1
00:00:00,000 --> 00:00:03,300
Luke, this is a great pleasure for me.

2
00:00:03,460 --> 00:00:06,680
I've been waiting for this episode for, I think, years now.

3
00:00:08,460 --> 00:00:10,540
Well, I'm definitely excited to be here.

4
00:00:10,920 --> 00:00:13,280
And to all your listeners, I'm sorry.

5
00:00:13,960 --> 00:00:20,780
There'll be lots of rants, lots of unhinged, maybe unhinged thoughts.

6
00:00:21,260 --> 00:00:22,980
But I'm really excited to be here.

7
00:00:23,660 --> 00:00:27,340
Well, you've had an open invite to the show for, I think, at least two years now.

8
00:00:27,340 --> 00:00:33,120
And you said, you've been saying for two years when the time's right, and I feel like I have something to say, I will let you know.

9
00:00:33,340 --> 00:00:34,960
And that happened a couple of weeks ago.

10
00:00:35,080 --> 00:00:41,260
And here we are, thinking of how to start off this episode.

11
00:00:41,380 --> 00:00:43,820
I think it's important for the audience to get context.

12
00:00:44,020 --> 00:00:55,120
Luke has been somebody who's helped me immensely behind the scenes here at TFTC, thinking about how to position the brand and how to increase our SEO.

13
00:00:55,120 --> 00:00:59,560
So not only that, how to lean into this AI revolution.

14
00:00:59,560 --> 00:01:14,640
And I think just to start off the conversation, let's get a little history of your career, what you've built, where you've worked, what you're working on now, and what people may learn if they stick around for the whole episode.

15
00:01:15,520 --> 00:01:15,860
Yeah, sure.

16
00:01:15,940 --> 00:01:17,380
So I'll do my best to keep it short.

17
00:01:18,280 --> 00:01:19,600
Yeah, so a little bit about me.

18
00:01:19,960 --> 00:01:21,800
I grew up in the middle of nowhere in Maine.

19
00:01:21,800 --> 00:01:27,180
And up until when I first went to college, I had always lived on a dirt road.

20
00:01:28,060 --> 00:01:33,620
I grew up in a small town in Central Maine.

21
00:01:33,880 --> 00:01:34,980
It was about 800 people.

22
00:01:35,060 --> 00:01:38,540
I think half of the town was on some form of general assistance.

23
00:01:39,320 --> 00:01:40,820
I was homeschooled growing up.

24
00:01:42,140 --> 00:01:45,360
I attended a mixture of homeschooling, private schooling.

25
00:01:45,360 --> 00:01:52,780
in high school, I ended up getting into web design because I wanted to customize my MySpace profile.

26
00:01:54,320 --> 00:01:58,000
I thought it would be cool and maybe more girls would talk to me.

27
00:01:59,460 --> 00:02:05,060
And so that's what I did. I ended up basically devoting, call it half of day. So I would

28
00:02:05,060 --> 00:02:09,160
homeschool for half of the day. And then for like the other half of the day, I would go to what's

29
00:02:09,160 --> 00:02:15,100
called a vocational technical school. And I was in a class with a bunch of kids that wanted to

30
00:02:15,100 --> 00:02:19,980
create video games. And I thought web design was cool. And I thought maybe there's something there.

31
00:02:20,220 --> 00:02:26,520
Little did I know that it would basically influence the rest of my life to date. And so, yeah, in high

32
00:02:26,520 --> 00:02:31,940
school, I kind of learned how to code. I wasn't very good at it, but I started creating websites

33
00:02:31,940 --> 00:02:39,240
for small businesses. I ended up graduating. I went to school one year in Boston because I thought

34
00:02:39,240 --> 00:02:45,080
sports management would be really fun. Turns out that spending tens of thousands of dollars a

35
00:02:45,080 --> 00:02:51,340
year for phys ed classes. Probably wasn't the best idea. So I ended up going to school for marketing

36
00:02:51,340 --> 00:02:58,400
and paid my way through school, kind of did the consulting thing, ended up graduating college

37
00:02:58,400 --> 00:03:05,280
and wanted to join the startup thing. And so long story short, my wife and I, the second we

38
00:03:05,280 --> 00:03:10,700
graduated, we moved to Boston. I started working in early stage tech companies. I originally joined

39
00:03:10,700 --> 00:03:17,820
as an engineer, quickly realized I wasn't good at writing code. But I always viewed writing code

40
00:03:17,820 --> 00:03:24,300
as a means to an end. For me, it was like, I loved to grow businesses. And so I ended up

41
00:03:24,300 --> 00:03:31,700
kind of falling into this industry called like growth, which is how to think about marketing

42
00:03:31,700 --> 00:03:37,620
through a programmatic lens, like a programmer would. And anyway, did that for a few years,

43
00:03:37,620 --> 00:03:42,540
you know, learned SEO, learned a bunch of, you know, internet marketing techniques and

44
00:03:42,540 --> 00:03:46,840
ended up falling down the product rabbit hole, largely because, you know, when you build,

45
00:03:47,500 --> 00:03:53,120
when you're building like a startup that is, you know, like a digital product, a lot of the growth

46
00:03:53,120 --> 00:03:57,580
work, so to speak, that you do ends up actually being product work. It's like, how can you create

47
00:03:57,580 --> 00:04:03,060
a product where these, these like flywheels that help you grow at a low cost? So, you know, for

48
00:04:03,060 --> 00:04:07,580
those who are familiar with like Dropbox, right, it's like people sign up for Dropbox to get free

49
00:04:07,580 --> 00:04:12,040
space. If you want more free space, you share it with a friend. I became very obsessed with that

50
00:04:12,040 --> 00:04:19,680
and ended up doing that for a while. In 2019, I decided to make the plunge, decided to start a

51
00:04:19,680 --> 00:04:27,080
remote work software company. I saw a bunch of these fully distributed companies building their

52
00:04:27,080 --> 00:04:33,300
own intranet is the best way of describing it. Zapier and Stripe and all these well-known

53
00:04:33,300 --> 00:04:37,820
remote companies had kind of hand-rolled their own system. So I started that and then six months

54
00:04:37,820 --> 00:04:43,980
later, COVID hit. And so we experienced a lot of growth. I did that for about two years,

55
00:04:43,980 --> 00:04:47,720
but I ended up shutting the business down because I didn't see a clear path to scaling

56
00:04:47,720 --> 00:04:53,300
on the revenue side in particular. So I ended up joining Zapier for about three years

57
00:04:53,300 --> 00:05:01,780
and went super deep there on AI and automation. And so, yeah, in many ways, a culmination of

58
00:05:01,780 --> 00:05:06,820
what your listeners will probably hear is maybe a little bit more of a deeper dive on AI,

59
00:05:07,580 --> 00:05:13,980
what it looks like, how it's changing things. I also left about two months ago and I started

60
00:05:13,980 --> 00:05:18,580
a new company called Formable. We basically are making it easy for businesses to respond

61
00:05:18,580 --> 00:05:23,380
to inbound leads way faster. And so for a lot of businesses, you have a contact form on your

62
00:05:23,380 --> 00:05:27,840
website. When someone fills it out, they usually have a high level of intent. You want to get back

63
00:05:27,840 --> 00:05:32,620
to them as fast as you can. Well, we're building simple and easy to use tools that make it easy

64
00:05:32,620 --> 00:05:37,520
for businesses to get back to their potential customers way faster using AI and automation

65
00:05:37,520 --> 00:05:44,400
and a better data collection or form experience. So long-term though, we want to build kind of a

66
00:05:44,400 --> 00:05:50,600
new school marketing automation platform, which is just like making it easy for businesses of all

67
00:05:50,600 --> 00:05:59,520
shapes and sizes to market in a way where you're leveraging AI as much as possible in new and we'll

68
00:05:59,520 --> 00:06:03,420
call it creative ways. We see a big opportunity there and we don't think the people in the space

69
00:06:03,420 --> 00:06:10,180
are moving fast enough. So that's kind of the spiel. I live in the Nashville area and I have

70
00:06:10,180 --> 00:06:16,760
four kids, seven and under. So life is good. But I think this context is probably useful for

71
00:06:16,760 --> 00:06:23,640
whatever else I'm going to say over the next hour or so. So that's my story. And yeah.

72
00:06:24,540 --> 00:06:29,380
Yeah. Well, like I said, like you've been helping me a lot behind the scenes, particularly

73
00:06:29,380 --> 00:06:35,100
as it pertains to how we grow this business, I think over the last year through the conversations

74
00:06:35,100 --> 00:06:41,200
we've had, you've made it clear to me that you're, you strongly believe that the nature

75
00:06:41,200 --> 00:06:47,300
of businesses, how they are started, how they operate, how they scale, and how big their teams

76
00:06:47,300 --> 00:06:54,460
get specifically is about to drastically change. And not only that, on the business side of things,

77
00:06:54,580 --> 00:06:59,520
you believe strongly that Bitcoin is going to play a role in accelerating these businesses as well.

78
00:07:00,620 --> 00:07:06,220
Yeah, yeah. So the way I kind of think about it is, the best way I can describe what I think is

79
00:07:06,220 --> 00:07:12,160
going on is kind of we live in an age where there's kind of this like concept of like unbounded

80
00:07:12,160 --> 00:07:18,140
leverage, right? So before there were certain constraints that existed in a business, it could

81
00:07:18,140 --> 00:07:25,460
be in particular teams in the business. And we've entered a phase where, you know, one person can

82
00:07:25,460 --> 00:07:34,140
accomplish a lot more with AI in particular. And so I think like, there's this rise, at least how I

83
00:07:34,140 --> 00:07:40,740
view it of these businesses that understand this reality, and they work their way through

84
00:07:40,740 --> 00:07:48,700
their own companies, trying to identify these areas of leverage, and then implementing solutions

85
00:07:48,700 --> 00:07:55,240
or tools or processes to kind of take full advantage of this kind of unbounded leverage

86
00:07:55,240 --> 00:08:00,740
idea, right? And so I think actually Bitcoin really fits into this thesis quite a bit, right?

87
00:08:00,740 --> 00:08:10,300
Because if you think about it, you know, in my world, you know, if you're an early stage startup, you especially if you're venture backed, you have to go out and you raise money.

88
00:08:10,460 --> 00:08:15,440
Right. And usually I would say usually it really depends on the strategy.

89
00:08:15,440 --> 00:08:21,040
But I would say in general, a business goes out and tries to raise at least 18 months of runway.

90
00:08:21,880 --> 00:08:27,340
Oftentimes, in some instances, it can be years of runway. Right.

91
00:08:27,340 --> 00:08:32,280
And so you basically end up having a bunch of fiat sitting in your bank account.

92
00:08:33,600 --> 00:08:41,620
And so if you think about this idea of where are the areas where there's leverage, it's like your balance sheet is clearly an area where there needs to be some amount of leverage as well.

93
00:08:42,380 --> 00:08:49,780
If you're an early stage startup burning with a burn rate, you're not making as much as you are spending.

94
00:08:50,120 --> 00:08:53,340
Obviously, you have to be a little bit more, we'll call it risk off.

95
00:08:53,340 --> 00:08:59,740
but for a profitable business in particular I think the the ability to be a bit more risk on

96
00:08:59,740 --> 00:09:05,400
here around your balance sheet in particular becomes much more interesting and compelling

97
00:09:05,400 --> 00:09:10,840
but like if you apply that principle of like where can I kind of like tap into this like

98
00:09:10,840 --> 00:09:17,640
almost like digital energy as sailor kind of puts it right obviously the balance sheet is one area

99
00:09:17,640 --> 00:09:22,400
But I think AI represents its own form of digital energy.

100
00:09:23,780 --> 00:09:26,320
And that can be applied in other parts of the business.

101
00:09:26,320 --> 00:09:40,500
And so I think as I survey the nature of where things are going, the businesses of the future will kind of understand this reality and will look for areas where they can implement this everywhere.

102
00:09:40,500 --> 00:09:52,800
I would say to maybe take it a step further, I actually would argue we're not seeing nearly – like we're not seeing that much yet.

103
00:09:53,260 --> 00:10:01,440
And I would argue the reason why is because existing businesses have a lot of – we'll call it baggage, right?

104
00:10:01,680 --> 00:10:05,540
They have – they made certain hires based on certain assumptions.

105
00:10:06,120 --> 00:10:09,180
They implemented certain tools based on other assumptions.

106
00:10:09,180 --> 00:10:20,660
And so they've created this system that is designed and aims to function in a particular way given certain assumptions.

107
00:10:21,160 --> 00:10:26,980
But with AI, it's literally coming in and it's like really rattling those assumptions.

108
00:10:28,140 --> 00:10:32,500
So if you're a business, it could mean that you need to change your pricing and packaging.

109
00:10:32,500 --> 00:10:45,440
Right. And for a lot of like software companies in particular, it could represent saying, hey, we're going to like literally axe a bunch of revenue to change our business model around to be more future proof.

110
00:10:45,660 --> 00:10:51,160
Most businesses will not do that. It could mean laying off people.

111
00:10:52,160 --> 00:10:58,660
Right. And so I think we're only starting to see the beginning of this shift.

112
00:10:58,660 --> 00:11:14,300
And I would argue that the tooling and the tech is far ahead of what is actually in use and in practice at these businesses. And so the constraint is not the tech. It's the existing structures in place.

113
00:11:14,300 --> 00:11:34,180
And I saw this firsthand, and I see this firsthand where it's like, businesses, we want to do things the way we want to do it. You can sprinkle AI on top of it, go for it, have fun. You can have a CEO mandate, but it doesn't drive the necessary change or the change that will be coming.

114
00:11:35,060 --> 00:11:39,400
And so, yeah, I think like we're kind of entering an age of where there's unbounded leverage.

115
00:11:40,620 --> 00:11:49,240
Startups, when you start from scratch, or if you're building a business from scratch, you can start with a greenfield environment, but the existing business cannot.

116
00:11:50,240 --> 00:11:54,820
And so that's why you see a lot of these startups that are like they're shipping code way faster than others.

117
00:11:54,820 --> 00:12:08,620
They're moving way faster than others. It's because they're tapping into all that like unbounded leverage where the existing business has the structures in place that just are not they're not set up in that way.

118
00:12:08,620 --> 00:12:17,340
I'll give you one more analogy. I was maybe too young to experience this firsthand. I wasn't working in tech, but, you know, there was a season.

119
00:12:17,340 --> 00:12:24,300
And I feel like it was maybe like in the early or middle 2000s where there was this concept of like software moves to the cloud.

120
00:12:25,200 --> 00:12:33,220
Right. And so you had these like, you know, code that was on prem or it was like, you know, in the confines of the four walls of the business.

