Transcript 0:00 But from my perspective, radical action actually comes from desperation. Hmm. You were desperate enough to take the action, and that's what-- where I come- came to. 0:08 So I was desperate enough in my current role, in the previous roles at, that I needed to take an action, and this was the one I wanted to take. So I, uh, yeah, I-- that's a long way of saying it. Okay. 0:16 You're gonna have to talk a little bit about the desperation 'cause when you first said that, I thought of it kind of as a forcing function, that something was changing that was causing you to kinda weigh the risk and say, "Well, now the, the scales are a little bit more balanced. 0:30 Now's the time to do it." Am I reading that wrong by what you mean by, you know, desperate? Yeah, so it's-- I mean, that's, that's a good way of thinking about it. 0:39 The way I perceived it and the way I perceive it now, even, like, with radical decisions I make in my life, is that there are moments in your life where you, you've kind of fallen and you've hit, quote-unquote, "rock bottom" in different aspects of life, physically, mentally, financially, whatever else. 0:54 And for me, in that situation, I kinda mentally hit rock bottom because I was- Mm... in the corporate world for about a decade, and I knew how to play the game. I knew how to, you know, get through the ranks quickly. 1:05 I, I did it a few times, and I was like, "You know, this is-- it's just the same game over and over with different brands." I, I realized, like, this is just not the game I wanna play anymore. It's not fun. 1:14 It's not entertaining, and I'd rather fail at entrepreneurship than succeed at employment. 1:20 That's a huge insight, and I think that a lot of times people, and, and I've talked about this before on, on this podcast, a lot of times people will make a slow transition. They'll come to an awareness where... 1:32 And they can't put their finger on it. There'll be this sort of sense of unrest kind of in the, in the center of who they are, like, "What am I doing here?" You know? They come to this conclusion over time. 1:44 They sort of grow into it. 1:45 And other times, there's external pressures or, or, uh, external things that are going on at the same time that cause them into more of an inflection point, more of an aha moment or epiphany or something like that. 1:59 Sounds like yours is a little bit tilted more towards the epiphany, but it did take you a while to get there. Yeah, I would actually say it was more of the former, not the latter. It is? Okay. 2:09 So it was, it was more gradual in the sense that it was probably maybe six months or eight months of me telling my wife almost every day or every other day- I'm gonna quit... 2:19 about how much I wanted to go off and do something and do entrepreneurship, but I just didn't have the idea, and I used the fact that I, quote-unquote, "didn't have the idea" as my excuse as to why I can't do it. 2:31 And then when I realized that, I was like, "Okay, that's just fear. That's just me being afraid and me having fear manifest in a different way of logical reasoning as to why this isn't going to work." 2:40 'Cause like you said, I have a computer science background, so I can logic my way through a lot of things, and I can disprove the ability for something to be successful through that thinking. Mm-hmm. 2:49 So I realized that was the case, and I was like, "Okay, well, the idea is almost irrelevant. I just need to do something." And that's when I kinda just jumped right into it. 2:56 But it took about eight months of me talking to my wife nonstop, and she's like, "All right, enough. Just, just do something. Just, just quit. Stop talking about it and do something." 3:04 Well, that's almost the opposite of what happened to me years ago. I made a transition, and I kept telling my wife that I was gonna quit the position I was at, and I did it probably for a week. I didn't do it for months. 3:14 And one day I came home and said, "Okay, I quit." And she went, "What?" She was, like, surprised [chuckles], and I was like, "Oh, no, what have I done?" You know. So yeah, that's, that's interesting. 3:23 So made that, the change and-- but stayed, if you will, in the technology space overall, moving into AI. 3:31 As terms of what you were doing from a domain perspective and what you are doing from a domain perspective, were there other aspects that you had to adjust to when you stepped into this world of being an entrepreneur? 3:46 Were there... 3:46 I mean, I know you did-- Internally, I'm sure you did a lot of selling, persuading in your corporate roles and presentations and things of that nature, but were there other things that you had to adjust to, uh, in making the transition? 4:01 Everything. So well [chuckles], I mean, there was-- Still that's the case. So when you're an employee, especially when you're on the technical side, you specialize in a certain area. 4:10 So either you're really good at research, you're really good at development, you're really good at whatever else, and that's your, that's your shtick. So people come to you for that thing. 