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/AI adoption: from FOMO to fundamentals
45 Plays20 days ago
Has AI finally met its moment of truth?
This week, James sits down with Jim Spignardo, Director of Cloud Strategy & AI Enablement at ProArch, to explore how enterprises are moving from curiosity to competence with AI. They talk data, security, productivity, and the shift from “let’s try AI” to “let’s solve real problems with it.”
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Transcript
Introduction to Podcast and Hosts
00:00:00
Speaker
You should be using data loss prevention and information protection. All those things that we were telling you three years ago that you kind of went, this seems like hard and difficult to do. But now that this other technology is here, it's it's brought all those things back to the table.
00:00:36
Speaker
Welcome to the forward slash podcast where we lean into the future of IT by inviting fellow thought leaders, innovators and problem solvers to slash through its complexity. I'm your host James Carmen and today we have with us Jim Spignardo.
00:00:49
Speaker
Welcome to the forward slash Jim. Thank you so much. very excited to be here.
Jim Spignardo's Career Journey
00:00:53
Speaker
Jim is the director of cloud strategy and AI enablement at ProArc, a global IT services and consulting firm.
00:01:00
Speaker
With over 25 years in IT, Jim's journey spans network engineering, cloud management, cybersecurity, and strategic consulting. What drives him is helping organizations cut through the noise and deliver real, measurable business outcomes.
00:01:14
Speaker
That's a lot of stuff. You've done a lot in your career. yeah A lot of different things. Sometimes I forget I did all that. And sometimes I wish I wasn't still doing all of it at once. yeah i've had I've had my bio written by others in the past and and somebody's asked me about it. I'm like, wow, that, yeah, somebody put that in there. That's that's interesting.
00:01:32
Speaker
Exactly. Yeah. All right. oh So you've been in the IT field for 20 something years in in the Microsoft world. And just tell us a little bit about kind of your background.
00:01:46
Speaker
Sure. Yeah, absolutely. So my I did not come to IT t from a traditional pathway, which and The more and more I talk to folks, you know, is is it's not all that uncommon.
00:01:57
Speaker
I actually had a degree in social studies education and ah kicked that kicked around in that for a few years. and And this was right around when the Internet was kind of exploding. It's 1995.
00:02:11
Speaker
And I decided, to let let me try and parlay those skills as an educator, communicator into something in tech, because I still started to really get excited with a burgeoning internet world.
00:02:24
Speaker
I got a job a few years later with a company out of Long Island, New York, that sold math, science, technology labs to school districts. So there was a connection there. right nice I had experience in school districts. And they needed someone who was a tech specialist,
00:02:38
Speaker
as well as a trainer for the the instructors who would have to take over these labs once we left. And I learned a tremendous amount doing that job. It's really where I got my feet wet.
00:02:49
Speaker
I learned how to build cabling, you know, how to set up PCs, connect equipment in, probably things that have nothing to do with IT t as well. When I left that position, because they wanted me to get into sales, and I was like, don't know if I'm really fit for that.
00:03:05
Speaker
I ended up going back and kind of investing myself in getting my Microsoft certifications, a plus Net+, plus MCSE, Got hired with a New Horizons training company in upstate New York where I'm based and became their IT manager as well as their lead technical instructor.
00:03:21
Speaker
That organization took a big risk on me. I've only been doing this for a very few years. And I spent the next nine years really, really becoming very conversant in Microsoft server and network technologies as well as IT t in general, not only only having to manage our own environment as well as training on this, and these materials five days a week, you know, four days, four you know, four weeks out of a month.
Transition to IT in Healthcare
00:03:47
Speaker
I left that organization after about nine years, went into IT healthcare care with a hospital system in here in the, Syracuse area, which was more enterprise, really got exposed to ah large environments.
00:04:00
Speaker
you know We had a person for every single thing in IT. Mine was, I was the Microsoft guy. ah my man My director always told me, well, why don't you know that? You're the Microsoft guy.
00:04:11
Speaker
And I was really focused on the core networking technologies, Active Directory Exchange, server, Windows server, and we got acquired by a larger hospital system.
00:04:25
Speaker
and my, saw the writing on the wall that, you know, my job was going to be absorbed by corporate it. t And i really started to i really wanted to get back into that learning mindset and staying on top of the newest technology. And I felt being at that position, i was becoming so very very much an expert in and a few things. And and um at the same time, cloud was becoming extremely popular.
Role at ProArc and AI Focus
00:04:50
Speaker
And so I took a position with the company I'm at today, ah ProArc, where I started as a senior strategy strategic consultant.
00:04:57
Speaker
working with customers on cloud migrations and, know, a lot of still legacy traditional on-prem stuff. And over time i took a manager position for a while and led a group of about 40 engineers.
00:05:12
Speaker
Um, and just in the last couple of years, um, I've really taken a role within the organization of both helping us strategically, but also our clients.
00:05:22
Speaker
Being very strategically engaged with our customers around how do they take all these investments that they have in technology and extract as much value as possible. At the same time, making sure that there their maturity level continue to improve around these technologies so they can remain competitive in whatever industry they're in.
00:05:43
Speaker
And then, you know, Just recently with the advent of AI, or at least ah the current version of the advent of AI, right? yeah um I took to that really quickly and became the the expert in the room for our organization as far as our generative AI journey.
00:06:05
Speaker
and um also developing solutions for our customers to get them off the up off the ground and figure out where these tools are going to fit into their portfolio of technology and and really how do they become a business enabler.
AI's Impact on Business and Challenges
00:06:20
Speaker
And that's what I've been spending the last couple of years of my career doing. And it's been amazing. Extremely exciting um to the point of exhausting, trying to keep up with all of that that's going on. yeah And also learning a lot about what makes businesses tick because this technology means so much to so many in so many different ways.
00:06:44
Speaker
And seeing how companies have approached ah incorporating it into their business has really opened my eyes to where why certain business businesses succeed while others struggle to kind of figure out their footing as the pace of change is is just accelerating across the world. So...
00:07:06
Speaker
Yeah, that's what a career. That's awesome. ah So you're no longer the Microsoft guy. ah Well, you're the ai guy now. Yeah, yeah. yeah it's For the most part, um for us being such a strong Microsoft partner, that translates into co-pilot, but yeah not just co-pilot. You know, we definitely um are into other types of generative based generative AI solutions as well.
00:07:31
Speaker
Nice. Yeah, i I was the Java guy and now I'm the AI guy. So I understand. There you go. Feel your pain. it is It is difficult to just, and maybe we can take a little aside just talking about it's so difficult to keep pace with everything that's going on. And and if I feel like it's it's really funny, you know, you try to establish yourself as like expert level on AI. And, you know, many aspects I'm sure you and I both are. you get Everybody will ask you question. Oh, you heard about this?
