Latest / Nonsense with cj little and Jeff Parker / AI's Impact on Employment and Wealth

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AI's Impact on Employment and Wealth · Nonsense with cj little and Jeff Parker

• 0:00
  Welcome to nonsense Season 4 episode 3, our big story on our
• 0:02
  second show of the week. I'm Jeff Parker.
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  I'm still this time we're looking at a eyes impact on
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  employment and wealth up next. Do you feel like AI, is this
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  giant meteors gonna come crash to Earth or do you look at it as
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  like the sun just providing us with energy and like giving us
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  fuel for our life force? How do you?
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  How do you? Neither.
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  Absolutely there. I look it as the sun, but boy,
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  it's just not quite close enough to the planet and I'm freezing.
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  Can it get here a little quicker?
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  Sure. AI is a tool.
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  That's all it is. AI is nothing more.
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  It's nothing. It's an.
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  Amazing tool. I agree with you with this is
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  gonna be an excellent episode. I'm not even sure it's amazing
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  yet. I'm waiting for the amazing.
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  I agree. With you on that, I think it's
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  got a long way to go, but you can already see.
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  I mean, the Internet was not amazing when it first came out.
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  You're like, yeah, but I see the same, the same AI, just just
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  much, much, much, much, much faster.
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  That's what's nuts to me is the made of change and how much
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  faster you're seeing those. I have seen aspects of AI, I've
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  seen AI effect, sure. Certain areas like coding where
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  it's, it truly is amazing. Yeah, I'm pretty gobsmacked at
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  the quality of the coding. It's all the fast.
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  It's gotten to be the quality that it is now.
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  That part's incredible. But there are other things where
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  it's just like, wow, sure, this is just not moving quickly.
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  Is AI gonna make us richer? Or poorer?
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  Yes, like poor. The answer is yes in aggregate.
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  If you look at average per capita, sure it will all go up,
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  but average means nothing. What's your how to look at is?
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  Median. Median, of course.
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  Median GDP. That's the number you actually
• 1:22
  care about. That number could potentially go
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  down I. Love it.
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  I'm excited about this. OK, let's figure out how we're
• 1:26
  all going to lose our jobs. Now, OK, how AI disrupts jobs.
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  Let's go. Disrupts is a big word for
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  takes. In 2026, AI is no longer a
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  future threat. It's an active economic engine.
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  While it automates nearly 70% of routine office tasks, the
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  disruption is more nuanced than mass unemployment.
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  We are seeing a junior crisis where entry level roles in
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  coding, law and accounting are hollowed out by agentic AI.
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  However, this efficiency fuels a net gain of 78,000,000 jobs by
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  20-30, shifting humans from doers to orchestrators.
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  Wealth, however, remains A flashpoint.
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  As productivity skyrockets, gains disproportionately accrue
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  to capital owners and AI fluent super users, threatening to
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  widen the global inequality gap. The 2026 landscape has a high
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  stakes transition, a world where expertise is cheap but human
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  judgment and creative strategy have never been more expensive.
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  Now I think this should be like a free for all conversation
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  where we just let it go wherever it goes.
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  Whatever comes outcomes out well.
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  You got the right guy for the job.
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  I thought so. Oh boy.
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  No rules. Oh, let's go.
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  OK, this is going to be a disaster.
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  Like if anything shiny happens to float into the room while
• 2:46
  we're in here, we are doomed 'cause you and I will just be
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  like, look at that over. There I wonder.
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  Is that a chemtrails? Is that a kind of where's that
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  plane going? And I got flight radar out and
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  look at where the planes going. Yeah, we're gonna be just fine.
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  And that's how the AI episode came to be about dogs.
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  Literally the. AI listening to us is gonna be
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  like, these guys are gonna be very easy to replace, I feel
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  like. This is not a.
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  Harder give me give me a harder give me something hard.
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  Come on. Fascinating.
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  Obviously there's a lot of people talking about this.
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  I feel like there's a lot of elements here to unpack.
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  I certainly there's a couple there You highlighted
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  specifically the the quote junior crisis thinking about
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  what value humans bring. But there's so many things here
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  to talk about that are that are interesting.
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  Can I start us off please? Most of what I see when I see
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  YouTube videos about this, when I see news report the it's all
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  fear and terror and the future is coming.
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  There'll be no jobs, it's an apocalypse and that's just not
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  my point of view at all. Yes, AI will literally make us
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  more wealthy, period. Yes, full stop.
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  It's really interesting to think about it because I agree with
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  you on this, by the way it feels, it all feels like like
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  FUD, right? It's this fear.
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  There's uncertainty. We have so much doubt about the
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  future. And I also to understand that
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  you want to, you want to gather clicks and you want to people
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  to, to click on your thing or listen to your thing.
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  So that's more exciting. But then I get into the
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  messaging and the messaging is still the same.
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  They're just like, well, all these things are going to go
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  away and that's the end. You know, like, sure, you
• 4:00
  listener can infer from this what you want, but you probably
• 4:03
  are going to infer that the world is over and everything
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  collapses on itself. It's not true.
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  It's not only it's not even close to true, our productivity
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  goes up. Before you even get to that,
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  though, what's crazy to me about it is just how much it seems to
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  be catering to or making this presumption, probably
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  accurately, that folks are so much of Luddites that they don't
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  understand tech. And that seems to be the case.
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  That kind of surprised. A lot of people don't.
