Pragmatic AI with Matt Stauffer

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Hey, and welcome back to Pragmatic AI, where we talk about using AI in the real world,
what works, how to use it well, and when it causes more harm than good, practical tools

and real trade-offs for builders and business leaders.

My guest today is my friend Greg Storey, the author of Creative Intelligence, Don't Ask
AI, Think With It.

And Greg, you've done a lot more things other than write that book, but obviously the book
is kind of the reason why we are connected today.

So before we go into anything else, would you mind just saying hi and kind of telling
everybody like, who are you and what do you do on a day to day?

Yeah, and thanks for having me on the show, Matt.

I appreciate it.

uh My name is Greg Storey and I have been working in the digital world since 1995.

A lot of that has been in design, but also in operations, uh owning studios, working at
large scale.

You and I were talking about IBM earlier.

I worked at IBM design for a bit.

uh

and mostly doing a lot of leadership from team or team of teams.

These days I am writing quite a bit, but also serving as a uh fractional chief of staff
for a software company.

That's one part that we haven't talked about before.

So I actually, I want to dig more into that one because I think it's probably a little bit
relevant to the type of input that you have.

A lot of us have only ever heard the phrase chief of staff when it comes to politics,
right?

And I actually first heard it outside of the realm of politics when one of my main mentor
five years ago was like, Matt, you need to choose as chief of staff.

And I was like,

That sounds great.

What is it?

So if somebody is unfamiliar with kind of like what your role is, especially in a
fractional perspective, kind of what type of work are you doing with the companies you're

working with?

Yeah, so it's it's working.

It's kind of managing up and managing leading down, right?

So working with leadership to understand what are the goals?

What are the needs?

What are the pain points, etc?

uh And then helping them think about that compost strategy, come up with operational
ideas, and then to take that work and manage across the know the departments below them.

Just making sure that everybody is communicating as best they can, pointing in the right
direction, doing the work that we need everybody to be doing, pulling them back from like,

whoa, whoa, you've gone too far.

A lot of ways I see myself as both sometimes a coach, sometimes a mentor, but there to
support everybody and just make sure that the

organization is running as optimal as possible.

Got it.

Yeah, I love that.

And I've always thought it in the, it's in the direction of the COO role, but it's
definitely distinct.

But you know, it's similar to a COO, like hands at every single pie really understands
kind of what's going on.

I love that you led with leading up and then helping them kind of lead down or whatever.

I mean, that's, that's a, it's a pretty big commitment to be able to make.

um And it does, think, transition into a conversation around kind of like what led you,
you you mentioned that you've been, you've led teams, you've led teams of teams.

um

you don't write or speak like someone who thinks of themselves below, you know, like
hands-on work.

And so I get it.

I get that chief of staff is a place where you're doing a little bit of everything.

So I do want to do that transition though.

What was your, you know, what led you from being a person who's working in the business in
those ways to someone who's more education?

Was AI kind of like the first step that you took there or were you doing other education
prior to doing this?

I'd say, it's funny, I just thought of this when you asked that question.

There was a moment in the late 90s when I was offered a professor role at the University
of Alaska Anchorage, full-time professor.

I was just like, oh my gosh, this is amazing.

But I knew if I stayed there, I wouldn't be able to, there's just so much I would miss
with the internet and.

and the web and so I declined and took a job elsewhere.

But education is something that if I can, I typically lead by trying to teach people, get
them up skilled, point them in different directions and that's so much of a kind of lead

the way as like, let's pour in this together, right?

Type of thing.

so it's always been kind of a,

a bit about how I operate, but when it came to AI, uh I definitely saw that there was
knowledge and experience that I had that when I shared that uh in conversation with

people, it changed their perspective in how they see things, they see AI, how they see how
they could potentially use this as a uh different kind of tool than what they were.

And so that's where I thought, you know, I've been asked many times to write books in the
past, but I didn't really know what it was that I could write that was going to be unique

or like super beneficial that wasn't already in the, in the world.

And after a number of months of trying to talk myself out of doing this, um, I finally
decided, okay, let me sit down and knock out an outline that, know, and, you know,

basically share what I'm seeing, you know, my,

kind of different vision of things.

Yeah.

And so when we hear people talk about AI education these days, the vast majority of those
conversations are very hands-on practical.

And I don't know about you, but uh when I went to school, I went to school, studied
graphic design, and I considered a computer science degree.

Didn't end up getting one.

But I had a lot of friends who would go to community college or trade type schools for
programming.

And we realized that the big distinction between the two was their education there was
here's how to open Photoshop.

Here's how to create an image size, this particular size in Photoshop.

Here's how to adjust the layer styles in Photoshop.

And my education at the university level was, here's how to think about art, and here's
how to think about creativity, and here's how to think about those things.

And it feels like a similar distinction to the majority of AI-based education that I see
today, and kind of what I see you doing, and I want to ask you if I'm reading you right,

in that the majority of AI education I see right now is, here's how to do a thing, right?

Like, here's how to set up your claw to do this way.

Here's how to...

set up a Claude bot or whatever.

Here's the type of prompts, 10 key prompts to get blah, blah, blah, blah.

And not a lot of the education is around how to think and how to relate and how AI does or
does not fit kind of within your world and your workflows and how to adjust the way you

might be working with AI to not work with AI.

So first off I wanna ask, am I telling it correctly?

And if so, can you give a pitch for folks who aren't familiar with your work for kind of
like what the overall direction of your education looks like?

Yeah, and so, you know, when you describe the difference between like, you know, community
college type of education versus university, right?

So um I look at that as like, you know, vocational versus academic, right?

