
BIZ/DEV
David Baxter has over fifteen years of experience in designing, building, and advising startups and businesses, drawing crucial insights from interactions with leaders across the greater Raleigh area. His deep passion, knowledge, and uncompromising honesty have been instrumental in launching numerous companies. In the podcast BIZ/DEV, David, along with Gary Voigt, an award-winning Creative Director, explore current tech trends and their influence on startups, entrepreneurship, software development, and culture, integrating perspectives gained from local business leaders to enrich their discussions.
BIZ/DEV
The Zen Lens w/ Brian Moynihan | Ep. 185
What if AI didn’t just automate tasks—but actually helped you breathe again?
Brian Moynihan, Founder and CEO of Dreamspace AI Solutions and published author, joins David and Gary to break down how real companies are enabling, enacting, and harmonizing AI into their workflows.
This episode goes beyond the hype—into practical frameworks, the future of the workforce, and where AI will cut the noise so humans can focus on what matters.
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David Baxter has been designing, building, and advising startups and businesses for over ten years. His passion, knowledge, and brutal honesty have helped dozens of companies get their start.
In Biz/Dev, David and award-winning Creative Director Gary Voigt talk about current events and how they affect the world of startups, entrepreneurship, software development, and culture.
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[00:00:00] David: Tell me, I wonder there's a lot of people who say they're an AI consultant or AI strategist or whatever, and I'm always dubious, so I want you to prove me wrong,
'cause I like being wrong sometimes, unless it's Gary. I always think that the, how could you be, this stuff's so new. Are you just trying to cash in on the hot terms of today?
[00:00:22] David: Hi everyone. Welcome to the Biz Dev Podcast, the podcast about developing your business. I'm David Baxter, your host, joined Per Usual by Gary Voight. What's up man?
[00:00:32] Gary: how are you?
[00:00:33] David: I am good. I'm good. Ready for another exciting edition. We ready? You
ready to be excited? I can't really contain myself.
We are joined today by Brian Moynihan, who is an AI strategist and the CEO of Dreamspace AI Solutions. Welcome Brian. How you doing?
[00:00:52] Brian: I am doing well. Nice to be talking with you both.
[00:00:55] David: So ai, I mean it's, it's a buzzword,
[00:00:58] Gary: I've heard of I'm just, it's
It means Adobe Illustrator.
[00:01:03] David: that's
Right.
Yes. tell me, I wonder there's a lot of people who say they're an AI consultant or AI strategist or whatever, and I'm always dubious, so I want you to prove me wrong,
'cause I like being wrong sometimes, unless it's Gary. I always think that the, how could you be, this stuff's so new. Are you just trying to cash in on the hot terms of today?
[00:01:24] Brian: I don't like to misrepresent myself in any way. My background is, I have a master's degree. Actually. I have a background in MBA in strategy from UNC Chapel Hill, one of the great business schools as well as a master's in information science, also from UNC. And my third degree is in Zen Buddhism.
So that, those are the things I can, speak to with some expertise. Business with a strategy lens information science with an emerging tech lens. And in the human side of things with a little zen lens. And from that, I've been interested in emerging technology for a long time. That had to do with first I was, going beyond. Apps and databases and web applications mobile. I was really interested in digital health and how we could use applications and especially wearable devices to improve people's health. So I did that for a number of years at UNC Chapel Hill. Was thinking about the research component of it, the clinical side and consulting on there.
Thinking about it in teaching and learning. And from there my interest grew into virtual reality and I have grew a number of groups on Bo in the Raleigh area both of which grew to over 1500 people. One around the digital health side, one around the ar VR side. And then in the last couple years, as many other people did. Although I had a background interest in AI that was going back a number of years and, ran my first line of machine learning code in 2017 or something like that, and had read books about this. It was really after the gen ai side of things with Chachi PT that I started getting interested in.
So last year I was, vP of marketing at a company called Ulti Sim, which are real pioneers, both in virtual reality and ai. And it was from that period of time that I really got up to speed from a professional standpoint in terms of consulting, thinking about AI readiness and such. So my expertise is less on the technical side.
I'm not the guy who writes the code. It's more on the strategy and consulting side. What can we do with this? So I've written a couple books on this and have some sort of custom frameworks and work with a number of people to try to bring this into their organizations. So that's my business.
[00:03:20] David: I suppose that sounds like credentials. Gary, do you think we're gonna give him a pass? It sounds
like he knows what he's talking about.
