We Built Our Own Salesforce in Months. Here's Why We're Cancelling the $600K Contract | Curative CEO

Lockdowns had just started. Everybody

[music] was starting to freak out. There

was basically nowhere to get a test. So,

our chief scientific officer had in his

spare time developed a COVID test. I

think our peak day was 26,000 people

tested in a single day. I'm so excited

for a freaking wild story today. Fred

Turner, co-founder and CEO of Curative.

This is an English founder in the valley

who scaled a COVID testing business to

$5 billion in revenue. Then he had to

scale it all back. [music] It did not

last postcoid for obvious reasons.

Today, he turned it into a health

insurance provider that's worth $1.3

[music]

billion. And in the show, he says some

pretty wild stuff. And the company went

from about 7 to 7,000 employees in those

first 9 months. We did 2.5 million

[music] vaccinations. That was another

service we did. We also lost a ton of

money on that. That was a terrible

business. We're cutting about 80% of our

SAS spend this year. What's the single

largest contract you signed?

>> Ready to go.

>> [music]

>> Brad, I'm so excited for this. Dude, you

have the most wild story and I heard it

from Justin first uh and then from Anil.

So, thank you so much for joining me,

man.

>> Yeah, thanks for having me.

>> Now, I always find it very telling

entrepreneurs often kind of compelled

either by the fear of losing or by the

thrill of winning. If I were to ask you

which one drives you more, what would

you say it is?

>> Uh, thrill of winning. I feel like

during um certainly during co with what

some of what we built at curative, I got

kind of a taste for the the speed at

which you can move when everything is

like is behind you and all the momentum

is behind you and uh I've been chasing

that ever since.

>> I mean that is the biggest tailwind that

one could have ever expected. We're

going to get to that. You actually grew

up in the UK and then you moved to

Silicon Valley very young. 17.

>> Uh 19.

>> 19. Okay. Could you have built the

business that you did in the UK?

>> No, definitely not.

>> Why is that?

>> I just think the UK doesn't have like

some of the the kind of infrastructure

for um for startups and investing of

like that many people that have kind of

done a startup before and then are

willing to invest in the next

generation. Particularly investing in

younger people. like when I found I

tried to raise a venture round in the

UK. Um, and I couldn't even get

meetings. This was when I was like I was

18. I was in like first year of college

and I was doing this startup on the side

and I couldn't even get meetings with I

think I got like one fund to take an

associate meeting with me. [laughter]

>> Naturally, it went very far.

>> Yes. And and so it just it seemed like

people were more investing like purely

on credentials. And this was a while

ago, right? This was this was, you know,

more than 10 years ago. But it seemed

like people were investing just on, oh

well, you came out of this university.

Um, so if you, you know, you're an

undergrad, like, how could we possibly

look at this? This doesn't make any

sense. Whereas you go to Silicon Valley

and it was like, well, what's the

possibility here? What could you

envision in 10 years if if everything

succeeds? Like, how big a company could

this be? And it it just it was a very

different mindset that they were

optimizing for how to get the best

outcome rather than I always felt like

in the UK it was sort of optimizing for

like mitigating the the worst downstream

outcome.

>> Yes. How do I not get fired,

>> right?

>> Yeah, I totally get that. Um [laughter]

that's pretty funny. Um okay. And so we

decide to move to the valley. Great. Um

>> how does because we go from sepsis

detection. No. Well, cows to sepsis to

>> Can you just walk me through how we go

from cows to sepsis to co just so I

understand this?

>> Yeah. So, my first company that

>> I've never said that statement before in

a 20 VC episode, by the way.

>> There we go. It's a new a new phrase for

you. Yes. So, um I went from initially

cattle testing uh through sepsis to to

co. So it started off my first company

in the UK which was called TL Biolabs at

the time basically sequencing dairy and

beef cows to predict various traits

about the animal from an early age. So

it started off with beef you can predict

that certain cows are going to have more

musculature um from an early age and

some cows can have too much musculature

and then they have trouble giving birth

and so there's like an optimum that

you're shooting for um and I found this

like completely by chance. I won uh the

UK National Science Engineering

Competition and um like was on TV a

little bit and this farmer reached out

to me because he wanted help testing his

cows and he was sending his samples to

the Netherlands and it was taking weeks

and it was terrible. And I initially

told him like I'm not interested in

cows. I was interested in human genetics

at the time. Um like no thank you. Um

and then he kind of kept pressing and he

like sent me samples with a check

attached to the front and I was like oh

okay like this is interesting. And so I

did the first batch of samples for him

and then all of his friends started

sending me samples. And so it kind of

grew from there. And this was all still

in the north of England. I was in the

first year of of college at the time. Um

and uh we started branching out into

dairy and predicting how much milk

animals would make. And I tried to raise

uh the first venture round for the

company in the UK. Didn't get very far

and so ended up uh going to the US for

the US ACT investing conference in San

Francisco. It's my first time in the

States, never been before. Um, and I was

like my last ditch attempt to try and

raise some money. And I met a bunch of

VCs. Didn't raise any money, but I did

meet a guy who had just finished doing Y

Combinator. And he was like, "Oh, you

need to apply to YC. That's like that's

what you need to do. You need to move

the company to the US. You need to apply

to YC. Like that's the only thing you

can do here." Um, and I was like

familiar with YC uh but had never

applied.

>> What year was this? This was like the

end of 2015.

>> Okay.

>> Yeah. So, I went back to the hotel room

and it turned out like the application

deadline was 6 days away. So, I was

like, "All right, it's meant to be." So,

did the application, you know, got the

interview, came back for the interview,

uh, and then moved to to Silicon Valley

for the summer 16 batch.

>> Paul, so how was the interview? Who was

it with?

>> Tim, Jeff, and somebody else. Yeah, it

was I mean, it was all a bit of a blur.

It's very fast.

>> And then you found out you get in.

>> Yes.

>> You moved to the valley. moved to the

valley and then it was the same, you

know, pitch the same company. We were

doing uh mostly dairy testing at that

point. So testing dairy cows to try and

predict uh their milk yield, which for

farmers is actually very valuable

because they don't make milk until

they're 18 months old. And so from day

one, all your animals have to have a

cough every year to keep making milk. So

your herd doubles every year.

>> Is this still the same curative company?

>> No, this is a completely different

company.

>> Okay. I was about to say, god my this is

where investing is so difficult because

like if you hear a founder pitching milk

yield optimization [laughter] and I'm

sure it is like logistically a big town

I'm sure

>> well not big enough that was the

problem.

>> Okay.

>> Yeah. So so we did this went to YC and

we raised a seed round from Andre

>> a seed round from Andre. Yeah, their

their bio uh fund uh did our seed round

right out of YC. Um and I don't think

they did the TAM calculation.

>> Um

>> they backfound us.

>> Credit to you.

>> Yeah, they they were like, "Oh, this

sounds interesting." And they did the

round. It was a small round. It was like

1.65 million. So

>> chum change.

>> It was for the coffee.

>> It was, you know, for for Andreason, it

was like a smaller round.

>> Sure.

>> Um and so we kept developing the

technology. We had customers. Uh, and

then we went to go raise an A. And then

people did do the TAM calculation and

there's about 100 million cows in the

US. If you're doing well, you could

charge 15 to $20 per test. So even if

you assume you could test every cow

every year, you'd be at 1.5 billion like

total market, which is not enough to do

a series A off of. And so what we end up

doing is taking some of the core DNA

testing technology that we had developed

and pivoting and using that for human

diagnostics. And so that was my kind of

first foray into healthcare. Uh we

actually first launched a high

throughput STD testing lab. Um yeah,

which was and we launched an at home STD

test. It was that was tons of fun.

[laughter]

>> I don't I used to run a lot when I was

young and my knees were wonderful. Uh,

and I used to love how I built this cuz

they would ask the questions like this,

which is like, how do you go from like

cows and musculature on cows and milk

yield optimization to at home STD

testing? [laughter] Like, it doesn't

feel that natural a jump.

>> Yeah. On the back end, it's more

natural, right? All of these things have

DNA in them. And so, if you're if you're

looking to do better DNA testing, you're

just looking for markets where people

care more about that. and anything human

people obviously care a lot more about

are more willing to pay for and are much

larger markets. And so we sort of did

like a market first approach of, you

know, where where could there be

interesting things and we narrowed in on

uh antibiotic resistance in STDs as

being like a particularly interesting

area where they're getting harder and

harder to treat because you get more and

more antibiotic resistance. And if

you're doing the DNA testing, you can

predict what the best drug is going to

be early, treat with that drug, and then

you're not using the most aggressive

antibiotics.

>> Do we have more STDs than ever?

>> Yeah. Yeah.

>> [laughter]

>> This conversation's pivoting somewhere.

I didn't expect but I thought we were

having less sex than ever.

>> Yeah, but more STDs.

>> Wow.

>> Yeah,

>> that's worrying.

>> Yeah, it is. And and well, it's a while

since I looked at the statistics because

I've not been doing this for a while

now. Um but when I was like last in this

Yeah. The statistics were just kind of a

like steady increase and then an

increase in resistance. And so it's

getting to the point where certain STDs

are like harder and harder to treat and

some of them might eventually become

untreatable or like you have to be

hospitalized to get a certain really

powerful antibiotic to treat it which is

crazy. Um and so antibiotic stewardship

was a whole thing. And so we did that

with STDs [snorts] and then [laughter]

I love this conversation keep. And then

[clears throat] and then we found a

fascinating market in sepsis. Um and so

sepsis is a disease that kills hundreds

of thousands of people a year. It's

basically where you get bacteria in your

bloodstream. And what kills you is not

actually the bacteria. It's your own

immune system. So, you're not supposed

to have bacteria in your blood, right?

