– English Lyrics

Lyrics & Translation

[English]

You'll read a lot of press that

basically says AI is coming for our jobs

is most of the press is not inside of

big companies seeing how much time we

spend on useless activities that are

necessary but not strategic. There's a

very very long list of things that

software never did before that AI agents

are perfectly primed to go do now. And

that's basically the opportunity set.

Now is the moment. This window will end.

In this window, between a year ago and 3

years or so, plus or minus from now,

this is when the next hundreds of great

companies will get started.

[Music]

So Aaron and I go way back. I don't know

if you remember this. Um I went and

searched my old Bump. So Bump was my

startup. I searched my old Bump email

for Aaronbox.net.

Yes. Um, and I found very old emails

where we would coordinate in Mountain

View times to meet up with three

founders. Yes.

You, me, and this guy named Sam Alman.

Yeah.

And we would coordinate to try to like

do brunch or lunch or whatever. And then

I saw emails between us saying like,

"Oh, yeah. Well, Sam's going to probably

like not show up again."

And so that's No, he would always

remember this. You started Box um

probably before many of the people in

the audience were alive.

Okay. Um uh who's uh let let me just

show of hands. Who's like below 20 years

old?

Wow. Okay. Great. Yes. Then accurate.

Very very accurate. Maybe to start.

Yes. Like we're going to talk about AI a

lot. But to start you went through

another major transformation which see I

use the word transformation digital

transformation. Yes. Um

around cloud going to cloud. maybe just

walk us through like what that looked

like at a very high level and then maybe

what is different or similar about the

transition to AI. Now

we started the company in 2005 and this

was a this is a time where you have to

kind of you know literally go back 20

years and think about a world where the

internet was much slower, browsers were

way worse. We didn't have the iPhone. We

didn't have Android. Chrome didn't

exist. Like everything was just like way

worse on every dimension. We basically

had a an initial kind of idea that as

the internet got faster, as you worked

on more mobile devices, um you'd want to

be able to access your data from

anywhere. And that was the original idea

of Box. Um where we said you'd go

between different computers, you'd

access your files, you you'd share them,

you'd collaborate. So we launched the

company. It was initially focused on the

consumer market um or consumer slash

just kind of proumer, anybody that

wanted to sign up. we uh started to get

a little bit of traction and by you know

a little bit like we're talking like 10

people signed up like you know in the

first week or something. So it was just

very very slow very slow and steady

growth and what happened was we um uh we

got a we got a little bit more growth.

We we got some early funding from Mark

Cuban and some angel investors. We then

uh dropped out of college. We got you

know sort of more of an upswing. We um

uh had a premium business model. We let

people sign up for free and start to use

the product. And then one day we we kind

of run ran into this fork in the road

which was uh do we stay the consumer uh

going down the consumer path or do we

pivot to the enterprise? And the

calculus was um we felt like it was

going to be way too hard to compete with

all the consumer uh technology platforms

that would give away storage for free.

They they'd sort of embed it into their

operating system or their social network

or whatnot. it would be way too hard uh

to go in and and and monetize this. So

we decided to pivot to the enterprise

where we could be cheaper, faster,

easier than a lot of the big incumbents

at the time. Um so we pivot to the

enterprise and we got extremely lucky on

the timing because we rode this growth

wave of mobile and cloud that were sort

of working in tandem to effectively

create a new IT architecture within

enterprises. And so for us, we we got to

ride this wave where once we had better

security, um you know, more more

functionality than a lot of the

incumbent services as companies moved to

the cloud, they needed a way to share

their data, access their information,

and so we became a an increasingly

obvious choice. So that was the the

cloud wave and that kind of propelled us

to to where we're at today. Um, and

there's a lot of similarities to the

early days of cloud and the early days

of AI. With um, maybe one big

difference, which is the early days of

cloud, we were having to go convince

people that the cloud was going to be

this big deal, right?

And we had to go tell everybody that

that, you know, the future is going to

be cloud computing. It's totally safe to

trust us with your data. A lot of people

didn't believe us. And so that meant we

just couldn't win, you know, deals in

entire segments of customers. So,

conversely, with AI, uh, you're no

longer really having to convince people

that AI is the future. Everybody tends

to be bought in in the enterprise

segment. There's a lot of of still

slowness in adoption in large

enterprises, but it's not because people

aren't convinced that AI is the future.

It's just because there's lots of

natural sort of pace of change that an

enterprise has to go through.

Why are they convinced? Is it just that

they themselves personally have used

chatbt? Yeah. Is that the main driver?