121
00:12:33,420 --> 00:12:39,900
And then like, you know, Salesforce comes along and is like, hey, it's like an address book in the cloud, whatever the cloud means, you know.

122
00:12:39,900 --> 00:12:49,500
But those old businesses had to make a decision around how serious they were about this new cloud thing.

123
00:12:50,640 --> 00:12:55,120
And I think the same is true now with existing even software businesses.

124
00:12:56,020 --> 00:12:58,920
Are we going to fully embrace this AI thing?

125
00:12:59,440 --> 00:13:06,360
And I just think that you're going to see a lot of, we'll call it a flippening, that takes place over the next few years.

126
00:13:06,360 --> 00:13:09,220
Anyway, I digress, but that's kind of like the thesis in a nutshell.

127
00:13:09,900 --> 00:13:15,340
Well, speaking of digressing, let's regress and do like a retrospective on the last one

128
00:13:15,340 --> 00:13:17,400
or two years, the evolution of AI.

129
00:13:17,660 --> 00:13:18,480
And let's get more specific.

130
00:13:18,560 --> 00:13:21,320
You're talking about this unbounded leverage that it provides.

131
00:13:21,320 --> 00:13:24,540
But what has happened since GBT3 launched?

132
00:13:24,880 --> 00:13:26,300
Like how good are the models get?

133
00:13:26,720 --> 00:13:28,400
What specifically are they good at?

134
00:13:28,540 --> 00:13:34,260
And how are you and other founders leveraging them to outcompete incumbents?

135
00:13:34,300 --> 00:13:39,600
And then on the incumbent side of things, let's get into the specifics of what sort

136
00:13:39,600 --> 00:13:43,900
of confines them and makes them unable to make the necessary changes to compete.

137
00:13:44,660 --> 00:13:44,980
Yeah, sure.

138
00:13:45,060 --> 00:13:48,440
So I'll kind of walk you through my personal firsthand experience using AI.

139
00:13:49,140 --> 00:13:51,040
So it's kind of a funny story.

140
00:13:51,280 --> 00:13:56,320
Back actually at my previous startup, I think it was like, I don't know, it was maybe early

141
00:13:56,320 --> 00:13:57,900
2022, late 2021.

142
00:13:58,700 --> 00:14:00,300
And I chatted with a fellow founder.

143
00:14:00,860 --> 00:14:02,360
He's kind of a bit of a brainiac.

144
00:14:02,540 --> 00:14:05,020
And he's like, you got to go get an invite.

145
00:14:05,440 --> 00:14:06,480
Email this guy.

146
00:14:06,480 --> 00:14:10,720
and I think it was Greg Brockman, I think one of the co-founders of OpenAI,

147
00:14:11,180 --> 00:14:12,900
he's like, email him and ask him for access.

148
00:14:13,640 --> 00:14:18,580
So I emailed somebody at OpenAI, and they gave me access to,

149
00:14:18,820 --> 00:14:24,740
I think it was either it was ChatGPT, or it wasn't ChatGPT,

150
00:14:24,820 --> 00:14:27,260
it was GPT2 or 3.

151
00:14:28,380 --> 00:14:32,000
And I started playing around with it, and it had a developer experience.

152
00:14:32,120 --> 00:14:33,760
And I'll just share my screen for a second.

153
00:14:33,760 --> 00:14:37,680
We'll come back to this later as well because there's some stuff I want to show you guys.

154
00:14:38,100 --> 00:14:40,080
But it looked something like this.

155
00:14:40,620 --> 00:14:43,340
It was a developer-first experience.

156
00:14:44,300 --> 00:14:49,820
And once again, nobody ever hired me, at least for a long period of time, to write code.

157
00:14:50,220 --> 00:14:52,400
But I started playing around with it.

158
00:14:53,060 --> 00:15:00,300
And at the time, I was like, wow, this is kind of like autocomplete.

159
00:15:01,300 --> 00:15:02,640
It's like autocomplete.

160
00:15:02,640 --> 00:15:10,580
At the end of the day, like AI in many ways, like this is maybe a simplistic way of describing it.

161
00:15:10,580 --> 00:15:24,015
But at the end of the day it like if it uses math to determine what the next word or set of characters should be Like that kind of that how it works in a nutshell It like it makes guesses

162
00:15:25,395 --> 00:15:26,435
It's trained on data.

163
00:15:26,575 --> 00:15:29,535
It makes guesses about what the next words or words should be.

164
00:15:30,215 --> 00:15:32,755
And so I was like, oh, this is pretty cool.

165
00:15:32,815 --> 00:15:36,455
And obviously, as you know, someone coming from like the content marketing and the SEO

166
00:15:36,455 --> 00:15:42,015
background, I'm like, I get my head of marketing, who's like an amazing content marketer, right?

167
00:15:42,075 --> 00:15:43,855
He writes blog posts, they rank in Google.

168
00:15:44,155 --> 00:15:59,035
Like, we got traffic, I think we were doing like, you know, 15,000 signups a month with like a $2,000 a month marketing budget, right? And I'm like, you got to start using this to, to basically help scaffold up some blog posts.

169
00:15:59,035 --> 00:16:06,235
um and and so he started using it and we went from like if it was like 200 a post right 200

170
00:16:06,235 --> 00:16:11,135
a post like we had you know people off in yonderland writing posts and they were okay but they

171
00:16:11,135 --> 00:16:17,595
weren't that great right and all of a sudden it's like uh this is like 25 30 dollars and it's like

172
00:16:17,595 --> 00:16:22,415
wow that's pretty cool and so you know i used it ended up shutting you know shutting the business

173
00:16:22,415 --> 00:16:29,655
down, joined Zapier. And then I think it was maybe like six months later, ChatGPT comes out.

174
00:16:30,175 --> 00:16:34,595
One of the founders was going down the rabbit hole on AI. It's going down the rabbit hole.

175
00:16:35,295 --> 00:16:43,035
And all of a sudden it's like, hey, we need to care about this. This is like a big bang moment

176
00:16:43,035 --> 00:16:48,015
in the tech world. Everybody needs to care about this. And so they pulled this, what we're looking

177
00:16:48,015 --> 00:16:53,575
back called a code red, which is kind of just like an internal, we'll call it fire drill. It's like,

178
00:16:53,615 --> 00:17:00,055
we need to care about this. And here's how we're thinking about this. And so immediately, at the

179
00:17:00,055 --> 00:17:06,875
time, I was a product manager there. And I started playing around with it because I knew that it was

180
00:17:06,875 --> 00:17:12,195
powerful before, but it was like, how am I going to use it now? And at the time, I would actually

181
00:17:12,195 --> 00:17:17,935
say I was a little bit of a skeptic, even though I'd experienced the power in one particular

182
00:17:17,935 --> 00:17:25,735
area. I was like, Hannah, what is the scope here? What are we dealing with? How useful is it,

183
00:17:25,795 --> 00:17:31,395
especially with this new launch? And so at the time, I kind of had this fun little hobby,

184
00:17:31,395 --> 00:17:35,335
and I still do, where I would read these old books written in old English.

185
00:17:36,835 --> 00:17:43,855
And I find that there's something cathartic about reading old books outside of the current

186
00:17:43,855 --> 00:17:51,915
moment that we're in. And I was like, I bet you, I bet you I could use this to update the text so

187
00:17:51,915 --> 00:17:57,535
that I can make sense of what the heck I'm reading right now. And so I ended up doing that. I was

188
00:17:57,535 --> 00:18:01,955
like, oh, it's good, but it's not great. Like it would maybe make it a few sentences in a paragraph.

189
00:18:02,175 --> 00:18:06,315
It would update it. And then all of a sudden it just kind of go off the rails. I was like, man,

190
00:18:06,335 --> 00:18:11,215
that's kind of a bummer, but like, cool. Well, three months later they launched, I think it was

191
00:18:11,215 --> 00:18:16,655
like a new model. And so I returned to that problem. And it was like, oh, wow, I'm getting

192
00:18:16,655 --> 00:18:22,535
like full paragraphs now. And so I decided to have a friend build me a little tool where I could

193
00:18:22,535 --> 00:18:28,535
update like, you know, 20 pages of text at a time. And then I decided, oh, I'll just keep going down

194
00:18:28,535 --> 00:18:32,755
the rabbit hole. So I'm learning how to prompt. I'm learning how to use different models. I'm

195
00:18:32,755 --> 00:18:37,595
learning how to kind of adjust things. Like, how can I make it less creative and more,

196
00:18:37,595 --> 00:18:42,035
based on that original text with minor updates.

197
00:18:42,835 --> 00:18:45,035
And so I just kept going and going, going down the rabbit hole.

198
00:18:45,835 --> 00:18:48,695
And then I ended up, wow, I'll just put it up on Amazon.

199
00:18:49,975 --> 00:18:53,595
Well, long story short, I think I've sold about 50,000 books in the past three years.

200
00:18:53,595 --> 00:18:57,215
But I modernized Old English.

201
00:18:58,595 --> 00:19:01,875
And now all of a sudden, it's like my world is AI.

202
00:19:01,875 --> 00:19:10,575
And then at work, we launched a feature that used AI, and it just took right off.

203
00:19:11,055 --> 00:19:13,935
It was this basic capability where you could ask questions.

204
00:19:14,855 --> 00:19:18,635
You could embed this widget on your website and ask questions.

205
00:19:19,615 --> 00:19:26,375
And so if business could put a widget on their website, people would ask questions, and then they wouldn't have to ping you and ask you generic questions over and over again.

206
00:19:26,855 --> 00:19:28,975
So I'm like, I'm way down the rabbit hole now.

207
00:19:28,975 --> 00:19:34,715
right and then it's been one of those things where i just consistently as a result of tinkering

208
00:19:34,715 --> 00:19:40,835
um you know just trying things the models have just continued to get better and better

209
00:19:40,835 --> 00:19:47,695
some models aren't as game-changing as others um but you just continue to see this

210
00:19:47,695 --> 00:19:54,895
improvement being made where before you know i could ask a question of a 10-page pdf and now i

211
00:19:54,895 --> 00:20:00,575
can ask a question of a 300-page PDF and get the right answer, right? Or summarize this short text,

212
00:20:00,735 --> 00:20:09,815
summarize this long text. And so I'm, once again, I'm digressing, but as a result of tinkering and

213
00:20:09,815 --> 00:20:15,515
kind of building in the space, you're able to kind of monitor things and see the nature of the

214
00:20:15,515 --> 00:20:23,495
progression. And so as a founder, gosh, where do I even begin? Maybe I'll walk you through

215
00:20:23,495 --> 00:20:24,935
how

216
00:20:24,935 --> 00:20:29,715
yeah, like where do I even begin?

217
00:20:31,335 --> 00:20:34,935
What's the best way of describing? Maybe I'll talk about agents for a couple minutes.

218
00:20:36,575 --> 00:20:39,635
Okay. So for those who

219
00:20:39,635 --> 00:20:43,335
you've probably seen the pieces in the news and all that,

220
00:20:43,335 --> 00:20:46,795
there's this whole kind of idea of like AI agents. What are AI agents?

221
00:20:47,695 --> 00:20:51,395
It's like, well, a lot of it's hype, but there is a reality underneath it. And it's

222
00:20:51,395 --> 00:20:58,575
basically that agents are, I view them as almost like little digital coworkers, right? Where you

223
00:20:58,575 --> 00:21:01,935
can tell them what to do and they'll do something for you and then they'll give you back a result.

224
00:21:02,255 --> 00:21:06,115
So the way I describe this is, you know, if you've ever used ChatGPT before,

225
00:21:06,975 --> 00:21:15,155
you give it an input, hands on keyboard, you type in something that the agent goes to work

226
00:21:15,155 --> 00:21:22,975
and then it returns text for you to take a look at. Well, the chat experience is just one

227
00:21:22,975 --> 00:21:30,655
implementation of an agent, right? It takes an input, it does a thing, it gives you back an output,

228
00:21:31,415 --> 00:21:39,175
right? And this instance, it does it through a chat experience. Well, one of the big things that I

229
00:21:39,175 --> 00:21:48,235
I guess learned is, well, that's cool. But when it's initiated by a human, there's only so like

230
00:21:48,235 --> 00:21:53,035
you have, you basically have to rely on human behavior change to get the result that you're

231
00:21:53,035 --> 00:21:57,935
looking for with AI, right? It's like, oh, I need to go to chat GPT. I need to remember to use it.

232
00:21:57,935 --> 00:22:03,575
Like that's actually really difficult. But there's no reason why you couldn't feed

233
00:22:03,575 --> 00:22:10,295
these little digital brains information behind the scenes where it does a thing and then it gives you

234
00:22:10,295 --> 00:22:16,555
back a result and then you use it further down in some type of workflow and so zapier is a workflow

235
00:22:16,555 --> 00:22:21,615
automation product um it's been around for 10 years and what we saw is like people would build

236
00:22:21,615 --> 00:22:26,875
these automations right when this happens in this tool i want to do something else in another tool

237
00:22:26,875 --> 00:22:32,055
well what we saw people doing was they were saying yeah i want that to happen but in the

238
00:22:32,055 --> 00:22:40,535
middle, I want to use basically ChatGPT to do a thing for me. So, oh yeah, when I get an email,

239
00:22:40,635 --> 00:22:45,435
I want to summarize the email, and then I want to insert that information into another tool.

240
00:22:46,575 --> 00:22:55,135
And so agents is kind of the big topic these days for startup founders. And once again,

241
00:22:55,135 --> 00:23:00,695
there's a decent amount of hype, but there is a very real reality. And it's that these

242
00:23:00,695 --> 00:23:10,895
these digital employees um kind of do work for you and so in the old world when you're building

243
00:23:10,895 --> 00:23:19,255
software you kind of it's like you assemble tools in a toolbox right and um and then they give you

244
00:23:19,255 --> 00:23:23,175
the toolbox you pay for the tools in the toolbox and then they say have fun we'll see you later

245
00:23:23,175 --> 00:23:28,775
maybe we'll do a little training with you um but like ultimately it's up to you the human to um

246
00:23:28,775 --> 00:23:34,875
pick up the tools and use them. Well, with AI and with agents in particular,

247
00:23:35,515 --> 00:23:40,895
you can basically almost have this intermediary between you and the tool.

248
00:23:41,715 --> 00:23:47,615
So now there's like these little digital employees that can kind of start doing work for you.

249
00:23:49,595 --> 00:23:55,815
And so all of a sudden, the human labor that I would need to do, whatever I was doing before,

250
00:23:55,815 --> 00:24:01,175
I don't have to do as much of it because the agents are doing work. And so all these startups

251
00:24:01,175 --> 00:24:07,695
are looking for ways where agents or these little digital employees can basically be plopped into a

252
00:24:07,695 --> 00:24:17,495
workflow or injected into a business process. And so you're just seeing this explosion of

253
00:24:17,495 --> 00:24:22,315
startups looking for places where they can just stuff a little digital employee.

