How to raise a series A in 2026 | TechCrunch Disrupt 2025

everyone and thank you so much for

coming today. I'm super excited to help

kick off disrupt with this fun panel on

how to raise a series A. I'm Dominic

Madori Davis, a reporter here at

Techrunch and I'm joined here today by

Thomas Crane, a managing director at

Insight Partners, Katie Stanton, the

founder and general partner at Moxy

Ventures, and Sanjene Zeb, a general

partner at GB. We will be doing audience

questions, so please start thinking

about what you want to ask so near the

end we can answer them. Um but before we

dive in, I will just give everyone just

a brief moment to further introduce

themselves and their work.

>> Would you like to begin?

>> Sure. Yeah. Hey everyone, Thomas Crane,

managing director at Insight Partners,

New York-based fund, kind of multi-stage

in terms of our focus just on growth

software primarily uh in terms of uh

markets and I've been with the firm for

13 years. Actually started as a summer

intern. Uh so it's been an interesting

journey and I've seen the firm grow a

lot over those years. Hey everyone, my

name is Katie Stanton. I'm the founder

and GP of Moxy Ventures. We're an early

stage uh preede and seed fund. We talk

about software solutions to hard

problems that help a lot of people. Um

we are former operators. My background

is as a PM and uh bisdev person at

Yahoo, Google, Twitter, and color. And

then my partner Alex Rudder was head of

engineering at Twitter. And Ashwin um

and Prateique who who I think may be in

the audience um they're former engineers

and or former founders. So excited to be

here today.

>> Uh I'm singing Zeb. I'm a general

partner at Google Ventures out on our

west coast office. We're a multi-global,

multi-reional fund, multi-stage as well.

Uh we're the independent venture arm of

Alphabet. So that means we get to invest

in a bunch of cool companies that have

nothing to do with Google. For us,

that's like Zipline, Robin Hood, Stripe.

And we also get to invest in products

that compete with Google like Uber and

Slack. I'm on the boards of Verscell, a

AI company called Harvey, which is AI

for lawyers, and Open Evidence, which is

AI for doctors.

>> All right, let's dive in. It seems like

so much has and hasn't changed with what

it takes to raise a series A in the last

few years, especially with, you know,

the AI companies getting so much money.

Um, my first question really for all of

you is, what is the biggest change

you've noticed in what it takes to raise

a series A today? Um, Thomas, would you

like to start?

>> Sure. Look, I mean the there's no doubt

these are big markets there. There's a

lot of white space that's being taken

that, you know, for the most part we're

not seeing it's a displacement of SAS.

It's actually kind of new white space

that can be addressed in a way that

these workflows just weren't possible

before LLM. So, a little bit of just

trying to understand where, you know,

where the problem space is that these

companies are addressing and

understanding why that's not necessarily

going to be uh an adoption cycle that is

inhibited by um kind of like traditional

sales and go to market. It's more of a a

true bottoms up type of adoption wave.

So, you know, it is marrying that value

prop, that whites space and that go to

market in a sort of set of ingredients

that we've never really seen before in

kind of this wave of LLM.

>> I think for us, one of the things that

we're observing is that it has never

been easier to start a company and it

has never been harder to build something

that is defensible and something that's

really durable. And it feels like so

much of you know the builders right now

it's like you're building on quicksand

like things are moving just so fast and

when we see a lot of these deals we're

like wow that's really interesting but

like can open AAI do this in the next

release um so you know increasingly

while things are moving really really

fast I think from a VC perspective and

investor perspective we sometimes have

to kind of pause and really think

through that there are so many of these

really interesting AI companies out

there but are there real big really big

AI businesses out there and how do we

make sure that we're betting on, you

know, those teams that can really build

something that is defensible and

durable.

>> Yeah, look, I think for us, um, we have

a lot of capital. We have a big fund

like Thomas. Um,

and we've come at the AI stuff with a

ton of enthusiasm. So, I think we lean

into our series A's. Um, we're pretty

excited and and been deploying capital

pretty rapidly. I think one of the

repercussions of the downturn in 2022

though that we ask ourselves is, you

know, not every company needs to blit

scale to success, right? They don't need

to raise hundreds of millions of

dollars. And and so the thing I think we

push the most on is, hey, if everything

can go right, can this company be truly

truly massive? Right? We see that for

example with Harvey. you know, they're

past a hundred million of AR. They're

gonna triple this year, right? Um, and

that is a a business that, you know, has

is going to be very very large. And so,

we push on that a lot. You know, we

we'll sit in the room with our founders

and and actually say like, you know,

does this company need round after

successive round of funding? Like, is it

an appropriate venturebacked business?