[00:03:26] Gary: it sounds a lot cooler than just some random guy on social media trying to sell you prompts, and once I heard Zen Buddhism, I was hooked. So yeah, way
[00:03:36] David: Yeah, you and Gary need to have your own podcasts at another time. But it is, I think our audience as well. It's not just me trying to be like. A skeptic, but I think a lot of people are gun shy about that because there are a lot of people who came outta the woodwork, right? Like we joke that the crypto bros became AI bros. And they've
been selling the courses and we don't want to fall prey to that per se. We wanna make sure that the people who come on our show are actual experts. So we'll give, you've written books and stuff. We're gonna give it to you. We'll give it to you unless you were a crypto
bro before.
And this's machine learning code, so yeah.
so tell me at a high level, I'm a new company, new-ish. Let's, no, let's say I'm an ex existing company. I'm not like a startup. I'm an existing company. Been around, let's say 10 years. I have a website, I have this, that and the other, but I don't know anything about ai. And so I see, hey, this guy seems smart. He wrote a book. What are you gonna tell me? Like, how do you tell me. Who I don't know anything about it except for what I hear on the news. What are you telling me? How are you encouraging me to embrace it?
[00:04:41] Brian: a couple things. So I, one of my frameworks that I talk about is shot, SHOT for that stands for Strategy, humans Operations and Tactics. So one of the things, when we're thinking about ai, it's not just a single thing that we're trying to bring into our business, but we're trying to think on these different levels.
Strategies at the highest level. Operations is more on the team and operational level. Automation and augmentation. And then the tactics is more sort of the prompts and how people use it and how we're bringing it to proof of concepts and bringing it into our work. And around all that is the really interesting human component, which actually not, I think not nearly enough people are talking about.
So thinking about how do we. You Bring together an organization to get all the best ideas and insight and make sure that people are aligned in the same direction. And that there're there's a transparent process by which we can make sure that AI is being tested in a safe environment that we understand its risks, but people are also playing with it and understanding we can do and take it to the next level. So I think that the first place to start is with strategy. So I'll pause there. I have another model that I'd like to bring up as well that I would definitely bring to people if we're thinking about how to implement it.
[00:05:45] David: So when you're talking about the human side, that's really interesting because the news is really clear that AI in humans don't really coexist in a lot of ways.
If you get the CEOs to say the quiet part out loud, they all say, we're coming for your job. And so how do you blend AI in the human side? That seems like a really interesting pairing.
[00:06:09] Brian: Yeah, there are a couple things there. One, I think that if you think about the sort of the famous Gartner curve, the, we're talking about the diffusion of innovations and where we are on the hype cycle. In fact, a lot of times you see that curve and it's what is that? Why axis? What are they talking about? What they're talking about is expectations. So when there's a new technology, it's generally the expectations are relatively low, that it's gonna have much of an impact. Then you hit at some point where you have very high expectations after people realize there's a crash, and then really it's not gonna work as well as they thought after which it starts to rise again and you reach a plateau of productivity, in my opinion.
For instance, there was something recently from the CEO of Ford Motor Company who said. 50% of white collar jobs are gonna be gone. I believe that is a comment from the top of the hype cycle because it's also true that when people have taken AG Agentic AI and then implemented in their company, something like 40% of those are not done right.
And we're only beginning or are not continued once they've done some work with Ag agentic ai, 'cause they run into some problems. So they have security problems. The pro problems. When an agent has to work with other agents, they realize that AI is not much like a traditional computer program.
It's more like a person that doesn't always give the same outputs. And it's not just like a computer program that you set it and forget it and let it run. It's more like an employee where you have to follow up with it weekly, make sure that you know what it's doing, give it a good plan, and understand what it's happening, and manage it, and manage how it's working with other people and also with other ai. So I think that's one part of it is I personally think that some of this is people getting a little bit ahead of themselves. That's not to say that people won't lose their jobs, certainly people will lose their jobs. And it's something I've been concerned about for some time. And it may end up having to do with a revamping of our society actually of how we do things.