254
00:24:22,315 --> 00:24:31,955
And so every time, though, that Grok or OpenAI or Anthropic releases a new model, the digital employee gets smarter.

255
00:24:33,255 --> 00:24:40,695
The digital employee couldn't do a thing before, but now it's like it received better training and it's able to do some new things now.

256
00:24:41,515 --> 00:24:44,615
And so every time a new thing is released, it gets smarter and smarter.

257
00:24:44,615 --> 00:24:59,675
So anyway, startups, I would say in general, are looking for ways to use and kind of get these agents to do work, to augment human labor, to take work off people's plate.

258
00:25:00,415 --> 00:25:03,475
And the agent is really, really good at what it does.

259
00:25:03,575 --> 00:25:06,115
It can contain a bunch of information about your business.

260
00:25:06,115 --> 00:25:15,075
like it can literally have libraries of content in its brain or in its memory um and it can

261
00:25:15,075 --> 00:25:22,015
reference that so that it does the job in many instances better than the human because the agent

262
00:25:22,015 --> 00:25:29,055
doesn't forget the agent keeps keeps all this stuff in mind and so anyway it's it's kind of

263
00:25:29,055 --> 00:25:34,795
nuts honestly like i've never in the you know decade plus i've been in tech you know there's

264
00:25:34,795 --> 00:25:40,835
been some shifts and all this. This is easily the biggest shift I've ever seen. And it's like,

265
00:25:40,855 --> 00:25:44,855
and we're still really only in the beginning stages. And so if, you know, as a start, like,

266
00:25:44,875 --> 00:25:48,735
this is part of the reason why I'm working on a new thing is because it's just like, I can't sit

267
00:25:48,735 --> 00:25:55,515
by and watch this happen. Like I want to build stuff, you know? So anyway, I don't know if that's

268
00:25:55,515 --> 00:26:00,795
useful, but that's how startups are using AI and what's happening in the market right now.

269
00:26:00,795 --> 00:26:26,375
Yeah. No, I'm thinking of, because you've heard it, startups are even more mature companies. There's always like one or two employees that know the code base extremely well. And they're like a key man risk. Like if they were to leave, they know how everything works. And now you can sort of automate that task. You know, that risk doesn't isn't as high as it was because you have these agents now that can just.

270
00:26:26,375 --> 00:26:41,195
I'll give you an example. So, you know, we have a code base, the new product that we're building has a code base. I don't go in and I don't really know the code base. I mean, I could like fiddle around to see what's going on and I can roughly read what's going on.

271
00:26:41,195 --> 00:26:47,535
But now I can just get the code on my machine, point Cloud Code at it.

272
00:26:48,175 --> 00:27:03,175
And so yesterday I was playing around, and in a startup, you kind of need to create product documentation and help docs so that if someone needs to find their way around the product, there's like a little repository or a series of web pages that you can go to to say, how do I do this?

273
00:27:03,195 --> 00:27:03,835
How do I do that?

274
00:27:03,835 --> 00:27:11,535
I pointed Cloud Code at this and said, hey, look at my code base and literally write the help docs for me.

275
00:27:12,395 --> 00:27:13,635
And it did it.

276
00:27:13,635 --> 00:27:14,895
And it did like five minutes.

277
00:27:15,775 --> 00:27:26,475
And so it wrote like 20 super comprehensive help docs and like literally walked people through how to access certain features because it has knowledge of the code.

278
00:27:26,835 --> 00:27:32,235
I will tell you, there are dedicated people in companies that literally do this all day.

279
00:27:32,235 --> 00:27:38,015
it's just like that's just that's just one example that's just one example

280
00:27:38,015 --> 00:27:44,915
yeah well and then i guess shifting this towards the companies that already exist have these code

281
00:27:44,915 --> 00:27:50,875
bases have these teams and these processes like let's dig into how they're about to get disrupted

282
00:27:50,875 --> 00:27:57,295
and how if at all they can reposition themselves to not get blown out of the water

283
00:27:57,295 --> 00:28:25,235
Yeah, yeah. So this is a fun one. Okay, so I'll kind of walk you through what I'll call the roadblocks or the constraints are. So the first is we'll maybe start with the people. So I think there's two pieces. The first is there's a lot of people that are just like, I don't care about AI and I don't care to know and I'm just going to keep collecting my paycheck and screw what the CEO says.

284
00:28:25,235 --> 00:28:31,595
you know this mandate i don't care like i i don't care right and so i would say that is the fool

285
00:28:31,595 --> 00:28:38,975
um that is a foolish approach um and so you have you know you could have

286
00:28:38,975 --> 00:28:45,775
i mean depends on the company right but i mean even in a tech company you might have 20 percent

287
00:28:45,775 --> 00:28:50,955
of your employee base that thinks that way right because if you just think about it there's kind of

288
00:28:50,955 --> 00:28:58,755
this idea of these technological adoption curves. There's the innovator, the early majority,

289
00:28:58,915 --> 00:29:01,955
the late majority. Some percentage of your business is the late majority.

290
00:29:03,335 --> 00:29:06,395
They're at the tail end of adoption. They're not at the cutting edge.

291
00:29:07,995 --> 00:29:15,375
And so they are going to not necessarily fight the initiative, but they're definitely not going

292
00:29:15,375 --> 00:29:25,475
to look for ways to try to improve. And in some instances, they will kind of block things and be

293
00:29:25,475 --> 00:29:31,335
a naysayer. So that's part one. Part two is the organization itself is structured in a particular

294
00:29:31,335 --> 00:29:35,355
way. Certain people have certain roles and responsibilities, and they like that, right?

295
00:29:35,495 --> 00:29:40,535
People like having consistency. People don't generally like when their job description gets

296
00:29:40,535 --> 00:29:47,355
torn up and they're like, you're doing something new. So when it comes to some of these new tools,

297
00:29:48,415 --> 00:29:54,915
there are new tools that because you have these agents and AI doing more of the human labor,

298
00:29:57,555 --> 00:30:02,355
they rightfully notice that this is disruptive to my job.

299
00:30:04,195 --> 00:30:09,255
It's kind of like, I see these stories on the internet where you have these people in IT or

300
00:30:09,255 --> 00:30:14,555
whatever and they're like they're training their replacement that's overseas it's like it's kind of

301
00:30:14,555 --> 00:30:20,495
like that you know they they know they're like something's wrong here and so they will fight

302
00:30:20,495 --> 00:30:28,275
right they'll stonewall things they will um say we don't need the software they'll that once again

303
00:30:28,275 --> 00:30:44,450
kind of be a naysayer and i like for what it worth i i uh i have a certain degree of empathy for that situation But I don think the answer here is letting the big tidal wave smack you in the face

304
00:30:45,010 --> 00:30:49,930
Don't go to the beach and let the big tsunami run over you.

305
00:30:50,550 --> 00:30:51,630
I just don't think that's wise.

306
00:30:52,630 --> 00:30:53,910
So that's just the people.

307
00:30:54,530 --> 00:30:55,770
That's just the people.

308
00:30:56,610 --> 00:31:03,510
Now, we'll talk about the tech or the assets that the business has, right?

309
00:31:03,930 --> 00:31:06,970
So in my world in software, it's code, right?

310
00:31:07,090 --> 00:31:09,150
The asset is the code in the code base.

311
00:31:09,690 --> 00:31:18,470
Well, for a lot of businesses, unless they were started like recently, they have a lot of baggage tech debt, right?

312
00:31:18,910 --> 00:31:24,790
And so when someone wrote that code, they built it in a particular way based on certain assumptions, as I mentioned earlier.

313
00:31:25,770 --> 00:31:40,130
Um, well, if you, if, if you want to make a meaningful change and like put AI like deeply into an existing feature, you basically have to rewrite the thing from scratch.

314
00:31:41,130 --> 00:31:41,650
Right.

315
00:31:41,650 --> 00:31:49,830
And you have to build it in a way where like you're throwing out a lot of like, you know, old code and like, you know, you're making massive investments.

316
00:31:49,830 --> 00:31:55,970
And like tech debt is not something that the companies generally want to invest in.

317
00:31:57,070 --> 00:32:02,430
They like revenue generating features, revenue generating code that's written.

318
00:32:02,830 --> 00:32:05,930
Right. And so it's easy to kick the can, kick the can, kick the can.

319
00:32:06,370 --> 00:32:13,490
So that's why if you look at a lot of these software providers, if they've done AI, it's very surface level.

320
00:32:13,590 --> 00:32:15,290
It's like, oh, here's a little copilot.

321
00:32:15,290 --> 00:32:20,590
Right? Here's a little co-pilot on the side. You can load it, and then you could talk to it,

322
00:32:20,670 --> 00:32:23,290
and it will answer some questions, but it's kind of useless.

323
00:32:24,030 --> 00:32:28,690
But the whole rest of the experience is the same thing. So that gets into maybe part three,

324
00:32:28,990 --> 00:32:36,470
design. When you onboard people, and when you have been around for a long time, you have a

325
00:32:36,470 --> 00:32:42,470
user experience that has been built in a particular way, and your customers are used to it. And they

326
00:32:42,470 --> 00:32:47,550
might be a little bit of a, I wouldn't say the naysayer, but let's call it the late majority.

327
00:32:48,830 --> 00:32:54,530
So if you go in and you start ripping, like you just start making huge changes to the user

328
00:32:54,530 --> 00:33:03,350
experience, they are going to just moan and complain because their workflow was disrupted.

329
00:33:03,470 --> 00:33:09,230
Once again, rightfully so. So it's like, wow, well, to do some type of change, like let's just

330
00:33:09,230 --> 00:33:11,930
Sprinkle a little bit of AI on top of what already exists.

331
00:33:12,190 --> 00:33:13,430
And that's from a design perspective.

332
00:33:14,010 --> 00:33:16,110
Moving on, pricing and packaging.

333
00:33:18,870 --> 00:33:22,790
Businesses love to sell features.

334
00:33:23,190 --> 00:33:24,490
They love to sell seats.

335
00:33:25,730 --> 00:33:27,630
Seats is probably my favorite example.

336
00:33:28,430 --> 00:33:35,730
Well, if a business, like in the markets that we play in, if a business makes a ton of money selling seats,

337
00:33:35,730 --> 00:33:39,710
and AI comes along and says, you don't need as many employees.

338
00:33:41,950 --> 00:33:46,690
Well, A, like they literally, it's kind of, it competes with their own business model.

339
00:33:48,030 --> 00:33:55,730
Right. And so are you going to cannibalize existing revenue for the ambiguity of the unknown?

340
00:33:56,670 --> 00:33:59,130
I don't think they will unless they're backed into a corner.

341
00:33:59,130 --> 00:34:07,170
um and so in general you know start businesses like to grow and ai is a big enough shift where

342
00:34:07,170 --> 00:34:12,630
you kind of have to rethink your your um your your pricing and packaging you have to shift away from

343
00:34:12,630 --> 00:34:19,450
um selling seats i think you have to shift towards um this concept of agents doing work

344
00:34:19,450 --> 00:34:24,510
right and how do you build based on the work and especially if the work is done well

345
00:34:24,510 --> 00:34:32,170
right um and so that's a pretty big shift so it's a huge shift so that's on the pricing and

346
00:34:32,170 --> 00:34:37,450
packaging front trying to think of what else i mean it just works its way through basically

347
00:34:37,450 --> 00:34:43,430
every single department in the company and so when you add it all up it's like they're mired

348
00:34:43,430 --> 00:34:49,470
in the old world yeah i think the other thing that we've discussed before too is just like

349
00:34:49,470 --> 00:34:55,370
the bureaucratic administrative layer that's been implanted into a lot of these businesses,

350
00:34:55,530 --> 00:34:59,930
particularly the larger ones. Oh, I mean, I could go on and on about that.

351
00:35:00,270 --> 00:35:06,310
But it's like, you know, this whole managerial class concept where you have these people steering

352
00:35:06,310 --> 00:35:12,690
the work that don't have any idea what they're doing, you know, at least on the practice. So

353
00:35:12,690 --> 00:35:17,950
like you have an engineer, let's say, who goes deep in AI and they're like trying to explain

354
00:35:17,950 --> 00:35:25,810
what the heck this new technology does. And the middle manager that's selling their RSUs and making

355
00:35:25,810 --> 00:35:31,970
plenty of money off the old world is not going to really entertain this unless they're forced to.

356
00:35:33,050 --> 00:35:42,070
And so you just have this, the politics is crazy. It's absolutely insane. And so you put all of this

357
00:35:42,070 --> 00:35:48,710
stuff together and this is why i say that the the roadblock is is around the existing structures it

358
00:35:48,710 --> 00:35:55,050
the ai the tech itself is way further ahead than how businesses have implemented it and then you

359
00:35:55,050 --> 00:36:01,730
also have this whole kind of um consultant class we'll call it where they come in and like ai is

360
00:36:01,730 --> 00:36:10,410
changing the game um pay us lots of money and we will recommend mediocre things like you know maybe

361
00:36:10,410 --> 00:36:13,710
I mean, and I don't want to be too facetious here, I guess.

362
00:36:14,410 --> 00:36:17,010
But we will make it so you can process your PDFs.

363
00:36:17,950 --> 00:36:20,770
They implement, in some businesses, this is actually a game changer.

364
00:36:21,050 --> 00:36:23,210
But they kind of just sprinkle it in.

365
00:36:23,530 --> 00:36:25,110
Oh, AI transformation.

366
00:36:25,270 --> 00:36:27,050
Your entire company needs to be on ChatGPT.

367
00:36:27,430 --> 00:36:35,370
OK, I will take my monthly retainer, and I will come back next month and tell you some other basic, obvious thing that you need to do.

368
00:36:35,730 --> 00:36:37,450
And so that's why I think I was reading recently.

369
00:36:37,630 --> 00:36:39,170
I think it's like an MIT story or something.

370
00:36:39,170 --> 00:36:43,950
95% of AI initiatives fail.

371
00:36:44,190 --> 00:36:45,310
It's like, it's no wonder why.

372
00:36:45,530 --> 00:36:54,730
Ever after the last five minutes of explaining every part of a business where things could go wrong, it just makes sense, right?

373
00:36:55,650 --> 00:36:57,610
Yeah, it makes total sense.

374
00:36:57,610 --> 00:37:02,890
And that's why, number one, I'm very happy that I met you and we've been having these conversations.

375
00:37:03,030 --> 00:37:07,750
Number two, I feel fortunate at TFTC and at 1031 that we have relatively small teams.

