HomeVideos

Why Now is the Best Time to Buy Public Software Companies

Now Playing

Why Now is the Best Time to Buy Public Software Companies

Transcript

1808 segments

0:00

My guest today is Mitchell Green, the

0:02

founder of Lead Edge Capital. When I

0:04

think about Lead Edge, I sort of think

0:05

about this giant money machine that

0:07

Mitchell and his two partners have

0:09

designed over the last 15 plus years to

0:12

make remarkably consistent investment

0:13

returns for their clients. They have all

0:16

sorts of unique aspects to the machine

0:18

that they built, whether that's their

0:19

collection of LPS, their eight-point

0:22

criteria for how they select companies,

0:24

the way they do cold calls, the way they

0:25

construct their portfolio. This is just

0:27

a totally different way of approaching

0:29

markets. They're trying to hit singles

0:31

and doubles and deliver very consistent

0:33

returns. Mitchell says it's really

0:34

important in life to be memorable.

0:36

That's just a great simple thing that

0:38

you can do. I think you'll find

0:39

listening to Mitchell today and him talk

0:41

about his entire machine and the firm

0:42

that he's built that he himself is

0:44

extremely memorable. I hope you enjoy

0:46

learning about his business.

0:55

So the first time that I heard about

0:57

lead edge capital was was the very

0:59

famous list of what companies report

1:02

starting with cash profits and then if

1:04

they don't have cash profits and you go

1:05

down this very funny list

1:06

>> hierarchy of [ __ ]

1:07

>> Yeah. And the the bottom one is the

1:10

place that's voted the best place to

1:11

work in New York City or something.

1:13

>> Absolutely.

1:14

>> Where did that list come from? Why did

1:15

you put that together? We've always

1:16

found that the best way to communicate

1:18

with, you know, our audiences, which is

1:19

entrepreneurs

1:21

and also our investor

1:27

letter about a different topic. And I

1:29

started my career cold calling companies

1:32

and that's the way we source deals. But

1:34

when you start your career talking to I

1:36

think Brian and I probably spoke to like

1:38

10,000 companies

1:41

and if you want to know it's a good

1:42

company just, you know,

1:45

call 10,000 of them. You'll figure out

1:46

really quick. It's pretty good pattern

1:48

recognition. Until like our head of PR

1:49

coms came in a few years ago. We had

1:51

actually never posted any of these

1:52

things online. We joked that we sent

1:55

this letter to some people in the VC

1:57

community. one of which is like our

1:59

buddy Andre Horowitz and they posted it

2:01

online for us. Um we just thought like

2:04

think like it's like a very simple way

2:07

like in a world where people spout off

2:09

total [ __ ] all the time and like you

2:12

see everything in DAX this is just like

2:14

a good way to distill it.

2:16

>> Talk to me about the 10,000 calls. What

2:18

did you learn calling that many

2:20

companies? You learn to be very

2:22

disciplined actually and you learn that

2:24

most things are actually just noise and

2:27

to figure out like what makes a lead

2:30

edge company and then try to ignore

2:32

everything else. You learn a lot about

2:34

like responsiveness of people and like

2:36

more I think more responsive CEOs tend

2:38

to be better CEOs. I think another thing

2:40

you learn that's really important for

2:41

young people, if you tell an

2:43

entrepreneur that you're going to

2:44

actually do something, then actually do

2:47

it. And in a I think that's actually

2:49

true of like life. Um there are so many

2:52

people that say they'll do they do

2:53

things that just like never do them. And

2:55

so if you're known as a as a firm and a

2:57

or a person that actually does what you

2:59

say you're going to do, it goes a long

3:01

way. So if you tell an entrepreneur,

3:02

hey, I know somebody at

3:05

Adobe. do you want an intro because it

3:07

looks like it would be helpful for your

3:08

business? And he says, and here she

3:10

says, I'd love to. Well, then guess

3:12

what? Follow up with that. Like, do what

3:13

you say you're going to do.

3:14

>> Can you describe what seems to me like I

3:17

would call it a machine that is Lead

3:19

Edge

3:20

>> much more than most investment firms

3:22

where a lot of great investors will tell

3:24

you there's a lot of art, there's a lot

3:26

of um, you know, everything's different.

3:28

Lead Edge feels to me like unbelievably

3:30

well constructed as a machine to produce

3:33

returns. Um I'd love you to just before

3:35

we go into all the details of the as

3:37

component aspects of the machine

3:39

describe the machine itself at a high

3:41

level before I you know I was

3:44

>> um

3:45

>> we run this place like it's a software

3:47

company um my background was at Bessemer

3:50

uh where I worked for somebody that was

3:51

extremely disciplined that was building

3:52

the code program my other partner Brian

3:55

worked at Bessemer we were the first two

3:56

cold cars and my other partner Nema

3:58

worked at Insight and I think insight

3:59

and I know you know Jeff was on recently

4:02

is is one of the best like software

4:04

investment or invest technology

4:06

investment machines on the planet. So

4:08

we've like modeled ourselves on that,

4:11

you know, to build a good investment

4:14

firm that stands the test of time. If

4:16

you want to go build the next TA

4:18

Associates or General Atlantic or, you

4:21

know, Bessemer or Sequoia, you just have

4:24

to be like extremely rigorous. And so

4:26

our number one KPI that we run this

4:30

place by is what is our gross dollar

4:33

retention for LPS? We want like 95%

4:36

gross dollar retention because the only

4:38

way you can get that is one have good

4:41

investment returns and great client

4:43

services. So how do you through long

4:46

periods of time across people that will

4:49

come and go generate like world-class

4:52

returns is you need to have like a

4:53

process and the process for us starts

4:56

with you know 18 22 to 24 year olds that

5:01

you know talk to about 9,000 companies a

5:04

year. You get those 9,000 companies like

5:06

how do you figure out which ones to work

5:08

on? So then you need this like framework

5:12

to guide these 18 people to like well

5:14

it's gonna be an interesting company

5:15

because in the investment business like

5:17

we have one asset it's time and it's

5:21

like precious and so like how do you

5:22

guide people to say no quick and so we

5:25

built this framework that we really took

5:28

from coming out of Bessemer and so like

5:30

they helped build the Bessemer 5 we took

5:32

the Bessemer 5 turned it into lead eight

5:34

and it's like drives everything we do

5:36

now when we find the company We're then

5:39

super creative. We'll buy 10% 80% LPS

5:42

out of a 20-y old fund, buy employee

5:44

secondary, you know, fund somebody's CV,

5:47

we don't care. We'll do anything.

5:48

>> If I think about the two sides being the

5:50

LPS and the companies that you invest

5:51

in, I'll come back to the eight

5:52

criteria. The LP story that you have is

5:54

also quite distinct and different. Can

5:56

you describe that in a lot of detail?

5:58

>> Sure. Our LP base is all like

6:00

world-class exeacts and entrepreneurs.

6:02

Um, I know we do have some big

6:04

institutions, but 95% of our capital is

6:06

like all these world-class execs and

6:07

entrepreneurs and

6:10

we use these LPs

6:12

throughout the entire investment life

6:14

cycle. It literally starts with

6:16

sourcing. If a company won't call us

6:17

back, we'll email our LPs. Two, let's

6:21

say it's like an automotive software

6:22

company. We'll have Rick Wagner, the

6:24

former CEO of GM, who's a longtime

6:26

investor. We will be like, will you send

6:29

them like the CEO a note? And if you're

6:32

like an automotive software CEO and the

6:33

former CEO of General Motors calls you

6:34

like they're way more likely to take an

6:36

email than like my any knucklehead email

6:37

on them or a 22-y old email in them then

6:40

for diligence we'll say hey it's like

6:42

you're a healthcare software company 25

6:45

million of revenue maybe you say like

6:47

biotech or pharmaceutical software it's

6:49

like oh I see fizer is a customer how

6:51

big is it 2 million bucks could be

6:53

bigger oh it could be 10 million I'll

6:54

meet the former CEO and then I'll call

6:56

up Ian Reed and be like hey Ian can you

7:00

talk to this company they'd love to talk

7:01

to you. By the way, can you like tell us

7:03

what you think? And then if it's super

7:04

interesting, could you like call could

7:05

you [ __ ] call Fizer and like back

7:07

channel it? And then you you might say

7:09

the entrepreneur, hey, I don't see

7:10

Biogen as a customer. Would you want to

7:11

meet the former CEO? So you call up

7:13

George, you're like, "Hey, George, I

7:14

found this company. It meets seven of

7:15

our eight criteria." Then like post

7:17

investment, we literally send emails to

7:18

our LPs. Be like, hey, you know, Toast

7:21

is looking for intros to these

7:22

restaurants. Do you know anybody? And it

7:25

turns out all these people invest in

7:26

funds and never get asked for help.