And and I think that actually is a, is an interesting separate discussion. But. I think one of the things that we're gonna see is over time, that certainly a lot of the white collar work that people do is gonna go away. Now I think one of the things that is really helpful about when we're thinking about this is less thinking about a job description and more thinking about the tasks that make up an individual person's job. So we're, I think that there are probably not that many job descriptions that are gonna be completely blown away in in 2025, for instance. But I do think a lot of those tasks that make up just about everybody's job description is going to, or some of those things can be taken over by automation, by ai, et cetera. And so in the process of that, we have to think, for an individual, how do they upskill themselves? How do they continue to add value? And from a company's point of view. For instance, I have a friend who's a, an entrepreneur and he hired a number of people on different products that they had. And as soon as Chat GPT hit, he said, oh my gosh, so many of the things that these people are doing could be done by Chat GPT even in its first formulation going back almost two years now. And so he basically said, I have a choice. I could fire a bunch of people and have AI do what they were doing and produce the same amount of stuff. Or I can do even more. I can empower my people, make them mini CEOs of what they're trying to do, and then he had to shift his own role in the company to be something that was more about guidance and taking them to that level. So I do think there's gonna be this basically you can do the same amount of work with fewer people with ai. You could do a lot more quantity with the same number of people plus ai. Or, and this is where the real opportunity is, you can use those people to come up with creative thinking and make sure that they're using it right. And working with AI to make sure that the prompts are good, the strategy's good on the front end, and then when AI does it work, then you're getting good quality output on the back end and iterating through that process and coming up ideally with new solutions for your clients.
And thanks for your customers coming. So it's like basically do the same amount with fewer people. Keep all your people and do more in quantity or just change the quality. Actually do something new that no one hasn't done before.
[00:10:00] Gary: The third option sounds like the best, but how many companies are actually gonna adopt that if they could save a book here or there?
[00:10:07] David: it's hard cause I've heard that argument before where you're like, Hey, why don't you take this
free time that your team now has? 'cause they don't have to do this grunt work and put them on these creative tasks and thinking, but most of your employees aren't capable of doing those.
[00:10:22] Gary: Yeah, not everybody's
[00:10:23] David: high level thinking stuff and there's a reason why they were the data entry person. That sounds harsh, but it's true. You said something earlier that spoke to me as a developer. One of the things that's, if any industry right now is being targeted by ai, it's us, right? Writing code. Because there's a lot of things AI is promised to do that hasn't lived up to the hype, but it can write some code flat out, it can write some code. And what's interesting about that is 'cause we're diving deep into that stuff and we've talked about that a lot and how we're embracing it. But one of the things that we're finding is, yeah, we don't write as much code when we're using ai, but you start to see the value of the other things that we do as developers that have nothing to do with writing code.
And it's yeah, I don't need there's a classic I think it's Ben Hoff, is that how you say his name? The CEO of Salesforce. Saying he will never hire any more developers. He's only gonna use ai, and 90% of code will be written by ai. And this was his big. Be him. And then the CEO of anthropics said something very similar that AI is gonna write all the code in the world. And when we look at how we're using it and when we look at a project that is an AI driven project, probably ha half, if not 80%, maybe on some parts of it. Are written by ai, but we aren't any less busy. Like it's writing a lot of code, but that code often is crap. And we have to, as all of our people are seniors, we just don't hire juniors.
It's the whole thing. But we have only seen, and they're basically, their job is to be the conductor of these amazing bots that. It can write, GA can write good code but often will not. And their job is to make sure that it is guided and building it right and doing it in a way that's sustainable and scalable and all this kind of stuff.
And you start to value those other things. And I think that's true for these other things. I'm only speaking from my experience, maybe this person who lost part of their job 'cause AI is writing all their stuff. Maybe you can value some of the other tasks or skills that they bring or maybe you invest in those and let them run and stuff like that if they're rock stars. I think where I'm afraid for humans at large is those C level employees, you're gonna lose your job. I don't know how you're gonna slice and dice. There's no way to sugarcoat that. 'cause AI is vastly better at creating c plus. Quality anything than a human. And if that's all you're good at, man you're not doing great.
And I,
[00:12:56] Brian: Well, I think one thing that's,
[00:12:57] David: way to say that, right?
[00:12:58] Brian: one thing that's interesting I was thinking about this model, and this is actually pre ai, but people talking about how you, automate your business, right? And some of it is thinking about basically these three steps. And step one is the preparation of everything.
You're start to do the planning of what you're doing, et cetera. Like deciding what's important and setting it out. And outlining the tasks. Step two is the automation of those tasks. And step three is some sort of looking at the results of it, quality assurance, reiterate through it and clean it up and ship it basically.
