Latest / Founder Talk with Alex Sheridan / The Future of Work No One’s Ready For With Jason Krantz

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The Future of Work No One’s Ready For With Jason Krantz · Founder Talk with Alex Sheridan

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95% of AI pilots fail. Is that surprising to you, and
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why do you think that is? No, it's actually not surprising
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to me. If you're in school right now
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and you're going for coding, or maybe you're even a seasoned
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coder right now, yes. What does the future look like?
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Really good question. Do you think college has become
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a scam? I have a pretty strong opinion
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on this. College isn't for everybody, but
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a lot of people get pushed into that.
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Are we in an AI bubble right now?
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Yeah. There's just a ton of money
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that's been invested. All the companies out there,
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they're hemorrhaging cash. What does it mean for the
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everyday founder business owner? How is it going to impact them?
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If your business is in this AI space, you build a company real
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quickly or it's maybe even something you've built over
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time. The very thing that creates the
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opportunity in terms of getting the market fast.
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Cheap is also a thing. Could also be your Achilles
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heel. Jason Krantz, pleasure to have
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you on the show, man. I really appreciate you coming
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in. I love your energy already just
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came to the door. Let's go.
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You know, like I appreciate that I founder and CEO of Titan
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Strategy, Titan and then labor titan.com, right?
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So I see AI advisory firm staffing recruiting you've been
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in obviously. So we've got some fun stuff to
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talk through. One of the things I wanted to
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bring up right away since I've seen you do a lot of posts about
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AI is I saw a recent stat, this was a Forbes article, maybe
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we'll link it up here, but you can look it up if you just
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Google forbes.com and Google 95% of AI pilots fail.
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And the the article talked about what business leaders should do
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because of this or as a result of this.
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What are your thoughts on that? If 95% of AI pilots fail, is
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that surprising to you and why do you think that is?
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No, it's actually not surprising to me.
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So with my background in data analytics, one of the things
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that I found is you're, you're trying to lead a corporation in
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through change, right? Transformation of some kind that
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ultimately hopefully lead to some kind of value creation
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trying to go from here to here. And The thing is, is in order to
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do that in any realm, even outside digital realm, you have
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certain fundamental things in place.
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And AI is really reliant upon like quality data.
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And having run through these, run through this process in many
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companies, I've seen first hand how many times people want to do
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the big adventurous thing, but they don't have that fundamental
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blocking and tackling in place. And so therefore, it's kind of
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like starting a race with a flat tire.
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You're kind of, you're kind of in trouble, like out of the
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gate, you're just not going to get there.
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And so in many, in many instances, you can have
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companies that see the big shiny object and they want to chase
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that because it's what everybody's talking about.
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And the, the challenges is that you really got to make sure you
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got the blocking and tackling with the data quality in place,
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because AI in many instances right now is just taking that
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you give it, applying logic to it in some capacity and helping
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you extract meaning from it within the context of your
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business. But if that data is junk, it
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can't really do its job very effectively.
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And so this is one of these things where that's the first
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problem. The second problem is, is for a
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lot of companies right now, it's kind of normal where they're
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trying to figure out what is it that we can do with this?
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That's right. So as a result, you're going to
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have a lot, there's going to be a lot of blood on the streets
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because you're figuring this stuff out.
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So that's where it's kind of being clear on what are we
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really trying to do with this? And then defining even before
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you start, like what does success look like?
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Because you could have something great and you kind of miss the
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mark. If you just recalibrate a little
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bit, you can hit the mark on that.
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So, you know, it's a journey, like we were saying before,
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it's, it's a crawl, walk run progression.
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And when you're in this crawl phase for corporations, it's
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hard. And then there's also the the
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cultural transformation side, which comes further down, you
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know? You make some really good points
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there. And I, I wholeheartedly agree.
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I was listening to a podcast from a former client of mine and
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he was talking about how a lot of boards now are like, show me
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the AI project. You know, that you guys are
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doing, where are we spending money AI And it's, it's not
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about what results do we need to get what outcomes and how can AI
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help us achieve those? It's just what are we doing with
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AI? You know, I don't care what it
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is, just we got to be doing something with AI, right?
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And it's like, is that really the mentality though?
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And I think you, you and me are aligned there where it's like AI
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can be a massive advantage and amplify results and help you do
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things more efficiently. But you do got to have some
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things in place first. You do got to be intentional
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with how you're using it. Right.
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Yeah, it's, it's the analogy that I use because I like
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analogies because we relate to them.
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And it's this idea of if you want to lose weight, you don't
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jump to using fat burners or creatine or something like that.
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First thing you do is make sure you're exercising, you sleep,
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you're eating right, basic blocking and tackling things
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that if you get those right, then you're going to get the
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benefit of all the other stuff. But you're going to get 9599% of
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your benefits from that basic stuff.
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And The thing is, it's not sexy. You don't go into a board
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meeting like we cleaned up our data, we did this.
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It just doesn't get people excited.
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So yeah, it's fun. And The thing is, is it's
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exciting. It's something new.
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There's potential there. So, you know, as somebody who
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has advised many companies on this type of transformation and
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kind of making sure we're pointing the cannon in the right
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direction and both time, energy and money.
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I understand that it's, it's hard, but it's also like focus,
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like what are we really trying to do?
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And if you get clarity on that, that can typically help you
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figure out like, are we at the right point to really be
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pursuing this type of AI journey?
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To your point, I think everybody can benefit from it.
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But again, it's coming back to defining what does that initial
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AI success look like? That's right.
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Yeah. So in your experience, what do
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you think it is that 95% of the AI pilots fail blocking,
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tackling, that kind of stuff? But specifically what what do
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you see when you look at companies like what are they?
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What are they not doing that they should be that it's not
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working? Yeah.
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I think for a lot of companies, it starts with my perspective of
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AI is really good for process improvement, identifying maybe
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like cost saving opportunities, like in a procurement sense,
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things like that can augment like analytical capabilities.
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So I would say for many companies, they're not as well
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structured in these areas as they would like to think they
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are. You know, specifically on the
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process side, people say like, well, this is the way that we do
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this and it's very custom and you know, this is how we've
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always done it. Rather than looking at, hey,
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maybe we should consider a new way of doing this, whatever it
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may be. It may be order processing, it
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might be shipping, it might be receiving, whatever it is.
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I saw this a lot when we were doing like ERP implementations
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where you got like a standard module and people like, well,
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our business is different. We're, we're unique.
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And it's like, no, you're really not.
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And a lot of times there's best practices built in there, but
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there's a natural resistance to change because change is
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inherently scary. And when you're walking away
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from things that, you know, that makes it even more scary.
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So I would say that there, there's no clear answer that
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because it really depends on like the size of your business,
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where you're at, where you're at, even in your, your
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maturation process digitally. Because there's some companies
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that are pretty new in this digital journey.
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They manage things in spreadsheets.
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And you know, when you're moving to something more advanced like
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AI, it's just it's a different like rules of engagement if you.
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Yeah. So what if you were talking to a
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company right now, founders listening to this entrepreneur
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company, Yeah. And they're saying we're
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thinking about watching this new AI program or software.
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Yes. What would you, what would you
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say? Hey, time out for a quick
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second. Yep.
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And what would you say? I have been there and I would
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say it's be very, very clear on the problem that you're solving
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for, as I stated before. But the other thing is, is talk
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to people that have this problem.
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I've made the mistake as a startup owner myself of creating
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something in a vacuum, thinking that I knew what people wanted.
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And then I bring it to people and they're like, what the hell
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is this? This is the how has this helped
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me? So I would say the great thing
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about being a startup founder right now is, is obviously with
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a lot of the AI and automation tools, you can build things very
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quickly, very cheaply. If you have any kind of
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engineering or technical background, the Vibe coding
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tools can be really, really good.
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Get into that in a second. Yeah, because I've used it
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myself where it gets you like 8590% of the way there.
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But you don't have all this overhead, you don't have all
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this legacy stuff. So you can move quicker, right?
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You can be very innovative. And, you know, I would also say
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it gives you the opportunity to help these companies that are
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starving for solutions in this realm, or maybe they don't have
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the expertise in house or they don't have the creativity in
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house. So I would say for those that
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are looking at this is like, you know, rather than just building
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something in a vacuum, go talk to people.