Your blood is supposed to be sterile.

And when bacteria get in there, your

immune system kind of freaks out and it

triggers this whole downstream cascade

where your blood vessels start to leak

and all of your organs start failing and

it's basically really bad. And that's

what kills you is your own uh immune

reaction to the bacteria rather than the

bacteria. And so this is, you know, one

of the leading causes of death in the

US. Often if you're dying from something

else, like if you know, you have serious

cancer, it'll be sepsis that ultimately

ends up being what kills you. Um because

you get more susceptible to it uh with

other diseases. And so it's leading

cause of death, like increasing

mortality. It's incredibly expensive.

Outcomes are terrible. Um and so we were

working on basically a better testing

technology where from the earliest date

uh you could detect these bacteria and

what antibiotic they are going to be

susceptible to and treat people faster

because with sepsis basically every hour

that you don't treat somebody is about a

12% increase in mortality. So you want

to get the treatment as soon as

possible.

>> Every hour you don't treat someone is a

12% increase mortality.

>> Yeah.

>> Okay. And so we start the sepsis

testing.

>> So start the sepsis testing. And so this

>> does it instantly go well?

>> No. So this company died at the end of

2019.

>> Oh, I'm sorry.

>> Yes. So, uh, we went to the testing was

working great. Prototypes were, you

know, pursuing the FDA approval process.

We went to do a series B round, uh, with

ended up being a strategic.

>> Sorry, just so I understand. So, we

raised the A from A and it's still the

same company as this milky.

>> Same company. Yeah. It changed its name

from TL BABs to Shield.

>> Oh, love it. Good. It's a good single

name. Okay. So, we go to raise the

series B, bigger TAM, sepsis, death,

more bigger

>> TAM gravitas. Yeah. Many many billions

of dollars TAM uh for testing for this

and ended up getting a term sheet from a

strategic uh large public diagnostic

company. Signed the term sheet, did

three weeks of of work on docs. We were

in the second round of docs and then

their CEO killed it because it was too

competitive with their core products.

Meanwhile, we told all the investors

that, oh yeah, we've got the lead. We're

good to go. Oh, here's the paperwork.

And so, uh, that was the death of the

company. It had, we had about 3 weeks

worth of cash.

>> Would you be where you are today,

though, if that round had come together?

>> No. No. Cuz I don't think we would have

pivoted as hard into CO when CO hit. Um,

I mean, it would have probably been

easier cuz we had at that point, we

actually had a lab license. So, you

know, in the US, you need this thing

called a clear license to run these kind

of tests. And we had got one of these

licenses over like a painstaking

two-year process. Uh, and then in

December of 2019, as part of the

windown, I sold that license to a

company in San Diego for $150,000

uh to pay some of the creditors and then

5 months later acquired a company in

Southern California to get the same

license for 27 million.

So, timing is everything.

>> Whoa, whoa, whoa, wait, wait. So, we're

winding down the company and we sell

this license for $150,000,

>> which is it roughly its market value if

there is not a pandemic.

>> Totally get that. Cool. Okay. And so,

we're winding down the company. I want

to go chronologically cuz that's like a

wild [laughter] number like flies in

shutting down the company in 20 now 20 I

guess.

>> Uh it was Yeah. kind of right at the end

of 2019.

>> Okay. End of 2019. Shutting down the

company strategic alle [ __ ] that.

[snorts] Um

>> and then what happens then? So then I

was kind of looking at what to do next.

Um, and

>> were you like personally devastated?

This is five years of your life. Yes.

Any lessons for founders? Reflections on

that?

>> I think it's a lot easier to build a

company the second time around. Like

there's so many mistakes the first time

where you just you don't know how to do

like thing X, like the first time you

fire somebody, like how to build a good

interview process, how to build a

pipeline. Like there's so many things

that it's really easy to screw up the

first time around. And then when you've

seen them go wrong, it's so much easier

to build it the second time around. And

so like, yes, it's the worst thing in

the world to go, you know, to go through

is having something you poured all that

time and energy into and like, you know,

the 7-day work weeks and the late nights

basically go to zero. But you learn as

long as through that you you learn and

you take those lessons and you go solve

an even bigger problem, I think, you

know, you got something out of it.

>> Okay. And so this company is like

winding down,

>> need to find something else. What

happens now?

>> Yeah. So originally the pitch behind

curative uh was we were going to also

solve sepsis but in a completely

different way. [laughter]

>> You really focused on really. [snorts]

Yeah. So

when we were going through all of this

work with the sepsis diagnostics, one of

the things that kept jumping out in the

data was when you look at other

companies that had tried to do sepsis

diagnostics because we were not the

first. A bunch of big pharma companies

like Ro spent a couple hundred million.

Um Seaman spent a hundred million. A

bunch of companies spent a lot of money

trying to make better sepsis

diagnostics. So it's kind of this like

graveyard of dead sepsis companies. And

when you dig into the data, you find

this really interesting thing that in

academic medical centers when you try

out these new sepsis tests, they work

great and you see much better outcomes

and you see, you know, people live

longer and it's saving lives. And then

you try to replicate that in bigger

studies and they fail. And when you dig

in and look why, it's when you expand

that aperture of who's in the trial out

of the academic medical center and into

community hospitals. What's happening in

a community hospital is they're so

understaffed, they're so overwhelmed

with the volume, particularly in the

emergency room, they don't suspect

sepsis fast enough and as I said

earlier, it's every hour is 12% increase

in mortality. And the intervention that

they have to do is actually pretty

severe. They basically put a big IV line

usually in your femoral artery. They're

pumping you full of fluids. They're

pumping you full of nasty antibiotics

that have bad side effects. So, it's a

pretty aggressive treatment. But if they

don't suspect sepsis early enough and

jump to that treatment, by the time they

get there, it's already too late. And so

if you're in a community hospital and

it's 2 a.m. on a Saturday, is there

someone on staff that actually suspects

sepsis early enough or does it wait

until Monday morning?

And so it doesn't matter if you have a

better test if no one ever runs it. And

so the original pitch behind curative is

let's take the learnings from an

academic medical center and go out to

community hospitals and basically build

mini hospital in a hospital uh that just

manages their sepsis patients. So

whenever they get somebody you know we

will diagnose them as having sepsis out

of the emergency room. We will then take

on that patient. They would pay as a

fixed fee. So no matter what happens

we're on the hook. If we can drive a

better outcome by applying mostly just

getting doctors to follow the

instructions but at scale then you could

drive better outcomes um by getting

those academic medical center type um

like clinical results but helping a

community hospital actually do that.

>> So what happens then we we start that

business

>> start that business we raised uh a

million dollars of seed money. Uh Justin

was the first investor you mentioned at

the beginning Justin Matine. Uh he came

in uh right as I was shutting down

Shield. He was an investor in Shield. Um

and he wanted to put more money into

Shield. And I said, "No, I I don't think

you should do that. I think that company

is is, you know, is not going to make it

unfortunately, but I'm thinking of

starting this new thing." And he was

like, "Yes, I'm in." And he didn't even

know what it was.

>> How much did he put in? He

>> put in, I think, $125,000

uh at a $3 million valuation. Wow.

>> So, he was the first

>> Okay.

>> First money in.

>> First money in. Love it.

>> Um and and so we had a pilot set up with

a first hospital in Wisconsin. This was

a clinician that we'd worked with

before. He was really enthusiastic. And

then we got a call from his assistant

saying this is all on hold and I can't

speak to you for at least 3 months.

>> Huh.

>> And we were like, that's really out of

character that he wouldn't at least call

us or text us or that he's having his

assistant. And when we dug in, they were

getting ready for this thing called CO

19 that they were expecting to see the

first patient in their hospital. And so

that was the first inkling for me of

like, oh crap, this is going to be a big

thing. This is going to be bigger than

people think it is. And so they were

shutting down the entire hospital. And

so it started off for us as like, okay,

well, we can't run our clinical studies.

We can't actually launch this product

because all the hospitals are on

lockdown. maybe we can go help out with

this testing thing for a couple of weeks

until all of this blows over um and then

we'll go back to sepsis.

>> And so at that point we're like we've

move into CO 19 testing.

>> Yes. Yes. And so it all happened quite

quickly from like a lot of me saying no

no no this is not going to be a thing

like don't worry about it like just it's

>> What was the moment where you realized

like where were you like this is

substantially going to be a real thing?

So, I was like in my apartment in San

Francisco looking at some data that I

think was on Twitter. Um, and and I was

like, "Oh crap, if that if this

continues at this rate, like this is

going to be way more substantial than

people realize." And so this was

probably midFebruary. Um, and so then I

started to reach out about sort of

setting up testing capacity uh to well,

first of all, we had the problem of

finding a lab license cuz I just sold

the lab license. [gasps] This was the

150 grand you just sold.

>> So just sold the lab license and so we

didn't have a lab anymore that was

capable of running these kind of tests.

We had a test. Um so our chief

scientific officer at at Curative had in

his spare time developed a COVID test.

And one of the things they' done at a

previous company is they developed one

of these flu tests and just offered it

to employees to make them feel better.

And so he said, "Hey, can I develop a

COVID test? I don't think it'll be very

useful, but it might make our employees

feel good, and it's like a good training

exercise for the team. And so, they had

worked on through January and the early

part of February a COVID test that

they'd been developing uh basically in

their like spare time in evenings and in

weekends. And so then when everything

started to really take off, we actually

already had the test. What we didn't

have was a lab to deploy it in.

