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Speaker 3: Good morning, guys, and welcome to
the podcast today. I've got a fantastic guest
for

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Speaker 3: you coming out of the AI field,
Steven Shrembeck from

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Speaker 3: Georgia, rights out of, right outside
of Atlanta. It's gonna be a really fascinating

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Speaker 3: conversation because he's a startup
founder working on AI for self-control and

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Speaker 3: stability. And I'm always trying to
get a pulse of the emerging technologies,

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Speaker 3: trends, and fields, and I'm really
in- interested and curious about, or in this

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Speaker 3: area. So I'm really happy to have
Steven on. So welcome, Steven.

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Speaker 4: Good to be here. Nice to meet you,
Chris.

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Speaker 3: Yeah. You have a very interesting
background and talk about your early experiences

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Speaker 3: and what you're doing, and we'll dive
right into the conversation.

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Speaker 4: Yeah. I'm gonna sound like the
opposite of impressive at first because I
started out

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Speaker 4: in, in college thinking that computer
programming was something that was too hard,

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Speaker 4: and then ended up switching into a
computer science related major. From there, I
did

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Speaker 4: a pretty routine software
development, and then I got a job at Amazon, not
AI

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Speaker 4: related, just regular software. About
2016, I started realizing that deep learning

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Speaker 4: is having a second renaissance. This
is incredible stuff. This is now like entering

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Speaker 4: the level of complexity where as a
regular software developer you can begin to

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Speaker 4: understand it with a little extra
work. So I started training deep learning models

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Speaker 4: and, uh, mostly vision models, some
audio models, stuff like that. And then of

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Speaker 4: course there is a third wave of AI
revolution here where natural language

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Speaker 4: processing, the advances there
combined with transformers and other deep
learning

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Speaker 4: models to give you, yeah, large
language models that you're all familiar with.
And

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Speaker 4: all right, great, so now I'm gonna
learn this. It's at an even higher level of

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Speaker 4: abstraction. And so I've been
building my own stuff for years, some models as
well

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Speaker 4: through my day job, and now I'm
applying everything I've learned to just make
tools

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Speaker 4: that help people. Not like
sensational AI, just like really practical. I'm
using it

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Speaker 4: where it's the right thing to do.

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Speaker 3: Really interesting foray, and I was
actually have this kind of curiosity 'cause I

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Speaker 3: was watching this YouTube with a
podcast with, it was Marc Andreessen and Ben

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Speaker 3: Horowitz and like Peter Diamandis and
a lot of these AI innovators, and they were

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Speaker 3: talking, and also Sam Altman, and he
was talking about large language models as the

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Speaker 3: baseline and was very akin to the
browser wars, like which, which company is gonna

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Speaker 3: come out with the, the most dominant
one. And right now it looks like OpenAI, but

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Speaker 3: does doing a lot of things with their
LLaMA. But the question I have for you, 'cause

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Speaker 3: it really sparked my curiosity, is
like these AI models are based on language, but

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Speaker 3: they, he was talking about AI models
being based on video and pictures. And what

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Speaker 3: are your thoughts on models, AI
models based on things that are not based on

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Speaker 3: language, but like videos and
pictures?

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Speaker 4: Yeah. This is slightly less explored,
but this is coming to the foray in

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Speaker 4: multimodal models. There's been a lot
of advances in the encoding. At the lowest

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Speaker 4: level, your large language models
have taken little chunks of words. You can
imagine

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Speaker 4: the word, I don't know, waffle,
broken up into just a few pieces. So sound wa
and

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Speaker 4: then ful. It's not necessarily how it
gets split, but that's about right. That's

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Speaker 4: like the lowest, that's the atoms of
large language models. And then those little

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Speaker 4: pieces get rearranged in a sort of
autocomplete way, and that's how it thinks,

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Speaker 4: right? It thinks at that low level.
It's, those are how it represents its

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Speaker 4: information. But how do you go from
the word waffle to a picture of waffle?

