WEBVTT

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Let's talk about Palunteer
just for a minute.

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>> Yeah,

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>> you guys are obviously crushing it.

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>> What's really interesting to me is what

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are going to be the most highstakes

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questions that complex organizations are

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going to have to ask about where AI is

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really going to change
the work that gets done. Alex.

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>> Well, um,

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the the there's like a there's the first

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wave of actually the first wave of AI

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really happened in the military,
but then my version of it was partly is

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classified, but you see it
in Ukraine and other places,

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>> but we're private here. You can
talk about classified things. Yeah, no

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problem. But um but I think actually the
real problem in disseminating the truth

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was

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you the truth in in America which is the

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defining place for AI which is also
super interesting because normally you

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have a revolution and like I spent half
my life in Germany you'd expect a German

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version a French version an American

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version but really you have America and

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China and and this is already completely

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unique um because yeah I mean if you

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think of other revol olution's

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philosophical industrial if you look at

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the history of Asia for example um um

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when Deng Shoping took over China he he

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immediately got industrial mines from

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America Chinese Americans um and then

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Japan's rise visav v China and but these

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things were pretty intertwined so Japan
rose because it it took over Chinese

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culture and then it took over western
culture of how to do industrial this is

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a revolution that is

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basically At least the original thinking

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and research is completely done here and

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then derivative advancement fast

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follower or China. So that's already

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super unique. Then it that leads to a

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lot of confusion because the first wave

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of AI which was you give us your data we

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put it in a model. The model kind >>
Are we still in the first phase or we're

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moving to >> we're we're
in the I think we're both in

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the first and second phase. So a lot of

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people are in a phase of you give me mo

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I take your model I run it I chillax on

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paying you a lot of money I get very I

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get I get value on very easy use cases

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it doesn't work on complex use cases and

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I may or may not be in danger of

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outsourcing my primitives my knowledge

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that the my alpha what makes my business
special to a model company that will

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compete with me effectively and put me

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out of business Um, and then but it's

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this unique phase. So like if you
just may take a neutral example, why is

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Europe not scared of AI? Why aren't
they adopting it on the battlefield even

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though they have all this information
of it's the thing that works? It's because

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you can still look at the things that
don't work and then say, okay, well this

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doesn't work. It's not worth it.
But then so this let me just get to your

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question which is this is all backdrop

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for what are what is actually working

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and then the what what does it mean to

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work? The first big difference like it

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used to be that the delta between a good

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software implementation and one that was

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second rate was real but it wasn't

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determinative for your life. And so
when we built Foundry, which is a data

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integration platform, which we're using
with you, that would save you time and

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money and make you more efficient,
it would make you A+ but B minus, which

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would take longer, was still in a range
of if you were better at marketing and

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you had B minus or you owned your you
you had a high moat, like just say

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you're you're building a certain kind
of missile, right? Okay. Yeah, maybe you

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could build them faster with foundry,
but you have a moat because it's hard to

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build this missile. And also, say you're
a French company or a German company,

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they're German government's going
to buy your missile even if it's B minus

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because it flies and it's German, right?

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Okay. So and we do the same thing but um

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so it okay so what happened what's

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happening in the second phase of AI was

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yeah but your missile isn't going
on target against the Russians or I if if

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you do not have a way of putting it
there and that way is going to be an

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application layer with a model and

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without that your interestingly your B

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minus missile is a triple plus with this

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and your A+ missile is useless

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>> so that's just binary and that this the

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profoundity of that minimal example is

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something that we don't have that you

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know in philosophical systems I I I was

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going to be an academic and I my form of

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>> law degree from Stanford
you have your PhD in philosophy

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>> your family's got to be somewhat
proud of your academic accomplishments

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>> no my they we can go back to that
but it's like and my dad's like you could

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have been something with that [laughter]

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literally it's like But uh I'm not

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joking. It sounds like

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um uh

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>> you you rarely have when these massive

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things happen it it from modernity to

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postmodernity to or or the or what is it
let's just take an American example.

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What does it mean to internalize the
first, second and fourth amendment? The

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it it the first amendment being
our right of free expression which is

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first of all the constitution was given
to us by a higher being. So it's already

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different than Europe. But then first,
second and fourth amendment, right of

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first expression, right to defend
to first expression which is really what

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the second amendment is about
and the right of privacy.