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There's a guy I really like. I'm going to give Rob Snyder a
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shout. He's over at the Harvard
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Innovation Labs and he has this concept called the product
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market fake pain cave. And as he was talking about it,
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I was like, I live that for two years, didn't even know this is
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what they call it. But he's like telling me about
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it. And it was all of these things
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where it's like, hey, here's what, here's what happens if you
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just develop in a silo. And basically the solution is go
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talk to people. And I just say from my own
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business, once I kind of flip that switch, I, I started to see
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things change almost. We I'd say within two to three
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weeks. Wow.
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We're just just talking to people.
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Yeah. What do you think of this?
9:05
Yeah. What do you think of this?
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Like, what do you like? What don't you like?
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How might you use this? Yeah.
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Because as a founder, it's easy to get in our own heads and be
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like, this is what people want. Yeah.
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Cool idea. Yeah.
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And they're like, this is hard to use.
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Well, what value is this? Like there's what do we do at
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it? Yeah.
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Are we in an AI bubble right now?
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Yeah, I would say. And what does that mean to you?
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I would say there's just a ton of money that's been invested.
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When you look at the profitability of Open AI and
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Tropic all, just all the companies out there, they're
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hemorrhaging cash, right? So you're on that front.
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You're probably going to have a shift in the model of the
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pricing model that goes to that and how you get those services.
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I would also say for corporations that have invested
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in AI projects, as you were saying, the 95% failure rate,
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it's a loose definition, but I would say most companies, at
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least ones that are profit seeking will look at projects
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like that and be you know what, maybe we should pull back on
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this a little bit. And we've seen these natural
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kind of ups and downs throughout history, especially.
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Is it? Kind of like the Internet
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bubble.com bubble. A little bit, I would say
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there's, there's hype. I mean, you got crypto, remember
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NFTS you've got. Those disappeared fast.
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Not crypto, I mean crypto block chains around here to stay for
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sure 100% technology, all that stuff.
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I even think Bitcoin and X are been also but but but the NFT
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wave hit hard and then it kind of just.
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And and you get a lot of excitement towards it and then
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it's kind of like, you know, you get the see that maybe we're not
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going to be able to do all the things that we thought we'd be
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able to do. We're not going to deliver the
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value as fast as we thought it would.
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And non fungible tokens are what NFTS are.
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For anyone that's listening, that's like, what the Hell's an
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NFT? Basically a kind of digital on
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the blockchain token type thing where maybe it's a concert
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ticket and it stamps it in the blockchain and it's there
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forever and you can't change it. You can't say whatever you own.
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If it's a digital piece of art, that's an NFT.
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If it's a a token, whatever it is, it's on the blockchain.
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And that was like a big, big, there was a hype train.
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But again, I think you'd probably agree.
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I think the technology is going to be here.
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There'll be concert tickets that are NFTS, if not already.
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There will be, you know, there's already digital arts.
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Like there will be a lot of things.
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But it's like anything, there's a massive hype cycle.
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Then it kind of comes down to reality and then it kind of
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suddenly builds back up again. Yeah.
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And I think that that that's actually a healthy part of any
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cycle. It's natural.
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It's humans. We follow these cycles over and
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over. We.
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React, it seems like, as humans. Yeah, we're, we're emotional
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beings, so we get very excited. There's nothing inherently wrong
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with that, but it's being able to step back and try to as
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objectively as possible assess the situation, you know, make
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informed decisions, rational decisions, not off of emotion
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where we've got a like we were saying the board, we got to do
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this. Yeah, I understand that's a
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feeling, but is that really the best use of our time, energy and
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resources right now? And, and so it's the idea
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though, is that like, it's, it's good because after you get
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burned, like I'll say this as an entrepreneur, I've made many bad
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investments after I get burned. After you get burned, you, you
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learn to be like, it's not that I'm not going to do it, but I'm
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going to be more diligent in how I assess the opportunity, how I
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deploy my capital resources or whatever it is.
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And, and that's what I think. I, I, I'm not alone in this that
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you get that. I think articles it the through
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of disillusionment where it's just you get punched, yeah,
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punched in the face and you're reassessing and then you come
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back and then you kind of hit that stability wave where, OK,
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we, we, we, we took some blows. We're going to be smarter about
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this. We're going to be more
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calculated in how we approach this now.
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So that's usually what it takes. And again, we this is nothing
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new. We've seen these cycles not only
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in the digital realm, but throughout human history.
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You've seen equivalent kind of waves of things.
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Remember the Tulip, what was it back in that was 16 hundreds or
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whatever it was? I think it was somewhere in
12:52
Europe where the the price of tulips went like crazy.
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I believe it was they went like $10,000 per Tulip or something
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like that. There was actually nothing
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fundamentally driving it was just more the perception of
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value, things like that. So interesting it's but we'll
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see another one too. I'm I'm positive of it.
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Oh, for sure. Yeah, man.
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Where you spend your time, money and resources.
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You mentioned that that is just the critical thing.
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Yeah. I think if you're listening
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right now, and I ask myself this all the time, Alex, where are
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you spending your time, money and resources, and does that
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align with where you want to go in your business and in your
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life? Totally.
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And if you just ask yourself that question every day, it's
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easy to start working on stuff that's like kind of easy or fun
13:27
or whatever it is. And then you're just like, but
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is this really the thing that I need to be working on right now?
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Is this the exact use of my time right in this at 9:00 AM this
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morning? You know, it's a good question
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to ask yourself. And I think it's it's humbling
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in a lot of ways because you're like, yeah, I guess I'm focused
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on this. This doesn't somebody else can
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do this or this doesn't need to be done now or urgently.
13:45
You know, 100%. You mentioned crypto or I guess
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we both talked a little bit about crypto.
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I know you're not, this is not necessarily your expert area of
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expertise, but I'm curious what you think about Bitcoin XRP.
13:56
Yeah, I would have, I would have said two to three years ago,
14:00
it's a joke. Like like seriously, I was like,
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yeah, there's there's no way. There's no way at all.
14:06
But you can't ignore the acceptance and facts that are
14:11
now staring us in the face about becoming a much more viable
14:14
again. This is reassessing our
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perspectives in the light of new information.
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And there's certainly a lot of momentum, positive momentum, I
14:23
would say towards these types of, of currencies becoming more
14:27
mainstream. So I would say that yes, they,
14:30
they are in my mind, are becoming much, much, much more
14:33
viable for everyday purchases. It's like this niche thing that,
14:38
you know, I, I wouldn't be surprised if in like 5 to 10
14:40
years my kids are using this stuff for sure to purchase.
14:44
I'd be shocked if they weren't. Yeah, Yeah, absolutely.
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And it's one of these things where I'm fine saying that
14:49
because it's one of those where, you know, you've got to be open
14:53
to, you have an opinion today based upon the information that
14:56
you have, but that information or that perspective can change
14:59
based upon new information that becomes available.
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And that's, you know, I remember when it first came out, I was
15:04
like this, this is hilarious. Like, because there's no, you
15:07
know, in the beginning, you remember there was like
15:08
thousands, thousands of them, you know, like which ones are
15:10
frauds are real. And I think for a lot of people,
15:14
at least the circles that I ran, and that's The thing, is trying
15:16
to figure out like which ones are legitimate, which ones are
15:19
not legit? How do you maintain the
15:21
legitimacy of this, right? I think you've seen a lot more
15:25
stability come to kind of these core currencies, so.
15:28
Bitcoin, XRP, Solana, Ethereum. Are you invested in some of
15:33
these? No, I am not.
15:34
Why not? I would say that I missed my
15:39
opportunity, maybe earlier, I'm not sure exactly.
15:42
This is where I don't spend a lot of.
15:43
Time. I know it's my area of
15:44
expertise. Yeah.
15:45
I know my area of expertise, but I am highly curious about it.
15:47
And sometimes you look at the valuations and the inherent
15:50
volatility that comes with that. I have a finance portfolio
15:53
management background. So I tend to be calculated
15:57
risks, very, very calculated risk.
15:59
And these are ones where I just have a tougher time putting my
16:01
finger on the risk profile assorted with these things.