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Speaker 4: Something only knows text. It has no
conception. This is like describing color to

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Speaker 4: somebody who has never seen it in
their entire life. So this is a dimension that

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Speaker 4: they've never experienced. So how do
you get them to understand it, a picture of a

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Speaker 4: waffle intuitively like we do? And
there's a lot of techniques for converting from

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Speaker 4: one to the other, but what they've
started doing is actually training these things

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Speaker 4: at the same time, and so that the
lowest level encodings are shared
representations

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Speaker 4: between all of them, so that you can
actually seamlessly move from one to the other.

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Speaker 4: It's really crazy. You input like the
text waffle, and then it has an internal

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Speaker 4: representation of the different
meanings of the word waffle in context, like
what a

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Speaker 4: waffle is, what it looks like. It can
actually generate output out the other side of

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Speaker 4: a picture of waffle, and that doesn't
necessarily look good 'cause that's not what

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Speaker 4: it's for. But it, it shares, like it
co-locates these representations together so

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Speaker 4: that... And you can do that with
sound, and then you can train it again with
other

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Speaker 4: low-level stuff. And now it begins to
be able to intuit like how these concepts are

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Speaker 4: related in ways other than just text.
And I think that OpenAI's model can, what is

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Speaker 4: it, Sora, its low-level encodings are
basically pixels and sound.

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Speaker 4: But it als- it does this technique.
It also starts to marry these things together

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Speaker 4: with words, and it's pretty cool.
It's hard to train. [laughs] These are not easy
to

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Speaker 4: build. No one's gonna train them
anyway. Just use theirs.

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Speaker 3: It's really fascinating 'cause I'm
just always trying to just keep grasp 'cause,
you

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Speaker 3: know, when OpenAI's, like their
ChatGPT came out in November of, uh, '23.

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Speaker 3: Was it '23 or what was... It s- it
seems so long ago. It was very clunky. It was

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Speaker 3: just like the texting, it wasn't
really... But now it's like the, the large
language

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Speaker 3: models have been trained really well
that you put in text or even images now, the

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Speaker 3: output is actually pretty decent and
it just reminds me of when I was using Google,

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Speaker 3: like Google for search. It was just
all text, right? But then you could use like

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Speaker 3: Google Lens, like pictures, and you
could use your voice as well, and it's like what

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Speaker 3: you were describing, this multimodal.
Which brings me to my next question is, 'cause

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Speaker 3: you talk about everyday usage of AI
and I had another guest who was also, he was,

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Speaker 3: his focus was to educate those who
don't have access to AI so that they're not left

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Speaker 3: behind. So when you talk about these,
they're these tools to help everyday people.

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Speaker 3: You talk about developing AI tools to
help individuals regain control over their

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Speaker 3: attention and choices in a
increasingly distracted world. Elaborate on that
and, and

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Speaker 3: what that means.

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Speaker 4: Just like the general concept, and a
lot of these general concepts you can start to

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Speaker 4: apply in your own life. You don't
need to use anything that I'm making or anything

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Speaker 4: else. But think of it this way, like
large language models specifically, and all the

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Speaker 4: stuff that gets bolted on top of
them, right? The... I'll just shorthand it to
large

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Speaker 4: language models. There's a lot of
magic under the covers. It's the same with
Google.

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Speaker 4: You type in a search box, but you
just know that there's an ocean of code under

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Speaker 4: there. So there's a lot of stuff that
goes into this, but for now assume it's large

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Speaker 4: language models. It's basically
commodity intelligence. You can think of it as
not

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Speaker 4: like an especially bright person,
just like your average person, like a, a, an

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Speaker 4: average level of reasoning in a box.
A general reasoning, and that is really

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Speaker 4: powerful. One thing you can use that
for, yes, you can use it to replace people.

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Speaker 4: Yeah, however you feel about that,
good or bad, is neutral. But you can use it to

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Speaker 4: replace commodity intelligence.
That's... Everyone tends to focus on that. But
you

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Speaker 4: could also use it in places where it
would be unethical, unreasonable, or just not

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Speaker 4: preferable to have a human do the
same thing. So think of it like a hazmat suit,
or

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Speaker 4: if you've seen the show Cher-
Chernobyl or whatever, where they have, they try
to

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Speaker 4: get the robots to go in and clean it
up. [laughs] So like y- you put it in an

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Speaker 4: environments where you wouldn't want
a human. So you can imagine there's a lot of

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Speaker 4: environments like that on the
internet. It's a lot more dangerous, predatory.

