Hi everyone, thanks so much for joining me today.
Today I'm talking to Amit Mehta.
He's an interventional radiologist and a general partner at Builders VC.
Builders VC is a $450 million venture capital firm.
They invest across all verticals, including healthcare.
I hope you guys enjoyed the conversation with Amit as much as I did.
Amit, thanks so much for coming on the podcast.
Really looking forward to this call.
To start, if you want to give us a brief introduction and then we'll get right into it.
Sure.
So, I grew up in Canada.
I spent my childhood in Toronto, went to school in Canada and then saw some need for some
technology as I was moving through medical school and figured that I couldn't do it there
in Canada.
So, for residency, decided to come to the US and work specifically on some specific
problems.
So, I trained through the Harvard system at Mass General, did essentially all my training
there, fellowship and then ran a lab, research lab there for a few years while I was doing
residency and did a few other things that were of interest.
But during that time, got interested in investing and startup and got involved in that whole
ecosystem there.
Once I finished training, I had a thesis to run that lab there but then decided, had spent
an infinitesimally small amount of money on my medical school education compared to my
cohorts in the US and felt bad.
So, I said, I'm going to come back to Canada and not contribute to the brain drain.
So, moved back to Canada and worked in Canada for a couple of years, again, trying to move
forward some of these ideas that I was working on in telemedicine and teleradiology and all
of this kind of stuff.
In that process, my wife who was from LA hated the cold and said, we got to move somewhere
warm.
And so, in that journey, moved back to the US and kept going on all the things that I
was doing.
Tell me a bit more about what tech did you foresee that was not feasible in Canada and
you hinted towards teleradiology and telemedicine.
And was it not feasible because of reimbursement issues, regulatory issues or something else?
Yes.
Basically, all of the above.
So conceptually, what I was working on when I was doing residency and fellowship was a
combination of telemedicine but also applying telemedicine and teleradiology into the clinical
trial sphere.
And that didn't work in Canada for a couple of reasons.
One, I mean, there was no concept of telemedicine from both a technologic infrastructure standpoint
nor from a reimbursement standpoint.
There was no drive to even innovate in that space, venture and startup and all of which
now is very robust in Canada through Mars and through BDC and a lot of the entities
that as a VC now, those entities are actually limited partners in our funds.
There was none of that.
This was 15 years ago.
And so I tried to push this agenda of what at the time I thought was sort of revolutionary
in terms of bringing care to underserviced areas, which was a big problem in Canada,
right?
Northern Ontario and lots of other places.
There was just no appetite for it.
And the extension of that was what I initially had dreamt of was working on a clinical trial
company where we had some technology and some ideas around making clinical trials more efficient
and subsequently, several years later, did start that company, ran that and then we sold
that company last year to a public.
So in the end, it turned out and there was fruition to all the goals, but in Canada,
I just didn't feel like I could get it done.
Have you seen, and I've had similar experiences with my startup in Canada and talking to the
Ministry of Health here as their primary goal is being reelected and nothing else.
Have you seen any changes now and if you were a resident or in med school now, would you
have stayed in Canada or do you think things are more or less the same still?
No, I think it's done a complete 180 and it's completely changed.
I mean, we're sourcing a lot of our deals on the venture side from Canada.
We have a mandate because these Canadian entities, Alberta Enterprise and a few others are LPs
in our fund.
We have a Canadian mandate that we need to spend a certain amount of money in Canada
and we don't have trouble finding deals.
So I think that entire innovation ecosystem has completely blossomed from the time that
I was there and the difficulty what I had in terms of just the whole life cycle of a
startup from fundraising to infrastructure to human capital.
I just don't see that happening now.
I mean, it's not, I don't think it's Silicon Valley, but it's also not as difficult it
was when it was when I was doing it.
Okay, yeah, that's good to hear.
Let's go back to your childhood, Ahmed.
Let's go back to when you were about 10, 15, maybe in high school.
What did you want to be then?
And once you were in med school, did you, most people in med school think they're going
to be a doctor forever, as did I.
When did that change for you?
And did you say, okay, this isn't enough for me and I want to do something else or something
more?
I always wanted to be a doctor.
I think I grew up in a family with physicians and all of the rest of, you know, typical
sort of immigrant story, but I had a very, I think an interest in technology and a technological
bent in terms of tinkering and, you know, ran illegal bulletin boards out of my attic
and got in trouble with my parents and all of that kind of stuff when I was a kid.
And so I was at an interest in technology.
And so I was driven towards a technologic field and it was more finding the right time
to start working on those ideas as opposed to trying to generate the idea or is it something
I want to work on?
I had determined I wanted to work on it very early.
It was just, you know, back then it wasn't cool to be 17 and start a company as it is
now, if you're 30, it's not cool.
You need to be 15 to start a company.
So that dynamic was very different.
It was hard to get taken seriously as a 17, 18 year old, you know, and I mean, you guys
are in Canada, you're in Canada, the back of the, I mean, I did the two year university
four year med school thing.
And so on top of that, I was going into being, you know, medical school really young, like
16, 17.
So it was hard to get, it was hard to be taken seriously.
But I had those ideas and I was always working on those ideas as I kind of progressed through
the system.
So medicine was sort of, it was the day job and work on going through medical school and
the academic component of it, but was working on those things at my own time.
Okay, perfect.
And why did you decide to pick intervention radiology?
Primarily, again, like I'm at a very tech bent.
It was very, I think it was a combination of a couple of things.
One is, you know, you say, there's so many experiences shape who you are.
So like I was telling you, like I went to medical school very early.
Like I remember taking a primary care rotation and just patients just were like, you're too
young to be my doc.
Like I just was young and so people didn't take me seriously.
So that was sort of steered me away from patient facing things almost off the bat because of
this sort of this discrimination on age to a certain extent.
But I did have a very tech bent.
And so I was looking for things that were very heavy in that.
So it almost fed me towards surgical specialties off the bat.
And as I got further, I realized that maybe I'm a little bit ADHD and that, you know,
I like to move very quickly and efficiently.
And so radiology was something that was like that one.
It wasn't as patient facing as I didn't want completely not patient facing, which, you
know, interventional reality still is patient interaction.
It's not all interpretation, but it was less patient facing.
It was tech oriented.
I could innovate in that space and it was still it was a high volume of cases moving
very quickly, which was very attuned to my personality.
