The one thing I think that's going to be

truly future proof is judgment. Why?

Because you have the big challenge of AI

slop. Every product leader I've talked

to is extremely worried that because you

have these engines running rampant,

they're just going to produce lots of

code. In an era when you can do

everything, the question is which of

these things matter and you should truly

do.

I thought an interesting place to start

would be the changing nature of how

people are building products. The

biggest story by far in technology seems

to be cla or claude co-work as well. The

ease with which both technical and

non-technical people are able to build

something that they can imagine. It

seems to have been just a complete

explosion in their ability to do so.

You've built a million things. You've

invested in 700 companies watching

people build things. You're about as

prolific as they come as a product

person. Maybe just give us your sort of

state of the union of how the world

feels to you in terms of technologists

building products and how fast that's

changing.

>> What was interesting about product

development is uh that 10 years ago or

even 5 years ago there were very clearly

defined roles. Product managers

articulated what to build, designers

designed it and engineers built it. Over

the last few weeks, over the last few

months, I've been talking to many

companies, but over the last two months

in particular, December and January,

December 25 and Jan 26, it's become very

clear that something has fundamentally

changed. And what that thing is is the

notion of a long horizon, a longunning

agent. I've experienced it myself about

6 months ago. I tried to use clot code

in the early days to build something. I

call it a video transcription tool. So,

I tried to build it. It kept failing and

then I had to go in and try to debug it.

Ultimately, I gave up. Two weeks ago,

while watching some episode of some TV

show, in one hour I was able to

basically prompt my way to a good video

transcription tool because these agents

now are resilient to failure. You and

you don't have to be very technical to

use them. This changes the expectation

of product teams. After I did that, I

started talking to three kinds of

companies. One, portfolio companies,

portfolio CEOs of companies I've

invested in. Second, the large AI labs.

and third a bunch of AI native young

companies to see what the similarities

are between them. So there are few a few

things that emerge. First product

development as we know it is changing

because the models and the capabilities

are growing so fast that if you try to

be very u strict and stringent about

exact describing exactly what you're

going to build or prescribing what

you're going to build it is going to not

work. So almost everybody has gone to a

bottoms up approach where it's not

driven by product management anymore.

Product managers the only thing they do

now is they articulate what the customer

needs are at the highest level and then

they are the guardian of the why. But

the actual product is built bottoms up

by engineers, researchers and product

managers and designers all working

together on the code itself. So

capabilities and models are changing

very fast. If whatever you think of 6

months ago, if you continue thinking on

that dimension, you have fallen behind.

So it's very very important for the

product managers to be understanding of

what these models are capable of and to

be hands-on. So they sit with the

engineers and the researchers and write

code, do prototypes, do anything and

everything it needs in a hands-on way.

So the first thing we are seeing now

happen is that PMs are starting to check

in code with either codec cloud code or

whatever into the actual production

repository. uh right now engineers have

to review the code but you're going to

soon see that clot codeex and other

tools actually review the code itself

before engineers commit all the

companies are struggling with how to

evaluate these people earlier there

there was nothing called the prototyping

interview now there's explicit interview

in the interview loop called prototyping

literally forces product managers to be

hands-on second the product manager and

designer role are merging increasingly

so the designer role is an interesting

role in particular a lot companies are

going through headcount allocation this

year and I'm hearing from many teams

that when given the choice between an

extra designer and extra engineer

they're saying you know what the design

systems are already laid out now that we

have the design system already laid out

we can use AI to do work around these

design systems so we need maybe a small

number of designers at the company level

to manage the design systems and the

design language but AI can leverage the

design language to do designs so please

give us an extra engineer so the number

of designers and product managers number

of engineers when I is growing up in

product. It used to be 1 to 3 or 1 to

10. It's going to 1 to 20 now. And then

I think the other very very important

thing that's happened which is

fundamentally different is when I was

growing up products were deterministic.

There was a workflow you knew if X

happened and a user did X Y happened. It

was very clear when you did X Y

happened. Today you could do X Y

happens. But if you do slight variation

of X completely something completely

different happens. Non-deterministic

software. What that means is you have to

be on the other side an evaluation or

what is called evals in AI and someone

has to evaluate whether or not what the

software is producing is reasonable or

not across various use cases. Obviously

they can be human evals, AI evals etc.

But who owns the evals? It's the PMs.

It's the PMs and the researchers. So the

PM's job is to be very clear at a high

level about what the user needs are and

then have a very clear sense of whether

this product is good to ship or not by

evaluating it. So you've got to actually

to evaluate it many times you got to

write AI yourself to evaluate the

results of AI because humans can't. So

PMs are very good at coming up with

evaluation techniques. So it's the

non-determinism of software the speed of

which things are going and overall the

notion that these things are just the

capability frontier is being pushed out

every two months makes it an incredibly

challenging yet incredibly exciting time

of product developer. If you think about

uh my friend Zach has this great way of

thinking about AI which is we had the

industrial revolution for goods and that

basically this kicks off an industrial

revolution for services. This is an

interesting opportunity to ask about

what your philosophy of product is. Um

you're such a product ccentric person

and builder that's that we that's what

you've done that's what you've invested

in. As we face down this like industrial

revolution for services

what what is your like broadest possible

philosophy of product as we enter this

era?

>> Very simple. A product person or product

manager if you call them their job is to

balance customer needs and business

needs. The product manager there has to

be somebody at the company who's the

keeper of the why. Why are we building

it? What customer need are we solving?

Why is this a pain point? How intense is

it? How deep it is? And second, how does

this add value to the company? If you

build this thing, solving this customer

need, how does value add to the company?

And I think balancing those two is a

very delicate act. You can build

something amazing that adds a tremendous

amount of value to the customer but

doesn't build any value to the business.

And you can do something that is awesome

for the business by raising prices but

is value detracting for the customer. So

balancing customer needs and business

needs at the highest level is what I

think of the product. And what it comes

down to in my opinion over the last 10

or 15 years I've really gone down to

this notion of outcomes. Outcomes I

think are what define the best product

people and outcomes have to be defined

in the form of customer behavior. I

strongly believe that the be because

customer behaviors are leading

indicators for every business outcomes.

If you think about it, the simplest

thing that a product does is to make

somebody go from not a customer state to

becoming a customer state and from

becoming a customer state to becoming a

loyal customer and then maybe to

becoming a loyal customer to become a

paying customer. So there are all these

different product states or if you do a

poor job they can go from becoming a

loyal customer to becoming a churned

customer. So these are all behaviors.

Everything you do or build should be

attuned to the goal of what customer

state change does it lead to? What

customer behavior change does it lead

to? So I tell every CEO I meet that is

trying to hire their first PM or doing

their first product review, you need to

ask why. The only question you need to

ask is why. Why are you launching this

feature? And you should not let any

feature go out if there's not a clear

hypothesis behind this feature. And the

hypothesis has to be articulated in the

form of a customer behavior change. We

we believe that by launching this thing

the customers will go from doing X to

doing Y or from spending X minutes a

month doing this to Y minutes a month

doing this. You have to have a

hypothesis which is grounded in some

data or some something you know about

the customer, some secret about the

customer. You mentioned at the start the

difference between the video

transcription tool six months ago versus

you know more recently and how quickly

that changed. It's just such a hard

future to uh reason about given the pace

of change. So how do you reason about

it? Like is there anything that can be

truly futurep proof?

