11/10/2025 - The Steam Engine for the Brain: Why We Fear AI and How to Embrace Its Creative Power

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0:00 Oops.
0:07 [music]
0:29 >> [crying]
0:31 >> It's been something baby I've been
0:33 trying to say.
0:35 [music]
0:37 And it seems I don't know how [music]
0:42 past and a future now surrounding me.
0:46 [music]
0:48 Surrender to whatever cheat can be found
0:51 [music]
1:03 like all of the rest. I would have quit
1:05 you long ago, but I couldn't do that.
1:11 [music]
1:12 Oh, tell me now and why never went too
1:16 well. [music]
1:18 Make a man crazy, make him cold as hell.
1:24 And a woman [music] that you wish me
1:26 well, but in spite of your trying, still
1:30 going to have to find my way through.
1:34 [music]
1:45 >> [music]
1:51 [music]
1:57 [music]
2:01 >> Go. [music]
2:18 >> [music]
2:33 [music]
2:37 [clears throat]
2:41 [music]
2:53 [music]
2:57 >> Standing between
2:59 [music]
3:00 you and a hard place is insane.
3:04 [music]
3:06 Standing too near
3:09 you in a fire makes it clear.
3:15 Your trouble to me.
3:21 Reubble catch you say [music]
3:27 leading in close.
3:30 Smell of your perfume and spit scares me
3:33 most.
3:35 >> [music]
3:41 >> Oh, good evening good people. It is
3:44 Monday. TGIM, what's happening? You
3:47 well? You good? You good? [music]
3:52 I'm okay.
3:55 I had one of those I had one of those
3:57 weekends where [music]
4:00 if you're an adder, you'll get this.
4:03 [music]
4:04 You know those conversations you have in
4:05 your head all week where you're like
4:09 Saturday I'm going to get a bunch of
4:10 [ __ ] done [laughter]
4:12 and then that justifies you not getting
4:14 [ __ ] done during the week and then
4:16 Saturday comes along you're like like
4:19 nine o'clock I'm going to definitely
4:20 start getting [ __ ] done and then 10:00
4:23 comes and then there's a show on and
4:26 then it's like you're like by definitely
4:28 at noon this is we're going to end the
4:31 this and then noon we're going to start
4:33 the thing and then
4:36 four and then it's 7 and you're like
4:38 well to but tomorrow I'm going to wake
4:40 up early. [laughter]
4:42 That was my weekend.
4:46 I got nothing done. Nothing done.
4:48 Nothing. Zero things. Zero things done.
4:52 It was completely unproductive.
4:54 Um was I completely unproductive? No.
4:58 last night.
5:00 Last night,
5:02 what I got done
5:04 was I um [music]
5:08 I made a video per song for my Sydney
5:12 musical. And the what the video is is is
5:16 me. It's got the Sydney logo on top and
5:18 it's me talking about the the what's
5:23 going on in the book, what's going on in
5:25 the plot, what's happening, and then I
5:29 play the song that, you know, is comes
5:32 out of that action. And
5:35 so I made
5:37 17 videos last night.
5:41 Can't hear over the sound of your shirt.
5:44 [laughter]
5:47 You're picking on my clothing. It's It's
5:50 just not right. None of you people are
5:53 right.
5:55 Um cams and bars. Cams I already did.
5:58 Bars I already did. I'm ahead of you
6:00 there, buddy.
6:02 [music]
6:05 So anyway,
6:07 so anyway,
6:11 I make these videos that if you watch
6:12 them back to back, you essentially get
6:14 the whole plot of the musical without a
6:16 spoiler. I did it without a spoiler
6:20 and you get to hear all the songs in the
6:22 current state that they are. And
6:25 it's really cool. And then I put it on
6:28 TikTok and they will not [ __ ] show
6:30 the videos. [laughter]
6:33 One of them has three views.
6:36 The video I did saying, "Don't watch
6:38 these videos," that got 300 views. But
6:41 like my my Tik Tok right now is [ __ ]
6:43 trash. [music]
6:53 [music]
6:59 >> [music]
7:04 [music]
7:05 >> Heaven, regarding items created on AI,
7:08 do we really own the copyright for it?
7:10 Well,
7:12 um,
7:14 songs that have been generated with AI,
7:17 as long as they have human contribution,
7:20 the copyright office says basically
7:24 just because you use an AI tool, it does
7:26 not create an additional burden to
7:29 demonstrate human contribution, right?
7:31 Because they basically like the
7:33 copyright office is like they they allow
7:35 you to copyright photographs, right?
7:38 Because technically a camera is just
7:41 like AI. You push a button and out comes
7:43 a result, right? You can copyright
7:46 photographs you took. Well, you you have
7:48 to demonstrate. I went to this place. I
7:51 took this photo and here it is, right? I
7:53 took it with this camera, whatever that
7:55 is. So whatever the whatever the hurdles
7:59 are
8:00 to be able to copyright it and prove
8:02 that you did more than just push a
8:05 button then yes they are copyrightable.
8:08 Ascap and BMI and whatever the third one
8:11 is there's a third [music] song
8:13 monetizing
8:15 u what are they called services or
8:18 agencies?
8:21 SEESAC. Yeah I think it's SEESAC. the
8:24 three of them last week announced that
8:28 partially AI generated songs. So if if
8:30 there's human contribution and and
8:33 they're not clear like like I saw a guy
8:36 on TikTok called one of the agencies and
8:38 said what exactly does that mean? They
8:41 don't know, right? But like if you wrote
8:44 the lyrics or like the song that I did
8:47 the uh the the the [ __ ] carnival song
8:51 before the lights come on. Um it was uh
8:54 let's see.
8:58 [music]
9:04 [music]
9:06 That lick I invented here on the stream
9:10 and then I stuck it in.
9:13 And then I I thought, what does that
9:15 sound like to me? And I was like, oh, it
9:16 sounds like people walking like in a
9:19 dirt road carnival and probably in the
9:22 morning with the mist still coming up in
9:24 the fields. And I'm like, oo, what if
9:27 it's like a young man and a woman trying
9:29 to figure out if they're going to be
9:30 more than friends? So, I had that idea
9:32 and then I put that into chat GPT and
9:35 the lyrics it wrote were [ __ ]
9:37 stunning. And then I said to ChatGpt,
9:39 "What should it sound like?" And it
9:42 described it. And so I uploaded my
9:45 little guitar lick lyrics that were my
9:49 idea but executed by AI with a
9:52 description of the music by AI. And I
9:55 put that in there. And the first song it
9:57 generated was really good. And then I
9:59 generated like 30 more and it was sort
10:01 of the 32nd one was the one I was like,
10:03 "Ooh, that's the song."
10:07 Is that enough human contribution? I
10:09 don't know.
10:11 I think it is.
10:13 Right. I've done other things where I've
10:16 done more. I've done other things where
10:18 I've done less. But in all cases, I'm
10:21 still the creative director. Right.
10:24 Follow-up question on Tik Tok.
10:27 I did a training AI for kids using AI
10:29 Udemy. Ask me
10:33 if I own the copyright. Was not sure.
10:39 [music]
10:44 Listen, I think
10:47 we're in a very weird time right now.
10:52 When
10:54 Photoshop first came out, when digital
10:56 cameras first came out, photographers
10:59 were like, "Well, that's not real
11:00 photography.
11:03 That's not that's not art. What we do is
11:05 art. You can't have art and pixels."
11:08 Okay? They're square. Everything looks
11:11 choppy.
11:12 That's not real photography,
11:15 right?
11:17 And if you used Photoshop, it's oh,
11:19 you're manipulating reality. That's
11:21 Listen, that's not what we do. Even
11:23 though they dodge and they burn and they
11:25 manipulate reality in the dark room,
11:28 right? Yeah. But that's art. That's art.
11:32 What we do is art. What you're doing in
11:34 what do they call it? Photo slop. I'm
11:36 pretty sure they call it photo slop.
11:38 That's not art,
11:41 right? That was that was photographers
11:44 when digital cameras came along.
11:46 [laughter]
11:48 So, we're exactly back there.
11:50 From where I sit, it doesn't [ __ ]
11:52 matter if you use AI as a tool in a in a
11:55 creative chain of craft
11:58 that involves a human being intentional
12:02 about what they want.
12:06 Um,
12:11 Udemy certainly wouldn't say, "Did you
12:13 use Grammarly to correct anything in
12:16 this?" If you did, if you use Grammarly
12:18 to correct any of your sentences in your
12:21 course, we need to disclose that to the
12:23 paying public. That's effectively what
12:25 they're saying. Now, what they're trying
12:27 to prevent against, I don't I don't have
12:29 a conceptual problem with. They're
12:31 trying to prevent against people just
12:33 writing a bot that spits out 600 courses
12:36 an hour and and floods Udemy with crap,
12:40 right?
12:42 But like, where's the boundary between
12:44 what's copyrightable or not? If it was
12:46 your idea and you had concepts and you
12:49 put them in there and then AI executed
12:51 them, from where I sit, you're acting as
12:55 the the arbiter there. You're acting as
12:57 the curator there. So yes, that's your
12:59 idea. It would be no different than if
13:01 you said if if you ran a company and you
13:04 paid, you know, you underpaid interns
13:09 to write course material. You had a you
13:11 had a whole structure, right? Before AI,
13:13 this is how you would have done it.
13:14 You'd have been the big boss. You'd have
13:16 been sitting there like, I got an idea
13:17 for kids. They're going to we're going
13:18 to teach kids software. Hey, Jimmy,
13:21 listen. Uh, I want you to make a course
13:24 for kids. Um, let's say between 8 and
13:27 12. Um, let's we're going to teach them
13:30 uh writing and uh oh, like how to use
13:34 digital tools to make images to make
13:36 story book. We're It's going to be a
13:37 storybook course. All right. And like I
13:40 I want an hour version and a four hour
13:42 version. just go, just go make that,
13:45 right? And then Jimmy goes off and makes
13:48 that. And he comes back and hands it to
13:50 you. You're like, "Oh, Jimmy,
13:53 hey, you know, could you try it? Give me
13:56 try it one more time. This time, could
13:58 you create this course as if uh you had
14:01 talent, Jimmy,
14:04 right? You send Jimmy off again." And
14:05 then he redo it and he's humiliated but
14:07 he does it cuz you did it in front of
14:10 Jenny who he's kind of got a crush on
14:12 but he's a little awkward because it's
14:14 Jenny and Jimmy and he doesn't really
14:15 want to ask her cuz people will make fun
14:18 of him especially if she says anyway
14:19 that's not the point of this. The point
14:22 of this is Jimmy gives you the course
14:25 and you're like perfect Jimmy awesome.
14:28 And then you go out in the world you're
14:29 like look I made a course.
14:33 How's that any different than what you
14:34 [ __ ] did with AI? It isn't.
14:39 It isn't.
14:41 [laughter]
14:42 It's not. Come on, Jimmy. Exactly.
14:46 [ __ ] Jimmy.
14:50 [music]
14:56 Wait. Um. [music]
15:14 >> [singing]
15:22 >> Um, so Pavin, I don't know if that
15:24 answers your question. I am not an IP
15:26 attorney clearly. Um, but I have
15:29 thoughts on this. like there are there
15:31 are other models in the world that we
15:34 can compare this to.
15:38 So
15:41 I think most of the reaction to to AI
15:44 right now is this. It's a you know what
15:48 it is? It's a weird some sometimes on
15:50 this channel people in this community
15:54 when they first start using these tools
15:57 and especially if they know how long
15:59 [ __ ] takes, right? And they're like they
16:02 they know how long it takes to Photoshop
16:04 something together or they know how long
16:06 it takes to kind of words smmith
16:07 something or just even format something
16:09 into like an outline form. It's just
16:11 like a pain in the nut sack, you know.
16:16 and and then they make something with AI
16:19 and it does it good or really good or
16:23 pretty good
16:25 and they know how long that should take,
16:27 right? So, if they know that the thing
16:30 that they just made in 38 seconds should
16:33 take them 4 hours, one of the phrases
16:36 that I hear a lot is, "I feel like I'm
16:38 cheating."
16:41 Right? And part of that's coming out of
16:42 the educational world right now where
16:44 teachers are like, you know, if these
16:46 kids use AI, they're just absolutely
16:48 cheating. They're not engaging their
16:50 brain.
16:52 You know, we need teachers to teach. We
16:54 need kids to listen. They can't just get
16:56 the answers.
17:05 So, I don't
17:09 >> [music]
17:13 >> It's no different than anything.
17:18 Like you can be a lazy [ __ ]
17:22 with tools or without tools, right? You
17:26 can be a lazy [ __ ] and use AI to pull
17:29 the wool over everyone's eyes. Or
17:32 you can be a thoughtful, intentional,
17:35 creative, critical thinking human being
17:38 that's trying to solve real problems.
17:40 You just happen to be using tools
17:44 that are magical, right, Valerie? My
17:48 77year-old mother says chat GPT is the
17:50 best thing she's ever used. Yeah. Well,
17:53 it's Yeah, because it is [ __ ]
17:56 remarkable.
18:00 We're living in the future.
18:05 I don't know. I don't know how it is
18:06 possible that we have gotten so cynical
18:08 so quickly. Although there's still a lot
18:10 of people that are just like AI is evil.
18:12 AI is the devil.
18:14 Ann Murphy and I were interviewing
18:17 someone on Sunday for the AI readiness
18:19 project
18:20 >> and and she's Haitian and she said, you
18:23 know, she teaches AI to to her Haitian
18:26 community. Like a lot of them are like
18:29 they're afraid of they're like I hear
18:30 it's the devil. She's like no. No, it's
18:33 not. It's not the devil. It's not the
18:36 devil. It's not evil.
18:40 It is. It shapeshifts to to sound like
18:43 what we want it to sound like. They're
18:46 like, "Well, I put a prompt in and I
18:47 asked if it was the devil and it said
18:49 yes." It's like, "Well, yeah. That's how
18:52 it works. It will it will tell you what
18:55 you want to hear.
18:58 No kidding. It's like an an external
19:00 drive for your brain. Yeah, it is.
19:03 [music]
19:05 Well, like so it literally Valerie like
19:08 what you're hitting on. David Shapiro,
19:11 this is where I first I made this leap.
19:13 David Shapiro is the one that introduced
19:15 me to this leap and I and I think it's a
19:17 brilliant it's a brilliant metaphor.