So I think I was kind of lucky to find that early on that I found something that fits
my personality.
I never went through that concentration of is this the right thing for me or is this
the right specialty?
Like I loved it from the beginning and I've always loved I mean, to this day, I still
enjoy it.
Okay, perfect.
You've had a lot of different experiences in the past 10 years.
I'm and you know, someone would look at the resume and say, I'm a doesn't stick with things
to an extent is tell me a bit more about joining your most favorite experience and then your
least favorite if you'd like to.
And what made the decision to were you like, I'm here for this job.
I'm going to take this company from point A to point B when it's a point B, I'm going
to leave or what was the thought process behind that?
Yeah, it's funny.
I think my detractors would say the opposite, I stick with things too long.
So a lot of these Yeah, interestingly, I probably doing too many things and doing all of them
at the same time as opposed to doing one and letting it go.
But you know, the most interesting thing I think is definitely all for me as always been
is been venture and being a GP and a fund and investing and all of the cool ideas and
things you think about and figuring out a process of how to be a good investor and how
to work on that.
I mean, absolutely, that's been it's been fun.
And it's been the exposure is incredible.
You get to see things and touch things and do things that just you don't get any other
way.
Interesting way I would tell you that the flip side of that probably and I wouldn't
say this is the worst experience, but the most difficult has been starting and selling
this company like it was eight years of, you know, it was 100 hour weeks just working,
it was stressful.
And you know, it was enjoyable to a certain extent for certain things.
But at the same time, it was very stressful to running a company running a you know, being
a physician doing venture like it was just probably a lot of things at the same time.
But at the same rate, it was instrumental, I think, in in forming a foundation for me
to be a better investor, you know, coming from an operator perspective, to becoming
an investor is a very different mode than just trying to be a primary investor.
You know, I mean, this morning, I spent, you know, three hours on calls going through with
entrepreneurs looking at 2023 budgets and pro forma is an understanding how to work
out, you know, how to run a pro forma to make sure that your cause doesn't exceed your revenue
and that your human capital is being, you know, all of that only comes from operational
experience.
It's hard to get that unless you've seen hundreds and hundreds of things or you've spent time
very focused and understanding that specific problem.
And so it was an education by fire to a certain extent that I think has helped me as an investor
Okay, perfect.
A lot of people are looking at the rising interest rates, recession and kind of buckling
down, keeping more money in cash, not deploying as much capital.
You know, I look at public and private markets as two different entities.
I don't even try and compare the two.
What is your strategy moving over the next six or 12 months?
Are you changing the way you look at startups?
Are you looking for startups that are almost maybe revenue neutral and whereas before you
would be have more laxity there?
Is your investment thesis changing at all and are you deploying less or more capital
over the next six or 12 months?
So I mean, there's a personal component and then there's an institutional component, right?
And I would say on the institutional side, we are a series A fund and a seed fund.
And so what's just evolved in the venture landscape is sort of valuations more than anything else.
I mean, we're still with the companies we were investing in already were in a situation
where they were often were not that revenue positive.
They were beyond proof of concept, beyond seed stage companies, but they had not hit
that hockey stick of growth yet.
So that hasn't changed.
I mean, we're still investing at the same level and series.
It's just some of the deal metrics have changed in terms of valuations, in terms of ownership
or what we're doing for that company.
Our stage size of check and involvement in the company has stayed the same as it was
a year or two or five ago.
So we're not, you know, there's just these, I think, you know, part of the benefit of
now being older is that this is cyclical, right?
And I've been through a couple of cycles of this now and understand that all we did really
honestly be truthful with you is we told our companies that, you know, you should stockpile
30 months, you know, going out into the fundraising environment in the next 12 to 18 months is
going to be really difficult unless you are one of the winning companies.
I mean, if you're a winning company, there is money in the system, venture, whatever
you want to say that has to be deployed, right?
By definition, funds work by deploying capital.
So that capital is going to be deployed to the winners.
And so if you're a winner, it should be okay, but if you're on the precipice of being a
winner or you're not a winner, then you need to hoard cash now.
It's not that we think you're a bad company.
It's just your life cycle over the next 18 months is going to be very different than
a year ago when everyone was falling all over themselves.
We had deals that were valued at 100 X ARR.
I mean, I haven't seen a deal like that in nine months.
Like, I mean, if you try to sell a deal now at 100 X ARR, people will just laugh at you
and be like, you know, good luck.
So I think that's the biggest shift is be conservative and, you know, we all hope our
companies are winners.
So if they're a winner, it's great.
We can help them raise money.
But if they're not or their inflection point is going to be a little more difficult.
Okay, perfect.
Talk to me about your first LP.
How long did it take to get that investment?
And does it get much easier after the first LP?
There's a few GPs with smaller funds who listen to this, and I think they'd be very interested
in the answer.
Contrary to what everyone else says, I find fundraising the most difficult thing in the
world.
I mean, every single meeting is a different minefield.
So in essence, right, in venture, I mean, as well as personal probably trackers, if
you've had a track record of great investments, it speaks for itself.
And this is like when you run a company.
You know, when there's sales, everyone's happy.
When there's no sales, then all of the problems start to come up.
And, you know, this person is not doing this and that person is not doing this or this
infrastructure is broken.
So in venture, if your funds are doing well and you have returned that follow up meeting
with an LP to ask for a check for the next fund is very straightforward because so look,
we returned you 5x on our last fund.
It's almost a fait accompli.
Like, why wouldn't you put money into this next fund?
The trouble is when your funds are not doing well, and you're asking for re-ups on checks.
That's when it's difficult.
But my philosophy has always been, you know, and this is somewhat medical, you know, driven
in medicine into that if you're not doing something well, then maybe you need to look
at some other, you know, don't kill people, like maybe pick another surgical specialist
or something like you need to you need to pivot.
And so luckily, our funds have done very well from the inception.
And so we, you know, going into these LPs is more of a relationship driven fundraise
rather than trying to prove our economics, our DPI and our, you know, everything has
been good.
So we haven't had that issue.
Okay, perfect.
When I think about my past investments, when I look at companies, I'm looking to invest
right now, I usually look at the level of conviction I have and the potential reward.
And usually sometimes I may have a lower level of conviction, but I'm getting in at a cheap
valuation and there's a high level of reward.
Talk to me about, I'll ask you about your best or your favorite investment first and
we'll talk about your least favorite next.