>> Yes. The one thing I think that's going

to be truly future proof is judgment.

Why? Because what is the biggest

challenge you have when you have

thousand AI engineers writing code? You

have the big challenge of AI slop. Every

product leader I've talked to is

extremely worried that because you have

these engines running rampant, they're

just going to produce lots of code.

Which of this code is even valuable?

Which of these are even valuable? When

in an era when you can do everything,

the question is which of these things

matter and you should truly do on the

product side is judgment around what

needs to be built and evaluating the

output. on the engineer side is

evaluating the code because if you don't

understand what the code says I think

you can have engineers writing AI

engineers writing beautiful code that

could be wrong that could have bugs in

it that could be vulnerable someone

needs to review it and make sure you

have to have human review at some point

especially a critical code that is in

the core of your system and similarly in

design you have to have judgment around

does this make sense does it make sense

in the broader design system so I think

judgment is the number one thing that

humans are going to bring in an era of

infinite productivity. The question is

what are the things to be productive on

and are we building the right things?

>> As you evaluate companies today, build

things yourself and just think about

this problem and the trajectory of these

tools. Maybe walk through how someone

should think about building an AI

application like if if there's so many

people excited about it feels like a

gold rush with this new technology. so

many things that we can do that we

couldn't do before or things that people

specific people couldn't do because they

weren't technical that they can now do

how should people think about attacking

building something new an application

using AI starting today

>> first and foremost it has to be a deep

and compelling problem the good news is

there's a tremendous number of deep and

compelling problems today in every

vertical in every industry why because

till today till recently software was

used more as a tool by people by humans

we finally have software that is agentic

in nature which means it can do the job

of people. So the the question you have

to ask is where are what industry are

there roles of people that are highly

paid that are doing somewhat of a

repetitive job and that can be done by

software. Every 3 months the answer gets

deeper and deeper. You couldn't have

told me that a designer's job could be

automated by AI like 6 months or 9

months ago. You couldn't have told me

that an architect's job could be

automated by AI. a lawyer's job could

you auto? It turns out increasingly in

every vertical these capabilities are

getting better and better. So you want

to start with first and foremost what

industry do you want to be in and what

kind of job do you want to do. Second

you want to target a high value

workflow. You want to target a workflow

uh a way of working that is deep that is

complex and that is u that is basically

uh that that requires custom data. I met

with the CIO of a fortune 500 company a

few weeks ago. I think one of the

challenges with this with this whole

space is that the models are becoming so

good that if you try to build a company

that is light that is not a hard problem

the foundation model companies are going

to eat you. So this CIO that I met at

this company said I I was asking him

over a few startups I had invested in

and worked with. He said look I don't

know why I would use any of these

startups. Gemini has an agent builder

product and I also use Chad GDP

enterprise and they also have an agent

builder product and I have a thousand IT

engineers who work for me.

>> They all want to be retrained as AI

engineers.

>> So I'm just going to put them using

these horizontal tools to build my AI

agents. Why do you need any startups?

And so that's the kind of thing you're

going to face that if the CIO of a

company of your target customer can

build what you're building these agent

building tools, you're not going to be

successful. So you've got to really go

one step ahead of what can be built a

multiple steps ahead and you got to

extrapolate to where can the

capabilities of these agent building

products go and you got to do something

very very different. So what that means

is you've got to have an you got to have

durability because ultimately as venture

capitalists are or even as an

entrepreneur your time horizon can't be

building something that lasts for one

year and that's the biggest challenge.

It's not building an application. It's

building an application that's durable

that basically will last a test of time.

And I think there are a few things

around durability. One, you need to have

ownership of a scarce asset. Uh a scarce

asset could be it could be a license of

some kind. It could be a a regulation of

some kind where you have unique insight

into it. Second, you might need to you

might basically own a control point. A

control point is a thing that controls

how people interact with money or with

data. So if you you want to own that.

Third, you want to maybe have hardware

which is hard to replace. Fourth, maybe

you want to be part of an essential

workflow. Fifth, you want to have

network effects. You want to think about

those things and figure out how after

you take on that workflow, you can make

it more durable. And finally, I think

your ambition has to be to replace the

entire system. In other words,

increasingly what is going to happen and

I'm seeing this more and more is every

vertical has either a legacy or somewhat

new what is called a system of record

which is a system where most of the data

is stored for that system. For example,

in legal there's a company called

Filevine or another company called Cleo.

There's a few of these companies in

sales at Salesforce. In in healthcare

it's Epic. Now for many years these

companies all had APIs that if you enter

that industry you could build an agent

company on top of these APIs.

In 2025 things changed. These companies

started seeing that these agent

companies, AI companies that are being

built, they are starting to take on the

functionality out of these companies and

are treating them like a dumb database.

So you started seeing last year that

these companies are cutting off access

to APIs. Slack has done it most

publicly. Slack is owned by Salesforce.

They cut off access to Glean where Glean

can no longer access Slack data. And the

reason is they don't want Glean to build

on top of them and then slowly suck out

the value that Slack has. And I'm

hearing from other verticals that

they're doing one of three things.

They're blocking access to APIs. They're

offering their own agents for free

bundled or they're charging these AI

agent companies to access the data. Let

just to access data. The API was free.

They're saying now it's like $2 an API

call or something like that. So they're

basically making they're trying to make

the model of these agent companies

unviable. I think it's going to be very

hard for a end customer to use multiple

companies where you have a system of

record and then you have this agent that

sometimes doesn't work with it properly.

So the agent companies have no option

but to also start building and offering

a system of record. So every company I

know is now trying to figure out how do

I build the entire platform and not just

a system that does some workflows. I

think last year everyone was like, "Oh,

we can do workflows. We can build what

is called the system of action uh and

live on top of the system of record." I

don't think that's an option anymore.

>> The Slack example is a good one of uh a

sort of last generation software company

which was very big and very successful.

One of the most interesting investor

questions and I'm curious for your

answer from the perspective of a builder

and a technologist is that uh the degree

to which these horizontal model

companies are going to destroy or be

very bad for old software companies

because over time it will be trivial to

spin up your own Slack that has features

that you want for your company and it's

very reliable in all the same ways that

Slack is and therefore Slack's in a lot

of trouble. How do you think about that

question of like obviously public

markets seem to think software is in a

lot of trouble. The multiples are really

really low. How much would you be

worried if you ran like a good solid but

older software company today?

>> There are two or three kinds of software

companies. I think the the software

companies that are should be the most

worried right now is where they are

pricing the product based on utility.

