0:00

This is the everyday

0:02

AI show, the everyday

0:04

podcast where we simplify

0:06

AI and bring its

0:09

power to your fingertips.

0:11

Listen daily for practical

0:13

advice to boost your career,

0:15

business, and everyday life.

0:18

The generative AI world

0:20

is barely recognizable from where

0:22

it was when I started

0:24

this everyday AI show more

0:27

than two years ago. And

0:30

as we celebrate our

0:32

500th episode, wow, that's

0:34

crazy. But yeah, as

0:36

we celebrate our 500th episode,

0:39

you all thought it would

0:41

be a good idea to

0:43

talk about some of the

0:45

top takeaways. from everyday AI

0:47

so far. So I'm excited

0:49

to share about that today

0:51

and talk about some, you

0:53

know, some of the, you

0:55

know, future of work discussions,

0:57

how AI is going to

0:59

be impacting and is already

1:01

impacting employment, how it's going

1:03

to change traditional service industries

1:05

and even redefining our own

1:07

human skill and value. So

1:09

I'm excited today to talk about

1:12

the top. takeaways of everyday

1:14

AI so far as we celebrate our

1:16

500th episode. All right, what's going on

1:18

y'all? My name's Jordan Wilson and I'm

1:21

the host of everyday AI. This is

1:23

your daily live stream podcast and free

1:25

daily newsletter, helping us all not just

1:27

learn AI, but how we can leverage

1:30

generative AI to grow our companies and

1:32

our careers. So, is that what you're

1:34

trying to do? If so, you're definitely in

1:37

the right place. It starts here

1:39

with our daily live stream and

1:41

podcast, but how you actually leverage

1:43

this and take advantage of all

1:45

of this is by going actually

1:47

to our website, your everyday ai.com.

1:49

There you can sign up for

1:51

our free daily newsletter where we

1:53

not just recap every day's show,

1:55

but keep you up to date

1:57

with everything else happening. in the

1:59

world of generative AI, large language

2:01

models that day. So if you

2:04

haven't already, you need to go

2:06

read our free daily newsletter. Speaking

2:08

of our free daily newsletter, well,

2:10

if you're looking for the daily

2:12

news, it'll be in there. But

2:14

in our newsletter, we asked you, said,

2:16

hey, what do you want to know? Right? We

2:18

can do a lot of different things

2:20

for a 500th episode. I asked you

2:22

all, hey, do you want former guest

2:24

to interview me? Should the... live stream

2:26

audience is grill me. Do you want

2:28

to hear about some of my favorite

2:30

episodes? But no, you all wanted by

2:32

a far margin. You wanted to hear

2:34

the top takeaways of everyday AI so

2:36

far, which is kind of broad. So

2:38

I just put together a lot of

2:41

my different thoughts. But you know, ultimately,

2:43

this is about you all, right? So first

2:45

of all, yeah, maybe you don't know, maybe

2:47

you just listen on the podcast, maybe, you

2:49

know, you don't listen too much to the

2:51

show at all. Maybe today's your first time.

2:53

But what this thing ultimately is.

2:56

It's for you all, right? And I'm gonna

2:58

get into that a little bit more, but

3:00

I'd love to hear from you guys. I'd

3:02

love it here. You know, if you have

3:05

questions, if you have thoughts, if you have

3:07

comments, please get them in. You know, Jay

3:09

saying, what a great milestone, 500 episodes. Congrats,

3:12

and thanks for all you do for

3:14

us. This is our 500th episode. Happy,

3:16

you know, I have a lot of

3:18

stuff planned that I want to talk

3:20

about, but mainly, I do just want

3:22

to hear from you guys. about AI,

3:24

obviously, you know, if you want to

3:26

ask me something, personally, sure, I'll try

3:28

to answer as much as I can,

3:30

whatever you want to know, but I

3:32

do have some of my top takeaways

3:34

from 500 shows, yeah, Hot Spot for

3:36

the Wind, we'll see about that, Douglas,

3:38

we'll see if the hot spot can

3:40

keep up with this. So, let's get

3:43

going, hey, Brian felt. says congrats

3:45

on the 500th. Thanks Brian. Good

3:47

lifelong college friend and roommate right

3:49

there and Brian's got a great

3:51

AI podcasting out too. So love

3:54

to see it. All right, let's

3:56

get into it. Let's talk about

3:58

our biggest takeaways. So First, it's

4:00

unrecognizable, right? AI today is unrecognizable

4:03

from where it was when I

4:05

started, when I started the everyday

4:07

AI show more than two years

4:10

ago, right? At that time, you

4:12

know, ChatGPT was out, but that

4:14

was it. right for the most

4:17

part yes chat gPT had just

4:19

kind of gone viral and everyone's

4:21

talking about it and everyone was

4:24

using it and everyone was kind

4:26

of confused but that was really

4:28

it right so I believe I

4:31

started this show I'm looking at

4:33

the I think it was April

4:35

so yeah just just over two

4:38

years ago Generally,

4:40

the AI was an afterthought, right?

4:42

Like, people weren't talking about it.

4:44

It wasn't integrated into how we

4:46

work. It's obviously completely different now.

4:48

You can go into any enterprise

4:51

company and not, you know, and

4:53

they don't have a generative AI

4:55

plan every single. enterprise company has

4:57

a generative AI plan. It's obviously

4:59

evolving. Not everyone has it figured

5:02

out, right? Very few people actually

5:04

do just because of the speed

5:06

of developments, but it's completely different

5:08

now, right? You have obviously, you

5:10

have every single big player in

5:13

the game right now, but you

5:15

know, even before we get into

5:17

that, I should probably start it

5:19

where this started, right? So yes,

5:21

more than two years ago. I've

5:24

maybe told the story once or

5:26

twice, but not in a lot

5:28

of depth. And maybe if I

5:30

tell that story, maybe this will

5:32

make sense and maybe this will

5:35

resonate a little bit more. So

5:37

I was a writer, I was

5:39

a journalist, right? in a former

5:41

life. So I spent about seven

5:43

years as a multimedia journalist. Then

5:45

I spent almost a decade, nine

5:48

and a half years in nonprofit

5:50

leadership, but we just really became

5:52

an activation agency for Nike and

5:54

Jordan brand. And then I started

5:56

my own company, called Accelerant Agency.

5:59

So I remember very vividly, as

6:01

soon as the GPT technology came

6:03

out in late 2020, so this

6:05

is two years before chat GPT,

6:07

I was using it every day,

6:10

the day it came out, right,

6:12

all these third parties, there is,

6:14

I don't know, copy AI, Jasper,

6:16

a bunch of other ones. The

6:18

day these pieces of software came

6:21

out, I started using them, heavily.

6:23

And my agency, you know, all

6:25

of our team started using it

6:27

as well. And you know, at

6:29

first, it was helpful. But then

6:32

I learned, the more I understand

6:34

about the technology, the more I

6:36

work with it, the more I

6:38

learn how to apply it to

6:40

the work that we were doing

6:42

at the time. It wasn't just

6:45

the more impactful it was, but

6:47

I realized that wait, you know,

6:49

I've been getting paid to write

6:51

for 20 years. I did okay

6:53

in my early journalism days. I

6:56

want to pull at our fellowship.

6:58

ACP Store of the Year, so

7:00

I did okay, you know, my

7:02

early days as a journalist, but

7:04

there's a point where I'm like,

7:07

wait, this AI tool is better

7:09

than me at writing. And that

7:11

was weird. It was a hard

7:13

kind of conversation to have with

7:15

myself. But that really

7:18

made me open my eyes to

7:20

what generative AI is capable of,

7:22

right? And again, this is two

7:24

years before chat GT. So in

7:26

that two years, I was using

7:28

and trying every single generative AI

7:30

tool that was out. And I

7:32

wanted to learn more. So try

7:34

to gobble up all the information

7:36

there was online about, you know,

7:39

this GPT technology and there wasn't

7:41

a lot. And, you know, we

7:43

also had some early, early diffusion

7:45

models, you know, on the image

7:47

side. And I realized that any

7:49

information out there, it was super

7:51

technical. I didn't understand it. It

7:53

was almost like showing up to

7:55

a party that you weren't invited

7:57

for. That's what it was like

7:59

for me, you know, back in

8:01

2020. 20, 2021, trying to learn

8:04

generative AI. And I'm like, this

8:06

stinks. I knew how transformative this

8:08

technology was, but I couldn't find

8:10

any good place, any good avenue

8:12

to learn. So I said, okay,

8:14

well, I'm gonna start it eventually,

8:16

right? At the time, you know,

8:18

at the time I was having

8:20

one of my best months, one

8:22

of my best seasons ever at

8:24

accelerant agency, you know, we had

8:26

a nice little team. good clients,

8:29

you know, from a business perspective,

8:31

like, when I had that epiphany,

8:33

it was the best month I

8:35

had ever done in my company.

8:37

But at that point, I made

8:39

a decision. I said, I have

8:41

to slowly shut this thing down.

8:43

It took longer than I would

8:45

have wanted to in order to

8:47

be able to do this everyday

8:49

AI thing daily, right? It took

8:51

like a year and a half.

8:54

to kind of wind things down.

8:56

We had a lot of clients,

8:58

right? We signed very long-term contracts

9:00

with clients sometimes 12 to 18

9:02

months. So it took a long

9:04

time to kind of quote unquote

9:06

wind, you know, that business down

9:08

so I could focus on every

9:10

day AI. And it actually started

9:12

in the car. I'd been thinking

9:14

about it for a very long

9:16

time. And I was actually driving

9:19

to a friend's wedding with my

9:21

wife and one of my one

9:23

of my good friends Kenny. And

9:25

I told them about this idea.

9:27

And you know, so we kind

9:29

of spitballed it on the way

9:31

and, you know, I think both

9:33

of them told me, you know,

9:35

like, this sounds like a good

9:37

idea, but are you sure about

9:39

doing it every single day? And

9:41

I don't know, I made that

9:44

decision back then. And maybe you've

9:46

come to this realization too, that

9:48

unless I was going to get

9:50

left behind, right? And don't get

9:52

me wrong, even though I spend

9:54

the majority of my days now

9:56

doing that exact same thing, right?