What was your level of conviction?
What was the balance between your level of conviction and a potential reward in your
favorite investment and then your least favorite?
Yeah, I mean, I think that's a pretty difficult question to answer from a VC perspective.
The decision is multifactorial, right?
There's a myriad of things that go into deciding whether you make an investment, whether it's,
you know, of which the entrepreneur is very important, the total market is important,
the product is important, fit, all of those things go into that decision.
I would say I've never made an investment that I didn't have a hundred percent full
conviction on.
Whatever got me to that level of conviction was different probably every time.
And there's ebbs and flows.
And like I think, again, like I said, as you understand, there's cycles in this stuff,
there's different things at different times that are applicable, especially in healthcare,
right?
Healthcare investing is probably to me is more difficult than some of the other disciplines
just because it's so heterogeneous.
There's multiple verticals, there's payers, there's providers, there's patients, there's
a FinTech component, there's a tech component, there's, you know, applicability in the market,
there's hospitals, ACOs, clinics, I mean, it goes on and on and on, right?
And so it's always at the end of the day, it's always been a hundred percent conviction,
but the conviction has been around different things.
And that's dependent on the cycle we're in, you know, decreasing reimbursement rates,
is there opportunity of FinTech opportunities in healthcare right now, as opposed to, I
think, during COVID and the pandemic, there was a lot of opportunity for remote care and
moving tertiary care outside of the hospital to the home, remote monitoring, IOT.
So there's a different, the conviction comes around different elements of the opportunity
at the time in the cycle we're at.
Okay, perfect.
Amit, would you rather have a life of many successes, but no major success?
Or would you rather have a life similar to Vincent van Gogh's?
He had massive, what we would call failures, was not recognized in his own life, you know,
infamously famous now.
Would you rather have Vincent van Gogh's life, a hard life, lots of failures, no success
while you were living, or a life of many successes, but you're not known, and you don't change
the world in any substantial capacity?
Yeah, I mean, I don't think the human brain is probably not wired to enjoy failure.
So I don't, you know, I think it'd probably be the former.
Yes, obviously, success feels good.
But success and failure, I think, again, are also probably very, it's a very individual
term.
And what one may, you know, if you have an exit out of your company for $50,000, is that
successful versus someone who has a $50 million or a $500 million exit?
Once you've had a $500 million exit, then your next exit needs to be $5 billion, or
you weren't successful.
You know, your next exit at $500K is not successful, right?
So I think some of that is just shaped on your experience.
And what I've done, you know, I've tried to build a career around three facets, right?
So there's a medical career, an actual physical operating career, the investment career, and
then the innovative or the operator career of starting a company, running a company,
and tried to bring all three of those things together to optimize what I can do as an investor,
as a physician, and as an operator for each of those.
So I think, I feel like success has been different in each of those things, and failure has been
in each of those things.
Like, you know, our failure on the operating side is very different than failure on the
investing side, which means we lost $15 million in investment.
Failure on the operating side is that we couldn't motivate our salespeople to make enough sales.
You know, the magnitude of importance of those things are very different as for me as an
individual, but as in my responsibility in each of those entities, is probably of equal
importance.
So it's just very dependent on what lens you're looking at it from, but I would say I don't
like, I mean, I don't like failure.
So I'm going to go with success more than failure.
Okay, perfect.
What advice do you have for founders trying to sell to health systems right now?
How much should they, a lot of founders that come to me, they focus too much on clinical
ROI and not enough on immediate financial ROI, which I feel a lot of health systems,
ACOs, family health teams are more focused on and decisions are made more on financial
ROI.
You have a lot more experience than I do.
It's more of a selfish question for me and what advice I should give to my founders right
now.
What advice would you give to founders trying to sell into health systems right now?
You know, I said the thing that I think is the hardest thing to do in the world is to
raise money from LPs.
Let me give you a very, very close second is to sell into a hospital system.
So, you know, selling to a hospital system, the problem is the incentives are probably
perverse and it's very difficult to understand what those are in that the driver for a hospital
system may not be what you...
If you are not a provider or been on the medical staff or a CMO or a CMIO, whatever it may
be, you may not understand what the driver is for that hospital system, hospital administrator
who, you know, not a popular thing to say, but as we all know, they seem to rotate every
two months.
There's a new hospital administrator, right?
The velocity of change in the hospital administrator is incredible.
So I would say try to focus on products that probably don't sell to the hospital first,
but saw more of a large clinical need where the hospital is where you end up as your larger
clients once you've established a base with whatever else it may be.
So telemedicine is a good example.
Telemedicine is very applicable to hospital interactions, but maybe start in another setting,
both prove out your infrastructure, prove out your business model, prove out your finances,
and then that's the bigger fish to go after.
Okay, perfect.
Yeah, I mean, A16Z recently released their report about the pay-vider model and their
banking on BTC consumer health.
Let's talk a bit about the reimbursement structures in healthcare.
And then particularly, do you think healthcare should be profitable?
If so, what parts of healthcare should be profitable?
Should it be primary care?
Should it be more acute care, hospital care?
As it stands now, the most profitable parts of healthcare are cancer therapy, surgeries,
which I think should be perhaps at least profitable.
And I also think innovation in healthcare should be decoupled from delivery of healthcare.
So I'd like to get your thoughts on innovation and delivery in healthcare.
Should they be different financial systems and incentives for both and profitability
in healthcare?
Yeah, that's a very interesting question.
So I've worked in the US system and the Canadian system, and we've done a lot of work in the
UK system.
So I've seen three very different models of healthcare, worked in two of them and worked
very closely in the third.
And so I will tell you, I think my personal opinion is there's probably no optimal system.
But the answer to your first question is I do think healthcare should be profitable.
I think there's a governor on how profitable and some of that is ensuring that it needs
... I think part of the problem right now is, and CMS and some of the other systems
have made an effort towards this, but there is an essential decoupling of quality versus
reimbursement.
And we're moving towards trying to fix that, but in a lot of ways that's almost not fixable
or has not been fixed.
But I think that it is reasonable to make it a profitable system where you're based
on quality and pay for quality.
And the reason I say that is, I know you're saying a decouple innovation, but I think
innovation is driven by that.
People do go into medicine because financially it is satisfying.
You do make good money as a doctor.
It's not a secret.
If you start eliminating the financial benefit, if you're building a system from de novo
and that there's that opportunity, that's different.
