0:00

This episode is brought to you by

0:02

TIGUS, the only investing research platform built

0:04

for the investor. With traditional research vendors,

0:06

the diligence process is slow, fragmented, and

0:09

expensive. That leaves investors competing

0:11

on how well they can aggregate data,

0:13

not on their unique ability to analyze

0:15

insights and make great investment decisions. TIGUS

0:17

offers an end-to-end platform with all the data you

0:19

need to get up to speed on a company

0:21

or a market. up to the

0:24

minute financials, customizable models, management and

0:26

culture checks, and of course our

0:28

vast and growing library of expert

0:30

call transcripts. Tegas is changing the

0:32

world of expert research. Learn more

0:34

and get your free trial at

0:36

tegas.com slash Patrick. You

0:39

may have heard me reference the idea of maniacs

0:41

on a mission and how much that idea excites

0:43

me. Well, David Senra is my

0:45

favorite maniac on one of my favorite missions

0:47

with his weekly crafting of the Founders Podcast.

0:50

Through studying the lives of legends, he

0:52

weaves together insights across history to distill

0:54

ideas that you can use in your

0:56

work. Founders reveals tried

0:59

and true tactics, battle-tested by the

1:01

world's icons, and has David's infectious

1:03

energy to accompany them. With

1:05

well over 300 episodes, your heroes are surely

1:07

in the lineup, and his recent

1:10

episode on Oprah is particularly great. Founders

1:12

is a movement that you don't want to miss.

1:14

It's part of the Colossus Network, and you can

1:16

find your way to David's great podcast in the

1:18

show notes. Hello

1:23

and welcome everyone. I'm Patrick O'Shaughnessy, and this

1:25

is Invest Like the Best. This

1:28

show is an open-ended exploration of markets,

1:30

ideas, stories, and strategies that will help

1:32

you better invest both your time and

1:34

your money. Invest Like the

1:36

Best is part of the Colossus family

1:38

of podcasts, and you can access all

1:41

our podcasts, including edited transcripts, show notes,

1:43

and other resources to keep learning at

1:45

joincolossus.com. Patrick

1:48

O'Shaughnessy is the CEO of Positive Some.

1:51

All opinions expressed by Patrick and podcast

1:53

guests are solely their own opinions and

1:56

do not reflect the opinion of Positive

1:58

Some. This podcast is for

2:00

informational purposes only and should not be

2:02

relied upon as a basis for investment

2:04

decisions. Clients of their

2:06

lifting may maintain position to the security

2:08

of the customer's interest. To

2:11

learn more visit psum.com. My

2:17

guest today is Dave Iticheria. Dave

2:20

is the CEO of MongoDB, the developer of

2:22

Data Platform with tens of thousands of customers

2:24

in a hundred different countries. He

2:26

joined the company as CEO in 2014, taking

2:28

it public in 2017 and now approaching

2:31

a decade of leading MongoDB to become

2:33

a go-to choice for the most sophisticated

2:35

organizations around the world. We discussed

2:37

Dave's philosophy for constructing an exceptional

2:39

enterprise sales organization, why he feels

2:41

a leader must be incredibly judgmental

2:43

to drive excellence, and how he

2:45

plans to guide MongoDB through another

2:47

technological transition. Please enjoy this

2:50

great conversation with Dave Iticheria. So

2:54

we were just talking about what

2:56

it's like to live through

2:58

technology transitions. And often,

3:02

I talk about this with investors from

3:04

the perspective of what opportunities

3:06

does this unlock that weren't there before.

3:09

And lots of investors have made fortunes around

3:11

some big platform change or something. But

3:13

I'd love to focus on it from

3:16

the perspective of a CEO and operator

3:18

who's running a business and has run

3:20

other businesses through other technology changes and

3:22

transitions. And just begin by

3:24

having you riff on this experience. We're going

3:26

through a huge one maybe right now, everyone's

3:29

trying to figure it out. So

3:31

what's it like from the trenches? Obviously,

3:33

the transition we're talking about now is

3:35

this transition to AI and what it

3:37

means to see when OpenAI released chat

3:39

GPT, kind of made AI feel

3:42

real for people because all of

3:44

a sudden you can use general

3:46

common English language to engage with

3:48

a computer and give you answers

3:50

and generate content that never

3:53

happened before. So it kind of made things feel

3:55

much more real where before AI was

3:57

the purview of machine learning and engineering. and

4:00

data scientists. I've learned a couple lessons

4:02

because I've been through a number of these, I would say

4:04

I've been to three transitions, the move to the internet in

4:06

the mid to late 90s, obviously,

4:09

cloud and mobile, about

4:11

a decade ago. And now, obviously,

4:13

we're going through the AI transition.

4:16

A couple lessons learned is

4:18

one is value always accrues first at

4:20

the bottom layer of the stack. I

4:22

think about SelectaNy or the internet. In

4:24

March of 2000, Cisco was the world's most

4:27

valuable company. A lot of people thought they

4:29

were linchpin of building up the broadband

4:31

internet and everyone wanted high speed internet

4:33

access. March 2000

4:36

also went the bubble burst. And

4:38

people look back and said, well, Cisco really values

4:40

fairly when it's valid, like I think like 300

4:42

times P multiple, which doesn't

4:44

make up a lot of sense. So

4:46

the obvious question is that now people look at

4:48

Nvidia and saying is

4:50

Nvidia really the Cisco 2000 or

4:53

some people are asking is Nvidia, the Google

4:55

of 2003, even though they've accrued a lot

4:58

of value, they're the cusp of being the

5:00

seminal company for the next 10, 15

5:02

years. I don't know the answer to that question.

5:04

But one thing, the Nvidia is not trading at 300 times

5:07

that are P multiple, there's obviously tons of

5:09

demand of compute. And one thing we do

5:11

know is that the more compute you have,

5:13

the bigger breakthroughs you can have in these

5:15

AI models. So one is the value

5:17

is definitely first accruing at the bottom layer of the

5:20

stack. But I do think and

5:22

that's where the eye is going in the ROI

5:24

equation, but the returns will come into the apps

5:26

that customers see in terms of whether

5:29

you deliver great customer experiences, whether

5:31

you drive a lot of costs out of your

5:33

business through automation, or whether you

5:35

either create new business models or disrupt existing

5:38

business models with the use of AI. So

5:40

I think that's on the come. The

5:42

analogy I use with my team is the

5:44

iPhone App Store, when it first came out,

5:46

came out a year after the iPhone was

5:48

released, the first set of apps was incredibly

5:50

trivial. You may remember the flashlight

5:52

app, you may remember stupid apps like iDeer,

5:55

where you could simulate drinking a beer from

5:57

your phone, why people would build those apps

5:59

was still not clear to me

6:01

but they were very simplistic and trivial but

6:04

then all of a sudden when people really

6:06

view the iPhone as an important computing device

6:08

and people were running businesses from their phone

6:11

or consumers were really having amazing

6:13

experiences, you had things like Uber

6:15

and Airbnb and enterprises building iPhone

6:18

apps. I can essentially when

6:20

I'm not from my computer, I can use my

6:22

phone to do work which is pretty profound when

6:24

you think about where we've come. So I think

6:26

the same thing is going to happen in the

6:28

AI world where we're going to go from

6:30

these simple chatbots that give you answers

6:32

to questions and tools that help

6:34

you summarize the research information to

6:37

doing things far more profound, leveraging

6:39

real-time data to really make smart

6:42

decisions about how you're running your business. What

6:45

is the hardest part about running

6:47

a business that has obviously

6:49

existing product, existing customers that was built

6:51

not on top of AI or with

6:53

AI for a long time and

6:56

facing down one of these transitions? This is sort

6:58

of like the innovator's dilemma question I guess. How

7:01

does it feel to you right now running a

7:03

very big business and

7:05

watching this thing unfold? Obviously,

7:08

it can be both exciting and scary. There's some degree

7:10

of is this an opportunity and a threat in some

7:12

ways it could be both and I

7:14

think what obviously we're working on is trying to

7:16

really understand for us our

7:18

primary customer is the developer and

7:21

how does the developer workflow change

7:23

in a world of AI. I'm

7:25

not one to believe that you don't need

7:27

more developers because all of a sudden developer

7:29

productivity grows 10x. There's no development team

7:31

right now that doesn't have a backlog of things they

7:34

want to do and I think

7:36

if you look at every generation technology

7:38

transition from the mainframe to client server

7:40

to the internet to cloud and mobile,

7:42

the cost of building apps went dramatically

7:44

down. So one, you had far more

7:46

apps and a lot more data. I

7:48

think with AI, you can see a

7:50

step both increase in developer productivity

7:52

which means that you'll see that many more

7:54

applications. Consequently, I think we're going to be

7:56

a beneficiary of that. But that being said,

7:58

how do we position ourselves? to

8:00

be a winner. We think we have a flexible

8:02

platform, we think we have a highly scalable platform,

8:05

we see thousands of startups building AI

8:07

apps already on MongoDB. So to me,

8:10

that's a good crystal ball into the

8:12

future in terms of where large enterprises

8:14

are going. But it's still very,

8:16

very early days. Then the question is, how

8:19

much of the workload do we need to own

8:21

ourselves versus where do we need to partner? For

8:24

example, when we launched our cloud

8:26

business, this was in 2016, a

8:28

year before we went public, a

8:30

lot of people thought we were crazy. We were

8:33

the first infrastructure service that was

8:35

launched across the hyperscalers. And a lot of

8:37

people thought, wait, you're going to partner and

8:39

compete with like Amazon, Azure and

8:41

GCP. They said they're going to eat

8:43

you for lunch. And what they didn't fully

8:45

appreciate was that the product market for MongoDB

8:47

was really strong. But people didn't

8:49

really want to be the business of provisioning, configuring

8:51

and managing MongoDB. They want to be the business

8:54

of building apps among MongoDB that transformed their business.