4:16 And for me, my shtick was research and AI, so I could talk really well to AI and research. But when it came to sales and marketing and accounting- Right... 4:23 and finance and, and blank and blank and blank and so many, I, I had no idea. I had some idea, but I wasn't, like, a guru. So as soon as I transitioned to entrepreneurship, I realized everything is on me. 4:33 And most importantly, and this is something I've seen in a lot of technical people, is when they create a company, they focus too much on the technical side because that's where they're comfortable. 4:40 That's where, that's where I'm good. I'm confident. This is what I'm best at, so I'll focus on that. But in the end, you can build something, but if nobody knows about it, nobody's gonna buy it. 4:51 And that's the situation I fell into. I was like, "Okay, well, I need to actually pull myself away from the technical side and focus more on marketing." Mm-hmm. 4:57 "I need to focus more on sales and persuasion and communication because that is what's going to actually bring dollars in the door, not me building in my closet by myself." 5:06 So that was a, that was a big one that I had to transition for. Yeah, 'cause you have to cover all those other bases that in a way you took for granted. Now, and you know what? 5:15 When I made the transition into-- And I did this a couple times, stepping out of the CIO role for periods of time. I was on my own doing consulting and things like that. 5:24 When I did that, I was aware that I was going to need to drum up business and manage all the administrative stuff, but I tend to minimize the level of activity and focus I would, I would need to, uh, put into the, these other areas. 5:38 So I'm just, I'm just kinda curious, how did you adjust? I'm sure you used AI to help you with some of these other aspects. Yeah, no. E- everything that I do has some form of AI. 5:49 So there's, there's very things I do in my life that don't have AI involved. And, uh, I mean, most of the administrative things, like expense, reconciliation, accounting, that's all automated. 5:59 When it comes to really writing and/or assessing anything, AI's involved. Uh, so a lot of that's a- automated. For the sales aspect, there was a lot of research. 6:09 So figuring out what are the different channels that one develops leads, and then of those channels, which ones have the, I would say, longest staying power? Which ones have more leverage? 6:21 Which ones are aligned with my experience? Which ones resonate with my ICP? 6:25 I started asking all these questions to understand different aspects, and if I didn't have AI, the amount of time it would have taken me to learn that would have probably been five, ten, six-- like, you know, twenty x the amount of time. 6:35 But if I can condense all that down because I can have all these books, and then I can ask questions of these books, and I can get advice from the quote-unquote "experts" in these books, then it drastically shrinks the amount of time it takes me to learn these things. 6:47 If you were thinking about back on your transition, and I'm looking forward to getting into some of the more specific aspects of your consulting and your support work for mid-sized companies and others. 6:58 But looking back in this transition you've made to be an entrepreneur in this space, if you were to have the magic way back machine and go back to the very beginning in time when you were starting to think about this, is there any pieces of advice you would give to yourself, and this would apply to others as well, in considering making this kind of shift? 7:21 So, like my immediate thought, my reactive thought was just to do it sooner. Like stop waiting, you dum-dum. Instead of waiting ten years, just do it in one or two. 7:28 And reason being is that you think that you're preparing for this thing, this entrepreneurship journey, but you don't realize that all the preparation is... 7:37 It's not completely obsolete, but it's close to that because through the ac-activity of doing the thing, you learn way more- Mm. -way faster. 7:45 And this is something I've told a lot of people I've worked with in the past that have kind of like trying to start catching up with me recently, is I've told them that like in the last seven to eight months, I've learned more in that period than I have probably in the last like six years 7:56 just because of the, the forcing function of sur-- You have to survive, survivorship. And it's, you have to learn these things, and you have to dedicate time every single day. It's not nine to five. 8:07 It's, it's, you know, you wake up until you go to sleep, and then you do it seven days a week until you're successful. And that kind of, yeah, that ability to learn that quickly. So I would say start sooner, don't wait, 8:21 and, um, yeah, that'd probably be the big one. There's, there's a big difference between sort of, you know, 8:27 book knowledge, I'll call it, although it's rarely books these days, knowledge ahead of the time and the experiential space you'll be in and the actual practicing of those things and leaning into them and feeling the weight of the need to do them. 8:44 There's, it's, it's like going from academic... It's like going from, you might appreciate this, learning calculus, advanced calculus, to applied mathematics. There's, there's a big difference between those two things. 