Zenesk is a good example where literally

Zenesk prices seats and each seat comes

with utility. In other words, each seat

corresponds to a customer service agent

that tax certain number of customer

tickets. So that company should be

worried. Why? Because I can have an AI

agent sit right next to Zenesk and you

can slowly siphon off. You can use

instead of paying for 50 Zenesk seats,

you can pay for 20 and I can have 30 AI

agents sitting next to Zenesk and that

siphoning can hap happen over time. You

don't have to have a all-in-one

decision. It can be a two-way door

decision. Those are the most endangered

companies in my opinion. You need to

change your pricing model to be based on

outcome and you need to actually build

the product to be based on outcome. It's

easier said than done because literally

you're going from a 20 or $30 per seat

to maybe charging a buck or 50 cents or

20 cents per ticket result and you don't

know how that's going to turn out. So

you've got to change your pricing model

and I think that's a very challenging

thing. That's why I think many of them

probably need to go private because they

have to make this business model

transformation in private. I think it's

going to be hard for them to stay

public. The companies that are less

exposed are ones where the utility is

not based on seats but it's based on

data that has been collected and

captured over a period of time and the

the more uh timeless the data is the

more protected they are. Slack for

example I would say might be in a little

bit more precarious state because the

data in Slack is half time halfife is

very short that's a great way of putting

it but if you have ERP is a great

example somebody uses Netswuite as a ERP

now I don't know if how Netswuite

actually charges but it doesn't matter

however many seats you buy the reality

is it runs your whole business and there

is no compelling reason for someone to

put their career at stake by ripping out

Netswuite I know there's a lot of now

over the last year there's been a lot of

AI enabled ERP businesses but there's

There's no compelling reason to take

Netswuite and say I'm going to rip it

out because it is career limiting to

suddenly take Netswuite out when you're

a company running on Netswuite. So I

think those companies are much more

insulated and I think obviously and you

could argue that Netswuite has more time

to build AI agents on top of it because

they have the data they have data and

they can train the AI agent on top of it

and bundle it. So you could essentially

I think the software public markets are

not distinguished between these two

types of companies. Companies where the

half level data is low and where you can

actually have you can literally take

half of the value of this company and

put it onto an AI company that sits next

to it. Well something like an ERP system

or even Salesforce for sales data and

records those are real customer records.

It's going to be hard. So what are AI

native companies doing? The first thing

you've got to do if you ever have to

compete against them is you got to spend

a year or two first building a system

that literally takes migrates your

Salesforce instance to your own

company's platform. One of the one of my

companies is Na native company. They

literally hired engineers in a European

Eastern European country for 2 years to

build this migration thing transition

tool. So you have to build the migration

tool because

>> who's going to migrate it? you can just

present your spanking new system but

this data is still there even for square

for a small business I remember they had

a point of sale they wouldn't they

wouldn't move to us even though it was

cheaper because they had gift cards

customer data loyalty data payments data

all of that you know even credit cards

so we had to build scripts and and that

took us months or years to build it for

a simple POS for something like

Salesforce you can't just say well here

I am I'm a great I'm a much better CRM

because I connect there is this thesis

which I completely agree with that if

you look at CRM what does a CRM contain?

It contains your customer record. Your

customer support system contains what

your customers are complaining about and

Jira or Atlacian contains what your

product development team is building.

Now all of these things should be linked

right because there is no linkage. You

you should be building the biggest you

should be addressing the biggest

complaints of your customers which are

in Zenesk and you should those Zen

customers you should know where they

came from who bought them who sold them

what the AM is. So all these three c

three systems should be linked together

but they're all three different

companies. So they're companies that are

trying to unify these things and it's a

great value prop but guess what none of

your customers is ever going to move

unless you build a simple seamless way

to take the Salesforce data and move it

to your instance. the data from GM move

to your instance the Zender data move to

your instance. So literally it's a

two-year effort to build migration

otherwise you've got to get Accenture.

>> How do you think about um stickiness in

this era just as a general concept when

the friction for creators to build

something net new is so easy is so low

you can do whatever you want really

fast. How do you how's anyone going to

use anything for a long period of time?

>> The age of AI stickiness I think comes

from a few sources. I think you need to

have network effects. So Door Dash is

sticky not just because it has this

beautiful app, but it's because it's a

network of restaurants and dashers and

consumers. So you can't just attack one,

you've got to go,

>> you can't vibe code your way to those

two.

>> Exactly. And so network effects. Uh

second u second example of stickiness is

when you have financial or money moving

through you. I think that's another way

to be sticky. I think uh many of the

system of records I think like for

example toast have payments going

through them and I think that really is

interesting because you can't just start

building the point of sale you also have

to have money flowing through it and I

think uh if you look at the banks banks

are a good example a business bank once

you have something like mercury as a

business bank it is hard you have money

flowing through it is hard to then

switch because you have regulations

other stuff embedded so I like things

that are combination of financial

services and software because of That

the third stickiness is from hardware.

You can actually have hardware. Toast is

a good example where toast gives you

hardware for free but if you try to give

return the hardware you have to pay

them. But either case the hardware is

there and somebody can't just build

software. They also have to take

hardware and put it into the thing and

rip out the toast hardware. The fourth

one is uh access to a uh unique asset.

Uh, and I I was thinking about a good

example and I came up with the example

of Sierra, which I think the unique

asset is Brett Taylor. I mean, they have

full control of Brett, who's one of the

best salespeople, chairman of Open AI.

He can make a call to any company, any

country, and they'll take his call. You

can't really outsell Brett. And so, I

think there's alpha in that. And so, I

think there are, you need one of these

four or five things which are basically

indicators of durability. The halflife

of software today is so short that

unless you're one of these things that

make it durable. Harrison Helmer has

this thing called uh seven powers. And

so you got to have a few of those seven

powers that that basically are embedded

in the business model from day one.

>> You you've been so lucky to work for

some of the most well-known CEOs and

founders of this sort of modern era. I'd

love the chance to ask you a little bit

about each of them and what you learned

from them and then more generally just

things you've learned about what great

leaders do to run companies. Maybe going

back all the way back to Google and

starting with Larry, Larry and Sergey,

what what did you learn from watching

them operate and lead?

>> Yeah. One of the most interesting things

about all the leaders that I've worked

with which I think have built

generational companies is that they have

a superpower that is very aligned with

what the company needs to succeed. And

the company was really shaped in their

image. the company, the culture, the

early hires, the products. When I joined

Google, I joined Google in 2003 January.

The first product I got exposed to

actually which I didn't know about was a

product called Caribou. Caribou was an

internal code name for a product that

was launched on April 1st, 2003.

Publicly, it was called Gmail.

>> I I I didn't believe that this product

existed because in the internal alpha,

it said this gives you 1 GBTE of

storage. Back then, remember, Yahoo mail

was the dominant product and it gave 10

megabytes of storage. So this thing had

100x more storage and this really

epitomizes Larry and Sergey's philosophy

which was basically built the best

technology on the planet. They were

deeply technical and every product was

held to technology and scale and I'll

never forget AdSense was the fastest

growing product in Google history and we

went in to reviews and Larry would be

disappointed in us and we asked why.