You know, so in my experience, you know, had the you have design theory versus graphic
design, right?

oh You're taught the history of things, um why things worked, why they didn't and

how to take that and turn that into thinking about the future, ya know, about contemporary
applications and whatnot versus like you say, open up Photoshop or Figma or whatever and

make things, right?

And so, and you're right in that when I was looking at the, when I was trying to talk
myself out of writing a book and looking at, you know, like who else is writing about

this?

And you had

Some folks that were writing about kind of how I saw things at a very high level, you
know, this is how the world is going to transform and blah, blah, but not landing, like

not getting into, you know, like what does that potentially mean for somebody?

Even if it's not, here's your top 10 prompts now, but just, you know, how should that
change my thinking about my particular role or my team?

You know, staying at very much like a high level.

then I was seeing some parallels in

the there's two stories that I bring up when I talk about this.

The first is when I was a freshman in college at the University of Alaska Anchorage, all
the freshmen were encouraged to take a class uh LS Library Sciences A101.

And that was it was only two weeks.

It wasn't a full semester.

And essentially it was like an introduction to an academic library.

Right.

So, you know, we have

libraries and our communities and our schools, but in taking that class, because I was
kind of interested and wanted to see what I was missing, uh I found out that this is like

a library of libraries.

And so essentially the class was a tour of all the different kinds of collections and
realizing, now this is, dating myself, but this is back in the 90s.

So this is before the internet.

uh

which meant that when you went into a collection, it had its own way of classifying the
content, right?

Categorizing it, labeling it.

It had its own distinct computer systems with distinct databases, right?

So you couldn't just go up, it wasn't like a card catalog of looking up subjects.

There was a number of ways that you could search for information and correlate it and find
out what's in this collection.

So we went around, the first collection we visited was the government science, or sorry,
the government documents.

And it was kind of boring as you can imagine, but it was fast.

Like there was all kinds of, wasn't just anything a government has done is here.

There was just all kinds of government stuff.

And then you go to, I learned that the periodicals collection isn't just magazines and
newspapers, that it actually has.

a lot of different indexes of information that are published annually by these companies.

So think of like a lot of metadata about people who read things, subscribe to things, et
cetera, right?

And, so you go through all this and then eventually you go to the antiquities, you know,
where a lot of it is, you know, behind closed doors and we're kind of made aware of like

what's in there, but not really shown around, you know.

Even students aren't really allowed in there unless they have special blessing type of
thing.

So, but the thing is, that, you know, very few people took that class.

I think seriously, there was maybe only six other people in my class and that's that
semester.

But later, you know, I was just aware, like I knew that this information existed and where
to go and how to access it.

And I used that several times in my, in college, right?

I knew who to go if I couldn't find it at least.

who to go talk to and how to use their language, right?

So then fast forward, I mentioned that I worked at IBM.

I was part of the IBM design team in Austin, Texas.

And IBM design was a relatively new organization that was looking to scale the practice of
design through this 400,000, 150 plus country company.

And one of the ways they did that was to introduce design thinking.

which meant that everybody who got a job at IBM design had to go through training.

It was like our, very first thing we did is a two-day workshop to go through the practice
of design thinking.

And in the, very first thing that we did is you, had sticky notes and you know, markers
and whatnot.

And we were asked, everybody was asked take 20 seconds and draw a flower vase.

So it was like, you know, drawing a flower vase and then hold it up.

pretty much everybody's flower vase looks exactly the same, right?

And we're taught that the reason why all of our sketches look the same is because the ask
has already prescribed what the solution is, right?

It's a flower vase.

then, so the next ask was take two minutes to create an experience for enjoying flowers.

Hmm.

And it was really weird because the room all of a sudden kind of went from, you know, kind
of, this is our icebreaker activity to, oh my God, there's some pressure here.

Right.

Like, because all the constraints had been completely lifted.

I can't come back with a different looking flower vase.

Right.

I got to, you know, this is a design thing.

I got to come up with something.

And so we spent a chunk of time, like, you know, people holding up and presenting.

their ideas for enjoying flowers and they were all over the place as you can imagine.

And that was a really important lesson that we learned and that that was for designing
products.

But the same too is this is exactly what it was seeing in prompts, right?

In YouTube videos of top 20, top 10, top whatever, or like, here's my perfect prompt,
right?

I have been spending evenings and weekends creating the perfect

thing to share with your computer and it will give you exactly what it is that you need.

And it's like, you're limiting this thing, you know, so for starters, it's just looking at
AI and thinking, this isn't just a, I saw a lot of people that were using AI as I coined,

like a vending machine, right?

So they're putting in a gigantic prompt.

like you print it out.

could be like five feet tall.

Yeah.

to give you exactly what it is that you asked for it.

You're not taking advantage of what this technology knows, right?

And it is like, I remember asking, what is it you know?

And we had a conversation, we meeting me in the, I think it was Claude, and eventually got
to like, look, if you take the library of Alexandria, I pretty much know the equivalent of

10,000 of those.

Right?

Pretty much everything that has ever been created, explored, documented.

You know, I know, I know science and languages.

know the arts.

I have academic papers that have never seen a light a day.

Right.

It's just, it is the library that I went to, you know, for that kind of tour and kind of
getting into this idea of, my God, this thing, you know, we're, we're using it to.

do the stuff that we get paid to do to do it faster and quicker and maybe make my emails
sound smarter.

And these are to some degree like parlor tricks.

And it's like, man, if you just add a little bit of curiosity and think a little bit like
a researcher or think like a problem solver, that to me is like, that's the first thing

that people are missing is the capability and the capacity of

what these LLMs hold, what they can access instantly in any language, right?

Just, know, da da da da da.

And this is one of my favorite parts is you can correlate data from one thing to the next.