Because like I'm not aware of a lot of

AI solutions that are deployed to

enterprises that have like really made a

difference.

Yeah. I think it's maybe unlike cloud

like cloud didn't didn't have like

decades and decades of of sort of

societal level conversation about cloud.

It just like emerged one day and it was

like this is like it seems kind of cool

and efficient but if you're in an IT

department the cloud was actually very

scary because you're taking your servers

that you manage you can see them you you

manage all the software for and you're

relying on AWS or or or Microsoft or

Google to manage that infrastructure.

And so there was a real big shift on it

and the CEO or the head of marketing,

the head of sales, they didn't really

care how the infrastructure was

delivered. So you didn't have anybody

kind of pushing on the IT org saying we

have to go to the cloud. Like nobody

really cared.

AI totally different situation. We've

had, you know, science fiction for, you

know, probably 100 years that has

basically said you're going to have

robots, you're going to have artificial

intelligence. over the past, you know,

20, 30 years, it's been in the

zeitgeist, um, self-driving cars,

watching, you know, Watson on Jeopardy,

uh, using, you know, early products like

Siri and Alexa. So, it's it's it's sort

of been pervasive that, okay, at some

point AI is going to get good enough

that it's going to be this helpful aid

for us. And now that that you have the

chatbt moment where the head of

marketing can go and play with chatbt

and be like, "Wow, this seems to write

marketing copy maybe better than even my

own marketing people." Mhm. There's you

don't need to sell them anymore that AI

is like clearly the future. Now it's

actually just about like how can you go

implement something that's going to be

safe, reliable, works with your data,

you can trust it, which is now the new

set of changes that that all these

companies have to go through.

Got it. Cool. So, so Box started as

basically like a a folder in the cloud

effectively. Yeah. And then you added a

bunch more

stuff to that, but that is still kind of

the core of it. AI seems to be able to

like completely change what you can do.

Yeah. maybe just help us understand what

what are those cool things that you can

now do for big companies.

Yeah, so uh for us the exciting thing is

is that AI agents basically thrive on on

unstructured data. So if you think about

it, there's basically two data types

that really matter in the world. There's

structured data. This is what goes into

a database. You know, if you launch an

app tomorrow, you're going to start with

a database and the stuff that's going to

go in the database are like customer

names and ids and user IDs and all that.

If you go to a big company, the stuff

that goes into a database is all of the

invoice numbers and the the client

record numbers and the amount of revenue

they generate and their distribution

partner names. That's what's in their

database. Then they have a lot of

unstructured data and that's all of

their documents. It's their contracts.

It's their invoices. It's their

marketing assets. It's their

presentations. All of that data. The

vast majority of data in the enterprise

is that content. It's it's all of this

unstructured data. And it's it's called

unstructured because basically it can be

totally free form text. there's no

inherent kind of, you know, kind of

computer structure to it. And so the

problem is is all of the data that goes

into something like Box historically,

you've never been able to really

automate anything about it. You know, if

you just think about 2 years ago, you

can't go to your your sort of all of

your files and ask them a question. You

can ask a question in your database. You

can, you know, say, "Please find me all

of the records above the, you know,

following value." You can't do that in

your files because the computer doesn't

know how to read all those documents and

understand what's in them. AI agents

basically changes this. So all of a

sudden all the data that's inside those

folders becomes immensely valuable to to

companies because now they can ask all

that data questions. You can begin to

automate workflows around that data. Our

whole uh vision is basically what if you

turned all of this information into this

new kind of corporate asset or or set of

knowledge that companies can operate off

of. And that's where you know I think

there's going to be immense startup

opportunity is a world of how do you

have AI agents for almost every task or

job function in the enterprise.

Let's talk about that then. Let's say

this world emerges and we have AI agents

that do a bunch of jobs. I think a lot

of people are worried like oh that means

that we don't need the humans to do

those jobs anymore. And I know you have

you have like a strong perspective that

like no actually it will go the exact

other way.

Yeah.

