In this episode of How I Invest, I speak with Arjun Sethi—Chairman and co-founder of Tribe Capital, Co-CEO of Kraken, and one of the sharpest thinkers in venture capital and crypto today. Arjun breaks down how he approaches investing in “N-of-1” companies, what most VCs get wrong about data, and why the traditional funding stages like “pre-seed” and “Series A” are being rewritten in real time.
We also go deep into Arjun’s frameworks for scaling world-class companies, the evolution of crypto in a changing political landscape, and the big bets he’s making at the frontier—including humanoid robotics.
Whether you're an allocator, founder, or just fascinated by the future of finance, this conversation is packed with sharp insights and original thinking.
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Transcript
Episode Transcript
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(00:00):
Today, I'm thrilled to welcome Arjun Sathi, coCEO of Kraken and chairman of Tribe Capital, a
leading venture capital firm with over$1,800,000,000 in assets.
We dive into how Kraken differentiates itselffrom giants like Coinbase and Binance, the
latest on the crypto markets in 2025, and TribeCapital's edge in the highly competitive
(00:20):
venture capital market.
Without further ado, here's my conversationwith Arjun.
Arjun, you started as co CEO of Kraken lastOctober, obviously, a month before the
election.
How has crypto changed with the incoming Trumpadministration?
It's less so deregulation.
It's more that in the last, let's call it, fourto five years, really post FTX, I would say it
(00:42):
was the linchpin.
You had a pretty regulation by enforcementheavy SEC, and in some cases, the regulators
that surrounded them.
What you've seen with the currentadministration, the current House, the current
senate, and the regulatory regime of the SEC,CFTC, etcetera, that they're much more willing
(01:02):
to and now engaging with the industry.
You're in a space where you compete againstCoinbase, Binance, how does Kraken
differentiates itself in the ecosystem?
Take a step back away from crypto, you look atany financial product that's out there, and
what the use cases, that's what's mostimportant.
(01:23):
So there if you were to were to separate theminto three buckets, I would say you have retail
consumers, you have professional slash daytraders, and then you have what I say is
products that are catered towards institutionalslash clients.
So what does that really mean?
So consumer products, so that's like the SoFi'sof the world, the chimes of the world to eat or
else the world, right?
(01:43):
It's enabling people to be able to trade, or tosave and get access to yield.
And you're seeing this as a worldwidephenomenon.
Coinbase and Robinhood also fit in thatparadigm, which is like, do I get access to the
everyday person to be able to help enumerate orinvest in crypto?
On the opposite side, you've got commodities,I'd say commodity products for institution,
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which institutions are always going be there.
They're trading, they're thinking aboutcollateral, they're thinking about custody.
And so that's a separate set.
Professional trading and day trading, I think alot of people overlook it, which is, you know,
what does interactive brokers do?
What do they do for the ecosystem over the lasttwenty years?
What did the CME Group do with their retailbrokerage products?
So on and so And so there's a large sector ofwhat I'd call the trading community or the
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economy that's generally been overlooked, butthat's where we spent our time.
So the people that are focused on tradingterminals, API's, SDKs, getting access to
directly to exchange, especially in crypto tobe able to, you know, day trade, professional
trade, turn their book on a daily basis.
That's our customer base.
And so today it's about, you know, 2,000,000people per month as Kraken.
(02:52):
Crypto evolves, do you see these tradingstrategies evolving as well?
Or are they relatively mature at this point?
They're not really mature.
They've just started four years ago, you werejust thinking about Bitcoin, and then you had
Ethereum, and then you had all the alternatecoins that came from that.
But there was no options desk.
There was no staking yet.
There was no fixed futures yet.
(03:12):
There was no new options desk that are outthere.
Now your people are thinking about equityoptions and perpetuals on top of tokenized
equities.
And so across asset strategies become more andmore important, given that there are so many
strategies worldwide, you're just seeing anevolution of what's continuing to happen in
what I'd say the democratization of finance.
It's like the 70s and 80s.
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But now it's happening on on top of cryptorails and crypto back end.
You also have another hat.
You're the chairman of Tribe, a venture fundwith 1,800,000,000.0 AUM.
What lessons do you take from being a venturecapitalist to how you now run Kraken as Co CEO?
We have a document actually internally.
We called it Tribe's 2030 vision.
So it was it was based off of a globalunderstanding of how to underwrite the risk of
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any asset and and in this case, privatecompanies.
Private companies are inherently private.
They don't share their information.
They want to be able to be left to operating ontheir own for the long duration.
So as a venture capitalist, you want to partnerwith companies that are thinking about growing
in the long term and are not susceptible to thesame sort of market cyclicality of what you'd
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see that might be volatile in the publicmarkets.
And we've seen that, you know, over the lastten years with the ups and downs of the
markets, high highs and low lows.
We worked at Facebook.
We had helped with the Instagram and WhatsAppacquisition.
We were former partners at a firm called SocialCapital where they helped build a lot of these
frameworks.
And then myself and my co founders have workedin social gaming and mobile gaming space where
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we leveraged a lot of our quantitative, what wecall approach to product market fit and
features around what is healthy and what's not.
And that was usually one company at a time.
And then what we did over time is we were ableto benchmark against thousands of companies and
its feature sets.
So what I call leading to lagging indicators ofoperating metrics and KPIs.
(05:04):
And so when you have this very bottoms up, verytactical surgical view of how companies work,
you actually get a very good view on what worksand what doesn't, and what actually makes
companies more and more successful by thethings that they need to sort of focus on.
And then our last stated goal is that we wantedto be as small as possible to be able to do
this so that we had a very good understandingof how to move at speed, build and automate
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build software around it, and do whatever ittook in order to make sure that we can have the
best outcomes, not just for us and our limitedpartners, but also the companies that we work
with.
And so the reason you see myself and mypartners is that we build and incubate, we
invest at certain stages.
And then we've also now helped run companiesthat at large scale that we've incubated from
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scratch in some some respect.
I run Kraken.
I started a humanoid robotics company, twobiopharma companies with my partners.
So it's not me alone.
So the team sort of makes the dream work.
You mentioned that you want to invest into n ofone companies.
How's that different from investing into marketleaders?
At any given point in time, that could besynonymous with each other.
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But what's more important is that you can have50 companies and you decide to invest in the
market leader of the top one or two companiesthat are in the top 50 companies.
So let's just say interior decoratingcompanies, whereas automating that was a big
thing back in the day.
Then there's health care, then there's drugdiscovery.
I think what's really important is that at anygiven time, when you've got a large amount of
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companies competing in the same market orecosystem, who's working and who's not working
is really important.
So you could have a market leader that's not nof one.
And what that means is that they're just by farand ahead, maybe the best company in this
class, but there's lots of companies thatcompete with them.
So what usually happens that they might, themargins might go down, you might not have
network effect.
So they have to think about other adjacentproducts and territories.
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The reason we like to say N of one is n of oneis essentially inherently monopolistic.
What I mean by that is something like Carta,like no matter what Carta does good or bad,
they just continue to compound and grow theirbusiness, grow their customer base, grow their
shareholder base, they can think about theproducts that they want to add to it.
We have a company like that called Shiprocketin India, where no matter what happens, there's
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no competitors.
It's inherently monopolistic in that merchantsuse the product, customers use the product,
everyone in between that are market aggregatorsuse the product.
And so they become their own default CRMdatabase system for small to medium businesses.
I think the same thing about Capital, which iswhen we started the company we helped incubate
it, it was 6,000,000 in revenue.
Today, it's about $210,000,000 in revenue.
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The revenue doesn't really matter more so thanthe the product is so embedded into the
workflow of small and medium merchants inColombia, Mexico, Peru, that they have to use
it.
So they use it for payroll, they use it forbenefits, they use it for lending, they use it
for card and expense management.
Last time we were chatting, you mentioned thatwhen you started Tribe, you were stupid with
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your data sets.
What does that mean?