00:08:00
Speaker
No. And you feel like, am missing something? Am I supposed to? Yeah, am supposed to know that? Because there's like a gazillion things going on. You just can't know everything. So I guess that's kind of like the, why don't you know that? You're the Microsoft guy. Same sort of thing.
00:08:14
Speaker
Yep. Yep. So you've been, your job is, is, is talking to, to clients and customers about ai and, and, and bringing that into their organization and leveraging that to kind of optimize business workflows and and such things.
00:08:31
Speaker
How's that going for you? How, how's your experience been with that? ah it Honestly, initially it was pretty slow. um We've always had a digital engineering division at ProArc, which um has been using ai you know, prior to the whole,
00:08:46
Speaker
generative ah AI ah wave that's occurred and built into systems that we developed for them, whether it's with machine learning or other types of things. With this democratization of Gen AI where it's down at the user level or your mom is using it or yourre you're your, my case, my sister-in-law is an elementary school teacher.
00:09:07
Speaker
It has been different for for different organizations. Some who have always had a very innovative mindset jumped right at it and got went out of the gate. And some cases, the misstarts, right? They spend a lot of money and then get a lot of returns and they realize they weren't approaching it just the right way.
00:09:24
Speaker
and there's But there's still ah probably even more so, and I would say the vast majority of companies that are still experimenting and trying to understand where this stuff is going to fit within their business.
00:09:36
Speaker
And that has been a large part of what we're trying to do with those customers is to educate them. about the possibilities. i think ill To use the Microsoft marketing term, the art of the possible way. Yeah, the art of the possible way. yeah but yeah. yeah And i think, yeah from my perspective, I'd say the last six months, the light bulbs are starting to go off. Yeah, I agree.
00:09:59
Speaker
And they're finally saying, okay, think we've got a use case here where I think people have ah been exposed enough through shadow AI, possibly, possibly, to this technology that they're demanding it.
00:10:12
Speaker
um And they ah have also have a certain level of literacy to be able to use it in a way that's responsible as well. And that's kind of where we are in that journey where we're just starting to see companies coming to us engaging and saying, I'm
Practical AI Use Cases and Strategy
00:10:26
Speaker
ready, let's go. We're going to buy a hundred licenses. We're going to buy 200 licenses. We're going you know, use your, your, your program to help us do this correctly.
00:10:34
Speaker
um Look at the, what the, you know, the problems that we're trying and solve with this, this technology and how we transform the culture of our organization so understand that this is here and not going away.
00:10:47
Speaker
Yeah, i I agree. I think about that six months timeline sounds exactly right. As my observation and my experience as well of like, Before it was kind of like these organizations were, you know, they're playing around with AI tools and, you know, they'll install Copilot and and Tinker and and they'll do little toy projects. and And they were throwing a lot of money at it.
00:11:07
Speaker
Understandably, people need to learn, right? I mean, it it does cost some investment to learn. ah But I think people are starting to settle down and and they're going back to kind of those first principle thinking of like, At and least this is what we're advising people. I'm sure you guys are too. But like, let's start with a business problem, right? Like, what are we trying to solve for? who how Whose life are we trying to change here?
00:11:26
Speaker
And then, you know, does this does this add value to the organization? And then, you know, I think somebody i was in a conference last week and the guy said, AI should be like basically in the third sentence, not the first anymore. And it seems to be like, what's the business problem? What value does it bring to the organization?
00:11:41
Speaker
And how can we leverage AI to solve this um like or any Or any other tool. or Or any other. Yeah, exactly. Any other tool in our tool belt because AI doesn't, you know, we don't want to be in, you know, was it a hammer looking for a nail all the time or a nail looking, which way?
00:11:56
Speaker
Yeah. The other way around. Interesting. Yeah. So i I do think it's settled down. People are kind of, they're being a little more pragmatic about it and they're starting to approach these things better.
00:12:07
Speaker
um What about your observation? um felt It felt like that, I know you're in ah you're in a consulting organization as well, services organization. A lot of clients were, they were kind of just installing products. So we're a custom software development shop. So our experience has been that people have been somewhat hesitant to delve into, well, I can't,
00:12:28
Speaker
I can't develop AI application. We're not that sophisticated. That's like black magic voodoo stuff. like we We'll buy Microsoft Copilot. We'll consume products that are already built like that. But i don't know about building things. That sounds crazy.
00:12:44
Speaker
That's where, you know, we've done all a great job of having those initial conversations because folks will come to us and say, we want 25 lessons from Copilot. and And I'm kind of, hate to say this, determinative I'm kind of the gateway drug, right? I help them from a workforce productivity standpoint.
00:12:59
Speaker
But we're we're not making great, the huge margins on those engagements. Because ultimately, we what we ought to do is get them past that and move quickly to the maturity level of, well, wait a minute, how do we really tackle huge big business problems with this and this stuff?
00:13:13
Speaker
and actually drive high-end efficiency? How do we ingrain it into the the services and products that we're creating? And so we have a whole division, a team that does that.
00:13:25
Speaker
I'll be honest, sometimes they some folks are like, we don't care about the end-user productivity stuff. We just have a big use case. we want to you know We sell this product or this service or this software. How do we bake that into our solution? or how do we solve for x right? So if it's a manufacturing customer,
00:13:41
Speaker
we know we can ascent we can reduce the amount of waste that our our manufacturing lines is generating by using machine learning and AI um because we know our our competitors are doing it.
00:13:53
Speaker
How do you help us to do that? And they just go kind of go, yeah we don't care about anybody but else in the company. and And that's not necessarily the wrong approach, but um its it's at the same time, if you're trying to transform your business,
00:14:10
Speaker
ah with these tools, you can't silo the technology into a single problem or single business as well. It has to be something that's broad based. um and But the way you approach that and the timelines, you know those things are negotiable and can be adjusted.
00:14:27
Speaker
But if at the end of this journey, you have one process in your business that's completely automated with AI, but the rest of the company can't spell it, that's probably that's probably not the the best outcomes.
00:14:39
Speaker
um So we we take it from both both sides, right We take it from the the kind of the beginning stages of workforce productivity all the way up to fully integrated systems that are and leveraging AI that can and solve big problems.
00:14:53
Speaker
Yeah, I think the consumer-facing folks, people building software products for consumers, they don't have a choice. The demand is there. No, absolutely. If you're not, if you don't have ai enabled or whatever or some sort of flavor or the word copilot in your market texture, you're in trouble right now. So I think they are they're forced to. ah the The enterprise folks, you know, leveraging it internally and those sort of things and building things for their but there are people and their workflows, that's where it starts to, yeah, they've yeah they've
AI Demand and Caution in Enterprises
00:15:22
Speaker
been a little more hesitant, I think. i mean we're doing this even with our our own platform, internal platforms that we're building for our customers.
