I'm looking at a piece in front of me.

This is from a while ago, but

it's you discussing long-held dogma that

ends up being unviable. So, for

instance, the common-held belief after

PayPal's sale to eBay that fraud will

kill you in the payment space, right?

>> Yeah. And I'm wondering how you orient

yourself as an investor to

stress test

those types of dogma. It's really hard

because you often end up You start out

with some set of beliefs. You think

something's interesting.

Or maybe you invest in it, maybe you

start a company in it.

And then it turns out the thing you

think is really interesting turns out to

be really hard and you get killed.

And then 5 years later a company comes

up that actually does it and wins. Mhm.

And the question is why? Why did the

thing suddenly work when it didn't

before? Or there's 10 attempts to do X

and then

suddenly is it that technology got good

enough? It could be a regulatory change.

It could be a market shift. It could be

whatever. An example be Harvey AI Legal

where selling to law firms traditionally

has been awful.

And Harvey's not much broader than that,

right? They also have very strong

enterprise adoption and

lots of different people using them in

different ways, but the dogma was always

like building stuff for law firms is

crappy as a business and you should

never do it. But what AI did is it

shifted things from selling tools to

selling work product or selling units of

labor. That's really the shift in

generative AI.

We're going from seats and we're going

from software

and SaaS and we're moving into a world

where we're selling human labor

equivalents. We're selling work hours or

labor hours or whatever you want to call

it. Mhm. of cognition. And so, Harvey is

effectively helping really augment

lawyers in different ways. And part of

that's a knowledge corpus, but a lot of

it is this tooling that really helps

lawyers achieve the goals that they have

in different ways in a collaborative

manner in some cases. And so, this is a

fundamentally different type of product

from what people were selling before.

And so, it opened up the market in a way

that the market wasn't open before.

There's actually a broader conversation

around is the world market limited or

founder limited in terms of

entrepreneurial success. The Y

Combinator school of thought is that we

just don't have enough founders, and if

we had 10 times as many founders, we'd

have 10 times as many big companies.

And there's an alternate school of

thought, which is how many markets are

actually open in any given moment in

time, and those are the ones where you

can build big companies. Cuz if the

market isn't open to innovation or

change or whatever or hasn't is

undergoing a shift, you can't really

build anything or anyhow, so why do it?

And the striking thing about AI is it's

opened up tons and tons of markets that

were closed for a long time.

And it's opened it up because of

capabilities, but it's also opened it up

because every CEO is asking themselves,

"What's my AI story?"

And there's way more openness to try

things than I've ever seen in my life.

And so,

we have this odd moment in time where

things are massively available for

founders to do new things.

And if you're an AI company and you're

not seeing explosive growth quickly,

something's fundamentally broken.

Because the markets are so open

that you can suddenly grow at a rate

that you've never grown before. There's

always been cases of companies that just

go like this.

But again, you look at the ramps of

OpenAI and Anthropic, and it's the

fastest ramps to tens of billions ever.

Percentages of GDP, it's like crazy. If

we come back to your comment of

not necessarily market first and

strength of team second all the time,

but like you said, you 90% agree with

that, right? And

if you have an excellent team in a

terrible market, like that's going to be

that's going to be a difficult one to

execute. How do you determine what is a

good versus great market or just what is

a great market? What do you look for?

And the example you gave, I might be

overreading this, but what you said that

when Google shut down, I think it was

Maven, right? That's an interesting kind

of event-based approach as an input to

investing, right? Cuz you're like,

"Okay, if they're not going to build it,

we're

that suddenly creates

a playing field for

startups. Yeah. to play in that space.

So, could you speak to more

of how you determine or look for great

markets? I mean, there's a few different

ways to think about it. One is like,

some people take the framework of why

now. What's shifted now that makes it

something interesting market because

people have been trying to do things for

a long time in every market. And so,

that may be a regulatory shift, right?