376
00:37:07,750 --> 00:37:14,750
tftc there's four of us and some contractors 1031 there's five of us and i feel like i've been able

377
00:37:14,750 --> 00:37:20,890
to adapt i mean i'm not saying that we're on the cutting edge of ai um in terms of implementing it

378
00:37:20,890 --> 00:37:26,030
on the business but we have implemented it to a certain degree like we're making i think we've

379
00:37:26,030 --> 00:37:32,370
got some automation on the back end very simple stuff just to get my head of gross and sort of my

380
00:37:32,370 --> 00:37:35,470
multi-tool guy, Ed,

381
00:37:36,030 --> 00:37:37,690
gives more time on his plate.

382
00:37:37,810 --> 00:37:38,590
And then on the front end,

383
00:37:38,690 --> 00:37:39,970
the AI-generated videos,

384
00:37:40,110 --> 00:37:41,190
obviously opportunity costs,

385
00:37:41,310 --> 00:37:42,870
which you were the inspiration

386
00:37:42,870 --> 00:37:44,530
for pivoting that from a mobile app

387
00:37:44,530 --> 00:37:46,330
to a browser extension.

388
00:37:46,570 --> 00:37:48,750
We were able to build that in a month.

389
00:37:49,170 --> 00:37:51,670
And it's been fun implementing it

390
00:37:51,670 --> 00:37:52,890
in this business,

391
00:37:53,030 --> 00:37:55,570
but we're not providing AI products.

392
00:37:55,670 --> 00:37:57,450
We're leveraging it to make our media business

393
00:37:57,450 --> 00:37:59,730
and our investment platform

394
00:37:59,730 --> 00:38:01,950
more efficient.

395
00:38:02,370 --> 00:38:03,370
in many different ways.

396
00:38:03,510 --> 00:38:05,430
And I guess this gets to the question,

397
00:38:05,510 --> 00:38:06,930
like it seems pretty obvious to me

398
00:38:06,930 --> 00:38:11,770
that there seems to be an arms race in Silicon Valley

399
00:38:11,770 --> 00:38:16,170
and in tech more broadly to figure this out.

400
00:38:16,250 --> 00:38:18,130
And there's been billions, hundreds of billions,

401
00:38:18,450 --> 00:38:21,250
probably over a trillion dollars now at this point

402
00:38:21,250 --> 00:38:23,430
that's been thrown at the space.

403
00:38:23,590 --> 00:38:25,570
And even though you just described

404
00:38:25,570 --> 00:38:29,350
that the advantages for startups are massive,

405
00:38:29,690 --> 00:38:31,170
I find it hard to believe

406
00:38:31,170 --> 00:38:35,450
that a lot of that capital is not being misallocated and people haven't really clued in on

407
00:38:35,450 --> 00:38:39,550
what they should build specifically and how this is actually going to change.

408
00:38:41,010 --> 00:38:47,930
Yeah. I mean, I certainly think there's quite a bit of that. And so I could kind of share some

409
00:38:47,930 --> 00:38:53,350
examples that kind of pop, you know, are top of mind. Actually, maybe I'll save it for a little

410
00:38:53,350 --> 00:39:01,350
bit. So I think the first thing is, in many ways, I actually understand the rationale for why the

411
00:39:01,350 --> 00:39:11,830
money's sloshing around. And I think it's because the people that are pretty invested and are in the

412
00:39:11,830 --> 00:39:17,410
weeds, they kind of understand that things are going to change in a meaningful way. And for all

413
00:39:17,410 --> 00:39:21,650
the reasons I mentioned earlier, there will be a meaningful amount of disruption, in particular to

414
00:39:21,650 --> 00:39:27,870
these existing established businesses. And so I actually, I don't know if I,

415
00:39:28,870 --> 00:39:34,210
I understand the rationale for why investors and venture capitalists are plowing a bunch of money

416
00:39:34,210 --> 00:39:41,650
in space. So, you know, I'll give an example. And this is happening, I would argue, like,

417
00:39:41,670 --> 00:39:46,270
it seems like just everywhere, right? So you see it in the late stage where, you know,

418
00:39:46,270 --> 00:39:49,230
Open AI is valued at some large amount of money.

419
00:39:50,490 --> 00:39:51,530
Anthropic is raising.

420
00:39:51,950 --> 00:39:53,970
So you have that at the foundation model level.

421
00:39:54,510 --> 00:40:00,310
And that one feels honestly maybe a little bit, I don't know if I'd say riskier, but

422
00:40:00,310 --> 00:40:04,350
somebody is going to win and the revenues are scaling in a meaningful way.

423
00:40:04,810 --> 00:40:09,990
Profitability may be a different story, but the revenues are scaling massively.

424
00:40:09,990 --> 00:40:18,130
um and so it kind of makes its way throughout all stages of um the tech sector and so i'll give

425
00:40:18,130 --> 00:40:24,270
maybe my favorite example um so maybe a little bit of background before i do though um

426
00:40:24,270 --> 00:40:31,290
these startups that latch on right because there's so many people out there saying what is this ai

427
00:40:31,290 --> 00:40:39,890
thing um how do i use it like i've never seen any time in technology where you could just

428
00:40:39,890 --> 00:40:44,250
basically walk up to anybody on the street and you could have like a conversation and they're

429
00:40:44,250 --> 00:40:48,470
going to have like questions and thoughts and curiosity around AI. Like I've just, I've never

430
00:40:48,470 --> 00:40:53,830
seen that before. Like it's, it's like, it's very top of mind for a lot of people. Like, you know,

431
00:40:53,830 --> 00:40:58,210
I take my kids to the pool down the street and I'm like chatting with a neighbor about it. You know,

432
00:40:58,250 --> 00:41:03,370
it's like, it's just, it's everywhere. And so because there's so much attention there,

433
00:41:03,370 --> 00:41:12,310
you have these startups that come out of nowhere and like scale like super fast so i think notable

434
00:41:12,310 --> 00:41:18,190
examples are like you know products like lovable or cursor if you're a developer there's kind of

435
00:41:18,190 --> 00:41:23,830
these stories right where it's like hey we went from zero to 100 million in annual revenue in like

436
00:41:23,830 --> 00:41:33,410
eight months. And it's like, no one's ever seen that before, ever. And so some of that's maybe

437
00:41:33,410 --> 00:41:40,750
because of the fiat debasement. But people have never seen that before. And so what that means is

438
00:41:40,750 --> 00:41:46,690
if you're a venture capitalist that is in the business of identifying one out of 10, one out of

439
00:41:46,690 --> 00:41:55,930
20 companies where you think it could be a home run, your spreadsheets, you can make your

440
00:41:55,930 --> 00:42:01,490
spreadsheets make sense if that one business, instead of scaling to $50 million in annual

441
00:42:01,490 --> 00:42:05,350
revenue, scales to $150 million in the same amount of time.

442
00:42:06,290 --> 00:42:09,070
So the spreadsheet math, I think, actually kind of makes sense.

443
00:42:10,070 --> 00:42:16,630
So what they do is you have these bigger funds that have a billion dollars that they have

444
00:42:16,630 --> 00:42:22,670
to deploy, they'll still write checks into the open AIs of the world. And that's like,

445
00:42:22,670 --> 00:42:27,790
stroke $100 million check or whatever. But they're also getting involved in the earlier stages too.

446
00:42:29,150 --> 00:42:36,670
And so it creates, it kind of reminds me of the COVID era. I dare say hysteria,

447
00:42:37,350 --> 00:42:43,990
where early stage businesses that had traction, people were ripping massive checks into these.

448
00:42:43,990 --> 00:43:03,450
And so I heard from one of my existing investors that a startup that graduated, this is not a rare occurrence, but a startup that graduates from the last Y Combinator batch, which is a big, really well-known accelerator that fetches a premium for the startups that go through it.

449
00:43:03,450 --> 00:43:13,050
It's like she was saying, oh, yeah, like, you know, this individual like raised at a forty five million dollar valuation after like three weeks of work.

450
00:43:13,770 --> 00:43:19,170
Like barely had a product that was raising at like a forty five million dollar valuation.

451
00:43:19,670 --> 00:43:26,290
And like I have friends that have raised at 50, 60 and like some of them didn't even have any paid customers.

452
00:43:27,430 --> 00:43:29,910
So like there is a level of froth in the market.

453
00:43:29,910 --> 00:43:34,950
um so what that means is if you're an early stage founder you kind of need to know like

454
00:43:34,950 --> 00:43:42,370
hey the model is nine out of ten of us are gonna fail one out of ten of us is gonna make it work

455
00:43:42,370 --> 00:43:46,970
and that will return the fund for the venture capitalists and that's the way that the game

456
00:43:46,970 --> 00:43:55,510
is played and if you don't like it don't raise vc um but i actually think that the money is

457
00:43:55,510 --> 00:44:03,910
in some instances probably not being allocated well, but I understand the rationale. I do.

458
00:44:04,430 --> 00:44:10,570
I will say the thing that irks me is, and once again, I kind of understand this logic as well,

459
00:44:10,650 --> 00:44:18,010
but I think it's kind of maybe a sleight of hand, is you have these startups. I think Cursor might

460
00:44:18,010 --> 00:44:24,470
be one of them. Not hating on Cursor because I think they built a good product, but they basically,

461
00:44:24,470 --> 00:44:29,590
it's a land grab. So they're competing with, you know, Cloud Code and Cursor and all these other,

462
00:44:29,870 --> 00:44:35,790
all these other like code tools. So what Cursor does is they give away a bunch of credits.

463
00:44:36,350 --> 00:44:40,710
So you sign up and they're like, here's $200 in free AI credits to use

464
00:44:40,710 --> 00:44:45,670
so that you can get up and running. It's a great idea, right? Because people

465
00:44:45,670 --> 00:44:52,170
use those credits when they're writing code and then they learn to like your product and they

466
00:44:52,170 --> 00:44:55,850
learn how it works, and then they're less likely to go try the other product down the street.

467
00:44:56,530 --> 00:45:00,370
Well, what happens is maybe if you're a cursor, and I don't know the numbers, so I'm just

468
00:45:00,370 --> 00:45:05,810
using hypothetical examples, you might be doing $100, $150 million in annual revenue,

469
00:45:06,130 --> 00:45:12,590
but you might be spending $50 of that, $75 of it, on literally your open AI bill.

470
00:45:14,530 --> 00:45:18,250
So in the old world, software margins might have been like 80%, 90%.

471
00:45:18,250 --> 00:45:28,170
In the new world, in land grab mode, you might actually have a negative – you may actually be losing money.

472
00:45:30,750 --> 00:45:34,690
And so in the old world, they would still kind of do this with sales and marketing and other things.

473
00:45:34,690 --> 00:45:45,230
But I've never seen this maneuver that I'm seeing now where you're basically just paying the anthropics and the open AIs of the world this monster bill.

474
00:45:46,490 --> 00:45:47,710
And that's top-line revenue.

475
00:45:48,250 --> 00:45:51,550
But you're paying massive infracosts.

476
00:45:52,010 --> 00:46:03,105
Coming in the front door going right out the back door Yeah So everybody goes oh my gosh they killing it My startup is not nearly like and sure maybe your startup isn actually that successful

477
00:46:03,105 --> 00:46:03,345
Sure.

478
00:46:03,685 --> 00:46:12,205
But what they're doing is they're kind of more like a 50 million AR business, not 100 million AR business when you think about it.

479
00:46:12,525 --> 00:46:13,865
But top line is top line.

480
00:46:14,045 --> 00:46:15,145
So I get it.

481
00:46:15,185 --> 00:46:17,945
Once again, I understand why they're doing it.

482
00:46:18,025 --> 00:46:19,005
It's a competitive space.

483
00:46:19,005 --> 00:46:24,925
But these are some of the shenanigans that are currently happening in the market.

484
00:46:26,125 --> 00:46:42,325
Yeah, on the topic of hysteria, it is crazy how quickly people develop amnesia, like both on the investor side, but on the founder side, too, because like raising at insane valuations puts a lot of pressure on you and sort of handcuffs you in the future if you don't get the traction that was expected of you.

485
00:46:42,325 --> 00:46:56,985
Yeah. And I think a lot of founders will basically, you know, a lot of founders look at it and say, you know, when I take a VC check, this is the path that I am signing up for.

486
00:46:58,125 --> 00:47:08,105
Right. Some decide, you know, maybe part of the way through, you know, if they don't have the revenue and the traction, it's like switch to profitability, you know, make the business profitable.

487
00:47:08,105 --> 00:47:12,705
you know it's not going to grow as fast um it's not going to return the fund like the like the

488
00:47:12,705 --> 00:47:18,065
vcs want but it is um but you still at the end of the day have a business that employs people and

489
00:47:18,065 --> 00:47:23,165
you're still delivering our product into the world you know um so which is you know no shame on that

490
00:47:23,165 --> 00:47:28,585
but but when you get on the treadmill you need to know you're getting on the treadmill yeah i mean

491
00:47:28,585 --> 00:47:36,305
on that topic of bringing a product to the world how what effect is ai going to have on what products

492
00:47:36,305 --> 00:47:42,865
look like moving forward like to my point earlier like not only does it seem like vcs are

493
00:47:42,865 --> 00:47:47,425
in this arms race and pouring a bunch of capital and a lot of that's being misallocated

494
00:47:47,425 --> 00:47:52,445
just because of just nature of spray and pray but then on the execution of the startups like do you

495
00:47:52,445 --> 00:47:57,385
how many startups out there do you think have like the right idea of how to implement

496
00:47:57,385 --> 00:48:05,605
ai and bring ai products with new ux new ui to market does that make sense yeah definitely so

497
00:48:05,605 --> 00:48:08,745
So this is a really good question.

498
00:48:10,285 --> 00:48:17,245
I think maybe the – I think all of us are honestly figuring it out as we go.

499
00:48:18,465 --> 00:48:25,125
There are certain patterns that have been, we'll call it, proven in some ways to work.

500
00:48:26,205 --> 00:48:35,425
So this idea of AI being a chat-like experience, it's like for certain jobs to be done, for certain use cases,

501
00:48:35,425 --> 00:48:39,465
That's a great way of interacting with AI.

502
00:48:40,125 --> 00:48:44,605
I think we're going to see a lot of different approaches in the future.

503
00:48:45,585 --> 00:48:53,885
And I actually think a meaningful, feels like almost 50% of the innovation is actually undesigned.

504
00:48:55,365 --> 00:49:00,945
And so a startup, when they hire a product designer, somebody who helps build out the UX,

505
00:49:00,945 --> 00:49:05,285
I mean, we just went through a hiring process.

506
00:49:05,505 --> 00:49:07,325
We brought on a product designer a few weeks ago.

507
00:49:07,425 --> 00:49:07,945
She's amazing.