8:56

And that business when we went public in 2017 was 2% of revenue

9:00

now at 68% of revenue. So we really built

9:02

that business. As a public company, we

9:05

obviously saw a big, big opportunity as a big

9:07

driver of our growth. When I joined the company

9:09

in 2014, we're doing about 30 million revenue. Now

9:11

we're close to a $2 billion run with the

9:14

business. So that's an example where we

9:16

saw an opportunity. And we really

9:18

doubled down this technology transition

9:20

to cloud, the way people were consuming

9:22

infrastructure as a service and felt we

9:24

had a big opportunity. I think

9:27

probably people listening, maybe

9:29

I put myself even in this category, take

9:31

for granted that a major part of the

9:33

world's technology today lives on top of databases.

9:36

I don't think anyone really think about

9:38

like any system, it's a database, an

9:40

interface and a couple of other things.

9:42

The database is a common theme across

9:44

basically every digital system. And

9:47

I doubt many people have stopped to think like, wait

9:49

a minute, what is a database? Who runs that? Is

9:51

that Oracle? Is that something else? Like what is the

9:53

history of this? And I'd love you

9:55

to offer your perspective on just the importance of

9:57

a database, you run a database business. role

10:00

that it plays, why there should

10:02

be more than one of them, why

10:04

different kinds of databases help us accomplish

10:06

different things. This is like a fundamental

10:08

building block of the world's technology. And

10:11

obviously, Mongo is one of the few

10:13

examples of a very modern

10:15

database company, a lot of them are very

10:17

old, that has succeeded. And so I just

10:19

love to hear you describe how and why

10:22

that happened. Just at a

10:24

very basic level, if you go to any

10:26

website, whether the shopping website or travel website,

10:28

it's all about the data. So imagine going

10:30

to a shopping website, and there'd be no

10:32

data, it'd be completely useless. Same with a

10:34

travel website. So when you think about what

10:36

a development team has to do, about 70%

10:39

of their time is spent working with data,

10:42

how do I present the right information or

10:44

the right data at the right time to

10:46

the right user with a relevant context. And

10:49

so working with data takes an

10:51

enormous amount of effort for a

10:53

developer. So a database plays an

10:55

important role for how people think

10:57

about building and constructing applications because

10:59

of so much about the data.

11:02

And one of the challenges of database business

11:04

is that if you don't have developer adoption,

11:06

don't have a business. So when I joined

11:09

MongoDB, one of the knocks on MongoDB was

11:11

there's been a whole generation of modern databases

11:13

that tried to be the next Oracle

11:15

or the potentially Oracle killer, but they've

11:18

all failed. Whether they're XML databases, in

11:20

memory databases, graph interfaces. One of my friends

11:22

said, why do you think MongoDB is going

11:24

to be the winner? And when I thought

11:26

about MongoDB was one of the things that got

11:28

me excited about MongoDB when I joined was that

11:30

the developer adoption among the viewers very high because

11:33

what developers are really excited by was that the

11:35

way all other databases made you

11:37

work with data was in a tabular format.

11:39

A database is think about it as really

11:41

like an Excel spreadsheet on steroids. And

11:43

everything's organized on rows and columns.

11:46

What the founders of MongoDB did was

11:48

they came up with this novel approach

11:50

of organizing data in documents. And

11:52

the reason that that was novel was that it

11:55

really aligned to the way developers think and code.

11:57

So all of a sudden, I didn't have to

11:59

go through this cognitive load of translating what

12:01

a product looked like into a data

12:03

setting, a bunch of tables, or what

12:06

a customer looked like, and then decomposing

12:08

that customer into a bunch of data

12:10

sitting across different tables, whether it's name,

12:12

location, order history, etc. And

12:15

so if you can keep all that information in

12:17

the context of one document, all of a sudden

12:19

it's much more natural and intuitive to work with

12:22

that data. And that's why MongoDB's developer adoption really

12:24

took off. And it truly, we are the most

12:26

popular modern database in the world. So

12:28

that's a reason why databases are so important.

12:31

So when you think about an application, whether

12:33

it's a gaming application you're using at home,

12:35

whether it's a mobile app you're using on

12:37

your phone, whether it's an enterprise app you're

12:40

using on your computer, there's a database behind

12:42

that application. That's the persistent data

12:44

store that stores that information. And

12:47

you can argue, I mean, the joke is to

12:49

make every web app is basically an

12:51

HTML wrapper or through your CRUD function

12:53

on a database. Databases are

12:56

incredibly important, and they're also very sticky.

12:58

I don't think I'm coming any lies

13:00

when I say Oracle's not exactly the

13:02

most liked vendor in the world. But

13:04

there's still tons of Oracle databases around

13:06

because it's such a sticky application. And

13:08

it's very hard to move applications once they've

13:10

been built on a database from one database

13:12

to another. If you think

13:15

about the most exciting version of

13:17

MongoDB in 2040 or something like

13:19

that, like just deep into the

13:21

future, what adjacencies do you

13:23

think where you are today allows

13:25

you to bleed into over that kind of

13:28

long term time horizon? I think you're 10

13:30

years in now at Mongo, so a

13:32

similar period of time, let's say, in the future. What

13:35

would get you the most excited about

13:37

how a company like yours can help

13:39

developers and others enable yet more cool

13:41

things to build? 2040

13:43

is a long time away. So there's all these deals,

13:45

especially in this world of AI, it seems like

13:48

three months is the way it all goes. I

13:50

would say our whole goal, our whole

13:53

strategy is to really actually get the database

13:55

out of the way of the developer so

13:57

that they could really focus on building great

14:00

applications, embedding really great logic

14:03

to enable people to do wonderful things. And

14:06

so the problem with existing databases is that

14:08

it takes such a tax in figuring out

14:10

how to work with data that so

14:12

much time and effort is spent by

14:14

developers working around the constraints of the

14:16

existing database. Our goal is to

14:18

remove those constraints so they can just focus

14:20

on building great business logic. Obviously

14:23

with AI and all the reasoning capabilities

14:25

that come with AI, the power of

14:27

these applications will be far greater

14:29

than what even we see today. And

14:32

how the transformative impact of what it will

14:34

do to businesses, I think is

14:36

to be determined if I knew all the answers, probably

14:39

not be talking to you right now. I do

14:41

think you will need an online data persistence store.

14:44

One of the things that's become clear with

14:46

these large language models is the switching costs

14:48

from going from one model to another model

14:51

is actually quite low. Because you can go

14:53

from OpenAI to Anthropic to Llama

14:55

fairly easily and start engaging with

14:58

it. Now, if those

15:00

LLMs start embedding memory, where

15:02

now they have a history of what Patrick has

15:04

asked, maybe history of all of

15:06

Patrick's activities, all of a sudden that foundational

15:08

model has a history which is stored in

15:10

some data persistence store, all of a sudden

15:13

the switching costs now become greater because you

15:15

don't want to lose all that history. So

15:17

that's an example where databases will play an

15:19

increasing important role as people start using

15:22

AI but leveraging also the history of

15:24

what you've done, what actions you've

15:26

taken, who you've communicated with,

15:28

etc. You're one of

15:30

a very rare breed, maybe it's

15:33

you and Slootman who are active

15:35

and a few others that you

15:37

could name that have founded, led,

15:39

been the CEO of multiple different

15:41

large technology companies across different periods

15:44

of time. And so it

15:46

makes me very curious about the formative

15:48

experiences for you as a founder, as an

15:50

operator, as a CEO, going all the way

15:52

back to however far back you want to

15:55

go. I'm just curious if you

15:57

think about your timeline and try to bring

15:59

to mind the most formative experiences that you

16:01

went through that have led to where you are

16:03

today and how you think about the world. I'd

16:06

love to hear about a few of those and you can begin

16:08

with whichever one you think makes the most sense. Well,

16:10

first of all, it's very nice of you to compare

16:13

me to Frank. Frank, I think is on a very

16:15

different league, have a lot of respect for him. He's

16:17

just recently made the decision to retire, which was a

16:19

little surprising, but his track record is second to none.

16:22

With regards to the lessons I've learned,

16:25

one of the big lessons I've learned

16:27

is that to drive excellence, you

16:29

need to be incredibly judgmental. And

16:32

most people, when push comes to shove, are

16:34

afraid to make the decisions they need to make

16:37

to be truly successful. They're not

16:39

willing to hold people accountable, they need to

16:41

be held accountable. They're not

16:43

willing to be extreme about the practice decisions that need to

16:45

be made, the way products are

16:47

positioned, whether they're priced, and

16:49

they're not also willing to be extreme about the

16:52

go-to-market decisions. And what I find

16:54

is most people fold with the pressure to make hard

16:56

decisions. I think that's why there's a lot of very

16:59

average and mediocre companies out there. And

17:02

I think really confronting problems directly

17:04

and dealing with them directly, most

17:06

people are social animals. Most people

17:08

don't want to have a painful

17:11

conversation. Most people don't want to

17:13

point out the flaws and what people are doing. And

17:16

so in many cases, you have

17:18

these very passive-aggressive meetings, everyone nods

17:21

politely, but in the back of

17:23

the mind, they say, this is probably not

17:25

going to work. We work really hard to

17:27

create a culture where we can be intellectually

17:29

honest about what's working and what's not working,

17:31

have fierce conversations about what to do or

17:33

what not to do, who's performing, who's not

17:35

performing, and then really focus on

17:37

executing really well. I would say

17:39

we're perfect. There's many times when we also make lots

17:41

of mistakes. But that to me is one big thing. The

17:44

second thing I've learned is in the B2B

17:46

business, I find a lot of founders and

17:48

CEOs focus a lot on

17:50

the product side of the house, which makes sense

17:52

because they typically are technical founders and

17:55

they're very, very focused around like, if I build

17:57

a great product, it will come. But

17:59

the reality is that... And part of the way

18:01

I grew up was that I grew up early

18:03

in my career when the best technology didn't always

18:05

win. You had large vendors like IBM and HP

18:08

and others who had so much account control that

18:10

even if you had a better mousetrap, the

18:12

customer would always pick a safe decision which was

18:15

to go with the large organization. And

18:18

so I realized that not only do

18:20

you have to build a greater product, but you

18:22

also have to build a ferocious go-to-market organization. And

18:25

in those days, it's all about sales, but

18:27

now go-to-market has become much more sophisticated with

18:29

sales and PLG and so on and so

18:31

forth. But to me,

18:33

the magic happens when you can

18:35

marry a great product with a great go-to-market

18:37

organization and that's where you can really differentiate

18:40

yourself in the industry. And

18:42

for example, at Blade Logic, my last company,

18:45

we have such a great sales force that

18:47

I think about 35 people out of that

18:49

sales organization became CROs of seminal software companies

18:52

in our industry. I don't think another company

18:54

has ever had that kind of track record.

