I would still be probably loading up on

all of the Frontier rounds. These

numbers could continue to get much

larger.

>> Now, I think Aaron Levy is one of the

luminaries on AI pervading enterprise.

And he did a viral tweet the other night

and I said, "Dude, we've got to do a

show on this." So, this is specifically

on how AI will impact the biggest

enterprises in the world, how agents

will be introduced into the largest

enterprises. And we couldn't have anyone

better than Aaron, founder and CEO of

Vox, one of the public companies of the

last decade. This is an incredible

discussion.

>> What we are in is a commercial and

economic race. We haven't removed humans

from the loop. We've just changed where

they enter the loop. Everybody is so

myopic about this. I want to just like

shake the industry. There are going to

be more lawyers in the next 5 years than

we have today. The workflow needs to be

redesigned for agents, not for people.

The budget of tokens will have to move

out of it spend and into regular OPEX

spend. Is your job harder than ever?

>> Yes. If you're in software or

infrastructure or building agents, it's

a year of complete unrelenting

execution. Ready to go.

>> Aaron, dude, it's so lovely to have you

on the show. You know that we have Rory

on every week and he's just like Aaron

is the greatest. I'm not going to do his

accent because I suck at them, but he's

like the greatest. You can't you can't

easily do an Irish accent.

>> Well, you know, I I can't really do the

Irish accent so well, but that's right.

Exactly. Uh but you basically, I'm sure,

bought Rory one of his houses. So, no

wonder he's grateful. Uh but

>> we we Rory uh we got more out of Rory

than he got out of us. So, uh

>> exceptional man. But I wanted to start

and we were just chatting. I was running

around the pot listening to the Dwark

and Jensen episode and I was like, I

don't think Jensen came out very well.

Do you agree with me that Jansen didn't

come out very well from that episode?

>> Um, I I think this is like the greatest

roarshack test of all time of of where

uh where where somebody is mentally on

AI. Um I if I so I happened to see a

bunch of the tweets before I watched it

and so I was a little bit obviously

biased in advance but if I hadn't seen

any of the commentary and I had just

watched it um I would have been very

confused by the by the commentary post

uh you know post uh interview and and um

to be clear I kind of jumped to the more

uh salacious part of of you know China

and that topic but I'm I'm almost

probably 80% with Jensen um and um and I

I my my my sort of uh kind of way of

thinking through the logic actually

works much closer to uh to Jensen. Um

you know the idea that we're in some

kind of you know kind of race

existential race where a month or two of

advantage is going to you know change

the total outcome of of AI progress and

and what everybody does between us and

China. I I just don't agree with. I

think what we are in is a commercial and

economic race obviously with safety you

know built into that. There's no

question. Um, and I think we actually

have a lot more power globally uh if

it's our technology stack that's

powering AI. And so I I I kind of am

more in the camp of of Jensen on on his

lines of logic. And you know, Doresh

kind of oversimplified a few a few

components. You know, he said, well, you

know, with Mythos, if if we get early

access to that, then we can go and

upgrade all of our systems. And you know

with with again great respect to Dores

Cesh it's like it's like upgrading

software is a multi-year effort. So

unless they somehow keep Mythos you know

closed for the next decade there's not

like some magical moment where you can

just secure everything. This is an

ongoing endless you know till the end of

time. You're always in this sort of

leaprogging you know between the

defensive side and the offensive side.

Um and so I just don't think these

things are as binary. And so I I

actually more am inclined to uh to to

Jensen's view of that. And then Jensen

had a really key point that was didn't

go viral yet. So maybe you could kick it

off, but he had this little small

vignette about 90 seconds in the whole

conversation where he said, you know,

we're going to do ourselves a disservice

if we scare people out of engineering,

if we scare people out of radiology, if

we scare people out of healthcare

because they think all these jobs are

going to get eliminated with AI. That is

not helping us. uh that is that is uh

it's doing a disservice to the next

generation. It's doing a disservice to

society as a whole. Like we we don't yet

know any way to use AI in a capacity

other than augmenting our work where we

still eventually have to go and review

the work in some in some form. Maybe you

don't have to review the tiny little

parts of it anymore. You can review a

bigger you know part of the of of the of

the you know work product that happens.

But um but we haven't removed humans

from the loop. we've just changed where

they enter the loop. Um and uh and I

think that that Jensen has a more

pragmatic view of of the technology. We

should be, you know, very thoughtful

about how we make these systems safe,

but I much more land in Jensen's camp uh

on the overall kind of contours of the

debate.

>> Oh Jesus, dude. You didn't leave me. You

didn't quite

Okay. first a disservice by discouraging

people to go into categories like

radiology or engineering. Do you think

you will have more engineers at box in 5

years time?

>> Uh we will and and I think the part that

everybody misses is that they everybody

is so myopic about this I want to just

like shake the industry. We are we are

so myopic and and self-interested and

and we think that the entire industry is

the tech industry and when you go around

the country or world and you go and talk

to a tractor company and a bank and a

pharma company and you ask them do you

think you have enough engineers to go

and automate what is going to happen in

your industry going forward they

absolutely unequivocally universally

always say no and so what what the

breakthroughs of cloud code or codeex or

others are are doing is it's making it

so those companies companies now can

actually do the same kind of engineering

that Silicon Valley has been able to do.

And so we are myopic because we think

that that tech is the only use of of

engineers and tech is only I don't know

what the right number is 8 10 12 15% of

of GDP in the economy. What happens when

85% of the economy now gets access to

engineering like tech has always had?

That is what will happen. That and and

so yes, maybe if you're graduating, you

know, name your computer science school

today, you don't go immediately to

Google. You go to literally John Deere

or Caterpillar or Eli Liy, but the

skills that you have are going to be

just as relevant in just a different

domain. You're not going to be building

a little app with little buttons. You're

going to be automating pharmaceutical

research. You're going to be doing AI

for the future of of of, you know,

farming and industrial equipment. So,

we're just too myopic about about how

this works. And um and and you know uh

uh you can already start to see this

sort of playing out. There was a really

funny FT article which is lawyers are

being inundated by all of these kind of

AI responses that they're now getting

from their clients saying, "Hey, can you

review this contract or can you review

this memo or can you look at this this

case?" Well, guess what happens when

everybody thinks that they're a lawyer?

