Vlad Tenev - Navigating Robinhood's Evolution - [Invest Like the Best, EP.384]

Transcript from https://podmenti.com/t/33e3f555dc09382e

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My guest today is Vlad Tenet. Vlad is the CEO and co-founder of Robinhood.
It was such a treat to sit down with him and discuss the behind the scenes of a revolutionary business we all know well.
He details Robin Hood's journey to zero cost trading and what it means to build a consumer centric financial product.
Vlad believes in finding the harmonies across mathematics and art and applies this lens to everything he builds.
We discussed Robin Hood's new credit card and products on the horizon, the company's toughest moments, including the GameStop episode, and the compelling future of AI in financial services. Please enjoy this conversation with Vlad Tenet.
So Vlad, when we last talked, this is a strange place to start a conversation with you, probably for most people listening, but it was sure intriguing to me when we last spoke.
Can you explain what mathematical
Superintelligence is
To us.
Mathematical superintelligence is basically
An artificial intelligence that can solve math problems.
At a superior capability to
The sum total of all humans on Earth.
So
I think there's various degrees of mathematical intelligence.
And
One thing I personally believe
Which I think is a little bit
Not controversial, but I think most people don't understand this. When you say mathematical superintelligence, most people think you're building some fancy calculator that can multiply big numbers or
Come up with very, very large primes.
And those are impressive things that computers have been better than humans at for a very long time.
But
Really, I think the next frontier in artificial intelligence is building agents that can reason and can think like humans. And a lot of the big AI labs are talking about reasoning as sort of this.
next goal and you can see the limitations of the current models with reasoning because they just make obvious mistakes.
And they very, very confidently say wrong things.
It's particularly bad with math, but also
Language based
logical deductions.
So
My belief
is that mathematics is reasoning.
And so when you talk about building a mathematical superintelligence, that's another way of
Saying something that can reason, take logical steps, make deductions.
figure out itself when its own logical deductions are wrong and course correct.
And really something that can think and solve problems at a level
that's in excess of what humans are capable of solving.
And I think the litmus test for this will be
Millennium prize problems.
Which are basically some of the world's most difficult unsolved problems in mathematics.
And these are things like the Riemann hypothesis.
probably the most famous unsolved problem.
And
These are very rarely solved.
Бамен.
I was privileged to study under this professor Paul Cohen at Stanford.
Who solved one of them.
One of the most famous ones, and he won a Fields Medal for it.
It was called the independence of the continuum hypothesis.
And so like solving one of these problems is very, very rare.
And
My belief is that the next one will be solved by artificial intelligence. And once we get to that point,
All future
Millennium prize problems and like
Difficult
Mathematical problems will likely be solved by artificial intelligence.
And I think that's not too contrarian of a view. If you look at, for example, Metaculus, which is a prediction market where people make predictions about
advances in AI and when certain things will happen.
Last I checked, it was a forty-three percent chance that the next Millennium Prize problem will be solved by AI. So I think the chances is higher than that, and there will at least be AI augmentation in the critical workflow. But I think once we get to that point.
We'll basically have
mathematical superintelligence at our disposal.
What do you think is the right way to think about building this? Like is this a whole adjacent
Pursuit.
to the text based, chat based foundation models from OpenAI and Anthropic, is it
something that they should do and fold in? Is it something that should be built separately? I've got a million questions about this because
If it is the reasoning engine.
then that seems really important and like we want to pursue that and build it.
So like how does this get built? Is it way different than what we've become used to with just scaling something against a ton of data?
to get a foundation model and the traditional AI path.
Say a bit more about how we might get to this. And then the next question will be like why is it so useful?
Oh yeah.
We could talk for hours about this. Let me tell you my sort of
Contrary take on this.
And why it's different.
So
I'd say the approach that is
predominant among the large AI labs.
Is that
Reasoning capabilities.
Which includes mathematical reasoning is gonna be an emergent
phenomenon an emergent property of bigger and bigger models.
So basically by feeding these models
More and more English text.
They'll sort of get better at reasoning.
Automatically.
And
I think that might work.
to a certain extent.
I'm not even necessarily saying that that's incorrect.
Even though there's all sorts of problems with
manufacturing data. And we basically trained on nearly all the public data that's on the internet with the latest generation of models being GPT four and cloud three point five.
So now there's a bit of a data wall and one of the big questions is how are you gonna get
More data.
So that these models can continue to progress on the capability curve.
And
People are looking at various ways to overcome that, including synthetic data, which basically boils down to using the last generation of models to create more content that then you use to train the next generation.
And I think there is a big open question about whether that particular approach will lead to recursive self improvement.
Because
The great thing about
The human data on the internet, it's pretty diverse.
You get new things from time to time, it increases.
And you can get some real nuggets in there.
But then
Can synthetic data generated by the previous generation of the model
actually increase capability.
My bet is not significantly it'll probably be much less valuable than the human data because otherwise you would have some kind of perpetual motion machine.
I don't think the capabilities of the models can actually
Extract and learn and self improve that way.
So that's a problem.
One of the really interesting things that's happened in the past
couple of years is you have these models and the advances in AI. You also have advances in the field of formal mathematics.
Basically there's a language called lean that just came out a couple months ago.
It was
fully released lean four.
It was created by this guy, Leo De Mora, who was a research scientist at Microsoft Research, but is now at Amazon.
And harmonics a early adopter of lean.
What Lean has done is it's taken math out of the realm of chalkboard and chalk and
put it into the realm of V S code and GitHub. So it's turned math into
Essentially a programming.
Where
Now you see prominent mathematicians like Terry Tow from UCLA or
Robbie Vakil
From Stanford. And these are kind of
The young
millennial gen X mathematicians. So the guys that are a little bit more technologically savvy, they're adopting new tools. The older mathematicians are kind of resisting this to a certain extent.
But the new mathematicians
Are basically formalizing their papers in this language.
They're using it to actually find errors.
And they're doing these large scale collaboration projects where they kind of distribute the work to mathematicians around the world and
You can actually break apart complicated math problems into small bits and have graduate students and others formalize them. This is all happening in lean.
Without the use of AI.
And so
One of the things harmonic is doing is combining these two things, lean and formal mathematics that digitizes math and turns it into a programming language.
And all the advances in AI.
Popularized by
Alpha zero and GPT four that take a first step into reasoning and
We kind of
Put these two things together.
In service of what?
I wanna come back to
An insight you had about
the sorts of things that the best, say, human mathematicians are doing to solve a problem that's not just brute force data, but like
inserting concepts into a problem that might help you solve it or something like that.
So I want to come back to like the how, but
Let's just say we could like snap the thing you wish existed into existence and tomorrow we have the first mathematical superintelligence.
What problems do you think that we would send that thing to solve?
most immediately. Like why is the tool exciting to you?
long long term
Mathematical superintelligence if you believe that math is reasoning, which
I do.
