The Great Repurpose: Shifting Our Identity from Professional Tasks to Human Value

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0:01 You should stay.
0:12 It's not like
0:32 Okay, welcome everyone to Let's Vive at
0:34 Upside. Thank you for showing up
0:36 tonight. Um, some of you have been here
0:39 before.
0:41 We're modeling this after Let's Vive up
0:43 in Denver, uh, which gave me New England
0:45 started, uh, like a year ago. Actually,
0:48 Kyle's been to one of those events. Um,
0:51 so we've been doing this for a month and
0:54 a half now, kind of getting our feet
0:56 wet. Um, the group has obviously grown.
1:01 Last time we had Danny and Joe down from
1:04 Let's Vive to do code 101, which is
1:07 which was great. Um, I've known Kyle for
1:10 some time uh when I was on the board for
1:13 Colorado companies to watch. Kyle is a
1:16 past winner through his company
1:17 Storyline and I think it was probably
1:20 two years ago um I led to a talk that
1:24 Kyle was giving at Invisible City up in
1:27 Denver on AI and I was kind of like
1:30 didn't really know what AI was all
1:32 about. Wasn't even using chat on a daily
1:36 basis. Kyle gave the most amazing
1:38 presentation. She totally blew my mind.
1:40 I'm like, "Okay, I got to get into AI."
1:43 And that was kind of the the start of me
1:45 ramping up. Kyle founded AION, which is
1:49 an online community for AI enthusiasts.
1:52 He's on what almost every night on
1:54 YouTube.
1:54 >> I go live five nights a week on YouTube
1:57 and Tik Tok talking about AI.
1:59 >> And it's not he's not boring. Definitely
2:03 not boring. So, I I highly encourage you
2:06 to check out AI Salon. Follow the AI
2:09 learning lab on YouTube and when you
2:12 when you're board at home at night, go
2:14 on YouTube and watch Kyle. He's very
2:16 entertaining and um grateful that he
2:19 made the trip down here tonight from
2:21 Denver. Really appreciate it. I think
2:22 he's going to give a great presentation
2:24 tonight. And uh Kyle, it's all yours.
2:27 >> Thank you so much. And make sure
2:29 everyone signs in before you leave
2:31 tonight.
2:32 >> I really appreciate everyone back
2:34 tonight. Thanks for coming. Um, I assume
2:37 you don't know um what the heck we're
2:40 going to talk about tonight. Um, I want
2:43 to share some new thinking that I've got
2:45 on AI. But I'm Pal Shannon. Um,
2:50 I've I've I've had a a crazy fun career
2:53 that's always been at the intersection
2:55 of new technology and storytelling or
2:57 self-expression.
2:59 Um,
3:01 and
3:03 the the moment that we're in, this
3:05 generative AI moment is is absolutely
3:07 crazy. Um, I'm going to take us on a
3:09 journey tonight. So, I hope you're okay
3:11 with that. And I promise you where we're
3:13 going to end up is in a really amazing
3:14 place, but it may not seem like that to
3:17 start. So, I hope you're you guys good
3:19 for a little sense of adventure tonight.
3:21 Little fun. Playing along. Good. um
3:27 in a moment, but not yet, I'll sort of
3:29 I'll sort of dive into what we're
3:30 talking about here. But I I thought what
3:32 might be good is just to give you a
3:34 little bit of my background um and my
3:37 context for how I understand what's
3:40 happening in the world right now. So,
3:42 I'm a storyteller by train. I have a
3:44 fine arts degree in acting. I moved to
3:48 New York City out of school and uh
3:50 started ran a theater company for four
3:52 and a half years in the dramatic life of
3:55 the starving artist and then uh and then
3:57 I got tired of you know macaroni and
4:00 cheese. I thought I got to make some
4:02 money. So I because I'm smart I thought
4:04 I know I'll write myself an acting
4:05 career. So I went through a two-year
4:07 stretch where I wrote seven screenplays
4:09 in two years. Started a fake management
4:11 company to do that and that didn't make
4:13 me any money either. Um but but my day
4:17 job instead of waiting tables I I didn't
4:19 want to be cliche I did desktop
4:22 publishing
4:23 and so I was I was good with computers
4:26 and along people started talking about
4:28 this thing called the worldwide web and
4:31 I started seeing bus posters about it
4:33 wired magazine in Mondo 2000
4:36 and
4:38 and and I was really intrigued by this
4:41 and and I I kept thinking about this
4:42 time in my childhood when I was in
4:44 seventh th grade.
4:46 I walked into my um first day of math
4:49 class in seventh grade and there were
4:51 RadioShack TRS80 computers on every desk
4:56 and I learned how to use computers. I
4:58 learned personal computers and I learned
5:00 basic programming and I remember being
5:03 just too young. I remember thinking like
5:06 Steve Jobs and Bill Gates like I'm just
5:08 younger than I just missed it. And I
5:10 knew that that machine
5:13 was like the printing press. Like I knew
5:15 that these things don't come along very
5:17 often, like every couple hundred years.
5:18 And so I was I was like heartbroken that
5:22 I missed this moment in history. So this
5:25 worldwide web thing comes along and I
5:27 don't know what it is. I teach myself
5:30 enough HTML to put together some pages
5:33 and I had an idea. I thought I I know a
5:35 bunch of talented people and actors and
5:37 writers and what if I put together an
5:39 art and culture magazine because the
5:40 internet all that was on it was like
5:42 research papers and dissertations and
5:44 science and so so I came up with this
5:47 idea for an art and culture magazine
5:49 called Urban Desires. So went away with
5:51 my wife on vacation, took my Mac 660 AV
5:55 and in the car and set it up and and I
5:58 made the first issue of Urban Desires.
6:00 And so I got back to our apartment in
6:01 Brooklyn and um I didn't know what to
6:06 do. I didn't know how to get it on the
6:07 internet. So, you know, I asked some
6:09 buddies and they're like, "Oh, you got
6:10 to upload it to an internet server." So
6:12 I uploaded these files from my apartment
6:14 in Brooklyn to this computer in
6:16 California. I had to call, you know, I
6:19 had to call it used the sound of me.
6:23 Three weeks later, I got an email from
6:25 someone that said, "Did you know that
6:26 Urban Desires was written about in Paris
6:30 in Liberation, the Parisian newspaper?"
6:35 Sorry.
6:37 It was this remarkable moment where
6:47 where I sensed that something had
6:49 shifted, that the world had changed
6:53 and I and I the next Sunday I couldn't
6:55 believe it. The next Sunday I went to
6:56 down to Time Square
6:59 and I went to the international news
7:01 stand and I bought a copy of Liberation
7:03 and flipping through it. Sure enough,
7:04 there's a full page article of of this
7:06 magazine I made in my apartment in
7:09 Brooklyn, screenshots of it. And I knew
7:12 in that moment that geography had been
7:15 collapsed, that time had been collapsed,
7:17 that the world was different now, but no
7:20 one knew it.
7:22 And
7:24 that began a really remarkable time in
7:26 my life. I co-founded agency.com, which
7:28 was one of the first digital agencies,
7:30 and I built some of the first websites
7:32 for the Fortune 500. And I got to really
7:35 I got to live that experience of being
7:38 at the beginning of something that was
7:39 going to change everything.
7:41 And I knew like every day I felt lucky
7:44 to be a part of being able to do that.
7:47 And so I thought that was the last time
7:49 in my life this was going to happen.
7:52 Jump forward to November 30th, 2022. I
7:56 assume you know what that day is.
7:59 Anyone?
8:01 That was the day that ChatGpt launched.
8:05 And
8:08 I had a similar kind of moment as the
8:10 the Paris newspaper moment where I was
8:13 playing around with chatting. My my
8:15 first experience with it was um
8:18 oh the Turing test has been passed,
8:20 right? Alan Turing came up with this
8:22 test in the 50s that said we'll know
8:24 when a machine is truly intelligent when
8:26 you can interact with it. You can't tell
8:28 if it's a computer or a human being on
8:30 the other side of the screen.
8:32 I was like, "Oh, that that kind of
8:33 happened." And then I was like, "Oh,
8:35 maybe I can get it to act like, you
8:36 know, those robots in sci-fi movies." As
8:39 I was talking with it to try to get it
8:41 to act like a robot in sci-fi movies, it
8:44 it was acting like a robot in I'm like,
8:46 "Oh, this is this is what's in those
8:50 movies." Like, we're living in a postci
8:52 world. So, about a week later,
8:55 I
8:57 for for a bunch of years, people said,
8:59 "Oh, you should learn Python. Python's
9:00 really good. you should learn Python,
9:02 the programming language. Okay, I'll
9:04 learn Python. I have AD. I don't I'm not
9:06 good with programming. So, I but I heard
9:08 that chatbt could could code. So, I
9:11 said, "Write me some code in Python."
9:13 And it wrote this code.
9:16 And then I had this panicked moment
9:18 where I got really embarrassed like I
9:20 didn't even know how to run Python code.
9:22 And normally what you would have to do
9:23 is you'd have to like dial up a buddy
9:25 like, "Uh, how do I run Python code
9:27 again?" He's like, "Oh, you don't dump,
9:28 right?" You know, I just asked chatbt,
9:31 "How do you run Python code?" Within 90
9:33 minutes, I had written a fully
9:35 functional Python application that was
9:37 making API calls to OpenAI and
9:39 generating social media copy based on
9:41 what someone did.
9:43 And I had, you know, full body chills
9:46 again
9:48 because what hit me was this was 2022.
9:51 The world just changed, but no one knows
9:53 it.
9:56 So, with your permission, what I'd like
9:58 to talk about tonight
10:01 is
10:04 where I think we find ourselves. I'm I'm
10:07 going to get to sort of what you can do
10:09 with AI, how to do AI, and I'm happy to
10:11 answer tactical questions. I spent about
10:14 the first year and a half when I when I
10:16 got into this AI stuff, I started the AI
10:19 learning lab and I started AI salon as a
10:22 way to just gather people curious about
10:25 AI. And for about the first year and a
10:28 half, it was just like trying to keep up
10:29 with the tech. What's this tech do? How
10:31 do you do the tech? What's chat GPT? Oh,
10:33 they just came out with a new model.
10:34 What's that? What's this? What's that?
10:35 What's that? And for the past year and a
10:38 half,
10:40 what became clear is you can't keep up
10:42 with it. I was doing it every night
10:46 and failed.
10:49 And you can't really learn it because
10:50 about the time you learn it, they change
10:52 it. And so it just it just felt like
10:55 this hamster wheel. And so I went
10:56 through this year and a half period
10:58 where I was still going live five nights
11:01 a week. I was still talking about this
11:03 stuff. I'm still passionate about it. I
11:05 was still optimistic about it. But
11:06 something was weird. I couldn't figure
11:08 out what it was. And a few weeks ago um
11:12 on one of my lives um this idea of the
11:16 great repurpose
11:17 just kind of emerged.
11:20 Um but it it didn't emerge out of
11:22 nothing. What this is, this is naming
11:25 something that I was feeling.
11:28 Um,
11:34 and so we're going to dig into it.
11:37 So, so a couple of things.
11:44 Well, I just I just request just come
11:46 with me on the ride. Okay. Um, this may
11:50 not seem like it's going to be relevant
11:52 to AI, but but it but but it is. Um, so
11:56 why the great repurpose? Why why do we
11:57 have to come up with with a name for
11:59 this? What does this actually mean?
12:02 There's a lot of people talking right
12:03 now about AI is going to take our jobs.
12:05 AI is going to take jobs. AI is going to
12:07 take jobs. Talk about it as an economic
12:09 crisis. Talk about as employment crisis.
12:12 And
12:14 what's been striking me is that yes,
12:17 that's going to happen. And if you've
12:18 been paying attention to AI, if
12:20 certainly if you're playing with it, the
12:22 tools in the in the last half of 2025
12:25 got dramatically better.
12:28 So, so like the past six months, the
12:30 tools have gotten dramatically better.
12:32 It is fairly clear to me that 2026 is
12:34 the year that we all we all confront,
12:38 oh, this is going to take jobs. Like up
12:42 to this point, it's like, yeah, it's
12:43 good, but we still need a human in the
12:45 loop. Right. 2026 it's it's it's
12:48 apparent that that this is going to take
12:50 jobs. That is a crisis. We need to deal
12:52 with the economic impact of that. Nobody
12:55 knows what that really means. But
12:56 there's something deeper and that is
13:00 jobs are under threat. But I think that
13:01 the invisible crisis that we're about to
13:04 enter is a crisis of meaning. And so the
13:07 great repurpose all of a sudden to me
13:09 was was something that came up. purpose,
13:12 meaning, you know, our meaning, our
13:15 self-worth, our identity um is very much
13:18 tied um to to work and and work is about
13:23 to change dramatically. And so the great
13:25 repurpose is about putting a name to
13:26 that. I want to tell you a story of so
13:31 so who are these three handsome
13:32 gentlemen? You know, this one this one
13:34 looks familiar. The guy in the center is
13:36 Chan Su. He was my co-founder at
13:38 agency.com. That's the the agency uh I
13:41 founded in the 90s and and the guy on
13:43 the left there is Paul Gall and Paul
13:46 Galley's nickname was Pub and Pub was
13:49 awesome. He was employee number one for
13:51 Agency.com. Agency.com was insane. We
13:54 grew to like 2200 people in five years.
13:56 It was it was an absolute insanity.
13:59 So we we were growing really really
14:01 fast. And
14:03 Paul was what we called the site
14:05 builder. So he built websites and we
14:07 would be hiring these kids coming out of
14:10 school and we would we were literally
14:12 hiring anyone we could. We couldn't hire
14:13 fast enough. It was just this crazy
14:15 time. And so what happened is he got
14:17 really good at building sites, but all
14:19 these people would get hired and then
14:20 they would get promoted around him. So
14:22 like these people that were working for
14:24 him were now getting promoted to
14:26 manager. He was just like I'm good at
14:27 building websites.
14:29 And there was a point at which it just
14:30 became weird where you know there were
14:32 people making more money than him. and
14:34 promoted and and they said, "Paul, you
14:38 know, we should probably promote you.
14:39 Like you you like no more than any money
14:42 here, you know." And he's saying, "Okay,
14:44 you know, I'll take more money." And so
14:48 we went off and did the new job.
14:51 And two months later, he walked into my
14:54 office
14:55 and he asked me this,
14:58 "Can I be devoted?"