>> And so at that point, you then go back

to the old one and buy it for 27

million.

>> No. So I bought a different lab license.

you bought a different lab.

>> So, we reached out I reached out to a

bunch of people I knew in the Bay Area

that had facilities with this kind of

license. Nobody wanted anything COVID

related on site. Nobody wanted, you

know, anything to do with it. And so we

um I like put it out I just put out an

email to like everybody I know. Um, and

there's actually a guy who uh was in the

same YC batch as me um who had become a

VC and he uh connected me to a group in

LA and they had this license and they

were using it for like uh sports doping

testing and they were in what I thought

was LA. I remember telling Justin, "Oh,

Justin, I'm going to to LA. I'll be in

Sand Deas." And he was like, "Where the

hell is Sand Deas?" It's like basically

very far east of actual LA. It's still

in LA County. It's a little city uh best

known for uh Bill and Ted. It's a little

town of like 30,000 people.

>> And that's where the lab test

>> and that's where the lab was. And so I

flew out there to look at that lab. Uh

this was from uh from San Francisco. And

to look at one other lab license that

was I think affiliated with um with one

of the universities and you know they

had a good space, they had this license

and they were doing pretty minimal

testing. So they just kind of like a

blank slate. And so it started off as a

50/50 JV between Curative and this

company that had the lab license. And we

would bring the test, we would bring the

expertise, they would bring the license.

And it became pretty clear quite quickly

that they didn't have the expertise to

scale it up. Like they were actively

getting in the way of scaling it up. Um

and so we

>> What did you do?

>> We bought them out

>> and that was that was the 27 million.

Where did you get 27 million from?

>> Uh forward revenue from customers. So we

were getting paid. We had our first

testing contract. We were doing the uh

police and the fire department.

>> And so how do you do you have the chief

science officer who's created this

brilliant task kit?

>> Yep.

>> And you go to like San Francisco state

or government.

>> So this is mostly Yeah. And so actually

our very first customer was the sheriff

department in Sand Demos. Well, we did

some like private testing for

individuals that were paying for the

tests. But our first, you know,

government customer was the sheriff's

department in Sand Demus and that came

about because they got wind that we were

setting up a CO lab because people were

freaking out about it in the town. And

so one of their sheriffs reached out to

me on LinkedIn and was like, "Hey, what

are you guys doing?" Um, and so I

connected with him and I explained what

we're doing and how it was very safe and

how we had this way of deactivating the

COVID as soon as it went into the sample

and so there was no live virus on site

and we were not presenting a risk to the

community and actually this was going to

be a good thing and we're going to be

hiring a lot of people and kind of got

him on board that you know we're doing

we knew what we're doing and we're doing

this in a safe way. And then he was

like, "Well, well, we really need

testing." And then the fire department

wanted testing. And then our first

really big contract was the city of LA.

And that came about from a tweet. Um, so

we had uh Laura Deming

>> who was a

>> Yeah, I remember she's YC uh longevity.

Yeah, exactly. So she um you know was

was a friend and would trying to

basically help with the pandemic. And so

she actually drove me down to LA with a

car full of PCR machines um so I could

like work on a laptop and she helped

with a lot of the early development work

and she tweeted, "Hey, we've got CO

testing capacity. Does anybody want some

deputy mayor of LA slid into her DMs

and was like, "Yes, please. We would

like to talk about that."

>> Wow.

>> So that was how our first big contract

came about. And so you speak to

[laughter] the deputy mayor of LA.

>> Yeah. And then so they were doing a

pilot. They said, "Look, we got a couple

of labs. You know, you're going to have

to demonstrate this." Because we were

complete unknown, right? We' done

>> And co wasn't peak ramps now, was it?

This was

>> This was like early March. So people

lockdowns had just started. Everybody

was starting to freak out. There was

basically nowhere to get a test. Like

you unless you were ultra high risk and

in a hospital, there was pretty much no

chance you were getting a test. So

everybody was freaking out. This is when

everybody was still like cleaning their

um you know supermarket bags with wipes

and nobody knows what's going on.

Everything's shutting down. Um it wasn't

so bad on the West Coast, but New York

was like was really bad already by this

point.

>> And so they're paying ahead of time. So

the best thing we could get with the

city of LA because they have obviously

their city there are certain

restrictions is that they would pay

after delivery but they would pay net

one on the invoice. And so we would

deliver the tests for a day and then we

would send somebody to city hall the

next morning to pick up a check for

those tests.

>> Wow.

>> So the tests had been done. They were

paying after we delivered them. Um but

which was not you know your standard

like net 30 [laughter] or net 60 for a

government contract. They were having we

were invoicing them every day for the

number of tests they did and they were

having somebody in their finance

department like get us the check because

we needed that to pay for supplies to

basically grow out that testing capacity

for where they wanted to be.

>> What's the single largest contract you

signed?

>> Probably one of the Florida contracts

was maybe the largest. So we did a

contract with the state of Florida for

all of their nursing home testing. Um I

forget what the dollar figure was, but

it was, you know, in the hundreds of

millions of dollars. And so we were the

they put it out out to bid and we won

it.

>> Hundreds of millions.

>> Yeah. They tested every employee at

every nursing home across the state once

a week for a 3-month period. And so they

did a great job of basically keeping

things open, keeping these nursing homes

open, keeping visitation, but making

sure that the employees of those nursing

homes were not spreading COVID to the

people in the nursing homes. Um, and so

they wanted to test every single

employee that was working at those

nursing homes and then exclude the

people that weren't uh that that had

COVID so they weren't exposing the uh

the residents there. And so we ran this

big program, a bunch of labs or they put

it out to bid and everybody said, "No,

that's too crazy. Like that's

impossible. We cannot possibly test that

many facilities with that tight a

turnaround time. Like this is

impossible." And we bid. We're like,

"Yeah, we can we can do that. We'll make

that work." Um, and we delivered it.

What did you see that others didn't?

>> That you have to kind of scale like

something like that up from scratch that

the existing labs like the lab industry

in general is a very low margin industry

and it's built on efficiency. You look

at the big labs, the Quest and Lab

Corpse and they are ultra efficient

machines. Like they're some of what they

do with automation is incredible. But if

you're asking them to 10x capacity,

that's literally the opposite of what

they're built for. they are built for we

will get 1% extra margin by optimizing

this bit of the process over here so

that it is perfectly efficient and they

are really good at that but if you ask

them to 10x that it really doesn't work

and the mindset isn't there the people

don't know how to scale those kind of

things up all of the supply chain broke

down and so we basically said okay start

from scratch throw all of that away

imagine that you're going to have to

scale this up to hundreds of thousands

of tests a day where do you start and so

we built what we called an orthogonal

supply chain which is just basically a

fancy way of saying we don't use the

things other people use

>> sound like a Mackenzie consultant

specializing in innovation an orthogonal

supply chain yeah great

>> well I found that was like a good fancy

word that like you know was helpful from

a sales

>> stand

what it basically means is everybody was

chasing the same uh consumables the same

supplies everybody was trying to use the

same stuff and if if you know you can

make 1x of that maybe they can increase

to make 1.2x. If everybody's trying to

buy that, us also trying to buy that

doesn't help. That doesn't net increase

the number of tests being done, right?

It just makes us all squabble over it.

>> So that's pointless. So you got to find

other ways of doing the testing using

supplies that maybe wouldn't

traditionally be used for this kind of

testing. Um, so we were sourcing swabs,

you know, from other types of vendors

that were being used for, you know,

electronic testing and then sterilizing

them. we were sourcing. There's this

kind of extraction material that you

usually use and magnetic beads is kind

of the default standard, but there's

this other way of doing it with filter

plates which is more scalable because

it's basically just glass and plastic

and you can scale that up faster than

you can scale up magnetic beads where

they all come from basically two

factories in China. And so we're like,

okay, we should never use magnetic beads

because that's not going to scale as a

technology. we need to go find vendors

who can scale up the plastic and glass

manufacturing and partner with them to

basically 10x it. And so you kind of

approach every single bit of the supply

chain that way. You end up with this

massive scale. Now, outside of a

pandemic, that doesn't work because

people don't want 10x more testing than

they wanted yesterday. But within a

pandemic, you got to approach it

differently. And so we peaked, I think

our peak day was 26,000 people tested in

a single day.

>> 206,000 people tested in a single day.

And that was December of 2020. So that

was within

eight months from zero zero to 26,000.

So and the company went from about 7 to

7,000 employees in in those first nine

months.

>> 7,000 employees in 9 months.

>> Yeah. [laughter]

>> Yeah. It was it was a little crazy.

>> Do you sleep at all? I mean

>> I don't sleep very much now.

>> But like in that time, what was the

craziest thing that you did?

Um, I mean some of the hiring, you know,

you have to get licensed people for

certain roles, but other like more

administrative roles, you don't need

licensed people. And so we would

literally a lot of people wanted to work

on the pandemic, which is very helpful.

We'd have people like line up in the

parking lot um, socially distanced like

down the street and then give them five

minute interview slots and just have

somebody sit there with a clipboard and

it's like 5 minutes and next just to get

the volume of people um, in the door.

>> How much money did you make from co

testing? I think the total revenue ended

up being about five billion over a

three-year period.

>> Five billion. Is that the largest

private provider?

>> We were Yeah, we were the largest like

non-labcest

testing company.

>> That is extraordinary. What is the

margin profile on a co test?