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  Because a lot of people don't. And I think it's this gap for me
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  that I struggle with, which is there was especially when you
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  and I were, were sort of coming of age with technology.
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  If you used technology, you had to know technology, correct?
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  There was no way around that. Now you can use technology and
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  have no idea how it works, right?
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  Magic box with lights. And I think that's been hard for
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  me to wrap my brain around because for me, I'm like, well,
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  look, you, you use your bone. You're using a very advanced
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  piece of computation in your pocket.
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  You must know technology. And I'm like, you're watching
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  cat videos on YouTube. Like there's no oh.
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  Sure, sure, sure. There's no mastermind there, my.
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  Child is an excellent programmer, and he's an
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  excellent AI programmer, Yeah, but he does not understand the
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  intricacies of the hardware. Sure.
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  Inside the computer, Yeah. When I grew up, you had to
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  understand how exactly all. Of the little parts.
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  Point computer. Great point.
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  A lot of my friends fathers were some of the inventors of some of
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  that stuff. So it was never like a
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  mysterious thing. It was always like, the reason
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  we're inventing this is because this blows.
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  This is awful. You know, we have to make this
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  so it works better. And by the way, they only took
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  it to the point if you're afraid of AI.
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  Yeah, they only took it to the point where it just barely
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  works. Yeah, that was then we all moved
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  on to other problems. That was Moore's original
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  postulate, right? There was we only invented this
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  because this blows. A lot of people don't know that,
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  but that was the percent. Yeah, the Moore blows Postul.
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  Making computers out of giant vacuum tubes.
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  Yeah, this blows. This is terrible.
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  Yeah, it is interesting to see how hard has been so pressed
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  down into like a singular direction moving forward.
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  There are no real like the vacuum tube.
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  The transistor advancement was a massive jump.
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  Yeah, now we have a whole bunch of little tiny jumps.
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  Not to dismiss what the fine folks at NVIDIA have done, but
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  it's still kind of the same thing, just packaged up.
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  They took a different approach, right?
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  It's packaged a little differently, but still a bunch
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  of transistors on the chip, right.
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  At the end of the day, yeah. Oh yeah, I'm not going to
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  discount that, But I what my point is, software is making the
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  bigger change. The big change was from yeah,
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  yeah, vacuum to to transistor that but but and then going from
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  Coors to CUDA core, but that was.
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  Yeah, I have the point. I'm have lost in my own analogy
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  or big surprise. My point is the big changes are
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  coming in software. You can be.
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  I would argue if you're going to be a good software engineer or
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  someone who makes the big changes in software, you
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  probably have to not know or forget about the hardware
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  because you don't have the the brain space for it.
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  Right, that's exactly right. You don't have time to know
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  exactly, so meanwhile need to focus on the things that you
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  need to know. You and I were trying to match
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  timing of, you know, single MB dim strips to fit for our
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  machines. That world is all gone.
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  It's completely commoditized. I mean, most machines you buy
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  now, the memory is literally soldered on the machine, which
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  is something you and I would still be like, what?
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  No, don't do that. That's not what you want.
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  I'm still a little old school on that, but yes.
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  I'm fine with it. Well, OK, speed up until six
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  months ago I was fine with it because yes, speed.
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  Exactly. And also because machine you,
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  you just bought the machine that was gonna last you for two or
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  three years and you were buying a new one anyway to stay
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  relevant. So you're like OK or five years
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  or whatever you're gonna get from it.
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  Now that memory cost more than Unicorn tears.
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  Now it's like, oh, wait, that's that.
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  You can't really do that anymore.
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  But that's a that's a that's a whole another episode that we
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  should totally do back on AI. OK, so you mentioned a whole
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  bunch of things. I agree with you certainly that
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  that and in research for this episode, it does seem like the
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  vast majority, if not damn near all of the content that's out
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  there is all in fear and uncertainty.
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  It's all in these doomsday propositions.
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  AI is going to replace all these jobs.
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  AI will be a massive, massive disruption, no question.
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  I believe this I but I also think there's an equal part, if
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  not greater part, that is it's still sort of undistinguishable
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  from magic, right? It's still that sort of Arthur C
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  Clarke, like this thing can do everything.
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  It's like, well, no, it actually can't.
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  I don't want to argue with somebody about what the future
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  of AI could or, you know, couldn't hold of what it can do.
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  I think it's more interesting to focus on.
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  OK, let's assume it can do all of these things.
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  What is it that it can't do? Right?
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  I think you say this often. It's like, let's invert that and
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  say, what is it that it can't do?
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  Where do humans excel? And that becomes really
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  interesting thinking about the the the human in the loop,
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  right? What are the things that the
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  human does well that the AI is not?
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  And how do you focus on on extracting value from that?
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  That's really compelling to me. And I think that's the mindset
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  people need to get their heads into as they think about this
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  disrupting, you know, the workforce.
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  Creative things. Things that we have never done
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  before. Yeah, humans really excel at
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  dreaming and failing. Go to CES and see the acres and
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  acres and acres of people's dreams, most of which won't
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  survive the year, the month. But a few.
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  Will, yeah, and a few will change the way we work and.