Do you know what the ultimate constraint

is? the ultimate constraint is the

actual number of lawyers that that

actually are able to go and review all

of this stuff being produced. So like I

would take the other side. I'd rather I

like like there are going to be more

lawyers in the next 5 years than we have

today because we've made it easy to

generate legal content. But it has not

gotten any easier to actually get any of

that approved by any court system or

file a patent or any of the things that

law actually ends up relating to. So

these are again this is where I I I just

differ from the rest of the industry.

>> Do you really think so? With the

greatest of respect we are seeing the

eradication of kind of lower ranking

legal positions

>> and that that is a different issue which

is how do you do the next generation of

mentorship and apprenticeship when AI

does automate the maybe u traditional

tasks that those workers are doing. big

question, a big question facing every

bank in the world, every law firm in the

world, anybody who had a sort of an

apprenticeship model. I don't doubt that

that's a real issue, but that's

different from the constraints that that

all of this work ends up resulting in

that you still have not been able to

automate. We had a customer conversation

two weeks ago and and and this is just

going to sit with me forever. I'm going

to always have this example. They've

automated or they're working on

automating patient referrals when you

know when you want to go and see the

radiologist or the the high-end doctor

for whatever issue you have. They're

automating that which is awesome. So now

you don't have to be on the phone for

you know a week or whatever. Well guess

what you can automate anything but if it

still is 18 months out before an

appointment is available. What what your

ultimate constraint is still the

healthcare institution and the amount of

doctors we have and actually the amount

of of of real labor we have across those

organizations. So yes, maybe maybe you

you don't want to, you know, stake your

career on being a frontline, you know,

customer ser in healthcare right now,

but but first of all, that same person

will have a lot of other types of jobs

that they'll have access to. Um, but you

still will end up having all of these

other constraints that that that

eventually we will need to produce more

and more jobs to go and resolve. So

automation is going to actually just

force us to see the next set of

bottlenecks that are in all of these

industries that we didn't perceive that

we had before because everything was so

slow and manual.

>> What job title does not exist today that

will be incredibly prominent in 5 years

time?

>> Yeah. So I'm workshopping and and a

bunch of people are doing this. So this

is like not my invention, but I'm I'm

workshopping.

>> Aaron, you you've got to take

attribution as a venture investor. It's

all about coining a term. Okay. This was

your original thought in the shower.

Aaron Lavies, share it with me.

>> I've been influenced by nothing I've

seen online. Uh, this is all from me.

Um, so there's some kind of and and who

knows if this sustains as as a full-time

role or where it gets diffused into. I'm

not I'm not uh I'm not 100% clear on

that, but there is 100% a role right now

that there's going to be

500,000 a million jobs created for and

and it's basically some kind of agent

operator and and this person is um is

actually going to be needing to be uh

somewhat technical. They're going to

have to like be deep in the AI world.

They're going to have to understand MCPs

and CLIs and they're going to have to

know how to write skills. They're going

to have to understand agents.mmd files.

The it's going to be this group of

people that will know how to go into

your marketing team or your legal team

or your operations team or your life

sciences research team and and this is

the person that is basically going to

enable that function to get leverage

from agents. And um and the problem that

the real world has that startups and and

frankly many of your guests don't

understand is that is that when when you

start a company from scratch, you've got

like you know the world is your oyster,

right? You can design your workflows

however you want. There's really no risk

if you if something goes wrong because

you don't have much scale to begin with.

There's no real regulator that that is

sort of calling on you to say, hey, you

know, are you doing things the right

way? It's it's it's effectively infinite

upside in whites space. when you go into

a a you know a Fortune 1000 pharma

company or bank or or you know

consultancy um that doesn't that's just

not the case right these guys have

they're regulated they have data

fragmented across their organization

they have employees that are that are

sort of wired to do workflows a

particular way so there needs to be

somebody that can basically say hey if

we actually want to get real leverage

from automation we need to start to

redesign the workflow that we're doing

and the workflow needs to be redesigned

for agents not for people and so So what

do you do when you when you reimagine a

business process where the agent is now

doing much more of the work than than

what you know than what the human used

to do in that process. And that just

means it's a it's a very different sort

of implementation cycle. It's there's

real change management. You've got to

get data organized in the right way.

You've got to connect up systems in the

right way. Guess what? The second a new

model drops your workflow probably

breaks. Um because the way you prompt

that agent now is different. there's a

different way that that it wants its

syntax to be to be handled. So that it

just requires care and feeding and and

and a real level of kind of technical

and business process acumen. Uh so I

think we're going to create you know an

untold amount of jobs that look like

that. Some of those people will come

from it. Some of those people will come

from operations. Some of them will come

from engineering. uh if you're in a

maybe more technically inclined company

where it's like the next generation of

if you know there's a a limit to again

the number of software you need to build

that looks like an app on your phone

there's an unlimited amount of software

you need to build that looks like a

background system process that's

connecting different data sources

automating workflows that's where the

the work is going to go well this was

really going to be one of my main

questions which is you know Jensen very

clearly said AI won't kill software it

will explode the amount of software

needed and when I thought about that you

know the thesis is obviously kind of you

have this kind of core AI that crawls

over 15 SAS tools and they really become

databases that agents crawl on top of.

Is that what it looks like? And are they

not just valueless SAS tools then?

>> Yeah, I mean I I think that that I'm I'm

sympathetic to that argument in some in

some categories. I think there's some

software where because the person was

the user of the of the software and they

were clicking all the buttons that your

sort of ratio of buttons to underlying

APIs was like more in favor of buttons.