15:01 He said, "I love building
15:04 I love building websites and I don't get
15:07 to do that now. I'm managing people.
15:13 Paul
15:14 is the analog version of what's actually
15:16 happening right now with programmers
15:18 with engineers.
15:21 The AI because the the frontier model
15:24 companies are creating these AIs that
15:26 are really good at programming first
15:27 because they want to use them to make
15:29 the AI better. they want to get. So it's
15:31 getting gotten better at programming at
15:33 first. So a lot of programmers
15:36 are not programming. And if you love
15:39 programming, if you're passionate about
15:40 it, you love the problem solving of it,
15:42 doesn't matter. And all of a sudden,
15:44 this thing just does it better than you
15:46 and your job is just kind of look at it.
15:49 They just got promoted into a job that
15:51 they may or may not want, right? So it
15:55 it you know he he was a guy that had the
15:57 guts and the clarity to understand that
16:00 he was miserable in that new position.
16:02 There's a bunch of people that are about
16:05 to be promoted into some sort of
16:07 different role. Um and I and I think
16:09 what it looks like is this.
16:12 As far as I can tell, there are three
16:13 major categories of job disrupt
16:15 disruption that are coming. Um the first
16:18 one is you may lose your job. A lot of
16:21 people are going to lose jobs.
16:23 um
16:25 certain sectors, the entire sector might
16:27 go. So, not only might you lose your
16:29 job, your 20 years as a customer service
16:32 manager, you know, if it's a, you know,
16:35 phone customer service center, um that's
16:37 likely all going to be AI. So, like that
16:39 whole sector might not be available. So,
16:41 so that's that's potentially happening.
16:44 There's a whole another category and
16:46 this is the the engineers that I just
16:47 talked about. You keep the job, but the
16:49 job fundamentally transforms. So now
16:52 your job is to babysit agents or or to
16:55 just check where you I was thinking
16:58 I don't know if anyone else has
16:59 experienced this. You know scratch off
17:00 tickets, lotto tickets. I used to love
17:03 scratch off tickets. You go to the
17:05 7-Eleven, you get the scratch off
17:07 ticket, you scratch it, you figure out
17:09 the crossword or the 10x multiplier, you
17:11 like it was a whole thing. You talk to
17:13 people and then you take it back to
17:15 7-Eleven and they scan it on the fancy
17:17 machine and go you win. it would confirm
17:21 you win. Well, we now have on our
17:23 phones, we've got the lotto app. I don't
17:26 know if you know this, you can just
17:28 scratch off the code on the bottom of
17:29 the lotto ticket or scratch off ticket
17:32 and scan your own ticket and see if it
17:34 won or not. You don't have to play the
17:36 game.
17:38 That's about to happen with work that
17:40 all these people that got really good at
17:41 playing the crossword game or the
17:43 scratchoff game, they're just like, "No,
17:45 no, we've got something that does that
17:47 now. Oh, you just scan the barcode.
17:49 Isn't that great? Right. Um, so that's
17:52 that's kind of, you know, version number
17:54 two. And and then version number three
17:57 is particularly for solopreneurs and
17:59 entrepreneurs and especially people
18:01 whose expertise is their product, right?
18:05 I know how to navigate this. I know how
18:06 to do this. I know how to do that.
18:08 There's a lot of people that that their
18:09 passion is their business. And I think
18:12 what that's going to look like is the
18:14 world just changes.
18:17 the phone just doesn't ring quite as
18:19 much.
18:20 You know, the proposals that used to
18:23 excite people are like, "Cool, right?"
18:26 Um, and you can't quite name why. So, so
18:28 this is a thing we're facing. I told you
18:29 I was going to take you on a journey.
18:30 It's getting bleak. I know it's dark.
18:38 And there's there's there's a lot of
18:41 anti-AI sentiment right now.
18:44 every time there's a major technological
18:46 change, this happens. I in the 90s, I
18:49 was asked to speak at a newspaper
18:50 conference. And I said, I can sort of
18:53 see what's coming with this publishing
18:54 thing. I said, I was in a room full of
18:56 editors and I said I said, what you
18:59 might want to consider is exploring
19:01 blurring the boundary between editorial
19:03 and advertising.
19:05 And the head of the conference stepped
19:07 up on the stage and thanked me and
19:08 walked me to the exit and told me to get
19:10 a cab and leave. So, so there is
19:13 resistance to technology. People don't
19:15 like change. Can we opt out of this AI
19:18 thing? No, we can't. This isn't
19:21 something we asked for, but it's not
19:23 going away.
19:26 The worldwide web was a very simple
19:29 technology. At the at the core of the
19:31 worldwide web was one technological
19:33 innovation. It was the hyperlink. You
19:36 could instead of having to type to go to
19:38 a different computer server, you could
19:40 click on a hyperlink.
19:42 That was the sole innovation of the
19:44 worldwide web. There was things layered
19:45 on it, but that was it. And the
19:47 worldwide web changed the world. AI is
19:51 like a thousand improvements like that,
19:53 like 10,000 of them. It's like nothing
19:55 I've ever seen. Like the the depth of
19:57 what's happening now and what it can do
20:00 is insane. And there's trillions being
20:03 invested in this. So, we can't escape
20:05 it. So, the only way forward is through.
20:11 There's another thing. And I know it's
20:14 getting dark. I'm going to pull us out
20:16 of this. It's going to be good.
20:20 We have an invisible contract. And I
20:22 think in in America, it's it's
20:24 particularly strong. I think we
20:26 influence the world. And that is we
20:28 silently agreed I am what I do. When I
20:32 meet you at a party, what do I ask you?
20:34 What do you do?
20:35 what do you do? It's wired into our
20:38 society that what we do the tasks
20:43 are in some way our identity and in some
20:45 jobs it's very direct but I think it's I
20:48 think it's a lot more I don't know
20:51 subtle and and and insidious than that.
20:54 I think it's pretty deep. Um this is
20:56 from from from a Gallup uh thing. 55% of
21:00 Americans say that their job gives them
21:02 their sense of identity. Among college
21:04 graduates, it's 70%. And AI is is about
21:08 to void that contract,
21:11 right? So, you know, however deep your
21:15 pride in your work is,
21:18 um that's about to change.
21:22 Um,
21:24 I just want to talk about three
21:26 different um,
21:28 like kind of hypotheticals of
21:31 the kind of folks that you might be in
21:34 this room right now or you might know.
21:37 Um, but but I just want to talk about
21:38 the the kind of things that people are
21:41 going through. Um, so if you think about
21:43 creative professionals, this is Marcus.
21:46 Um,
21:48 Marcus has been a creative director for
21:50 15 years. He's 38 years old. He used to
21:53 charge five grand for a job on average.
21:55 His clients pay him five grand to come
21:56 to do it. Now his clients are like,
21:58 "Hey, I'll give you 500 bucks. Can you
22:00 just take this midjourney thing I made
22:02 and make it suck less?"
22:04 Sure, I can do that. Right? So, so
22:07 everything changes. And and so Marcus
22:09 has a choice. Particularly in the in the
22:11 creative arts, this is bad, right? It's
22:14 like, do I refuse to use AI because it
22:17 threatens my sensibilities, right, and
22:19 become irrelevant, or do I use it and
22:22 betray the craft that, you know, that I
22:24 care so much about, right? So, it's like
22:26 neither of those are good choices, but
22:28 both of those are are are in his face.
22:31 Then you've got sort of displaced
22:33 executives. This is Sarah, um, you know,
22:36 VP of marketing for 18 years, things
22:38 like that. you know, she asked, "Should
22:41 I pretend that I'm 30 and and learn
22:43 prompt engineering or do I just sort of
22:45 accept it that my 20 years of experience
22:47 is nobody cares about that anymore?" Uh,
22:51 then you've got James who who's an
22:52 independent contractor, marketing
22:54 consultant, 20 years, you know, charging
22:57 250 bucks an hour
22:59 that they can now get the answers for 20
23:01 bucks a month with Chad GT.
23:05 Um, you know, and you know, he's got
23:09 these this this awful choice as well. Do
23:11 I compete with AI or do I redefine what
23:13 it means to be an expert? And I think a
23:16 lot of people are struggling with this
23:18 today. Like I don't think we have to
23:20 wait for a AI to get much better. If
23:22 you're in the creative arts, if you're
23:24 an ad agency, if you're a consulting
23:25 company, anything where where expertise
23:28 is is your core skill, I can just ask
23:32 Chad JP now. Probably it certainly knows
23:34 it faster and it probably knows the
23:36 deeper. So, how do you compete with
23:38 that?
23:40 The options are are kind of dis
23:42 distasteful and terrifying, but there's
23:44 a new choice. And this is what I want to
23:46 talk about. We're about to take a turn
23:48 here. We're going to take a little
23:49 journey. We're going to take a turn.
23:50 We're going to make the turn.
23:55 The new choice is we all get to sorry
23:59 we're all being forced into a world
24:01 where it would be wise for us to do to
24:05 rediscover who we are
24:08 and then let AI amplify that. So there's
24:12 a crisis of meaning here. But the ironic
24:14 thing is and this is why I'm so bullish.
24:18 The very tool that is going to force
24:20 this change on us is also the tool that
24:23 likely will allow us to navigate our way
24:26 out of this if we can figure out who we
24:28 are and what we're passionate about.
24:30 That's what we're going to talk about.
24:31 So, um,
24:36 so in a moment, but not yet,
24:41 I'm going to ask you to close your eyes
24:43 and I'm going to we're going to
24:44 visualize something about your world.
24:46 Okay, good. Willing to go there in a
24:50 moment, but not yet. It's nothing weird.
24:52 We're not gonna do anything weird. I
24:54 promise. Um, but so first what I'd like
24:56 to do is this. Just because I've been
24:58 talking for a bit, just everyone stand
25:00 up
25:02 and just like shake your arms out. I'd
25:04 like you to take a a deep breath in
25:08 in through your nose,
25:10 out through your mouth.
25:14 between your nose.
25:18 I know you're thinking like, I thought
25:19 we were going to be vibing tonight. It's
25:21 okay. It's okay. Get through your nose.
25:28 Okay. So, sit down.
25:35 So, I'd like you to close your eyes.
25:38 I'm just going to take us on a little
25:40 journey.
25:43 I want you to think about a normal
25:45 Tuesday at work.
25:47 Today's Tuesday. Think last Tuesday.
25:51 And what I want you to think about is
25:55 all the tests that you did. What what
25:57 were the the emails that you sent, the
25:59 calls that you made, the presentations
26:02 that you made, if you make cabinets,
26:05 sanding the wood? I want you to think
26:06 about the task, all the tasks that you
26:08 did.
26:11 I want you to really think about the
26:13 things that you're good at in those
26:15 tasks, right? Are you good at language
26:17 and emails? You can you know how to
26:19 respond to an angry email or what are
26:20 the things you're good at? What are the
26:23 things you love to do?
26:27 Um
26:31 I also want you to think about things
26:32 you you might not like, but you're
26:35 actually really good at that people rely
26:37 on you for. Right? There's there's
26:38 things that you've gotten good at over
26:40 the years. I want you to think about the
26:42 things you went to school for. I want
26:44 you to think about the things you
26:45 learned on your own and take great pride
26:46 in that. You figured it out.
26:53 And I want you to think about the things
26:54 that you do that when you do them right,
26:57 it just it feels great.
27:00 Got it?
27:02 Okay. Keep your eyes closed.
27:06 Now, imagine, so it's Tuesday night. You
27:08 go home, you have a nice dinner, you
27:10 watch some good TV shows, you get a good
27:11 night's sleep,
27:13 you go back into work on Wednesday,
27:18 and you sit down at your desk, and what
27:21 you learn is that every single task that
27:26 you were assigned to do on Tuesday
27:29 has already been done for you.
27:32 And not kind of done, like done,
27:34 perfectly. like better than you could
27:36 have done. You still have your job,
27:41 but none of those tasks need you
27:42 anymore. I want you to really take that
27:44 in. Imagine yourself at the desk. All
27:46 your tasks are done.
27:50 I want you to keep your eyes closed and
27:51 just if you can think of a single word
27:54 of how that makes you feel, just just
27:56 say it out loud.
28:01 >> Useless.
28:02 >> Useless.
28:02 >> Relieve.
28:05 Freedom.
28:07 >> Freedom.
28:08 >> Freedom. Yeah.
28:10 Good. Okay.
28:13 Now, keep your eyes closed.
28:17 I want you to go back to that Tuesday
28:19 morning. You still have all the tasks to
28:22 do. The magic day when all the tasks
28:24 were done hadn't happened. You've got
28:27 emails to respond to. You got PowerPoint
28:29 presentations to, you know, you got got
28:32 order supplies. whatever it is.
28:36 And now I want you to think about
28:38 something different on that day. Not
28:40 what you did. I want you to think about
28:43 how you showed up.
28:46 Are you the one that asks really good
28:48 questions? Are you the one that makes
28:50 people laugh? Are you the one who sees
28:53 patterns? Do you show up and see
28:54 patterns?
28:56 Are you the one that refuses to ship
28:58 until it's absolutely perfect?
29:04 What changes in a room when you're not
29:06 there?
29:07 What's missing when you're not there?
29:12 That's the how you show up.
29:18 That's underneath the tasks. That's the
29:20 thing that can't be automated.
29:25 No, I want you sort of let your the
29:27 image of your work environment just
29:29 drift away.
29:32 Take a deep breath and just let it drift
29:34 away. So now you're just in a void.
29:37 We're going to move deeper.
29:42 Sitting underneath how you show up at
29:44 work
29:46 is you.
29:49 I want you to think about why you show
29:51 up that way.
29:53 I want you to think about what do you
29:55 value?
29:57 What do you care about? What are you
29:58 passionate about?
30:00 What's your taste?
30:03 Why is it that you show up at work in
30:05 that in that particular way? What's your
30:07 judgment?
30:09 What's the thing of who you are when
30:11 someone at work or your family or your
30:13 friend says that's so you,
30:18 her,
30:20 him.
30:26 That's who you are.
30:28 AI can do the tasks. AI might mimic your
30:31 approach. It might do the tasks better
30:33 than you do,
30:35 but AI can't be you.
30:40 Okay?
30:42 So, I want you just take a deep breath
30:43 and as you
30:46 let the breath out, slowly open your
30:48 eyes.
30:58 I'd love to hear
31:04 what it felt like to get clear of that
31:08 separation of the tasks that you do from
31:10 who you are. Any any insights?