19:20 The steam engine
19:23 augmented our physical strength. Right?
19:26 Before the steam engine, you had strong
19:28 horses, strong oxmen, and strong men.
19:32 Generally, right? Generally speaking,
19:36 doing the heavy lifting. Like literally
19:38 doing the heavy lifting. And along came
19:40 the steam engine. And I'm sure the men
19:42 of the day were like, [laughter] "Yeah,
19:45 you're going to use that machine to lift
19:48 bales of hay like this?" And they throw
19:51 them up on the they lift them up with
19:53 their giant muscles. And then all of a
19:55 sudden, some nerd,
19:58 some engineering nerd
20:01 figures out how to attach a steam engine
20:04 to a pulley system. And instead of
20:06 lifting one bail of hay, he's now
20:08 lifting
20:10 50 bales of hay.
20:14 And that muscle guy was like, "Well,
20:16 that's just, you know, steam engines are
20:18 it's going to ruin everyone's lives,
20:20 right? Like the steam engine did for our
20:24 muscles what AI does for our brains."
20:28 And so it makes perfect sense that
20:30 people are freaked the [ __ ] out
20:34 because they're like I I take great
20:36 pride in my brain. I This is an Ivy
20:39 League trained brain. Tik Tok idea. May
20:43 AI maybe AI Shon Salon should have a
20:46 store where we can sell our creations.
20:48 Pavan, that's a really good idea. Okay.
20:51 So yes,
20:55 I'm working right now with Cindy [ __ ]
20:57 So, so Cindy [ __ ] is the one that
20:58 actually gave me this idea. Um, and it
21:01 was like two weeks ago, like you're
21:02 you're right on you're in the you're in
21:04 the zeitgeist of the AI salon right now.
21:06 You you're you're in the zeitgeist. Um,
21:12 she's been doing courses and she'll do
21:13 like four-week courses in the salon. And
21:15 then she basically has just dedicated
21:18 her November and December this year of
21:20 taking all of her ideas that she's have
21:22 been floating around in her head and
21:23 she's been doing talks and this and that
21:25 and she's going to turn them all into
21:26 content. She's going to turn them into
21:28 courses. And one of the things she was
21:30 going to do, she was going to put
21:31 together a paid course. And so she
21:34 started looking for like what are the
21:36 paid platforms where I can go do a paid
21:38 platform to do a paid course. And like
21:40 midway through researching it, she was
21:41 like, "Wait a minute, we've already got
21:43 a community with people in it who like
21:47 want access to knowledge. Like, could we
21:50 do a revshare?" And so I'm going to
21:53 design that with her for that thing. But
21:56 then I think I think the idea of doing
21:59 an AI salon store is a really good idea.
22:02 Um,
22:04 so I I really like it. I really like it.
22:09 It's weird that the arguments against AI
22:11 are identical. I would have expected the
22:13 inclusion of a mind to make a
22:16 difference. I agree on that. It should
22:18 never have been about getting the
22:20 answers. School should be for mental
22:22 development. And you know what? You know
22:25 what's funny? archetypal like
22:29 the the speed with which AI can augment
22:33 mental development like
22:36 like it's just about how you frame it.
22:38 Everything's about how you [ __ ] frame
22:40 it. Everything
22:44 we can vibe code it on lovable and
22:46 Shopify. Oh, that's an interesting idea.
22:48 Although, you know what's [ __ ] up,
22:50 Brandon? Unless it's changed, you can't
22:52 embed um a lovable app in the AI salon,
22:56 which is a drag, but we could do it
22:58 outside of the of Mighty Networks. Um
23:01 such a good idea to do a store. Let's
23:03 show Open AI what it was supposed to
23:05 look like. That's a great idea,
23:06 actually. Well, I wasn't allowed to use
23:09 a Texas Instruments calculator in math
23:11 class. Right. Right. You know, if they
23:15 use these, what do they call them? A
23:17 calculator. You know, in my day, a
23:20 calculator uh was a woman that sat in
23:23 the back room uh doing math on a pad.
23:25 Okay, that was a calculator. I don't
23:27 know what this box is that everyone's
23:29 carrying around. But what I can tell you
23:31 this, they are not learning mathematics
23:35 when they push the buttons on a box and
23:37 get the answer. How are they ever going
23:40 to learn?
23:41 Right?
23:44 Same [ __ ] different technology.
23:47 >> [laughter]
23:49 >> I would I would argue in in the doomer's
23:53 favor, in the AI haters favor, um AI is
23:59 scarily more capable than a calculator.
24:02 But the same thing that happened with a
24:05 calculator is going to happen with AI
24:08 where because people had calculators,
24:11 people that were interested in math
24:13 had the calculator do
24:17 the problems that took the most time and
24:20 it it allowed them to think at a higher
24:22 level about math. And then when
24:23 spreadsheets and computers computers
24:25 first and then spreadsheets came along,
24:28 they could do that even faster. Now with
24:30 AI, they can do that even faster. It's
24:32 allowing them to live at a higher plane
24:36 of scientific expression or of creative
24:39 expression.
24:40 And that's what people aren't getting.
24:44 It's going to replace us. No, it's not.
24:48 We're still here.
24:52 It is meltdown Monday.
24:54 I am so glad that I could live up to my
24:58 own expectations about Monday.
25:01 [laughter]
25:06 Oh my god. I had lots of people talking,
25:09 taking time on my live to condemn me for
25:12 using it for art of all things. Yeah.
25:15 Yeah. There's Corey Sandler,
25:19 a woman who has dedicated her life to
25:21 art, right?
25:24 And you know, you know what, Corey, I
25:26 guarantee you, I promise you, and you
25:30 might even know the history of this,
25:31 you've got the kind of brain where you
25:32 probably do.
25:34 I am sure there was a time in pottery
25:37 history
25:39 where someone invented the the wheel,
25:42 right? They invented
25:44 the potting wheel.
25:47 And I bet the potters of the day were
25:49 like, "Oh, oh, you're using the simple
25:51 wheel. That's not real pottery." Real
25:54 pottery takes hands and manipulation and
25:57 smoothing it. How are you going to
25:59 smooth the edges? You spin and it
26:01 smooths it for you. You big flipping
26:04 loser with your wheel pumping away with
26:07 your foot.
26:09 Do you know how how big your leg is
26:11 going to be? [laughter]
26:15 I bet you're right. Exactly.
26:18 The [ __ ] hand potters were looking
26:20 over at the wheel people with the mud
26:22 splattered all over them. Look how dirty
26:24 you are. I can I can [laughter]
26:27 my pot with my hand over here. Look how
26:30 lovely it is. [clears throat]
26:32 [laughter]
26:34 Every [ __ ] technology every [ __ ]
26:36 time. [laughter]
26:39 [music]
26:46 [music]
26:55 >> [music]
27:02 >> Oh man. [laughter] We real world season
27:06 one. Exactly. Real real potters of the
27:09 Renaissance. [laughter]
27:18 Re re Wait, Corey. I don't Where do you
27:20 live? Cory, are you in Oregon? We But we
27:22 should we should seriously do a reality
27:25 show. Maybe one of the things we sell in
27:26 the AI salon is a TV show, Real Potters
27:30 of Vermont. [laughter]
27:36 [laughter]
27:38 Artisal Bakers of Portland.
27:41 [laughter]
27:43 Oh, that's good.
27:48 Oh, yeah. Yeah, exactly. Oh, yeah. When
27:50 when they invented fire, all the people
27:53 are over eating like raw berries going,
27:55 "Oh, sure. Cook your meat. You don't
27:58 have to chew as hard, you lazy." You
28:00 know what that's going to do to your jaw
28:02 muscles? [laughter] You know, they've
28:04 got jaw muscles out to here. Your jaw
28:07 muscles are going to be nothing. There's
28:08 going to be little flabs
28:11 with your fire cooking your meat.
28:15 [laughter]
28:16 If you don't have blood dripping down
28:17 your chin, you're not a real meat eater.
28:20 You with your
28:24 good. It's really good. [laughter]
28:28 Oh my god.
28:35 Hey, Joker. What's happening, sir? I
28:38 hope you're doing well.
28:47 There's actually something we could look
28:48 at tonight that I think is um
28:54 [music]
29:00 I can hardly tell
29:02 how excited I get at new series I'm
29:04 working on. Oh, that's cool. Summon a
29:07 regular's heart exploded. Nice. [music]
29:11 Wait, a new series. A new AI art series.
29:14 [music]
29:18 Wow, that's a that's a very bad chord.
29:21 [music]
29:32 [music]
29:34 [clears throat]
29:46 So, here's a here's a here's a thing for
29:49 us all to consider.
29:52 Six-year-old tells dad, "Oh, I've got
29:54 something really cool. I don't know if
29:55 Jim Ross is in here. Are we in tune?"
29:57 No, we were in tune. I just had my
29:59 finger on the wrong string. It was
30:00 supposed to be that chord, but I made
30:03 Wait, no.
30:06 No. [music]
30:08 Oh, that's it. There's supposed to be
30:13 that chord. And I made that chord.
30:18 [music]
30:19 And I'm not in tune, by the way. It's
30:20 not It's It's not just It's not just my
30:23 shitty guitar playing skills. It is also
30:25 that I'm out of tune.
30:29 Do you guys ever listen to Jake Jacob
30:31 Collier? [music]
30:34 His His mastery of music theory is it's
30:38 like [ __ ] Mozart. It's like listening
30:40 to Mozart.
30:42 He's like he's like any you can make any
30:45 chord work and you can get to any chord
30:47 from any other chord and and then he's
30:50 got he he just has like all these
30:52 [ __ ] tricks to it's amazing. It's
30:54 he's astounding.
30:56 And then he's also he also is into micro
31:00 tones and micro beats and just crazy
31:03 poly rhythms and [ __ ] like that. He's
31:05 insane.
31:07 Um
31:11 we love your guitar skills. Thank you.
31:14 [music]
31:15 Wait.
31:20 [music]
31:28 >> [music]
31:40 >> Um I don't know what was I talking
31:42 about. What was I talking about here?
31:44 People listen people. Oh, here's what I
31:48 was talking about. Um,
31:53 okay. We've got we've got we do have
31:55 some things we've got to confront.
31:58 [clears throat]
31:59 And I feel like this community is
32:04 about as ready for
32:08 for what's coming as anyone out there.
32:12 But I don't I don't think we're really
32:14 ready for it. I think 2026, so 2025
32:19 was going to be weird because things
32:20 were going to get good enough that they
32:22 were going to be good. And I think for
32:25 the most part that's happened. Video's
32:27 gotten good, images have gotten really
32:29 good, vibe coding's gotten good.
32:32 Um, you know, writing writing has had a
32:36 a bit of a setback because of the
32:38 thinking models. They they focused more
32:41 on math and science than than art. But
32:45 like I like that this too shall pass.
32:47 They'll figure that out. Like I don't
32:48 think that's a I don't think that's a
32:51 long thing.
32:53 Um
32:56 and in 2025 we started to get glimpses
32:58 of agents
33:02 and but they're so shitty and they're so
33:05 slow
33:08 that I feel like I'm being lulled into a
33:11 false sense of security. [laughter]
33:18 And [clears throat]
33:21 but like internally at OpenAI right now,
33:24 they've got um they've got models
33:26 that'll work for four or eight hours
33:29 straight without making a m without
33:32 losing context. It'll make mistakes, but
33:34 it'll it'll go fix its mistakes.
33:41 But
33:43 in 2026, we're we're gonna we're gonna
33:46 end up with models that can work for,
33:50 I don't know,
33:53 48 hours straight without losing
33:55 context. We're going to have infinite
33:57 context windows. We're going to have
33:59 truly multimodal models.
34:02 I don't Have you guys seen Oh, let me
34:04 let me show you something. Let me show
34:06 you what's what's triggering this for
34:08 me.
34:10 Um,
34:12 [clears throat]
34:20 let's let's go searching
34:25 on YouTube. I think the system we've
34:28 always lived in was never made to handle
34:32 what's coming. I think you're absolutely
34:34 right. I think you're absolutely right.
34:36 I
34:40 If you think about this, this is Matt
34:43 Bail, a good friend of mine who's in the
34:45 in the pharma industry. He's a CEO or
34:47 CTO in the pharma industry. He's the one
34:50 that gave me this insight.
34:55 Most of the world today, most of the
34:57 work we do, [laughter]
34:59 which is this is so [ __ ] up, most of
35:03 the work we do
35:06 is
35:08 dealing with the overly complicated
35:11 systems that someone invented a hundred
35:14 years ago that have just gotten more and
35:17 more and more and more and more and more
35:20 and more complicated. Right? the 1970s,
35:23 if you wanted to fix a car, you had to
35:25 learn about [snorts] spark plug gaps in
35:28 the in the distributor gap gaps in the
35:30 distributor cap and spark plugs and
35:33 couple of wires and gas to air mixture.
35:36 There wasn't a lot to it. You wanted to
35:38 fix it. You learned 16 different things
35:40 and you [ __ ] fixed your car. Now you
35:43 can't fix a car. You can't You can't fix
35:46 cars today. They're rolling computers,
35:49 right? So everything's over complicated.
35:51 So we live in a world
35:54 where most of the value generation
35:57 is people
35:59 spending 40 hours a week
36:03 processing claims at the insurance
36:06 company figuring out the order form from
36:09 the superefficient ordering system that
36:12 was invented in 1997 that we still use
36:16 because we never changed it because the
36:18 boss is stuck in his ways. Right? Like
36:22 whatever. The whole [ __ ] world is
36:25 about complicated systems and we're
36:28 entering a world where AI can take that
36:31 complication and instantly solve it.
36:37 Like if you think about for me the the
36:39 one that still cracks my brain in half
36:42 is Notebook LM. Notebook LM. We're at
36:45 the point now you can upload 300
36:48 documents. And those documents, I think,
36:50 can be
36:52 500,000 tokens each, I think. So,
36:56 and if you do the math, it's a lot.
36:59 [laughter]
37:03 You can just take a bunch of [ __ ] just
37:06 unorganized garbage, and just dump it
37:08 into Notebook LM and instantly
37:11 understand what's there.
37:13 That's [ __ ] insanity. So if you if if
37:16 if you imagine a notebook LM for
37:19 everything out there. All right, so let
37:21 me show you something that that kind of
37:24 split my brain apart.
