E133: Lessons from Investing in 2200 Startups (in 23 Minutes)

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Unlike the public market where everyone has the
right the same access to everything, the

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private market is highly asymmetric.

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And so if you invest for a long time, but you
only have access to a corner of the market, you

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may be at one or the other end of that
spectrum.

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Maybe that you have like uniquely qualified
access and you do better than everybody else,

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or you have uniquely adverse access and, and
you do worse than everybody else.

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So to some extent, if you are a very large
family office or a very large investor, and you

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can be an LP in every major VC fund out there,
that's a great strategy, right?

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Over years years years, you'll do really,
really well.

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That's for an out in the field.

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But what if you aren't?

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Tell me about your philosophy on DEI.

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Mhmm.

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I tend to be, a very moderate person in my
views, but I also think that, like, everything

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in life, even when there is a really good,
solid moral reason to do something or to stand

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for something, there is always almost an an
inevitable kind of risk, that people co opt

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these things for their own for their own
purposes.

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And so you have the good version of DEI, which
is which says, you know, talent is universally

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distributed and doesn't see races or genders or
any other characteristics, but opportunity

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isn't.

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And that's the reality of the world in which we
live and we have lived in, is we can absolutely

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and I am the first one to stand by saying merit
is the most important thing.

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Right?

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It's not just about being an incredible worker,
hard worker person.

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It also matters where you grew up, what kind of
networks you had access to, what kind of

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resources you had access to.

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And so realizing that talent is uniformly
distributed and opportunity isn't is not a bad

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thing.

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What is bad is co opting this mission in ways
that are perverted and that ultimately don't do

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anything to advance equality, sometimes
perpetuate different inequality.

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So I think there's a lot of absolutely
legitimate criticisms that need to be levied at

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what DEI had become almost as an industry.

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At the same time, we at angels believe that
there is work that we can do to provide more

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access and more opportunities to people,
entrepreneurs, investors, folks that have

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traditionally just haven't been able to access
the incredible, wealth, and value and

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innovation engine that is venture capital, and
we exist to do that.

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What is angels?

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Angels today is one of the largest, most active
venture investment syndicates in the world.

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We invest in companies that look to us as being
partner with them to help them build truly

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inclusive organizations at the levels of
talent, governance, and capital.

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We help them with hiring, recruiting, bringing
onboarding board members, advisors, and we

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represent an incredibly diverse group of
investors that come from all paths of life, all

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genders, all ethnicities, really all type of
peoples that traditionally have found it hard

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to get access to the type of opportunities that
angels is able to bring them.

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And because of them, we've built a really, you
know, vibrant community of investors that care

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about our mission and get to invest in some of
the best and most highly performing venture

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backed companies in the world.

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When you guys started, you made a very
interesting decision.

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You allow LPs to invest as little as $1,000 per
company.

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Walk me through that decision making.

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And, you know, when you bring on a group, of
investors and you're basically trying to

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position yourself and message to folks that
often, while they have the means because, you

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know, we work only with accredited investors,
they have the means.

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They maybe traditionally have never had the
opportunity, the access, the ability, the

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education, the experience of investing in the
venture asset class.

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Then, you know, making it easy for them to do
so becomes, an important piece of the equation.

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So accessibility can take many forms, and one
of them is to allow people to make investments

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as little as a $1,000 into opportunities.

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When you take an amount of capital that an
angel investor would want to allocate to this

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asset class, say, 25, $50,000, and you get to
split it, and diversify across, you know, 10,

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20, 30, investments across the year, then
you're doing a lot of things.

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You are educating yourself.

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You're getting in touch with different terms,
different type of, companies, different

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sectors.

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You get to provide these individuals with both
that access and an education into what it means

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to be an investor in private company.

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So let's say you had a friend that was worth
$5,000,000, half of it liquid, half of it not.

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How much should a friend or a high net worth
investor invest into venture capital as a

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category?

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This is not financial advice to anybody, and,
everyone should kind of think in the context of

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their own risk aversion.

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I would say, probably 10 to 20% of your overall
liquid, net worth should be going into a

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venture capital type of asset.

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And so out of that 5,000,000, probably $500,000
is probably I would, say, okay.

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I wanna put this into venture.

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But then venture is especially now, it is such
a broad category.

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So I would really look at, you know, just like
you diversify by asset class and by risk

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exposure, you can diversify within the venture
asset class by risk exposure and time to

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liquidity.