And if we put percentages on that, we might, something thinks about like 10%, is that upfront work? 70% is the word work that now could be done a lot of ways by automation and ai. And that 20% at the end is that iteration process and cleaning it up and shipping it and taking it where it needs to go. And I'd heard somebody was saying that, for instance, in medicine when a doctor comes and does diagnosis and a lot of ai is chipping into being able to do what doctors can do in the diagnosis side. But what it can't do is all the prevention stuff that becomes before you come to see the doctor, and then all the planning and everything that makes sure that people are following up on their treatment plans after.
So if we think about medicine as being this, 1, 2, 3 step process of everything before you see the doctor, when you see the doctor and everything after. We're seeing that middle stage being automated a lot. That's no longer the bottleneck, but that only pushes the bottleneck out to the other sides.
And I think this is probably true of other things as well. I. Um, that when you see yes auto, the AI's coming for this one part of this multi-part system, and then you have to ask yourself the question, how does that affect the before the after? Where does the opportunity come? And one of the things I've been thinking about is say there's open ai just, day after day launches, new and new products that essentially destroy whole industries and companies.
So suddenly your startup got $15 million and was building something cool and then OpenAI crushed it, or. Or Microsoft or philanthropic or whoever else. Steve, your question has to be, what can you, if you're thinking into the forward forward into the future, e even if these co big companies do something, what could you still do?
So I think a lot of that's last mile stuff. So understanding what needs to be done, client interaction, a lot of it's how does this meet the real world in some physical sense either with people or. Still digging holes in the ground or whatever other physical aspect there's gonna be. And another one is maybe people will never trust those big companies.
So what can you do to come up with a system where people have their own setup or their data is protected or some sort of redaction program. So I think this is how I like to think is okay, this is what the capability is now what about around it? And this is where the capability is going, what will still exist and still be important in the new future?
[00:15:30] David: We find. There's a lot of similarities to this wave, whatever you wanna call it, and the Apple App Store, when that opened up a whole new world of opportunity, right? I have these phones that everyone has. Originally it was only Apple that had the store that, of course now Android has their own. But a while for, there was a brief period of a couple years probably, that Apple just cornered the market
and that's when you had just the crazy apps like a flashlight that was an app. It's 99 cents to get a flashlight. And there was the beer drinking app that you could use the gyroscopes to make it look like you were drinking a beer. People sold that for nine, 9 cents. Someone made a lot of money on it.
[00:16:10] Gary: there was a flip, a coin app,
[00:16:11] David: They flip a coin app and you paid nine,
9 cents for that. Some of those were free, right?
And then they loaded them up with malware. But what was interesting was, is a lot of companies were born in those early days and then.
Apple, we the term became sherlocked, where they just steal your idea and put it in the phone.
A good example, of course, is the flashlight. There is no flashlight app in the store anymore because you don't need one. Apple does it fine. You don't need I guess you never need a coin flipper, a beer drinking app, but you, a lot of those features now get brought into the core os and you learn something from that.
If you're. Building something that they can easily add. You're not adding really a whole lot of value. It's a feature you're gonna get stolen. That Android did it, apple did it. They're doing it all the time. I think chat, GBT and the like are doing the same thing. I warn people we consult with and we talk to.
'cause everyone's got AI ideas, and we tell them flat out, if you're taking a foundational model. 'cause no one's building another foundational model, at least not a startup. That takes a bazillion dollars. And there's gonna be the three big ones, maybe four if we're lucky, right? We've got open ai, anthropic llama, and whatever Microsoft's dreaming of.
Oh, and Gemini. We got Gemini in there. So maybe Microsoft will come out with one and the Chinese ones. Yes. Deep syn and whatever. You're not doing that. No one's building those. There's a few of those. Those will always be a few. Maybe they'll consolidate, whatever. But if you're just saying, I'm going to do AI and wrap it up and make it, so if you ask these certain questions, we're gonna give you these certain answers. Like they can do that. I can go to chat GBT and answer that. I don't need your app to do that. A lot of startups are leaning that way. I'm just gonna make it so they can ask questions about this and they're gonna, it's gonna draw them pictures or whatever. And I'm like, I don't need you for that. Why would I do that? And so it's what is your, if you are a startup and you're thinking of ai, what is your secret sauce? What are you e Even if your secret sauce is, it could be as simple as a really good prompt that no one has, right? That you've we've built apps internally that help us code and whatnot, and we could go to chat GBT and do this, but our code is doing a multi-step process to help us do certain things and. That process is useful, even though at the end of the day it is Che Beauty or Claude or whichever one. But that process becomes your almost your patented little thing. Is it unassailable? Of course not. But that's the value. Whatever, however that chain is or whatever secrets you're bringing in or outside sources you're bringing in to, to pepper in and to add a little spice and sizzle, that's the app. And I think a lot of people are forgetting that. They're just so enamored with these tools that can do almost anything.