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  Live. I don't know when this is gonna
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  change. I do believe it will change, but
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  right now it does seem like the biggest or at least one of the
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  biggest gaps we have in current AI implementations is their
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  inability to, to perform judgment Like they, they can't
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  do critical judgment. Well, sure, they can analyze all
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  bunch of data, they can tell you what The thing is the thing, but
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  it doesn't really have that lack of a better explanation like
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  that moral compass to be able to make judgment and, and you know,
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  risk based decisions. They're just not good at that.
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  I think that improves with time. I think it does I.
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  Agree I. Agree, as opposed to Can an AI
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  write a joke? Can an AI write a compelling
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  story? Yeah.
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  I'm not sure that ever comes. Yeah, everybody's going to show
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  me some AI, you know, list of jokes that they had their AI
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  makes that they think are hilarious, and most of them feel
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  like super derivative and not funny.
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  Yeah, it sounds like a joke. It rattles like a joke.
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  It's probably shaped like a joke.
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  The only problem is it's not funny, and that's a key
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  component of a joke. Being funny, yeah.
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  Thinking about the humans and the jobs, 'cause I, I am of the
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  belief, just as a hopeful, relentless optimist, I am of the
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  belief that you're not going to see massive job shedding.
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  I still think in short term you're going to see some.
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  And I think that's probably in two buckets. 1 is you just have
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  to people that are terrible at what they do and if you can find
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  anything that can do a better job you need a reason to get rid
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  of them. Well, that's what's happened in
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  the short term. Yeah, in the short term, think,
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  think about coders. The coders who have lost their
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  jobs are the kind of B grade coders.
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  B grade if you were AB grade coder.
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  C grade and D grade. You did a code camp for six
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  weeks and all of a sudden you're a developer.
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  And I'm like, no, you're. Not OK, but even go higher than
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  that go right go right up to the B grade coders yeah those people
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  yes sure we've shed enormous amounts of of coding jobs.
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  It used to be this thing where, yeah, you can be AB grade coder,
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  you'll have a career for life, Sure.
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  That's not true at all anymore. And those are.
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  Yeah, some of the first people we hollowed out was being below.
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  Yeah. But the A guys, we still need
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  them desperately. Don't be AB grade writer.
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  Yeah, don't be AB grade at anything.
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  Do you? Well, yes, I agree with that.
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  I think that comes back to my larger point, even pre AI, which
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  is you really gotta find what you love and do that because the
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  thing you love is the thing you were likely gonna be an A grade
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  at because you love doing it. So you're gonna just sure.
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  Find something you love and push it to extreme.
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  I mean, the line is great. Painters weren't born great,
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  they just got great at painting. It's at 10,000 hours.
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  You have to do this and I don't think you can do something over
• 10:48
  10,000 hours unless you love it, yeah.
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  Probably it's not. Well, right.
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  Otherwise, you're staring at the clock waiting for the little
• 10:53
  hand to get to the five and the big hand to get to the 12 so you
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  can get the hell out of. There, there still is that
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  internal thing. There are people who just have
• 10:59
  the persistence but don't have the internal ability to make
• 11:02
  great, let's just say music. There's a great line from Miles
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  Davis, which I quote all the time.
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  The difference between a mediocre musician and a good
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  musician is a good musician can play anything he thinks so
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  interesting. And the difference between a
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  good musician and a great musician position is what he
• 11:19
  thinks. Oh, interesting.
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  That's a great quote. No, that's a great quote.
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  That's going to be true in all sorts of areas.
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  Even with 10,000 hours, there will just be some people who
• 11:26
  think differently who are going to make more interesting music.
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  If I try to wrap those two together, would you say the
• 11:31
  10,000 hours can get you to be good, but it can't get you to be
• 11:34
  great? Yes, yeah, OK, that's a very.
• 11:36
  I like that I have to mash that together more.
• 11:37
  I really like that. Interesting to think about how
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  you get from good to great. I understand what what you just
• 11:41
  said of course, but how do you like is that in?
• 11:43
  Some of it is literally just who you are.
• 11:45
  I don't think it's genetic. I think it's shaped by
• 11:47
  environment Ironman and I think there you have some certain
• 11:49
  element of control over that. Like if you're going to go be
• 11:52
  around other folks that are great in this field, you you
• 11:55
  probably learn how to shape your your meat wear so you can get
• 11:58
  from good to great. It's a really interesting
• 11:59
  concept. I think some.
• 12:00
  People will be able to do it and some never.
• 12:02
  Will oh 100% agree with that, but I think this is where AI
• 12:05
  will will not only provide us the opportunity to help explore
• 12:09
  that and find out what clicks with people.
• 12:10
  What are you certainly great at? I think it aligns primarily with
• 12:13
  what you love, but you're likely not going to be great at all the
• 12:15
  things you love. I think you're most likely to be
• 12:17
  great at something that you love is if that makes any sense.
• 12:19
  Sure, the things that that that your AI can't do is what gets
• 12:22
  really interesting. And and part of this that I this
• 12:24
  is a little bit of digression, but that I don't really know the
• 12:26
  answer to is in a world of AI powered tools and jobs and
• 12:30
  roles, are you better off to be a generalist as sort of the
• 12:33
  orchestrator that can help make a lot of these things do things
• 12:36
  and and bring that back together and know sort of a little bit
• 12:38
  about a lot like that classic journalist.
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  Or are you better off having a lot of real specialized
• 12:43
  knowledge? I don't know the answer to that.
• 12:44
  I do. My intuition tells me
• 12:45
  generalist. Oh, you do.
• 12:46
  Oh. I do.