9:58

Like getting to talk with some

10:00

brilliant people here at the, you

10:02

know, Cloud Next conference and learning

10:04

from literally the smartest people in

10:06

the world, but I still feel

10:09

that way, right? I still feel

10:11

like man, it's so hard to

10:13

keep up with what's possible now

10:15

in how we work. So that's

10:17

kind of how this thing started.

10:19

If I'm being honest, I didn't

10:21

think that the podcast would turn

10:23

into what it's turned into. Mainly,

10:25

I started a podcast because I'm

10:27

like, I'm a writer. And I'm

10:29

going to write a daily newsletter

10:32

and I want exclusive content in

10:34

the daily newsletter because there was,

10:36

you know, a handful of good,

10:38

you know, daily AI newsletters at

10:40

the time, but they were all

10:42

the exact same. I'm talking copy

10:44

and paste, right? Right. They covered

10:46

the same things. They talked about

10:48

the same things. They was formatted

10:50

in the same way. I'm like,

10:52

I want to do something different.

10:54

So in my newsletter, I want

10:57

to be able to talk to

10:59

smart people, right? I want to

11:01

write like I used to, right?

11:03

For me, writing is important. I

11:05

still write, you know, the leverage

11:07

portion of the newsletter with these

11:09

fat fingers, with my own two

11:11

hands, you know, I don't hand

11:13

it off to a generative AI,

11:15

which, by the way, I was

11:17

using M-dashes way before generative AI.

11:19

Brian can probably attest to that,

11:22

right, Brian, tell them, use the...

11:24

M-dashes way back in the Daily

11:26

Egyptian days. So I thought actually

11:28

that the podcast was just going

11:30

to be so I can create

11:32

fresh daily content for the newsletter,

11:34

but it was actually, you know,

11:36

the podcast that, you know, got

11:38

kind of popular, and not the

11:40

newsletter, but that's okay, right? You

11:42

know, in business as with anything

11:44

else, you have to be adaptable,

11:47

you have to be flexible. So

11:49

that's kind of the genesis of

11:51

everyday AI, and it's much different.

11:53

right doing this every single day

11:55

and being able to work with

11:57

literally the biggest companies in the

11:59

world you know I'm very fortunate

12:01

and I hope that you know

12:03

this journey over 500 episodes. You

12:05

know, I hope you found a

12:07

little bit of value here. Yeah,

12:09

yeah, here we go. Okay, Brian,

12:12

Brian's, Brian's, Brian's saying this, he

12:14

said, I distinctly remember Jordan telling

12:16

me about Jasper AI six months

12:18

before chat GTT came out and

12:20

telling me AI was the future.

12:22

Looking back at it, it was

12:24

a clear inflection point for me

12:26

using AI tools on the regular

12:28

as he was usual, as he

12:30

was usually, I have head of

12:32

the curve in this case, the

12:34

AI boom, boom, boom, yeah. All

12:37

right, let's let's keep going. Let's

12:39

talk a little bit about the

12:41

future of work. And y'all, if

12:43

you do have questions, I'd love

12:45

to tackle some of your questions,

12:47

you know, kind of as we

12:49

go along, as I'm seeing some

12:51

of them, I'm starring them, you

12:53

know, I'm gonna get to them.

12:55

You know, so thank you for

12:57

all the congratulations, comment. But yeah,

12:59

if you have a question, you

13:02

want me to tackle, please let

13:04

me know. It is like five.

13:06

45am in where am I Vegas?

13:08

I got nowhere to be. I

13:10

got nowhere to be. All right,

13:12

but I'm not gonna keep this

13:14

one going on for too long.

13:16

So let's just quickly talk about,

13:18

you know, like when it comes

13:20

to top takeaways of 500 episodes,

13:22

I mean, the biggest one has

13:24

to just be the future of

13:27

work. I've been saying this for

13:29

a long time. I didn't say

13:31

this day one, right, because this

13:33

was before every single, you know,

13:35

big player was involved. So now,

13:37

you know, Microsoft with their co-pilots,

13:39

amazing in all the updates that

13:41

they just announced over the last

13:43

two weeks, Google, obviously, right, meta.

13:45

pivoted from, at the time they

13:47

were, you know, social media company.

13:49

Now I think most people no

13:52

matter as an AI company. And

13:54

then you have every single, even

13:56

legacy tech company has transformed in

13:58

the last, you know, four to

14:00

five years since the GBT technology,

14:02

kind of hit the scene. So,

14:04

you know, everyone from, you know,

14:06

IBM and Intel and Oracle, Dell,

14:08

Salesforce, Adobe, right? I just saw,

14:10

you know, Bank of America. just

14:12

invested $4 billion into their AI

14:14

efforts, right? So every single big

14:17

enterprise tech company, everyone's turning into

14:19

an AI company. So if you

14:21

don't think yet that generative AI

14:23

is the future of work, I

14:25

mean, probably if you're listening or,

14:27

you know, reading this, you probably

14:29

know and you probably understand that,

14:31

but that's the biggest takeaway is

14:33

I, you know, I was having

14:35

a conversation with someone at Google

14:37

last night. about this very thing.

14:40

I don't think that we're gonna

14:42

have a choice soon to not

14:44

use AI, right? You'll have to

14:46

kind of go out of your

14:48

way soon, right? Obviously, you know,

14:50

the all the enterprise software that

14:52

we use is being, you know,

14:54

infiltrated in a good way with

14:56

generative AI with large language models,

14:58

right? So if you're a Microsoft

15:00

Windows organization, obviously with co-pilot, Apple

15:02

is like, you know, 30 years

15:05

behind, but I think eventually Apple

15:07

intelligence will be able to do

15:09

more than, you know, add two

15:11

plus two. and obviously everything with

15:13

Google right so most people you

15:15

know you're either a Google or

15:17

a Microsoft organization and those two

15:19

companies have obviously been huge leaders

15:21

in the space along with open

15:23

AI with invidia you know really

15:25

going from a company no one

15:27

had heard of you know if

15:30

like if you weren't a gamer

15:32

you didn't know what in video

15:34

was like three or four months

15:36

or three or four years ago

15:38

right now in video you know

15:40

depending on when you look they're

15:42

the biggest company in the world

15:44

when it comes to market cap

15:46

or you know at least a

15:48

global superpower literally driving the the

15:50

future of the economy so generative

15:52

ais the future of work so

15:55

anyways what i was saying this

15:57

conversation last night is i think

15:59

it's gonna be very hard for

16:01

us not to work with a

16:03

i soon because I think that

16:05

even everyday non-technical people are starting

16:07

to see the benefit of generative

16:09

AI, you know. A funny story

16:11

here, I'll share another personal story.

16:13

My wife, she's amazing. She, you

16:15

know, she, she listens to every

16:17

single episode. You know, she's, she's

16:20

taken like, you know, my, my

16:22

prime prompt polished course a lot

16:24

of times and, you know, she's

16:26

trying to help me improve and

16:28

all these things. And funny enough,

16:30

right, even though I talk about

16:32

generative AI every single day. It

16:34

was when I was at the

16:36

Invidia GTC conference. two weeks ago

16:38

and I came back and she

16:40

had replaced her searching of Google

16:42

with now she's just talking with

16:45

perplexity right and you know I

16:47

was joking about it and I'm

16:49

like oh you know you you

16:51

decided to you know take the

16:53

time when I was gone for

16:55

a couple of days to start

16:57

using generative AI near day today

16:59

but I'm starting to see this

17:01

shift. you know, another one of

17:03

my good friends, his his fiance,

17:05

you know, same thing. She's like,

17:07

hey, now I'm using chat GPT

17:10

for everything, but she's not, you

17:12

know, technical person. I am now

17:14

seeing non technical people, you know,

17:16

start using this generative AI technology

17:18

that I think a lot of

17:20

us, you know, if you are

17:22

a more avid, you know, maybe

17:24

listener of this show, or if

17:26

you're, you know, someone that's using

17:28

AI every single day. You know,

17:30

I think we've been in this

17:32

bubble sometimes and I forget that.

17:35

But now I think that the

17:37

average, even non-technical person is starting

17:39

to see huge value from using

17:41

AI, right? Not just in time

17:43

savings, but in the quality of

17:45

outputs, right? So. Generative AI is

17:47

the future of work and it's

17:49

going to be very hard in

17:51

the future to do any work

17:53

without using generative AI. Just like

17:55

right now, it's pretty much impossible

17:57

to complete any work of real

18:00

business value without in connected to

18:02

the internet. Right. I think the

18:04

same thing. And as we talk

18:06

about generative. and you know, models

18:08

getting smaller, better edge AI, right?

18:10

Like, you know, right now on

18:12

this, on this iPhone here, right?

18:14

There's technically a small language model

18:16

because I have the newer iPhone,

18:18

but I would assume in two

18:20

years, two to three years, on

18:23

the average smartphone, we are going

18:25

to have a model that lives

18:27

locally that is more powerful than

18:29

today's state of the state of

18:31

the state of the art model.

18:33

Right? Yeah, it might not be

18:35

Apple first, you know, you might

18:37

have to have a Google phone

18:39

or something like that. But I

18:41

do believe that we are going

18:43

to have in two to three

18:45

years a local model running on

18:48

the average smartphone that is more

18:50

powerful than a GPT-40 as an

18:52

example. So even your personal life,

18:54

your work life, you have to

18:56

understand generative AI is the future

18:58

of work. There's no way around

19:00

it. And that's both good and

19:02

bad. Because it changes how we

19:04

work. And I'm going to get

19:06

to that a little bit later

19:08

when I talk about agency. And

19:10

when I talk about human skills

19:13

and human value, yeah, like, you

19:15

know, Makka here says, you know,

19:17

looking forward to using agents at

19:19

work one day. I think that

19:21

one day is coming for people

19:23

much quickly than we all may

19:25

realize. All right. Let's get onto

19:27

my next big points, right, because

19:29

we talked about big tax all

19:31

in pivot, right. which I've mentioned

19:33

a couple of times on the

19:35

show before, but this is the

19:38

first time in US history when

19:40

you look at the economics of

19:42

work, right? And that's something I

19:44

always do. You know, yes, I

19:46

know on this this podcast live

19:48

stream, I I ramble and sometimes,

19:50

you know, I seem a little

19:52

disorganized, but I promise you, I

19:54

do a lot of research, right.