There's no linear relationship to it, but I could say compare this moment in time, like
what's going on here with something that happened.

uh

in the during the Greek Empire days, you know, that was badly worded, but you know, my
point being like, I can I could take things that I can I can compare and contrast.

Right.

And there's man, it's just it's incredibly powerful, not so much in the output, but more
of being able to very quickly go gain perspectives that, you know, would take hours, days,

weeks.

to gain some of these perspectives, right?

So that was the first gap.

The second was with how all these very, very, very like hyper vocational uses of AI of all
these very prescriptive prompts.

And now we're even kind of getting a little bit into it with skills is we're essentially
asking AI to just create more vases, right?

We're creating faster horses.

We're basically...

When you use AI like that, you're indexing on faster, cheaper, right?

Not necessarily stronger, better.

And in tying those two experiences in between all the other life and work experience I've
got, it's like there's a different way of using AI that I want to help people to hopefully

open their eyes.

And so they could see it, whether they use it or not, I don't know.

But there are some things that really help.

um in developing hopefully new and improved ways of thinking.

Okay, so that's a that's a big um It's a big ask on you when you were setting out to do
that you kind of said I am recognizing that people asking me these questions and I'm

consistently answering something that may not be out there You said you spent potentially
months trying to talk yourself out of writing a book what was the ...

Because I tried to talk myself out of writing a book and the thing that finally kind of
clicked it for me There's so many different reasons to write so many different reasons not

to write

for me was like, got a degree in computer science and I'm trying to be a leading
programming thinker.

Having an O'Reilly book, you know, hanging on my wall behind me helps validate me.

And then this technology stack that's young that I really love, having an O'Reilly book
for this technology stack helps validate the technology stack.

There's a million reasons to do it and not to do it, but those are the ones that kind of
like were my final, whatever the opposite of a deal breaker, my final deal makers were.

Did you have some final deal makers where you're like, this is what finally tipped me over
to say this is why this needs to be out in the world?

Yeah, because I basically

I don't remember the exact moment and I can't tell you exactly what was shared with me.

But essentially, you know, the computer is like, look, we keep going over these searches.

You you keep looking at Blue Ocean, you keep looking at ah these different ways to look at
is there a gap?

Yes, no.

And, you know, eventually coming to yes, there is a gap.

So then the second part of it is can you get past your imposter syndrome,

right, to put something out there.

And I think too, you know, some friends and family who helped validate that, you know,
because it almost seems like, am I missing something?

You know, um it's like, why aren't people talking about this?

Why aren't there already a hundred blog posts about this on Medium or whatever?

You know, and I think that's the part where it's like, gosh, either

Either I've either something's missing or what I'm thinking is just like, well, duh, you
know, kind of thing.

Right.

And so I just thought, well, you know what?

I'm going to do this.

And I knew I didn't I didn't want to work with a uh traditional book publisher.

So there's no gate.

Right.

And uh at that point.

That and I think when your wife is kind of like, will you do this already?

Stop talking to me about it and go write your book.

That helps out a lot too.

Yeah, yeah, it's, yeah.

So we've talked kind of around the topic of the book in circles quite a bit, which I think
is a really good intro, but let's, let's talk about the book that kind of kicked off this

being the thing you're doing.

Cause I know you have like workbooks and other materials and you know, then, but the book,
you know, tell me, tell me about the book.

So the book, first and foremost, I describe it as a book about thinking, how to be
becoming more aware of thinking in general, different ways of thinking, different tools to

use thinking.

In the book, there are things to do with AI, but this is not dependent upon technology.

I wanted to make it technology agnostic because I feel like what I learned when I'm trying
to pass along to some degree is timeless.

Right?

Like you, you could take this curriculum and stuff I'm developing now, you could take AI
out and put a team in and it'd be the same.

You know, I would still recommend it.

I would still teach it.

And so a lot of it is naming things and being very, you know, kind of like slow to, to
point things out and to name them because I've also found a pattern that people would

know.

or even practice a thing, know, a thinking, or type of thinking, but didn't know it was
called something.

And so my best example this is there's divergent and convergent thinking.

Divergent is where we go get more information, more data, more ideas.

And then as we validate it, we start to converge, right?

We start to come down and start to get things to a point where a decision or a way forward
can be made.

A lot of folks I talked to,

were very well aware of divergent thinking, but they never heard of convergent thinking.

And it made total sense.

Like as soon as I uh described what convergent thinking is, they got it.

They just had never had a name for it.

And so uh I think first and foremost, it's like taking people through a lot of uh ways to
think about things, how to develop divergent, uh methods for divergent.

thinking, convergent thinking, decision making, etc.

And then as the book progresses, it just kind of walks through, you know, how I typically
work, which is very much grounded in design thinking.

And then getting to the point where, okay, you kind of understand a basic workflow.

Now let's look at how we can make this better.

So that led to the development of the collaboration profile, you know, recognizing that,
hey,

Um, not everybody, uh, you know, thinks in English or even thinks the same way, you know,
and so that was like, that was actually a big epiphany of like, my gosh, this thing is

defaulting to a single way of interacting in a single kind of way of, of, of entering and
even getting information back out.

But that's not how we work, right?

How you think about things and gain understanding.

is going to be different than my path, right?

Because the way our brains work and just even the way that we process language.

So that led to things like I might speak or interact in English, but I might think in
Spanish, right?

um And getting into things like um I might prefer big picture, ya know, big picture, let's
work in.

And some people are very much like, no, let's start and go literally all the way to
finish, right?

And so things like that, like the um using frameworks, uh that's actually been a really
big kind of eye-opener for folks is wait a second, I can use these things that I uh caught

wind of in college uh or at some kind of workshop or company retreat.

And now I can do these things at the speed of AI.

And more importantly, start to chain them together.

so that I'm not spending days and weeks going through this process of getting through
these frameworks.