Venture is a expensive way to finance

your company.

Have series A rounds gotten bigger in

the past few years?

>> I mean, go ahead.

>> I there was a Carter study recently and

I think the data there was that the

number of rounds have at least in the

first half of this year have actually

the count has gone down about 18% and

the sizes have actually gone down 23%.

But what's interesting is that the

valuations have actually netted up. I

mean it depends obviously like the AI

companies are raising up very high

valuations but I think what that means

is that at series A and you guys are the

series A investors not me but at series

A they're getting pickier you know that

there there there are just so many VCs

out there's so many cap so much capital

out there are there really enough of

these high-erforming high growth

sustainable durable companies that are

worth betting on and so those valuations

and those deals tend to get marked up

quite high And to Sin point, Sangin's

point, a lot of uh the bigger firms

including ourselves are have gone

earlier uh just by virtue of if you look

at I think the average is like an 8x

increase between series A and series B

valuation with eight months of data on

these kind of AI high-f flyers and then

it's another 8x increase after that or

at least four to 5x. So you have to go

earlier and then that of course creates

the scarcity value that uh ultimately

drives the round sizes up.

Yeah, we did a an analysis of the AI

companies we wish we had been investors

in and um at the end of last year the

series A's were still in the 20 to30 $30

million range. Those have ballooned up.

Now they're closer to 30 to 40. But the

bigger jump was at the series B because

once you saw some sign of inflection by

the B, those rounds went from 20 to 40

to now 50 to 70 million. you know, we've

written $50 million checks into series

B's, which is like pretty novel for us.

And so, um, the time for a new round is

accelerating and and the rounds are

getting much much bigger. I mean, that

extends even further at the series C

now.

>> Is that good or bad that they're getting

so big?

>> Well, I mean, if you look at capital and

to Singin's point, it's not necessarily

a good moat. uh and it's been proven

that capital I think if you look at some

of the case studies of the very big

firms that tried to use capital just as

uh sort of a a driver of mode in these

companies it didn't play out universally

so well and so look it from the

founders's perspective if you can raise

it okay I understand the rationale but

it's going to set the bar high and you

always have to be thinking about okay if

you're taking an investor dollar at this

valuation their expectation especially

at series A is at least 5x or more. And

then that's going to of course put some

artificial constraints in terms of how

you orient the company and ultimately

the strategic outlook for the business.

>> What do you all look for to know when a

company is ready for a series A? Like

what are you what do you judge them by?

For

>> for us, I mean, we actually have a a

formula because we went back and looked

at some of the series A's and that we

were happy we did and those that we were

less happy we did. And I think what uh

really stood out to us is at that stage,

you know, people talk about, okay, you

want to see product market fit, but what

does that actually look like from an

analytical perspective? And it's pretty

simple. It's just quarter over quarter

or in some cases month over month

sequential increase in new bookings or

new logo acquisition. Just something

that you're growing through just kind of

at this stage that there should be

enough pent-up demand and enough market

space that every quarter should be your

best quarter. And that that sequence

should be happening, you know,

consistently uh and sequentially.

>> Yeah. What I would add to that, I mean,

obviously product market fit, but the

number one thing and the the big word

for us is just velocity. Um we're in a

company, and this may get spicy. Um but,

uh we're in a company called Spellbook,

which is another AI for lawyers product,

which is growing fast, maybe a little

bit faster than um Harve. No, I'm

kidding. Um but they um but they're an

awesome team. And when we invested, we

led their seed round. And when they were

ready for their series A, it was all

about velocity. The team was growing or

not the team, but the product was

growing. Um, revenue was growing, the

number of customers was were growing so

quickly that we knew that they were

ready for their series A and that has

only continued throughout their

fundrais. So for the founders in the

room like really, you know, you are

transitioning from seed to A. Seed is

all about vision. Your series A is all

about velocity. Can you prove that you

can repeatedly sell? Can you prove that

you can repeatedly grow in a big and

growing market?