8:57 And so- The way I- Yeah, that's, that- The way I con- the way I convey it is actually just because knowledge versus just-in-time knowledge. Mm. 9:05 So just because knowledge is all the knowledge that I read in all those books of those entrepreneurs that I studied throughout that period, hoping that I would have to use it someday. 9:12 And now it's just in time knowledge where I have this thing I have to do. I'm not really sure how to do it, so I need to go research it, read the books, and then apply it immediately. So there is almost no theory. 9:21 It's like, it's reactive learning instead of proactive learning. Yeah. And, and your first response about why didn't you do it sooner reminded me of something that I heard in a, 9:32 a seminar with Seth Godin, this marketing guy, right? Um, and someone asked a live question, and his response just shocked, shocked us. He just said, "You're stalling." 9:45 Just the act of trying to get more information, you know, uh, like you said, you sort of can trick yourself into, "I'm preparing," but really you might be rationalizing in the process of getting more information 'cause there's never enough. 10:00 And in this case, he saw through the question that-- And many of us do this. We, we, we think, "Well, I just need to answer this one more question before I'm ready to actually step into that space, take that risk." 10:12 And, uh, yeah, so sometimes you're just stalling, and you won't really know what you need to know just in time until you're experiencing what you, what you've stepped into, which sounds kind of weird, but I have felt that too. 10:28 Yeah. And it's interesting because people like myself and likely you as well are more susceptible to that, where you're, you're like a... You're, you're a very brainy individual. 10:37 You think a lot, you read a lot, you consume a lot, you logic about things, you plan, et cetera. 10:41 And you're more susceptible to overthinking and never taking action versus the other person that's the opposite, where they only take action and don't think about what they're doing. 10:50 There's always like a happy medium, and you have to, on that pendulum of the spectrum, you need to try to find a way to get to the center- Mm-hmm. -instead of overthinking and/or acting too much. 10:59 Well, actually, to be completely transparent, I'm probably more on the other side than, than what you might think. My wiring is actually to do things quickly, that'd be a quick start. 11:11 And I used to joke around with folks on my team when I was running IT that all I needed was two points to make a line, and I was ready to go. 11:20 And this used to freak my heads of in-infrastructure completely out of their minds 'cause I would make rapid changes, and thank God I had them to keep me out of trouble. So it was a balance. 11:32 Now, you're, you're on your own, but you often need to leverage either AI or other people you know to help you offset knowledge or to get them to do things for you. 11:46 And that was one of the biggest learnings that I made probably mid-career was just realizing that people that worked with me, worked for me, were much better at certain things than I was. 11:58 And so I would just give it to them and say, "Hey, look, will you take this?" And I would honor them in that delegation. But that was really hard for me to do. Now, that was the probably the same. 12:08 It was really hard for me because in a technical discipline like IT- It was seen as weakness if you needed to get help often. So yeah, that's, that's interesting. Anything else come to mind in terms of advice? 12:22 That's great advice, though. 12:24 No, but I mean, I think what you've stated is interesting around having some buddy or something to compensate for your weaknesses, kind of the, the yin to your yang, and how you can actually use AI for a lot of that now these days, if you know how to, if you know how to interact with effectively- If you know what you're doing. 12:39 Yeah. So that, that's perfect segue. What do you think are some common mistakes from your interaction with your clients that people make as they implement AI and maybe rush towards deployments or external deployments? 12:55 So some of the ones that I would say are like the bigger ones that come to mind would be first not having an established goal in mind. So I've, I've seen it's like a sixty/forty right now. 13:04 So it's like sixty percent of the people that talk to me for engagements, they're like, "Hey, we want to apply AI because..." And there's nothing after that. Just, it's just silence. 