16:05
And as a bootstrap founder, unfortunately I don't have the
16:08
time necessarily that to invest. Yeah, I get that to really like
16:11
understand what's what are the fundamental things driving the
16:16
volatility that right 'cause if you can't under so you always
16:19
have it pinned. But you want to have a sense,
16:20
right? Or at least feel like, hey.
16:23
Yeah. Be knowledgeable, understand why
16:25
the markets change and things like that.
16:27
Yeah. And I think that's the
16:28
opportunity. I think I think you're right.
16:30
Two or three years ago, I wasn't.
16:31
I was like, maybe I'll jump a little bit in there and see what
16:35
happens. But it was just felt very risky
16:37
and very volatile. And now what you're starting to
16:40
see with crypto is a few different things.
16:42
But I think once becoming global, the global economy is
16:45
starting to accept these things more.
16:47
The technology is so much better than the traditional systems.
16:51
It's payments instantly, there's lower fees, there's faster
16:54
transact. It's just like it's more more
16:56
typically more safe because it's on block chains and it can't be
17:00
tampered with and things like that.
17:02
And then you've got just like the political landscape, which
17:04
is just much more in favor, not only us, but across the world,
17:08
much more are in favor of crypto.
17:11
And so I think we're at this time very now where it's the
17:14
best time to get in because I think it's and I am not a
17:17
financial advisor or anything like that.
17:19
So please don't, you know, take this and like do your damn
17:21
research. But I am invested in these
17:23
things personally because I think it's a good time period
17:26
where we know these things are coming.
17:27
The hype train has kind of gone up and died down and now it's
17:30
steadily inclining or increasing, I think.
17:36
And I think, but we're still early enough to where most
17:39
people are kind of like we're like kind of like, I don't know
17:41
if I want to put money in this yet.
17:42
So it's early enough, but it's not late.
17:45
It's not too late either to where I don't know.
17:49
For me, it makes it makes sense. But to your point, the
17:52
volatility, you will if you're uncomfortable with it going up
17:56
and down every week. I don't think the swings are as
17:59
wild as they used to be, although they're still probably
18:01
coming. I'm sure they'll still be some
18:03
wild ones. Like be prepared, right?
18:05
Be ready if you're going to be in it for the long haul in the
18:07
next few years, I think you're going to be fine.
18:09
But you'll see it go up and down, up and down, up and down.
18:13
And if you're emotional or if you put money in there that you
18:16
really couldn't afford to put in there, you're going to hold
18:19
these. I need people panic.
18:21
People stole Bitcoin at 20,000 and now it's at 115 or 120,000.
18:25
So I mean, yeah, there's there's opportunity, but but with
18:29
everything there, there comes risk.
18:30
As well, I think you you highlighted the big thing for
18:32
me, which is the the kind of big check mark is the political
18:35
Yeah, right. You're getting political
18:36
acceptance on the notion that this could be an alternative to
18:40
the dollar and other. Yeah, that paper currency,
18:43
right? I think we're almost in a place
18:44
where it's kind of, you can kind of see the dollar and the old
18:46
currency. It's on a lifeline now.
18:49
You know, it's like probably a matter of time before it gets
18:51
phased out. Yeah, it just feels that way.
18:54
It's that's a reasonable, I'm not a fiscal policy.
18:58
Expert but. But it's one of those that as
19:01
you look at that, there's many moving parts in there.
19:03
But it, it seems like you've got that, that general direction
19:07
it's moving because you are seeing what is it payment
19:11
processors now I believe are starting to take crypto like
19:14
credit cards. If I like credit card
19:16
processors, I believe I I could be off on that.
19:19
Once you kind of see like these major checkpoints hit, yeah, you
19:21
need so much. Bank start.
19:23
Bank start, yeah, there's so much regulatory that's
19:25
associated with that. That's the tough part.
19:27
That it's, it's like, but if they start getting through those
19:30
hurdles, you're over, you're over the Mount Everest.
19:33
That would be the other category I didn't mention, which is the
19:35
regulatory oversight. It's starting to loosen up.
19:38
Banks are starting to adopt it. There's ETFs now for, you know,
19:42
the various cryptos. And that's a big deal, which
19:44
means kind of just everyday investors can invest in some of
19:47
these things without having to go directly to the the
19:49
cryptocurrency. It's going to be interesting,
19:51
man. Going back to the AI bubble,
19:53
what does it mean for the everyday founder business owner
19:57
that might be listening to this now?
19:59
Like how is it going to impact them?
20:00
Yeah, I, I would say that, you know, if your, if your business
20:05
is in this AI space, the first thing that I would say, I've
20:09
seen this happen a lot. You build a company real quickly
20:14
or it's maybe even something you've built over time.
20:17
And then Google adds that into their browser as an add on,
20:20
right? The very thing that creates the
20:22
opportunity in terms of getting the market fast, cheap is also,
20:26
I think it could also be your Achilles heel.
20:28
So I think it's very, very wise to be aware of that because
20:32
people tend to look at, in my experience and you know, I, I'm
20:36
around entrepreneurs pretty much all day and I talk to
20:39
entrepreneurs all day and they're like, I'm just going to
20:41
build this. And then we're going to, we're
20:42
going to do this and this and this.
20:43
And it'd be like one guy I was talking to, he was finding a lot
20:47
of success very, very, very quickly.
20:48
He made some great money on it, Very high profit, very
20:51
profitable business. He was looking at an exit.
20:54
He had built it in the span of like 9 months and was looking at
20:56
an exit and other people are looking to buy him.
20:59
Said what if Google just adds this and he's like, I don't
21:05
know, like they could do that. And basically the deal died.
21:10
And it's one of those now where he's like, I never thought about
21:13
that, but it's like Google can crank the stuff out like this.
21:17
And it's one of those things I would say just be cognizant of
21:20
that opportunity there. There's the flip side of that.
21:24
So it's, it's looking at, you know, I've had this discussion
21:27
with a number of people where it's not necessarily I'm, I'm of
21:31
the opinion that the data is the Moat, the data that you have is
21:35
the most like one of the things we do with labor Titan is we
21:37
have a proprietary data set around like what does an HVAC
21:40
technician today get paid in like the Chicago metro?
21:43
That's proprietary data. So I'll never be feeding that in
21:46
any online AI model or anything like that because that's our
21:49
Moat. The, the, the stuff that we put
21:51
on top of it. Anybody can copy that.
21:53
But. Can't anyone just find that
21:54
information? No.
21:56
So for like us is like if you're going to use like using the pay
21:59
data, most of the pay data that they use in the United States is
22:02
going to be if you're looking free, it's the Bureau of Labor
22:03
Statistics right now. That data is like two 2 1/2
22:06
years old. Yeah, which can be wildly
22:09
different than what it is today. Especially for certain segments
22:11
of the workforce. So we focus on the trades and
22:14
how do. You get the data.
22:15
So we start with that data, it's kind of like the flower and the
22:17
cake. And then we do a lot of
22:19
modeling, we'll say using probably 50 different data
22:22
sources. I'm a former data architect and
22:24
engineer, did a lot of financial modeling in my early days and I
22:28
built a basically a algorithm sequence to create from this
22:33
base data set, the BLS and then a whole bunch of other data sets
22:37
create an output. It basically makes an estimate
22:39
of like what's the market paying today for a job like in Saint
22:42
Charles and what do they get paid at entry median expert
22:47
level. And then we also do forecasting.
22:49
And so with forecasting, we're about about 9095% accurate if
22:54
you give like a 5% margin of error from where the BLS comes
22:57
out. So for us, that's the secret
22:59
sauce. It's not like what AI does to
23:02
our data because that, that anybody can copy literally in an
23:06
afternoon if, if you know what you're doing.
23:08
So that's what I would say to many of the founders here is
23:12
that, yeah, there's, there's a lot of great stuff that you can
23:15
do with AI. And again, this is just my
23:16
perspective, but but that, that mode is really what proprietary
23:21
data do you have? What are you collecting?
23:24
You know, when you're doing that back and forth with the
23:25
customer, you're collecting a lot of valuable data that's
23:28
defendable. Generally speaking, that's going
23:30
to be the defendable part. And that's what creates a lot of
23:32
the value. Like if I was investing or when
23:35
I'm assessing companies, that's what I look at is I'm not saying
23:39
that the tech is commoditized in in not that it's not valuable,
23:42
but you show me something and be like, I can copy that with a
23:46
team of engineers. You can copy it.