>> So really good during surges and then

really bad not during surges. [laughter]

Um, so what we found was when when there

was a peak, right, so we get a new

variant or, you know, this usually

winter was the biggest peak, but then we

started having these summer peaks, which

was kind of weird. Um, everybody would

run to get tested. Um, and these were

all public testing sites. So these were

in parking lots. These were the

drive-through tests. That was what we

were doing. So if you went to a

drive-through testing site, like the

biggest one was the uh Dodger Stadium

site in LA. It was seven lanes of

traffic, 7:00 a.m. to 7:00 p.m. 7 days a

week.

So they were testing at the peak about

10,000 people a day coming through their

cars getting tested and coming back to

the lab. So when you're at peak capacity

and you're filling all of the labs

volume,

it's very profitable. Then those uh

basically surges subside, right, and you

end up back at testing, you know, using

20 or 30% of your capacity. All your

fixed costs the same. You're still

paying 7,000 to people. Now you don't

have to buy as many consumables, but all

of that infrastructure has to be

maintained for the surge. And so this is

again where it's like the opposite of

the traditional lab industry where they

have a very flat volume. Every year

people do roughly the same amount of

blood work as they did last year or

maybe do like predictably slightly more,

but it's it's within a couple of

percentage points. here you're kind of

building it for that peak capacity

and then during the lulls like

maintaining that capacity is incredibly

expensive and so it was kind of

necessary and this was part of the way

it was set up they increased the price

the reimbursement price uh that they

were paying for these tests because they

needed to incentivize the capacity to be

built because if you don't build that

peak capacity then when you have a surge

it all goes horribly wrong and no one

can get a test but that means you

basically have to pay to overbuild

Because during the dips you have to have

that capacity. You can't just shut it

down, right?

>> And you can't build up 7,000 in 24 hours

in

>> and so you need to maintain that. And so

we would lose a lot of money in every

one of the dips basically.

>> Well, you would actually lose money.

>> Yeah. Yeah. Yeah. We would lose money on

every test during the dips.

>> Oh wow.

>> Yeah.

>> So of the five billion, how much is

profit? So after all was said and done,

the money that we basically put forward

into the uh insurance business, the

health insurance company was about 500

million that we invested into the health

insurance business.

>> It's absolutely astonishing.

>> Yeah.

>> Can I ask you when we saw the vaccines

roll out, did you know they were

ineffective in the way that they've kind

of turned out to be? It was not clear at

the beginning and I think also it's it's

sort of changed like that when nobody's

had any exposure to co being vaccinated

probably provides a lot more benefit

once everybody's sort of had co a few

times then the vaccines benefit is much

less because you've already had it also

the varants got weaker and weaker uh

when we were first rolling them out I

mean I think in you know December of of

2020 there was benefit for a lot of

people getting the vaccine

>> did you get vaccinated.

>> Yes, we did that. We did 2 and a half

million vaccinations. That was another

service we did. We also lost a ton of

money on that. That was a terrible

business.

>> Why?

>> Um because the government wasn't paying

enough. We lost money on every single

dose. It cost more to administer them

than we were getting paid. So

>> why did you do it?

>> Uh giving back. A lot of our partners

wanted it. So a lot of the partners on

the government side we're working with

for testing also wanted us to administer

vaccinations.

>> Was it sounds awful? Was it a hard like

your business with co obviously being

eased

>> Yeah.

>> completely changes

>> and you have to pivot again.

>> Yeah. And so that started very early for

us cuz I wasn't going to last very long.

>> You were always aware it wouldn't last.

>> Yes. When we started hiring people at

the beginning, we told them this is 3

months. You have a job for 3 months.

Like don't bank on anything beyond 3

months. This is a three-month gig and

we're going to shut it all down in three

months. Um, so the the CFO and now the

president of Curative joined at the

beginning and for her it was going to be

a six-month gig. [laughter]

Um, she came out of retirement to help

with the pandemic for 6 months. Now 6

years later she's still here. But um, it

was supposed to be temporary and every

time you know a surge we got through a

surge I was like all right that's it.

It'll be over now. And then they just

kept happening. [laughter]

So, we started looking at kind of what

comes next middle of 2020, like really

early. Um, yeah.

>> How did that search for what comes next

change? You just started looking at

middle of 2020. It's not until end of

22, start of 23 when that actual search

is activated into real-time plan.

Correct.

>> Yeah. I think we started probably like

late 21 is when we got really serious

about health insurance. It just took a

while to actually get the license.

>> Yeah. Why health insurance?

>> Well, it wasn't the first idea. We

looked at a bunch of other stuff. We

looked at other stuff in the lab testing

industry. Unfortunately, it's just not

that big an industry. And so even like

we had this interesting technology that

could theoretically let you do a lot of

lab tests that are individual tests

today like as just one single test,

which would be scientifically quite

cool. But even if you say, okay, I'm

going to displace all of LabC and Quest,

that's about 30 billion of market cap.

So that's like the largest company you

could possibly build is about 30 billion

which that is a big company but coming

out of what we did with co I wanted to

build a much bigger company than that

and so there's just not a big enough

market in lab testing um so the lab

testing was was out and then we briefly

looked at trying to buy a hospital

um or multiple hospitals we looked at

one in Florida and we looked at one in

Texas and the idea was well if the

hospitals kind of like the the health

system becoming the center of where care

is delivered, they buy have bought up a

lot of the primary care offices. Um, if

you can transform that with technology,

can you drive much better outcomes? What

we ultimately decided is it doesn't work

that well because the payer mix is too

broken up. And so, as a hospital, your

customer is like 50% the government and

then a whole bunch of like split up

smaller insurance plans. and they all

want different things and they change

their mind every 5 minutes about what

they actually want and you're trying to

like keep them all happy. So your

ability to really change things from the

hospital side is quite limited is what

we ended up deciding. Um and when you

come back to it like we looked at a

bunch of preventative care things we

looked at a primary care chain

everything sort of ends up coming back

to the payer like the payer is the one

that drives behavior in the US healthare

system. If you are providing the dollars

people will go where the dollars are. If

you say I'm gonna pay for this service,

people will go do that service. If you

say I'm not going to pay for this,

people will stop doing that. And so the

payer is the one that's kind of driving

things.

>> If you could do one thing to change the

structure of the US healthcare system

today, magic wand, what would you do?

>> Um,

I think you have to break up the

negotiating into smaller units. like

it's gone to this point where I think

it's it's quite an efficient system as a

market when the counterparties are small

when everything gets very consolidated

it becomes incredibly inefficient. So

when we look at for example health

systems right so we pay for for care at

health systems

some of that care you can get in other

places if we look at how much we'd pay a

primary care doctor who's independent

compared to a primary care doctor

affiliated with a system affiliated with

a system they get paid an average double

same service

you know same credentials it's just that

this one is part of a hospital system

and that hospital system will use the

fact that they

have a ton of beds that They have this

ultra special surgery center that you

need like we need to have that capacity

in our network because some people need

to be hospitalized, some people need

those services that if you want to get

access to that, you got to pay me double

for my primary care doctors.

And so when all of the players are

small, when you have smaller payers and

smaller hospitals, you end up kind of

getting to reasonable negotiations.

What's happened is you have these

massive payers like the market is ultra

consolidated. You basically have like

four large players that control the

entire market on the payer side and then

you get these ultra consolidated

hospital systems because that's the only

way for them to survive if they want to,

you know, fight with Blue Cross. The

only way to survive is to get really big

so they have the negotiating power and

then they just reach these loggerheads

where nothing gets done and everybody's

overpaying for everything and

everything's inefficient. And when you

have more competition in the market,

more smaller payers entering more, you

know, smaller health systems, you start

to get like an actual efficient market.

When you're just negotiating for like,

hey, I have a third of healthcare in the

state and I have a third of all of the

employees in the state. It's not an

efficient market anymore because there's

no alternative. You h you must reach a

deal.

>> If I am sick, is the best place to be

treated in the US?

>> Yes, definitely.

>> Seriously.

Yeah.

Yeah. We have the US has the access to

by far the most cutting edge techniques

and facilities and drugs than the rest

of the world and they're willing to

spend a lot more.

>> What do you know now, sorry, that you

wish you'd known when you made the pivot

into insurance? I think I wish that I

knew AI was coming

because I think like the way we designed

the business in 2022 when we first

started, we had no idea that this wave

of AI and LLM was coming. Like we were

building a health insurance business

because we thought it was a good

business to build and we thought it

needed to be built. We needed a better

alternatives in the market for health

insurance. And then in the last like 18

months, how we do pretty much everything

is now a completely different workflow.

And we there's so much I mean all health

insurance does is like moving bits

around, right? Like we don't have a

physical product. We give you a little

plastic card, but apart from that our

product is that we move bits around in a

database that means care is paid for.

>> That's it, right? And we do a lot of

managing kind of managing a marketplace.

We work with the providers to negotiate

prices. We work with employers to

negotiate how much they pay and then we

try to work with employees to keep them

healthy. If we can get people to stay

healthy, we can avoid the long-term

downstream cost of care. Essentially,

it's marketplace business. Um, and that

has been fundamentally like shifted by

AI. But when we first started building,

we didn't know that was coming

>> by AI.