13:15 And it's like, oh, wait, hold on, and, and like I have to, I have to poke and prod. And sometimes, like the answers are, "Because my boss said so," or, "Because the board wants it," or, "Because whatever else." 13:25 And there is no logical reason as to why they want to apply it. They, they just wanna do it because everybody else is doing it. They're keeping up with the Joneses. And 13:34 that's okay to a degree, but you need to have some sort of rationale and ROI associated to the project, the initiative, to then reap the rewards of applying the tool. That's one. 13:43 Another one is connected to that is the lack of evaluations. So if you don't have a goal, then that's the bad issue. But if you do have a goal, you need to then measure the AI's ability to achieve said goal. 13:55 And oftentimes when people implement AI, especially AI, AI that's more chat oriented or more, I would say, AI heavy, you need to be able to figure out a way to evaluate that AI's ability to be in line with what you would expect a human to do. 14:11 And to do that, you need to set out a bunch of criteria of, say, put out fifty questions, and you have one human answer all fifty questions, and then you have the AI answer all fifty questions, and then you compare, 14:21 and you see how many times the AI get it wrong. And once you figure that out, then you feed that back into the system to then improve it to get it closer to what the, what the human would say. 14:30 And over time, you need to keep on evaluating the AI on those performances. And that's one thing I see a lot of companies miss is the, the lack of both specific evaluations and also binary evaluations. Yeah. 14:42 And so those evaluations, are they-- Are you thinking they're tied to a goal or just ensuring that there's integrity in what you're getting back from the AI? 14:52 So they should be tied to a specific goal in line with what that project is. For example, if I have an AI that answers questions in relation to medical information associated to my website. 15:01 So I have a website that has a bunch of blogs and a bunch of maybe wikis or something, and I have people coming to the site to ask questions about specific tools that I sell or drug that I have or whatever else. 15:10 And we need to make sure that the AI answers that question accurately. So then how do we create evaluation criteria for accurate? So one would be, is it referencing and ci-citing the right source? Is one. 15:22 Another one is, is it accurately calling out these three points related to the question that was asked? Yes/no. And you wanna make sure they're binary because if they're not binary, then people debate. 15:33 Is like between one and ten, they argue it's like it's a seven or an eight. Like which one's better and how do we know and things like that. 15:39 So I would say figuring out specific criteria for the given task you've given to the AI, and then making sure those evaluations are binary. Do you keep that going on over time just to make sure it's... 15:53 Is that what kind of a hallucination protection mechanism or is it some- Yeah... What would, what would you call that? Just- Yeah. So it's just a way to ensure the AI is, um, 16:03 is performing at its best in the way that you want it to. So it could, it could be emitting hallucinations, it could be mitigating the AI's inaccuracy of pulling in data from different sources when it should. 16:14 So maybe you don't want it to go to the Internet. You want it to go to your website, but it go-- it keeps going to the Internet. 16:19 That's a flaw in your system prompt, or that's a flaw in a, that's a flaw in a flag that you set up for the tool. So there's a variety of different ways that one needs to hone the model 16:28 to then target it towards a given task to and perform its best. That's pretty cool. And you're saying that often this is not done. People pre-pretty much if they do have clear goals, 16:39 they just make the assumption that the AI is staying, if you will, on the reservation and continuing to provide good results. Yeah, I know. Often they treat it like a black box. They, they... 16:50 Like a magic black box where if I drop something in, it's gonna work perfectly every time. 16:54 And if they lack evals and they lack goals, then they have, they have a bad taste in their mouth from the AI and from the experience they had with the AI. 17:02 And then sometimes they dismiss it, and they're like, "Oh, well, it's not there yet, so we'll wait six months to a year to then try it again." 17:08 And by doing that, they're actually hurting themselves in the long run because their competitors are likely effectively doing this now. Opportunity cost. Right. So they're doing it effectively now, and you're not. 17:18 So then by the time you retry it in six months, that competitor already has six months of experience implementing AI effectively against you. 17:25 And it's not linear, but it's exponential because their ability to compound those learnings into newer models and newer features is much faster than you. 17:34 So they're always likely going to be ahead of you in these aspects of the things that matter for the business. 