating on what's been the historical impact. I think that everybody's going to be better served. I think the client's going to be better served. I think the vendor's going to be better served. I think the overall macroeconomics of the marketplace will be better served because we'll be elevating the capabilities and the impact of the product. And then, oh, by the way, if you really want to go one layer above that, overall GDP of industries and countries will be better served because we're going to be driving greater productivity at less expense with less risk incurred. In other words, more reliable outcomes.

Don Finley: 19:43

That's a really solid place to go because if you think about if I implement a new CRM, I'm likely going to get like a 15 percent bump in sales, just making those numbers, but and it really comes about setting up the processes, setting up the workflow, getting things moving in a way that creates more repeatability in the business. But that's a very linear type of growth, right? Like I'm not seeing 15 percent year over year growth just based on that technology. The technology you're talking about and the integration of AI logic and reasoning. capabilities into this, not only allow you to get that initial 15%, but then to also identify the areas where you can get an additional 10%, an additional 15 percent as well. And that's a really exciting thing because you are, like you're saying, you're going to see this rise through as far as what businesses are doing and let's take it back to the country and GDP level. You can now attribute that growth directly to the productive machine that is helping to make those decisions. What do you think the world looks like when let's say 30 percent of our GDP is generated by

Gregg Carman: 20:55

I'm sure for many big thinkers in technology, they're going to give you an answer. I'm going to, I'm not there, I'm going to oversimplify and trivialize it. I think that just like with the advent of the browser and. What we now know as e commerce and cloud based computing, I think we will see greater productivity gains. I think we will see a change in academic study and skills. that become more in need than you might have seen before. So if you press rewind 30 years ago, what was really important to come out of college if you wanted to get into a programming environment was learn how to learn and or Learn a specific coding language. And then when you got into industry, if you knew how to learn something new, and if you had the basics of programming, they would teach you COBOL or something like that. All right, COBOL, or if you're an engineer in Fortran, but then today, as a result of the browser as a result of e commerce and cloud based computing, data science, data analytics, AI machine learning skills coming out of undergraduate and graduate programs have become prevalent. So I think the future looks like we're probably going to be scaling in other areas that we can't, I can't entirely predict. There are others that can do that. And I think we're going to see productivity gains. And I think that organizations that are adopting a hybrid or a combination of use of this collection of AI, large language models, machine learning, generative, that whole thing with supercomputing capabilities in the background, those organizations that are taking advantage of that are probably going to be the most profitable, most successful, most rewarding places to work, just like we saw a 25 years ago with the advent of the mosaic browser.

Don Finley: 22:57

I love bringing it back to that because there, it is. It's an odd memory of remembering the first time that I was using the Mosaic browser. And it was something that felt incredibly powerful, but also at the same time rather mundane in its original use. Yet you felt all of the internet was there available for you.

Gregg Carman: 23:21

Yeah,

Don Finley: 23:21

and find and whatever information could possibly be out there will soon be, within a finger's

Gregg Carman: 23:27

And there were just, there were few, there were a few people in select organizations who became more skilled at creating internet based experience, browser based experience than others. And there were a few companies like Netscape who really broke through with some capabilities. To help businesses and small businesses alike to be able to take advantage of it. But I think now because of all these other infrastructure capabilities, we have our ability to rapidly get broader adoption and skill capabilities, I think are going to be there. I think we're gonna be, on full display, but I think you still can't avoid the fact that it's gonna be more mundane, like you said at first. A lot of error prone capabilities at first. We're gonna talk in a certain vernacular that is quickly gonna be become acronym based and it's gonna become like just. More readily accepted and adopted by the masses, but it takes time. It's going to be, it's going to take time, but I do think that the curve will look differently because of all the other infrastructure that we have in place that we didn't have in place in 1994. We were still going to the library in 1994.

Don Finley: 24:40

which is amazing. Like I, I started programming probably around 12, 13 sometime. Yeah. Like you pick this stuff up and I tell a story, one of my CTOs, she actually, I've known her for 10 years now in person, but she, We, she's had an impact on my career for the last 30 years because she wrote the technical manuals for Microsoft Visual Studio 1. 0. And that was one of my like first major IDEs that I got. And at the time that was on floppy disks, right? So you got to get a big box. It has about a thousand, 1500 pages of documentation that physically

Gregg Carman: 25:25

Somebody had to write that documentation. Somebody had to edit and approve that documentation too.

Don Finley: 25:30

exactly. All of that work that goes to end. It has to be done right the first time. We get away with publishing something on the internet and then going back and making updates and seeing how people go, but that process was like, you're going to print this out. It's got to be part of the packaging. It's got to be done before then. And it has to match up with what it was actually

Gregg Carman: 25:50

And you had to have the manufacturing in place to be able to copy the Box the disc, make sure it's, yeah.

Don Finley: 25:59

Which, one of the examples that I give is like in, in the 1980s and 90s, in order for me to generate 10 million in revenue, I likely needed a team of 50 Mid 2000s to the 10s I could get away with three or four, right? Most outsourced service, cloud providers, service platforms, the, thankfully the Mosaic browser led the path. We can do three or four people and build a 10 million business. We're now in the realms of who's going to build the first 1 business.

Gregg Carman: 26:31

Yeah.

Don Finley: 26:32

And I think that we're seeing some of that where AI can take a lead or AI can take, the production side of it, but the skillset of combining this and working with it, like whether it's a collaborator, a partner, or helping you with strategy and more of a manager of the business. That's coming together. And so I'm excited to see how people tie all of this frameworks into one little beast.