And how has that changed?
If you look at most venture funds in 2018, whenthey were raising, everyone said they use data
to make decisions.
Of course, everyone uses data to makedecisions, they they'll use Excel.
And that doesn't mean that your data drivendoesn't mean that your data informed, it just
means that you're using certain technology tobe able to move forward.
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So of course, you can use your table, ofcourse, you can use your database.
But the question we really asked was a, are youstoring your data in perpetuity?
Do we have the ability to query against it?
And do you have the ability to come up withinvestment criterias on it?
Are you able to automate that?
Are you able to benchmark all those data sets?
And then also, where's that data coming from?
So for us, we built a company called Termina,which literally allows us to be able to take a
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raw data dump from the company.
We work with them, we give them a 5,100, 150,even a 200 page report on what the company
does.
And it's the same way if I was to come in as adata scientist or a product manager or head of
growth or head of quantitative metrics, that Iwould come up with all these reports.
And I would spend, you know, if not 10s ofmillions of dollars saying like, this is what
(09:10):
the company looks like.
And here's what's working, what's not.
Most companies actually don't have this at theearly stage, and even the mid stage.
And I used to think that late stage companiesused to have this, but they don't either.
There's a very, very small set of companiesthat actually have this type of expertise and
access this type of insights.
So we decided to build this.
And then we decided to use this and and help uscome up with investment criteria systems on top
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of this data set.
So when I said we were being, you know, prettystupid about it in the approach is that we made
the assumption that if you have this type ofdata, you could come up with these insights.
We made the assumption that if you had thistype of data, that you would query and
benchmark this, and so you can make betterinvestment criteria decisions.
But that actually never happened.
We didn't only build this for ourselves, but westarted building this out for the larger
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ecosystem and communities so that they couldhelp perpetuate themselves and get better.
So bring that to life.
Let's say you're looking to back a series acompany.
How do you know which company to back usingyour dataset?
All companies worldwide look very similar toeach other.
And a company in India shouldn't look anydifferent than the company in The United States
or a company in Indonesia or Mexico shouldn'tlook any different in The United States.
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What I mean by that is that they build aproduct or a service.
There's some value exchange somewhere.
It's really just cash in and cash out.
And how are you measuring that?
And then what are the nuances along the way,right?
Is it b2b b2b to c is a direct to consumer,like we use these terms for cash in and cash
out and the nuances along the way.
That's all quantifiable and so measurable fromour perspective.
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And that's what we've set out to do.
Frankly, we've been able to do with a large setof our companies.
So you take that and you say, okay, great, yourtype of company that might be a code augmented
augmentation for AI, that's the speed of thatgrowth doesn't matter.
As much as what is the way in which thecustomer is using it as it grows, you can have,
you know, 30,000,000 new customers, but you canchurn 29.9, like thirty days later, sixty days
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later, or a year later, that is quantifiable.
And that's measurable by the way in whichpeople will use your products.
And that's what we've done since day one.
So we did that with zoom.
We did that with, Slack, we did that withCarta, we did that with Apollo, this kind of
goes on where we saw these enumerations ofleading the lagging indicators.
And we ended up investing in these companies insome cases, before there was any revenue scale,
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because we were looking at usage and like howpeople actually use the product and what
monetization could look like over time.
And I think that insight is really importantbecause that's how investors over a certain
period of time, over the last ten to fifteenyears, had to think about investing into a
social gaming company or a social networkingcompany or a workflow product that wasn't
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monetizing yet.
There was a sort of laziness by VCs to applymore nuanced metrics to companies that had
revenue and growth versus in the gaming sector.
Sometimes these companies were pre revenue, soyou really had to double click deep down into
the leading indicators.
And you found that you could take that data andbring it into traditional companies.
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What's more important is that you can take alook at that across not just one company, but
thousands of companies, if not 15,000 companiesor 36,000,000 companies.
And so what it allows you to do is like how tobenchmark yourself and how you're performing as
a company against other companies that are verysimilar to you.
As an asset allocator, what you really careabout is benchmark because you want to invest
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in the top one to 25 companies, like and howthey're going to evolve over time.
It doesn't mean a percentile company can't be atop 10% company.
It doesn't mean vice versa that a top 10%company can't go down on benchmarks.
It just means that at least you know where youare and what you need to continue to improve.
A lot of people fly blind.
Founders fly blind, executives fly blind,investors fly blind, especially in the private
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market, because you generally don't know howyou compare against your competitive landscape
as you're scaling along the way.
So what you do is what do we do?
VCs will say, well, let's take a look at publiccomps and say, okay, great, when Square was at
this size and scale, what do they look like?
How do they get there?
And so should this company be similar or not?
Well, Square might not be the right analogy.
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Maybe it's a different company.
Maybe when you got access to capital, it'sdifferent.
Maybe the supply and demand in a certainecosystem is different.
If you're sitting in Brazil and you're growing,you're not going use the same strategy that you
used in a Silicon Valley company where they gotsubsidized with capital and they have access to
debt.
Order to think that way and systematically,there is a roadmap to what a company needs in
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order to be successful.
And once you're able to predefine that around,okay, here are our parameters, then you can
actually start building your products withinthose constraints.
A lot of the time that doesn't happen becauseyou'll read a blog, and it's really based off
of not using any sort of investment criteriadata set.
I'm not saying that there isn't a world forthat.
And I think especially at the early stage,you've got to focus and bet on team.
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There's an art and a science.
But what we like to do is we say we're going tofocus on the foundation of science And then
what we can do is we can double down on the artto be able to help what the company needs to do
and what the DNA of what success will looklike.
Most companies, they just see blogs or they maysee some heuristic three x LTV CAC equals good
and not even realize that it's for an entirelydifferent industry, maybe for entirely
(14:16):
different year.
You're getting data from all sorts of cohortsin that same exact space.
How do you get companies to open up all theirdata and send it to you?
And talk to me about that process.
So when we started, what we had said is thatlook, we helped Instagram grow on Facebook, we
(14:38):
were the growth data science team aroundFacebook.
We did the same thing for Square in their earlydays.
We did the same thing for Uber in their earlydays.
And so this is the process we use.
Here's the data set we'll ask for.
And here is the report we will give back toyou.
And I think that's really important.
Here is the insights and the report we willgive back to you.
So we built our brand and reputation aroundthat, which is how do we make sure that we can
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recognize what your company does and what itdid before.
No matter who you are, where you're located, wecan give you a really good perspective of how
well or how poorly you're doing in some cases.
Most and let's be frank, most companies at theseed series A and early B are actually, they
don't do a lot of this stuff.
And and, you know, 80 to 90% of them will fail.
(15:22):
It's normal, right?
Like that that's partly how you think abouteven your portfolio loss ratio construction in
a traditional mindset.
And so we built that out.
What we learned is that that became so thatthat had its own huge product market fit.
And companies were coming back to us again andagain and again asking for help.
So what we did is we decided to productize thatand spin that out as a separate product.
(15:44):
So that company is called Termina.
And it's led by our early data scientists andCTO and product managers that were working on
that.
And so we spun that out, and we actually justlet them work with companies directly to be
able to gauge what it means to be successful.
We actually separate that.
And then what we do is we use Termina to helpus identify and quantify and diligence
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companies when the companies come to us.
But because tribe is a client, we're able to dothat work for free for our portfolio and
companies that we're that we're talking to.
It's interesting, there's this inherentadvantage in knowing where you are, Even if
you're a super ambitious team and you'regrowing 200%, but all of your competitors are
growing 500, if you know that, you can nowrally the team to grow faster.
(16:31):
And knowing where you are kind of provides thisNorth Star for the entire team to galvanize
behind and and a benchmark to now try to
beat.
You could do that or a counter to it would be,how do you want to run your business?
Did you want a compound for the long term, ifyour retention expansion is really strong, you
just need to do a little bit on new customeracquisition, that's one way of doing it.
