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Market Hang (12:30–1:30 p.m. ET)

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Market Hang (12:30–1:30 p.m. ET)

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1754 segments

0:00

Hey, welcome to the market hang. I'm

0:01

Dandy D Franchesco. We have Jess here.

0:03

We have Julie here. We have Jed here.

0:05

It's the J show. Um and

0:07

>> I didn't even think about that, isn't

0:08

it?

0:09

>> Yeah, it's all the J's JJ and D. Um so

0:13

we've been talking a lot, you know, are

0:15

things going to go bad? Are things going

0:16

to go bad? And and in this sea of

0:18

markets, right, the the stock market

0:20

ship has faced a lot of headwinds, but

0:21

the what the gust in the sales has been

0:23

earnings time and again, it's pushed it

0:26

through everything, and earnings are

0:28

starting up again. and uh PepsiCo

0:31

reported and you know we had a very

0:34

interesting point made on yesterday's

0:35

show. It's another reason why you should

0:37

be watching every day by Chris Versace.

0:39

So I want everyone to listen in to what

0:40

Chris said

0:41

>> before earnings. This is yesterday.

0:44

>> We're all talking about AI and tech. You

0:47

know that's 40% of the market tech

0:49

adjacent 50% of the S&P 500. So you got

0:52

to sit there and you got to wonder about

0:53

the other half.

0:54

>> Mhm. And then you take a look at the

0:56

run-up in diesel prices, cotton prices,

0:58

you know, all sorts of other inputs. You

1:00

look at the warnings that you've got in

1:01

the S&P um global US composite report

1:06

for August, September about input

1:07

prices, the pass through of output

1:09

prices, something's going to have to

1:11

give. Mhm.

1:12

>> And if you look at PepsiCo and their

1:13

fleet, you look at PepsiCo and their

1:15

snack business in the ingredients, you

1:17

look at PepsiCo in sugar prices,

1:20

>> to me, they're going to be they're

1:22

they're going to be like one of the

1:23

first reads outside of tech that tells

1:26

us about all of these things that have

1:28

been moving higher causing inflation.

1:33

>> Crystal ball apparently. And he knew.

1:36

And what do you know? PepsiCo reports

1:38

today and and what comes out? It lowers

1:40

its guidance. It says consumers are

1:42

looking for cheaper products. They're

1:44

they're, you know, they're not

1:45

completely pulling back, but they're a

1:47

lot more costconcious and it's pulling

1:49

down on their margins. I think the Pepsi

1:51

CEO also said, "We don't feel good about

1:52

the beverage industry," which is not

1:54

what you want to hear the CEO of a

1:55

beverage industry person say. So, I will

1:58

put it to all of you. Is this the uh to

2:01

again to rely on an old journalism term,

2:03

the canary in the coal mine? Are we

2:04

starting to get nervous or is this just

2:06

kind of the status quo? And look,

2:08

consumers are being more costconcious.

2:09

Jasmine, we'll start with you.

2:11

>> Um, we've already known that consumers

2:12

are being very costconcious, especially

2:15

on the lower end, and I have been

2:17

concerned with that consumer for quite

2:18

some time, especially with this

2:19

environment. But we're seeing rising

2:22

input costs. This is a squeeze on

2:24

margins. If this bleeds over into the

2:26

rest of earnings season, then we could

2:27

really have a problem because what's

2:29

carrying the market right now is

2:31

earnings momentum. it is concentrated in

2:34

AI and technology and that is broadening

2:36

a little bit but if this is more of a

2:38

constraint on a consumer then that could

2:40

have a ripple effect

2:41

>> and that's just something to pay

2:42

attention to

2:43

>> right Julie where do you come out

2:44

>> yeah I mean I don't think that Pepsi is

2:47

necessarily that big flashing warning

2:50

sign I mean first of all the stock is up

2:51

today which is interesting right and the

2:53

company seemed to open the door on the

2:55

call at least more than they have in the

2:57

past to the possibility of separating

3:00

the businesses

3:01

which have been there have been

3:03

questions about that in the past. I

3:04

think they've kind of dismissed it. So

3:06

this time they were a little bit more

3:07

open to that. Maybe that's one of the

3:09

reasons the stock isn't down more. Um

3:11

>> international also doing I think better

3:13

>> doing better than domestic for sure. And

3:16

so I don't know. I mean in terms of the

3:18

read through for other stuff from higher

3:20

costs to Jess's point like yes we're

3:23

going to see that across the board.

3:24

anything that is touched by diesel, by

3:27

agricultural costs of any kind, by some

3:29

of the tariffs that are still in pace

3:30

place. Aluminum for example, right? All

3:33

of that, we're going to see those cost

3:34

pressures make their way around anything

3:38

that has anything to do with that.

3:39

>> Jed, what about you?

3:40

>> Uh, we own Pepsi in our dividend select

3:42

strategy at Argent. So, I'm offended by

3:44

this whole

3:46

um uh ju just joking, not really. Um, we

3:50

own Pepsi because uh they pay a high

3:52

dividend and we think they can grow the

3:53

dividend, you know, five or six or 7% a

3:55

year. And in a diversified portfolio,

3:57

that's a good thing to have, especially

3:58

when times get tough. But I think all of

4:00

your commentary is right. Input costs

4:02

are rising. Consumers are being pickier

4:04

than normal. Consumers are shifting to

4:05

healthier snacks. Um, a breakup would be

4:08

beneficial. I think um Coke has, you

4:10

know, significantly outperformed Pepsi

4:11

over the years. So, uh, all of that is

4:14

true. I don't think it's a canary in the

4:15

coal mine. Um, I think that um um like

4:18

the like the spokesperson said, tech is

4:20

over half of the S&P 500. So that's

4:22

driving the boat and uh everything else

4:24

is way in the back of the boat and

4:26

Pepsi's back there.

4:27

>> Sure. I will throw in one more, right?

4:29

Constellation also came in this week,

4:31

showed that shipping was up, but

4:33

depletions, right? Constellation is the,

4:35

you know, owner of a bunch of, uh, you

4:36

know, beverage uh, companies, a lot of,

4:38

uh, beer, I think Medela and whatnot.

4:40

Um, but depletions, which is also what I

4:42

like to say when I use their product,

4:43

um, which is sending to the retailers,

4:45

that was actually down. So, again,

4:46

another little bit crack. So, I I

4:49

definitely see your point though, Jess,

4:50

to your point, like this is something

4:51

we've known for a while. It's a matter

4:53

of is it going to continue to kind of

4:55

spiral out to to the other players in

4:57

the market, right? That's when we start

4:58

to get nervous.

4:59

>> Yeah. I mean, and Constellation's

5:00

actually doing a little bit better than

5:02

some of its

5:02

>> sure

5:03

>> competitors even though it's not doing

5:05

great because there's a lot of sort of

5:06

headwinds in the in the alcohol

5:09

industry, right? There aren't enough

5:10

depletions. You're not doing your job.

5:12

>> I'm not doing my job. Yes, I'm not doing

5:14

my job. Um, I guess we're talking about

5:17

the consumer. I'm just going to jump to

5:18

it because I'm very excited about this.

5:20

There's been a report. Imagine a world.

5:23

You're like, you know what? What do I

5:24

need? I need some coffee. I'm going to

5:26

go to Starbucks. I'm going to get my

5:27

Venti cold brew. And you know what? I'm

5:29

feeling pretty hungry, too. Why don't I

5:31

get a burrito? The the the massive

5:33

combination, Starbucks and Chipotle.

5:36

Now, there's a lot to unpack here. I

5:37

mean, my first inclination is obviously

5:39

I think of I grew up very close to a

5:41

Duncan BaskinRobins. You have the KFC um

5:44

Taco Bell combo or KFC Pizza Hut. Um do

5:48

we think these are two brands that are,

5:50

you know, working on a turnaround,

5:51

right? And we can get to the CEO

5:52

flip-flop, too. Uh what is what stands

5:55

out to you? Again, this is all reported.

5:56

Nothing this is all, you know,

5:58

reporting. I think the FT was the one

5:59

that broke it. I know Sephor was in the

6:01

mix, too. So, nothing is definitive yet,

6:02

but um what do we make of these two very

6:05

big consumer brands potentially coming

6:06

together?

6:07

>> I mean, can I just chime in and say like

6:09

I'll leave you guys to talk about

6:10

whether it makes business sense. To me,

6:12

this is like Brian Nickel who obviously

6:14

was at Chipotle, had a very successful

6:16

run at Chipotle, and now is trying to

6:18

turn Starbucks around. And meanwhile,

6:20

Chipotle stock has been cut in half, and

6:21

he's looking back and he's like,

6:23

>> "Oh, man. What about my legacy? I was

6:25

the guy at Chipotle. What are we going

6:27

to do?" Well, we're gonna buy it and I'm

6:29

gonna do work my magic on it again. I I

6:33

I don't know. It feels a little like

6:34

that.