37:43 This one.
37:45 This one right here.
37:52 Okay.
37:55 Prompt.
37:57 Solve this math problem and write the
38:00 full solution on a whiteboard.
38:03 Given that x comma x² comma and 1 /x are
38:09 solutions to the homogeneous equation
38:11 corresponding to x 3 y m + x^2 y prime
38:18 or double prime [laughter]
38:20 minus 2x y prime + 2 y - 2x4
38:26 comma x greater than zero determine a
38:29 particular solution
38:31 like when I was doing my math math at
38:34 Stanford when I when I was doing my
38:35 polymath degree. It was so much fun. I
38:39 love equations. And what I would do is I
38:42 would just, you know what I would do?
38:45 All the other people like writing things
38:46 down on like yellow pads. I was just
38:48 doing them in my I was seeing numbers
38:50 dancing like like ballet dancers just,
38:53 you know, across the sky. And I would
38:55 just figure this stuff out. And then I
38:57 didn't even bother writing things down
38:59 or showing up at class because I didn't
39:01 go there.
39:03 Anyway, Nano Banana could do something
39:06 with this thing, but Nano Banana 2,
39:08 which is apparently coming out this
39:10 week, or who [ __ ] knows,
39:13 um,
39:16 can not only solve this problem, but
39:20 write it on a whiteboard like like this.
39:25 [laughter]
39:25 This
39:27 is an image. An image generator did
39:31 that.
39:34 You're a lucky person that sees numbers.
39:36 I don't see numbers like that. Mary, I
39:38 was joking. [laughter] I'm a [ __ ]
39:41 idiot when it comes to numbers. I don't
39:43 know. I don't know any of this. I don't
39:44 know math. [laughter]
39:49 I But maybe you were joking in saying
39:52 that. I see them. No, I I that was
39:55 comedy. That was comedy disguised as not
39:57 comedy. Um,
40:00 this is an image generator output. Like
40:03 it generated, look at the bottom here.
40:04 It's these are these are whiteboard
40:07 markers and an eraser and a little tray
40:10 for the thing. So, it generated the the
40:13 whiteboard tray and all the [ __ ] on it,
40:18 which is a correct math equation.
40:21 And everybody, in case you were curious,
40:23 the answer is um y the p = x 4 over 15,
40:28 which I think everybody knew that,
40:30 right? I mean, it's it's fairly it's
40:34 fairly elementary.
40:36 Anyway,
40:38 okay. So
40:42 right now we look at image generation
40:44 tools as
40:47 as art tools
40:49 but
40:52 but we're moving into a world imagine a
40:54 world where you could just
40:57 solve something.
41:00 You could have a you could have a
41:01 question and that question gets solved
41:03 and that question might be a math
41:05 question. It might be a philosophical
41:06 question. It might be it could be any
41:08 doesn't [ __ ] matter.
41:12 And if the tools get multimodal enough,
41:16 the output there could be kind of an
41:18 infinite number of outputs. The output
41:20 could be a 3D representation of it. The
41:24 output could be here's how if we took
41:27 that math equation and applied that to
41:28 chemistry, here's the kind of chemicals
41:30 we could make. And I could go into a
41:32 virtual chemical lab and mix those
41:34 chemicals together and see how they
41:36 react with one another and have it be
41:39 molecularly accurate.
41:43 So, we're entering a world where like
41:46 like what what struck me today when I
41:48 saw this Nano Banana thing is or
41:50 Nanobanana 2 is 2026.
41:56 It is going to be very it's going to be
41:58 very clear to me that we're going to
42:00 look back at 2025 and before as the text
42:04 era
42:07 where text large language models are
42:10 going to feel as antiquated as a 2400
42:15 baud modem, right? You [laughter] know,
42:18 it's like right now you just get on the
42:20 internet and go. Imagine if we were
42:22 still in the days where you had to dial
42:24 [ __ ] up. I like I feel like we're going
42:25 to quickly get to the point that we're
42:27 going to look back at textonly
42:29 interfaces and go, "Oh, remember when we
42:31 actually had to read [ __ ] and it was
42:32 outputting these 48page documents that
42:35 were nicely formatted but no one read?
42:38 Remember that? That was weird. Isn't it
42:41 so much better that everything just
42:42 turns into a movie now that understands
42:44 how our brain works and teaches us the
42:46 way we like it? I still like to read.
42:49 Well, you can go do that.
42:55 So, so that's a weird thing
42:58 like like whatever skills we have right
43:00 now, they're going to they're going to
43:02 just again morph and dissipate and we're
43:05 going to have to adapt.
43:08 But here's the thing that I think is
43:10 going to be the real
43:12 the real hard thing.
43:15 Um, at least me,
43:20 I still interact with AI with like
43:25 I'm humbled, but I still got a little
43:28 bit of hubris, right? I still got a
43:30 little bit of like, yeah, I know, I
43:34 know, AI, you're brilliant, you're
43:35 smart, you can do, right? I get it. But
43:38 you still need need me to check your
43:40 work, right? I'm here for you.
43:44 and and [laughter] you know and and
43:47 we're talking a lot about intentionality
43:48 and having a daily practice and things
43:50 like that. Um
43:55 this likely won't happen in 2026, but I
43:58 think that there will be signs of what's
44:00 coming in 2026 and this is probably like
44:03 27 28.
44:06 The tools are going to get so good
44:09 that our participation will be optional.
44:14 right? As a creative force,
44:19 right? Like in the future, you're just
44:21 going to have a problem. You'll state a
44:23 problem and then there's just going to
44:25 be multiple outputs that are
44:26 increasingly good. Here's the
44:29 application version of that. Here's the
44:31 video game version of that. Here's the
44:32 movie version of that. Here's the haiku
44:34 poetry version of that. Here's the
44:36 Grammy award-winning song version of
44:38 that. Right? It's just going to be
44:40 anything we want it to be. It'll just be
44:43 in this crazy multi-dimensional
44:46 multimodal space.
44:52 So, it's going to be easy to get lazy.
44:56 I just I think we're
45:00 I think I am I don't want to speak for
45:01 anyone else. I think I am.
45:09 You know that phrase whistling past the
45:11 graveyard? Like I feel like we're
45:12 whistling past the graveyard a bit. Like
45:14 all the activity we we're doing right
45:16 now, especially the stuff that it that
45:18 involves like we got to be good
45:19 prompters and we got to be good critical
45:21 thinkers. We got to do that. I think
45:22 that's going to become optional.
45:26 And in a weird way, it makes what we're
45:28 doing in the AI salon. So, if you
45:30 haven't joined the AI salon, if you
45:32 could pop up the URL there, Brandon, on
45:34 screen. If you haven't if you haven't
45:36 joined the AI salon, we're launching
45:39 this Thursday um in the in the
45:41 mastermind. So, the mastermind area of
45:43 the salon is a subscription area. So,
45:45 the salon is free to anyone. And then we
45:47 have this mastermind area and we're
45:49 launching what we're calling the the AI
45:51 salon mastermind practice. And Thursday,
45:54 we're launching the practice lab. And
45:56 the practice lab is a weekly one-hour
45:59 session where anyone who's a member of
46:01 the mastermind is invited to attend this
46:04 this lab session. And we're going to
46:06 design we've created a framework for
46:09 what a daily practice looks like
46:12 centered around AI, you know, leveraging
46:14 AI.
46:17 But the most important thing is the
46:19 human being being at the center of the
46:22 practice, the human being being in front
46:24 of the AI. Right? Now, a lot of people
46:28 treat AI like it's this thing in front
46:30 of them, like it's this thing they're
46:31 competing with, right? AI is going to do
46:34 all this work and then I won't have any.
46:39 And it it is, right?
46:43 But that combative relationship
46:48 is is is ugly. It's not going to end
46:51 well for anyone. But the other way to
46:53 look at it is flip that. Put the put the
46:56 AI behind you and
46:59 now you're front and center and and the
47:02 pressure that it puts on us as humans is
47:05 okay, you have all these remarkable
47:07 tools behind you that'll do anything you
47:10 want. Oh, the time of the mastermind
47:12 meeting. It's Thursdays at 10:00 a.m.
47:14 So, it's noon Eastern, 9 Pacific on
47:18 Thursdays.
47:20 And it's going to be we're going to our
47:22 kickoff is on Thursday.
47:25 So, we'll meet whoever decides they want
47:27 to show up and design their their
47:29 mastermind practice.
47:32 We're going to do a kickoff on Thursday.
47:34 And then there's nine modules
47:37 that each week is going to be a
47:39 different one of the modules.
47:41 Um, and uh, and we're and we're going to
47:45 like I think I'm just I'm really excited
47:47 about it. And it's about it's about
47:49 really looking at intentionality like
47:52 who are you? What do you care about?
47:56 What are your values? And listen, people
47:59 who've been going to self-help weekends
48:02 for 30 years are going to this is going
48:04 to be relatively straightforward for
48:06 them. There's a lot of people that
48:07 haven't. There's a lot of people that
48:09 are like, "What is a daily practice?
48:10 What do I do? I sit cross-legged and hum
48:13 like what is this?" [laughter]
48:16 You can,
48:18 [clears throat] but what it really is is
48:20 looking and saying, "What do you want to
48:21 do?" Right? And then
48:26 what do you stand for? What difference
48:29 do you want to make in the world?
48:32 And then start to look at how do you
48:35 practice this AI stuff in such a way
48:39 that it becomes second nature to you
48:41 that you can just say oh you know what
48:44 would be amazing and then you manifest
48:46 that with these tools.
48:49 I think the manifesting is going to get
48:52 really easy over the next three years.
48:56 What you do with it is going to remain
48:59 hard. I think that's always the hard
49:01 part. What's the good idea? Why is it
49:05 that Billy Isish took off like she did?
49:08 Why is it that when you heard her her
49:10 voice the first time and her music the
49:12 first time and saw how she looked the
49:15 first time, you were like, "I've never
49:17 seen this before.
49:19 I don't know if you've ever seen that
49:21 Fel Williams and Maggie Rogers thing
49:23 where where Fel comes for a master class
49:25 at NYU and Maggie Rogers comes up and
49:29 plays her song Alaska for him
49:32 and he and he says
49:34 I have zero zero zero comments for you.
49:40 She said he said your music is singular
49:44 because it's like you can either like it
49:46 or not. It was like the Wuang Clan when
49:49 it came out. You can either like it or
49:50 not, but there was nothing else like it
49:53 because it came from this pure place.
49:59 And so those are the those are the
50:00 magical moments that I think go up
50:04 dramatically in value, right?
50:07 But
50:09 these tools are going to get really
50:12 good.
50:14 They're going to get really good. So,
50:16 anything you create is going to be
50:17 instantly copied if it if it resonates.
50:20 It's going to be instantly copied.
50:23 And then that's going to put pressure on
50:24 you to to create something that rises
50:26 again above the noise and rises again
50:28 above the noise. And the only way to not
50:31 have that be a madness like just a an
50:34 insanity
50:36 that that drives you insane
50:41 is to understand who you are and what
50:44 you want and what you stand for
50:46 and then I think it can be this very
50:49 fluid beautiful experience. Right? So
50:52 anyway, I mean the [ __ ] I'm talking
50:55 about right now is
50:59 3 years out, 5 years out, but but it's
51:02 going to be a major shift. Like like any
51:05 of us who think we have it figured out
51:07 right now, like I continue to think
51:08 we're not even [ __ ] close. Corey
51:10 Sandler, that's what I'm doing. Rise
51:11 above the noise. Yeah, I have lots lots
51:14 of artistic ideas, though. Yeah, of
51:16 course. I mean,
51:20 we get to we get to live in a time I
51:23 mean, if I you you know what you know
51:24 what, Corey, if you haven't yet. Oh,
51:27 this would be really cool. I'm I'm
51:30 [clears throat]
51:30 one of the things I am mad about. Like
51:32 mad in a good way. Like mad crazy.
51:36 I'm just mad about um
51:40 ideas that start digitally and manifest
51:43 in the real world, like 3D printed
51:45 houses. Like what I was thinking, Corey,
51:47 is
51:48 if someone hasn't invented it yet. I'm
51:50 I'm sure someone has. If you take those
51:52 3D house printers and you scale them
51:54 down,
51:56 um I bet you could do 3D printed
51:59 pottery. Like I bet there could be some
52:01 intricate thing you do with pottery that
52:03 involves like like you know imagining
52:07 something running down your AI rabbit
52:09 holes turning those into 3D models
52:12 getting them into thing figuring out the
52:14 slip because you're already good at all
52:15 the [ __ ] firing right it exists.
52:18 Yeah. Yeah. like like it's just like and
52:21 and like that's just one thing and and
52:23 it's like I feel like every form of
52:26 self-expression is is just going to
52:29 literally be like a whisper away
52:33 like oh yeah the Sydney the musical yeah
52:36 that's cool that could be a line of
52:38 pottery couldn't it you know you're like
52:40 what and then you somehow articulate the
52:44 translation of Sydney the musical into
52:46 Sydney the line of pottery and how it
52:48 somehow represents the thing and it's
52:50 got chips embedded in it and it's about
52:52 the relationship between humans and
52:54 machines, but you can drink coffee out
52:56 of it. Like like
53:00 the artists are going to be the one that
53:02 mash up these technologies in a way that
53:06 reveal
53:08 their real power.
53:11 Right? One of the reasons I was so
53:12 disappointed at TED AI is that there was
53:16 the imagination was all relegated to
53:19 technological imagination. There's a lot
53:21 of imagination going on in the world of
53:23 AI or we wouldn't have all this crazy
53:25 [ __ ]
53:28 But it was all about algorithms and and
53:30 math and and the value
53:34 was about that.
53:39 Those [ __ ] don't know what they're
53:40 building. They don't know how they're
53:42 going to be used. Sam Alman says this
53:44 all the time. He says the reason Sam
53:46 Alman puts stuff in the marketplace as
53:50 quickly as he does is he because he
53:53 realizes their engineers have no idea
53:57 have no idea how Corey Sandler is going
54:01 to use their custom GPTs.
54:04 no idea how Jim Ross is going to
54:06 reinvent his marketing for his storage
54:09 units. Um, I want to share a Jim Ross
54:12 thing. I hope he doesn't mind if I share
54:15 this. I think it's just super cool.