00:15:28
Speaker
you know where We have the benefit of being a digital engineering organization, but our objective at this point is everything has AI baked in from the beginning. It's not an afterthought. and There's definitely an advantage for startups because they can start fresh versus having to crowbar this technology into existing solutions, which feels clunky and it's stitched tough. It's kind of that concept of, you know, the development of the internet. We went in the, in the developed nations, we went through all of the stages from dial up O out of fiber, where in reality, the developing countries could skip all those steps and go right to the best technology.
00:16:09
Speaker
Right. Yeah. Yeah. Lucky them. Yeah. Right. they They don't have to have that AOL bill for all those minutes and everything. And that, that dial up noise in the back your head that will always trigger you.
00:16:22
Speaker
Exactly. Yeah. Now, the you you mentioned something that I thought was interesting. So the folks on the like on the manufacturing floor, so they they might want to use machine learning like for, you know, defect identification. And yeah one of the big use use cases is like, let's say you're making iPhones and they to detect, is there a scratch on the screen or whatever? So you can use machine learning rather than having a person pick up every unit.
00:16:43
Speaker
Maybe that looks great. um But that... I find myself, it's it's like I have to bite my tongue, like, you know, this technology has been around for like, you know, 50 years or something that you could you could have been doing this long before now. like well But I'm excited about there's kind of been this renaissance of AI, right? So...
00:17:03
Speaker
You know, yeah we've had a couple of false starts with machine learning and and artificial intelligence through the decades. um You know, but this now that we've we've had ah a lot of data and all that, we're starting to and this and I think the generative thing is just it's just lighting a fire and it's sparking, new you know,
Data Governance and Security with AI
00:17:18
Speaker
a new interest. Like you said, your mother and grandfather are using it, you know, youre yelling at the AI. All right.
00:17:25
Speaker
So what how about those? ah conversations have been for you, you know, with those kind of clients? so It's interesting because there were a lot of other things that we were trying to promote from a standpoint of this is what your business needs to be doing, and that we just kept getting kind of side glances from companies. Like, I don't know about that. but You know, one of them is identity security.
00:17:47
Speaker
Another is data governance. um And as well as things like machine learning. It wasn't until yeah Gen AI came around ah these that it made those things more important and relevant.
00:18:00
Speaker
And so ah for all these companies, we're having the hardest time of having those discussions or for them to take those things seriously. AI has forced them to start going, oh, yeah, you know what? If our data is a mess, AI is not going to work as well. So, you know, when you're telling us two years ago that we should engage with you as a data governance project,
00:18:19
Speaker
Hey, let's let's bring that back to the table. Let's have that discussion now need to do data and governance here. well I'm surprised you guys haven't told us about that before. you know Exactly. and And we're trying to keep that data safe and make sure that we're not putting ourselves at undue risk because we're absolutely going to use this stuff, but we have no idea the risk it's introduced in the business.
00:18:38
Speaker
Well, now one isn't that wonderful? You should be using data loss prevention and information protection. All those things that we were telling you three years ago that you kind of went, this seems like hard and difficult to do. But now that this other technology is here, it's it's brought all those things back to the table. So again, like you said, machine learning has been around for a long time.
00:18:55
Speaker
But um having AI around, regenerative AI, really is a force multiplier in getting information out of that. And so so now folks are saying, well, I can't do that without this other thing.
00:19:09
Speaker
All right, let's talk about that other thing. Right. ah Now, it's interesting. So I know there's there's always kind of been this this assertion in the market and and it's kind of been, don't a double-sided, you know, two-headed dragon or something for me. But like the the whole thing, like we got to have our data cleaned.
00:19:29
Speaker
Now, I would say if you're if you're training models, absolutely. You need very clean, very consistent labeled those sort of things. Yes, absolutely. But man, I tell you what, these LLMs, if you're using generative it's very squishy, right? I mean, is it allows you to have data that's not great as far as cleanliness. And it doesn't really matter. What's what's been your experience with those conversations? um It's to an extent, right? So, yeah and I've seen this more and more as we as we get folks.
00:19:59
Speaker
who are using it internally, who are still lacking good prompting skills. um Because I'll give you an example. you know, if we leave a lot of old data laying around um that has information that's no longer relevant, it's going to surface that information. sure And it's it doesn't really know what the what weight to put on it or priority.
00:20:21
Speaker
But if there was a if we were doing our good data governance and we're archiving that and just left, yeah the answers we would get would be more accurate um with with less well-scripted prompts.
00:20:33
Speaker
right right So right now we tell them, you're going to get less hallucinations when you you provide better context and are as specific as you want to be or as you can be with the output that you're expecting.
00:20:45
Speaker
And... Not everyone wants to do that, right? They they get an answer right away and they and they get in pattern where it's been right so many times, they just assume it's right every time.
00:20:57
Speaker
and so they're not looking at the information that they're getting as an output and they're just sending it along or introducing into documentation or po or ah some sort of deliverable. and And it's like, no, that's wrong. Right.
00:21:10
Speaker
You need to make sure this data is accurate because, know, and and if you decrease the chances of it happening when you when you do are making sure that your data state is is well planned, well organized.
00:21:25
Speaker
um but But to your point, it it does it doesn't necessarily, um it can it can overcome some of those obstacles just by the nature of it being able to look at the data overall. But there is risk there you need to think about.
00:21:41
Speaker
So it's more about, you would say, and I'm going to try to echo back to what I hear. yeah So it sounds like it's more about the freshness or staleness of the data as opposed to like the format, like all the sentences have to be proper grammar. Oh, um yeah. It's all about the freshness. and and Yeah.
00:21:57
Speaker
Yeah, it definitely could take, you know, very unstructured data and turn it into, i use this notepad called Remarkable, right, to take all of my notes now. And ah when I'm in a meeting where I i can't record, you know, and get audio transcript from teams and then have facilitator take wonderful notes.
00:22:15
Speaker
I could take those handwritten notes, turn into it a PDF, give the photo to copilot. And it creates a full outline of that meeting and with the notes better than I even recalled when I wrote them down myself.
00:22:30
Speaker
And so you're you're absolutely right. It it still can discern a meaning out of what sometimes can seem like just absolute noise. Yeah, maybe. So if I want to take your example and... and like maybe you have that hit home, it would be if you were taking notes and you wrote down the sky is green five times and you wrote down the sky is blue once and you fed that note into an LLM and you said, well, what color is the sky?