Then mathematical superintelligence is a more specific way of saying like artificial general intelligence.
So it can be used to solve pretty much any problem.
And I think in particular
It'll be problems that have like uh
quantitative element to it and require
actual quantitative reasoning and
Engineering. So
You have
A couple of specific domains that this is important.
Engineering.
Computer science.
If you boil down writing any sort of software and
In particular mission critical software.
The fundamental element in software is algorithms.
in mathematical superintelligence, one of the direct things it'll do is write software really well and ensure that that software
Is provably correct.
So that there's no bugs and it actually works to its specifications.
It can make new discoveries in engineering and physics, it can run experiments.
Over time, I think it can run organizations.
Anything that a very, very smart human that requires reasoning to do
It will be able to facilitate.
No.
There's some things that it might not have a huge advantage.
over current things in
For example
We have great calculators.
GPT is great at writing history essays, so you probably won't need mathematical superintelligence to write a nice history essay or a poem.
But I think
New fundamental research, discoveries.
Anything that requires
correctness in a chain of logical thought.
I think could benefit from mathematical superintelligence.
That's long term.
Verified software synthesis. I talked a little bit about
I mean you get to the point where
If you imagine how much a company is paying a software engineer.
If something could
Replicate the capability of
А рили амезінь хай трупт софтвор інженір.
Not only in writing code.
But proving that that code is correct and bug free.
That's a huge value proposition, particularly in safety critical domains like
Financial services.
blockchain smart contract where
There was a
High profile exploit due to faulty smart contract code just a couple of days ago.
You're seeing this.
The wormhole exploit that
Bled out.
I think four hundred million dollars.
From this wormhole bridge a couple of years ago.
Then you get into automotive and aerospace and if we're gonna be building
satellites and landers and things that go to other planets.
Those things are expensive right now. And so the standards for them operating correctly are really, really high.
So I think you'll first start to see impact in those domains.
But if you have something that can write bug free software.
That'll be generally useful and I think it'll expand.
to other domains.
And this is a thing right now. People are writing software and verifying it, but they're doing it by hand. So it's kind of like an artisanal thing that's very expensive.
And it's only basically done where
There's already a huge
financial impact for doing things wrong.
That's why Leo De Mora, who's the author of Lean, is at AWS.
Because
AWS has
high scale and if there's something wrong with the encryption library or their cryptography
the results could be catastrophic and
Incinerate tens to hundreds of billions of value. So it's those domains that they invest in.
Verification now.
I think that'll all be done by AI.
Let's ground this in your day to day. Like how if this snaps into existence
Do you start thinking about applying this to Robinhood, your products, your business?
What are the sorts of things that
experiments or ideas that it would start to unlock.
For you and the company.
One very practical application is
Robin Hood.
Is fundamentally
An engineering company.
in financial services
We produce a lot of software. The end product that you see as a user of Robin Hood is
Software.
Basically.
And that software is
high criticality.
We've had scenarios in the past where a relatively small error or bug in the software has cost the firm tens of millions of dollars. And those are all very, very disappointing.
And so let's say it was possible to
create software that you could validate.
And provably validate.
Is bug free.
Then a great place to deploy that would be
our trading stack or our clearing stack.
Anything that has to do with money moving or trades being settled.
And
Not to mention the crypto business where
We're certainly
Deploying
Web three technology, engaging in smart contracts, moving large amounts of money.
And so I think
If it were possible
That
You could build software, validate software at very low cost.
And
Prove that.
It holds certain properties. It can't double spend or
It uphold certain risk checks.
I think that we'll get to a situation where the regulators will actually require that.
The only reason it's not required right now is that it's just impractical to implement. It's so costly that you would have no software. So
If the cost of proving certain things and making software conform to
standards of correctness.
was actually practical, I think you'd see every regulator requiring that to be.
implemented.
I would love to go back to one of the episodes in your history and hear about
the reasoning or the thinking behind it, like tell us the story.
When I was in an adjacent business building software that was also trying to push some dimension of investing, in our case custom indexing, like index quantitative strategies.
We often use the Robin Hood analogy where like if you plotted
the cost portrayed.
at the major brokerages and the discount brokerages over time, you saw this natural downline in the trend of the price.
And then something incredibly innovative that Robinhood did is like, let's just take this to its natural conclusion, put it at zero.
It strikes me that that was an incredibly important decision and trigger point for like the adoption of the platform.
Can you tell us about that behind the scenes? What was going on
When did that idea come up? Was that like the fundamental idea? Was that
something different. Like I'm just always fascinated by how companies decide to do something like that, which
On its face, it's like wait a minute, that's the source of revenue, so
Can't be zero, but
Obviously it changed the business model. So
I would love to just hear you like riff on that story and how that came to happen.
Yeah, well first it was the understanding that that was possible.
Even
Because I think if you talk to someone who's a lay person in that era and they're used to
Charles Schwab charging you ten to fifteen dollars every single trade.
The first thing that comes to mind is there must be some kind of reason.
Trading seems complicated. There's a lot of things that have to happen for that trade to get cleared and settled and executed. And probably some people have to touch it and
There's a cost to it.
And I think we've also been trained as millennials with some of the great movies that we've grown up with are
the trading movies at least involve people
throwing the paper tickets in the trading pit.
You probably remember trading places with Dan Ackroyd and Eddie Murphy.
That's what I thought trading was and
When I was growing up.
To some extent, it still was that.
So
I applied for some jobs out of college, and one of the things I was considering going into was options trading. And this was really before options trading was
fulomated and the options traders were
doing all the calculations and calculating the Greeks really quickly in their head and
Some of them were in the pits, others were
clicking mouses and actually trading manually.
And you don't have to
Squint too hard to imagine.
That
There's humans involved somewhere in the process, and so it's expensive.
By its nature.
But then
My co founder Beju and I
decided out of grad school
to start a high frequency trading firm.
And
This was in part because he got a job.
Beju did at a high frequency training firm in two thousand and eight.
on a whim and kind of learn the space.
And it was a very, very new space, so I hadn't really heard much about it.
And then we figured out that this is an interesting problem. It's a new market. It's growing. You're not really hearing much about it, but
The approach makes so much sense.
And the approach is put servers close to the exchange matching engines, write really efficient code that takes advantage of arbitrage opportunities between different exchanges.
Build up the capability from there.
Eventually this high frequency trading business that we tried to create, which wasn't very successful, led to us creating a software business where we served other high frequency traders.
And big banks that didn't really have the know how to get into this new space.
But saw that it was the future and didn't want to get disrupted, so
They were buying our software.
And
realize pretty directly is you can kind of see what's going on here.
The old mental model of trading involving humans.
didn't exist anymore.
And in the equities markets, which were the broadest and deepest markets and the ones that most consumers wanted to trade.
Everything was fully automated.
And not only that, but
The lengths and the costs were dropping precipitously.