Gregg Carman: 26:58

It's interesting. You talk about, the one person billion dollar business, I think, I think you're right. The ability to have fewer people to get there is. Is going to be like a, it's going to be a couple of milestone breakthroughs that we're going to report on. I also think though that in many ways we've lost sight of how you can survive and thrive in an early stage business without having to raise so much money. There's like this, there's this sadistic, almost perverted way that we've contorted ourselves lately. I remember, 28 years ago it was the first time I got visibility into how you'd fundraise and, you'd fundraise and you raise a million dollars, and you would build your pro your initial product, your first couple of customers, and then you'd raise five or 6 million. And then. You would probably never raise again until you went IPO when you had a 20 to 35 million dollar run rate, which to translate for those of us that don't know what that means, that meant that you had a quarter, where you did at least five million in the quarter. And because of the way that we delivered stuff, we would recognize all the revenue and whatever shipped out the door by the end of that quarter. It wasn't recognized over time. It was recognized then. And, uh, but we figured out a way to do it and we didn't have all this infrastructure. We had to buy all the infrastructure with all that with The six or 7 million that we raised in total capital. And it's not like we were driving profitable businesses. Sometimes we were, but mostly not. But at the end of the day, it was still about This frugality this sort of scarcity, we have limited resources versus get as much money as you can. Let's raise a pre seed and then a seed and then an A and then a B and then a B 2 and then a C and then a C 2 and a C 3. And oh, by the way, let's raise a D. People are raising F funds, and you just say, wow, but there's a reason why we've adopted that mentality. I just think that we've lost sight. There's another way to do it that wasn't totally flawed,

Don Finley: 29:09

I have some very strong opinions in this matter, but I completely agree with you that raising funds for startups has separated itself from the actual like economics of the business. And that's been happening for a

Gregg Carman: 29:23

like a 20 year trend. And I think we finally

Don Finley: 29:26

Yeah,

Gregg Carman: 29:27

That crucible moment of. It failed for both sides of the transaction.

Don Finley: 29:32

exactly. Exactly. And I think what you're getting at is as we're looking at these smaller teams, That we need to be taking a look at what is that capital need that can be necessary to actually grow, scale this business? And then on the other side, I think it's also incredibly important for the individuals that are involved to feel that their purpose is aligned with that

Gregg Carman: 29:56

Right.

Don Finley: 29:56

And as we continue to go through this edgy, the educational phases of AI is common, it's eliminated this job, and there's going to be an additional training that person needs. Having an understanding in the workforce that like people are going to, Not just job hop, but really career hop

Gregg Carman: 30:14

Yeah.

Don Finley: 30:15

on a regular basis to be, delivering something that is either of their heart's desire, but really what the market is needing at this moment. And that's going to be a really cool transition to be a part of. Now you have variety in what you can do. I would imagine stints. in locations or like the building of businesses can be happening at a much greater clip. Those productivity gains that you were talking about as well as if I had a software tool, I had to go learn that software tool before. And even today we were playing around, I was playing around with Adobe Premiere. I had to learn that tool. Whereas we're now going to get into the realm of the tool learning how to work with us.

Gregg Carman: 31:00

Yeah.

Don Finley: 31:01

And that can

Gregg Carman: 31:01

No, I think you're right. And this idea that some jobs are going to become less prevalent. But other jobs are going to become more prevalent, and jobs we haven't conjured up yet are going to become more prevalent. 20 years ago, we weren't trying to figure out who was going to be our data scientist, at least I don't recall having those conversations 20 years ago. And gosh, it Eight years ago, it became the hottest job in the market. Hottest job, couldn't find enough people, needed more people coming out of university that were skilled in it. So I think that we're going to see that, but I also think that means we can in some ways be more capital efficient right now with some of the gains you can get by being able to get broad based. High quality coding frameworks with fewer developers having to develop those and then having, humans, interact and review the code and quality of the code and, compile it and deploy it. I think things like that, you can translate that into sales. You can translate that into marketing. You can translate that into legal and finance. I'm not sure that there are many departments in a tech company that are going to be absent some sort of impact.

Don Finley: 32:11

No. And I think one thing I love about being in this industry is being surprised on a regular basis. If you were to ask me which jobs were getting automated two years ago, I probably would have steered towards blue collar. And I was definitely heavy on self driving cars being the biggest impact that we would see in the next couple of years. And then you see how LLMs Just the emerging qualities that came about as they got bigger, like we're now seeing that everybody is on the chopping block isn't the right

Gregg Carman: 32:43

Being impacted.

Don Finley: 32:44

job, yeah, is going to be impacted. Okay, perfect. Greg, I absolutely love speaking with you today.

Gregg Carman: 32:52

It's been a

Don Finley: 32:52

have a very solid thought process. about how you're looking at this and like, where it could be impacted and applied today as well as where it's going. And that's very healthy to see in this world of which we can always talk about the pie in the sky, but like, how do we get there? Like, where's the actual first step? And I really feel that you've connected that for me and also for the audience today is. If anybody has any questions for you, is there a place for them to reach out to

Gregg Carman: 33:18

absolutely, I'm on LinkedIn. People can also reach out to me at my email address at any time at my company chief site. So Greg, with two gs@chiefsite.ai and that's chief as in, chief Officer and Site sig HT ai.

Don Finley: 33:36

I love that. That's a great name for the company and what you're doing at Chiefsight. Everybody go and check it out, chiefsight. ai. And as we wrap things up again, Greg, thank

Gregg Carman: 33:46

Thank you, Don. I really appreciate it. Thanks for inviting me.

Don Finley: 33:49

Not a problem. Thank you for tuning into The Human Code, sponsored by FINdustries, where we harness AI to elevate your business. By improving operational efficiency and accelerating growth, we turn opportunities into reality. Let FINdustries be your guide to AI mastery, making success inevitable. Explore how at FINdustries. co.