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So for example, at Kraken, we've raised lessthan $25,000,000 in Qum since we started.
We didn't raise $1,000,000,000 We didn't raise$2,000,000,000 like some of the other folks to
get to their size and scale.
And we're on track.
We released our financials last year, we do itevery quarter.
As of 2024, we had a 1,500,000,000.0 of revenueand about 400,000,000 of EBIT.
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And then and this year, we should be on trackto sort of double that.
I think like what's really important is, like,what was the pathway to get there?
And what are the decisions that you wanted tomake?
We inherently decided that we wanted to befundraising light and very capital efficient
with where we put our capital.
Some companies need to grow in order to dothat, to be able to be competitive in the
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landscape, because there might be multiplecompetitors, some people don't.
And then you have other companies, especially,I'd say, emerging markets or even in Europe,
where you don't have access to the samecapital.
So you start thinking about capital ratio withyour debt plus equity differently.
And how do you want to rebalance that?
And how do you want to reallocate that andreinvest that into the things that work?
The more you know about what's working, what'snot, the better allocator you will be of your
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time and your capital and your human resourcesthat are there, cause they're ultimately the
same.
And so then what your roadmap is is that youwanna do 10 things right now or do you wanna do
two things?
I've seen this analogy of top companies, evenSpaceX, they have this eye of Sauron.
They focus on one thing at a time, sometimesonly for a week, but they have this hyper
focus, and you see this over and over in thetop companies.
They don't focus on a bunch of things at once.
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I think focus is a little bit of a misnomer.
What are you trying to achieve, right?
So if start with your client base or yourcustomer base, what do you need to be able to
build for them?
So we're Tribe Capital, and we've got amultitude of LPs that invest across all stages.
And so the reason we came up with our coinvestment strategy is a lot of them want to do
mid stage, late stage pre IPO to public holds.
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So how do you facilitate that and work withthem is a type of product mentality and
thinking.
So you end up building multiple financialproducts for them, not just early stage funds,
but how do they get access to our companies?
What are the ways in which they can get accessto raw data?
What are the ways in which they can come inthrough a vehicle or help lead something?
It becomes, an ecosystem slash product play.
When I think about Kraken, we're a multitude ofproducts.
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We're not just ones.
You have to do everything at the same time inorder to be successful.
I go back and think about Alibaba.
Used to a board observer there through Yahoo.
That wasn't one company.
They were a payments company, lending company,marketplace company.
Like, there were multiple companies at the sametime.
Why?
Well, if they didn't do that, they wouldn'thave been able to have come customers in their
marketplace in the place.
So I think it really depends where you justneed to know the nuances of the market, what
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your clients or your customers need, and thenhow do you build against that.
In The US, we've been told you should onlybuild one product, because we've got a large
ecosystem of companies that help service eachother, help support each other, and you're help
supporting multiple sorry, you're helping youhave multiple products that support one
customer.
That's actually great.
And then helps innovation, helps speed thingsalong.
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But there are also certain parts of the sectorwithin The United States, like health care, for
instance, where you have to be verticallyintegrated.
You need access to data.
You need access to payments.
You need access to medical codes.
If you don't, then you're not able to buildwhat the customers need.
In some cases, I would argue, in order tochange aspects of the health care system, you
might need to own the hospital.
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So you've seen other firms say, let's own thispart of the stack, let's own the hardware,
let's own the software.
And I think like that's really healthy for theecosystem because they won't evolve unless you
try different mechanisms of what helps to grow.
You're seeing this now in the AI stack, right?
Like xAI and OpenAI, where we're alsoinvestors, has to build hardware.
They have to think about now energy production,which is full stack.
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You've never really thought about any of thesecompanies, especially when they were building
data centers thinking about energy production.
You're also thinking about the software on topof it.
And lastly, it's a very important piece.
They're still thinking about the value accrualof the application layer, which is like, what
is your workflow?
What do you use?
How do you click into what you need to getdone?
And that actually ends up being very, veryimportant.
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That's not one product.
That's 10.
So every company, every ecosystem has its ownunique solution for that time and place.
You have to use it.
principle's thinking.
You have to.
And it's one of the reasons why we ultimatelylike deferring back to the data is that let's
just say there's a company that's actually 10inherent products that they have to build.
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Well, I can measure that and I can quantify itand say, great, out of the 10 products that
they build in order for the company to succeed,here's where they rank across all 10 products.
If it's a one product company that's scalingand growing pretty quickly like a Slack, great,
here's how I benchmark them bottoms up withseat based pricing.
Next one's gonna be a token company.
Next one's gonna be a value accrual through anapplication layer.
(21:40):
Next one might be software licensing.
These are all quantifiable because software isjust helping us to enable and move at a speed
we were never able to, but we should be able toquantify and measure at a speed that we were
never able to.
And I think traditional private equity,traditional venture capital, in my opinion, is
still stuck, you know, using thirty, forty yearold models and and doing everything very
(22:02):
manually, where they're just going to look ateither the financials, if you're a late stage,
and then either the team at the early stage,and then some things in the middle.
And we want to be able to do both, we want tobe able to understand and quantify, like a
private equity or like a hedge fund wouldquantitatively, even at the earliest stage if
we can, because there's signals that arestarting to emerge even during what I call
(22:23):
primordial ooze stage of pre seed deceit.
Everyone has seen the stats.
A handful of venture capital firms have raisedalmost all of the capital over the last twelve
months, and they have these large war chests.
How do you compete against them in the midstage and late stage?
What's really important is not competingagainst them.
It's working with them.
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That's one.
There's this view where I think people have avery particular notion of zero sum.
I do think that's the case in some parts of theasset classes.
Like, look, companies are staying privatelonger.
There is more liquidity in the ecosystem.
We do the same thing.
We're an RIA.
We do primary and secondary.
So you want to be able to work with the companyaround what their needs are.
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What are the products that you build for them?
What's the unique value proposition that youoffer them?
This is why we're structured the way we are,which is we're operators.
We think quantitatively, we build software, andwe want to work with the companies.
And a lot of the times, these mega funds,they're having a harder and harder time
deploying a small amount of capital.
They need to buy a larger portion of thecompany.
So that basically means that kind of pricesthat prices them up, but pushes them back to
(23:27):
invest at a later stage.
So pre seed and seed is getting rewritten, inmy opinion, seed to series A is getting
rewritten, in my opinion, A to B is gettingrewritten, in my opinion.
So I would I would actually argue, if you takea look at the stack where capital is being
deployed, there's a larger and largerbottleneck at the early stage, even though
people keep saying early stage early stage.
But if you take a look at the capital flow, thebottleneck has just gotten larger, there was
(23:49):
always a bottleneck for venture capitalcompanies, there was always a bottleneck for
high quality assets, the bottleneck has justgotten larger.
And why is that the case, there's morecompanies that need access to that capital,
there's more companies being built, there'smore companies that are venture backed more
than ever, The quantum of capital might belower over the last couple of years, but it's
still the slope is up and to the right in termsof directionality.
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So it just becomes harder.
And so I think these guys are going towards adifferent type of ballgame.
And I think it's good for the ecosystem.
It's healthy.
And a lot of the people that want to investinto private and venture have also never been
typically asset allocators into venture.
So you've got your traditional venture assetallocators.
You've got your new entrants, and then you'vegot long duration capital thinking about it.
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There's only one reason why that's the case isbecause companies are just private much, much
longer.
And so you can make an argument for that beinggood or bad.
But that's happening across the world.
And it's happening in multiple areas.
And we're seeing that in India, we're seeingthat in Brazil, we're seeing that Mexico, we're
seeing that in Europe.
And so there's going to be the next step.
And I think this is where crypto really comesin, which is like, now how do you think about
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crypto and liquidity and issuance of thesetypes of companies, tokenized equities for
private and public, which will change the gameagain, but that'll be over the next ten years.
And so I don't want to pontificate.
That's what I'm working on.
I view the world that way.