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It these are concepts that are so

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radical it takes generation. So here you

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have something that's very s like you've

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now have a thing a technology that will

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make a rocket to use a very simple

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example that was third rate first rate

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and deadly or you have something without

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it that will take the first rate rocket
and it's not useful. So this is true in

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every single enterprise commercial
enterprise and and and and what is it

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that is special about AI. So just
take an example you have unique ways of

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understanding how a market
would react to a message.

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>> Yes. >> Okay.
You are going to how do you share

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those insights with a with a partner
where you only share the insights that

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you want to share and they want to share
with you and how do you augment them

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where both the data the insights
and the models you run against them are

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sovereign meaning unique to them
or could be white labeled and sold to

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others. Well, and that's one of the
things we love so much about Foundry.

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Our integration of our data cloud
on Foundry gave us far more ability to do

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those things. And we're now able to

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onboard clients in hours that used to

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take months, but give them control. I'm
I'm going to pivot us back and bring us

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a little lower to the ground so most of us
here can understand the vast majority

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of what you say.

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We talk about data sovereignty a lot. We

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have a lot of CEOs in the room, a lot
of CMOs in the room. Alex, what does that

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really mean? >> It means
that well, first of all, and

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this is an very advanced thing,
and we're going to be able to augment this

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and then put models on it and then train

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the models so that the models reflect

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just what you know and do not expose it

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to the outside. So basically, okay,
every business, what is a business? A

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business a business meaning something

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that at some point in the future will

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provide high quality revenue meaning
free cash flow. Okay. And what is why is

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free cash flow what everyone thinks
about analysts? Um why is this an

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important concept? Because it basically
tells you you have something unique in

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your business that is valuable enough
where you have pricing parity so that

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you can charge more than the cost of the
goods. Okay, that is a business. Every

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business in the end of the day comes
down to that. Why can you charge more

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than it cost you produce it? Because you
have some unique way of doing something,

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whether that's how you build it, how you

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produce it, how you distribute it, and

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how you market it. Okay? And preferably,

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it's unique along the whole stack.

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>> And the more unique it is along
the stack, the better your financials at

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some point in the future will be.
I mean, there's always a lapse of time,

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but I basically

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I do I think the free market will get
you to pricing parody over a 18-month

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period,

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>> right? Or so uh and okay. So in every

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one of those things, the way you produce

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it, so supply chain, how you how you how

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you how you integrate it, what the final
product is, what the aesthetics of the

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product and how you
explain it to the market.

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You need to advance your unique

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capability, learn from the world, and

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never ever expose to anyone else how

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you're doing it exactly. And the minute

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you ex someone else can do any part
of those things as well as you can your

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pricing parody goes down and at some
point your value goes down. I mean these

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are like a lot of times is okay. So

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normal software is built to to force you

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to adopt something that's parasitic.
So you they take every one of those things

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turn it into a commodity and sell it
to everyone else. That's how you We

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couldn't get financing because I kept
telling these VCs, "Yeah, but we're

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going to make we're going to make
our partners and clients happy." They're

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like, "Why would I?"
>> Wait, what? Happy clients?

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>> No. Wait. When you want to start
a a company and you talk to VCs, what they

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wanted to hear was clients will be
unhappy, but they can't get rid of you.

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Like they want to hear bad
marriage, >> aka sticky, right?

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>> Yeah. No, it has to be sticky
is a metaphor for parasetic.

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>> Correct. >> I get your data.
I get it into something

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you can't get rid of. The thing turns
into something I can sell to everybody

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else who then can't get rid of it. And

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de facto, your multiple goes down and my

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multiple goes up and all of us are
happy and hope at some point you realize

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you're sad. Hopefully after it's too

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sticky and okay, so that's how you get
we couldn't get finance because I kept

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telling people no, we're going to make
we're going to make spec special

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operators more lethal and we're going
to bring them home and they're like but

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where's the parasite? I'm like, "No,

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we're not doing the parasitic thing."

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And uh and then if you look at the stack
of what we're doing, Foundry will bring

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all your data together and protect it
granularly. So you can share the data

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and not share what you don't.
>> Well, you get to decide what you share

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and what you don't share with Foundry.

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>> Yeah. And then the the the application
layer on top of it will allow you to do

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the same thing with openweight models
or closed weight models. I mean, close

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weight models, you need to get them
to post train, but either way, you are not

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going to be seeping your alpha to

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everyone else. And so, at every stack,

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every part of the stack, you augment

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what's particular about your business
without losing that particularity by

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giving it to somebody else who's

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anti-polled with that. And that that for

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those of you who are
like VCs and others who

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>> bismerch us, whatever. Any case, I get

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along with them now that I'm standing
on their head. But um it's uh who are

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basically they just want to finance.