So at the time when we got into the business.
Which was
Late two thousands.
Two thousand and ten.
The different exchanges were competing with each other on latency.
So Nasdaq came out and said we can
Offer you matching engine latencies of forty microseconds.
This became purely a computer science problem.
And the cost of the trades basically was zero. I mean, we had customers trading tens of billions of dollars a day.
And
We had three people managing the software.
So it's very, very scalable.
And we were charging like a monthly SaaS fee for our enterprise software.
I was at a party in San Francisco.
One time. This was my previous company, Kronos, that was selling the software. We had a New York office and a San Francisco office, and I went to start the San Francisco office.
Because
Beju and I were Stanford grads, so we wanted to get closer to Stanford because that's where we knew.
the engineering community and where we could
bring engineers that could help us.
I went to this party.
And I met a couple of people there. I was talking about what I was building.
And I was like building the software, our customers are trading millions of times a day and
We're charging them very little.
And one person was
Looking at me he says.
Can I use your software?
I love trading.
You're telling me that
Your customers can trade millions of times a day and it's very, very cheap.
I'm paying fifteen dollars a trade at Schwab. I would love to have
a modern easy to use technology solution where
I don't have to pay that fifteen dollars.
And at first I was like no, that's ridiculous. You have to be a hedge fund. This is for sophisticated people.
But it did kind of plant a seed.
And we started digging into
why retail didn't have access to this technology.
And we thought there must be some reason, maybe there were different regulations governing retail.
But there was no fundamental reason.
There was nothing that said you couldn't actually like
Replicate the stack of a sophisticated high frequency trading firm and combine it with a retail platform.
And I think when we figured that out.
We just got very excited.
Because we knew what was possible then. We were like, Well, we could deliver
Free trades to people.
And it's very, very clear that
That's gonna be a huge market opportunity.
And
When we got that idea.
We were also thinking through what the product would be. And a lot of initial skepticism about Robin Hood was that.
They looked at us and they were like, Okay, here are a couple of mathematicians and physics people.
They're not gonna know the first thing about building consumer products. They don't have that consumer product DNA. And so there was like skepticism that we would make something good.
We knew our way around latency and backend systems and performance and all this technical stuff, but
We wanted to build a consumer product that was beautiful and
We had this feeling that
Mobile was gonna be really important.
And this was at a time before Venmo was really popular and
before financial companies were really taking mobile seriously. And I think there was a little bit of hesitancy from people to actually do serious financial stuff on their phones.
And so
But like
popular financial product that came out.
at that time kind of felt like toys.
Venmo was a little bit of a toy. It had the social thing, and those were the things that worked because people were skeptical of putting their serious into a mobile financial app.
But
We thought there was one major advantage.
to customers that are trading, which is that the device is with you at all times.
And if you're an active trader and you really care about what's going on in the markets.
That's just the capability that
You can't get
On desktop.
So we really wanted to like focus on that.
And then we also understood that
We didn't really have a fundamental advantage on web.
Of course the cost was an advantage, but
These platforms were scaled and established and they had
Reasonable websites.
The last revolution where
The internet came about, led to a lot of new trading platforms.
And so we thought if we could be the first in mobile and focus on that.
Territory that nobody was really paying much attention to.
We sort of like
Did two hard things with that product.
One is introduced free trading, but the other is we kind of redefine the full market.
The market
Yeah.
mobile predominantly now. That's the growth segment. And
All of the apps that
came after us, and to some degree the incumbents that had to rush in to s make sure they didn't lose their existing market.
had to adapt their interfaces to look exactly like Robinhood too, because that's what customers
We're expecting.
If they did something different.
the feedback that you would get would be
Why can't you just make it look exactly like Robin Hood?
That's the interface that I want.
I love the story because
I think if you ask the average random person about Robin Hood's business trajectory, they would say, Oh, it was this brilliant
Simple
fast light mobile UI.
Plus this really clever low cost customer acquisition tool. And it's so interesting that the actual story is like a deeply technical story first, and then the mobile UI story laid on top of that.
And it makes me wonder, like, having done both, what your product philosophy has become. If so much of your success was
adopting the next platform, making it low friction, simple, beautiful, elegant, whatever.
How would you distill down
Many years later now
your overall product philosophy for all the things that you do.
Whether that's design, performance, UI UX.
However you want to approach it.
I do think a lot of people just assume that
If you really care about math and engineering, then you don't really care about design and art.
But I actually think that there's a huge overlap between math and art.
When you talk to mathematicians and they're talking about
a proof to you or some result that they really like.
They sound like
art enthusiasts talking about a beautiful painting.
They'll use words like elegant.
Oh that's really elegant.
That step is really
Beautiful.
There is sort of a difference between
different types of proofs. Some are shorter and more elegant and they have a element of creativity to it. Others maybe are a little bit more computational and
Mathematicians care and understand about this stuff.
And I do think when you're solving a consumer problem.
There are
Differences.
Maybe it'll get solved either way.
But
There's like a certain artistry in creating an interface that solves it in the best possible way for the customer.
And so we obsess over that here. And we do really care about how things look and how things behave and
Making it intuitive for people.
And
I think Beju really cared about this.
And I really cared about it.
As well.
So I don't think there's
necessarily a conflict. I know not a lot of people do it, but we are motivated by aesthetics and beauty and not just performance and accuracy.
Maybe use like a recent release like Gold or something.
to
Bring that to life. What was the process like of
Conceptualizing, designing, rolling
that out through that lens of elegance in product.
Yeah, I mean the gold card.
Is probably a the best recent example.
We announced the gold card.
At an event.
in March of this year.
And
The event itself, we spent a lot of time on. Not a lot of financial companies use events to launch consumer products.
But
We cared a lot about the vibe. We wanted to have a certain aesthetic, which was
More of like this.
nineteen eighties.
luxury vibe. So we looked at
print magazine adverts as inspiration.
If you look at the Robin Hood Gold credit card website
It should evoke the feelings.

Porsche ad or like a nineteen eighties Rolex ad that you would find in a magazine with the serifed fonts.
Spotlight and camera features.
And
People at Robinhood, we have a lot of great artists and they want to build beautiful things and get excited when
It's something more than just rolling out the features and meeting the requirements.
So at every level of that product.
There was like high quality care and craftsmanship.
We spent
so much time obsessing over
The card itself.
Got really excited about the physical card.
The app experience.
We acquired a company X One that had an existing product.
And it had all these great capabilities and they really cared about design as well.
Some of them were.
I think buried in the product. We wanted to bring them out and surface them a little bit more.
And then we asked ourselves
Can we go beyond just having really good design and a great product?
And can we disrupt the economics, much like free trading did?
And that's where we got the three percent cash back on all categories value prop.
Which if you talk to customers is
so shocking that they just assume we're losing a bunch of money and that this is going to be bad for the business. And it's sort of in the too good to be true category, much like free trading initially was.