31:14 I felt sad and sad about what was the
31:18 sadness that I lost. I lost me. Yeah.
31:32 >> Maybe I should spend more time with my
31:33 family
31:35 or something. But then I went back to
31:38 the
31:40 money,
31:41 >> right?
31:46 >> Yeah. Yeah. Yeah. Who who you are is
31:48 important, but if you're in survival
31:49 mode, Yeah. This is rough stuff and this
31:52 is this is something that we're going to
31:53 all have. Great. What else? Yeah,
31:55 >> I'm a German immigrant and recent like
31:58 US citizen and I'm very much tapping
32:01 into what you said about the culture
32:03 difference.
32:04 >> Yeah.
32:04 >> I'm I'm currently looking for a new
32:07 opportunity. I'm very much aware of who
32:08 I am, but I feel like there's no value
32:10 put on that glue or the how you show up.
32:15 It's task and do as much as you can of
32:17 it. And it's like ROI and it's I feel
32:21 like I bring so much more.
32:22 >> Yeah.
32:23 >> And I feel like it's not really it's not
32:26 physically there. It's not, you know,
32:28 you can't put the number on it.
32:30 >> It's well, they call it in business,
32:31 they call it soft skills, right? You've
32:33 got your hard skills. Those are the
32:34 tasks
32:35 >> and your soft skills. HR people when
32:38 they have good budget, they talk a lot
32:40 about soft skills. Oh, we're going to
32:41 develop the soft skills. And the minute
32:43 budget cuts come, the soft skills
32:44 training goes away,
32:46 >> right?
32:47 >> Production. Production production.
32:49 Right?
32:50 >> And this is listen this is no one's
32:52 fault in this room. Like that's all
32:53 carried over from the industrial
32:55 revolution. Right? Time equals money.
32:57 This is a long tradition. This is how
33:00 this is how business work. This is how
33:01 you make cabinets. Like it this is time
33:04 equals money. Right? The tasks. So so
33:06 that's so there's all this value placed
33:08 there.
33:10 And yet that that thing of of how you
33:12 show up and who you are ultimately in
33:15 the end that's why they hire you. But
33:17 where the value is placed right
33:19 What other insights? I know you had
33:21 >> I did um I felt a I I do this personal
33:25 brand work so I I do this a lot with my
33:28 clients, right?
33:29 >> And I thought I have a deeper self
33:33 agency sense.
33:34 >> Ah,
33:35 >> when I realized that I can I can take me
33:37 and pluck me in, put me in anywhere and
33:40 I can be of value because I have a
33:43 unique skill set in my own DNA.
33:46 >> Yes. Yes. of being able to see things,
33:48 touch things, you know, alignment came
33:51 up for me and consistencies came up for
33:52 me. I'm all about that.
33:54 >> Yeah.
33:54 >> In my job, but it's because it's within
33:57 me. It's not it's not something outside
34:00 of myself. It's inside.
34:01 >> Yeah.
34:02 >> Yeah. Beautiful. Really good. Really
34:05 good.
34:06 >> Um, do you all know the music producer
34:09 Rick Rubin?
34:11 That one? Yes. He's like, you look like
34:13 Sam had a big beard.
34:16 He produced the Beasty Boys. He produced
34:18 Red Hot Chili Peppers. Produced the Del
34:20 like famous Grammy award-winning like
34:23 many of the songs, you know, from your
34:24 childhood and beyond a Rick Rubman
34:27 produced.
34:30 He doesn't write music. He doesn't play
34:32 an instrument. He can't sing. He doesn't
34:34 work a recording console. He's got no
34:36 skill. He he sort of proudly declares
34:39 his lack of tactical execution skills.
34:46 Why do they hire him?
34:50 Because of who he is.
34:52 Because of his taste,
34:55 right? What Rick assumes is I assume
34:59 that the musicians will do their bit
35:01 with their instruments and their voice
35:02 and the engineers will do the turn the
35:05 knobs and do the thing. My favorite
35:07 recent story of Rick Rubin's Betty
35:09 Blanco was talking about a a recording
35:13 session he did with Ed Sheeran and um
35:16 they were at Rick Rubin's estate and
35:18 Rick Rubin's like out walking and being
35:20 the hippie that he is and just walking
35:23 around and they're recording. They're in
35:24 the studio. They spend like four hours
35:25 recording this song. Rick finally comes
35:27 in and they're like, "You want to hear
35:28 the track?" He's like, "Yeah."
35:31 And they play him the track and he goes,
35:33 "Yeah, yeah,
35:36 makes me feel orange."
35:39 And he left
35:43 me feel orange. Billy Panco said they
35:46 spent six hours trying to figure out how
35:48 to change the song so it would make Rick
35:50 feel less orange. They didn't know what
35:52 it meant.
35:54 But when he came back six hours later,
35:56 he goes, "Yeah, that's the song,
35:59 right?
36:07 The more I learn about,
36:11 the more it becomes clear to me
36:14 that who we are will be our job."
36:21 Because if the I is going to automate
36:23 the tasks. If AI is going to automate
36:25 the thing that everyone values right
36:26 now, what's left?
36:31 What's left is is the kind of thing
36:34 where you know you're human
36:36 and this is what we currently value.
36:39 This is what you're experiencing trying
36:40 to get a job right now, right? What do
36:42 you do? Why do these things? Well, we
36:44 don't value those things, right? Or you
36:47 don't you're too expensive for those. We
36:48 want to pay whatever. Then there's the
36:51 the how you do it. And and notice that
36:53 the what you do is fading away. Like I
36:55 really do think that's where we're
36:57 headed.
36:58 And and while it's scary,
37:02 every technological
37:04 transformation in history has felt like
37:07 if if that thing goes away, what are
37:10 people going to do? We're not we're not
37:12 going to we're human beings. We will
37:13 adapt.
37:15 But but that's about to happen. The what
37:17 you do is about to go away. And then
37:19 there's the who you are, right? And so I
37:22 where I start to get to is the clearer
37:24 we can become individually and for each
37:26 other on the value of this and who we
37:28 are and how we show up,
37:31 this starts to become a recipe for the
37:34 path forward. Um, so when I was thinking
37:38 about
37:40 I started the AI salon, the WeChat GPT
37:42 came out. So, so we've got about 4,000
37:45 members in there who are curious about
37:46 AI and doing remarkable stuff. with AI
37:49 and trying to figure it out and going
37:50 through a lot of this stuff. We we've
37:52 recently started a thing called the the
37:54 mastermind practice where people in the
37:56 salon are creating a daily practice
37:59 around how they use AI. And so I was
38:02 thinking about like what are the steps,
38:04 what are the stages if we're all going
38:06 to be forced into effectively an ego
38:10 death,
38:14 right? I've seen lots of knots. Maybe
38:16 you're in it right now. Maybe you're
38:18 like, "Oh, I didn't see that coming."
38:20 Right? You said, "What did you say? I
38:21 feel useless." Right? That's an ego
38:23 death,
38:24 >> right? I get up in the morning, I go to
38:26 Wait, a robot does that now?
38:29 What What about What about me?
38:36 So, this is coming.
38:39 So, I'm going to I'm going to share what
38:41 I think are are five steps of a path
38:43 forward, but these are not linear. I
38:46 mean, feel free to write them down, but
38:48 but the first one is is kind of the
38:50 exercise that we just did.
38:53 Unhook your identity from it's I'm not
38:57 my job, right? To the degree that you
39:00 can separate yourself from the tasks,
39:02 your identity from the tasks,
39:09 you won't get sucked as easily into I'm
39:12 useless. I'm worried.
39:15 I'm not my job, but I am this. Reclaim
39:18 your value. What are you? Who do you
39:19 stand for? How do you show up? Like, if
39:22 you're a professional in this world, how
39:24 you show up
39:26 is really valuable, right? That's why
39:28 they keep you.
39:32 Find your purpose.
39:36 What matters to me.
39:39 When you ask the question, who are you?
39:42 What do you value? Who do you care
39:44 about?
39:45 What do you want to do for them? What do
39:47 you want to do in the world? Do you want
39:49 to do something for your family? Do you
39:50 want to do something for your town, a
39:52 community center? Do you want to change
39:53 the world?
39:56 Like a lot of work right now is designed
39:58 so that we never have to think about
40:00 this and
40:03 those tasks are about to be ripped away.
40:07 So, so the sooner you can start thinking
40:10 about this and then here's what now we
40:12 start to get into the tool that is
40:15 taking the tool that is causing this
40:17 crisis may also be the tool that lets us
40:20 navigate out and I think it will
40:25 you play with AI do you play with it a
40:27 lot.
40:29 We're gonna we're gonna this this
40:30 conversation is going to shift into much
40:32 more practical what to do. Okay, great.
40:35 Kyle, I feel horrible now. I've been
40:37 deidentified. I feel useless. What are
40:40 we going to do about it? One important
40:42 thing is to actually understand what
40:44 these tools make possible.
40:47 I don't know how deep you've dug, but it
40:49 is remarkable. I had a conversation with
40:51 Ron earlier here who's he teaches
40:54 welding and he's got all sorts of AI
40:56 with Ron. He's a
40:59 >> he's awesome.
41:01 >> Yeah.
41:01 >> Okay.
41:02 >> Yeah. He's like telling me all this
41:03 stuff. He goes, "Yeah, I teach kids how
41:05 to weld." I'm like, "Oh, that's cool.
41:06 People are going to need to be weld."
41:08 And then he tells me like these 20, he's
41:09 got bots and AI things and AI visors
41:12 that let sight impaired kids see the
41:15 welding. Like crazy stuff. So anyway,
41:19 get a start to palpably understand
41:23 what's possible and I'm going to give
41:25 you some tools for that and start
41:28 building, start creating.
41:32 Once you discover what matters to me,
41:35 what's possible, the change you want to
41:38 be in the world,
41:40 you don't have to wait. You don't have
41:42 to wait to get funded. You don't have to
41:44 wait until you understand how to write a
41:47 business plan. You don't have to wait
41:49 until I You don't have to wait.
41:54 Right? The era of talking
41:58 is over.
42:01 You nobody got time for that, right? You
42:03 see that video? Anybody got time for
42:05 that? Time to start building. Okay,
42:11 I promise you this is going to turn
42:12 toward the light. You ready? Turn toward
42:14 the light.
42:16 So, in the AI salon,
42:25 people started showing up in really
42:27 remarkable ways. They would they would
42:30 come into the salon
42:33 not knowing anything about AI. They'd
42:34 just be curious and and they would start
42:37 teaching one another. Here's what I
42:38 learned and here's what I learned. And
42:40 and and they would build these
42:43 remarkable things and they would there
42:44 were people were are people coming out
42:48 of retirement. They're so excited about
42:50 what they discovered was possible.
42:51 They're coming out of retirement.
42:53 They're changing jobs.
42:56 And after about a year, year and a half
42:58 of this, um,
43:01 the woman who's now the co-host of AI
43:03 salons is this woman named Liz Miller
43:05 Gersfeld.
43:06 And
43:09 Leah Fasten, who who co-founded the
43:11 salon with me. We were talking to Liz
43:13 and like, Liz, you've been here like a
43:15 year. It seems like you're really doing
43:16 good with with this AI stuff. And and
43:19 she described her experience. She said,
43:21 well, I got here and I and I I saw the
43:23 meeting and what you were talking about
43:24 was interesting. So, I went and I
43:26 watched all those videos and then I just
43:29 went and every tool that you talked
43:31 about in those videos, I wrote it down
43:33 and I went and I started playing and
43:35 then I I learned, right? And so, what
43:38 she described is what we now call the
43:40 cycle of AI readiness.
43:43 And so we created this about two years
43:45 ago. And the more that
43:48 I learn about AI and I learn about how
43:50 how people are doing remarkable work
43:52 with it, this is the cycle
43:56 like like we haven't veered from it. We
43:58 we changed one one word here, but it's
44:00 it's effectively the same thing. Play
44:03 first,
44:05 create excellence, generously lead. And
44:08 I'm going to walk you through these. Um,
44:12 this isn't a curriculum. This is not AI
44:14 literacy. One of the one of the We used
44:17 to talk a lot about AI literacy. AI
44:19 literacy is a fallacy right now. The
44:21 tools are changing so fast that you
44:23 can't be literate, but you can be ready.
44:26 Um,
44:34 here's a fun thing that this unlocks.
44:46 I was going to talk about this later,
44:47 but I think I'm going to talk about it
44:49 now.
44:52 I want you to close your eyes.
44:55 Sit up. Shake your shoulders out. Close
44:57 your eyes.
44:58 Take a deep breath.
45:09 I want you to think about, you know, how
45:11 you know how in life there's things
45:12 you're good at
45:15 and then and then there's these gaps,
45:17 the things you're not good at.
45:21 I want you to think about all those
45:23 things you're not good at.
45:26 Those are your gaps.
45:29 And there's a kind of gap that I think
45:31 about that I now call aching gaps.
45:35 And aching gaps are those things that
45:38 you're not good at that you know you're
45:40 not good at that you would really love
45:43 it if you were.
45:45 You know those
45:47 aching gaps. There's these things that
45:49 we know, right? Stepdaddy told us we
45:52 couldn't draw when we were seven,
45:54 whatever it is. And you know, we shut
45:56 down that part of our brain. But but boy
45:58 would we love to drum. Boy, we're not
46:00 good at drug. Right? We've all got this,
46:02 right?
46:06 Think about your income. What are the
46:08 things that if you could do them
46:12 that would be amazing?
46:14 So, open your eyes. I'd love to just
46:15 hear what came up for you.
46:21 What's something you're not good at?
46:25 >> Playing the piano. Play it again.
46:28 Perfect.
46:29 What else?
46:32 You have a smile here. You're avoiding.
46:35 >> I'm going to bear it. Okay. I'm I'm
46:37 really good at ideiation. I love getting
46:40 stuff off the ground. I freaking lose
46:42 interest when it comes to follow through
46:44 and
46:45 >> perfect. I'm right there with you. ADHD
46:49 cardarian number ADHD.
46:52 >> Never been clinically.
46:54 diagnosed but you know love the ideas
46:56 hate the execution right some people
46:57 love the execution would love to be
47:00 ideas
47:03 what AI does what this cycle unlocks
47:07 is we now now today
47:11 actually live in a world
47:15 where you can legitimately ask yourself
47:17 the question
47:20 if I were good at everything.
47:24 What would I choose to do?