[00:18:56] Brian: I would say a few things. Like one of the things that I think is most interesting about mobile is the stuff that nobody thought. Okay, now you've got a computer in your pocket. And so guess what the, that's gonna completely change the hotel industry and the taxi industry. And like when you're, what, and sure enough, Uber is mo because you mobile phones made Uber possible and it totally changed the mobility and then the way people use.
Phones totally changed Airbnb and that completely upset the airline industry. I'm rather not the airline, but that too, of course. But there were other things from flights and stuff I think, and one of the ones that surprised me is phone cases. So somebody ca Apple came out with this this device and then everybody wanted one, that it was pink and had shiny things on it and little bunny ears and, everybody wanted a different version of that.
So there's these non-obvious things that you could do to tack onto, what are the big, what big boys are planning doing? But another one is solving a problem, right? So I really think that there are, I was saying that there are like a million multimillion dollar ideas that are basically just writing a, like a prompt that a reasonably good person could write, but in a domain that needs it. So are you selling cars? Are you a lawyer? Are whatever it is. Some very specific niche group that could use this stuff. And I think that there's a lot there.
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[00:20:43] David: So if I am getting started or in this world. What are and not a developer not something like my world, but I'm just a CEO of a brick and mortar, or a restaurant, or a, a construction company, whatever. What are some practical things that I could use AI for?
[00:21:03] Brian: one of the things I'll back up, and this is the model I was talking about earlier. I've, I have a model I call map, MAP, and it's mission ai. And the basic, the p is everything else. It's the people. The process is the plan. And if you've ever heard of in finance, sometimes you'll hear about zero based costing, I dunno if you know this concept, but basically it's many people who have a budget from last year for their department might just, they get, take all the lines, add 3% to all of them and ship it.
I was like, that's the coward's way of planning, financial planning,
the, the good way of doing finance. The good way of doing financial planning is to take everything off the table. Zero. You start with zero, and then you bring back the most important stuff one at a time. And you say, how important is this thing?
And then you might end up with more or less, these things are all gonna be resized. You might put something in there that you never had before, and some things may never come back into the budget again. And I think that's how I'm thinking about AI is that basically you're gonna start with your mission.
What is your why? And I like Simon Sinek on this, where he's, start with why. So you've got why you do what you do, you've got how you do it, and then only after that what you do. So famously he talks about Apple, you begin, why do we do it? We think differently. And then after that, it's how do we do it?
We have the highest quality hardware plus the vertically integrated and a beautiful ux. And then the, what they do is then computers and phones and iPods and everything else that Apple does. And so trying to start from that why, and then how, and what the why is the center of everybody's business.
And that's not always obvious. And so for instance Clayton Christensen talks about this idea of disruptive innovation, and he's and here's another example of you know if you were. In the 1990s, if you were a record company, what you did was print CDs and sell them to tower records so they could sell to people.
It was all about a physical product and some sort of distribution channel, and obviously that has gone away. If a com, if an A music company said instead. We take great musicians and have them create great work and get it into the hands of people who love music then that is their why.
That is their true, like what they do. And so I think AI is gonna change a lot of these ways of doing business. But that why what they fundamentally are doing for somebody doesn't change in many cases. And that helps rethink it. So you start with your why. The AI part is like now we live in the age of ai.
c c AI an do a lot of things. It can change your strategy, operations, tactics. You can use it to write emails, you can use it to do strategic thinking. You could use it to customer service. You can do all kinds of things. So with that in mind, only then do we think about what do we do with our people, our processes, our plan. Around that. So in fact, I did work with somebody who is a restaurateur and he has a couple of restaurants and they make great food. And he was saying one of the ways that he wanted to use AI was for his his managers. So if you're in a restaurant. You're gonna think. Okay. Sometimes we cater that tends to happen at certain times of year.
So if it's around a holiday or depending on the weather we might plan and do inventory a certain amount, right? Or certain things are in season. I. So part of that manager's job was to do all this planning, all this inventory, all the thinking ahead, and another part of their job was working with their employees and thinking about what customers want and being more customer focused. So really he was thinking about how do we take the AI to do a lot more of that I. Prediction about what sort of inventory we're gonna need, and then just schedules and some of the boring stuff. And then have that person spend more of their time on really what they were hired to do, which is focus on people their own people, their employees, and also their customers, and how they can really bring an amazing experience to their customers and maybe bring new things to the menu.
