E174: The State of Venture Capital in 2025: Insights from a $1.8B AUM Chairman and Co-Founder

Today, I'm thrilled to welcome Arjun Sati, co-CEO of Kraken and chairman of Tribe Capital, a leading venture capital firm with over $1.8 billion in assets.

We dive into how Kraken differentiates itself from giants like Coinbase and Binance, the latest on the crypto markets in 2025, and Tribe Capital's edge in the highly competitive venture capital market.

Without further ado, here's my conversation with Arjun.

Arjun, you started as co-CEO of Kraken last October, obviously a month before the election.

How has crypto changed with the incoming Trump administration?

Aaron Ross Aaron, it's less so deregulation.

It's more that in the last, let's call it, four to five years, really post-FTX, I would say it was the linchpin, you had a pretty regulation by enforcement heavy SEC.

And in some cases, the regulators that surrounded them, what you've seen with the current administration, the current House, the current Senate, and the regulatory regime of the SEC, CFTC, et cetera, that they're much more willing to and now engaging with the industry.

Aaron Ross Powell, you're in a space where you compete against Coinbase, Binance.

How does Kraken differentiate itself in the ecosystem?

Take a step back away from crypto.

You look at any financial product that's out there and what the use case is.

That's what's most important.

So

if you were to separate them into three buckets, I would say you have retail consumers, you have professional slash day traders, and then you have what I say is products that are catered towards institutional slash clients.

So what does that really mean?

So consumer products.

So that's like the sofa's of the world, the chimes of the world, it's the eToros of the world.

It's enabling people to be able to trade or to save and get access to yield.

And you're seeing this as a worldwide phenomenon.

Coinbase and Robinhood also fit in that paradigm, which is like, how do I get access to the everyday person to be able to help enumerate or invest in their crypto?

On the opposite side, you've got commodities.

I'd say commodity products for institution, which is institutions are always going to be there.

They're trading.

They're thinking about collateral.

They're thinking about custody.

And so that's a separate set.

Professional trading and day trading, I think a lot of people overlook it, which is, you know, what does interactive brokers do?

What do they do for the ecosystem over the last 20 years?

What did the CME group do with their retail brokerage products?

So on and so forth.

And so there's a large sector of what I'd call the trading community or the economy that's generally been overlooked, but that's where we spent our time.

So the people that are focused on trading terminals, APIs, SDKs, getting access directly to an exchange, especially in crypto, to be able to day trade, professional trade, turn their book on a daily basis.

That's our customer base.

And so today it's about 2 million people per month as Kraken.

As crypto evolves, do you see these trading strategies evolving as well, or are they relatively mature at this point?

They're not really mature.

They've just started.

Four years ago, you were just thinking about Bitcoin, and then you had Ethereum, and then you had all the alternate coins that came from that.

But there was no options desk.

There was no staking yet.

There was no fixed futures yet.

There was no new options desk that are out there.

Now people are thinking about equity options and perpetuals on top of tokenized equities.

And so across asset strategies become more and more important, given that there are so many strategies worldwide.

You're just seeing an evolution of what's continuing to happen in what I'd say the democratization of finance since like the 70s and the 80s, but now it's happening on top of crypto rails and crypto backend.

You also have another hat.

You're the chairman of Tribe,

a venture fund with 1.8 billion, AUM.

What lessons do you take from being a venture capitalist to how you now run Kraken S CoCO?

We have a document actually internally.

We called it Tribe's 2030 Vision.

So it was...

It was based off of a global understanding of how to underwrite the risk of any asset.

And in this case, private companies.

Private companies are inherently private.

They don't share their information.

They want to be able to be left to operating on their own

for the long duration.

So as a venture capitalist, you want to partner with companies that are thinking about growing in the long term and are not susceptible to the same sort of market cyclicalities of what you'd see.

that might be volatile in the public markets.

And we've seen that over the last 10 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 WhatsApp acquisition.

We were former partners at a firm called Social Capital, where they helped build a lot of these frameworks.

And then myself and my co-founders had worked in social gaming and mobile gaming space, where we leveraged a lot of our quantitative, what we call 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 able to benchmark against thousands of companies and its feature sets.

So

what I call leading to lagging indicators of operating metrics and KPIs.