>> Yeah, at the A I think it's two things

for me at least personally. Um, one is I

really do sit with the founder to say,

hey, look, uh, your end goal at all of

this, right, from here to one day

hopefully your public very large

business is to own as much of your

company as possible. And it's not worth

even taking this money unless you think

it can be a really big business, right?

Most companies should not venture scale.

They should not take hundreds of

millions of dollars. Like you know, most

businesses can go 20 to 50% forever

burning very little cash and you will

own a ton of your business. So the first

thing I do is like try to convince them

not to take my money or anyone's money,

right? Like build your business in a

normal way. I think blitz scaling is

like very inappropriate for most

companies. Um the second thing is if I

can't convince them of that is like

really try to understand like some

magical insight intowards like hey you

know prove to me that this market is way

bigger than than even I realize right

like you think of something like stripe

I think people were underestimated the

size of that business and I think the

best founders can articulate why to you

it's like so much larger than you

realize. Um, and the last thing I'll say

which has been great is a lot of our

seed companies, a lot of our series A's

companies,

you know, those companies like worst

case have been aqua hired to our bigger

companies. We just had that with open

evidence. They aqua hired a seed deal of

mine and that has worked out great,

right? The founders are very happy

there. And then for the company, you

know, having that founder energy and

that founder speed back into parts of

the business have been awesome. And so I

I do think we're operating in a world

for these early stage founders, like if

they're truly special with like very

limited downside.

>> What is something that when it comes to

a founder pitching you guys, what is

something that kind of gives you the

ick? Like what are the red flags that

you look for when a founder is pitching?

I mean, look, I I think we we see it

all. There's a little bit of that, oh,

the name dropping, a little bit of

trying to play the round off of people

maximizing optionality. I think at some

point this is you're going into a

marriage. It's actually even more more

than a marriage because you can't get

divorced. So, uh, you really have to

feel like there's trust and relationship

and rapport and that you can have hard

conversations and that, you know, you

can still you can argue and still come

back together and work through a

solution. So, if it feels like it's this

is purely a transactional sort of

process, that to me is just a huge

turnoff.

>> Yeah, totally. Like I mean obviously

like just don't lie. Like you find out

and you know to your you know good

example we think about this a lot too.

It's like if you're dating someone

you're like I really don't want any kids

and then you get married you're like yep

we're having five kids and like that

just doesn't work out great. So you know

just be really honest be transparent. Um

you know you are in this for the long

haul. And one of the things we tell a

lot of founders too and it goes you know

both ways that you're obviously doing

reference checks on your VCs. Um, you

should always reference reference check

VCs with other founders and especially

with founders who have failed because

it's really easy to have something great

to say when things are awesome. Um, what

do people say when things are really

tough? That's when real true character

is revealed. So um, so just be as

transparent um, and long-term thinking

as you possibly can.

>> Yeah, I um have the fortune and

misfortune to see companies get very big

and then plateau at different points for

different reasons.

And so trying to assess from the founder

like what is the underlying thing that

is propelling you to do this and is that

sustainable? I don't fault anyone for

you know you've done some secondary all

of a sudden you're very wealthy right

does it change motivation does it change

drive you know we've seen that and so

it's spending a lot of time with the

founder be like understanding their

psychology right like will that maniacal

drive to build a very big company change

at any point um and so I think the more

more honest they are like the better it

is and easier it is to sign up for that

journey with Because as Thomas mentioned

like you know the truth is any one of us

we can't do beyond a certain number of

deals. We can't invest the amount of

time that is appropriate and so that

that is a high bar

>> and you end up spending more time with

the ones that are challenged. I mean,

I'd love to spend time with the winners

because it's great. You show up, they

hit their numbers, you know, things are

good, but it's the ones that really, and

to your point, Katie, you know, spending

time with uh or getting the references

on the situations that didn't go well

because that's really when you see the

investor true colors.