Some Sara, the fleet management company

benefited from the fact that somebody

was regulation around needing in-cab

monitoring of drivers. So, you had some

of the cameras watching people so they

don't fall asleep while they're driving

trucks on the road, right? Mhm. And so,

that was their entry point to that start

building out a suite of software.

But, it was a regulatory shift.

Sometimes there's technology shifts,

like what's happening in AI. And the

crazy thing about the AI shift is

the foundation models instantly plugged

into a massive set of markets, which is

basically all enterprise data and

information and email and just all white

collar work was suddenly available to

AI. Mhm. Cuz it was the perfect market

for that. It also plugged into code,

which is a type of white collar work.

So, it's just suddenly it just inserts

into language and language is used

everywhere in in enterprises as well as

in consumer. And so, there's just a

massive market to tap into and transform

or set of markets. Robotics is a little

bit different from that because even if

you had the world's best robotic model,

the submarkets that already have robotic

hardware are quite small on a relative

basis.

And so, you don't have that instant

runway that you would with

language unless you come up with

something new there. That's kind of an

aside that I think robotics is really

interesting and be important. It's more

just that nuance of like what's that

instant thing you plug into

commercially. And then,

there's regulatory shifts and technology

shifts, there's

incumbency or company shifts,

competitive shifts.

A company may blow itself up, it may get

bought by a competitor. One company I'm

I'm excited about on the security side

is called In-Q-Tel and they're basically

competing in part with Hashi. Hashi got

bought by IBM. Anytime you get bought by

IBM, you slow you slow down a lot

usually. Mhm. Suddenly it creates more

opportunity for a startup. So, I I feel

like there are these different things

that can change at a given moment in

time. Mhm. [clears throat] It could be

the market trying really fast as

Coinbase and crypto, right? You just

have suddenly this adoption and

proliferation of token types. There's

lots and lots and lots of different

markets that are interesting. The

commonality is usually like is it also

big? Is there a big enough town? And

there's two types of towns. There's fake

town. Just for people listening who

might not have it. Your total

addressable market.

>> Total addressable market. So what's the

market you're in?

And sometimes people come up with these

fake markets. They're like, oh well,

we are facilitating

global e-commerce and global e-commerce,

I'm making up the number is $30 a year

and so we're in a $30 a year market and

if we get just a tenth of a percent of

that is 300 billion of revenue and

you're like, that's not

that's not your market. Your market is

like you built this little optimization

engine for SMB websites or whatever.

That's not a $30

market. And so really it's kind of

defining the market. There's a really

famous example of this where defining

your market changes how you think about

it.

And so that was Coca-Cola, right? So

Coke and Pepsi were roughly neck and

neck in terms of market share

for decades.

And then one of the Coke CEO said, hey,

maybe we should be thinking about our

share as share of

liquid sold.

Like drinks, not share of soda.

And so we just went from 50% market

share to 0.5%.

And that's why they bought Dasani and

that's why they entered all these other

markets, right? Because they said,

our definition of our market is wrong.

>> Mhm. We're not in the soda pop business,

we're in the drinks business. And so I

think also conceptualizing what you're

doing can really help change

your scope of ambition or how you think

about what you're doing. If you're

trying to spot

along the lines of the fraud kill you in

the payment space, right? Any

dogma in the AI world, the sphere of AI,

right?

Anything anything hopped to mind where

you think, uh, maybe that's not true now

or maybe in like two years it'll be

completely untrue, but people will have

latched onto this belief as

one of the thou shalt not or thou thou

shall

commandments. I don't know. I mean,

there's some things that have circulated

in the past around what's the ROI on the

capex spend of that and whatever be paid

back and I just like

I think that stuff is probably off. But

yeah, I think fundamentally there are

moments in time where it's very smart to

be contrarian. And there are moments in

time where being consensus is the

smartest possible thing you can do. And

I think right now we're in a moment in

time where being consensus is very

right.

You know, and you can really overthink

it and what's the contrarian thing? We

should go do a bunch of hardware stuff

cuz blah blah blah. And like maybe just

buy more AI. You know what I mean? I

think people make these things way too

complicated.