7:28

That's how we do it and how we leverage

7:31

them. But it's not actually why we did

7:32

it. It would be a lot easier to go have

7:36

20 giant institutions write you 50 to

7:38

$300 million checks versus me spending a

7:41

huge amount of my time running around

7:42

the world all the time spending time

7:44

with these people. Because if you want

7:46

95% retention, that's what you need to

7:47

do because they're your clients. The

7:49

reason we did it is because I knew that

7:52

the returns in this sector in the tech

7:54

investing sector flow to the top 10% of

7:58

funds. Like they they just do it is and

7:59

by it probably is the same in real

8:00

estate. It probably the same as

8:01

industrial buyouts. But like I knew in

8:03

the venture world that it definitely

8:05

flowed to that. And I had the pleasure

8:07

of working for one of these firms best

8:09

venture partners. So when I was starting

8:11

lead edge I was like why in God's name

8:14

is anybody gonna take my money? I could

8:16

teach him how to ski, but that isn't

8:17

going to be very helpful. But I said,

8:19

you know what? Had I been the global

8:23

head of HR at Proctor and Gamble and my

8:26

partner been the global head of HR at

8:28

Microsoft and the other one been the

8:29

head of HR at Nike. When I called

8:31

workday 80 times at Bessemer and Dave

8:34

Duffield by the end was like, I'll hire

8:36

you as a salesperson. I'm not taking

8:37

your guy's money. Um, if I had been like

8:40

a world-class HR exact, he would have

8:41

engaged with me because he would have

8:42

known that I could have introduced to

8:43

those companies. Like I have tons of

8:44

other HR exacts. I know these people in

8:47

a world that's super crowded and

8:49

undifferentiated and I think it's

8:51

exponentially the case more today even

8:54

than what it was 15 years ago. Um, it

8:57

just like differentiates us and we do

8:58

what we say we're going to do.

8:59

>> How many LPs do you have?

9:01

>> Probably like 800. 95% by number are

9:05

these executives. Yeah. If you think

9:06

about the level of returns versus the

9:08

consistency of returns, how much does

9:11

one matter versus the other for the ex

9:12

for this 95% gross retention?

9:15

>> I think consistency is more important on

9:16

a per deal basis.

9:19

We're trying to make a 2 to 5x in 3 to

9:23

seven years. That's like a 25 net IR if

9:27

you just actually map it on a curve. Put

9:29

it into a fund.

9:32

We want to generate you two to 2 and

9:34

a/4x nets with 20 net IRS. Some of those

9:38

deals aren't going to be 5xes. Some of

9:40

them might be 7xs. We try to our

9:42

downsides have been very low. We've I

9:43

think we've only lost all of our money

9:45

like in one deal ever. And that's

9:46

because of the like the the kind of

9:49

criteria we look for in a company, what

9:50

our average company looks like and the

9:52

fact that very few of our companies have

9:53

any debt on them now. So I try I'm

9:56

trying to make a two to two and a/4x net

9:58

which is more like a two and a halfx

10:00

gross.

10:02

However, if something is a really big

10:05

investment in the fund and we do not run

10:08

funds with like a 100 15 companies in

10:10

them. We have we run funds with like 20

10:12

investments in them. So if we've made

10:14

something a 7 10 12 15% position and

10:18

that goes like 8 10 12x that's how you

10:20

can 3x net a fund.

10:22

>> Yeah. And so because you rarely lose

10:25

money, does that mean you also almost

10:27

never hit some like giant grand slam?

10:29

>> Correct. We're like Cal Ripken doubles

10:31

doubles and triples. Uh yeah, we're not

10:34

uh we were not Sammy Sosa or like Mark

10:38

Magguire. It's all about um hitting

10:40

doubles and triples and and if you do

10:42

that with very little leverage in the

10:45

portfolio, 90% of our companies or 85%

10:48

of our companies are like recurring

10:49

revenue. So if you invest today and know

10:51

what revenues are in July, that's like a

10:53

pretty good way to invest. 50 60% of our

10:55

companies are like profitable

10:56

businesses. Now you you may get it wrong

10:59

like you may back the wrong team. You

11:02

may overestimate the size of the market,

11:05

but I think like 70% of the time we own

11:06

the prep. So you may get your downside

11:09

1x. Now sometimes you need to like go

11:10

cut the recut the deal with the

11:12

entrepreneur or the management team. So

11:13

you're making slightly less than that.

11:14

But if you can avoid zeros like you in

11:18

and turn those zeros into like 08 X's

11:20

or.1 X's, it massively helps return.

11:23

We'll sell like we we will out of

11:26

probably a third of our exits have been

11:27

secondaries. We will buy secondaries. We

11:29

will also sell. We constantly

11:30

underwrite. We've been referred to as

11:32

traders or like for like hedge fun guys

11:34

and we're like no no we're just trying

11:35

to actually make money because this

11:36

company is about to be a living dead and

11:38

you're going to be in this thing for the

11:39

next decade.

11:39

>> Maybe spend a minute before you go

11:40

through the buy criteria talking about

11:42

selling more. So what is the process?

11:45

>> We have an investment committee. There's

11:46

three of us. Myself, Brian, and Eman

11:47

been here all since fun one. We have a

11:49

disposition committee. Same thing. We

11:51

meet. We think a lot of firms do a

11:54

really really good job on the buy. Very

11:57

very few firms do a very good job on the

11:59

sell, like knowing when to sell,

12:01

pressuring to sell, and we would we

12:04

would tell you that the private equity

12:05

funds tend to do a much better job on

12:08

the sell than most like venture growth

12:11

guys. Um and like hedge funds if you do

12:13

invest public equities or long only

12:15

funds like you constantly can buy and

12:16

sell. The three of us meet you know one

12:18

to twice a month and just like walk

12:20

through the portfolio and just talk

12:21

about it like hey there's a round going

12:24

down in this company should we sell like

12:28

how can we try to position this company

12:30

for a sale over the next 12 months? The

12:32

fastest way to get fired at Lead Edge is

12:34

have a company and not tell us when

12:36

there's a liquidity opportunity or just

12:38

like something's about to happen before

12:39

it happens. What does the holding period

12:41

end up being on average then?

12:42

>> I bet our average holds are three and a

12:45

half to four years probably.

12:46

>> Yeah,

12:46

>> we took advantage. Everybody gets all

12:49

excited by these by our 2015, 2016,

12:52

2017, 2018 returns. Like our 15 and 18

12:55

returns look very good, but it's just

12:57

multiple expansion and we sold. That's

12:59

it. Like if you think you're going to

13:01

make a 2x in four years and you make a

13:04

4x in two years, it's amazing what it

13:07

does to to net IR, right? People forget

13:10

the reverse happened in 2021. Nobody's

13:13

20 and 21 funds. I think the venture

13:15

growth uh ecosystem gets like a bad rap,

13:20

but it's going to be every alternative

13:22

asset. Their 20 and 21 funds are going

13:25

to be awful relative to earlier funds

13:27

because you had, you know, people

13:28

thought they were going to make, you

13:30

know, a 4x in, you know, in in two years

13:33

and are instead making a 1.6x in eight

13:36

years. And so like that's going to drive

13:38

that's going to have huge impacts on the

13:39

industry.

13:40

>> Most software companies try to maximize

13:42

your time on their app to juice

13:43

engagement. Ramp does the exact

13:45

opposite. Ramp understands that no one

13:47

wants to spend hours chasing receipts,

13:48

reviewing expense reports, and checking

13:50

for policy violations. So they built

13:52

their tools to give that time back using

13:55

AI to automate 85% of expense reviews

13:57

with 99% accuracy. And since RAMP saves

14:00

companies 5%, it's no wonder that

14:02

Shopify runs on RAM, Stripe runs on

14:04

RAMP, and my business does too. To see

14:06

what happens when you eliminate the busy

14:08

work, check out ramp.com/invest.

14:11

Every investor should know about Rogo

14:13

because ROAI's platform is not just

14:15

another generic chatbot. Instead, it was

14:18

designed to support how Wall Street

14:19

bankers and investors actually work from

14:21

sourcing, diligence, and modeling to

14:23

turning analysis into deliverables. For

14:25

me, three key things differentiate Rogo.

14:27

First, it connects directly to your

14:29

systems, so it can work with your actual

14:31

data. Second, it understands your

14:32

workflows, how work really happens

14:34

across a deal or an investment. And

14:36

third, it runs end to end and produces

14:38

real outputs the way the best people do.

14:40

Auditable spreadsheets, investment

14:41

memos, diligence materials, and slide

14:43

decks that match your standards. This

14:45

all comes from the fact that ROGO is

14:46

built by finance professionals for

14:48

finance professionals. And it's already

14:50

being adopted by some of the most

14:51

demanding institutions in the world. To

14:53

learn more, visit rogo.ai/invest.

14:57

OpenAI, Cursor, Enthropic, Perplexity,

14:59

and Verscell all have something in

15:01

common. They all use Work OS. And here's

15:04

why. To achieve enterprise adoption at

15:05

scale, you have to deliver on core

15:07

capabilities like SSO, SKIM, Arbback,

15:10

and audit logs. That's where work OS

15:12

comes in. Instead of spending months

15:14

building these missionritical

15:15

capabilities yourself, you can just use

15:17

work OS APIs to gain all of them on day

15:19

zero. That's why so many of the top AI

15:21

teams you hear about already run on work

15:23

OS. Work OS is the fastest way to become

15:26

enterprise ready and stay focused on

15:28

what matters most, your product. Visit

15:30

works.com to get started. What is the uh

15:33

most interesting thing about the skill

15:35

of selling and making the transaction

15:37

happen? Like presumably it's easiest to

15:39

sell in private markets when a lot of

15:41

other people are really excited about

15:42

buying. Uh you can't just hit sell like

15:45

in public markets.