And I'm I'm oversimplifying, but there

there are some tools where you open it

up and there's like 93 features um that

you're kind of clicking around on and

the and the user has been so accustomed

to exactly how to do that that the that

the software's value proposition was

correlated to to roughly that that sort

of mass in a world of APIs and a world

of agents being able to do more of the

of the work that you used to do on

clicking those buttons then then again

the value goes more to the API layer. So

then the question is how many APIs do

you have? Not not in like a you just

need a thousand APIs, but like like how

robust and useful and and proprietary

and how much business logic is embedded

in those APIs versus it's just calling a

database and pulling a record like does

the API surround a a a set of business

logic of like no it actually secures the

data or it knows exactly what person

each piece of attribute should have

access to inside the organization.

That's you know at the end of the day

all software has a database behind it.

So you could oversimplify it and be

quite reductive to that. But there's a

lot of business logic in the layer above

the database that that software players

have. Like if you're an ERP system, you

know, you're way more than a database at

this point because you've written a

tremendous amount of business logic of

how your supply chain should be

automated and work and how you should do

accounting. None of that goes away. So

then the question is what changes is the

user interface that the either the user

or the workflow is interacting with. The

user interface might be now you're just

chatting with an agent. I think

increasingly the right way to do this is

there's some kind of agent in the

background that's connecting multiple

systems. So you're you're not even like

the user is maybe not even seeing half

the value that's happening, but the

agent is sort of working across an ERP

system, a CRM system, an HR system, a

you know a document repository and then

doing work across those systems, which

means that the value proposition has to

be how good are your APIs, how

well-designed are they, are they ready

for agents, and then can you monetize

that in some way that makes sense? and

and we we are treating software too too

much like one gigantic sort of of

monolithic industry and you know it'd

probably be better to have some kind of

2x two which is like how much business

logic is there how much sort of human to

agent you know collaboration does there

need to be and and like so the reason I

bring that up is the moment you have

human and agent collaboration you need

some kind of you know usually you need

something that the user can pop into to

to experience the work that the agent

did and and that probably doesn't go

away so much. Um uh and then and then

you know when more agents are working on

the software which parts of software do

the agents need those APIs even more

than humans ever did and I think there's

a lot of categories of software where

actually agents using the tools is a

massive boon for the technology as

opposed to a dilemma.

>> Where will agents use the tools more

than humans do and those API calls

become much more frequent?

>> Yeah, I mean an easy one is just

unstructured data. You know, agents are

going to be this incredible consumer and

creator of your unstructured data.

They're going to read through every one

of your contracts and generate all of

your contracts. They're going to

generate marketing assets. They're going

to write reports for you. And so, when

it becomes trivially easy for you to

generate all this new information or

have agents review it all, well, guess

what? You still need a backbone that

kind of manages and coordinates and

creates the guard rails of those

workflows and and all the agents doing

that work. So we're about to see an

explosion of unstructured data as an

example.

>> With the greatest of respect, Aaron, can

I just interject?

>> 100%.

>> Does that increase the value of your

business? When I think about that, I I

asked Aaron from Monday, if you become,

you know, a data repository which agents

crawl on top of,

>> how do you retain value in that? I would

ask the same to you with respect

>> 100%. It's it's the question on the mind

of every investor on the planet right

now. So we're we're used to it and it's

not a it's not it's not a scary

question. Um, one thing that that helps

us is we've always had a a a an API sort

of maybe not first but equal strategy.

Um, uh, if if I told you the number of

API calls we did last year, you'd and or

you guessed first, you'd probably be off

by an order of magnitude. Um, uh, so so

the volume of of API usage on our system

is already enormous and already, you

know, is outsized relative to any of the

enduser interactions on the system. Um

and that's just a virtue of you use

content in a variety of applications and

workflows that that you know far exceed

what what people you know kind of you

know open up their finder and and upload

a document into like like an ERP system

generates files. A a wealth management

portal you have clients uploading

documents into the portal and they never

see box. Um you have workflows of

invoice processing that's happening

behind the scenes. So the headless

version of box has been alive and well

for you know almost since the day we

started the company. And so agents to me

just again represent a force multiplier

on that. So it's not a it's it's it's

actually an exciting proposition for us.

We already know how to monetize it. The

question is like will the exact dollar

and cents be the same between an agent

user and a previous application user. We

don't know. But we do know that if the

number goes up by 100x or a thousandx

that that's actually more opportunity

for us in the future. Now that's not all

the same for all software providers. for

where we sit in the workflow where you

just you generate a document it needs to

go somewhere you have to secure that you

have to protect it um you have to govern

it over the long run that's just more

data going into our platform and uh and

that's you know so that's why it's just

all upside for us

>> you said secure and protect it we

mentioned our mutual love for Rory

O'Driscoll I do a show with Rory and

Jason every week Jason has bluntly said

that this will be the golden age for

cyber security because the security

threats are going through the roof are

you concerned with the system

vulnerabilities and the security threats

that are coming with AI and what do we

not know about security that we should

know.

>> I am concerned but not uh in any kind of

like new concerned sense. Uh this this

to me was kind of priced in the moment

that we were generating code with AI. So

if you can generate code you have two

problems. One you're going to generate

way more code than anybody's ability to

review that code. So, you know, starting

with GitHub Copilot six years ago or

whatever the date was five years ago,

like that was just priced in which is

which is as soon as as AI writes most of

the code or and then like 90% of the

code and then 95% of the code then by

volume we're just going to produce this

unbelievable amount of code and and any

you know any change in a system uh you

know everybody kind of thinks about

security as like um you know is there a

zero day where there was an unpatched

you know component of your technology.

ology or somebody found a clever new

packet uh package that that that you

could kind of slip into. Uh every time

you you ship a new feature, you have a

chance of a security vulnerability

because the the AI could have written

in, oh, you know, we want to actually

open up that port in in the system

because we need to do something and

maybe that was the wrong decision for

the agent to go and do. So, so we're

going to be living in this new world of

of cyber risk uh in the form of of using

agents more and then on the other side

obviously if you have the offensive side

able to use AI probably more in the form

of open models and and whatnot then they

can find more vulnerabilities because

they can scan across the internet far

faster than before. So you actually have

two new forms of risk in the development

process and you only have one benefit

which is agents can also review the code

and and try and keep it secure. So, so

it's it's it's going to be a a very

dynamic um uh you know, period. I I

think you know, for better or worse,

agents are the solution to the problem

that agents have caused and um and and

that's why there's going to be a lot of

money made in agentic security uh as

well.