18:57

And so as much thought as we put into our product

18:59

and how we position our products, and I'm not saying products

19:01

are not important, in fact it's very important, you don't have

19:03

business, you don't even have a good product, but

19:06

that's necessary but not sufficient in building

19:08

a B2B business. You need to

19:10

be just as thoughtful about how you go to market. What

19:13

is the mark of an exceptional

19:15

enterprise sales organization? If

19:17

you were evaluating 20 of them, not

19:20

Mongo's but others, is

19:22

it just idiosyncratic and it depends on each company or are

19:24

there things that you would say, no, this

19:26

means good, this means great, this means bad? I

19:29

would say a couple of things. One, obviously starts

19:31

with a leader in terms of how

19:33

they've designed and architected the sales force.

19:36

One sign of how good a sales force is is

19:38

broad-based performance. You can always have one person who's knocking

19:40

it out of the park. But

19:43

you don't want the 80-20 rule where 20% of

19:45

the reps are killing it 80% or not because

19:47

obviously that doesn't create a great culture and a

19:49

great environment. So you want to

19:51

create an environment where people are performing well. So

19:53

that's an output. So then what are the inputs

19:55

to drive that output? So to

19:58

me, the best organizations are very good at

20:00

reporting. recruiting, they're very good at recruiting hungry

20:02

people who are very smart, and

20:04

who really want to make a mark. The second

20:06

thing they're really good at is developing those people.

20:09

Just because you recruit someone doesn't mean that

20:11

they're going to be great. How do you

20:13

develop them not just on product skills, but

20:15

how to prosecute a deal, how to qualify

20:17

an opportunity, how to assess where

20:19

you are in the decision process and

20:21

the sales process and what potential risks

20:23

there are in closing that deal, how

20:25

to forecast. One of the things in

20:27

a high-growth business is your revenue forecast

20:29

or your booking forecast is a proxy

20:31

for your expense forecast. If you don't

20:33

forecast well, you can burn through a

20:35

lot of cash very, very quickly. Those

20:38

are fall marks to me of a great

20:40

sales organization and then obviously consistency in terms

20:43

of execution. They're not like a yo-yo, one

20:45

quarter of the great, one quarter of the

20:47

hair not, they're consistently delivering their numbers. If

20:50

you have those attributes, then that means you're

20:52

doing something special. It becomes

20:54

even harder in a high-growth business because not only

20:56

are you trying to make the number but you're

20:58

planning for where the business is going to be

21:01

two, three quarters out. You're trying to recruit people

21:03

because you have to assume roughly a six-month ramp

21:05

for someone to become productive. How you

21:07

think about territory planning, how you're making sure that

21:09

the new people joining the organization are set up

21:12

for success and the old guys or gals don't

21:14

have all the best accounts so the new people

21:16

are starving for good accounts. There's a whole process

21:18

around making sure that you're setting your team up

21:20

for success. How do you think about one of

21:22

the things we do is like sell divisions. Once

21:24

you get to a certain number of reps for

21:27

manager, you divide and promote or hire another manager

21:29

and so on and so forth. How

21:31

do you do that and who's the right

21:33

manager to lead that organization, etc. are

21:35

all things that we spend a lot of time on. What

21:38

have you learned and this is a

21:40

selfish question from just the current experience

21:42

looking at some enterprise companies that have

21:44

naturally very long sales cycles just

21:46

based on the nature of the customer and the buyer

21:48

and how they work. It's going to be hard to

21:50

change that. What have you learned about sales

21:53

cycles, especially if they're longer ones and how

21:55

to think about and manage those things, especially

21:57

when the juice is worth the squeeze. of

22:00

dollars per customer or something like that. Yeah,

22:02

what have you learned about that kind of motion

22:04

that's not just a demo and a sale? I

22:07

hate deals where it's just a very

22:10

long sale cycle because there's always a

22:12

chance of something going wrong. But if

22:14

you think about any sales process, any

22:16

sales process is essentially designed to address

22:18

three core questions. Why does the

22:20

customer want to do anything? i.e. what pain

22:22

or prom do they have that's going to

22:24

force them to take action? So that's with

22:26

the discovery part of the sales process, you're

22:28

trying to discover what pain or prom customers

22:30

have that are relevant to what you can

22:33

solve for. The second phase of

22:35

that is why MongoDB? Why is

22:37

MongoDB the best choice to solve

22:39

that pain relative to all the

22:41

alternatives and substitutes available? And then

22:43

the third part of the sales

22:45

process is why now? Because

22:47

you can do the first two things but the

22:49

customer can easily kick the can down the road.

22:52

And in many cases, that's the struggle most salespeople

22:54

have. It's not that you lose a deal but

22:56

the customer never makes a decision. Can you create

22:58

a manufacturer or is there a compelling event you

23:01

can use to force a customer or induce a

23:03

customer to make a decision sooner than later? So

23:06

those three questions, I don't

23:08

know how you can forecast the deal if you don't

23:10

have answers to those three questions. So that's essentially how

23:12

our sales process is broken down. Then

23:14

the certain interim steps in the

23:16

sales process that tell you, are

23:18

you on track to kind of getting a deal?

23:21

Have you met with the economic buyer? Have you

23:23

qualified how much budget is available? Have you qualified

23:25

even that this is a priority for them? And

23:27

because you're not just competing with your own

23:29

competitor, you're competing with other vendors and other

23:31

spaces for budget dollars. And so how do

23:33

you know, is this problem that you're solving

23:35

for as important as another problem that another

23:38

vendor might be trying to address? And

23:40

then obviously, what is the decision criteria? One

23:42

rule of thumb we have is you should

23:44

never be answering RFP. Because invariably,

23:46

if you're getting an RFP that you've never worked

23:48

on before, some other vendor has written the RFP.

23:51

So what that means is you have to set

23:53

the table on the decision criteria. How is a

23:55

customer going to make a decision? What

23:57

features or capabilities are they going to weigh?

24:00

and how they're going to wait then relative

24:02

to other things they can consider for them to make a

24:04

decision. Have you educated the customer

24:07

and built what we call champions who

24:09

will understand the value of MongoDB

24:11

and understand why for their own

24:14

business MongoDB is the best choice?

24:16

And then building a champion, a champion you

24:19

define as someone who's selling for you when

24:21

you've left the building. Obviously, someone who's a

24:23

change agent, has power and influence in organization,

24:26

and is really selling for you after

24:28

you're not there, there's a big difference what

24:30

we call between champions and coaches. Coaches want to

24:32

see when but they're not going to take either

24:34

any personal risks themselves or they just

24:36

don't have the credibility or views to kind of influence the

24:38

decision. But they can be helpful to kind of give you

24:41

some insight or radar into what's happening in

24:43

the account. But ultimately,

24:45

there's a champion for every deal that are

24:47

close. Sometimes you may not know who your champion is,

24:49

but there's someone who's advocating for you when you're not

24:51

alone in the room or advocate frankly for someone else

24:53

and you will got to make sure your champion is

24:56

more powerful than your enemy champion. And

24:59

that's all part of the sales process. The

25:01

champion idea reminds me of the first thing you

25:03

said, which is that most people don't want to

25:05

make hard decisions and confront

25:07

trade offs. And it

25:09

makes me wonder what your first experience

25:12

with this was from a

25:14

personal standpoint that made you aware

25:16

of or suited to or better wired

25:19

to be decisive, have

25:21

judgment, make decisions, make trade offs.

25:24

I started my career at AT&T and Bell Labs and

25:26

then I moved into the business side. There's

25:28

some very talented people there and this

25:31

is the old AT&T, not the AT&T of

25:33

today, but there's some very talented people there,

25:35

but I saw a lot of passive aggressive

25:37

behavior and I saw there'd be a meeting

25:39

and the senior person would essentially advocate for

25:41

a decision. Everyone would knock politely.

25:43

There wouldn't be any fears today, but then

25:45

people leave the room and you could see people's

25:47

eyes rolling saying that's never going to work. And

25:49

to me, I view passive aggressive as a

25:52

form of duplicity because you have to create

25:54

a culture where people are free to say

25:56

what they think constructively about a

25:58

particular idea or a particular story. for a

26:00

decision because I always believe all of us

26:02

are smarter than any one of us. And

26:04

one of our core values among DB is

26:07

intellectual honesty because I am born passive aggressive

26:09

behavior. That was one thing that I learned not to do.

26:12

The second thing was when I founded BladeLogic,

26:14

I got my first round of capital

26:16

five days before 9-11. So 9-11 happened,

26:19

the mid-burst. So it was a pretty tough time

26:21

to start a business. So

26:24

I had only $6 million wired to me. We

26:27

were essentially trying to build a business using

26:29

a direct sales force. It was a pretty

26:31

tricky time to build a business from scratch.

26:33

And ultimately, we raised 29 million

26:35

of which some was still in the bank when

26:38

he filed our S1. So we're pretty efficient in

26:40

how we use our capital. And that was a

26:42

forcing function saying I didn't have time, the luxury

26:44

of being patient with people who aren't working out.