And by the time I do, I'm so deep inside of the work I put in it.

I don't have the energy or the capacity to look at it from a distance to be able to do
anything with the data.

Now we can sit above all of this and have AI run through the frameworks, even if we have
to validate it and go back and redo it.

but we could stay at enough distance that we can start to uh both get into divergent and
convergent thinking like very quickly, um ya know, up down or however you want to put it,

which that to me is, uh you know, another thing of what people I don't think we're seeing
at all, you know, goes back to the capacity and the capabilities of this technology.

em One thing that often happens, I think, when we go, because you have kind of, even
before writing the book, you've kind of casually mentioned, well, was going back and forth

with Claude and saying, let's explore whether there's actually even a need for this book.

You are pretty deep in on doing a lot of your thinking.

And then you've also written a book about AI as your creative partner.

One of things I did before we got on the call was I went back to

view your website again, you know, after however long it's been.

And I was like, let me just view this website as if I had never met Greg and I didn't know
anything about him.

And I read through all of the testimonials for the book.

And there was two things that I found really striking about the testimonials that I would
love for us to talk about a little bit more.

You know, I told you this before the call, but my hope to have you on is to expose kind of
some of your way of thinking, you know, to folks who are interested.

And then of course, if they are...

They say, oh, I want more of this.

They can go buy your book and want to support that.

But also I want them to get some of the chunks now.

And there's two things that I noticed from this.

The first one is there's a thread of if you're overwhelmed and stressed, you've been
forced to use AI and it's feeling like I don't want to do it.

Or one guy said something about competitor.

Yeah, Marty Ringling says to better understand the role of AI, not as a competitor, but as
a companion.

And the other thread is multiple people in here talking about how

The biggest takeaways they had from your book was the experience of seeing AI as a
creative partner or a thought partner or something like that.

Which when someone says the expansive capacity of AI and 20, 10,000 times the library of
Alexandria these days, you usually either roll your eyes because you're like, it's another

maximalist or you get stressed because you're like, yeah, I don't have that.

It's going to take my job.

You have this pretty optimistic and hopeful view of

the future of our relationships with AI and what our role is in a world in which AI has
this kind of power and capability.

Can you talk a little bit about what you think the future is, especially towards someone
who's nervous, someone who's stressed, or someone who's tired of AI maximalists?

What different thinking do you feel like you wanna start giving people so that they can
see AI differently?

So I want to be clear in that um I'm not 100 % on this, right?

there's, well, um because the companies that are making these things are...

I've the companies that are making making this technology at the end of the day, they're
trying to get to a point where they can cash out and just use it as an ATM.

Right.

And I am optimistic because I saw this at IBM.

I should add that what we're going through right now, especially in the last couple of
years.

This happened at IBM 10 years ago.

So when at the time I was at IBM, uh Watson was becoming a product to sell, a service to
sell.

just almost as soon as I started, our work was very much like human-centered um type of
outcomes to human-centered type of outcomes with Watson.

Mm-hmm.

Like, you know, find a way because companies like that, like IBM is like, hey, we've just
invested, you know, bazillions of dollars in this thing.

It's finally to a point where it can do stuff for other people.

Now we need to start making money with it.

Right.

Same thing is happening now.

Right.

That's so.

So, you know, do I do I think these companies are trying to go after all of humanity's
jobs?

No.

But is change going to take place?

Yes.

That's why when I opened the book with looking back in history of when there had been
times where either a new way of thinking or a new technology was a huge shift in what I

guess you could say is like the human evolution.

And the reason that this is hitting differently is that our ways of thinking and our ways
of

our technology, um those are changing at the same time.

They're joined at the hip.

But the reason I started the book out here was to give people some hope of one, when these
shifts happen, it's not overnight.

I know right now a lot of companies are uh using AI as kind of like a crutch of why
they're getting rid of people, right?

Why they're laying people off.

um

But I know uh it may seem sudden, but there's still a lot of folks that are still working.

There's still a lot of work to do that AI can't.

ah The other thing I should add to this too is when I worked at IBM, one of my very first
projects, I worked in an incubator program.

So we worked on very small prototypes of things.

And one of the first projects that I was assigned was working with IBM consulting.

on business process outsourcing.

And if you have never heard of that, that is where, this is again 10 years ago, IBM would
be hired to come in and look at a process that essentially like, how do we take the humans

out of this and automate it with computers?

And this has been going on since, let's take the people out and put robots in to make
cars.

So it's been going on for a long time, but it is exactly the same thing that's happening
now.

It's just a different tool set.

so, kind of looking back at my own kind of firsthand perspective on this, of the work I
did at IBM, but also looking back in history, uh there has been incredible change, but

humanity has always found a way through.

And I'm not saying that there's not collateral damage, there always is, ah but it doesn't
have to mean necessarily the end of the world.

And so that's about as far as my optimism goes.

Otherwise, I'm very much a, I really appreciate tools like Claude.

Am I gonna be wearing an anthropic uniform tomorrow?

No, right?

um But I do, so switching this over is while we're here, so.

let's use this, and this is why I really want people to look at this as, I'm not saying go
do your job with AI, right?

What I'm trying to say is think about things and use AI as, you know, leverage AI to uh
expand your thinking to go further than you would be able to do by yourself especially,

right?

So if you've ever worked with an incredible team,

before and for a while enough that you're just jelling, right?

You don't even have to finish a sentence and things happen.

And then if then all of a sudden you are separated from that team, it just kind of feels
like I've lost the ability to function in some ways, right?

And I feel like that's where AI, no matter your experience, if you use it in a different
way, you're

you have the ability to go create your own team, as it were, and then you're not alone.