6:35

>> Plus, he hasn't moved since leaving

6:37

Chipotle. You know, he hasn't moved up

6:39

to he still lives where he's

6:41

>> right. So, do you think he secretly just

6:43

wants his old job back? Maybe. Um I've

6:45

I've never had a coffee in my life, so

6:47

I'm I'm unqualified to join this

6:48

discussion, but um I think it's a it's a

6:51

horrible idea. uh fixing Starbucks is is

6:53

yeah I think he thinks that fixing

6:55

Starbucks is harder than he than he

6:56

probably bargained for a year a year

6:58

year and a half ago and it would be easy

6:59

to buy something that he is cheap and he

7:02

knows um

7:03

>> J I'm sorry never had coffee

7:05

>> never not once

7:06

>> really are you a tea guy? No, no tea. My

7:09

wife, so you're not a caffeine guy,

7:11

>> correct?

7:12

>> Good for you.

7:13

>> Yeah.

7:13

>> Wow. Interesting. I almost I want to

7:16

give you a coffee and see like we're

7:18

going to unlock things. This is like

7:19

limitless.

7:20

>> I want to analyze all of his health

7:21

levels in comparison. That's the the

7:24

detail where my

7:25

>> wife's working hard on it. Um

7:28

>> if you've gotten this far without it, I

7:30

think you're probably in good shape.

7:31

>> Yeah, you're definitely better off than

7:32

the rest of us. Um, sorry, Jess. I Where

7:34

do you come out on this the Starbucks uh

7:36

Chipotle monster?

7:38

>> Um, I'm curious on this massive deal

7:41

just how they would fund it and what

7:43

that would look like because right now

7:45

we're in this capital constraint

7:46

environment. We're have equities

7:49

issuance to raise capital. We have free

7:51

cash flow coming down from big tech and

7:53

then that's going into the bond market.

7:55

So, how are they going to actually fund

7:56

it?

7:57

>> Interest rates are high today. I mean,

7:58

the financing on something like that

7:59

would probably be like seven or eight%

8:01

I'm guessing.

8:01

>> Yeah. But does does Starbucks have the

8:03

cash though? Don't they have I mean I

8:04

don't know. I haven't looked at their

8:07

>> Now I want to look at their

8:08

>> Yeah, I believe that they sold their

8:09

China subsidiary and probably improved

8:11

their balance sheet significantly when

8:12

they did that in the past year. So

8:14

>> I mean they have some cash. It looks

8:16

like they've got a not a huge amount

8:18

three and a half billion or so but um

8:20

and they already have some debt it looks

8:22

like.

8:22

>> Right. So Jed top line though a

8:24

combination not something that like oh I

8:26

want that in my portfolio. the history

8:28

of large consumer M&A and retail M&A is

8:32

very poor.

8:34

>> So I you know this is one where you're

8:35

like 9010 this is a bad idea.

8:38

>> Jess do you kind of land the same place

8:40

or do you see a little more optimism in

8:42

a potential deal here and for for

8:43

investors perspective

8:45

>> you know this is definitely not my area

8:47

of expertise in looking at M&A but from

8:50

I just think it's odd

8:51

>> as in I can't really point to anything

8:54

that is of recent of that. It seems like

8:56

an odd time to do that just to where the

8:57

consumer is. And I just think the timing

9:01

makes me question management.

9:03

>> Pumpkin spice burrito bowls. I mean,

9:06

guacamole frappuccinos. Guys, there's

9:08

real synergies here. I think we're

9:10

selling short on it.

9:11

>> Does it mix?

9:12

>> Julie, you mentioned the legacy thing. I

9:14

think another interesting thing I was

9:15

having this conversation before uh is so

9:18

have you ever had a friend you didn't

9:20

like their significant other and they

9:23

broke up and immediately you're like

9:24

thank god you got rid of that person

9:26

they're the absolute worst. Do you think

9:28

there's any people sitting in the uh in

9:31

Chipotle management that like the second

9:33

Brian was out the door maybe not

9:35

publicly maybe behind the back talking a

9:37

little trash and now they're like wait

9:38

he's coming back like

9:40

>> I think this is going to be a nightmare.

9:42

I'm pretty sure his reputation there was

9:44

pretty good.

9:44

>> I'm sure, but you never know. You

9:46

>> know, I I don't know. I you know, who

9:48

knows?

9:48

>> You know, people have, you know, once

9:50

somebody's out the door. Oh, I would

9:51

have done it way differently than that

9:52

guy. Um, not that I mean, he has a great

9:54

obviously reputation for for ways to do

9:56

Chipotle. Um, I guess do we think it's

9:59

tough, right? I know we're not M&A

10:01

bankers here, but ultimately, does

10:03

anyone want to put odds on the reality

10:05

of this happening? You know, I I trust

10:07

in FT's reporting and and stuff like

10:08

this and semaphore, but just curious if

10:10

this is the type of thing that it gets

10:11

floated and then it doesn't eventually

10:13

land.

10:14

>> Yeah, I would say low probability of

10:16

actually happening.

10:16

>> Yeah,

10:17

>> I think I think investor interest would

10:19

be real low from both sides of this

10:21

deal.

10:22

>> I mean, Starbucks shares are selling off

10:23

on this, so clearly we're already seeing

10:26

that vote. I mean, and I'm with you. If

10:28

you look at the history of consumer

10:30

conglomerates,

10:31

>> brands and stuff,

10:32

>> I mean, Pepsi obviously a different type

10:34

of business, but you know, melding

10:37

things together, unless there are really

10:38

clear synergies or strategic reasons to

10:40

do so. Chipotle is also a lot smaller

10:42

than Starbucks, like in terms of the

10:44

number, it's something like 20,000 plus

10:46

Starbucks and I think under 5,000

10:49

Chipotle, even though it feels like

10:50

they're everywhere, they're not

10:51

everywhere. Um, and so I just I just

10:53

don't know like what is it for? What do

10:55

you

10:55

>> who is this good for other than the CEO,

10:57

>> right? The ingredient, you know, if you

10:59

think about supply chain, the there's

11:00

not a lot of overlap in ingredients. I

11:02

also frankly like and this is something

11:04

I've said about I think Starbucks

11:07

quality is meh at best. And like I

11:10

remember when they bought um Labul or

11:12

whatever it was called when they brought

11:13

in the new food and they made that

11:14

acquisition, they were like the food's

11:15

going to be so good. And I'm like uh no

11:18

it is not.

11:19

>> And I actually think Chipotle is pretty

11:21

good in terms of the quality of the food

11:22

for a f, you know, for a chain. Yes.

11:24

>> Yeah.

11:25

>> And so like if it mean I don't know. I

11:27

just

11:27

>> What's your call? Are you a Duncan? Are

11:29

you a Waw Wa? Are you a Tim Hortons? I

11:32

know we don't get a lot of Tim Hortons.

11:33

>> Lately I've been making it at home.

11:35

>> Oh. Do you have a fancy setup?

11:37

>> Um I usually do um French press and

11:40

grind the beans and then make the French

11:43

>> or or I make it in the machine here.

11:45

It's like one or the other. It's just

11:47

the m the the office machine coffee or

11:50

the fancy coffee at home.

11:51

>> Jed, I know we're speaking a different

11:53

language for you right now. I don't know

11:54

what any of this means.

11:54

>> Yeah. Jez, are you a Starbucks or a

11:56

Duncan or where do you have a specific

11:57

preference or you kind of like whatever

11:58

is closest?

11:59

>> Um, I prefer a really good local coffee

12:02

shop to be honest. I like that. I do.

12:04

Um, also there is no event contract

12:06

officially. I was trying to see if we

12:08

could get at least

12:11

for CMG and and Starbucks there, but the

12:14

only connection that I could find is the

12:16

CEO and perhaps he just wants a

12:19

multibrand conglomerate. And we forgot.

12:22

I love breakfast burritos.

12:24

>> That is okay. We have

12:26

>> I don't I have a low degree of

12:28

confidence that it would be well

12:30

executed.

12:31

>> Oh, I I agree with that completely. I

12:33

think this is someone um

12:36

>> wanting to have a big conglomerate just

12:38

to have a big conglomerate is not a good

12:40

idea. We need we need the financials.

12:43

>> We need more fundamental reasons than

12:45

just uh it looks really cool if we have

12:47

these all. All right.

12:49

My dreams of a cold brew burrito combo

12:52

seem to be dashed. Um,

12:54

>> you just have to make multiple stops.

12:55

>> Yeah, you just have to make multiple

12:56

stops, which I know there's a bunch of

12:57

apps out there and I'll just use my muse

12:59

instinct to just, you know, ask, so

13:01

it'll be fine. There you go.