15:46

>> Correct.

15:46

>> Um yeah, maybe in like a a bad medium

15:50

good. Like there's different kinds of

15:51

outcomes that you'd be selling into. Are

15:54

most of your sales into everyone else is

15:56

excited and you're less excited?

15:57

>> It can be like everything in between.

16:00

Like if a company goes public, it's just

16:02

hit a 2 to 5x in 3 to seven years

16:04

>> and then sell

16:05

>> and then and then like so you're like

16:07

the company goes public, you're at like

16:09

a 3.3x

16:11

in 18 months or 24 months. You're like

16:14

that annihilates a 12% or 20% net IR.

16:18

It's a great company, but we constantly

16:21

are underwriting like what's a forward

16:22

net return from here. And we're like,

16:24

well, okay, we made a we made like a 3x

16:27

and 18 months. That's like an IPO. Um,

16:30

in a secondary sale, it's about

16:34

underwriting the forward IR in toast,

16:35

which is one of our biggest investments,

16:37

which we put like 12% of our fund three

16:40

into. And we'd always get crap. Our fund

16:42

three was like a $290 million fund. And

16:45

we put like 36 million bucks into it.

16:47

And before the IPO, we had sold 180

16:49

million bucks. We think we'd make like

16:50

350 to 400 in it total. People like,

16:52

"Why are you selling? You don't believe

16:53

in us." We're like, "No, no, all these

16:54

other knuckleheads like that invested

16:56

alongside us." None of them put 12% of

16:57

their fund in it. And by the way,

16:59

somebody is paying us a price in the

17:01

secondary markets that we think, you

17:03

know, is just like lunacy. We sold like

17:06

in the secondary markets like 40 or 50

17:08

bucks in toast. The stock today is like

17:11

30 bucks. We think it's cheap, but it's

17:13

just like, by the way, we sold like six

17:16

years ago. Um, and so it's a constantly

17:18

underwriting forward IRRa.

17:20

>> Okay, now I get to talk about the eight

17:22

buying criteria. Uh, I don't know if you

17:25

want to like tick them off or give us

17:27

some highlights or

17:27

>> Okay, some highlights. Uh, so there's

17:29

eight criteria. I get 10 million plus in

17:32

revenue.

17:33

Why do you have like product market fit?

17:36

Are you growing? Because we don't invest

17:38

in startups. Are you growing like 25% a

17:40

year? We generate returns through

17:42

growth. Um, we don't use leverage. you

17:44

have 70% plus gross margins. Why?

17:47

Because at the end of the day, you trade

17:49

on multiples of earnings. Revenue

17:52

multiples are just like shorthand math

17:54

for like what what it will be even more

17:56

multiples or earnings multiples when you

17:59

uh you know don't grow that fast.

18:00

There's a reason that Facebook you know

18:03

gives away like you know electronics in

18:05

the in the vending machines and Dell

18:07

charges for Cokes. just like one has 80%

18:10

gross margins and one has like 15% gross

18:12

margins and we think that just drives at

18:14

the end of the day earnings. Um are you

18:15

recurring? It's like a heck of a lot

18:17

easier to invest knowing what revenues

18:20

will be today. So I know what they'll be

18:21

in July than they are today. Um are you

18:24

capital efficient? This metric is

18:27

probably kept us out of the most

18:28

trouble. It's like our version of return

18:30

on equity. I mean I think it's like

18:32

Warren Buffett would think we're idiots.

18:33

Um, are your revenues today greater than

18:37

your historical cash burn? So, what do I

18:40

mean by that? Are you your 20 revenue?

18:43

Have you burned 80? Like, you know,

18:46

every other tech company.

18:47

>> Cumulatively. Yeah. Have you burned 80

18:49

since inception or have you burned 10

18:51

since inception? We're looking for like

18:53

this one:1 ratio. In a world where

18:55

capital is a commodity, if you can build

18:58

a business that's growing nicely while

19:00

burning less than your while burning

19:02

less than your revenues, you've got a

19:04

pretty good business. Look, we don't

19:06

invest in startups. If you invest in

19:07

startups or $2 million revenue

19:08

companies, then obviously it's harder.

19:10

Are you profitable at the bottom line?

19:12

Do you have any customer concentration?

19:13

Like I just don't want to wake up and

19:15

find out 40% of my revenues like

19:17

disappeared because some customer didn't

19:18

decide they didn't want to work with

19:19

you. I want to talk about the price

19:21

you're willing to pay for companies and

19:24

where this like how you would plot

19:26

yourself on the so much so much of this

19:28

sounds like a private equity strategy

19:30

but you mentioned toast and it's not

19:31

like it grow toast was 25 million of

19:34

revenue growing 150% a year and it was

19:38

like we paid like 500 million bucks it

19:39

was like 20 times revenue people like

19:41

that's crazy it's like not when it went

19:43

from like 10 to 25 so we just try to

19:46

build like a forward model and you're

19:47

like look you could You can pay as high

19:50

as price as you want. You just got to be

19:52

right on your exit. You got to be right

19:53

on your multip. You know, how people got

19:56

in a bunch of trouble in 20 in 2020 and

19:58

2021. I think how they're going to get

20:00

in trouble today and all this AI stuff

20:03

is they just assume the exit multiple is

20:05

20 to 25 times. That's insanity because

20:08

when your exit multiple collapses now,

20:10

so you can pay 20 or 25 times revenues

20:12

and if you're right like some of our

20:15

companies have been, then it's

20:17

fantastic. But you can also be wrong

20:19

like some of our companies have been and

20:20

you look like an idiot and I think

20:22

investing in Open AI 800 billion is a

20:23

little insane personally but like I

20:25

don't know if it goes on to do like a tr

20:27

a trillion dollars of earnings. Yeah, I

20:29

I was going to be very wrong. I I should

20:31

have invested. It's almost like

20:32

shorthander. If you're like if this

20:34

company grows and doesn't del like 18

20:39

months, am I in the money and like can I

20:41

make like a decent return for what I'm

20:42

paying? And if the answer is like oh am

20:44

I even in the money in 18 months or 20

20:46

month 24 months? Yeah, you're paying way

20:48

too high price.

20:48

>> So, so right now there's this seismic

20:50

thing. You can look at like the

20:51

constellation and the constellation

20:52

software stock price or something as

20:54

like the perfect visual indicator of

20:56

what's been going on, which is

20:57

>> like a ski slope.

20:58

>> This intense skepticism of the market

21:01

that like boring traditional high gross

21:03

margin software businesses are worth

21:05

like much at all. But I'm curious how

21:07

you process this moment where I'm sure a

21:10

lot of the companies you're looking at

21:11

are software companies that uh have a

21:15

lot of the components that make people

21:16

fearful of those similar kinds of

21:18

companies in public markets.

21:20

>> Our belief for right or wrong is that

21:24

the competitive advantage of software

21:26

company has never been about R&D. We're

21:28

not building semiconductor chips. Like

21:30

we're not it's we're not building

21:31

biotech and pharma companies. This isn't

21:33

that to build like chamber of commerce

21:35

software. You too could build this. Like

21:38

you know my mother couldn't. But like my

21:40

brother could no problem. At least an

21:42

engineer. Um so could Microsoft. Any of

21:45

our companies in our portfolio. If

21:46

Microsoft took 500 people and gave them

21:48

a month, each one of our companies could

21:51

be out of business. But they just don't

21:52

care about the chamber of commerce

21:53

market. They don't care about the price

21:55

optimization market for manufacturing

21:57

companies. um they don't care about like

21:59

the tax the tax software market for a

22:01

very specific niche product. So like the

22:03

software companies like are really about

22:04

like distribution sales and marketing

22:07

customer success client services. So

22:12

we believe that it is the incumbent's

22:14

game to lose in in software today. Um

22:18

there's a reason I'll give you a couple

22:19

examples. Workday

22:21

has like 98 or 99% gross dollar

22:24

retention. It grows like 10 10 15% a

22:27

year. Oh, it only goes 10% a year. I'm

22:29

sorry. It's like 10 billion of revenue.

22:31

Um, it only took like 20 years to get

22:33

there and it does like three billion of

22:34

free cash flow. Exxon or the hospital

22:37

system or um, Waro Pinkis or KKR or

22:42

Proctor and Gamble probably spent three

22:45

to five years like implementing the

22:46

software. If you think they're going to

22:47

like start building their own HR

22:49

software, you're on your mind. Now the

22:52

guey in how you access it is going to be

22:54

far different but actually they already

22:57

have the customer relationships and the

22:58

only reason they built it is because

23:00

Dave Delfield and Neil realized 20 years

23:02

ago that Oracle and SAP had really

23:04

crappy products but they have like

23:06

thousands of engineers that are like

23:07

trying to build the product much better

23:08

and are going to use workday versus like

23:10

Mitchell Green's cousin like vibe coding

23:12

his way uh to build workday.

23:15

At the flip side, why did Koopa get

23:18

built? And the reason that it was able

23:19

to be built is SAP bought Aribba like

23:22

and they just like left it for debt. So

23:23

they built this like big business.