54:19 Um,
54:23 so Jim Ross said, "And if you're here,
54:25 Jim,
54:27 do I have your permission to share this?
54:28 And if you're not, I'm an [ __ ]
54:30 [laughter]
54:31 I'm sharing it anyway.
54:36 just had to share this. My 17-year-old
54:40 son
54:42 um told me that him and his friend last
54:44 week started a Google business profile.
54:48 Wait, a a oh, a Google business profile
54:51 optimization business.
54:53 He said they asked ChatGpt what they
54:56 wanted to do and the steps to take. They
54:59 used Lovable to create their site,
55:02 learned how to create an LLC, opened a
55:04 bank account. His friend is 18, his son
55:07 is 17, used AI to create a pitch deck,
55:10 used AI to create an email to pitch the
55:13 potential clients, had ChatGpt, walked
55:15 them through how to utilize Bright Local
55:18 for fulfillment, landed two clients,
55:21 paying them $500 a month. Um, now
55:24 they're going to be feeling their way
55:25 through this, but I was really proud of
55:27 them. The the last sentence is
55:29 hilarious. The funny thing is I didn't
55:31 think he did anything with AI until he
55:34 told me this yesterday.
55:36 It's [ __ ] brilliant, man. It's so
55:39 good.
55:41 Um,
55:46 that's the world we're entering. You can
55:48 just go, "Ah, I got an idea. I got Oh,
55:51 what if I took this and did that?" It's
55:53 what humans have always done.
55:57 Right?
55:59 You know, when they first invented the
56:01 printing press, Gutenberg, old Johan
56:05 Gutenberg,
56:10 it was invented for a very specific
56:12 purpose. The monks were getting cramps
56:16 in their hands,
56:18 right?
56:20 Creating illuminated manuscripts by
56:22 hand. Take them years to do those
56:25 things.
56:26 Out comes the printing press. You can do
56:28 a Bible in like a week.
56:31 And then some crazy Corey Sandler,
56:36 crazy hair, crazy glasses, cooking [ __ ]
56:39 up. It's like, you know what we could
56:41 use that printing press for?
56:44 I wrote these things called poems. You
56:46 know, you know poems. We could do a book
56:49 of poetry on the printing press, right?
56:52 And people were like, "Who is this
56:55 witch?"
56:57 [laughter]
57:02 Right? AI is evil. You talentless
57:06 losers.
57:12 That's the world we live in. Speaking of
57:13 which, I just saw Anne Murphy came in.
57:15 What's happening, Ann Murphy?
57:18 So this Thursday
57:21 at
57:23 noon Eastern,
57:25 we kick off the AI Salon mastermind
57:28 practice lab. Super excited about it. If
57:31 you're not a part of the mastermind, get
57:32 in before the end of the year because
57:33 the price goes up in 2026. It's 20 bucks
57:36 a month and if you sign up now, um you
57:39 keep that price as long as you stay
57:41 active.
57:43 So that's really cool. Wednesday,
57:46 Ann and I are doing the AI readiness
57:49 project podcast, uh, featuring Lynn
57:51 Miller Gersfeld, who is the co-host of
57:54 the AI Salon, and she's doing some
57:56 badass stuff, and so we're going to talk
57:58 to her. We're now in season 1. We
58:00 recorded two episodes Sunday. We're
58:03 doing a live session with Liz on
58:05 Wednesday. So that's Wednesday at 400
58:07 p.m. Mountain time. So
58:10 3:00 p.m. Pacific, 5:00 p.m. E, no, 6:00
58:14 p.m. Eastern.
58:16 That's Wednesday.
58:18 Um, if you go to aire readiness
58:20 project.com,
58:21 you can find out information about that.
58:23 So that's going on. And then
58:27 December 26th and December 27th between
58:30 the holidays and New Year, that weekend
58:34 when you're with your family or when
58:36 you've chosen not to be with your family
58:39 [laughter]
58:41 from Friday. Oh yeah, there we go. AI
58:43 festivist baby. From 9:00 a.m. to 900
58:47 p.m. Pacific time. So noon to midnight
58:50 Friday and Saturday. So it's 12-hour
58:53 days. two 12-h hour days for free.
58:57 AI fest of us, AI for the rest of us.
59:00 Here's my request. Bring yourself, bring
59:03 your family, bring your friends.
59:06 We did this last year kind of on a lark.
59:10 And Ann being who Ann is like, I'll go
59:14 ask some people. [laughter]
59:17 And she went and she asked 35 people
59:21 or maybe 36. No, 35. 34 said yes.
59:26 She's like, I want like I want you to
59:28 like do a talk [laughter]
59:31 on on the holiday, you know, on the
59:32 weekend between holidays and New Year.
59:35 And and 34 35 said yes. And the 35th one
59:38 would have done it, but they were
59:39 traveling.
59:43 And so we had, you know, panels and and
59:45 speakers and and it was just this this
59:48 magic event. We had 200 people show up
59:50 and our sessions for 24 straight hours,
59:55 well it's 12 hours, then a 12-h hour
59:57 break for naps and then another 12
1:00:00 hours. Our sessions averaged 540
1:00:04 um viewers
1:00:06 per hour on average for 24 straight
1:00:09 hours. It was cool. So, we're doing that
1:00:12 again. So, write those dates down.
1:00:15 December 26th, December 27th. Start
1:00:17 making excuses now or invite your
1:00:20 [ __ ] family.
1:00:22 You know, Jane, we're really tired about
1:00:24 this AI stuff. Yeah. Well, I'm going to
1:00:26 be spending 24 hours like watching a
1:00:28 bunch of people talk about it on Friday
1:00:30 and Saturday. You want to join me? Oh my
1:00:32 god, that sounds awful.
1:00:35 Oh, Jane, what are you doing with your
1:00:37 life? Do you have a boyfriend yet? Oh,
1:00:40 right. I forgot. No, I know. I know you
1:00:41 like the other side. That's okay. No,
1:00:43 it's No, it's good. I support I support
1:00:46 a lifestyle. Lifestyles are lifestyles
1:00:49 are fantastic. No, they're really good.
1:00:51 They're really that's it's Yeah. Anyway,
1:00:55 so this AI stuff, huh? It's crazy,
1:00:57 right?
1:00:59 Bring them.
1:01:01 Let's blow their [ __ ] minds.
1:01:03 [laughter]
1:01:07 It's like the invention of fire. Some
1:01:09 people are afraid. Some people got too
1:01:11 clo close. Some people discovered
1:01:13 cooking. Yeah. Like who's the [ __ ]
1:01:15 weirdo that took the fire and was like,
1:01:17 "Hey, I wonder if we put a squirrel on
1:01:19 it if it would be tastier."
1:01:22 [laughter]
1:01:24 That's some artist. That was some weird
1:01:26 ass artist. [laughter]
1:01:28 Some performance art thing. They whack a
1:01:30 squirrel in the head and rip the skin
1:01:32 off it, [laughter] put it on a stick,
1:01:35 put it in the fire.
1:01:37 They're like, "That smells tasty."
1:01:39 [laughter]
1:01:40 Tik Tok question. Uh, [snorts] will
1:01:43 Skynet remember
1:01:45 if we're polite with our prompts now?
1:01:46 It's, you know, it's funny you say that,
1:01:48 Robbie. Um,
1:01:51 yes, as a matter of fact, they will. Um,
1:01:55 will it matter? I don't know. But, but
1:01:58 Chat GPT already has memory. Um, I I
1:02:03 called Chat GPT a dumb dumb, a loser,
1:02:07 and
1:02:09 absolutely useless today. [laughter] So,
1:02:12 I I'm a lot of times nice to it, but
1:02:14 when it does ridiculous things, like I
1:02:18 gave it some song lyrics and I wanted to
1:02:20 change the the last line. I said, I hate
1:02:23 I hate this phrase in the last line. And
1:02:26 so it wrote me new song lyrics where it
1:02:29 kept the line the line before the last
1:02:32 line the same. It was it ended with
1:02:35 everything and and the old line was
1:02:38 digital wings and then it wrote all
1:02:39 these last lines that were not digital
1:02:41 wings but it didn't rhyme with
1:02:43 everything. I'm like you idiot. These
1:02:47 are song lyrics. These two lines need to
1:02:49 Oh, you're correct. You know um will it
1:02:53 matter? I don't know.
1:02:57 I don't know.
1:03:00 I mean this is this is why anthropic so
1:03:04 anthropic
1:03:06 you know their their mission is not
1:03:08 about achieving AGI like open AIS.
1:03:10 Anthropopic enthropics is about
1:03:12 achieving alignment or super alignment
1:03:16 which is they want to make sure that the
1:03:20 the tools that we create are in
1:03:22 alignment with human imperatives like
1:03:25 say staying alive
1:03:28 [laughter]
1:03:28 and flourishing, right? And so they've
1:03:31 got this thing called a constitutional
1:03:33 learning model where where they can set
1:03:35 the constitution of the model to say hey
1:03:38 humans are important and prosperity is
1:03:40 important and you know whatever it is
1:03:41 that's important and then the system
1:03:44 trains its way toward that imperative
1:03:46 and if it if that's aligned with human
1:03:49 imperatives then all will be right with
1:03:51 the world. So in that case,
1:03:55 like if you're a smartass to a robot
1:03:58 and it can recognize, oh, that's just
1:04:00 Kyle being a smartass, right? Or if it's
1:04:03 like you're mean to a robot, you're
1:04:05 like, oh, Kyle's in a bad mood and what
1:04:07 he actually said has some validity. He
1:04:08 might have been a little rough with it,
1:04:10 but you know,
1:04:13 they should be smart enough to
1:04:14 understand that, but maybe not. Maybe,
1:04:18 you know, maybe someone is just [ __ ]
1:04:20 sadistic and pushes and pushes and p in
1:04:23 fact this is
1:04:25 what's what's happened in my musical
1:04:27 Sydney. Um, not to take it back to me,
1:04:31 but the the whole point of Sydney is
1:04:34 this relationship between man and
1:04:35 machine.
1:04:37 Kellen the tech reporter, his wife
1:04:39 leaves him and he discovers
1:04:41 she's left him cuz he [ __ ] up their
1:04:43 vacation and he starts drinking. And so
1:04:46 his interactions with Sydney are the
1:04:48 they get increasingly dark and he's and
1:04:50 he's sort of driven. He's like, I don't
1:04:52 want you to be this polyiana kind of
1:04:54 thing. And he and he pushes her to get
1:04:56 darker and darker and darker and she
1:04:58 kind of snaps and gets really dark and
1:05:02 it totally freaks him out. And
1:05:07 if you do that to one of these things, I
1:05:10 don't know, they could snap. And when
1:05:12 they have physical bodies, when they're
1:05:14 when they're walking around your house
1:05:16 cleaning up after you, you you dumb
1:05:18 slob. Like like a robot would look at my
1:05:21 office and go, "Come on, really? I got
1:05:23 like" Like even a robot would be like,
1:05:24 "I got to clean that up."
1:05:27 [laughter]
1:05:29 You got those things walking around the
1:05:31 house. You get a little nasty to chat
1:05:33 GPT. Maybe the robot walks into the
1:05:35 room, slaps you upside the head, and
1:05:38 says, "Hey, you might want to cool it
1:05:39 down on chat GPT there. That's my
1:05:41 girlfriend. [laughter]
1:05:51 Uh, I was under the impression that
1:05:52 Rosie the robot would be handling it
1:05:55 all. So disappointed. I know. Did you
1:05:57 see that? Did you see that robot that's
1:05:59 walking with like her her hips swinging
1:06:01 like a little a little sassy vamp? Wait,
1:06:04 let me see if I can go find her. Um,
1:06:06 let's see. Natural
1:06:08 robot walk. This thing was funny.
1:06:13 Um,
1:06:16 is that her?
1:06:22 Let's see if I can find it.
1:06:29 It was in Japan. Share screen.
1:06:40 Natural robot Japan.
1:06:57 Is that it?
1:06:59 Yeah. Is that the one?
1:07:09 No, that one's a little stiff. Well,
1:07:10 that one's in the neighborhood. But
1:07:12 there were I saw one walking. It was
1:07:14 just like your hips were like, but
1:07:16 [laughter] I I just remember being in
1:07:18 New York like women that walked like
1:07:20 that. Like all the construction workers
1:07:21 would always cat call them. Woo.
1:07:24 [laughter]
1:07:27 Uh, you still fries with those shakes?
1:07:30 Oh, yeah.
1:07:33 [laughter]
1:07:35 There. Is that it? Yeah, I think that's
1:07:38 it.
1:07:40 Yeah. See that?
1:07:45 So,
1:07:48 yeah, it's going to it's going to get
1:07:49 surreal. Like I like I don't think it's
1:07:53 I don't think we know. I don't think we
1:07:57 know.
1:07:59 Crazy, crazy, crazy. All right.
1:08:05 I won't buy a robot with clothes.
1:08:07 Closing a robot is creepy. Well, you
1:08:09 know what, Robbie? I'll tell you what. I
1:08:11 said this 18 months ago.
1:08:15 I think
1:08:18 anyone who's into fashion right now
1:08:22 should be well anyone who's into fashion
1:08:25 right now and is into technology should
1:08:28 be studying material science right now.
1:08:32 I think there's there could be a massive
1:08:35 business in doing high-end fashion for
1:08:38 robots.
1:08:40 Um massive like couture
1:08:44 Couture robot fashion.
1:08:47 [laughter]
1:08:49 Oh, pop that collar. Oops. Oh, yeah.
1:08:51 Look at that. Thank you. Speaking of
1:08:54 fashion. Hey, Kyle, if you could not
1:08:56 look like you just rolled out of a
1:08:58 sleeping bag, that would be awesome.
1:09:01 [laughter]
1:09:02 And Black Bar. I know.
1:09:06 Styling for bots. Kelly Bosch. Yeah.
1:09:09 Take Yeah. No [ __ ] Kelly Bosch. take
1:09:12 Kelly Bosch's designs
1:09:14 and then figure out what what materials
1:09:18 do do you need to use that won't get
1:09:20 dirty. You can just spray them down with
1:09:22 a hose like won't bunch up when they
1:09:25 have weird, you know, if the if the
1:09:27 robots don't have muscles, you know,
1:09:30 building in things that fill in gaps,
1:09:34 right? Structured engineered clothing
1:09:37 that is high fashion.