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They've pass someone comes to pound you
for two days, they'll give you like $10

00:11:19.200 --> 00:11:20.797
million, start a business like planning

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plots. But um uh but any case, the the

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the radical thing here
is the obvious nature of this,

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>> right? >> And and by the way,
just to why did we

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do this? We did it because we knew we
could not win on popularity. So that

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>> if you can't win on popularity,
you better win on alignment.

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>> And and what I was literally just going
to take exactly what you're saying to

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the next level. One of the things I
love so much about the elegance. Can

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>> you come over to my family?
I I'm not used to this love.

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>> I'm sorry. >> I'm not used
to When did I get all this love?

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>> I can I can give you later. I promise.

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>> Yeah, please.
Please do. I'm not I won't

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believe you if it's positive.

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>> Exactly. the this

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really sits inside of your entire

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concept of forward deployed engineers
from the way I see it like we have your

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FTEES in our office every day working
with our FTEs. Well, there's this

00:12:14.320 --> 00:12:17.837
concept. I mean, another reason we
couldn't get financed and every single

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person made fun of us is we were like,

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okay, to extend the unique nature of the

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enterprise into our product and into
the enterprise itself. We have to send in

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people who are highly technical
and understand our product and then

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understand your enterprise so that we

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can augment our product specifically for

00:12:35.760 --> 00:12:39.037
you. But that's so different for a

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software company. Like we pivoted a huge

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part of our business to follow you
guys on this because it's so freaking

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efficient.

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>> Yeah. It it Well,
it also gets you again

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it allows you to basically bespoke build

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what we have to exactly who you are. And

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and then over time we're training your
people. Like we're not a body shop. So

00:13:01.840 --> 00:13:06.317
we want to train your people to be
your own FDS. And we do that. But we have

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4,500 people. We're not going to have

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50,000 people. So, we we need this is

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where we need we need partners because

00:13:14.240 --> 00:13:18.477
we have to work through you because we
have we're an artist shop. We we manage

00:13:18.560 --> 00:13:21.597
a certain kind of person very well.
I that's what I do for a living.

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>> It's not just a certain kind of person.

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You manage an extraordinary group of

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people. I I mean, the more time I have

00:13:28.160 --> 00:13:31.037
spent with people like Elias and and and

00:13:31.120 --> 00:13:35.997
all of the other people on your team,
the more impressive it is the people who

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are there.

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>> Yeah. We we had
long dark period by most

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standards 17 years uh and uh and in the

00:13:45.920 --> 00:13:47.917
desert of everyone making fun of us

00:13:48.000 --> 00:13:51.597
every day. Um and and especially people

00:13:51.680 --> 00:13:55.597
who are the most knowledgeable. But um

00:13:55.680 --> 00:13:59.677
the one thing everyone would always say
is yes, but they have the best people.

00:13:59.760 --> 00:14:03.357
And it's still true. In fact,
it's even more true now. We've had our our

00:14:03.440 --> 00:14:05.997
recruiting for whatever reason.
We were just getting

00:14:06.080 --> 00:14:08.877
>> Well, I I think your
success is probably helping.

00:14:08.960 --> 00:14:11.437
>> Um, you know, it this obviously success

00:14:11.520 --> 00:14:15.037
always helps, but it's you we had it's

00:14:15.120 --> 00:14:19.757
interesting. It's it really is that it's
more and more clear to engineers why you

00:14:19.840 --> 00:14:21.597
would want to power a sovereign stack,

00:14:21.680 --> 00:14:26.877
why that's good for clients, why it's
good for society, why it's what is it's

00:14:26.960 --> 00:14:30.317
the thing that will transform America
and hopefully the rest of the world. And

00:14:30.400 --> 00:14:33.517
so at like every part of our stack, it

00:14:33.600 --> 00:14:35.677
has become much more charismatic. And so

00:14:35.760 --> 00:14:37.917
we've had we've had I mean we've always

00:14:38.000 --> 00:14:42.957
been working at the way way and high
end of talent, but even for like we have

00:14:43.040 --> 00:14:44.877
different we have different vintages.