>> So, so much of that back office work,

right, has been completely changed by

AI. There's we now have entire

departments that used to be people like

rubber stamping things. Um the first one

that went to zero people was our

credentiing department. Um where you

know this is a process that's incredibly

labor intensive where you have to check

all doctors that join our network have a

valid medical license and aren't being

sued for malpractice. And this is, you

know, a person going to the medical

board website, checking that the license

record is there, checking transcripts

from their school, checking like a

database of of who's been sued by who,

um, and then like rubber stamping. And

that used to take us two to three months

on average and cost about $50. We've now

built in-house an agent that runs on on

Claude that does this end to end. and it

goes to the website, it verifies the

license, it goes and reads the

transcript, it puts it all together, it

stamps it for approval. Um, and we're

now averaging about 12 hours turnaround

time for credentiing somebody. And it

cost us about 20 cents. And so this is

like a mind-numbing process that payers

have to do, which is important. We want

to know the doctors in our network,

right, are are validly licensed to

practice medicine. Um, but it's like

historically has always been kind of

terrible and payers have been bad at it,

right? If you're a doctor and you join a

network and it takes 3 months before you

can see any patients. It's just

bureaucracy, right? Like they don't

Doctors hate that and it's not actually

adding the value that it should be

adding. It's just creating paperwork.

>> How many people did you have in

credentiing?

>> That one wasn't that large. I think

there was like five or six people. We

had a few other departments that have

shrunk more than that with the

>> What other departments? We've seen a lot

on the claims side, claims processing,

right, is used to be a very manual

process where claims comes in and people

are like manually tweaking and editing

it. Um, and also on the underwriting

side, underwriting, you know, the

process used to be uh a broker comes to

us with a group, an employer that

they're looking to insure and they ask

for competitive bids from multiple

different insurance companies. And what

that means is basically sending us an

email with a bunch of PDFs and

spreadsheets attached of who are the

employees, what current claims do they

have, what's the current insurance look

like. And you'd think that over time

they would develop like a standardized

format for how that should run, but no,

every single one is like a different

spreadsheet format, different PDF. And

we tried to sort of solve that problem

with software and build like universal

importers and universal intake. And it

like it kind of worked, but what we

found works amazingly is literally to

give the files to an agent, tell it to

write Python to get these files into a

standardized format because they're not

very good at parsing files. But they're

incredibly good at codegen. And so you

can tell it to write a Python script to

convert any random file into this known

format and then test it and loop and

iterate on your script until it's

working. And then you throw away that

script. And so it's single use code that

never gets used again. and you just

generate that code one time and then

throw it away. Um, and that works so

well. And so now brokers, providers,

employers, when people are sending us

files, we always used to like insist,

oh, you have to use our standard format

for this. And they'd hate it and they'd

get mad cuz somebody's sitting there in

a provider office like manually

reformatting these files into our

spreadsheet. Now send us whatever you've

got, whatever format. It can be

scribbles on a napkin, it doesn't

matter. The model will figure it out.

The model will convert it into our

standard format. and it will do it in

about 15 minutes. And so you build these

data ingestion pipelines that used to be

hundreds of people sitting moving

spreadsheets around and it's now a model

writing Python code to do that same

thing and then every single time you

throw that Python away and start from

scratch.

>> Dude, I have so many questions to ask on

the back of this. The first one is you

mentioned there kind of the internal

agent buildout that you've done for the

company and for your specific processes.

Yeah.

>> Do you buy the SAS is dead theory that

we will

>> Why?

>> Because I see the number of contracts

we're canceling.

>> Like we we just recently canceled our

Salesforce contract because we have an

internal CRM that was built, you know,

was vibe coded, that is working better,

that is managing our process better, um

is more integrated into what we're

doing. We run our agents inside of it

and no one was using Salesforce anymore.

$600,000 a year.

>> Wow.

>> Gone to zero. How long did it take?

>> Two months.

>> Is it worth because argument back I

always like to do both sides. I'm never

Is it worth the engineering hours to

vibe code that and then to maintain it?

>> The maintenance is is definitely one of

the most challenging pieces. Um I agree

with that. I think for most businesses

of of any reasonable scale, yes, it is

worth it. Now whether they will have the

tech resources to do that soon, I think

that's like the bigger question is kind

of when will this happen? But when you

build those things custom to your

workflow, they work better. Like most of

these big, you know, systems, you're

paying an administrator. Like we had a

full-time Salesforce administrator,

right? You're paying people whose sole

job is to manage this like archaic

software platform. Not that Salesforce

is archaic, but you know, we have a few

other like internal apps that we were

paying for like industry software that

is taking multiple FTEEs to maintain it.

You can transition that into one great

engineer and then whenever you want a

custom feature, you just go build it.

>> Absolutely [ __ ] wild. [laughter]

$600,000 a year on Salesforce.

>> Yeah.

>> Wow. And so we're seeing, you know,

there's pockets of software that I think

persist because they are more

infrastructure based.

>> Okay. Which persist?

>> So we're seeing a lot of backend stuff

like uh like Sentry like stuff like

that, right? Where it's like kind of

become part of your infrastructure. Um

Slack has been like notoriously hard

internally for us to like too many so

many people have built integrations and

like workflows that are now working in

Slack. Uh, I think that while they keep

putting the prices up, if they put the

prices up too much, then eventually

it'll make sense to replace that. But,

um,

>> what else is on the chopping block?

>> We we're cutting about 80% of our SAS

spend this year.

>> Wow.

>> So, we have like in in one of our

internal meetings, we have a slide of

like when when are SAS contracts due and

whose job is it to tell them that we're

not renewing this year?

>> Well, you can do it in one fell swoop.

>> Yeah. [laughter]

>> Well, they have renewals. We have to pay

them through the renewal. Ah, is it all

like legacy software like Salesforce

though?

>> Some of it's like that. Some of it's

like very insurance specific software.

Um, so like our claim system for

example, right, is this like massive

off-the-shelf platform that we just

migrated to a few years ago. This is

again why like if I'd known AI was

coming, we would have probably

approached things differently.

>> Um, and it's just it's very hard to use.

Like it's hard. Their API barely works.

It's hard to get the data out of their

database. Uh, they won't let us manage

it. It's it but that's how insurance

companies are running things and so

we've built our own claim system

completely from scratch in house that's

now uh we've migrated most of the

workflows off will be fully off in July

>> I am a health insurer you know other

health insurers

>> yes

>> I do not have the in-house capability

potentially technically to build the

agentic workforce that you are building

>> am I screwed [laughter]

>> I [snorts] think some of the biggest

insurers will struggle because they they

will not be able to keep up from a

margin standpoint with where we can get

to with agents. I think some of them do

have technical expertise. It's more like

operational and kind of people ops. If

you've built a company of 100,000 people

and in order to get this margin

improvement 50,000 of them have to be

laid off, somebody's fift just got a lot

smaller. And so they will do it slowly

over 10 years.

It will happen. But will it happen

quickly? No. And will we be able to

compete more effectively in the

meantime? Yes.

>> How do margins change?

>> Insurance is a very low margin business.

So 85% of your uh premium that we

collect must go out the door to pay for

care. So if we get in a dollar, we got

to spend 85 cents. Have to

[clears throat] by law.

>> If less than that goes out the door, we

have to give it back to the employer.

Which is another thing that's broken

about US healthcare because that drives

completely the wrong incentive where

actually from an insurance company

standpoint if your profit's capped at

15% the only way to increase profits is

to increase total spending which is not

what you want your insurance company

incentivized to do.

>> Why would I encourage people to go to

the gym eat healthily if actually I'm

not going to get that back anyway? So,

this was part of Obamacare and it's one

of the like

>> there's a lot of

>> there's some good things in Obamacare,

but there was a lot of things that I

think like the second order consequence

was not considered. It sounds like a

great PR thing to say we've capped

insurance company profits, right? That

sounds good, but it's BS.

>> It's like capping a CEO's like fiscal

base pay. Sounds great. Yeah. So, let's

just pay them 27 million in equity

compens. That's the reason why we have

such egregious comp packages for exacts

cuz they cap the equ the salary pay.

Ridiculous. With that, how's your

anthropic cost gone? [laughter]

>> Yes. So, I mean, this is one of I think

the kind of leading indicators for us is

that our anthropic cost over the last

like six or seven months has 6xed every

month from, you know, a base of, you

know, a couple of tens of thousands of

dollars now up to millions of dollars a

month. and it just keeps eventually

we're going to have to stop that

spending increase because you know it'll

get unreasonable but um we just keep

finding new things to do with it. And

then the other thing we found that's

been fascinating we're seeing a lot of

areas where it's not that we are

necessarily replacing the team. It's

that we're repurposing the team

[clears throat] and they are now so much

more productive. And so one area that

has always been like a particularly

challenging thing that makes it hard to

build a new insurance company is we have

to build this network. So the network is

all the doctors and all the hospitals

and all the people that we have to

contract with. And there's about 1.2

million of those in the US that you want

to have contracted. That ends up being

like 60 70,000 contracts that you have

to do. That's just a lot of work to go

out, get their attention, get them like

do a negotiation, get them to sign an

agreement, load all of their data and

have them in your network. And this has

been one of the biggest like pieces of

staying power of the big health plan

businesses is they built that over 100

years for Blue Cross and over like 50

years for United Sign. And so they did

it slowly over a long period of time. If

you're trying to from scratch come in

and start a new health plan, you've got

to reach out to all of those doctors and

negotiate. And so we have a team of

about 45 people who do those network

contracts and they reach out and they

negotiate. What we launched earlier this

year is an agent called Gwen.

And Gwen does the same workflow. You

give her basically a lead. Hey, there's

a primary care office over here. Uh

here's the address. and she will go

Google it, research them, learn a little

bit about their practice, um, figure out

what other payers are paying them

because there's a lot of this data out

there and these transparency files now

of how much are they getting paid. Find

their email address from Zoom Info.