23:25

They took it public and now it's been

23:27

sold to to Bravo. So what I actually

23:29

worry about to Bravo or any of these big

23:31

private equity funds if they're putting

23:33

a bunch of debt on it's not growing that

23:34

fast anymore. If they're putting a bunch

23:35

of debt on it

23:38

and then what they do is they like they

23:40

like they brag. They like oh yeah we

23:41

drive all our companies to like rule of

23:43

50 businesses. Now, do they end up

23:47

cutting a bunch of people in R&D and

23:50

sales and marketing and product that

23:52

they should have that if you were being

23:53

run by an entrepreneur with no leverage,

23:55

you would have kept and and is now I I

23:58

worry that a bunch of these private

23:59

equity owned assets that are overlevered

24:01

are ripe for disruption versus like

24:03

independent software companies that are

24:05

that are focused on growth that are

24:06

trying to innovate. And I like to remind

24:08

people that the um if you look at

24:12

e-commerce, everybody in 99 and 2000,

24:15

everybody thought every big box retailer

24:16

was going out of business. But if you

24:18

look at the top 50 largest e-commerce

24:20

companies in the United States, you

24:21

know, yes, Amazon is number one. You

24:24

know who like two through 10 are?

24:27

Walmart, Home Depot, Lowe's, Macy's,

24:30

Target. I mean, Sax is a crappy company.

24:32

Their online business is actually pretty

24:33

good. Nean Marcus, same thing. a lot of

24:36

the incumbents will win. Now again, you

24:38

know, Montgomery Ward,

24:40

Kmart, Sears, busted bust for either

24:43

like overlevered, didn't innovate. So

24:46

like for us, that's what we're

24:47

constantly thinking about.

24:48

>> Does that mean that right now feels like

24:50

an especially opportune time for your

24:52

style because entry multiples are lower?

24:54

>> I think the best riskadjusted returns

24:56

right now are in

25:01

public software names. By the way, when

25:03

you b, you know, Warren Buffet says,

25:05

"Buy when everybody, you know, is

25:06

fearful and sell when like everybody's

25:08

super excited, people hate software."

25:10

You know, when we bought a bunch of our

25:11

bite dance stock two years ago when

25:13

everybody hated China, Alibaba has

25:15

doubled off its lows and doesn't grow

25:16

and trades at 15 times earnings.

25:18

>> If you think about the uh the CV like

25:21

the very specialist type buys that

25:23

you'll do. Can you explain an example of

25:25

one of those?

25:26

>> So, we like to use like the house

25:28

analogy. You walk down the street, you

25:30

go into apartment building, you're like,

25:31

"My apartment needs to have like these

25:33

six things. You can go in the front door

25:35

and you can lead the primary round um

25:38

and put money on the balance sheet or

25:40

you can buy the whole business. You can

25:42

go in the side door and buy like an

25:44

early uh investor or early employee out,

25:46

but like maybe that's not available. So,

25:48

we'll go through the basement window

25:49

with a pickaxe and buy like a

25:51

derivative." Because if you run a

25:52

business and this can of Pepsi owns 30%

25:54

of your business and I go to the glass

25:56

that is an investor in the can of

25:57

Pepsi's fund and that like is there half

25:59

the LPS and I like literally buy that

26:01

out and you own 30% and I buy half the

26:03

fund. I just bought 15% of your company.

26:05

It's the same damn thing. It's just a

26:06

derivative. Um now do you have as much

26:08

control? No. Do you have as much

26:10

insight? No. But like you trade off

26:12

price for access. We made a big

26:15

investment in uh in Zoom. Um, so we

26:20

couldn't go into the front door. The

26:22

company didn't need money. We sure as

26:23

heck weren't buying the entire business.

26:26

Um, there was you couldn't buy

26:27

secondary. There was secondary to buy.

26:29

You couldn't buy it because Sequoia

26:30

would roll for you. They're smart.

26:32

They're not dumb. They're like, "Why

26:33

would we let these knuckleheads in?"

26:34

Like, we'll take the stock and make two

26:35

to three times our money. And the

26:37

company was one that took a long time to

26:39

get funded and like wasn't backed by

26:41

Sequoia. They wanted it. It was back for

26:42

random Chinese people and Chinese funds.

26:44

So, there was it was actually second

26:45

year by, but you couldn't because

26:46

they're over. So, we're like, "Huh, why

26:49

don't we go to this fund that like has

26:51

stock and their LPs have been in this

26:52

thing for 10 years." Like, maybe their

26:54

LPs want to sell and we can do it one of

26:56

two ways. Like, we'll just buy your

26:58

position in the fund and we'll know

26:59

exactly how much we'll know exactly how

27:01

much Zoom we have to it. Or why don't

27:03

you just create like a new vehicle? Any

27:05

LP that wants to sell, we'll step into

27:07

their shoes. Well, if you own 2% of Zoom

27:10

and half the LPs want to sell and I then

27:13

step in those shoes, I now own 1% of

27:15

Zoom. And if I say to you, listen, we

27:17

get to vote them like we own them, but

27:19

you still hold it. So if you if you

27:21

sell, you know, if the company gets an

27:22

M&A offer and you get to vote, you have

27:23

to call us day 181 of the IPO after the

27:26

lockup, you got to give us the stock. We

27:28

just we just bought um the position in a

27:30

world where LPS and GPS are desperate

27:33

for liquidity. That part of our business

27:35

is absolutely booming. And that part of

27:37

our business uh is headed by Tim Beamer,

27:40

who's one of my oper one of my partners

27:41

who was actually a Notre Dame alum as

27:42

well. If I think about the dollars

27:44

deployed I don't know last year over the

27:47

next year how much of it is direct

27:50

capital on a balance sheet secondaries

27:52

something creative like what you

27:54

>> 70% creative balance sheet

27:56

>> 70% is special sets or like secondary

27:59

>> yeah and by the way we will evaluate in

28:02

an IC a public position a control buyout

28:07

a minority deal or a special sit like it

28:10

could be you could hit four different

28:11

things in one week And literally we just

28:14

all has we underwite the same return.

28:16

But today the opportunity is in it's

28:18

only gonna we are a market draw down

28:20

away from it exploding in in value or

28:24

like exploding in stuff to do.

28:25

>> So the hard part it seems like is

28:28

finding a company that has six of the

28:30

eight criteria that you can also buy at

28:33

a multiple that you're excited about for

28:34

the forward return. What percent of

28:37

companies meet like of the 9,000 or

28:40

whatever meet like all eight criteria?

28:41

>> By the way, no correlation how it

28:43

performs either. If we do like an eight

28:44

criteria deal versus like a five

28:46

criteria deal, there's like actually no

28:47

correlation to like it was a better

28:48

deal.

28:49

>> What about if you What about like four

28:50

or three?

28:50

>> We've never looked because we um so what

28:53

we try to do is if you say it must meet

28:55

eight criteria, 9,000 companies becomes

28:57

90.

28:58

>> Okay.

28:58

>> To do five or seven deals a year, it

29:00

just doesn't work. Um, and so for us,

29:03

what we say is it just like must meet

29:05

five. That's about a 10% yield. We're

29:07

trying to get to like 900 to a set of

29:09

companies that we can then like actually

29:11

do work on. So you have 900 companies

29:14

that meet five or more criteria.

29:16

You get to

29:19

you do work on about a you do diligence

29:21

on about 150 to 175 to do five to seven

29:24

deals a year. And you're like, why not

29:26

more? I'd love to, but like we're cold

29:28

calling entrepreneurs. They're like, oh,

29:30

I'm sorry. I want to sell my business

29:31

tomorrow. Like, oh, you just happen to

29:32

call me on this day. No, the sales

29:34

cycles can be a decade. Um, and it's

29:36

about staying in touch as entrepreneur

29:38

because we're not the only ones calling

29:39

them. There's great firms like Summit or

29:41

TA or Insight or, you know, Bessemer or

29:44

Battery and like great firms. And so,

29:45

it's like, well, ask the entrepreneur,

29:47

how do they need help? Try to like tease

29:49

information out of them. Oh, you sell

29:50

into like the consumer space. You want

29:52

to meet the former CEO K Pomolive. Um,

29:55

and you're doing that to try to like

29:56

build a relationship with somebody. So

29:58

if five criteria companies don't

30:00

outperform eight criteria companies,

30:02

doesn't that imply the criteria aren't

30:04

predictive? So then why have the

30:05

criteria?

30:05

>> Because you need to set a framework for

30:08

what to focus on and what not to focus

30:10

on. That's it. Like it's just getting to

30:12

a small predictive necessary. not

30:14

predictive, but it's getting us to a

30:16

small enough pool to like it's like

30:18

knowing your strike zone is like my

30:20

partner is a big baseball fan that uses

30:22

a baseball analogy like Ted Williams

30:24

knew in the hitting zone exactly where

30:26

to swing and what is probabilities for

30:28

swinging the ball. Like yes, you can hit

30:30

a ball 2 in above home plate and it

30:33

could be a grand slam and have hit the

30:34

ball the farthest you've ever hit it,

30:36

but if you do that over an entire

30:38

career, your entire career won't be very

30:40

long. Um, and so it just enables us to

30:43

know like what pitches to swing at. Our

30:45

biggest mistakes have honestly been not

30:49

swinging at the pitches when they were

30:51

in our strike zone. And I think that's

30:52

like what we've learned over the last 15

30:54

years to get more comfortable and like

30:56

when it's in our strike zone, swing at

30:58

it.