And then you kinda put this together.
And
I mean you should look at sometimes I just read the reviews of the Robin Hood credit card app.
before bed.
I haven't seen reviews like this for any financial product.
They're better than free trading initially. It's just
All five stars people saying this is the best credit card they've ever used.
And the only one star reviews are the people that don't have it yet.
That wanted so bad that
They like are leaving one star reviews on the app out of frustration.
Can you do something similar as you did with the free trading for the three percent and explain to us?
what you learned, what the traditional model has been, what the governing variables have been, how you're changing things and being innovative.
The card itself, yeah, it looks beautiful. I'm sure it's a great experience, et cetera. But like talk us through like the back end physics of this and what you learned and what you've done.
One thing that
has been helpful is
looking at existing credit card companies and their economics.
So capital one is a great one. It's like a credit card business. They do a great job. They're efficient.
If you take
their revenue divided by their total transaction volume.
And this is just simple surface level.
They generate revenue from a variety of sources.
But if you just simply look at
Total revenue from card.
divided by transaction volume.
you'll get to something like six percent.
Which basically means there's like a
Six percent.
revenue yield on transactions.
And of that I think they give out about
Two to three percent.
in rewards closer to two percent.
very profitable business. They've got a healthy
Profit margin.
gives us a little bit to play with.
And credit cards are
Some of the most profitable businesses.
out there.
If you can do it right, it's a great business.
And so it really just
Came out of looking at that.
So there's some profit margin.
And maybe we don't want to do
Can we go a little bit over
The two percent.
Now we probably don't want to go to five percent, even though that would be really, really cool, because maybe that's a little bit tight and we don't expect to be as efficient at running a credit card business.
as capital one out the gate. They've had decades of experience.
But
If you could give more rewards and get three percent.
then there should be
plenty of monetization to make this a good business to us and simultaneously put more money in customers' pockets.
And I think the shocking factor is that
This is like a greater reward.
Then the interchange.
economics that you would typically get. So interchange is like between two and two and a half percent. That's the rebate we would get from the network on each transaction.
So we're actually paying a greater reward than we get from the network.
And we compensate for that in two ways.
One of them, which is what Capital One has, is
Interest on people carrying balances.
So revolving activity.
And I think that's gonna be enough.
In the long run, at least to make the card portfolio very, very profitable on a standalone basis.
But there's also another thing.
That
Basically to be conservative, we sort of underwrite at close to zero.
But
If you look at fidelity.
Fidelity has this product.
Which is a three percent
rewards.
Credit card.
that they give to their highest net worth customers.
So if you have something like two million under management with Fidelity Advisory Services, you can get the Fidelity Rewards credit card. It's a very nice green card.
So you get three percent for that card, but you have to have millions under management.
Now
What that should signal to you is I don't think they're doing this.
out of the goodness of their hearts.
It's a profitable enterprise. Their customers probably if they were there for
Advisory services.
They would be happy with just an at market credit card that wasn't losing money for them. So I don't think it's losing money for them.
And what they're likely seeing is that
The secondary effects on the rest of the financial relationship.
For being
the primary credit card account for someone
Particularly if there are
high quality, high FICO.
individual that's predominantly using the card as a transaction tool.
Is accretive.
And so we think
The ecosystem second order effects will actually be very significant for us.
Where we think there's a good chance that
Once someone has
a primary card relationship with Robin Hood. They'll invest more money, they'll deposit more money in our gold offering.
And it'll help drive
The gold flywheel that has been working very effectively for us.
If you had to like
ultra simplify the business as it exists today.
Like an understanding from an investor's perspective, let's say.
of the business. I'm curious how you would do it.
I asked that first so that I can ask the next question, which is about
This cross.
effect that you just described and what the vision is for all the things you might do for the
Robin Hood consumer, customer over the longer term.
But maybe you start by orienting us in the business today.
Just in terms of like where the revenue comes from, what the customer base looks like, however you want to do it in simple format, so that we can build on that in terms of where the business might go from here.
Yeah. So basically
The business
Is focused on three things.
The first one is being number one in active trading.
And
These are options traders, equity traders, active trading drives the majority of the revenue of the business. Crypto is kind of in that category.
It's being the number one place for retail trading.
And then
The second part of the business is growing wallet share with millennials. You can think of it as
Robinhood has more millennial customers than all the major brokers combined, more than Schwab, Fidelity, Vanguard, E Trade.
Put together.
For millennial customers.
And we think there's gonna be close to a hundred trillion dollars.
in wealth passed down from baby boomers.
And it's already started, but it's really gonna accelerate.
Over say the next one to two decades.
So
close to a hundred trillion in wealth transfer. And so
We're one of the
few financial companies that actually has tens of millions of millennials who are trusting us with multiple products.
And we think we can be the beneficiary of that. So it's sort of like
building the tools and the capabilities and putting the incentives so that
the lion's share that ends up in Robinhood accounts.
Over the long term.
Then
That's what we mean when we say we want to grow wallet share with our customers, predominantly
Millennials.
All of your money should be in Robin Hood, all of your financial transactions.
should go through us.
And that's why
UCR work in retirement.
The credit card.
Which will eventually expand into a broader neo banking offering.
all of your money will eventually
be best served in Robinhood accounts. High yield savings, eventually advisory.
We're gonna serve all of your assets and all of your financial needs.
And then the third category.
International
recently started we launched in the UK in the EU so still small
But I think over a
Ten to twenty year
Time scale.
We're gonna be live in all major markets. All of our products will be available there. And I think there will benefit from
the rapid wealth building in the developing world.
Where if you look at some of these
overseas markets.
Eastern Europe, South East Asia, Latin America.
Africa.
Right now they don't have very much
Disposable income.
But over time that will increase the standard of living worldwide will continue to increase and
they're gonna be increasingly interested in investing.
So
Core business active trading.
The second priority is setting ourselves up for this wealth transfer with
Products that help us build wallet share and help our customers build their wealth.
And then expanding internationally.
Can you double click on the active trading portion since that's the core original piece and predominant piece still today? And then we'll get into some of the future stuff.
Can you just explain how it works?
I feel like everyone knew the answer to this question like three years ago and payment for order flow and all this other stuff was like in the news all the time.
But I would love you just explain like the model of how the business works now.
to understand the foundation that you're gonna be building on.
Yeah, for sure. So
You're primarily asking in terms of revenue.
What drives the revenue of that business. Yeah.
Options trading is a large piece of it.
So options trading is
Annualized in the five hundred million to one billion revenue range, if you look at the last few quarters.
Crypto trading last quarter crypto trading was
Ballpark a hundred and fifty million in quarterly revenue. So that's a big business as well.
Equities trading is smaller.
predominantly because the payment for order flow.
take rate that we collect is
Quite small.
That's I think ballpark.
a hundred million in quarterly revenue.