And so, when you have this very bottoms-up, very tactical, surgical view of how companies work, you actually get a very good view on what works and what doesn't, and what actually makes companies more and more successful by the things that they need to sort of focus on.

And then, our last stated goal is that we wanted to be as small as possible to be able to do this so that we had a very good understanding of how to move at speed, build and automate, build software around it,

and do whatever it took in order to make sure that we can have the best outcomes, not just for us and our limited partners, but also the companies that we work with.

And so the reason you see myself and my partners is that we build and incubate.

We invest at certain stages.

And then we've also now helped run companies at large scale that we've incubated from scratch

in some respect.

I run Kraken.

I started a...

human robotics company, two biopharma 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 of one companies.

How is that different from investing into market leaders?

At any given point in time, they could be synonymous with each other.

But what's more important is that you can have 50 companies and you decide to invest in the market leader of the, you know, the top one or two companies that are in the top 50 companies.

So let's, you know, let's just say interior decorating companies, whereas like automating that was like a big thing back in the day.

Then there's healthcare, then there was drug discovery.

I think what's really important is that at any given time, when you've got a large amount of companies competing in the same market or ecosystem, who's working and who's not working is really important.

So you could have a market leader that's not N of one.

And what that means is that they're just by far ahead,

maybe the best company in its class, but there's lots of companies that compete with them.

So what usually happens is that

the margins might go down, you might not have network effect, so they

have to think about other adjacent products and territories.

The reason we like to say N of one is N of one is 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 their business.

They grow their customer base.

They grow their shareholder base.

And then they can think about the products that they want to add to it.

We have a company like that called Shiprocket in India, where no matter what happens, there's no competitors.

It's inherently monopolistic in that merchants use the product, customers use the product, everyone in between that are market aggregators use the product.

and so they become their own default CRM database system for small and medium businesses.

I think the same thing about Capitol, which is when we started the company we helped incubate it, it was $6 million in revenue.

Today it's about $210 million in revenue.

The revenue doesn't really matter more so than

the product is so embedded into the workflow of small to medium merchants in Colombia, Mexico, Peru,

that they have to use it.

So they use it for payroll, they use it for benefits, they use it for lending, they use it for card and expense management.

Last time we were chatting, you mentioned that when you started tribe, you were stupid with your data sets.

What does that mean and how has that changed?

If you look at most venture funds in 2018 when they were raising, everyone said they use data to make decisions.

Of course, everyone uses data to make decisions.

They'll use Excel.

And that doesn't mean that you're data driven.

It doesn't mean that you're data informed.

It just means that you're using certain technology to be able to move forward.

So of course you can use Airtable.

Of course, you can use that database.

But the question we really asked was: A, are you storing your data in perpetuity?

Do we have the ability to query against it?

And do you have the ability to come up with investment 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 raw data dump from the company.

We work with them.

We give them a 50, 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 a data scientist or a product manager or a head of growth or a head of quantitative metrics, that I would come up with all these reports and I would spend, you know, if not tens of millions of dollars saying like, this is what the company looks like and here's what's working and what's not.

Most companies actually don't have this at the early stage and even the mid-stage.

And I used to think that late stage companies used to have this, but they don't either.

There's a very, very small set of companies that 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 us come up with investment criteria systems on top of this data set.

So when I said we were being

pretty stupid about it in the first approach is that we made the assumption that if you had this type of data, you could come up with these insights.

We made the assumption that if you had this type of data that you would query and benchmark this and so you can make better investment criteria decisions.

But that actually never happened.

We not just, we didn't only build this for ourselves, but we started building this out for the larger ecosystem and community so that they could help perpetuate themselves and and get better.

So bring that to life.

Let's say you're looking to back a Series A company.

How do you know which company to back using your data set?

All companies worldwide look very similar to each other.

A company in India shouldn't look any different than the company in the United States or a company in Indonesia or Mexico shouldn't look any different than the United States.

What I mean by that is that they build a product 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 it 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 it's all measurable from our perspective.

And that's what we've set out to do.

And frankly, what we've been able to do with the large set of our companies.

So you take that and you say, okay, great.

Your type of company, that might be

a code augmentation for AI.

The speed of that growth doesn't matter as much as what is the way in which the customer is using it as it grows.

You You can have 30 million new customers, but you can churn 29.9, like 30 days later or 60 days later or a year later.

That is quantifiable and that's measurable by the way in which people 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 with Carta.