Tell us tell us why you believe that. I

think basically if you go to most

companies um and you you sort of say

tell us everything that you do all day

long across the company and you you you

sort of assess how valuable is all that

work that's getting done. How valuable

is every email you send and all the time

you spend going and finding information

or all the manual work it takes to read

data kind of you know look at that

document extract information from it

versus the time that really is the high

impact stuff. you're with a customer,

you're coming up with a product

breakthrough, you're supporting a

customer to to to use more of your

product, and you kind of did a ratio of

that time. The vast majority of of time

inside of a company is on the stuff that

really is not strategic. It's it's sort

of necessary work, but it's not

strategic to get done. So when you think

about that ratio, if you could free up a

company to work on the stuff that's

strategic and not the basically

unstrategic stuff that doesn't

differentiate them, most companies

actually have a large set of things they

would go do with their time. They would

spend more time on breakthrough

innovation. They would spend more time

with customers. They would um launch

more marketing campaigns. They would

proactively support their customers

instead of just being reactive. The

reason why I think the press gets this

wrong, and you'll read a lot of press

that basically says AI is coming for our

jobs, is most of the press is not inside

of big companies seeing how much time we

spend on useless activities that are

necessary but not strategic. And so when

I go talk to companies and they and I

say, "What if you had AI agents do all

this kind of work?" they instantly their

eyes light up because they realize,

well, now I can actually free up my time

and my employees time to go do much more

interesting things or they start to have

this list of all of this work that would

be much more strategic if it got done

if AI agents could go and do it as

opposed to the work that never gets done

because it's too unaffordable and it's

just economically not viable to go and

do.

This is like the backlog of stuff in

your company that you're like, "Oh, if I

had more people, I could go do those

things, but I can't."

Exly. And basically it's there's an

entire category of work where if you

just did like pure microeconomics I

could pay for the labor to do that work

if I knew that it would produce enough

value to pay for that labor.

Okay.

But the threshold of starting that work

is too high. I can never even try and

see if it's useful.

Okay. So I would I would argue that

literally the like if we go 10 years

into the future, the vast majority of

work that gets done in 10 years from now

will be work that today is in that

category. It's the work that like right

now we can't we can't even attack

because we're like I'm not going to hire

somebody pay them $120,000 a year to

just see if that thing produces value.

So I'm never going to get around to it.

Yeah. And then in 10 years from now when

you just deploy AI agents everywhere to

go do those things we will be doing so

much more as a company when we you know

launch an ad campaign internally we

translated into like three to five

languages our top markets that's about

all we have time for because it's just

too expensive. It it you know it sort of

just hurts your brain to think about

doing it across every segment of the

market in every region. When an AI agent

just takes an ad copy, translates it

into a 100 languages, our company will

just grow more. We will we will just be

in more markets. We will serve more

customers and agents will be the reason

that we were able to do that where

previously we were bound by people time

and we would never have been able to

justify getting that work done

previously.

Makes a lot of sense. And yet today,

Amazon announces that you should expect

that they have fewer headcount over the

next few years because of AI. Yeah, I

totally agree with everything you just

said, but then the press sees these

announcements. What are they to make of

that?

To be fair, I I I only saw that snippet

literally 1 hour ago. So, I I I didn't

see the full memo. I'm sure Andy Jasse

had some other thoughtful points. This

is why startups are in such an

incredible uh position. You know, I

think if you're at the point where, you

know, I don't know the the corporate

headcount of Amazon, but let's say the

total headcount is in the hundreds of

thousands to low millions just across

all like every poss, you know, every

delivery function, etc. I could totally

see the scenario where for them they're

like, okay, given the markets that we're

in, given the things we do, you know, if

we can't get this done with hundreds of

thousands of people and AI agents don't

just augment that, like we're probably

running the company wrong. I I'm just

picturing that's the internal kind of

corporate meeting. But now imagine the

50 person company where all of a sudden

they can act like a 500 person company.

Then you just have to ask yourself if

the 50 person company can act like a 500

person company because of AI, will that

company become a 100 person company more

quickly than preAI? And then that

basically tells you does this thing

create jobs or not? And my argument

would be that the 50 person company that

is in more markets serving their

customers better doing better research

on their customers. They're more armed

with the next feature they should build.

They can build that feature faster

because of you know cursor winds surf

etc replet will that company grow more

quickly in a post AAI world on the human

side? I would argue yes because they

they get themselves into more markets

they get more done. So I think it's more

of a a case of you're going to read

headlines about the biggest companies,

Amazon, etc. And I think there's a case

we made where AI isn't is is an

efficiency gain for them. But now the

hundreds of thousands of startups and

small businesses or millions of startups

and small businesses, I think it becomes

an economy where they can get so much

more leverage than ever before. talking

about startups like I think maybe a lot

of folks in this room look at the like

B2B SAS companies or the enterprise SAS

companies and just think like oh every

problem has been solved like there is a

big company incumbent like you are one

of those big company incumbents how

should they think about like starting a

company that could one day take down a

company like yours not yours

specifically like the other guys

I'm not going to give you any advice on

taking me down but I'll give you advice

on everybody else so interestingly it's

it's a very fascinating um proposition

uh in question. So starting with

consumer for a second. Three years ago,

I was I was having these kind of like

not like existential questions um but

like deeply like deep philosophical

questions. What what year did you join

YC?