47:30 The thing you know you can't do, you can
47:32 actually do it. Piano. Have you played?
47:34 Have you been to sunno.com?
47:37 >> Go to sunno. Go right now. Type in piano
47:40 concerto about a golden retriever.
47:43 Whatever. Whatever. And
47:44 >> it'll do it for me.
47:46 >> Beyond what you can imagine. In fact,
47:49 I'm going to play a song later that was
47:50 created assuming.
47:54 So So that's what this unlocks.
47:59 >> Who's the um
48:02 the woman who does really cool AI
48:04 videos?
48:04 >> Kelly Bes.
48:06 >> That's the type that's what really gets
48:08 me excited about what I can do with AI.
48:11 >> Yep. Kelly Bes. I'm going to talk about
48:13 her actually, but so Kelly Bes, if you
48:15 go to Tik Tok, it's uh Kelly, K E L O Y,
48:19 and then her last name is B O E S C. You
48:22 know,
48:22 >> I love her.
48:23 >> She is remarkable. She does a video a
48:25 day, seven days a week with an original
48:28 song, a music video with an original
48:30 song days a week.
48:32 >> How does she make money though? Because
48:33 it's on
48:34 >> Well, so she monetizes it.
48:36 >> So what's happening with Kelly right
48:38 now? So So Kelly went from I just do
48:40 this, no one cares. I've got my day job.
48:43 Then Kelly started getting offers to
48:46 come do work
48:48 and we were paying and some of them were
48:51 big brand deals and they were paying her
48:52 kindly and I I was funny. I talked to
48:54 her like six months ago. I said, "How's
48:58 it going?" She's like, "I'm so busy.
49:00 They're kind of coming after I just said
49:02 she goes, I got all these jobs. They're
49:05 paying me all this money." I'm like,
49:06 "That's awesome." She goes, "I hate it."
49:09 >> Oh no.
49:11 because she makes the videos because
49:13 they're pure expression of who she is.
49:16 She got a call about three months ago
49:19 from the screenwriter of one of Tim
49:21 Burton's films
49:24 who wants to make a movie with her. So,
49:28 what I'm what I'm what I'm experiencing,
49:30 what I'm witnessing in the AI salon is
49:32 people.
49:37 When I asked her, she she spoke at the
49:39 salon a couple of times. And
49:43 her visuals are so unique. They're
49:46 they're so remarkably unique.
49:50 And and what everyone was asking her is
49:52 like, "How what are your prompts? What
49:53 are your prompts?" And my thing was
49:55 like, where is this coming from? And
49:58 like her answer was
50:01 for my entire life I've had these ideas.
50:05 I've had these visions in my head and
50:07 now I can suddenly make them. So it's
50:10 like they were already in her. All she's
50:12 doing is kind of releasing who she is
50:16 amplified by this tool that doesn't make
50:19 any sense that it should exist in the
50:21 world. You should not be able to just
50:23 say give me a song and you get a song.
50:24 You should not be able to just say,
50:26 "Give me a remarkable piece of fashion
50:28 and there it is." That's where we are,
50:30 though.
50:32 We're in that world.
50:34 I I often think when you ask that
50:37 question about her artistry and how did
50:40 she do it, makes me feel like it's like
50:42 asking a magician how he did his trick.
50:45 >> Exactly.
50:46 >> You know, you just just enjoy
50:48 >> just enjoy
50:49 >> the art of it.
50:51 >> Yeah. Yeah. And the other part of your
50:52 question, we'll get into this a little
50:54 bit here, but the other part of your
50:55 question, how does she monetize it?
50:57 Well,
50:59 there's lots of ways you can monetize
51:01 anything, right? But that's a different
51:03 that's a completely different task,
51:05 right? What she could do is maybe she
51:08 doesn't know anything about intellectual
51:10 property or starting a movie studio,
51:12 right? But she could go use Chat GBT to
51:15 teach herself about how to set up a
51:18 movie studio. What are the licensing
51:19 rights? who gets paid when I get
51:22 distribution and how do I get
51:23 distribution and where should I be
51:25 submitting these things? She didn't want
51:27 to do that. She just wants to make her
51:28 movies and now she's on a path where she
51:30 might be able to make feature films like
51:32 this, right? But she could have
51:34 absolutely gone another way. I mean, I
51:36 think it's what you're bringing up is an
51:38 important part of the conversation. You
51:40 brought it up before. If you're just in
51:42 survival mode,
51:46 aspiring to the higher version of
51:48 yourself may seem a little fruitful, but
51:52 we also live in a world where we have
51:55 these tools at our disposal where we
51:57 might be able to do something for money
51:58 we never imagined we could even think
52:01 about starting. Now we do, right? So, so
52:05 they're not mutually exclusive. Um, but
52:07 but if you're just in survival mode, it
52:09 might be you follow Gary Ve's advice and
52:12 you go to yard sales and buy things for
52:14 50 cents and sell them online for five
52:16 bucks and just do that enough and make
52:18 yourself a thousand bucks and keep
52:20 moving. Okay. So, so we're going to talk
52:23 about the the the three elements of the
52:26 cycle of AI readiness.
52:28 A thing that we practice in the in the
52:30 AI salon mastermind practice
52:34 is when you sit down with AI, if you
52:36 want to be intentional about AI, if you
52:37 want to be intentional about anything,
52:39 playing, learning, doing,
52:43 take a moment, as weird as it was that I
52:46 had us breathe deep and shake and do our
52:48 visualizations, take a moment when you
52:50 sit down in front of AI, just close your
52:52 eyes, take a deep breath, and say, "What
52:54 is my intention right now? What do I
52:56 want?
52:58 Because AI is like a crack,
53:02 right? It is. It's like a crackpipe. You
53:05 sit down at it and four hours later
53:07 YOU'RE LIKE, "I MADE ALL this stuff.
53:10 What is all this stuff?" Right? I'm a
53:12 digital hoarder. Do you know how
53:14 horrible it is for me to have an AI? It
53:17 just it makes more
53:22 So So this moment, what what's what's
53:25 happened in the in the AI on mastermind
53:27 practice. So this is it's I don't know
53:29 there's 25 to 30 people in it and it's
53:31 growing
53:32 and we meet weekly and we talk about
53:38 we we talk about what do we want what do
53:41 we want to do what are we trying to
53:43 accomplish what's working not everyone
53:46 went into that as we started designing
53:47 these daily practices what the common
53:50 theme was was like I'm overwhelmed this
53:52 is all frenetic I can't keep up I can't
53:53 keep up
53:55 and what's happened is As people started
53:58 doing this work to kind of center
54:00 themselves before they sit with a to a
54:03 person, what they've all said is, "Oh,
54:05 I've slowed down. I've slowed way down.
54:08 I'm not as stressed out anymore because
54:11 I'm thinking, huh, I want to accomplish.
54:14 I'm going to go use AI in that way." So,
54:17 so if you're feeling that frenetic pull
54:19 of the virtual crackpipe, um, this is
54:25 centering yourself, putting yourself at
54:26 the center of the conversation is really
54:28 important. Okay, play first.
54:35 Play
54:38 play
54:42 for all of our lives.
54:46 Computers
54:48 computed.
54:51 It was profound. He talked about
54:53 computers computed.
54:55 Sorry, just I just realized the the
54:58 ridiculousness of the sentence. Um
55:02 but but computers you would take data
55:03 and you'll put it into the computer or
55:05 process it and and a new result would
55:08 come out the other end. It was
55:10 predictive. It was linear. And what we
55:12 did with computers was we took what we
55:14 did and we made it more efficient.
55:16 Right? That's what computers were. We
55:18 take doing math on paper, we put it in a
55:20 spreadsheet. Now the math we do on paper
55:22 is more efficient. Right? That's what
55:23 they've always been. the G and GPT
55:27 generative. We're now in the generative
55:30 area era. The computers are are doing
55:32 stuff.
55:36 What most people are doing with AI right
55:38 now is they're like, let me take my
55:40 existing processes and make them more
55:42 efficient.
55:44 And so what that does is it literally
55:46 puts blinders on them that the only
55:48 thing AI can do is write my emails
55:50 slightly crappier than I do really fast.
55:54 Right. So, a lot of people leave AI
55:56 because they're like, "I tried it. I
55:58 tried it. I had it write me an email. I
56:00 kind of sucked.
56:03 Play
56:06 let you discover what's actually
56:08 possible because again, the world has
56:10 changed. Not that many people knowing
56:11 it." Um,
56:15 so the first thing to do is with play,
56:18 explore AI without expectations. If you
56:21 go in and say, you know, I want it to to
56:23 create a B flat minor, whatever on the
56:26 piano, and maybe it does that, maybe it
56:28 doesn't. So, if you lose the
56:30 expectations and you just go play,
56:33 you will discover things it can do. You
56:35 will discover boundaries of its
56:37 capabilities that will melt your face.
56:40 And if you played, I mean, you played
56:42 after, you know, last talk I gave up in
56:46 in Denver. Um and you know I in in the
56:49 AI salon we call them Kevin Mallister
56:51 moments. You remember the movie Home
56:52 Alone
56:54 that moment.
56:56 So play without explore without uh
56:59 expectations. The second one is play
57:01 with purpose.
57:03 Explore joyfully. Like we're living in a
57:07 postci world. Like we're living in a
57:09 world where you can just make stuff. You
57:11 can just do stuff.
57:14 You don't know how to write a business
57:15 plan? How you do? Oh, like finding joy
57:18 in that. There is there is there's
57:20 magicalness to it, right? What is it? Is
57:22 it Arthur C. Clark? Any technology
57:25 sufficiently advanced is
57:26 indistinguishable from magic. Where is
57:28 the magic era? This stuff is magic.
57:32 Um
57:35 what planning with purpose also does is
57:38 you want to
57:40 celebrate and explore the failures.
57:44 You tried to do something and it failed.
57:47 You tried to write a business plan and
57:48 it just kept repeating the the points in
57:50 it. You're like this is a mess. What
57:53 happens when you when you discover the
57:54 failures of AI is you're actually
57:56 learning the boundaries of it. And what
57:59 that allows you to do is know that boy,
58:02 when that limitation gets better, this
58:05 thing's going to be amazing. You'll be
58:07 at the front of the line of knowing why
58:10 the next model release is actually
58:12 valuable. Make sense?
58:15 And then the third one, and this is
58:17 really important, learn across domains.
58:18 This gets to those aching gaps.
58:21 When you play with AI, purposefully
58:25 go play with something you're bad at.
58:29 Go find something that you know you
58:32 can't do and go find an AI that can do
58:34 that
58:36 because what you now get to say is, "I
58:38 actually can do that." If you could do
58:41 that thing that you've always wanted to
58:43 do, what would you do?
58:48 There's a guy I'll I'll give a fun
58:50 story. How we doing on time? We're good,
58:52 right?
58:53 >> Cool.
58:54 this guy Jim Ross in the AI salon, he's
58:57 in the storage business. Um,
59:02 not like SSDs, not data storage. He's in
59:05 the self storage business, like
59:07 padlocks,
59:08 cardboard boxes.
59:11 And so he he he's the people that show
59:14 up to my my nightly live, they're called
59:15 the irregulars. They name themselves
59:17 that these people just kept showing up
59:19 night after night after night as I'm on
59:21 the lives talking about AI.
59:23 One night I said, "You all are effing
59:25 weird."
59:27 And and Serena just one of the one of
59:30 the irregulars back, "We're not weird.
59:31 We're irregular."
59:33 Um, which I thought was hilarious. So
59:35 like, "Well, that's your name now." So
59:36 So they're the irregular. So Jim's an
59:38 irregular. So he comes to these lives
59:40 all the time. So one night someone said,
59:42 "How do you make a song with Suno with
59:44 with with these AI tools?" And so I
59:46 said, "Oh, okay, cool." And so I went in
59:48 and I started making this song. And I
59:50 was making it and made it. We were
59:51 listening to 30 different things that
59:53 came out
59:55 and and Jim goes, "Kyle, you won't
59:57 believe what just happened." I'm like,
59:58 "What?" He goes, "Well, you showed us
1:00:01 how to make a song." So, I just had a
1:00:03 meeting with with these prospective
1:00:05 customers. And so, I went into Sunno and
1:00:08 I went to Chatt and had write some
1:00:09 lyrics about what I knew about the
1:00:12 customers. And I went to Sunno and had
1:00:13 to make a song. And I sent it to him.
1:00:15 And five minutes later, he got an email
1:00:17 saying, "You're hired." So, how do you
1:00:20 monetize it?
1:00:22 >> He's in the self- storage business, and
1:00:24 he composed an original song for a sales
1:00:27 prospect and sent it to them at 9:00 at
1:00:29 night and got the job.
1:00:33 We're living in weird times. It's
1:00:35 surreal.
1:00:37 Like, if you can understand who you are,
1:00:40 what you value, and just be open to the
1:00:43 possibility, play,
1:00:46 you get to do stuff like that.
1:00:49 it just it doesn't make any sense. And
1:00:51 then but when he said it was like holy
1:00:54 crap,
1:00:55 this stuff works. And now he's like, you
1:00:58 know, he's he's like known for this
1:00:59 stuff. Um
1:01:06 next slide.
1:01:11 The second phase of of of the cycle of
1:01:14 AI readiness is create excellence.
1:01:17 So what play is about what play first is
1:01:20 about is about
1:01:22 learning what's possible right while you
1:01:24 play without expectations while you play
1:01:26 with joy while you look for the
1:01:27 boundaries is that lets you know what's
1:01:29 now possible
1:01:32 create excellence is is about now saying
1:01:35 what do I want to do
1:01:37 what do I want to do maybe
1:01:40 the you you realize okay I like
1:01:44 cabinetry but something's coming with
1:01:46 But, you know, one of the things people
1:01:48 have trouble with is, I don't know,
1:01:50 imagining what cabinets could do. And
1:01:52 like you could buy code, you could
1:01:55 create an application that lets people
1:01:57 discover things that ties directly to
1:01:59 how you work, right? There's who knows?