We did that with Apollo.

This kind of goes on where we saw these enumerations of leading the lagging indicators.

And we ended up investing in these companies in some cases before there was any revenue scale because we were looking at usage and how people actually use the product and what monetization could look like over time.

And I think that insight's really important because that's how investors over a certain period of time over the last 10 to 15 years

had to think about investing into a social gaming company or a social networking company or a workflow product that wasn't monetizing yet.

There was a sort of laziness by VCs to apply

more nuanced metrics to companies that had revenue and growth versus in the gaming sector, sometimes these companies were pre-revenue.

So you really had to double double-click deep down into the leading indicators.

And you found that you could take that data and bring it into traditional companies.

What's more important is that you can take a look at that across not just one company, but thousands of companies, if not 15,000 companies or 36 million companies.

And so what it allows you to do is like how to benchmark yourself and how you're performing as a company against other companies that are very similar to you.

As an asset allocator, what you really care about is benchmark because you want to invest in the top 1% to 25% companies, right?

Like in how they're going to evolve over time.

It doesn't mean a 50th percentile company can't be a top 10% company.

And 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 you are 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 market, because you generally don't know how you compare against your competitive landscape as

you're scaling along the way.

So what you do is, what do we do?

Like, VCs will say, well, let's take a look at public comps and say, okay, great.

When Square was at this size and scale, what did they look like and how did they get there?

And so, should this company be similar or not?

Well, Square might not be the right analogy.

Maybe it's a different company.

Maybe when you got access to capital, it's different.

Maybe the supply and demand in a certain ecosystem is different.

If you're sitting in Brazil and you're growing, you're not going to use the same strategy that you used in a Silicon Valley company where they got subsidized with capital and they have access to debt.

It just, in order to think that way and systematically, there is a roadmap to what a company needs in 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 within those constraints.

A lot of the time that doesn't happen because you'll read a blog and it's really based off of not using any sort of investment criteria data set.

I'm not saying that there isn't a world for that.

And I think especially at the early stage, you got to focus and bet on team.

There's an art and a science.

But what we like to do is we say, we're going to focus on the foundation and science first.

And then what we can do is we can double down on the art to be able to help what the company needs to do and what the DNA of what success will look like.

Most companies, they just see blogs or they might see some heuristic 3x LTV CAC equals good and not even realize that it's for an entirely different industry, maybe for entirely different year.

You're getting data from all sorts of

cohorts in that same exact space.

How do you get companies to open up all their data and send it to you?

And talk to me about that process

so when we first started what we had said is that look

we helped instagram grow on facebook we were the growth and data science team around facebook we did the same thing for square in their early days we did the same thing for uber in the early days 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 to you and i think that's really important here is the insights and the report we will give back to you so we built our brand and reputation around that which is how do we make sure that we can recognize what your company does and what it did before?

No matter who you are, where you're located, we can 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 the seed series A and early B are actually,

they don't do a lot of this stuff.

And, you know, 80 to 90% of them will fail.

It's normal, right?

Like that, that's partly how you think about even your portfolio loss ratio construction in a traditional mindset.

And so we built that out.

What we learned is that that became so

that that had its own huge product market fit and companies were coming back to us again and again and again asking for help.

So what we did is we decided to productize that and spin that out as a separate product.

And so that company is called Termina and it's led by

our early data scientists and CTO and product managers that were working on that.

And so we

spun that out and we actually just let them work with companies directly to be able to gauge what it means means to be successful.

So we actually separate that.

And then what we do is we use Termina to help us identify and quantify and diligence companies when the companies come to us.

But because Tribe is a client, we're able to do that work for free for our portfolio and companies that we're talking to.

It's interesting.

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I think there's this inherent advantage in knowing where you are.

Even if you're a super ambitious team and you're growing 200%, but all of your competitors are growing 500%.

If you know that, you can now rally the team to grow faster.

And knowing where you are kind of provides this North Star for the entire team to galvanize behind 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?

Do you want to compound it for the long term?

If your retention expansion is really strong and you just need to do a little bit on new customer acquisition,

that's one way of doing it.

So for example, at Kraken, we've raised less than $25 million in QM since we started.

We didn't raise a billion.

We didn't raise $2 billion like some of the other folks in the ecosystem to get to their size and scale.

And we're on track.