Um 2022.

Okay. Actually, so great timing. So, so

around 2022, I I kind of made this list

of like nouns and verbs of just as like

a just a fun kind of mental thought

experiment of like think about all the

nouns and verbs of like what we do in

our life. Okay, we eat, we sleep, we we

travel, we watch something, we are

entertained or whatever. And I went

through that list and you know the list

is not a thousand words, right? It's

like 50 or something. And basically down

that entire list I tried to plug has

that problem been solved

relative to like 15 years ago just

choosing an ar arbitrary point in time.

If we had this conversation in 2008 and

we said you know music, travel, uh

entertainment, hospitality, you know,

food, all of these things we would we

would basically sit around and be like

all of these things kind of suck.

Like it's just like it kind of sucks to

get food. It kind of sucks to get, you

know, listen to music like like you had

to download illegal music like

everything was painful. Fast forward to

2022, we we've solved a lot of problems.

Like when I want food, it comes in 20

minutes from Door Dash. When I want to

listen to music, it's on Spotify. When I

want to watch a movie, I got Netflix or

YouTube or whatever. So, it was a tough

environment for startups because you're

kind of like, "Wow, now we're really

only able to do derivative things

because the core nouns and verbs like

have been solved." And you know,

coincidentally, YC basically created

like half of them and or more. And so

and so like basically we we had this

period of like 2008 to like 2014

where like every noun, every verb just

got solved. The same was largely true in

the enterprise. So now do the nouns and

verbs in the enterprise. Payroll, CRM,

email, calendar. You just go through all

of those things and basically every

problem had some kind of incumbent or

like atscale startup.

Yep.

Which is very bad for startups because

because you basically had this era of

companies that that knew how to build a

modern technology and they were solving

these problems. like you don't really

want to compete with Gusto because Gusto

is still a modern really good payroll

system. There's not like a lot of

vectors into competing with Gusto. So

that was 3 years ago. Today, it's the

first period in probably about a decade

where I'm extremely confident that

there's now a new set of nouns and verbs

where startups are in the right position

to go and create the next set of

solutions for because AI has created

enough of a change in the landscape to

create those opportunities. They're not

going to be always the most obvious

things that you start out with. Like it

won't just be like, oh, it's CRM but

with AI because Mark Beni off in

Salesforce is going to do CRM with AI.

Like like he's gonna figure out a way to

do that. He's they're very good at

executing. Like that will happen. But

there's a very very long list of things

that software never did before that AI

agents are perfectly primed to go do

now. And that's basically the

opportunity set which is what categories

of professional services or work is

there no incumbent technology for that

AI agents are basically finally able to

go and solve and there will be 100

startups that get created between last

year and and in three years from now

that all become 5 10 20 billion dollar

companies

because they're able to find the next

set of nouns and verbs or you know a a

mixture of nouns and verbs that are like

Okay, it is, you know, legal work for

this thing and there's an agent and and

for for the first time in history, you

can go and deliver that via software as

opposed to it used to only be able to be

delivered by people. And that's the

opportunity that I think everybody has.

Very cool.

YC's Next Batch is now taking

applications. Got a startup in you?

Apply at y combinator.com/apply.

It's never too early and filling out the

app will level up your idea. Okay, back

to the video. When you create one of

these new nouns or verbs, a lot of them

don't look like software in the sense

that we think about software today where

you like sell a company access to some

number of seats of the software and the

humans click the buttons and type the

keys. Um, how will business models need

to change or will they change? How will

companies charge for these things?

Yeah. So if you were building a SAS

company again prior to literally this

year or last year, your your only real

monetization uh strategy was how many

humans are there that need licenses to

my software? And in the SAS world, you

know, we we call those seats and

basically how many people need a seat of

that software. And um and you were maxed

out based on the demographic size of

that particular category. So if I sold

software for lawyers and I go to a

company, I can only sell the amount of

licenses as that company has lawyers,

which is like a huge, you know, limiter

to the addressable market size of of

your company. And so agents basically

completely blows that up because all of

a sudden you can have AI agents that

effectively contain the labor of of that

job function in the software itself. So,

you can go to a company and you can say,

"I know you only have three lawyers, but

my agents could do the amount of work of

basically unlimited lawyers, which means

you're obviously no longer going to sell

based on the number of of of, you know,

humans in that company related to legal

work. You're going to sell based on some

approximation of the amount of volume of

work that has to get done related to

legal work." And that's the new

monetization strategy that I think we

all have which is let's make the example

of of uh of you're doing some kind of

you know legal review of some you know

set of contracts and you basically say

okay uh previously a human would cost5

or $10 per contract to review based on

you know human time. AI agents you don't

tell them this but AI agents let's say

can do this in for 10 cents. Yep.