26:47

And one of the lessons I've seen, and

26:49

I've also been an investor for a little

26:51

bit is that sometimes raising too much capital

26:54

breeds bad behavior because it takes the pressure

26:56

off. When I had very little capital,

26:58

some wasn't working out. It wasn't like, hey, Joe,

27:00

sorry, it's not working. I'm going to put you on this

27:02

special project. I know you're a good guy. And the answer

27:04

was Joe's not working out. It's better for you and for

27:06

us that we have hard time. It's just now because I

27:09

just can't afford for this not to work

27:11

and treat the person with respect when you

27:14

move on. And so that builds

27:16

muscles in terms of dealing with problems directly,

27:18

not picking the can down the road. And

27:20

so many management teams pick the can down

27:22

the road. If you ask anyone, did you

27:24

ever fire someone too quickly or too late?

27:27

99.9% of the time they say they fired people

27:29

too late. Why? Because they introduced hope into the

27:31

process. And we still do that even at MongoDB.

27:34

People say, oh, give that person more

27:36

time. He or she just needs more

27:38

time to get a sense of how

27:40

we do things. And invariably, the

27:42

answer was staring in the face, but you just didn't want

27:44

to acknowledge it. And so that was also another

27:47

lesson I learned is deal with problems head on and

27:49

quickly. And that's play logic

27:51

that went through multiple rounds of leaders.

27:54

And not that I was purposely looking to change leaders,

27:56

but leaders can come and go because

27:58

they're good for certain stage of growth. but then

28:00

they cap out even among DB

28:02

the leadership team I inherited is no longer

28:04

here when a business scales not everyone scales

28:06

with the same way One

28:09

of the things I've learned in life is that if

28:11

you see a problem and don't act on it

28:13

That's calm is no longer that person that think

28:15

I promise you if you have the authority

28:17

to solve that problem You're not doing it then you're the

28:19

problem. I always feel like whenever

28:22

I see something bad if I don't

28:24

act on it then I'm actually accepting

28:26

mediocrity or I'm setting for performance and

28:29

That's contrary to everything that we're trying to do

28:31

and some way if you're penalizing all the good

28:33

people who are working really hard because you're Accepting

28:36

mediocre performance from the other person and they're

28:39

actually penalizing all the good people who have

28:41

crowns of constraints or the limitations That's other

28:43

person One of the ideas of

28:45

yours that I like best when I was reviewing kind

28:47

of your history and your thinking was This

28:49

idea that people perform to the level that

28:52

you inspect not that you expect. I love

28:54

that idea Can you just like explain that

28:56

philosophy and the mechanism of how you put

28:58

it into practice? The

29:00

short answer is that if grown adults were supposed

29:02

to do what we asked them to

29:04

do You wouldn't need that many leaders or managers You

29:08

would have theoretically one leader

29:10

and a bunch of individual contributors but the

29:12

reality is that human nature doesn't operate that

29:14

way and you need people who can

29:16

challenge and push you and When

29:19

people know that there's a high degree of

29:21

inspection There's a joke at blade logic was

29:23

that they love you placement There's a

29:25

lot of sunshine because there's no place to hide

29:27

because we constantly inspect what's going on And when

29:30

people know that their performance will be inspected that

29:32

there'll be constant review of what's going well What's

29:34

not going well, which is healthy? It's not mean

29:36

that the person is bad But sometimes they're running

29:38

into an issue sometimes that issue is bigger than

29:41

they can solve it elevates up and saying hey

29:43

We got to figure out a way to respond

29:45

to this issue business person has it we're gonna

29:47

see this with other people That

29:50

just creates a very healthy dynamic and

29:52

it also creates a bias to action

29:54

So people who thrive in those kind of environments love

29:56

it because saying hey when there's problems this company really

29:58

cares and wants to solve problem, but it

30:01

starts from really understanding what's going on and

30:03

deeply inspecting what people are doing relative to

30:05

the goals and expectations you have. Yeah,

30:08

it's a beautiful idea. And

30:10

I wonder if it ever gets exhausting. Does

30:12

it ever tire you out to constantly have

30:14

to inspect every aspect of something going

30:16

on or are you wired to just enjoy that

30:19

and do that well? Well, to

30:21

be clear, on a certain scale, I can't

30:23

be involved in every meeting or every decision

30:26

becomes another approach. But at a face level, it

30:28

is exhausting, right? This is one of the reasons

30:30

why people don't want to do it is that

30:32

it takes energy to say, hey, what's

30:34

going on? This project is not tracking. What

30:37

are you doing? What's breaking down and really

30:39

having a very lengthy, a hard

30:41

to hard talk about why is

30:43

this project not tracking? And most people have

30:45

a very superficial conversation. You'll

30:47

tell me, David's okay. This is just a

30:49

temporary setback. We're all good. And if

30:51

you don't really ask the next set of questions, it's

30:54

very easy to assume a project has got this. And

30:56

then three months later, the project fails. And

30:59

so it does take energy and effort. And I think that's

31:01

one of the reasons why people don't like doing that. With

31:04

regards to as the business scales, one

31:06

of my other axioms is that bad

31:08

news travels very slowly up the organization, but

31:11

very quickly down the organization. So imagine a

31:13

situation where a sales rep in front of

31:15

a customer, customer says, I'm going to throw

31:17

you out. I'm really unhappy about the quality

31:19

of service I'm getting blah, blah, blah. The

31:22

rep tells their manager, oh my God, we have a

31:24

problem with Acme company. And then it slowly

31:26

moves up the organization. And a typical organization

31:28

I may hear, David, we're having a problem with

31:30

Acme company, but we're all over it. And if

31:32

I operate in that way, I say, okay, no

31:34

big deal. They're on top of it. And then

31:37

months or two later, the Acme company turns. My

31:39

philosophy is different is that if I hear

31:42

bad news, I immediately start

31:44

digging in. And invariably, and because I know when

31:46

I hear bad news, I know two things. One

31:49

I'm the last to know. And two, it's

31:51

far worse than what people tell me because

31:53

the filtration process of sending bad news up

31:55

the organization dulls all the sharp edges of

31:57

that bad information. So a whole new thing.

32:00

the crap moment with a customer with a rep

32:02

is now, hey, there's a small issue with Acme

32:05

company. Now, we don't have that culture here, MongoDB. I'm

32:08

just describing what a typical organization goes through. And

32:10

that's why so many people get caught flat-footed when

32:12

they get surprised by some bad news because they

32:14

always assume that things are far better than they

32:16

were. So our culture is the opposite

32:19

where, and obviously, I can't be in every meeting

32:21

or decision, so I do sampling. Whenever I see

32:23

some bad news, even today, I sent

32:25

one of our leaders feedback on one of his

32:28

people because I had a very mediocre experience of

32:30

saying, this person is coming up and showing up

32:32

to me in a very mediocre way, not very

32:34

well prepared, nothing really innovative

32:36

or creative in what they were doing,

32:38

how are they showing up to everyone else in

32:40

the organization? And so that generated

32:43

a slack message from me to the leader

32:45

saying, hey, I'm really concerned about this person.

32:48

And so I'm always assuming that if

32:50

I see something bad, it's far worse. And

32:53

if I don't do anything about it, no one else will. In

32:55

addition to this, I think for sure

32:58

the average company is low on inspection,

33:00

like that's the default inertia mode or

33:02

something. In addition to that difference,

33:04

where Mongo is much more on the

33:07

high on the inspection spectrum or something,

33:09

where else do you feel like Mongo is

33:12

the most different from the sort of like

33:14

average company that's intentional on your part? We

33:17

are building and selling a very technical product.

33:20

And there's often other companies that have very

33:22

technical products. What I would

33:24

say is we've had to deal with the open

33:26

source dimension. And then we've

33:28

also had to deal with building a

33:30

traditional enterprise software. Well, now it's a

33:32

subscription software delivery model and then a

33:34

cloud model. So I would say one

33:36

of the challenges I worry about in

33:39

our business is that we are like

33:41

a multi-product, multi-channel business. Yes,

33:43

we're $2 billion in size, but there's a lot of $2

33:45

billion companies who have one core product

33:47

and one core channel. So how

33:49

we think about like organizing, doing capital

33:51

allocation across different product sets as well

33:53

as different channels, the same things that

33:56

we spend a lot of time and

33:58

energy on. constantly

34:00

is, are we over-complexifying the business? I think there's

34:03

value and simplicity. So always trying to figure out

34:05

do we really need to add in any channels.

34:07

So for example, on Go to Market Channel, we

34:09

have a direct time and sales force, we have

34:11

a mid-market sales force, we have a

34:14

self-serve channel, and then we have a partner channel. All

34:16

those organizations play an important role. We

34:19

also have expanded our customer success functionality

34:21

and so our customer success people, because

34:23

you're selling the cloud service, play an

34:25

important role in understanding and assessing customer

34:27

health, then they have some up-shell opportunities

34:30

as well, and there's the opportunity that

34:32

the customer could take advantage of with

34:34

MongoDB. It's a fairly complex

34:36

Go to Market. I'm not necessarily saying it's great

34:38

that we have it so complex, but it's just

34:40

a virtue of going after a very large market

34:43

and a one-dimensional channel model wouldn't work for us

34:45

because how big our market is. You

34:47

are an interesting breed as well because you've done lots

34:49

of investing. You led an early round in Datadog, you've

34:52

made lots of really good investments, you're on a bunch

34:54

of boards. I'm curious the

34:56

investor in you how that leads

34:58

into thinking about capital allocation within

35:01

Mongo. You mentioned that maybe because

35:03

of the complexity, there's more opportunity

35:05

or more requirement for capital allocation

35:07

thinking. What is your framework

35:09

for thinking about allocating capital inside the business?

35:13

I mean, it's all about where do you get the best returns.