You're not left to your own devices of the experience, work experience, the life
experience, and even your perspective, your knowledge.

You can use this as a competitive advantage.

It just depends on what you're trying to do.

And so that's where the, I think I've,

written a few times is I'm not really a big fan of this timeline per se.

I kind of liked it when this was a science fiction story, not current events.

But now that we're here because our fiction, our science fiction didn't really prepare us
for, hey, wait a second.

If you don't have to do all this stuff by yourself anymore or even do it, then what do you
do?

And I think that that's part of

what the anxiety, big chunk of the anxiety right now is, you know, does this mean we all
get to be, you know, working on a starship exploring space now, you know, because we don't

have to, we don't have to manually reroute power, right?

We could just talk to the omnus, you know, always present computer and it just does things
like, what does this mean?

And, and so I'm trying to say,

I don't have answers for that just yet, but I don't think that

not using this or choosing to stay away from AI, don't think that's the answer either.

Because historically that hasn't really panned out for those folks.

Yeah, that's you're not the first person to say that in the podcast and I appreciate your
willingness to be open like because as someone who's Again, your book is about AI a lot of

your teaching a lot of your blog posts right now are about AI to say This is not the
timeline.

I wish we were in it's it's it's It makes it a lot more relatable for you to say I don't
want want to be here necessarily, but hey, we're here So let's let's be creative and let's

keep our humanity and let's figure out how to you know

how to adapt versus I'm running forward into the future because this is the best, you
know?

Yeah.

So like when, when people started posting all these AI generated images on social, I, that
just never interested me at, you know, zero interest in that.

It's just like, I guess, um, and I get it, you know, um, people who had no artistic talent
suddenly can do anything that's in their brain.

Um, And I get that.

That's kind of, you know, an interesting exercise.

I'm trying to do the same thing for thinking.

Right?

um Stop generating stuff, start thinking about things, and then hopefully you come up with
something that's actually worthwhile to make.

And if AI can help you make it better, huge asterisks, then cool.

If not, then start making stuff.

Yeah.

So if we were to think about how the average person uses AI, and I know that a lot of your
stuff is in the context of creativity and work environments, and you can kind of lean

there if you want.

if you were to just say, like, what's your most common, your 80 % use case for how to say,
this is a way that someone is currently prompting an AI that I think if they were to

switch it to be more creative, know, co-creative, you know, work.

ah This could make a big switch is there like a like an easy win an easy example to give
that says This is something a lot of people are doing and they should just make this one

change and they'll already see a measurable movement towards this kind of direction that
you're pitching for everyone

Yes, but before I answer that question, I want to be clear about the word creative because
I didn't come up with that word.

um The World Economic Forum, I feel like chose that word for me because it was so the
World Economic Forum is an event, you know, that they have their event in Switzerland

every year and it's a big deal.

It is an organization of, I want to say like 400

companies, 400 member companies.

And there's more that happens in this forum than just they have a party in Switzerland.

So one of the things that in 2004, I think it was near the end of 2004, they released a
survey that they had conducted with all of their members to look at what are the skills

that you're going to be hiring for in the next five years.

So at that time from 2025 to 2030.

And creative thinking,

uh appeared for the first time ever in that list and it appeared at number three, in the
top three skill set.

so you think creative thinking is what shade of lavender should I use or something like
that.

My interpretation of creative thinking is how do you needing to be curious and be aware of

essentially problem solving.

How do I solve problems?

That to me is creative thinking.

And so to go to your answer, um to me the best first thing to do, actually, well, there's
three questions about what it is you're trying to do.

And that is, what don't I know that I don't know that I don't know?

What is missing?

And what assumptions am I making?

Right, so those to me are like the three questions that should be asked continually, you
know, in addition to validate that now, right?

ah What am I missing?

What assumptions am I making?

uh But to me, the best thing to do would be to validate what is the problem you're trying
to solve, right?

um And it's not what is it you're trying to do, because what you're trying to do typically
is trying to solve for a problem.

That could be a critical thinking problem, could be a creative thinking problem.

But right then and there is where, you know, kind of goes back to are we are we making a
vase or we make an experience for drawing drawing or sorry, enjoying flowers.

That has when I've done that work with people in through coaching, that's usually so I'll
give you a give you a perfect example is working with a person.

who was about to go pitch a company for a completely brand new role.

And they felt I need to get my portfolio together.

I need to create a pitch deck that's got all my best stories and yada, yada, yada.

And I said, well, why are you doing that?

And they said that they had gotten wind from an early interview that the leadership
thought that this person was

uh had a lot of good ideas, but there wasn't much behind it.

So it's like, great.

And so when I heard that, when I got them to kind of share exhaustively all the things of
like, why are you doing this?

Or should say, why do you think you need to do this?

Then it was like, ah, let's talk about that.

What does this mean that you're all ideas, but all hat, no cattle, as it were.

um

And in digging into that and knowing who said it, just a little bit about who said it, and
even their, like their world right now, found that it was like, you don't need a portfolio

of your projects, right?

What you need is to come up with ideas for how you're going to create distinctive work.

Okay.

Yeah.

Mm-hmm.

so instead of coaching that person to make a better portfolio deck, we then came up with,
um let me tell you about where this industry is right now.

Why, what's happening here that's a problem and ideas for how, um how people have broken
through the minutia, the bland.

um in time.

So different moments in time, what companies did, why they did it in response to current
conditions, and to show that, look, I've identified how to do this based on success and

failure.

um And this is just a quick model.

This is just some quick work.

This is me doing this for

free as it were, but to show as a demonstration of, I think different.

I can do different, right?

And I feel like that's so going back to what is the problem you're trying to solve for and
validate that.