We released our financials last year and we do it every quarter.

And so 2024, we had 1.5 billion of revenue and about 400 million of EBIT.

And this year, we should be on track to sort of double that.

I think

what's really important is

what was the pathway to get there?

And what are the decisions that you wanted to make?

We inherently decided that we wanted to be

fundraising light and very capital efficient with where we put our capital.

Some companies need to grow in order to do that, to be able to be competitive in the landscape, because there might be multiple competitors, some people don't.

And then you have other companies, especially I'd say in emerging markets or even in Europe, where you don't have access to the same capital.

So you start thinking about

capital ratio with your debt plus equity differently and how do you want to rebalance that and how do you want to reallocate that and reinvest that into the things that work.

The more you know about what's working and what's not, the better allocator you will be of your time and your capital and your human resources that are there because they're ultimately the same.

And so then what your roadmap is is that do you want to do 10 things right now or do you want to do two things?

We've seen this analogy of top companies, even SpaceX, they have this eye of Sauron.

They focus on one thing at a time.

Sometimes it's only for a week, but they have this hyper focus.

And you see this over and over in the top companies.

They don't focus on a bunch of things at once.

I think focus is a little bit of a misnomer.

What are you trying to achieve, right?

So if you start with your client base or your customer base, what do you need to be able to build for them?

So we're tribe capital and we've got a multitude of LPs that invest across all stages.

And so the reason we came up with our co-investment strategy is a lot of them want to do mid-stage, late-stage, pre-IPO to public holds.

So how do you facilitate that and work with them is a type of product mentality and thinking.

So you end up building multiple financial products 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 access to raw data?

What are the ways in which they can come in through a vehicle or help lead something?

It becomes an ecosystem/slash product play.

When I think about Kraken, we're a multitude of products.

We're not just once.

You have to do everything at the same time in order to be successful.

I go back and think about Alibaba.

I used to be 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 same time.

Why?

Well, if they didn't do that, they wouldn't have been able to have customers in their marketplace in the first place.

So I think it really depends where

you just need to know the nuances of the market, what your clients or your customers need, and then how do you build against that.

In the US, we've been told you should only build one product because we've got a large ecosystem of companies that help service each other, help support each other,

and you're help supporting multiple, sorry, you're helping, you have multiple products that support.

one customer.

That's actually great.

And that helps innovation and helps speed things along.

But there are also certain parts of the sector within the United States, like healthcare, for instance, where you have to be vertically integrated.

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 build what the customers need.

In some cases, I would argue, in order to change the aspects of the healthcare system, you might need to own the hospital.

So, you've seen other firms say, let's own this part of the stack, let's own the hardware, let's own the software.

And I think that's really healthy for the ecosystem because it won't evolve unless you try different mechanisms of what helps to grow.

You're seeing this now in the AI stack, right?

Like, you know, XAI and OpenAI, where we're also investors, has to build hardware.

They have to think about now energy production, which is full stack.

You've never really thought about any of these companies, especially when they were building data centers, thinking about energy production.

You're also thinking about the software on top of it.

And lastly, it's a very important piece.

They're still thinking about the value pool of the application layer, which is like, what is your workflow?

What do you use?

How do you click into what you need to get done?

And that actually ends up being very, very important.

That's not one product.

That's 10.

So every company, every ecosystem has its own unique solution for that time and place.

You have to use it.

First principles thinking.

You have to.

And it's one of the reasons why we ultimately like deferring back to the data:

let's just say there's a company that's actually got 10 inherent products that they have to build.

Well, I can measure that and I can quantify it and say, okay, 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 scaling and growing pretty quickly, like a Slack, great, here's how I benchmark them bottoms up with seat-based pricing.

Next one's going to be a token company.

Next one's going to be a value accrual through an application layer.

Next one might be software licensing.

These are all quantifiable because software is just helping us to enable

and move at a speed we were never able to, but we should be able to quantify 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 30, 40-year-old models and doing everything very manually,

where they're just going to look at either 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 to be able to understand and quantify like a private equity or like a hedge fund would quantitatively, even at the earliest stage, if we can, because there are signals that are starting to emerge.

even during what I call primordial ooze stage of pre-seed to seed.

Everyone has seen the stats.

A handful of venture capital firms have raised almost all the capital over the last 12 months and they have these large war chests.