>> And this is something I'm just curious

about because AI companies, they grow so

fast and technically those growth rates

might not apply to every industry. And

this is kind of a niche reference, but

it reminds me of when the artist Hoy was

saying that like her record label was

judging her by Taylor Swift metrics, but

Taylor Swift is Taylor Swift. And so I'm

actually quite curious to know um how

how investors are judging nonI companies

these days compared to their AI

counterparts.

I mean, we we so at Insight, I feel like

we've done a pretty, you know,

interesting job just using our scale to

somewhat shift our strategy on the fly

based on the market conditions and the

opportunity set that's in front of us. I

mean, we're talking to hundreds of

thousands of companies globally, really

boiling the ocean, bottoms up, uh,

through our analysts and outbound team,

80 plus folks that are really

cultivating these relationships almost

at inception oftentimes with the

founders. And many of them are not AI

native companies. Some of them are

companies that are you wouldn't think

are necessarily fit for the traditional

growth or venture model. Uh think like

salmon fishery monitoring software for

example. And these are companies that

bootstrap themselves to like actually

reasonable scale 10 even 20 million. But

you know they're not going to go raise a

traditional series A. And for us, we

find that as a really attractive sort of

uh uh asset class for us to build kind

of really, you know, apply our company

building expertise to help those

companies, take them to the next level,

but they're not necessarily going to be

IPO unicorn type businesses, but we

think they can create a lot of value and

in some cases they're what seem like

kind of niche markets are just in early

phases of really mass adoption and some

of those companies have ended up getting

very large.

>> I agree. And also, it's awesome having

Thomas being to your left because he

gets to go first every time. So, I get

to riff off of him, which is awesome.

Um,

>> I'm going to make you go first.

>> So, AI obviously like so much hype, so

much opportunity, and there's a lot of

excitement and it's all very welld

deserved. Um, but there are so many hard

problems in the world that need to be

solved um in deep tech and medicine and

healthcare and robotics. Um, and and and

many of you are probably in those

categories. And so, you know, encourage

you all to, you know, keep building and

keep solving these problems. And I think

one, you know, founder and team that

comes to my mind that I think is a a

great representative and answer maybe to

your question um is a company called

Zone Homes, which is providing a great

service to homeowners. Um it's not

necessarily AI, but um it's in the

embedded finance case. And and for them,

they have a product that customers love.

You look at the Google reviews and

people are like, "This is the best thing

to ever happen to, you know, to home

buyers to make it easier for them to

afford a home." Um, and then you look at

the team, those guys, I remember Ashman

on our team went to go visit them and he

was like, "I can't be the first to

leave. It's 11 o'clock at night. This

team is so dedicated. They're working so

hard and it's reflected in their

metrics." Um, you know, they have great

revenue. They have great retention.

They're growing all these things. So,

you know, keep relying on those

fundamental metrics that you have and

customer love. While you may not be in

AI, showing that customers love you, the

market's pulling for you, you have these

repeatable um amazing growing metrics, I

think you'll be in amazing shape.

>> Yeah, we um to Katie's point, we just

backed a frontier investment in the

fusion energy space.

>> Wow.

>> And right, I can't say yet. Uh but a

founder we're very excited about. Look,

the odds are it may not work, right? We

we go into these things very eyes wide

open. Um but we ask oursel you know if

it if it does right and and open ads

like a great example of this like in the

early days it was a research lab it was

a nonprofit. There was this question of

like what will it become? Um here we

just said if there's any chance it works

it's worth leaning into and it's a

founder that we're very excited about

both investing time and dollars in. And

so again, the the bar is high, but if

the outcome can be impossibly huge,

we'll take that risk.

>> Yeah. My next question was actually

going to be like, how can the nonAI

companies stand out to you while they're

pitching?

>> How can they what?

>> Stand out.

>> Oh, stand out.

>> Which

>> I mean metrics, right? Like you know,

you know these, you know, most venture

capital firms, they're they're they're

banks and the ATM password is going to

be traction, right? And so like if you

have the traction to be able to unlock

um I think that's great. And the other

thing that I think might be as an

underrepresented

um I know category is just like tenor

you know what you know what h how how

passionate is this founder? This is such

a long ride like why are you doing this?

And if you kind of feel this energy and

this is the founders or the team's life

work that goes really really far. So,

um, so, so make sure you have that. And,

oh, sorry. Did you want to

>> No, you nailed it. Passion's number one.