Reach out to them and then basically

ping them repeatedly until they answer

her with custom emails like, "Hey, I

know about your practice. I know what

you're doing." Like customized content

to them. Uh, and then when she gets

their attention, negotiate the rates

back and forth, usually over like

multiple rounds of negotiation,

negotiate and redline the language. And

that's another place where we found

Python is great. These models are

terrible at editing Word documents, but

if you tell them to write Python to edit

a Word document, they're great at it.

Great hack. Um, and then sign the

agreement. And so she now signs the

agreements with my signature. She'll

open up the docyign link and then click

the button and it's my signature on that

agreement. And so this has taken us from

doing about a 100 contracts a week to

about 100 contracts a day.

And the last year as an entire team we

did 2,300 contracts. So far in about the

last 8 weeks the agent alone has done

3500. And so what this is letting us do

is like that team doesn't go to zero.

We've refocused that team to work on

these bigger contracts, right? Because

some of these deals we can do entirely

over email. This agent is email only.

And some of these providers will work

completely over email to enter into an

agreement. And actually, how many of

them will do the whole thing over email

surprised me. There's a lot of

millennials I guess on the other end

that don't want to get on the phone um

and would rather do the whole

negotiation completely electronically,

which is fantastic because the model is

great at that. [snorts] But some of

them, the bigger hospital systems, the

bigger doctors uh doctor groups, they

want to have a phone call. They want to

meet in person. They want to learn who

we are. And the team now get to spend

their time going and having those

inerson meetings, going and developing

those relationships, working with those

bigger groups. And then even when it

gets to the paperwork, handing the

paperwork off to the model and then all

of the smaller the individual PCP over

here, the small behavioral health

provider here, the therapist over here,

the agent just gets it done and can sign

a contract end to end in a few hours

where you wouldn't be able to do that

volume with people. Given the

transformational nature of what you're

describing, if Anthropic doubled their

price, would it impact your usage? When

we look at a lot of the financials of

these core businesses today,

>> yeah,

>> they are challenged businesses in their

current infrastructure and pricing.

>> If they double pricing, would it stay

the same?

>> If I say yes, I don't want our anthropic

rep to double our pricing. [laughter]

>> But it would

>> it would work. It would be fine. Yeah.

So, it costs with people, it cost us

about $1,500 to $2,000 on average to do

a contract. Um, the average with Gwen

has been about $70.

So it would still work fine. Um and so

that's what we've seen is like partly

why the token use has exploded for us.

>> Am I being a complete idiot then? But

then if they 5x their pricing if you

went on the labor displacement theory,

>> it would still work.

>> It would still work. I think what

they're betting and what also we've seen

is you don't just displace the labor. So

here like I think contracting is a

perfect example. We've not said okay

we're doing 100 a week so we'll get the

agent to do 100 a week. What we've done

is said, "Well, now that we have the

agent, we can do 10 times as many

contracts this year as we could do last

year. So, we're going to do 10 times and

then we're going to try and do 20 times

and we would just do a lot more volume

than you could possibly have done with a

human team."

>> Everyone's like, "Oh, I lose my job.

Lose my jobs." Do you think that's

warranted?

>> I think for a lot of these back office

jobs, yes, because

>> So, how how do we determine between I'm

just going to do more?

>> Yeah. A lot of people say with

developers, we're not going to get rid

of developers. There's an insatiable

appetite for more software, better

software.

>> That side I do agree with. I think

>> how do we determine between functions

where we'll do more versus we'll be

replaced.

>> So what we've tried to kind of

differentiate at curative is there's

like two areas where we're really

investing in people. That's technical

skills and relationships. Those are two

aspects that I don't see going away

anytime soon is we still have a team

that are actually deploying all of this

AI. They use a ton of AI in all of their

day-to-day work, right? They're not

writing any code anymore. They're not

even reading the code anymore. They're

deploying all of this with cloud code or

codecs. Um, and seeing like incredible

results out of one senior engineer now

is so much more productive than they

were a year ago that we're investing in

having those people. At the same time,

there's a side particularly to health

insurance that is relationship driven

that I don't see as going away anytime

soon. Ultimately, we ensure a member and

that member wants to be able to call and

talk to a person. We have a lot of AI

they can talk to. The AI is great. They

love talking to the AI, but there has to

be a person somewhere in the loop. We

also work with these provider groups. We

have a relationship with that provider

group that we're providing a chunk of

your revenue. You know, we work with

you, you work with us. There's a

relationship aspect there that has to be

maintained particularly for the larger

groups by a person and then on the sales

side we sell through a broker and that

broker wants to have a finalist

presentation. They want to go to dinner.

They want to go and play golf and so

what we've seen is on the sales side

like that relationship is if anything

more powerful. Do you think they still

will in 5 years? A lot of people talk

about agent agent transactions and how

that changes the process. Do you think

we will still have that heavy

relationship interpersonal cell in 5 10

years? I think on in in some aspects yes

because I think in some aspects that's

kind of becomes the foundation of trust

and it's like almost the scarce resource

right of if you want to do a deal that's

important then you're going to use your

scarce resource of people to manage that

as almost like

>> it's also the bigger the contract

>> the more important it is to have the the

whites of the eyes and the trust in the

relationship

>> and and most of these contracts right

most employers even our smallest

employers is it's a million-doll

contract at least.

>> I always think they like when you look

at accountants and lawyers and a lot of

the people who bluntly could be

replacing some of the more simple

especially NBAs or

>> but you would never not have a law firm

do it because if it goes wrong they're

getting fired.

>> Yeah. But I think I I I think you'll see

it work differently though where I mean

what we're seeing with with Gwen is we

had a contract a standard template

contract that was drafted by a law firm

and then we have kind of like guardrails

for what Gwen can agree to. But she just

redlines it and then signs it. She

doesn't it doesn't go to a law firm for

review. Like we're signing hundreds of

these contracts a day. It would be too

encumbering. It would be too slow and

they would just be reviewing with AI

anyway. So we kind of trust the agent to

do that legal review within certain

parameters.

>> In 3 years time, knowing what you do now

about the capabilities that you use it

for, how big do you think anthropic will

be?

>> A lot bigger than they are today.

>> Do you think it could be 5 trillion?

>> I think it could be 10 trillion.

>> Bugger. [ __ ] [laughter]

>> Is just extraordinary, isn't it?

>> Yeah. because I think you just find all

these new things that you can do that

you just couldn't do before that it like

wasn't possible to do. So Gwen is

sending on average 15,000 emails a day.

Customized emails to providers that know

about their practice, that know about

their work, and one of the things we

found is like that relentlessness of the

follow-up is what works. A lot of

providers will get them on the ninth

email. There's no way that a human is

going to email them nine times because

you know people that's like you have to

kind of have no shame to reach out that

many times.

>> Do you want to hear something funny? You

mentioned Salesforce. I got Mark Benny

off on the show cuz I emailed him 53

times [laughter] once every week for a

year and a week.

>> There we go.

>> I'm basically an AI model. I lost my

personality.

>> Very effective AI model.

>> That is extraordinary.

>> But that works so well in sales and it's

and and the best sales people will will

do that. But it's really hard to scale

that and you end up getting people that

reach out three times then give up.

>> Yeah.

>> And when you're trying to scale

something up if you can scale up that

relentlessness like that is really

valuable.

>> So you fundamentally buy the companies

will be inherently smaller in the future

and that's why we're seeing layoffs.

>> Yes.

>> Are layoffs today just an excuse for

overhiring in 2021 and 2022?

>> I think it's a mix. Yeah,

>> I mean I think there is definitely some

of that and you know it's also companies

are seeing valuation boosts by doing it.

So that's incentivizing maybe bad

behavior but some of it for sure is that

these workflows are changing.

>> How big are you today?

>> We're about 650 people now.

>> How big will we be in 5 years time?

>> Well, in 5 years we'll probably be

bigger. In the short term I think we're

going to be quite a bit smaller.

>> Smaller?

>> Yeah. We're not done yet with all of

these backend workflows.

>> How does that go to 400?

>> Uh somewhere [clears throat] around

there.

>> Wow.

>> There's some aspects of the business

that are are clinical workflows. Uh so

all of our members get a care navigator

um who stays with them for their entire

journey and that is just going to grow

linearly with our membership. So we want

you to have that human point of contact

that is available. But the care

navigators are now getting significantly

more useful because they can actually

use the agents to do a lot of the

follow-up on their behalf and they're

not having to remember to reach out to

this diabetic member every week about X.

They can kind of manage it at a

population scale. And so there we're

like keeping the same headcount relative

to our membership growth, but just

letting them do so much more than they

could do before.

>> That's amazing. I was speaking to a

major airline where they were saying

actually about exactly that that like

premium care customer service where it's

like they're able to give so much more

for your recommendations for you and

your wife's trip to New York and

everything's so perfected and tailored

because all the [ __ ] that they used

to do is gone and for you as the end

consumer it's amazing

>> and the response time the response time

is so much better

>> you get a response back in a few minutes

that's that's the usual place where we

see people ask Gwen if she's an AI is um

when she responds to your email within 5

minutes because in healthcare. If you

get a response same week from an

insurance company, you're doing so well.

>> And people think that I'm an AI because

I respond very quickly on email and to

the point I'm like, no, I just have no

life. [laughter]

>> You said about kind of the different

data inputs like, oh, you can just send

us anything now. I always was like data

cleansing, data structures would be the

biggest inhibitor to enterprise adoption

of AI. Is that totally wrong [ __ ]

VC?