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And so you can invest in different companies,
different sectors, and at different stages.

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Brought up a couple of points.

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One is, of course, liquidity or illiquidity in
venture capital.

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You when you invest in a start up, especially
at the seed stage, you should expect a minimum

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of 10 years before you get your money back,
which a lot of people say, yeah, I could handle

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that.

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But in reality, it's they're not set up to do
that, so maybe they should be investing later

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stage.

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The second one is thing.

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I've never seen any data on this is what is the
actual correlation among different start up

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sectors?

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My intuition is that venture as an asset class,
you know, whether you invest into nuclear or

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defense tech or SaaS or consumer goods should
have not that much higher of a correlation from

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the S and P 500, just much more much more
volatility.

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So you have companies that are going up a 100
x.

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You have half the portfolio going to 0.

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It's not clear to me that the diversification
should be significantly worse than the S and P

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500.

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You certainly want to diversify by sector
primarily because of, the fact that you might

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have, like, different type of strategies or
different type of understanding of different

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sectors or simply because at different points
in time, there are cyclical sort of, tailwinds

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that kind of push certain sectors more than
others.

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You certainly see it today with things that are
lit early, mid, or late in the adoption curve

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for how, potential growth of those sectors may
represent.

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And, you know, there certainly is some
correlation to the S and P 500, but there are

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technologies in venture that or entire pieces
of the venture, economy that emerge long before

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they become a significant part of the public
market.

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A good example is quantum technology.

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5 years ago, or 10 years ago, if at all, was
pretty pretty much only a purview of private,

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holdings, private companies, and venture
backed, companies.

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I think there is some correlation and some
importance, that comes along with looking at

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the diversification within your portfolio to
be, not just by ticket and stage, but also by

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sector.

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We've had, the DuPont family, Virtis, on the
podcast.

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And one of the things that they figured out is
that if you just invest into everything or you

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get exposure to everything in venture over many
decades, you get a really good return.

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You know, high teens, low twenties.

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So venture is one of those asset classes where
you don't have to be too smart.

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You don't have to pick, you know, AI over
crypto or, you know, over ARVR.

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If you just continue and slowly and really in a
boring way continue to invest in the asset

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class over years, it it is an asset class that
has rewarded its investors for many decades.

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I'm glad that you bring this up.

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It relies on having a pretty broad funnel of
access.

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Unlike the public market where everyone has the
right the same access to everything, the

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private market is highly asymmetric.

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And so if you, invest for a long time, but you
only have access to a corner of the market, you

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may be at at one or the other end of that
spectrum.

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Maybe that you have, like, uniquely qualified
access and you do better than everybody else,

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or you have uniquely adverse access and, and
you do worse than everybody else.

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So to some extent, you know, if you are a very
large family office or a very large investor

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and you can be an LP in every major VC fund out
there, that's a great strategy.

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Right?

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Over years years years, you'll do really,
really well.

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That's that that's borne out in the in the
data.

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But what if you aren't?

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If you are just an angel investor, or if you
don't have the capital or the connections to

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be, a large LP or an LP in all of those funds,
The your options are are pretty, pretty small.

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And so you rely on either alpha, you know,
alpha because of access or because how smart

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you are or what kind of career you've had and
the fact that people seek you out.

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Or and, you know, you can look at something
like angels and see, like, okay.

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Through the power and the size of that network
and the fact that we collaborate and we're

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noncompetitive, we're cooperative with pretty
much every large fund out there, you get almost

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like the ability to kind of invest into a
really broad portfolio across the entire event,

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venture spectrum.

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And so, you know, to some extent, if I had a
lot of money, I could be like, okay.

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I'm gonna invest that $1,000 or $5,000 into
every company that the network gets to invest

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in, and then you'd have really broad exposure
to the venture asset class as a whole.

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You would be getting to the mean.

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So it it doesn't help if you could invest in
any fund in the world, but you have $5,000,000

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and the minimum is $5,000,000.

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You're not gonna invest a 100,000,000 of your
net worth into just one venture fund.

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So it's a it's a mix of both having access as
well as the minimum investment size.

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So going back to this hypothetical, so you have
5,000,000 to invest.

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Let's say you put 10% in venture.

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How and when would you allocate that $500,000?

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Thank you for listening.