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Speaker 4: There's a lot of influences. So some
simple ways to use it are just send an AI ahead

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Speaker 4: of you just to go look for things
that it's triggering or is it good, and just

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Speaker 4: pacify it or sanitize some of the
things, or even just censor some of the things
you

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Speaker 4: don't want to experience. Get rid of
the noise, the intentional bias and inf-

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Speaker 4: influences, all that sort of stuff,
right? So you can think of this as having a

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Speaker 4: hazmat suit. So that is a simplistic
way of looking at that, but there's a lot of

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Speaker 4: other environments and situations in
which you would like to have human-like

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Speaker 4: intelligence evaluate a situation
without a human so that you don't, a human

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Speaker 4: doesn't have to. So not just saving
work, it's also sparing a conscious [laughs]

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Speaker 4: creature from having to experience or
go through this.

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Speaker 3: Interesting. It's, and I actually
have some follow-up questions around just

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Speaker 3: developing tools for mental clarity
and focus, and also self-control and ADHD. I

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Speaker 3: just wanna understand it more. If
somebody... 'Cause I'm hearing a lot, 'cause I
use

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Speaker 3: the AI for a lot of content creation
and, but I hear a lot of people are starting to

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Speaker 3: use like AI for chatbots and
assistants. If somebody want- wanted to learn
how to

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Speaker 3: use AI for this area, where would
they go? Where would they start? How would you

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Speaker 3: recommend them play around and
tinker?

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Speaker 4: Most awesome part about this like
third wave of AI, assuming you don't count the

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Speaker 4: early work before the early 2000s, is
that it's mostly at, it's mostly

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Speaker 4: these big foundational models that
are trained on millions if not more dollars.

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Speaker 4: There's, nobody can run these things
on their computers, not really. Nobody c-

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Speaker 4: definitely can't train them. It's
highly sophisticated, but they're so

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Speaker 4: generalizable. It turns out that
basically everything I learned [laughs] about
how

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Speaker 4: to construct these neural networks
and the software on top of it is more or less

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Speaker 4: useless. Okay, it helps conceptually
understand it. Like the playing field got real

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Speaker 4: level because it's mostly prompt
crafting and some light software engineering,
but

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Speaker 4: even the AIs can write the software.
So it has leveled the playing field immensely

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Speaker 4: to, to the point where, yes, it's a
skill to learn how to interface with these

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Speaker 4: things, but once you get good at
using ChatGPT, like stitching together some

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Speaker 4: software to do that in an automated
way is basically just logic, like common sense,

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Speaker 4: like just trial and error. And then
you can use no code tools, Bubble, and there's

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Speaker 4: LLM specific ones like, uh, Flowise,
I think is one. There's a couple like them,

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Speaker 4: where it's just like a little
branching structure. If you've ever seen like a
f-

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Speaker 4: flow diagram. It's okay if this,
here's the prompt, then do this. Like you've got

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Speaker 4: customer intake or you've got, uh,
new patients or something. Did they fill out
this

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Speaker 4: form? Okay, was this empty? Check for
errors, like talk to them about it. If that's

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Speaker 4: all good, then send them to this
sign-up page. Okay, then send them to this
thing.

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Speaker 4: It's easy. If you're a human being
with a little bit of patience and you're willing

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Speaker 4: to l- learn a little skills, then you
don't really need software

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Speaker 4: developers like me. Uh, so that's the
good news, is that 80% of the use cases you're

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Speaker 4: enabled to do by yourself, and it's
much more approachable. So those are the tools

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Speaker 4: I'd recommend trying out, but there
is no replacement for getting in there and

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Speaker 4: learning the nuances of how it works,
like intuitively. And this is something I'd

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Speaker 4: recommend actually learning how to
intuit if you don't already use the AI tools.

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Speaker 3: Yeah. I, I love this process, how
you're describing just tinkering and just
playing

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Speaker 3: around. Um, go in and just like just
see what, you know, that's how you best learn.

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Speaker 3: Um- Well, the other question I have
for you is, so you talk about, um, the AI tools

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Speaker 3: assisting those struggling with ADHD
or addiction and, you know, what are... how is

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Speaker 3: this possible? What are specific
features designed to help those struggling with

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Speaker 3: ADHD and addiction?