19:56

But I don't know. I don't

19:58

want this show either to come

20:00

off as overly prepared, because there's

20:03

enough things out there. and those

20:05

all sound robotic if I'm being

20:07

honest, right? So anyways, I've talked

20:09

about it once or twice on

20:11

the show before, but you know,

20:13

talking about this big tax all

20:15

in pivot to everything AI, never

20:17

in the history of the US

20:19

have all six of the biggest

20:21

companies when it comes to market

20:23

cap been from the same industry

20:25

until now. Right. It's always been,

20:28

you know, very, very diverse. You

20:30

know, you have people in energy,

20:32

you know, you're mobiles, you have

20:34

people in commerce, you know, your

20:36

Walmart's of the world, right? So

20:38

if you go back and look

20:40

over the last, you know, 30,

20:42

40 years at the biggest companies

20:44

in the US by market cap,

20:46

it's always been very diversified. It's

20:48

not anymore, right. Which, you know,

20:50

you know, there's downsides to that

20:53

as well. But the big. The

20:55

six biggest companies in the US

20:57

when it comes to market cap,

20:59

they're all just now AI companies.

21:01

Microsoft is an AI company. Google

21:03

is an AI company. Amazon is

21:05

an AI company. Invidia is an

21:07

AI company. Meta is an AI

21:09

company. You get the picture. They're

21:11

the biggest companies in the world.

21:13

And that's really impacting, not just

21:15

employment, but also business models, right?

21:23

Are you still running in circles

21:25

trying to figure out how to

21:27

actually grow your business with AI?

21:29

Maybe your company has been tinkering

21:31

with large language models for a

21:33

year or more, but can't really

21:36

get traction to find ROI on

21:38

Gen AI. Hey, this is Jordan

21:40

Wilson, host of this very podcast.

21:42

Companies like Adobe, Microsoft, and Invidia

21:44

have partnered with us because they

21:46

trust our expertise in educating the

21:48

masses around generative AI to get

21:50

ahead. And some of the most

21:52

innovative companies in the country hire

21:54

us to help with their AI

21:56

strategy and to train hundreds of

21:58

their employees on how to use

22:00

Gen AI. So whether you're looking

22:02

for Chad. for thousands or just

22:04

need help building your front end

22:06

AI strategy, you can partner with

22:08

us too, just like some of

22:10

the biggest companies in the world

22:12

do. Go to your everyday ai.com/partner

22:14

to get in contact with our

22:16

team or you can just click

22:19

on the partner section of our

22:21

website. Will help you stop running

22:23

in those AI circles and help

22:25

get your team ahead and build

22:27

a straight path to RO on

22:29

Gen AI. I don't

22:31

know how to say this. AI

22:33

is going to take a lot

22:35

of jobs, right? I've never been

22:38

one to beat around the bush.

22:40

I've said since the very first

22:42

episode of everyday AI, which is

22:44

a little bit, it's a little

22:47

cringe if you want to go

22:49

back and listen to it, but

22:51

I still think a lot of

22:54

the first points that I've made

22:56

hold true today. AI is going

22:58

to take a lot of jobs.

23:00

AI is going to have a

23:03

net negative impact on traditional full-time.

23:05

US employment. All right, let me

23:07

say that again. AI will ultimately

23:09

have a net negative impact on

23:12

traditional full-time US employment. Let me

23:14

unwrap that. I think employment is

23:16

going to change very much because

23:18

at least especially for the last,

23:21

you know, since the digital revolution

23:23

over the last, you know, 30-ish

23:25

years, you know, we're now We

23:28

sit in front of computers, right?

23:30

Since the 90s, you sit in

23:32

front of computers and you're paid

23:34

for your knowledge, right? You're paid

23:37

to create business value, you sit

23:39

in front of computer, you create

23:41

new business value for a company

23:43

with your knowledge, right? That's what

23:46

we do as knowledge workers. Knowledge

23:48

work is going to completely change.

23:50

Because guess what's more knowledgeable than

23:53

all of us sitting in front

23:55

of a computer. A

23:57

large language model, right? Go

23:59

use, you know, Gemini 2.5.

24:02

Go use, you know, open

24:04

AIs of one probe. You could

24:06

get, and I don't care who

24:08

argues on the contrary, right?

24:10

If you argue the flip

24:13

side, that just makes you

24:15

not smart, right? To think

24:17

that, or to not

24:19

understand that a single AI

24:21

system is exponentially

24:24

more intelligent than

24:26

the world's smartest

24:28

humans. Going

24:32

back to my story, right,

24:34

when I was using these

24:36

tools, and I'm like, they're

24:38

better writer than me. Everyone,

24:41

if you haven't had that

24:44

moment yet, you're gonna

24:46

have that moment, right,

24:48

where, oh my gosh, this AI is

24:51

better than me. And that's

24:53

okay, right? Like, I think if

24:55

you ask the same conversation,

24:58

you know, 10 years ago,

25:00

hey. Are you smarter or is the

25:02

collective information on the

25:04

internet smarter? I think most

25:06

people will say, well, the

25:08

collective information on the

25:11

internet. Okay, that's what large language

25:13

models are. They are literally a

25:16

collection of the best intelligence,

25:18

hopefully the best intelligence on

25:20

the internet. Yes, large language

25:22

models can go off the

25:24

rack, off the rails, right?

25:27

Humans can too. It's always funny

25:29

when people look at these

25:31

benchmarks and they're like, oh well,

25:33

you know, looks like it only got it

25:35

right 93% of the time. So we need

25:37

humans. It's like, okay, let's

25:39

have a single human take that

25:42

benchmark, right? Let's have a single

25:44

person, a single human take the

25:46

MMU or the MMLU or the

25:48

ARC AGI test. The smartest human I

25:51

know is gonna get about zero,

25:53

correct. So, think about that. But

25:55

let's talk a little bit

25:57

about. business models.

26:00

and how that's going to change.

26:02

Well, I think traditional

26:04

full-time employment as we

26:06

know it is gonna look very different,

26:08

especially here in the US. It's

26:10

gonna look different in other parts

26:13

of the world, but here in

26:15

the US where the majority

26:17

of our listeners are from,

26:19

think of it like this. You know how

26:22

a lot of people now, you

26:24

know, there's this gig economy, you

26:26

know, you have people. It's not

26:28

uncommon for someone, especially in

26:30

a bigger city, I think,

26:32

to be just be full-time

26:34

gig economy, right? There, you know, oh,

26:36

I do a little door dash, you

26:38

know, I do some, some Uber, and

26:41

then I do some task rabbit, maybe,

26:43

I don't know, right? It's not

26:45

uncommon, especially in bigger

26:47

cities. That's what's going to

26:49

happen. with professional services. That's

26:52

what's gonna happen with knowledge workers. I'm

26:54

not saying that no one's gonna have

26:56

a full-time job in five years. That's

26:58

not what I'm saying at all. But

27:01

I'm saying it will be common

27:03

to know professionally educated people, people

27:05

who have been in corporate America

27:07

and leave, and then they just

27:09

have essentially the equivalent right of

27:11

knowledge work-based jobs. So think like,

27:14

you know, kind of fiver slash

27:16

upwork, but think if there was,

27:18

you know, you know, for whatever

27:20

your industry is, let's say

27:22

you work in marketing in

27:24

the logistics industry, okay,

27:27

there's gonna be like 50

27:29

different Uber-esque, you

27:31

know, or Fiver-esque, or Upwork-esque

27:33

services just for marketing in

27:36

the logistics industry, right? It's

27:38

going to be very common

27:41

in five years for the

27:43

average American worker. to have

27:46

multiple jobs, to have multiple,

27:48

you know, I think even

27:51

businesses, multiple side hustles, right?

27:53

But I really think we

27:56

are going to see this

27:58

re-emergence of entrepreneurship. And unfortunately,

28:00

I think that's going to

28:03

follow mass layoffs, right? We're

28:05

already starting to see it,

28:07

because when you talk about

28:09

AI's impact on employment and

28:11

traditional business models, right, most

28:13

enterprises, not all of them,

28:15

there's still some, and I

28:17

hope there's many, enterprises that

28:20

when they see and fully realize

28:22

the gains of generative AI, that

28:24

they'll make. good ethical decisions, right?

28:26

That's why AI ethics is good.

28:28

That's why I've for literally a

28:30

year and a half when I tell

28:32

people and when when companies hire

28:34

me to consult for them on

28:36

AI implementation and strategy, I say

28:38

you need to go solve for

28:40

the why and solve for the what happens

28:43

when, right? What happens when you

28:45

become 50% more productive? Right? Yes,

28:47

you have to train your people, which

28:50

no one wants to train their people.

28:52

Everyone just wants to hand out easy

28:54

buttons. That's not how generative AI works.

28:56

But what happens if you roll out

28:58

generative AI the correct way? What happens

29:00

if you invest in training and un

29:02

learning? That's what I say. We need

29:05

to stop with this upskilling, reskilling. It's

29:07

un learning and relearning. That's what we

29:09

need to do. But what happens? If

29:11

you're an organization of 5, 5,000 people

29:13

and you go through that process. What

29:16

happens when AI works? What are you

29:18

going to do? You're going to go

29:20

to four hour, or sorry, four day

29:23

work weeks, keep everyone on board? Are

29:25

you just not going to hire new

29:27

people? Or are you going to lay

29:29

off 30% of your organization?