I think if you approach it in the right

way, then the cleanliness doesn't really

matter that much because the models are

so good at cleaning up the data if you

give them the right context. And so

that's one of the things we found

actually with migrating away from some

of these SAS vendors is uh we we moved

away from Looker um right Google's

Looker product for visualizations. It's

super expensive. Um and we moved to do

it in Snowflake um and it's been a lot

cheaper. It's worked really well. Part

of that migration is moving all of our

dashboards and all of the things that

fed from Looker would have taken like

probably like a year and a whole bunch

of engineers and data scientists. Uh we

did most of it with an agentic workflow

that would spin up, find the next

dashboard, figure out how to convert it

into what we needed and then close it

down on the Looker side and boot it up

on the other side. And it ended up being

like a project for uh one or two people.

And it took it still took a couple of

months, but it was a lot more doable

because we didn't have to have somebody

ingest or like figure out that data. You

can just feed that data into a model and

let it figure out how to structure it

going forward.

>> It's just really interesting cuz I you

know I often think about what role does

not exist today that will be massive in

5 years time. And I thought like data

cleansing would be one of those roles.

If I asked you what role does not exist

today that you think will be very big in

5 years time, what would you say? agent

supervisor.

>> What does that mean?

>> One of the things we've found that's

been like a bottleneck is when you

launch these agent workflows, there's

always things that they you don't want

to let it do everything, right? So, like

with our contracting or our sales

workflow, like there's a certain margin

threshold where the sales agent can't

promise a client that we'll do it at

that margin, but we don't necessarily

want it to say no. we want to make a

business decision about whether this is

the right thing to do for that client.

>> Um, and so you end up generating this

like massive list of approval requests

that is now much longer than it would

have been because you're doing 10 times

as much work. So you're now getting even

if you're only getting an approval

request 1% of the time, you're still

getting 10% or 10 times as many as you

were last year. And so one of the things

we found is like actually how do you

manage all of those exceptions that now

become like a really high volume. So we

tried agents supervising agents which I

think works to a degree and maybe as the

models get better as well you can also

have like a more expensive right like if

we ever get mythos and it costs $100 per

million tokens you probably wouldn't use

it for the core workflow but you could

maybe use it as a supervisor

but how you actually manage those agents

at scale with like the volume of

exceptions that they generate um because

you don't want them just rubber stamping

yes or no either way like you need a

more nuanced decision there.

>> If you were advising your younger

brother or sister on how to prepare for

that role, what would you advise them to

do to be adequately skilled to do that?

>> I think just play with the models. Like

I think a lot of people severely

underestimate what they're capable of.

um because maybe they like tried ChatGBT

two years ago

[snorts] and and it like they're moving

so fast and they're so much better than

they were even six months ago that if

you're not like relentlessly trying them

then you're going to significantly

underestimate and then also like where

they are today is not where they're

going to be clearly in a few years. So

you got to skate to where the puck is

going to be.

>> Where will they be in a few years?

>> Ahead of humans on most capabilities.

>> Are you excited? [laughter]

Yes, cuz I think that opens up so many

possibilities like unlimited

intelligence.

>> Are you not worried about in the short

term societal unrest, labor displacement

and what that will do to a hollowing out

an inequality increase in the US?

>> I think that can be dealt with by

significant action whether or not we do

that or not.

>> What significant action would you do to

mitigate that?

>> I mean, I think eventually some version

of universal basic income.

>> Really?

>> Yeah. and you buy that works.

>> I mean, I think we have to build the

social structures that give those people

purpose and meaning outside of work

because I don't think that we're going

to have and I also I don't think that's

a bad thing. Like a lot of these

mid-level jobs that are being replaced

are awful jobs. They're people sitting

at a desk with like fluorescent lamps

shining at their face reviewing random

paperwork. Like that's not what people

like, you know, when you're little and

you say, "What do you want to be when

you grow up?" I want to sit in an office

and rubber stamp insurance forms. Like

it's not a good job.

>> I would be worried if my child.

[laughter]

>> Right. So these are not like it's not

like you're taking some like super

aspirational thing away from people. I

think these are jobs that we'll look

back and say, "God, I can't believe we

had people doing that kind of work.

That's crazy."

>> You know, I I walk with my mother a lot

and I always say my job is to invest in

the things that we say, "God, I can't

believe we used to do it that way." I

[laughter] said, "Do you remember? I

would never put my credit card on the

internet or you'd never find your like

husband on the internet.

>> You'd never get in a stranger's car and

uh and have them drive you where you

want to go.

>> What is insane today that will be

incredibly d obviously you have your

card online, obviously you meet your

partner online. What is insane today

that you think will be like obviously in

10 years? I think empowering agents to

do things on your behalf. Like we've

seen internally getting the team I think

like uh Isaac our our CTO and co-founder

and I have like trusted the agents

faster than most of the team and we're

okay like giving the agent authority to

do things like it was a big internal

dispute getting the agent to sign these

contracts. So the agent opens Docu Sign

and clicks the sign button and it's

legally binding and it has my signature

on the page. And getting that like

figured out internally was very it took

a lot of rounds of convincing people

that that was okay and that we could do

that. And so I think it will take time

for people to trust these agents with

stuff like you know give it your credit

card and let it go book a a holiday,

right? like getting getting people to

trust

it acting on your behalf I think will

take longer

>> but I'm thrilled that you signed me your

house for $12.

>> Uh do you worry about the concentration

of value when you look at the Mag 7

providing 85% of gains here today in

stock markets and then anthropic open AI

maybe one or two more. Do you worry

about that concentration of value? I'm

quite bullish now because I think a lot

of what's going on in AI is going to

massively boost earnings in other areas

of the economy that have struggled to

grow earnings any other way. Like if

you're health insurance,

>> like health insurance, like how do you

grow health insurance earnings? Well,

it's been or you go chase government

business and you pay a bunch of

lobbyists to get the government to

overpay for care. That's all now

backfired and all the government

business, Medicare and Medicaid is now

like a bad business and they're all

losing money. Everybody has insurance.

So unless you're going to increase the

total spending, how do you grow

earnings? Well, if you can make it more

efficient so you're not spending 9% of

your premium on admin tasks, that's a

way you can grow earnings without having

to deliver a worse product.

>> You're in a really good business as well

cuz it's like unwaveringly not in the

path of the model providers as well.

>> Yes, I not going to start an insurance

company. in the past like we're big

invest in wallets which is like business

[clears throat] banking like anthropics

is not going into business banking

>> in Southeast Asia [laughter]

>> I would be surprised I think things that

have some like regulation around them

and are like complex industries yes

they're going to see the advantages of

the models but they're not going to see

competition from anthropic or open AAI

>> I totally get that when I listen to you

I'm like Jesus if I was you I'd also

take a chunk of my money and invest it

actively into anthropic um can I ask you

have you taken secondaries along the

way?

>> Uh no, no, we haven't sold any

secondaries. We did uh there was a

dividend at the end of co we paid out

some uh all the investors got uh 10x

their money back uh before we started

the health insurance company and then

they still have their shares today.

>> We haven't sold any secondaries now.

>> Are you [ __ ] serious? They got 10x

their money back and then they kept the

shares.

>> We didn't have that many investors but

yes they they all did well.

>> That is an amazing deal. [laughter]

10x and then you keep the shares. Yeah.

>> What?

>> Well, I think that's why we've seen them

double down, right? It's like they made

money with us before and so, you know,

this last round was was led by insiders.

>> And how big was the last round?

>> 150 million.

>> What was the prize?

>> 1.3 billion.

>> Wow. Nice round actually. Not too much

dilution. Enough that it's really

impactful cashwise to come in.

>> Yeah.

>> Wow, dude. That's insane. So, can I ask

you then personally? I asked this

actually, do you know Josh Browder? He's

another Brit in the valley. Okay. Um, a

phenomenal guy, but like when you look

at your personal allocation today, given

our insider access and what we know,

>> is there anything funky that you do with

your money

>> outside of of curative? Yeah,

>> I invest primarily in companies of

people that I know and I do very little

investing if I don't know the founders.

>> Does that work well?

It's had mixed results, but some of them

are too early to tell. Some of them are

the best investment.

>> Um,

they're all they're all a bit too early

to to tell. [laughter]

>> Do you have any energy investments?

>> Uh, yes. So, there is a company that um

I co-founded with my wife, Subcritical,

that is um in the nuclear fision space.

So, this was based on an an idea that I

had a few years ago that um we need more

power and that nuclear is a really good

way to do this. Uh and it started off

actually as looking for an investment.

This was like one of my f first times I

was like we should find a company that's

doing nuclear power and try and invest

in it and see if we can make it go

faster. Um because I kind of thought

I'm pretty good at making things go

faster in really regulated spaces. Like

that's kind of what I'm what I'm good

at.

>> That's your thing. Yeah, that's my

thing. You know, everybody's got to have

a thing.

>> And so,

>> is that your hook on the first date?

Regulated industries make a good first

hook on our first date. So, after our

first date, we both shared our genome

files with each other, our VCF like um

and so she said she'd done this before

and the guy thought it was really

strange and we both were like, "Oh, we

should share our genomes and then, you

know, compared and check that we were

compatible so it was worth having a

second date." And we were both totally

into that. So, we We knew it was meant

to be. We were compatible by genome.

>> We have two beautiful kids, so we uh we

knew it was meant to be.

>> I'm sorry. If you're incompatible by

genome, you have like a

>> If you both have like the same

>> You have a ginger child.

>> Well, that was a concern. My brother is

ginger. So, I carry the ginger.