13:02

>> Um, so again, to get back to, you know,

13:05

beyond the consumer stuff, we're, you

13:07

know, more and more it feels like every

13:08

day another analyst or someone's coming

13:09

out saying, "Oh, this indicator is

13:11

showing that we're a lot closer to a

13:14

crash than we And I know this has been

13:16

the kind of the topic dour for a while

13:18

now. Um we talked about this yesterday

13:20

Julie about how we feel like there will

13:22

be a come down. Um when it will come and

13:25

to what degree it will be I think is the

13:27

question. But J Jess I want to bring you

13:29

in. Do you you know the bubble talk and

13:31

all this? How much do you buy into it?

13:33

How bullish or bearish are you feeling?

13:34

What's what's your sentiment right now?

13:36

>> Uh feeling pretty bullish. I don't think

13:38

there's a bubble. I don't think

13:39

anything's going to pop. I don't think

13:40

anything's going to crash. I think we're

13:42

um we're building new infrastructure for

13:44

a new, you know, type of computing and

13:47

uh we're in the middle innings.

13:49

>> Um interesting.

13:50

>> And so I think there's a long way to go.

13:51

I think Nvidia is going to grow their

13:52

revenue a lot next year and the year

13:54

after that. And I think that the big

13:55

tech companies are making um high return

13:58

investments in these data centers and

13:59

they're going to keep going.

14:00

>> Okay.

14:01

>> So um we uh we think the outlook for the

14:03

stock market is really good. So no the

14:06

circular financing the trying to find

14:08

product the the revenue none of that

14:10

gives you sweat makes your palm sweaty.

14:12

>> We uh the circular financing is worth

14:14

paying a lot of attention to. I think

14:16

Nvidia has made um guarantees and um you

14:20

know like backup facilities and stuff

14:22

like that to about $600 billion worth of

14:25

of um of loans and that's a heck of a

14:28

lot but their their EBITDA is over 200

14:30

billion now and growing. So I think in

14:33

the scope of their balance sheet and

14:35

with a $6 trillion market cap um 500

14:38

billion is actually manageable and thus

14:40

far actually Nvidia's made a lot of

14:42

really good investments. If you look at

14:43

coreweave, if you look at um a lot of

14:45

their model maker investments in private

14:47

companies, they've actually invested

14:48

really well. So we think um uh

14:51

management of Nvidia and also the big

14:52

tech companies deserve the benefit of

14:54

the doubt and are doing very well thus

14:56

far.

14:56

>> Yeah, Jess.

14:58

>> Yeah, I I completely agree. I think the

15:00

market is in a healthy spot. I do think

15:01

it's been rather narrow just as of late,

15:04

but I think that what's happening

15:06

underneath the surface is actually

15:08

looking better from a technical

15:09

perspective and that gives me more

15:12

positivity.

15:13

>> What do you mean what's been looking

15:14

better

15:14

>> as as in every other sector aside just

15:17

from technology? I think we focus on

15:18

that because it has been holding up the

15:20

market. But there they they were coming

15:23

down breaking all my technical levels

15:25

and now I'm seeing areas of support

15:26

which means that I

15:27

>> in the other groups

15:28

>> in the other groups. So I want to see

15:29

broadening now more specifically from

15:32

that's a technical perspective solely.

15:34

Now what my biggest risk is that I've

15:36

I've flagged within the market right now

15:38

is what's happening with yields.

15:40

>> If we can get a ceiling on the 10-year

15:43

that would be really great for the

15:44

equity market and that has a lot to do

15:46

with oil as well. So once we

15:48

>> get some stabilization I think that's

15:51

all that the bulls need. We just need

15:52

some stabilization within yields. It's

15:54

not necessarily them coming down just

15:56

being stable. Well, we see right here

15:58

it's, you know,

15:59

>> yeah,

16:00

>> you know, okay,

16:01

>> that's Yeah, but one day doesn't make

16:02

stability.

16:03

>> Yeah, I know.

16:04

>> Little wins, Julie. We're looking for

16:06

little wins, you know, here and there.

16:07

But, okay. So, yeah. And I and I think

16:09

to the to both of your points, right?

16:11

Even if ultimately there will be a drop,

16:13

like you can still be right but be wrong

16:15

because if you're screaming like you got

16:16

to get out, hold cash or whatever, and

16:18

the market keeps rising, even if

16:19

eventually drops, you're missing out on

16:20

obviously all those gains, you know. So,

16:22

I Yeah, I I told Julie, what do you what

16:24

do you think? Are you as optimistic as

16:25

these two? Well, we you know I'm not

16:27

because we talked about it yesterday.

16:29

No, I mean listen, do I think that

16:30

things are going to crack tomorrow or

16:33

even next year? Not necessarily. Do I

16:35

think like to Jed's point, are there

16:36

things to pay a lot of attention to?

16:38

Absolutely. And do I think everyone's

16:41

going to be a winner? Like for example,

16:42

do I see a scenario where um the Nvidias

16:45

of the world could still do great, but

16:46

open AI and Anthropic that their busts,

16:49

that their IPOs don't go well, that

16:51

there's not a lot of demand, that they

16:52

get supplanted by some of the openweight

16:55

models? I think that's not a zero

16:57

chance, right? Is it a 50-50 chance? I

17:00

don't I don't know about that. But like

17:01

there are definitely um scenarios in

17:03

which a not everybody's a winner and b

17:05

that there are um some areas of weakness

17:08

that could spill over into bigger parts

17:10

of the market. Sure.

17:11

>> I don't think that's happening

17:13

immediately,

17:13

>> right? The AI stocks that we like least

17:16

or I just outright dislike are the

17:17

Neoclouds. I think heavily levered um

17:21

super dependent on Nvidia um for supply

17:24

and even financing and uh no competitive

17:27

advantage. Also massive customer

17:28

concentration. So, so yeah, I agree with

17:30

you. You've got to um discriminate

17:32

within the AI group. It's not

17:34

everything's not going to go up and to

17:35

the right.

17:36

>> Yeah. So, Jess, you mentioned yields,

17:38

right? Jed, for you, is there anything

17:40

out there that that's the one where it's

17:42

like when things start to change in that

17:43

specific sector or that stat line or

17:46

whatever the technical figure might be,

17:47

then that's where you're like, okay, now

17:48

we're now I'm keeping a keener eye.

17:50

>> Yeah. The main leading indicators we

17:52

focus on is uh number one GPU pricing

17:54

where we see, you know, pretty pretty

17:57

strong results. Typically, you would

17:58

expect to see like a steady gradual

18:00

decline in GPU pricing. M um another one

18:03

is the pace of model development from

18:05

the labs and we see improvement an

18:08

actual like acceleration there. A year

18:10

and a half ago inv or uh Anthropic was

18:12

releasing a new model every six months.

18:14

Now it's every three or four months.

18:15

It's really amazing.

18:16

>> And then um a third leading indicator is

18:19

uh is just the the revenue growth for

18:21

the big hyperscalers who are doing all

18:22

that capex spending. If they continue to

18:24

deliver accelerating revenue growth and

18:26

profits um by all means they should keep

18:28

investing. Mhm.

18:29

>> Um the one thing I just want to um point

18:31

out when it going back to rates for a

18:33

second is that um Reesfor wrote this up

18:36

a note from McQuary um on Yahoo Finance

18:38

today that pointed out it's not just

18:40

about yields getting to a certain level.

18:43

It's the pace at which they move, the

18:45

velocity, right? Absolutely. And that we

18:47

have seen such a big move in a pretty

18:49

short period of time in yields. And

18:51

historically, if you go back, that's

18:53

when you see cracks,

18:54

>> right? So, you know, could we see a

18:56

sell-off as we continue to get yields

18:58

going higher?

18:59

>> We could definitely see a sell. Does

19:01

that mean like it's a bare market and

19:02

everything's cracked? No. But like we

19:04

could definitely see another pullback

19:05

based on that.

19:06

>> We've been experiencing that though.

19:08

We've had increased volatility within

19:10

the bond market and that's translated

19:12

into the volatility that we have within

19:13

the equity market.

19:14

>> But not not much, not a lot at all

19:17

>> because of artificial intelligence. If

19:19

we were to strip out those artificial

19:20

intelligence stocks, then we would see

19:22

>> for sure. But I but there is a

19:24

possibility that even with the AI, you

19:26

know, cushion, if you will, that you

19:28

could still see a little bit of more

19:31

alarm than we've been seeing.

19:32

>> That's a good term though, AI cushion.

19:34

That is a new cushion on the market. I

19:35

like that. I guess if we think about and

19:38

again play ifs and buts or whatever but

19:40

if things do go bad is this something

19:43

because of how and just I see your point

19:45

about you know things broadening out but

19:47

because so much of the risk is so

19:48

concrated is this something where when

19:49

it turns it will turn very quickly or

19:52

will it be a kind of a slow burn as far

19:54

as like this is it going basically is it

19:55

going to be a pop or is it going to be a

19:56

deflation

19:58

>> depends on why hopefully it's because we

20:00

have some resolution within the straight

20:01

of Hormuse and then that will be very

20:03

positive for equities yields will tame

20:05

and And I mean, we even saw the the the

20:08

auctions earlier this week. There was

20:10

really good demand there. That made me

20:12

feel so much better about the market.

