All right, Sean, welcome to New York State Podcast.
Glad to have you here. Great to be here.
Thanks. So we worked together several
years ago on what became USDC and I was the lead on the
Coinbase side and we set up the center consortium and you and
Jeremy were the Co founders of Circle.
And I think the Circle Coinbase Center partnership has been
pretty, pretty impressive for the world or last 7-8 years.
Do you want to talk about that give just you know, introduce
people because you know, you're a Co founder of Circle, you've
done a bunch of other things. You can give the give the quick
spiel Sean on Sean. Yeah, yeah.
So Jeremy and I started Circle in 2013.
So it's been, you know, 12 years, which is like 120 years
in crypto or something. Yeah.
And so, you know, we were, we were just obsessed with this
idea about democratizing and sort of decentralizing global
finance and, and you know, sort of have this vision for what
that might look like. And the vision really hasn't
wavered the way that we've tried to execute on the vision.
And obviously it's had a lot of different sort of Criss crossing
paths and probably should have been obvious in 2013 that we
needed something like a stable coin.
But it was actually 2017 when we figured out that that's what we
needed to, that's what we needed in order to build everything
else we were interested in. And, and obviously I was going
to say, obviously you know that part of the story is as you came
into the picture and helped make it happen as well.
Yeah. And I think basically what's
funny about that was that was, I think that was true teamwork.
And what was interesting about stable coins at the time as you
may remember is a lot of people poo pooed them and said, wow, is
your great innovation is putting a dollar on chain.
That's a great innovation, right?
And it was kind of like people not understanding how big a deal
it was to put like, for example, news on online, right?
Or, you know, they, they just didn't understand that, for
example, once it's on chain, you've got programmability and
you've got, you know, anybody can send anybody and you can use
it in smart contracts and you can slice and dice it down to
smaller amounts and you can have devices using machine payments,
as we'll get to with your new startup with the Catina.
And people didn't understand that stuff at the time, but I
think we, we saw that. And you know, what were you
thinking about? You said the vision had changed
for stables over time, but what were what was the number one
thing that you guys were thinking about at the time you
you started work on USCC? Yeah, I mean, it was pretty
simple, honestly. In order to to enable global
payments that didn't posit borders and that we're almost
free, we needed some representation that was, that
was stable and capable of moving over Internet rail.
So the idea was multiple chains, not to not to be religious about
anyone particular chain or piece of infrastructure, but to rely
on block chains to deliver value.
And that in in itself was really a building block so that we can
enable these other use cases. You know, I'd say today stable
coins, you know, largely the use case has been in crypto capital
markets. We haven't yet seen that unlock
of payments, treasury management effects, you know, these other
things. But we're right on the cusp of
it now. And you know, we certainly
needed that building block technically, but also it
couldn't just be a circle coin or a coin base coin.
You know, That's right. That's what I say.
USCC, if you recall, I think we named it so that the C was
Circle and Coinbase and Centre because the Centre consortium,
the consortium meant it was decentralized because we were
partners on it and it also meant that others could in theory
join. That's right.
And that was the idea. We expected there to be
multiple, you know, potentially multiple issuers, all of whom
participated in a consortium, even though they may be
competing at other layers of the stack.
You know, it's the, the idea is just interoperable standards,
right? So like back in the day,
Microsoft had a slightly different version of HTTP than
than that scape. And ultimately, that's
interesting. Well, you know, there was this,
there used to be, it was, it was sort of like, you know, build
your service that ran in IE. You mean you mean do you mean
like blink tags versus marquee like that?
Kind of thing. Exactly.
Yeah, yeah, yeah, yeah, yeah, yeah, yeah.
But ultimately everybody agreed, let's just let's just agree on a
standard unless I argue over different implementations to say
SSL because we can compete at the e-commerce layer so long as
we have this foundation of interoperable standards that no
one vendor really owns. And when it comes to, you know,
delivering dollars or other currencies but stable quints
today, largely people largely want dollars today is what they
mean when they say stables it it can't be circle dollars or
strike point. Based dollars?