It's like what percentage of all ads on

the internet are you be like like less

than 1%. His goal was not to again he

didn't care about the revenue. He cared

that Google is involved in serving every

single ad on the planet versus like

making a making a business of like

whatever billion or two billion or 10

billion. So the focus on scale and the

focus on technological superiority and

that investment Google Street View I

mean and and basically TPUs

uh Whimo all of these I think show the

10 plus years of investment to an

uncertain future but knowing that if you

invest in technology good things are

going to happen and good things happen

but it took a decade and that's

investing in technology capabilities.

Before we leave Google, um you had this

interesting idea about communication and

Eric Schmidt obviously another key

Google person. Can you talk tell the

story about him presenting the company

strategy using nothing but images and

just like a this is like an interesting

example of communication?

>> Yeah, Eric Eric was a I mean I think one

of the interesting things I've seen is

that the other interesting thing I've

seen is that almost every great founder

or founding team needs an Eric needs an

Eric figure. If you look at it, Mark

Zuckerberg had Cheryl Sandberg, Jack

Dorsey at Keith Reoa and Tony at Door

Dash, we had Christopher Payne. So,

everyone had somebody who was

complimentary to them and really helped

uh you know they they're amazing at say

technology and scale. Eric was amazing

at bringing a team together leading and

I think Larry and Sea learned a lot from

it and Larry of course became CEO after

Eric stepped down but Eric was

incredible. So uh Eric would give a

product leader. We would become

secundered to Eric for uh the weekly

strate or the annual strategy planning

session. So I did it I think in 2007

where my job was to go to Eric and say

Eric how do you want to present the

strategy of the company? He's like well

it's very simple. I want you to go and

interview each of the folks each of the

different leaders of uh the different

teams. There's only one constraint I

have. I'm like what is that? You can't

use any words to describe what they're

doing.

>> I'm like what do you mean you have to

use words? Nope. you've got to use only

images. I'm like, why is that? He's

like, people don't remember words. They

remember how things made them feel. And

you can put words in the speaker notes

I'll use, but I want you to come up with

the most compelling image that that

exists for what they're describing to

describe. And so it was a crazy thing

because I never thought of doing a

presentation that way. And uh so I went

to you know each each of the businesses

adwords, search, YouTube, AdSense and

then had to come up with a compelling

image that was easily accessible to the

whole company yet represented what they

did.

>> Do you remember like a specific image

like an I'm so interested by this

exercise. It seems like potentially

productive for anyone to try to jam what

they're trying to say into only images.

And so I'm trying to pin down like an

image and how you how you arrived at it

or

>> I think for YouTube it was a graph. It

showed the graph the number of videos

that being uploaded every second how it

had changed from the time Google brought

them to them. So it was not even a

graph. It was literally showing this

incredible hockey stick that happened

over the last 18 months and then it it

had I think we couldn't even show the

numbers. So the the thing had to be

compelling enough that it could just the

line would have to be like a U or

something like that when it went like

that because we just show it like this.

you have to say something 100x or

something where you couldn't say that.

So, so we had to show that was the one

thing we wanted to show that Google

search has gone from being used by small

and midsize companies to being used by

the largest companies in the planet. We

showed the logo of um of I think they

had a very large Fortune or Fortune50

company that they had acquired.

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>> What did you learn from Zuck?

>> Zuck was u and is actually I think the

greatest mind on growing building growth

and engagement in consu building

consumer products broadly. I've seen him

basically sit in a room and critique

some a product team would have come in

with a very wellthoughtout

product uh consumer product flow and he

would look at the flows and he'd say

that is not going to be compelling to

users that is not something that a user

is going to engage to change it to this

and you say my god why didn't I see that

before so he's very very good at

thinking about how consumer product

should be designed to maximize

engagement and maximize just growth both

is probably the best way to put it. The

second thing he's amazing at is learning

by following. When I joined, I was uh my

task was to lead the ads product team

and Zach at that point knew a little bit

about ads uh because he had worked with

Cheryl quite closely. Cheryl had worked

on ads before. But then within I think

about a year he shadowed us. He came to

the ads team. He basically sat with us.

He came to many of our meetings and

within a year he got to the point where

he was generating ideas for the ads

team. One of the most foundational ideas

of Facebook ads came from what is called

custom audiences. Custom audiences is

the foundation of most ad systems now is

the is the idea that you as an

advertiser you want to reach people who

are similar to your customers. So if

you're a bank and you have say 100,000

customers, how can you give this set of

customers to your ad platform and say

look instead of describing these

customers right what do what did before

they would describe their customers I

think they are 25 to 34 year old women

that's too that's not good enough

instead if you can just tell us who your

customers are and we can map it to our

users we can then find people similar to

them so uploading that data into our

system securely early and doing it in a

way that doesn't compromise an EPI was

was the key thing and it all came from

Zuck. How? Because Mark Pinkers was the

CEO of Zinga. Zinga was the largest

advertiser on Facebook. Zinga basically

wanted to like most gaming companies

they were very focused on acquiring

Wales.

>> Uh because Wales for any gaming company,

casino etc. 80% of all probably all the

betting companies 80% of all revenue for

any gaming company comes from Wales. So

he was very frustrated at us. We would

do uh these quarterly reviews with Zingo

on the ad side because they were large

spenders on ads and they would

constantly be yelling at us saying we

want to get more whales. We were like

yeah you're getting users and you it's

your idea you need to figure out how to

get whales from your games. What do you

want us to do? We can help you acquire

users. So he once I think talked to Zuck

and Zuck came to us and said why can't

they just upload their whales into our

system? We know who the whales are. Why

can't we just find them people similar

to those whales? We were like that's

interesting but we actually didn't know

who the whales were. So they needed to

tag it for us who the whales were and

and basically we started doing it

similarly. We started finding users

similar to the whales that they had and

it worked so well. Then we said why

don't we take this approach and use it

for other types of customers who we

didn't have data on and it became truly

it was a transformative thing for ads

and it was all it was all Zuck's idea.

He just has something about connect

making connections between disparate

domains which is uh pretty pretty

amazing and unique. Jack is the I mean

he's I think on par with Johnny Iv and

Steve Jobs as in terms of his thinking

with design. I understood what good

design means. Good design doesn't mean

visually pleasing. It means a a product

that is designed so well that you don't

have to give your customers a manual on

how to use it. They should be able to

see the product and use it. Think about

your point of sale. Every point of sale

except Square and things that have

copied Square, you have to train a

barista still for several days after

they join on how to use the point of

sale. Square is something you can

download from the app store and start

using it as a point of sale to run your

business. A category where you have to

you have to you have to train somebody

for weeks. That's the example of a of a

good design. He brought that to every

part of the company and removing

friction from what is traditionally I

mean Square's whole premise was removing

friction from small businesses applying

for financial services and that extended

to the product that also extended to

risk. One of the most interesting things

that I didn't realize is that Square at

its core is a risk company. when you

apply to a bank for payment processing.

In fact, the company was founded because

Jack's co-founder Jim was rejected many

many times to accept AMX uh by by banks.