And then we
generate revenue from these customers holding cash on the platform. So we collect a small interest rate spread on their cash.
Securities lending
also is a additional revenue source.
And

smaller things like if people want to
withdraw money to their bank account. We offer that service and charge a small transaction fee there.
And if you break it down in another lens, transaction revenue versus interest revenue.
Couple of quarters ago, interest revenue actually flipped transactions.
It used to be very, very heavy on the transaction side. So payment for order flow was much bigger than that interest margin back in the zero rate environment.
But now the interest rates have gone up and we've retooled our business to have more
Asset building products.
Then
Net interest.
margin actually flipped transactions as a greater contributor to revenue.
And then we also have a subscription offering, Robin Hood Gold.
Which ties all these together. And we really think of Robinhood Gold as the product version of growing wallet share with our customers.
Once you get
sufficiently engaged into Robinhood and you find value.
you almost always end up being a gold subscriber. And then becoming a gold subscriber actually creates a strong incentive to
Try out all of our other products where you now get industry leading economics.
And gold subscriptions are now uh
nine figure revenue business as well. I think the last number we announced at the quarterly earnings was
One point seven million gold subscribers, which was an all time high. And the majority of those customers are paying us just five dollars a month.
To be gold subscribers.
I love this idea in businesses.
It's just so cool. You're a public business, you've got all these segments. The numbers are big. It's great. You made it, you did it, you built the big business.
On the way to doing so
I love the idea of crucible moments, like the incredibly hard choices that companies have to make or difficult situations they have to work through.
To get to that promised land.
If you had to think of one or two
that the episode of it itself was the most impactful on you, or you just feel it the most as you think back on it.
Which one or two pop most immediately to mind? I'd love to just like hear the story how you processed a hard moment on the way to building a big business.
A lot of people their minds when they hear about Robin Hood go to
Game stop.
For better or for worse. And they're like, Oh, that must have been very, very difficult for you.
It was in a certain way.
But
І вас дико на
A certain set of steps that we had to take.
Make sure that we serve our customers, raise a bunch of capital, strengthen the balance sheet, and then deal with.
Yeah.
PR fallout and the congressional hearing and all of that.
Not a lot of uncertainty in how we operate there.
Other than
how best to message what was actually happening to the press.
And to the public.
Which was challenging. I don't think we did a particularly great job of that.
It's sort of like a meta problem rather than
An actual
problem with the product or the business.
I think what was more difficult for me is navigating 2022.
Where
We had a company that had recently gone public.
The entire uh macro environment was reversing from
very, very loose monetary policy to the tightest monetary policy in multiple decades.
Um
When that happens, when interest rates get hiked up very quickly.
trading basically slows down to
much, much lower levels.
And so we were seeing that.
And
We had a business that was
dependent on trading and we were acting in twenty twenty one like those trends would continue indefinitely.
So there was a huge amount of headcount growth and
Lots and lots of investments in
kind of ancillary things that weren't gonna generate value to the business.
Any time in the next five years, let's say. So
huge investments in like very, very long term projects.
And
When the rate environment shifted and our core business was weakened.
We had to basically change everything.
About the company.
I mean we have to
cut headcount quite dramatically.
We had to
Focus and
prioritize on the core business, which was the
The most active customers
Less so the novice customers that were actively trading, but doing so more as a novelty. We were focusing more on.
pro Sumer, very active options traders and equity traders that were more sophisticated and driving the bulk of the revenue.
And that was a big shift.
We couldn't just focus on the core business.
Because
We had to diversify away from trading as well.
It was clear that there wasn't gonna be a huge amount of growth.
in the active trading segment for
Possibly two or three years.
And we had to
Focus on the core while also making sure that the business in the medium term was diversified away from the core and that we had
another way to grow customers and grow assets outside of active trading.
That was all very tough. It played out over a long period of time.
And
pain inflicted was much less acute than GameStop, but it burned over a long period of time until
Relatively recently, actually, when
The market
And the public
started realising that
Hey, these things that Robinhood has been doing since twenty twenty two are actually working and we left this company for dead, but
Now they've actually like strengthened the core, retooled and diversified and growing and expanding aggressively.
Like they did in twenty twenty one, but under a very different environment.
Let's say tomorrow a young entrepreneur comes into your office that you know and like a lot and you want to be helpful to, and they say, Look, I'm in a situation that sounds like the one you just described in early twenty twenty two.
And you know that lots needs to change, but nothing's changed yet. And it's like all in front of you.
What would you tell that person in terms of like how to start
biting away at that problem piece by piece. Like what were the good elements of the methods that you use to get through twenty twenty-two?
That you think might be portable to other
Entrepreneurs, all of whom, if they're gonna build something huge, go through hard trying times. What worked and what would you do differently?
A couple of entrepreneurs
have asked me this and one exercise that I found useful for myself.
Was
To sit down and imagine what the company would look like if
A new CEO came in to run it.
And
A new CEO who's very, very good.
This might be a great chat GPT or Claude prompt too.
And at the time what I used was Frank Sludman, you know, because he was kind of like the business book CEO who everyone
Pointed to as hard ass, came in and fixed companies and got them right on track.
He's my archetype of central casting CEO coming in to fix things and turn things around, even though I've never met the guy.
I would ask myself, all right, if Frank Slootman came in here to clean this place up.
What are like the ten things that he would do?
I came up with a list and for us
It surface these obvious things that
We weren't doing
But that we
For a variety of reasons.
Maybe we were like clinging on to decisions that
We had made in the past that we wanted to be consistent with. And those are the most dangerous because it's very, very difficult to go up in front of the company and say,
Hey, this thing that I just told you that we were gonna do three months ago.
I was wrong. That was the wrong decision. We're just gonna completely reverse that.
Much easier for a new CEO to come in and do something like that, because all you have to do is say the old guy was a an idiot and everything they did was wrong.
So we're just gonna change it.
So I think that was the usefulness of the thought exercise and
It's like
What was the answer to that?
Gonna have to cut head count, focus on the core of the business.
At the time we had very few people actually working on options trading, which was driving a ton of our revenue.
And so
We like
Looked at that and said.
A smart capital allocator would put
More and more people on options trading, make sure those customers are very, very happy with the service they're getting because they're generating the lion's share of our revenue.
When we were in a situation where you look at the numbers
The more active a trader you were on Robinhood, the more revenue you were generating for us.
The less satisfied you were with our product.
There's an inverse relationship between revenue and NPS.
And
When we kind of grock that.
We were like, This is a five alarm fire.
We have to
solve this problem immediately.
And we did. We solved that problem.
Within a couple quarters.
much, much faster than I thought possible because we just
Put our best people on it.
Yeah, what did they literally do? What were the changes that were made?
To make those customers happier.
A lot of those changes were like incredibly simple. So
For example, one thing that
Was a source of a lot of problems was that.