30:59

>> How do you train these young people to

31:01

be able to get all this information to

31:03

know whether or not it's an eight-point

31:04

score or whatever out of an

31:06

entrepreneur? Like what is the art of

31:08

getting someone on the phone and then

31:09

actually getting them to tell you the

31:11

information that you need?

31:12

>> It is incredible what people will tell

31:14

you on the phone. People are like, "Wait

31:15

a second, you just like call people and

31:16

they talk. People love to talk." Um,

31:19

it's investigative journalism with

31:21

sales. We tend to hire

31:26

people that are like former athletes.

31:29

But like getting a C or a D on a test is

31:32

not your like biggest failure. dropping

31:34

the ball at like the Rose Bowl or like

31:37

not making the Olympic team, that's like

31:39

failure. And so you're looking for

31:41

people that are like insanely

31:43

persistent.

31:45

People that are really inquisitive

31:48

and and then it's just, hey,

31:53

Patrick, pretend you're toast. We're

31:55

doing work on the restaurant point of

31:57

sales system space. I read a bunch of

31:59

articles that like sounds like you're

32:01

kicking butt. Oh, by the way, I just

32:02

talked to like Square and Clover and you

32:05

know, set a couple. We'd love to talk to

32:06

you on the phone. And oh, by the way,

32:08

I'm sure you're getting bombarded by

32:09

other people, but by the way, we're

32:11

we're different than a lot of firms. A

32:13

lot of our capital comes from world

32:14

class exacts. Like, oh, by the way, one

32:16

of our LPs, the former CEO Wendy's. We'd

32:18

be happy to talk to them if you want to

32:19

meet these people. Huh? Sure. Love to

32:22

chat. By the way, we used to get to cold

32:24

call people like when when Brian and I

32:26

on email were doing this like literally

32:27

cold call people and you like you feel

32:29

like the person who calls you at 6 PM,

32:30

you know, and you know, 20 years ago,

32:33

you like slam the phone done on today.

32:35

It's like my you guys get to send emails

32:36

to people, give me a break. Uh we

32:39

actually try to now encourage some of

32:40

the analysts to start calling people.

32:42

The biggest issue is like it's hard to

32:43

get people cell phone numbers versus

32:45

like, you know, work phones.

32:46

>> Um

32:47

>> and it's just like once you get the

32:50

person on the phone, you just have to

32:51

show knowledge. That's where, by the

32:53

way, AI is incredible. It's like you

32:56

give every analyst an associate, you

32:59

give them like the power of knowledge

33:01

and you can sound super smart and you

33:02

won't get everything. It's like, hey, I

33:04

saw on LinkedIn you have like 80

33:05

employees. So, what do you like 10

33:07

million revenue, 15 million revenue? Oh,

33:10

I see like your employee cost growing

33:11

like 80% a year. What are you growing

33:13

like 150%. Not that fast like oh what

33:17

like 100%. Yeah, around there. So, it's

33:19

like it's like trying numbers

33:21

>> if you think about this machine. And so

33:22

we've got this very unique LP base. We

33:24

do, you know, 9,000 calls, 5 to seven

33:26

investments per year.

33:27

>> We just raised our seventh fund. It was

33:29

three and a half billion.

33:30

>> Okay. So three and a half billion dollar

33:31

fund. Um two to two and a half%, you

33:34

know, net IRA or net netic to your

33:37

investors. So that's kind of the

33:39

machine.

33:40

>> Where do you feel the most tempted to go

33:43

tinker on the machine for the next

33:44

decade? Like how do you hope the machine

33:47

>> improves? continuing to

33:51

as the firm gets bigger.

33:55

How do you build a culture of teaching

33:59

people to still be creative scrappy

34:01

hustlers? That's the most important

34:03

thing. Like how do we get creative and

34:05

do CVS? We were doing CVS and nobody

34:07

wanted to do CVS. We didn't know they

34:08

were called CVs. We just thought it was

34:10

paying somebody a profit share. Um it's

34:13

like continuing to innovate on that.

34:15

What's really interesting is the

34:18

secondary markets now for some of these

34:19

names are so liquid. So actually you

34:22

almost don't even have to underwrite to

34:24

this thing going public. It's like can

34:25

it just get big enough with enough

34:27

escape velocity where I can then sell

34:28

out?

34:28

>> If you think about all the investments

34:30

you've made the last 5 years or

34:31

something. How often are you like

34:32

personally excited about the company and

34:34

its product? Frankly, this is what

34:36

drives me nuts about uh a lot of people

34:38

in the venture capital ecosystem is like

34:41

they think they're actually like like

34:43

changing the world and everybody should

34:44

which they are, but they should tell

34:46

everybody about it and they're like

34:47

doing God's greatest gift to mankind.

34:49

Like we don't think that we love helping

34:50

entrepreneurs. Like that is actually

34:52

what gets me excited and gets us up in

34:54

the morning. I think gets everybody up

34:55

at Lead Edge is like helping an

34:56

entrepreneur try to bend the curve and

34:58

like make that customer intro and like

35:00

help find that great CFO um or the audit

35:03

chair or whatever. We love making

35:05

customer intros. Like that's what gets

35:06

us the most excited and I and I think we

35:08

are still actually just scratching the

35:11

surface on how we can leverage our LP.

35:12

>> How often do you control the business?

35:16

>> We are in a control position about a

35:18

third of the time.

35:19

>> And when when that's the case, how

35:21

different is that?

35:22

>> It hopefully should be no different at

35:24

all, but there's less knuckleheads

35:25

around the table. Um there's less people

35:27

around the table. And what's really

35:29

interesting is when you have a lot of

35:31

different people around the table, you

35:32

can have a lot of different competing

35:33

interests. And so it's about building

35:35

consensus. Um, and you have people that

35:38

are in at one cost. Well, that's why all

35:40

there's all these 20 and 2021s companies

35:41

haven't sold. Like there's these late

35:43

stage guys that are like, "Oh, just get

35:44

me out. I own the pref. I'll make a 1x

35:46

today or I'll make a 1x in a decade."

35:48

But we don't go into companies and say

35:54

we're replacing the entire management.

35:55

This is not what we do. When we invest

35:57

in a business and when we exit, it's

36:00

something like 75% of the time, the

36:03

person who was running the business when

36:06

we invest is still involved in the

36:08

company. It may not be running it, but

36:10

it's like back people who just want to

36:12

build awesome businesses and great

36:14

companies and like it's like listen, if

36:15

I'm not the right CEO, well then make me

36:18

the chairman of the board or make me the

36:19

chief customer officer or make me the

36:21

chief product officer, whatever. that um

36:25

that's what's really important.

36:26

>> I want to go back to the culture thing.

36:27

Yeah. The lead edge culture. I mean,

36:28

what have you learned about culture in

36:31

the many years now that you've been

36:32

doing this and and especially given this

36:33

is the thing that you're you want to

36:35

keep nurturing?

36:36

>> I didn't think I appreciated how much

36:37

culture comes from the top. Um and so

36:41

like follow-ups, send handwritten thank

36:44

you notes. I've sent handwritten thank

36:45

you notes to everybody I meet. Almost

36:47

everybody I meet like every

36:48

entrepreneur, every company. Guess guess

36:50

who also does now? The 22-y old analyst.

36:52

And by the way, we track it and report

36:54

on it. And you know, if you just treat

36:56

people the way you want to be treated,

36:58

like that just flows. We've built a

37:00

culture of like

37:03

treat LPS like you yourself want to be

37:05

treated. People appreciate that and it

37:07

comes from the top. And like the

37:09

intellectual honesty comes from my

37:10

partner Nema. A lot of the creativity

37:12

comes from my partner Brian. Now, of

37:14

course, as you get to be 85, 90 people

37:16

at a firm, we've built like a real

37:18

training program, which is a result of a

37:19

lot of work Nean and like our our COO

37:23

Suz's done and that team and the

37:24

recruiting team. We didn't have like

37:27

weekly IC meetings before like three or

37:30

four years ago. Why? Because I was the

37:31

three of us. We talk every day.

37:33

>> Um, and so it's just like building

37:35

processes in place.

37:36

>> Can you talk about this crazy one-on-one

37:37

thing you do with every employee?

37:39

>> I got the idea from Tom Barnes at Excel

37:41

Kickare. he's built a true machine in

37:43

Excel KKKR. Um

37:46

I asked him

37:48

like what's what's like something I

37:51

should do like what do you think

37:52

something you do that like really helps

37:53

the firm? He's like interview everybody

37:55

once a year. So we sit down we start

37:57

with like a survey and then you need and

38:00

then you sit down with every employee.

38:01

>> You personally do. I personally do sit

38:03

down with every other partner, every VP,

38:05

every associate, the accounting person

38:07

on the back end, every receptionist, and

38:10

be like, "What do you like about your

38:13

job?" And so first, give me everything

38:15

you do. Green, red, yellow, green you

38:18

love, red you hate. And by the way,

38:20

let's figure out what you hate and why.