17:39 And do you find that most of your engagements, you're, you're really in this space of how to interact effectively with the tools and how to... 17:47 I mean, the first thing you said was often they don't have a clear picture as to what they're even gonna do with AI. They have no goals, or they're just responding or reacting to board or top senior leadership. 18:00 "Thou shalt use AI, make something good happen," requests. You spend most of your time in this space on how to, how to be oriented to and train the human part of this equation to work effectively with the tools. 18:14 Is that where most of your time goes? I would say initially, most of my time goes towards education. 18:19 So it's, it's basically asking discovery questions, figuring out exactly what they want to achieve, and trying to get them to avoid the topic of AI at all costs in the beginning and only focus on business goals. 18:30 So that's very classic. That's very classic approach to, you know, systems, implementing systems. That, that is the same thing we've preached for decades, right? Is don't give me a solution. 18:43 Tell me what your problems are. Tell me specifically what you want to achieve. We'll talk about what's the right solution later. And that's always been a challenge. Exactly. 18:52 Maybe it's more so a challenge now, going back to what you said about most people viewing, a lot of people viewing AI as sort of the magic black box. Right. 19:03 And that's exactly what happens here, is where you ask these questions, and you avoid the topic of AI because it does distort their vision. 19:10 And when you focus on the business, oftentimes the solution to the problem they've brought up, that's the highest priority because if solution is solved, then it gets them closer to the said goal within a shorter timeframe. 19:20 It may not even have AI involved. It may just be basic code, basic, basic automations. And it... And if it does have AI, maybe it's like ten percent of the process. Hmm. 19:30 If you have, you have a hundred percent, ten percent is AI oriented, and the rest is automated through code. 19:35 And the things like-- That, that's why it's important to kinda stay away from the AI conversation because you don't want to start with AI in mind. 19:41 Often, if you do that, you spend a lot of time, waste a lot of resources, et cetera. So there-- So we, we talked about one myth about, you know, the magic black box. 19:50 AI is gon-gonna just sort of read your mind and give you something great as a result, I guess. Are there other myths that you c- have come across when dealing with businesses when it comes to AI? Here's a good one. 20:07 So, um, uh, open source. A lot of people like to talk about open source models and using models locally because- Mm. of privacy reasons or whatever else. 20:16 Very rarely do they realize the amount of effort it takes, not only just to stand up those models effectively, but to maintain them over time and not realizing the lack of quality to the model, usually to the use case they care about. 20:29 So almost every single client I've worked with, I have never recommended local models. 20:34 And it's not because I can't do it, because I, I used to have to do local models for some government contracts that I did in previous roles. But the... You have to constantly have GPUs up and running. 20:46 You have to worry about the infrastructure of latency between GPUs. You have to always be training and fine-tuning these models for given tasks over time. 20:56 You have to do a variety of things that people don't realize that is involved with local models. So it's, uh, it's usually a no-brainer just to go with commercial because it's ridiculously cheap. 21:08 The quality is ten times better, if not more. Mm-hmm. And the ease of implementation is night and day. Mm. So people just don't realize how big the delta is between the two. 21:18 And we talked about this when you jumped on our professional community meeting to talk to CIOs, and, uh, I mean, they're very concerned about data leakage and trade secrets, even in the prompting process, exposing kind of the company's direction. 21:35 But none of them want to stand up their own environment either. I'm just-- This is just a, a curiosity. Do you see that those security concerns have been, 21:47 uh, addressed by the large models that are available on the cloud- Mostly, yeah. To a greater... Yeah. Yeah. 21:54 So I've, I've, I've worked with all types of organizations of all sizes, and you can, you can buy different types of plans and establish different types of contracts with OpenAI and Anthropic and Google that are, that meet all the compliance needs one would want to, one would wanna care about and know about. 22:09 So, and the privacy associated data is fine. They can turn off training, so your data is not trained on. You can have your data purged every day and or every thirty days, depending on the provider. 