23:48
Maybe it was like 1,000,000 bucks before and I can copy with
23:50
like an engineer and a ton of AI credits.
23:55
It doesn't necessarily make it mean it's easier, but you can
23:57
compress the cost and the time frame to copy.
24:01
So as you're looking at that, you know you're you're looking
24:04
at to get back to our original point on the AI, you're looking
24:07
at what are the problems that we can solve, right?
24:09
And how does that create value for our stakeholders?
24:11
But then like how defendable is that?
24:13
Yeah, and I think any. Brand I think plays a role in
24:15
that too, right. What kind of brand have you
24:17
built and or are you building in the marketplace?
24:19
Because people don't just buy the thing, they sometimes buy
24:22
the brand or the feeling or emotion or whatever it comes
24:24
with. It totally Do I trust you?
24:26
Yes. Do I feel like you can help me
24:27
solve this problem? Maybe.
24:28
Does your brand give me something else, a status?
24:31
Does it give me a good feeling when I buy it?
24:33
Does it give me bragging right? You know, there's totally,
24:35
there's that type of stuff too. Absolutely.
24:37
You know, and that's like, really, really important, yeah.
24:41
I think if Apple can, if a company produced the same exact
24:44
thing as Apple, Macbooks, cell phone, whatever, but it had a
24:49
different label on it and it was $200 cheaper or $500 cheaper per
24:53
item, whatever it was, I still think people would choose Apple.
24:56
I would choose that just by default, you know, unless they
24:58
really spend days looking into, you know, just, I think you'd be
25:01
like this kind of the same thing, this Apple, this is
25:02
another brand you'd ever heard of.
25:03
They'd be like, I don't know if I trust that, you know, I'm
25:06
gonna go with Apple, I'll pay a little bit more, but it's cool.
25:09
I drive, I've had Apple, I know Apple, it's my ecosystem.
25:12
I've got it totally. You know, so that's brand.
25:14
But you, you did a recent LinkedIn post or a LinkedIn post
25:18
where you said you, you spent six months treating AI like your
25:21
coding partner. Yeah.
25:22
And here's what you learned about the gaps that get less
25:26
press among all of the hype. Yes.
25:29
Oh yeah. So, so I had fun with that one.
25:31
So, so it was one of those where.
25:33
Is that vibe coding? Vibe coding?
25:35
Yes. What?
25:35
Is vibe coding. So, so it's vibe coding as I put
25:38
it is it's having AI help you code.
25:42
That's the overly simplistic way where you give it a prompt, you
25:47
ask it to develop something and then it goes and it codes it for
25:50
you. So.
25:50
You don't need to be a coder. You don't need to be a coder,
25:53
but this is kind of what I was trying to get there too with my
25:56
post is that people assume that like a tool like a lovable,
26:02
that's what I use, is going to get everything right for you.
26:05
And that is a gross misconception because as you add
26:09
more complexity, it inevitably happens where the AI kind of
26:13
starts to get off the rails a little bit.
26:15
Then you can almost have like a butterfly fight.
26:18
You know how if you, if you like shake something and you move a
26:22
whip a little bit here in it, but then at the end it
26:24
oscillates a lot. It's kind of the same concept
26:26
where you make a little change here maybe, and then it could,
26:29
it could cascade through your solution.
26:32
So maybe you've got something that works like a really stable,
26:34
kind of like first build because it's simple.
26:37
Maybe you've got like just a basic interactive page.
26:39
Now you want to add payment processing, you want to add
26:41
login, you want to add credit consumtion, all these other
26:44
things. Well, every layer of complexity
26:47
you're kind of building, it's trying to build upon what it's
26:50
already done. And that's what I have found
26:54
where it starts to kind of get shaky, where you're like, OK, I
26:57
make this one simple change, but then bust the login or this one
27:01
change completely changes my database structures and I didn't
27:04
archive it. And now my old structures gone,
27:07
so I can't go back. And so this is the thing where
27:10
in talking to a lot of people that have tried vibe coding,
27:14
they go, that was not as easy as I thought it would be.
27:16
Like I did it in a lot of projects get abandoned because
27:19
they have the expectation that the AI is going to do this.
27:23
Boom, done. Perfect.
27:24
This works perfectly that. Was the case everyone would have
27:26
their own apps and companies and be worth a billion dollars you.
27:28
Know like 100% so so this is. Never that easy.
27:32
Well, and, and so I said, you know what I'm I'm gonna get, I'm
27:34
gonna give this thing a pretty good challenge.
27:35
So it's something I had built before.
27:37
And you've done coding before in the.
27:38
Past Oh yeah, you've done years and years in coding.
27:40
Pretty, pretty advanced stuff. Database architecture, design,
27:44
data engineering, all that stuff.
27:45
So I knew what I was doing and it was one of these things
27:48
where, you know, I, I, I was looking at, I was doing a lot of
27:52
geospatial analytics. So you put a pin down, you
27:54
calculate a drive time around it.
27:56
And then I wanted to pull in like, what's the population in
27:59
this area? What are the, what's the mix of
28:00
workforce, All these other things that were pretty basic.
28:03
You know, I was setting up basic API calls to like the Census
28:06
Bureau and I was using this software turf turf to do spatial
28:11
joints, things that weren't like crazy on the front end.
28:15
But we had database integrations and all this other stuff and
28:18
edge functions. And so we, I just started
28:21
layering it step by step by step.
28:23
And then as I noticed as I got to a certain point, like every
28:26
change was breaking something. So then I was having to actually
28:29
manually go in and be like, no, no, no, no, no, this isn't the
28:31
code. It should be this.
28:32
You're making the wrong table reference.
28:34
You're doing this wrong. You're doing that wrong.
28:36
And even after I tell it like, OK, you have a value of X, it
28:39
should be Y, it would still miss the mark.
28:43
So this is the thing where my, my point in that is saying like,
28:45
listen, nobody talks about like this dirty side of vibe coding
28:50
and saying like just expectation management.
28:53
You, you, you can go in there and you can do some of the basic
28:55
blocking and tackling, but you're going to get to a point
28:58
inevitably where you're going to need some engineering expertise,
29:01
you're going to need some programming expertise.
29:03
And it just be ready for that. And, and so that was the idea.
29:07
And, and there were a couple times I got stuck.
29:09
I'm like, I don't even know what the hell you built here like
29:11
this. This is, this isn't even
29:12
remotely close to what I wanted. So it's a process, as you know,
29:17
and I think with that is just understanding that you hear, I
29:22
built a fully functional healthcare management system in,
29:27
in one day. Well, you didn't account for
29:30
HIPAA or security or any of this other stuff.
29:33
So there's this entire layer of it's like, because you don't
29:36
know about it, you don't even know what's coming for you on
29:39
the Pike. And I think for a lot of people
29:41
that don't have technical backgrounds, it's those things
29:44
that sink their ideas. So it's just more, again, as we
29:47
said, when you're building something in AI, understand what
29:51
are you trying to do? Do the due diligence, have fun
29:53
with it. If you, if you want to build
29:55
that, if you want to build your AI, do it.
29:57
It's awesome. It's great to learn, but just be
29:59
aware that if you're expecting to get there in a week, probably
30:03
not going to get there, you know, And I'm not saying to be a
30:05
pessimist, it's more of a real a realist, you know?
30:07
That's I've never tried it, but that's kind of what that was my
30:10
mindset coming into it is that it's just never as easy as and,
30:13
and nothing's as easy as you think it's going to be.
30:15
You know, it's like entrepreneur, start a business
30:17
launchers easy, you know, quit your job, work your full time
30:21
job, just do your own thing. It's like, yeah, it sounds nice
30:24
and it is nice, but it takes a lot of work and sacrifices and
30:27
you're going to get punched in the face a million times and
30:29
you're going to have to get back up, guaranteed.
30:31
Yeah. What's the future for coders, do
30:34
you think? Like if you're in school right
30:36
now and you're going for coding, or you're going to go to school,
30:38
or you just got out of school, or maybe you're even a seasoned
30:41
coder right now, what does the future look like?