But if you look at the view today, it's thatcompanies are staying private longer.
These companies are worth like what, one, five,ten, twenty, fifty, one hundred, three hundred
(25:17):
billion as they stay private.
Frankly, asset allocators are going to investacross different stages.
And so a venture capitalist, in my opinion,shouldn't be thinking about, you know, a
$300,000,000,000 investment.
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(25:39):
You mentioned that the VC stages are beingrewritten.
Give me an example of that.
So you had this advent of solo GPS, you hadoperator GPS, you had investors that are coming
in at series a and b, sorry, the series, preseed and seed.
There was no such thing as pre seed and seed.
Like the concept of pre seed is crazy becauselike seed is where you're supposed to start.
(26:00):
And now, yeah, and it what it really means isthat like valuations that are less than, you
know, 30,000,000 posts and, you know, 10 to 20,are you going to be doing a note that's
converting at a certain stage?
Are you doing it pre yc rounds is what youknow, some people are calling it as well.
So I think like that's going to continue toevolve, there's going be a certain amount of
what I call disruption and revolution andconsolidation in that part of the market and
(26:23):
people will build their own value proposition,right?
Like, round capital was kind of famous forbeing their own disruptor in the ecosystem.
But if you look at them today, they're, they'rean institution.
And so you do that across all stages.
Again, we just talked about it, the late stageguys like GC, who knows, they may or may not go
public and recent, they may or may not gopublic, but they're, they're may be thinking in
that direction.
And they're doing things that are much morearound late stage growth, in some cases,
(26:49):
private equity style takeovers.
And I think that's really cool.
It's really interesting to watch multiplepeople come in.
They're also thinking about debt relatedproducts on behalf of companies at the early
stage because of generally been starved.
So again, I say like the rules are beingrewritten.
It's because the venture capitalists arebecoming more bold in terms of the types of
products and offers that they want.
(27:10):
Some of the asset allocators that were hedgefunds are becoming more bold coming into the
private markets.
And you'll have them clash, right?
And you'll also have them compete.
And then you'll have the market continue tochange and be more dynamic.
That's very good for an entrepreneur, becausethe more competition there is, the better
partners you get around the table.
And so what we really need to question is,what's speed at which that will happen?
(27:33):
You have a thesis on tokenization, not just incrypto, but in traditional venture and other
asset classes.
What's something that you expect to happenaround tokenization in the next decade?
Look, tokenization and liquidity in the cryptoecosystem is is pretty novel.
(27:53):
Right?
Because you have global participation, you'vegot global liquidity, you've got global order
books, and you've got demand for what I callquality assets.
Today, lot of those quality assets sit in TheUnited States private and public.
And so you've already seen this huge demand forit for for these quality assets, especially US
based assets, US based yield, and then USB USbased investment savings and yield.
(28:18):
A lot of that demand is going to be for privatecompanies, you see that today, you know, from
institutions trying to buy, let's call itSpaceX, or OpenAI, that's at the later stage,
they consider them safe assets because of thesize and scale and revenue that they have, or
the size and scale and subsidy that they have.
And so people want access to it.
Think of it as safe assets, some of it isgambling in some cases.
(28:40):
But what's really important is that there'sdemand for it.
When you've got global liquidity, you've gotglobal access to capital, which has been a over
the last couple of years, especially withcrypto, you're going to see these products
start coming out more and more where you'regiving this access in this yield to somebody in
Argentina, to somebody in Mexico, to somebodyin Indonesia, somebody in Vietnam, somebody in
Cambodia.
(29:01):
And I think it makes the world much, much moreinteresting.
Is that what you think happens to liquidityversus an influx of IPO?
Do you see this kind of secondary becoming itsown solve for liquidity for early stage
investors?
No, I think you'll see a combination of both.
It'll be multiplicative.
I think we're going to have to figure out whatit means to go public, right?
(29:22):
And do you go public on a exchange in TheUnited States?
Do you go public on a on a crypto exchange inthe future?
Where do you issue your shares?
Who do you work with?
What are the partners that you're gonna thinkabout?
As a private company, how do you get access tocapital, these are changing very quickly.
And and a lot of people have grand aspirations,and and I wish them luck because, like, this is
(29:42):
what I would want as an entrepreneur.
This is what I want as a venture capitalist.
This is what I want, you know, as someone who'srunning a company as well.
You texted me a few months ago telling me thatyou had started a humanoid company, a
foundation.
Tell me about the company, and where is it attoday?
So we built a company called FoundationRobotics.
(30:02):
It's an it's an incubation.
I worked with my founders, Michael and Sanket.
Sanket came from the fintech space, and Michaelcame from a company called Cobalt Robotics.
And we had this thesis around what robotics aregoing to look like.
And the thesis was that you've got a lot ofvertically integrated applications.
(30:24):
And we think that's really important.
But moving from vertically integrated to beingable to enable your customers to be able to
build their own systems was really importantfor us.
And so you've got to build hardware.
You've got to build software.
You've to build an operating system.
And you obviously have to build systems thatcontinue to learn on the software and on the
hardware side.
You've got to build robotics that communicatewith each other for manufacturing, for supply
(30:47):
chain logistics.
So that was the master plan.
We really wanted to see what are the ways inwhich we can build multiple robotic systems
that are inherently talking to each other.
If you actually go to the website, you just yougo to the page that calls it master plan.
We're trying to build a multitude of products,not just one.
So we think about power production and storage.
(31:07):
We think about what the robots need at anygiven time.
We want to be able to make sure that they canconnect across a multitude of use cases.
So what are those use cases?
So picking and packaging, knitting, assemblyline systems, things that like they have to
move around and touch, where you traditionallywould have more humans moving around.
(31:27):
So you were we were like, our mission statementis building technologies that make life self
sustaining on Earth and beyond.
And so you have to make sure that the robotsare capable, similar to how other humans are
capable.
You have to be able to make sure that they canwork as a fleet.
You wanna be able to build a multitude ofrobots that can work with each other or
separate from each other.
And you want to be able to make sure that youcan build that in any environment whatsoever,
(31:51):
in the desert, in the cold, in space.
And so that was the mission around how wewanted to build foundation is that, like, in
theory, you could take this robot, so thishumanoid robotic, and have it work in space,
have it work on the moon, have it work on Mars.
You have competitors, Tesla and Elon Musk andFigure.
How do you compete against them?
(32:12):
Again, think it's really just use case.
If you think about this market as trillions ofdollars, you know, millions of use cases, the
markets huge for this, right.
And I think, you know, Elon would probably bethe to say that, he wants to see more companies
like this and more products like this out thereso that we can all move in the same direction.
And we're hoping to be number one for thefocuses that we have.
(32:34):
So as I mentioned, supply chain and logistics,movement of small parts, defense related
activities, transport of energy, these are thetypes of things that we're thinking of.
An important question, when could we expect ahumanoid robot at home in cleaning the house?
(32:54):
So that's a really great question.
Our focus is for them to be in productionfacilities.
Our focus is for them to be focused on defense.
Our focus is for them to focus on supply chainlogistics and, you know, large materials or
hazardous materials in some cases.
So a lot of what we're thinking about is whatare the areas that are very hard for humans to
work through, and then how do we make sure thatthere are robots there to help augment that
(33:16):
today?
Well, Arjun, it's been it's been amazing to seeyour incredible career since we met around ISOC
in 02/2009, I believe, in your office in SanFrancisco.
So thanks.
Thanks for jumping on the podcast and lookforward to seeing you down soon.
Yeah, thanks for having me.
And and and look, we're we're lucky to have youguys as partners.
(33:38):
We look forward to working with you more.
And if there's folks that you know that weshould work with or talk to, we'd always be
willing to think about that across incubating,investing, and partnering together.
Awesome.
Thanks, Arjun.
Thanks, David.
Appreciate it.
Thanks for listening to my conversation.
If you enjoyed this episode, please share witha friend.
This helps us grow.