38:22

And if there's things you hate, well,

38:23

then let's figure out other people that

38:24

may be able to do them or how can we

38:25

make your job easier. Okay, that's the

38:28

first bucket. Second bucket, if you were

38:30

me running lead edge, what would you

38:32

change?

38:34

Three, what's something we can do to

38:36

make your job easier?

38:39

What you learn is incredible. You get a

38:41

bunch of really good ideas every year.

38:42

It actually drives my two partners nuts

38:44

because sometimes I'm like, "That's

38:45

amazing. Do it." And then like they're

38:46

like, "Come on, we need to have build

38:47

consensus." I'm like, "No, we don't need

38:48

to build consensus on some of these

38:50

things."

38:50

>> Is there anything else that you do in

38:52

the culture that you feel carries that

38:53

much freight? being like the good person

38:56

is like just not that hard frankly. And

38:58

in a world that's insanely competitive,

39:01

if like being the nice guy gets you the

39:03

call back and being like the helpful

39:06

person, um then then do it all day long.

39:08

And then it's another really important

39:10

thing about running this place is that

39:12

like I can't be the bottle. I can't know

39:15

every LP. And so like if you're a 25

39:17

year old or 23 year old associate here

39:20

and you have to go to Seattle next

39:22

weekend for a wedding, then I'll pay

39:25

your trip if you stay on Monday and go

39:26

meet a bunch of LPs. By the way, you're

39:28

23 years old. Like 99% of firms on this

39:31

planet wouldn't put 23-y olds in front

39:33

of LPs. I'm like, if you're smart enough

39:34

to work here, you're smart enough to

39:35

meet this LP. Like, I don't care. And

39:37

people love that. The 23-year-old

39:39

associates love it, which helps us get

39:41

great people, but then also the LP loves

39:43

it, too, because then they'll be like,

39:44

"Oh, my son is your age. Like, would you

39:46

would you would you mind like talking to

39:48

him?" Or, "Hey, you went to Notre Dame?

39:50

Oh, my son's like plays lacrosse and is

39:52

like thinking of going there. Would you

39:53

talk to him?" And be like, "Oh, well,

39:54

actually, no, talk to my partner Tim."

39:56

Because he like played Notre Dame

39:57

lacrosse. You just build really real

39:59

relationships with people.

40:00

>> If you think about the average month for

40:02

you and the major slices of the pie are

40:05

time with LPs, time with companies. I'm

40:08

so curious. It's actually kind of hard

40:10

to guess what maybe there's different

40:13

buckets than those three LPS companies.

40:16

>> Internals internal.

40:17

>> That's right.

40:18

>> What What does yours look like?

40:20

>> Um and mine's by the way very different

40:21

than Brian and Es. And this is by design

40:23

and it I mean it es and flows a little

40:25

bit with fundraising obviously.

40:27

>> I probably spend

40:29

60% of my time with LPS.

40:31

>> Wow. Now again that could be getting

40:34

somebody to help a company though too or

40:36

coordinating with the team um of people

40:39

with us like hey let's figure out a way

40:41

to get into Exxon and then I would say a

40:43

third of my 25 30% of my time is

40:47

investing related which could be reading

40:49

memos helping people win deals that's

40:51

frankly how I want to help like if we

40:53

lose a deal because I didn't meet the

40:54

company like I'm not saying I can help

40:55

us win but like we got to at least put

40:56

our best foot forward and then probably

41:00

15 20% is operational

41:02

the operation stuff's come down um

41:04

because

41:06

uh we hired one of our partners Susie

41:08

who lives in Greenwich um used to be an

41:11

investment partner a few years ago she

41:12

became our COO so that's like my time

41:16

neay probably spends 90% of his time

41:17

investing 10% of his time on everything

41:19

else which is what he should do uh and

41:21

kind of like running the IC partner

41:23

Brian probably spends 60% of his time

41:26

investing and probably

41:31

2020 on LPs and operations and it's if

41:35

like each the three of us if you were to

41:37

meet the three of us it would be very

41:39

it's very clear to people that spend

41:41

time with Brian Eman and I that we like

41:43

play to our strengths and weaknesses.

41:45

>> You mentioned Tom Barnes as someone that

41:46

you've learned from.

41:47

>> Yeah.

41:48

>> If you had to like create a Rushmore of

41:50

like other investment machines that you

41:52

most respect, who is the Rushmore?

41:55

>> Insight TA and probably Excel Kat. I

41:59

think Devin, Jeff, Triplet, the guys,

42:01

uh, Liberman at Insight have just built

42:03

like a factory. It's like it's, you

42:05

know, how you know what a good software

42:06

company is, it's talked to like they

42:07

probably talk to 30,000 companies a

42:09

year. It's it's like an absolute factory

42:12

and you're trying to like it's process

42:14

and so I think they're like amazing at

42:16

it. Um, TA is the one that like

42:17

pioneered cold calling. um in you know

42:21

insights obviously stayed true to itself

42:23

like you know in 2001 they they're I

42:26

would guess Insight's growth rate in

42:27

their portfolio between 2001 and like

42:29

today is actually pretty similar. TAS

42:31

has definitely come down. Uh they're

42:33

more private equity like it's just

42:35

discipline and process like I I think I

42:38

get the sense that TA is very good at

42:39

selling too. Um, and then Excel Exc has

42:43

built like an incredible value creation

42:45

team that I think actually adds a lot of

42:46

I think there's a lot of people that

42:47

talk about value creation. They don't do

42:48

much, but I get the sense that these

42:50

guys are um just like very good at um

42:54

actually helping companies and trying to

42:56

bend the needle.

42:57

>> As your business scales up, everything

42:58

gets more complex, especially your

43:00

compliance and security needs. With so

43:02

many tools offering band-aids and

43:03

patches, it's unfortunately far too easy

43:05

for something to slip through the

43:06

cracks. Fortunately, Vanta is a powerful

43:08

tool designed to simplify and automate

43:10

your security work and deliver a single

43:12

source of truth for compliance and risk.

43:14

There's a reason that Ramp, Cursor, and

43:16

Snowflake all use Vanta. It frees them

43:18

to focus on building amazing

43:19

differentiated products, knowing that

43:21

compliance and security are under

43:23

control. Learn more at vanta.com/invest.

43:28

I know firsthand how complex the tech

43:30

stack is for asset management firms. And

43:33

seemingly every new tool and data source

43:34

makes the problem even worse, adding

43:36

more complexity, more headcount, and

43:38

more risk. Ridgeline offers a better way

43:40

forward. One unified platform that

43:42

automates away the complexity across

43:44

portfolio accounting, reconciliation,

43:46

reporting, trading, compliance, and

43:48

more, all at scale. Ridgeline is

43:50

revolutionizing investment management,

43:51

helping ambitious firms scale faster,

43:53

operate smarter, and stay ahead of the

43:55

curve. See what Ridgeline can unlock for

43:57

your firm. Schedule a demo at

43:59

ridgeline.ai.

44:00

What have we missed about what makes the

44:04

machine tick that you think is really

44:07

important?

44:08

>> I would have said that the three of us

44:09

who run the machine are all very very

44:11

different and we play to our strengths

44:14

and I don't and I don't think that

44:15

should be like underestimated. Um, and I

44:18

think that's what makes the machine like

44:20

we literally negotiate carry economics

44:23

for the three of us in like 10 minutes.

44:25

like we and like there's firms you hear

44:27

about that like get into month-long

44:29

fights like two-monthl long fights over

44:30

Carrie. We all highly respect each other

44:33

and like know what we're each really

44:35

good at. Uh I think that's the I think

44:37

that's honestly and like just a focus on

44:39

intellectual honesty that I think a lot

44:42

of firms just don't have. If you go to

44:44

our investment comm some of our

44:45

investment committee meetings especially

44:47

out we our investment committee is the

44:49

three of us but then we like everybody

44:52

everybody that's basically VPN gets to

44:53

come but if you sit in the room and and

44:56

listen to Brian and Eay and I talk about

44:58

a deal you would think the three of us

45:00

hate each other or you might think we're

45:01

Israeli um because they it was like just

45:04

like a joke in Silicon Valley that if

45:06

you listen to like Israeli board meeting

45:07

from the outside you like these people

45:08

hate each other like how do they work no

45:09

that's that's just how they talk like uh

45:11

and then like right after we have the IC

45:12

we're the buddies and so it's like no

45:14

it's like let's debate the merits of

45:16

this deal.

45:16

>> Maybe riff a little bit more on just all

45:18

the ways that you're excited and fearful

45:20

about AI both in the investment process

45:23

at Lead Edge for running lead edge the

45:25

business and for the companies that you

45:27

invest in.

45:27

>> Yeah, I'm the most fearful for what I

45:29

don't know and just like AI is going to

45:32

change the world and it's going to do it

45:33

in ways that nobody can think about just

45:35

like the internet did. I mean in 2009

45:37

999 2000 we got sat here we wouldn't

45:39

have mentioned social media. I mean it's

45:40

today it's $3 trillion of value. I'm the

45:42

most like fearful whether it comes to

45:45

companies

45:46

and processes for that. It's like what

45:48

don't we know like which is what are we

45:50

missing? Um what am I the most excited

45:53

about for us? Like AI in the long term

45:57

will create the biggest productivity

45:58

game of the last you know 7500 years.