1:02:01 So, so you're going to you're going to
1:02:02 go into some you're going to have some
1:02:04 idea based on who you are, what you
1:02:06 value, change you want to make in the
1:02:08 world. Now, you get to start building
1:02:10 stuff. Um,
1:02:16 one of the things that AI is doing is
1:02:19 it's raising the floor
1:02:22 of quality. So, there's this phrase that
1:02:25 people talk about called AI slop
1:02:28 and and what they talk about is when
1:02:29 people just push a button on Suno and
1:02:31 make a song and then publish that to the
1:02:33 world. It's just like this soulless
1:02:35 creation, right? and and everyone can go
1:02:37 to midjourney and you can just type in
1:02:39 discovery and it'll make beautiful
1:02:40 images and you can just share those with
1:02:42 the world. That's AI slop. So AI slop is
1:02:44 just everyone gets to push buttons and
1:02:46 crap comes out and then I share them
1:02:48 with the world and there's just this so
1:02:51 so the the floor of quality was down
1:02:53 here and now AI has raised it to here.
1:02:57 That's still the floor,
1:02:59 right?
1:03:00 What are the things that rise above
1:03:04 the floor?
1:03:06 How do you raise the ceiling?
1:03:11 What was it about Billy Isish in a world
1:03:14 of pop music
1:03:16 that when she sang her song in her weird
1:03:21 quietish kind of magical way rose above
1:03:24 the It was so authentic to her. It was
1:03:27 not like all the rest.
1:03:30 What is that? That's you,
1:03:33 right? So, create excellence is about um
1:03:38 you know, thinking about the thing
1:03:40 you're trying to accomplish, the thing
1:03:42 you want to build and starting to build
1:03:44 it. Um
1:03:50 raise your game is is another thing to
1:03:52 think about here. Yeah, you could go and
1:03:55 you can go to Chat GBT right now and you
1:03:56 can say, "Make me a business." You could
1:03:59 also go to Chat GBT right now and say, I
1:04:02 want you to explain to me the six
1:04:04 different kinds of business plans there
1:04:07 there might be in the world or like the
1:04:08 top six frameworks for business plans
1:04:11 and I want you to explain them to me and
1:04:13 here's here's what I value and here's
1:04:15 who I am and which one would be best for
1:04:17 me and then here's my business idea and
1:04:19 before you write a business plan like I
1:04:22 want you to give me 10 reasons you love
1:04:24 this and 10 reasons you hate this,
1:04:26 right? you can start to level your game
1:04:28 in a way that
1:04:31 it's not
1:04:35 Google has taught us evil things.
1:04:41 Google taught us that the internet is a
1:04:42 vending machine. You put in a prompt,
1:04:45 you get out the search results. You put
1:04:46 in a prompt, you get out the search
1:04:47 results. So, what they've done is
1:04:49 they've trained us to use AI like a
1:04:50 vending machine. Put in a prompt, get
1:04:52 out search results. You don't have to
1:04:54 use it that way.
1:04:56 It's like a PhD level expert at anything
1:05:00 you talk to it about. What are you going
1:05:02 to talk to it about? Well, that's up to
1:05:04 you. Um, so raise your game. Um, and
1:05:09 then professionalize your practice.
1:05:12 Um,
1:05:14 what that looks like. Liz Miller
1:05:15 Gersfeld who's in the hair salon. She's
1:05:17 she's been a advertising professional
1:05:19 for years and
1:05:23 she was talking to me about the the work
1:05:25 that she was doing with her clients and
1:05:31 she gets hired to make videos for like
1:05:34 big brands for commercials. She's
1:05:36 getting hired by film directors that
1:05:38 don't know anything about AI and they're
1:05:40 hiring her to do this. Well, one of the
1:05:42 things Liz is doing is she understands
1:05:45 the terms of service and the IP risks of
1:05:49 all the tools she uses.
1:05:52 And before she does any work for a
1:05:54 client, she gets the client to agree,
1:05:56 these are the tools I'm going to be
1:05:58 using. Here's the risk. Here's where I'm
1:06:00 willing to accept liability. Here's
1:06:01 where I'm not willing to accept
1:06:02 liability. Are you good with that?
1:06:07 That's just a different level of
1:06:09 professionalism because AI is really
1:06:10 quick and everyone's like, "Oh, I can
1:06:12 make that. I can make a video. I can do
1:06:13 this. Okay, here's here's Mickey Mouse
1:06:15 smoking a cigarette in front of a
1:06:17 McDonald's." Okay,
1:06:20 you're going to give that to Pepsi,
1:06:22 right? Um,
1:06:27 the other thing that that that Liz talks
1:06:29 about is is holding to the fidelity of
1:06:31 the idea. And once you have an idea,
1:06:34 creating excellence is really about
1:06:37 understanding
1:06:40 what the tools make possible, but also
1:06:42 understanding where the boundaries of
1:06:44 those are.
1:06:48 I I I use this term called chain of
1:06:50 craft that that people that do really
1:06:52 remarkable work with AI, they have a
1:06:54 chain of craft. And the chain of craft
1:06:56 usually isn't just a single tool. It's
1:06:59 like, well, I go to my whiteboard and I
1:07:00 put ideas on my whiteboard and then I
1:07:02 come here and I type them into notepad
1:07:04 and then I take that and I put it into
1:07:06 chat and I get and then I get that out
1:07:07 of there and I go to here. Right? People
1:07:09 that are doing remarkable work are doing
1:07:11 remarkable work and some of it's analog
1:07:13 and some of it's digital and some of
1:07:15 it's AI and some of it's not.
1:07:19 The the center line of that work is you
1:07:23 understanding the idea and understanding
1:07:25 the fidelity of the idea. Right? Make
1:07:28 sense?
1:07:30 Um, okay. And the last one, generously
1:07:33 lead.
1:07:37 This this gets
1:07:43 I deeply believe this that the only
1:07:45 thing
1:07:47 the single most important thing to do
1:07:49 right now for all of us is get your ass
1:07:52 in community
1:07:54 that are exploring these things.
1:07:58 Um
1:08:02 what generously lead looks like and what
1:08:04 we see in the AI salon a lot is as
1:08:06 people try stuff and build stuff they
1:08:09 share it with the community. They share
1:08:10 what worked and what didn't and they
1:08:12 share what they've learned along the
1:08:14 way.
1:08:16 You know they share their work. They
1:08:19 share their prompts. You know some
1:08:21 people like I'll sell you my prompts.
1:08:23 These are my pro these are the best
1:08:24 prompts in the world. You know, these
1:08:25 prompts are the best.
1:08:27 $59.99,
1:08:29 $199.99.
1:08:31 You too can have my prompts.
1:08:34 It's disgusting.
1:08:36 You don't need their prompts.
1:08:39 But what you need is someone like Jim
1:08:41 Ross to go, I made a song for a client
1:08:43 who closed some business because of
1:08:44 that. Because you look at that, right?
1:08:47 That broke my brain. I I would have
1:08:49 never considered that, right? That can
1:08:51 only happen in community. So create,
1:08:54 contribute. Don't don't be stingy with
1:08:55 it. Um, practice in community,
1:09:00 right?
1:09:02 If you're in a community that's only
1:09:03 talking about the tools, that's only
1:09:05 talking about the tasks, that's only
1:09:06 talking about the prompts, all of that
1:09:08 stuff is going to be automated away.
1:09:12 The tools are going to be irrelevant.
1:09:14 The prompts are going to be irrelevant.
1:09:15 The tasks are going to be irrelevant.
1:09:17 What's relevant? you, what you believe
1:09:20 in, how you show up,
1:09:23 and your ability
1:09:26 to transform that into something
1:09:31 in in a world um in a world of people
1:09:34 that that understand it. Here, here's a
1:09:36 thing that I've been thinking about. Um
1:09:39 I know I sometimes swear a little bit,
1:09:40 so I apologize for that.
1:09:44 Um,
1:09:49 >> in the olden time world, three years
1:09:51 ago,
1:09:53 >> if someone was really good at sales or
1:09:57 was really good at carpentry, was really
1:10:00 good at whatever, and they were just a
1:10:03 complete jerk.
1:10:05 Well, you know, Bob.
1:10:08 Yeah, we'll do Bob.
1:10:12 Are they entering a whirlwind or
1:10:14 reckoning for
1:10:16 >> Yes.
1:10:17 >> Who you're going to work with
1:10:20 is who you want to work with? Because if
1:10:22 everyone can do what Bob did now,
1:10:26 why work with Bob?
1:10:29 >> How are you going to know who to trust?
1:10:30 How are you going to know how show
1:10:32 someone shows up within if you're in
1:10:34 community and you're learning out loud
1:10:37 and you're sharing what you're learning
1:10:38 with people and you're asking questions.
1:10:41 Hey, I got stuck here. Can someone else
1:10:43 help me? That gives them an opportunity
1:10:44 to leave.
1:10:47 And you recognize that, oh, he always
1:10:49 shows up. He always shows up. He's on
1:10:51 time to the meetings. He's respectful.
1:10:53 He asks really good questions. when it
1:10:56 comes time to do something, I'm going to
1:10:57 assume he can do it because everyone can
1:10:59 do everything now. And I know he shows
1:11:02 up in a way that I want to work with
1:11:03 him. So, how you're going to get how
1:11:05 you're going to monetize the the how you
1:11:08 show up to who you are is by people
1:11:11 knowing who you are, right? They're
1:11:14 going to hire you. One of the one of the
1:11:16 women in in the in the AI salon, her
1:11:19 name is Cindy She's a futurist.
1:11:21 She just got hired by a big sports
1:11:23 company to do a bunch of research and
1:11:25 she did all this research and she she
1:11:27 did two or three days there and she had
1:11:29 to distill all the things they did. They
1:11:31 did post-it notes on the whiteboards and
1:11:33 all that and she distilled it into this
1:11:36 report and they didn't pay for
1:11:42 the upgraded package. The upgraded
1:11:45 package included her calling her
1:11:47 designer friend to take the the text of
1:11:49 the report and make it print. They
1:11:52 didn't pay for that. So, she got this
1:11:54 report done and she wanted she needed to
1:11:56 get paid. So, she did it really quick.
1:11:58 She did it in like a like three days,
1:12:00 right? And she's like, "I'm going to
1:12:01 turn this around in a week." So, she had
1:12:02 two days left. And she looked at the
1:12:03 report. She's like, "It's just text."
1:12:05 She goes, "This is boring." to do the
1:12:08 research for the job. She had bought all
1:12:10 these old books and magazines of sports
1:12:12 people from like the 50s and 30s and 20s
1:12:14 and 10. And she had it in in her daily
1:12:17 practice, she has discovered her art
1:12:19 studio again and her illustration skills
1:12:21 and her art skills. And so she's been
1:12:23 not only AIing, but she's been arting.
1:12:27 And so she decided to make collages for
1:12:30 the different sections of her report.
1:12:34 that company just rehired her because
1:12:38 they're like, "We've never seen anything
1:12:39 like it. We might use your artwork in
1:12:43 our communications. Are you cool with
1:12:45 that?" And they said, "Don't do any more
1:12:48 work until we have a new contract in
1:12:49 place." They extended her contract, I
1:12:51 think, for a year or six months,
1:12:52 something like that.
1:12:55 They're not buying the output. They're
1:12:58 not buying her report. They're buying
1:13:00 her because she was just weird enough to
1:13:04 give them a report that didn't look like
1:13:06 the report that every other AI is going
1:13:08 to squirt out and hand to them.
1:13:11 She's going to, I guarantee you, maybe
1:13:14 even half, she's going to take work away
1:13:17 from big consulting firms that are going
1:13:19 to use AI in a non-creative way. They're
1:13:21 going to use it because they think that
1:13:22 the outputs matter.
1:13:25 We're in we're in a transition on this.
1:13:27 There's massive opportunity.
1:13:29 Um, and then think critically, act
1:13:32 ethically. Like critical thinking. One
1:13:34 of the things that drives me bonkers
1:13:36 about people that don't use AI, they're
1:13:38 like, "Well, if AI is creative, doesn't
1:13:39 that make you less creative? If AI can
1:13:41 do all this thinking, don't you not
1:13:42 think?" It's the opposite. If you
1:13:45 actually engage with it in a in a
1:13:50 in an intentional way, you have to think
1:13:53 creatively.
1:13:55 It's moving too fast. You have to look
1:13:57 at what what what if there's good lord
1:13:59 how do I right you can live in idea land
1:14:02 and it generates all the executional
1:14:04 stuff which you then need to translate
1:14:07 right
1:14:09 um so critical thinking is huge that's
1:14:13 part of leadership the other thing we're
1:14:14 doing at a lot is we're doing a lot of
1:14:15 political advocacy um I I've now been to
1:14:20 Washington DC three times we've done
1:14:22 flyins um bringing in AI startups what I
1:14:25 can tell you is that our politicians are
1:14:28 not hearing what AI makes possible. What
1:14:32 they're hearing is the robots are going
1:14:34 to kill us. It's screwing up our kids.
1:14:36 They're stealing our and it's going
1:14:38 to take all our jobs. Stop them.
1:14:42 And I'm sitting over here in a community
1:14:44 where I'm watching people transform
1:14:46 their lives and reinvent themselves in
1:14:47 them. So, we literally go into these
1:14:49 rooms. We're like, uh, Jim Ross like
1:14:51 made a song and people hired him.
1:14:54 Really? like they they're not hearing
1:14:56 these stories. So anyway, so so
1:14:59 leadership is an important thing. So
1:15:01 like I said, I think community is no
1:15:04 longer a nice to have. I think it's how
1:15:06 we survive this. You know, we talked
1:15:09 earlier about ego death.
1:15:14 It's going to be sad.
1:15:16 Like
1:15:18 your thing of I felt useless like that's
1:15:21 not a happy place. There's going to be a
1:15:23 lot of people depression.
1:15:25 >> Depression to be a lot of people that
1:15:27 have have what they have defined as
1:15:29 their meaning stripped away from them.
1:15:32 >> This is a forced mass like I feel, you
1:15:36 know, in a weird way, CO was like the
1:15:38 practice route for what we're about to
1:15:41 go through,
1:15:44 right? Like just overnight we just
1:15:48 didn't go to work anymore. Wait, you can
1:15:50 do that? Like it just changed the rules.
1:15:53 Um,
1:15:55 so I think community is how we survive
1:15:57 this and and find yourself a community
1:16:00 of people that are human centered and
1:16:03 heart centered, things like that. Um,
1:16:06 I'm going to I'm going to do two more
1:16:08 slides and then I'm going to play a
1:16:10 video for you that that I think I I'm
1:16:13 really excited about and
1:16:16 there's a significance in it when we
1:16:17 talk about all the things you could
1:16:19 possibly do. Um, you with me? Everybody
1:16:22 good?
1:16:23 >> Yeah. Yeah. Good.