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(33:59):
Thank you for your support.
Today, I'm thrilled to welcome Arjun Sathi, coCEO of Kraken and chairman of Tribe Capital, a
leading venture capital firm with over$1,800,000,000 in assets.
We dive into how Kraken differentiates itselffrom giants like Coinbase and Binance, the
latest on the crypto markets in 2025, and TribeCapital's edge in the highly competitive
(00:20):
venture capital market.
Without further ado, here's my conversationwith Arjun.
Arjun, you started as co CEO of Kraken lastOctober, obviously, a month before the
election.
How has crypto changed with the incoming Trumpadministration?
It's less so deregulation.
It's more that in the last, let's call it, fourto five years, really post FTX, I would say it
(00:42):
was the linchpin.
You had a pretty regulation by enforcementheavy SEC, and in some cases, the regulators
that surrounded them.
What you've seen with the currentadministration, the current House, the current
senate, and the regulatory regime of the SEC,CFTC, etcetera, that they're much more willing
(01:02):
to and now engaging with the industry.
You're in a space where you compete againstCoinbase, Binance, how does Kraken
differentiates itself in the ecosystem?
Take a step back away from crypto, you look atany financial product that's out there, and
what the use cases, that's what's mostimportant.
(01:23):
So there if you were to were to separate theminto three buckets, I would say you have retail
consumers, you have professional slash daytraders, and then you have what I say is
products that are catered towards institutionalslash clients.
So what does that really mean?
So consumer products, so that's like the SoFi'sof the world, the chimes of the world to eat or
else the world, right?
(01:43):
It's enabling people to be able to trade, or tosave and get access to yield.
And you're seeing this as a worldwidephenomenon.
Coinbase and Robinhood also fit in thatparadigm, which is like, do I get access to the
everyday person to be able to help enumerate orinvest in crypto?
On the opposite side, you've got commodities,I'd say commodity products for institution,
(02:05):
which institutions are always going be there.
They're trading, they're thinking aboutcollateral, they're thinking about custody.
And so that's a separate set.
Professional trading and day trading, I think alot of people overlook it, which is, you know,
what does interactive brokers do?
What do they do for the ecosystem over the lasttwenty years?
What did the CME Group do with their retailbrokerage products?
So on and so And so there's a large sector ofwhat I'd call the trading community or the
(02:31):
economy that's generally been overlooked, butthat's where we spent our time.
So the people that are focused on tradingterminals, API's, SDKs, getting access to
directly to exchange, especially in crypto tobe able to, you know, day trade, professional
trade, turn their book on a daily basis.
That's our customer base.
And so today it's about, you know, 2,000,000people per month as Kraken.
(02:52):
Crypto evolves, do you see these tradingstrategies evolving as well?
Or are they relatively mature at this point?
They're not really mature.
They've just started four years ago, you werejust thinking about Bitcoin, and then you had
Ethereum, and then you had all the alternatecoins that came from that.
But there was no options desk.
There was no staking yet.
There was no fixed futures yet.
(03:12):
There was no new options desk that are outthere.
Now your people are thinking about equityoptions and perpetuals on top of tokenized
equities.
And so across asset strategies become more andmore important, given that there are so many
strategies worldwide, you're just seeing anevolution of what's continuing to happen in
what I'd say the democratization of finance.
It's like the 70s and 80s.
(03:33):
But now it's happening on on top of cryptorails and crypto back end.
You also have another hat.
You're the chairman of Tribe, a venture fundwith 1,800,000,000.0 AUM.
What lessons do you take from being a venturecapitalist to how you now run Kraken as Co CEO?
We have a document actually internally.
We called it Tribe's 2030 vision.
So it was it was based off of a globalunderstanding of how to underwrite the risk of
(03:59):
any asset and and in this case, privatecompanies.
Private companies are inherently private.
They don't share their information.
They want to be able to be left to operating ontheir own for the long duration.
So as a venture capitalist, you want to partnerwith companies that are thinking about growing
in the long term and are not susceptible to thesame sort of market cyclicality of what you'd
(04:21):
see that might be volatile in the publicmarkets.
And we've seen that, you know, over the lastten years with the ups and downs of the
markets, high highs and low lows.
We worked at Facebook.
We had helped with the Instagram and WhatsAppacquisition.
We were former partners at a firm called SocialCapital where they helped build a lot of these
frameworks.
And then myself and my co founders have workedin social gaming and mobile gaming space where
(04:42):
we leveraged a lot of our quantitative, what wecall approach to product market fit and
features around what is healthy and what's not.
And that was usually one company at a time.
And then what we did over time is we were ableto benchmark against thousands of companies and
its feature sets.
So what I call leading to lagging indicators ofoperating metrics and KPIs.
(05:04):
And so when you have this very bottoms up, verytactical surgical view of how companies work,
you actually get a very good view on what worksand what doesn't, and what actually makes
companies more and more successful by thethings that they need to sort of focus on.
And then our last stated goal is that we wantedto be as small as possible to be able to do
this so that we had a very good understandingof how to move at speed, build and automate
(05:27):
build software around it, and do whatever ittook in order to make sure that we can have the
best outcomes, not just for us and our limitedpartners, but also the companies that we work
with.
And so the reason you see myself and mypartners is that we build and incubate, we
invest at certain stages.
And then we've also now helped run companiesthat at large scale that we've incubated from
(05:48):
scratch in some some respect.
I run Kraken.
I started a humanoid robotics company, twobiopharma companies with my partners.
So it's not me alone.
So the team sort of makes the dream work.
You mentioned that you want to invest into n ofone companies.
How's that different from investing into marketleaders?
At any given point in time, that could besynonymous with each other.
(06:11):
But what's more important is that you can have50 companies and you decide to invest in the
market leader of the top one or two companiesthat are in the top 50 companies.
So let's just say interior decoratingcompanies, whereas automating that was a big
thing back in the day.
Then there's health care, then there's drugdiscovery.
I think what's really important is that at anygiven time, when you've got a large amount of
(06:34):
companies competing in the same market orecosystem, who's working and who's not working
is really important.
So you could have a market leader that's not nof one.
And what that means is that they're just by farand ahead, maybe the best company in this
class, but there's lots of companies thatcompete with them.
So what usually happens that they might, themargins might go down, you might not have
network effect.
So they have to think about other adjacentproducts and territories.
(06:57):
The reason we like to say N of one is n of oneis essentially inherently monopolistic.
What I mean by that is something like Carta,like no matter what Carta does good or bad,
they just continue to compound and grow theirbusiness, grow their customer base, grow their
shareholder base, they can think about theproducts that they want to add to it.
We have a company like that called Shiprocketin India, where no matter what happens, there's
(07:21):
no competitors.
It's inherently monopolistic in that merchantsuse the product, customers use the product,
everyone in between that are market aggregatorsuse the product.
And so they become their own default CRMdatabase system for small to medium businesses.
I think the same thing about Capital, which iswhen we started the company we helped incubate
it, it was 6,000,000 in revenue.
Today, it's about $210,000,000 in revenue.
(07:42):
The revenue doesn't really matter more so thanthe the product is so embedded into the
workflow of small and medium merchants inColombia, Mexico, Peru, that they have to use
it.
So they use it for payroll, they use it forbenefits, they use it for lending, they use it
for card and expense management.
Last time we were chatting, you mentioned thatwhen you started Tribe, you were stupid with
(08:04):
your data sets.
What does that mean?
And how has that changed?
If you look at most venture funds in 2018, whenthey were raising, everyone said they use data
to make decisions.
Of course, everyone uses data to makedecisions, they they'll use Excel.
And that doesn't mean that your data drivendoesn't mean that your data informed, it just
means that you're using certain technology tobe able to move forward.
(08:26):
So of course, you can use your table, ofcourse, you can use your database.
But the question we really asked was a, are youstoring your data in perpetuity?
Do we have the ability to query against it?
And do you have the ability to come up withinvestment criterias on it?