35:15

I will just step back and say

35:17

being on boards and being an investor

35:19

really helped me appreciate being in investor

35:21

shoes when they're coming to my board

35:23

meetings because it's very easy for management

35:25

to get frustrated with investors, but then

35:27

you really appreciate the pressures investors have

35:29

in terms of their under the

35:31

gun for their LPs and so on and so

35:33

forth. It's easy to say, but it's really hard

35:36

to understand until you live that shoes where you've

35:38

been in a partner meeting and you're doing a

35:40

portfolio review and you're seeing why some companies are

35:42

being successful and why they're not. One

35:44

of the interesting lessons I've learned at being

35:46

an investor is there's an inverse correlation between

35:49

work and outcomes. You're best performing companies, you

35:51

show up kind of eat the doughnuts and

35:53

lead because they're doing so well and we're

35:55

doing a lot of work. You're helping the

35:58

matching team rebuild the business maybe. helping

36:00

them hire people, that maybe the companies

36:02

are struggling. So it's a very weird

36:04

dynamic. I'd play logic. I should go to

36:06

my investors. I never really hear from you that much. And

36:09

they go, Dave, that's a good thing. Because if

36:11

you heard from us a lot, that means you'll

36:13

be having serious problems. And it took me a

36:15

while to appreciate that. But I would say, that's

36:17

your question around capital allocation.

36:20

We take an orientation around like what's selling the

36:23

return. So I've been old enough where

36:25

I've seen good marks and bad marks. So obviously for

36:27

the last 10 years until 22, now with the benefit

36:30

of the high-speed, I realized that was a really good

36:32

market. But for us, because we

36:34

have seen bad markets, we never really spend

36:36

money like drunken sailors, just to put things

36:38

to perspective. When we were in public, we

36:41

had trailing $100 million in revenue and negative

36:43

38% off with margins. Our

36:45

numbers were exactly like super compelling. But

36:48

as a public company, last year we did

36:50

16% offing margins. And as I

36:53

said, we're now approaching a $2 billion run rate business.

36:55

We've shown almost 55% plus

36:59

operating margin improvement while growing the business

37:01

very, very quickly. So our capital allocation

37:03

process is all about where do we

37:05

get the best returns, having good discipline

37:07

about investing here and not investing, divesting

37:09

on certain investments when they're not working

37:11

out and just constantly asking

37:13

ourselves what's working, what's not working.

37:16

And are we perfect by no means, but we

37:18

try and be very disciplined about how we run

37:20

the business. Can you explain your

37:22

philosophy of recruiting? It sounds like that is a key

37:25

thing that you've always focused on in your businesses, and

37:27

I know it is at Mongo too. What

37:29

do you think is the most important part

37:31

of how you think about getting the right

37:33

people into the business? Anything that you've done that

37:36

you feel is especially impactful? I

37:38

think one of the things about recruiting,

37:40

most people make the common mistake of

37:42

just focusing on what the

37:44

person's background experiences, where they work,

37:46

what skills they had, and

37:49

maybe like what successes that they can

37:51

talk about. I think a big

37:53

part of recruiting is trying to figure out what makes a person

37:55

tick. What is it about them?

37:57

What is it about their upbringing? drives

38:00

them, what motivates them in terms of who they are and

38:02

where they want to go and what they want to be.

38:05

And I think if you don't

38:07

really understand that underlying psyche of

38:09

a person, how do you

38:11

know what you're really getting? It's one thing

38:13

to say like, hey, you have experience

38:16

building product, you're experiencing enterprise software, but

38:18

how do you assess them as values? Do you believe

38:20

in the value of hard work? How

38:23

do you measure grit? One of your

38:25

common guests that I love made a

38:27

statement that I completely agreed with was

38:29

Jeremy Gippon who talked about that

38:31

the only enduring edge in life is

38:33

psychological as human nature doesn't change. That

38:35

was like words out of my mouth.

38:38

How you manage grit, how you manage

38:40

your ego, are you comfortable with low

38:42

status, are you comfortable being unconventional, can

38:44

you delay gratification, you have long term

38:46

orientation. Those are keys to

38:48

being really successful but it's so hard to

38:50

do because it's so contrary to human nature.

38:53

So how do you like find someone who

38:55

can really do those things and what drives

38:57

them to do those things? I've heard some

39:00

amazing stories about people. I ask them questions,

39:02

what's the most difficult thing you've ever endured?

39:04

And I keep it generally open-ended and

39:06

some of the stories you hear about what

39:09

they have to deal with in their upbringing,

39:11

they were came from broken home or they

39:13

came with very few resources and they're so

39:15

driven about making sure that their

39:17

family and their children never have to go

39:19

to what they have to go through just

39:21

tells you this person is intrinsically

39:24

motivated. We should joke at

39:26

Blade Logic. If someone has

39:28

some character flaws, the parents

39:30

can fix their character flaws growing up. There's no way

39:33

we're going to be able to do so at a

39:35

company where they may spend x number of years at.

39:37

So for us trying to really understand the person and

39:39

who they are and what they want

39:41

is important. So now one way to qualify that

39:43

is trying to ask them questions about okay, help

39:46

me understand what school you went to, help me understand

39:48

what major you picked and why did you pick that

39:50

major, help me understand why you went to this company

39:53

and then why did you go from company A to

39:55

company B because in some ways those are

39:57

some of the most important professional decisions you can make in

39:59

your life. And if someone is not

40:01

very thoughtful about why they went from company

40:03

A to company B, then

40:05

the question I'm going to say is how thoughtful

40:07

they're going to be prosecuting a deal or when

40:09

they're making a decision on a product or when

40:11

they're thinking about a new idea to come up

40:13

with. And so, that

40:16

gives you a sense of how thoughtful they are and

40:19

what makes them tick. What's the most

40:21

difficult thing you've ever endured? I

40:25

set myself up with that question. I

40:27

shared this before. I came from a

40:29

broken home, per se. My natural father

40:31

was not a very good person. He

40:34

was a misogynist. And so, my mother really had

40:36

a tough time when I was very,

40:38

very young. In the early

40:40

late 60s, early 70s in India, divorce

40:43

is a very unspeakable thing. My

40:46

parents, my grandparents were really

40:48

well-to-do people. And so, it was a black

40:50

mark in the family. My mother faced a

40:52

lot of pressure to stay in the marriage.

40:55

And I give her so much credit for refusing to do

40:57

so. So, I grew up in an

40:59

environment. My mother ended up marrying my stepfather and who

41:01

I considered my real father. And they

41:03

decided to leave India because my mother realized the stigma

41:05

of being divorced would be too painful for both her

41:07

and for me. Staying in India, so we

41:10

end up emigrating. And I lived all over the world and

41:12

then lived in Africa, lived in Canada, lived in the UK

41:14

for a while, and then moved to the

41:16

US. Part of me has always

41:18

felt like, am I good enough? Because in

41:20

some ways, I've had this very weird upbringing.

41:23

I'm a Christian Indian. So, I'm

41:25

a minority in my own country. Only

41:27

about 2% of India's population is Christian.

41:29

So, even though 1.3 or 4

41:31

billion is still a lot of people, but you're a very

41:33

small minority. Coming from a broken

41:35

family, I always had this stigma about

41:37

being good enough. And then, when

41:40

I was applying to college, my parents were living in

41:42

Africa. My dad worked for an oil company and decided

41:44

he wanted to emigrate to the United States. They

41:47

kind of viscerated the balance sheet and he

41:49

went back to grad school, got

41:51

a job in the aerospace industry. Income level basis,

41:53

they looked like a fine-load class family, but the

41:55

balance sheet was eviscerated because they had used all

41:57

their funds to kind of pay for going back

41:59

to the US. school and so I

42:02

had a chip on my shoulder going to a state

42:04

school when I got accepted to some quote

42:06

unquote more elite colleges and now

42:08

I look back I'm so grateful for that chip

42:11

on my shoulder but like it was always like

42:13

I want to prove to myself and prove to

42:15

others about am I really good enough

42:17

I've got all this baggage and background and

42:20

so that's I think one of

42:22

the reasons back to why I asked what motivates

42:24

people my motivation is to prove to people that

42:26

I'm good enough to prove to people that I'm

42:28

just as good as people who graduated from a

42:31

elite college and may have had a more quote

42:33

unquote normal family childhood looking back I

42:35

think that really served me well. Objectively

42:39

you've proven that I'm curious

42:41

then if it persists as a source of

42:43

motivation or if that has morphed into something

42:45

different. Oh it definitely persists

42:48

I don't think you lose your upbringing any

42:51

setback you always start questioning oh my god am

42:53

I good enough again any bad decision you start

42:56

questioning yourself and so I

42:58

don't think that ever disappears I think sometimes

43:00

you can suppress it for a

43:03

while if things are going reasonably well but I

43:05

think it's always there. Who is

43:07

another leader that you've learned the

43:09

most from observing? I

43:11

would say one of my key mentors

43:13

was a guy named Steve Walski so

43:15

I had raised money for Blade Logic

43:17

but I never actually worked at a

43:19

software company and obviously I've never

43:21

been a CEO of a software company. I was very surprised

43:23

to say there's a lot I don't know so Bessemer

43:26

and Battery were my two lead investors I went

43:28

to the Bessemer folks and said who's the best

43:30

CEO in the Boston area that

43:33

you can refer me to that I want to go speak

43:35

to this guy named Steve Walski who was the chairman of

43:37

PTC. They said great give me

43:39

his number and they said here's the number but good luck

43:41

eat snails for breakfast and he might never return phone call.

43:44

I kept pestering him and then he finally returned

43:46

my call me and my co-founder went to visit

43:48

him we had a good conversation

43:51

but then he kind of said okay let me think

43:53

about it I'll give you a call back and I

43:55

kind of said oh god is this the I'll call

43:57

you don't call me kind of response turned out me

44:00

back. And I used to go visit

44:02

him about once a month at his house in

44:04

Chestnut Hill in Massachusetts and

44:06

just walk him through what's happening to the business.