30:44
That's a really good question. I have this debate a lot with a
30:47
lot of people I respect that are experts in this.
30:50
And I would say for senior engineers, they're they're going
30:55
to be worth gold. They're always worth gold, but
30:57
especially so now because in my experience, these tools like
31:02
lovable right now are like junior programmer level.
31:04
They crank out good code. It's it's good, generally pretty
31:07
darn good, maybe little tweaks here or there.
31:11
They they need some redirection, but they're it's only going to
31:14
get better. I believe it's only going to get
31:16
better. The problem becomes is that it's
31:20
like this paradox because if I was a young kid, I want to learn
31:23
coding, but then I'm not going to be able to get a job really
31:25
because these things are doing it.
31:27
But then if you don't know coding, you're not going to have
31:30
the baseline capabilities that are needed to address the
31:32
problems I just talked about where the structures aren't
31:35
right, the code's wrong, so you don't know how to read and
31:37
interpret it. So, so this is where I kind of
31:40
go back and forth. I don't really have like a
31:42
solidified opinion yet, but I do think inherently just the mental
31:46
process of thinking about because it's, it's how do you
31:49
structure code? How do you think about it?
31:51
How do you set up tables? How do you, how do you make this
31:54
stuff work? So it's kind of, it's not just
31:56
about like the actual code itself, but like, what am I
31:59
trying to build? What are the, maybe those
32:01
modules look like within the modules?
32:03
What are those things, cascading dependencies and other things
32:06
that I need to make this thing work?
32:08
That's like the mental muscle of how do I want this app to
32:12
function? Because if you want to build
32:14
something in vibe coding, at least today, you got to
32:17
understand like what I want this thing to do.
32:19
And you kind of have to in the beginning try to give it some
32:22
guidelines and like this, this is the nature of what I'm trying
32:25
to build. So I would say that's really
32:27
hard to do if you don't know how to code, if you've never been
32:29
through like the process of developing these these types of
32:33
apps. So I would say learning to code
32:37
is inherently a good thing. I don't see a downside.
32:40
It's just how much time do you put towards that?
32:42
I think that's the big variable. And there are people that just,
32:46
they gravitate towards this stuff, they love it.
32:48
And you do still need engineers. You need a pipeline of engineers
32:52
to come from somewhere. So I would say, yeah, it's it's
32:56
worth pursuing. Just as with anything,
32:58
understand your career prospects in that particular area.
33:02
And it's changing so fast. Right now it's it's kind of hard
33:05
to say exactly which is the that's a very politician's
33:07
answer. It's a non.
33:08
No, but it's true, though it's hard to say.
33:10
Yeah, it's hard to say. It's really, really hard to say.
33:11
If I would say if my kids were looking at that, I would say
33:15
pursue it because you love it, but but have a backup plan.
33:18
I. Think just know how you fit in
33:20
the marketplace and how it's evolving fast.
33:22
Think be thinking about that. Don't just, like, I'm gonna
33:24
learn to code. And then, like, you get out and
33:26
like, three years from now and it's like the basic coding that
33:29
you learned is now being done. But if you learn, how would I
33:31
integrate with AI? What are some things I could use
33:33
as I'm in class, you know, that that would go along with this,
33:39
that would make me valuable to the marketplace.
33:40
And some of it is just hard to tell.
33:42
Some of it really is just hard to tell.
33:43
Yeah. But I can predict where we're
33:44
going to be in 5-10 years. 20 years, definitely.
33:46
Well, the thing I would say is going to transcend any of these
33:50
AI solutions is the ability to think.
33:52
And I know that sounds but like think critically, not like I'm
33:56
an order taker. Like come up with new ideas, be
33:58
creative, assess opportunities. Like how do you make decisions?
34:02
Those are invaluable skills. Like they are, they are worth
34:06
their weight in gold. I know if I'm hiring people,
34:08
that's the number one thing I am looking for is I don't care.
34:12
I can, I can get a ton of tools to do all this other stuff, this
34:15
commodity stuff. I need somebody to help me think
34:19
through problems, think through solutions.
34:22
That's and that, and that takes time and, and, and unfortunately
34:24
the educational system doesn't really teach you that as well as
34:28
maybe like real world experience does or a startup.
34:30
You, you learn this very quickly in the startup world.
34:32
You know, you're like, you learn how to, how to assess the
34:35
opportunities and decisions, things like that.
34:37
So Speaking of the education system, you went to Notre Dame,
34:40
is that right? Yeah.
34:41
Do you think looking back and and now, do you think college
34:45
has become a scam to a certain degree?
34:47
I have a pretty strong opinion on this.
34:50
So, so I'm going to be a hypocrite by saying I went
34:53
through the educational system at both the undergraduate and
34:55
the graduate level. So I am, I'm biased in that
34:59
assessment. But I would say from a factual
35:04
basis, the the ROI for traditional white collar jobs,
35:10
it's becoming much, much more difficult to justify the
35:15
investment. It's like one of the things I'm
35:16
building right now is a college ROI tool.
35:19
So basically you're going to go to school.
35:21
Here's here's what you want to go into.
35:23
Here's the schools that offer these particular programs.
35:26
Here's the different degrees I have upon graduation of this
35:30
degree, Here's the typical jobs you can get.
35:33
And of these jobs in the market that you're looking at, here's
35:36
what they tend to pay all across entry, median expert level.
35:38
What we're trying to do is give an idea of if you get a
35:41
literature degree, OK, and you want to go to the New York area,
35:45
here's kind of jobs you can get and here's what you can probably
35:48
earn over the first five years. Focus on just the first five
35:51
years because after that it's kind of who knows, who knows,
35:54
But you know what your investment is.
35:55
You have a pretty good idea of what your earning potential is.
35:58
And the idea of the tools to just give people an impartial
36:01
resource to honestly assess the earning potential of of
36:06
different careers and and answer that fundamental question is, is
36:10
it worth it? You know what a?
36:12
Great way to approach it. Yeah, We need to start
36:14
approaching it like what is the ROI or return on my investment
36:18
if I were to make this decision the same way we do if we buy a
36:20
house, if we invest in the stock market, if we choose a right
36:23
partner. Is this the right partner?
36:25
Is this the right thing for me? Should I make this move?
36:27
What are the pros and cons instead of just saying go to
36:29
college because if you don't you're not going to get a job?
36:32
And so to that point, this is what I say in my bias.
36:35
I I naturally want to say to my kids, because I did it, you're
36:39
going to go to college. Because when I was growing up in
36:41
my parents generation, that was a differentiator.
36:44
It created opportunity, incremental opportunity.
36:47
I would say it's unquestionable in my generation and in your
36:51
generation I would say, yeah, it still did.
36:54
I'm not convinced in this generation that it's there
36:57
because the nature of white collar work and I do delineate
37:00
between blue and Gray collar work, which is a totally
37:03
different animal. Like we got a major problem on
37:05
that side. Gray What's?
37:06
That Gray like a CNC operator, right.
37:08
So you're using you're using engineering things like that,
37:11
but you're also using your hands for things.
37:13
And then you've got like your, your trades.
37:15
What's the trades? We've got pretty big
37:16
infrastructure problem on our hands in the United States.
37:19
We don't have the people to do it.
37:21
And so it's one of those where when you look at the ROI of like
37:24
trades in general, traditionally they they have been looked down
37:29
upon. And I would say that is not true
37:33
at all anymore. And the problem is these legacy
37:36
perceptions persist. Most people think like as an
37:40
example, most people think a plumber will make like 30, Forty
37:44
$50,000. Not the case.
37:47
Not at all. I and I, I have numbers to show
37:50
this and I try to share it with people, but I talked to a guy
37:53
and I was like, how much do you mean how much do you make?
37:56
If I'm over 7 bounds, let me know.
37:57
But he's like, yeah, no, I made like $275,000 ish last year.
38:01
I was like, what did you work overtime?
38:03
And he's like, no, I don't need to.
38:04
I go fish on the weekends. I'm going, how much do you think
38:07
you can make if you worked all the time?
38:08
He's like, I probably make $400,000 like just in pay mainly
38:13
benefits, things like that. So the point is, is that like
38:16
people don't have optics to these things.