29:31

I think unfortunately, a lot

29:33

of especially public companies

29:36

are going to do the latter in

29:38

that scenario. They're going to lay

29:40

off a lot of people. Well,

29:42

number one, they're going to stop

29:44

hiring. especially as we get this. I

29:46

think it's now is a good time

29:49

or bad time depending on how you

29:51

look at it. But it's a convergence

29:53

of all these things happening,

29:55

right? So we finally have

29:58

large language models that are. Agetic,

30:00

right? They're able to, on their

30:03

own, no code, right? That's the thing

30:05

people don't realize. And there's

30:07

some announcements. I should have

30:09

wrote down what time the embargo here

30:11

at Google goes away. I think it's

30:14

maybe still, I'd be now, might be

30:16

30 minutes, so I can't talk

30:18

about it, but okay, Microsoft

30:20

Copilot Studio. If your organization

30:23

has Microsoft Copilot set

30:25

up correctly, even if you

30:27

are not a Microsoft Copilot

30:29

studio, you could probably spend an hour,

30:32

it's no code, low code, and

30:34

you could probably build an autonomous

30:36

agent that does one of your most

30:38

annoying manual tasks without any experience,

30:41

you could probably get it doing 80%

30:43

of that one task, autonomously, right? So

30:45

when we talk about autonomous agents

30:48

and how they're going and people

30:50

are always a little bit confused and

30:52

I get it, right? Essentially you have

30:54

large, like you have generative AI or

30:57

large language models, right? I talked to

30:59

chat GBT, chat GPT gives me

31:01

answers back. Then you have AI

31:03

workflows, right, which is I talked to

31:05

chat GBT, chat GBT has access to

31:07

all of my files and some tools,

31:10

and then it comes back to me,

31:12

right? But I still have the agency,

31:14

right? And I'm choosing in

31:16

that instance to give decision-making

31:18

power temporarily to an AI

31:21

agent. So that's not, or sorry

31:23

to... a large language model, but that's not

31:25

an agent. So me talking to chat GBT,

31:27

that's not an agent. Me talking to chat

31:29

GBT that has access to my files, that's

31:32

an AI workflow, that's not an agent. An

31:34

agent is when it doesn't need me. I

31:36

go in one time, I go to Microsoft

31:38

Copilot Studio as an example. I set up

31:40

an autonomous agent. It sets on a trigger,

31:42

any time I receive this type of email,

31:44

you know, people asking me for a quote,

31:46

I don't do that anymore, right. Like it's

31:48

going to go through. it realizes, you know,

31:50

yes, this is someone reaching out asking about

31:52

a quote. It goes and looks at all

31:55

your all your dynamic data, all your most

31:57

up to date information, you know, across multiple

31:59

parts. of your organization, and then

32:02

it goes back and it

32:04

can reply to that email

32:06

automatically. That's agency. That's an

32:08

agent, right? That's when you

32:11

set up the guardrails. A

32:13

large language model has tools,

32:15

it has a defined role,

32:17

and it goes out without

32:20

you telling it to, without

32:22

you handing or handing over

32:24

that agency or asking it

32:27

to be agentic, it's working

32:29

on its own. And that's

32:31

where we're at. And I

32:33

do think unfortunately... Once companies

32:36

see and realize the game

32:38

gains of this combination of

32:40

agentic AI, number one, models

32:42

that are much smarter in

32:45

models that are reasoning, number

32:47

two, and costs going down,

32:49

unfortunately that means a lot

32:52

of big companies are going

32:54

to be laying people off.

32:56

But ultimately, what I think

32:58

that means is there's going

33:01

to be first, and I

33:03

talked about this on the,

33:05

on our 2025 AI roadmap

33:07

prediction series. It's going to

33:10

be a huge disruption. in

33:12

traditional service industries. Okay? Slow,

33:14

expensive sectors are gonna be

33:17

rocked. Okay, I'm talking about

33:19

consulting, finance, legal, tech writing,

33:21

accounting, CPAs, right? High priced,

33:23

slow, expensive service services. they're

33:26

going to get crushed, right?

33:28

Check, checking the newsletter, we're

33:30

going to be covering. I

33:32

can't talk about this because

33:35

they did release this information

33:37

before the embargo. Google just

33:39

updated its deep research tool

33:42

to Gemini 2.5 Pro, right?

33:44

I think open AIs. Deep

33:47

Research is one of the more

33:49

impressive AI tools I've ever used.

33:51

Google did update theirs a couple

33:54

of weeks ago to Gemini 2.0.

33:56

Now that it's Gemini 2.5 pro,

33:58

I've only used it very... because

34:01

it just got released like last

34:03

night and been a little busy

34:05

here at Google Cloud Next. That's

34:08

going to be extremely disruptive. I

34:10

don't see if I'm being honest,

34:12

right? So let me just give

34:15

an example here. Let's say right

34:17

now, there's a thousand consultancies in

34:19

the US. I know that's not

34:21

the right number. I know there's

34:24

more, but. I'm here for easy

34:26

math. It's still 6 a.m. here,

34:28

local time. Okay, let's say there's

34:31

a thousand consultancies. I think half

34:33

of them are going to persist

34:35

with their traditional business models, right?

34:38

They're going to keep charging an

34:40

Asenine price. They're going to be

34:42

saving a lot of time because

34:45

these deep research tools, there's a

34:47

reason why when Open AI launched

34:49

their deep research, they partner with

34:52

Bain. right? One of the biggest

34:54

consulting firms in the world. And

34:56

you go look at that little

34:59

case study and it's like, oh,

35:01

okay, yeah, like you could see

35:03

that deep research tool can do

35:06

the work of a junior, probably

35:08

better and exponentially faster. So what

35:10

happens then? Are these consulting firms

35:13

going to continue to charge this

35:15

same amount? They're charging, right? If

35:17

an AI tool can get 80%

35:20

of the work done, in

35:22

10% of the time. Okay, so

35:24

I think half of them will.

35:26

They'll continue to do business as

35:28

normal, whether they are outwardly communicating

35:30

that they're using these new deep

35:33

research tools, which is essentially a

35:35

consultant, but better, faster, more accurate,

35:37

sorry to my friends and consulting.

35:39

I already came to that realization

35:41

myself. Chad GBT is a better,

35:43

faster, writer than me. Okay. fear

35:45

in the consulting industry. Now open

35:48

AIs deep research, Google's deep research,

35:50

open even Microsoft announced theirs. Within

35:52

a month or two, once they've

35:54

worked out the Kinks, it's gonna

35:56

be better than most consultants. Okay,

35:58

so out of those 1,000 consultancies,

36:00

I see half of them continuing

36:02

to go on with traditional methods.

36:05

And I think that they're eventually

36:07

by doing that, they're going to

36:09

lose the top and bottom 20%

36:11

of clients. All right? Because the

36:13

top 20% they're going to know

36:15

and they're going to have their

36:17

own essentially internal consultancy spinning up

36:19

and they're going to be like

36:22

all right we don't need to

36:24

pay this big four company eight

36:26

figures a year anymore we're cutting

36:28

that and then they're going to

36:30

lose the bottom 20% of clients

36:32

right so those smaller businesses were

36:34

normally hiring a big four is

36:36

a huge expense and it's painful

36:39

but they feel they must they're

36:41

not going to do it either

36:43

so these big consultancies I think

36:45

they're going to lose the top

36:47

20% of 20% other clientele over

36:49

the next two years massive layoffs

36:51

because they're going to get crushed.

36:53

Right. The other half, I think

36:56

you're going to do it the

36:58

right way. They're going to adjust

37:00

their prices. They're going to provide

37:02

better, faster, and more accurate services.

37:04

Right. You're not going to have

37:06

to go on a quarter long

37:08

seven figure endeavor with some of

37:10

these big name consulting consulting companies

37:13

anymore because they'll realize, okay. If

37:15

we want to stick around this

37:17

in the long term, right? You're

37:19

seeing all these stories. Now the

37:21

big, big four consulting companies aren't

37:23

hiring as much anymore because I

37:25

think they're starting to understand that

37:27

this is a threat to their

37:30

traditional way of doing business, right?

37:32

So what I think, half of

37:34

those, so again, easy math, 500

37:36

are going to have massive layoffs,

37:38

500 are going to pivot and

37:40

shift their business model. But for

37:42

those that have massive layoffs, what's

37:44

going to happen? is you have

37:47

very smart people that are gonna

37:49

be out of a job. What

37:51

are they gonna do? They're gonna

37:53

crush their competitor. They're gonna crush

37:55

their previous employer. Because they're gonna

37:57

know, oh wow. you know, we're

37:59

using AI, and you know, we're

38:01

just, you know, pocketing the profit,

38:04

let's come in, let's do the

38:06

same thing, let's go steal these

38:08

clients, and let's charge them 10%.

38:10

Let's charge them 10% of what

38:12

that they were doing at the

38:14

big four, the big eight, whatever,

38:16

right? And I'm not trying to

38:18

call you guys out. I know

38:21

we have listeners there, so hopefully

38:23

you all aren't mad at me

38:25

for saying this, but this is

38:27

the truth. that are going to

38:29

be 10% of the price. It's

38:31

going to be the same people

38:33

that were working there. And it's

38:35

going to be faster. It's going

38:38

to be better because they're going

38:40

to leverage AI. And they're going

38:42

to do what I like to

38:44

call expertise in the loop. I

38:46

think we need to stop talking

38:48

about human in the loop. I

38:50

just had a great conversation with

38:52

someone last night from Gardner, actually

38:55

on the shuttle ride back from

38:57

the sphere. which was a fun

38:59

event. You know, Google announced, you

39:01

know, they're kind of like remaking

39:03

with AI with their VO tools

39:05

and, or Vio tools and others,

39:07

you know, they're kind of remaking

39:10

the Wizard of Oz with AI,

39:12

you know, to fit on the

39:14

sphere big screen, which was, you

39:16

know, pretty cool. So I was

39:18

having a conversation with a researcher

39:20

from Gartner on the way back

39:22

about this, about this very thing,

39:24

and just, you know, how, I

39:27

think we're going to see hundreds,

39:29

hundreds, probably thousands of hyper niche

39:31

consulting services. So now apply that

39:33

same scenario, applied across legal, legal

39:35

is going to get hit hard,

39:37

financial services, you know, CPA accounting,

39:39

etc. That's what's going to happen.