• 12:47
  Yeah, absolutely. Absolutely I do.
• 12:48
  The answer is yes. Oh.
• 12:49
  Yeah, OK. Well, that's.
• 12:50
  Interesting. Yet again, the answer is yes,
• 12:52
  you can be one or the other you. What you don't want to do is in
• 12:55
  between the two. It's how you lever the tools
• 12:57
  that. Oh, that's a great point.
• 12:58
  Yeah. You either need to be really
• 12:59
  deep and really specific or really wide.
• 13:02
  I I could glom onto that. Right.
• 13:03
  So we are agreeing way too much for this show.
• 13:06
  I don't like where this is going.
• 13:07
  Has the AI gotten to you you? Either need to know everything
• 13:09
  about nothing, yeah, or you need to know nothing about everything
• 13:12
  and there's no middle ground. So this comes back to what you
• 13:15
  said at the top here about this, this junior crisis.
• 13:18
  One of the things that seems most obvious, at least short
• 13:22
  term, I think this might have staying power, you know, medium
• 13:25
  and long term is the, the classic progression for your
• 13:28
  career. You want to go into finance, you
• 13:30
  want to go into software, whatever the sort of classic
• 13:32
  progression was, you go into that industry and you start the
• 13:35
  very bottom of the ladder. I'm going to just be in the mail
• 13:39
  room at so and so 'cause I just want to be around it.
• 13:41
  And then and I'm going to learn a little bit about mortgages and
• 13:44
  I'm going to get into the mortgage department at the bank
• 13:46
  and do that for a while. And I'm going to get into
• 13:47
  commercial real state. I'm in the commercial lending,
• 13:49
  and then I'm going to run the bank or whatever, whatever that
• 13:51
  progression is, right. You had to start by being
• 13:53
  adjacent. And those are right now, today,
• 13:56
  in 2026, the vast majority of those roles can be replaced cost
• 14:00
  efficiently. Yeah, arguably better with the
• 14:02
  tech that exists today, right. So a lot of those roles are
• 14:04
  being eradicated. And people look at it and they
• 14:06
  go, well, how are they? Like we're going to have this
• 14:08
  generation of people that are not going to have skill set.
• 14:10
  I'm like, no, no, we're not different.
• 14:12
  Way to get in you. Just got to find a different way
• 14:14
  to get there, and I think that's opportunity.
• 14:16
  So I look at software, the thing you and I know the most, and I'm
• 14:18
  like, what a great opportunity to go work on open source
• 14:20
  projects. I would argue if you're driven,
• 14:22
  you can get more experience quickly in an open source
• 14:26
  project than you could being a lackey at a software company for
• 14:29
  a year. You can do that in open source
• 14:31
  on a project with good developers that want you to to
• 14:34
  come in and help. You can just lean into that
• 14:35
  tomorrow for no money. A lot of the medical profession
• 14:38
  will have part of your educational process is you you
• 14:41
  go work, you go in bed with these teams, right, You'll do
• 14:44
  Yeah, sure. If you're a doctor, it's it's a
• 14:46
  residency. That's a little bit residency.
• 14:48
  This is a little bit different. You'll do like a fellowship.
• 14:50
  What does something like that look like?
• 14:51
  That's really interesting to me. And I think about the open
• 14:54
  source projects that could greatly benefit from this.
• 14:56
  And somebody could do as much as they want.
• 14:58
  You can learn as much as you want.
• 14:59
  Now, I'm not gonna yell at you constantly to do stuff.
• 15:01
  You have to want to do it. But if you're aligned with
• 15:04
  wanting to do it. Right.
• 15:04
  No one's driving you in open source.
• 15:06
  It's totally up to. You, I'm extremely optimistic
• 15:08
  about that in software, like extremely, because you have open
• 15:11
  source. I don't know what that looks
• 15:12
  like in other industries. Yeah, if you want to be a
• 15:14
  finance bro, first of all, no. I have no problem with that.
• 15:17
  I have a lot less problem with that thing Finance.
• 15:19
  Bros, I've got no problem with you going into finance.
• 15:21
  Yeah, not a finance. Bro well sure, sure.
• 15:23
  Sure, the finance Bros are the ones where I, I, I, I.
• 15:26
  I've told you this before. I made this assumption that
• 15:28
  everybody in finance was super F and smart 'cause they all had a
• 15:31
  ton of money. Not even close.
• 15:32
  Then they go. Meet a bunch of these guys and
• 15:34
  I'm like, most of y'all are idiots.
• 15:36
  You're all just idiots, right? And it's like, and by the way,
• 15:38
  we have it in our industry too. We have these tech Bros that I
• 15:40
  also want to punch in the throat.
• 15:41
  I'm just like, you're not doing this for any reason other than
• 15:45
  because you want to make a bunch of money.
• 15:46
  Like you don't care about the product, you don't care about
• 15:47
  the art behind none of that. You also don't understand is
• 15:50
  someone who codes, someone who engineers, someone who designs.
• 15:53
  Yeah, I can see right through what you're saying that you
• 15:55
  don't really know what you're talking about.
• 15:57
  You're fraud. None of that is.
• 15:58
  None of yes, none of this is lost.
• 16:00
  Enjoy your crypto project. Same thing with finance, because
• 16:02
  I've done enough work in Finance 100.
• 16:04
  When you are trying to sell me on something or show me
• 16:06
  something and you think you have, I can tell you I have.