20:15

The bid to cover ratio was that was

20:17

good.

20:17

>> Right. Right.

20:18

>> Things I care about. But we've got

20:19

another one in 10 minutes. So, we'll see

20:22

how that goes.

20:23

>> Jed, what about for you? What what's

20:24

your prediction on the timeline?

20:25

>> I think I think investors fear the

20:27

scenario where um the supply of

20:30

accelerated computing catches up to

20:31

demand. We we haven't we haven't seen

20:33

that in the you know the four or five

20:35

years that Nvidia has been releasing

20:36

these chips. Um it'll happen one day. Um

20:38

when that happens that's obviously

20:40

really bad news for all the companies in

20:42

the data center capex supply chain, the

20:44

comfort systems of the world and the

20:46

eatens of the world and the Nvidas of

20:47

the world. Um

20:49

>> I don't though necessarily assume that

20:51

that's bad news for like Amazon and

20:53

Google. After all, they're the ones

20:54

doing all the capex spending. If we get

20:56

to the point where they don't need to do

20:58

that and they can pull back on capex,

20:59

then their free cash flow explodes. Um,

21:02

so I think there are scenarios where

21:04

Nvidia and the data center capex group

21:07

struggle, but many of the big weights in

21:11

the SP500 in broader tech land, Meta,

21:14

Google, you know, etc. actually do well.

21:17

So I don't I don't really fear this like

21:20

wipeout scenario that I think like gets

21:22

kind of talked about and assumed quite a

21:24

bit.

21:24

>> Okay. there. I mean I think you could

21:26

spin up a scenario like maybe I just

21:29

have bias because I covered the

21:30

financial crisis right but like you

21:32

could see a scenario where you know you

21:35

had the recent report that Oracle was

21:37

talking about declaring force majour one

21:39

of its projects where it wouldn't have

21:40

to pay on the same timeline if you had a

21:43

more severe and it's still paying it's

21:46

just asking to pay on a more delayed in

21:48

a more delayed way but you could

21:50

envision a scenario particularly if

21:51

you're talking about the neoclouds where

21:53

there's delay delayed payments or

21:56

there's even suspended payments. We know

21:58

that there is a lot of exposure to that

22:03

debt and to those financing instruments,

22:05

right? Um because of all of the

22:07

offbalance sheet financing and how

22:09

sophisticated it has been. So you could

22:11

see a situation where there is some

22:13

degree of spillover into the financial

22:16

system. It's it's not out of the

22:18

question, right? Not again, I'm not

22:19

saying it's gonna happen, but like these

22:20

are the things that it's, you know, I

22:23

think we have to talk about this stuff.

22:24

Jess is just as skeptical.

22:25

>> Sure. Well, I it makes me think about

22:28

bank earnings, which we have next week,

22:30

>> right?

22:31

>> Um, and I will be listening for any

22:34

signs of credit stress. Are they

22:35

increasing loan provisions and what's

22:38

happening there? I think that will give

22:39

us more of an

22:41

>> insight into the consumer, but that

22:42

might give us a little more insight into

22:44

this as well. I know they're more

22:45

sophisticated with their debt structure,

22:47

but that's something that I think could

22:49

at least give us an idea.

22:50

>> Yeah. And it's not just, you know, the

22:52

banks of the world. It's the Apollo's

22:54

parent company of Yahoo. Um, my little

22:56

disclaimer. Um, you know, it's the

22:58

Apollo of the world. It's the Aries of

22:59

the world. It's the banks of the world.

23:01

Yeah. We have to

23:02

>> Julie, is it fair to say that the banks

23:03

are better capitalized, a lot better

23:05

capitalized than 08 and 07?

23:07

>> I think Yeah, I think that's fair to

23:08

say. um you know, but they're not the

23:12

ones holding all of this either. You

23:14

know,

23:15

>> they're not carrying the bulk of it. Uh

23:16

so where are the safe harbors? If things

23:18

do get a little hairy, where do we feel

23:21

comfortable then for investors that they

23:22

should look to to put their money? Any

23:24

any suggestions?

23:28

>> It depends on why,

23:29

>> right? I know. I know. I'm giving you a

23:30

lot of like absolutes.

23:33

>> It's just it depends. I mean, I've not

23:35

I'm going to go back to the bond market.

23:36

So if the earnings yield all of a sudden

23:39

comes down, maybe we could look at

23:40

something with pricing power,

23:43

>> high quality, high dividends might be a

23:46

good solution. But then if yields are

23:49

increasing, that to me is the biggest

23:51

risk within the market that could cause

23:53

that selloff. Then that would make

23:56

anything the yields more attractive and

23:58

that's going to be your safe haven to be

24:00

honest.

24:00

>> I know. I'm sorry, Jess. I'm g I'm

24:01

asking you to finish a painting and I

24:02

have not told you at all what the

24:04

painting is.

24:04

>> We painted it there.

24:05

>> We did. We did. You did a great job.

24:07

Jed, what about you? What do you What do

24:08

you

24:08

>> Yeah. Um you you ask a difficult

24:11

hypothetical to answer. And so what I

24:12

where my mind goes is this is why it's

24:15

important to have a diversified,

24:16

well-balanced portfolio.

24:17

>> Sure.

24:18

>> Um because there will be surprises that

24:21

pop up over the next year or two. We

24:22

have some ideas about where that might

24:24

come from, but we don't know for sure,

24:25

right? So it's important to have that

24:28

balance um so that way your portfolio

24:30

can survive a gut punch.

24:32

>> Sure. So one thing and Julie you

24:34

mentioned it this anthropic IPO right so

24:37

June 1st it it confidentially files

24:39

supposed to come rumors were September

24:41

October now we're hearing they want to

24:43

get it out before Thanksgiving uh is

24:46

that a massive bell weather for this

24:48

whole AI trade really working meaning

24:51

the IPO goes well then okay we're all

24:53

systems go the IPO doesn't or is this

24:55

just one piece of the puzzle I will just

24:57

say my I think it's I think it's the key

25:00

I think if things go badly there I think

25:01

there's a knockon effect just because a

25:04

lot of people are invested in it because

25:05

it's a signal if this is one of the top

25:07

players and they can't figure out how to

25:08

go to the public market and investors

25:09

aren't interested in them then we're

25:11

really in trouble. Maybe I'm

25:13

overindexing on the importance of that.

25:15

Um I don't know you you guys tell me

25:17

where do you fall on on the importance

25:18

of the anthropic IPO. I mean, if you saw

25:20

what I mean, SpaceX wasn't the end- all

25:22

beall,

25:23

>> but SpaceX is much more nuanced, right?

25:25

That's a that's a space company. That's

25:27

a a social media company. That's a lot

25:30

of different things. Anthropic is it's

25:32

it's AI. That's I mean, when you think

25:34

of the AI trade, you think of Nvidia,

25:36

Open AI, and you think of anthropic in

25:38

my mind, at least, maybe I'm simplifying

25:40

it. So, that's why I think boomer there,

25:42

that really tells a bigger story.

25:46

>> Yeah, I mean, I get where you're coming

25:47

from.

25:48

Something that pops into my head though

25:49

is the Google IPO went really bad, you

25:52

know, a long time ago and then a year

25:53

later Google stock has doubled or

25:54

tripled.

25:55

>> Facebook IPO also was a disaster.

25:57

>> So, so I get I get where you're coming

25:59

from and that resonates with me what you

26:00

said. I I I think you're right.

26:02

Anthropic is a bellweather. Um I mean I

26:05

think Anthropic's valuation has been

26:07

doubling every like three or four

26:08

months. So, um I what what's in my head

26:12

is um

26:14

>> they're going to release a pretty cool

26:15

model or two that they've got locked

26:17

away right before that IPO.

26:19

>> They're going to promote like ever here

26:21

over the next month just like SpaceX did

26:22

and it's going to be all that we talk

26:23

about for a couple weeks.

26:25

>> And um and then they're going to do this

26:26

IPO and I think it'll probably be

26:28

successful. I think demand will probably

26:29

be really high and and then I think

26:31

Anthropic and Nvidia are going to be in

26:32

a race to see who can get to 10 trillion

26:34

first.

26:36

Yeah,

26:37

>> I think I think the financials of

26:38

Anthropic are going to be really

26:40

interesting. We've already gotten some

26:41

leaked financials, but most of it was

26:42

from 2025. We haven't gotten so much

26:44

this year. Right. Right. We already got

26:47

the leaked like risk factors page, which

26:49

is like ending all humanity as a risk

26:51

factor, right? But um you know, but I

26:53

think that's going to be illuminating

26:56

>> just to know exactly how much they are

26:58

spending and how much they are losing um

27:01

as a result of of their buildout. I

27:03

think it'll do one thing for the market.

27:05

Just like when um we had the most recent

27:07

election results,

27:09

>> a couple years ago, the market doesn't

27:11

like uncertainty. So, this will give us

27:12

some type of certainty. So, any

27:14

certainty that we can bring to the

27:16

market outcome, good or bad, however you

27:18

feel about it, is tends to be really

27:21

good for equities.