44:09

And he was so valuable to me because

44:12

he obviously had built, if you look at PGC, they

44:14

were one of the great companies in the 90s that

44:16

built an amazing business. They delivered 40% offering

44:19

margins and grew north of 100% for literally

44:21

like, I think like 10 years straight. And

44:23

they had also built an amazing sales force. And

44:26

so he was very helpful to me to kind

44:28

of understand how to think about building a business,

44:30

how to think about dealing with a board, how

44:32

to think about capital raising, because it

44:35

was a very tough time. As I said, raising

44:37

capital right before 9-11, we're in

44:39

the nuclear winter of tech, investors are

44:41

very skittish, because they've just

44:43

seen their portfolios crumble. And any

44:45

new investments, if there's any sign of hint of trouble, they're

44:47

panicked because the last thing they want to do was see

44:50

a new investment start struggling. So I

44:52

felt a lot of pressure. And he was really

44:54

helpful to me in terms of understanding what it

44:56

meant to be a CEO. And he really informed

44:58

my leadership philosophy around marrying product with

45:01

go to market excellence, thinking about how to build

45:03

a great sales force. He helped me recruit

45:06

a bunch of CROs, including one guy named

45:08

John McMahon, who was a legend in the

45:10

space unit was a CRO, play

45:12

logic, ultimately became COO. And then he

45:15

also worked with me and joined the board

45:17

at MongoDB. So he was incredibly helpful to

45:19

me. And the thing I really liked about

45:21

him is I always felt safe, that

45:24

I could ask him any dumb question and he wouldn't

45:26

belittle me. And I think one of the advice I

45:28

give people is to really have someone that's a mentor

45:30

to you, you got to be able to open up

45:32

the component, you got to be able to really share

45:34

your deepest, darkest worries, and be able to put them

45:36

on the table. And one of the things I realized

45:38

is being a CEO is a very lonely job. Because

45:41

you really can't open the kimono always to your

45:43

board, because you're worried about how they're

45:46

gonna react, you can't always open the kimono to your team,

45:48

because sometimes you may be thinking about an org change that

45:50

could actually marginalize someone on your team and

45:52

they're not gonna be too happy about it. So

45:55

having someone you can go talk to is

45:57

super important. See play that role for

45:59

me, I will will be always very, very grateful to

46:01

them. What's your deepest, darkest worry

46:03

at Mongo? I mean,

46:05

how we navigate right now, the AI wave, is

46:08

something that is really important. It's really the

46:10

future of how software will be

46:12

built. And we want to make

46:14

sure that we're a key component of the

46:16

tech stack. So how could

46:18

that go wrong? AI gets adopted, it's everywhere.

46:21

It goes really badly for Mongo, the pre-mortem

46:23

here. Like, how would it go really wrong?

46:26

If people feel like MongoDB is not the right

46:28

architecture for the best AI applications. Now, I don't

46:30

think that's gonna happen. It's kind of like people

46:32

think about using Oracle for

46:34

a new modern application. I can't think of

46:37

a startup today who's building on Oracle. It

46:39

would worry me a lot if the next generation of

46:42

companies and the next generation of apps, people

46:44

felt like MongoDB was not suitable for those

46:46

applications. That means like we need to work

46:48

on our product roadmap, make sure

46:51

we're building out the right capabilities, being

46:53

responsive to customers, because it's

46:55

very easy to become complacent. Do

46:57

you think that there's any chance that AI is

46:59

not the thing that everyone seems to now

47:01

think it is, and that it's not as

47:03

transformative as is the very

47:06

common consensus today? No, I

47:08

think AI is gonna have a massive impact, but I

47:10

think you raised a really good point. I

47:12

was just telling people yesterday, I said, when I

47:14

wake up, how much is AI

47:16

influencing my life? Like the internet today has

47:18

had a massive impact on our life. Every

47:21

day, all day, yeah. Exactly. How much is

47:23

AI really impacting life? Yes, you may get

47:25

some hints about writing this note

47:27

maybe a little bit more crisper than you

47:29

originally thought. Yes, if you drive a Tesla

47:31

or something, you can see the benefits of

47:33

autonomous driving, but it's not really

47:35

impacting your life on a day-to-day basis. But

47:38

I always believe people overestimate the impact of new

47:40

technology in the short term, but underestimate in the

47:42

long term. The reason for that

47:44

is that I think technology adoption happens in

47:47

S-curves. And so it's very easy to take

47:49

a couple data points on the rise up

47:51

and extrapolate too much. Conversely, it's

47:53

very easy to take a couple of data points on

47:56

the downward slope and extrapolate this illusion

47:58

too quickly. look at

48:00

the S-care of adoption for

48:02

technologies that have really taken

48:04

hold, it over time goes up and to the

48:07

right. Now, this clearly technologies have not

48:09

done that. I think blockchain and crypto, the

48:11

jury, fill out about those technologies,

48:13

AR and VR. I think there's still some

48:15

questions about how impactful those technologies

48:17

will be. But I definitely believe

48:19

AI is going to be incredibly transformative. I think

48:21

the way it's going to show up for people

48:23

is back to the way we started this conversation

48:26

is around the applications. A lot

48:28

of people thought software would be really

48:30

disruptive and dislocate a lot of jobs.

48:32

But if you look at what happened

48:34

with software, pre-cloud and pre-SaaS, only

48:37

the largest companies in the world were able

48:39

to access the best software, the best CRM

48:41

software, the best HR software, the best supply

48:43

chain software, etc. When software

48:45

became democratized, the small companies

48:48

could take advantage of the best software.

48:50

And so it just grew the market

48:52

overall in such a big way. A

48:54

lot of people worry that AI

48:57

will go after the white collar

48:59

jobs, the services jobs, legal, accounting,

49:01

finance, etc. I would

49:03

argue, and that's potentially a pessimistic view,

49:05

I would argue, yes, the cost of

49:08

building those services will come down. But

49:10

now small businesses will be able to leverage the

49:13

best legal minds, the best accounting minds, the best

49:15

financial minds, much like the FMD

49:17

companies can take advantage of the best software

49:19

that only the top few Fortune 500 companies

49:21

can do so before. So I think this

49:24

will be a net positive for everyone. But

49:26

I do think it's gonna take some time.

49:29

The list of investments that you made, it's pretty

49:31

impressive 10 plus years ago at

49:33

OpenView. What is

49:35

your investment philosophy? What is it that

49:37

you're consistently looking for when making

49:40

an investment in another technology business

49:42

outside of one that you're running?

49:45

What I look for is a big market,

49:47

because by definition, your outcome is directly correlated

49:49

to the size of market you're going after.

49:52

Two, I look for is what is the

49:54

defendable technology advantage that the company has and

49:56

what proof points are there to prove that

49:58

it really has. a durable advantage.

50:01

Three, I look for investments

50:03

is a CEO who's smart

50:06

but also coachable. And

50:08

the coachable part is important to me because I don't

50:11

believe that there's a compression algorithm for experience.

50:13

Some people just learn faster than others. And

50:15

I don't expect a CEO to do everything that

50:17

I'm telling them to do because that's why they're

50:19

in charge. But to me, I

50:22

worry a lot if someone doesn't feel

50:24

like they have all the answers. And

50:26

I think vulnerability is a strength, not

50:28

a weakness. And so Joti at AppDynamics

50:30

and Olivier at Beardog are two incredibly

50:32

sharp people. And they

50:34

both build fabulous multi-billion dollar businesses.

50:37

But they're also, while we would

50:39

have fierce conversations, they will listen.

50:41

Sometimes we'd agree, sometimes wouldn't agree, but it was

50:43

a very healthy conversation. And they

50:46

were both very, very motivated to build

50:48

great businesses. In the

50:50

early stages of a business, how do you

50:52

know when the product is

50:54

ready for that bigger go-to-market investment and

50:56

explosion? I guess the private market fit

50:59

question. How in your experience do you

51:01

know when a company with its first

51:03

product or Mongo with its second or

51:05

third product or whatever is

51:07

on to something sufficient to pour fuel on

51:09

the fire? To me, it's

51:11

if the customer comes back and buys more. Because

51:14

any customer can buy something as a science

51:16

project. And this is a trap

51:18

I see a lot in the database space. So

51:20

I'll get calls, diligence calls from investors saying, hey,

51:22

do you see this company? They have some single

51:25

purpose functionality. And they have a nice logo set

51:27

of logos. This space is so big, some of

51:29

them try something for some corner case. The

51:32

question I'll say is, yeah, but can they

51:34

prove that they can repeatedly get more business

51:36

from that customer or show a pattern of

51:38

getting a simultaneous case winning on the customers. And

51:40

so to me, one homework is like

51:42

a product market fair because we're coming

51:44

back and buying more. So people

51:46

call that NDR or public

51:48

companies. You want rates of 120% and higher where

51:51

if you look at the same core a year

51:53

later, are they spending net

51:56

of churn? Are they spending 20% more than

51:58

they did the previous year? So

52:00

that to me is a very good sign

52:02

of something real. How. Easy.

52:05

Or. Difficult as a to make that

52:07

sale because if is a very complex

52:09

go to markets process and you to

52:12

jump through seventeen hoops that I would

52:14

worry about. This is like a

52:16

uniform that very to customizable go to

52:18

all that came to acquire. Or

52:20

conversely is it really is is one thing the

52:23

gummy bears inches about the the dog was I

52:25

invested when they were day but a million. In.

52:27

Revenue and now the North two

52:29

billion. But. I saw was a

52:32

month over month growth of existing customers. Mosque.

52:36

With. Us on our as a with us home.