But in the current system, if you said, well, doctors are going to start making a 10th of
what they make now, you're going to lose some of the best and brightest from going into
medicine and then quality will drop and et cetera.
There's a fallout from that.
So I think in the confines of the current system, it does need to be profitable, but
I do believe insurance companies have taken this to a different level and the system has
been perverted in order to have oversized returns for United.
If you look at just look at their filing, the amount of money insurance is making is
out of proportion to what we see on the street and what happens in terms of patients being
either not getting a pre-op or being steered towards certain providers or whatever is happening
for the people in the trenches.
Okay, perfect.
Let's talk about tailwinds.
One tailwind I'm banking on as a hybrid home care model for acute care.
Take me back 10 years.
What are some tailwinds you were identifying then that you were right about and what are
some you were wrong about?
So I sort of built at Builders our healthcare thesis around sort of four pillars of which
I think they've all sort of come true.
So the first and the paramount was the concept of moving care from hospital, surgery center,
tertiary care center to the home as much as possible, cheaper, faster, better, more convenient
and using technology in order to do that.
The first iteration or generation of that tech was sort of remote monitoring, IOT, host
of techniques such as that companies like Lavongo and even Fitbits and that kind of
thing have used.
So a concept of moving, it's not necessary to treat a copper strep in a tertiary care
hospital at three grand a visit.
You can do that at home, telemedicine for 15 bucks.
So that is a generic concept of moving care away from the sort of very expensive to cheaper
care centers.
That was a big thesis of which we made some investments around that happening into a company
called Carbon Health and a couple of others.
Second was a true understanding that I think the omics space is going to revolutionize
a lot of what we do whether it's genomics, protanomics, metabolomics, radioma, all of
these omic kind of things.
Basically driven towards a better understanding of each individual rather than at a population
level.
And so I can tell you personally, we see this all the time, people that come into the emergency
room, they have abdominal pain, trigger a CT, which is a thousand dollar test.
They had some bad chicken and they go home because it's a normal CT.
I think we had a test at home that we knew that you had a, you know, whatever it may
be, a tryptophan allergy and you probably shouldn't drink this kind of red wine.
And it's because you had that red wine with your chicken and that's why you have belly
pain.
And we just saved the system a thousand dollars, an ER visit and a CT scan.
So that personalized medicine component of it, I think is coming.
And we're seeing that with companies like Everly Well and a lot of the home testing,
you know, home testing has become much more robust and a lot of companies doing so just,
you know, either whether it's blood, urine.
I was on the board of a company that has a breast cancer detection algorithm out of tears.
So lots of that kind of stuff, saliva, tears, sweat, blood, urine, stool, that having these
tests that will give us a lot more information about an individual that can give us more
preventative healthcare.
Number three was some novel techniques around the finance of healthcare.
So we were an early investor in Oscar.
This is a healthcare insurance company in New York that took advantage of a lot of the
Obamacare.
They were doing some very interesting things with tech.
You know, they were able to, for example, they were one of the first ones who would
give you a fitness tracker.
And if you were using the fitness tracker and walking a certain amount every day, you
would get a reduction on your rates.
They understood, you know, they would look at clusters of claims and they, you know,
I remember a very good example where they had a cluster of asthmatic kids in one area
in New York and they realized what was happening was that there was an infestation of bed bugs
and these bed bugs were eliciting asthmatic reactions in these kids.
So the insurance company paid for exterminators to go exterminate these bed bugs because the
Senate exterminated it out for 59 bucks was cheaper than three hospital visits for the
asthmatic kid.
So, you know, all the understandings of sort of payment mechanisms, both whether it's a
pay-by-their, but whether it's third-party administrators, whether it's ACOs or whatever
it may be, the novel mechanisms of payment for healthcare that can make the system more
efficient and not necessarily do sort of just the conventional insurance model.
And then the last is just AI as a generic catch-all for sort of things.
And, you know, generative AI and diagnostic AI, I hesitate to use that term because every
company we look at now in 2022 has some AI component and it doesn't really mean anything.
But I think there is a rule, especially as a radiologist, we see a ton of AI and my clinical
trial company that we had worked with that did almost all the FDA approvals for all the
AI algorithms and radiology.
So we had a lot of exposure and a lot of work in that space.
But I think that's something that is going to keep on growing.
Okay, I think I have a trillion questions.
The one thing I'll ask first, I ask you the next question, the fitness tracker for reduction
on rates, did that work?
No.
So I think there was two problems.
One is they were using Misfit, which was an old school tracker, which, you know, there's
a limited amount of information.
And we've now invested in a company that is actually the reiteration of Jawbone.
I don't know if you remember that Jawbone had a headset and a boombox.
Well, they've like come back and they actually have a fitness tracker that they went and
bought a bunch of technology for a bunch of sensors, green light sensors from Phillips.
But they're building an ecosystem around a full fitness tracker for humans.
And so you think about it sort of like in your car where you get a red light for when
something's going wrong with the engine.
It's a tracker for it's tracking everything 24 seven in real time, but then informing
you when there's when there's an issue.
So I think tracker technology has progressed a significant amount.
That was number one.
And number two, just adoption by people.
You know, at the end of the day, the problem with that technology was people weren't walking.
Like it wasn't enough of an incentive for them to say, if I get three dollars off my
insurance premium, but I have to walk seven miles a day, I'm not going to do it.
We have more data now.
What is beneficial both from a human hack perspective, from both a diet, from sleep,
from all of these things.
Again, we're talking about personalized medicine, right?
Ketosis, prognomics, intermittent fasting, walking, all of these things.
We just have a better understanding so we can be more meaningful now about what we're
what an insurance company would recommend if you're trying to get a true reduction in
rates.
OK, perfect.
Let's talk about how we make decisions.
And the basis of this is health care is a need.
It's not a want.
We pay more for wants than our needs.
If we look at Robert Cialdini's principles of marketing, and I'm a big fan of his reciprocity,
commitment, consistency, social proof, liking and scarcity, needing something is not a principle.
How do we gamify health care so prevention is a want, not a need?
Yeah, I mean, it's interesting.
I would say, if I put my investor hat on, I don't think I'm not prepared right now to
make bets in gamifying health care just because human behavior, the way the system is set
up probably doesn't lend itself to being successful.
I think the things that we've the companies we've seen have tried to gamify things have
not traditionally been overly successful.