46:01

Don't know if it'll be like electricity

46:02

but like it'll be pretty damn close.

46:03

That's really exciting. like people and

46:05

but like it's not going to be like like

46:07

don't people get too excited about oh

46:08

we're going to go like build the next

46:09

piece of workday or we're going to go

46:11

build like better call center software

46:12

this stuff is going to like you're going

46:13

to see industries that we're not even

46:15

thinking about how to add even thinking

46:17

about what's going to like be possible

46:19

is going to happen that's like really

46:20

exciting it's going to be the age of

46:22

entrepreneurism and like people are

46:24

going to be able to build awesome

46:25

businesses what I worry about whether

46:27

it's internally at lead edge or outside

46:30

at our portfolio companies is do we have

46:32

the right people in place so that we

46:34

don't get disrupted and like cuz like

46:37

look it's you constantly want you want

46:39

to like I I joke you want to hire a

46:40

bunch of young people and these young

46:41

people but people worried about the

46:42

young people aren't going be able to

46:43

find jobs it's like the young people are

46:44

the ones that's going to figure out AI

46:45

more than the 60-year-old or 55-year-old

46:47

and so it's do we we actually rank all

46:50

we take all over our portfolio companies

46:52

and we're saying like okay like what's

46:54

your like AI readiness score and then

46:57

it's okay this company's like really

46:59

high this company's pretty low huh we

47:02

should like connect those entrepreneurs

47:04

together to figure out what they're

47:05

doing.

47:06

>> What goes into that score?

47:07

>> What's your data look like? Is it

47:09

structured in a way that you're going to

47:10

be able to leverage AI? Um, are you

47:12

iterating like how many new AI products

47:14

have you come out with? What's your AI

47:15

revenues on new products? You know, have

47:18

how much more product releases are you

47:21

able to release? It's not did your

47:23

engineering come stay flat or go down.

47:24

We actually I I for one strongly believe

47:27

that if you think in 2020 if your budget

47:29

in 2024 for 2026 was to have 150

47:32

software engineers, you should still

47:33

have 150 software engineers because

47:35

those software engineers can be like

47:36

exponentially more productive and they

47:39

can then create more products that your

47:41

sales team can then go sell.

47:43

>> Who do you compete with?

47:44

>> We would bid against Insight, FTV, JMI,

47:48

Battery, Bessemer's late when they do

47:50

late when they do like bootstrapish type

47:52

stuff. Um, okay. But sometimes we

47:55

compete against mech and IVP and like

47:57

but you like rocket ship companies in

47:59

Silicon Valley are freaking awesome.

48:00

Like I was not pay 100 times revenues

48:02

for them.

48:05

Uh, that's the that's the problem right

48:06

now. There's like too much money. Matt

48:08

Kohler said it best. It's like they back

48:10

these giant internet companies when

48:12

distribution was loose and capital was

48:14

tight. It's like the reverse happened.

48:16

So like capital's everywhere but like

48:18

four companies control distribution. So

48:19

like good luck going to build a giant

48:20

internet company. Um and right now

48:23

there's just like too much money chasing

48:25

you know at least in Silicon Valley do

48:27

few great things. So expand on that like

48:29

like decompose and expand on that a

48:31

little bit in so I guess the question is

48:33

like your view on the state of markets

48:35

and technology markets in general

48:37

>> overhyped over frothd um

48:41

and I believe this AI capex bubble will

48:44

end badly

48:46

uh in a way I just think people it's

48:47

like the telecom bubble all over again

48:49

and it will be it will be very

48:51

interesting if Apple may have been maybe

48:53

look like the really smart one in all

48:55

this at the end of the day uh we've seen

48:56

what they're I think people are just

48:57

going overspend. I think I'm convinced

48:59

that people invest in all these AI

49:00

companies, all these VCs, like have to

49:02

portray the view that software is dying,

49:05

is going to be dead because they have to

49:06

justify how much money they're going to

49:08

spend. Like if you if you start to run

49:10

these assumptions on like how much money

49:12

is going into these companies and what

49:14

that means for how much earnings you

49:15

have to drive and what that means for

49:17

like how much power you need to

49:18

generate. Like it just doesn't where are

49:20

the nuclear power plants coming up and

49:21

it like just doesn't work. Um but that

49:24

presents the opportunity. That's when

49:25

you're going to buy it. That's when

49:26

you're going to buy these companies. The

49:27

counterargument would be in telecom, you

49:30

know, it was all dark fiber. In AI, it's

49:32

all burning GPUs. And yes, the capex is

49:36

crazy, but we it's still we everything

49:40

still feels mega under supplied. And I'm

49:43

just curious how you think about Yeah.

49:45

when the opportunities will present

49:47

itself for an investor. I think um look

49:49

our fundament my fundamental belief is

49:52

that the models will commoditize

49:55

and that companies like Google have a

49:58

and Facebook and Amazon and Apple have a

50:01

competitive cost advantage. Amazon

50:02

companies like Amazon and Microsoft and

50:04

Google have more data to train a model

50:06

than than these new model companies will

50:08

ever have. If and then oh by the way uh

50:12

if you are all these like Chinese models

50:13

or European models a bunch of these

50:16

things cost a fraction of the cost to

50:18

run and so like and you can run them

50:20

locally and especially if your countries

50:22

company's outside the US like why would

50:24

you pay that amount for open AI tokens

50:26

or fantic tokens when you can just run

50:27

deepseeek or one of these other 10

50:29

models and so like I think we worry the

50:31

most about modelization. I have no clue

50:35

when this will like stop. It will

50:37

probably go longer than people think. In

50:39

99 and 2000, people also thought we were

50:41

in a bubble. They also think people

50:42

think we're in a bubble now and it will

50:44

just like stop. Is it one of these

50:45

monster IPOs happening that um you know,

50:50

and then it just doesn't go like people

50:51

think it does? You know, I think this

50:53

anthropic round was kind of like an IPO.

50:55

We're trying to hit doubles and triples.

50:57

A lot of these companies we struggle

50:58

with like they're either going to be 200

51:00

x's or 100 x's or zeros. Like it's just

51:02

that that's a str that's a struggle for

51:04

us. What kind of company in the AI like

51:07

center of the heat map? I know you're

51:09

probably not investing in any of them,

51:10

but because of the multiples or

51:12

whatever, what kinds of companies are

51:14

the most interesting to you? I think

51:15

it's like fascinating some of the stuff

51:17

that's being done in infrastructure

51:19

software like um and actually that like

51:22

agents appear to consume more resources

51:24

and actually people and so like the some

51:27

of these consumptionbased models like

51:29

the growth of companies like by dumb

51:31

luck we were very early investors in

51:32

click house u which a database company

51:35

we were early investors in graphana labs

51:36

infrastructure company that competes

51:38

with like data do data do like 29 like

51:40

high 20s 30% a year at scale um like

51:43

it's those types of companies I think we

51:44

find super interesting are I find them

51:46

fascinating. It's I really struggle with

51:48

the valuations but like the the growth

51:50

rates are like we've never seen and with

51:51

with very good economics. You see how

51:54

much money a company like Click House

51:56

has raised like what they've burned is

51:58

like

52:00

very little compared to what you might

52:02

otherwise think.

52:03

>> What do you think is the most surprising

52:04

thing about you? like like you have a

52:07

good sense of you from how you operate,

52:10

persistence, enthusiasm, energy, uh

52:13

process.

52:15

>> What do you think if I spent 10 hours

52:16

with you, I would be most surprised

52:18

about?

52:18

>> How like so probably how driven I am and

52:22

how much I like truly love what I do and

52:24

like I just put my like heart and soul

52:26

into everything I do. Whether it's like

52:27

racing cars, which I race cars

52:28

competitively, I was a national ranked

52:30

ski racer, or how I run the edge, like I

52:32

probably sleep like 5 hours a night,

52:34

four hours a night. It's cuz I love what

52:35

I do. I absolutely like just I'm

52:37

insanely competitive and and I think

52:40

that if you spent 10 hours with me,

52:41

you'd be like, "Oh my god, this guy is

52:42

the most persistent competitive person

52:45

we've ever I've ever met."

52:47

>> Were you born that way?

52:48

>> Yeah, I think I was born that way.

52:49

>> Was it enhanced through formative early

52:51

experience?

52:51

>> Ski racing. Ski skiing growing up as a

52:54

kid. Ski racing 100%.

52:55

>> Can you make that tangible for us? Like

52:57

what was it like?

52:58

>> Process like do these things and you'll

53:01

get better. do these things on video in

53:03

a GS course and constantly analyze video

53:05

and do these things the next run and

53:06

change this and like you fell get up and

53:08

go do it 10 more times. I grew up on a

53:10

ski hill that was 500 feet. I mean

53:11

Lindsay Vaughn, one of the best skiers

53:12

in the world, she grew up skiing on 500

53:14

feet buck hill in Minnesota and doing

53:17

laps like from 400 p.m. to 10 p.m. at

53:19

night. Like just repetitive like

53:21

Michaela Shiffron who's one of the best

53:23

female skiers in the world like views it

53:25

as her time on snow is like limited. So

53:29

like when you get off the chairlift like

53:31

constantly like everything is a drill

53:33

like just constantly be trying to

53:35

improve. I think that's at lead edge and

53:38

and like what you would find in me. It's

53:40

like constantly trying to improve. I

53:41

what what would surprised me the most

53:43

actually if you had to say like huh you

53:45

started the firm 15 20 years ago like I

53:47

think I've been able to recruit and

53:51

maintain

53:53

and motivate and build a really good

53:55

team. I would very good to pick really

53:58

good partners and that treat other

54:00

people really well and that like you

54:01

know feeds on itself.