52:38

He was knowledge it was easy because they

52:40

were closing. lot of customers with a fairly

52:42

do yourself for some. Wasn't very public sale

52:44

but customers are also growing very very quickly

52:46

once it ball so that's me was a

52:48

great sign. The buses. That. Bedroom Mail

52:50

print. Edition to

52:52

Ai which is obviously the dominant

52:54

once. What else going on in

52:57

the technology ecosystem is most interesting

52:59

to you today. I

53:01

think security is an area that blows be

53:03

a born in a as you come out

53:05

with you solutions to existing problems. you'll find

53:07

work rounds. To. Find new

53:09

ways to. Britain. To attack

53:11

since. Ah yes, and so to me

53:14

that's a space that a forces attacks

53:16

those tax that we ought to pay

53:18

because we all care so much about

53:20

security and nasty so. But to me,

53:22

the security best. Something that will just

53:24

continue to be incredibly innovative. And now

53:26

with a I, the notion of potential

53:28

deep barracks and all the implication that

53:31

come with a I I think the

53:33

security doctors will have to spare. You

53:35

figure out is Patrick who he really is

53:37

when is calling me or city me this

53:40

email and the slack message and I think

53:42

that's going to continually be an area that

53:44

requires a lot of investment. If

53:46

you think about like handling the most

53:48

contentious things the you have to deal

53:50

with. As. A leader of the

53:52

business. What comes to mind and what

53:55

is your like method of handling something

53:57

hard and contentious. Most. My

53:59

issues are people. I had a

54:01

joke with my head of HR that I feel like

54:03

I'm a glorified head of HR because 70 to

54:06

80% of my time is all around people. Who's

54:08

moving up and why? Who's moving sideways

54:10

and why? Who's moving down? Why is there

54:12

a lack of alignment between different teams? And

54:15

we're all kind of imperfect creatures. Like everyone

54:17

has their strengths and weaknesses and in times

54:20

of stress and tension, you see people's

54:22

weaknesses showing up. And so

54:25

a big part of my, where I spend

54:27

my time, it's all around people issues, whether

54:29

it's with my direct team or with structural

54:32

issues around people issues around comp,

54:34

people issues around like culture. We

54:37

spend a lot of time, for example, on leadership development. What

54:40

I said is one of the struggles young leaders have

54:42

is knowing how to hold people accountable. And

54:44

I tell people, if a leader is

54:46

incredibly self-aware, knows how to recruit

54:48

and knows how to hold people accountable, they

54:50

will be a fantastic leader. But those are

54:53

skills that you just don't absorb, maybe you

54:55

can learn from observation. But if you have

54:57

a program that can help people develop those

54:59

skills, that becomes incredibly powerful. So we spend

55:01

a lot of time on leadership development. So

55:03

that just scaling that middle-mentioned layer

55:05

becomes a very, very important role in terms

55:08

of the culture you create and your ability

55:10

to execute. Because at the end

55:12

of the day, I'm not really making lots of

55:14

direct decisions myself. I'm leading through others. And

55:17

ultimately, others are really driving

55:20

the business day to day. What are

55:22

your preferred tactics of

55:24

accountability, of keeping people accountable? What has

55:26

worked best for you? Again,

55:29

most people struggle with knowing how

55:31

to keep people accountable. So

55:33

we have this three-step process that we

55:36

encourage people to consider. The

55:38

first one is you need to be very,

55:40

very clear on expectations. That's the first mistake

55:42

people have. They're not very clear expectations or

55:44

expectations are very fuzzy. By definition, if you

55:46

have a fuzzy expectation, then you're

55:48

setting your person up prepared because they don't know

55:50

what good looks like. So why be very, very

55:52

clear on expectations? Two, when

55:55

they miss an expectation, the

55:57

initial approach you take is that the owners

55:59

is on you, their manager or their

56:02

leader, that you weren't clear enough on

56:04

the expectation. So they misunderstood

56:07

why that expectation was important or why the

56:09

expectation was partially met or unmet. And the

56:11

point is, is that you're not beating them

56:13

up. You're saying, you know what, I wasn't

56:15

clear. I should have done a better job,

56:17

explained the why. I should have like, so

56:19

I'll give you a simple example. Say Patrick,

56:21

you run a team and every week I

56:23

say, Patrick, I need an update from you

56:25

on what's happening. Say you're running customer service,

56:27

a success function and saying, I need an

56:29

update every Friday on what happened the week

56:31

and what trends you're seeing. And the

56:34

Friday goes by, I don't get anything from you. So I'll

56:36

come to you, say Patrick, maybe I wasn't clear on why

56:39

this is important to me. The reason this

56:41

is important to me is really gives me a picture of what's

56:43

really happening with the customers, what the

56:45

feedback is on the products, how the

56:47

buying behavior may be changing, what potential

56:49

competitive dynamics are happening, or the competitors

56:52

may be underpricing us, etc. So

56:54

Patrick, are you clear on why this is important?

56:56

Yes. Okay, I got it. Now the

56:58

third step is now to miss it again, it becomes

57:01

very easy for me to hold you accountable because

57:03

I've done steps one and two. I've made it

57:05

clear what the expectation was. First time

57:07

is missed. The onus was I made the

57:09

mistake, not you. Next time you

57:12

make the mistake, there's no place to hide. But

57:14

most people don't do step one and step

57:16

two. So then you barely get at the

57:18

end of the year, Patrick, I'm going to

57:21

give you a meets expectation. You're like, meets?

57:23

I thought I was doing a great job.

57:25

Well, you know, and then you'll be like,

57:27

well, why the hell didn't you tell me

57:29

becomes a very dysfunctional conversation, you get demoralized,

57:31

I don't feel great. And God forbid, maybe you

57:33

start thinking, maybe MongoDB is not the place for you. So

57:35

this is a thing that young leaders really

57:37

develop and young leaders know how to hold

57:40

people accountable in a constructive way. They will

57:42

have a dramatic impact in their career. What

57:45

else have you learned from Andy Grove? That just

57:47

makes me get in like an Andy Grove mindset

57:49

or something that very nice, simple, elegant way of

57:51

approaching management. Love Andy Grove. I think

57:53

he was truly one of the seminal leaders of our

57:56

industry. The best thing I've learned from

57:58

Andy was that there's only two reasons. why

58:00

people fail. One, they fail because

58:02

they didn't have the skills to do job or

58:05

two, they fail because they didn't have the will

58:07

or the drive to do the job. And you

58:09

net it out, that's the two reasons. And people

58:11

overcomplicate things and all that. So we call that

58:14

the skill-will matrix. Do they have the skill

58:16

to do the job and do they have the will? And invariably,

58:18

we find that if you ask

58:20

people on a two by two matrix to plot

58:22

people, invariably, let's say they have high will but

58:24

kind of they don't have necessarily all the

58:26

skills to job. But then say someone who

58:28

has a skill to do job suddenly is not

58:30

performing anymore. And why did

58:32

their will change? Well, maybe they felt they should

58:34

have been promoted and they did it and they

58:36

get demoralized. Maybe something's going on in their personal

58:39

life as a fact in their performance. So

58:41

that skill-will matrix is an incredibly powerful way to

58:43

assess your team and say, what gaps or problems

58:45

or issues do I have with my team if

58:48

you knock people on those two

58:50

dimensions. Anything else in the

58:52

vein of that very elegant three step process for

58:54

setting expectations? Any other tool

58:56

in the toolkit like that that you

58:58

find yourself using again and again in the

59:00

management of the business? Don't

59:02

ignore bad news. In your

59:05

house, if your dog poops on the floor,

59:07

are you going to step over and keep

59:09

walking? You're going to get your pooper scooper

59:11

and come clean it up. Similarly, like if

59:13

you see bad news, you can't just ignore

59:15

it. Your responsibility is to investigate and

59:18

really get at the root issue. And invariably, you

59:20

always find out when you ask someone, hey, after

59:22

you find someone, oh my god, I found out

59:24

so many more problems. Point is,

59:26

again, like I said, bad news travels very slowly

59:28

up the organization. So even you as a leader,

59:30

you're only seeing a tip of the iceberg. What

59:33

happens is that when that person leaves, then he started

59:35

really digging in. So there's so many other problems I

59:37

didn't see. Another potential thing

59:39

that I find is really important

59:41

is a tell that I use

59:44

is when a leader is not scared. The

59:46

biggest tell for me is losing their team.

59:48

Because again, one of the actions I have

59:50

is you can usually fool the people above

59:52

you, you can sometimes fool the people around

59:54

you, you can never fool the people below

59:56

you. Why? Because they see how effective you

59:58

are and resolve results. problems for them. They

1:00:01

see how effective you are in the decisions you

1:00:03

make. They understand the rigor and logic you're making

1:00:05

or the lack of rigor you're logic in making

1:00:07

and making decisions. So they get to see who

1:00:09

you really are, but you can kind of mask

1:00:11

them without your peers into your boss. So

1:00:14

when I first joined MongoDB, one of the first

1:00:16

things I did to assess the leadership I was

1:00:18

inheriting was to kind of meet

1:00:20

the whole leaders across the business and

1:00:23

became very clear to me who were the good leaders or

1:00:25

the bad leaders by the quality team they had and look

1:00:28

at attrition data as well as the people they were

1:00:30

hiring. The inverse of that is

1:00:32

I find A's hire A's, B's hire C's, and

1:00:34

C's hire S. So as soon as you have

1:00:36

a bad leader, all the good people leave and

1:00:38

the quality people they're recruiting is far lower than

1:00:40

the team they inherited. So those are all tells

1:00:43

about how effective a leader is. And that's usually

1:00:45

a sign that you got to go take

1:00:47

some action. Do you feel

1:00:49

like there's any major unfinished business

1:00:52

at Mongo? Oh, big time.

1:00:55

We're constantly getting pushed on product. We

1:00:58

have a very scalable platform, but we

1:01:00

have customers who are demanding even more

1:01:02

performance and scale. We have a whole

1:01:04

bunch of features that customers are asking

1:01:06

for that we need to kind of work on. We're

1:01:09

pushing ourselves on the go to market side to

1:01:11

become more efficient as we scale. Investors

1:01:13

want to see a classic rule

1:01:15

of 40 high growth with increasing

1:01:18

profitability. One of the challenges that we

1:01:20

have in our business is that we're not

1:01:22

a technology we make a centralized decision. We're

1:01:24

not like an HRIs platform, where we're standardized

1:01:26

on work day or everyone's standardized or CRM,

1:01:28

where we're standardized on Salesforce or

1:01:30

even say like a data warehouse like snowflake.