He was a fairly successful glass blower

in St. Louis and uh he basically was

selling two $3,000 glass sculptures to

people who would send him checks. So, a

woman called from Panama one day and

said, "I want to buy this on his

website." He had this beautiful piece of

glass. He said, "Great." They agreed on

the price and she said, "I can you take

my credit card number?" So he said, "I

don't accept credit cards." So she said,

"Sorry, I can't send you your travelers

check or check or whatever the case is."

So he lost the sale. And so he went to

his friend Jack Dorsey. They had never

built hardware. They had never done any

of that stuff, but they brainstormed and

realized that the phone, the iPhone,

which had just been released a couple of

years ago, had this thing called the

audio jack that basically could be used

to uh put a piece of hardware in and

process cards. I I can't even imagine

the leaps you have to make to get there.

But the number one thing that they

realized is people most of most small

business are denied by banks when they

apply. Square instead said we are going

to accept 95% and but what they did was

they put risk at the transaction level.

So they accepted you as a person as a

business but then once you started

processing transactions they would then

run machine learning models and every

transaction this transaction risky this

is not. shifted the level

>> shifted the level and so that kind of

lazy but brilliant onboarding is

something that characterizes a lot of

good thinkers Sergey very similar I've

come up with this conclusion when we're

going to launch AdSense in 2003 I I'll

never forget this 2003 May was when we

were doing our final launch things

Sergey was our sponsor he came and sat

in the meetings he said what are you

guys building here we're like oh you

know website publishers are going to

apply from all across the world it's a

self-s serve product we have to review

them we have to review them and say we

should approve them not approve approve

them to run AdSense. He's like, why do

you need to approve them? We were like,

what do you mean? Our ads are going to

we are going to be running ads on on

these things. Google ads or ads powered

by Google. You don't want to be on a

porn site or something else. He's like,

why not? We didn't really have good

answer to why not. I was like, well, you

know, standards or like policies. Okay,

but what if they lie? He was right. What

if they lie? Like I could We had so many

people applying with Nike.com, for

example. It's true. It was very hard to

know who owns a domain, right? I could

apply with with your domain uh and

basically, you know, get accepted. He

was right in some ways. We were just

doing it to cover our asses, turns out.

And so he said, "Okill all this." So we

had literally spent half of our

engineering team building this complex

approval system with ops and so on. Ops

are super excited. They hired a lot of

people and now you're telling us not to

do and instead do it in real time for

every page that loads because we had the

JavaScript on it. We know what URL it

is. Look at the content at that point.

>> And we were like it's too slow. We won't

be able to look at the content because

it's billions of pages. That's fine. Let

it load for 100 times and after 100

impressions if any URL hits 100

impressions then start reviewing it. not

trying to put lots of checks up front,

>> but being intentional about where and

why. Most things don't even get to the

level where you care about. So only do

stuff. The same thing happened with

click fraud. Click fraud was one of

these biggest challenges that we faced

and where people click on their own ads

and make money. How the hell do you

solve that? The reality is you don't.

You just wait and you start

understanding what click fraud is and

then you solve it. So be reactive and

solve it when it needs to be solved at

that point versus waiting. So the square

thing was exactly move risk from the

business level to a transaction level.

The same with AdSense. Move risk from

the publisher level or the you're

basically you cannot gate because

getting somebody to come to you and sign

up is one of the rarest things in

history. Someone is coming to you and

expressing an interest and you're saying

you're going to put 10 different

barriers. That's the opposite of self-s

serve.

>> So pure self-serve product would never

have any reviews of any kind. You're

going to be immediately activated. go on

and we'll do checks in real time based

on what you're doing versus banning you

or stopping you.

>> You me in both these amazing examples

and then you also said that Jack would

do this across the company, not just in

the product. How would you sum up the

process of great design that you've

observed from the people that are the

best at design? What is the what is the

thing they're the method that they're

going through over and over again as

they apply it to different parts of the

company or product?

>> The number one thing I've seen is they

try to minimize the number of steps.

Everything should be in one page and you

need to cut down things. In fact, Jack

called the product manager role product

editor. Why? Because he believed rightly

so that the role of the product manager

is not to add more features. Any of us

can look at a product and say here's 10

things you should build. The best fe the

best designers, the best product people

edit down things. Similarly, we have 100

features. What are the two things that

really matter that will drive the

customer outcome? So the best designers

really take 10 pages of design and say

cut out all the experience. So I think

it's the process of editing and this

goes to judgment. I think this is in an

AI age humans with amazing judgment

which is really editorial capabilities

are the ones that are going to do well

and thrive.

>> Apparently uh Rick Rubin would say that

he wasn't a producer he was a reducer.

>> Great example reducer. I like that.

>> I wonder how that applies also to

communication. Um maybe this is a fun

opportunity to ask you about the format

that you've lighted on that a leader can

send to his team on a weekly basis. I

think it seems like this idea of

reducing and simplifying can be applied

in so many ways by great leaders. Talk

about it in terms of communication uh

from leadership to a team. One of the

things that people especially founders

of startups don't realize is initially

most startups start with two or three

people and then they go to people who

are all sitting in a room together.

Everyone can hear what you're saying.

But as soon as a company goes into I

think I call it two rooms where they're

not in the same room together. Then you

have to communicate. You have to you

have to let people know what's going on.

You have to bring everyone together. And

there are a few artifacts that companies

need to start putting into place. One is

a notion of an all hands where I think

an all hands it seems cliched but an all

hands is actually and it seems

unnecessary but even with a 15 20 person

company just getting together once a

week um maybe on a Friday or a Monday

depending or Thursday and and basically

just sharing what people have built have

been working on in a way and then having

the leader address uh everyone or one of

the leaders address everyone is a great

way to get people together. The second

thing is a weekly CEO email. And I think

this is a very powerful way for the CEO

to get across to the to the team what is

on their mind. The best way I think is

uh that I've done myself is during the

course of the week, you start jotting

down things that you think you want to

communicate and then you'd spend Sunday

or Saturday, whatever the case may or

taking all of those things and adding it

to two or three things that matter that

you want to get across. Most businesses

I think can be communicated along three

dimensions. Progress, product, business

and team. What's happening on the

product? How is it becoming more

remarkable or serving our customers

better? What's happening on the business

side? How are we doing better as a

business? And then what's happening on

the team front? Who have we added,

subtracted? What changes have we made?

And most importantly, don't be afraid of

repetition. Don't be afraid of

repetition because repeating it once,

twice, thrice, four times is what people

that's when people actually it seeps

into their bones. What is the literal

format that you do? So you've got three

in your email. What is the structure

that you do personally?

>> So the format I've used in the past and

what I recommend and what people I've

seen now I've seen at least 15 CEOs

adopt it and to good effect is three

sections. One is called top of mind. So

this is product, business and team. Like

what is top of mind on the product side,

on the business side, on the team side.

Doesn't need to be all three. What's top

of mind for you? What's keeping you up

at night? I think this is the thing that

literally everyone is hanging on to. I

mean because I remember seeing it from

from Jack, from Mark, from Cheryl. I I

think just seeing it put in paper or put

in an email is just so powerful. That's

one. The second thing is performance

update. I think everyone wants to truly

understand how's the company doing.