How do you compete against them in the mid-stage and late stage?

What's really important is not competing against them.

It's working with them.

That's one.

There's this view where I think people have a very particular notion of zero sum.

I do think that's the case in some parts of the asset classes, but like, look, companies are staying private longer.

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 company around what their needs are.

What are the products that you build for them?

What's the unique value proposition that you offer them?

This is why we're structured the way we are, which is where operators, we think quantitatively, we build software and we 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 the company.

So that basically means that it kind of prices, not prices them out, but pushes them back to invest at a later stage.

So pre-seed and seed is getting rewritten in my opinion.

Seed to series A is getting rewritten in my opinion.

A to B is getting rewritten in my opinion.

So I would actually argue if you take a look at the stack of where capital is being deployed, there's a larger and larger bottleneck at the early stage, even though people keep saying early stage, early stage.

But if you take a look at the capital flow, the bottleneck has just gotten larger.

There was always a bottleneck for venture capital companies.

There was always a bottleneck for

high quality assets.

The bottleneck has just gotten larger.

And why is that the case?

There's There's more companies that need to access that capital.

There's more companies being built.

There's more companies that are venture-backed more than ever.

The quantum of capital might be lower the last couple of years, but it's still the slope is

up and to the right in terms of directionality.

So it just becomes harder.

And so I think these guys are going towards a different type of ballgame.

And I think it's good for the ecosystem.

It's healthy.

And so, and a lot of the people that want to invest into private and in venture have also never been typically asset allocators into venture.

So you've got got your traditional venture asset allocators.

You've got your new entrants and then you've got long duration capital thinking about it.

There's only one reason why that's the case is because companies are just private much, much longer.

And so you can make an argument for that being good or bad, but that's happening across the world and it's happening in multiple areas.

And we've seen that in India.

We're seeing that in Brazil.

We're seeing that in 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 comes in, which is like, now how do you think about crypto and liquidity and issuance of these types of companies, companies, tokenized equities for private and public, which will change the game again, but that'll be over the next 10 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 that companies are staying private longer.

And these companies are worth like, what, one, five, 10, 20, 50, 100 to 300 billion as they

stay private.

And, you know, frankly,

asset allocators are going to invest across different stages.

And so a venture capitalist, in my opinion, shouldn't be thinking about a $300 billion investment.

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You mentioned that the VC stages are being rewritten.

Give me an example of that.

So you had this advent of solo GPs.

You had operator GPs.

You had investors that are coming in at Series A and B.

Sorry, the series pre-seed and seed.

There was no such thing as precede and seed.

Like the concept of pre-seed is crazy because seed is where you're supposed to start.

And now, yeah, and what it really means is that like valuations that are less than 30 million posts and 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 some people are calling it as well.

So I think that's going to continue to evolve.

There's going to be a certain amount of what I'd call

disruption and revolution and consolidation in that part of the market.

And people will build their own value proposition.

First round capital was kind of famous for being their own disruptor in the ecosystem.

But if you look at them today, they're an institution.

And so you do that across all stages.

Again, we just talked about it.

The late stage guys, like GC, who knows?

They may or may not go public.

And Recent, they may or may not go public, but they're maybe thinking in that direction.

And they're doing things that are much more around late stage growth.

In some cases,

private equity style takeovers.

And I think that's really cool.

It's really interesting to watch.

multiple people come into.

They're also thinking about debt-related products on behalf of companies at the early stage because they've generally been starved.

So, again, I say like the rules are being rewritten.

It's because the venture capitalists are becoming more bold in terms of the types of products and offers that they want.

Some of the asset allocators that were hedge funds 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 to change and be more dynamic.

That's very good for an entrepreneur because the more competition there is, the better partners you get around the table.

And so, what we really need to question is: what's the speed at which that will happen?

You have a thesis on tokenization, not just in crypto, but in traditional venture and other asset classes.

What's something that you expect to happen around tokenization in the next decade?

Look, tokenization and liquidity in the crypto ecosystem is

pretty novel, right?

Because you have global participation, you've got global liquidity, you've got global order books, and you've got demand for what I call quality assets.

Today, a lot of those quality assets sit in the United States, private and public.

And so, you've already seen this huge demand for it,

for these quality assets, especially U.S.-based assets, U.S.-based yield, and then U.S.-based investment savings and yield.