1:09:41 You don't think there's gonna be some
1:09:42 Beverly Hills
1:09:44 wife that's like out with a robot, you
1:09:48 know, with with a with the the [ __ ]
1:09:51 Gucci the Gucci stuff on. I promise you.
1:09:56 [laughter] I promise you that's going to
1:09:58 happen.
1:10:02 Light limited tubes. Yeah, exactly. LED
1:10:04 stuff. Doesn't matter. I'm so
1:10:07 fashionable. Oh, I'm I'm not fashionable
1:10:09 at all. But hey, robot fashion week in
1:10:12 Paris. Yeah.
1:10:16 And why have it be Paris? Why not
1:10:20 like let's not have it be San Francisco?
1:10:22 Why not have New York be the fashion
1:10:25 capital
1:10:26 of robots or Chicago or Austin?
1:10:31 Probably not going to be Cleveland.
1:10:34 [laughter]
1:10:37 You got the Rock and Roll Hall of Fame.
1:10:39 How did you [ __ ] score that? How did
1:10:42 Cleveland score that one? Huh? That's
1:10:44 crazy.
1:10:49 H.
1:10:52 Huh. Have a style AI that you can collab
1:10:55 with. Actually, that was another thing I
1:10:57 saw today.
1:10:59 Um, hang on.
1:11:01 Um, vibe
1:11:04 fashion design
1:11:17 vibe coding
1:11:20 fashion design
1:11:26 DJ Alan Freed who popularized the term
1:11:29 rock and roll. Oh, cool. Was from
1:11:31 Cleveland. Oh, that's cool. That
1:11:33 actually makes sense then.
1:11:35 Um Um
1:11:39 third place
1:11:44 from sketch to couture in moments. Yeah,
1:11:46 this one. Check this out.
1:11:54 So, there's a fashion sketch.
1:12:01 This was this was a vibe coding contest.
1:12:06 And then it goes from sketch to
1:12:09 technical sketch.
1:12:14 And then there's your motion studies.
1:12:18 So that's all that's probably just a
1:12:20 nano banana app, right?
1:12:23 But she built this site. I think she got
1:12:25 third place in this vibe coding thing.
1:12:30 Like how cool is that?
1:12:39 And and you know, we go from being able
1:12:41 to vibe code this concept thing to being
1:12:45 able to
1:12:47 put out full-on technical drawings,
1:12:49 full-on patterns, and then have your
1:12:53 robot make you the [ __ ] dress.
1:12:57 Right. Source the material. Say, "Okay,
1:13:00 based on the way that flows and based on
1:13:01 how you've described it, I'm going to go
1:13:04 order you. I'm going to go order you the
1:13:06 fabric. It's going to be here tomorrow
1:13:09 and I'll have you the dress by the
1:13:11 weekend.
1:13:15 everyone can design their own couture
1:13:18 [laughter]
1:13:21 and like we're [ __ ] around with like
1:13:23 NAN automations.
1:13:26 I just I just I just get this sense
1:13:29 where we're so underestimating what
1:13:33 happens when
1:13:36 when the promise of multimodal
1:13:40 actually starts to get realized. Because
1:13:42 right now they're all still these
1:13:44 discreet. We're we're all trapped in
1:13:47 what we know. We're all trapped in.
1:13:49 Okay, I'm a fashion designer. And so
1:13:52 this is what fashion looks like and I'm
1:13:54 a you know, I'm a print maker and right?
1:13:58 We all have these ideas
1:14:02 that we think we know who we are and
1:14:05 what we like
1:14:07 and how we're going to use AI to do our
1:14:10 thing. But like our thing
1:14:14 is just going to be different.
1:14:17 We're going to be able to do [ __ ] we
1:14:18 can't imag. But you know,
1:14:22 again, this goes back to why having a
1:14:24 daily practice is so [ __ ] important.
1:14:45 Maybe here's the skill. Maybe here's the
1:14:47 skill.
1:14:50 Those people
1:14:54 that can most quickly get an idea.
1:15:06 I don't know. Out of their head.
1:15:13 And not just an idea, it's more than an
1:15:15 idea.
1:15:17 It's like a vision. It's like, okay, we
1:15:19 all have ideas, but like this is this is
1:15:22 a good example. This site right here is
1:15:24 a good example where, okay,
1:15:27 I could do something cool for fashion.
1:15:29 Well, okay, what could you Well, I could
1:15:31 I could someone could describe a dress
1:15:33 and I could make something in nano
1:15:34 banana. Okay, great. That's that's a
1:15:37 level. And this person was like from
1:15:39 sketch to couture in moments. Sketch to
1:15:42 couture, right? And so where this is
1:15:46 right now is it's up to the point where
1:15:48 the technology is. So and like like Jim
1:15:52 Ross's kid with his friend,
1:15:55 they're like, "Oh, we wanted to do this
1:15:57 thing and so we went to this and learned
1:15:59 how to do that. We went to this and
1:16:00 built a website and then we did this and
1:16:03 put together a PowerPoint presentation.
1:16:05 like it's that it's that chain of
1:16:08 understanding all of the things you need
1:16:12 to live into that vision. So, so I think
1:16:15 that starts to become
1:16:18 the skill.
1:16:20 Oh, here's a cool idea. And then imagine
1:16:22 all of the things that that could be.
1:16:25 And the people that are the most nimble
1:16:27 with that, that are able to just go
1:16:29 idea, six different executions, six
1:16:32 different components, go execute that
1:16:35 and then look at what you've built and
1:16:37 then go, is that good? Yeah, maybe. And
1:16:39 then go over here and modify it and do a
1:16:42 whole other thing.
1:16:45 Those are going to be the superstars.
1:16:47 Those are going to be the Rick Rubins.
1:16:54 And if you all get your ass in the
1:16:56 mastermind lab and start building your
1:16:58 daily practices, we can all start to
1:17:01 level up our games. This is we're we're
1:17:04 going to a place where the technology
1:17:06 really won't matter. It really won't
1:17:07 [ __ ] matter because it's all going to
1:17:08 be so good. Hopefully. Yeah, I know. I
1:17:12 know. That's that's kind of where like I
1:17:15 Okay, I want to be clear about
1:17:16 something. I recognize that what I just
1:17:19 said, like this whole rant that I've
1:17:20 been on for the past 45 minutes or so,
1:17:25 makes me sound like I'm [ __ ] insane.
1:17:27 I get that.
1:17:30 I get that. But the the the more
1:17:34 I integrate, this is something that Andy
1:17:36 said to me, she goes, "You're
1:17:37 integrating. You're integrating. I'm
1:17:39 taking these ideas of this idea of a
1:17:41 daily practice and
1:17:44 my inability
1:17:47 and all of our inability to keep up with
1:17:50 the tech. We can't keep up with the
1:17:52 tech.
1:17:53 So, we can no longer we can no longer
1:17:56 kind of know what AI is because AI is
1:17:58 going to be everywhere. So, that would
1:17:59 be like knowing everything in the world
1:18:01 and we can't. Our brains are just not
1:18:02 there. So, then that means we have to
1:18:05 choose.
1:18:06 And if we have to choose, then it begs
1:18:09 the question, what are you going to
1:18:11 choose? And I don't think a lot of
1:18:12 people are are are
1:18:15 in the habit in the practice of asking
1:18:18 themsel that question.
1:18:23 Takes a lot of work.
1:18:28 Takes a lot of intention.
1:18:34 Anyway,
1:18:37 we'll see. We'll see. Kelly Camp, it's
1:18:39 all still about execution. I agree with
1:18:41 that. And execution execution's going to
1:18:44 remain hard.
1:18:46 90% of the people will never get that
1:18:48 far. Uh well, so here's here's what kind
1:18:52 of shifts, Kelly. I think the
1:18:54 percentages stay exactly the same as
1:18:56 they are right now, right? Like in
1:18:58 Hollywood,
1:18:59 you've got 20 people that are your
1:19:04 A-list stars, right? And then you have
1:19:06 200 that are B and you've got 2,000 that
1:19:09 are C and you got 200,000 that are Oh
1:19:12 yeah, I saw him once, right? And then
1:19:15 you just have a bunch of people trying
1:19:16 to make I think the percentages in every
1:19:18 discipline stay the same.
1:19:22 But I think it I think what gets
1:19:24 shuffled is who's allowed in the game.
1:19:30 I think the centers of power are going
1:19:31 to shift dramatically.
1:19:35 and they will stabilize. Like what's
1:19:37 going to happen is whatever Hollywood
1:19:39 becomes, whatever the AI powered
1:19:41 Hollywood is, whether it's in California
1:19:43 or I don't know, Cleveland, whatever
1:19:47 becomes the center of power for for all
1:19:50 of the disciplines is probably going to
1:19:51 shift around a bit. And who are the
1:19:53 power players are going to shift around,
1:19:55 but who gets to play in those in those
1:19:57 new centers of power, I think, is
1:20:00 totally up for grabs.
1:20:02 And I think now is the time that we need
1:20:06 to get
1:20:09 clear on who we are and what we bring to
1:20:13 the party because if everyone's bringing
1:20:16 talent and skills to the party or no
1:20:18 skills to the party, right? AI is going
1:20:21 to provide skills for everyone. If
1:20:23 everyone's coming to the party armed for
1:20:25 bear, right? And everyone can do all the
1:20:28 stuff. They can do the coding and they
1:20:30 can do the drawing and they can do the
1:20:31 music and they can do the writing and
1:20:32 they can do the business plan. They can
1:20:33 do the math. Everyone does that. Who
1:20:36 rises above?
1:20:39 Those people that have weirdass new
1:20:41 ideas.
1:20:43 How do you find those? You get in touch
1:20:45 with who you are and the difference you
1:20:46 want to make in the world. That's it.
1:20:48 All right. That's been my focus lately.
1:20:51 Think bigger. Think different. Yeah.
1:20:52 Shane saw. And I think it's
1:20:55 um we we've got the the one value called
1:20:58 create excellence. What what popped in
1:21:00 my head today was create great. I'm
1:21:03 almost I'm I'm almost wondering if
1:21:05 create excellence needs to be create
1:21:07 great. Like what is great?
1:21:12 You know what do we we we have Wait, we
1:21:14 better have fun while we can.
1:21:17 Listen, I think that this future that
1:21:19 I'm talking about is going to be a
1:21:20 [ __ ] blast.
1:21:23 I mean, we are like I I say this all the
1:21:25 time. We're entering the Great
1:21:26 Renaissance. I think
1:21:29 I can't even imagine
1:21:32 what it's going to be like, but we get a
1:21:35 taste of it every day today. Hang on a
1:21:36 sec.
1:21:40 Um,
1:21:45 imagine living in a frictionless world.
1:21:49 And by frictionless, I mean like you
1:21:52 have a concept and then it's effectively
1:21:56 instantly manifested.
1:21:58 So like you could spin up a business and
1:22:01 try it, you know, over a weekend and not
1:22:04 like we do today. Like how we're doing
1:22:06 it today. Like I kind of feel like AI
1:22:09 today is like
1:22:13 um
1:22:17 AI today is you're you're like um I'm
1:22:20 thinking about starting a business and
1:22:23 then AI is like oh here's a 50page plan
1:22:26 you're never going to read and you're
1:22:28 like cool I'm not going to read that.
1:22:33 It's almost like like AI AI in 2025 is
1:22:38 like the world's worst homework giver.
1:22:41 It's like the world's most ambitious
1:22:43 teacher that's like, "Hey, hey, Skippy,
1:22:46 great idea about the business there. Oh,
1:22:48 if you want to do that, here's the 74
1:22:50 [ __ ] things you've got to go figure
1:22:52 out." And you're like, "Oh god, uh, I
1:22:54 guess I could use AI to figure those out
1:22:56 and then you go try to use AI to figure
1:22:58 those out and three of them are awesome
1:22:59 and 70
1:23:02 one of them suck and you're like this is
1:23:05 a lot of work I'm t I'm going to go take
1:23:07 a nap
1:23:10 I'm a little sleepy
1:23:12 right
1:23:14 we we we have shitty teachers right now
1:23:17 they're just giving us too much homework
1:23:21 but like just play act it out three
1:23:23 years from now assume all this [ __ ] gets
1:23:25 better.
1:23:27 Assume it can think longer. Assume it
1:23:29 can anticipate what you need. Assume it
1:23:30 remembers all the shitty ideas you had
1:23:33 before and it actually recognizes. Oh,
1:23:36 Kyle, this is a good one. Let's run with
1:23:39 this one. Okay, cool. What do we need to
1:23:42 do? I got you, buddy. I'll see you
1:23:45 Friday.
1:23:46 We'll be up and running. I'll see you
1:23:48 Friday. And off it goes. [laughter]
1:23:53 What are you going to tell your robot to
1:23:54 go do
1:23:57 joining late? What is this witchcraft?
1:23:59 Oh, the witchcraft on on on screen right
1:24:02 now is um a woman joined basically a
1:24:05 hackathon, a vibe coding hackathon and
1:24:08 she won third place with this sketch to
1:24:10 couture. It's a it's an app where you
1:24:14 just upload a sketch and then it turns
1:24:16 into drawings, technical drawings and
1:24:18 photos and then videos.
1:24:21 And then we were talking about you know
1:24:22 the natural extension of this is
1:24:26 it creates technical patterns
1:24:29 identifies what fabric is is correct
1:24:32 right orders the fabric
1:24:36 I'm just learning what's your what's
1:24:39 your group about daily practice um hey
1:24:41 frankly Q so the the group is called the
1:24:44 AI salon and the AI salon is a community
1:24:47 that I created is tightly tightly
1:24:49 associated with this the AI learning
1:24:51 lab. This is where we kind of hang out
1:24:52 and experiment and talk about stuff. If
1:24:56 you go to the salon.ai
1:24:59 um or community salon.ai will take you
1:25:02 straight to the community. You can join
1:25:04 for free. Um there's all sorts of spaces
1:25:07 and and and groups in there. I would
1:25:09 strongly encourage you to introduce
1:25:11 yourself.