If you were trading a lot.
You were marked uh
Pattern day trader.
And if you were marked uh pattern day trader.
For a while
We basically would not let you trade options.
Because we hadn't built the mechanisms to like softly off ramp you into other products.
You just basically had to turn to a competitor once you became a pattern day trader.
And
The solve for that was
building cash accounts, which is a different account type, non-margin. And once someone became a pattern day trader, we had like a simple ramp
to off ramp them into a cash account and they could continue trading with us.
And that alone was both solving a pain point, increased NPS for customers.
And led to them.
staying on the platform and these were some of our most active people.
And
This was
below the line before because we just had a very small team of people working on this. And so
little paper cut improvements, even significant ones, were just not getting prioritized when you have
A handful of people working on options, which was a
multi hundred million revenue business.
So from a revenue per engineer standpoint, before we did this, it looked great, but we were very nomadic in how we built.
People would build the old things.
Then they would move on to new things and we had
Lots and lots of projects that weren't gonna generate revenue for the next
Two or three years.
At least and we basically had to
cut all of those and make sure we fed the core that was driving the business first and expand outward from there.
So there's
Huge changes in the service model, huge changes in the product roadmap.
Um
And
I guess the other advice I'd give entrepreneurs is it can seem kind of daunting if you see a lot of things that you have to fix.
But it really is true that you tend to underestimate what you can do in a year.
Everyone wants things done in two weeks. You can do a lot of stuff in two weeks, but
Pretty much all these problems can be fixed.
If you give yourself a long enough time horizon.
And one benefit we had
at Robin Hood is we had a
Very large balance sheet.
because of all the capital that we raised in twenty twenty one.
Um
And so we did have some leeway and
We wanted to turn things around quickly, but
We had six billion dollars of cash in the bank, which can also
Solve a lot of problems.
It's pretty ironic that the one crisis led to help
Solve the solution for the next crisis. That's pretty interesting. Interesting silver lining I hadn't considered before. I had never really thought of it that way, too, but yeah.
We navigated the game stop.
Crisis and
Left it with
A reputation that we had to repair.
But also a lot of capital because
that crisis led to us growing a lot and we grew our users and revenue tremendously and
It kind of propelled us to
go public as a company.
right as the window was closing. I mean, I think we were kind of at the tail end of the time that companies could even go public. So if we'd waited a couple more months,
We probably still would be private.
What are the keys to repairing a reputation?
I think it really is true that
Reputations can be lost very, very quickly.
We see this in our data.
GameStop obviously had a
A negative effect. And you saw that in NPS. It took a dive pretty much immediately.
In our NPS survey that we ran right after the GameStop events.
It was at the bottom. And then you could actually kind of see it.
gradually increasing
over the next several years. So
It got to like
A decent level
The biggest increases were
Right after GameStop.
You saw it go from very negative to like
slightly less negative and
But really
You do good things, roll out good products, those have a gradual effect.
on NPS. And so
It's been three years.
We're probably now at the point where
were pretty much on par with
pre-game stop Robin Hood. So it's been a journey and
Obviously doing
good things can speed it up marginally, but I think the biggest thing is time.
And particularly in our space.
If you're handling someone's money
There's no getting around the fact that
Uh time is important.
And the time scale that you've been a company, particularly a public company.
It factors into people's decisions for where to put their very serious finances.
One advantage that the incumbents have on us.
They've been around for multiple decades.
Customers have more confidence that
they'll continue to be around for decades since they already have been and
That's uh uphill battle that
We have to
Climb.
But the benefit is
It gets easier over time. So there's just this tailwind behind us where our brand and reputation and trust, provided we don't have
Missteps, knock on wood.
Time actually helps us in financial services and
Now we can say we've been around for ten years, we've been public for three and
look at what we've been able to accomplish and we have seen that
Reiterating that message does itself build trust.
One of the interesting things about your business is the data set that you sit on top of. Do you just see what people do in investing in active trading?
And if you go back to when Robin Hood started, around the same time was this crop of robo advisors. They were called
venture funded like Robin Hood was and had big exciting
addressable markets and
The reality is, I think the pitch of those firms was this is really simple, low cost, easy, responsible way to invest for the long term.
And you shouldn't be actively trading. You should just set it and forget it.
And it's interesting to me that like those firms there isn't like a big dominant one.
They didn't really achieve
Venture scale outcomes Robin Hood did.
What does that teach us about how people are with trading, with their money, with investing?
What have you just learned on sitting on top of watching all this trading for a long time now? Just about people and the nature of trading and markets.
Robo advisors
Are interesting.
Robo Advisors were kind of the original
application of AI
to investing.
At least that's how it was marketed.
But they really weren't doing
Anything sophisticated in terms of AI.
And I think the reason that those products have failed to
gain significant market share or grow super quickly.
Is that
Automating the actual asset allocation is
And I think that's
A commodity service, and even if you have a human advisor.
They spend a very, very small percentage of their time.
Doing investing. Yeah. Automating your portfolio. Yeah.
And
The value is in
All these other things.
Helping you consider your financial situation holistically, helping you with your will and inheritance and trust and estate planning.
Giving you advice on
your budgeting situation, doing your private banking.
So
Helping you file your taxes.
And
I think that
There's so many different services that
registered investment advisors and financial planners and private bankers provide to customers.
outside of just the portfolio allocation that
AI was misapplied.
There.
I think what people really want is
The experience of a private wealth manager or a private banker.
deliver to them digitally.
In a lower cost.
So then many, many more people can access it.
And I think that that's the really valuable and really interesting application of AI to our industry.
And one that Robinhood can really help drive.
Роботвайзер земс.
Have
Some advantage here relative to the incumbents.
They also utilize
Technology.
But yeah, I think you're gonna start to see
generative AI and this new intelligence applied to advisory in the next couple of years.
And I think that's gonna be
A big transformation in in the wealth management industry.
Do you think that you'll play a big role in that?
Do you have ambitions to play a big role in that?
We do, yeah. I think there's two big
technology trends that could affect financial services. One is crypto, the other is AI, and
Robin Hood will be a leader in both. I mean, we're already a leader in crypto and
We're making lots and lots of investments to make sure we're the leader in AI.
I don't think the competition is particularly formidable, but I also think that's not an excuse to get complacent. So
Yeah, I do think we're gonna be doing a lot.
And we also just recently announced an acquisition.
of Pluto, which it's basically an AI based
investment research products.
So
You can
put in information about
companies and investments
And they built a very sophisticated system that can pull public filings, synthesize the information and
Answer questions and
help you with investment research.
So
We're gonna be looking to
integrate that capability and
Actually build awesome tools for customers.
Both.
self-directed and in the managed account space with advisory.
Where do you think it all might
Go.
With both crypto and AI, like I'm interested in both separately and maybe they intersect or overlap or whatever, but
Seems like the pace of change of this stuff is just hard to wrap one's mind around.