Are you able to automate that?
Are you able to benchmark all those data sets?
And then also, where's that data coming from?
So for us, we built a company called Termina,which literally allows us to be able to take a
(08:48):
raw data dump from the company.
We work with them, we give them a 5,100, 150,even a 200 page report on what the company
does.
And it's the same way if I was to come in as adata scientist or a product manager or head of
growth or head of quantitative metrics, that Iwould come up with all these reports.
And I would spend, you know, if not 10s ofmillions of dollars saying like, this is what
(09:10):
the company looks like.
And here's what's working, what's not.
Most companies actually don't have this at theearly stage, and even the mid stage.
And I used to think that late stage companiesused to have this, but they don't either.
There's a very, very small set of companiesthat actually have this type of expertise and
access this type of insights.
So we decided to build this.
And then we decided to use this and and help uscome up with investment criteria systems on top
(09:33):
of this data set.
So when I said we were being, you know, prettystupid about it in the approach is that we made
the assumption that if you have this type ofdata, you could come up with these insights.
We made the assumption that if you had thistype of data, that you would query and
benchmark this, and so you can make betterinvestment criteria decisions.
But that actually never happened.
We didn't only build this for ourselves, but westarted building this out for the larger
(09:56):
ecosystem and communities so that they couldhelp perpetuate themselves and get better.
So bring that to life.
Let's say you're looking to back a series acompany.
How do you know which company to back usingyour dataset?
All companies worldwide look very similar toeach other.
And a company in India shouldn't look anydifferent than the company in The United States
or a company in Indonesia or Mexico shouldn'tlook any different in The United States.
(10:20):
What I mean by that is that they build aproduct or a service.
There's some value exchange somewhere.
It's really just cash in and cash out.
And how are you measuring that?
And then what are the nuances along the way,right?
Is it b2b b2b to c is a direct to consumer,like we use these terms for cash in and cash
out and the nuances along the way.
That's all quantifiable and so measurable fromour perspective.
(10:41):
And that's what we've set out to do.
Frankly, we've been able to do with a large setof our companies.
So you take that and you say, okay, great, yourtype of company that might be a code augmented
augmentation for AI, that's the speed of thatgrowth doesn't matter.
As much as what is the way in which thecustomer is using it as it grows, you can have,
you know, 30,000,000 new customers, but you canchurn 29.9, like thirty days later, sixty days
(11:05):
later, or a year later, that is quantifiable.
And that's measurable by the way in whichpeople will use your products.
And that's what we've done since day one.
So we did that with zoom.
We did that with, Slack, we did that withCarta, we did that with Apollo, this kind of
goes on where we saw these enumerations ofleading the lagging indicators.
And we ended up investing in these companies insome cases, before there was any revenue scale,
(11:25):
because we were looking at usage and like howpeople actually use the product and what
monetization could look like over time.
And I think that insight is really importantbecause that's how investors over a certain
period of time, over the last ten to fifteenyears, had to think about investing into a
social gaming company or a social networkingcompany or a workflow product that wasn't
(11:46):
monetizing yet.
There was a sort of laziness by VCs to applymore nuanced metrics to companies that had
revenue and growth versus in the gaming sector.
Sometimes these companies were pre revenue, soyou really had to double click deep down into
the leading indicators.
And you found that you could take that data andbring it into traditional companies.
(12:06):
What's more important is that you can take alook at that across not just one company, but
thousands of companies, if not 15,000 companiesor 36,000,000 companies.
And so what it allows you to do is like how tobenchmark yourself and how you're performing as
a company against other companies that are verysimilar to you.
As an asset allocator, what you really careabout is benchmark because you want to invest
(12:27):
in the top one to 25 companies, like and howthey're going to evolve over time.
It doesn't mean a percentile company can't be atop 10% company.
It doesn't mean vice versa that a top 10%company can't go down on benchmarks.
It just means that at least you know where youare and what you need to continue to improve.
A lot of people fly blind.
Founders fly blind, executives fly blind,investors fly blind, especially in the private
(12:50):
market, because you generally don't know howyou compare against your competitive landscape
as you're scaling along the way.
So what you do is what do we do?
VCs will say, well, let's take a look at publiccomps and say, okay, great, when Square was at
this size and scale, what do they look like?
How do they get there?
And so should this company be similar or not?
Well, Square might not be the right analogy.
(13:11):
Maybe it's a different company.
Maybe when you got access to capital, it'sdifferent.
Maybe the supply and demand in a certainecosystem is different.
If you're sitting in Brazil and you're growing,you're not going use the same strategy that you
used in a Silicon Valley company where they gotsubsidized with capital and they have access to
debt.
Order to think that way and systematically,there is a roadmap to what a company needs in
(13:32):
order to be successful.
And once you're able to predefine that around,okay, here are our parameters, then you can
actually start building your products withinthose constraints.
A lot of the time that doesn't happen becauseyou'll read a blog, and it's really based off
of not using any sort of investment criteriadata set.
I'm not saying that there isn't a world forthat.
And I think especially at the early stage,you've got to focus and bet on team.
(13:54):
There's an art and a science.
But what we like to do is we say we're going tofocus on the foundation of science And then
what we can do is we can double down on the artto be able to help what the company needs to do
and what the DNA of what success will looklike.
Most companies, they just see blogs or they maysee some heuristic three x LTV CAC equals good
and not even realize that it's for an entirelydifferent industry, maybe for entirely
(14:16):
different year.
You're getting data from all sorts of cohortsin that same exact space.
How do you get companies to open up all theirdata and send it to you?
And talk to me about that process.
So when we started, what we had said is thatlook, we helped Instagram grow on Facebook, we
(14:38):
were the growth data science team aroundFacebook.
We did the same thing for Square in their earlydays.
We did the same thing for Uber in their earlydays.
And so this is the process we use.
Here's the data set we'll ask for.
And here is the report we will give back toyou.
And I think that's really important.
Here is the insights and the report we willgive back to you.
So we built our brand and reputation aroundthat, which is how do we make sure that we can
(15:01):
recognize what your company does and what itdid before.
No matter who you are, where you're located, wecan give you a really good perspective of how
well or how poorly you're doing in some cases.
Most and let's be frank, most companies at theseed series A and early B are actually, they
don't do a lot of this stuff.
And and, you know, 80 to 90% of them will fail.
(15:22):
It's normal, right?
Like that that's partly how you think abouteven your portfolio loss ratio construction in
a traditional mindset.
And so we built that out.
What we learned is that that became so thatthat had its own huge product market fit.
And companies were coming back to us again andagain and again asking for help.
So what we did is we decided to productize thatand spin that out as a separate product.
(15:44):
So that company is called Termina.
And it's led by our early data scientists andCTO and product managers that were working on
that.
And so we spun that out, and we actually justlet them work with companies directly to be
able to gauge what it means to be successful.
We actually separate that.
And then what we do is we use Termina to helpus identify and quantify and diligence
(16:09):
companies when the companies come to us.
But because tribe is a client, we're able to dothat work for free for our portfolio and
companies that we're that we're talking to.
It's interesting, there's this inherentadvantage in knowing where you are, Even if
you're a super ambitious team and you'regrowing 200%, but all of your competitors are
growing 500, if you know that, you can nowrally the team to grow faster.
(16:31):
And knowing where you are kind of provides thisNorth Star for the entire team to galvanize
behind and and a benchmark to now try to
beat.
You could do that or a counter to it would be,how do you want to run your business?
Did you want a compound for the long term, ifyour retention expansion is really strong, you
just need to do a little bit on new customeracquisition, that's one way of doing it.
(16:51):
So for example, at Kraken, we've raised lessthan $25,000,000 in Qum since we started.
We didn't raise $1,000,000,000 We didn't raise$2,000,000,000 like some of the other folks to
get to their size and scale.
And we're on track.
We released our financials last year, we do itevery quarter.