>> You said agents are the solution um to

the problem that agents have caused. It

almost reminded me of when Yansen went

on TV and was like, "Oh, every engineer

should be spending I can't remember the

amount. I think it was either 250 or

500,000."

>> Yeah. or like half the salary

essentially.

>> Yeah. Yeah. And it's kind of like, you

know, drug dealer, you should buy drugs.

Well, okay. No [ __ ] Uh

>> I again I'm I'm you know obviously Jen I

mean listen we love Jensen for that

level of of uh of you know grandiosity

and and charisma. So I I actually I but

you know whether he's off by half or

not. I mean directionally the idea is

actually pretty salient which is which

is you're going to be spending more on

compute per person in the future than

than you ever thought. and that you

certainly are today.

>> What percentage of salary are you going

to spend on compute in box in five

years?

>> Uh great great question. Uh I don't

think we've modeled that out in in five

years and obviously the joy of being

public.

>> Well, this is your chance.

>> No, no, totally. I you know I was told

not to model long-term financial

projections on podcasts. So, um so let

me let me Yeah, it's a weird SEC

financial thing.

>> So boring.

>> Don't ever go public if you don't want

to model on uh on podcasts. out. This is

why the Collisons don't. Everything else

is great. They just didn't podcast.

Yeah. Cheeky P.

>> I don't know if you I don't know if

you'd be able to pin Patrick or John on

the same question for their five-year

view, but but you know, it'll be a

larger number for sure than it is today.

So,

>> I'll smash them with four tequilas and

then ask them. Um, you said one of your

observations in your very viral tweet uh

was about token maxing and kind of token

allocations within enterprises. I'm

really intrigued. How do you think about

advising CIOS on token allocation? token

maxing. What we should know that we

don't know. Yeah. How do you think about

that?

>> This one's tough. It's it's it's you

know, the the general advice will end up

sounding kind of like um uh you know,

kind of generic by definition. Um it you

know, usually I mean it's going to have

it's going to have something to do with

with your tokens will have to correlate

to where there is the most amount of you

know, value generated for your company.

Like like most bland statement of all

time, but just obviously has to be true.

So in the software industry, we're into

token maxing because guess what? Like

generally the value proposition of your

company will correlate to how much

software can you produce. And so so you

know if you're trying to drive a lot of

change and you want to make sure

everybody's shipping lots of soft

software and you want to be able to

teach the best practices faster, then

token maxing and leaderboards are an

interesting way to do that. I you know

it's not obvious that you're going to

see that across every industry. Um uh

we've we've seen a couple of interesting

examples. One company had this sort of

like Shark Tank pitchathon type thing

which is you know teams have to show up

and they have to go pitch for for

compute you know token budget and then

you kind of allocate it in some central

fashion like a VC would and then you

sort of you know I don't know their

exact interval but I would imagine you

review that 3 months 6 months in being

like okay did you get the upside that

you thought on on that token usage. So

that that's an interesting one. I think

you have a another company had a kind of

a view of like you know it's it's some

kind of like natural stratification of

you know 5% of your users are doing the

most valuable things 20% are doing the

next tier of most valuable things and

then everybody else is sort of doing

general productivity I'm making up their

numbers but but the idea would then be

like well for that five or 10% give them

the the best models with unlimited

capacity for the next 20% have some have

some limits maybe it's a a little bit

more efficient of a model and for

everybody else it's sort of like we're

going to just use the cheapest thing on

the market. It's it's not going to be

like the game changer of the employee

productivity. Um and so I think

everybody's kind of working their way

through this. the the part that that

back to Silicon Valley's again kind of

you know sometimes more um uh you know

let's just say like like positively

naive view is is like real world they

have like budgets and they have like

annual budget planning cycles because

they have EPS numbers they they commit

to Wall Street and so you don't get to

just be like oh we're going to token max

across the enterprise where everybody

gets unlimited token budgets because

obviously then that company would just

miss their their earnings throughout the

year. So you have to like wait for the

earnings. You have to wait for the

budget cycle. You have to figure out

what teams you know make are are most

interested and and have the best use

cases. That's a that's a natural

journey. One final bookmark one final

one final bookmark um that that I think

is is well understood now at this point

is the budget of tokens will have to

move out of it spend and into regular

kind of opex spend. this can't be

treated like a oh, you know, I'm going

to trade off between Salesforce licenses

or or or compute tokens like like it's

going to more be I'm going to trade off,

you know, this next marketing campaign

uh and and instead I'm going to go and

drive more automation in our in our

marketing engine. Like it's it's going

to be that kind of of set of trade-offs.

>> What happens to that token budget when

it transitions to that different spend

category? Um well first of all it goes

up because because no well because it

spend as a percentage of revenue of of

large enterprises is is

>> but is this the same as the kind of

classic VC blog post which every [ __ ]

firm has written which is like you know

AI it's moving from software budgets to

labor budgets and every partner goes and

likes the tweet and there's like no

[ __ ] [ __ ] like really.

>> Yeah. Uh I mean if you do it in that

voice it sounds it sounds kind of like

um you know maybe uh you know simple but

like yeah that that but like that's just

like a very big deal in technology.

We've never had there's never slash

rarely been a technology that you could

sell into an enterprise where you

weren't capped by that company's

corporate IT budget. And so now for the

first time ever, you have a technology

where you can go into the line of

business and you can say, I can now

offer you a a a new tool in the form of

an agent that will augment a workflow

that will make you 50% or 100% more

productive. And so maybe I should be

able to get 5% of your opex budget this

year to go and do that. Like that that

is a new budget to tap into. And I don't

think it like you know 10xes the size of

of IT spend or or technology spend

globally but it certainly doubles it.