27:22

>> That's a great point because there have

27:23

been so much unknown out there. Now, we

27:25

have kind of a definitive data point.

27:27

I'm curious. We I think you know the S1

27:29

drop is going to be like must readad,

27:31

you know, must readad uh uh thing. What

27:33

jumps out to you? Like the S1 drops,

27:36

what's the first thing you're going to

27:37

look at? First thing you're going to

27:38

search, you know, command F, where are

27:39

you going?

27:41

>> ARR, they won't disclose that. I don't

27:44

think, you know, SpaceX didn't really

27:45

disclose that. It's the way SpaceX works

27:48

was they they disclosed a bunch of the

27:50

boiler plate and a bunch of the like

27:51

kind of gap audited financials and then

27:53

they did the road show and a bunch of

27:54

additional kind of like non-GAAP metrics

27:56

came out of that

27:58

>> and so I guess my assumption is similar

28:00

will happen with anthropic.

28:02

>> Um but we'll see. Yeah, the the S1 is I

28:05

I agree with you. I'm I'm looking

28:07

forward to it but uh I feel like it's

28:09

going to be a little antilimactic and

28:10

then the road show might be better.

28:12

>> Yeah. Yeah.

28:12

>> Very interesting.

28:13

>> I'll give one data point. We had a it's

28:15

San Francisco Tech Week right now.

28:17

Business Insider had an event out there

28:18

and um we we had one of our reporters

28:20

had a conversation with an anthropic

28:22

investor and then afterwards he asked

28:23

the crowd would you invest in Anthropic

28:25

at a $3 trillion valuation which is a

28:27

little bit of a leading question I

28:28

understand because they're talking about

28:30

going to market at two but in the entire

28:32

crowd three people raised their hand and

28:34

then he dropped it down and cut in half.

28:36

He said what about 1.5 trillion and a

28:38

couple more people. Granted this is not

28:39

a scientific experiment. I understand

28:41

that doesn't show real market sentiment,

28:43

but I think that's what gives me a

28:45

little bit of pause is that, you know, I

28:47

think what was SpaceX was 1.77 trillion,

28:50

very mature Starlink business, Anthropic

28:53

looking to go to. It's big. I I guess

28:54

the last question.

28:55

>> Well, listen. Sure.

28:56

>> Just to interrupt you a little bit, the

28:58

difference between Star between um

28:59

SpaceX and and Anthropic. Um Daario,

29:03

Elon,

29:05

>> Sure.

29:05

>> And in terms of who's the better

29:07

salesman,

29:08

>> Sure. for retail investors in

29:10

particular, but I think for investors

29:12

more general. I mean,

29:13

>> well, I mean,

29:14

>> Dario's one more weekend update away

29:16

from being an SNL.

29:18

>> I mean, like whatever whatever else you

29:20

you can like say whatever you know about

29:22

Elon being great a great technologist

29:24

blah blah blah. He is a very good

29:26

marketer. I mean, that's

29:28

the cloud users though, they are very

29:30

dedicated.

29:32

>> I'm a cloud user. Listen, I'm a fan.

29:33

Does that mean I'm buying I'm investing

29:35

in it? That's another question.

29:37

It's just it's interesting the salesman

29:38

part because I think that's really

29:39

shifted within markets now and I I spend

29:42

a lot of time in the creator economy and

29:43

I've been going to a lot of events just

29:45

understanding the creator economy and it

29:47

it's so interesting to me

29:49

>> and are those people interested in

29:50

investing in anthropic?

29:51

>> Well, that's where the marketing

29:53

happens. So that's where taking away the

29:55

salesman and what it is. So, and I I say

29:59

this so many times, but going back to

30:00

the initial release of these models when

30:03

we had Bard come out from Google, it

30:05

just completely flopped. Even though but

30:07

>> but that was a PR issue and that's it's

30:11

just so important to have good marketing

30:13

around these. So, I think paying

30:14

attention to that is also going to be a

30:16

very important inflection point. And a

30:18

lot of that happens on social media.

30:20

It's so interesting have virality, how

30:22

it takes the world by storm. If a lot of

30:25

consumers are buying into it and that

30:26

translates into revenue, arguably you

30:28

could draw some parallels into the

30:30

psychological aspects of the stock

30:31

market and what happens with social

30:32

media.

30:33

>> I totally agree and I think a great

30:35

example too is what happened with Meta,

30:36

right? You have Muse, oh this fluffy

30:38

little thing. This is such a cute mascot

30:41

and you have Alexander Wang, this like

30:43

prototypical stereotypical Jenzer. He

30:45

comes out with Crocs and he's got the

30:46

Australian mullet and it's like this is

30:48

cool. we can get behind this like let's

30:50

forget about all the other you know

30:51

meta's history with privacy and whatever

30:53

and and so I totally agree that like

30:55

marketing is a huge aspect of it I guess

30:57

to that point with the last thing and we

30:58

can kind of move on when it comes to the

31:00

this two- horse race between open AI and

31:02

anthropic do you think the fact that

31:04

anthropic will be first to market will

31:06

that ultimately benefit them because

31:07

they're going to be the first mover

31:08

advantage or will they have to kind of

31:10

like plow the trail that then open AAI

31:13

can kind of follow in their tracks and

31:14

understand what mistakes were made I I'm

31:17

giving you a lot of hypotheticals I know

31:18

this is tough. I'm sorry, Jess.

31:19

>> I mean, my thought process is is

31:21

thinking about what Apple's done.

31:23

>> Okay.

31:23

>> Apple's waited for everyone,

31:25

>> right?

31:26

>> That's done really well for them.

31:27

>> Sure. It helps they have the best

31:29

distribution model in the world in the

31:30

iPhone.

31:31

>> That's true. They have a big ecosystem

31:32

and and really great free cash flow. But

31:35

um but they had that because they

31:36

waited,

31:37

>> right?

31:37

>> They had a good story before that, but

31:39

nonetheless, so I think any more

31:41

information as you're going to market

31:43

could certainly help you. It's different

31:44

if you're going to market as in from a

31:46

consumer perspective, but if you're

31:47

going to market from the public markets,

31:49

any more information, I think, is

31:50

helpful.

31:51

>> Jed, what about you? Anything on like

31:53

better to be first or better to be

31:54

second and get it right.

31:56

>> Um, Jess, you mentioned earlier like the

31:59

the competition for capital that's

32:01

pushed up yields in the bond market. Um,

32:04

there's only so much equity capital um

32:07

out there. We don't know what that limit

32:09

is. Um SpaceX did an $80 billion equity

32:12

issuance. I think you know what what was

32:14

a week or two before Google issued 80

32:16

billion dollars of equity as well. So

32:18

that's 160 that's a lot of billions.

32:20

>> Um Anthropics is going to be somewhere

32:22

between 50 and 100 billion as well. So

32:24

man we're these are huge amounts of

32:26

money. How much is left over?

32:27

>> Sure.

32:28

>> And um and have the people willing to

32:30

pay the most um you know bought

32:32

something already. So yeah I think you'd

32:34

rather be first. I think Elon you know

32:36

Elon in so many ways is so smart. He

32:39

rushed his IPO out there, got out first.

32:41

Um, it wouldn't surprise me if that ends

32:43

up being a good strategy and and you'd

32:45

rather be second than third,

32:47

>> right?

32:48

>> Okay. So, we're going to try something

32:49

new now. We, you know, us here, we have

32:52

a little voice of God, but the voice of

32:53

God is gracing us with our presence.

32:55

Avana, our producer, is here and we're

32:57

in the next segment. We're going to

32:58

we're going to talk about some of these

32:59

very fun consumer profiles that Amazon

33:01

is building all of us. So, Avana, why

33:03

don't you take it from there?

33:04

>> Okay. Well, um, so this is based on the

33:08

recent Amazon story talking about the

33:10

about you profile and it kind of like

33:13

reading through a little bit on your

33:14

like spending habits. And so our team as

33:17

we were discussing it this morning, we

33:19

were therefore wondering the question of

33:22

if you would have an AI dossier, what

33:25

would it reveal about your spending

33:27

habits? And personally, I fear that it

33:29

would tell me that I spend too much on

33:31

going to concerts. I'm not going to lie.

33:33

There's no such.

33:34

>> Probably a little high. Um,

33:35

>> what's the last concert you went to?

33:37

>> That is a really good Oh, uh, role model

33:40

um, back in September, Radio City.

33:42

Really, really good time. Good

33:44

performance there. A lot of movement on

33:46

stage. I'm not going to divulge a little

33:48

bit more on that, but yeah. Uh, it was a

33:51

good time. Um, and also merchandise

33:53

surprisingly. That's that's my

33:56

>> like concert merch.