Not that it can't be done in specific things for children, for you know, it works.
But I think as an overall health care system, I think that's difficult to do.
So I think, you know, for me personally, some of that the motivation to do that again is
I strongly believe, unfortunately, or fortunately, is driven by money.
You know, if your insurance rates are lower, we've seen and shown that people are motivated
to do things.
And then there's an upper and a lower band of what is considered reasonable, right?
Like, you know, if we said to you, we'll reduce your insurance by, like I said, $5, but you
have to walk 10 miles a day, you're not going to do it.
But if we reduce your insurance by $50, and you have to walk three miles, maybe you'll
do it.
So there's some upper and lower band of human dynamics that you just need to understand.
And we're looking and working with insurance providers who are trying to figure that out.
You know, in a they're trying to figure out in a smaller cohort, we're working with a
company that works only with small businesses, and they have a lot of healthy population.
And so they're able to do that because they are there.
There's not a lot of variation between their sickest and their healthiest person.
So they have an internal control that they can look at.
So I think it's it's understanding human behavior and human dynamic, and then trying to layer
on realistic things that will allow those things to be to be valuable.
And I remember, you know, there was a time when I was looking at, you know, trying to
health hack myself.
And I was watching these movies, Game Changers and Fat, Sick and Nearly Dead.
And this guy was like juicing himself across the country.
And I remember I live in Texas, but I remember this very vividly sat down with these these
people in a in some barbecue place in Texas.
And I said, you know, I'm juicing my way across the country.
And the guy said, I'd rather die than not eat barbecue.
And I think that that sentiment is probably there are people who are like, it doesn't
matter.
I'd rather smoke, drink, eat this, that, whatever, and just die happy than, you know, eat lettuce
every day for 30 years and live an extra 20.
I mean, there's just there's a human dynamic component that you have to understand.
And it's very population driven in the population you're serving.
And so it's a local and regional thing that you have to look at.
And I think the companies that we're looking at are successful, have different models for
different regions.
Perfect.
I'll say something a little bit inappropriate.
I don't know if I should.
I looked into juicing.
And the reason I didn't do it is because there was a lot of mention of enemas.
Yeah.
Let's talk about each other.
Yeah, exactly.
But not for me, just to clarify.
Let's talk about how to best incentivize people for healthy behavior.
And I'll just give you two options to make it simple.
Is it better to tug at loss prevention, which is essentially reducing rates or asking people
for money and giving them back some if they meet the targets?
Or is it better to tug at positive reinforcement or give them money on top of whatever the
rates are?
And it's more of a way of how you phrase or deliver this reward that is essentially the
game here.
Which one do you think is better?
I would say all of the education and reading that I've done would illustrate that positive
reinforcement is better than negative.
Carrots are better than sticks.
I would say that my real world experience of the same thing and me personally has been
a reduction in rate or whatever is more motivating than the other side.
So I don't know the answer to that question.
We've looked at companies that have done both.
So we've made investments in the secondary healthcare companies that run incentive programs.
If you join the gym, you get a discount.
If you do something else, you get a free Apple Watch.
So that's the two things you're talking about.
One is a reduction because you do some of the other is you get a free Apple Watch if
you do this.
And I think when they've studied that, it's been very, again, very heterogeneous depending
on the population they're serving.
And it's not one size fits all.
A 75-year-old probably doesn't care about getting an Apple Watch.
A 21-year-old wants an Apple Watch.
The 21-year-old doesn't understand a reduction in rate will give you money that you can compound
interest for the rest of your life and become a millionaire because you are healthy.
The 75-year-old, so it's very different and you have to, it has to be applicable to the
population that you're trying to serve.
And that I think has been part of the problem.
It's a one size fits all and it doesn't fit all.
And so some of these innovative payments, like we have a family of four, we're fairly
healthy.
We use almost no healthcare.
I pay a huge deductible, a huge premium every month, but we don't use healthcare because
we're at a phase in our life where we're healthy.
We'll need that later.
Well, if you gave me an incentive to save some money and do things that would set up
the insurance company and you could amortize that over some period of years, that would
be a novel way of doing it.
So we're looking at sort of those kinds of models where insurance companies are saying,
let's take a small cohort.
We have to analyze you as a cohort and see whether this fits for you.
Traditionally, that's been too much manpower to do that.
But now with algorithms, AI, whatever it may be, you can get that information on a much
more efficient basis and make those decisions.
So I mean, we looked at a company that on your phone, it can read all your vitals.
So just by looking at the screen, it projects a red light, projects it off your skin, gets
heart rate, temperature, O2 saturation, blood pressure, all from that.
They're starting a pilot with an insurance company in Europe.
So if you not even, you don't even have to check in.
If you put the app on your phone, when you do FaceTime or whatever, or unlock your phone,
it records that data and sends it to the insurance company.
So now insurance company has a longitudinal view of your blood pressure, your heart rate,
and now they can do your premiums without you having to do anything.
That kind of novel stuff is I think where the future of this is where you can now, like
you said, cancer and surgery, you can still pay for quality up there.
Because the number of people using that is less out of the general population, but it's
not the general population subsidizing that anymore.
You can actually divert dollars where they need to go and save money where it doesn't
need to go and have a very novel sort of payment and an insurance mechanism as opposed to this
one size fits all.
Yeah, I think that makes sense.
Risk pooling is needed, but distribution of that risk can be triaged and personalized.
What's the end game for you, Amit?
If we define retirement by when you reach a point where every day is complete in itself,
you're looking forward to things, but you're perfectly happy with the day as it was.
Would you consider self-retire right now?
And then the second part of this question is, I'll take you 50 years down the line.
What do the last five years of your life look like in an ideal world?
I think my wife probably has a very different answer to this question than I do.
So for me, I don't think there is retirement.
Part of what I like about investing and what I like is I pick a topic every year and go
deep and try to understand, read, experience, whatever it may be around that topic.
And there's no end of topics.
And I enjoy doing that.
So I'll continue to do that.
And as long as I can be in it, obviously, there's a potential finite life as an investor.
I mean, if your funds aren't returning, then there is no next fund.
And it may be self-fulfilling that it's over for me.
I'll continue to do the intellectual and experiential investigation that I do now on a yearly basis.
But I think there's a physical component to when do you tire out?
I stand in a lab 13 hours a day wearing lead, heavy lead for when I'm doing cases.