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Speaker 4: There's lots of different hows. It's
like a constellation of different tools, and a

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Speaker 4: lot of it's just regular software.
But one of the fundamental problems is you have

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Speaker 4: an, the untrustworthy operator
problem. Let's say you've got a bunch of system
that

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Speaker 4: keeps you healthy, in check. I
meditate at this time. I take my medication at
this

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Speaker 4: time. I don't go buy drugs or alcohol
'cause [chuckles] I'm not doing that. I

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Speaker 4: don't... I, I make sure that I check
into work, or I, I leave by this time. You can

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Speaker 4: imagine a whole bunch of systems that
people with ADHD and autism rely on. However,

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Speaker 4: the operator themselves is not
trustworthy, both in the sense that they forget,
uh,

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Speaker 4: they have low object permanence, they
just don't even realize that they should be

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Speaker 4: doing this, or they have emotional
irregularity or motivational instability. So you

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Speaker 4: simply can't operate in a way
that's... Okay, I have a personal rule not to go
buy

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Speaker 4: alcohol on the way home. Okay that's
not gonna stop you. [chuckles] Like, y- you-

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Speaker 4: the operator themselves can't be
trusted. So now what do you do when you- the
system

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Speaker 4: you rely on, you can't trust the
person who's operating it? And you can have a

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Speaker 4: nanny, or you can have [laughs] I
guess a, a babysitter. You could have a sponsor.

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Speaker 4: There are piecemeal solutions to all
this stuff. But what would be really nice is if

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Speaker 4: you had a system of accountability
that understood the nuance. There's that

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Speaker 4: commodified intelligence. This is
where the AI part comes in. What state are you
in?

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Speaker 4: Can I trust you? Yes or no? Like,
normally you can change your rules. It's just a

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Speaker 4: rules engine. Like, I do this, I
don't do this, make it hard to do this, hide
this

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Speaker 4: from me. It's more or less it, it
knows you can't be trusted, so there's like this

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Speaker 4: balance between this is where you
need the intelligence. Do I let you just turn
all

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Speaker 4: this stuff off? Do I try to block a
transaction at a liquor store? Okay I'm just

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Speaker 4: buying this in order to make a, a
flambé or [laughs] later. There's a lot of
nuance

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Speaker 4: here that brute force, like
simplistic tools don't work. So in... you need
something

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Speaker 4: that understands. Also, you don't
want it, it interrupting you or stopping you or

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Speaker 4: turn- blocking your websites when
you're trying to do stuff for work. There's an

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Speaker 4: enormous amount of nuance in when to
apply, like enforcement, and the net result of

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Speaker 4: all this is that it just makes it
easy to do what you wanna do, harder to do what

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Speaker 4: you don't wanna do, and it makes it
more or less impossible to not realize what you

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Speaker 4: should be doing. And then the rest is
more or less just set up your own rules. So

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Speaker 4: that's the general system. But yeah,
it's for sleep, it's for electronic addictions,

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Speaker 4: avoiding substance abuse, spending
control. These are the most common problems that

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Speaker 4: people have, and so that's what we're
focused on. But the principles are general,

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Speaker 4: right? It's whatever rules you got
for life. But it's just imagine a little, you

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Speaker 4: know, guardian angel that is
constantly paying attention to what you're
doing.

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Speaker 4: There's some AI there as well. And
then whatever information you choose to give it,

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Speaker 4: it's using that to evaluate whether
it should step in to enforce your own rules or

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Speaker 4: not if you don't.

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Speaker 3: Really interesting. And then when you
talk about ADHD and addiction, the other

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Speaker 3: question is how do the A- AI tools
you're developing help users main- attain mental

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Speaker 3: clarity, and can you share examples
of how these tools are used?