00:22:56
Speaker
It's not going to say blue. It's going to say green because that's the largest signal that it's hearing. Yeah. Other than it knows that the sky is blue. You know what I mean? Yeah, yeah, yeah. That yeah yeah would be the idea. Okay. Yep. Yeah. So if you have a lot of but ah garbage kind of hanging around, cluttering up your context, you want it to... and and That's one of the risks, right? and We totally look at what we are getting from ah from our media today and and just the preveance of ah chatbots in social media and on websites um that are that are just kind of amplifying noise.
00:23:28
Speaker
All AI, so the risk there is AI may just reamplify that as well. So again, it's it's about making sure that what it's being fed is good sources of information, true sources of information, and not just regurgitating the the the volumes of noise that we have out on the internet sometimes.
00:23:48
Speaker
Yeah, and and I know like with Microsoft Copilot, you think about like, Intranets, you know, people in document repositories within companies. How many old documents are out there with just garbage from years and years ago that nobody wants to and wants to go through all the hassle of cleaning all that stuff up?
00:24:03
Speaker
You turn Copilot loose on it you start asking questions like, what? That doesn't even make any sense. We don't even have that business anymore. And these companies know that and they're trying to make that that cleanup easier.
00:24:14
Speaker
So I'll give an example. Microsoft just released, a it's in preview right now, something called Knowledge Agent, which is embedded in SharePoint and can actually help you go through your document libraries and some of your lists the and actually put some governance around it, but also tell you, hey, this stuff's old. You should probably get rid of it.
00:24:32
Speaker
And it probably is not too long from now where it's going to say to you, hey, do you do you want to archive all this data? And you're going to review and say, one button, go do it. And it's going to take care of it for you. So they understand that there needs to be additional ah assisting technology to to to clean this stuff up. And they're but the funny thing is they're using AI to help AI, right?
00:24:54
Speaker
I don't think this is relevant. Yes, right. And we'll watch them battle each other. Yeah. Yeah, i I can't wait until like this technology gets to the point where I can just say, hey, Microsoft Co-Pilot, go down to my back room in my basement and tell me all the things I need to just throw out that I haven't touched in 20 years. Can it do that? And then i'll that that's changing lives right there. Yeah, yeah, yeah, yeah.
00:25:17
Speaker
right. So yeah um I know we mentioned when we when we spoke earlier, you know, kind of prepping for this for this episode, you mentioned something about kind of the FUD, the fear, uncertainty and doubt aspect of a kind of what what you're you encounter with your your clients.
00:25:33
Speaker
Talk about that a little bit. What is that still still happening? is that Was that only in the past or is it still a thing?
Trust and Regulation of AI in Industries
00:25:39
Speaker
No, it's absolutely still a thing. We're, especially our customers that are in regulated spaces where healthcare care or we have, we actually do have a ton of customers that are um power generation facilities, power plants. Oh yeah. We we manage about 150 power plants across the United States and Canada.
00:25:54
Speaker
And like the, the, the comment is mark I can't trust it. You know, I've heard, I've read these stories on the internet and they things are just going to go completely off the rails. And you know, the next question is, well, what are you doing to control the AI that's being used today?
00:26:08
Speaker
they're like, what do you mean? Like, you you know what people are using in your organization, right? Well, I mean, we tell them to be careful, not do it. um like Do you have an AI usage policy? No.
00:26:19
Speaker
I said, well, wouldn't it be better to just put put guardrails in place and accept the fact that this is this is a reality and and use a system that respects your data and respects your security parameters um and give your employees ah the appropriate ah guidance on what's acceptable and not acceptable than to just pretend that nothing's, you know, there's no risk already.
00:26:46
Speaker
but right you're You're worried about the risk of the known, but you have no idea about the unknown risk that already exists. And we actually can help organizations with this. We have a security AI assessment, which will come through using Microsoft tools. Surprise, surprise. and and And that will actually look at all the third-party AI that's in use already and what people are putting into it and how they're using it.
00:27:08
Speaker
it not not meant to scare them, but just give them ah information to empower them and go, I had no idea that our or research and development team was using that tool. And wonder why we've gotten 10% more productivity or or you know product solutions out of that team in the last six months.
00:27:25
Speaker
um But at the same time, ah they're also putting all this IP in that system and we now could end up in our competitor's hands. So thats sort the tail there yeah tale there is yeah it's working.
00:27:38
Speaker
Let's just make sure that you have control of it and get it out there and put it in place.
Education and Risk Management in AI
00:27:43
Speaker
And so, like I said earlier, there's a lot of education that still has to occur. It's probably going to still be the case a year from now. We're still going have to be spending time educating um our customers um and the general public as well. You know, we, we like to do just a lot, a lot of outreach through social media and webinars and what have you, just to provide, you know, some base context to,
00:28:04
Speaker
you know, what's going on in the world? Where are we headed and and how do you navigate it? Yeah, I think, and if we go back to kind of like the first principles, and we've gone through this, you know, anytime you want to standardize, ah you want to try to make doing the right thing the right way easy, right? And same thing like with DevOps and all those, so you know, any sort of standards you want to have, you know, don't stick your head in the sand and and just just hope they'll do it right. Make it easy for them to do it the right way.
00:28:29
Speaker
and Put the, like you said, the guardrails and the facilities in place to make it easy for them to do the right thing. Yeah. Have you, this one ah this one comes up sometimes. I've noticed this with some clients, especially in regulated industries.
00:28:41
Speaker
When you tell them about a problem, now they know about it. There's a legal problem with for them. You know what I mean? Like if I know about it, I'm supposed to be doing my best effort. and I'm doing air quotes here for the yeah audience.
00:28:52
Speaker
I'm supposed to be doing my best effort at mitigating that issue. So if you tell me about it, now I got to go clean this up. Did you hear anybody like kind of giving you the Heisman, keeping you a hand, like an arm length because of that? Not really. i think that those are the ones that just don't want to have the conversation. yeah And so – but most part, most organizations want to keep themselves fixed. They just know that without a strong ah partner with expertise in this area, they're flying blind. And it's more risk not knowing than it is knowing.
00:29:22
Speaker
And um because it's if if you if you're not paying attention to this stuff, it will come back to bite you. And then you look even more foolish. Like, wait a minute, you didn't have an a AI usage policy. You weren't tracking and monitoring what people were using. You didn't have data loss prevention and weren't aware of where where your information was going.
00:29:42
Speaker
And if the answer is no, that's worse than saying, yeah, we did. And we were we were making an effort to, but it's something still happened, right? At least that then you could say, well, we we were doing our best. And just like everyone else, ah you know it's not if, it's when something was would happen, right? and And also being able to how you can deal with that more quickly and and resolve it and um get back to an operational state.
00:30:07
Speaker
Yeah. Yeah. I think um that's that's absolutely the the tactic to take with with companies like that. You make sure that they understand and knowing is is better than not. And it's kind of yeah like, oh, it's just hope we don't get sued.