00:14:44.960 --> 00:14:48.557
It's like your wine like we vintage like

00:14:48.640 --> 00:14:52.957
vintage 2008 is different
than vintage 2012. But

00:14:53.040 --> 00:14:55.677
>> eight is much better in burgundy
but not as good in California.

00:14:55.760 --> 00:14:58.317
>> Yeah. No. And it's very similar
interestingly because for we have

00:14:58.400 --> 00:15:01.837
different roles and like but right now

00:15:01.920 --> 00:15:05.197
we are crushing it on and by the way

00:15:05.280 --> 00:15:07.277
anyone here has a precocious person they

00:15:07.360 --> 00:15:10.557
you want to like recruiting we manage

00:15:10.640 --> 00:15:16.317
uniquely shaped I'm dyslexic which I
I next you're you're stealing my next

00:15:16.400 --> 00:15:21.037
topic. >> So well any case >> because
I am too. Well, I I was it's the

00:15:21.120 --> 00:15:22.317
only thing I was ever in the closet

00:15:22.400 --> 00:15:24.797
about and I was super and then any case

00:15:24.880 --> 00:15:28.957
but we manage highly uneven

00:15:29.040 --> 00:15:31.597
essentially brilliant people and then we

00:15:31.680 --> 00:15:34.237
slot them and grow them and Palanteer is

00:15:34.320 --> 00:15:36.397
not everyone's cup of tea but for some

00:15:36.480 --> 00:15:39.757
people and ex-punterians who are missing

00:15:39.840 --> 00:15:42.797
the Palunteer vibe uh they'll tell you.

00:15:42.880 --> 00:15:47.677
In fact, the best references for us are
tend to be people who stormed out the

00:15:47.760 --> 00:15:52.397
door. They're like, "Another crazy
lecture from Karp stormed out the door

00:15:52.480 --> 00:15:55.677
and now they're unhappy with the
shagging of their current business and

00:15:55.760 --> 00:15:58.557
they want to come back, but it's hard
to come. I mean, it's emotionally hard to

00:15:58.640 --> 00:16:00.717
go back, but they're our best reference.

00:16:00.800 --> 00:16:03.357
We're we're not for everybody, but for a

00:16:03.440 --> 00:16:05.357
certain kind of person, we are the only

00:16:05.440 --> 00:16:09.037
place." And we I spend a lot of time

00:16:09.120 --> 00:16:12.477
actually my favorite times besides
of course hanging out with you. Oh, there

00:16:12.560 --> 00:16:16.317
we go. >> Hanging out on the factory
floor with they all you know these

00:16:16.400 --> 00:16:19.837
>> By the way, you live that like your
office is in the middle of the factory

00:16:19.920 --> 00:16:22.797
floor. >> Yeah. No,
I I but I It's what I enjoy.

00:16:22.880 --> 00:16:24.717
It's like, you know, it's funny. One of

00:16:24.800 --> 00:16:27.597
the great luxuries I have is I mostly

00:16:27.680 --> 00:16:30.317
get to do not always, but I really do

00:16:30.400 --> 00:16:35.997
get to do mostly what I enjoy. And what
the thing I like most about my thing is

00:16:36.080 --> 00:16:37.117
just hanging out with my fellow

00:16:37.200 --> 00:16:40.317
palunteerians and working on things and

00:16:40.400 --> 00:16:43.277
fixing things and being frustrated and

00:16:43.360 --> 00:16:48.237
you know and then and they say the cra
you know I just I really enjoy it.

00:16:48.320 --> 00:16:51.997
>> I always look back on our first
conversation. So we're both very

00:16:52.080 --> 00:16:56.637
dyslexic. We both from come
from similar backgrounds.

00:16:56.720 --> 00:17:00.877
We both, I think, have a big chip on our
shoulder from not getting financing and

00:17:00.960 --> 00:17:04.717
not being seen. At least for me, it
was as a kid, not being seen. And then we

00:17:04.800 --> 00:17:07.917
couldn't raise money for our business
either. Everybody thought we were nuts

00:17:08.000 --> 00:17:13.117
>> until a few big part platforms
like, you know, Bob House.

00:17:13.200 --> 00:17:17.037
>> And actually, you're a funny guy.
I think in private comedy gets me.

00:17:17.120 --> 00:17:19.837
>> It's I think I'm not
the least unfunny guy either.