508
00:49:09,965 --> 00:49:18,085
But there's a lot of people that have an old world view, and they haven't spent time playing

509
00:49:18,085 --> 00:49:18,865
around with products.

510
00:49:18,965 --> 00:49:21,285
They haven't spent time learning AI for themselves.

511
00:49:21,905 --> 00:49:26,845
So you'd be able to kind of understand, at the end of the day, I'm building a user experience

512
00:49:26,845 --> 00:49:34,045
that sits on top of this core piece of technology that has certain things that it needs to function,

513
00:49:35,145 --> 00:49:39,165
a lot of designers in particular just haven't spent the time.

514
00:49:40,425 --> 00:49:45,305
But the ones that do, I think, will really kind of pave some interesting paths.

515
00:49:46,045 --> 00:49:53,705
And so I think the thing that I, and I'll kind of maybe present a high-level way of thinking about this,

516
00:49:53,705 --> 00:49:58,905
but I mentioned earlier that these agents are kind of like little digital employees.

517
00:49:59,845 --> 00:50:05,765
Well, if that is true, right, or even remotely close to true, the user experience may actually

518
00:50:05,765 --> 00:50:12,365
need to end up feeling a bit more like you are working with like a coworker, right?

519
00:50:13,165 --> 00:50:17,165
Maybe these agents, this sounds so cheesy and I can't believe I'm saying it, but like

520
00:50:17,165 --> 00:50:23,425
maybe these little agents need to have little cheesy names, right? Maybe you need to be able

521
00:50:23,425 --> 00:50:29,385
to like tag that, the name of that agent, like you tag them when you're like, you know, using Slack or

522
00:50:29,385 --> 00:50:37,145
Microsoft Teams, right? And so, you know, and like, how do these agents or little employees interact

523
00:50:37,145 --> 00:50:42,205
with each other? Like, when do they hand off data from one thing to the next? Like, let's make sure

524
00:50:42,205 --> 00:50:50,205
that this agent has enough information in its digital brain. And like, if one agent has different

525
00:50:50,205 --> 00:50:56,785
information and another agent has another set of information and they aren't sharing well then you

526
00:50:56,785 --> 00:51:01,585
run into these issues and then there's also this concept of like oh maybe an age like maybe there's

527
00:51:01,585 --> 00:51:08,785
a boss agent too right that kind of like is scanning right it's like are these things working

528
00:51:08,785 --> 00:51:15,105
like maybe you need like little one-on-ones with your with your little with your little

529
00:51:15,105 --> 00:51:21,745
employees like oh let's check in see how they're doing so anyway the reason why i bring this up is

530
00:51:21,745 --> 00:51:26,465
because that's kind of like those are almost like lego building blocks right but there's like these

531
00:51:26,465 --> 00:51:30,125
user experiences on top of that will that will need to be built i just i'm like it's kind of

532
00:51:30,125 --> 00:51:34,545
look different and so that's why to get back to the original comment that i made um i think we're

533
00:51:34,545 --> 00:51:41,685
all just trying to figure this out what have you seen that's been have you seen like a oh

534
00:51:41,685 --> 00:51:52,285
these guys are doing it right this makes sense ux yeah you know i think some of my favorite tools

535
00:51:52,285 --> 00:51:57,265
that i like playing around with are you know uh replit replit's pretty great i'm a big fan of

536
00:51:57,265 --> 00:52:06,345
replit um i like uh v0 which is another similar tool um i've been really having quite a bit of fun

537
00:52:06,345 --> 00:52:09,985
with cloud code but that's more for like a developer like experience because it kind of

538
00:52:09,985 --> 00:52:18,405
sits in your terminal. Honestly, I feel like the number of products that do it poorly is

539
00:52:18,405 --> 00:52:23,965
significantly higher than the ones that do it well. I'm trying to think of this. There's this

540
00:52:23,965 --> 00:52:28,705
one product that I used for a little bit. It was called Howie, and it was almost like this little

541
00:52:28,705 --> 00:52:34,165
meeting assistant, but it would interact only through email. So it's almost like Calendly,

542
00:52:34,165 --> 00:52:37,325
if you've ever used that before, but it was like, there was no user interface.

543
00:52:38,425 --> 00:52:42,865
Right. So I think we'll see more of that, but honestly, like I, I,

544
00:52:42,985 --> 00:52:46,725
I'm constantly trying new tools just because I, I feel like once again,

545
00:52:46,725 --> 00:52:47,945
we're all trying to figure this out.

546
00:52:49,305 --> 00:52:55,185
Yeah. What, um, how do you approach UX UI formable?

547
00:52:56,785 --> 00:53:00,705
I think we, we definitely lean on, uh, the concept of,

548
00:53:00,965 --> 00:53:03,405
so there's a few things that we, that we talk a lot about.

549
00:53:03,405 --> 00:53:08,765
One is this concept of a primitive, or it's like a building block. In the world of, we'll call it

550
00:53:08,765 --> 00:53:15,345
marketing, if you're trying to collect leads and get back to them, you may have a form,

551
00:53:15,585 --> 00:53:19,565
and that's a primitive. You may need to send an email. That's another primitive.

552
00:53:20,745 --> 00:53:27,365
These Lego building blocks, so to speak, that you need to construct together. I'm of the opinion that

553
00:53:27,365 --> 00:53:32,125
all of those primitives, there's an old world primitive, and then there's a new world primitive.

554
00:53:32,125 --> 00:53:40,785
The new world primitive is like, they're still probably called the same thing, but they are actually an agent.

555
00:53:41,185 --> 00:53:49,765
So like the product that we're working on, the initial product, it literally looks like a multi-step form, like if you've ever used type form before.

556
00:53:51,045 --> 00:53:55,705
And so you fill it out almost like you're filling out a form, but it's actually an agent behind the scenes.

557
00:53:56,705 --> 00:54:04,305
And so because it's an agent, it is literally as you're filling it out, it's like it's kind of reasoning on the fly about what should we do.

558
00:54:04,765 --> 00:54:09,385
Right. So someone enters their email. We're like, hey, we can enrich that information.

559
00:54:09,865 --> 00:54:13,545
Right. So we can figure out a little bit more about you. You fill it out.

560
00:54:13,605 --> 00:54:16,245
Maybe we show you questions and we don't show you other questions.

561
00:54:16,245 --> 00:54:23,185
And then at the end, we can actually have like another agent that goes, is there anything else that we need to ask?

562
00:54:23,185 --> 00:54:27,585
It's like, oh, yeah, there might actually be because you have gave us this job that we need to do.

563
00:54:27,805 --> 00:54:31,825
So at the end, it might ask you a couple final follow up optional questions.

564
00:54:32,125 --> 00:54:36,765
So as a result, if you're a business, you're able to collect this really rich information.

565
00:54:37,525 --> 00:54:41,825
And then you can feed that really rich information into like your follow up email.

566
00:54:41,965 --> 00:54:49,765
So your follow up email is way more personalized because you were able to collect this like amount of information that helps you deliver a super personalized email.

567
00:54:50,445 --> 00:54:52,805
And so we talk a lot about these primitives to get back to my point.

568
00:54:53,185 --> 00:55:10,685
And these primitives are actually kind of like agents. So instead of trying to convince the world that you should be using agents, we're like, no, no, no, there's an existing pattern. There's forms, there's emails, there's these things. And we're infusing them with AI and rebuilding them as an agent first.

569
00:55:10,685 --> 00:55:32,525
So you still think about your world through this lens of these existing Lego building blocks that you're used to. So that kind of constructs things. But then you have this kind of coordination that needs to happen, like this intelligence layer above those primitives, where maybe you have a world where in the future, I can describe the funnel that I'm trying to build.

570
00:55:32,525 --> 00:55:37,025
Hey, I want to collect leads and I want to get back to them really quickly.

571
00:55:37,625 --> 00:55:43,345
And then I want to enroll them in some type of drip sequence where they get an email three days later and five days later.

572
00:55:44,505 --> 00:55:52,685
And an agent should be able to construct those different primitives or building blocks, put them all together, connect them all, and you don't have to do it yourself.

573
00:55:53,685 --> 00:56:01,625
Even better, there could be another agent or another piece of your code, we'll call it, that has knowledge about your business.

574
00:56:02,225 --> 00:56:03,305
Maybe it scraped your website.

575
00:56:04,185 --> 00:56:06,505
And it understands your pricing and packaging.

576
00:56:06,705 --> 00:56:08,505
It understands the tone of voice that you're trying to use.

577
00:56:08,545 --> 00:56:10,685
It understands these things about your business.

578
00:56:10,985 --> 00:56:15,725
And it literally gives that information to every single one of those little agents.

579
00:56:16,345 --> 00:56:19,145
So all of a sudden, your emails are smarter because it knows about your business.

580
00:56:19,145 --> 00:56:23,925
Your forms are smarter because it knows about the job that you're trying to do, but also it knows about your business.

581
00:56:23,925 --> 00:56:35,625
And so there's this intelligence layer on top of these primitives that we believe will be really transformational when it comes to assembling the Lego building blocks.

582
00:56:36,225 --> 00:56:43,025
And then there's almost like another level where you'll have another thing that sits above it, and it will analyze everything.

583
00:56:43,445 --> 00:56:47,365
It'll analyze your entire marketing funnel and go, hey, there's drop-off rates here.

584
00:56:47,705 --> 00:56:48,805
There's drop-off rates here.

585
00:56:48,945 --> 00:56:50,565
You're not converting as well as you could be.

586
00:56:50,905 --> 00:56:52,145
Would you like us to make some changes?

587
00:56:52,445 --> 00:56:53,725
Like, heck yeah, of course.

588
00:56:53,925 --> 00:57:01,185
click, right? It applies to change. I don't need to go in and click 18 buttons over and over again.

589
00:57:02,245 --> 00:57:06,285
And so it's like, I honestly don't know exactly what the user experience for that looks like,

590
00:57:06,545 --> 00:57:11,265
but I feel like I have at least, you know, maybe I'm being foolish, but I feel like I kind of have

591
00:57:11,265 --> 00:57:17,605
an idea about what the world will look like in the future. And it's, instead of humans being like

592
00:57:17,605 --> 00:57:21,345
the first thing that you plug in to solve a problem, it's going to be these little digital

593
00:57:21,345 --> 00:57:33,585
employees. Unless you need that extra, unless the variance in the task is too high. And sometimes

594
00:57:33,585 --> 00:57:37,205
you'll send a person in to learn more about it so that you can then build an agent to put it in

595
00:57:37,205 --> 00:57:44,685
there instead. So it's almost like people are gap-filling the work of the agents instead of

596
00:57:44,685 --> 00:57:51,185
agents gap-filling the work of the humans. But right now, it's like human plus agent or human

597
00:57:51,185 --> 00:57:57,405
plus AI. And I'm like, no, no, no. It's AI plus human. Yeah. No, it's got me thinking.

598
00:57:58,025 --> 00:58:05,205
I was just like thinking about how I could use this at TFTC. Just one, just thinking of

599
00:58:05,205 --> 00:58:08,105
a meeting I had earlier this morning. One of our goals is

600
00:58:08,105 --> 00:58:14,865
newsletter has been word of mouth. I haven't really spent any time like focusing on building

601
00:58:14,865 --> 00:58:19,605
that funnel and pushing people towards that. We've put a little bit more effort into it

602
00:58:19,605 --> 00:58:28,385
in recent months with like a read at the end of a of a podcast or whatever but like we can make the

603
00:58:28,385 --> 00:58:33,485
newsletter experience number one much bigger by actually trying to grow it and then number two

604
00:58:33,485 --> 00:58:39,505
much more hopefully insightful by if we had a forum where people were getting onboarded to sign

605
00:58:39,505 --> 00:58:42,945
up for the newsletter like what interests you most about bitcoin what topics do you

606
00:58:42,945 --> 00:58:48,705
are you most interested if you've been reading like what topics that we cover

607
00:58:48,705 --> 00:58:52,205
make you the happiest. I'm just thinking of examples here.

608
00:58:52,945 --> 00:58:56,325
That's something, if we could use your tool to implement that, I don't have to hire

609
00:58:56,325 --> 00:59:00,165
a marketing expert, per se, to build these funnels.

610
00:59:00,165 --> 00:59:04,085
Formable could do it for us. As I'm thinking through that,

611
00:59:04,185 --> 00:59:08,265
it's like, okay, me as a business owner, that really empowers me and allows me

612
00:59:08,265 --> 00:59:11,945
to do things for cheaper and hopefully increase our audience

613
00:59:11,945 --> 00:59:15,445
and ultimately revenues here at the media business.

614
00:59:15,445 --> 00:59:18,685
and I like to think I have agency

615
00:59:18,685 --> 00:59:20,865
and we're trying to lean into these tools

616
00:59:20,865 --> 00:59:21,945
so it would be good for our business.

617
00:59:22,225 --> 00:59:24,085
The broader question I'm getting at is

618
00:59:24,085 --> 00:59:30,425
is this AI revolution truly a 10,000 flowers will bloom situation

619
00:59:30,425 --> 00:59:33,065
or are you going to have a crazy, not even Pareto,

620
00:59:33,265 --> 00:59:37,065
but crazy distribution of companies that exist and succeed

621
00:59:37,065 --> 00:59:40,245
versus those that simply don't exist?

622
00:59:40,945 --> 00:59:43,605
What's the nature of working going to be like?

623
00:59:45,445 --> 00:59:49,005
I think my short answer is it's almost like chaos is a ladder.

624
00:59:50,685 --> 00:59:54,225
We would sometimes, my co-founder and I would say this a decent amount.

625
00:59:54,345 --> 00:59:55,285
Chaos is a ladder.

626
00:59:55,385 --> 00:59:56,605
It's an opportunity, right?

627
00:59:57,025 --> 00:59:59,265
I think there's the first part, which is chaos.

628
00:59:59,265 --> 01:00:01,345
And I'm like, yeah, that's going to happen.

629
01:00:03,025 --> 01:00:06,545
You see it in every other part of our world, right?

630
01:00:06,805 --> 01:00:09,305
Just like total nonsensical.

631
01:00:10,725 --> 01:00:14,145
You read the news and you're just like, I can't believe.

632
01:00:14,145 --> 01:00:28,705
If it was maybe a few years ago, I never would have believed it. But now it's like, this is normal. This is pure chaos. And so I think that in some ways it will apply here as well.