22:18 You can make sure that your data's separated in a secure enclave. You can establish a co-- Like, there's all types of things you can do with these providers that meet the compliance needs of these organizations. 22:28 So there's almost like no reason to do anything locally. 22:31 The other thing that's interesting, and this is kind of stepping a little bit out of AI here, but the comparison I think is helpful, is most businesses or many businesses are running their email in the cloud these days. 22:44 And it's interesting that you don't hear concerns anymore about that from a security standpoint, where there's... 22:51 I mean, if you wanna find and farm some interesting data and potential, uh, data leakage, you could certainly do it through email as well. 22:58 Uh, well, let's take a little bit of a pivot here, and let me ask you about your, I guess it would be called the other hats you've had to put on your marketing process. Obviously, I found you on a... 23:10 I saw you on a YouTube channel that you have. Um, let's talk a little bit about what the life of a entrepreneur in this space is like. 23:19 And just before we jumped on and pressed record, I asked you how often you put something out, because I see something from you, I think, you know, on average daily. 23:29 So talk about that a little bit, 'cause that's a, that's a big transition as well. Yeah. 23:35 So I, uh, for the, for the whole marketing aspect of entrepreneurship, I guess it goes back to the point of when I made the transition, I needed to figure out how to, how do I generate leads? 23:43 This is the, this is the first question you ask. And then I realized that there's four ways you can generate leads. 23:48 And this is from a book that I read where it states that you can either do it through content, you can do it through ads, you can do it through warm outreach or cold outreach. Those are the four, four areas. 23:57 And I said, "Okay, these are the four areas. I'll start with warm outreach because that's the lowest hanging fruit. I can connect with people I've talked to in the past." 24:04 I reached out to around two and a half thousand people and then saturated that bucket. I can return to it in eight months, but after that, I need to figure out what's another one. 24:12 So then I moved to content, and the reason I moved to content is it's one of those higher leverage activities that has a semi low cost. The cost is really time. 24:22 And if I can put out content consistently and I can get better at communicating, not just in written word, but spoken word, 24:28 and I can kind of build a quote unquote brand around those pieces of content I put out either on LinkedIn or YouTube, then the leads start to come to me instead of me having to chase them. 24:39 'Cause with cold outreach and ads, usually you're sending something to somebody cold, obviously, and they don't know you and nor care about your offering. 24:46 But if they've seen your videos, they've seen your content on LinkedIn, they've consumed probably up to two hours or three hours of you talking about a given topic, and they then reach out to you, there's a parasocial relationship between the two. 24:58 They're like, they're like, "I kinda like feel like I already know you even though we've never even met." You have warm. They're warm leads now. Exactly. Yeah. So the sales process is like ten X easier. 25:08 They just-- They're, they're usually... I mean, oftentimes it sounds crazy, but oftentimes they're like: "Hey, like, I'm ready to, like, let's just do a project. Like, I don't really care what it is. 25:14 Let's just do something." And in that case, like it's... Yeah. And I realized that was, that was the path for me because I first, I like teaching, so it, it's easier for me to do the YouTube videos. 25:24 Um, second off, I'm learning stuff constantly, so everything, every single day I'm working on a new project or a new task or something like that, that I can then turn into content. 25:31 So it, it seemed like an easy path for me, and it's not easy by any means, but it's simpler- But you're leveraging that investment into staying- Right... 25:40 at the head of the field and say, "Okay, I learned this, so I can put this out," or, you know, "Here's this application I did with a client. I'm gonna put this out." 25:48 So you're getting more use out of one investment and time than just going off cold and trying to write something for consumption. Right. And it's much more scalable as well. 25:58 So if I put out one video and a thousand people watch it in five days, then from that I can get maybe twenty leads within that time frame. But that's in that five-day period. 