>> I mean current enterprise technology

spend is estimated between 10 and 12%.

To see that going to like 20% as you

said there is like I think relatively

feasible. You said about kind of

companies being like based on earnings

per share and actually having budgets

that they have to adhere to. Very

strange not to have venture funded

companies.

>> Yeah. They don't have a limited VC to go

and solve this.

>> Can't we just go to our venture investor

and ask for more money? Um, the one

thing that I worry about is we see this

insane demand side pull. Every company

in the world needs an AI story. Everyone

wants to kick the tires with something.

And I think we project the same demand

side pull and extrapolate it

continuously. Do you worry that we are

in a momentary 18-month period on the

demand side pull and that may not always

be lasting?

>> You know, it's very possible I should be

more sensitive to that. Um uh but uh I I

I would take the opposite side of of of

that particular wager at the moment

because um partly because we I already

saw one diffusion cycle with cloud and

actually how long that ended up taking

and the and and the the the kind of

spiky early nature you would have just

been like oh my god this is this is on

fire it's it's and how could this last

and 20 years later it lasted and got way

bigger than we ever realized if it

works. The market's always larger than

you ever think. And um and then the only

the only part why why 18 months is like

not even a relevant window to me is I

think diffusion is going to take longer

than Silicon Valley thinks. And it's

back to the very first kind of that new

role idea. When you go to most

companies, they can't yet just deploy an

agent to do you know full uh you know

financial proposals for all of their

their clients without a human reviewing

the thing. And because the SEC will just

show up and be like, "Hey, like you you

just you just gave this person bad

financial advice and you're going to

lose your license." Like that that will

just start to happen kind of across the

board. And so um and and so that that's

why, you know, people take time. That's

why we we we there's a lot of regulatory

controls and compliance teams, security

teams have to figure this out. That just

takes time in the economy.

>> I I had I think Matt Fitz Fitzpatrick

from Invisible, which is like a cheuring

or a Mccor competitor. Okay. And

>> he said you cannot sell into enterprise

without an FD model. It is impossible.

>> I mean it rounds to being true. So

>> yeah,

>> super interesting to hear that because

we're seeing like the rise of oh we go

PLG and then we like seep up into

enterprise.

>> Well I I I don't sorry I wouldn't I I I

don't uh think of those as as mutually

exclusive for what it's worth. I guess

what I'm saying is when you think about

adoption within the largest enterprises,

aren't AI services companies the best

positioned companies of the next 5

years?

>> As in you're saying like traditional

professional services?

>> Yeah, I'm saying Accenture's AI team

that come into Bank of America.

>> No, 100%. These these these spaces are

going to be again both bigger and more

sustainable and robust than people

realize. We we are always so back to the

myopic thing. We're so myopic. We're

like AI will replace all of this stuff

because it just does it for you. And

it's like like uh I'm trying to think of

um uh you know maybe my most recent

experience with the best models in the

world. I probably had to go and change

15% of the thing that that that that was

the output. And so and so like you just

like we're nowhere near eliminating the

human from the workflow. And so in a

world where you don't eliminate the

human then there's a lot of like real

change management of like where should

the human enter that business process?

How would you want to review that that

work output? How do you wire up your

systems to make them effective for a for

the agent and human collaboration? How

do you connect all of these data sources

together? One one thing that we see is

um you know, if you wanted an agent

right now in a Fortune 500 company to go

and and give you an answer to where is

the most risk you have in your upcoming

renewals for your contracts.

that agent might find 10 different

systems that contain contracts in them.

And half those systems will be like

legacy technologies that don't work well

with the agent. They're kind of low

throughput or maybe you can't even wire

them up. They're on network file shares.

They're in legacy document management

systems. So, first of all, half your

data state is not even ready to work

with the agent. The other half of the

data state is probably fragmented

because you have two decades of

employees bringing their own tools. And

so the agent will just go and find the

wrong document or the wrong contract or

the wrong piece of data because you

never really cared to have some kind of

standardized system for your contract

because people could just always go and

find what they were looking for. Agents

can't do that. They I mean they'll find

what they're looking for, but they'll

just as often find the wrong thing as

the right thing. So they have to be

targeted. They have to have that

information get curated. They need to

understand the context of of what is the

process that they're doing. That is like

what I just described right now is 10

years of work for Accenture in every

enterprise on the planet or the nextg

Accenture that does this in particular

industries or workflows like we have to

go upgrade your systems. We have to

start to understand and organize your

data in the right way. We have to start

to describe these workflows to the agent

itself. We have to figure out where the

human is in the process. That is just

real change management that every

organization will have to go through.

>> We also have to have someone to blame.

>> 100%. This is why a lot of these

industries last, which is like I have

lawyers, not because I can't necessarily

ride an NDA. It's because it's your

freaking fault if anything goes wrong.

>> Yes. No, literally. And and and we don't

know. We're not like like I promise you,

you're not going to be able to blame

Anthropic when something goes wrong. And

so if you can't blame Anthropic when

something goes wrong, then then at some

point it it doesn't really work to tell

the comp like like to tell your

customer, well that that sort of system

that we set up screwed up your data or

it automated something the wrong way or

create a security vulnerability because

the company will just say, well, I'm

never working with you again. So then

you have to have some accountability in

your own organization for who is liable

to when when something goes wrong. And

and the moment you have to have any

liability, you have to have some amount

of ownership and accountability and and

and people have to have have sort of,

you know, they have to roll up to

somebody who has more liability and more

ownership and more accountability. Like

this hasn't really changed the

fundamental pattern of of human behavior

and contract law and and you know, the

regulatory regimes that everybody's a

part of. We've just sort of given our

our our computers a machine gun to go

generate way more information and work

with all of our data.