At some point, physically, you wear out from being able to do that.
But I'm not at that point.
So I think I enjoy that.
I'm now that I'll keep doing that until physically I'm not capable.
But one thing that I've learned to do is multitask.
And so while I can pursue these intellectual things at my level of my satisfaction, I'll
just keep doing that till I can.
So I don't know what the last five years, that last five is.
I think there's a sentence that, tell me how I'm going to die so I can avoid it.
So when that's coming, I hope I have some personalized medicine, genomic, proteomics
markers that will tell me that you have 447 days left.
Would you want to know?
Yeah, I think I would.
I mean, my personality is I'd rather know than not know.
Both our kids, I'm a radiologist.
We ultrasounded them in the first time.
We knew what sex of kids we were going to have before we had them.
There was no surprises.
We're not doing, there was no gender reveal stuff.
So yeah, I've always been a personality that I'd rather know and deal with what it is and
have the knowledge rather than the surprise.
The surprise doesn't engage me.
Interesting.
What's the perfect birthday for you?
You know, I mean, I like to, you know, this sort of, I like to work.
Like I like to do things.
And so it doesn't necessarily have to be medicine or investing or these other things that I
do, but active things.
So obviously spend time.
Family is obviously very important.
You know, we have young kids, so probably that's the majority of it is that carve out
time specifically to be with family during what is usually a very hectic week.
Do you work on your birthday?
I work if I have to.
If I, if I can maneuver out of it, I would, but if I have to, I would.
Would you classify yourself as an operator, someone excellent at execution or a visionary?
And when you look at a founding team, do you look for both and which one is easier to replace
or find source externally from your network?
It's an interesting question.
It's hard to say you're a vision, in my opinion, to say you're a visionary without being an
egotistical visionary.
So I'm going to, I'm going to dance away from that.
But I think, yeah, my, I think my skillset has been more around strategy and vision than
operation.
You know, when we accepted this company, my company, I mean, I got on the ground and plugged
in computers and wrote SOPs and did whatever it took as an operator, more as a skillset,
learning how to do it so that, you know, when someone failed at it, I was the backup, I
could do it.
I wouldn't say I enjoyed the operational component as much as the strategy, vision, guidance
part of it.
And so I think also, you know, as you look at things that you do in your life and you
converge into things that are more your personality, you know, as it takes time to figure that
out, you know, that's why I prefer to be on the board of a company and help with direction
and strategy using the experience from being an operator to help them rather than, than
being the operator.
Having said that, we've been toying with being an operator again.
Your friend of mine has come to me and said, like, let's start another company.
And so maybe that does come again, but it has to be the right idea and the right execution.
But I prefer the, you know, he's an, he's an incredible operator and has operated at
a very high level.
So we compliment each other really well and that I'm more strategy vision.
He's very operate, he's less strategy vision.
And you know, so that compliment works well.
And do you look for both in a founding team and which one is easier to source from your
network?
I mean, absolutely.
I look for it in a founding team.
I mean, it's always in the back of your mind.
The issue is more at the stage of when you're making an investment.
So if it's a series CD, whatever, I mean, they figured it out, right?
I mean, you're not getting to a hundred million in revenue.
If the CEO is a tech guy, was no tech person who has no operational experience and can't
motivate people.
Like it's just not going to happen.
Right.
Or it's very rare that that happens at the stage where we invest, which is seed and a,
all of that is very important, but hasn't necessarily always manifested.
So we see lots of companies where the CEO is great for the seed or for the early a,
but once you get to a B or a C, they really need to step aside and bring in adult supervision,
so to speak, because it's not there.
They're a great founding CEO and they're the ones, you know, two guys in a garage, you
know, all of that sort of stuff, but they're not the ones that sit with an investment bank
to negotiate, you know, book running an IPO.
I mean, that's not who they are, right?
They don't, the attention to detail, the experience, whatever it may be.
And so that, I think it's very much dependent on what stage you're investing at to figure
out who the right founders are.
Okay.
You know, something I'm doing right now is looking at companies that have made it and
going back to see if I would have invested in them.
And oftentimes the answer I'm getting is no.
The companies I'm talking about, I'll just say some names as Romans and Four Hymns, you
know, they've done really well and they're pivoting to more being almost at home hybrid
health system, which is great, but that's not what they were when they started.
Do you do this exercise?
Do you go back and look at companies you did not invest in and maybe you didn't come across
or you did and you passed on them?
And then do you change your investment thesis to any extent and say if you get one of these
or say if you get 10 of these companies?
I would tell you, I don't do the exercise, but my partners definitely do the exercise
for me because they send me the deals.
You said no on this.
Look at this billion dollar exit.
So no, I'm kidding.
They don't.
Thankfully we have a great partnership.
We don't do that.
But I would say I do, I look at that from a, from a just an experiential intellectual
perspective.
I don't beat myself up about not making the investment.
I mean, some of these ones that you're talking about, we had the opportunity to invest.
I think if you stay fundamental to a thesis, some things just don't fit.
And those, the ones that you hear about are the outliers.
One thing I've learned when I got into investing, I mean, we look at 70, 80, a hundred deals
a week, right?
But you can't invest in all of them.
And the ones that make the headlines are the ones that break away like that.
But categorically, if it doesn't fit your thesis, then you'll make a mistake 99 times
and have success once.
And I think that's okay in venture if you've right sized your venture investments probably,
you know, that one has a hundred billion exits, so to speak.
It's fine that the 99 went to zero in venture math, but you better be pretty sure that you
can do that on a repeated basis or there is no fun two or fun three or fun four.
So I don't beat myself about the misses, but I do, I do look at them and I try to understand,
you know, did I actually miss something or is this off thesis or this is a one off?
Yeah, I'm really happy you said that.
And I agree with it.
You should not define your thesis chasing after Google.
It was the 18th search engine.
If you decided this wasn't for you after the 16th one, you would have missed out.
So it's something you just have to have an infinite amount of money to pull off, I feel.
Yeah.
I mean, a lot of these businesses, you know, it's interesting.
We've made an investment in a company called Stampede, which is a novel movie studio.
This guy named Greg Silverman, who was the producer manager at Warner Brothers for 20
years, super successful, highest grossing producer of all time.
He did Harry Potter series, Batman, Hangover.
This guy, I mean, this is the guy.