39:41

We're going to see a huge

39:44

disruption in traditional service industries. All

39:46

right. Yeah. Douglas

39:48

saying consultants could be some of

39:50

the $20,000 a month access to

39:52

open AI service that have been

39:54

referenced. Yeah, that's a good point

39:56

Douglas. Yeah, there's there's always these

39:58

rumors out that. You know, all

40:00

these big, you know, tech companies

40:02

are working on these versions of

40:05

their models that are going to

40:07

cost thousands of dollars a month.

40:09

So yeah, maybe, maybe there is

40:11

something much better. Obviously, Open AI

40:13

did announce that we're going to

40:15

see an O3 full. We're going

40:17

to see an O4 mini soon.

40:19

So I do assume that their

40:21

deep research tools are going to

40:23

get updated because Google's that they

40:25

just announced. And looking at some

40:28

early benchmarks, it's extremely impressive. Yeah,

40:30

Monica saying, I already see on

40:32

LinkedIn people leading huge companies and

40:34

high level positions to start their

40:36

own businesses and their specialty. That's

40:38

a great point. And I'm not

40:40

going to name names, right? But

40:42

I've had many, many conversations. Many

40:44

people reach out to me and

40:46

I'm like, hey, Jordan, I'm at

40:48

a big company. Companies you all

40:51

have heard of. Right. And they're

40:53

like. I know I can

40:55

go out and start my own thing.

40:57

And that's going to happen a lot.

40:59

And that's why, you know, my kind

41:01

of point number three, you know, kind

41:03

of the impact on future employment. I

41:06

don't think traditional full-time US employment is

41:08

going to look the same because of

41:10

this very recent, right? And I don't

41:12

think it's wild to think that people

41:14

are going to spin off and they're

41:16

going to have multiple, right? they might

41:18

have two or three of their own

41:20

businesses that they own and they provide

41:23

services and then they might be you

41:25

know kind of freelancing for five to

41:27

ten more. I think that's going to

41:29

be it's going to be very common

41:31

just like I said it's it's common

41:33

for maybe your Uber driver to also

41:35

do task rabbit and to also do

41:37

I don't know I forget you know

41:40

door dash right so it's it's very

41:42

common for someone that's already in this

41:44

gig industry to do two three four

41:46

five and I think it's going to

41:48

be the same knowledge workers, you know,

41:50

with 15 years of experience in corporate

41:52

America, highly educated, you know, they're going

41:55

to be doing this exact same thing.

41:57

All right, let's go to five. This

42:00

one's tough, if I'm being honest. Again, these

42:02

are, you know, some of the highlights of

42:04

my first 500 shows and, you know, it

42:06

goes without saying or maybe I should say

42:08

it. You know, I've obviously got to speak

42:11

with some of the smartest people in AI.

42:13

So these are just my thoughts, right? That's

42:15

the fun thing about having a podcast. I

42:17

can just say, I can open my email

42:19

in, you know, any given week, I

42:21

have a couple dozen people pitching to come

42:24

on the podcast and I can be like,

42:26

who I want to steal knowledge from today.

42:28

Right. Who do I want to like,

42:30

I want to get some secrets from

42:33

someone and I want to share those,

42:35

you know, AI secrets with everyone else.

42:37

So, you know, I've been lucky enough

42:39

to kind of steal some secrets and,

42:41

you know, absorb knowledge from people across

42:44

all different industries, you know, huge, you

42:46

know, tech trillionaire companies to startups, you

42:48

know, medium enterprise, enterprise

42:50

businesses. But one of the biggest things

42:52

that I see is redefining human

42:54

skill and value. And that's going to

42:57

be tough. Right. I think it's going

42:59

to be especially tough if you are in

43:01

like the 30 to 50 year old range

43:03

right now. If you're younger, you know, maybe

43:06

you grew up on the tail end of

43:08

chat. GPT or, you know, if you're

43:10

still in college, I think it's going

43:12

to be a little easier. You know,

43:15

if you're more closer to retirement, I

43:17

don't think this is going to impact

43:19

you as well. But, you know, for the most

43:21

part, for 30 plus years, the

43:23

way that business has worked here in

43:26

the way that you know. Right

43:28

and then you have to be able

43:30

to sit in front of a computer

43:32

and you have to make

43:34

your company more money based on

43:36

what you know It's not gonna be

43:39

like that It's not gonna be like

43:41

that anymore It's weird right

43:43

and the more smart people

43:45

I talk to about this exact

43:47

thing sometimes the harder it is

43:49

for me to even grasp it

43:51

Right, but I mean, let me just

43:54

talk about even myself Right so

43:56

so my skills right so

43:58

I've been working full-time since

44:00

when I was 16

44:02

or 17. So more

44:04

than 20 years, I've

44:06

been working full time.

44:08

And for the most

44:10

part, you know, those

44:12

have been in roles

44:14

like, you know, I

44:16

was a writer, strategist,

44:19

marketer, advertiser, etc. So

44:21

let's just say, digital,

44:23

marketing, advertising, writing, etc.

44:25

My skills don't matter

44:27

there anymore. They

44:30

don't. Matters in a different way.

44:32

It's almost like I think that

44:34

many of us are going to

44:37

become tastemakers in very niche ways.

44:39

I don't know if that makes

44:41

sense. But now as an example,

44:43

even what I do, right? Yes,

44:46

I still sit down and you

44:48

know, I write my newsletter, but

44:50

aside from that for all those

44:53

other things, I'm using AI. And

44:55

so doing jobs that I used

44:57

to do. Right, even even researching.

44:59

I used to spend so much

45:02

time researching. And, you know, as

45:04

a former journalist, I really valued

45:06

my, you know, my, my, my,

45:08

my researching and analytical skills. I'm

45:11

a tastemaker now. So what that

45:13

means is I, I hand that

45:15

job off, I give agency. to

45:18

go do that research, to go

45:20

be that the creative strategist, to

45:22

multiple large language models. And then

45:24

essentially it's like, oh, I have

45:27

them report back to me. I

45:29

am a curator and I am

45:31

a tastemaker in terms of my

45:33

skills for things that I've been

45:36

doing for 20 years, right? So,

45:38

hey, different AI models, go put

45:40

together a strategy plan on this.

45:43

Hey, different AI models. I need

45:45

new advertising. Here's all the data.

45:47

Here's our results. Go out and

45:49

work. Go do this. And then

45:52

they come back to me. I

45:54

curate. And it's almost like I

45:56

taste make, right? I'm like, okay,

45:58

this is good. This is past.

46:01

this is passing the vibe check,

46:03

this isn't, right? So I think

46:05

as we look at where our

46:08

skills are, because here's the thing,

46:10

that thing that you've been getting

46:12

paid to do for 10 years,

46:14

in most cases, if you haven't

46:17

already found the AI tool or

46:19

the large language model that does

46:21

it better, you will very soon.

46:23

And a lot of times it's

46:26

just going from the piece to

46:28

the system. Right? And that's this

46:30

phase of generative AI that we're

46:33

in right now, right? So from

46:35

large language model, going to AI,

46:37

going to a gentic AI, going

46:39

to multi-agentic AI, right? With huge

46:42

context windows, with rag, right? With

46:44

up-to-date dynamic data. So I'm not

46:46

saying your skills are useless. You're

46:48

just kind of using them in

46:51

a different way. Right, so hopefully

46:53

that example where I used to

46:55

physically go right, right, I still

46:58

do that, but a lot of

47:00

times for some things, AIs, we

47:02

need it. I'm so getting my

47:04

input in on the front end,

47:07

for the, for like, for some

47:09

things, I used to be the

47:11

digital strategist, not anymore. It looks

47:13

a little different now, right, because

47:16

unfortunately, the business were in the

47:18

US. It's make more money in

47:20

less time, right? It's, it's, it's,

47:23

it's, especially if you work at

47:25

a public company. Sad, it's sad

47:27

to think about, you know, we

47:29

are, we are a headcount. Companies

47:32

will fire you tomorrow. Doesn't matter

47:34

if you're a director of blah

47:36

blah blah blah or senior manager

47:38

of important project, doesn't matter. As

47:41

soon as that, that board, you

47:43

know, and they're looking at the

47:45

stock price. And they're like, oh

47:48

look, when we use AI, this

47:50

sector of our business is bringing

47:52

in so much money and this

47:54

sector isn't. They don't care about

47:57

it. They don't, right? I'd hate

47:59

to be that person. Unfortunately, in

48:01

America, corporate greed is at an

48:03

all-time high, I did a show

48:06

on that. It was actually very

48:08

telling, right, how much executives at

48:10

these large, you know, Fortune 500

48:13

companies make. And when they see,

48:15

oh, when we can, you know,

48:17

implement AI, multi-agentic AI in this

48:19

way, we can cut, you know,

48:22

20% of that department and still

48:24

make more money. they're going to

48:26

do it. They don't care about

48:28

you, they don't care about your

48:31

experience, they don't care about your

48:33

background. So that's why I think

48:35

it's important that we start to

48:38

redefine our not just human skills,

48:40

but also our value, right? And

48:42

I kind of shared a little

48:44

bit with you all about what

48:47

that was like for me. It

48:49

was weird. It was weird when

48:51

I saw all these different AI

48:53

tools that could be a better

48:56

writer than me, could be a

48:58

better. advertiser than me, could be

49:00

a better researcher than me. It's

49:03

weird. You're gonna run into that,

49:05

right? But hopefully, you can hit

49:07

it head-on, right? Because I think

49:09

we do, you know, we've kind

49:12

of traditionally hung our hats on

49:14

a job title, right? It's like,

49:16

you know, you meet someone new

49:18

and they're like, hey, I'm a

49:21

marketing director. Oh, okay, well. wasn't

49:23

asking about that, right? But people

49:25

play so much of their identity

49:28

in their job title. And I

49:30

think that you have to be

49:32

willing to pivot from that, right?

49:34

And re-look at what your human

49:37

skills are and what your value

49:39

is as a human, right? There's

49:41

great, you know, deep podcast on

49:43

this, you know, sometimes it's people

49:46

that maybe, you know, like, okay,

49:48

Bill Gates. right he's he's had

49:50

some great podcast topics on this

49:53

obviously he's you know than all

49:55

of us. You know, but even

49:57

him talking about, okay, well, what

49:59

do we do in the future?