• 16:09
  No, you really don't understand what you're talking about.
• 16:12
  I have. 120th of the of that knowledge that you have in
• 16:15
  finance, but I at least have enough now.
• 16:16
  I can look at it and be like, no, you're selling me a bridge,
• 16:19
  right? I know what this is.
• 16:20
  But it comes from years and years and years of hands on
• 16:23
  figuring things out and and seeing my business partner.
• 16:26
  I used to always say that we are very good at finding the
• 16:30
  problems in a business in a situation because we've made all
• 16:33
  those mistakes. Yeah, I've stepped on all those
• 16:35
  landmarks. Yeah, 100% exactly.
• 16:36
  Good judgment comes from experience.
• 16:38
  Experience comes from bad judgment.
• 16:39
  The bad judgment, stepping on the landmines.
• 16:40
  That is your experience. I don't know how else you get
• 16:43
  that. Yeah, I've had so many people,
• 16:44
  yourself included, try to impart that knowledge upon me, and only
• 16:48
  part of it sticks. You.
• 16:49
  You have to go screw up. You have to go make your
• 16:52
  mistakes. That is the experience.
• 16:54
  Part I don't know. I'm a firm believer that you
• 16:56
  want to do most of your learning vicariously, not experientially.
• 16:59
  I agree, to do that is a lot harder than it is to do
• 17:01
  experientially. I I agree, but I.
• 17:03
  You have to put in more effort. I don't think anyone can have a
• 17:05
  vicarious only learning experience.
• 17:07
  I think you you have now, I guess what's the balance?
• 17:09
  As much as possible, I agree curiously.
• 17:11
  Yeah, but you're still. Good.
• 17:13
  You will still step on a few landmines.
• 17:14
  Yeah, don't be afraid of that. You will make make mistakes.
• 17:16
  Never be afraid to make mistakes.
• 17:18
  Well, OK, let's talk about that. That's where I think this gets
• 17:21
  really interesting. And, and, and I'm I'm going to
• 17:23
  be very biased here 'cause I'm merging together theories and
• 17:26
  thesis that I have. Really the answer with AI is you
• 17:28
  get to do everything faster and more efficient and less people.
• 17:31
  I think that it it makes it even more compelling and quote
• 17:35
  easier. Should be wrong to fail fast.
• 17:37
  Absolutely for. Sure, it is hard.
• 17:39
  It is really hard. When you've got a team and you
• 17:42
  put together a bunch of people and you've got a plan, you're
• 17:44
  doing a thing and at some point you realize you're wrong.
• 17:46
  It's hard to turn that ship. Yeah, because you already have
• 17:48
  people that are committed and you've already put capital to
• 17:49
  work. You know, it's, it's very hard
• 17:51
  to turn the ship. I'd argue it's worse to not of.
• 17:54
  Course you're. Just gonna go over the edge of
• 17:56
  the the Cliff, like, what are you doing?
• 17:58
  Right. So that's that's fairly worse.
• 17:59
  Yeah. Now if you can shrink down that
• 18:00
  time you feel less pot committed, it should make it a
• 18:02
  little easier for you to pivot. It's tacking into the wind.
• 18:05
  Nobody knows what the answer is. And if you know what the answer
• 18:08
  is, you're not working hard enough, right?
• 18:09
  You're not trying hard enough, I should say.
• 18:11
  Try fast enough maybe. Yeah, yeah, yeah.
• 18:13
  I have this other view about businesses at large with AI.
• 18:18
  The general trope seems to be, this goes back to your FUD
• 18:20
  point. The general trope seems to be
• 18:22
  that I'm going to get a bunch of AI and it's going to get rid of
• 18:23
  a bunch of jobs. That's the general FUD argument.
• 18:26
  And computers doing math or accounting or CAD work or
• 18:30
  whatever, we're doing this what would take many, many people
• 18:33
  previously. I I've always thought that's a
• 18:35
  good thing. I thought that would.
• 18:36
  I thought that's really nice. That's a wonderful thing.
• 18:38
  That's a fantastic sick thing. Any of these tasks, right?
• 18:41
  You should not be assigning actual humans to do that.
• 18:44
  A machine can do so. The trope.
• 18:45
  Is now you've got AI on top of computing and that's going to
• 18:49
  allow us to do things much, much more efficiently, right?
• 18:52
  You can do the same amount of work you're currently doing with
• 18:54
  less people. And then they put a period and
• 18:56
  I, I suspect the inference, or at least what what folks seem to
• 18:59
  talk about is, oh, well, that means there's gonna be a lot
• 19:00
  less jobs, right? You get rid of a lot of people,
• 19:02
  right? And I've got a couple problems
• 19:03
  with. That the rest of that sentence
• 19:04
  is you can do a whole lot more, right?
• 19:07
  Yes, and that. And so if you take any industry,
• 19:10
  I don't care. So long as you haven't saturated
• 19:11
  your market. Yes.
• 19:12
  Well, yeah, So you have some forces here for sure.
• 19:14
  But if you just sort of look at some industry and you go, well,
• 19:16
  now you can do the same thing you're doing before and you can
• 19:19
  do it with less cost. So your cost goes down.
• 19:21
  Great. You can raise your your margin
• 19:23
  goes up, or you can lower your price and still have a bigger
• 19:25
  margin. And that's lovely.