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Look at what your, expected returns and
liquidity needs are and just kinda project out.

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Okay.

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So maybe 30 to 40% of that, I'd like it to, be
liquid sooner than the mean, and so maybe in

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the 3 to 5, kind of year time frame, and I
could allocate those into series c or later.

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Those investments will return lower multiples
on average.

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They've already kind of are higher valuations.

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And if and when they exit and go public or get
acquired, those multiples on on investments

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will be lower.

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But you'll have a larger pool that has, in been
invested into those, and you will get, it back

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sooner.

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You'll have a positive effect on IRR on your
IRR, whereas you could take, you know, 10 to

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20% of that and invest it into series a and
series b.

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And then, again, another 10% invested in seed
and precede opportunities.

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And that will kind of, you know, give you some
exposure to the go big or go home kind of,

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potential.

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Prior to cofounding Angels, you had this
portfolio of a 100 investments.

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How did that affect and instruct how
Gainesville is run?

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I learned a few lessons that I think a lot of
other angel investors in you know, end up,

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learning.

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When you're truly an angel investor, meaning
you're investing at angel rounds, precede, you

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know, a a pitch, an idea, a founding team, but,
like, not a lot more than that.

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There just isn't much more that you can invest
in than the team and the founders.

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And so your own assessment of, you know, their
agency, their grit, their their kind of

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doggedness, their unique unique positioning
within that market.

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All of those become, like, the really important
things that you can leverage to invest.

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And and in fact, you know, very early in my
angel investment career, the first thing I did

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was to just kind of reliably go after and
invest in whatever companies the people I had

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worked with or knew really well, were going to
go and and and start.

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And, sometimes being their very first investor,
and and that paid out really well, especially

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because we had some amazing people, within the
team at Powerset.

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That was the name of the company I founded back
in 2003, whose companies you know, they they

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went on the the folks from that team went on to
start companies like GitHub and Weights and

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Biases and Touring and Runway Financials.

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And and the ones that didn't go and start
companies went to, lead very large

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entrepreneurial organization within a large
company.

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So really a fantastic team.

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And then you know that, you know, great
founders just attract other great founders.

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You mentioned investing in your friends.

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Some of the top portfolios in venture capital
history were actually the angel portfolios of a

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David Sachs or a Marc Andreessen or Chris Sacca
because they have such intimate understanding

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of the execution ability of their friends.

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One of the hidden things there is that their
friends were not pitching to them the full 5

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years that they knew them.

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They got this ability to observe their friends
in a way that they were not always selling to

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them.

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Investing in people that you've worked with,
that you've observed up close, maybe your

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students, if you're a professor, people that
you've gotten a a chance to really kind of, see

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how they behave under pressure, see what kind
of character they they have, and, what their

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approach to kind of moving mountains that kind
of got put in front of them.

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That's probably the single most, you know, best
predictor of a first time entrepreneur.

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With the second time or serial entrepreneur,
then you've got those points.

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Right?

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And I think that the other aspect the the other
side of what you were saying, which is, I

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think, is equally true, is you've got great
portfolio of people who invested in first time

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entrepreneurs because they knew who they were
and they had worked with them.

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And then you've got, investors who bet again on
entrepreneurs that did well the first time and

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they worked with them before, and they wanted
to back that horse again.

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And I think that there's a really high
correlation of repeat success for, for

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entrepreneurs.

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So I I would say that's the other aspect of it,
and I think that it puts us, meaning angels, in

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a good position.

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Again, having a such a broad portfolio, we can
see what the execution ability of founders

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that, may make it or even may not make it the
first time for a lot of reasons.

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There's so many reasons why a startup doesn't,
you know, doesn't go well or doesn't go as well

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as one would have liked, and, you know, be able
to assess much better the second time around,

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whether or not, you know, you would want to
invest in that in that entrepreneur again.

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You've been in the AI market longer than 99% of
investors and VCs out there.

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Tell me about your thoughts on AI today.

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As I mentioned, I started cofounded a company
called PowerSet, 20 plus years ago, which was

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bringing to market a lot of the ideas and
visions that are only becoming reality now.

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You know, we were one of the pioneers in trying
to bring Symantec into AI, into web search at

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scale.

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And some of the intuitions we had, you know,
we're not very kind of removed from some of the

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things that that we see today in how semantic
searches approach.

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Right?