00:17:19.920 --> 00:17:24.477
>> I think you're very funny. >> So,
it it goes like in private. You're

00:17:24.560 --> 00:17:27.277
funny here too, but you guys have no
idea what we're dealing with here. This

00:17:27.360 --> 00:17:31.357
[laughter] is like in private is a
different level. And you're laughing

00:17:31.440 --> 00:17:36.637
proformer some of these jokes and I am
too, but in private you really laugh.

00:17:36.720 --> 00:17:40.957
By the way, put put that on my tombstone.
He said I'm funnier in

00:17:41.040 --> 00:17:44.477
public. In private. No,
but in all seriousness, we had our first

00:17:44.560 --> 00:17:48.317
conversation. We were supposed to be
together 10 minutes. 40 minutes later,

00:17:48.400 --> 00:17:51.997
they're pulling us out of the room.
We start with philosophy. We move on to

00:17:52.080 --> 00:17:56.557
wine and watches. And then you looked at
me and said, "So why are we doing this?"

00:17:56.640 --> 00:18:00.877
And I said, "Alex, because you've spent
20 years solving the world's biggest

00:18:00.960 --> 00:18:04.957
problems, and we can help our clients to
solve one of their biggest problems that

00:18:05.040 --> 00:18:07.597
you don't have a current solution set
for." And you just looked up, you're

00:18:07.680 --> 00:18:09.357
like, "Oh, great. Let's do it."

00:18:09.440 --> 00:18:13.117
>> It's true. Yeah. >> Is that how
you make all decisions? Like

00:18:13.200 --> 00:18:14.557
I mean,

00:18:14.640 --> 00:18:19.197
>> um, well, I would
say if I I I asked I I

00:18:19.280 --> 00:18:23.117
sometimes ask people like because I
it's very hard to know. It's very hard to

00:18:23.200 --> 00:18:27.997
perceive yourself. So I ask people I
work with like, well, what is it like

00:18:28.080 --> 00:18:31.277
the people, you know, I've worked
with them a long time and we're we have

00:18:31.360 --> 00:18:33.597
pretty we have a very honest relationship.
So it's not like they're

00:18:33.680 --> 00:18:36.397
telling me things I want to hear.
In fact, I often tell them, could you tell

00:18:36.480 --> 00:18:38.877
me something I want to hear,
>> please? [laughter]

00:18:38.960 --> 00:18:40.077
>> By the way, it sounds like my

00:18:40.160 --> 00:18:41.837
conversations with my kids,

00:18:41.920 --> 00:18:46.317
>> like please something. Uh but um uh um

00:18:46.400 --> 00:18:48.797
and I I a very precocious person and

00:18:48.880 --> 00:18:51.117
he's like look we prepare for hours and

00:18:51.200 --> 00:18:54.477
then you kind of have a bias pretty

00:18:54.560 --> 00:18:55.997
quickly

00:18:56.080 --> 00:19:00.877
minutes and I would say I have a kind of

00:19:00.960 --> 00:19:04.317
I probably think they have this for my mom
but maybe in a different way from my

00:19:04.400 --> 00:19:06.797
dad. I have an aesthetic idea of what

00:19:06.880 --> 00:19:10.957
could work and what won't work and and

00:19:11.040 --> 00:19:13.597
then I just that's what I do all day.

00:19:13.680 --> 00:19:16.957
It's like, okay, well, this could work,
that couldn't. This everyone does this,

00:19:17.040 --> 00:19:21.197
it won't work. No one does this,
it could. And then about once a month, I

00:19:21.280 --> 00:19:23.837
have some idea that I think
is important. And then I know it's

00:19:23.920 --> 00:19:26.397
important when everyone tells
me we could never do that.

00:19:26.480 --> 00:19:26.877
>> By the way,

00:19:26.960 --> 00:19:28.877
>> like DPO

00:19:28.960 --> 00:19:34.317
like DPO or or sovereign or AIP or a lot

00:19:34.400 --> 00:19:36.717
of other things. Foundry. Foundry

00:19:36.800 --> 00:19:39.757
famously Ted, who's a wonderful person

00:19:39.840 --> 00:19:43.997
who runs US Commercial, famously
said, "Please stop talking to your

00:19:44.080 --> 00:19:46.957
Palunteerians about how big Foundry
is going to be. It's depressing and

00:19:47.040 --> 00:19:48.757
everybody knows you're out of touch."

00:19:48.840 --> 00:19:51.357
[laughter] >> Well, I would tell you not.