So I think that's an example. And then by domain, by demand, you can use that same sort of framework to think it through.
[00:24:41] Gary: Brian, with your experience consulting for these various companies, big and small, would you have three pieces of advice that you would give today's startup or entrepreneur, including how they might use ai?
[00:24:53] Brian: Yeah, I think what I laid out is about mission AI and humans. So number one it's about your mission. And so again, Clayton Christiansen talks about what you sell is not exactly what you sell. Um, a black and Decker doesn't sell drills. It sells holes in the wall. So if somebody can get a hole in their wall without using a drill, they would do they might find some other way to do it. And so it might be that you think you sell there's a classic example of. Of McDonald's selling shakes, but actually what they were selling was a treat for children or something for someone to do when they're on their commute. And so then you have to think about what the replacements are and in a time when everything's changing very fast and people are losing their jobs and new entrants are coming into industries that have never been there before. Thinking about your mission, why your company does what it does and this is really important. And so that's for companies and it's also for nonprofits. Why does your nonprofit do what it does? Like to try to end hunger or whatever else. And therefore your old ways of doing things might be shifted up, but you keep your core of what you were meant to do.
And I would even say that this is for individuals, so for people who are looking for their next job and what they're trying to do in life. Starting for with why they want to do a specific thing. And to some degree that aligns with their passions and the things you're passionate about, the things that you're gonna bring some energy to that you're gonna bring more than other people are because you're gonna do it in your off time whether you want to or not.
You just, ideas you have in the shower are gonna be leading towards things that you could bring into your career. That's the mission side of things. The next one is of course, ai. So that's changing everything. It's gonna change your strategy, it's gonna it's gonna change the way you organize your company and what the org chart looks like. It's gonna change the tactics of every single person in the company, down from the person on the front lines of doing things all the way up to the CEO and the full suite C-suite. And I'm interested to see how that might change strategy too, actually for companies in the sense that traditionally strategies have been very simple. In fact, the entire strategy industry was based on this idea of a four part chart where everything was the cash cows and stars and dogs and question marks in all of a company's portfolios or, so a huge company like GE would be. Spit into four categories. And I think that one of the reasons that was the case is that first of all, you had to make things simple so the CEO could understand it.
And then they had to translate to their, everybody who does marketing and finance and everything else, so they could understand it. And then they had to pass it on to their their employees so they could understand it and operationalize it. So there's this idea of understanding, communicating, and logistics that required this like simplicity of strategy at the top. I'm curious that with AI being able to improve all of these things communication across of an idea getting lots of market data, have more complex ideas of how we can bring things together, and then also operationalizing things at light speed in dynamic ways if we might actually see shifts in, in strategy there. And then the third thing I would say is humans. So the human EL element is really critical. I don't think there's that many people who really understand people who are working with this tech and vice versa. I think, and I think it's really helpful to think, we live in these socio-technical environments.
Every time you bring some sort of new technology into an organization. There's gonna be misalignment, there's gonna be fear about it, there's gonna be confusion about how to use it. People, there's gonna be AI literacy problems that they don't know what it can do, or they don't know what what kind of dangers might appear, et cetera.
So the human element I also think is really important pretty much in every industry.
[00:28:23] Gary: You mentioned something at the very beginning that was a this kind of goes back to what we were talking about before, if people are in that sense of fear or questioning if they're gonna have a job in the future because of ai. And then you mentioned using AI to find you a new job just by.
Maybe talking to it, telling 'em what you're passionate about, seeing if there's an avenue or lane in that direction, you can go. I thought that was interesting.
So if anyone wants to learn more about Dream Space AI Solutions, or about yourself, how can they reach out?
[00:28:52] Brian: Yeah, thanks. Dreamspace AI Solutions is my company, and so you can find us at Dreamspace Consulting. And I'm Brian Moynihan so you can find me on LinkedIn. So I'm looking forward to connecting with people. I.
[00:29:05] Gary: We'll make sure we put those links in the show notes as well.
[00:29:09] David: thank you so much, Brian, for chatting with us. This has been a lot of fun.
[00:29:12] Brian: This is a lot of fun. Yeah.
[00:29:15] David: on that note, we will see you all next week. Thanks again. Have a go.