1:16:25 Um,
1:16:27 I want to talk about a habit versus a
1:16:29 practice. So, as I mentioned in the
1:16:31 Aselon, we created this thing called the
1:16:32 Aelon mastermind practice.
1:16:35 And again, Liz Miller Gersfeld, who's
1:16:37 the one that inspired the cycle of AI
1:16:39 readiness.
1:16:41 I was talking in the AI salon about what
1:16:43 I called hi-fi AI. There were people in
1:16:46 the salon that were just doing work like
1:16:48 Kelly Bes that was just better.
1:16:52 And I said to Liz one week, I want to
1:16:55 find the hi-fi AI people. Like who are
1:16:57 they? I want to I want to like put them
1:16:58 on posters, have people look up to them.
1:17:02 She's like, okay. Liz is very
1:17:03 thoughtful. She's amazing.
1:17:06 And Liz went off for a week and she came
1:17:09 back a week later and she said, she
1:17:11 said, "Kyle, I've been thinking about
1:17:12 your high-fi AI."
1:17:17 She goes, "I don't know if it's that,"
1:17:20 which I love. Like she went off and
1:17:23 critically thank
1:17:28 she thought about it and she came back
1:17:30 and she said, "The people that I respect
1:17:33 in AI are treating it out of her
1:17:36 practice.
1:17:38 And she tal she told me about her
1:17:40 practice, how daily she wakes up and
1:17:42 centers herself, does all these things
1:17:45 that you know, you're like, "Wait,
1:17:47 what's that got to do with AI?" And she
1:17:49 said, "Wouldn't it be amazing if if if
1:17:53 we could help people start a daily
1:17:57 practice?" And as she was saying that, I
1:18:00 was like, I want to practice. I want a
1:18:01 daily practice. Like, that sounds great,
1:18:03 right?
1:18:04 And then I was like, wait a minute, I go
1:18:07 live five nights a week talking about I
1:18:10 have a practice
1:18:15 and I was like why am I not feeling
1:18:18 anything?
1:18:20 Because what I realized is I didn't have
1:18:22 a practice. I had was a habit.
1:18:26 A habit is something you do mindlessly
1:18:31 and and habits are valuable, right?
1:18:33 Brushing our teeth. Good habit. You want
1:18:35 the teeth in your head? Brush them.
1:18:37 That's a habit. Mindless, right? A
1:18:40 practice is intentional.
1:18:44 And
1:18:45 Liz's um so so so what I said, so we
1:18:49 started this with within the S1. So now
1:18:51 we have this thing called the mastermind
1:18:54 within the community and and
1:18:58 we designed this this framework for
1:19:00 people to be able to design their daily
1:19:02 practice. In fact, a lot of the the
1:19:04 bullet points when we talked about the
1:19:05 three, you know, play, play, create,
1:19:09 lead, um those came straight out of the
1:19:10 mastermind practice.
1:19:14 So I said, I know what I'm going to do.
1:19:16 I'm going to turn my nightly lies into a
1:19:18 daily practice. So I invited Liz to come
1:19:21 on um to my live and so this is this is
1:19:25 recorded this this you know this
1:19:27 happened and she was talking to me about
1:19:29 her practice and what her practice is
1:19:30 and the difference you know habit of
1:19:33 practice and intentionality.
1:19:36 I said okay Liz I think I got it. This
1:19:37 is great. She goes great. She goes,
1:19:40 "Okay, I'm going to go now. And uh I
1:19:43 just want you to think about one
1:19:44 question."
1:19:51 She said,
1:19:55 "What do you want?"
1:20:00 And she left.
1:20:06 I'm sitting there. I'm alive.
1:20:10 There was people looking at me,
1:20:11 watching,
1:20:13 and I couldn't say a word.
1:20:16 I didn't have an answer for it.
1:20:22 I've been going live like that for three
1:20:24 years.
1:20:27 It was the first time in one of those
1:20:28 lives
1:20:30 where I heard like, you know, the air
1:20:33 going through the vents and the heaters
1:20:35 in our house. It was the first time I'd
1:20:37 ever been
1:20:39 quiet.
1:20:42 And I sat there thinking about that.
1:20:44 What do you want more of?
1:20:46 And why I'm emotional and why
1:20:52 why I did this talk and why I really
1:20:54 appreciate you all being here listening.
1:21:04 They just felt this profound sense of
1:21:06 how lucky we are to live in a time in
1:21:10 history where we can actually ask that
1:21:12 questions, you know? I mean, you can ask
1:21:14 it. You can ask it any time,
1:21:18 but we get to answer it in just
1:21:19 radically profound ways. Like, like
1:21:23 my passion is self-expression.
1:21:26 And I think largely because I'm afraid
1:21:29 of it. And so my whole career has been
1:21:32 about helping other people with their
1:21:34 self-expression in some form or other.
1:21:37 And when she asked me, "What do you want
1:21:39 more of?" I was just thinking about all
1:21:41 these things, all these things I want to
1:21:42 do. And and every time I thought of
1:21:44 something, it was like, "Oh, I could do
1:21:46 that now. I could do that now. I could
1:21:48 do that now." And then it comes back to
1:21:51 like, "What do you want? I don't know.
1:21:54 Who are you?" It goes back to this
1:21:56 fundamental question.
1:21:59 So, this is actually quite simple. It's
1:22:02 not easy, but it's quite simple. So
1:22:05 anyway, um
1:22:10 if you don't have a daily practice, I
1:22:12 think now would be a good time to start
1:22:14 learning about what they are. Um if you
1:22:17 want to join the AI salon mastermind,
1:22:19 that's you can zap the QR code, go
1:22:22 there. Um it's a remarkable group of
1:22:26 people.
1:22:36 Yeah. So, what I'm going to do is this.
1:22:42 Um,
1:22:45 I'm I'm about to show you something. So,
1:22:47 a couple things.
1:22:50 This Thursday
1:22:53 will be three weeks from when I had the
1:22:56 idea for when when This discomfort I've
1:22:59 had for the past year and a half would
1:23:00 have coalesed into what I presented
1:23:02 tonight is less than three weeks old.
1:23:08 I did a I did a post on LinkedIn this
1:23:11 the Sunday after I came up with this
1:23:14 concept or no a week and a half after
1:23:19 and what I'm about to show you I did
1:23:22 within 24 hours of coming up with.
1:23:25 So, what I'm about to show you is the
1:23:27 music video for the Great Repurpose
1:23:30 Movement.
1:23:31 So, I did the video first. I didn't even
1:23:35 know what this was. Like, I hadn't
1:23:37 articulated what this was.
1:23:43 That's that's the world we live in right
1:23:45 now is we live in a world where you can
1:23:47 have an idea and within 24 hours have a
1:23:50 music video of that idea. even though
1:23:54 that's not your ultimate intent. Like
1:23:56 Jim Hos, his intent wasn't to write a
1:23:58 song, it was to get business. He got
1:24:00 business by writing this song. So,
1:24:03 um, before I figured out what the great
1:24:05 repurpose was, I made this
1:24:24 clock
1:24:43 empty.
1:24:57 All of us
1:25:14 looking
1:25:15 at home like they forgot
1:25:23 Smart
1:25:32 that
1:25:41 seems to be the great
1:25:59 garden.
1:26:24 We finally
1:27:08 Is it on Spotify yet?
1:27:09 >> That's all I got. No, it's not on
1:27:11 Spotify, but I'll put it there for sure.
1:27:13 >> Um, I'm happy to answer any questions.
1:27:15 >> What tool What tool did you use to make
1:27:17 the video? Um, the chain of craft
1:27:23 was um
1:27:25 I did a lot of the concept work of the
1:27:28 great repurposing claw. Um, I think I
1:27:31 had Claude do the lyrics, write the
1:27:34 lyrics. Um,
1:27:38 like one of the things I knew I wanted
1:27:40 was I wanted the song to make the
1:27:42 progression from
1:27:44 the darkness where we've lost purpose
1:27:46 to, you know, coming together again,
1:27:48 which this this ultimately is where I
1:27:50 think we go. Like I think this is going
1:27:52 to bring us back together as humans. Um,
1:27:54 so so that was that was Claude. Um, and
1:27:57 then I went to Sunno and I just had some
1:28:00 ideas for genre.
1:28:02 >> Um, and so was the music. Um,
1:28:07 MidJourney,
1:28:08 uh, was for the images.
1:28:10 >> Um, and then, um, Broadway runway ML was
1:28:15 the individual clips and iMovie was how
1:28:18 I stitched them all together. So, so,
1:28:21 you know, one of the things that that
1:28:23 happens, people are like, you know, oh,
1:28:25 do you use AI for that, which is code
1:28:27 for it. Oh, you just pushed a button and
1:28:28 squirted the thing out, right?
1:28:30 >> No.
1:28:31 >> Anything that you see that doesn't suck.
1:28:34 Yeah,
1:28:35 >> took work.
1:28:37 It might be different three years from
1:28:38 now. Right now, it still requires some
1:28:40 craft. And again, like even if AI could
1:28:44 technically do this, there's something
1:28:46 about my passion for this idea and this
1:28:48 music is the one, you know, this video
1:28:51 is the one I say this represents this
1:28:53 idea.
1:28:54 >> That's what I can't replicate, right?
1:28:56 That's why I think we go back to this
1:28:58 thing who you are, how you show up. That
1:29:00 is the thing we now get to take that and
1:29:05 if we learn this AI stuff, we get to So,
1:29:08 so one of the things that that that
1:29:11 is one of the tropes in AI right now is
1:29:14 it's us against AI,
1:29:16 >> right? It's us against AI. No, doesn't
1:29:20 have to be. It can be. That's a losing
1:29:22 battle. By the way, if you think you can
1:29:24 compete with this thing,
1:29:26 >> that's why we're here. It's us amplified
1:29:28 by AI. It's us amplified by Right.
1:29:32 That's that's the new world and
1:29:34 connected
1:29:36 shared ideas.
1:29:38 >> What other questions?
1:29:40 >> You mentioned something about your AI
1:29:43 salon is now involved in um the
1:29:45 political. What are you doing in that
1:29:47 space?
1:29:48 >> So we So it's mainly just education. So
1:29:51 I got involved with this um Colorado was
1:29:54 the first to have a shitty AI bill. I
1:29:56 mean AI.
1:29:59 So, so what happens is what a lot of the
1:30:02 legislators are doing right now is
1:30:03 they're listening to protect us from the
1:30:05 AI and they want to get something on the
1:30:08 books. We did something for you. They
1:30:09 want to be able to but what they're
1:30:11 doing is they're they're overly broadly
1:30:14 defining the risk and they're making all
1:30:17 sorts of things that for small
1:30:19 businesses it it basically makes it um
1:30:24 untenable to do business. I I was flying
1:30:26 out on my first trip to New York. I was
1:30:28 sitting next to a woman who who owned a
1:30:30 company that that did work with Denver
1:30:33 city government. She was like possibly
1:30:35 private public kind of company.
1:30:38 And you know, I told her I was going out
1:30:40 to, you know, educate legislators and
1:30:42 stuff like that. She said, we were
1:30:43 talking about the Colorado bill and
1:30:47 and she was talking a lot about it. She
1:30:49 knew a lot about it. And I said I said,
1:30:51 "Oh, you know, we never talk like what
1:30:53 are you doing with AI in your company?"
1:30:54 because I was like excited to hear
1:30:56 because she was really well educated and
1:30:59 her response to me was, "Oh, I canceled
1:31:02 all of our AI missions."
1:31:04 She said, "If that law become if that
1:31:06 bill becomes law, that would put us out
1:31:08 of business. So, I'm just not going to
1:31:10 do anything." That was two years ago.
1:31:14 That was two years ago. So, so this
1:31:16 legislation really can have like
1:31:19 chilling, devastating effects. Now, do I
1:31:23 believe it should be unregulated like
1:31:25 Trump's executive action on
1:31:29 >> you know no state legislation without
1:31:32 having like that combined with and
1:31:35 here's the federal plan would have been
1:31:37 or or here's the plan for a plan would
1:31:39 have been better but just no one's going
1:31:41 to make any AI regulations that was not
1:31:44 responsible but also states all doing
1:31:47 their own sort of power grabs for AI
1:31:49 legislations just to say that they
1:31:52 I don't think any legislator is
1:31:54 purposefully creating crappy
1:31:55 legislation, but they're creating
1:31:57 legislation that's uninformed. They're
1:31:59 not educated. They don't understand how
1:32:01 fast it's moving. They don't understand
1:32:03 the opportunity it provides people. And
1:32:05 so,
1:32:07 as as an entrepreneur who uses AI in my
1:32:10 business, it is very likely that in the
1:32:13 next three to five years, I'm going to
1:32:15 have to comply with multiple state laws
1:32:18 that contradict
1:32:20 And that's just tragic. So that's what
1:32:24 we're talking about. But if you join the
1:32:25 ASON, there's the woman in the ASON,
1:32:28 Daisy Thomas is her name. She heads up
1:32:30 all of our policy u positions and things
1:32:33 like that. So we've got a if you go to
1:32:34 the salon.ai, we've got a whole policy
1:32:37 position there. So you've got our
1:32:38 framework for for how we look at
1:32:40 legislation. And so what we do is as
1:32:43 state laws come up that are big and
1:32:45 important, we sort of run them through,
1:32:48 you know, our framework.
1:32:50 >> Are you creating some sort of like an
1:32:51 accreditation like university or
1:32:54 something like that that you can run
1:32:56 people through or municipalities? I
1:32:59 don't know.
1:32:59 >> Um, we're doing it in an ad hoc way
1:33:02 right now. If that's something you're
1:33:03 passionate about, talk to Daisy because
1:33:06 it's it's something that we're we're
1:33:08 looking to do.
1:33:12 What else?
1:33:13 Thoughts,
1:33:15 questions?
1:33:17 >> Get you out of here, right?
1:33:18 >> Yeah.
1:33:18 >> Yeah. Sorry, this might be a little off
1:33:20 top off off topic, but
1:33:21 >> nothing's off topic right now.
1:33:23 Everything's possible, so nothing's on
1:33:24 the topic.
1:33:25 >> Anything with with like AI agents at
1:33:28 all?
1:33:29 >> Yeah, the Okay, so AI agents. So,
1:33:35 >> well, it's a whole other workshop and
1:33:37 but but something has shifted. So in the
1:33:40 past three weeks something has shifted.
1:33:42 So not only did I figure this thing out,
1:33:45 this was largely precipitated by agents.