We ran an exercise at our annual meeting last month where he had a grid of seven by seven
movies, which were script titles that were pitched to him.
And we were supposed to pick based on, you know, it was a British kid who is a wizard
who lives below a stairwell and has plays at this school that's, you know, whatever.
And everyone's like, absolutely would never do that.
Right.
It was Harry Potter.
And so it was interesting when you go through what they, you know, his trade craft and his
discipline of picking these movies.
I mean, he can obviously pick winners.
The skill set to pick, I mean, he even said it in our meeting.
We get lucky sometimes, right?
Like there are outliers to the Harry Potter.
He picked he was everyone had rejected that every studio had rejected the books before,
you know, and now look at the one of the great biggest grossing franchises of all time.
So I think you could learn from it, but I don't like you said, I don't we don't I try
not to define by what I consider mistakes.
Do you think you learn more from your successes than your failures?
And I will give my answer.
Yes.
I have learned more from my successes.
And I know this is not the popular answer.
I have learned humility and introspection and reflection from my failures.
But in terms of decision making, I feel like I've learned more from successes.
Yeah, I would agree with that.
I mean, I think I've learned more from the success.
But I think what I've learned from failures is how to be more successful, not necessarily
learn a task or a skill or an idea.
It was, you know, we had we invested in a company where the founder had, you know, we
should have done better due diligence on the founder and his background, etc, etc.
So now, you know, we run a background check on everybody before we make it like those
kinds of things.
They're operational infrastructure things that I think I've learned over the years.
Investor, you know, I've never done a reverse merger IPO with an Israeli shell company.
Well, now we've sort of done it and we understand how to like those kinds of things from those
kinds of failures where we ended up in a situation that we had to navigate out of.
We've learned something that now for other companies that we have, we have a better toolbox
of saying, hey, this is one of the possibilities now.
So I don't for me, it's not been so cut and dry of the conventional, you know, is your
success versus failure learning.
And you know, you teach this to your kids or they tell you to teach it to your kids
that your kids fail so that they can understand success kind of thing.
It's so different, I think, in investing and understanding how this kind of stuff works,
because there's a mechanistic component to just investing, like how to read a term sheet
and how to do a deal and IPO and this and caps and all of these things that come into
liquidity preference, how it all works, that plays such an important role in success or
failure.
You can have something that's very successful.
We're looking at a company right now that they're recapping the company.
We looked a few years ago, it was too rich for our blood.
Now they're recapping the company where the founders have ended up with 1% of the company
after two rounds and that everyone's realized that there is no company unless we recap the
company and give the founders back 30% equity.
You know, that kind of thing is just an experiential thing.
It's got nothing to do with no one fail.
It's just the fundraising went in a way that there were so many people involved that the
cap table got completely squeezed down that these guys sold all their equity out and now
there's no motivation to grow a company.
But the company is good.
So there's investors who are interested in recapping the company.
Okay, let's talk about hiring employees, co-founders and finding a partner.
The lens I want you to answer this question through is Danny Kahneman's decision-making
framework.
I used to hire based on intuition and that was the wrong thing for me.
I've made some terrible mistakes because how do you approach hiring employees and looking
for a co-founder, do you have a structured approach and how do you factor in intuition?
Yeah, I mean, I think co-founder is a very different whole thing, right?
I mean, co-founder is there's a personal component, a professional component, an intellectual
component and a financial component.
I mean, it's very different and that for me and all of the things that I've done where
I've had a co-founder or a partner in a business has been we were friends first and then we
moved into a business relationship.
And we've but very upfront built a business relationship with tax and blocks and tackles
in the documents that shotgun clauses, whatever it was that we understand upfront that if
we get into a fight, which everyone tells you don't do business with your friends, which
I have done business with all my friends is we just build a way that there's a structure
that no one gets into a fight and everyone understands how it's going to be.
So I think as a co-founder, it's a very different exercise.
On the employee side, both my company, our fund, all of these other things, we've tried
360 evaluations and neograms.
There's a host of tools that you fill in these questions, all of this stuff.
I personally have never had that much success with these orchestrated tools.
I think they give you, if you have a limited time of assessment with somebody, they do
give you insight that's very valuable in terms of are they a high performer?
Are they obsessive compulsive?
Whatever these factors that you're looking for.
But I think if you spend enough time with somebody that all of those things as an employer,
as a partner, we're able to garner.
And so that's what we try to focus on.
We try to spend a good amount of time with someone upfront and then to a certain extent
hope for the best.
I've been proven wrong on lots of the 360 evaluations that we've done where the thing
says this person is awesome and they turn out to be awful and vice versa.
We've had people who we thought there's no way this person could succeed and then they're
the most successful person on whatever entity it was.
Okay.
Do you have time for one more question?
If not, we can...
I do.
Yeah.
Let's talk about...
And I had questions for each one of the four pillars and I think maybe in the next round
we'll get to it.
I'm already marking down the next round by the way.
Let's talk about AI and explainability.
I talked to this about Amit from Tao Ventures.
I don't know if you know him.
I do.
We're invested in a company together actually.
Okay.
Yeah.
And he gave an amazing answer.
So the pressure is on Amit.
All right.
AI and explainability in the sense of right now the regulatory framework in healthcare
requires us to an extent to understand what the AI is doing, to understand the networks
or the processes behind the outcomes.
When do we let go of that need for explainability?
If the AI is providing amazing outcomes, maybe outcomes better than humans, when do we say,
okay, let us let this algorithm do its job, provide us with care, with decisions on when
to operate, when not to operate, what drugs to use even, what diagnoses, and maybe we
don't even answer the diagnoses.
At what point do we let go of that need for explainability?
Because by not doing so, we're limiting the scope of AI, I feel.
Yeah.
So interestingly, like radiology has been on the forefront of this, right?
And so through our clinical trial company, we did the approvals for a lot of these AI
products.
The FDA as a regulatory body has already given blessing on not knowing how the AI works.
So in a compositional neural network, in a pure CNN, it truly is a black box, right?
So it's input in, input out, back test.
So no one understands how, I mean, there is no understanding of how the black box works
per se, but those algorithms are approved.
So we have FDA approval for several algorithms that nobody knows how they work, quote unquote,
right?
Oh, perfect.
So AI exists, and the FDA is moving through this in terms of defining, there's a whole
host of secondary.