How's the company doing on the

dimensions, I think. And this is where

especially being a startup, I think most

people are one dimension removed from

how the company is doing. They all want

to know that they're doing well. And I

think this is the way. And the third is

miscellaneous is things like recognizing

specific people. It's quotes from

customers. It's maybe an off-site

announcement. But the most important

section where you should spend 60 or 70%

of your time on is top of mind.

>> How transparent should one be in that?

As a leader of a business, I could tell

you what's top of mind, but a lot of it

either might be sensitive or uh I would

worry about scaring people or worrying

people about something that I'm thinking

about or worrying about. like what keeps

me up at night might create stress in

the business. So like where where where

should one draw the line in terms of how

candid they are about

>> I personally think more candid is better

than less why but if you're more candid

what you can do is you can actually get

people you can actually ask people to

suggest ideas and that's the thing I

think you by by you just if you have

good talent at the company if you

actually ask them what do you think I

should do what do you think we should do

in this situation I think people will

rise up to the occasion especially when

the company is small we want people more

input and there's a oneway road decision

that we're going to make where making it

takes us one way or the other. I think

it'd be great to get um get get feedback

from more people.

>> I want to talk about ads and um

everything you've learned about building

like an incredible ads product. You

basically have built like the core

business the important core business

engine at multiple places at at the sort

of main character company across across

your career

>> as a company. You either die or you live

long enough to become an ads company.

And so we are seeing now with OpenAI

it's happening. Now how do you build an

ads business? There are three

fundamental ways to succeed in the ads

business. Three and only three. One, you

need to own a very coveted uh group of

users and you need to have a surface on

which those users with which those users

interact. Google search is a great

example. It's a surface on which a very

coveted set of users interact with. U

obviously they express high intent. So

Google is one of the most profitable ad

businesses. Facebook very similar. It

took us a while to figure out what was

coveted of both these users. Turns out

what was committed was the identity. We

knew who these users were and we could

match them to customer and other data

and so you could precisely target these

people with messages you wanted and you

could find people similar to them. Chat

GPT their combination of intent and

identity data is unparalleled. I mean

Google had intent data but not identity.

Facebook identity but not intent. These

things been both together. I mean it is

a it's the dream of any any advertising

person. I mean shoot I mean I don't know

how many searches they see but they

going to see they're going to see more.

And these are complex complex

multi-phase searches, right? That's the

other beautiful thing. You search or you

and each of the queries is kind of like

a search and then you search again and

you're just building up searches. At

Google, you typically search and then

you lose the person because they go off

and click and you don't hear. These are

like natural language queries ripe for

amazing amazing targeting. That's one

way of making money. But you have to own

a firstparty product. You have to be the

first party. Second, you have to drive

outcomes. That's another way of making

money where you don't own any inventory

but you can drive outcomes for

advertisers. The best example of this is

a company called Apploving. Apploving is

a 100 plus billion dollar company. They

drive one outcome really well, mobile

app installs. And no one believed that

people would need that many mobile app

installs. Turns out everyone wants to

get mobile app installs. It was

initiated only restricted to gaming. But

now every mobile app where they sold one

mobile app installed. So app loving has

built a massive infrastructure. Now they

control the buy side, they control the

sell side, they even control the

middleware. You could argue that they

kind of control the auction for most

mobile apps in a way that almost Google

used to control or people say they

control for the web. But apploving has

built an amazing engine to deliver

mobile app installs at a certain cost.

>> So that's the other way. Second way to

do it. You deliver an outcome at a

certain cost.

The third way to do it is if you are the

exclusive

provider for a large advertiser or a

large source of demand where you become

a good example is a company called the

trade desk where Proctor and Gamble for

example go to the trade desk and say I

spend with Google I spend with Facebook

all my other display budget trade desk

here you go you can figure out how to

distribute it and how to run it and so

those are the three ways but you got to

be exclusive so Those are the three ways

that you can make money.

>> What business ideas don't work in in

advertising? Like what are the business

models that just are doomed to fail?

>> Trying to be a middleman on top of these

large platforms from my understanding

work trade desk I know doesn't work on

Google or Facebook at all. Doesn't work

with Google or Facebook as a first

party, but applovin I think only little

bit works on Google and Facebook. Mostly

they do their stuff on the on the

unwashed web basically outside. So,

you've got to stay out of Google and

Facebook's ecosystems because if you're

trying to build your business on top of

Google and Facebook or probably soon

OpenAI uh as an ad company, you're going

to get squeezed over and you every time

you build a new capability on top of

Google, turns out Google learns what

you're building

>> and Google has the best engineers on the

planet. So do Facebook, they will take

your capabilities, incorporate into

their platform. There's going to be

almost certainly a cottage industry of

companies that are going to come and

say, "I'm going to help you optimize ads

and chat GPD." There's already companies

that help you optimize placement in what

is called these answer engines called

AEO instead of SEO. All of those are not

going to create durable enduring

companies.

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>> What would you be worried about if you

were one of these fairly monopolistic

owners of a massive ad network like the

ones we've discussed?

There Uber and Amazon in the mix, Door

Dash, Facebook, Google. If you were

there running their ads businesses, what

would scare you?

>> Consumer behavior change. Consumer

behavior change where they don't open up

the apps anymore, but they use agentic

interfaces. They use AI interfaces which

are not owned by my company, this

company to to do their transactions. If

you assume that a big percentage of

things are repeat, then could you put

those repeat things on autopilot through

an agent and you never open the app and

so you lose opportunities to then

advertise and so and you lose the

relation with the customer over time

because the customers start trusting the

AI agent. You can't bury your head in

the sand. You have to go and experiment.

That's why when Chad GPD opened up their

apps platform, all of the commerce

platforms are experimenting. And the

thing I would look for very carefully is

there are going to be early adopters

using the app. I'm going to look for

obviously they're going to connect their

account, their Uber account with the

chat GBD account. I'm going to look to

see these people who are connected.

How's their behavior on my app? Are they

going to my app or not?

>> Are they opening my app or not? Are they

opening my app much less frequently?

Because if that's the case, then

obviously this experience is so

compelling that I would then have an

choice to make. How do I make this

experience maybe not as compelling as my

app experience or how do I incentivize

them here to open up my app?

>> There's a new battle happening for that

first category which is a new interface

to be owned. We know chat GBT is sort of

does I'm curious if you think being the

first mover matters to build a new ad

network because there's there's Gemini,

there's Anthropic, there's a bunch of

people that have tons of users using

this new interface. How do you think

about the landscape of the new potential

entrance to build the next dominant uh

at network? What advice would you give

these various parties?