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Speaker 4: Moving things. I'm operating from the
state that your standard human at rest is

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Speaker 4: already healthy, so if that's not
true, that's a different target audience. So

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Speaker 4: assuming that at rest when healthy
you're functional, then it is mostly about

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Speaker 4: removing influences. It's about
decreasing your level of stimulation to improve
your

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Speaker 4: baseline dopamine. So a lot of this
is like the hazmat suit I mentioned, like it's

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Speaker 4: creating different interfaces to
influences. Okay, you wanna listen to podcasts?
You

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Speaker 4: go through this other tool that
desanitizes it. You wanna browse the web, you
want

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Speaker 4: to look at social media, you're gonna
do it through this alternate interface that

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Speaker 4: doesn't allow these things to pull
your attention away. You can also tell it what

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Speaker 4: your intentions are. This is what the
first version of the software was. Tell it

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Speaker 4: what your intentions are, and then
it's paying attention to what you're doing, and

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Speaker 4: if there's a discrepancy, it can just
make you aware. But if you choose to... You're

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Speaker 4: doing this to yourself. If you choose
to follow up by adding more restrictions,

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Speaker 4: "Hey, I said I was doing this thing
for work and I'm not doing it after 45 minutes,"

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Speaker 4: go through this pretty well-known
psychotherapy routine, mirroring. There's...
None

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Speaker 4: of this is new, right? I'm just
putting together existing Legos. Follow this
step,

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Speaker 4: then this step. If I completely
ignore it, then I want you to turn off my
internet.

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Speaker 4: Not everyone's gonna do this kind of
thing, but for certain problems it makes sense.

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Speaker 4: Like substance abuse, for instance.
You need a hard guardrail which says, "If a

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Speaker 4: transaction comes through or is
trying to be processed from these merchants or
in

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Speaker 4: this way, deny it." And that's just a
hard enforcement. There are other rules, of

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Speaker 4: course, to... It's never gonna be
able to stop you. The purpose is just to add

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Speaker 4: friction or to remove the presence of
things that are making your life worse so that

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Speaker 4: you don't have to use willpower. It's
the, the whole purpose is you cannot rely on

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Speaker 4: willpower. These people specifically,
I'm definitely in the target audience, cannot

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Speaker 4: rely on willpower reliably. So this
removes, it adds a backstop, and ultimately

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Speaker 4: allows you to retrain your brain for
what you want and what you pay attention to

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Speaker 4: because there's something, there is a
digital adult in the room that will eventually

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Speaker 4: step in, and that is something that
we lose when neurodiverse people come from

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Speaker 4: childhood to adulthood. There's
nobody to step in anymore if you live alone or

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Speaker 4: you're supporting yourself or others
are dependent on you. You need reliable ways to

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Speaker 4: not crash and burn. There's no one to
step in. And so now this sort of preserves

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Speaker 4: autonomy and independence and allows
some software to step in by your own design.

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Speaker 4: You're doing this to yourself. It's
configurable. So that's the premise.

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Speaker 3: Really the next question I have for
you is, 'cause talking a- about just going away

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Speaker 3: from the AI and just talking about
more broader, talk about this what are your

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Speaker 3: thoughts on society's current
challenges with self-control, and how can
technology,

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Speaker 3: particularly AI, foster more mindful
and intentional behaviors?

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Speaker 4: Anyone relatively studied in like
psychology or sociology recognizes just how we

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Speaker 4: like to think we're, we have free
will, but... And like we have a lot of agency.
But

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Speaker 4: most of our behaviors and the ways in
which we can be influenced are very well

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Speaker 4: documented. Like we are very well
doc- they're super well-documented blueprints on

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Speaker 4: how to get humans to do what you want
them to do. And the sad part of this is, is

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Speaker 4: that has been very well perfected and
engineered upon by basically everything.

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Speaker 4: Everything from business processes to
the well-known attention and influence

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Speaker 4: economies, ads, all this sort of
stuff. Um, it's obvious people have figured out

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Speaker 4: really how to perfectly manipulate
others through technology. The nice part is that

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Speaker 4: you can do that to yourself, and you
can also detect that, and you can stop it. So

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Speaker 4: that is the role of software in this,
is that you can use software to harm yourself

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Speaker 4: or to be harmed, and you can just
accept that. Or at the individual level or an

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Speaker 4: organizational level, you don't have
to wait for society to change. You can just

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Speaker 4: make your own tools or set your own
rules, like none of this has to be software. But

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Speaker 4: what to access and what not to
access, um, and become aware of what's

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Speaker 4: manipulating you or influencing you.
And so that is really how I see it, is yes,

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Speaker 4: collective action is great. The man
is slow, frustrating, and often ineffective.