38:19
And the, the reason why to bring it back full circle to is the
38:22
ROI there. I, I, I don't think I'm alone in
38:25
this. I've talked about this for a
38:26
number of years about how the nature of our, of educational
38:31
ROI is changing. And so you've got these legacy
38:35
perceptions. We need to challenge those with
38:37
facts and then also for these other jobs that are very viable
38:41
career paths because college isn't for everybody.
38:43
A traditional four year college is not for everybody, but a lot
38:46
of people get pushed into that. And it's like, what if you could
38:50
do the thing that you want, make more money than your white
38:53
collar alternative that your parents may be pushing you into?
38:55
Oh, and not only that, you have to payless money to get that
38:59
degree. And what it comes down to is
39:01
it's just kind of one of the core ideas that I like to
39:03
operate from, which is information, giving people
39:06
information so that they can make informed decisions and not
39:11
letting biases take over because biases are crazy powerful.
39:15
So I was all over the place there.
39:16
But to bring it back is that I just, I'm not convinced that
39:19
college, traditional college especially is delivering the ROI
39:24
that was there like it did in the past.
39:27
Yeah, I agree it's become more costly and delivers less ROI and
39:31
yet people are being forced into it.
39:32
Still not forced into it, but pushed influenced into going to
39:35
the to college. It doesn't feel like it's a
39:38
problem that our government wants to solve.
39:40
I would agree. So I've talked to a lot of
39:44
people about this. I've not met one person that was
39:46
like, I think college is the institution of college and
39:48
everything around it. Nothing should be changed.
39:50
It's perfectly fine. You've got 2.
39:52
You've got people on one side where it's like college is a
39:54
scam in most cases, and on the other side you've got people
39:57
that are like, I think it needs some pretty deeper form and I
39:59
think people need to assess if it's really worth their time.
40:02
I don't see anyone on the other side being like, I think it's
40:04
great. It's good for everyone.
40:06
If you're getting them, you're going to school for marketing or
40:09
to be an analyst. Or you know, sales or business
40:12
or entrepreneurship. What is the point?
40:14
Like I I don't see the ROI there when you could probably go
40:18
online, build your own personal brand, start your own side
40:20
hustle, make money, have zero debt and get better hands on
40:25
experience in real world shit what do?
40:27
You think about it, it's like, I mean like like I think I think
40:30
you're on to something. And think about this.
40:34
When I was going to college, there really wasn't online
40:37
alternatives. No, the Internet, you know.
40:39
Like Khan Academy didn't. Sorry so.
40:40
No, go ahead. But, but like the Khan Academy
40:42
didn't exist, YouTube didn't like, I can I see now what you
40:46
can learn online. And it's, it's like one of those
40:50
things where you're learning, you're, you're pursuing that
40:52
knowledge out of genuine interest.
40:54
Now, like I have to take accounting.
40:56
I got to do this, which don't get me wrong, there's, there's,
40:58
there's value in that, but you're paying a lot of money for
41:01
something that's kind of like, do I really need to know this?
41:04
And again, this is just my philosophy.
41:06
I'm not saying it's inherently right or wrong.
41:07
It's just my view of the world. But but you were going to say
41:11
sorry guys. No, I just, it just feels like
41:13
college, the institution is an old sort of slow, outdated model
41:19
that just hasn't adjusted with the times.
41:22
We haven't looked at it and gone, OK, there's the Internet
41:24
now there's YouTube, now there's personal brand, there's social
41:27
media, there's AI. Are we taking care of our kids?
41:32
I mean, that's what pisses me off about this is because I have
41:35
kids. You have kids, right?
41:37
This is our youth. How do we not care about our
41:39
kids? How do we not care about their
41:41
education? And I think there should be some
41:44
form of like a decent path for a free education if you want to
41:48
continue on at a certain level and then if you want to pay for
41:51
something, great. But are we assessing, especially
41:54
if they're public and state ran schools, we should look at that
41:58
almost like we're running a company and say what?
42:00
What's the bang for the buck that these kids are getting?
42:02
I just think it's sad to me that kids are in their 20, late 20s
42:05
or 30s still paying off college debt.
42:08
They have a job that their college degree did not really
42:11
influence them getting it all. It's not even in the same field
42:14
in most cases. And here they are.
42:16
They have a mortgage when they leave college, they're 22 years
42:18
old, they're in all this debt right off the bat.
42:21
It's like man. You know.
42:23
That's not serving our youth. Well, you, yes, that was kind of
42:28
the impetus of this college ROI thing I'm talking about is I
42:31
have a friend whose daughter went and got an art degree and
42:36
she paid $300,000 for a degree, didn't understand upon
42:40
graduation what her job prospects were.
42:44
And she's got a job now that pays, you know, $35,000.
42:50
She's never, she's never. She's like, I have to live at
42:51
home. I can barely make my interest
42:54
alone. That's it.
42:55
You're spot on. That's it.
42:56
She's like, she can't start her life because no, she was just
43:02
duped by the system. And that's where I was like, we
43:05
got to do better than that. Like you, you can't be you.
43:08
And you also as an individual have to go $300,000 for an art
43:10
degree. Maybe I should rethink this.
43:12
Therein therein lies giving people the information.
43:16
OK, before we jump in the shark infested waters and.
43:19
Needs to. Maybe we should think about this
43:21
a little bit. So, so again, it gets back to
43:23
that's great you want to do that.
43:25
Let's run the numbers. Let's see what they work out to
43:29
and let's understand what can you actually make?
43:32
Because sometimes with with kids and even parents, they get so
43:36
enamored with like the idea of a degree from an institution that
43:39
they don't take a step back and realize that this four years
43:42
might be great. But then am I hamstringing my
43:44
child to get on their own, start their own life, buy a house,
43:49
right. Because the other thing is too,
43:50
is I do believe that this trickles into economics because
43:53
you're, you're, you're procrastinating people's ability
43:56
to get out and actually contribute to the local economy
43:59
instead of paying off student loans that are exorbitantly
44:02
priced, right. They, and they did sign up for
44:04
those loans. To be honest.
44:05
They they, they took that responsibility.
44:07
So it's a complicated conversation.
44:08
Yeah, but in most cases they're 18.
44:10
It's like, you know how you're at 8, You're not thinking about
44:12
bigger picture or type. You're like, sure, I'll pay it
44:15
off later, whatever. You know you're 18.
44:17
Totally. I mean, I think about like 30.
44:19
I was still figured I'm like. Exactly, Exactly, dude.
44:22
Exactly. And yeah, no 100.
44:25
And you're right, it plays into why do we think kids or adults
44:29
in their 20s and 30s are forgoing having kids or waiting
44:32
longer to have kids until they're older?
44:34
Why are they buying houses later?
44:36
Now? I think the average age is like
44:37
mid the late 30s when people for our first time home buyers, all
44:41
of this plays in a role that they're coming out of college
44:43
with. There's all this debt.
44:45
They're like, I got to pay off this shit before I can do
44:47
anything else. And I got to have a good job
44:48
that allows me to take care of myself and my family.
44:51
And so it's kind of crazy. I wanted to ask you because on
44:54
your on your LinkedIn banner, you say win the battle for
44:58
talent. Yeah.
44:59
How do companies win the battle for talent?
45:01
And what does that even look like now with humans versus AI?
45:05
Yeah. Well, it's changing very, very
45:06
quickly. So when I say win the battle for
45:08
talent, a lot of times specifically for the areas that
45:12
we we focus on, which is, as I said, Gray and blue collar type
45:16
jobs in general, they they tend to be a little bit more price
45:19
sensitive in terms of pay than other like white collar works.
45:25
They still get benefits, still do all that other stuff.
45:27
But you know like forklift driver, forklift driver would
45:31
move for 1/4 an hour is that? Because the pay is lower.
45:34
Pay is lower generally, there's more substitutes for certain
45:38
types of jobs, and typically they tend to be clustered
45:42
together. So you go to like an industrial
45:43
park, Elk Grove Village. Right, that's the hub of the
45:48
industrial. Parks totally so you go there
45:51
and they're driving by and they're like I'm making 14 bucks
45:53
now I can make, you know 15 there they're moving like that.