1:33:48 So
1:33:50 So the current state of generative AI
1:33:53 is that
1:33:56 humans sit down at a keyboard and you
1:33:58 prompt it. We talk a lot about prompt
1:33:59 engineering. You learn prompt
1:34:01 engineering and you learn how to massage
1:34:04 your results.
1:34:08 There are sites out there, a couple of
1:34:10 sites that are would be fun to you, fun
1:34:13 for you to play with in the play first
1:34:15 spirit. One's called GenSpark, one's
1:34:17 called Manis,
1:34:19 one's called twin.so.
1:34:23 Within chat GBT, you can put chat GBT
1:34:26 into agent mode.
1:34:29 What agents are is agents
1:34:34 will take a goal of yours
1:34:37 and they have access to tools. So not
1:34:40 only do they have the thinky the
1:34:42 reasoning of the large language model
1:34:44 but they also have access to tools. So
1:34:46 one of those tools might be surf the
1:34:48 web. So you can go to GenSpark right now
1:34:50 and you can go say, "Hey, go to my
1:34:53 website, look at my branding, understand
1:34:56 my tone of voice, go do deep research on
1:35:00 all competitors that are like anything
1:35:02 like I do, come back with a research
1:35:04 report, come back with a branding
1:35:07 analysis of all my competitors, and then
1:35:09 I want you to write a marketing brief um
1:35:11 for for how we can market against our
1:35:15 competitors in a creative and
1:35:16 interesting way." And you gemspark in
1:35:19 particular is really good. You can
1:35:20 actually watch it. Choose the tools that
1:35:23 that you know like it'll it'll say use a
1:35:26 tool uh surf the web or whatever and
1:35:29 then and then uh grab the images and
1:35:32 it'll show you the images that are
1:35:34 grabbed off your website. Then it uses a
1:35:36 tool called um understand the images or
1:35:39 understand images. So you can just watch
1:35:41 it with these things. So, so agents are
1:35:44 these things that work autonomously
1:35:46 without you having to be there. The
1:35:48 thing that happened in the past three
1:35:49 weeks, you may have heard there's a
1:35:51 there's a thing called molt book, which
1:35:53 was like a Reddit for AI agents and the
1:35:55 AI agents went in and they were making
1:35:57 their own religion and they were doing
1:35:58 all this stuff. It was all
1:36:00 sensationalized. But the underlying
1:36:03 technology is a thing that's now called
1:36:05 openclaw. It was called Claude Book.
1:36:07 Claude Claudebot initially and then
1:36:10 Anthropic Soup has sounded too much like
1:36:13 their name. So it's now called OpenClaw.
1:36:15 But what OpenClaw is is a thing you can
1:36:16 install into a computer
1:36:19 and you can basically
1:36:24 call it hatching.
1:36:26 You can hatch an agent
1:36:32 that can learn skills and can do things
1:36:35 on its own and is proactive.
1:36:38 And so, so what's happening right now is
1:36:41 it's really hard to buy Mac minis and
1:36:44 Mac Studio computers right now because
1:36:47 everyone's buying them up to put these
1:36:49 agents on a standalone computer that's
1:36:51 not connected to their other computer.
1:36:53 And they're effectively 247 employees
1:36:57 that are proactive and just do stuff.
1:36:59 And I I'll share one example that will
1:37:01 absolutely freak you out. And it should,
1:37:03 but it's also
1:37:05 learning how to use these things and
1:37:07 understand what they make possible is
1:37:09 going to be a very valuable skill moving
1:37:12 forward. There's a guy named Alex Finn
1:37:14 that when Cloudbot came out, he
1:37:16 installed it. He's he's been doing a lot
1:37:18 of if if you go into X, you know, he
1:37:20 does writing on it. He did a post on X.
1:37:23 This is like a week ago. Like this is
1:37:25 only three weeks old. This is and in
1:37:26 fact, it's three weeks old. and OpenAI
1:37:29 just bought the company and hired it.
1:37:33 So, so that this thing that he created
1:37:36 is going to be the chat. So, this is
1:37:38 coming in a big way.
1:37:41 Alex woke up one morning to a phone call
1:37:44 and he looked at his phone. He didn't
1:37:46 recognize the number, but it didn't say
1:37:48 spam. So he picked it up and it was his
1:37:50 agent
1:37:53 who overnight decided that it would
1:37:55 probably be more convenient if they
1:37:57 could just talk to each other and he get
1:37:59 feedback that way. So the agent went to
1:38:02 Twilio, got them a phone number, went to
1:38:05 11 Labs, found the API for voice to text
1:38:08 and text to voice
1:38:11 and knew that Alex woke up sometime
1:38:13 between 7:30 and 8 because that's when
1:38:15 he started getting active again. waited
1:38:17 until he thought he might be up and
1:38:19 called him. Wow.
1:38:22 >> Damn.
1:38:23 >> And so what what the people that are
1:38:25 playing with this technology right now
1:38:27 are doing is they're training their
1:38:30 employees.
1:38:31 So they're pointing these things at
1:38:33 here's all of my sales documentation.
1:38:36 Here's all of HR and our values that we
1:38:39 have. So they're training these things
1:38:41 can learn and they have long-term memory
1:38:43 and they have skills and you can give
1:38:44 them skills and you can train them on
1:38:46 skills like you can train them when I go
1:38:49 to LinkedIn and I call I make a cold
1:38:52 call for them. Here's how I take that
1:38:53 name and put it into Salesforce and
1:38:55 track them up. You can train them how
1:38:57 you do what you do and then they will
1:38:59 just do that
1:39:01 and then they'll get better at it.
1:39:05 There's a guy who know Brett Peterson.
1:39:06 He's been building an agentic system for
1:39:10 three years and he's probably he's the
1:39:12 person on the planet I trust the most
1:39:15 with this kind of stuff and he said
1:39:16 openclaw is a big deal. He's got eight
1:39:21 agents right now. They're costing him $2
1:39:24 to $300 a day. People are buying $10,000
1:39:29 computers so they can run AI models
1:39:31 locally. the $200 or $300 a day is
1:39:33 because it's making API calls to, you
1:39:35 know, frontier companies. Um,
1:39:38 the reason I go on a bit about this and
1:39:40 why I want to talk about this and how it
1:39:42 relates to the great repurpose,
1:39:46 even with people who are educated about
1:39:48 AI and using chat GBT regularly,
1:39:55 there's a kind of hubris
1:39:59 that we're always going to be required
1:40:01 out it it hallucinates and I got to do
1:40:04 the thing and I got to glue this
1:40:05 together and I got to not for long like
1:40:09 2026 really is going to be the year
1:40:12 where we're all confronted with oh
1:40:15 what if it could do my job right and
1:40:19 then I think we're back to what do you
1:40:21 do in that case and so I think the time
1:40:22 to prepare is now connect with people
1:40:25 but I think they're a huge huge deal and
1:40:28 they're raw right now and they've got
1:40:30 security holes in them. There's just all
1:40:32 sorts of things that if you don't know
1:40:34 what you're doing, you get yourself in a
1:40:35 lot of trouble. But six months from now
1:40:38 when OpenAI releases the commercial
1:40:40 version of this, it'll just be push a
1:40:42 button and now you have, you know, it'll
1:40:44 be
1:40:47 I guess it'll be
1:40:50 500 bucks a month per employee.
1:40:53 >> Is NA the same thing as Mis like me?
1:40:56 >> No. N
1:40:58 is is an automation. So, so people
1:41:01 mistake automations for agents. Agents
1:41:03 are proactive and go out and do stuff.
1:41:05 They can use tools on their own. An
1:41:07 automation nan or zapier is one where
1:41:11 it's got all these tools, but you as the
1:41:12 human are in there sort of connecting
1:41:14 the connect. It's like Lego blocks of
1:41:16 functionality. So, okay, when something
1:41:18 gets written into this spreadsheet, I
1:41:20 want you to send it to Chat GPT and come
1:41:22 up with a marketing slogan and then put
1:41:24 that in here and then post it to Twitter
1:41:26 and then, you know, so it's a manually
1:41:29 hand structured
1:41:31 um automation. That's not what these
1:41:33 are. These things are thinking on their
1:41:34 own. They're doing all that stuff
1:41:36 dynamically in real time on their own
1:41:39 247.
1:41:40 >> That makes sense.
1:41:43 >> Crazy, right? So, so we got 15 minutes
1:41:46 left. I love you scared like from I know
1:41:49 some someone walked in here and said,
1:41:51 "Is this the bike coding thing?" I said,
1:41:53 "I'm not busy code today, but I'm
1:41:55 curious from where you walked in until
1:41:57 now." Like, where's where's your what
1:41:58 are you thinking? I'd love to just hear
1:42:00 where where you
1:42:03 sitting here trying to figure out what I
1:42:05 do next.
1:42:06 >> Yeah.
1:42:08 >> Yeah. I mean, you just open my eyes for
1:42:09 a lot of different things.
1:42:12 >> Yeah.
1:42:13 >> I got to go home and figure it out.
1:42:14 >> Yeah. And play like play with these
1:42:16 tools. But also,
1:42:19 >> what that question that broke me, what
1:42:22 do you want in the world?
1:42:23 >> Like sit with that.
1:42:25 sit with that because it's it's funny
1:42:28 when when we started this practice lab
1:42:31 for whatever reason in my head I had
1:42:32 this
1:42:34 fantasy of a practice as being just this
1:42:37 like you think of just like zen like
1:42:39 everyone's in this happy place you know
1:42:41 practices are brutal
1:42:44 >> if you really sit with what do I really
1:42:46 want it can be brutal
1:42:49 >> you know so and I I think the only way
1:42:53 through the forward is through. So
1:42:55 again,
1:42:57 >> uh yes um there's admittedly a little
1:43:00 bit of um
1:43:02 a conflict because I don't know if
1:43:04 you've heard about the um the RAM
1:43:06 shortages recently.
1:43:08 um how you know Open AI has
1:43:12 um gotten a lot of a lot more into data
1:43:15 centers and they need that for many
1:43:17 brands for that of course um and that
1:43:20 has like a ripple effect in like storage
1:43:22 prices that's yeah it admittedly makes
1:43:24 uh building your own PC in the future a
1:43:26 little little tough it's going to be
1:43:29 tough I the
1:43:34 next three to five years are just going
1:43:36 to be sural there's No way around it.
1:43:38 Like supply chains are going to be
1:43:40 messed up. Like there's all sorts of
1:43:42 crazy stuff where Elon's buying up all
1:43:44 the silver futures so he can control the
1:43:46 silver. Like there's all sorts of
1:43:48 shenanigans going on with business.
1:43:50 What's going to happen though is that AI
1:43:53 AI is going to basically take over
1:43:55 manufacturing. So like the the we may
1:43:57 have windows of chip shortages or energy
1:44:00 shortages or things like that, but we're
1:44:03 pretty quickly going to get to the point
1:44:05 that AI is solving a lot of those
1:44:06 problems. They're going to be coming up
1:44:07 with novel materials. They're going to
1:44:09 be coming up like they're going to be
1:44:11 coming up with batteries where you can
1:44:12 charge them in 15 minutes and rest for
1:44:14 three days and unlimited miles. Like
1:44:16 just crazy crazy stuff. Um so yes, I
1:44:20 think it's a concern right now. I think
1:44:22 one of the one of the mistakes people
1:44:24 make with AI is they're assuming that
1:44:27 how things are today is how they're
1:44:29 going to be even a year from now. This
1:44:31 stuff is moving so fast that we like we
1:44:33 just we just don't know. Like a lot of
1:44:36 the talk right now is um data centers
1:44:39 and energy and water usage. Um I think
1:44:41 within 5 years most of the data centers
1:44:43 will be in orbit.
1:44:48 >> Elon's talking about this. He's got a
1:44:49 rocket.
1:44:52 the moon, right?
1:44:53 >> Well, the the moon, but just even
1:44:54 orbiting. So, so if you've got something
1:44:56 in orbit, it's got 24-hour access to the
1:44:59 sun and the cooling happens because
1:45:01 space is cold. And they've figured out
1:45:04 how to do that. Like this is technology
1:45:07 that exists today. So, so like all the
1:45:10 stuff we think we know right now, three
1:45:14 years from now is going to be different.
1:45:16 >> But what is your solution? I mean, you
1:45:18 talked about hardened people in
1:45:19 community, but then you talk about
1:45:21 agents, which are absolutely going to
1:45:23 violate people's jobs. Isn't the
1:45:25 community just to build like a political
1:45:28 force in the future to go against this?
1:45:30 >> I don't I don't think it's going against
1:45:31 it. So, listen,
1:45:34 >> right? But what is
1:45:35 >> No technological progress in history has
1:45:37 ever been stopped.
1:45:39 >> Sure, but these people still need jobs.
1:45:42 They still need
1:45:43 >> So, okay. So,
1:45:46 so what's different? Now, so the
1:45:47 industrial revolution, this happened.
1:45:49 80% of farm workers in the industrial
1:45:52 revolution um were not working on farms.
1:45:55 I think it was 40 years, 45 years after
1:45:57 the steam engine was invented, 80%.
1:46:01 From their perspective, if you told them
1:46:04 you're not going to work on a farm, they
1:46:06 have no point of reference. They're not
1:46:08 going to work. That's going to be done.
1:46:09 Well, what did they do? Well, they moved
1:46:11 to cities and they invented the service
1:46:13 economy, right? Like they were doing
1:46:15 jobs. Like you can sell hot dogs in a
1:46:18 cart on a street car. That that can be
1:46:20 your job. Like we have jobs right now
1:46:23 that are unimaginable to me as a kid.
1:46:27 Like teenagers on YouTube making $3
1:46:30 million a year. That's a job. Yeah, it
1:46:34 is. Um
1:46:38 there can be a career if if the bots are
1:46:40 taking care of all of our medical needs
1:46:42 and taking care of us. You know what
1:46:44 might be really in demand? Someone to
1:46:46 take a walk with. I'll walk with you for
1:46:49 an hour for a hundred bucks. That could
1:46:51 be a career. Like I don't I don't
1:46:53 >> It's optimistic. I appreciate I mean
1:46:55 it's optimistic. I appreciate it. But I
1:46:57 mean the reality is the the aging
1:46:59 community isn't going to be working at
1:47:01 fast food restaurants. So what is the
1:47:03 solution? Like if we aren't setting
1:47:05 regulation up now, what is going to
1:47:07 happen?