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Speaker 4: Solutions are not great. So if you're
waiting for US Congress to pass laws banning

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Speaker 4: social media so that your 12-year-old
isn't being unduly influenced, I think you're

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Speaker 4: gonna be waiting a long time and
you're gonna be disappointed. However, you can

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Speaker 4: begin to take action now beyond
just... A lot of it's simple, and a lot of it is
the

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Speaker 4: willingness to

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Speaker 4: notice how things are making you
feel. That is su- such a simple thing to say,
but

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Speaker 4: notice what is making you feel bad,
become committed to that, and then be willing to

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Speaker 4: live differently or to be creative on
how you remove those, remove or blunt those

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Speaker 4: influences on you. That's like the
most important thing to do regardless of what
ch-

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Speaker 4: tools you use, 'cause nothing is ever
perfect. You gotta fit it to your life. Remove

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Speaker 4: the bad stuff and do more of the good
stuff. I don't think that any of this is

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Speaker 4: actually surprising. My insight for
building a business in software was that people

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Speaker 4: know what to do. The average person
knows what is healthy for them and not healthy

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Speaker 4: for them generally, but they have
trouble actually doing it or not doing it. So

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Speaker 4: that's where you should focus. Less
on shame. Stop using effort and willpower, and

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Speaker 4: just make it so that it's really
hard, if not impossible, to do the things that
are

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Speaker 4: bad for you, and it's really easy, if
not inevitable, to do the things that are good

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Speaker 4: for you.

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Speaker 3: Very insightful, and I'm sure the
audience is gonna have a lot of follow-up

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Speaker 3: questions. I have two more questions
before we have around three, four minutes left.

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Speaker 3: The other question is, the... One is
AI can feel impersonal, and how

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Speaker 3: do you ensure your tools foster
genuine human agency and are accessible? Because
I

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Speaker 3: was... There's this concern from
people that have access to AI and that know how
to

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Speaker 3: use it. They're gonna use it to, of
course, enrich themselves and progress, whereas

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Speaker 3: the common average person that
doesn't know or is gonna get left behind. How do

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Speaker 3: you address this?

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Speaker 4: That's a profound problem, and I
think that it's accurate. But that's a question

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Speaker 4: that is well beyond the scope of just
AI. This is any technology, what happens when

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Speaker 4: you have exponential, uh, abilities.
Like some people are becoming superhuman.

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Speaker 4: That's a major challenge that is
really a philosophical one. So that's... I won't

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Speaker 4: weigh into that too much other than I
would advise you don't need to be on the

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Speaker 4: cutting edge. But, uh, uh, usually
being about 20, 30% behind the cutting edge,

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Speaker 4: being an early-ish mainstream adopter
is about good. Just pay attention [laughs] and

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Speaker 4: try to use these things. There was a
second part to that question that I forgot.

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Speaker 3: Yeah. It was this, the kind of the,
the next question is just with AI,

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Speaker 3: how do you help people use technology
to create more meaningful lives? Just 'cause I

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Speaker 3: know in our day and age, it's really,
it's just more efficient, instant

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Speaker 3: gratification, just more effective
and just bam. But ultimately, with technology,

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Speaker 3: we're losing meaning. For example,
we're very connected, but we're in the, we're

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Speaker 3: what some of the most disconnected
people in human history, even though the

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Speaker 3: technology is supposed to bring us
together. So how, how do you, uh, use AI to

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Speaker 3: create more meaning for people?

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Speaker 4: Okay. That's a great question, and
I'm willing to be late for my next thing to

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Speaker 4: answer that because that's an amazing
question. And I feel very strongly about this.

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Speaker 4: We should not be replacing the
behaviors that we want to do.

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Speaker 4: We... This is where capitalist
profiteering, like efficiency mindset falls
flat, is

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Speaker 4: that it, it... If we keep going,
we've automated away everything, right? We have
AI

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Speaker 4: raising our children. We have
technology that does everything for us.
Eventually, it

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Speaker 4: can just live for us, and what are
we? You can just be- Put on a, uh, a feeding

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Speaker 4: tube, um, and just [laughs] go
unconscious. Uh, what are you replacing? Uh, I
think

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Speaker 4: this is where we, we have to be quite
mindful of the fact that we are...