633
01:00:28,705 --> 01:00:38,445
right and so you know but but with that chaos there is opportunity um and

634
01:00:38,445 --> 01:00:47,745
i think i am of the opinion and i try to be an optimist um you know i try to be realistic about

635
01:00:47,745 --> 01:00:53,425
the situation at hand but i i tend to you know envision a bright and interesting future i think

636
01:00:53,425 --> 01:01:00,025
I just like to follow. I love to tinker. I love to try things. I love to learn new things. And so

637
01:01:00,025 --> 01:01:10,845
I think, yeah, being an optimist is kind of part of that job, right? But also, there is a reality

638
01:01:10,845 --> 01:01:16,605
that things are going to look very different. And I don't necessarily think that changed

639
01:01:16,632 --> 01:01:25,992
will happen all at once, gradually, then suddenly. Or actually, I think it'll be maybe a little bit

640
01:01:25,992 --> 01:01:31,652
more of a gradual change. Because those bigger businesses that are sitting on their hands right

641
01:01:31,652 --> 01:01:36,192
now, they won't lose all of their revenue overnight, but it'll just kind of go,

642
01:01:36,332 --> 01:01:44,852
right? It'll be this gradual decline, unless you're Chegg. And then if you do quizzes,

643
01:01:44,852 --> 01:01:54,192
online quizzes, you're totally cooked, right? So, yeah, where am I going with this?

644
01:01:55,872 --> 01:02:00,392
So I think like, here's what I would encourage you, like forever, whoever who's still listening

645
01:02:00,392 --> 01:02:06,272
to my diatribes, the way that I would encourage you all to think about it is maybe keep two things

646
01:02:06,272 --> 01:02:15,372
in mind. One is that these AI companies in particular are honestly in the business of

647
01:02:15,372 --> 01:02:23,172
narrative. They're in the narrative business. A year and a half ago, it was like, AGI is here.

648
01:02:25,552 --> 01:02:29,412
That's wonderful if you're going out and trying to raise a mountain of cash.

649
01:02:29,412 --> 01:02:35,092
right it's like that's a great that's a great idea say agi is near

650
01:02:35,092 --> 01:02:48,112
um turns out yeah two weeks until agi right um and so on one hand they will hype this

651
01:02:48,112 --> 01:02:53,392
right they will hype it and then there are moments where you actually i feel like you

652
01:02:53,392 --> 01:02:59,972
see their true colors where they will like in other areas undersell it so it's almost like they're

653
01:02:59,972 --> 01:03:06,592
kind of uh uh like they they it's almost like i can't parse these companies because one minute

654
01:03:06,592 --> 01:03:11,172
they're saying agi is near and then the next minute they're like kind of almost like walking

655
01:03:11,172 --> 01:03:15,612
that back and it's like why is that right and i think that there's like two things that are true

656
01:03:15,612 --> 01:03:21,152
right one is like obviously i was changing the game um i think that agi is not near unless you're

657
01:03:21,152 --> 01:03:27,852
fundraising. But on the other end, there is meaningful disruption that will take place

658
01:03:27,852 --> 01:03:35,252
that they are not going to tell you about. And so that organization that maybe had, I mean,

659
01:03:35,352 --> 01:03:41,752
this is happening in customer support right now, for sure. You have these chatbot products that

660
01:03:41,752 --> 01:03:46,372
have come out that are way better at answering questions than people. Because once again,

661
01:03:46,372 --> 01:03:50,632
they have knowledge about the business and they can hold it in their little digital brains way

662
01:03:50,632 --> 01:03:57,812
better than a human can. And so as a result, it's like customer support is one of the first things

663
01:03:57,812 --> 01:04:03,092
that's just going to be roasted by AI. And we're seeing it like there, but you don't see a lot of

664
01:04:03,092 --> 01:04:10,092
it in the news. You will see more of it. And that's like a huge amount of, you know, there's

665
01:04:10,092 --> 01:04:15,332
a lot of people that are employed in customer support. Like there are a lot of people that are

666
01:04:15,332 --> 01:04:22,432
out in, you know, rural America that work at a remote customer support job. Well, you know,

667
01:04:22,452 --> 01:04:27,892
maybe there's fear because of outsourcing, but, um, well, like, you know, and, and they're,

668
01:04:28,072 --> 01:04:32,412
you know, they're working this job and they're for most part, you know, happy with the situation

669
01:04:32,412 --> 01:04:36,832
that they're in. It's like AI comes in, bang. It's almost like, uh, uh, growing up in Maine,

670
01:04:36,932 --> 01:04:43,692
we had these, uh, mill towns, right? So you had these paper mills, um, and, uh, you had these

671
01:04:43,692 --> 01:04:52,352
paper mills and they started outsourcing everything. And my grandfather, he would haul lumber and he

672
01:04:52,352 --> 01:04:59,792
would haul wood chips to these paper mills. And I remember being five, six years old and him

673
01:04:59,792 --> 01:05:04,732
complaining about outsourcing happening. I would go on trips with him in his tractor trailer truck.

674
01:05:04,992 --> 01:05:11,492
I would be in the back, take naps, and then he would take lumber from Maine, drive it across

675
01:05:11,492 --> 01:05:15,532
into Canada, they would process and he'd bring a load back. And it infuriated

676
01:05:15,532 --> 01:05:19,572
him. And he would constantly talk

677
01:05:19,572 --> 01:05:23,332
about it with my dad. And so I think

678
01:05:23,332 --> 01:05:27,572
there's going to be some element of that that happens, but it's going to happen

679
01:05:27,572 --> 01:05:31,552
in white-collar work, which is kind of

680
01:05:31,552 --> 01:05:32,392
wild to think about.

681
01:05:34,292 --> 01:05:36,272
It's wild to think about because

682
01:05:36,272 --> 01:05:47,532
I mean, there are, I mean, I think an overwhelming majority of people in these white collar jobs are asleep at the wheel when it comes to this stuff.

683
01:05:47,712 --> 01:05:52,552
I think they're, I don't know, but it's definitely a form of cognitive dissonance where they don't want to believe.

684
01:05:52,552 --> 01:05:59,992
And especially for white collar workers around our age, millennials who've struggled enough to get to where they are.

685
01:06:01,732 --> 01:06:04,672
It's pop culture or popular culture right now.

686
01:06:04,672 --> 01:06:06,672
It's like the millennial trajectory.

687
01:06:06,852 --> 01:06:10,892
You go to school, you get a degree, you get a good high school, good college, right?

688
01:06:10,972 --> 01:06:12,152
Major, get a degree.

689
01:06:12,352 --> 01:06:14,512
And then that doesn't panned out well.

690
01:06:15,152 --> 01:06:23,972
A lot of the people who hasn't panned out as well as they expected are in these white collar jobs already not very happy with their position in life.

691
01:06:24,572 --> 01:06:26,952
And about to get a double whammy with this.

692
01:06:27,472 --> 01:06:28,412
I'll give you another example.

693
01:06:28,412 --> 01:06:35,132
um so um there's this guy that i follow on the internet and he basically built um i don't know

694
01:06:35,132 --> 01:06:42,752
exactly how he built it but imagine like if ai was in excel right so imagine all these uh financial

695
01:06:42,752 --> 01:06:49,512
analysts that are really good at writing i don't know i hate excel but like macros i guess yeah

696
01:06:49,512 --> 01:06:57,652
yeah v lookups macros whatever right it's like he built this tool and it's like

697
01:06:57,652 --> 01:07:01,652
the people that are using it are freaking out because it's like the analyst jobs.

698
01:07:03,872 --> 01:07:10,832
And so it's not only happening to like, you know, the low end, it's like, you know,

699
01:07:11,552 --> 01:07:14,612
somebody who works at like, I don't know, Goldman Sachs or whatever, you know,

700
01:07:14,612 --> 01:07:18,532
some financial business that I'm unaware of, right? It's like, analyst, bye.

701
01:07:18,532 --> 01:07:28,372
um and so you know and right now we don't see the i don't you know like because the models are

702
01:07:28,372 --> 01:07:35,312
not perfect not everything can be solved by ai obviously and i think that even in the future

703
01:07:35,312 --> 01:07:40,292
like not everything will be solved with ai but once again if you think about it ai first then

704
01:07:40,292 --> 01:07:49,792
human it just like the the amount of labor when you go from human first then ai to ai then human

705
01:07:49,792 --> 01:07:55,312
it's like there's going to be a meaningful delta and so i really think you know i'm an optimist

706
01:07:55,312 --> 01:08:01,992
and i am optimistic on the future and i'm a technologist for a reason um but that doesn't

707
01:08:01,992 --> 01:08:08,872
mean that there isn't some type of short-term chaos yeah but moving on from the cast to the

708
01:08:08,872 --> 01:08:14,412
the optimism like for teams out there that are building like it's incredibly powerful it's

709
01:08:14,412 --> 01:08:19,392
exciting it's fun we're having a ton of fun at tftc implementing the stuff and working on

710
01:08:19,392 --> 01:08:25,112
particularly the videos it's um it's been something that we've really been somewhat

711
01:08:25,112 --> 01:08:29,992
addicted to over the last three months and it's just getting better and easier for us as we

712
01:08:29,992 --> 01:08:36,392
get the process down and the reception is still pretty pretty remarkable once we get it out there

713
01:08:36,392 --> 01:08:48,152
I was watching one earlier today and I'm going to follow up with you after and be like, tell me your secrets because I haven't spent much time here, but I'm just like absolutely loving it.

714
01:08:48,192 --> 01:08:53,772
I think you guys had one video to get like 20,000 retweets or something crazy like that.

715
01:08:54,432 --> 01:08:59,872
Yeah, I think the 19 – going off the gold standard one, that was the most popular so far.

716
01:09:01,372 --> 01:09:01,812
Amazing.

717
01:09:02,252 --> 01:09:04,192
And it was such a great video.

718
01:09:04,192 --> 01:09:06,532
Obviously, it's like, oh, it's a little AI generated in there.

719
01:09:06,752 --> 01:09:08,712
But it was like the storytelling was amazing.

720
01:09:09,232 --> 01:09:09,412
Yeah.

721
01:09:09,652 --> 01:09:15,192
I think that's what we phoned in on is just using it to tell stories and really storyboarding.

722
01:09:15,192 --> 01:09:18,592
That's what most of the time is generating.

723
01:09:18,772 --> 01:09:20,252
You have to iterate through the generations.

724
01:09:20,972 --> 01:09:22,532
And thank God I don't have to do that.

725
01:09:22,692 --> 01:09:26,492
That's Trevor Elijah's job to do that.

726
01:09:26,592 --> 01:09:33,172
And I think they definitely have moments where they're beating their head on the table because the generation isn't what they need.

727
01:09:33,172 --> 01:09:35,932
But once the end product's there, it's like, holy crap.

728
01:09:36,032 --> 01:09:40,872
A lot of our time spent on storyboarding and deciding what story to tell, which is fun.

729
01:09:42,132 --> 01:09:50,912
I like to think I'm somewhat of a creative person, but I've never been able to manifest that outside of conversations and writing.

730
01:09:50,912 --> 01:09:55,652
I love movies and I like art, but I can't draw.

731
01:09:56,012 --> 01:10:00,152
I can't produce a movie, but now we can sort of start that process with AI.

732
01:10:00,152 --> 01:10:16,132
I mean one of my favorite things to do and this is such an easy example right is I have a bunch of kids right I have four kids seven and under And you know one of the favorite activities is to do coloring pages And it like I will

733
01:10:16,132 --> 01:10:21,052
generate coloring pages for the kids, right? And so I'll ask them, what do you want? And like,

734
01:10:21,092 --> 01:10:27,092
I want a princess riding a pony, jumping over this thing. And it's like, it gets really wild

735
01:10:27,092 --> 01:10:31,132
really quickly. It's like, it generates it. I print it off. I give it to them. And they're like

736
01:10:31,132 --> 01:10:38,332
coloring they're having a great time yeah and we have um we've been uh in the car ride we've been

737
01:10:38,332 --> 01:10:45,292
using chat gbt voice we named our gbt daryl and uh if the kids the boys ever have a question in

738
01:10:45,292 --> 01:10:50,232
the back of the car we just pop daryl open give them the context hey daryl yes we've got a five

739
01:10:50,232 --> 01:10:56,512
and a three-year-old here they're very curious and they're looking to learn and um my my oldest

740
01:10:56,512 --> 01:11:00,752
son two weeks ago we were playing with daryl he's like how long does it take to count to 100

741
01:11:00,752 --> 01:11:02,812
Trillion Daddy. And I was like, I don't know, let's ask Daryl.

742
01:11:03,112 --> 01:11:04,772
And the answer blew my mind. I was like, ah.

743
01:11:05,432 --> 01:11:06,752
But then it went from there. His cousin

744
01:11:06,752 --> 01:11:08,912
was in the car and similar to the

745
01:11:08,912 --> 01:11:10,692
coloring

746
01:11:10,692 --> 01:11:12,732
pages, we asked

747
01:11:12,732 --> 01:11:14,792
Daryl to craft a story for

748
01:11:14,792 --> 01:11:16,752
my oldest boy and his cousin

749
01:11:16,752 --> 01:11:18,792
who's a girl. Like a heroic story of them

750
01:11:18,792 --> 01:11:20,272
traveling through a forest and

751
01:11:20,272 --> 01:11:22,592
in 10 seconds had a five minute story.

752
01:11:22,892 --> 01:11:24,672
And his parents in the car was like,

753
01:11:24,732 --> 01:11:26,512
oh, we get five minutes of relative silence.

754
01:11:26,852 --> 01:11:28,532
And it was fun.

755
01:11:28,692 --> 01:11:30,652
And they were amazed. Like the fact that they were the

756
01:11:30,652 --> 01:11:39,152
main characters in the story it's like it's so much fun as you know i my son loves uh insects

757
01:11:39,152 --> 01:11:44,592
and so you'll turn on the little video mode and you'll like pull up an insect he comes in he's

758
01:11:44,592 --> 01:11:49,112
like got this thing on his you know on his arm or whatever what is it like i don't know let's find

759
01:11:49,112 --> 01:11:56,092
out right yeah and it's like untapped and that's actually one thing the uh the school my boys go to

760
01:11:56,092 --> 01:12:00,612
And now they actually I'm happy to see that they've put feelers out there to the parents.

761
01:12:00,612 --> 01:12:09,292
Like we're looking to before we're thinking on AI, we're putting together like an AI board or committee to help us implement it in the school.

762
01:12:09,372 --> 01:12:21,612
I'm like, thank God you're thinking about this because that's like the thing positively, optimistically, like the potential for this to really accelerate human knowledge is unbounded.

763
01:12:22,732 --> 01:12:23,892
Really, it really is.

764
01:12:23,972 --> 01:12:24,512
It really is.

765
01:12:24,512 --> 01:12:34,592
you almost have to like teach yourself when, um, like historically, you know, there would be

766
01:12:34,592 --> 01:12:40,572
these questions that I would have, or it'd be like, how do I do X? Right. Or is it possible to do X?