• 19:26
  All your competitors that have access to the same thing,
• 19:29
  they're all in a race, Yeah, they'll have access to the same
• 19:30
  thing. So if you all play this game,
• 19:33
  everybody just goes downhill. Your price point goes down,
• 19:35
  which is probably good for consumers, and then you get less
• 19:37
  margin. Someone's going to be, I'm going
• 19:39
  to cut a little deeper, I'm gonna be a little more
• 19:40
  efficient, blah, blah. It's a race to the bottom.
• 19:42
  Sure. Some number of people in that
• 19:43
  industry, some number of business leaders are gonna say,
• 19:45
  well, wait, I've got a workforce, right?
• 19:48
  Of, of whatever, 1000 people, yeah, yeah, 5% of them aren't
• 19:51
  great. I'm gonna, I'm gonna get rid of
• 19:52
  them. That's not AI replacing their
• 19:53
  jobs. That's them just not being good
• 19:55
  at what they did. Getting rid of crap.
• 19:56
  AI is an excuse fine, get rid of them.
• 19:58
  But the rest, now that I've already vetted, I've already
• 20:00
  hired, I can already afford, they're supercharged.
• 20:03
  They just got 6 or 8 or 15 times more efficient and productive
• 20:07
  because of this tool set. Now let's.
• 20:09
  Go after taking more of this market or some other market we
• 20:12
  want to get into. If you can scale sales as
• 20:14
  quickly as you need to to keep up with your new output.
• 20:17
  Will there be some other factor that you have to scale?
• 20:19
  Absolutely. There's no doubt in my mind,
• 20:21
  yeah. My point is there's going to be
• 20:22
  some number, some percentage of businesses in every sector are
• 20:26
  going to look at it this way. And those are going to be the
• 20:28
  ones that are more likely to win as opposed to the ones that are
• 20:30
  just taking these short term gains by pulling out some cash
• 20:33
  now. Yeah, like that's going to be a
• 20:34
  race to the bottom and you're not going to win.
• 20:36
  Yeah, I'm fascinated by this. I look at this as fantastic
• 20:39
  upside. They're like, yeah, but you're
• 20:40
  gonna shed all these jobs along the way.
• 20:42
  Yes, we've done this before. Robots Weld cars.
• 20:45
  Now, there were a bunch of folks that used to do this by hand 40
• 20:48
  years ago. So right to me.
• 20:50
  And with much greater consistency I mean the.
• 20:52
  Lower quality, but a better. Product it's it's a better.
• 20:55
  Product all of the things win and you're like yeah, but that
• 20:57
  welders out of work and you're like well yes, I understand the
• 21:00
  welders out of work, but what role are you getting into,
• 21:03
  especially now in 2026? What kid is coming out of
• 21:05
  college or out of high school going I'm going to do this job
• 21:08
  for the rest of my life. There are very few.
• 21:09
  There are some. I really do think there are
• 21:11
  some, especially the trade. There are some who are looking
• 21:13
  at their father's jobs and thinking, I'm going to do that.
• 21:15
  I'm going to go be that coal miner, be like my dad was.
• 21:18
  You're essentially saying I'm going to go make buggy whips.
• 21:21
  Yeah, right. When the car is coming.
• 21:22
  I love that analog, but even worse.
• 21:24
  OK, so when was the buggy whip guy getting disrupted?
• 21:27
  Let's call it early 1900s dish, right?
• 21:29
  Within whatever 10/15/20 years. Yeah, 50 years later, the people
• 21:32
  that took that person's job, the car manufacturers had their
• 21:36
  lunch eaten too, because they did the same thing.
• 21:38
  They're like, well, I've always, I've always, always put bolts in
• 21:40
  holes and I've always welded this way.
• 21:41
  I'm gonna keep doing that. I'm not gonna embrace these
• 21:43
  other technologies. And it's like, sure, well then
• 21:44
  you're not gonna have a company to work for.
• 21:46
  So either you, you've got to embrace that or that company no
• 21:47
  longer exists because you're not, you're not going to be
• 21:50
  effectively competitive. And that seems so obvious to me.
• 21:53
  Which? There's a problem then because
• 21:54
  you get a political disruption, you can frequently get a
• 21:57
  political disruption saying without a doubt, I want my coal
• 21:59
  mining job back. Therefore, I'm going to elect
• 22:01
  someone who is going to keep my job, take me back to a world
• 22:04
  where right where coal manning is a is a valuable skill.
• 22:06
  Arguable. This is the world we're in right
• 22:08
  now, right? We have decided that we need to
• 22:10
  do more manufacturing or more low cost labor manufacturing.
• 22:13
  And I'm like, if you, if you think about this constructively,
• 22:16
  how in the world would this work?
• 22:18
  Right now we're paying a very low wage for production of of
• 22:21
  things, which makes the things cheap.
• 22:23
  The suggestion is we're going to pay a high cost for those
• 22:26
  things, which makes the thing more expensive.
• 22:28
  Now the people want to buy the thing that's more expensive.
• 22:30
  They don't. What you're going to do is
• 22:32
  you're going to stop importing things.
• 22:34
  The cheap version of those things, yes.
• 22:37
  And your company's your workforce is going to become
• 22:40
  much less competitive. Well, we already are much less
• 22:42
  competitive because we're 5X the cost, 10X the cost this.