00:19:51.440 --> 00:19:55.277
>> And he was right. I had to stop talking
to people for like six months cuz But it

00:19:55.360 --> 00:19:59.677
worked. >> I know. I know. I I when when
I first sort of came up with the idea for

00:19:59.760 --> 00:20:02.157
Athena, normally I go into Steve

00:20:02.240 --> 00:20:06.797
Gerber's office, who's my partner, and he
looks at me and he says, "All right,

00:20:06.880 --> 00:20:10.397
David, that's great. Let's keep that ju
just between us. We're not going to go

00:20:10.480 --> 00:20:13.757
talk to other people about that because
you're going to freak everybody out."

00:20:13.840 --> 00:20:17.997
>> And I brought him Athena.
I had been I had decided to take

00:20:18.080 --> 00:20:21.517
>> my three older kids. We went over
to Africa for the weekend because I'm an

00:20:21.600 --> 00:20:25.197
idiot. And we did like a safari and I
was trying to squeeze everything in and

00:20:25.280 --> 00:20:29.437
nobody slept for days and I came
back and I go into a very manic state

00:20:29.520 --> 00:20:34.397
>> which I did a lot more when I was
younger than I do now that I'm old >> but

00:20:34.480 --> 00:20:37.837
>> and I sort of came out with Athena
and I went in and Steve was like you know

00:20:37.920 --> 00:20:39.437
that's actually a really good idea. It

00:20:39.520 --> 00:20:41.037
was the first one I'd gotten in many

00:20:41.120 --> 00:20:45.917
many years but let's once again I like

00:20:46.000 --> 00:20:48.957
you're so smart and you're so sort of

00:20:49.040 --> 00:20:52.157
open. I I want though to go a little

00:20:52.240 --> 00:20:55.437
myopic for just one second. If you're

00:20:55.520 --> 00:20:58.477
talking to the CEOs in this room, of

00:20:58.560 --> 00:21:03.357
which there are many, other than signing
up with Palunteer today, which is we

00:21:03.440 --> 00:21:05.357
believe the absolute best decision they

00:21:05.440 --> 00:21:08.637
could make today, what's the one thing

00:21:08.720 --> 00:21:11.917
that every CEO in this room, what's the

00:21:12.000 --> 00:21:13.597
one decision they should make today

00:21:13.680 --> 00:21:15.917
before they go home?

00:21:16.000 --> 00:21:19.597
Um, in your mind's eye, what is the

00:21:19.680 --> 00:21:21.757
thing in your business that makes it

00:21:21.840 --> 00:21:25.437
special that is not quite understood?

00:21:25.520 --> 00:21:27.437
And

00:21:27.520 --> 00:21:31.277
how do you get complete vision from the

00:21:31.360 --> 00:21:33.517
factory floor, prefactory floor

00:21:33.600 --> 00:21:35.997
distribution all the way up to cost of

00:21:36.080 --> 00:21:39.197
goods in front of you immediately. and

00:21:39.280 --> 00:21:43.357
and every [clears throat] single person
who's crucial at each one of those

00:21:43.440 --> 00:21:45.277
points

00:21:45.360 --> 00:21:49.117
it that like in total granularity where

00:21:49.200 --> 00:21:53.517
you impose this thing up and down
the stack and make every single shirt and

00:21:53.600 --> 00:21:56.477
there's a tech version that you would
need to do this but that's the business

00:21:56.560 --> 00:21:59.917
thing and then then how do you get AI to

00:22:00.000 --> 00:22:02.557
enhance that without

00:22:02.640 --> 00:22:05.437
it a model company or your competitor

00:22:05.520 --> 00:22:07.517
understanding exactly what that is and

00:22:07.600 --> 00:22:10.797
that's what I It's what I focus on. But

00:22:10.880 --> 00:22:13.197
but it the thing is the thing about the

00:22:13.280 --> 00:22:16.797
shortest version of AI is it just makes

00:22:16.880 --> 00:22:19.037
it it makes the real things 10 times

00:22:19.120 --> 00:22:23.837
more real. So you have to get
them right. There's no room for up

00:22:23.920 --> 00:22:27.917
the way there was. And this is
an advantage for America because

00:22:28.000 --> 00:22:32.637
corporate leaders in America are on
the front line and there's no chillaxing

00:22:32.720 --> 00:22:34.557
vibe like you know basically

00:22:34.640 --> 00:22:36.957
>> this is not a chillax week. No, this is

00:22:37.040 --> 00:22:40.077
so like um I I I had a of a very a

00:22:40.160 --> 00:22:43.037
really talented um somebody I admire a

00:22:43.120 --> 00:22:48.077
lot, a European CEO, and he he's like
he was saying, and I'm going to provide

00:22:48.160 --> 00:22:52.077
references for him, but he's like,
"Look, no one will hire me in America."