As of 2024, we had a 1,500,000,000.0 of revenueand about 400,000,000 of EBIT.
(17:14):
And then and this year, we should be on trackto sort of double that.
I think like what's really important is, like,what was the pathway to get there?
And what are the decisions that you wanted tomake?
We inherently decided that we wanted to befundraising light and very capital efficient
with where we put our capital.
Some companies need to grow in order to dothat, to be able to be competitive in the
(17:36):
landscape, because there might be multiplecompetitors, some people don't.
And then you have other companies, especially,I'd say, emerging markets or even in Europe,
where you don't have access to the samecapital.
So you start thinking about capital ratio withyour debt plus equity differently.
And how do you want to rebalance that?
And how do you want to reallocate that andreinvest that into the things that work?
The more you know about what's working, what'snot, the better allocator you will be of your
(18:00):
time and your capital and your human resourcesthat are there, cause they're ultimately the
same.
And so then what your roadmap is is that youwanna do 10 things right now or do you wanna do
two things?
I've seen this analogy of top companies, evenSpaceX, they have this eye of Sauron.
They focus on one thing at a time, sometimesonly for a week, but they have this hyper
focus, and you see this over and over in thetop companies.
They don't focus on a bunch of things at once.
(18:23):
I think focus is a little bit of a misnomer.
What are you trying to achieve, right?
So if start with your client base or yourcustomer base, what do you need to be able to
build for them?
So we're Tribe Capital, and we've got amultitude of LPs that invest across all stages.
And so the reason we came up with our coinvestment strategy is a lot of them want to do
mid stage, late stage pre IPO to public holds.
(18:46):
So how do you facilitate that and work withthem is a type of product mentality and
thinking.
So you end up building multiple financialproducts for them, not just early stage funds,
but how do they get access to our companies?
What are the ways in which they can get accessto raw data?
What are the ways in which they can come inthrough a vehicle or help lead something?
It becomes, an ecosystem slash product play.
When I think about Kraken, we're a multitude ofproducts.
(19:07):
We're not just ones.
You have to do everything at the same time inorder to be successful.
I go back and think about Alibaba.
Used to a board observer there through Yahoo.
That wasn't one company.
They were a payments company, lending company,marketplace company.
Like, there were multiple companies at the sametime.
Why?
Well, if they didn't do that, they wouldn'thave been able to have come customers in their
marketplace in the place.
So I think it really depends where you justneed to know the nuances of the market, what
(19:32):
your clients or your customers need, and thenhow do you build against that.
In The US, we've been told you should onlybuild one product, because we've got a large
ecosystem of companies that help service eachother, help support each other, and you're help
supporting multiple sorry, you're helping youhave multiple products that support one
customer.
That's actually great.
And then helps innovation, helps speed thingsalong.
(19:53):
But there are also certain parts of the sectorwithin The United States, like health care, for
instance, where you have to be verticallyintegrated.
You need access to data.
You need access to payments.
You need access to medical codes.
If you don't, then you're not able to buildwhat the customers need.
In some cases, I would argue, in order tochange aspects of the health care system, you
might need to own the hospital.
(20:13):
So you've seen other firms say, let's own thispart of the stack, let's own the hardware,
let's own the software.
And I think like that's really healthy for theecosystem because they won't evolve unless you
try different mechanisms of what helps to grow.
You're seeing this now in the AI stack, right?
Like xAI and OpenAI, where we're alsoinvestors, has to build hardware.
They have to think about now energy production,which is full stack.
(20:36):
You've never really thought about any of thesecompanies, especially when they were building
data centers thinking about energy production.
You're also thinking about the software on topof it.
And lastly, it's a very important piece.
They're still thinking about the value accrualof the application layer, which is like, what
is your workflow?
What do you use?
How do you click into what you need to getdone?
And that actually ends up being very, veryimportant.
(20:58):
That's not one product.
That's 10.
So every company, every ecosystem has its ownunique solution for that time and place.
You have to use it.
principle's thinking.
You have to.
And it's one of the reasons why we ultimatelylike deferring back to the data is that let's
just say there's a company that's actually 10inherent products that they have to build.
(21:20):
Well, I can measure that and I can quantify itand say, great, out of the 10 products that
they build in order for the company to succeed,here's where they rank across all 10 products.
If it's a one product company that's scalingand growing pretty quickly like a Slack, great,
here's how I benchmark them bottoms up withseat based pricing.
Next one's gonna be a token company.
Next one's gonna be a value accrual through anapplication layer.
(21:40):
Next one might be software licensing.
These are all quantifiable because software isjust helping us to enable and move at a speed
we were never able to, but we should be able toquantify and measure at a speed that we were
never able to.
And I think traditional private equity,traditional venture capital, in my opinion, is
still stuck, you know, using thirty, forty yearold models and and doing everything very
(22:02):
manually, where they're just going to look ateither the financials, if you're a late stage,
and then either the team at the early stage,and then some things in the middle.
And we want to be able to do both, we want tobe able to understand and quantify, like a
private equity or like a hedge fund wouldquantitatively, even at the earliest stage if
we can, because there's signals that arestarting to emerge even during what I call
(22:23):
primordial ooze stage of pre seed deceit.
Everyone has seen the stats.
A handful of venture capital firms have raisedalmost all of the capital over the last twelve
months, and they have these large war chests.
How do you compete against them in the midstage and late stage?
What's really important is not competingagainst them.
It's working with them.
(22:43):
That's one.
There's this view where I think people have avery particular notion of zero sum.
I do think that's the case in some parts of theasset classes.
Like, look, companies are staying privatelonger.
There is more liquidity in the ecosystem.
We do the same thing.
We're an RIA.
We do primary and secondary.
So you want to be able to work with the companyaround what their needs are.
(23:04):
What are the products that you build for them?
What's the unique value proposition that youoffer them?
This is why we're structured the way we are,which is we're operators.
We think quantitatively, we build software, andwe want to work with the companies.
And a lot of the times, these mega funds,they're having a harder and harder time
deploying a small amount of capital.
They need to buy a larger portion of thecompany.
So that basically means that kind of pricesthat prices them up, but pushes them back to
(23:27):
invest at a later stage.
So pre seed and seed is getting rewritten, inmy opinion, seed to series A is getting
rewritten, in my opinion, A to B is gettingrewritten, in my opinion.
So I would I would actually argue, if you takea look at the stack where capital is being
deployed, there's a larger and largerbottleneck at the early stage, even though
people keep saying early stage early stage.
But if you take a look at the capital flow, thebottleneck has just gotten larger, there was
(23:49):
always a bottleneck for venture capitalcompanies, there was always a bottleneck for
high quality assets, the bottleneck has justgotten larger.
And why is that the case, there's morecompanies that need access to that capital,
there's more companies being built, there'smore companies that are venture backed more
than ever, The quantum of capital might belower over the last couple of years, but it's
still the slope is up and to the right in termsof directionality.
(24:13):
So it just becomes harder.
And so I think these guys are going towards adifferent type of ballgame.
And I think it's good for the ecosystem.
It's healthy.
And a lot of the people that want to investinto private and venture have also never been
typically asset allocators into venture.
So you've got your traditional venture assetallocators.
You've got your new entrants, and then you'vegot long duration capital thinking about it.
(24:35):
There's only one reason why that's the case isbecause companies are just private much, much
longer.
And so you can make an argument for that beinggood or bad.
But that's happening across the world.
And it's happening in multiple areas.
And we're seeing that in India, we're seeingthat in Brazil, we're seeing that Mexico, we're
seeing that in Europe.
And so there's going to be the next step.
And I think this is where crypto really comesin, which is like, now how do you think about
(24:56):
crypto and liquidity and issuance of thesetypes of companies, tokenized equities for
private and public, which will change the gameagain, but that'll be over the next ten years.
And so I don't want to pontificate.
That's what I'm working on.
I view the world that way.
But if you look at the view today, it's thatcompanies are staying private longer.