50:02

What's human purpose, right? When AI

50:04

is more powerful, you know, maybe

50:06

when we, you know, tiptoed toward

50:08

this artificial general intelligence, artificial super

50:11

intelligence. So I think you really

50:13

have to, I love using the

50:15

term unlearn. It's a turn, like,

50:18

I think I coined it. I

50:20

didn't hear anyone else talking about

50:22

it. You know, people are talking

50:24

about upskilling and reskilling, but I

50:27

think for this, we have to

50:29

redefine human skills, human values. So

50:31

you need to, if you haven't

50:33

already developed AI literacy, that's why

50:36

I do this every day. You

50:38

can join me for, you know,

50:40

I know sometimes these podcasts go

50:43

a little longer. This is my

50:45

five-hour show, y'all, I'm not gonna

50:47

make this a 20-minute one. But

50:49

you need to practice it every

50:52

day. You need to learn. Because

50:55

ultimately, I think what a

50:57

lot of us are doing,

50:59

instead of sitting in front

51:01

of a computer, creating business

51:03

value with our fingers and

51:05

with our brains, I mean,

51:08

we're still going to be

51:10

doing that, but AI and

51:12

agentic AI is going to

51:14

be doing the heavy lifting.

51:16

All right. Number six, I

51:19

got two more, y'all. Two

51:21

or three more. Human

51:24

in the loop, I already talked

51:26

about this, but you know, I

51:28

really think active human engagement in

51:30

AI orchestration is going to be

51:33

big. I really want to control

51:35

all delete, command a delete, every

51:37

time someone talks about human in

51:39

the loop. I think it's dangerous,

51:42

right, when we don't really explore

51:44

what that means, right? You know,

51:46

maybe you're new to AI, maybe

51:48

you're tuning in for, you know,

51:51

the first or second time, you're

51:53

like, okay, what's human in the

51:55

loop, right? You know, this is

51:57

one of those like blanket terms

52:00

people say to kind of, you

52:02

know, give everyone ease. It's like.

52:04

like, oh, well, is it weird

52:06

to, you know, be handing all

52:09

this out to large language models

52:11

and, you know, agentic AI? And

52:13

they're like, don't worry, human in

52:15

the loop, right? That's gonna keep

52:18

us safe. No, it's not, you

52:20

know, because I think human in

52:22

the loop, it's a problem because,

52:24

number one, you have thousands of

52:27

companies promoting, you know, agentic AI

52:29

is the best thing since sliced

52:31

bread. Also with slice bread like

52:33

that big of a deal. Sometimes

52:36

I just love getting a hunk

52:38

of French bread and just biting

52:40

into it. I don't need to

52:42

slice it. Anyways, you know, everyone's

52:45

like, oh, agentic AI, agentic AI,

52:47

right? So as business leaders, you

52:49

know, making decisions on, you know,

52:51

what tools and in models your

52:54

company should be using, all you're

52:56

seeing is a gentic AI and

52:58

you're like, you're like, you're human

53:00

in the loop, right? To me,

53:03

I don't think you know these

53:05

these thousands of companies trying to

53:07

push us agentic software Necessarily care

53:09

about human in the loop, right?

53:12

It's it's more of like a

53:14

You know, it's a warm blanket

53:16

on a cold day It's not

53:18

fixing anything. It's just making you

53:21

feel better about the exterior situation.

53:23

I really think we need to

53:25

pivot to talking just like we

53:27

shouldn't be talking about upskilling and

53:30

reskilling we need to talk about

53:32

un learning That's what you have

53:34

to do. We also need to

53:36

talk about expertise in the loop.

53:39

Human in the loop. I think

53:41

people are looking at it as

53:43

passive. It's like, okay, yeah, I'm

53:45

gonna read the prompts. Let me

53:48

check in on the agents. Good

53:50

job, agents. All right, I'm gonna

53:52

sit here and sip my coffee.

53:54

I'm the human in the loop.

53:57

I'm on an assembly line. You

53:59

know, making sure the assembly line

54:01

doesn't break. That's not it. Expert

54:04

in the loop. Right. Organizations need

54:06

to be sticking the right expertise

54:08

in this, in this, you know,

54:10

agentic AI. loop and you know

54:13

I talked a little bit you

54:15

know about AI orchestration so if

54:17

you're interested to that you know

54:19

go back and listen to our

54:22

2025 AI roadmap series where you

54:24

know I did have some dedicated

54:26

things on agent orchestration but you

54:28

know I don't think that's going

54:31

to happen this year completely I

54:33

do think that we're going to

54:35

see you know roles being created

54:37

at large companies I've already seen

54:40

it where someone's role is essentially

54:42

an agent orchestrator, right? And they're

54:44

essentially overseeing agentic systems. But we

54:46

need expertise in the loop, because

54:49

as we hand off more and

54:51

more agency, that's what we're going

54:53

through right now in 2025. And

54:55

that's one of the biggest takeaway

54:58

over 500 shows is we're giving

55:00

more and more agency, you know,

55:02

this generative AI wave started as

55:04

like, oh, this little program, this

55:07

AI chatbot is fun. Right. And

55:09

now we're at the point where

55:11

organizations are trying to offload as

55:13

much of their manual knowledge human

55:16

work as possible. So it's different

55:18

now. We need to be intentional

55:20

about sticking expertise in the loop.

55:22

And that's not just someone who's,

55:25

you know, a great prompt engineer

55:27

or a technical person. It's security.

55:29

Make sure you stick your expertise

55:31

in that loop. Right. Don't let

55:34

the, you know, one person. Don't

55:36

let a generalist. oversee a multi-agentic

55:38

AI operation, right? You need multiple

55:40

people. So I do think that's

55:43

another way how our human engagement

55:45

in our roles are gonna change

55:47

is we are gonna have expertise

55:49

in the same way, right? Like,

55:52

oh, you have your people, they

55:54

check in on your CRM, you

55:56

know, you have your project managers,

55:58

they're checking in the projects, I

56:01

think those, they're all just gonna

56:03

shift now, right? You're gonna have

56:05

these agentic loops performing a lot

56:07

of these manual knowledge based tasks.

56:10

that are hopefully fine tuned on

56:12

your data, but that's what it's

56:14

gonna turn into. All right, two

56:16

more quick ones, and I'm gonna

56:19

get. your questions, if you do

56:21

have anything, any questions, please, please

56:23

let me know. Some of these

56:25

comments are making me laugh, y'all,

56:28

this is funny. All right, number

56:30

seven, the AI race, it's exciting,

56:32

right? It's one of the top,

56:34

top takeaways, you all want to

56:37

the top takeaways. The AI race

56:39

is exciting, right? I'm a Chicago

56:41

guy, you know, growing up, watching

56:43

the 90s bulls, was an unworldly

56:46

experience, right. No one could compete

56:48

with them. You know, two three

56:50

peats, you know, MJ, Scotty Pippin,

56:52

Dennis Rodman, no one, no one

56:55

could compete when that group was

56:57

together. You know, I know that

56:59

they kind of swapped out characters

57:02

there between the two different three

57:04

peats. No one could compete with

57:06

them. You know, a couple months

57:08

ago. I would have said that's

57:11

how the AI race is going.

57:13

You know, maybe, I don't know,

57:15

maybe like October, I would have

57:17

said open AI is, they're the

57:20

90s bulls, right? They're running away

57:22

with this. No one can touch

57:24

them. Google and Microsoft have made

57:26

things very interesting, very interesting, right?

57:29

I'm fine, I'm fine saying this.

57:31

I'm literally partnering with Google, I'm

57:33

at Google Cloud Next. A year

57:35

and a half ago, I told

57:38

people, don't use Google Gemini. No,

57:40

don't. That started to change, you

57:42

know, in quarter, quarter, three and

57:44

quarter four of last year. I

57:47

think Google made some great hires.

57:49

They made some great restructuring. I

57:51

think bringing Gemini under deep mind

57:53

was probably a good call. Google's

57:57

right up there. using Gemini 2.5

57:59

Pro, it's such a weird experience,

58:01

right? As someone that uses large

58:04

language, models way too much, it

58:06

is baffling how powerful that new

58:08

model is from Google, and then

58:11

Microsoft as well. Microsoft has slid

58:13

under the radar, I don't know

58:15

how, with a lot of their

58:18

recent co-pilot announcements, right? Last Friday

58:20

at their, you know, 50th anniversary

58:22

celebration, they just announced like seven,

58:25

like, like, essentially, I called it

58:27

like a greatest hits. they like

58:29

I don't know if this is

58:32

what happened internally right but they

58:34

saw all these other you know

58:36

popular AI modes and they're like

58:39

yeah let's just go ahead and

58:41

release that for co-pilot right oh

58:43

like notebook LM right we can

58:46

put all your information and it's

58:48

gonna create you a customized podcast

58:50

yeah we're gonna do that for

58:53

co-pilot oh deep research yeah we're

58:55

gonna release that right Microsoft went

58:57

a little bonkers we're gonna get

59:00

a lot a lot more announcements

59:02

today at Google cloud as well

59:05

but what I'm saying is like

59:07

the the AI race it's actually

59:09

a race now Whereas, you know,

59:12

like I said, maybe maybe nine

59:14

months ago, you know, so for

59:16

the better part of 18 months,

59:19

it was just the Bulls dynasty.

59:21

No one could touch them. It

59:23

was not close. It's close now,

59:26

right? Which actually makes it a

59:28

little more difficult, I think, for...

59:30

all of us for business users,

59:33

right? I talk sometimes about you

59:35

need to choose your AI operating

59:37

system. That choice was a lot

59:40

easier nine months ago. Sometimes you

59:42

might have to use multiple, but

59:44

it is extremely competitive, which I

59:47

think is both exciting and also

59:49

frightening, right? Because now, you know...