33:57

>> No, no, online sales. Okay. I did not

34:00

realize that to be honest. I thought,

34:02

you know, it's a little bit of a divide,

34:04

you know, experience economy and like

34:07

goods economy. I'm in both. I'm in both

34:09

fronts. I'm I'm steering the ship on

34:10

both ends.

34:12

>> So, we were wondering if you guys if you

34:14

had an AI dossier, like what would it

34:16

reveal about your spending habits?

34:19

>> Mine

34:19

>> good thing, bad thing?

34:20

>> Yeah. Well, I I think so. 5 years ago,

34:23

I'd be embarrassed by how much takeout I

34:25

have ordered. It'd be like, "Bro, you

34:27

need to learn how to cook here. Like,

34:28

settle down." Um, the one thing I got a

34:31

kick out of my Amazon about me was

34:33

because I've I we got a new home. It's

34:36

an old home, so trying to do some work

34:38

around the house. And it's like, oh,

34:39

must work in construction or manual

34:41

labor. It's like that's me punching in

34:42

the clock at the newsletter factory. Um,

34:45

so that's the the one thing I get. But

34:46

yeah, probably my take takeout pullback

34:49

has been good. So I I'd be proud of

34:51

that. But yeah, I don't know. What about

34:52

you guys? Anything stand out for?

34:54

>> Just spend too much is probably the

34:56

standout. I mean, I have two teens, so I

34:57

spend a lot on groceries and like

35:00

>> all the other things

35:02

>> that they do. Like, I'm going to a rock

35:04

climbing competition in a couple weeks,

35:05

so that's going to spend money

35:07

>> to travel to the thing to pay for the

35:09

fee, entrance fees, all of that. So,

35:11

that's definitely

35:13

Yeah,

35:14

>> that is exactly where my mind went. I

35:15

have I have a 15-year-old son, so

35:17

there's a bunch of 15year-olds and

35:18

16-year-olds at my house all the time.

35:21

They eat so much.

35:24

instead of constantly buying food or

35:27

giving them something to go somewhere

35:29

and that that's where all my money goes.

35:31

>> Way too much Iowa Hawkeye clothing for

35:33

me. Mostly for nephews and nieces and

35:35

>> not to be confused with the Atlanta

35:36

Hawks.

35:37

>> Don't you dare.

35:39

>> Sorry.

35:39

>> Don't you dare confuse the Atlanta Hawks

35:41

for Caitlyn Clark. That would be a

35:43

terrible thing. That was

35:44

>> Well, it's been it's been done recently,

35:46

but we won't get into that.

35:47

>> That is one of the best clips of the

35:48

year, wasn't it? That was a Missouri

35:50

senator, I believe, from my my home

35:52

state. Um

35:53

>> should know better. I think he lives

35:54

like 10 minutes away from me, too. He's

35:56

Yeah. kind of funny. Um, anyways, I have

35:59

a question for you guys. Are you buying

36:01

fresh um produce or meats from Amazon

36:04

now that they're offering it? Are they

36:06

offering it in your guys'

36:07

>> Yes, I have, but I don't do it

36:09

regularly. Okay.

36:10

>> Cuz I'm a um I'm a farmers market girly,

36:13

so I probably spend a lot on that.

36:15

Although the the gap between what you

36:17

spend at the farmers market and what you

36:18

spend at the store has has shrunk. And

36:20

I'm a Trader Joe's,

36:22

>> okay,

36:22

>> person also, but I do buy some. I have

36:24

done it on Amazon.

36:26

>> I'm desperately looking for convenience

36:28

in my life. And so we we're doing more

36:30

and more fruits and veggies from from

36:32

Amazon.

36:34

>> I'm a big And my wife gets very upset

36:36

with me. I'm a big Costco guy. Um we

36:38

don't have a massive home. I don't have

36:40

a second fridge. I don't have a big

36:42

pantry. So it's literally like the I

36:45

went last weekend and I called on my

36:46

way. I'm like, I'm going to go to

36:47

Costco. I said, I promise it won't be

36:49

that bad. I'll behave. But I always,

36:52

why'd you get so much chicken in the

36:53

freezer? Why'd you do this? We don't

36:54

have enough. But I'm a big I'm a big

36:56

Costco person. That's that's my um

36:58

that's that's that's my sweet spot. They

37:00

have a great

37:00

>> I think I should be a Costco person and

37:02

I'm still I'm not.

37:03

>> He he loads up on increased inventory.

37:07

>> Exactly. Yeah. Exactly. So there you go.

37:10

Ivon, do we have any other questions for

37:11

for the group or Okay. Yeah. I mean,

37:13

when it comes to um I guess how do you

37:16

feel about cuz I think we all understand

37:19

that these tech companies are collecting

37:21

a ton of data on this. That's always

37:22

been the case. The Amazon, you know,

37:25

trend was interesting because you kind

37:26

of see it in blatant terms. Um but I

37:29

wonder now with Muse or Instinct like

37:32

people are opening up their you know

37:34

data castles to these companies. Um like

37:37

let me start there. Are any of you AI

37:39

agent users?

37:41

Okay. All right. Which ones?

37:43

>> Muse.

37:44

>> Muse.

37:45

>> I have so many with Rod.

37:48

>> Are there do you have moes where you're

37:50

like that's something that I won't share

37:51

or is it like anything goes as far as

37:53

data?

37:54

>> Um I have specific things but I I have

37:56

um a whole team where we have specific

37:59

AI agents for specific things and then

38:01

we have a Slack channel for our AI

38:03

agents.

38:03

>> This is for work.

38:04

>> I can go nut.

38:06

>> I mix personal and work. I feel like I

38:09

don't know if anyone's watching for tax

38:11

purposes. This is for work. So,

38:15

>> what what are your home AI agent use

38:19

cases?

38:20

>> Um, at home, I don't think I use them

38:23

for I do not use them for anything

38:26

specifically as in within my household.

38:28

Okay. But because I I juggle so much, so

38:31

I obviously talk about the market a lot

38:33

and then I've somehow ended up being a

38:35

financial influencer, which is complete

38:37

accident, but now most of my income, so

38:39

I got to keep doing it. And

38:42

so I have agents that one keep me up to

38:45

date on the market and then it pulls

38:47

together multiple different things. I

38:50

even I have Claude editing my videos now

38:52

which is great. So um there's

38:54

>> lots of use cases but it's specific for

38:57

me in my ecosystem and what I need. And

38:59

to your point earlier the biggest asset

39:01

that I would love more of is time. And

39:04

so these agents just saved me time by

39:07

automatically going through my email,

39:08

giving me an update for the day, telling

39:11

my agent what he needs to do, and then

39:13

keeping me on top of being a mom, a

39:15

wife, a content creator, talking about

39:16

the markets, and then my other little

39:18

software company that is totally for tax

39:20

purposes.

39:22

>> Jed, you mentioned you use Muse. What

39:23

about what's your use case for it?

39:24

>> Yeah. Yeah. So, we're we're meta

39:26

shareholders, so I'm I wanted to try out

39:28

Muse. Um, I have at home like a old

39:31

Excel spreadsheet that I tracked our

39:33

personal spending on before I even met

39:35

my wife. And so I'm like have been

39:37

entering like I spent $6 on groceries or

39:40

ice cream or whatever. And it's a heck

39:42

of a lot to maintain when you have a

39:43

wife and three kids. And so I've been

39:44

doing a bad job keeping up with this

39:46

thing, but I I can't abandon it. I put

39:48

like 15 years into this thing. Anyways,

39:50

so I connected my checking account and

39:51

my credit card to Muse and it now

39:53

updates it and puts all the spending in

39:56

the right categories. When it has a

39:57

question, it asks me. It does it every

39:59

morning at 7 a.m. It tells me what it

40:01

did. I like it a lot. It is cool. And my

40:04

wife yells at me for entrusting Meta

40:07

with with our personal account.

40:09

>> Yeah. What's the priv privacy concerns

40:10

there?

40:11

>> Yeah. She she thinks she thinks I'm I'm

40:13

nuts. Um

40:14

>> and you think And you

40:15

>> and I and I and I say to myself, "This

40:17

is convenient. This is great.

40:19

>> So, it's a price you're willing to pay

40:20

to give Amazon your checking account

40:22

information and your credit card

40:24

information.

40:25

>> I feel like our credit card is saved on

40:28

a dozen or two dozen websites. Um, I

40:31

assume they get hacked every so often.

40:34

>> Um, I haven't we haven't um had money

40:38

stolen from our our checking or credit

40:40

card accounts in the past. Um, I grew up

40:42

in Iowa in the middle of nowhere. We

40:43

didn't really lock our doors a whole lot

40:45

in the house I grew up in. We didn't

40:46

lock our car doors when we drove places.

40:48

I'm probably way too trusting. Um, and

40:52

uh, probably irresponsible, but

40:54

nonetheless, I do it anyways.

40:55

>> I mean, I would just say Meta has proven

40:56

that it's not a great custodian.