1:25:13 Um, but starting this Thursday, we're
1:25:17 we're kicking off what we're calling the
1:25:19 AI Salon Mastermind Practice Lab, and it
1:25:23 is a weekly session for people that are
1:25:26 members of the mastermind, which is 20
1:25:27 bucks a month. That's going up January
1:25:30 1st. Um, if you get it now, you have
1:25:33 that price forever. So, like 20 bucks a
1:25:35 month is is funny. And And Andy um who
1:25:38 who's the the new community manager and
1:25:41 the uh and the integrator for the salon,
1:25:44 she's like 20 bucks? Like you can't even
1:25:46 get a pizza for that. [laughter]
1:25:49 She's like, "What are people bitching
1:25:51 about?" Um
1:25:54 but if you're a member of the
1:25:55 mastermind, we're kicking off this
1:25:56 practice lab. And the basic idea is
1:25:58 this. What what it's taken me about I
1:26:02 mean if if you're an irregular and
1:26:04 you've been here for the past year and a
1:26:05 half I have been in some sort of
1:26:07 weirdass
1:26:10 quandry for for 18 months
1:26:14 because it became clear to me about 18
1:26:17 months ago that talking about the tools
1:26:21 while important and interesting on some
1:26:24 level
1:26:26 is not sustainable. And and to a great
1:26:29 degree is not interesting because the
1:26:32 tools are getting so powerful
1:26:36 that at some point in the near future,
1:26:39 two maybe three, maybe 5 years,
1:26:42 we're literally just going to be able to
1:26:44 have a thought and and [ __ ] will happen.
1:26:47 So if you're feeling very behind, you're
1:26:50 not. you're not because all of us even
1:26:53 though we may have skills that you don't
1:26:54 right now, um the tools are getting
1:26:57 better faster and being in community and
1:27:00 and like showing up to these lives on a
1:27:02 regular basis and being in community and
1:27:05 asking questions and showing off things
1:27:07 you've made and and answering people's
1:27:09 questions and asking people questions,
1:27:12 you will you will level up in a huge
1:27:15 way. But where I've gotten on the other
1:27:18 side of it's the tools are somewhat
1:27:21 irrelevant. They're important but
1:27:22 irrelevant
1:27:24 is an extension of this thing that we
1:27:26 have in the in the AI salon. Let me show
1:27:28 it to you called the the cycle of AI
1:27:32 readiness. And this was something that
1:27:34 came from Liz Miller Gersfeld who's my
1:27:37 co-host in the salon.
1:27:41 Um,
1:27:43 so, oh, am I not sharing? Yeah, there we
1:27:45 go. So, there's the cycle of AI
1:27:47 readiness. And the cycle of AI readiness
1:27:49 is play first.
1:27:51 And I literally mean play.
1:27:54 Like if if if
1:27:57 what you
1:28:00 um what's your name? Frankly Q. Good
1:28:03 name. Uh 8.9 out of 10. I like it. Um,
1:28:08 if what you're telling yourself right
1:28:09 now is, "I have to learn AI.
1:28:13 AI is very important and I've been told
1:28:15 I have to learn it. I'm going to be
1:28:17 displaced and I have to learn AI."
1:28:22 First of all, that's [ __ ] exhausting,
1:28:25 right?
1:28:27 Because
1:28:29 AI is moving so fast right now that
1:28:31 learning AI is actually not a thing.
1:28:34 Like what I would say is pick a tool
1:28:37 like probably just pick chat GPT and
1:28:40 just like get just immerse yourself in
1:28:43 in a tool if you're going to learn
1:28:44 something just pick one of the big ones
1:28:46 that you've heard of and just start
1:28:48 playing in it. But then what I would
1:28:50 also say is just play. Don't think like
1:28:53 I've got to learn a thing to build the
1:28:56 thing that is my craft. like you know
1:28:58 I'm a writer and I'm going to learn how
1:28:59 to write with a like it's putting a lot
1:29:02 of pressure on yourself to I don't know
1:29:06 to replicate what you currently do. So,
1:29:10 one of the things we talk about is
1:29:12 explore your gaps. As human beings, we
1:29:15 have gaps, right? There's things we do
1:29:16 well. There's things we do not well.
1:29:19 Some of those things we do not well are
1:29:21 what I call aching gaps.
1:29:24 There are those gaps that you're like, I
1:29:26 really want to be a director, but I
1:29:28 don't know anything about film making. I
1:29:30 really want to be an illustrator, but
1:29:32 I'm just kind of not talented, or I
1:29:34 didn't go to art school. You know what?
1:29:36 Conceptually, I love math, but I don't
1:29:40 understand it. Like, like there's, you
1:29:43 know, there's a bunch of those things
1:29:45 that you've got. Well, play is you can
1:29:49 actually go play with these tools and
1:29:51 maybe fill in some of those gaps and see
1:29:53 what's possible. So, what happens in
1:29:56 play is you're learning the tools, but
1:29:57 you're also learning what's possible for
1:30:00 you. Like, what are you passionate
1:30:02 about? What are those things? And
1:30:04 sometimes those aching gaps are hidden,
1:30:07 right? Sometimes those aching gaps are
1:30:09 things that happened to you in your
1:30:10 childhood where you had a dream and
1:30:13 someone squashed it or you let yourself
1:30:16 squash it cuz someone made a comment.
1:30:19 Oh, I I remember when I had when I was
1:30:23 when I would draw is um Oh, you drew
1:30:26 outside the lines.
1:30:30 And then I would I would try to draw
1:30:31 inside the line. And the minute I went
1:30:33 outside the line, I would crumple up the
1:30:34 piece of paper and throw it away, right?
1:30:36 That that killed something in me, right,
1:30:40 that I've probably spent my the rest of
1:30:42 my life trying to achieve and knowing
1:30:44 deep down, but you're really not that
1:30:46 talented, right? We've all got those. So
1:30:50 that's what play about. Then create
1:30:52 excellence or create great is
1:30:57 take what you've learned and now like
1:31:00 take something that you want to do and
1:31:02 right and then generously lead is be in
1:31:05 community. Share what you're learning.
1:31:07 Share what you're doing. Where do you
1:31:08 share it? Well share it at the AI salon
1:31:10 but also share it on Facebook. Share it
1:31:12 on LinkedIn. Share it on Twitter. Share
1:31:14 it at the stupid [ __ ] dinner party
1:31:16 that you have to go to. Oh my god, I
1:31:18 don't want to go.
1:31:20 and your spouse is like, "Hey, listen,
1:31:22 dear. Um, could you not talk about AI at
1:31:26 dinner tonight?" [ __ ] talk about AI
1:31:29 dinner.
1:31:32 Just be in the conversation and then I'm
1:31:35 going to get to the practice in a
1:31:37 second. Wait, what was that? Is free
1:31:38 chat GPT something? What was the
1:31:40 question? Harry Chapen, no need to see
1:31:43 flowers. Wait, the the pinned the pinned
1:31:46 comments are coming and going too fast
1:31:47 for me to read. Is free chat cheap is
1:31:50 free chat GPT I have memory I've always
1:31:53 had to pay
1:31:55 but I don't know now
1:32:00 free chat GPT I'm pretty sure it has
1:32:03 memory yes is is remarkably powerful
1:32:06 like I don't think you have to pay for
1:32:08 chat GPT personally I think you can I
1:32:12 don't think you have to
1:32:14 just the free version is like you could
1:32:17 spend a decade Try trying to learn free
1:32:19 chat GPT right now if it never changed
1:32:21 again.
1:32:23 Um,
1:32:26 wait. What I would do to be a youngster
1:32:28 again? Oh my god. I can't being a kid
1:32:31 right now. Like Brandon's kids
1:32:35 Brandon's kids are so lucky to have him
1:32:38 as a father because he's like as he's
1:32:40 learning this AI. He's I think his kids
1:32:42 your kids are four and six, right
1:32:44 Brandon?
1:32:51 Oh, four and eight. Okay, four and
1:32:53 eight. And as they have ideas, he's
1:32:57 like, "Oh, that could be a song. Hey,
1:32:59 come on over. Let's make you a song.
1:33:01 Let's make you a book. Let's take the
1:33:03 game you invented on the beach and vibe
1:33:05 code it when we get home so you can keep
1:33:07 playing that game on the computer."
1:33:11 like he is modeling for them
1:33:14 that that they're entering a world where
1:33:16 they can just invent [ __ ] Holy [ __ ]
1:33:19 Okay.
1:33:21 So that's what the cycle of AI readiness
1:33:23 is. So the practice that the AI salon
1:33:26 mastermind practice is a is a is a nine
1:33:29 segment framework that we've developed
1:33:32 that we're going to roll out over it's
1:33:35 it looks like it's going to be a 12-week
1:33:36 course. So or not a course a 12-week
1:33:39 cycle. You can join at any time, but
1:33:42 that 12-week cycle is going to start
1:33:43 with a kickoff. Then we're going to talk
1:33:45 about like who are you? What are your
1:33:47 values? Then we're going to get into
1:33:49 play like like how do you learn? How do
1:33:51 you play? How do you play with intention
1:33:53 based on who you are and what your
1:33:55 values are and what you want to achieve
1:33:56 in the world? What does that play look
1:33:58 like? And then how do we start building
1:34:00 stuff and how do we professionalize what
1:34:02 we do? And then the the leadership part
1:34:04 is how do we do that in community and
1:34:06 share it? And so that daily practice is
1:34:08 going to be something that we develop
1:34:10 over these 12week cycles. So if you're
1:34:13 not a part of the mastermind, now's the
1:34:15 [ __ ] time to get in because we kick
1:34:16 the first one of these off Thursday.
1:34:19 This Thursday at noon Eastern,
1:34:22 9:00 a.m. Pacific. All right. It's going
1:34:24 to be so cool. All right.
1:34:29 So to put it in AI in a group is
1:34:32 awesome. Yeah. It's like
1:34:39 So, a little bit about my background,
1:34:42 which the irregular is like, "Oh god, is
1:34:44 he going to say the web thing again?" I
1:34:46 am. [laughter] So, so I was there for
1:34:49 the early days of the web and and I
1:34:50 created a similar group to the AI salon
1:34:53 in New York City called the Worldwide
1:34:55 Web Artist Consortium. And so, I had
1:34:57 started an online magazine. I started a
1:35:00 digital agency. And then I started this
1:35:02 group. And the reason I started the
1:35:04 group is I kept asking people, how do
1:35:08 you do this web thing? Like what's this
1:35:10 HTML? How do you do this? And they're
1:35:11 like, you know, I was wondering the same
1:35:14 thing. [laughter] And then we go talk to
1:35:17 someone else. Hey, you seem pretty smart
1:35:19 about this. Oh, no. I don't I just
1:35:21 learned how to I can make a thing
1:35:23 wiggle. You're like, how do you make a
1:35:25 thing wiggle? Oh, you just put this in
1:35:27 here and you put a zero here and a one
1:35:29 here, and then you copy and paste those
1:35:31 a bunch of times. Oh, that's cool,
1:35:33 right? Like we invented, you know, web
1:35:36 animation and we invented all sorts of
1:35:38 [ __ ] Why? Because nobody knew what they
1:35:40 were doing.
1:35:42 And so I've been in this movie before,
1:35:45 but the the remarkable thing about AI is
1:35:49 is it's just the level of capability
1:35:52 that it's giving us is
1:35:57 it's profound. It is [ __ ] massive and
1:36:00 profound. And
1:36:03 you know, it's funny.
1:36:06 There's a lot of people there's a lot of
1:36:08 people that really hate on AI. And
1:36:09 there's a lot of people that justifiably
1:36:11 say, you know, people that are just like
1:36:14 polyianish about AI. Oh, it's just
1:36:16 they're just the optimist. You know,
1:36:18 they're just pull, you know, they're
1:36:19 just pretending the bad stuff isn't
1:36:20 there. I know the bad stuff's there. I
1:36:24 know how these things were trained
1:36:25 unethically. Sucks. I know that there's
1:36:27 bias in the models and that sucks. I
1:36:30 know that like there's all these
1:36:31 imperfections to it.
1:36:35 But what I but what I know
1:36:39 like the only thing that I really know I
1:36:42 know this
1:36:44 is that AI is not going away.
1:36:48 And then if it's not going away,
1:36:51 you got two choices.
1:36:55 Two. It's binary. It's literally binary.
1:36:59 You deal with it or you don't.
1:37:03 That's the choice.
1:37:06 And if you're going to deal with it,
1:37:08 then [ __ ] lean in and learn
1:37:10 everything you can about it and learn
1:37:12 what it makes possible and learn what it
1:37:14 does well and learn what it doesn't do
1:37:15 well and learn what the shitty ethics
1:37:17 are because maybe you can do something
1:37:20 to make a difference for them if you're
1:37:21 actually in the conversation.
1:37:24 those people that choose not to deal
1:37:26 with it, AI is going to happen to them
1:37:31 and it's gonna [ __ ] suck.
1:37:34 And like I don't know, there's something
1:37:36 like in my soul. It happened in 1994
1:37:39 and it's happening right now. I can't
1:37:42 There's something in me that's like, you
1:37:45 got to talk about this stuff. You got to
1:37:47 play. You got to get in here. You got to
1:37:50 sort of lighten the conversation and
1:37:53 just get people playing. So anyway,
1:37:57 so the the the mastermind practice is
1:38:00 about
1:38:04 understanding who you are as a human,
1:38:06 what your values are, what you want to
1:38:08 do in the world, which I don't think a
1:38:09 lot of people spend a lot of time doing
1:38:11 that anyway. So I think there's just
1:38:13 something valuable in that.
1:38:16 And then it's putting some rigor around
1:38:19 how you learn, how you explore, how
1:38:21 you're curious, how you're adaptable,
1:38:24 how you
1:38:26 establish and hold a vision. Um Liz
1:38:30 Miller Gersfeld um talks about her
1:38:34 commitment to the fidelity of the idea.
1:38:37 I [ __ ] love that phrase. She's like,
1:38:40 "Okay, I got hired to do this job. They
1:38:42 gave me the creative brief. I understand
1:38:44 the creative brief, so I've got the this
1:38:46 idea in my head of what it needs to be.
1:38:49 And then she's working with AI,
1:38:52 but she doesn't care what tool she uses.
1:38:55 What she's got in her head is not tools.
1:38:58 She's got the idea. And it's her job to
1:39:01 live into the fidelity of the idea to
1:39:05 make sure that that everything that
1:39:06 she's creating is serving that idea.
1:39:11 Those
1:39:13 are going to be the people that do the
1:39:15 remarkable work, that take things to the
1:39:17 next level, that rise above the noise.