That is the question we ask our clients more than probably anything else at the beginning
of projects is I understand that you've come to us with this solution and you want us to

implement the solution, but what's the actual problem?

And it's incredible.

I don't know if you're familiar with the five whys.

I'm trying to remember what the, okay, is that safe?

I'm trying to remember who it comes from, but some manufacturing ideologies for those
unfamiliar, just basically.

when they come to you and say, when you do this, you ask why, and you have to ask why to
that and then to that, then when you do it five times, and it's incredible how much em

just uh rudimentary exposure to some of your thinking has led me to be more likely to say,
what am I actually trying to get out of this session with AI?

Because the majority of my personal interaction with AI is coding.

And, you know, I, I want to be an expert in thinking about AI coding so I can guide my
team and my industry and how to use it.

And I'm an expert in coding, which means I know what I want it to do because I'm asking it
to do a very specific task.

So it's more in my, you know, personal and also my non-coding, my CEO life where I'm
starting to explore the world that you're talking about.

I it's incredible how creative you have to be to speak your creativity to know

what's the right thing to be asking for help with and when.

And that was one of the reasons I told my team, I want you all to be experienced AI users
in your programming.

Not because I actually care whether you use it in a day to day or not, but I want you to
have the mindset shift that comes from being aware of what type of questions to ask and

how to prompt and what prompts work and don't and how to, know, like, what is it good at
and was it not good at?

Like it has the knowledge of 10,000.

uh libraries and also make some of the stupidest mistakes you could possibly imagine on
rudimentary arithmetic, whatever, right?

So thinking differently.

Go ahead.

Yeah.

you you talk about.

You talk about the coding coding expert and...

You know which gives you a perspective on this is what I I need to get done and here's how
I want it done.

So my my wife is a senior data.

Engineer.

And.

She's she was a chemical engineer before that, so she's just.

Very smart, we used to call her the rocket scientist.

um And anyway, so she's been in this work for maybe four or five years.

And obviously has read my book, um helped make it better.

And uh she works with some folks who are very much like the, here's my five foot tall
prompt, use this prompt to do a thing.

And they get good work.

but not always great work, right?

Or even like work that goes in the wrong way.

Whereas my wife actually uses some of the workflow of creative intelligence of, you know,
before we get into the work, let's think about what the problem is and let's think about

what the approach is.

And so even in doing just a little bit of that, you know, she's not spending five days
waxing poetic about, you know, different computer science philosophies or whatnot, or

theories.

But in doing that work, um she's now has a of a pattern of coming up with solutions that
her colleagues would never have thought of.

And some of that is kind of bringing the kind of the new eye to it.

But it's also, um she's very hesitant to be ultra prescriptive because it has led to
honestly some pretty amazing innovations um that her company is like.

Holy shit, like we were never thinking about it in this way, right?

And so that's why I see where the power of this is, is you don't have to, this book was
never meant to be a do this one through 10 step process.

If anything, it's like, want you to learn these things and then I want you to riff on it,
right?

Like don't learn Beethoven, be aware of that.

but use it to inspire your jazz.

That's what I want.

I want people to be thinking about thinking like jazz and there's times to riff, there's
times to get into some very prescriptive sheet music or whatnot.

I'm not a musician, I can't take this analogy any further.

uh I just wanted to throw that in there is even in the work you do is to consider

You know, here's how I would think about this ah is if I was doing programming now is I
would go back and say, how did Cobalt thinkers think about this?

Right.

Like, what are some things back in those days that, you know, we've basically paved over
ah because no one's doing that kind of work anymore.

ah But there's there's so many innovations and interesting ways that people did things
back then that

apply to today and in some cases are very innovative.

I love that because one of the things that you push back there on, which wasn't clear
until you kind of gave the example there about COBOL, is we are thinking of primarily AI

as a tool that does the most rote work.

Because if you're asking it to do the work, at least in my industry, it's not going to do
nearly as good of a human, but it can do certain clear, well-defined, repetitive things as

well as a human to say that human to do the more creative stuff, right?

So for right now, Claude code.

can build templates or can, if you did a pattern once, it can do that same pattern 20
other places because it's watched you do it.

So it's very much like allow the humans to do the creative thing by having the AI do the
rote thing.

um And often when people are talking about, you know, non rote stuff for AI, that's when
they're like, well, we don't need programmers.

We don't need designers.

We don't need writers.

We'll just have it do it.

So I really appreciate that.

of like, it's not just the AI doing the rote thing versus the AI doing the creative thing.

You're talking about the AI doing the rote thing versus the AI being something that we can
use to resource our creative endeavors, right?

Like to, you didn't say have it be creative and tell you how to program.

You said use it as a conversation and thinking partner as you explore new ways to program.

You know, and I think that's fascinating.

Yeah, I mean, to put it very simply, AI is the best tool for us to throw spaghetti against
the wall.

And we can do it a thousand times before we ever decide to make what we're going to make
and how we're going to make it, why we're going to make it.

um yeah, that to me is when we go, it's actually when we have a go and generate things.

that's when it starts to fall apart.

But if you haven't retrieved information and correlate information, compare information,
and this is why I look at it as, know, trying to frame it as a collaborative thinking

partner.

Never the think, like I never want AI to do the thinking for me.

Sometimes I will say, want you to think about it, like, how would you do this?

Because I'm just kind of curious, but I don't, I do think it's incredible

incredibly dangerous for a number of reasons when we're trying to look at this as a easy
button for everything, right?

It should never be used in that way for so many reasons.

But first and foremost is like that might be what people are reaching for right now, but
that's not going to last long.

And if you're using AI too much and especially in that way, then you are

you know, working yourself out of a job, right?

um And so again, that goes back to this is where, you know, people say, well, then I won't
use it because then it can't replace me.