1:01:33

We have to win business application by

1:01:35

application or workload by workload. So

1:01:37

that can be a fairly expensive

1:01:40

sale cost of sales. And so how do we reduce

1:01:43

that by becoming a standard? How do we

1:01:45

create virality by getting developers to self select

1:01:47

us more quickly? So those are things we're

1:01:49

constantly trying to work on and become better

1:01:52

at. And Obviously, it's a very

1:01:54

competitive space. We're competing with the Hyperscalers, we're

1:01:56

competing with the Legacy vendors, always competing with

1:01:58

new entrants. On the

1:02:00

point of investors and how they view

1:02:02

your business, one lands that eat growth

1:02:04

always is that the sensibility of the

1:02:06

business. If you continue to

1:02:09

be successful the Prophet Boys they're that

1:02:11

invites new entrants. They wire process the

1:02:13

he that they want to come for

1:02:15

them to have to have some sort

1:02:18

of sustainable differentiation around the business. Do

1:02:20

you think about. Art. Detecting

1:02:22

that is, it's something that as you strategically

1:02:24

think about the business you're returning to over

1:02:26

and over gimmick. Where's the power in the

1:02:29

business? Where's that of sensibility? Is that an

1:02:31

active part of your strategic thinking? And if

1:02:33

so, I'm so I would love to get

1:02:35

was into the room on how you apply

1:02:38

that concept among us specifically. While.

1:02:40

I was. In general, you almost care

1:02:42

about turn red because by definition your

1:02:44

do believe this. This is an inverse

1:02:46

of your turn rate. Ceos.

1:02:48

Care about the sun and your business

1:02:50

and it becomes even more profound. Consumption

1:02:52

business and it as. A sense

1:02:55

of business you recognize a roundabout usage, some

1:02:57

awesome synthesis gives you real to my view

1:02:59

on demand and sometimes you consumption doors down

1:03:01

because not with anything you done wrong but

1:03:03

it's customers online businesses like now. Maybe they're

1:03:05

selling hundred which it's a day now the

1:03:08

some katie which is a day and is

1:03:10

not much we can do about that because

1:03:12

the consumption of our online platform has gone

1:03:14

down by twenty percent. But. Sometimes

1:03:16

you can also see hey, something's going

1:03:19

awry because. Either. The performs a

1:03:21

system is not as with should be

1:03:23

or maybe the costs going up disproportionate

1:03:25

to the uses. Amazed because it miss

1:03:27

configure their database gema maybe they've missed

1:03:29

and figured. Some. Parameters made a

1:03:32

indexes are. Optimized for the

1:03:34

things we can do to really deliver

1:03:36

a superior performance. And that's why we

1:03:38

really invest in the test for success

1:03:40

function because in a assumption business is

1:03:42

not like we sell something and move

1:03:44

away. We're engaging in the customers almost

1:03:47

on a daily. It was his weekly

1:03:49

basis to understand what's going on so

1:03:51

we care a lot about that. Beams

1:03:53

on currently databases are very sticky. The

1:03:55

ones the sticky as technologies customers on

1:03:57

use. While. We don't think that for granted.

1:04:00

Hundred. Bucks and I've seen you reference. His

1:04:02

talent is overrated by Jeff Colvin I think as

1:04:04

his name's I'm curious what you learned from that

1:04:06

book. Kind of in the same spirit of what

1:04:09

you learn from Andy Griffiths. That's.

1:04:11

Been a while since I've heard about but

1:04:13

the take away from me was that is

1:04:15

your sorrow if you raise little bit more

1:04:18

money or far better talent and your competitor

1:04:20

that has disproportionate out and. As.

1:04:22

An Athlete If you're an athlete, And.

1:04:24

You get recruited say union Then he tried

1:04:26

for like be a team and you're on

1:04:28

the beat. Him and one of you makes

1:04:31

the A T Now Sunday first. Round

1:04:35

them the getting better So chain and

1:04:37

all some of their performances increasing kristen

1:04:39

sleep so basically putting yourself in a

1:04:41

position where you're working with the best

1:04:44

people around you deliver sire performance and

1:04:46

I see that. I have a son

1:04:48

who's a division one athlete. Booth. I

1:04:50

saw that happened. has Hebrew and his

1:04:52

career his development he grew exponentially with

1:04:54

the Better Says rounded and the same

1:04:56

thing with start us the volume bastard

1:04:59

of the quality of people around you

1:05:01

and have a disproportionate impact on the

1:05:03

item. A Us. What? Do you

1:05:05

learn from Rule Us being on your board and working with

1:05:07

your business? Sequoias been historically

1:05:09

our largest investor. I really

1:05:11

admire Sequoia and roll off

1:05:13

recoveries and. I and the

1:05:15

sorority really respected Sequoia for how disciplined they

1:05:17

are. Less lot of bunch of friends out

1:05:19

there. a single very found her family and.

1:05:22

I've. Been involved in situations where investors don't

1:05:24

want to shoot the sea of because

1:05:26

of the founder because the worry about

1:05:28

the reputation impact upon themselves to you

1:05:30

to get a Ceo and they do

1:05:32

some weird things organizationally to. Preserve.

1:05:35

Their good name but in some way starting

1:05:37

the business I was respected. Sikora.

1:05:39

And how disciplined their about of these sites with

1:05:42

building a great business and working from their options

1:05:44

are want to be supportive of founders. Why?

1:05:46

Things are really respect Our rule off

1:05:48

I've been on boards were the largest shareholder

1:05:50

feels like the have to have the

1:05:52

loudest voice in the boardroom that can get

1:05:55

him low class of because sometimes. It's.

1:05:57

Other people who have more inside the nestle the Lord.

1:06:00

The best one things I really respect to with

1:06:02

Rule Off is that. Even. Though he

1:06:04

was always the largest investor in mind

1:06:06

he be he would listen very carefully

1:06:08

and when he spoke thus signal to

1:06:10

noise ratio was very very hot. And.

1:06:12

So I didn't try and use

1:06:15

his ownership percentage to kind of.

1:06:17

Found. A table. All that he would relax, understand

1:06:19

the business, And. When I joined a

1:06:21

gym me of the can be as an acquired a

1:06:23

fragile say so he was very very supportive and mixer

1:06:26

I was such a success. And are times

1:06:28

when there were some silences in the business when

1:06:30

I would ask Law for help and he would.

1:06:33

Have been a nanoseconds and so he's always been

1:06:35

there for me when I needed it and I

1:06:37

was stuck that again. Back to the point that

1:06:39

the see a job as a brave normally jobs

1:06:41

and so when you want the board to help

1:06:44

it's really helpful. What? Are you most excited

1:06:46

for next? In the business. It's

1:06:48

really this transition to a I think it's

1:06:51

gonna be a multiyear transition. How be,

1:06:53

position ourselves and navigate. This transition is gonna

1:06:55

be really, really important. As. It

1:06:57

is really exciting! And. At this is just

1:06:59

another day than the same job. day in day out

1:07:01

and get a little boring. Zebra the

1:07:04

growing as a business. One of things that

1:07:06

you see the most joy is when employees

1:07:08

some to me. And tell

1:07:10

me how grateful they are because

1:07:12

the valley the traded at monkeys

1:07:14

naval them soon either put money

1:07:16

away for their kids, By.

1:07:19

Of potential home or second home. And.

1:07:21

Has given them a certain level economic security

1:07:23

that they didn't have before. And

1:07:25

is nothing that makes me feel better than

1:07:28

to see the impact were having on our

1:07:30

employees lives. And I'll sell people Don't

1:07:32

Thumped among the be for a job Compton monkey

1:07:34

be to build a career. I draw

1:07:36

the picture where the slogan line before he dumped

1:07:38

among the Be as a black box were among

1:07:40

the Be under the slippery line leading wanted to

1:07:42

be celebrated the level as it's the My goal

1:07:45

is that. The skills you gain

1:07:47

here? Delicious you bills. On.

1:07:49

Expenses you have. Will. Save

1:07:51

who you are for the rest of your career. And

1:07:53

of we the second held. David.

1:07:55

So much fun talking. You're hear about the business

1:07:57

and although us as you've learned a did you.

1:08:00

No my traditional causing question for everybody. What's

1:08:02

the kindest thing anyone's ever done for you?

1:08:05

I. Think bleeding a me. As a share

1:08:07

with you I've always had this inner doubt

1:08:09

about am I good enough? And. As

1:08:11

make people believe in me. When.

1:08:13

Maybe I don't think I deserved it. Whether

1:08:15

it's like a Zesty Walls believes me when

1:08:17

I had no experience building fabric of the.

1:08:20

It's investors who believes in me and.

1:08:23

And investing in Mali be when the questions about

1:08:25

with mommy to be make it. Weather's.

1:08:27

People who believes in me to me and join

1:08:30

A because the. And. Trusted

1:08:32

me an ongoing on the journey. My.

1:08:34

Wife's because believe me at times, maybe

1:08:36

I didn't always deserve that believe something.

1:08:39

I'm so so restless, simple and wonderful

1:08:41

place to close. Daves think so much

1:08:43

her. Don't thank you Patrick's the great.

1:08:47

If you enjoy this episode, check out

1:08:49

join colossus.com Stereo find every episode of

1:08:51

this podcast complete with transcripts, show notes,

1:08:53

and resources to keep learning. You can

1:08:56

also sign up for our newsletter Colossus

1:08:58

Weekly where we can dance episodes to

1:09:00

the big ideas, quotations, and more as

1:09:02

well as you're the best content we

1:09:04

find. On the internet every.