If you think not just two years tense, but
five or ten or fifteen years hence.
Where do you think these two categories bring us? What does financial services look like that's most different from today as a result of these two?
technologies.
I think that
With crypto
The short term
thing that has happened and I think has led to
Maybe some sulling of the brand of crypto is that people see all the meme coin activity and
Lots and lots of things that don't have any fundamental backing being created just because it's very easy to create a new token.
On a blockchain. And so that's
I think distracting a lot of people from the underlying potential of the technology.
Now at the same time, here's what
We can see
So
Abroad.
Outside of the US
If you look at
transaction volumes.
on crypto blockchains, they've been going up.
And what's driving that increase is
largely dollar stablecoin volume on low cost networks.
So
For a while
USDT, which is a tether stablecoin on Tron, was
a huge amount of actual crypto transaction volume outside of the US.
And this is people that want to hold US dollars.
They want to hold US dollars.
In a lot of cases, they're in local markets where their currencies aren't doing very well. They're rapidly depreciating.
The dollar has been a safe haven for a long time. They rather hold that than Bitcoin because they trust it more.
It's got
A great brand and perceived stability.
And so
The best way that they found to do that is to use crypto. So they're using
custodial wallets and getting dollar stable coins.
Because it's cheap, it's efficient, it's easy it's available on any blockchain.
It's rapidly surpassed the kind of
traditional financial infrastructure.
I think that
You can extend that to stocks. You'll see tokenization of stocks.
And that'll get very, very interesting.
And you'll see tokenization of
Pretty much any asset.
What I think about a lot is
I started thinking about this when there was that whole ICO.
Mania that happened.
twenty seventeen where
Companies were I COing and
The SEC came in and cracked down on that.
And Robinhood was a small startup at the time and we were kind of looking at what could happen in the space.
I think a very disruptive force in capital markets.
Is
Companies starting out and issuing tokens.
Upon their formation.
So
Imagine you're a software engineer and you're considering
Two different companies. One has
traditional cap table, maybe they're using Carta or something, and they've got their traditional legal docs and
You get stock that vests over four years and
You get liquidity either when the company gets so big that they can do a tender offer or they go public.
And you tend to
discount the value of that equity as someone that's applying for jobs because you just
Never know if it's actually gonna materialize.
And you have a choice.
On the other side, it's a startup doing a
substantially similar thing, but
They've been incorporated and they have a crypto token and they're crypto native.
And maybe their business doesn't have anything to do with crypto. It's the same business, but you just get a token right away and they can tell you, hey
Our token is liquid.
Once it vests periodically, you can just exchange it for
dollars or whatever you want.
I think that if that were possible, pretty much everyone would choose the latter option.
And that's gonna be a force that
changes how startups incorporate and manage their equity.
And then if you see that continuing and a large portion of new startups doing that.
There's gonna be less companies going public in the traditional way and
Companies will
Do ICOs
Instead.
And that could fundamentally change the equity markets.
На
There's regulation that doesn't want this to happen and a lot of embedded special interests.
So it looks like that might happen outside of the US first, but
As the US tends to do.
It will eventually catch up.
And you will see
Crypto infrastructure.
getting more and more embedded into
non token non crypto native projects
There's clear benefit.
Look at the
dollar stablecoin analogy.
we see the efficiency gains of using crypto infrastructure because we have a crypto business and a traditional brokerage business.
The cost of offering those services is dramatically lower on the crypto side.
I think it's very, very likely that
We move off of
Mainframes.
and onto blockchains and
There's like a efficiency benefit outside of all these things that I've mentioned.
I think it's inevitable in
Robinhood can help drive that both on the product and technology side and the policy side.
'Cause we want the US to be a leader here and
For us to benefit from all this technology and not clutch our pearls because we are the market leader.
already in traditional finance.
So how does AI then play a role in some of this?
And or drive totally different.
Things for
Your product roadmap, your future, the future of financial services in general.
Crypto's impact is gonna be more on the market infrastructure and on the market side.
AI's impact is likely gonna be a little bit different.
I think that when you think about the impact of AI, you should think about
What are the types of things that a human is
doing for me in financial services.
that I'm paying a decent amount of money for.
I think there's a lot of distraction in the AI realm.
The speculative technologies
Things that people aren't really doing.
And some of those might work and there might be new behaviors.
But the things that I know will work are
things that you're paying a human a decent amount of money for already that could be done by AI.
And
That's both on the company side.
Where are we investing our CapEx? Where are we spending money on things that could be automated? But also on the customer side, what are services that are provided by humans?
That
could be automated by this technology or
If they're not automatable already with a bunch of elbow grease.
And you can trace the curves and assume the technology is gonna be better and make less hallucinations and less errors.
What's going to be automatable in two years?
And I think what you come up with is
Near term.
Customer support, the global customer support market is gonna see a major dislocation. I mean, not just
In finance, but across the board.
I was looking at this market. It's one of the biggest markets. I think something on the order of five hundred billion dollars is spent annually on call center.
And that's gonna be reallocated in the next ten years.
You can kind of see that happening very, very directly.
those folks their jobs are fundamentally changing.
They're gonna have to do different things.
And then in the long run.
the really interesting opportunity in finance, I think is
private banking and private wealth management.
and advisory if you look at
The dollars and the revenues
It's quite dramatic, and I think there's uh
user experience issue on
both sides of the barbell of this product.
So on the one side, if you're
not a high net worth individual and you have
fifty thousand dollars
Or less
And you're going to your local
Edward Jones or something of that sort, you're paying a very high percentage
Тупер три пер.
'Cause it has to be worth it to have a human helping you with this.
And you're getting not the best service.
It doesn't take much to
be a financial advisor.
at one of these firms and you're not getting elite quality service there.
And so you're unhappy.
And then on the other side of the spectrum, if you're a high net worth individual.
And you have
Hundreds of millions of dollars with a financial advisor.
And your wealth is growing over time.
You're being charge a fixed percentage.
So basically the service you're getting
Isn't gonna be very much
Different at all.
If you have ten million dollars, a hundred million dollars, or a billions, but you're just paying ten times more.
And so
The more money you make.
the more dissatisfied you are with your financial
advisor relationship.
And it really should be the opposite.
The more money you have.
the more you're utilizing that product.
You should be happier, it's inverted in a very strange way.
So I think the whole space
Is gonna be disrupted.
And I think AI will play a big role in that.
If I reinvoke Slootman again.
And he storms into your office and spends a week tearing apart your business. What do you think he would say is the worst part?
of the Robin Hood business today.
After all this improvement that happened.
After twenty twenty two.
I mean I think there's a lot of things that
А стіль на
Perfect. And we're on the journey of making them better.
Yeah.
For example
There's probably still a little bit too much bureaucracy, a little bit too much
Process.