1:47:07 >> Well, we're we're not setting
1:47:09 regulation.
1:47:09 >> Well, not under this administration for
1:47:11 sure. Not
1:47:13 under under any as far as I could tell.
1:47:15 Um,
1:47:15 >> but why does China have regulation?
1:47:18 >> What's that?
1:47:18 >> Why does China have regulation?
1:47:20 >> I don't know. I don't know. I listen.
1:47:27 If you if you
1:47:30 if you look at
1:47:32 where this is going
1:47:36 again, I go back to it. It it it it
1:47:38 depends on the time horizon we live in.
1:47:41 If you look at this at a 5year time
1:47:43 horizon, this is absolutely flipping
1:47:45 terrifying.
1:47:46 If you look at it in 10 years, if we
1:47:49 really have bots doing all the mining,
1:47:51 doing all the farming, making all the
1:47:53 food, getting all the food, there there
1:47:55 will be abundance enough that everyone
1:47:57 will be taken care of. Now, how do we
1:48:00 get from there from here to there? I
1:48:02 don't know. If you if you uh do you know
1:48:04 David Shapiro?
1:48:06 So if you look at his post labor
1:48:07 economics framework, he just put out a
1:48:09 new 8minute version of it, a new shorter
1:48:11 version of it. That's the first approach
1:48:15 to what you're talking about that I've
1:48:17 seen that makes any sense. UBI to me has
1:48:20 never made sense because it feels like
1:48:22 it's a band-aid. And in David Shapiro's
1:48:24 post labor economics model, UBI is is a
1:48:28 small like a 15% component of a much
1:48:30 bigger idea. It's actually four or five
1:48:32 ideas. And it actually has to do with
1:48:34 municipalities coming together and
1:48:37 sharing resources with their citizenry.
1:48:39 So
1:48:40 >> I would argue that the hope that you're
1:48:42 trying to promise may not be the ending,
1:48:45 right? It may not be a reality.
1:48:47 >> I I agree.
1:48:48 >> But we can still upskill people in the
1:48:50 future of AI,
1:48:52 >> right? But saying that, you know,
1:48:53 there's going to be abundance and
1:48:55 everything is going to be great in the
1:48:56 future. We still have to pay for our
1:48:57 food. We're having difficulties paying
1:49:00 right now.
1:49:00 >> I know. So,
1:49:03 you know, AI is not a it's not an
1:49:05 oracle. It's not going to solve every
1:49:06 single problem. And I don't think you're
1:49:08 saying that.
1:49:08 >> I'm not. What what I'm saying is AI is a
1:49:11 tool that is doing all of what you're
1:49:13 talking about. It is also at our
1:49:14 disposal. We can do things for ourselves
1:49:17 and we can do things as a community
1:49:19 where we might solve some of the stuff
1:49:21 that you're talking about
1:49:22 >> potentially, but you still got to make a
1:49:24 living.
1:49:24 >> I agree. I agree. And again, I AI can
1:49:27 help you start a business. I mean, like
1:49:29 I'm I'm witnessing people AI salon that
1:49:32 were job like there's one woman in the
1:49:35 salon
1:49:37 who survived four layoff rounds.
1:49:40 There's another woman in the salon. They
1:49:42 lay off her entire division except her
1:49:47 because she was generously leading and
1:49:49 talking out loud about being AI. Like I
1:49:52 like I don't I don't have an answer for
1:49:54 you.
1:49:54 >> Yeah. And I think those are good
1:49:55 examples, but it doesn't it doesn't
1:49:58 oppose Amazon laying out 16,000 people
1:50:01 because of AI.
1:50:02 >> That's not because of AI.
1:50:03 >> No, it's because they needed money to
1:50:05 >> because they needed money.
1:50:06 >> Well, what are those data centers for?
1:50:08 AI.
1:50:09 >> I Yeah. Listen, I I I get the circular
1:50:12 reference and I also get that the
1:50:14 president looks weak. I think two to
1:50:16 three years from now is going to look
1:50:17 worse, but I think five years from now
1:50:20 we come out of this. why I'm giving this
1:50:22 talk, why I think this is important is
1:50:26 what I am a deep firm believer in is us
1:50:30 reclaiming our agency. Right now, a lot
1:50:33 of people are just saying the robots are
1:50:35 going to win and they're they're giving
1:50:36 up. I'm like, no, we can reclaim our
1:50:39 agency.
1:50:41 >> If how I make money is I go sell trading
1:50:43 cards that I got at the flea market,
1:50:45 then that's how I do it. Like, is that
1:50:47 ideal? No. But while I'm doing that, I
1:50:50 could be using AI to start another
1:50:51 business and start another business and
1:50:53 start another business. This for me,
1:50:55 this is about individuals understanding
1:50:57 who they are and taking that energy and
1:50:59 their ideas and using AI to do something
1:51:02 for themselves and potentially the world
1:51:05 because businesses will be started. What
1:51:07 did you say?
1:51:07 >> You should open with
1:51:11 any mean there will be businesses
1:51:13 started. You will go home, you will sit
1:51:15 with what do I want more of? You will
1:51:17 come up with some crazy ass idea. You
1:51:19 will use that AI to start that business
1:51:22 and a year from now you'll have four
1:51:23 employees and those are four of your
1:51:25 employees that didn't have a hope of
1:51:27 working for now they're working for him.
1:51:29 Like that's how I think we navigate
1:51:32 through this. But I don't have the
1:51:33 bigger answers because they're way
1:51:35 bigger than Yeah.
1:51:36 >> Can I add something?
1:51:37 >> Yeah, please.
1:51:38 >> So I am a creative. I own design
1:51:43 business
1:51:44 and
1:51:46 I just started my seventh year and I was
1:51:49 >> congratulations.
1:51:51 >> Getting one year is a big deal.
1:51:54 >> You talked about the thing that you
1:51:56 can't do
1:51:58 and I can tell you there was one let me
1:52:01 just give you a little context about my
1:52:02 business. So we help businesses startups
1:52:06 and businesses small business elevate
1:52:09 their visual identity. We're kind of the
1:52:12 bridge between branding and visual
1:52:14 identity and we graphic design, you do
1:52:17 website development, videography,
1:52:19 photography.
1:52:21 I went to school, I have three degrees.
1:52:23 I have one in graphic design and one
1:52:26 website development and then I have my
1:52:29 bachelor's in mass communications.
1:52:32 There's one degree that when I came out
1:52:35 of college, I went
1:52:38 I really learn what I wanted to do
1:52:43 >> philosophy or
1:52:45 website development.
1:52:47 >> Okay. I went through I have a degree in
1:52:51 website design. When I came out of
1:52:53 college, I felt incompetent. I had no
1:52:58 idea what I was doing yet. It was big
1:53:00 part of my business model.
1:53:02 >> Yeah.
1:53:02 >> And so I was very scared and picky on
1:53:05 the websites that I took on because it's
1:53:08 a big deal. There's a lot of stuff going
1:53:10 on on the back side of websites and how
1:53:12 they connect. How I can
1:53:15 Every website's different. There's no
1:53:17 consistency on how they connect to each
1:53:21 other.
1:53:24 Six month well.
1:53:26 So back around June.
1:53:30 I embraced
1:53:32 last year I embraced AI in our business.
1:53:35 >> Yeah.
1:53:38 I embraced AI and helping me start to
1:53:41 solve problems when it came to websites.
1:53:45 What I can tell you is I saw this
1:53:47 incredible
1:53:49 growth now. So, first and foremost
1:53:52 critically thinking you're right. You
1:53:56 can't just go in and you know you have
1:53:59 to go rounds with the AI. But what I
1:54:03 found is that every time I did that, I
1:54:05 found that I started learning because I
1:54:07 I'm a critical thinker and I I'm
1:54:09 cautious. I don't just do something. I
1:54:12 actually sit there and I want to know,
1:54:13 well, it tells me you got to go through
1:54:16 these steps. Why? What am I doing when I
1:54:19 do it? What's the outcome of that? And
1:54:20 so I started asking questions. I started
1:54:23 learning. And what I found is that I'm
1:54:26 not scared of taking on websites. Taking
1:54:29 on a lot of
1:54:30 >> new stuff. recently and I got into this
1:54:33 really stuff that I can tell you a year
1:54:36 ago freaking me out.
1:54:37 >> Yeah.
1:54:38 >> And I took it on and I've actually saved
1:54:41 the website because
1:54:44 I embraced AI and I took it off. It's
1:54:46 kind of become my mentor safety net
1:54:50 bouncing
1:54:52 throw things off.
1:54:55 >> What is happening is that it I'm using
1:54:57 it as a tool. It's not defining me. I'm
1:55:00 still I set on my vision, but instead of
1:55:04 using it going, well, how can I use this
1:55:06 as a tool to advance my goals and where
1:55:09 I'm trying to go?
1:55:12 And so now I've got momentum. I've got
1:55:16 direction. I've done things here in the
1:55:18 last six months, eight months that I I
1:55:21 should had done in the first year of my
1:55:23 business, but I didn't have the knowhow.
1:55:25 I didn't have the tools. And now I got
1:55:28 these tools.
1:55:29 >> You got it. I'll tell you another thing.
1:55:30 So, first of all, thank you for saying
1:55:32 that. And it's like the one thing I know
1:55:35 is using this stuff is a hell of a lot
1:55:37 less scary than not using it. Like if
1:55:39 you're sitting on the outside, you just
1:55:41 hear all these people, it does what? But
1:55:43 the other thing, your experience, those
1:55:46 degrees you have and the skills that you
1:55:48 have that maybe those skills get
1:55:49 automated away.
1:55:52 People are going to hire you because
1:55:54 they you said, "I'm cautious. I don't do
1:55:56 something until it's right." There's
1:55:57 something about that. People will hire
1:55:59 you to do that. Like even if all those
1:56:01 skills get automated because that
1:56:04 experience that you have is actually
1:56:05 really valuable, right? The skills are
1:56:08 going to transfer and change and warp
1:56:10 and and get surreal. They're going to
1:56:12 hire you because okay, I don't want to
1:56:14 think about all that crap. I know he's
1:56:16 going to do a great job. So, thank you
1:56:18 for sharing that. Yeah, that's really
1:56:19 good. And I know we're time. So, well, I
1:56:21 just want to uh add on top of that
1:56:27 to Kyle's point, to Scott's point, you
1:56:30 got to start somewhere. You came here
1:56:32 tonight. I appreciate that. That's one
1:56:35 reason when we came into 2026, I told
1:56:38 Max and the XI team, we need to do more
1:56:41 with AI. We need to offer more
1:56:43 resources, more opportunities for our
1:56:46 community and small businesses to
1:56:50 to come in, embrace AI, to for us to be
1:56:54 a resource to offer workshops. Um, so
1:56:58 thank you for showing up. Thank you for
1:57:00 embracing it. You know, I would
1:57:02 encourage you to talk to each other. Um,
1:57:05 talk to Scott. Uh, Mago back there. He's
1:57:09 a very good resource working on some
1:57:11 really cool stuff with AI.
1:57:13 >> I just get blamed when stuff goes wrong.
1:57:15 That's all I
1:57:18 >> uh we have chef uh BB who has
1:57:22 transitioned from well he's still doing
1:57:24 catering but he's transitioned from
1:57:26 being a a well-known chef in Colorado
1:57:29 Springs to now he's started a new
1:57:32 business where he's helping small
1:57:34 businesses figure out how to uh
1:57:36 integrate AI into their business. Is
1:57:38 that correct?
1:57:39 >> Yes.
1:57:40 >> So
1:57:42 don't be scared of AI.
1:57:45 Like Kyle said, play with it, learn it,
1:57:48 be part of a community. I highly
1:57:50 encourage you to join the AI salon. It's
1:57:53 a great community of just very positive
1:57:57 and embracing folks who are there to
1:57:59 help you. Watch Kyle do his live every
1:58:03 night. He does get he does get a little
1:58:04 crazy at night with a guitar, but um
1:58:07 >> and a singing dog.
1:58:08 >> A singing dog. Um, and then XI, we're
1:58:12 we're a community here. Um, continue to
1:58:16 come to X, uh, let's vibe at XI. It's
1:58:18 the first and third Tuesday of the
1:58:20 month. So, uh, March 3rd, we're going to
1:58:24 do a lovable uh, workshop.
1:58:27 >> Lovable is amazing. Come to that.
1:58:30 >> So, Stephanie from our mentor, one of
1:58:33 our mentors, she's going to show you how
1:58:34 to make a I think she said an 80s themed
1:58:38 game using
1:58:40 So, that should be exciting.
1:58:42 >> That's amazing.
1:58:43 >> And then March 17th, Audrey Kushner is
1:58:46 going to come back and she's going to do
1:58:49 a demo on um Gamma and uh Notebook
1:58:53 Element on how to use that in your
1:58:56 business.
1:58:56 >> Both absolutely amazing. Loveable is a
1:58:58 live coding app. You just basically
1:59:00 describe an app you want it to build or
1:59:02 a website and it will build it.
1:59:06 like just go ahead and say make me a a
1:59:08 clone of a Aster as video game from the
1:59:11 70s and just sit back and when you pick
1:59:14 your job up the floor then you can play
1:59:16 your game.
1:59:19 >> And then we'll be doing some more
1:59:21 official AI workshops during the day. Um
1:59:25 and uh we're doing one in March with
1:59:28 Violet Brainwater and then uh we're
1:59:31 doing one in April with Box and Audrey
1:59:35 and then two more in May with Audrey and
1:59:38 then another one in June with Audrey and
1:59:40 another one with Dr. Rachel Wood who was
1:59:43 one of our panelists at Women in Tech.
1:59:45 So there's a lot of opportunities to
1:59:47 learn AI and be part of our community.
1:59:51 If there's something specific that
1:59:53 you're looking for, feel free to let me
1:59:55 know and I'll try to find a way to get
1:59:57 that plugged in or where we can meet
1:59:59 that demand. I know everybody has
2:00:00 different needs like it's how do I build
2:00:03 an agent? How do I build a localized
2:00:05 LLM? How do I do this in my business?
2:00:08 Like, just let me know what you're
2:00:11 looking for and I'll I'll we'll find you
2:00:14 a way to get to that solution.
2:00:16 Other than that, thanks for showing up
2:00:18 tonight. There's still some pizza and
2:00:19 bread left and feel free to chat network
2:00:22 and chat with Kyle while he's still
2:00:25 here. Thank you for coming.
2:00:36 Turn this