>> You said before when I've tried the

latest model, it's got like 85% of the

way there. I speak to many of the best

early stage and more mature you West

Coast based companies and they say,

"Hey, we use frontier models to set

where we can be and then we use

open-source Chinese models to get as

close as we can to that frontier

benchmark." Is Silicon Valley being

funded by a generation of open CCP

funded open models?

>> I mean that that must be kind of

empirically true. Um I uh I I I don't

have the same kind of like uh oh that's

so scary you know kind of element. Now

obviously again holding out some some

element of risk of of some some backdoor

weights that that can get triggered at

some moment or some parameters but like

like like I'm not I I just like that's

not how I'm perceiving it. But um uh but

yeah and but also that's yeah I would

say that's kind of orthogonal to my

point about like the best frontier model

still will go and do the wrong thing. Uh

and so thus I have to be in the I have

to be in the workflow loop to make sure

that I review its its work.

>> You know as a vantage investor I

specialize at making bold statements

with little substantive evidence. Um

>> it's worked for the greats. So

>> do you know what I'm just following

their lead. Jason Lmin, my dear friend,

says, "Why has no public company created

any good agent product? Everyone creates

60% [ __ ] agents, but he's like the one

person who's done it, Palunteer, and no

other public company has created a

sufficiently good agent product." Why is

that?

>> Um, you know, I I don't know that I can

fully endorse the point, but I'll I'll

I'll give you the because I I I would

argue our agent is sort of the best

agent for working with content. you

know, this is a very fastmoving uh space

and you have to be kind of wired in at a

level that that I don't think you've

ever had to be wired in in tech. Um uh

like I am, you know, and and the

information sources aren't the classic

ones. It's not the it's not the rollup

review two weeks later from your

traditional news publication that is

going to give you any kind of alpha.

It's it's it's the practitioner who's

the you know literally the engineer at

the you know agent sandbox company and

their their long form article on how

they are handling you know memory and

the harness and you know like like like

if you're not wired into that ecosystem,

it's very hard to then have your team

you know be at the kind of forefront of

all of what is happening. And so it just

is a it's a different pattern than what

we've ever had to do. Like like you know

co was was pretty crazy like we all had

to kind of like hunker down and be

paying attention to daily news cycles on

on coy stuff. Um but it wasn't like a

tech problem like it wasn't hard

technologically. Um so there's like

there but there's not been a moment

before where the speed of change and

responsiveness you have to have is quite

literally on a multi- uh you know

multiple times a week cycle. Is your job

harder than ever?

>> Yes.

>> Because of that speed of transience of

superiority of technology.

>> Yes. Uh you have you basically have this

this you know component of one there's a

tsunami of change that you can just feel

and so you're you're like okay we got to

like run faster than ever before. And

then there's a and then there's just

like the pure technical underpinnings

which some of it has business and

strategy implications some of it has

product implications. Some of it has

partner ecosystem implications.

uh because of that tsunami that you have

to very quickly kind of wire up what you

are doing about that shift uh and and

where the market is going. Uh at the

exact same time you have to also be like

you know find a way to be a bridge for

your customers that that you know also

don't want to get you know crash into by

the tsunami and they want to be able to

to be able to have a bridge into the

future and so there's just you're

juggling a lot right now.

>> You said your agent product is the best

product. Again, Jason and Rory said

this, and Rory might kill me for this

because he gets a little bit more

sensitive about when I quote him or

misquote him more appropriately, but

like he basically says if, and this is

Jason again, if you can't like charge

way more for your agent product

that Wall Street doesn't give a [ __ ]

that you have to reacelerate revenue

with agent products, can you charge

significantly more for an agent product?

The the answer is yes, but but there's a

little bit of nuance which is our our

business model is we have a new plan

tier that we just introduced last year

that basically houses our you know best

workflow capabilities, our business

automation, you know, uh our application

development capabilities and then the

agent is sort of central to that because

it's going to help you automate the work

that that you're actually doing with

your content. So it'll read a document

and extract metadata from it. it'll

process information inside of a of a of

a workflow. So that is actually causing

a re reaceleration of our revenue

growth. Last year we we we saw an

inflection in our revenue growth. And so

that that it's already happening in our

business. Um and and so we are we are

doing the thing that I think Rory is is

sort of probably saying is the new

benchmark. Now to be fair to what's

what's happening though is I think Wall

Street still is sort of saying we kind

of need to just step back and see where

everybody lands in this because of how

much change there is. So um so this is

very much a year where if you're in

software or infrastructure or building

agents you just it's an ex a year of

complete unrelenting execution.

>> Do you look at the ticker?

>> Yeah.

>> Every day.

>> Yeah.

But I was like a day trader.

>> I've never met I've never met a public

company CEO who hasn't. The Nan CEO was

on the other day and he's like multiple

times a day. Multiple multiple.

>> Yeah. No, 100%. I'm but like but like

partly I just I have like you know ADHD

or something and so I just need like I'm

like it's will we look back on this

period and be like what the [ __ ]

Companies trading at three times cash

flow like way over exaggerated or not?

>> Well three times cash flow is is very

much overexaggerated. I would say that

we're in a period right now where

basically the market is being treated

roughly as you know in in as a kind of

indiscriminately

you know kind of bucketed se sector and

the next year two years or whatnot

you'll start to see some separation and

parsing between the companies because as

I noted in the beginning agents will be

really good for some parts of software

and agents will put pressure on others

other other parts of software so and

it'll mean some companies have to fully

pivot and some companies can just sort

of ride their wave and and if they

respond, you know, effectively, like

clearly 3x free cash flow is is like,

you know, that that seems like

aggressively low territory. But I also

think that at times in software things

have been aggressively overvalued um

beyond the the realm of of likely what

the terminal value is of of particular,

you know, category or or or company as

well. So So I think we're I think

there's just a pendulum that that needs

to kind of find its equilibrium right

now. Um and uh and that that'll play out

over the next year.