59:51

the race toward right you like

59:54

you have a lot of these

59:56

companies now openly working toward artificial

59:58

super intelligence right And that

1:00:00

can be scary. And I

1:00:03

get that, right? So, you know,

1:00:05

I guess if Microsoft and Google

1:00:07

hadn't quote unquote caught

1:00:09

up to open AI,

1:00:12

you know, as business

1:00:14

leaders, it could have made

1:00:16

the AI adoption and

1:00:19

the AI transformation journey

1:00:21

a little less stressful,

1:00:23

right? But now. both fortunately and

1:00:26

unfortunately, you know, I think

1:00:28

we have three major players

1:00:30

that are on that like

1:00:32

first tier. And I think now

1:00:35

you have to constantly

1:00:37

be evaluating the quality

1:00:39

of these models for your domain,

1:00:41

right? So I think it's always

1:00:43

a good start. to look at the

1:00:46

kind of like quote unquote scientific

1:00:48

benchmarks right to look at the

1:00:50

you know MMLU and the MMM

1:00:52

MMU that the diamond all those

1:00:54

things and then the human preference

1:00:56

as well so the elo scores.

1:00:58

on the LM chatpot arena, but I

1:01:00

think also companies if you haven't

1:01:03

already, you need to start developing

1:01:05

your own domain specific company specific

1:01:07

evals, right? So it could be

1:01:10

as simple as, you know, a

1:01:12

hundred different, you know, quote unquote

1:01:14

prompts or, you know, a hundred

1:01:16

different tasks, right? And, you know,

1:01:19

as we talk about, you know,

1:01:21

what happens when you start, you know,

1:01:23

gaining, gaining time back? Well, this

1:01:25

is what you need. You need

1:01:27

an evals team. and this is

1:01:29

going to be one of your

1:01:32

busiest teams in your organization. They

1:01:34

need to be constantly manually running

1:01:36

those, you know, 100, you know,

1:01:38

tests, those 100 use cases through

1:01:40

these models on a weekly basis

1:01:42

and doing your own quote unquote

1:01:44

internal ethos, right? Because the large

1:01:46

language models themselves are becoming commoditized,

1:01:48

right? You can, you know, there's

1:01:51

systems pretty easily, you know, if

1:01:53

you're working on the API side,

1:01:55

you can swap a model out fairly

1:01:57

easily. So you have to understand.

1:02:00

What all the major players are

1:02:02

doing, you have to know how

1:02:04

to evaluate them all internally in

1:02:07

order to keep up. All right,

1:02:09

I'm gonna tackle a couple of

1:02:11

these questions. So thanks for getting

1:02:14

them in and I have one

1:02:16

more thing to wrap up. I'm

1:02:18

gonna end on a personal note.

1:02:21

if that's okay with you guys.

1:02:23

So Melissa says, what's the most

1:02:26

impressive or game-changing AI development? You've

1:02:28

experienced a date. Oh, Melissa, that's

1:02:30

a tough question. You know, I've

1:02:33

talked about this. I never had

1:02:35

the chat GBT moment when chat

1:02:37

GBT came out. I was like,

1:02:40

you know, I think at the

1:02:42

time their GBT technology was being

1:02:44

better used and better utilized by

1:02:47

third party people. So chat GBT,

1:02:49

that wasn't it for me. If

1:02:51

I'm being honest, I would say

1:02:54

notebook LM. was probably one of

1:02:56

them. I'm still astonished at the

1:02:58

at the team that puts that

1:03:01

together. I'll also say open AIs,

1:03:03

deep research, you know, which now

1:03:05

might be Google's, you know, I'll

1:03:08

have to see. I would say

1:03:10

those are probably some of the

1:03:13

most impressive, but again, I don't

1:03:15

press easily, I guess. Also, GPT-40

1:03:17

ImageGen, you know, that just came

1:03:20

out, very impressive. Jackie is asking,

1:03:22

have you switched to Android? Not

1:03:24

yet. I don't, like, Jackie, you

1:03:27

probably know, I can't text. If

1:03:29

any of you guys ever text

1:03:31

me or DM me, I can't

1:03:34

do anything on my phone. So

1:03:36

that's one reason why I'm still

1:03:38

on a Mac is just so

1:03:41

I can text people on my

1:03:43

computer a little faster. Brian, Brian,

1:03:45

man, Brian's been showing up for

1:03:48

like two years. You're awesome. Brian's

1:03:50

asking, what are you most excited

1:03:53

about? I'm most excited. about non-technical

1:03:55

people. Finally, discovering what the rest

1:03:57

of us have been doing for

1:04:00

the past year or two. That's

1:04:02

honestly what I'm most excited for

1:04:04

because then it makes education a

1:04:07

little bit easier, right? Companies hire

1:04:09

us a lot to train their

1:04:11

employees and, you know, whether it's

1:04:14

a dozen or hundreds, if it's

1:04:16

difficult, it's difficult to go train

1:04:18

someone on generative AI, right? When

1:04:21

I go into a room with

1:04:23

100 people and a third of

1:04:25

them use generative AI for three

1:04:28

hours a day and a third

1:04:30

of them have never done it.

1:04:32

So I'm personally like maybe that's

1:04:35

a cop out. I'm personally excited

1:04:37

for people that haven't used generative

1:04:40

AI. to start using it and

1:04:42

to start discovering it because what

1:04:44

that happens is, you know, it's

1:04:47

like, oh, it raises the tide

1:04:49

for all ships, right? It does.

1:04:51

And I think, you know, so

1:04:54

many organizations have been limited on

1:04:56

the top side, just because, you

1:04:58

know, like such a high percentage

1:05:01

of their organization doesn't know what

1:05:03

generative AI is. They don't know

1:05:05

how it works. Another

1:05:07

good question here, any suggestions on

1:05:10

how to get late adapters to

1:05:12

embrace and see the value of

1:05:14

Gen AI? I think a lot

1:05:16

of it, you know, I kind

1:05:18

of gave the example of my

1:05:20

wife, right? I'm always telling her

1:05:23

like, oh, you know, hey, this,

1:05:25

this, this, and you know, bless

1:05:27

her for like still, you know,

1:05:29

listening to me, you know, two

1:05:31

years later, talk about AI, but

1:05:34

for her, I think. She needed

1:05:36

AI in her personal life, right?

1:05:38

I think, you know, it's like

1:05:40

quite literally handsful, you know, talk

1:05:42

to perplexity. And she's like, oh,

1:05:44

wow, you know, and now I

1:05:47

think, you know, you know, I

1:05:49

don't want to speak for her,

1:05:51

but I think maybe she'll think

1:05:53

a little bit differently. And I

1:05:55

think this is just more in

1:05:57

general. When people. find value of

1:06:00

AI personally and, you know, give

1:06:02

them a couple of months, then

1:06:04

it's just gonna change their brain,

1:06:06

right? It is this un learning

1:06:08

process. You know, so I think

1:06:10

that for late adapters, right, it's

1:06:13

not like, all right, let's sit

1:06:15

down in Microsoft Copilot Studio and

1:06:17

we're gonna no code your job

1:06:19

away. No, it's like, hey. Oh,

1:06:21

what's that? You have three kids

1:06:23

and it's hard to get a

1:06:26

meal schedule because, you know, one

1:06:28

is allergic to peanuts, one only

1:06:30

eats peanut butter and, you know,

1:06:32

the other one hasn't touched a

1:06:34

vegetable and, you know, okay, use

1:06:36

chat TVT to meal plan, right,

1:06:39

like talk to it, right? So

1:06:41

I think when when business leaders

1:06:43

who are still not using generative

1:06:45

AI, you can't continue to fight.

1:06:47

the battle on the same battlefield,

1:06:49

right? They need to get it

1:06:52

at home. And I think that's

1:06:54

what we're starting to see a

1:06:56

lot in 2025, you know, strangely,

1:06:58

strangely enough. All right, let me

1:07:00

just double check. Any more questions

1:07:02

before I wrap this thing up?

1:07:05

All right, good, good one here

1:07:07

from CM on YouTube, saying how

1:07:09

will the new economies work in

1:07:11

practice? If white collar workers don't

1:07:13

have jobs, how will they pay

1:07:15

for the people who do the

1:07:18

manual work? I'm trying to imagine

1:07:20

how the new systems will work.

1:07:22

Yeah, I don't know. This is

1:07:24

why, you know, a lot there's,

1:07:26

and I did say this in

1:07:29

my 2025 AI prediction and roadmap

1:07:31

series. I do think UBI. I

1:07:33

don't think it's gonna happen, universal

1:07:35

basic income, but I think it's

1:07:37

gonna actually be a common discussion.

1:07:39

now, right, especially with how the

1:07:42

US economy is headed right now.

1:07:44

So I don't know. What I

1:07:46

will say to this question is

1:07:48

I think, like I said, I

1:07:50

think full time, nine to five

1:07:52

employment in 10 years is going

1:07:55

to be, it's going to look

1:07:57

a little antiquated, right? And when

1:07:59

I said that the first time,

1:08:01

like a year and a half

1:08:03

ago, I think people thought I

1:08:05

was weird. And then the LinkedIn

1:08:08

CEO said something similar and now

1:08:10

people are like, oh, okay, yeah,

1:08:12

that adds up, right? You know,

1:08:14

saying, hey, traditional nine to five,

1:08:16

it's not gonna work in the

1:08:18

future of AI. This is not,

1:08:21

it's not going away, right, but

1:08:23

I do think a lot of

1:08:25

people, you know, are going to

1:08:27

have multiple. side hustles. They're going

1:08:29

to have multiple companies. They're going

1:08:31

to have multiple freelancing opportunities, right?

1:08:34

I do think that's how it

1:08:36

works, right? Obviously, there's still going

1:08:38

to be, you know, I think

1:08:40

the majority of US workers are

1:08:42

still going to have nine to

1:08:44

five jobs, but not by a

1:08:47

lot, right? Now it's like, okay,

1:08:49

I look around at everyone, right?

1:08:51

either a full-time worker or you

1:08:53

know, you know, raising kids and

1:08:55

their spouses is a full-time worker.

1:08:57

I don't think it's gonna be

1:09:00

like that in five years. You

1:09:02

know, maybe it's gonna be 60%.