>> The good news is the being first doesn't

matter. Why? because you control

especially if you're in category one

which we described you control your

first party inventory in fact being

second or third you can learn from the

iterations and mistakes that the first

one makes your inventory is not going

anywhere now some might have more

urgency to monetize than others but

Gemini doesn't need to monetize anytime

soon so they can just sit back they have

a lot of ads expertise and data from

Google they can sit back and wait till

they need to monetize uh in fact a good

strategic move for them might be to say

I am I am the zero ad platform like

Apple claims or Google can claim that

Gemini has no ads in it and there is a

certain set of customers or consumers

who care about that. But the biggest

thing is I think and and OpenAI has done

a good job of articulating this ads

should not ads and content ads should

not influence the content that is served

to me or the recommendations that AI

gives to me. I think they should be they

should be relevant and but they should

not be um influencing the the

recommendations. And second, you have to

keep a high bar for engagement and

usefulness. Unfortunately, however

relevant ads are, the reality is that

this wasn't proven is that once you

start showing ads in an previously

unmonetized uh no zero ads uh surface,

engage engagement of users goes down

over time. It does because some of the

engagement gets siphoned off by ads and

some of it gets siphoned off in

different ways. But this many hold out

groups across many companies have proven

this. So the question for any one of

these companies is how much engagement

are we willing to take in exchange for

monetization. And so I think first you

need to have a hold out group. I'm sure

they're having it a hold out group of

people who never ever see any ads

because that's your fresh group that

never sees ads and you need to

understand that's their behavior. And

then you need to always understand how

uh how you know people with ads are

behaving and then you need to figure out

uh what the engagement hit is from each

quantum of ads and you need to then give

your ads team a certain engagement

budget and so that's what at at Facebook

there was an engagement budget every

year that between the newsfeed team and

the ads team we had to adhere to. In

other words, uh we yes we wanted this

much revenue but it the the check metric

on the revenue was we can't take more

than x% dip in engagement overall for

newsfeed.

>> What are the attributes of a good

northstar metric? Like what advice would

you give someone that's trying to pick

the thing around which the company is

going to optimize?

>> Yeah, the northstar metric is a is a

metric that is an indicator of company

growth and customer value. So it

actually balances customer value and

business value nicely. Nostra metrics in

my opinion should not be revenue. It

should be something that is directly

correlated with customer value. So for

example, if customers are doing well,

the Nostra metric should go up and to

the right, but it should also lead in

business the business doing well. For

example, for Square, the Nostar metric

was GPV, which is volume of payments

processed. It was not correlated to re

it was somewhat correlated to revenue,

but it most importantly showed that the

number of the amount of payment

processed to the company was continuing

to grow. At Facebook, the northstar

metric was DA us. It was actually

monthly active users. Then it over time

went to daily active users because it

was a sense it was an indication of how

engaged C users were. Now, one of the

most important things about an NSM is

that it needs to be coupled with what we

call check metrics. In other words,

NSTAR metrics if they're left alone can

as you know incentives drive behavior.

So if you tell a team go and optimize

this Nstra metric they will do what it

is going to go up 100%. But then many

things that you don't want to go down

could go down. So for example in in the

Door Dash case you could say I want to

grow GMV which is the gross

merchandising value which is the

Nordstar metric. Now GMV is the total

order of total value of all the orders

that go through the marketplace. I could

make it grow up by offering by setting

delivery fee to zero by setting

everything to zero and what happens

then? The company's revenue goes to

zero. So you basically want a check

metric that is maybe a check metric

around the health of the customer and a

check metric around the health of the

company that basically hold this that

are the guard rails around this Nstra

metric. So in the case of Door Dash it

might be I want to maintain a certain

gross margin percentage or I want to

maintain a certain customer retention

percentage something like that. Again it

might be margin is typically a good one

to use because in some ways that is a

indicator of the company health.

>> There's these two ideas that we talked

about when we first met. One was the

need the need for the very best software

companies to sort of stand alone in the

sense that someone can just go use it

without talking to a human and it just

it works for their problem. So like

fully fully self-s serve. Love to hear

you talk about that. And a related idea

was that's sort of on the builder side.

On the investor side, you mentioned to

me that all the great investments that

you've had, the companies that have

really had like explosive growth have

had a high number of one of four

qualities which is I think was gross

margins, low cost to acquire the

customer. um high retention and a tight

sales cycle which maybe match maps back

onto the self-s serve thing.

>> Yeah.

>> So talk about the relationship between

those two things.

>> The self-s serve notion actually came

from Google was Google was the first

company I worked at which achieved

massive scale and what happened at

Google was within the ads team. Uh we

basically had wide number of customers

using us the millions of customers using

us. There were a lot of small businesses

but there were also large companies.

what we ended up doing to serve the

large companies. Large companies didn't

want to use the product themselves. They

had uh agencies using it for them on

their behalf and they also had internal

people at Google support and sales and

operations people using them. So on the

product side we built a lot of tools for

this internal for our internal

colleagues for our sales and operations

colleagues to manage the system for our

large customers. One day I think we were

at a Larry review and we were showing

these what we called ICS internal

customer systems to Larry. I think we we

were not meaning to show it but I think

to show him a demo we somehow got into

it. He was like what is that? We're like

well it's a system used by our internal

teams. He's like why'd you build it? We

were like well we have to help our large

customers. He said I don't want you mean

our small customers don't have access to

it. We're like no end it right now. We

were like what do you mean end it? I

want to make sure that everything you're

building for large customers is also

available to small customers. And so we

basically had to take everything we had

built over years for in this IC system

and made it make it available to

customers. And turns out an interesting

thing happened. Turns out the smaller

customers adopted it much faster because

some of these things we're building had

advanced knobs and so on that we didn't

think they would use. Turns out the

self-s served customers were the most

sophisticated users because if you do

something that's interesting, there's

all these small agencies, entrepreneurs,

hustlers, all of these folks, they if

you can help them make more money, the

it's it's a testament to human

creativity and ability, they exploit the

system in ways that you never you never

even know and you learn a lot from

working with them. So I've seen in every

case when you open up your system to

selfs serve you learn so much more about

the capability of your product than if

you basically it's your sales team doing

it on their behalf. In fact, I'll never

forget in AdSense, I think we had some

of the largest publishers in the world

sign up and start using us on a self-s

served basis and then we engage with

them after that. And I think companies

like Atlacian, Square, I think we had

Nike, I think start signed up for a uh

for a for a Square uh device and and

sell some onboarded and start using in

one of their stores. We had I think

Whole Foods. So, I think it just changes

it does two things. One, it makes your

product better. It makes your product

better because these folks they use the

product in ways that you don't expect or

anticipate and it helps you it forces

you because what is the definition of

self-s serve? The definition of self-s

serve is the customer can onboard not

just use but onboard and use the product

without ever talking to or engaging with

a single member of the employee base at

the company. So when you do that that

means you have to think about how do

they actually get set up with the

product. So it really puts a lot of

effort on onboarding because onboarding

is one of those things where most people

drop off if you don't do a good job and

then you've got to get them to a moment

of delight very quickly. All of those

things a large if you're not building a

sales product you don't even think about

and a seller product you think about it

every day. It's like a consumer product

or sells a business product. And then

second what it does for you is it opens

up the aperture to your customers

because with say a 100 salespeople yeah

you can reach maybe 10,000 customers but

with a self-so product with the right

word of mouth you can reach millions of

customers look at cursor for example it

is used in every large company I bet

only maybe 1% of companies is maybe the

top down motion 99.9% of companies some

engineer got it great example is a

company is Figma actually after I

invested in Figma I joined square one

and a half years later I tried to

basically push Figma down top down into

the design team because learning design

I said you got to use Figma designers

refused to use it they're using a tool

called sketch and they said we're not

going to use it sketch is much better

and so I felt okay it's not my place to

tell them what tools to use so I backed

off two years later a mid-level design

manager came in and they brought in

Figma from their prior company and they

basically got got it to be used across

and it kicked out sketch so I think with

self-s serve you can get into these

things where even there's an incumbent

But you can infiltrate and be an

insurgent in a unique and powerful way

which a sales direct sales motion could

never have produced then.