>> Okay. I'm going for spicy. Uh I I

interview most of the public company

CEOs that you know and I know and Jason

Lin said on the show if Aaron Levy is

the best which you a phenomenal No, but

you're a phenomenal AI first mind and

leader. Uh to just roll with me on this

and because it gets worse. Sorry. And

even he is struggling.

>> Wait, why am I struggling?

>> Well, I mean

>> I just said I'm tired. I Wall Street who

I mean Wall Street does its things like

we're like we're not like we're cranking

>> dude I it's Jason blame him

>> but like I I do think I think that that

there's a little bit

>> I think this generation of CEOs that you

have around you though is equipped for

the AI transformation that is ahead

cuz I don't like I think I'm I'm not

blowing smoke up your ass you are you're

so versed in this you're so fluid but a

lot are like now one said to me the

other day no we don't have the AI chops

in house, we might need to bring it in.

>> This one's hard. I think um I think you

still have a lot of kind of founder or

or tech uh you know, forward, whether

they were an engineer or just they're

just very technical, you know, category

of folks that are are pretty dialed in

and like like I I have Slack channels

and and WhatsApp groups where people on

the weekend are are just like working

with Cloud Code or Codex building stuff

and they're public company CEOs. So, so

like like they they are clearly wired

in, tapped in, they they can feel the

technology and they are not going to let

their company lose. Um, you know,

assuming that that as a as a category

they're in a spot where where there's a

lot of upside. Um, so yeah, but like

every every technology wave there's

winners and losers. I don't know that

the this won't be any different. Um, I

and I I just think that you just have to

you just have to be super dialed in and

work through it.

>> Hard one before we do a quick fire.

Okay. Who has the world turned their

back on who you think should be much

more appreciated?

>> I I don't I like you know I'll give

maybe a shout out to like um Atlassian

uh as an example. Um uh I I think um I

think that that feels like like oversold

territory. You know

>> you think 78%'s a bit harsh.

>> I I think I think I think I think

possibly. and uh and and you know it's

in the category of I just like like what

they've they've been fighting this this

narrative and I'm not going to speak too

much for them but like I think what I

perceive is is oh no engineering gets

commoditized and so like where in the

stack was was their engineering you know

revenue generation and again with my

headset I'm like no there's going to be

more engineers and so now does that mean

that Alassian's product set will have

will look exactly like it does today no

like obviously it's got to evolve and

whatnot but but I think if you're like a

company selling infrastructure for

engineering to be more automated. Uh

like that seems like a good spot to be

in and and you know I you look at what

linear is doing and it's it's fantastic

and it's awesome to watch. Um but I

don't I think there'll be you know

multiple plays in that space just given

how big the market is. Um I think right

now this is a moment where you need to

be deep in the workflow and you need to

have data. uh you you you have to you

have to have data uh in your platform

and you have to be the best place for

that data to go and you have to be the

best place where agents want to work

with that data. That's like the mandate

right now is if you are not the best

place that for that an agent would would

sort of intentionally choose for working

with data of that particular category or

automating the workflow in that

particular you know area. That's a tough

spot to be in and that that's the the

job for all of us. You know, if you're

building software

>> and the best place where Asians want to

work is defined by great API,

>> great APIs, great pricing models, um,

uh, you like the the surrounding

features to the API. So, if you were to

say, hey, I want to be able to wire up a

workflow where this is a, you know, the

box sales pitch. I want to be able to

wire up a workflow where an agent is

interacting with FINRA compliant

documents where you when you know FINRA

compliant document means the things gets

generated or seen or shared with the

customer and it it can't ever be deleted

and and removed you know for a certain

amount of time then then on one hand the

APIs have to be super clean for the

agent on the other hand you have to have

a bunch of surrounding capabilities to

ensure that that company can go to uh

you know uh go to their regulator or

auditor and say yeah we we are complying

with FINRA so that combination is what

makes it though you would build that

kind of agent on something like Box and

that that persists across a variety of

industries.

>> I'm going to do a quick fire around with

you. Uh you have to go and be a public

company CEO. I know. Um so what have you

changed your mind on in the last 12

months most significantly?

>> I do think that that I've I've become

more convinced that software is headless

in the past year than I was maybe three

years ago. And it's because of the the

level of agentic capabilities on tool

calling and searching across systems and

the accuracy of that. Uh and that that

has happened faster than I I would have

uh perceived. So two to three years ago,

if you were to kind of, you know, wire

up an agent and tell it, hey, go work

inside of Box and find a document to

work with and do some process, it would

it would basically almost always find

the wrong document and it wouldn't be

able to handle actually like cracking

open the file and reading through it.

And so thus, you know, going headless

wasn't sort of the the most urgent

priority uh from an agentic standpoint.

And in the past year, those capabilities

have just absolutely accelerated to the

point where I'm fully convinced that

that you just you have to be, you know,

headless first as a software platform.

>> What acquisition did you not make that

you wish you had made over the box

journey? Jensen said in the show, "Oh, I

wish we'd invest in Frontier Models."

That was my big mistake. What

acquisition did you not make that you

wish you had done?

>> I honestly don't uh I don't think I have

any M&A regrets. I actually the the the

the it's the deals that I wanted to do

that that we ended up not doing that I

don't regret um is probably more the the

situation. So

>> which one is which one is that?

>> I'm not going to tell you those. But but

there are some where left to my own

devices I would have done and I look

back and I'm like oh thank god that

there was uh there was more rational

logic in the process.

>> Who is going to win the enterprise race

open AI or anthropic? Oh god, that

that's impossible. Back to the cloud

piece, I think um you know I think it's

it's totally fair to think about it as a

race and certainly if if you're in

either of those companies, you have to

treat it like a race because because you

know like you obviously want 80% market

share, not 55% market share. So like you

have to treat this as a you know we got

to dominate. Uh that's exactly how they

should be executing that way. Everything

is going according to plan. if you

compare it to other areas of compute.

Um, and I I ran this analysis recently

in 2010.