00:30:20
Speaker
ah All right. Well, this ah are we need to transition to our next segment of the show. The next segment is what we call our ship it or skip it.
00:30:31
Speaker
Ship or skip, ship or skip. Everybody, we got to tell us if ship or skip. So you mentioned you are a Microsoft partner. ah We've had pretty good results. you see You guys seem like you have too, but it takes a little time to build up a little momentum as a partner for these sort of things.
00:30:50
Speaker
would you Would you recommend it to smaller organizations such as, you know, kind of like are in our world? Is that a thing? Would you say absolutely go for it? Or is that kind of like, yeah, you either have to go all in. like what would be your guidance on that? Is that a ship it or skip it?
00:31:04
Speaker
That's definitely a ship. but And again, i'm ah I am extremely biased on this because I've, in the last 25 years, 18 of those years has been with companies as a Microsoft partner.
00:31:15
Speaker
and And the ecosystem that Microsoft builds with with their partner community is it can be matched in the world, in my opinion. I just came back from a selling conference um in Dallas with Microsoft partners and sellers.
00:31:31
Speaker
And the ability to unlock opportunity um between the partner community and the Microsoft community is just tremendous if if you take advantage of that um and lean into it um and co-sell with those organizations and um have them help you learn about what's coming next so you can you can stay on top of those things to make sure um that you're offering or or including certain technologies in your own practice.
00:32:02
Speaker
Going blind and in trying to do that on your own without without that type of relationship is very tough, especially if you're going to be um ah using Microsoft technologies or implementing Microsoft technologies as a part of a product or solution. So...
00:32:16
Speaker
Ship 100%. Got it. Yeah, I think it's, for us, it's it's it's been a good experience being a Microsoft partner, I would say, oh overall. it It does get to, you know, don't know, especially with like some of the bigger ah cloud providers.
00:32:31
Speaker
There's only one bigger one. Maybe two, I guess. But yeah it it feels like as a smaller organization, we're not real big organization. We're like 100 A little over 100 now. um It can feel like you're not going to get enough attention from them. You're you're not a big enough, you know, fish for them.
00:32:46
Speaker
ah So that that can be rough at times. But, ah you know, when you lean in and you build relationships with the folks, that they're very supportive and they've they've they've done a great job. Okay, so one of the things that comes up with with AI in particular, and it'd be interesting to hear your take on this, like using AI for creative works, you know, art and those sort of things.
00:33:05
Speaker
What's your take on that? I would say... Ship it with an asterisk. We get a lot that. If you're you trying to use it to to um run your business, should should you should be using quality tools, that kind of quality, but you should have someone who's operating it that has expertise, right? It's kind of like, ah you know, if you're trying to navigate a ah shipping container or ship, right?
00:33:34
Speaker
You're not going to just put someone who who's ah who does yachts, right? You can sail yachts, right? That's a good analogy. like that. And the more experience you have in that area or domain, the better off. So you're not going to put someone who's not a marketing person or doesn't have some sort of design philosophy concepts behind that if they're creating marketing material for you.
AI in Creative Fields and Business Integration
00:33:55
Speaker
but You're not going turn the the intern ah summer intern who is you know working on the imaging laptops into your marketing director and using AI. You want people. So um as long as there's qualified people,
00:34:09
Speaker
Doing it, I'd say yes. ship it And if it's for personal use, who cares? You know, just yeah have fun. Have fun. yeah Enjoy it it. It can help you, you know do creative things faster and and maybe things you couldn't do before.
00:34:20
Speaker
Just be willing to hear the criticisms of people and they tell you, that's AI garbage, isn't it? And you're like, well, yeah, maybe. No. no what you so I always put in dashes in my writing. i think you see Yeah. Yeah.
00:34:34
Speaker
ah yeah I love to see the marketing intern. Those folks are they're having a rough patch. You know in the last couple of years, there's been a lot of like, oh, that was the marketing intern. And they have now been, you know, sacked or whatever.
00:34:46
Speaker
Yep. Yep. A rough go. And Wendy's is, you know, on social media will lean in in those situations. of Yeah. They're interns. Yeah. Pretty funny. Yeah. Yeah, i'm I'm with you on the the ah ship it for creative. And and i I consider software development to be a creative endeavor myself, you know, just because it's self-serving and I like to feel like I'm an artist.
00:35:06
Speaker
um But ah that that theme keeps, prop you know, coming up time and time again of like, you know, the, you know, don't don't let the the yacht captain do your container ship, right? Those sort of things like the There still needs to be a level of expertise. I mean, AI is just, as you said, it's amplifying things. It's allowing you to do dumb things faster. Like it's, you still have to be careful. You have to have people who know and what they're doing to to guide it.
00:35:32
Speaker
Yep. and you've talked about it think the answer is probably pretty clear but like maybe maybe you do have a hot take on this like um these copilots number one like I'm a little like what is the copilot product like there's good hub copilot there's Microsoft copilot and everybody is kind of using this I don't think anybody like trademarked it everybody's calling everything a copilot I like the sense of of of calling these things co-pilot because that kind of implies I'm still the pilot.
00:36:00
Speaker
I'm still in charge. yeahp You're helping me. You're a partner in this and you you help me. I'm not turning everything over to you. So i like that that that concept. But like, what about, um you know, implementing this within, you know, your business and your organization?
00:36:13
Speaker
I would assume you're a ship it or maybe maybe you're not. I definitely ship it. Yeah. So, I mean, there's kind of three stages. There's, there's, you know, a co-pilots and whether you're talking about Microsoft or any other company that's using that term, there's co-pilots in the assistance of just general work, know, just improving the general work.
00:36:32
Speaker
Um, but then there's kind of the human led, uh, agent assisted type of work, which I think has a lot of value, but we just don't push that out there without explaining what exactly it is and how to do it correctly.
00:36:46
Speaker
And then the last stage there is really agent led, but human advisor or human oversight. and um As long as you follow those principles and don't kind of have this concept of,
00:36:57
Speaker
we're going to all of our business over to AI and just take vacations, you know, three weeks out of the month. I, you know, I, there's, there's absolutely benefit here. um But what, ah one critical thing that I think a lot of organizations are missing and we're trying to emphasize as much as possible is you have to have someone who, who is the owner of this and who is driving adoption within your organization.
00:37:20
Speaker
It can't be just, we're going to roll out some tools and, and we're going to use them in specific areas um because what will happen is it will, you'll get a, you'll get a good uptick and then people will just kind of get tired of it and, and, and kind stop using it.