So then you charge that customer $2 and

all of a sudden they're like wow this is

incredible. you've just saved me 80%.

And and you know, you're now extracting

obviously a very meaningful profit from

that and there's no particular limiter

to how much they're going to pay you.

It's just going to be how many contracts

do they have to go through the system.

And so, you know, every company I think

is every space is going to have a

slightly different version of that

business model. But the new business

model is some form of consumption. The

only you know concern that you have to

have of going of overly veering on

consumption is the recurring nature of

of of the revenue. You generally want to

be in a position where you have some

kind of subscription fee for your

software as opposed to only being paid

you know the moment that it happens

because then you run into this problem

where the customer you know plows

through your system and then next year

they don't show up because they used

they used they've reviewed all their

contracts. So you you have to figure out

how you basically keep some kind of

ongoing recurring revenue stream, but

besides that, you're you're going to see

more of a consumption orientation with

AI.

And and I guess what you're saying is

you think the prices these AI companies

will be able to charge per unit of work,

let's call it, or outcome will be a a

fraction of the human cost as opposed to

what we would maybe consider more of

like a software cost, right? Because if

it costs 10 cents to do the job, are

people really going to be willing to pay

$2 for a thing that they know cost 10?

Well, the question is basically how much

software do you have to build on top of

the AI tokens?

Yeah.

And and you know you can it's like very

obvious like imagine a continuum where

there's like almost like no software.

You will get price compressed down to 2x

max of the token cost versus a world

where there's like a tremendous amount

of software. you could probably support

80 or 90% gross margins, which means a

five, you know, 5x plus, you know, you

know, an eight or nine 10x plus increase

over the tokens. I I'm not going to tell

you guys the number um because it's

proprietary, but if I told you the

amount that we spend at Box on storage

of storing files,

Yeah.

you would be surprised.

Yeah.

Because you would say, well, I thought

you were in the storage business.

But the reality is what customers are

paying for all of the software above the

storage.

So eventually we're going to get to a

point where customers are no longer

going to just be paying for the

intelligence tokens. They're going to be

paying for the workflow software that

goes on top of the the tokens

themselves. They're going to be paying

for your ability to build AI agents that

have a unique set of of context and

proper and and connections and

capabilities and and access to data that

you know can command a a meaningful

premium on the underlying AI token.

Totally. Yeah. I mean I saw this at

Google Photos, right? And when we

proposed that we should build Google

Photos, a lot of people at Google were

like, why would you do that? You can

never make money. It's a commoditized

market. It's just storage. Like there's

Amazon. You can just store your photos

there. And uh it turns out it's like a

90 plus percent margin. It's really

great.

And and and this is what's amazing about

um we we are all incredibly lucky to be

in effectively I'm sure there's other

industries, but let's just say one of

the top slashthetop industry that has

deflationary economics on the supply

side.

Yeah.

The reason why that matters is because

it means that that over time your raw

materials will get cheaper. you know,

you don't have to basically raise your

prices in perpetuity like many other

industries. You can actually just get

more efficiency gains over time. And so,

you know, I don't know the latest price

on Google Photos, but let's just say

it's 10 or 20 bucks a month, right? If

you told anybody, we'll just store all

of your photos ever created for $10 or

$20 a month or whatever the number is.

Like, you'd be like, "Yeah, that's

fine." That customer doesn't need to

show up and say, "No, I'm only going to

do it for $8 because I know your costs

are going down." They're like fine to

pay 10 bucks for all their photos to be

stored. Yet every year, you know, your

underlying costs are going down. That's

what's going to happen in AI.

As long as you can find not how to not

be so greedy that your pricing is sort

of like is kind of like offensive.

You know, look at like again Windsor,

Replet, Cursor, etc. Like we're at like

non-offensive levels of pricing. It's

like it's 20 bucks a month. 50 bucks a

month, but we know that in 10 years from

now,

they'll probably be able to drive down

their raw materials lower, but we won't

be able to command lower prices for

those things because it's just like

within a reasonable amount of spend.