>> One of the other dimensions that's

changing fast is careers. I'm curious

what you think about the sorts of people

that will thrive best in this new era.

If you're a person hiring someone, what

are the sorts of things that you would

place extra emphasis on now in the sort

of AI era?

>> The number one thing I think is going to

be the focus on doing and building. I

think CEOs have gotten too comfortable

over time and I think this is changing

hiring middle management very very

quickly and hiring sea level people

instead I think you're going to see the

rise of AI agents doing a lot of work

but then humans who manage the AI agents

and our IC's so I think what the number

one skill that is going to be relevant

two years from now probably even one

year from now is to become a functional

expert that knows how to build AI agents

to do that function and orchestrate an

army of AI agents to do that function.

Well, there was a great article the

other day I read about an PM at Meta

who's non-technical but who basically

built a bunch of AI agents to do his job

as a PM so well that even his engineers

like teach me how to use a AI agents

well. And so I think that's what you

want. You want somebody who is

essentially acting as a manager but not

of humans but of AI agents. And

management has to be a full-time job.

What I mean by that is if you manage

three, five, 10 people that's not

enough. You either need to be managing

50 humans or you need to be an IC. And

so there would there's something called

span of control which means how many

people you manage in some ways. And so

span of control less than 10 should not

be allowed at any company at this point.

I think everyone should have I think a

full-time because think about it if

you're managing even 15 people maybe you

meet with them once a week that's 15

hours. What are you doing for the other

25, 30, 40 hours?

>> You should be working. And on the

company side, don't hire managers as

long as possible. Hire doers. Hire

builders.

>> How do you what is your favorite way to

assess whether or not someone is is that

in interviewing them or learning about

them?

>> Best way is to give them a work project.

Engineering does a great job.

Engineering has always done a great job.

Every company I've been at, they would

have engineering coding interviews,

programming interviews.

>> Yeah. Do stuff. Everywhere else you can

just BS your way without doing stuff.

You can just talk and talk is not you

got to actually do stuff. Produce an art

artifact. So at square we established

work projects where even for corp dev I

remember corpdeev our our work project

was tell me about give me one company

that square should buy and analyze the

company and tell us why we should buy it

and tell us what the synergy should be.

So the best candidates had to do that.

So every every function needs to have a

work project that you need to put them

in a room without AI and get them to do

the project. Get them to do the work

that is ideally very similar to the work

they're going to do. I we would almost

give them for product managers we would

take a product we were thinking about

and we would just say here's a product

we're thinking about figure it out

should we build it. The first and most

important thing you want for these kind

of thing is especially for customer

facing roles they need to take the voice

of the customer. In other words, they

need to justify the why. The best PM

candidates rejected the premise

completely

>> and they did it in a beautiful way. They

went and talked to 10 customers on the

street. It's so brilliant. They said, "I

talked to 10 customers. I they were all

square users, which is so easy. Mint

plaza, you go there and we found that

none of them want a pre want this

premium insights product. So, we don't

build it. We're going to build this

other thing." And said it was amazing.

That's what you want to see. You want

agency. You don't want people to just

say, "Give me what to do and I'll do You

want people to reject the premise or

question the premise in the first place.

Square should not buy a company. That

would be great. Why? Tell me why. And so

that's the kind of thinking you're

looking for.

>> What was Tony's thing?

>> Tony's thing was he would give people

either $10 or $20 and ask them to

acquire a,000 customers. A,000 customers

for Door Dash consumers. And literally

some people would say, "I'm not going to

take this challenge. I'm not ready for

it or something." and great that if you

literally opt out of it and then some

people would take it and the goal nobody

even came close to acquiring a thousand

or even 100 I think but the goal was to

see how many different things they were

able to try in the course of few hours

someone went to the gym printed flyers

out and gave it out people tried all

kinds of things it it was a brilliant

way to just just filter out people who

didn't want to do stuff

>> is there any other advice that you would

give the person building the career we

talked about you know evaluating and and

uh be a builder and all these sorts of

things. How should one think about

managing a career in the AI era?

>> Stay at every job long enough to have

impact. I have over the last 18 24

months I've been seeing this phenomenon

of job hoppers or job optimizers I call

them who stay at a job for 12 to 18

months and then they move to the next

job and then they say 12 to 18 months

and move to the next job. I think that

that is one of the biggest red flags as

a hiring manager that I see because I

don't think you can achieve anything of

value. You can't have any impact on a

company in 12 to 18 months. I think it

takes minimum 3 to four years to have

impact on a company. So my top advice is

stay long enough to have an impact,

build a network, have fun. Don't from

the moment you start a job, don't be

thinking about what my next job is. once

in a while maybe one job it didn't work

out uh amongst a series of jobs okay you

left it 18 months but if I'm seeing two

or three jobs back to back immediate red

flag I posted this on X and tons of

managers wrote to me saying it's an

immediate red flag so you do a massive

disservice and you won't even know the

problem is you'll get rejected you won't

know what happened it's that people want

people who stick around and build who's

going to hire you if they see that's

your behavior so I think it's a very

shortserving or it's it's a very

short-term thinking you got to build

something of value and that comes with

time.

>> So much of the theme here has been uh

identifying a superpower, having one in

the first place, evaluating one,

matching it to a problem with a leader

and so on with your investor hat on and

your new firm marathon. How do you

assess the capacity or existence of a

superpower in a person? Like what what

how have you learned to do that? Well,

>> the most important thing I look for is

founder authenticity. If you think about

it, three of the four companies I worked

with, Google, Facebook and and Door

Dash, all started in school, all started

in colleges and they all started as a

way to just a toy problem almost that

that the founders are curious about and

they started with an authentic

curiosity. Can this be built and then it

became it got built and it started and

similarly with Jack and Jim, they

started solving a real problem. So my

first question to every founder is tell

me your founding story. Why did you

decide to start this company? And so the

founding story in my opinion is what a

lot of it expresses why they chose this

problem and ideally it should touch on

what the superpower is and what

compelled them to work on this problem.

I really I I've had many people work

with me or for me who have gone out to

start companies with the only reason

being well I have my buddy and we both

want to start a company together. I

really advise them not to do that

because just going out and starting a