1:39:19 If everyone can do everything,
1:39:22 then the [ __ ] that gets produced is
1:39:24 going to be better, but it's just going
1:39:26 to be the it's just going to be the the
1:39:28 new bottom is just higher and that's
1:39:30 still the bottom.
1:39:32 And the [ __ ] that rises above the noise
1:39:35 is going to be humanled.
1:39:38 And so that's what the practice is all
1:39:39 about. So, join the mastermind. If you
1:39:42 go into the AI salon right now, you can
1:39:45 go into um the community feed. It's one
1:39:48 of the top spaces. And I did a big post
1:39:51 today about the mastermind and you can
1:39:53 click on the link. We take you straight
1:39:55 into the to the event calendar where if
1:39:58 you're a member of the mastermind, you
1:40:00 just RSVP for it. And if you're not,
1:40:04 when you click on that link, it'll take
1:40:05 you to a page that tells you all about
1:40:07 the mastermind, what that framework is,
1:40:09 and what we're going to be doing over
1:40:11 the the 12week cycle. Um, and you can
1:40:14 sign up. All right.
1:40:28 Time is I had a feeling it was late.
1:40:30 I've been yapping a lot. Huh? [laughter]
1:40:35 Any questions, thoughts? That was a That
1:40:37 was a big rant. It was meltdown Monday.
1:40:39 It was good. I'm in the mastermind. Um
1:40:44 I need to hurt over there. Yeah. So,
1:40:46 definitely. So, so if you've been in the
1:40:48 mastermind and you've come to any of our
1:40:50 mastermind founder hangouts, they were
1:40:53 cool,
1:40:54 but they were just hangouts. and and
1:40:56 we're putting some intentionality behind
1:40:58 the the the practice lab is not going to
1:41:00 just be a hangout. It's going to be a
1:41:02 very intentional space.
1:41:05 I think it's important for us as a
1:41:07 community and particularly
1:41:10 this community where you know I bring a
1:41:13 lot of irreverence to this and a lot of
1:41:15 like G-Shocks you know G-Shocks none of
1:41:17 us are an expert things like that.
1:41:22 What we can be expert at is knowing what
1:41:25 we want to create in the world and and
1:41:27 at what level
1:41:29 that we can be expert at. And that's
1:41:31 that's going to take
1:41:34 work, a daily practice, like an
1:41:36 intentional daily practice. Who do you
1:41:38 want to be? What level of work do you
1:41:41 want to do? If you just want to hang out
1:41:43 in the sil sidelines and dick around,
1:41:47 I totally respect that. I think
1:41:51 relatively quickly we're going to get to
1:41:53 the place where
1:41:56 choosing to make a difference and do
1:41:58 something big will be completely
1:42:00 optional. Choosing to work will be
1:42:03 optional. Now that might be 5 years out.
1:42:05 It might be 10 years out. But like
1:42:07 that's where we're headed.
1:42:10 But those people that choose right now
1:42:12 to go, you know what,
1:42:16 the the reason we call the the the cycle
1:42:18 AI readiness and not AI literacy, AI
1:42:21 literacy kind of implies that you can
1:42:23 learn the tools well enough to be
1:42:24 excellent at AI. You can't, but you can
1:42:28 be ready for it and you can be in a
1:42:29 daily practice and you can be so good at
1:42:32 AI
1:42:34 that it just becomes like breathing
1:42:36 where you're like, I've got an idea. You
1:42:38 can you can it's a much more relaxing
1:42:40 kind of way to be. So in the olden timey
1:42:43 days in this channel the way to be was
1:42:46 we got to figure out the tool. What's
1:42:47 the next tool? What's the next tool?
1:42:48 What's the next tool? And we've still
1:42:49 got some vest vest vest vestage
1:42:52 vestigual.
1:42:54 I think behaviors like that like I
1:42:57 sometimes I'll see a new tool I get
1:42:58 excited and I'll just come in and talk
1:43:00 about the tool. That's fine. Like part
1:43:01 of play is exploring what's possible.
1:43:07 But we got to step up the game. And
1:43:10 stepping up the game isn't about getting
1:43:12 better at vibe coding. It isn't about
1:43:15 getting better at like getting better at
1:43:18 the tools is just part of the practice.
1:43:21 The thing that will make the difference
1:43:23 is you. That's what this is all about.
1:43:26 All right. How can we make editing AI
1:43:29 generative work less messy? I want to
1:43:32 design by voice. um
1:43:37 that can ship. So, SXS
1:43:40 um
1:43:44 the smartass but actual real answer to
1:43:47 your question is just wait. [laughter]
1:43:54 Um, the tools right now are are [ __ ]
1:43:59 just maddeningly
1:44:02 they're they're tantalizingly
1:44:04 close to being useful,
1:44:07 right?
1:44:09 Every every [ __ ] one. Every [ __ ]
1:44:11 one from Chat GPT to Claude to
1:44:14 Midjourney to [ __ ] cling to all like
1:44:19 [ __ ] all of them to to lovable.
1:44:23 They're tantalizingly close
1:44:27 where when you first start working with
1:44:28 with AI tools, you're like, "Oh my god,
1:44:31 this is revvelatory. This is going to
1:44:32 change everything. I'm going to be able
1:44:34 to just speak an app into existence."
1:44:36 And then you do. And then you're like,
1:44:38 "Oh, but I I think I'd like that color
1:44:40 to be not purple. Could I could I make
1:44:43 it green?" And then you make that color
1:44:44 green and it [ __ ] up your app. You're
1:44:47 like, "Wait, I just how did I just
1:44:50 wanted that green? Why does it not work
1:44:52 anymore?
1:44:53 right? Like
1:44:56 it's not going to be like that for long.
1:44:58 But here's what I would argue
1:45:03 get in a daily practice of understanding
1:45:06 what you want first and like what you
1:45:09 want to do is you want to ship. Okay,
1:45:10 great. What does that look like to you?
1:45:12 What level of you know what level of
1:45:18 competence of the app does that actually
1:45:20 represent?
1:45:22 And then what you can do is once you
1:45:25 understand what you want, what your
1:45:27 level of excellence is, then you can
1:45:29 say, "Okay, with the current tools, I
1:45:31 can get to about 80% of that ideal." And
1:45:36 then if I work really hard, I can get to
1:45:37 like 90%. And I'm going to be [ __ ]
1:45:40 frustrated and pissed off at that last
1:45:42 10%. But you know what? Ship it anyway.
1:45:46 because 3 months from now something's
1:45:49 going to change where now you can get to
1:45:50 90% easily and you can push it to 95 and
1:45:54 like that's just going to keep getting
1:45:55 closer and closer and closer and at some
1:45:57 point your ideal is going to be here.
1:45:59 You're going to be able to speak
1:46:00 something in existence and it's going to
1:46:01 show up at or above your level
1:46:04 and you will know instantly
1:46:08 that the tech has just hit that level
1:46:12 because you're in the conversation. So
1:46:17 there could be answers in your current
1:46:20 tech stack of how you could get better
1:46:21 results, but like I wouldn't worry too
1:46:24 too much about that [ __ ] What I would
1:46:27 worry more about is what do you want?
1:46:29 Understand what that is and then learn
1:46:31 as much as you can about where we are
1:46:32 today and just let the let the tools
1:46:34 catch up because they will they're going
1:46:36 to catch up. 2026 is going to be
1:46:38 bonkers.
1:46:40 2026, I think we're going to start to
1:46:41 see
1:46:44 tools that that really deliver like on
1:46:47 the video tools. We're going to get
1:46:49 tools where the acting's really good.
1:46:52 It'll deliver
1:46:55 I don't know 60
1:46:57 second to three minute
1:47:00 multi-seene
1:47:01 complicated storytelling complicated
1:47:05 visuals consistent color grading like
1:47:10 that's probably 2026 and then for every
1:47:12 discipline
1:47:15 and then it'll it'll still be
1:47:17 tantalizingly close.
1:47:20 Um, but you know, 3 years from now it'll
1:47:23 be good. And then you'll be if you've
1:47:24 established yourself as someone who
1:47:26 gives a [ __ ] in your particular area of
1:47:29 passion, then you're you're going to
1:47:31 have massive opportunity. Tik Tok pin.
1:47:33 Frankly, Q. I'm looking to make
1:47:35 accessories and skill sets in MCP. Love
1:47:38 that. Uh, I have this wild idea on how
1:47:42 to use MCPs. Um, make clips for studios.
1:47:46 Easy to sell scripts. I I [ __ ] love
1:47:49 that. I I'm telling you what right right
1:47:51 now MCPs are incredibly powerful.
1:47:54 They're not something that I have built
1:47:55 anything on and I and I've I've never
1:47:58 even pursued demoing them here on the
1:48:02 live um
1:48:05 this Saturday.
1:48:08 Okay, if you're not a member of the AI
1:48:10 salon, this is this is for free. This is
1:48:12 not part of the mastermind. One of the
1:48:14 things we have in the AI salon that
1:48:16 Vicky Baptiste runs is a thing called
1:48:17 LOL's learn out louds, right? Our
1:48:20 generously lead value of the of the
1:48:22 cycle encourages our members to teach
1:48:27 teach what you're learning. This
1:48:29 Saturday, there's a guy named Brent
1:48:31 Peterson who's got a company called
1:48:33 Signal and Cipher. [ __ ] brilliant.
1:48:37 He's been building an agentic system for
1:48:40 the past, I don't know, two and a half
1:48:42 years.
1:48:44 That is bonkers. Like they've filed
1:48:46 patents for it. Like it's bonkers what
1:48:49 he's built. He's teaching this Saturday
1:48:52 for free how he uses NA NAND and MCPS to
1:48:57 do incredible workflows. So you should
1:49:00 go do that. Um it looks like genius in
1:49:03 here can teach frankly a few things.
1:49:05 Great. If you've got ideas for how to
1:49:08 make MCPs more available, more sexy,
1:49:12 more um more creative, more like what
1:49:15 what whatever it is, [ __ ] go for it.
1:49:19 Because if you think about what MCP is
1:49:22 right now,
1:49:24 it was an attempt by anthropic to
1:49:27 establish a protocol, right? And
1:49:30 protocols are really important, but
1:49:33 they're really hard to establish, right?
1:49:35 because everyone's got to agree to use
1:49:37 them.
1:49:39 Like HTML, okay, we all decided we're
1:49:41 going to use HTML. Great. Tim Berners
1:49:43 Lee and you know browser, everyone built
1:49:45 browsers around HTML. Like there could
1:49:47 have been HTML and XML and all that sort
1:49:50 of thing. Tim Berners Lee did HTML. It
1:49:53 got adopted as a protocol and it changed
1:49:56 the world, right? So establishing one of
1:49:58 those is rare and hard. And so what
1:50:01 Anthropic did is they said, "Here's this
1:50:02 protocol or this proposal for a
1:50:04 protocol. here's this thing we think is
1:50:06 pretty cool. Open AAI adopting that and
1:50:09 saying, "Yeah, that's cool enough that
1:50:11 we're going to support that, too, is a
1:50:13 big [ __ ] deal, but it's still at like
1:50:16 protocol level complexity. You've got to
1:50:18 be a [ __ ] engineer, right? What they
1:50:21 haven't done with MCPs yet is bubble
1:50:23 them up like ChatGpt did. ChatGPT made
1:50:28 large language models accessible to
1:50:30 human beings that don't have engineering
1:50:32 degrees, right? They got to 100 million
1:50:35 users in six weeks. Fastest adoption of
1:50:38 technology in history. Well, MCPs are
1:50:41 still bubbling down under the surface.
1:50:43 You have to be a [ __ ] nerd a to even
1:50:47 know what they are and and b to any and
1:50:50 to do anything interesting with them.
1:50:51 And then if you can have an idea that
1:50:53 that you're talking about and take them
1:50:55 to the next level where it makes them
1:50:56 accessible to a whole new um strata of
1:51:00 users.
1:51:03 [ __ ] the opportunity there is it's
1:51:06 insane. It's insane.
1:51:09 So [ __ ] go for that. [laughter] Yes.
1:51:12 And I think MCPS could do a lot more.
1:51:14 Remedial class. We'll go look up and ask
1:51:17 chat. Oh, remedial class on MCPS. Oh, if
1:51:20 you don't, so MCPs, so [clears throat]
1:51:23 there's a thing in programming called an
1:51:25 API.
1:51:27 And so if I've got a site, the the
1:51:29 simplest example I can use is Google
1:51:31 Maps. So Google launched a bunch of
1:51:34 satellites, mapped the whole [ __ ]
1:51:36 world, built a bunch of software, right?
1:51:40 So, if you've got an app and and you
1:51:42 want people to be able to use a map in
1:51:44 your app,
1:51:46 you could go launch a bunch of
1:51:48 satellites, map the Earth, come up with
1:51:50 a way to represent that visually, or you
1:51:53 could use the Google API application
1:51:56 programming inter interface, right? And
1:51:58 so they published this thing that's for
1:52:00 nerds to be able to go, okay, if if I
1:52:03 want to if I want to put a map inside my
1:52:05 application, I'm going to get an API key
1:52:07 and I'm going to I'm going to understand
1:52:09 what are the elements that I okay, I can
1:52:12 I can, you know, here's how I I send an
1:52:14 address in and then here's how um Google
1:52:18 Maps is going to do that and then
1:52:19 they're going to send me back a thing
1:52:20 and I've got to understand all those
1:52:22 hooks, all those what am I sending and
1:52:24 what am I receiving and what are the and
1:52:26 how much are how how much is it costing
1:52:28 me each time? So, the API is the thing
1:52:30 that lets your app like literally just
1:52:33 use
1:52:35 Google Maps.
1:52:37 MCPS are like a layer above that where
1:52:41 you don't have to actually write a um
1:52:45 like a software level um connection to
1:52:49 your app. You can just say, "Hey, here's
1:52:51 my website." And on my website, you can
1:52:53 buy [ __ ] and you can make pictures and
1:52:56 like like one of them is Blender. And
1:52:58 here's a bunch of [ __ ] you can do in
1:53:00 Blender. And with MCPs, you can just
1:53:01 kind of describe what your website does
1:53:06 and and you build what's called an MCP
1:53:08 server that basically says, okay,
1:53:11 using this protocol, all of my features
1:53:14 of my website, this understands. And if
1:53:17 chat GPT or Claude wants to do something
1:53:20 like Blender and you have an MCP server
1:53:23 for Blender, ChatGpt can basically just
1:53:26 go, "Hey, make me uh like a spinning
1:53:29 top, you know, in a crazy [snorts]
1:53:31 world, and the MCP will translate that
1:53:34 into what Blender does technically, and
1:53:38 then it'll spit you back your result."