Yeah.

And so, you always want to be in a

technology category where that is

happening. And probably by being here

today, you've you've effectively chosen

to be in that kind of of category.

Yeah. And I think that's true so long as

there's not infinite competition driving

prices down.

Okay. But here's what's amazing. So, so

let's just take um we we haven't been in

this war uh directly for a long time. Uh

we pivoted from consumer to enterprise,

but you know, let's just take Google

Photos for a second. Uh everybody knows

Dropbox. Would you agree that Dropbox

has been in a infinitely competitive war

for 10 years?

Yeah.

Okay. And the company generates

somewhere on the order of a billion or

so in cash a year. No economist in

history would be able to understand

this. They would be able to say, "Wait a

second, like storage is getting com

commoditized. How is it that people

still pay $10 a month for something that

has switching that has basically limited

switching costs and other choices in the

market?"

And it, you know, people build

familiarity. There actually are

switching costs because there's some

data network effects. Sure. There's user

experience things you get used to. So

even even in a world where of hyper

competitive thing as long as again

you're not getting too greedy on your

pricing then then you can usually sort

of you know land in a spot where people

will stay with you as long as you're

innovating.

Makes a lot of sense. Um okay one of the

topics I've heard from folks in the

audience throughout the last couple days

is if you believe that AI is going to

really keep growing over the next 5

years which I think most of us do. Are

we not going to be in a world where

companies just build all of their own

software internally? Right? Instead of

hiring Box to do a job for me, why won't

I just command my AI agents to go write

the software that emulates what Box

would have done? Like what's your take

on the reason why I'm not afraid of it

is there's a concept that I think

Jeffrey Moore um if if you read if I'll

leave it with a couple books that you

should definitely read. This comp this

book called Crossing the Chasm is

probably one of the top five business

books ever and you should definitely

read it. And right after you read it,

read something called Innovator's

Dilemma, which is basically the number

one business book of all time. But in

this book, um not this book, but the the

author Jeffrey Moore came up with this

idea of core verse context.

Yeah.

And the the the premise of core verse

context is every company has to decide

what is core to their business, what's

context to their business. If you are uh

Disney, core to your business is like

you know designing amazing IP and

characters. Context to your business is

your HR system. So what does Disney need

to do? They need to get really really

good at technology to make Pixar

insanely powerful. They don't need to

get really really good at technology to

run their HR department. The Disney

value proposition doesn't relate to, you

know, did they pay their people on time

or not. they just need to pay their

people on time. They don't need to, you

know, they don't need to innovate on

that. Every company has a choice of what

time they're spending on innovation

versus again like I just want that to be

in autopilot. And so this is this is

more where just because you can do

something, the vast majority of the

world doesn't end up doing something.

and and coding your own custom software

for every single bespoke need in your

business tends to be in that category

because most people basically say, you

know what, cool. I can build an HR

system and I could go negotiate with

Workday or whatever to lower my pricing.

But, you know, here's the problem. Three

years from now, there's going to be a

bug. That bug is going to like pay

people the wrong amount of money. I

don't want to have to go and call my IT

team in the middle of the night to be

like, "Shit, you have to go fix this bug

that paid everybody the wrong amount of

money." I I want to be able to go to a

company that I know that I can sue if if

they up or switch to a competitor,

right? Or switch to a competitor because

I can't sue my internal IT team and I

certainly can't sue anthropic. So, you

don't want to be having that liability

for things that are context. It's not

you don't get the the upside of of

getting really really good at that. And

that's that's how most companies work

and operate. And so, you know, I I read

these things from Clara and others where

they built their own systems and I think

it's like fun to read about. I think

it's very novel. I'm glad that they're

doing it because it lets us have this

conversation. I think it's going to be

basically useless

and um other than for like being cool

fireside fodder, most companies won't do

it. Now, I'm still very bullish on

custom software because there are lots

of things inside businesses that are

custom software for the core where

actually the company can't get around to

building custom software for the core

parts of their business. And so having

things like replet or cursor or wind

surf or whatever is actually very useful

because now they can go and work on

software for those things. And that that

actually I think ends up being very

powerful.

Makes a lot of sense. Okay, we're going

to open it up to audience Q&A. But

before we do that, while you guys queue

up, um my last question is just this is

an audience of, you know, college

students, grad students, recent grads. A

lot of them want to do a startup one

day. What's your advice? What should

they do in this new world? Read

innovator's dilemma, read Crossing the

Chasm, read Blue Ocean Strategy. Those

are the three books you have to read. If

you do what's in those books and you are

going after the B2B market, I guarantee

you, you will be 10 times better off

than any other startup that is just

starting from scratch.