1:09:04

Maybe it's gonna be 70% I

1:09:06

don't know, but you know, it

1:09:08

is, it is hard to tell.

1:09:10

All right, let me wrap this

1:09:13

thing up here. I just want

1:09:15

to end by talking a little

1:09:17

bit personally. I

1:09:20

started this show a little selfishly.

1:09:22

You know, I kind of started

1:09:24

it almost for myself. You know,

1:09:26

I did not envision it would

1:09:29

become this, you know, this time

1:09:31

intensive, right? Maybe I should have

1:09:33

listened to my wife and my

1:09:36

friend on that drive that one

1:09:38

day when they're like, are you

1:09:40

sure you want to do this

1:09:42

every day, right? But for me

1:09:45

and at least where my skill

1:09:47

sets were, I knew my skills.

1:09:49

first to go right writing and

1:09:52

marketing and in advertising and you

1:09:54

know some of those things I'm

1:09:56

like this is low-hanging fruit even

1:09:58

though at the time my agency

1:10:01

had the best month we'd ever

1:10:03

have, I'm like, this isn't going

1:10:05

to stick around for too long,

1:10:08

right? We weren't a, you know,

1:10:10

a multi-million dollar, you know, organization

1:10:12

with hundreds of employees, you know,

1:10:14

we're small. I did not envision

1:10:17

that every day AI would, would

1:10:19

turn into what it's turned into,

1:10:21

but I did start it for

1:10:24

me, but I started it probably

1:10:26

for you, right, because I was

1:10:28

able to. go through that process

1:10:30

in 2020, 2021, of learning AI.

1:10:33

And I'm like, this sucks, this

1:10:35

is hard. And I'm like, this

1:10:37

is my background, right? I was

1:10:40

a journalist, I interview people, I

1:10:42

talk to people, I tell stories,

1:10:44

right? And I've been in different,

1:10:46

you know, Martec Combs roles for

1:10:49

20 years. I'm like, from 2020

1:10:51

to 2022, I feel I at

1:10:53

least figured it out, right? I

1:10:56

got from a zero to a

1:10:58

five. So. I wanted to selfishly

1:11:00

get from a five to a

1:11:02

six, five to a seven. So

1:11:05

I'm like, all right, let me

1:11:07

start this everyday AI thing. You

1:11:09

know, maybe it'll fail. Maybe it'll

1:11:12

go for, you know, two months

1:11:14

and no one will care and

1:11:16

I'll stop. I'm glad I didn't

1:11:18

because here we are 500 episodes

1:11:21

later, you know, partnering with Google.

1:11:23

I've had partnerships with Microsoft and

1:11:25

Invidia and Adobe, some of the

1:11:28

biggest brands of the biggest brands

1:11:30

of the world. So I'm very,

1:11:32

very, very lucky. a big sense

1:11:34

of gratitude to you all for

1:11:37

tuning in like who like how

1:11:39

the heck are there still you

1:11:41

know all of you people I'm

1:11:44

rambling you know it's I'm an

1:11:46

hour ten in so thank you

1:11:48

all but I also did start

1:11:50

this for you right there's a

1:11:53

reason why you know our domain

1:11:55

is your everyday AI I mean

1:11:57

number one every day ai.com was

1:11:59

not available and I started this

1:12:02

thing but I do want this

1:12:04

to be yours. Right, so as

1:12:06

I look at the future, like,

1:12:09

will we have another 500 episodes?

1:12:11

I don't know. I don't know.

1:12:13

Maybe not, right? I'm a human.

1:12:15

I'm tired. Personally, I am tired.

1:12:18

I am exhausted. This is hard.

1:12:20

This is hard work. Yeah, this

1:12:22

is hard work. I don't sleep

1:12:25

a lot. I miss out on

1:12:27

a lot, which, man, like, blessed

1:12:29

up, like, my wife, she's amazing.

1:12:31

So if you benefit it from

1:12:34

everyday AI say say thanks Jordan's

1:12:36

wife I'm lucky I get to

1:12:38

show up, you know, you know,

1:12:41

click click go live at 730

1:12:43

a.m. Central and hopefully it helps

1:12:45

you and I know it has

1:12:47

because I've literally heard from hundreds

1:12:50

of you that have left testimonials

1:12:52

and you know, I read them

1:12:54

all and hear those stories, but

1:12:57

it's you know personally this is

1:12:59

a lot for it's been a

1:13:01

lot for me to take on

1:13:03

and I feel sometimes I fall

1:13:06

short but I think that's reflective

1:13:08

of probably how everyone feels about

1:13:10

AI. Right? Because it's like, hey,

1:13:13

no matter how much I try,

1:13:15

it feels like I'm always falling

1:13:17

behind. It feels like, you know,

1:13:19

oh, as soon as I got

1:13:22

this, this AI implementation going in

1:13:24

my department, it seems antiquated now,

1:13:26

right? There's all these new things

1:13:29

and it's hard, right? Succeeding in

1:13:31

today's business with the pace of

1:13:33

AI is difficult. So, you know,

1:13:35

I just personally, I wanted to

1:13:38

thank you all. I

1:13:40

mean, like in my wife, I

1:13:42

mean, she's amazing. Like what she's

1:13:45

able to do behind the scenes

1:13:47

to, because let's be honest, I

1:13:49

intentionally knew I wasn't gonna make

1:13:51

a dime off this thing in

1:13:53

the first year and I could

1:13:55

have, right? There's a lot of

1:13:57

people. you know, as the show

1:13:59

started to grow a little and

1:14:01

they reached out and, you know,

1:14:03

they're like, oh, you know, I

1:14:05

want to, you know, pay you

1:14:07

and I'll give you money and

1:14:09

I'm going to put my product

1:14:12

on your podcast and I'm like,

1:14:14

no, your product stinks, right? So

1:14:16

it was very hard for me

1:14:18

to not make a dime, right,

1:14:20

not make a dime from this

1:14:22

endeavor. Yes, I still have my

1:14:24

other business. We still have clients,

1:14:26

but I spend the majority of

1:14:28

my time on everyday time on

1:14:30

everyday AI and everyday AI and

1:14:32

I had so many opportunities. to

1:14:34

monetize this thing. So maybe I

1:14:36

could sleep a little more, right?

1:14:38

Maybe I could be a little

1:14:41

more present in my personal life.

1:14:43

But I didn't want essentially, right,

1:14:45

even, it's hard to say no

1:14:47

to money when you're starting something,

1:14:49

right? I didn't want to bring

1:14:51

on, you know, advertisers and, you

1:14:53

know, for you all, if I've

1:14:55

gained your trust. I didn't want

1:14:57

you to start using these things

1:14:59

and then it's like, okay, six

1:15:01

months later they're gone. Why did

1:15:03

you, you know, bring this little

1:15:05

AIs startup and, you know, I

1:15:08

trusted you and, you know, I

1:15:10

got my company on board and

1:15:12

now this thing went under, right?

1:15:14

So it's been extremely hard to

1:15:16

do this 500 straight Monday through

1:15:18

Fridays, right? So first of all,

1:15:20

I wanted to thank you all.

1:15:22

your words of encouragement, you know,

1:15:24

sticking with these rambling podcast, but

1:15:26

you know, I hope they're helpful

1:15:28

in some regards. Like I said,

1:15:30

I feel so much information now

1:15:32

about AI, just information in general,

1:15:34

it's robotic, right? Everyone uses the

1:15:37

same formula, it's copy and paste.

1:15:39

That's not me. I'm real. I

1:15:41

want to be able to tell

1:15:43

you when something's good, when something's

1:15:45

bad, when something's hard, when something's

1:15:47

easy. And this hasn't been, you

1:15:49

know, 500 episodes hasn't been easy,

1:15:51

but it's been worth it. So,

1:15:53

you know, I do want to

1:15:55

thank, you know, all of you,

1:15:57

you know, our partners, you know,

1:15:59

at places like Google, Microsoft. you

1:16:01

know, Adobe and video, you know,

1:16:04

that's obviously been helpful to work

1:16:06

with big brands. You know, all

1:16:08

of you that have supported me,

1:16:10

you know, sometimes it's just like

1:16:12

one little comment, you know, I'll

1:16:14

have a bad show and, you

1:16:16

know, at the bottom, I'll say

1:16:18

someone's, you know, someone that I've

1:16:20

never seen before, right? They're like,

1:16:22

you know, I've been listening for,

1:16:24

you know, a year and a

1:16:26

year and a year and, you

1:16:28

know, and it sucked, right? And

1:16:30

then someone's like, hey, I got

1:16:33

tons of value out of this

1:16:35

and I went back to my

1:16:37

company and we were very uncertain

1:16:39

in this area and now we're

1:16:41

certain. So thank you for that.

1:16:43

I don't know. What do you

1:16:45

guys want for the next 500

1:16:47

episodes? I'm not getting any younger,

1:16:49

you know, I wouldn't encourage everyone

1:16:51

go back and, you know, screenshot

1:16:53

maybe me from from two years

1:16:55

ago. I've probably aged like 20

1:16:57

years. It's been fun. It's been

1:17:00

an adventure. So my top takeaway,

1:17:02

I'm grateful for you all. I'm

1:17:04

grateful. to my wife, to everyone

1:17:06

who's shown support out there at

1:17:08

all. So thank you for tuning

1:17:10

in to 500 episodes. If you

1:17:12

haven't already, please go to your

1:17:14

everyday ai.com. I don't know how

1:17:16

I'm gonna wrap this one up,

1:17:18

but I'm gonna do it anyways

1:17:20

in our daily newsletter. So thank

1:17:22

you all for all of your

1:17:24

support for everyday AI. I hope

1:17:26

to see you back tomorrow and

1:17:29

every day for more, everyday AI.

1:17:31

Thanks y'all. And that's a wrap

1:17:33

for today's edition of everyday AI.

1:17:35

Thanks for joining us. If you

1:17:37

enjoyed this episode, please subscribe and

1:17:39

leave us a rating. It helps

1:17:41

keep us going. For a little

1:17:43

more AI magic, visit your everyday

1:17:45

ai.com and sign up to our

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1:17:49

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1:17:51

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