Still the most important thing, right?

There are great consumer companies.

They're great frontier companies.

They're amazing companies we meet every

day where we just want to go on the the

journey with that founder.

>> And some of the nonLLM, nonAI companies

have the advantage of a really

predictable long-term cash flow model. I

mean, it's the things that have gotten,

you know, investors so excited about

software for so long. A high gross

margin, highly recurring revenue, very

sticky, you know, relatively low cost of

sale. And so, a lot of those

fundamentals are really thrown out the

window with certain LLM based companies

around gross margin, around retention.

And that, you know, that calls into

question sort of the long-term valuation

and potential of these companies even if

you know the traction in terms of the

inbound demand is stronger than we've

seen in typical SAS adoption cycles. So

just because you're not AI doesn't mean

uh you don't have a very attractive sort

of asset uh intrinsic quality to you.

>> And I wanted to ask a question on the

flip side kind of about AI companies

because it seems like so many companies

are using AI and everything is AI now.

How do AI companies stand out when

pitching you when it seems like so many

companies are so similar?

>> I I just don't want to be the first one

because I've been uh

>> We'll start with

>> No, I I can't. I mean, look, again, at

the end of the day, I think we go back

to the value prop, time to value, how

big can the ASPs be? I mean, we look at

some of these markets where you've got

large incumbents that kind of signal,

okay, within a certain vertical of

software. Look, you take Epic, how how

much revenue does Epic have? I don't

know exactly what the number is, but

then you comp that to what ambience or a

bridge or these other, you know, kind of

digital scribe companies are going after

in terms of their own, you know, what

their new market, what their new

valuation has to imply in terms of

future revenue and market cap. And you

start the numbers can start to become

tricky. Plus you have open AI and the

big platform companies plus the old old

school incumbents that are building

their own solutions. So I guess at the

end of the day we try to understand like

if if it's a market with a lot of

competition both incumbents and nextg

competitors and platform players like

what is going to be the standout path

and ultimately I think especially at

later stage growth the numbers become

very tricky in terms of what has to be

implied in terms of a lot has to go

right then of course we're we're

oftentimes humbled with uh uh how

amazing these companies go out to per

perform like Harvey's of the world.

them.

>> Yeah. One thing I would add is um

industry expertise. So obviously like

having AI engineers again table stakes

if you're building an AI business and

everything is basically AI at this

point. Um but you know increasingly for

us we look at vertical applications and

AI and it is such a great winning model

when you have that combination of of

technical expertise and industry

expertise. So with Spellbook, you know,

doing AI for lawyers, they have um one

of the co-founders is a lawyer. Keith Ra

Boy just led their series B and he is a

lawyer and that's really helpful to have

that sort of industry expertise. We

backed another company called Ferros

Health, which is AI for patient safety

data working with hospitals and Felix

and the team, they're both really

talented um engineers, but they have all

this amazing experience selling into

hospitals. And I would say especially in

healthcare, you know this very very well

that you know you can you know be the

most brilliant software engineer but if

you're selling into health care systems

that may take a long time. You really

need to have that credibility that

industry knowhow because those sales

cycles are very long and the stakes are

very high.

>> Um weird answer on my part. Uh I'd say

the common underlying theme of a lot of

our founders that are doing well is just

paranoia. and and admitting like I

remember the Harvey guys came in at the

B. Um there was this question like do we

need to build a massive AI team? What is

more important domain expertise or

having AI luminaries and constructing

your like we were talking about building

our own models, right? But they in that

meeting with an investor they just met

and presumably wanted on their cap

table, they were very honest of like we

actually don't know the the answer to

this question. What do you think? And we

argued back and forth, right? And you

know the the thing that's true about

them that's true about the founder of

open evidence that's f true of like

mirror morati at thinking machines who

we backed is like they are keeping pace

with the rate of change which is very

very hard thing to do right now. There

is a model out there that is faster than

the previous generation that's better

they're open source models even the way

applications look going forward is going

to change. And the commonality amongst

all these people from Meera to Ilia who

we back to the Harvey folks is we have

to move faster and and that has been the

underlying theme of of all those

founders. Where did you land on your

debate to to

>> you know at the series B which

unfortunately we missed we invested at

the sea you know I was kind of pushing

back that like I don't think you need

these people right I don't think you

know you don't need to go out and give a

ton of the company to some AI luminary

right um now it's great to surround

yourself bring them on as advisers but

the the view was I think the models get

better and it's more can you build

quickly on top of them and not be wed to

any single model. I can be wrong five

years from now, right?