45:56
So one of the things that I like to help companies with is to
46:00
calculate, OK, like and understand if we were to pay
46:04
having a big turnover problem, if we were to pay a dollar an
46:07
hour more, what would the cost of that be?
46:09
Then? What's the cost of our turnover?
46:11
And then you just do that basic mathematical exercise.
46:14
Cheaper to pay more sometimes. Exactly.
46:16
But as, as with all of the, a lot of the themes we come back
46:18
to is it's doing the analysis, having the numbers to
46:21
understand. So it's not just like, no, we
46:23
can't pay that. Well, there's an opportunity
46:25
cost of that and that like you're paying, maybe you're not
46:27
paying the dollar an hour or more, but you're paying five
46:30
times that in turnover cost and lost productivity as an example.
46:34
There's a real situation we dealt with this company was
46:38
thought that they were paying very competitively up in Elk
46:40
Grove and they were paying like I'm making a number of 17 bucks
46:44
an hour and they're like, well, you know, for our peer set
46:48
that's really competitive. And I go, you're right, it is
46:50
very competitive for the manufacturing skill set, but
46:53
you're surrounded by a bunch of distributors that pay 20 bucks
46:56
an hour. So this is where it's
46:58
understanding market rate and this is where one of the things
47:01
you do a lot with like these groups, you get an association
47:07
and they survey their members, but it's a sampling bias because
47:10
it's all manufacturers. You're not getting a real market
47:13
sample. So if you're like, OK, we're
47:15
really competitive in our view of the world, but you're
47:18
surrounded by a whole bunch of other people that pay more,
47:20
you're going to lose, even though you have the perception
47:24
that you're competitive in the market, but you're competitive
47:26
to your peer side. So what we do is that's whereby
47:29
focusing on the market pay, we can say, yeah, yeah, no, we
47:32
understand. Keep your survey.
47:34
That's all great, but here's what the market's paying right
47:37
now. Now, whatever you choose to do
47:39
that information, that's your choice.
47:41
But at least you know, hey, this is what you're, you need to pay
47:45
to win in this market. And we do a lot of industrial
47:48
site selection. You're going to open a new plant
47:50
in an area that you don't have a presence in.
47:52
This is a very important question we got to understand,
47:55
like how much does the talent that we need cost?
47:58
1, is it available? 2, where is it coming from?
48:01
Three, can we afford it? And then if if you've got
48:04
automation initiatives like, OK, well, then you can do the
48:07
calculus to say like, well, we're going to spend $10 million
48:10
in equipment. The people we need aren't there.
48:12
We really like the land. So we might have to up that
48:14
investment to 15. I'm just making numbers up.
48:17
So what it comes down to is just having clarity because for many
48:21
jobs, pay is going to be a major determinant.
48:24
Do you keep those people or not? And so that's kind of the the
48:28
long winded answer to how is information is power.
48:31
That same thing again, you know. So Jason, outside of pay, if you
48:34
had to sum up in one word why employees leave companies and go
48:39
to other ones, what would you? What would that culture culture?
48:42
Culture. You have a crappy boss.
48:43
I don't care how much you pay any if I got to go in every day
48:47
and I'm getting anxiety from having to deal with my Co
48:49
workers or a pain in the butt or my boss is up in my grill every
48:53
single day, even when I do something, well, I'll I'll take
48:56
less pay to go somewhere else. I've been in a situation like
48:58
that where I despised my manager and I'm just like, I couldn't
49:03
pay me enough to work here. And I actually don't even.
49:06
And I think that's that's pretty common.
49:08
You know your, your manager specifically can make or break
49:11
your, your experience and you're spending most of your waking
49:13
hours in this environment. I would say it's going to be
49:18
culture. What's your What's your take?
49:19
No, I think that's, that's what I was going to say.
49:21
Yeah. Management culture, I think
49:23
purpose ties into that. The mission, you know, do you
49:26
feel fulfilled by what you do? I think it's kind of a
49:28
combination of those things, right?
49:30
How you what is the environment you show up to and what does it
49:34
do to you internally? You know, does it fulfill you?
49:36
Does it make you happy? Doesn't.
49:37
I think that's a big factor. So there's lots of talk about
49:41
about unemployment going significantly higher.
49:45
You know, some people talk employments, unemployment is
49:47
going to be 1015, twenty, 25% in the next few years.
49:51
With AI taking a lot of these jobs or a minimum displacing
49:54
people and creating a lot of change.
49:56
Do you think that's going to happen, and if So, what do we
50:00
do? Yeah, I don't, I don't know.
50:02
I'm still forming an opinion on this, just.
50:04
Looking at Crystal. Ball.
50:05
Yeah, crystal ball. I would say, as with anything,
50:07
in the same way that AI was going to save the world and do
50:11
everything we found out that's not necessarily true.
50:13
I'd say it's probably the same. There's these grandiose visions
50:16
of how it's going to replace everything, but there's many
50:19
rudimentary things that it's terrible at.
50:22
So I would say no. The nature of work changes.
50:26
You know, as we talked about, it's not that you're not going
50:28
to need coders, you're just going to need less of them to do
50:31
XY or Z in the same way that I was talking about.
50:34
This relative was telling me about how back in the day I
50:39
never used a typewriter really, but people with typewriters
50:41
versus word processors, we didn't need the typewriter that
50:44
the work still was getting done, but it just changed the nature
50:47
of that type of work. I would say that I do think with
50:52
the workforce challenges that we have as going back to kind of
50:54
that infrastructure challenge that we've got in the United
50:57
States, which is very significant.
50:59
We had we had a lot, we got a lot of work to do.
51:02
In addition that is you're looking at, you know, reshoring
51:06
near shoring, all these other things related to manufacturing
51:09
and trying to bring that back. I think that you're going to see
51:12
a lot of kind of more emphasis put on kind of these jobs that
51:15
were maybe less glamorous or less focused on before.
51:20
White collar work will always be there.
51:22
I do believe that. I think we'll just need maybe a
51:25
slightly less people on that. But yeah, you do hear a lot
51:28
about people that are they just just stopped looking for work.
51:32
Yeah, because they don't know where to go.
51:34
They don't know what to do, I do believe.
51:36
Think that's gonna be a big piece of it, just feeling lost.
51:39
Feeling. Lost and not really knowing
51:40
where to go. Yes, and then?
51:42
Yeah, I was just gonna say you got the obvious things like kind
51:44
of like the analyst and the people that if you're just like
51:46
looking at spreadsheets, type different information, moving
51:48
things around, like that's something that I can probably do
51:51
pretty damn well. Yeah.
51:52
You think about the Waymos, you know, take an Uber, you know,
51:55
like the autonomous driving, you know that there's a lot of Uber
51:58
drivers, right? So, but again, at some point
52:01
there weren't zero and then they all did something else.
52:03
Yeah. So and then you got.
52:05
But even it's interesting when you think about like, OK, truck
52:08
drivers, you know, they're going to be displaced, let's say, for
52:11
example, by AI, because AI is now just driving the trucks
52:14
themselves. But there's also a big
52:16
infrastructure that would need to be built for that to happen.
52:19
You and how are they going to charge if it's electric or I
52:22
assume it's electric, if it's gas, how are they going to pump
52:23
the gas? You know, you would need
52:25
basically wireless charging, which is out there, but it's not
52:28
readily available across the entire country.
52:29
And there's a million trucks. I mean, there's the amount of
52:33
trucks that are out there. So people are like going three
52:35
years are not going to be like it's not going to happen that
52:37
fast. It's going to be a slow build.
52:40
And I think that's kind of the the theme of this is that yes,
52:44
exciting times, maybe a little crazy times coming, some really
52:48
out of out there technology, but it doesn't happen overnight
52:51
typically. No, I think the macro theme that
52:54
will impact the workforce, but also a lot of the capabilities
52:57
to do those things is, is actually power.
53:00
You've got data centers, AI can choose Gorgantrin amounts of
53:04
power you're you're going to need.
53:07
As far again, I'm, I'm out over my skis a little bit, but logic
53:10
would say, especially in areas like Texas, you're, you got
53:13
brownouts that are common down there.
53:14
They don't have the power infrastructure to do that.
53:16
Where's the power going to come from?
53:17
Because power plants take a lot of regulatory approval.