40:58

>> Fair. Yeah, fair

40:59

>> in the past. I mean, you were saying

41:01

like, you know, you've got cute cuddly

41:02

muse. That's ahead of Aaron Circin

41:04

coming out and reminding us all what

41:06

what Meta is all about, right?

41:08

>> Interesting timing there. Yeah. Right.

41:10

Before before that,

41:11

>> we're like, we got to get this thing out

41:12

before that movie comes out. I mean, I I

41:14

I I joke, but you know, maybe please. I

41:19

I think you're you're spot on there. I

41:21

think this this the idea of like just

41:23

talking about where you leverage AI, it

41:24

works nicely into something else that I

41:26

want to bring up. We the Nestle CEO was

41:28

interviewed by a BI reporter and talked

41:30

about the most important skills in the

41:31

AI era. And I think one thing that

41:32

really stood out to me was the fact that

41:35

he said it's not so much about learning

41:37

like a specific tool. It's more so being

41:40

willing to adopt the trend and kind of

41:43

continue to evolve with it. So it's not

41:44

like, you know, because you it's this

41:46

tech evolves so fast by the time you

41:48

learn something and fully implement it,

41:50

it could already be too late. It's more

41:52

so being agile. But how do you all, you

41:54

know, so Jess, maybe we start with you

41:56

when you think about new tech,

41:57

especially AI, like how do you adopt

41:59

the, you know, the appropriate skills or

42:01

decide like this is something I want to

42:02

implement into my workflow?

42:04

>> Well, one, it's documentation of what

42:06

you do in order to optimize and have

42:08

efficiency. anything that you feel can

42:10

be automated, you need to document that

42:12

and understand that. So something that I

42:14

little busy work

42:15

>> the best way to utilize AI is just to

42:17

ask AI. So for example that literally AI

42:20

editing my videos is a new thing that it

42:22

I've started two days ago. I'm so happy

42:24

with the latest anthropic update. Um

42:27

>> but it was not explicitly said that it

42:30

could do that.

42:31

>> So I asked Claude, "Hey, can you do

42:33

this? I've done it with Codeex. Codex

42:35

does an okay job, but I want I I wanted

42:38

um Claude to do it. Claude had me run

42:40

some test scenarios. I already have

42:42

documentation and processes of what I

42:44

like and what I do. So, I showed it what

42:47

I did. I gave it examples of what I've

42:50

done and and past things. And then I had

42:53

it write a skill and we refined it

42:54

together. So, the best way is one, you

42:56

just have to have a keen understanding

42:57

of your

42:58

>> workflow, right? If you have that, then

43:00

you automate anything that is taking too

43:03

much time.

43:04

>> Sure.

43:05

>> And just ask AI to do that. But in an

43:07

enterprise perspective, that's where

43:08

consulting I think would be great and

43:10

why I like something like IBM.

43:12

>> Interesting. So Jed, you had the the

43:14

spreadsheet. Perfect example of

43:15

something that you could take off your

43:16

plate. What about on a professional

43:18

side? Anything there? How do you think

43:19

through it?

43:20

>> Yeah, a using AI for summarization and

43:23

and time savings is a is a great one for

43:26

me. I mean, I spend a lot of time

43:28

reading 15 and 20 page earnings

43:29

transcripts. Um, asking it to break that

43:32

down into 500 words is a really super

43:34

useful thing for for me and our team.

43:36

>> Um, also like AI in new idea research is

43:41

really helpful. You know, instead of

43:42

spending instead of sending one of our

43:44

analysts to go spend three days looking

43:46

into this company and all of its

43:47

competitors, we can have AI get 80% of

43:51

the way there in about 15 minutes and

43:52

then ask the analyst to go do the the

43:54

remaining 20%. So, it's a real it's a

43:56

really big efficiency tool for knowledge

43:58

work.

43:58

>> Juliana, I feel like with us it's like

44:00

it's like almost a taboo word sometimes.

44:03

>> Listen, I mean, yeah, I basically use it

44:06

for the same thing that Jed uses if

44:07

we're, you know, I ask it to summarize

44:09

things. Here's the thing about AI. No

44:11

matter how good it is, it cannot put the

44:14

information in my brain.

44:15

>> Sure.

44:16

>> So, we're sitting here talking about all

44:17

of this stuff. AI can't do that for me.

44:20

I eventually humans still have to learn

44:22

the information. I still like what

44:24

frustrates me is when I hear I'm going

44:26

off on a little tangent here, but like

44:28

when people talk about school and they

44:30

say, "Oh, you don't like when Jensen

44:31

says, "Oh, you don't have to learn basic

44:33

math anymore or you don't have to like

44:36

>> you need those things,

44:38

>> the foundations.

44:39

>> You need the foundations because it

44:40

teaches you how to think."

44:42

>> I agree with that so much.

44:43

>> And you need that background. You need

44:44

the historical context. You need like I

44:47

was an English major. I wouldn't trade

44:48

that for anything. I love to read books

44:51

and like that is valuable information in

44:54

my brain that then helps with all of the

44:56

other things that I do in tangible and

44:59

intangible ways. So anyway, that's just

45:02

a defense of not but but I here's I find

45:05

it helpful but not revolutionary.

45:07

>> Sure.

45:07

>> Thus far in my work.

45:09

>> Okay.

45:09

>> I mean I I think it can help you think

45:11

so very much.

45:12

>> I agree with that but again helpful but

45:14

not re in my experience so far.

45:16

>> Expertise oversight I think is extremely

45:18

important with AI. It does not replace

45:20

an expert whatsoever. Especially when it

45:22

first came out, I was drilling it with

45:24

options questions and it kept getting

45:25

them incredibly wrong and it doesn't

45:28

anymore. But but what's interesting is

45:30

if you have and I'm afraid I'm training

45:32

these models sometimes, but with the the

45:34

expertise oversight is I've learned if

45:36

you build some skills on just offloading

45:39

your brain, then that's when you can

45:41

really start optimizing artificial

45:43

intelligence. So, I've I've it took me

45:44

about I want to say two to three weeks

45:46

just to build my technical analysis

45:48

skill on how I look at the markets that

45:49

way and then the specific data sources

45:52

and how to pull the FRED APIs into a

45:55

spreadsheet and look at that and then

45:56

how I would look at the consumer. But

45:58

>> here's here's the other thing. Here's

46:00

here's the other thing with all of this

46:01

and like all of this thing about the

46:02

death of software software even with

46:04

vibe coding and all this stuff. I was

46:06

trying to vibe code something today like

46:08

what a drag it is.

46:10

>> I'm not a coder. Like I don't even if

46:12

I'm vibe coding. It's not though. It's

46:16

really not. Like I would I still want

46:19

somebody to give me a piece of software

46:20

to do all this stuff. Okay. I don't know

46:22

like that's good for

46:24

>> software companies Julie is your your

46:26

your lazy but like but like the people

46:28

in Silicon Valley whose job it is to

46:30

code they are the ones who see this as

46:32

most revolutionary because they are

46:34

native to that and it is most

46:35

revolutionary for what they specifically

46:38

do for what we do like I'm I don't know

46:42

I

46:42

>> I just get so nervous this idea of like

46:45

AI atrophy the idea of like okay I'm

46:47

going to outsource a little bit here and

46:48

I'm going to outsource a little bit here

46:49

and then it becomes the AI creep and it

46:51

does more and more and look the less you

46:53

do that like

46:54

>> I can barely write in cursive. I have

46:56

one vendor, one person that I need to

46:59

write a check to and it's like a I mean

47:01

it's ter if

47:02

>> you don't have to write the check in

47:03

cursive by the way.

47:05

>> You have to sign you have to sign your

47:06

name.

47:07

>> You can it doesn't even matter anymore.

47:08

Just put a line in there.

47:09

>> I know. Well, any fraudsters out there,

47:11

you you can have that in my bank

47:12

account. Um but it's that's where I

47:14

really get nervous and I think um you

47:17

know and and Jess maybe I'm interested

47:18

to hear with you. Where do you find the

47:20

most? Because for me, it's like, okay, I

47:22

might get some short-term gains here,

47:24

but if ultimately I'm losing those

47:26

skills or ultimately we're automating it

47:28

too much. Like the long term is I'm just

47:29

going to, you know, automate myself out

47:31

of a job. Now, I know you're in a little

47:32

bit of a different situation, but do you

47:34

ever get worried about like losing some

47:35

of those things you're automating?

47:36

Again, video editing, maybe that was

47:37

never your passion to begin with, so

47:38

it's like I'm happy to get it off my

47:40

plate.

47:40

>> I It's the tedious work. I am happy to

47:42

offload all of the tedious work.

47:44

Absolutely. But I mean, I did with my I

47:47

I have automated a lot of my job. I

47:49

built a quantua model completely for

47:51

stockbrokers.com that analyzes all the

47:53

brokerage firms and that is um not AI

47:56

powered but it would not have been able

47:58

to be done without artificial

47:59

intelligence because of the really deep

48:02

data that's there. So I I did have it

48:04

actually replace me right

48:06

>> but it increased productivity as well.