26:08 In the coming month, I may get a derivative, thirty leads from that because people come across it later on. So these, these for- forms of content, they're somewhat always giving out. 26:19 I think they call that the long tail, right? So I'm just kinda curious, what's the kind of... what's the makeup from an, an industry standpoint of people to reach out and wanna do a project with you? 26:34 I'm just kinda curious, you know, what that distribution is like. Is it one industry more than another? Is it a spread? Is it individuals? Yeah. So it's, it's kind of all over the board right now. Usually the... 26:45 It's usually a business owner and/or some sort of higher up leader inside of a, like a mid-sized organization, and the industries are all over the board. 26:53 So I've worked with healthcare, lawyers, accounting, construction, cybersecurity, obviously finance, sign, sign designers, just, just all over the board. 27:00 People, people that have, uh, have come across my content and likely own a business and/or work at a company at higher up and they, they wanna start implementing AI and/or educating themselves on how to apply it. 27:11 So yeah, it's, um, mixed bag. That's really wild. So the other thing that comes up often when we talk about AI, AI is the fear of being displaced, right? 27:19 And we know, of course, that there are businesses that are laying people off and taking sort of lower level administrative type of positions out of the equation. 27:30 I'm just kinda curious about what advice you might have or what observations you might wanna share that would maybe alleviate some of this fear or at least give some, some people some practical tips on how to approach this. 27:44 I mean, this is a major inflection point hitting businesses right now. Yeah. It's, um, it's tough 'cause like you said, it's, it's one of the biggest transitions that humanity has and probably will ever go through. 27:58 Going from a... creating a new species, basically. And the feedback that or advice that I see a lot of people giving, which I agree with, is, is just to embrace it and, and s- and don't try to avoid it. 28:11 Don't stick your head in the sand, don't dismiss it, but really think through how can I apply it to my day to day and how can I automate myself out of a job? 28:19 And the reason that I would recommend that is, like a lot-- many people say, is it's not gonna be AI that replaces you, but it's gonna be somebody that uses it more effectively than you that will. 28:28 Because all these business owners, in the end, what matters most is profit, and if I can cut headcount and do just as much with ten people as I did with sixty, then I'm going to do that. 28:41 So it's, it's important that you're a part of those ten. Be on the right side of this wave. Yeah. 28:47 And it's, I mean, it's not, it's not great to hear obviously, and it's not, uh, fun to say, but it's the reality and I think people should be more... 28:54 I think people should be more honest with this stuff and, and stop trying to be, I guess soft and, and not soft, but like too, like tiptoe-y about the topic. 29:03 I've seen a lot of different executives and leaders talk about this in roundabout ways, and it's, it's not fair for the person. 29:08 We just need to treat everybody like adults and say, "This is, this is what's happening," and- Right... you know, try to get on board. Yeah, exactly. 29:17 So I mean, it seems to me that you're positioned in exactly the right spot here because you're, you're both helping advise and implement, but you're also educating a lot. 29:28 And if so, individuals are fearful about how to approach AI, how to come up to speed on AI. Folks like you help them educate themselves. And don't wait. 29:38 My advice would be don't wait for someone to offer s- you something. You know, "Hey Dylan, take this AI class," or, "Hey Joe, take this AI class. I'd like you to come up to speed." It may not ever happen. 29:51 You need to initiate this stuff on your own. Maybe you need to ask for funding to do something like that, but get on the right side of this wave and I think it's gonna change the nature of jobs. 30:02 There'll be new jobs created. Obviously, there's a lot of energy going into prompt engineering and context in order to effectively utilize this technology. 30:13 So if you're in the technology stack, and even if you're not, I mean they still apply and these elements should be incorporated into new jobs. 30:21 Seems to me the pace of creation and the pace of product flow is g- just gonna accelerate. I mean, I think that-- and that becomes a competitive issue. So yeah, if you're just sitting there 30:37 waiting to be taken care of, it's not the best place to be. Yeah. And I heard this interesting analogy recently, which is like both creepy and interesting in re-in regards to new jobs. 30:48 So I think it was, I think it was one of the lead researchers at one of these big labs, and it's, it's a common agreement amongst a lot of people in Silicon Valley right now, which is most of the world is gonna turn into a massive reinforcement learning environment. 31:02 Meaning that a lot of these jobs that we do day in and day out, physically and digitally, will be monitored and tracked by AI in different ways, so it can then learn how to do those jobs more effectively. 