53:20
You know, who knows with nuclear power, what's going to happen in
53:24
that capacity? And do they even have an
53:25
appetite for that? I think I think we probably
53:28
will, but but without power, you, you can't, you can't do a
53:32
lot of this stuff. I mean your EVs, they require
53:35
power. And then you've got increasing
53:36
just residential demand in general and you've got data
53:39
center demand and then the water that comes from that.
53:41
It's a lot of like when we talk about infrastructure, I think
53:44
that's a lot of the stuff that we're talking about.
53:46
But you need people to do that stuff.
53:48
You need people to, to build, to dig, to trench, all that stuff.
53:53
And that has to come first to, for, for the kind of the larger
53:56
scale stuff that we're talking about.
53:58
And that doesn't happen quickly. I mean, I'm going to guess it's
54:01
probably a decade, 2 decades worth of work to really get all
54:04
the stuff in place. But you need people.
54:07
Yeah. And The thing is is you've got.
54:10
I don't. We have humanoid robotics up
54:12
there. Yeah, yeah.
54:13
But. That's probably like 1520 year.
54:15
I think that's a little ways out that would be.
54:16
For, for, for. At scale, you know, but you see
54:19
them doing laundry now and you see them doing household stuff
54:22
and I think they're 10 years out from having robots being in the
54:26
in the household somewhat commonly.
54:28
Maybe not everyone has them, obviously, but like, you know,
54:30
you occasionally go to someone's house that has some money and
54:32
they've got a humanoid robotic there doing laundry and doing
54:35
dishes and stuff. And it's weird, I just, I'm
54:36
waiting for Skynet to come alive, you know?
54:38
Dude, seriously, it used to be we used to watch Terminator and
54:41
be like, that's so crazy and like that.
54:43
Now it's like and 30 years I could kind of it is kind of
54:47
wild, but it's impossible to project 50 years out or 100
54:50
years out. But I do get concerned when you
54:53
get that far out and you start thinking because it's it's all
54:56
good when you still need people. But what happens when you get
54:59
the humanoid robotic that's like go do this.
55:01
And then it's just kind of doing the thing.
55:03
And it's like, man, we're living in A and what if they just say,
55:06
I think the problem is humans are kind of you guys are kind of
55:09
causing more harm than good. Maybe you're not needed here.
55:12
What if we eliminated the heat? You know, it's like, it's just
55:14
like, you don't know. I don't know, you don't know,
55:16
but like. Not out of the question.
55:18
Yeah, like even before that is the question of even if robots
55:23
could do all the work, would you want them to like as at that
55:28
point you probably need a universal basic income, which
55:32
that's scary. That's.
55:33
Scary. Too way bigger than.
55:36
Is that good for people? They're just kind of sitting
55:37
around and collecting money. I don't think that's good.
55:39
For people that and then the broader idea of like purpose.
55:42
I can't what I mean, yeah. How many people I've talked to
55:44
that are in retirement, they're like, I can only play so much
55:46
golf. Yeah, I need to do something
55:49
like the circles of people that I run.
55:51
Yeah, I want I need purpose, yeah.
55:53
And. Community too, yeah.
55:54
Community, yeah, that's it and and you think for a lot of
55:56
people that's how they get their community right now is is
56:00
through work or whatever it is. So yeah, it's it's it's a it
56:03
sounds like a great idea. I'm not convinced that it's
56:06
something that I would want. Maybe that's because it's the
56:08
world that I was raised in and I just know this but.
56:11
But that purpose thing I think becomes a very significant
56:15
concern culturally, even for people's individual mental
56:19
well-being. That's a big change.
56:22
It's a really, really, really big change.
56:23
And I'm not sure just because you can, you should.
56:26
I can make arguments against that very easily, but just begs
56:29
the question that you just doesn't always mean it's the
56:32
right decision to make. Yeah.
56:34
Jason, what is your purpose and why do you do all these
56:36
different things that you do in business and your life?
56:38
Like what drives it all? And has that changed over the
56:40
years? Yeah, well, I I take genuine joy
56:43
in kind of helping people. It's it's for me, it's like we
56:46
met the energy like bringing energy to a room as a yeah, you.
56:49
Do man. Is is right away.
56:51
Yeah, you see it too. There's there's people, there's
56:53
energy vampires, people that you leave their presence and you're
56:56
like, that's true. I feel drained.
56:59
I try to be an energy giver and, and that manifests itself in
57:02
many ways, shapes or forms, not through like blind optimism, but
57:06
being like, Hey, this is a problem.
57:08
We can do this or how can I help or whatever it is.
57:11
It's a, it's a life philosophy that has served me very, very
57:13
well in life. You, you make the contribution
57:17
with no expectation of anything in return.
57:19
And then like people ask me all the time, like, how do you get
57:21
so lucky with all this great stuff that happens to you?
57:23
I'm like, it's a karma boomerang.
57:25
I don't know. I just throw it out there and
57:27
help people out and it comes back, comes back.
57:30
It usually does. I'm not expecting it, but but
57:33
you know, it's one of these things like, you know, 10
57:35
seconds after meeting you, you're laughing, doing things
57:38
like that. And so you could, it's like
57:39
setting the stage that like, I want this to be a positive
57:42
experience between US and people's sense that.
57:44
But the thing that I've found is that it's rare.
57:48
And so, so I found it's helped me in developing relationships,
57:52
earning trust quickly, things like that, and just trying to be
57:55
a force for good in a world that tends to be kind of a Debbie
57:58
Downer, you know what I mean? People need that.
58:00
And it, it's, it's fulfilling. I was telling a buddy of mine
58:05
that so do you do it for altruistic purposes?
58:08
And I'd say, well, yeah, but then but I'd be lying because
58:11
it's selfish then, because I also enjoy I agree having that,
58:14
you know, so it's kind of a Nazi 100% Yeah, but like if you.
58:17
Were to go to help a family that maybe had fallen on tough times,
58:21
right? And you were to see a family.
58:22
I've done this before. We've all done this before.
58:24
You see a family, they've got kids, tough times are going
58:27
through. You help them out at Christmas
58:28
or a random act of kindness, give them some money for
58:30
whatever. Sure, you can say that's
58:33
altruistic, right? But at the end of the day, it
58:35
made me feel good, like it filled my soul a little bit, you
58:38
know? And so you can say that's
58:39
selfish. But if that's the case, I wish
58:41
everyone was selfish. Yeah, it's exactly, totally
58:44
100%. Man, I'm OK with whatever your
58:45
motive is. If you're helping people and
58:47
doing good in the world, I don't give a shit what the motive is.
58:50
And we all, we all are selfish to a core, you know, saying we'd
58:53
like to see our kids do well because it makes us feel good as
58:55
parents and proud to see them do well and we feel happy that
58:57
they're happy. It's like it's all comes back to
58:59
that. You know, but it's, it's, it, it
59:02
charges for me, it charges me back up And, and it's, it's like
59:06
just, it's connecting with people like that 'cause it, it
59:09
can be hard. And there's also too a lot of
59:11
people that are seeking that they can't find it.
59:13
And so when you're that beacon, people gravitate towards you.
59:17
And this is I, I, this is one of the things I'm trying to teach
59:19
my kids is try to be that, that, that positive force because
59:23
people will find you. The type of people that you want
59:25
to associate with will find you and and good things tend to
59:30
happen, you know? Exactly.
59:32
Yeah, Jason, this has been an incredible conversation, man.
59:35
I've really enjoyed this dude. Where can people go to find you,
59:37
connect with you, learn more about what you guys do?
59:40
Yeah, absolutely. So Labor, titan.com, I'm also
59:42
pretty active on LinkedIn. I'm starting to start back up,
59:45
probably working with you soon here.
59:47
But yeah, I just love having great conversations like this,
59:50
talking and challenging my preconceived notions and ideas.
59:54
So healthy debate, there you go. Healthy debate is very good.
59:57
Yeah, I agree. I think we need more help.
59:58
Conflict in in politics and economics and these types of
1:00:03
settings, talking through problems in a healthy way.
1:00:07
I think we need more of that. So shouting at each other, yeah.
1:00:09
Well, hey, thank you very much. I appreciate you coming on.
1:00:11
Thanks, Jason. Thanks.