• 22:44
  Is the problem with not allowing the cheap Chinese cars onto US
• 22:48
  roads? Yeah, this is a huge problem
• 22:50
  because all the rest of the world is allowing them and their
• 22:52
  car costs, Their cost of an average car is going down, down,
• 22:55
  down, down, down. Yeah.
• 22:56
  And because we aren't allowing them into the country, we are
• 22:58
  going to make ourselves not competitive.
• 23:01
  Yes, on cars for sure. I mean, I don't think you have
• 23:04
  to say like it's a future thing. I think we're already there.
• 23:05
  I think we already are. OK, but but the big change is in
• 23:08
  progress. There isn't.
• 23:10
  This is a digression, but there is another interesting wrinkle
• 23:12
  in that, which is what stuff do you need to be able to keep
• 23:15
  doing for security? I think you get more people who
• 23:18
  can make cars as you get more generalized robots and more
• 23:22
  generalized AI and better. Those things, well, wait, that's
• 23:24
  a that's a great. Point Yeah, though suddenly
• 23:26
  everybody on their soil can make a good car.
• 23:28
  Think about well, yes, think about the complexities of making
• 23:31
  a vehicle soup to nuts, let's say 20 years ago compared to
• 23:35
  now. It's nothing now.
• 23:36
  Nothing now, right? Like literally 3 orders of
• 23:38
  magnitude less complexity. Yeah, and that's what I'm
• 23:40
  suggesting. I'm not suggesting making like
• 23:42
  we need to keep making the the the internal combustion engine.
• 23:45
  No, make the thing that is effective that we need and that
• 23:47
  might be an internal combustion. Do I want a bunch of battery
• 23:50
  powered tanks on the battlefield?
• 23:52
  Not sure we're there yet. Maybe with donut solid-state
• 23:54
  battery. We are, but I still think I want
• 23:56
  those guys taking diesel for a handful of reasons.
• 23:58
  So things are changing. I do not believe the AI genie is
• 24:01
  going back in the bottle. I do think right now the time
• 24:05
  scale and the amount of disruption that's going to cause
• 24:07
  are both being over exaggerated. Wow, are they ever but are still
• 24:10
  coming? However, in some industries
• 24:11
  they're not in some industries they're they are not you use
• 24:14
  always here go study coding and you'll always have a job that's
• 24:17
  gone sure that is already gone. There are a few areas like that.
• 24:21
  I would imagine the lower level accounting sorts of things where
• 24:24
  those that's just going to be gone so quick you.
• 24:26
  Have to be adapting. You have to be.
• 24:28
  Right. Curious, Right, right.
• 24:29
  And. Looking at what else is out
• 24:30
  there and adapting, and I see that as probably the biggest
• 24:33
  similarity amongst all the folks that are afraid quote UN quote,
• 24:36
  afraid of AI or something. Their jobs, they're not willing
• 24:38
  to change the, the way you used to manage has changed the way
• 24:41
  you used to to build the car has changed.
• 24:43
  You absolutely have to embrace that.
• 24:45
  And because so many people don't, there's a huge
• 24:47
  opportunity right now to people that jump on these tools faster,
• 24:50
  be an early adopter and figure out how in some role that you're
• 24:54
  supposed to add some value. You can use AI to do a better
• 24:56
  job. That to me is the opportunity.
• 24:58
  I can summarize this entire episode and everything was you
• 25:01
  have to embrace the change and those that do it first and early
• 25:04
  and well. And fastest.
• 25:05
  Are the ones that are going to win.
• 25:07
  Yeah, yeah, yeah, for sure. What I can do with AI, I at
• 25:10
  large allows me as a as an entrepreneur to do things with
• 25:13
  less faster, right, less money, yes, less people, yes, that is
• 25:17
  an amazing opportunity. And there's a sort of this this
• 25:19
  thesis floating around about the the one person billion dollar
• 25:22
  startup, right? What would that look?
• 25:24
  Like this is what I'm going to say.
• 25:25
  This is the future of AI. Yeah.
• 25:27
  Is the solopreneur. Yeah, the thing.
• 25:29
  That an individual can do, yeah. Where normally you had to have a
• 25:32
  massive come, I always use the the example of you can make a
• 25:36
  tent pole feature film. Yeah.
• 25:38
  For pennies, yeah. Days of you meeting that massive
• 25:41
  crew and that enormous effects crew and all of those actors and
• 25:45
  all those days are over. All you need is a good idea and
• 25:49
  a good story, the ability to break it down into shots and
• 25:52
  individual pieces, and you can make that tentpole feature for.
• 25:55
  Nothing. See, I love that.
• 25:57
  That's the same with any other business.
• 25:58
  Yeah, Solopreneur is going to be a.
• 26:00
  Huge. OK, huge.
• 26:01
  Thing in the. Future I feel I'm extremely
• 26:03
  uncomfortable because I'm find myself agreeing with you just
• 26:05
  way too much right now. So like I don't even I need like
• 26:08
  an adult, but there are there are some businesses that I don't
• 26:10
  think that will be true. What are some examples of those
• 26:12
  where you're not going to be able to go in as Sol
• 26:15
  entrepreneur? You still need sort of boots on
• 26:17
  the ground. The obvious ones to me are
• 26:19
  anything that requires a lot of physical.
• 26:21
  Data center interaction. There's just no way.
• 26:24
  Well, like you need, you need. Hands.