You're also going to be out of a job.

know, um we all got to jump in this pool, man, and dog paddle, swim, float.

um But we've all got to jump in.

Yeah.

So we're coming up on time and I want to make sure that we get to all the things that you
want to make sure we've got a chance to get to.

Are there elements of how you would like to see people change the way they think or
elements of this book or your kind of mission in life right now that you feel like we

haven't gotten a chance to talk about today you want to make sure we cover?

I would just say, we've kind of touched upon it, but I use the spaghetti against the wall
to kind of frame how to use this to prototype ideas, thinking, whatnot.

um But there's also two uh using it, and this takes a little bit more effort sometimes,
use it to validate uh the work, but to put it through rigor.

Mm-hmm.

There's two ways to me to do this.

There's an incredible library of frameworks that are not new.

They've been with us for some cases decades, some cases centuries.

And those frameworks are how we're able to uh dissect and put back information to look at
it in sometimes abstract ways, to look at it and uh help make sense of what's happening.

And it's, you know, again, I, talked about this earlier, but I can't express enough the
power of using some frameworks to be able to, uh, you know, apply some rigor to the work,

uh, and, to the, to the thinking so that you're not going, you know, you're not at an hour
clocked in with AI and it looks confident, looks great.

And then you throw that against like blue ocean strategy and figure find that.

Yeah, great.

You just invented the spreadsheet or, you you just basically reinvented the very common
tool that we already have right now.

It's just you came up with cool names and a cool color palette or whatever.

So I think it's to use it.

This is where I go back to the three questions of, you know, what is it that I don't know,
which I've had several times, you know, seen gaps in my understanding of something or just

even my

my knowledge that something exists, right?

um Probably one of my favorite questions, um what's missing?

You know, which is a different way to ask the first question.

And the third is, ya know, what assumptions are baked into this?

And it is amazing how very little information or ideation you can put into this thing.

And you ask those three questions and, you know, it's like the best gap or overlap
analysis that you can get and very quickly, right?

Hmm.

with the assumptions, it's amazing how much unintended bias that we put into something.

Um, you know, bias has this connotation of being a bad thing or being malicious, but it's
not, you know, it just simply be a preference in color or something, but, um, that doesn't

appeal to the people that you're trying to reach, that you're trying to sell to, that
you're trying to teach.

I was, I had a guest recently, Nick Peterson, who is a, um, academician and a theologian.

And he talked about a little bit.

He's actually told me about this more personally about how, uh, he has to do a lot of big
writing, great proposals, stuff like that.

And it's very valuable for him to just say, please read this thing that I've created with
the mindset of, you know, uh, grant research or grant review or whatever else.

And just tell me, what am I missing?

You know, one of the things that he introduced to me was the, I, don't,

love requests for proposals, for those who are not familiar, it's basically when a client
sends you this massive document and requires you to generate a massive document, and then

they ask for those from like five different people, and then they evaluate it.

And so you've spent dozens of hours of work for a project you probably won't even get.

But we do them every once in a while, and they're exhausting.

And I've discovered, similarly, I'm just like, hey, know, like, what am I missing in my
proposal?

Imagine that you are the person who wrote this RFP, you know, like, what thoughts would
you have about my response here, and what?

positive and negatives and what assumptions am I making about their desires that I'm
missing?

it's weird because it's not, there's not a lot of people saying you should try AI so that
it can evaluate your assumptions and your biases and the gaps or whatever.

Like this is just, I feel like sort of undiscovered.

So maybe I am where you were when you were trying to talk yourself out of writing the
book.

I'm just like, yeah, nobody, somebody must know this, right?

So so I have another layer to add to that, you know, to help with that, and that is so one
of the things that I've come up with for like a second edition of the book is essentially

like.

A way to kind of think through what a process would look like aside from the kind of the
loop that I introduced in there, you know, and that is you've got the questions and then

you have keys.

You've got the modes, which is like the five thinking modes.

And then you've got what I'm calling partner and simulations.

So in the keys are the who, why, what, wow, and now.

Right.

And what that's to call out is, and I'm sorry, I'm going to read this off to you because I
don't know if top my head just yet, but who who are the people whose verdict decides

whether they basically what what works?

Right.

So in this case, like

The people who are going to decide, are we going to hire Matt?

Or are we going to hire one of these other four groups that submitted an RFP?

It gets into the why.

What are the structural problems that uh make the problem that the who is having persist?

uh The what is the outcome stated before any deliverable is named?

The wow is what's going to make your work distinguishable, uncopyable.

And the now informs, what do we make now?

Like what's the next step?

So what I talked about the who in this case is identifying who is not just one person.

actually three different roles.

And that is who is the one that's going to pay for the thing, right?

Actually make the decision.

Who's the, the second who is who's the influencer, which is likely in my experience with
the RFPs, you know, the, person who's been tasked with the project.

Right?

Like it's, it's your responsible to redesign the company website or whatnot, but they're
not the ones that are going to decide who gets the gig.

And, know, that's the person who decides who pay for it.

And then there's the who of who's going to use the thing that you're going to make for
your who one and who to starting to sound like Dr.

Seuss, right?

Um, but in doing this work, and I want to go back to the, uh, the, the portfolio deck
story that I shared earlier.

is once I knew that there was another problem, not I need a deck, but I need to showcase
my thinking and my ability to create distinction, I had a name of that person and was able

to go and do research on that person.

And on their LinkedIn profile, they'd done some public speaking, and then to find out
who's that person's boss, right?

And did more research into that.

person, brought that back to the computer and said, let's make some personas based off
this information.

Then found, in this case, the who, who are the types of people that would be making buying
decisions based off this person's work if they got the job.

Then I basically created uh a group of uh users that would be using the end users.