48:09

So I think what we're learning from this

48:11

conversation is it's different use cases

48:12

and it really depends on the person and

48:14

what you utilize it for

48:15

>> and the role

48:16

>> and yeah and the role that you're in. I

48:18

completely agree. So

48:20

>> I think in the next phase of I'm

48:22

bringing it back to the stock market.

48:23

>> Yeah, please.

48:24

>> Is we picks and shovels. I think we're

48:27

we're kind of on the the tail end of

48:29

that as soon as we see the the supply

48:32

demand from the GPU CPUs. Then I need to

48:36

see an increase in productivity from

48:37

that capex spend.

48:39

>> And that's what I think we need to look

48:40

for. But it's you can hear it

48:41

anecdotally by I I did it. It's

48:44

something that you used to do. You said

48:45

that took you three weeks, takes you 15

48:47

minutes, that's that's increased

48:48

productivity, difficult to measure, but

48:51

we could see once we start seeing that

48:53

more hearing it with earnings

48:55

transcripts. So, putting earnings

48:57

transcripts into AI, seeing how many

48:58

times they say the word tariff, you

48:59

know, that's that's some good use cases.

49:02

Um, I still find it revolutionary. I

49:04

think I'm trying to convince you, Julie.

49:07

>> When it comes to the productivity,

49:08

>> maybe I'm just too hard to impress.

49:09

Maybe I'm too cynical. It's not a bad

49:11

thing. When it comes to the productivity

49:12

gains, is the benefit for the company

49:14

ultimately we're more productive so we

49:16

can do more business or we're more

49:18

productive so we need less people?

49:19

>> Both. You can do more with less but

49:21

right now we've had a supply change in

49:23

the workforce. So

49:25

>> right

49:25

>> helpful timing.

49:26

>> Yeah.

49:27

>> Yeah. Yeah, I think it depends on the

49:28

company and I think you know um in the

49:30

case of if you're in an industry that's

49:32

growing rapidly and you're constrained

49:34

by the amount of R&D folks you can hire

49:36

or whatever then then yeah productivity

49:39

savings lead to more growth perhaps in

49:42

an industry that's not growing um like a

49:44

lot of financial services for example I

49:46

think AI is probably going to mean fewer

49:48

back office employees at insurance

49:50

companies and banks

49:51

>> sure well so to that point oh sorry go

49:53

Julie go

49:53

>> I was just going to bring it back around

49:55

to something you asked earlier which is

49:56

like how do you where's the safety or

49:58

how do you hedge? And I think like I

50:00

don't know it was I think it was a

50:01

couple months ago Mike Wilson over at

50:03

Morgan Stanley said now is the time to

50:05

look to companies to like yes you should

50:07

obviously you should still be invested

50:09

in the picks and shovels and all of that

50:11

but

50:12

>> you should start to look for the

50:13

companies that are going to benefit from

50:14

all of this right not the hyperscalers

50:17

not the tech but like and an example I

50:19

always come back to is United Healthcare

50:21

the last time it reported it did better

50:22

than expected because it had saved money

50:24

and been more efficient with its

50:26

customer service because of AI. So this

50:29

earning season, I'm going to be looking

50:30

for more of those examples. What are the

50:33

companies like, forget about tech for a

50:35

minute. What are the non- tech companies

50:37

that are leveraging AI to make their

50:39

business better? And maybe it's a little

50:40

bit early, but that's going to be the

50:43

next thing eventually.

50:44

>> So this is Can I give you So yesterday

50:47

we were disagreeing about robots. Now

50:49

I'm going to disagree on the United

50:50

Healthcare. Okay.

50:51

>> So this is my bare take on United

50:53

Healthcare. So Muse, right? Instinct,

50:55

all of these. I have two young kids.

50:58

Every couple days, some bill. Oh, we

51:01

went to the pediatrician. I kind of look

51:02

at my wife. Did we do this? I think so.

51:06

Sure. Okay. Send it. You know, write the

51:07

check with my my bad handwriting. Um,

51:10

we've heard examples now of these AI

51:13

agents going out and basically fighting

51:15

for you. I think that's a massive risk,

51:17

right? We've already heard about the the

51:18

hidden subscriptions, right? Which I'm

51:21

well aware of working in the media

51:22

business and the subscription model,

51:23

like you know, ending subscriptions. I

51:25

think the health care companies that can

51:27

be known to kind of insurance companies

51:29

send out bills or whatever and yeah yeah

51:31

just pay this. I think there's a massive

51:33

risk there that what was normally just a

51:35

okay yeah I have to do it people just

51:37

think oh I have healthcare bills I have

51:38

to do it now sending off their agents to

51:40

go and and fight that fight.

51:42

>> Well there's already been a Blue Cross

51:43

and Blue Shield just came out with that

51:45

study that said that hospitals are now

51:47

upcoding right so there's a diagnosis

51:50

code that goes with everything that you

51:51

get done by a healthcare provider. Now

51:53

they're putting on a secondary diagnosis

51:56

that says so they're then increasing

51:59

their billing to the insurance company

52:01

and ultimately probably to us. So

52:04

they're getting in other words they

52:05

might get squeezed from both sides.

52:07

>> Yeah. I don't know. Jess, where do you

52:09

come out on that? Do you view that as a

52:10

risk or not as much?

52:11

>> Yeah, I think that is a risk. Um first

52:14

thing that pops into my head when you

52:15

talk about the subscriptions and

52:16

negotiating is um the cable company, you

52:18

know, like I'm a charter cable

52:20

subscriber and

52:20

>> you know you haven't cut the cord yet.

52:22

Uh, I do have Hulu Live for cable, but I

52:26

get internet through Charter still.

52:27

Okay. And, uh, I recently called them

52:30

and had to spend a half an hour on the

52:32

phone and they cut my monthly bill from

52:34

120 a month to 70 and I was really happy

52:36

about that.

52:37

>> Um, but I spent a half an hour doing it

52:39

and I would have rather much rather sent

52:41

Muse to go talk to them and see if they

52:43

can do even better and I didn't have to

52:44

push that hard. So, they probably would

52:46

have done better. So,

52:47

>> yeah, I I think that I think that will

52:48

happen. Um, we have a a hospital

52:50

investment, um, HCA, a publicly traded

52:52

company, and I found it funny,

52:55

>> the health insurance companies say that

52:59

the hospitals are further along in in

53:01

adapting AI for their negotiations. Um,

53:04

and then you go talk to the hospital

53:06

companies and they say, "Oh, no, no, the

53:08

health insurers are way further along in

53:10

adopting AI. Like, we we're really

53:12

struggling to negotiate against them.

53:14

It's getting harder." So, I don't know.

53:16

I don't know where the truth lies in

53:18

that. They're both, I think, adopting AI

53:20

rapidly. Um, and I think that they're

53:22

kind of trying to do that under the

53:24

radar because I think that there is this

53:27

consumer concern about where this is

53:29

heading and how it's going to affect my

53:30

pocketbook.

53:31

>> Yeah.

53:31

>> Yeah. Yeah. Jess, I don't know. I we got

53:33

about a minute left here. I don't know

53:34

if you have a thoughts on these, you

53:35

know, agents fighting for us or

53:37

>> Oh, I think healthcare is one of the

53:39

best sectors that are primed for

53:41

disruption from artificial intelligence,

53:43

from a lot of different factors. It's

53:44

from pharmaceuticals. It's from finding

53:47

cures for diseases. It's from the

53:49

customer service and the operational

53:50

efficiencies within the hospitals. It's

53:52

for the relationships that you have with

53:53

doctors. And even I spend a lot of time

53:56

talking to my primary care about things

53:59

like this in our checkups where there

54:02

was been a big push where all of our

54:04

medical data has is all electronic and

54:07

then a lot of my family's in the medical

54:09

field. So you can see a prescription

54:11

that was made here that was made there

54:13

where you had people who were abusing

54:14

the system trying to you know get other

54:15

things. So there is operational

54:17

efficiency already where they push to

54:19

data and then I'm thinking about what's

54:21

needed for artificial intelligence is

54:23

step number one is good data. Healthcare

54:25

has already done that

54:26

>> always data is always the source. Well I

54:28

think on that we can leave it there.

54:29

Thanks so much all of us for joining us.

54:31

This was great and uh until tomorrow

54:33

we'll see you then.

56:01

Heat. Heat.

56:32

Down.

56:47

Heat.

57:31

Down.

57:36

Down.

58:09

Down.

Interactive Summary

The video discusses current market trends, starting with PepsiCo's earnings which reveal a more cost-conscious consumer. The panel debates the logic behind a rumored Starbucks and Chipotle merger and explores the bullish outlook for the AI sector, specifically focusing on Nvidia and the upcoming Anthropic IPO. Additionally, the hosts discuss the practical application of AI agents in their daily workflows and the potential for AI to disrupt the healthcare industry's billing and operational efficiency.

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