2010, not like, you know, maybe you were

12, but like the rest of us, we were

just like in companies doing things. Uh,

in 2010, AWS made $500 million in

revenue. Azure had just launched and GP

and GCP was called Google App Engine and

it had a little like a turbine logo with

like wings or something. So that was the

state of cloud. Fast forward to this

year and it's a couple hundred billion

dollar a year revenue ecosystem, right?

So so in 15 years, right? So and we were

in that moment being like who's going to

win AWS or Azure or GCP? What's how's

this all going to play out? And it just

turns out the market was so large like

obviously it was due to their execution

that they kept it going and kept it

large and the competition kept up, but

it it just didn't really matter. Like

everybody everybody kind of won. And so

I I sort of think of AI in a similar

fashion, which is I I can't predict if

it's going to be open AI 60% and

entropic 40% or it gets flipped or I'm

off by another 10% here or there. Uh but

but no matter what, these markets are

just fantastically large. Companies are

are going to adopt multiple of these

systems. They don't want to be single

vendor. Uh they don't want to be they

don't want a single vendor in this

stack. One service goes down or one

changes it APIs or one has a new

commercial model. you're going to it's

going to be a multi- vendor multi-AI

world and so uh and so that that's why

it's like very hard to kind of like call

it at this stage.

>> What does everyone think they know about

enterprise adoption with AI that they

get totally wrong? uh what they think is

that is that uh that the the outcomes

that you're seeing in AI coding will

quickly come for other areas of

knowledge work and um and that is a uh a

slight misread on the other areas of

knowledge work and uh and and some of it

is the idiosyncrasies of of coding and

some of it is the broad you know kind of

just elements of the rest of work and

how it happens. If you were a venture

investor today, which category would you

be most excited to invest in? Obviously,

I'm just hypothetically

speaking.

>> I mean, I I think I would still be

probably loading up on all of uh all of

the the hyp uh the frontier rounds. Uh

it's like these numbers could could

continue to get much larger and um and

then I think that the

>> could they get I mean much larger. I

mean like this is where in my at 850

billion you've got like a 3x to like a

2.1 trillion style with dition for

>> you know I always think it's hard

because um I I I kind of have said that

on the way up of many companies like

like like no just like

>> I did it with crypto like how much

further can it go? It's like

>> yeah well well that one I'm going to put

in a different category cuz that's that

can just sort of be me'd. Um I I

>> actually No, but I actually think but

like I think to the point on Atlassian

and bluntly you and your whole category

is the casinoization of the stock

markets which is like if you're a

momentum trader today, you still buy

Palunteer because the market's a casino

right now.

>> Yeah. Well, to to be a little bit more

fair, um I think you have some one-off

companies that have done, you know,

amazing job capturing the zeitgeist on

that. I do think you have I I think I

think the broad story right now is the

sector rotation story which is which is

sort of hey this AI thing is happening

right now I can get a higher return if I

if I get closer to the semi stack and

the and and the kind of you know where

the workloads are going and where the

data center buildout is happening and I

get less of a return if if I'm in

software you know with with kind of pure

licensing and so I think that that is

probably more of the color of of what

we're seeing now some of the some of the

data center and infra, you know, names

maybe have been nemified also. And so

that's kind of helping the case. Um, but

it's just a it's just a really weird

time, you know, overall. Uh, that

that's, you know, hard to hard to think

through.

>> So, you would not buy Allirds as an AI

company.

>> I mean, maybe you would because of that

exact point. So, I think you'll have

that will be in the kind of one-off

category. So, New Bird AI or whatever it

it's called. Um, but but I think um, no,

I I am still I I hear this is a generic

statement. there will still be a lot of

money to be made in the companies that

can take the innovation that we're

seeing in Silicon Valley and in the labs

and apply it to the real world you know

work that happens inside of enterprises

and whether that looks like vertical AI

whether that looks like you know the new

kinds of tooling that that companies

will need um there's a you know company

and a new category emerging on on uh

like agent observability and evaluations

I'll give a shout out to Brain Trust as

an example not an investor um where I

can just kind of sit back and be like,

"Shit, like we thought that that agent

builders were going to need eval." So

that's like a Silicon Valley TAM. And

then I'm like, "Oh, actually everybody

on the entire planet if you're putting

agents into an enterprise workflow needs

evals because you need to know if all of

a sudden your agent just stopped

producing, you know, like like uh you

know, loan origination documents the

right way." And so I, you know, that's a

category where, you know, it's probably

not going to be owned by one of the

labs. You kind of want it to work across

all the labs. It's it's it's, you know,

it's a very relevant kind of new form of

of of infrastructure for an agentic

enterprise. I think you're going to see

a dozen, two dozen, five dozen of things

like that that that start to emerge.

>> I've known you for a while now and you

put up with me for multiple different

sessions. Uh, so I want to finish on

something a bit off script, but you're a

phenomenal CEO. You're a public company

CEO. The pressure that you have on you

is intense. You're also like married and

have a great relationship.

Biggest advice on marriage when it's

super I'm being serious. When it's super

stressful, it's hard and you also have

to show up and be a great husband.

What's the advice on marriage?

>> Uh it feels dangerous if I actually

acknowledge the great husband uh piece

and other other parts that were embedded

in that. Um that that feels like you

need like a full 360 eval. I I will uh

I'll just say from my perspective and

I'm very lucky to have an amazing wife

and and family and you know you you are

you're in a grind in one of these roles

and um and so obviously having a a

strong support base um uh you know helps

a ton. Um we try and make time you know

for for the fun you know side of of life

uh as much as possible but uh obviously

that gets constrained in in the kind of

window that we're in. But I've been with

my wife for I don't know 15 years or so

uh 16 years and so she's seen the whole

the whole grind uh all the way and uh

she has her own set of grind uh in her

business and so it's it's just lots of

fun. So

>> dude, you're my hero. I want to be you

when I grow up. Thank you for being so

great. I really appreciate and I was 14

in 2010. Okay. All right. All right. So

I almost called it Yeah.