767
01:12:40,912 --> 01:12:48,572
Right. And before, if I were to Google it, right. It's like, I'm probably not going to get

768
01:12:48,572 --> 01:12:52,992
something interesting because it's such a like particular thing, unless it's, you know,

769
01:12:52,992 --> 01:12:58,172
how do I change my door or something, you know, like a lot of people search for, but usually it's

770
01:12:58,172 --> 01:13:04,292
like this kind of longer tail thing. Right. And, uh, and now it's just like, you almost have to

771
01:13:04,292 --> 01:13:12,172
teach yourself. I, I should just ask that question. Right. And, and then it will kind of prime my

772
01:13:12,172 --> 01:13:19,992
thinking with some ideas, which I can then use to dig deeper. And I see it with kids. I see it with

773
01:13:19,992 --> 01:13:25,832
myself, you know, it's like, is it possible to even build this into my product? Like, oh yeah,

774
01:13:25,832 --> 01:13:29,112
you could probably do it this way or that way or the other way. It's like, that's actually a great

775
01:13:29,112 --> 01:13:35,012
idea. I'm going to use that. Right. So you almost kind of have to have like a, there's a level of,

776
01:13:35,012 --> 01:13:39,792
you know, people would always say in, in for software engineers in particular, like you should

777
01:13:39,792 --> 01:13:44,872
go Google. Like if you ever have a question about code, go Google it. And then if you can't figure

778
01:13:44,872 --> 01:13:49,052
it out, come back and ask me. It's almost like we've kind of entered this phase where it's not

779
01:13:49,052 --> 01:13:54,112
just for software engineers anymore. It's like, you have a question, ask, you know, ask one of

780
01:13:54,112 --> 01:14:03,492
these AIs first to prime it. And then if you still can't figure it out, you know, go another level

781
01:14:03,492 --> 01:14:10,192
deeper. You know, someone who's homeschooled, the world has just will massively change in education

782
01:14:10,192 --> 01:14:17,872
as well. And we homeschool our children. And a lot of it was we were kind of teetering on like,

783
01:14:17,872 --> 01:14:22,432
Should we do maybe like some private schooling or something versus homeschooling?

784
01:14:23,012 --> 01:14:26,632
And at the time, I was playing around with AI and I was like, time out.

785
01:14:26,852 --> 01:14:28,852
No, we're homeschooling.

786
01:14:29,072 --> 01:14:34,332
Because when you have these superpowers in your hands, obviously, I don't want my kids

787
01:14:34,332 --> 01:14:37,452
to be playing around on screens all day.

788
01:14:38,372 --> 01:14:42,672
But if you selectively use it, it is a massive accelerant.

789
01:14:42,672 --> 01:14:47,232
And the homeschooler, at least the homeschooled parent, is always kind of trained or

790
01:14:47,232 --> 01:14:53,412
learns that the most important thing about homeschooling is the personalized instruction.

791
01:14:53,612 --> 01:14:56,532
And so if you apply that with AI, it's like it just makes it even more.

792
01:14:57,892 --> 01:14:59,732
You know, it's like personalization on steroids.

793
01:15:00,332 --> 01:15:03,852
Yeah, especially with the memory, with the agentic brain that exists.

794
01:15:04,212 --> 01:15:04,452
Yeah.

795
01:15:05,452 --> 01:15:06,752
And it is scary, too.

796
01:15:06,872 --> 01:15:09,032
It's like, how much information do we give these models?

797
01:15:09,032 --> 01:15:16,792
Like, can open source models and products like Maple get the parodies so you feel more comfortable doing all this?

798
01:15:16,792 --> 01:15:21,792
but that's why i think the big scary thing is uh is really around like the training

799
01:15:21,792 --> 01:15:30,592
you know it's like i if there's one area that i feel like some amount of maybe the free the free

800
01:15:30,592 --> 01:15:38,172
market maybe the free market figures it out um but the thing that i really think um should exist

801
01:15:38,172 --> 01:15:44,972
and should be transparent is you know they basically have these i guess i was listening to

802
01:15:44,972 --> 01:15:54,252
I think it was Sam Altman chatting about it, but they basically have these big documents that have these very maybe convoluted rules around like if this happens, don't be right.

803
01:15:54,312 --> 01:15:57,512
It's like it's kind of the teaching document for the foundation model.

804
01:15:58,232 --> 01:15:59,652
I want to know what that is.

805
01:16:00,912 --> 01:16:06,952
And I think we have – I think that those companies have a responsibility to tell us.

806
01:16:06,952 --> 01:16:17,672
because if anybody was concerned about social media censorship,

807
01:16:19,352 --> 01:16:22,372
this has the potential to be that on steroids.

808
01:16:23,652 --> 01:16:26,952
So publish, get that out in the open.

809
01:16:27,432 --> 01:16:28,872
I think that that makes sense.

810
01:16:29,412 --> 01:16:31,712
I think you can keep some of these other trade secrets, sure.

811
01:16:31,712 --> 01:16:35,732
But like that, we should know how the algorithm works.

812
01:16:36,552 --> 01:16:36,672
Yeah.

813
01:16:36,952 --> 01:16:46,452
I have a feeling that's going to be hard to get unless you have the free market come and somebody position themselves as we're going to be the company that does this and you should use us because of this.

814
01:16:47,792 --> 01:17:03,712
But tying this and the bow on the overarching conversation, like a lot of how we view a 1031 and me personally as a Bitcoin or businesses transforming is on the capital side, on the reserve asset side with Bitcoin.

815
01:17:03,712 --> 01:17:18,052
Like, let's just expand on how you view Bitcoin's role in not only business formation, but like how you run a business into the future, particularly if you're leveraging this unbounded leverage with AI.

816
01:17:18,872 --> 01:17:21,332
There's a lot of places that I could go.

817
01:17:21,452 --> 01:17:26,452
Maybe I'll start with the tech, maybe.

818
01:17:26,452 --> 01:17:35,672
um uh the first is like the idea of agents um exchanging some amount of currency between each

819
01:17:35,672 --> 01:17:41,852
other very quickly um i can see that happening i was never like super bullish on this idea of like

820
01:17:41,852 --> 01:17:48,712
i get i pay per amount of minute i consume like i was never a big fan of that but like with agents

821
01:17:48,712 --> 01:17:54,292
because like i think humans kind of are always like oh i'm paying more and i'm paying more and

822
01:17:54,292 --> 01:17:57,332
And there's a psychological roadblock, I think, to that model.

823
01:17:57,932 --> 01:18:00,412
Nick Zabo is the mental cost of microtransactions.

824
01:18:00,852 --> 01:18:01,412
Yeah, yeah.

825
01:18:01,452 --> 01:18:04,632
But when agents are doing it, they don't really care, right?

826
01:18:04,672 --> 01:18:09,272
Because they're not like – I think maybe they will care.

827
01:18:09,472 --> 01:18:09,772
I don't know.

828
01:18:10,252 --> 01:18:18,072
So I think that from a technological level, I think we can see more of that in the future or we will see more of that in the future.

829
01:18:18,072 --> 01:18:19,612
It feels like that's coming.

830
01:18:19,612 --> 01:18:24,132
and Stripe and all these other ones are doing it with different stablecoin rails and other things

831
01:18:24,132 --> 01:18:33,172
like that. I'm a big fan of these Bitcoin treasury companies. I think that they're

832
01:18:33,172 --> 01:18:41,292
Bitcoin treasury maxis. And so they recognize that there's an opportunity in the market. And so

833
01:18:41,292 --> 01:18:46,932
in some ways, the actual business is the sideshow to the main show. And the main show is

834
01:18:46,932 --> 01:18:50,852
like intelligent leverage, et cetera.

835
01:18:50,852 --> 01:18:52,732
MicroStrategy has done an amazing job there,

836
01:18:52,732 --> 01:19:09,412
and I a huge fan of what they done But I think most businesses will still maintain their normal business operations They won go public but any profitable business will have an opportunity to store their energy

837
01:19:09,412 --> 01:19:12,912
or store their capital in a way where it's not debased.

838
01:19:13,812 --> 01:19:16,452
And I think that that will be a wonderful thing for the world.

839
01:19:16,452 --> 01:19:22,592
I think that that will present new opportunities for startups amid their growth journey.

840
01:19:22,592 --> 01:19:29,952
So like one of my friends who I will not mention his name started a VC backed startup, grew it.

841
01:19:30,312 --> 01:19:36,592
I mean, the thing's profitable. And over the past few years, like he's accumulated a war chest.

842
01:19:37,692 --> 01:19:44,912
Like he's accumulated a lot of Bitcoin. And and it's like absolutely thrilling.

843
01:19:44,912 --> 01:19:48,072
And it's changed the way that he thinks about how he grows his business.

844
01:19:48,072 --> 01:19:59,232
So like in the past, you kind of you basically only had like maybe one option and it was let's throw money at trying to reignite that growth in a more meaningful way.

845
01:19:59,232 --> 01:20:25,872
But when you're able to store your capital in a better way, Bitcoin's a hurdle, right? Are you going to hire that super senior leader that wants a ton of money and may not work out? Or you could just shovel that into Bitcoin, shovel that extra profit into Bitcoin, and play the long game.

846
01:20:25,872 --> 01:20:29,372
I think that it's going to be a wonderful thing for businesses.

847
01:20:30,372 --> 01:20:33,972
I think the big question mark is profitability.

848
01:20:35,672 --> 01:20:43,252
Because I think if you're in my shoes, we hold a very small sliver in Bitcoin.

849
01:20:43,772 --> 01:20:45,152
And I'm happy about that.

850
01:20:45,272 --> 01:20:46,192
And I'm proud of it.

851
01:20:47,552 --> 01:20:55,452
But the reality is, we actually want to beat the hurdle rate.

852
01:20:55,872 --> 01:20:58,432
We want to beat the Bitcoin appreciation rate.

853
01:20:58,492 --> 01:20:59,432
If we don't, we're cooked.

854
01:21:00,732 --> 01:21:00,832
Right?

855
01:21:01,232 --> 01:21:10,392
And so in some ways, you kind of have to think about, like, there's a lot of areas that I feel like I can deploy the capital and beat the Bitcoin hurdle rate.

856
01:21:10,392 --> 01:21:14,572
That may not always be true, but it's true now.

857
01:21:14,572 --> 01:21:22,492
Um, but like for certain capital that I wouldn't deploy, I should think about storing it, um,

858
01:21:22,552 --> 01:21:30,272
in a way that is, uh, is wise and thoughtful, you know, like I, uh, I was in the, I was

859
01:21:30,272 --> 01:21:36,812
in the process of shutting my business down and I had a bank account at SVB, Silicon Valley bank,

860
01:21:36,812 --> 01:21:43,492
and I had some money in it. And then that whole SVB thing blew up and it was like, huh, okay.

861
01:21:44,572 --> 01:22:04,172
You know, like, this was never something I thought about before. Now you have to think about it a little bit. Right? And like every entrepreneur is just like, I put my money in SVB, I maybe put it in a savings account that yields, at the time, I think it was like, I don't know, 3% or 2% or something.

862
01:22:04,172 --> 01:22:12,192
but you know that's what they did and then all of a sudden you know the financial world kind of

863
01:22:12,192 --> 01:22:21,432
blew up so anyway I digress but I think for for businesses especially profitable ones

864
01:22:21,432 --> 01:22:29,192
you know Bitcoin is going to be an amazing recalibration moment

865
01:22:29,192 --> 01:22:34,912
it will recalibrate how they think about businesses, how they think about capital allocation.

866
01:22:36,212 --> 01:22:41,472
And I think that that will be a wonderful thing for the world because there's nothing

867
01:22:41,472 --> 01:22:50,052
that you just, when, when fiat is melting, the, I just think you end up making stupid capital

868
01:22:50,052 --> 01:22:55,132
allocation decisions because you, you intuitively know that the ice cube is melting.

869
01:22:55,132 --> 01:23:01,572
um and so yeah i'm really excited to see how things change and i hope to you know do a little

870
01:23:01,572 --> 01:23:06,932
bit of writing and kind of talk a lot about it a little bit more um for even like an early stage

871
01:23:06,932 --> 01:23:12,732
startup because i think that while we have to be we have to think about this different um it kind

872
01:23:12,732 --> 01:23:19,032
of feels weird that startups that are encouraged to embrace technology in every part of the business

873
01:23:19,032 --> 01:23:36,372
Like, well, that part's off limits. That doesn't make sense. You know, it's like, no, this digital transformation exists everywhere. And we and we should be thoughtful around how we do that and where and that applies to your balance sheet as well.

874
01:23:36,372 --> 01:24:06,212
Yeah, completely agree. I mean, we've seen it within the portfolio 1031, like the companies that have taken a portion of their raises, use it to buy Bitcoin, like the amount of companies that you were describing it earlier, you raise typically 18 months of runway, in some cases, 24 months, in extreme cases, 36 months, but there's a number of companies that raised well beyond that sort of threshold.

875
01:24:06,372 --> 01:24:09,632
that typical threshold that's thrown out there and have not had to go back to market because

876
01:24:09,632 --> 01:24:13,972
the Bitcoin treasury has worked in their favor and they're able to use that as working capital

877
01:24:13,972 --> 01:24:19,292
down the line. And not only that, we're investing in Bitcoin companies run by Bitcoiners who

878
01:24:19,292 --> 01:24:25,252
understand the hurdle rate. And so I think we have an anomalous portfolio in the sense that

879
01:24:25,252 --> 01:24:30,832
we have companies focused on profitability and growth alongside each other to make sure that

880
01:24:30,832 --> 01:24:36,772
they can stack as much Bitcoin as possible. Yeah. I really think the number one benefit

881
01:24:36,772 --> 01:24:44,972
is not price appreciation over time. I actually think it's that it rewires how you think about

882
01:24:44,972 --> 01:24:50,032
building a business. And that will make you a better founder. It will make you a better operator.

883
01:24:51,252 --> 01:24:55,992
And then maybe the second is like, there's a little bit of a hedge. Like you can create a

884
01:24:55,992 --> 01:25:00,872
little bit of a hedge against debasement in particular. And then thirdly, think about price

885
01:25:00,872 --> 01:25:10,652
appreciation last. I like that. I like that framing. And I know you said that like a lot of

886
01:25:10,652 --> 01:25:19,412
particularly other VCs, that's the thing that blows my mind. If we're like in a deal with a VC

887
01:25:19,412 --> 01:25:24,892
that's not focused on Bitcoin or quote unquote crypto and the founder has to go to them and be

888
01:25:24,892 --> 01:25:26,792
like, yeah, we're going to take a portion of this raise and put it in Bitcoin.

889
01:25:26,912 --> 01:25:27,712
I get a lot of questions.