00:37:36
Speaker
um We actually offer virtual AI, chief AI services the officer, right? Because what we've realized is if there's someone in there actually driving the adoption, you know,
00:37:50
Speaker
validating the the value and return on investment and creating a structured pathway and roadmap for the future, you're much more likely to to be successful in this. And we I've actually said this to a couple of Microsoft reps that I was pitching this to um this week.
00:38:05
Speaker
Our goal is to get out of there within a year. In fact, if we're still there, we failed. but Because we have not emphasized that enough to that organization is you need someone within your own organization who knows you best, that this is their primary responsibility.
00:38:21
Speaker
yeah And our goal is to work ourselves out of a job. so Yeah, I think that the when you're rolling out these copilots and stuff, and it's it's funny, you know, folks can, they'll latch on to kind of like that first use case that you you you give to them, right? and And you make things better for them.
00:38:36
Speaker
But users are are, they're funny and they're fickle and they they can get very used to, you know, processes that are, You know, it's that frog soup thing, right? Like they yeah they they get so used to doing like this and long, laborious process. They they think, that well, this is just normal. This is this fine.
00:38:53
Speaker
So having someone that can kind of provide that creative spark of like, well, hold on a second. Why are you, you know, doing all of this in this swivel chair, you know, integration kind of thing? Like maybe we can leverage AI for this. Let's let's think about that, right? Those sort of conversations, again, that art of the possible sort of ah sort of a conversation. Yeah, I think that's very important as well. Yeah, I think employees sometimes think their value is doing that, that those tasks, you know, and and what we're trying to do is I call them the three D's because it was robotics at one point, but the dull, the distracting and um ah well dull distracting and draining
AI as a Transformative Tool in Society
00:39:27
Speaker
work. Right.
00:39:28
Speaker
Because really, we hire you to to think and and, you know, and work with humans. So wherever we can get rid of all that other stuff, the better off we're going to be. Yeah, it's it's been hard. I mean, we're kind of in a a knowledge worker economy and like it's it's been hard for us to shake that industrial revolution of like we were cranking out people they thought kept me swinging this hammer thousand times a day. This is the value I provide this organization. But it's not now. You're you're ah a human being with a big brain up here. with that Big frontal cortex. up Yeah, that's why we like having you around.
00:40:00
Speaker
All right. ah That's been great. Okay, so now and I don't know if you're a ah ah longtime listener of the show or not, but we have this thing we do ah kind of towards the tail end here that we call the lightning round.
00:40:18
Speaker
It's time for the lightning Rapid fire,
00:40:26
Speaker
slow quick and make count. this game, out. the lightning round. If you have listened the show, you know how important this is. This is the make it or break it time for you. Absolutely. Yeah.
00:40:41
Speaker
um I'm sure you this is what you've been nervous about. And I'm not going sugarcoat it. This is serious. Okay. and im um Don't put away the smile, the laughs.
00:40:52
Speaker
so Let's go for it. Right. This is – the This is the the stuff that really counts. You know what i mean? Like this is like you so far we've gone through middle school. Right. And and no college is gonna be like, you know what? you You had a bad grade on that, you know, math test in sixth grade. I don't think we're going to admit. But this is this is the stuff that counts. So. All right.
00:41:11
Speaker
Very serious. Correct answers. But there are correct answers to these things. So ah this is and we will score you. All right. No pressure. Yeah, yeah. I actually work better when they're when I have a score.
00:41:23
Speaker
It makes me step up my game. So let's do this. Yeah. Yeah. I mean, and and I don't, again, I'm not going to show you. It is pressure. it's It's a lot of pressure. And i want to I want to emphasize that to make sure that this this gets its due respect.
00:41:34
Speaker
Okay. So what's your favorite car? My favorite car. um um this is I'm probably going to get this one wrong right out gate. I'm not a really car person. um I find cars to be a a necessary tool.
00:41:49
Speaker
I would say as I get closer to retirement, my goal is to live in a community where I can walk as much as I can and I use a car as little as I can. um But like got also I'm also a James Bond fan. So if I had to say pick a car, would have to be an Aston Martin DB5. Okay.
00:42:06
Speaker
okay We would have also accepted a Veyron. but those are the yeah Those are the two. You actually had okay the one correct answer other than the Veyron. Okay. So you got it. That's good. Not so good so far. but here we go You're doing fine. You're doing fine.
00:42:19
Speaker
I mean, on average. Yes. Got it. Got it. Neighbor word that starts with the letter Q. Q-Bert. Oh, nice. All right. Now you're going old school. I appreciate the 80s reference. I played a gazillion hours of Q-Bert myself.
00:42:35
Speaker
Are you a dark chocolate or a milk chocolate kind of guy? Dark all the way. The darker the better. 90% cacao? Yeah. Let's do it. It's hard to find that in like your normal grocery store. You got to go to a specialty. Aldi sells ah I think an 85% bar.
00:42:51
Speaker
That's acceptable. It's acceptable. that's that'll That's passable. Yeah. i i i agree. How would you rate your karaoke skills on a scale of one to Mariah Carey? In my own mind, ah yeah, it's right up there.
00:43:04
Speaker
um Although I'm not a big fan of Mariah Carey. um and But if I had to be compared to Mariah Carey, in my own mind, um i would I could probably be her understudy in Vegas.
00:43:16
Speaker
Okay. I like that. Mario Brothers, Super Mario Brothers or Zelda? um I like a good story, so it's got to be Zelda. It's got to have good... I mean, I know Mario Brothers, does but it's is it really that good? I think Zelda kind of out shines it in the story and the journey and the quest, you know?
00:43:34
Speaker
That's a good answer. Like Mario Brothers, it's like, oh, the guy stole Peach again. Let me go find her. You know, like that's one of those things. Isn't there a permanent problem the solution to this problem? Yeah. Like, hey, let's not hang out where Bowser hangs out. mean, you know.
00:43:48
Speaker
Exactly. Yeah. um Are you an ask permission or beg forgiveness kind of guy? I used to be an ask for permission. But as as I progressed in my career, I've definitely leaned more towards beg for ah forgiveness. um Because a lot of times organizations are are just getting by and and trying to get things done and they don't have the bandwidth to to approve or or sanction every single activity. And I've gotten to the point where I'm confident in my abilities where i don't think I'm going to break things too bad if I just go ahead and do this. And then if it turns out right, you know what?
00:44:28
Speaker
We got something done quickly. Like it. um If you could travel back in time, what period would you go to? And ask me back, not forward. Right, right. So ah ah being a former social studies teacher, i think I was always intrigued by the revolutionary period, you know, and to find out what was really going on. You know, what was it?
00:44:50
Speaker
Was it as as a. um where we ah where Were the the revolutionaries the actual good guys? Were we all the good guys? Was the purpose of of how we founded the the United States as as ah pure as as we say it was, or was there some other sinister stuff going on there?