>> My brother is ginger, too. Yeah.

>> We We don't see him anymore. We took him

to the woods and said, "Run free."

>> Makes sense. Yeah. [laughter] So, I do

carry the ginger gene. And if she had

carried the ginger gene, that would have

been a deep concern. but she luckily

doesn't. And so that was that was one of

the key tests.

>> You progressed to the second date.

>> Yes. So we made it to the second date.

>> What does no one know about nuclear that

everyone should know about nuclear?

>> That it is very safe. I think and that

it's not a science or engineering

problem. Like that was when when we

started looking at companies to invest

in that was for me that the thing that I

was sort of disappointed by is everybody

was approaching it as if nuclear is this

massive engineering challenge. And sure

like the engineering is hard. It is

complicated. But fundamentally we have

built safe nuclear reactors since the

60s. They work great. The technology has

not really changed or progressed since

then. We know how to build these. That's

not the problem. The problem is that due

to a lot of the anti-uclear push in the

80s, we have had a regulatory

environment that has been incredibly

restrictive and difficult to get new

nuclear reactors built particularly in

the US but also worldwide. Uh there's

been this push to say how do you

guarantee that under any possible

circumstance like once in a million-year

events that you will never have anything

go wrong. And in traditional nuclear

that is very hard to guarantee. In

traditional nuclear one of the reasons

it's difficult you're basically

balancing on this knife edge. So in a

reactor you have uh what's called

criticality right which is where you

have to produce enough neutrons each

generation that they go off and do

exactly one more reaction and it keeps

itself going. If you get too much of

that too many neutrons it's a bomb,

right? It will be a runaway reaction and

it will blow up. That's very bad. that's

only ever happened once by accident,

which is Chernobyl. Um, all the others

have been not criticality events. Um, so

you don't want that. If it happens not

enough, then it just turns off. So if

you go too far below this exact 1.0

threshold, you get no power out. And so

you're trying to balance perfectly on

that knife edge of exactly 1.0 where you

can control it. And that is a hard

problem to guarantee. And this is the

fundamental issue with nuclear

regulation. How do you guarantee that

under no possible circumstances will you

deviate from that perfect control?

And so I was initially pretty

disheartened. I was like, well, we're

not going to get new nuclear power. This

is not going to work. And then I

stumbled on this idea of what's called

the energy amplifier. And it's not a new

technology. It's been around since like

the late ' 80s, early 90s. It was really

pushed by a guy Kar Rubia who used to be

the CERN director. He was a new uh Nobel

laurat in physics. And the idea is you

always operate below that 1.0 threshold.

So we are designed to operate at 0.97.

So that means you never have enough

neutrons to keep the reaction going. The

reaction will always fizzle out. So no

matter what you do, it's going to fizzle

out. But normally that would mean you

get no power output. What you do in the

energy amplifier is you point a really

powerful particle accelerator at that

fuel and that puts in the extra neutrons

to drive the reaction forward. But if

you turn that accelerator off, all of

your energy output just stops. And so

you basically have this big onoff switch

where you can control fision and you can

guarantee that no matter what you do to

it, the fision will never run away. Even

if you put in 10 times as much power

from the accelerator, it will never run

away. There's nothing you can do to it

to cause it to go critical or to have a

criticality accident. And so it's a

fundamentally safer way of doing nuclear

fision that is

just approaching it from a different

angle. How will the composition of our

energy providing change in the next 5 to

10 years? Like will nuclear be a

demonstrabably larger part of energy

provision than it is today?

>> Yes, I think what we're seeing kind of

all across the supply chain in nuclear

is a push to get more nuclear online. Um

and I think you know Subcritical is kind

of leading the way there with a faster

path to market than any of the other

players. Uh but there's a lot of people

working on deploying a lot of new

nuclear power

>> which current provision will diminish

significantly.

>> Um I mean I think any power from coal

will will mostly go away. I think you're

still going to see a lot of gas just

because particularly in the US it's

cheap, it works, it's fast, but I think

coal is going to go away. Um and then

you're just going to see more of

everything. What company will be larger,

curative or subcritical?

>> Subcritical. Yeah.

>> Or subcritical.

>> That's a great question. Um, curative

has a larger market opportunity, but I

think they're both

>> has a larger market opportunity.

>> Yeah. I think they're both, you know,

>> power generation.

>> Yeah. The uh US spends or US employers

spend $1 half trillion dollars a year on

healthcare, which is that's our like

direct TAM every single year.

>> How much does the US spend on energy?

through energy that can be addressed

through um through nuclear. It's a

similar order of magnitude.

>> I mean, you chose good ts.

>> They're both they're both yield

optimization. I feel like you've really

really taken this

>> I figured out the TAM thing. [laughter]

No, they're both like trillion dollar

opportunities if we execute right.

>> [ __ ]

>> Yeah.

>> Wow. We're also seeing AI on the on the

nuclear side in the design

>> because design is like traditionally a

thing that is done by a whole bunch of

people sitting doing drawings and

mechanical engineering

>> and the models have gotten really good

at that. And so we're seeing that you

can do the design with far fewer people

using AI to optimize a lot of the design

parameters where historically you might

have needed a hundred mechanical

engineers to design every single nut and

bolt and part. You can do it with with

20 really good mechanical engineers that

are designing the critical pieces, the

important pieces um and overseeing the

AI on like well I need a little bracket

that joins this piece to this piece that

doesn't need a human to design that. I

was actually meeting a company the other

day which basically said like you know

the challenge with hardware engineers is

they don't often know what software

engineering and the beauty of today is

like we've turned hardware engineers

into software engineers overnight.

>> Yeah.

>> And that's amazing.

>> Well, it's another place where we saw

like codegen as the solution and I think

you know this is one of the bets

anthropic made and they're totally right

on.

You can generate really good CAD models

by having it write Python to make the

CAD model. like it's not good at

necessarily good at like 3D space

visualization or outputting a drawing

um right as as vectors but it's really

really good at generating plausible

Python code that can draw that part.

>> It is the most exciting time to be alive

in many respects.

>> Yeah. Yeah. Well, that's why we ended up

starting Subcritical is I you know very

busy running curative but that was an

idea that was just too important to pass

up and there was nobody else. So uh the

only one that is under like active

construction of those systems is in

China based on a US design from the

2010s that the US stopped working on

after Fukushima.

>> How much money do you need to make

subcritical significant?

>> Uh well each one of our deployments

would be about a billion dollars of

construction cost for a 300 megawatt

facility. So it's but it's not you know

it wouldn't be the same like you

wouldn't raise that as equity. It would

be a mix into the plant of equity and

debt. So, it's a different kind of it's

more infrastructure build financing.

>> What do you know now about marriage that

you wish you'd known at the beginning?

Seriously, like it's an amazing thing to

build a company with your wife.

>> It's a challenging thing as well.

>> Yes.

>> How do you make it work?

>> So, I we're very well matched, I think,

is one of the things is we basically

never argue. And that's, you know, how I

knew very early on that it was meant to

be is we're always on the same page

about things. And so it's actually very

easy to run a company together uh

because we're we we usually see eye to

eye on like how something should be

done.

>> Fatherhood. You said two kids. Two kids.

Two and a halfyear-old and 6 months.

>> Anything that you would advise a new

father knowing what you know now?

>> You should definitely have kids. Don't

wait. I mean I think there's too much

like um sentiment of people. Oh, you

know, live your life and wait until

you're in your, you know, late 30s and

then have kids. I think no, like have

kids early when you're have the energy

and can run around and not sleep and

it's one of the best things you'll ever

do. You should just get on with it.

[laughter]

>> Okay, we're going to do a quick fire.

Sound good?

>> Yep.

>> Dude, that was the most uh twisting and

turning conversation ever from like the

proliferation of STDs to fatherhood and

nuclear. I mean, really, we crushed it.

What have you changed your mind on most

in the last 12 months?

>> I think probably a year ago I have

changed my mind that there are workflows

that can't be done with the models with

today's models. I think today the

current gen models can do every back

office task we have at curative it's

just a matter of deploying them like

getting them set up getting them

configured having the right policies and

and I think a year ago

I thought there was opportunity I

thought there was things we could do but

I don't think I would have said you

could do every single one of our current

back office flows

>> what one change would you make to Europe

if I made you president of Europe in

this very strange title to stay in the

brace for competitiveness.

>> Uh you have to have some kind of like

burden for passing regulation. There

needs to be some penalty. Like right now

you pass a regulation that's like okay

you you did a good job. Like the goal is

to pass regulation. There has to be some

penalty. Like the if you pass regulation

your country must pay some tax

additional tax for having passed that

regulation. just adding and adding and

adding uh without like refining what

you've got today and like really going

and digging in how is this regulation

affecting things on the ground like just

more additive regulation is bad. You

need to be looking at the effect of what

you've done and refining it and

iterating on it and not just trying to

add some new landmark regulation.

>> It's very anti-European Fred. You're not

going to [laughter] do anything. You're

not going to do very well here for a

reason. I mean, you know, I'm a Texan

now. Um, uh, Mark Benio said he spent

300 million on Anthropic. Equated across

the developers that they have, it works

out to be about 3.8% of developer salary

spent on Anthropic. What do you think

total percent of developer salary spend

will be on anthropic in 3 years time?

>> Between maybe two and 5x be the two and

5x salary. I think that's probably

>> 2 to 5x is the whole salary.

>> Yeah.

>> Whoa.

So from 3.8% 8% of salary to

>> Yeah. Because I think the way I mean the

way we're driving workflows is that you