But then I also have the users of uh who is the VP and who is the director.

And this is all based on real people but creating personas.

So then once I have that information, then ask them to give me opinions on simulate
conversations and give me opinions on what do you think of this, which is kind of your

version of the think like a grant writer uh and where are their holes.

What that did is, and I want to really preface this by saying, nothing beats talking to a
real human.

Let's make that perfectly clear.

User research should always be with humans, but a lot of people don't want to pay for
that.

Or in this case, if we're having to work for ourselves or by ourselves.

And we just need to not use this to not have the personas make decisions, right?

Not have these simulations actually uh

define what it is that we do, but just give us some perspective that might be missing.

And I find that when I run those conversations, there's always some like one or two little
insights that help me then go back and dial in my thinking in other areas of the work.

Right?

So that's also, don't make it one grant writer.

It's the, you know, the grant writer and the person who

uh you know says yes we're gonna fund this grant right um you know go go wide don't go no
more than five or six you know quote people um and then just see what happens

Okay, that's awesome.

So that's all in V2 of the book.

What's the timeline for that?

So I'm trying to decide right now.

The book was meant to describe the what and the why of this.

And then I created the field guides, trying to create practical, like, OK, great.

This is kind of getting back to you.

That's the theory.

What's the vocation?

And the field guides was meant to be a, I took a look at what is the most common work
across all knowledge jobs, right?

And so things like.

coming up with ideas, writing reports, all that kind of stuff.

I don't know that too many people have kind of gone through that.

And it was kind of a little arduous to get through all those steps.

So now I'm looking at, should I do a version two of the book or should I just release a
shorter condensed version of a playbook?

And so that's the research I'm in right now.

Once I get through, feel like I've got enough real human reaction to that

then it's going to be go time and get that out because I do have a workshop to go through
this new content that has tested really well and just needs a little bit of a revision.

Then I've got a curriculum to teach this for people to learn this in a couple different
ways.

And so we'll see if there's, if we can get more people to learn how to think about
thinking.

Well, perfect segue you just set me up.

If people are interested in buying your book, reading your blogs, checking out the field
guys, or keeping up to date with you so that they can see when your latest stuff comes

out, how's the best way for them to do that?

go to brilliantcrank.com and you can buy the books there and subscribe.

ah I've got a dedicated site coming out for this.

It's gonna be called practicecreativeintelligence.com.

But until then, go subscribe to Brilliant Crank, say hi, send me an email,
gregatbrilliantcrank.com.

ah Would love to hear from people and uh yeah, try to keep it simple.

Yeah, I love that.

It's super easy and the will be the show notes for anybody who forgets that or you know if
you're driving or whatever you can always come back and take a at the show notes.

So Greg, you know one thing we do at the end of every episode is we take a suggestion from
community member about way that they are currently using AI and their day-to-day personal

life.

So my friend Matthew Davis responded, he said, went on a cruise in August.

Every day I plan the schedule for what we're doing using ChatGPT and it knew who was on
the cruise, like in the party with us.

each of our preferences for what to do and when to do it.

And it plants some great things to do we otherwise wouldn't have done.

Also, we just used it a few times to say, hey, we are at this specific spot in this
moment.

Please help us find some food.

You know, we want this particular type of food.

Again, you know our dietary restrictions.

Find us a couple of places to look for it.

What's good?

Greg, I got to ask you, like, do you, because you talk about all these really creative
kind of usages of things.

Do you?

going to chat and be like, hey, I'm looking for a new Italian spot in Seattle that I
haven't tried before.

Tell me where to look.

You know, are you using it the way a lot of people are?

On occasion, but typically no.

What I would add to Matthew's use of chat GPT is I would say, I love what he did, but then
I would add from what you know about us and the experience that we're all gonna go on,

what should be required for that person to come back and uh tell us, show us what it is
that they did.

Okay, that's fun.

Right?

And so I, I did, when I do things like that, I try to typically add another dimension
because that's when I feel like, again, you get some like things you would just never, you

know, but you look at them like, course, but just wouldn't have thought about that.

And so, you know, let everybody kind of goes, go through different directions.

But when they come back, who's going to be the one that has to perform a monologue who's
got to go, you know,

uh sing a song or perform a dance or tell a joke, know, whatever that might be.

um But that's where I would try to mix things up there.

um When it comes to like the dietary restrictions and whatnot, I typically like to go
sideways, like show me the place that nobody goes to that everybody should try to

experience once in their life.

You know, so um I'm always looking for the the left turns to make on this, you know.

um

because that's where I find some gold.

This is I love how inspiring is for you to say because one of the things I say early on as
I'm talking to somebody who's nervous about AI or trying to figure out as I'm like it's a

tool and it's a it's a Transformational generational tool but in the end it's just a tool
which means a it's not it's not human It's not a person but B it means you can use it or

not use it It's good at some things and not other things the way you use it can depend can
impact how useful you find it to be

And so one of the things I really appreciate about you and your ways of thinking and the
things you've shared here is that I feel like you are like, you picked up, I'm trying to

think about like, maybe if somebody came across their first laptop and they were using it
as a hammer, like to hammer a nail or something like that, like, no, hold on, hold on,

hold on, let me show you.

So I just appreciate that, like, look at all these other ways you can think about it.

And it really does kind of take putting your brain at a different angle to the problem.

And you just give us a great example with both Matthew's example on the one I asked you.

So um thank you for hanging out.

Thank you for uh being hopeful about how we can retain our humanity and our creativity in
the midst of this kind of like unasked for, but we're still gonna do our best in the face

of it and kind of big change.

um And yeah, just thanks for sharing today.

Yeah, again, thanks for having me on the program.

It's been fun.

I had a great time too.

And for the rest of you, we will see you all next time.