You will have a way to think about

markets, disruption, what incumbents are

vulnerable, which ones aren't. If you

really deeply internalize them, you will

be so much better off. That's the first

thing. Second thing is have an

incredible founding team. I'm I'm a I

mean I know solo founders that will

happen for sure, but but just try and

grab one friend. They could be like the

least like technical friend of all time.

Just be in the grind with somebody

just because you're going to have more

fun. You're going to see through more

more difficult times together. Um so so

have a team that you really are excited

to work with to to kind of get through

anything. Do not under uh estimate the

need for for tailwinds in your market.

So, make sure that you're going after a

market where I'm just going to assume

everything at this event is is AI,

obviously, but like if your market is

not truly transformed by AI, don't touch

it. It's not it's just not worth it

because you're going to be fighting

against a headwind that is just

unnecessary to fight against. Like, go

after markets where AI like

fundamentally changes like the very

economics or or or you know, actual

process of that thing. So, you always

run a want want to ride a tailwind. So,

ride a tailwind. Have a great team. Uh,

build a big vision. Now is the moment.

This window will end. It'll it'll be

over in two or three years from now.

You're in the window right now where,

you know, maybe it won't be your first

attempt. Maybe it won't be your second

attempt. Maybe it won't be your third

attempt. But in this window between a

year ago and three years or so, plus or

minus from now, this is when the next

hundreds of great companies will get

started. So be ambitious because because

these windows don't come you know but

for more than every you know 10 to 20

years. So I would exploit that take

advantage of that in five years from now

you can be less ambitious but in for the

next four years you've got to go big

because these are these are these

windows that that give you that

opportunity.

Love it. All right start over here.

Uh so I have two questions which

probably have the same answer.

Oh cool. very efficient like this guy.

Um but yeah, so I want to know like in

the core of your business that is

storage like only in the core do you see

uh a space for AI to manage anything or

help with anything? And the second is in

the storage space are there any new age

startups that perhaps like use some

emergent technology that can better

storage or is it a solve problem? Yeah,

I think I think if you're if I if I take

your question very literally at like the

do you mean like the literal hard drives

of storing the data?

Anything like software level behind

sharing storing security?

I think it's um and I invite anybody to

try and and and come up with a new

thing. I think the storing of the data

is a pretty solved problem. The thing

that that I think AI could augment is

like just to get so boring is things

like life cycle management of the data.

Um, in our business, Google Photos, you

tend to have this this curve, which is

the most active data needs to be, you

know, in the in in basically the part of

your servers and in the regions that are

most sort of fast, you know, fast

throughput and fast access versus the

stuff that nobody ever sees, you can

kind of store in some archive. AI will

probably help with that because it can

kind of predict what what uh what access

what data people want to access. But

higher up on the stack, that's where the

transformation will be. What do people

do with their data now? Not just the

storage of it, but how do you turn that

data into something that's much more

valuable than just a document? How do

you turn that document into a new type

of intellectual property or value for

that company?

My name is Charlie. Uh, I'm a game

designer here in the city working at a

startup. Um, graduated from USC last

year in computer science and game

design, which is the best major ever.

Um, and my question for you is, what is

the meaning of life?

Wait, for reals?

Yeah.

Oh, man.

Um and and I you're 24, right?

Yes.

Yeah. I I think you won't fully

understand it, but um you're in a period

right now where you're just in grind

mode. And I would just recommend just do

the grind thing. This is not a period

where you have got to do meaning of life

stuff. Over time, I think you start to

better have a sense of okay, like you're

on Earth for some amount of years, you

know, like you obviously want to try and

have as much of an impact as possible on

something. So, can you help society in

some way? Like that's the that's one

part of fulfillment. And then and then

you have another set of more personal

things, you know, kids, family, that

that side that has to be fulfilled. And

but but again, like you're in your 20s,

so like like I was just heads down

grinding, not overly worried about the

meaning of life. So I'd say like put a

pin in that. Be nice to everybody.

Like help the world as much as possible.

Check back in in about 5 years. like now

is your window for for just being super

commercial.

Okay,

so thanks so much for being here today,

Aaron. Uh my name is Gary and my

question is about like enterprise

products and their relationship with

design. So earlier this afternoon like

Dylan Field joined and was on stage

talking about the growing value of

designers, especially as AI makes the

development process faster. Yes. And how

that might imply how craft and like

great design becomes a bigger

differentiator for SAS companies. But

when I think about like enterprise

products and their motivations to just

like plainly deliver value at least for

some of these companies, how do you

think about like craft and great product

design when building enterprise

products? Uh, and how has that maybe

changed as Spock has developed?