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Speaker 4: At an individual or even an
organizational level, what are you omitting?
What are

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Speaker 4: you actually replacing? Did you get
rid of the things that you wanted to do? The

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Speaker 4: purpose of an AI tool is the obvious
that most people talk about, to replace the

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Speaker 4: jobs and tasks that people don't want
to do, or that it can do it better. Sure,

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Speaker 4: that's fine. Go use it for those
things. That's obvious. Pay attention to where
it's

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Speaker 4: overrunning and recognize that there
were... there is meaning in work, there's

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Speaker 4: meaning in helping people, and that
you're not remove... What are you doing with

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Speaker 4: this extra time? Unfortunately, if
the common denominator, like the status quo, is

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Speaker 4: that you go back to the attention
economy, you start grazing for information, or

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Speaker 4: you're in a world where nobody else
is around, in the physical world it's very

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Speaker 4: lonely because they're all zombies,
that's bad. What are you freeing up your time

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Speaker 4: and energy for? So you want time,
energy, and attention freedom. That's awesome.
You

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Speaker 4: can keep opening that up, but if the
way you allocate it is just pointless leisure

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Speaker 4: or it has no meaning for you, then
you're just getting more of a terrible thing. So

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Speaker 4: this is, uh, again, a neutral tool.
All it does is give you more time, energy, and

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Speaker 4: attention freedom, maybe some
financial freedom as well. But what are you
gonna do

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Speaker 4: with that? You have an excess, you
have a surplus of these things, but how you

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Speaker 4: allocate that for meaning is
critical. It doesn't... It creates more of a
thing, but

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Speaker 4: it doesn't mean that you're gonna use
your f- newfound freedom and resources. That

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Speaker 4: is an entirely different, uh,
conversation and problem. I have a, a lot to, to
say

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Speaker 4: on those, but I think we'll have to
leave it at that for now.

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Speaker 3: Yeah, I really enjoyed this
conversation, and very insightful just coming
from a

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Speaker 3: SaaS founder and just a leader in
this area. And what if people wanted to follow
you

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Speaker 3: and reach out to you and connect with
you, how could they do that?

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Speaker 4: Uh, there's a website,
impossiblelaboratories.com. If you're a software
dev or a

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Speaker 4: designer or project manager, I, I'm
looking for collaborators. This is a lot of

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Speaker 4: work.

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Speaker 3: [laughs]

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Speaker 4: But now that I've started, like,
doing user interviews and all this stuff,
running a

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00:27:04.506 --> 00:27:07.366
Speaker 4: business is, like, crazy hard.
It's... I don't have time for all this.

355
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Speaker 3: [laughs]

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00:27:07.886 --> 00:27:11.346
Speaker 4: The loose collection of contractors
plus me is not cutting it anymore. So yeah, if

357
00:27:11.386 --> 00:27:14.966
Speaker 4: you... It sounded cool and you wanna
try it out or you wanna help, this is mission

358
00:27:15.006 --> 00:27:19.666
Speaker 4: driven. Uh, it's got profit motive
because this is America. You can't do anything

359
00:27:19.706 --> 00:27:23.586
Speaker 4: without a profit motive. But really
it's a... This is not the easiest way to make

360
00:27:23.606 --> 00:27:24.386
Speaker 4: money. I could just-

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00:27:24.386 --> 00:27:24.826
Speaker 3: [laughs]

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00:27:24.866 --> 00:27:28.886
Speaker 4: This, this is about helping people.
So if that sounds cool, give it a shot. That's

363
00:27:28.966 --> 00:27:31.906
Speaker 4: impossiblelaboratories.com. I'll put
some links on there.

364
00:27:32.586 --> 00:27:35.746
Speaker 3: Excellent. Yeah. And, uh, keep up the
great work, and I really enjoyed this

365
00:27:35.806 --> 00:27:36.526
Speaker 3: conversation.

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00:27:37.386 --> 00:27:40.526
Speaker 4: Awesome. Well, it was nice to meet
you, Chris. And, uh, cool. Yeah, maybe we'll do
a

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00:27:40.566 --> 00:27:41.206
Speaker 4: follow-up in a while.

368
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