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So things like RAG, ultimately, what we were
doing at the time is you can you can describe

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it as a precursor to RAG.

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So, you know, pre deep learning, cost of
computation was 10,000 times maybe more what it

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is today.

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There just was a a universe of approaches that
was not open to us.

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We clearly brought, attention to something
which was search was not keyword search was not

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all that there needed to be in order to to,
advance the market.

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And, you know, we sold to Microsoft, became
some of the foundational pieces of the early

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bing.com and integrated in there and gave, on
to a lot of other really cool company in the AI

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space.

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CrowdFlower, Weights and Biases, Turing,
Runway, all of these folks, you know, went on

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to really make big innovations and and a big
impact on the market today.

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It's exciting from my point of view just
because I see so much of that vision and those

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thoughts kind of, like, finally being,
realizable and being able to, to be brought to

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market in a way that is compatible with the
cost and the scale of delivering services to

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the world, to consumers.

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And so I've been, you know, excited about on
the side of the investor backing a lot of

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founders in the space.

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The way that I've constructed my my investment
thesis, and I've been investing now in the

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space for the last three and a half years or 4
years.

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So just as, like, the the GPT kind of, LLM
revolution really kind of started to take place

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is to think about it in buckets that are, kind
of stag staggered, with respect to when they

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will become or they have become ready for
commercial exploitation and and and therefore

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revenue generations.

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When it comes to your portfolio in AI, are you
basically just making a directional bet on the

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space and trying to build a large portfolio of
smaller investments?

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Are you concentrating in a couple names?

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Are you doing some hybrid?

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How do you attack a thesis like AI in your
portfolio?

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So gain just broadly, I think, will continue
and does continue to invest in a lot of

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companies.

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And so spreading out that risk both because
different people will like different things.

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People will invest in the companies that they
want to invest in.

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And so bringing them high quality access, but
for a lot of companies is part of that.

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And the way that we kind of make sure that the
quality is high is by coinvesting with great

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funds that are, you know, bringing their own,
alpha to the market in terms of the the deal

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access that the deal flow access that they have
and the diligence that they that they put.

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I also run, an AI fund within angels, and so a
more traditional kind of VC approach, while

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maintaining some of the elements of the angels
network.

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Meaning, we still don't lead rounds.

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We're still a kind of a coinvestor alongside
others and therefore benefit from, you know,

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that additional social proof and diligence.

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We do a lot more direct diligence and,
directional, betting for that fund, than with

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the syndication process.

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And there, you know, the my north star, you
know, I'm actually working on this fund with a

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former colleague of mine from the PowerSet days
who most recently was leading AI development at

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Adobe.

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My north star there is on top of the kind of 3
pillars that I mentioned, earlier, is really

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looking at, you know, companies that can have a
generational category defining kind of

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opportunity there.

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Sort of just trying to stay as much as possible
away from things that feel like jumping on the

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bandwagon and kind of me too, things.

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And really from first principles, kind of
things where that team is uniquely motivated

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and positioned to make an impact on something
that has an opportunity to, start from a small

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market and expand into a or create a much
larger market down the road.

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The thesis is around those 3 buckets.

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We saw last week, Trump with with SoftBank and
with Sam Altman, who I know you have a

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relationship with, announces $500,000,000,000
investment into AI in the US.

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What are the repercussions of that investment?

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How do you think that'll affect the AI space?

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Clearly, you know, Sam and others who are
really close, and I'm I'm thinking about Dario

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Modet and others who are really think close to,
the economics and the dynamics of scaling out,

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not only the services that they are already
providing to the world, but the services that

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they know they are going to provide to the
world.

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They understand that the requirements from a
power compute perspective better than anybody

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else.

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And while I think, you know, to anyone looking
from the outside, investing anything investing

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$500,000,000,000 into anything seems like an
gargantuan amount of money.

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I can't look at this as anything but a good
thing, especially for the United States.

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I think it's, it's an opportunity to kind of
create a lot of innovation and a lot of

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scalability and a lot of resources within the
US, in a similar way to, say, if you had looked

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at, you know, the last century oil production
and be like, if oil if compute is the new oil,

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then you want to onshore as much of that as you
possibly can.

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Well, Lorenzo, we first met in 2012 in San
Francisco.

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We we've sat on ICs together.

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It's great to have you on.

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Great.

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David, it was such a pleasure.

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Thank you for a really fun conversation.