>> We're having the same debate at another

company. No, that's why I ask. I mean,

it's if your road map is converging with

Anthropic or OpenAI's roadmap, you know,

you might think about whether that's the

right use of your engineering, your

precious resources and engineering

capacity.

>> I'll give the Harvey team credit, which

was like we'll burn it down if we have

to. If we're wrong, we will move as

quickly as we need to. And that was sort

of the ethos for day one was just

admitting like we don't know what's

going to happen. We just need to know we

can adapt very very quickly.

>> I think we see actually it's really

interesting. I don't know if you guys

see this too, but first time founders

are very excited about how large their

engineering teams are getting and second

and third time founders are really

excited about how small their

engineering teams are getting, right?

And so, you know, so much about this is

all about scale and efficiency and

especially with AI like all the

turbocharging that can be done with and

and the speed that can be done with

smaller teams.

>> And I'll ask a few more questions before

I'll pass it to the audience. Um, one of

which is I want to talk a little bit

about preparing for a series A. How soon

after a company raises a seed should

they start thinking about a series A?

>> Same day.

>> Before

>> before. Exactly. You're always

fundraising. Um, see, I'm going first.

So, good. Um,

>> I again I think that this was a Cardo

number that I have in my head, but it

used to be, you know, the time from seed

to series A was about 18 months and and

now it's taking 20 months. is taking a

little bit longer and um and that's

again because I think the series A firms

are just getting a lot pickier and

looking for you know capital efficiency

and velocity and sustainability and

defensibility and all these things. So

you know you should always be ready and

be thoughtful. We actually ask at seed

um we don't necessarily expect an answer

but who would you like to raise your

series A? Like who is there somebody in

mind? Um because we want we want to make

sure you're thinking long term. Um and

we have relationships with all these

amazing series A firms. We want to make

sure we're matchmaking. Um and so you

should always be ready, but you also

don't want to go out too early. If

you're not ready and you start

showcasing and you're ready for the A

and you're not, word gets out really

fast and it can actually have, you know,

a really negative effect on that fund

raise.

I I encourage my companies to

raise as little as possible. So I have a

little counterintuitive example and you

know when they're doing well the A's

will find them.

>> It's interesting. I I kind of have a

different view which is you know you

have to go out there and test the story

with the market to some degree. And you

know, I think that a lot of the firms

that have more of an outbound team,

Insight being one of them, like that

relationship and that trust and rapport

that you establish with the analyst

early on, I mean, they're going to be

ultimately they're the ones to to steer

you through the halls of Insight or

whichever firm you're talking to. And

you want them to be empowered and feel

like they can trust you and vice versa.

And if if you do well by them, they're

going to do well by you. to make sure

that your story is articulated

thoughtfully and that you know you've

got credibility with the firm that

you're talking to because you've kind of

ma maintained a relationship and

maintained a dialogue that to us that

that matters more than you know you're

the hot company with 10 term sheets you

know for us how are we going to

differentiate in that conversation.

>> Yeah. My next well probably my last

question for audience questions is what

can a founder assess about an investor

to know whether or not they want them to

raise like want to raise their series A

from them like what should they judge

you guys by

I mean look you know we've spent a lot

of time investing in terms of the

company building and sort of

productizing a lot of the best practices

I mean I think at series A it kind of

boils down to two things which is help

me find customers help me find talent

and we've we've done some pretty uh I

think innovative things from a venture

firm perspective using our scale again a

little bit to our advantage. So we

acquired a business called Riviera

Partners which is a large executive

search firm for product and technology

roles which gives us a lot of great sort

of visibility into uh some of the best

talent out there and especially around

AI it can be really creative. So looking

for what are those firms that kind of go

the extra mile in terms of the edge and

you know oftent times scale is what

enables that. You've also got on the

flip side, I think, some great early

stage firms where you're just working

with amazing people and it's it really

comes down to the people. So that's

another big part of it.