These companies are worth like what, one, five,ten, twenty, fifty, one hundred, three hundred
(25:17):
billion as they stay private.
Frankly, asset allocators are going to investacross different stages.
And so a venture capitalist, in my opinion,shouldn't be thinking about, you know, a
$300,000,000,000 investment.
Thank you for listening.
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(25:39):
You mentioned that the VC stages are beingrewritten.
Give me an example of that.
So you had this advent of solo GPS, you hadoperator GPS, you had investors that are coming
in at series a and b, sorry, the series, preseed and seed.
There was no such thing as pre seed and seed.
Like the concept of pre seed is crazy becauselike seed is where you're supposed to start.
(26:00):
And now, yeah, and it what it really means isthat like valuations that are less than, you
know, 30,000,000 posts and, you know, 10 to 20,are you going to be doing a note that's
converting at a certain stage?
Are you doing it pre yc rounds is what youknow, some people are calling it as well.
So I think like that's going to continue toevolve, there's going be a certain amount of
what I call disruption and revolution andconsolidation in that part of the market and
(26:23):
people will build their own value proposition,right?
Like, round capital was kind of famous forbeing their own disruptor in the ecosystem.
But if you look at them today, they're, they'rean institution.
And so you do that across all stages.
Again, we just talked about it, the late stageguys like GC, who knows, they may or may not go
public and recent, they may or may not gopublic, but they're, they're may be thinking in
that direction.
And they're doing things that are much morearound late stage growth, in some cases,
(26:49):
private equity style takeovers.
And I think that's really cool.
It's really interesting to watch multiplepeople come in.
They're also thinking about debt relatedproducts on behalf of companies at the early
stage because of generally been starved.
So again, I say like the rules are beingrewritten.
It's because the venture capitalists arebecoming more bold in terms of the types of
products and offers that they want.
(27:10):
Some of the asset allocators that were hedgefunds are becoming more bold coming into the
private markets.
And you'll have them clash, right?
And you'll also have them compete.
And then you'll have the market continue tochange and be more dynamic.
That's very good for an entrepreneur, becausethe more competition there is, the better
partners you get around the table.
And so what we really need to question is,what's speed at which that will happen?
(27:33):
You have a thesis on tokenization, not just incrypto, but in traditional venture and other
asset classes.
What's something that you expect to happenaround tokenization in the next decade?
Look, tokenization and liquidity in the cryptoecosystem is is pretty novel.
(27:53):
Right?
Because you have global participation, you'vegot global liquidity, you've got global order
books, and you've got demand for what I callquality assets.
Today, lot of those quality assets sit in TheUnited States private and public.
And so you've already seen this huge demand forit for for these quality assets, especially US
based assets, US based yield, and then USB USbased investment savings and yield.
(28:18):
A lot of that demand is going to be for privatecompanies, you see that today, you know, from
institutions trying to buy, let's call itSpaceX, or OpenAI, that's at the later stage,
they consider them safe assets because of thesize and scale and revenue that they have, or
the size and scale and subsidy that they have.
And so people want access to it.
Think of it as safe assets, some of it isgambling in some cases.
(28:40):
But what's really important is that there'sdemand for it.
When you've got global liquidity, you've gotglobal access to capital, which has been a over
the last couple of years, especially withcrypto, you're going to see these products
start coming out more and more where you'regiving this access in this yield to somebody in
Argentina, to somebody in Mexico, to somebodyin Indonesia, somebody in Vietnam, somebody in
Cambodia.
(29:01):
And I think it makes the world much, much moreinteresting.
Is that what you think happens to liquidityversus an influx of IPO?
Do you see this kind of secondary becoming itsown solve for liquidity for early stage
investors?
No, I think you'll see a combination of both.
It'll be multiplicative.
I think we're going to have to figure out whatit means to go public, right?
(29:22):
And do you go public on a exchange in TheUnited States?
Do you go public on a on a crypto exchange inthe future?
Where do you issue your shares?
Who do you work with?
What are the partners that you're gonna thinkabout?
As a private company, how do you get access tocapital, these are changing very quickly.
And and a lot of people have grand aspirations,and and I wish them luck because, like, this is
(29:42):
what I would want as an entrepreneur.
This is what I want as a venture capitalist.
This is what I want, you know, as someone who'srunning a company as well.
You texted me a few months ago telling me thatyou had started a humanoid company, a
foundation.
Tell me about the company, and where is it attoday?
So we built a company called FoundationRobotics.
(30:02):
It's an it's an incubation.
I worked with my founders, Michael and Sanket.
Sanket came from the fintech space, and Michaelcame from a company called Cobalt Robotics.
And we had this thesis around what robotics aregoing to look like.
And the thesis was that you've got a lot ofvertically integrated applications.
(30:24):
And we think that's really important.
But moving from vertically integrated to beingable to enable your customers to be able to
build their own systems was really importantfor us.
And so you've got to build hardware.
You've got to build software.
You've to build an operating system.
And you obviously have to build systems thatcontinue to learn on the software and on the
hardware side.
You've got to build robotics that communicatewith each other for manufacturing, for supply
(30:47):
chain logistics.
So that was the master plan.
We really wanted to see what are the ways inwhich we can build multiple robotic systems
that are inherently talking to each other.
If you actually go to the website, you just yougo to the page that calls it master plan.
We're trying to build a multitude of products,not just one.
So we think about power production and storage.
(31:07):
We think about what the robots need at anygiven time.
We want to be able to make sure that they canconnect across a multitude of use cases.
So what are those use cases?
So picking and packaging, knitting, assemblyline systems, things that like they have to
move around and touch, where you traditionallywould have more humans moving around.
(31:27):
So you were we were like, our mission statementis building technologies that make life self
sustaining on Earth and beyond.
And so you have to make sure that the robotsare capable, similar to how other humans are
capable.
You have to be able to make sure that they canwork as a fleet.
You wanna be able to build a multitude ofrobots that can work with each other or
separate from each other.
And you want to be able to make sure that youcan build that in any environment whatsoever,
(31:51):
in the desert, in the cold, in space.
And so that was the mission around how wewanted to build foundation is that, like, in
theory, you could take this robot, so thishumanoid robotic, and have it work in space,
have it work on the moon, have it work on Mars.
You have competitors, Tesla and Elon Musk andFigure.
How do you compete against them?
(32:12):
Again, think it's really just use case.
If you think about this market as trillions ofdollars, you know, millions of use cases, the
markets huge for this, right.
And I think, you know, Elon would probably bethe to say that, he wants to see more companies
like this and more products like this out thereso that we can all move in the same direction.
And we're hoping to be number one for thefocuses that we have.
(32:34):
So as I mentioned, supply chain and logistics,movement of small parts, defense related
activities, transport of energy, these are thetypes of things that we're thinking of.
An important question, when could we expect ahumanoid robot at home in cleaning the house?
(32:54):
So that's a really great question.
Our focus is for them to be in productionfacilities.
Our focus is for them to be focused on defense.
Our focus is for them to focus on supply chainlogistics and, you know, large materials or
hazardous materials in some cases.
So a lot of what we're thinking about is whatare the areas that are very hard for humans to
work through, and then how do we make sure thatthere are robots there to help augment that
(33:16):
today?
Well, Arjun, it's been it's been amazing to seeyour incredible career since we met around ISOC
in 02/2009, I believe, in your office in SanFrancisco.
So thanks.
Thanks for jumping on the podcast and lookforward to seeing you down soon.
Yeah, thanks for having me.
And and and look, we're we're lucky to have youguys as partners.
(33:38):
We look forward to working with you more.
And if there's folks that you know that weshould work with or talk to, we'd always be
willing to think about that across incubating,investing, and partnering together.
Awesome.
Thanks, Arjun.
Thanks, David.
Appreciate it.
Thanks for listening to my conversation.
If you enjoyed this episode, please share witha friend.
This helps us grow.
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(33:59):
Thank you for your support.
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