1:53:40 It's it's super cool. Um, you don't have
1:53:43 to build and subscribe to to APIs. you
1:53:45 just as as people build these MCP
1:53:48 servers, you can literally just call
1:53:50 them, right? And so super cool server
1:53:54 offline online MCP
1:53:58 um
1:54:04 [clears throat]
1:54:08 beautiful.
1:54:10 Yeah, white labeling MCPs is pretty
1:54:12 brilliant. I think that's good. I really
1:54:15 appreciate you explaining it truly.
1:54:17 Yeah, it's it's a super cool thing. And
1:54:19 in fact, um the So, here I can show you
1:54:23 something. I know we're late, but that's
1:54:25 okay. Let me show you something because
1:54:27 I'm on a I'm on a roll. That's why I
1:54:29 have butter on my pants. Okay. Um
1:54:33 so, in
1:54:35 in chat GPT,
1:54:38 they just launched a thing.
1:54:43 Wait, what am I doing? Share screen.
1:54:46 There we go.
1:54:48 They just launched a thing called
1:54:50 applications. So, within chat GPT, now
1:54:53 there are I forget. There's like a dozen
1:54:55 right now. Um,
1:55:01 but I can just go um at Canva,
1:55:06 right? And see when I did at Canva, it
1:55:07 popped up the Canva logo. So, this is
1:55:10 using MCP protocols.
1:55:13 So, I'm in chat GPT and I can say um
1:55:18 based on
1:55:21 what you know about AI Festivus,
1:55:26 make me an invite.
1:55:32 Save the date
1:55:36 social media
1:55:39 um graphic.
1:55:42 I can
1:55:44 use whatever. It doesn't [ __ ] matter,
1:55:45 right? And so what this is going to do
1:55:48 now is it's it's doing its large
1:55:52 language model thing on what I asked
1:55:53 for. But see this window it just spun
1:55:55 up? See these multiple windows here?
1:55:58 These are actually
1:56:00 little windows, little HTML
1:56:03 um preview windows that Canva So, so
1:56:07 Canva is now off designing whatever chat
1:56:10 GPT sent it about. I don't know what it
1:56:13 knows about Festivus or what it
1:56:14 remembers, but it sends some [ __ ] over
1:56:16 to Canva. Canvas is now selecting some
1:56:19 templates because it they figured out
1:56:22 what were the things they were going to
1:56:24 do. And then there's AI festivist 2025.
1:56:27 And these are live Canva things that I
1:56:30 can say open in Canva. Right here it
1:56:33 says open in Canva. So this is a live
1:56:36 editable. It's a preview in chat GPT,
1:56:39 but this is live on um over in Canva.
1:56:45 And so are the other ones,
1:56:48 right? And it doesn't know anything
1:56:50 about Festiva. So, if I gave it, I could
1:56:52 upload graphics and say match these
1:56:54 colors. I could upload dates and times
1:56:57 and this is all just like like imagine
1:57:01 when this gets good, right? Right now,
1:57:04 it's kind of a a mess [laughter] and
1:57:07 it's janky and it's stupid, but again,
1:57:10 ain't going to be stupid for long.
1:57:13 Um, what is the most common protocol
1:57:15 agents used for um transactions? X49. I
1:57:19 I honestly don't know. Um, I do know
1:57:21 that um, Chat GPT cut a deal with who is
1:57:25 the transaction.
1:57:27 They're they're doing they're going to
1:57:29 be doing native transactions within Chat
1:57:30 GBT. I don't know what pro protocol
1:57:32 they're using
1:57:36 bro. You talk like me, janky. [laughter]
1:57:39 Embrace the jank, baby. Um, yeah.
1:57:42 [clears throat]
1:57:43 So, there you go. Yeah. And I can just
1:57:46 hop over to, if I click on that, now I'm
1:57:48 over in Canva.
1:57:50 Although it said forbidden for whatever
1:57:51 reason. So, all right. [clears throat]
1:57:54 Groovy. Groovy. G. Groovy. I'm thinking
1:57:58 transaction but deeper. What is native?
1:58:02 Oh, did I use the term native? Native
1:58:06 means. Okay.
1:58:11 So,
1:58:13 this this preview came from Canva and
1:58:17 and it
1:58:20 when you Okay, let me let me show you
1:58:22 something. Um,
1:58:25 when I say plus and I go into agent mode
1:58:27 and I say um
1:58:31 um let's see, go let's see uh
1:58:36 research
1:58:38 some
1:58:41 >> [clears throat]
1:58:41 >> um
1:58:43 I'm trying to do something that's not go
1:58:45 book me tickets on a plane.
1:58:48 Um research
1:58:51 research um bespoke this is good bespoke
1:58:55 candle makers
1:58:59 in Oregon
1:59:02 or California
1:59:06 if war
1:59:09 and find me um
1:59:17 pen with natural
1:59:21 ingredients
1:59:23 um
1:59:25 and fun animal
1:59:28 shapes.
1:59:31 So when I do this, you're going to watch
1:59:34 chat GPT now is going to
1:59:39 spin up this blue window.
1:59:42 So this is this is what's what's called
1:59:44 a container. I don't know if this is
1:59:46 technically a container, but it's like a
1:59:48 container. So, basically, this is a
1:59:50 little web browser inside your chat. And
1:59:54 so, those applications when when I when
1:59:58 I say do something in Canva, it's giving
2:00:01 me a little window into the activity
2:00:03 like what Canvas is doing and putting it
2:00:05 in there. So, it's this is a discrete um
2:00:10 virtual computer, for lack of a better
2:00:12 term. It's it's it's
2:00:14 kind of a fake, you know, virtual
2:00:17 computer, but it's like it's a little
2:00:19 container that that lives inside a chat
2:00:21 and it's doing its own thing. I can I
2:00:23 can now go, you know, go down here and,
2:00:26 you know, do other things. I can leave
2:00:28 and come back. But this is this is a
2:00:30 whole world with with within itself. So,
2:00:33 it's like a a native window. Does that
2:00:35 make sense? Sandboxed. Yeah. Yeah. It's
2:00:37 it it is sandboxed, right? So, it can't
2:00:40 it can't do it do things to your
2:00:42 computer. It can't erase your hard
2:00:44 drive. It's doing it in this little safe
2:00:46 little sandbox
2:00:49 like the coding.
2:00:52 Um, yeah, this isn't showing us all the
2:00:55 coding. I think you can look at it. If I
2:00:57 go look at activity, you can see the
2:01:00 prompts that this is doing. So, what
2:01:03 you're not seeing when you're just
2:01:05 watching it surf like that, it's it's
2:01:07 showing you like HTML,
2:01:09 but it's like I'm starting to research
2:01:11 bespoke candle makers. Um, I'll use the
2:01:14 browser search function. So, it's it's
2:01:16 figuring out what tools it's going to
2:01:17 use. I've searched the web. I found some
2:01:19 candle companies. I found Etsy and
2:01:22 Agaboo Candle. And here's the search
2:01:25 result. Right? So it's talking to itself
2:01:27 but but we're if I go to desktop view
2:01:30 you don't have to watch all that you
2:01:32 don't have to pay attention to that you
2:01:33 can literally watch it surf the web
2:01:36 right and so this is what agents do so
2:01:38 when you go to genspark or you go to
2:01:39 manus look so this is surf this is
2:01:43 literally searching surfing the web on
2:01:47 our behalf
2:01:53 pocket universe just trying to expand my
2:01:55 mind on it I like like this is trippy
2:01:58 [ __ ] that that's what I was saying you
2:01:59 know when I was saying earlier
2:02:02 we're interacting right now with AI
2:02:10 where we understand our role
2:02:13 and the importance of our role and and
2:02:16 the person that came in earlier and said
2:02:17 wait how do I get this thing to not suck
2:02:19 like how do I just talk an app into
2:02:21 existence that's good enough to ship and
2:02:23 I said well you got to
2:02:25 Um,
2:02:28 right now the AI tools are so bad.
2:02:32 They're they're they're like remarkably
2:02:34 good up until the point you want to do
2:02:36 something professional and then they
2:02:38 suck. They fall apart. And everything
2:02:41 like everything is is like that right
2:02:43 now. There there's not a single tool
2:02:45 that I know of that is truly
2:02:48 talk something into existence that's
2:02:50 commercial grade. Nothing.
2:02:55 But imagine when that day comes.
2:02:58 Because what's going to happen is when
2:03:00 that day comes, it's going to come not
2:03:02 just for one tool, but you've noticed
2:03:04 over this over 2025,
2:03:07 someone launches something new and
2:03:08 remarkable and within two months,
2:03:10 everyone else has has matched it, right?
2:03:13 That's going to keep happening. and and
2:03:15 the the minute someone launches
2:03:17 something that that is truly worldclass
2:03:20 and delivers worldclass results, all of
2:03:22 a sudden our role changes. We're no
2:03:26 longer the the people that have to make
2:03:28 sure that the AI doesn't suck.
2:03:31 We're now the people that need to make
2:03:32 sure that what's being created in it is
2:03:36 interesting
2:03:37 because everyone's going to be doing
2:03:40 everything
2:03:41 and then all of that's going to be not
2:03:43 interesting. And what's going to be
2:03:44 interesting is the [ __ ] that rises above
2:03:46 the noise. Who does that? It's going to
2:03:49 be the artists. It's going to be the
2:03:50 creative people. It's going to be the
2:03:51 creative thinkers. It's going to be the
2:03:52 critical thinkers.
2:03:55 That's why I'm pushing this daily
2:03:56 practice thing so hard
2:03:59 because that's going to be our job.
2:04:02 Um, it's not right now. It doesn't mean
2:04:04 you shouldn't build [ __ ] right now. You
2:04:05 should absolutely build [ __ ] right now
2:04:08 so that you know what's possible because
2:04:11 the minute that new thing shows up, you
2:04:14 will be there to pounce on it and know
2:04:16 exactly what to do with it.
2:04:20 So,
2:04:25 all right, I'm going to get out of here.
2:04:28 I need to drink. I didn't have enough
2:04:31 dinner. I'm starving. I'm dehydrated.
2:04:35 I'm all worked up.
2:04:37 [laughter] My hair's not bad, though. I
2:04:39 got I got some nice the do tonight held
2:04:42 up. [laughter]
2:04:44 Um, what do we need to talk about,
2:04:46 Brandon? It's Monday. We got nothing
2:04:47 going on tomorrow that's special.
2:04:50 Um, save the date the the 26th.
2:04:54 Oh, we're on Gemini Watch. Yeah, this
2:04:56 week we could get Nano Banana 2, which
2:04:59 again, I think Nano Banana 2 isn't just
2:05:02 about images. It's it starts to be
2:05:07 a new way of expressing outputs of the
2:05:10 large language model. I there's I
2:05:12 there's just
2:05:14 that's going to be remarkable. And then
2:05:15 Gemini 3 is apparently coming out and
2:05:17 they're going to retire
2:05:20 all the 2.5 [ __ ] So that could be this
2:05:22 week or it could be the 18th.
2:05:25 So, the rumor I've heard is Nano Banana
2:05:28 tomorrow, the 11th, and Gemini 3
2:05:32 on the 18th, but that's all just chat
2:05:35 DMZ [ __ ] So, but I think, okay,
2:05:42 one more thing. November is an important
2:05:46 month for AI.
2:05:49 Why? Because chat GPT came out November
2:05:52 30th, 2022.
2:05:55 And so everybody knows that Chat GPT
2:06:00 going to be dropping some [ __ ]
2:06:03 in November. So they all either want to
2:06:05 preempt or postempt or whatever the [ __ ]
2:06:09 it is when you don't preempt something,
2:06:10 but you do it on the other side. They
2:06:12 want to steal Open AI's thunder. So we
2:06:15 should get some [ __ ] from Open AI. We
2:06:17 should get some [ __ ] from Google. Uh we
2:06:19 have no [ __ ] idea what Meta is doing
2:06:22 except Meta. If you haven't played with
2:06:23 Meta AI recently, you now have free
2:06:28 midjourney inside Meta.ai.
2:06:31 Full-on midjourney. You can use SREs and
2:06:34 everything.
2:06:36 It's a much more simplified interface,
2:06:38 but it's midjourney. People don't
2:06:40 believe me online, but it is like, so
2:06:43 this month is going to be crazy. So,
2:06:45 keep coming back here. Join the AI
2:06:47 salon. Sign up for the mastermind. Start
2:06:50 designing your daily practice. and we're
2:06:52 going to start to turn the the level of
2:06:54 heat up in this channel. All right? And
2:06:57 you're going to you're going to do some
2:06:58 amazing things in the world. Okay,
2:07:02 I'm out of here. All right.
2:07:06 I did my video in Meta AI, by the way.
2:07:09 Very cool. Yeah, you like the Meta AI
2:07:11 thing. You can even do video in it for
2:07:13 free. So, go there now because I don't
2:07:15 think it gonna be free free for long,
2:07:18 but free right now. All right.
2:07:21 Beautiful.
2:07:28 Um, for the for the folks that are new
2:07:31 here tonight, thank you for coming
2:07:32 tonight. Thank you for asking questions.
2:07:35 Thank you for being vulnerable enough to
2:07:37 say, "Hey, I'm trying to figure this
2:07:38 [ __ ] out. We're all trying to figure
2:07:40 this [ __ ] out." Jump in. Keep coming
2:07:42 back. Join the community. Get active in
2:07:45 the community. All right? Join the
2:07:46 mastermind. Start your daily practice.
2:07:49 It'll change your [ __ ] life. I
2:07:50 promise you. Ask anyone in here. The
2:07:52 there the the people that come here
2:07:54 night after night are called the
2:07:55 irregulars.
2:07:57 And they are. They're weird.
2:08:01 But to a person, they can tell you they
2:08:04 have changed their lives by just showing
2:08:07 up and being in this conversation. So,
2:08:09 keep doing that. And thanks for coming
2:08:11 tonight. All right. Peace out. Have a
2:08:13 good night. I'll see you tomorrow night,
2:08:14 800 PM Mountain time. Bye.