>> Hey, one additional thing I'll add is

just, you know, be process ready. Um

make sure you have a very clear process

making sure that your data room um is

you know all clean that you know you

know you know you you have a cohort

analysis, you have your P&L, you have

examples of investor updates. How do you

communicate? Have you how have you

communicated? Um what do customers say

about you? And again number one thing is

traction traction traction. Um you know

can you show that forward-looking um

repeatability that vision that velocity

going forward and just having that um

just organized. I sometimes am surprised

when you know I've seen um not our

companies because our our companies are

already and we and we have a bit of a

boot camp around it but you know when

I've seen you know some of our friends

who are founders you know just not

having a lot of that process discipline

and that organization because I think

that goes a long way especially when

you're pitching to a lot of these great

series A firms.

>> Yeah. Look, I I think the the converse

is true too for all the founders out

there. Be super picky with who you

partner with. Ask yourself, you know,

make them take you out to dinner and at

the end of it, ask yourself, hey, even

if we fail, would I go on this journey

again? Odds are it's still at the series

A not going to work, right? But maybe

it's the next time you start, right? And

that if you pick that right partner,

they'll back you again. I just back

someone where he failed spectacularly.

You know, we said, "No problem. You've

learned a lot from this experience. We

will back you again." And he wanted to

partner with us again. Um, call them at

weird times too during the fundraising

process, right? They should pick up

immediately if you call on a Saturday,

if you call during dinner time and and

you could hear like whether they're

excited to hear from you or not. But

it's it's a two-way street and and make

sure you're enthusiastic about

partnering with whoever is at that firm.

>> Okay, I will do audience questions. Um,

there's a mic runner.

>> Okay. Okay. So, someone has the mic.

Okay.

Oh

um probably someone in the firm. Yeah.

>> So the ratio of pitches you get to the

actual investment uh it is 1 to 100 or 1

to thousands. Uh and there are so many

criterias and factors. If you have to

pick one factor that helps you make the

final call, the final judgment which

startup to invest in, what would that

one factor be?

For us, it's consistency. And so, you

know, just again, there's a reason why

we like to build these relationships

early on is because it does give us a

little bit of a reference point in terms

of, you know, does a founder or CEO just

deliver on what they what they say or if

you know, they're working through sort

of how they want to shape their vision

and and what the future is, we can see

kind of that progress and, you know, we

end up missing rounds early and that,

you know, ultimately we don't want those

conversations to preclude us from being

able to have that, you know, that shot

in the future where you've you've

delivered And there's amazing

investments that have worked out really

well for us and for the founders where

we didn't lean in at seed and A but we

did at B and you know went on to be very

successful.

I for us. Oh, sorry. Do you want all of

us or one of us?

>> Oh,

>> was it the Okay, sorry. One very

quickly. Um, you know, traction of

course, but just uniqueness like and you

know, is it kind of out there? Is it

bonkers? Like, is it a bit of an

outlier? Kind of a, you know, a newer

thing. I think that tends to get a lot

of attention as well.

>> Can it be huge? Right. I mean, our LP

has a different criteria. They're the

most cash generative business in in the

world in history. And so it's like we

need it to be enormous, right? Uh and so

then the second question is can this

person actually go and execute on that

vision?

>> I have a question about um markets

opening up and generative AI. I'm over

here. Hi.

>> Oh.

Um, so I'm the founder of a consumer

legal tech company and I saw how

generative AI completely cracked open

that market. Are there other examples of

markets where you really wouldn't have

been very excited about the market until

generative AI came along and now it's

completely changed your vision of that

market?

I mean look there's a lot of of net new

surface area that's emerged from this

and this is what I was talking about

before where you know if you look at the

selection of 80% of the AI generative AI

companies that we've brought to our

investment committee over the last year

or two they're actually again addressing

whites space net new product surface

area that didn't exist before as opposed

to you know displacing an existing

market or incumbents. So for us that's

super exciting. The shape it takes, you

know, it really varies by vertical to

vertical. Uh and you know, I think we're

looking for something that's more than

just a scribe, you know, and it actually

takes the workflow and and does

something unique with it?