00:45:10
Speaker
I'd like to get into the back alleys and conversations and find out you know what what what was really transpiring that we wanted to kick the British out. Yeah. I love the cynical nature of that. um i had a great history. but i think I heard this from a history teacher. that I attribute to him in my brain, but he said he said, history is not written by those who are right.
00:45:32
Speaker
History is written by those who are left. Right. Or the way remain. who when yeah Yeah. The remainder. So, yeah, that's an interesting. Woo. All right Yeah. I never, I guess I never really thought just took the the story hook, line, and sinker. So now I got a new conspiracy theory to to kind of go down that rabbit hole. I think a lot of these interesting, you mockumentaries or these historical fiction kind of shows have got you thinking in that regard, right? Like well what was, or even Alexander Hamilton, that play, the play. i really kind of ex exposed some some some threads there that you didn't know necessarily.
00:46:05
Speaker
Right. What's your favorite day of the week? um You know, this is very controversial in my mind. And i've I've actually thought about it. I hate that people dump on Mondays. ah hate that. feel bad for the underdog.
00:46:18
Speaker
um We're on Friday. where this is a friday and We're recording on Friday. I hate that Friday gets all the love. um I feel like Saturday and Sunday just, they they don't really do anything. They show up. So it's those middle days that I really think don't get enough love. And, i you know, so a good Tuesday cannot cannot replace anything.
00:46:36
Speaker
You know, it it just it just happens to between be between a Monday and a Wednesday where everybody's angry and hating. And Wednesday, we're like, oh, we're over the hump. Yeah, yeah. um You know, so I like to show love.
00:46:48
Speaker
I'm a Mets fan. So okay I like to shove show love to the underdogs. And I think Tuesday and Thursday are underloved. I love that. Yeah. Because you're right. Like ho my ah like Wednesday, it's got the whole, um boo you know, they got the camel talking and all that. Like, yeah.
00:47:04
Speaker
I like it. Okay, we are on the, it's Friday, October 24th, as you said. We are one week away from Halloween, so I'm going to ask this question.
00:47:15
Speaker
What was your last Halloween costume? I listened to the previous podcast, and I was actually thinking about this, and i don't recall. I used to get dressed up for Halloween every single year, right up until about a couple of years ago when my kids left the house.
00:47:29
Speaker
And my wife I lean heavily into great costumes. We've won costume competitions. um I think the last one that I got dressed up for, I was the, I had a yellow rain suit in my garage and i now have a graying beard. And I'm like, how can I, cause I like, I like simple yet,
00:47:50
Speaker
um easily recognizable um characters. So I decided to be the Gordon's fisherman. I knew you were going there. I love it. All right. I love it. So I, grayed my hair a little bit more filled more gray into my beard, threw on the yellow rain suit. bought a, know, the hat and, uh,
00:48:06
Speaker
people were like, oh, here's a Gordon Spishman. Yeah, I was going to ask. good People knew it like right off the bat, right? Yep. That's a good one. That's fantastic. I love it. All right. Okay.
00:48:17
Speaker
You did okay. Thanks. We'll have to pile everything, of course. take that. Yeah, we'll have to, you know, have to go through the the all the scoring algorithm and everything. We do use, it is the modern world, so we do use a large language model that we've Because it's a natural language. It's a good thing I've been polluting the internet with all of my information to throw it off and make it biased.
00:48:41
Speaker
It's funny. I've watched that the new Superman movie last night and there was this, have you seen it yet? My son, who's was ah a real big superhero, he said it was fantastic. I thought it was pretty good. Everybody kind of hated on it. I really enjoyed it. I had a good time. There was a scene where, like, ah Luther was, like, he's trying to give Superman a bad rap, right? And, like, he shows this setup where he's got, like, all these millions and millions of monkeys on keyboards, like, just hating on Superman on the internet. so yeah So, yeah. That's what I was imagining when you just said that. Now we have bot armies, right?
00:49:13
Speaker
Yes, exactly. All right. So any, you know, we're done with the the lightning round. Any sort of What's the vision for the future? what are What are we looking at from all the stuff we kind of talked about today? what do you Where are you seeing all of this AI thing going? What's the future look like for us?
00:49:30
Speaker
Yeah, I really just think that we're we're right in the middle of probably one of the most incredible times in human history, transformative times. ah As far as being able to predict, you know, what's going to happen or what's next, it's it's hard.
00:49:46
Speaker
um You know, we all, everybody's talking about an AI bubble and I think at some point there has to be some air let out of the balloon. I hope it's not all the air at once. um But from a a future vision standpoint,
00:50:01
Speaker
ah There's no going back from this. and we as a society and as a world need to start recognizing and training people to be able to exist with this technology side by side.
00:50:12
Speaker
and So, you know, we have to fundamentally look at our our education system, stop being so resistant to introducing this stuff into that environment, um but also train people to have the right skills to to work with this section, and whether it's analytical skill, the thinking, whether it's, you know, prompting, you name it, right? We have to create a new model of what it means to to live in the 21st century and beyond. And um oh ah some people are going to lean into it and some won't.
00:50:44
Speaker
And where where that leads to, Not quite sure just yet. I hope we have a lot of ethical, responsible people at the top of these organizations.
00:50:55
Speaker
Sure, they Some days I doubt that, that are going to hopefully, you know, ah make sure that they're not like going to destroy humanity in process.
00:51:06
Speaker
Yeah, guess you were saying that it's like, you know, are we... ah Absolutely. it's transformative. Are we at a point where, you know, right now we're kind of clinging to this, this notion of like, well, you still kind of got to learn ah the all the basics and know, cause you got to be able to guide this AI thing. But like, and I thought of like the one example I could think of off the top my head and like in the Navy, like for a long time, they weren't, they weren't teaching navigation by the stars. Right. And then they got into a situation where they're like, Hey, what happens if an EMP has dropped on our big boat? happens if
00:51:41
Speaker
How are we going to find our way? So they have to like kind of retrain this stuff. Do you think we'll get into an era where we we let go of this? we You have to know the fundamental, like all the like solid principles, software engineering and all all those sort of things. Are we going to let do those things just die off? Are they are they no longer or we do you think we'll always need those core concepts?
00:51:59
Speaker
I think at a certain level, we're going to need those. Like you take, for example, and I worked in healthcare too. and I would walk into one of our our patient rooms. I was just astounded by much how much technology that that was in that space. Stuff that we had three different engineering groups like that were essentially responsible for that one room.
00:52:17
Speaker
Clinical engineering and and you know IT. t and um But at the end of the day, they still had to have manual processes. And they had to run drills.