31:13 So it's basically a massive eye in the sky watching- Mm... everything, learning how to do it so it can do it more effectively than you. It's terrifying, but yeah. Skynet becoming self-aware. Yeah. 31:24 It's interesting how they, how they talk about it in the Valley. 31:27 A lot of people I follow and, and a lot of people I spend time with are engineers at these organizations that are doing the, the research, and how they talk about it is pretty, pretty insane. 31:36 Now, I heard something, I'm just gonna ask this because I'm interested. 31:38 It may not completely fit into this episode, but I heard or I saw someplace yesterday that Microsoft had invested a ton of money in their relationship with OpenAI, and I heard that they were pivoting to move to Anthropic. 31:54 Did you hear that? I didn't, I didn't hear it, but I know that Microsoft has been trying to build their own models recently, and I know that OpenAI just did a massive deal with Nvidia. So it, it makes sense- Right... 32:05 that like that relationship is bifurcating. 32:08 It, and it, yeah, it totally makes sense 'cause, I mean, in the end, OpenAI will become if not as big, then bigger than Microsoft, and they need to figure out a way to have their own model that can compete. 32:20 And part company. Yeah. That's interesting. Well, I'd like to, uh, open this up now if you-- Let's see. Yeah. 32:30 Uh, let's, let's talk a little bit about how people reach you and, and the different type of, types of engagement more specifically that you do, and ways you, you help folks. So... Yeah. 32:42 So I mean, I'm sure there's gonna be a link somewhere in the description of this video. There will. We can drop some links there. Uh, you can find me on LinkedIn, YouTube, are the two areas I spend most of my time. 32:50 LinkedIn is usually posting daily, and YouTube is twice a week. Stuff I do, so there's three different types of offerings I have currently. One of which is education, the other two are implementation. 33:00 So the first one for implementation is going to be an assessment. 33:04 So oftentimes, like I said, a lot of people are uncertain as to where to apply AI effectively, and it's a sixty-minute call to figure out exactly where that would be most suitable for your group. 33:12 The other one for implementation is custom builds. So if you have a specific project in mind or we come to a, a specific project in mind together, I then would help you build that. So I have computer science background. 33:21 I build a lot of automations myself, so I would kinda build that for you. 33:25 And then the third one is education, and this one's interesting and has weirdly become one of, one of the more popular ones, which is, uh, AI coaching. So oftentimes, executives have executive coaches, right? 33:37 Well, I've had a lot of executives and business owners coming to me asking me to act as an AI coach for them in a similar context. So we meet on a weekly to biweekly basis for two hours, and they drive, and I guide. 33:49 So they drive, meaning they build the thing or they do the, the action, and I give them targeted guidance along the way of building these projects. And they- So you're the human co-pilot. Right. 34:00 And the reason they wanna do this is they wanna understand AI more effectively themselves, so they can then invest their resources in the organizations that they, they lead more effectively. 34:10 And also, they wanna have more hands-on experience, so they can figure out what's... where AI can be applied in the organization faster. So that's, that's a weird one that's kind of manifested in a backwards fashion. 34:22 I didn't plan for that one, I guess. Well, that's fine. 34:26 That's really interesting, and I know-- I think when I, uh, looked at your website, you also had some content that people can consume sort of as a free thirty-day, or is it get on the email list kind of, uh- Yeah, yeah. 34:40 So- Yeah... all my YouTube videos have this and also on the main offering page. There's a thirty-day AI insight series. 34:45 So you basically get thirty emails over thirty days, and it's thirty insights of how you can apply AI to your business and your work, and that's just a free thing that anybody can get access to. Cool. That's cool. 34:56 Well, listen, Dylan, I really appreciate you coming on Titans. You have a very timely and fascinating transition story, and it looks like, you know, you're... 35:05 I mean, you said seven or eight months you've been out on this now. I'd say you've done really well. I've seen you. You're all over the place, and I wish you well. 35:14 But again, thanks a lot for coming on, and thanks for visiting with my group of CIOs. I really appreciate it. Of course. I appreciate the time, Joe. Yeah. 35:22 And so anyone else who's come to this point, I definitely will have links in the episode, and you should also, in the links I'll have, uh, links to Dylan's channels and his content as well. 35:34 So encourage you to reach out to Dylan. Hey, thanks for joining me today on Titans of Transition. I hope you enjoyed the episode. Please check the show notes for additional information.