Or maybe like
twenty five percent
Of the way to
building the company that I want to build from a culture standpoint. And
Maybe I should articulate what that is. So some things I believe
We want to have a relatively small
Number.
Um
The highest quality people.
I would rather have a small number of just elite people that I pay more.
It sounds obvious, but not a lot of people in my space.
believe this.
And
Actually a lot of the
incumbents and public companies, if you look at it, they invest heavily in offshore, which is
having large and large numbers of low cost, mediocre people and
There's a benefit to that to a certain extent.
But my preference would be small number of
Amazing people.
that are elite in their fields.
that we compensate very, very well. And I just think
For me personally.
I would have more fun being in that environment. I think people around me will have more fun. And if you're in small groups of elite people,
They kind of like push each other and
the end result is better than what they could do individually, which I don't think is the case for
People that are less talented.
So that's one thing.
I want as little bureaucracy as possible.
Things should be effortless to do here. It should be a joy to deploy code and get products to customers.
And
I want compensation to be sort of
close to perfectly tied to performance. So it's very, very clear who's getting promoted and
who's not
based on how well you're achieving your goals and doing the things that you're supposed to be doing and setting out to do.
And in particular, I want to diemphysize
I think a lot of times when we think about promotions and leveling
And
Recruiting outside people.
One the common things that
People look for is the scope of their existing role.
Which translates into how big of a team did they lead.
Oh if someone
Has led a team of a thousand people.
Surely they're good enough for Robin Hood where
They can lead a team of five hundred people or more.
I think at a lot of companies that creates an incentive to hire empire builders that are inefficient.
And what I instead want is
Someone that's done
Big things with as few people as possible.
Those are kind of the North Stars.
A culture of high performance.
Top talent.
In person.
I think in person is valuable and
I'd say I'm remote tolerant, but I don't think the future is fully remote and distributed companies.
At least while humans are involved. I mean, maybe if we get to mathematical superintelligence, things will look different.
I think there's a huge benefit and
I think if Frank Slootman came in
I don't know exactly what he would say, but
I'd say we're maybe like twenty five or thirty percent along these journeys and there's still ways we can improve.
I don't think there's anything major that hasn't been started yet.
If you could know anything.
That you don't
know the answer to, like what question would you have answered?
Just like in general about
Any of the stuff we've talked about or
What answer would you get?
I don't really even have to think very much.
I'll tell you
What got me really interested in
Physics
And in math in the first place was
I would read these books about the big bang and string theory, and it's all getting to the fundamental question.
First, what are the rules of the universe?
And how did they arise?
What is that fundamental theory that explains
the laws of physics and
Why the forces and
The subatomic particles are the way they are.
That's what got me interested in physics to begin with. I don't think string theory provides a very compelling answer.
I think there's probably something simpler, but I think that's really the fundamental question.
Why these rules of physics
what really happened before the big bang.
If we can figure out the rules of the machine that we live in.
I think that's inherently useful and valuable and that's kind of what drives me
Yeah, ultimately it's that long before you're at questions about a creator.
It's amazing how
The deeper into science and physics you go.
The closer you get to that fundamental question and like
Trying to glean the nature of or existence of a creator. It's a bizarre search.
And there's a lot of other related problems like
The Fermi paradox.
Where are all of the advanced civilizations? Why can't we see any?
See all these stars and all these planets and humanity been around for
Not that long. There should be civilizations that have had the benefit of billions more years of evolution, and you'd think in that amount of time they would
leave their solar system. Think about what we've done in a hundred years.
We've gone from
basic airplanes to
Sending Voyager out of the solar system in
Less than a hundred years. So if you add a billion years of that.
We should be populating
The entire galaxy, right? We don't see any civilizations populating entire galaxies.
Hopefully the answer is not AI kills us all. No
That's one of the locations, right?
I've read too much Nick Bostrom.
Probably for my own good.
This has been so much fun. I feel like we could talk about
Just about any topic and you're obviously a super curious guy.
Every time I interview someone, I ask the same traditional closing question, what is the kindest thing that anyone's ever done for you?
Oh well.
I'm sure many many people have done kind things.
One thing that I found myself reflecting on
recently is
When I left my PhD program
I left my phd program in two tausena eight to start my first business.
And
I remember being quite nervous about it because I had to go into the office of
The department vice chair.
Who is this guy, Dimitri Shlatenko. This is at U C L A.
And
Russi which which means
intimidating in his own right, but he was a very nice guy.
And I had to ask for permission to take a leave of absence, and at that point
I didn't really have any
Safety net.
Of course, my parents could support me, but
I was very
prideful and to me having my parents
Have to support me was just not very acceptable.
And I didn't have money and
I was a grad student and I had this idea that was very risky of starting a new business with my partner.
I wanted to ask for a leave of absence and I was like sweating. I was preparing for this meeting for a long time. What am I gonna say? And
I thought that there was a
pretty good chance you'd say, Yeah, you can leave, but
Taking a big risk and you're not gonna come back.
But this guy was so encouraging, he's like, Oh, well, you'd like to become an entrepreneur.
I wish you well.
And by the way.
If it doesn't work, we love you here. We'd always welcome you back.
And
That made me feel so good and it sort of like empowered me to
feel comfortable leaving. Just
Knowing that
I could come back.
And that
They wouldn't make it difficult for me.
And so a year later
They sent me an email and I had to figure out whether I was gonna like try to extend my leave of absence.
But they're like, Are you coming back?
And a year later nothing was working.
I was an entrepreneur, my first business was failing.
Everything was in disarray and on fire.
But
I had loved being an entrepreneur so much, and I knew it's what I wanted to do that.
I was just like
I'll figure it out.
I'm not going back. This is it for me. I'm an entrepreneur.
And there was no going back. But
Over that year.
A lot of
learning about myself and growth had to happen for me to get to that point. And I just think
That conversation was absolutely defining for me because.
I was still like very uncertain about
Whether I should even
Do it.
And then
About ten years later, I was invited to
Give the commencement.
At U C L A math.
So I was invited to give a talk in front of the students and they invited me to this dinner.
Where I think
Dimitri Shlatenko.
was there.
And we talked about this thing and he remembered the meeting very fondly too. He was like, you know, I remember
You came into my office, you asked for a leave of absence, you said you were starting a business. Very, very few people actually.
From the mathematics department.
Start businesses.
And I always use it as an example to people.
You don't have to be a mathematician. Everyone thinks like it's a dead end career, because if you're not a mathematician,
It doesn't make sense to do the major. And one of the reasons we invited you is very few people actually
start businesses and we want more people to do that.
I thought that was just very, very nice and he remembered it.
Yeah, I think
Sometimes you have to ask for stuff and you'll be
Surprise what happens.
What an incredible, cool closing story. I don't think we've had a story quite like that in four hundred of these. So thanks for the story and thank you so much for your time. It was a blast.
I really appreciate it. Thank you for taking the time.
Um
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