I mean, enterprise software for sure

historically has not had good design

because the people purchasing the

software tend to not really care about

the design of it. they just need to

solve a particular kind of utilitarian

uh uh you know task. So it's actually

been more voluntary that the companies

decide to have really good design. So

over the years you know companies like

Slack, Figma certainly others have sort

of said you know we're going to

prioritize great design even if I mean

Figma had to because of its demographic

but we're going to prioritize great

design because we should just have

better software that people can use. Um

so I think this has been a trend over

time. I would highly recommend building

just great looking feeling experience uh

enterprise software even if the customer

doesn't incrementally value that from

you. It just makes it much more fun to

build software. Um and so absolutely

raise the bar and and try and build

amazing software and some customers will

care, some some won't, but you'll feel a

lot better, you know, about what you're

producing.

Thank you.

Yeah. Cool. Think we have time for maybe

one or two more.

Okay. Hi Erin, my name is Orion. uh and

have I have actually built a unicorn

startup in China for the past 10 years.

Wow.

And uh planning to come to the US uh and

start something new here. Uh I know

number one step is to join vice for sure

but uh I want to know your answer. I

know you touched on this a bit uh in the

previous question that uh say if we do

things in HR in AI um how should I

answer the question about like

competition from workday in the future

since it has a massive amount of user

data. Yeah. about like what the user

like about the candidates about the

performance all that uh since you are

sort of incumbent in the data storage

like space yeah

and uh I know workday launches a lot of

agents this recently I don't know if is

if it's mostly PR or it's actually

product but I want to know your

perspective on that and I guess a second

question is what's your view on glean on

knowledge management

I think it's always good to um to

overestimate your competitor's

capability ilities uh and then figure

out your strategy in a world where they

have they have those capabilities. So

what I would I would do is I would s I

would assume all of Workday's agents are

amazing and then figure out what

strategy would be competitive with with

them. So you know couple a couple

examples. One you can go after parts of

the market that they're just not selling

into. Workday only has somewhere on the

order of let's say 10,000 customers.

Well, there's like, you know, 10 million

businesses globally that would be

relevant for HR related agents. So, at a

minimum, go sell to everybody else

that's not a workday customer.

Then, you know, there's certainly going

to be use cases where they're not the

natural sort of, you know, provider of

an HR agent and that will also be then

the right opportunity for a set of

startups. But um this is why I'm very

bullish on startups right now because I

think incumbents are only going to be

the agent providers for their existing

install base, which means that there's

going to be tons of opportunity for so

many more agents that those incumbents

aren't already selling into. On Glean, I

think I I like them, but um but I think

there's going to still be lots of

different approaches to to enterprise

knowledge management.

All right, I think we're out of time.

Everybody, give it up for Aaron.

Thank you.

Key Vocabulary

Vocabulary	Meanings
run /rʌn/ A1	verb - to move quickly on foot verb - to manage or operate
spend /spɛnd/ A2	verb - to use money or time
time /taɪm/ A1	noun - a period or duration
companies /ˈkʌmpəniz/ B1	noun - organizations that do business
data /ˈdeɪtə/ B2	noun - information
software /ˈsɔːftwɛr/ B2	noun - programs for computers
cloud /klaʊd/ B2	noun - online storage and computing
enterprise /ˈɛntərpraɪz/ B2	noun - a large business
customers /ˈkʌstəmərz/ B1	noun - people who buy goods or services
markets /ˈmɑːrkɪts/ B1	noun - places or systems for buying and selling
jobs /dʒɑːbz/ A1	noun - work or employment
AI /ˌeɪˈaɪ/ B2	noun - artificial intelligence
startups /ˈstɑːrtʌps/ C1	noun - new business ventures
agents /ˈeɪdʒənts/ C1	noun - representatives or automated entities
opportunities /ˌɑːpərˈtuːnɪtiz/ B1	noun - favorable circumstances
transformation /ˌtrænsfərˈmeɪʃən/ C1	noun - a complete change
strategic /strəˈtiːdʒɪk/ C1	adjective - important for planning
unstructured /ʌnˈstrʌktʃərd/ C1	adjective - not organized in a set way
content /ˈkɑːntɛnt/ B1	noun - material or information
access /ˈæksɛs/ B1	verb - to reach or obtain noun - the ability to use something