00:52:28
Speaker
that if this technology stops working, what do we do? and How do we still continue to care for the patient? And how do we make sure that, you know, because the doctor has hasn't done a real surgery with their own hands, right, and only have used a robot, what would that look like?
00:52:44
Speaker
um I got to believe that we're were going we're going to have to keep those, was really ah but it will be gradual, right? So some of those things we'll definitely probably never do again.
00:52:56
Speaker
Right. And then there's some of those things that we'll have to keep around. Again, it's a risk thing. We have to look at what the risk is. You know got to make sure these systems remain resilient, whether or not there is technology leading it or not. Right.
00:53:07
Speaker
So. Yeah, I watched like The Walking Dead and I was thinking about what you were talking about. Like, think if if a zombie apocalypse happened, I don't know that I'd be very good. Right? Like, I don't know how to make a windmill.
00:53:19
Speaker
You know what I I don't know how to shoo a horse. I don't know how to all this stuff. So, yeah, but we still have to kind of at least have that there in case we need it. I can grow food. know how to do that. But like, yeah, there's a lot of things that they had to do in The Walking Dead. I'm like...
00:53:35
Speaker
Yeah, I'd be screwed. Yeah. That's one of those things, too. I think the the need the necessity drives the ability, right, sometimes. time So when you get to that point, people learn new skills pretty quick when, I mean, it's a matter of life and death. so Yeah, zombies are going to be chomping on me. I'll figure out how to shoe a horse.
00:53:51
Speaker
ah so Right. I've seen the videos. And get good at it real quick. Yeah, exactly. What about any any takeaways? Any takeaways? actionable insights or strategies that that you would you share with folks based on your learnings and kind of the stuff were talking about? Yeah, just from from a business perspective, you know, if you're if you're in that position where you're at being asked to adopt AI as a technology or getting pressure from your C-suite or the board or whatever, um don't feel like you have to do it alone, right? Lean on experts, but also come up with the a logical
00:54:25
Speaker
way to to bring this stuff into your organization, ah don't don't be afraid to go slow. and Take your time, get it right. um Because the risk of getting it wrong is much greater than and not doing any any of them anything at all at this point.
00:54:41
Speaker
um And it's also important that you start hiring people who are passionate about this and who have these skill sets on their resume.
00:54:52
Speaker
And I've actually talked to our CEO this week and I said to him, you know, we need to start thinking about making sure that every candidate as is is AI literate and that they've already used it and understand how to use it because,
00:55:06
Speaker
you know, there's a costs sink there if we have to do that all ourselves. And at the same time, we're doing, you know, our AI and onboarding and making sure that people are trained in our ways of doing things. But, um and then lastly, you know, you don't have an AI usage policy, get one tomorrow. whether you Whether you're doing anything with AI or not.
00:55:28
Speaker
Make sure you have a policy that clearly states to your users what is and was not acceptable. If it says never use AI and for that's it in the policy, well, we at least stated it. At least people are afraid.
00:55:40
Speaker
Exactly. Yeah. And i would I would say that the AI tools are very good at writing those policies, too. They've been asked enough times now. they've they got Without a doubt. Yeah.
00:55:52
Speaker
Oh, use as much as you want. Yeah, for sure. Right. You're written by ChatGPT. Always use ChatGPT if you have a question. Yeah, exactly. um one One thing of that I would say to folks in the same vein with what you're talking about is like,
00:56:06
Speaker
A lot of this stuff can feel daunting. and And, you know, we live in this like Pinterest and Instagram world or whatever, right? or And I'm old, so Facebook, right? But the the perception of like what everybody else is doing is a little skewed. So when you think like, oh, I don't know anything. I'm i'm so far behind.
00:56:23
Speaker
You're probably not. I mean, most of what people convey to others in this this modern world, this Pinterest world is kind of a facade of what, you know, and and and it's it's through rose colored glasses. They're not, they're not telling you that stuff are down in the trenches, you know, they've had a breach, blah, blah, blah, whatever. Right.
00:56:40
Speaker
Yep. You're fine. Don't let that FOMO set in and and it's not daunting. Yeah. They're only putting their best face forward and they're not telling you all the, in you know, all the dark. secrets and mistakes they've made. But um yeah, for sure.
00:56:53
Speaker
Yeah. I mean, people are are in advanced states of AI usage, but a lot of folks are, they're just figuring it out too. So don't feel like you got to go hire the PhDs in order to leverage this. Yeah, don't bankrupt the company over this. Right. Yeah, exactly.
00:57:08
Speaker
Anything coming up you've got, like conferences or books or anything you got coming up that you'd like to talk about? Yeah, sure. um Two things. I'm actually starting in upstate New York, which is central New York, western New York. So Syracuse, Rochester, and Buffalo co-pilot AI user group.
00:57:24
Speaker
um that We have an event on November 20th that is virtual. The initial one is going virtual at 6 p.m. I have more information on my my LinkedIn page, Jim Spignardo. I'm the only Jim Spignardo in the world that I know about.
00:57:39
Speaker
check that out. And if you're in the upstate New York area, or even if you're not, you know, join. And we love having community. We really want to help people navigate this, both from a business perspective and a personal perspective. So I've taken that on as a new ah new initiative for myself.
00:57:56
Speaker
As well, I'm going to be doing a LinkedIn live presentation with the Team Copilot. Team Copilot is a group that is established out of the Netherlands, but they kind of have gone global.
00:58:09
Speaker
And they're doing a 24 days of co-pilot in December, kind of like an advent calendar. And so I submitted one of my sessions and I got approved. So on the 5th of December at 9 a.m., m I'll be doing LinkedIn Live about how to build a no-code gift-finding agent, whether it's for coworkers, and family members, or friends, you going through an exercise of showing you how to build no-code agents, but in the context of creating a gift-finder. Yeah.
00:58:39
Speaker
Can I feed it my gifts I've given in the past? Because my wife was, yeah, my wife was like, I gave her these earrings. I was like, do you like them? She's like, yeah, I really do. loved them when you gave them to me two years ago, too. The same exact pair. like, oh, of course I knew that. Well, I thought what you might, if you ever lose them, you have a backup pair now. Yeah, redundancy. We've got have that.
00:59:05
Speaker
Well, this has been great, Jim. Thank you so much for coming. We really appreciate you coming on the show with us today. No problem. Thank you. was a blast. All right. Well, if you'd like to get in touch with us here at the forward slash, drop us a line at the forward slash at Caliberty.com.
00:59:20
Speaker
See you next time. The forward slash podcast is created by Caliberty. Our director is Dylan Quartz, producer Ryan Wilson, with editing by Steve Berardelli. Marketing support comes from Taylor Blessing.
00:59:32
Speaker
I'm your host, James Carman. Thanks for listening.