00:22:52.160 --> 00:22:53.517
The head hunter said, "There's no

00:22:53.600 --> 00:22:55.837
point." And that's a problem, but it it

00:22:55.920 --> 00:23:00.397
it really is because we are at because

00:23:00.480 --> 00:23:04.637
more like it's like a war envir like so
you you have to get that right. And if

00:23:04.720 --> 00:23:08.397
your person down the street gets it right,
even if they're inferior to you,

00:23:08.480 --> 00:23:10.637
just like the missile, they will they

00:23:10.720 --> 00:23:15.757
will they will outperform you on not
just on margin. It's not just it's not

00:23:15.840 --> 00:23:19.837
this like the classic of private equities.
You strip out the costs. This

00:23:19.920 --> 00:23:22.317
is enhanced product and strip out the

00:23:22.400 --> 00:23:27.837
costs and that's a rare thing. And also
the timeline is different. So but the

00:23:27.920 --> 00:23:30.317
way to begin >> everything's
speeding up, right? the

00:23:30.400 --> 00:23:33.997
yeah the nature of time is it's one
of the things I feel like I I feel very

00:23:34.080 --> 00:23:35.837
proud of the things I got right the one

00:23:35.920 --> 00:23:39.197
of the things I didn't understand is and

00:23:39.280 --> 00:23:41.197
I it's just time is excel like time

00:23:41.280 --> 00:23:44.797
isn't time in this country in business

00:23:44.880 --> 00:23:47.837
is like just it's like 5x what it was 5

00:23:47.920 --> 00:23:52.637
years ago you it's everything is and
and you can make these things the other

00:23:52.720 --> 00:23:54.237
thing I would say which is a derivative

00:23:54.320 --> 00:23:57.357
of it the tactics of this are shorten

00:23:57.440 --> 00:24:02.477
the timeline of execution Anything
that's taking too long, it's because

00:24:02.560 --> 00:24:06.717
there's something in the stack that's
parasitic. We say time is the enemy of

00:24:06.800 --> 00:24:10.957
everything at this point.
It just you have to move faster

00:24:11.040 --> 00:24:14.877
>> and and and pentest. It's a very
important way to pentest because there

00:24:14.960 --> 00:24:18.317
are complicated things that take
time obviously. So maybe there's some

00:24:18.400 --> 00:24:21.837
important regulatory thing. But if you

00:24:21.920 --> 00:24:24.237
if you just say if you make a list of on

00:24:24.320 --> 00:24:26.557
that stack of things, what is taking too

00:24:26.640 --> 00:24:29.757
long? you'll pretty much articulate

00:24:29.840 --> 00:24:34.157
wrong person, wrong part of the stack,
wrong technology with a high degree of

00:24:34.240 --> 00:24:35.997
re reliability. And why is this

00:24:36.080 --> 00:24:37.837
important? Because most people running

00:24:37.920 --> 00:24:41.677
companies are not tech people or don't

00:24:41.760 --> 00:24:44.077
inherently trust their tech intuition.

00:24:44.160 --> 00:24:48.637
So, but this will give you a way
to pentest your actual intuition, which is

00:24:48.720 --> 00:24:52.637
business intuition against a tech
problem because if you can't understand

00:24:52.720 --> 00:24:56.077
what the tech is doing and it's taking
too long, there's definitely something

00:24:56.160 --> 00:24:57.357
wrong.

00:24:57.440 --> 00:25:01.597
Ladies and gentlemen, Dr. Alex Karp.

00:25:01.680 --> 00:25:05.517
>> That was the keynote.
That was um [clears throat]

00:25:05.600 --> 00:25:07.677
part of their first hour. It didn't get

00:25:07.760 --> 00:25:12.877
live streamed, so it
got posted later, but um

00:25:12.960 --> 00:25:14.477
I don't know. I I think I'd have to

00:25:14.560 --> 00:25:15.917
watch it a few more times to understand

00:25:16.000 --> 00:25:20.077
where Zeta fits into that. But obviously

00:25:20.160 --> 00:25:26.160
still pretty exciting
for uh a Palunteer investor.