890
01:25:28,992 --> 01:25:31,032
And it blows my mind that, to your point,

891
01:25:31,692 --> 01:25:33,692
we're in this digital transformation age

892
01:25:33,692 --> 01:25:38,192
and you're having a company focus on all areas of the business

893
01:25:38,192 --> 01:25:41,272
that are going to be disrupted by this digital transformation

894
01:25:41,272 --> 01:25:42,932
except for the balance sheet.

895
01:25:43,012 --> 01:25:44,232
It just doesn't make sense.

896
01:25:44,232 --> 01:25:47,412
But on that note, obviously you're well-connected,

897
01:25:48,452 --> 01:25:49,512
know a lot of founders.

898
01:25:49,792 --> 01:25:53,332
Do you get the feeling that people are waking up to this?

899
01:25:54,892 --> 01:25:57,892
I think it's still super early.

900
01:25:58,612 --> 01:25:58,752
Yeah.

901
01:26:00,032 --> 01:26:01,572
I think it's super early.

902
01:26:02,712 --> 01:26:10,192
So if you look in the public markets, I think the public markets are kind of indicative of the private markets, right?

903
01:26:10,272 --> 01:26:14,132
So the most notable example as of late is Figma, right?

904
01:26:14,232 --> 01:26:14,972
Figma went public.

905
01:26:15,552 --> 01:26:19,112
They had, I think it was like 5% or less in Bitcoin.

906
01:26:19,112 --> 01:26:48,152
And I think Dylan Field, I think that's his name, the CEO, was super involved in NFTs and all this stuff. And obviously, apparently, he's a Bitcoin fan. I think that that's generally – that feels like what will become a new de facto standard is like 5% or less for a business in this fast-growing venture-backed world.

907
01:26:49,112 --> 01:27:00,832
I don't think it – yeah, because you literally – the game, the way that you grow is like you're okay being unprofitable.

908
01:27:01,172 --> 01:27:03,812
You're trying to beat the hurdle rate meaningfully.

909
01:27:05,492 --> 01:27:07,732
So you just have to think about it differently.

910
01:27:07,732 --> 01:27:23,092
But like I said, if you're profitable and you, you know, I met, I was at a Bitcoin treasury conference last week and I stopped by and I met an individual and his father that run a, like a self-storage facility.

911
01:27:23,092 --> 01:27:31,052
And it's like, they're buying, like, I think he said, I mean, this is public. So I think I saw it on Twitter. It's like, you know, 10 grand a week or 10 grand a month.

912
01:27:31,052 --> 01:27:36,592
and they just you know they run a you know a self-storage facility and somewhere in in the

913
01:27:36,592 --> 01:27:41,592
states and but it's like that's awesome that's absolutely fantastic and there's going to be a

914
01:27:41,592 --> 01:27:58,372
lot more of those yeah and those who get on earlier are gonna be very happy that they did yeah that what i and that what i think you an incredible advocate for it because everybody going to be a bitcoin treasury company just like everybody is

915
01:27:58,372 --> 01:28:02,952
an internet company to a certain extent at some point and we're obviously in the early stages

916
01:28:02,952 --> 01:28:10,092
that very early stages of that transition um and obviously our core focus my core focus here at

917
01:28:10,092 --> 01:28:15,192
this business at 1031 is on bitcoin specific industry but that's something at 1031 particularly

918
01:28:15,192 --> 01:28:20,532
we talk about a lot is like, when do we sort of begin to cross that chasm? And I think advocates

919
01:28:20,532 --> 01:28:25,372
like you or Bitcoin are building a business that really doesn't have anything to do with Bitcoin

920
01:28:25,372 --> 01:28:34,072
and is on the cutting edge of his AI revolution. Like the more Luke Thomas's that exist in the

921
01:28:34,072 --> 01:28:38,692
world that are really putting this message out there and sort of de-risking it for others

922
01:28:38,692 --> 01:28:44,992
is extremely important. Yeah, it's going to be, it's going to be a fun time, but,

923
01:28:44,992 --> 01:29:02,372
We're still obviously early innings. And like I said before, I really think the number one unlock is that it rewires how you think about capital allocation. I've seen it with my friends. I have personally experienced this for myself.

924
01:29:02,372 --> 01:29:22,672
Right. So it's like a lot of Bitcoiners experience this personally. And then they're like, would this actually work in a business context? It's like, absolutely. Absolutely. And so I just think that that is the nugget is it's like it's almost like if you were to, you know, there's this concept of, you know, like CEO coaching, founder coaching.

925
01:29:22,672 --> 01:29:29,172
right it's like holding a little bit of bitcoin on your balance sheet even a small amount

926
01:29:29,172 --> 01:29:37,812
is like hiring a coach it teaches you to be more thoughtful it's like what is that worth

927
01:29:37,812 --> 01:29:44,432
priceless it's priceless it really is i love you describing it that way

928
01:29:44,432 --> 01:29:56,592
it's a founder coach yeah doesn't mean i'm not gonna spend money but it does mean that um that

929
01:29:56,592 --> 01:30:00,872
i'm gonna view it through through a through a different lens i'm gonna think twice yeah weigh

930
01:30:00,872 --> 01:30:08,372
the opportunity cost if you will the opportunity cost what um any final thoughts final pieces of

931
01:30:08,372 --> 01:30:15,612
advice as we wrap up here so many things i could probably say but i think if you've made it this far

932
01:30:15,612 --> 01:30:23,592
thank you um if you have comments uh shoot me an email luke at formable.ai um or leave a comment

933
01:30:23,592 --> 01:30:30,152
on the youtube video or whatever and i will uh read it and weep um but uh i think if you if you're

934
01:30:30,152 --> 01:30:36,552
skeptical about ai i understand um and i think that um the reason why you're skeptical is probably

935
01:30:36,552 --> 01:30:37,592
because you see a lot of hype.

936
01:30:38,372 --> 01:30:39,272
And that is true.

937
01:30:39,352 --> 01:30:40,432
But what is also is true

938
01:30:40,432 --> 01:30:41,472
is that there is substance.

939
01:30:42,312 --> 01:30:44,592
And if you want to learn

940
01:30:44,592 --> 01:30:47,672
and the analogy I always use is,

941
01:30:47,792 --> 01:30:49,352
I feel like sometimes I'm in a room

942
01:30:49,352 --> 01:30:51,852
and there's like $100 bills

943
01:30:51,852 --> 01:30:55,152
to use the fiat world as an example.

944
01:30:55,292 --> 01:30:57,932
It's like AI opens your eyes

945
01:30:57,932 --> 01:30:58,792
and you kind of realize

946
01:30:58,792 --> 01:31:00,072
that there's like a bunch of money

947
01:31:00,072 --> 01:31:00,832
lying on the floor.

948
01:31:00,912 --> 01:31:01,452
And you're like, well,

949
01:31:01,572 --> 01:31:03,232
like, I guess I could pick it up.

950
01:31:03,852 --> 01:31:05,192
Like, I guess I could pick it up.

951
01:31:05,512 --> 01:31:06,312
Because if I don't like,

952
01:31:06,312 --> 01:31:12,872
maybe someone else will. And so AI kind of presents that opportunity, whether you're a small business

953
01:31:12,872 --> 01:31:17,872
or a bigger business. I think small businesses, per your comment earlier around how you're using it,

954
01:31:18,072 --> 01:31:24,012
actually have a way bigger advantage. There's just so much more that you can do. And I feel like the

955
01:31:24,012 --> 01:31:33,292
only way to jump in is to just tinker. Start playing around with ChatGPT for a little bit,

956
01:31:33,292 --> 01:31:41,052
or Grok or whatever your tool choice is, then upgrade and start using AI in like workflow tools,

957
01:31:41,232 --> 01:31:48,312
whether it's Zapier, there's a product called N8N, Relay, Gumloop, those ones where basically you can

958
01:31:48,312 --> 01:31:55,052
start building out business workflows that kind of consistently do things for you. That's like the

959
01:31:55,052 --> 01:32:00,092
next leg. And while you're playing with those tools, they will kind of introduce you to some

960
01:32:00,092 --> 01:32:05,332
of the more advanced concepts as you're tuning the things.

961
01:32:06,472 --> 01:32:11,392
And then you'll be able to kind of build this worldview

962
01:32:11,392 --> 01:32:13,852
or mental model around how to use agents

963
01:32:13,852 --> 01:32:15,832
and how they can work for you.

964
01:32:16,452 --> 01:32:17,612
And then I think all of a sudden,

965
01:32:17,672 --> 01:32:19,192
you'll start to notice more areas

966
01:32:19,192 --> 01:32:21,592
where things could be transformed.

967
01:32:21,772 --> 01:32:25,072
I will say the other last thing is that you can actually,

968
01:32:25,252 --> 01:32:26,752
this sounds so bad and weird,

969
01:32:26,752 --> 01:32:34,552
um ask chat gpt how to use it if it has recommendations explain your business ask it

970
01:32:34,552 --> 01:32:40,012
if it has recommendations throw in images of like little whiteboard diagrams of your business process

971
01:32:40,012 --> 01:32:45,372
and stuff like that ask it it'll probably come back with some ideas that will help you um come

972
01:32:45,372 --> 01:32:50,252
up with some creative inspiration yeah i will say i mean i know we're wrapping up but i think

973
01:32:50,252 --> 01:32:54,312
it's important just to give an example of how we're leveraging it on the back end business

974
01:32:54,312 --> 01:33:01,312
process side but we use n8n for a couple things right now um for the newsletter we just a scaffold

975
01:33:01,312 --> 01:33:07,632
to get a scaffold of the newsletter every day we're we've used it we're currently like iterating

976
01:33:07,632 --> 01:33:14,712
on it should go live again next week but ed when i write the newsletter um ed usually i'm like all

977
01:33:14,712 --> 01:33:18,672
right i'm ready to write a newsletter and he goes in and manually like creates a new post make sure

978
01:33:18,672 --> 01:33:26,392
the ads are there like and then we have the section um which is basically a short summary of

979
01:33:26,392 --> 01:33:31,772
a section of a podcast that we recorded within the last week with a quote and a link back to the

980
01:33:31,772 --> 01:33:37,052
podcast and it's been a manual process of we'll record this on riverside we'll get the transcript

981
01:33:37,052 --> 01:33:42,232
we'll put that in dropbox then we'll take the transcript from dropbox and put in claude code

982
01:33:42,232 --> 01:33:47,312
that we've built this prompt that we've been iterating on for for months now at this point

983
01:33:47,312 --> 01:33:52,912
And then we'll get a couple of podcast sections that we can choose from to put into the newsletter.

984
01:33:52,912 --> 01:33:54,812
And that's through the manual process.

985
01:33:55,052 --> 01:33:59,972
And AI is sprinkled in, obviously, transcription and the prompt for clock code.

986
01:34:00,032 --> 01:34:02,792
But now with N8N, we can automate that.

987
01:34:02,932 --> 01:34:08,392
Like Logan can put the transcript in the Dropbox, and that triggers the flow where we just go in.

988
01:34:08,452 --> 01:34:09,432
And it's like, what section do you want?

989
01:34:09,492 --> 01:34:09,712
Click.

990
01:34:09,832 --> 01:34:14,252
And then you can even connect it to Ghost, and it'll create the post for you.

991
01:34:14,632 --> 01:34:17,072
And that will save ad like 15 minutes a day.

992
01:34:17,312 --> 01:34:19,872
Yep. Perfect example.

993
01:34:20,432 --> 01:34:23,492
Yeah. And it's, it works.

994
01:34:23,492 --> 01:34:33,172
and it's one that works like the power is that you you have this kind of digital brain thinking

995
01:34:33,172 --> 01:34:37,532
on your behalf but you still have guardrails on it right you're like no no no like after this

996
01:34:37,532 --> 01:34:44,452
happens i want you to put it over here right so you still feel like you have control um but you

997
01:34:44,452 --> 01:34:50,012
have a little bit of the magic sprinkled in parts of the process where it's most relevant and that i

998
01:34:50,012 --> 01:34:54,952
think is the big nugget is like, that's why I always recommend like play around with chat GPT,

999
01:34:55,072 --> 01:35:00,872
sure. Then upgrade these workflow tools because like, you'll still have some control,

1000
01:35:01,232 --> 01:35:05,912
but you'll be able to infuse the magic, so to speak, at different parts of the workflow,

1001
01:35:06,332 --> 01:35:10,512
but you'll still have the feeling of control. And that's really important because that's where

1002
01:35:10,512 --> 01:35:15,252
people go off the rails is they think like, oh, if I have this agent talking to this other agent,

1003
01:35:15,252 --> 01:35:19,992
and like, all of a sudden, like if it one mistake, like it makes one mistake, the whole thing blows up.

1004
01:35:20,012 --> 01:35:27,932
right so with these you have some level of control and that control like businesses want

1005
01:35:27,932 --> 01:35:35,052
predictability and so that's why infusing some element of control with the magic is kind of like

1006
01:35:35,052 --> 01:35:39,772
the key that picks the lock at least for step two and whatever step three is we'll figure out

1007
01:35:39,772 --> 01:35:46,432
as ai gets better yeah well hopefully as ai gets better we'll continue these conversations i know

1008
01:35:46,432 --> 01:35:51,192
you're a busy man and took you a couple of years to let me know that you're ready to come on. So

1009
01:35:51,192 --> 01:35:55,472
hopefully it doesn't take two more years, but I would be happy to come back on anytime.

1010
01:35:57,272 --> 01:36:01,672
This is all, you know, I'm, I'm in the thick of it right now with the new business,

1011
01:36:01,672 --> 01:36:09,452
um, learning every day and, uh, always happy to share, um, what I'm learning. Uh, hopefully it's

1012
01:36:09,452 --> 01:36:17,332
right. But always happy to share my learnings. Well, I want to sincerely thank you because you've

1013
01:36:17,332 --> 01:36:21,252
been extremely generous with sharing your learnings with me over the years. And it's

1014
01:36:21,252 --> 01:36:27,072
helped me really think about how to approach this transformation as it's happening. I think it's

1015
01:36:27,072 --> 01:36:32,932
helped us improve our business. So thank you. Appreciate it. All right. We'll do it again.

1016
01:36:33,272 --> 01:36:36,272
Let's go enjoy our Friday nights with our families. I can hear my boys playing downstairs

1017
01:36:36,272 --> 01:36:39,232
and we're going to win.

1018
01:36:39,692 --> 01:36:40,272
It's going to be okay.

1019
01:36:40,432 --> 01:36:40,752
Absolutely.

1020
01:36:41,572 --> 01:36:42,072
Never doom.

1021
01:36:42,892 --> 01:36:43,552
Peace and love, freaks.