A lot of that demand is going to be for private companies.

You see that today, you know, from institutions trying to buy, let's call it SpaceX or OpenAI.

That's at the later stage.

They consider them safe assets because of the size and scale and revenue that they have or the size and scale and subsidy that they have.

And so people want access to it.

I think of it as safe assets.

Some of it is gambling in some cases.

But what's really important is that there's demand for it.

When you've got global liquidity, you've got global access to capital, which has been a first over the last couple of years, especially with crypto.

You're going to see these products start coming out more and more where you're giving this access and this yield to somebody in Argentina, to somebody in Mexico, to somebody in Indonesia, to somebody in Vietnam, somebody in Cambodia.

And I think it makes the world much, much more interesting.

Is that what you think happens to liquidity versus an influx of IPO?

Do you see this kind of secondary becoming its own 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 what it means to go public, right?

And do you go public on an exchange in the United States?

Do you go public

on a crypto exchange in the future?

Where do you issue your shares?

Who do you work with?

Who are the partners that you're going to think about?

As a private company, how do you get access to capital?

These are changing very quickly.

And a lot of people have grand aspirations.

And I wish them luck because this is what I would want as an entrepreneur.

This is what I want as a venture capitalist.

This is what I want

as someone who's running a company as well.

You texted me a few months ago.

telling me that you had started a humanoid company, Foundation.

Tell me about the company and where is it at today?

So we built a company called Foundation Robotics.

It's an incubation.

I worked with my founders, Michael and Sankit.

Sankit came from the fintech space, and Michael came from

a company called Cobalt Robotics.

And

we had this thesis around what robotics are going to look like.

And the thesis was that you've got a lot of vertically integrated applications.

And we think that's really important.

But like moving from vertically integrated to being able to

enable your customers to be able to build their own systems was really important for us.

And so you have got to build hardware, you've got to build software, got to build an operating system, and you obviously have to build systems that continue to learn on the software and on the hardware side.

You've got to build robotics that communicate with each other for manufacturing, for supply chain logistics.

So that was the master plan.

We really wanted to see what are the ways in which we can build multiple robotic systems that are inherently talking to each other.

If you actually go to the website,

you go 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.

We think about what the robots need at any given time.

We want to be able to make sure that they can connect across a multitude of use cases.

So, what are those use cases?

So, picking and packaging, knitting, assembly line systems, things that they have to move around and touch, where you traditionally would have more humans moving around.

So,

our mission statement is building technologies that make life self-sustaining on Earth and beyond.

And so, you have to make sure that the robots are capable, similar to how other humans are capable.

You have to be able to make sure that they can work as a fleet.

You want to be able to build a multitude of robots that can work with each other or separate from each other.

And you want to be able to make sure that you can build that in any environment whatsoever, in the desert, in the cold, in space.

And so, that was the mission around how we wanted to build the foundation: is that, like, in theory, you could take this robot,

so this humanoid 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 and Figure.

How do you compete against them?

Again, I think it's really just use case.

If you think about this market as trillions of dollars, you know, millions of use cases, the market's huge for this, right?

And I think Elon would probably be the first to say that he wants to see more companies like this and more products like this out there so that we can all move in the same direction.

And we're hoping to be number one for the focuses that we have.

So as I mentioned, supply chain and logistics, movement of small parts,

defense-related activities,

transport of energy.

These are the types of things that we're thinking of.

An important question.

When can we expect a humanoid robot at home in cleaning and

cleaning the house?

So

that's a really great question.

Our focus is for them to be in production facilities.

Our focus is for them to be focused on defense.

Our focus is for them to focus on supply chain logistics and large materials or hazardous materials in some cases.

So a lot of what we're thinking about is what are the areas that are very hard for humans to work through?

And how do we make sure that there are robots there to help augment that today?

Well, Arjun, it's been amazing to see your incredible career since we first met around ISOC in 2009, I believe, in your office in San Francisco.

So

thanks for jumping on the podcast and look forward to seeing you down soon.

Yeah, thanks for having me.

And look,

we're lucky to have you guys as partners.

We look forward to working with you more.

And, you know, and if there's folks that you know that we should work with or talk to, we'd always be willing to think about that across incubating, investing, and partnering together.

Awesome.

Thanks, Sargent.

Thanks, David.

Appreciate it.

Thanks for listening to my conversation.

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