54:02

>> Is there anything else from skiing I'm

54:04

not a skier that you find visceral and

54:07

helpful as an analogy for how to do

54:10

things elsewhere other than reps and

54:12

practice?

54:13

>> When I asked the guy Scott Booth who ran

54:16

Eastern, I asked him why he hired me.

54:19

He said to me, and this was early08, he

54:22

said to me, because when things get

54:24

scary, you're going to want to buy. And

54:27

I didn't know what he meant because he's

54:29

like, you go on the hill at 80 miles an

54:30

hour. Like, this isn't scary. Like, this

54:32

is like nothing. You're like, you can

54:33

make a decision going down the hill at

54:35

80 mph and like what to do and what not

54:36

to do and how not to fall and fall

54:38

whatever. In the fall of the happened, I

54:41

was like, this isn't scary. Let's buy

54:42

and like it's eventually going to go up.

54:44

ski racing

54:47

helped me really understand like a very

54:50

fine line in risk adjusted and like risk

54:52

return behavior. I just think like being

54:54

an athlete, whether you play basketball,

54:57

whether you play hockey, whether you

54:59

play golf, like I think athletes just

55:02

have a work ethic and can un like if

55:05

you're trying to find it in young people

55:06

and like have a drive like there are

55:10

athletes that have incredible

55:13

athleticism

55:14

but also have incredible work ethic like

55:16

Michael Jordan. Those are the best of

55:18

the best.

55:19

Then you have people like Steve Kerr who

55:23

are like not very good athletically but

55:25

had a work ethic of Michael Jordan like

55:28

they could be good but then you have

55:30

wasted talent which is like Zan Rodman

55:32

of the world where like they were

55:33

amazing ath athletes but they like

55:35

didn't have a drive and I think the same

55:38

can apply to investing. Why did you

55:40

choose to start the firm? Because you

55:41

were quite young when you did it. And

55:43

what how how could you translate that

55:45

experience into advice for someone

55:47

listening that is thinking about

55:49

starting a fund to decide whether or not

55:50

they should

55:50

>> just go do it. If you want to be an

55:51

entrepreneur, I I can't. My partner

55:53

Brian is like, "The reason you started a

55:54

firm is because nobody was going to like

55:55

hire your ass." I've always wanted to be

55:57

an entrepreneur and be like really

55:58

really successful. It's always driven me

56:00

and like I always wanted to be by like

56:02

you know I just just was solely focused

56:04

on it and you know like if you want to

56:07

generate generational wealth or build

56:10

something like you need to be an

56:11

entrepreneur like yes if we build

56:14

Blackstone everybody who's here will

56:16

make an insane amount of money because

56:17

it was 90 people. One of my partners

56:19

Zach is very young I mean he's like 30

56:21

years old and he's a partner because he

56:23

joined here and he took a bet when the

56:26

firm was tiny. I just encourage people

56:28

if you want to do it like your own way,

56:31

there's no better time than now. What

56:34

are you waiting for? Like I actually

56:35

think it's easier to leave when you're

56:36

27, 25,

56:38

30, then when you're 45 and have three

56:40

kids. I had I had nothing to lose if it

56:42

failed. Like I was going to just go work

56:44

eventually. I guess work

56:45

>> once you made lots of money. Do you

56:47

still care?

56:48

>> 100%.

56:48

>> Why?

56:49

>> Keep score every day.

56:50

>> Because of score. This is gorgeous

56:52

because like I want to win like like you

56:54

know some of like people like Ken

56:56

Griffin and Steve Cohen are like mentors

56:57

to LPs of ours like those those guys

57:00

have built like it's incredible how hard

57:02

those people work like now again maybe

57:03

these are NF2 people but like or if you

57:06

look at some of these like tech

57:06

entrepreneurs that have like an Elon

57:08

Musk or Alex Karp from Palanteer or Matt

57:11

Prince from you know Cloudflare or like

57:13

George Curts from Crowdstrike like these

57:14

people are incredibly driven like

57:16

hardworking people that like live and

57:18

breathe what they do and so yeah I mean

57:19

people keep

57:21

But but I have like it's not work for

57:22

me. This is fun. I travel constantly and

57:26

like to meet companies, to meet LPs, to

57:28

meet entrepreneurs, to like meet

57:30

bankers, like people are like your

57:31

schedule like tell people my schedule

57:33

and they like cry. I'm like oh no that's

57:35

it's not work. It's fun.

57:36

>> It's pretty amazing what you've built.

57:37

Uh very unique model. Incredibly fun how

57:40

willing you are to just walk us through

57:41

it all. I had so much fun doing this.

57:43

When I do these interviews, I ask

57:44

everyone the same closing question.

57:46

What's the kindest thing that anyone's

57:47

ever done for you? Pete Wilmont,

57:51

he's passed away, was the former

57:55

um CEO of FedEx and he was a Williams

57:57

alum. I started a company in college and

58:00

he was like the first person that ever

58:01

believed me. I was like, 19 years old

58:03

and he became an investor with us and

58:06

the company completely failed and he

58:09

probably when I was trying to get my

58:10

first jobs and when he got my job at

58:12

Bassimer, he was my reference and he

58:14

basically told the person they were

58:15

insane if they didn't hire me cuz I was

58:16

the most persistent person he ever met.

58:18

>> I learned so much today about building

58:20

something unique. Thanks so much for

58:21

>> Thanks so much for having me on.

58:26

>> Most software companies try to maximize

58:28

your time on their app to juice

58:29

engagement. RAMP does the exact

58:31

opposite. RAMP understands that no one

58:33

wants to spend hours chasing receipts,

58:35

reviewing expense reports, and checking

58:37

for policy violations. So, they built

58:39

their tools to give that time back,

58:41

using AI to automate 85% of expense

58:43

reviews with 99% accuracy. And since

58:46

Ramp saves companies 5%, it's no wonder

58:48

that Shopify runs on RAM, Stripe runs on

58:51

RAM, and my business does, too. To see

58:53

what happens when you eliminate the busy

58:54

work, check out ramp.com/invest.

58:57

As your business grows, Vanta scales

58:58

with you, automating compliance and

59:00

giving you a single source of truth for

59:02

security and risk. Learn more at

59:04

vanta.com/invest.

59:05

Ridgeline is redefining asset management

59:07

technology as a true partner, not just a

59:09

software vendor. They've helped firms 5x

59:12

and scale, enabling faster growth,

59:14

smarter operations, and a competitive

59:15

edge. Visit ridgelineapps.com

59:18

to see what they can unlock for your

59:19

firm. OpenAI, Cursor, Enthropic,

59:21

Perplexity, and Verscell all have

59:23

something in common. They all use work

59:25

OS. And here's why. To achieve

59:27

enterprise adoption at scale, you have

59:28

to deliver on core capabilities like

59:30

SSO, skim, arbback, and audit logs.

59:33

That's where work OS comes in. Instead

59:35

of spending months building these

59:36

missionritical capabilities yourself,

59:38

you can just use work OS APIs to gain

59:40

all of them on day zero. That's why so

59:43

many of the top AI teams you hear about

59:45

already run on work OS. Work OS is the

59:47

fastest way to become enterprise ready

59:49

and stay focused on what matters most,

59:51

your product. Visit works.com to get

59:53

started. Every investor should know

59:55

about Rogo because Rogo Aai's platform

59:57

is not just another generic chatbot.

59:59

Instead, it was designed to support how

60:01

Wall Street bankers and investors

60:03

actually work. From sourcing, diligence,

60:04

and modeling to turning analysis into

60:06

deliverables. For me, three key things

60:08

differentiate Robo. First, it connects

60:11

directly to your systems so it can work

60:12

with your actual data. Second, it

60:14

understands your workflows, how work

60:16

really happens across a deal or an

60:17

investment. And third, it runs end to

60:19

end and produces real outputs the way

60:21

the best people do. auditable

60:23

spreadsheets, investment memos,

60:24

diligence materials, and slide decks

60:26

that match your standards. This all

60:27

comes from the fact that ROGO is built

60:29

by finance professionals for finance

60:31

professionals, and it's already being

60:32

adopted by some of the most demanding

60:34

institutions in the world. To learn

60:36

more, visit rogo.ai/invest. AI/ Invest

Interactive Summary

Mitchell Green, founder of Lead Edge Capital, discusses the unique investment "machine" he has built over 15 years. The firm differentiates itself through a base of over 800 LPs who are former executives and entrepreneurs used actively for sourcing and diligence. Green details their rigorous eight-point investment criteria, which focuses on capital efficiency, recurring revenue, and consistent returns over high-risk "grand slams." He also explores the firm's creative approach to secondary markets, the importance of a disciplined exit strategy, and how his background in competitive ski racing instilled the persistence and process-oriented mindset necessary to build a successful firm from a young age.

Suggested questions

6 ready-made prompts