So AI is going through this evolution of sort of what I call AI 1.0, which has been traditionally
sort of detection technology, and it's not controversial, right?
Is there a mass on this picture?
Is there an abnormality in the CBC?
Is there whatever it may be?
It's not controversial in understanding.
It's a detection technology, and there's been detection technology for a long time.
No one has an issue with that.
The detection is getting better, and the detection is getting to a level where we're asymptotic
and where you cannot, as computing power goes to, the cost of computing goes to zero, this
gets better and you can detect better and be more holistic about it.
This next generation of AI is, which I don't think we're at, which, and I'm going to get
to your point, is sort of where there's an interpretation of what is detected.
So you're making an evaluation.
And so for example, you find a mass on a mammogram.
There's a company that has a heat map that it takes and ingests your BRCA, it ingests
your family history, it ingests your diet, a whole bunch of other risk factors to give
an assessment of whether or not that mass is going to turn into a cancer.
1.0 tells you, is it a cancer or not?
And if it's not, 2.0 tells you, based on all these other risk factors, it's going to become
a cancer.
So that's sort of 2.0, and I think 3.0 is what you're talking about, where it's a true
decision maker.
I think as a society, we probably don't want computers to make that decision, open AI or
all the money, fear and all that.
But I think it's inevitable that a component of what we do will become, and AI will adjunct
what we do.
And imaging is a great example, right?
I think in 2022, as long as I am a licensed physician who is trained, who's willing to
sign off on something, I can use the AI to adjunct and augment what I do.
There's an algorithm that can find a rib fracture on a CT scan.
Does anyone in the world have a problem with me using that algorithm?
Absolutely not, as long as the algorithm detects and I say, I agree, and that's a rib fracture.
So that, I think we're there, and that's where we are today.
So the question becomes is, as we evolve, are we okay with AI making the ultimate decision?
And then the constituents there are going to be, again, the provider, the payer, and
the patient.
I think the patient reflects on society, FDA, everybody else to make sure, just like the
Consumer Protection Bureau protects consumers from ovens going on fire, right?
We as a society expect these regulatory bodies to protect us.
So I don't think the patients make a decision.
The patients say, if the FDA says it's okay, it's okay, as we've done with almost everything
else.
The providers, I think as long as they're getting an economic benefit or do not lose
an economic benefit, are absolutely fine using it.
So in my rib fracture example, if insurance is willing to pay for me to use the rib fracture
algorithm, I have no problem using it.
Makes me a better doctor, better diagnostician.
I miss less fractures all day long.
So it comes down to the payer, right?
And it comes down to money, which is what all of this comes down to.
So the payer says, why am I willing to pay for this?
The only reason I'm willing to pay for this, honestly, right, if we're true to ourselves,
is that it reduces my cost of providing care.
So if we go back to my rib fracture example, and I use this specifically, if you have a
rib fracture on a CT scan that's not significantly displaced, you know what we tell you to do?
Take two Advil and we'll call you in the morning, right?
There's no treatment for that per se.
I'm not talking about a flail chest or a pneumothorax.
I'm just talking about a non-displaced rib fracture.
So at the end of the day for the payer, did it really matter if I found that rib fracture
probably not, right?
Academically, for us, it matters that we don't miss a finding.
For the patient, it matters.
Now they have an explanation for their right side of chest pain.
But the payer, and this at some point was supposition, now it's playing out because
I've seen many, many, many AI companies that have closed shop because they went to the
payer and the payer said no.
They went to the patient and the patient said no.
They went to the hospital, the hospital said no, we're not paying for this.
And they have to close shop because they couldn't find a payer.
So I think that's what ends up driving some of this stuff at the end of the day is, is
there a economic benefit to that algorithm independent of, lots of time there's a clinical
benefit and there's no question there's a clinical benefit.
But that's not what the driver of the technology is.
The driver is who's going to pay for it.
So that's experientially what I've learned as an investor is like when we have these
companies that come, we say, who's going to pay for this?
Oh, well, we'll figure that out later.
Not investing in your company.
Or I'm going to get a CPT code and I'm going to get reimbursement for this.
Not investing in that.
You have not been through the system because the payer is not going to pay for that unless
you can prove benefit.
How far are we from the AI being the provider, at least for certain verticals like, you know,
UTI and birth control refills?
Yeah.
I mean, I don't know if you've used chat GPT yet, but I haven't.
Yeah, I mean, just type in.
I got a cold one.
I mean, chat GPT is amazing.
So AI inner sort of generational AI, I think, is at that level now.
So I think we're there.
I mean, if it's algorithmic algorithmic treatment, which is in essence what you know, there's
a whole host of companies doing asynchronous care, right?
You have an app, you log on, you say, I've got a cough, I've got a fever, I've got green
sputum, I've got shortness of breath.
Pretty high chance you got a pneumonia.
And if it's hurting on the right side, it's in the right lower lobe, right?
So that asynchronous data capture, they then send you for a chest x-ray and some labs,
and then they get that result.
And then they, you know, you get antibiotics.
There isn't a need for a level five or an ND visit.
I mean, you can go see a PA or maybe an NP if you need to.
But a lot, you know, for the most part, that visit doesn't add AI and even chat GPT, which
sounds crazy, but conversational AI on asynchronous data capture and treatment, I think is there
today.
Now it goes back to the same problem of, you know, again, in the money, talking about the
money again, there's obviously a, you know, the litiginous part of it.
There's, you know, we worry about all that.
What happens when the AI makes a mistake?
Who do you sue?
All that kind of stuff.
But I think as it augments to the position in 2022, it's worth, I mean, there is capability
there and radiology has been one of those places where it's been first.
I mean, we augment what we do in mammography with cat with AI, right?
We bring up the mammogram, we look at it, we hit a button, the algorithm will highlight
a mass recalcitration.
We use that and use that to make a better interpretation.
So I think for the foreseeable future, it's AI augmenting the physician.
There is a day where I think it crosses over, but it has to get to a level of sensitivity
and specificity where it ensures providers feel comfortable that the system isn't going
to screw you.
Okay, perfect.
Amit, thanks so much for taking the time to be here.
Yeah, absolutely.
I had an amazing time and we'll have to do it again.
Yeah, I appreciate the time and I'm excited about what you guys are doing and love to help
out with the forum and as people sort of make their way through investments, you know, feel
free to reach out.
I'm happy to help in any way.
Thanks.
Amit.