>> You mind if I

>> Oh, hi. My name is Dylan Murray. My team

is trying to be the face of at home

consumer diagnostics and we're a startup

battlefield company. We're also all 21

years old and trying to raise a $6

million seed. How do you guys think of

young founders? How do we compare

against founders that have that lifetime

experience that you love?

>> I think it's an asset. I mean, I think

that this is uh, you know, very much

early stage venture is often a young

person's game that you have the energy

and the drive and kind of the lack of

other sort of life distractions, right?

To be able to, you know, plug in so much

time and so much energy. So, you know,

play the cards you're dealt. If you're

young, like go hard. If you're a little

bit older, play your experience. But,

um, you know, I think you have a great

shot at it. Um, for what it's worth, I

do feel like six million seeds are

pretty big. Um, and I'm always I I have

a horse in this race, but um, I do often

believe that, you know, smaller rounds

just to get started and just to prove

where you're at and taking less

dilution, like do that. You want to run

really, really fast and don't let really

big seeds slow you down.

>> Hi. Um, way back here. Um, for those

that are doing something that is

different, edgy, you all have all

mentioned it. Um, or unseen perhaps.

What is the number one tip you would

recommend a founder share in a pitch

deck to articulate um a new emerging

market that's not currently

out there and scene?

>> Um

I think it's not losing that enthusiasm

like you said. Part of it is like the

harder it is, the more speed dating's

involved. And and so I think we're all

reticent of like this is going to be

very hard. And so being upfront of like

I want to acknowledge this is hard. This

is why I think we can get over it. And I

always joke that like I've done both

sides of this like Thomas where like

private equity is like math and science,

but very early stage is more like

religion, right? And you have to make me

believe that like you recognize how

difficult this is going to be, but all

the seed deals and series A's we do are

still very difficult at that point. Um

it's convincing the person in the room

that like you can get over that hump and

how you accomplish what you set out to

do.

>> Um thank you very much for the

insightful discussion. I have an unusual

question. Uh my name is Val Bever. I'm

founder of video engager video chat also

I've been early stage investors I've

been on both sides and the question is

um do you have examples of really

successful companies that are

bootstrapped they didn't use any funds

>> I mean one prime example for us is a

business called veh software uh the

founders bootstrapped that business to I

think close to $200 million of revenue

before they took any uh capital outside

capital and I think it just I think

speaks to if you've got great product

market fit and a great technology you

know it capital to growth to grow is not

necessarily what's going to build the

mode

>> and I think we have time for maybe one

more question

>> oh okay can I

>> can I sorry

>> hi my name is Masha Petrova our company

is null space we are not an AI company

and I feel like it's time that we can

actually advertise that Now um we have

we're developing computational software.

I have a question for Thomas. You

mentioned working with analysts. So we

just closed our series seed round and as

a founder I get inundated with emails

from junior people and analysts from VC

firm. Your analyst from inside partners

has been awesome and is very

knowledgeable and asks all the right

questions and clearly prepared. But you

get slammed with emails from some just

junior analysts sometimes that are not

prepared. How do you balance um

answering those emails, taking those

calls as a founder? Do you have any tips

on how to sort of filter if at all or do

you just take all of them? Uh appreciate

the answer.

>> You'll have to calibrate a little bit

based on your own experience, but look,

this is the challenge from our side is

we want we we we know that it's a very

competitive landscape and that we're not

the only firms with an outbound team.

And so showing that you've done your

homework and have a point of view and a

perspective and you're not just sending

a very bland form email because that's

not going to get a response. But you

know, we really look at ways that we're

going to build like a thoughtful

connection with the founder. And I tell

my analyst team, you know, you're

building your own portfolio. You're

betting your time on this company and

it's going to be three, four, five plus

years potentially before it becomes an

investment. Sometimes it happens sooner

in the AI world. those cycles have been

compressed. Um, but that's where when

you have the call, do they do they bring

a thoughtful perspective and they have

kind of a unique sort of vantage point

on the market and that you know that

sort of it should be you should be

getting something from it as well. If

you're not, then probably not a

relationship to prioritize.

>> And that is all we have time for. So,

thank you so much for coming and thank

you to the lovely panelists for having

us.