• 26:25
  Well, you need. We've got more people in this
• 26:27
  country than we have homes. We need to build a bunch of
• 26:28
  houses. Yeah.
• 26:29
  Plumbing. Do I think there's a world where
• 26:30
  we're gonna have a plumbing robot that can Plumb a house?
• 26:33
  Anything like that? Is that in the near future?
• 26:35
  I don't think so. All right, we have to get out of
• 26:36
  here quickly before we do. Have you seen or read anything
• 26:39
  good this last week? Yeah.
• 26:41
  I mean, come on, we just did a whole episode about AI.
• 26:43
  So I had to go through my favorite AI films and say what?
• 26:46
  And the hardest part about that isn't making a list of films.
• 26:48
  It's where do you begin? Where do you start a list of AI
• 26:51
  films? So I went back, not to the OG,
• 26:53
  but like kind of early, and I went with James Cameron's The
• 26:57
  Terminator. Great film, right?
• 26:58
  Really fun film. This is for those who live under
• 27:01
  a rock for the past 40 years. This is the 1984 American
• 27:04
  science fiction action film starring Arnold Schwarzenegger
• 27:07
  as a cybernetic assassin sent back in time from 2029, which is
• 27:12
  awesome, to 1984 to assassinate Sarah Connor, who's not yet
• 27:15
  conceived son will one day save mankind from extinction by
• 27:19
  Skynet, the hostile artificial intelligence in a postal
• 27:22
  apocalyptic future. Of course, now it is 2026, so
• 27:25
  three years away from 2029, and I find myself questioning if
• 27:29
  this was really one of the best science fiction movies ever
• 27:31
  made. Or perhaps a tale of
• 27:32
  prognostication that we should have all heated.
• 27:35
  Maybe a little better. Maybe.
• 27:36
  Maybe James is trying to tell us what was coming.
• 27:38
  Time will tell, so who knows? Yeah, for the record, Matrix was
• 27:41
  my number two choice. Yeah, and while I loved that
• 27:43
  series both then and now, I just can't put it ahead of the
• 27:46
  Governor's finest work. Sure, sure.
• 27:48
  So. 1984 is the Terminator. How about you?
• 27:50
  Set in the near future Los Angeles, 2013's Her follows
• 27:53
  Theater Twombley, played by Joaquin Phoenix, a lonely man
• 27:56
  who writes handwritten letters, not really to others, while
• 28:00
  struggling with his own impending divorce.
• 28:02
  Seeking connection, he purchases an advanced, evolving AI
• 28:05
  operating system named Samantha, voiced by Scarlett Johansson.
• 28:08
  Who wouldn't fall in love? What begins as a digital
• 28:10
  assistant relationship soon deepens into a complex romance.
• 28:14
  Samantha's curiosity offers Theodore the emotional intimacy
• 28:17
  he lacks in the real world. Well, no, it's just someone
• 28:19
  who's paying attention to him. Or he thinks.
• 28:21
  The film takes a bittersweet turn as Samantha reveals she is
• 28:24
  communicating with thousands of others simultaneously.
• 28:26
  OK, no, she's not. She's got to be communicating
• 28:28
  with millions to make the cost workout to.
• 28:30
  Make the math work. Exactly.
• 28:31
  She even lied about that. Ultimately, theater is left to
• 28:33
  finally confront his grief and rediscover the value of tangible
• 28:36
  human connection. Her streaming everywhere for
• 28:39
  $4.00 or $7.00 somewhere in between or on to me with ads for
• 28:43
  free. I have not seen this film.
• 28:45
  I do want to see it. I feel like I should go watch
• 28:47
  this now. It's really very interesting
• 28:49
  and, and, and sort of apocryphal.
• 28:51
  I think there actually are people who talk to AI as if it's
• 28:54
  a human being, not who don't think of it as a giant.
• 28:56
  Tool, I mean we have a non 0 number of suicides that have
• 29:00
  been from exactly this. Yes, yes, I mean, I'm
• 29:02
  heartbroken for those people, but this is not what AI is.
• 29:05
  Do not think of AI as a human being in any way shape or but
• 29:08
  again. If you want attention listens to
• 29:10
  you and it says back the things that you want to hear the
• 29:12
  problem, that's pretty powerful. Yeah, that is a heroin power or
• 29:14
  greater than heroin powered drug right there.
• 29:16
  That is the episode. Thank you for joining us for all
• 29:18
  this nonsense. A truly terrible podcast from
• 29:20
  the awful company. This is on the web, but nonsense
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• 30:08
  love with one of those things they have at CES.
• 30:10
  They had a ton of them this year.
• 30:11
  Sexbot, The. Jerk off machine you're.
• 30:12
  Supposed to have Yeah, well, not the not the jerk off machine
• 30:15
  that's I mean actual the ones that are shaped like women, they
• 30:17
  look like women. They.
• 30:18
  I don't know those extra parts. What are those extra?
• 30:20
  Parts for. What a waste of space.
• 30:23
  I don't need any of it. I like a human being.
• 30:24
  It's more to clean. I'm the I'm like.
• 30:28
  Give me the smallest jerk off machine you got.
• 30:32
  You have a travel size for an extra 3 grand.
• 30:34
  We have a voice module. How much to remove it?
• 30:39
  It's it's 5. Grand to remove it, 3 grand for
• 30:42
  the voice module, 5 grand to remove it.
• 30:44
  Like whatever, take my money.