Yeah, exactly. Point based dollars, whatever it
is, it's just dollars to people who are using it.
And so and so you know, we sort of saw a need for if dollars
were going to move over Internet rails and over block chains,
then then it needed to move as an interoperable standard.
And so that was the idea is put together a consortium, not sort
of Libra style of 30 people who can't agree on anything, but you
know, a small number of very like minded motivated
participants who could agree on these fundamentals and get it,
you know, get it going. Yeah, you know, I like the Libra
guys and I remember saying to them at the time and I think
David Marcus and Morgan Beller and so on would would agree with
me. Now, I guess it was it was
totally fine. You know, they did their thing
and I I give them props for seeing it through, even though,
you know, it didn't work. Another thing works, but I think
the issue with Libra at the time was a, they were using a basket
of currencies to back their thing.
And the problem with that is you had volatility without upside,
right? You didn't know if it was like
1. Libra is what?
It's $0.87 a day and it's $1.15 tomorrow, right?
And so it wasn't mapped anything that people had psychologically,
right? No, no, no, fixed price.
He had the other hand, they had volatility without upside
because it's never going to be 10X, right?
So it's like worst of both roles in that sense.
And then there are other kinds of things that were like that as
well where it was blockchain. So traditional banks thought it
was risky, but it didn't have any upside.
So crypto people didn't want to back it.
And actually this was something which I think we did right with
USDC. So I'll explain on the Coinbase
and how we were thinking about somewhat similar to how you were
thinking about it. So my view was because at that
time, if you recall, we were in the ZERP era, right?
And so we didn't know. I mean, only with the crystal
ball would you know that they would Jack rates to the moon in
2022, right? That was like 4-4 years out at
that point. And we had been in ZERP for like
almost 10 years, right, since the 2008 financial crisis,
right? And so the USDC, it was not
obvious that it was going to make any money anytime soon.
And the way I conceptualize on the Courtney side is we thought
about it similar to how you thought about it, but we thought
about it as Google login. Like Google did not make money
directly from Google login, but it's sort of projected, you
know, like projected power, projected login over the whole
Internet. And then people would come back
to Google except a decentralized version of Google login where
stable coins would be used everywhere.
And then people would come back and they'd trade on our venues.
They do things they'd basically be part of the crypto economy.
So just like Google logins sort of grows the Internet, we
thought USDC will grow the crypto economy.
That was one kind of process. The second thesis is we, we put
in capital behind it because we didn't think that.
So had it been an ICO for example, there would have been
pressure for a short term return.
So we capitalized it, you know, together and I think that proved
correct because had people gotten or wanted interest back
from it, now today it throws off whatever billion dollars a year.
It's like at 5% rates, 4% rates to 70 billion, it's like two $3
billion a year. Not bad for seven years, right?
But at the time it literally returned like nothing for like
the first four years or something like that because
interest rates were zero. So something like that is, you
know, something where you can't necessarily make money on it
because rates are not, you know, we're not with our control or,
or we, we didn't know. So we had to essentially assume
that it was just a utility thing for the entire ecosystem until
the returns came there. Let me does that comport with
how you you guys thought about it?
Let me know your thoughts on that.
Yeah, You know, the first version of it in 2017 actually
predating Coinbase, we did have a, you know, it's probably still
floating around out there. The first version of the white
paper contemplated the token being released on the network
that was called the Sent. And and so there was sort of
this, this alternative path that we quickly realized this is not
the right way to deliver this. But there was a little bit of a,
a different revenue model tied to it by virtue of, you know,
having a token. And this was, yeah, this was the
ICO, you know, sort of boom and bust.
And, you know, we explored a lot of things to try to deliver it
in that fashion before we did V2.
Yes, we realized that our. Collaboration and then we that's
right. We, we, we had patient capital
on the balance sheet. So we didn't need to we didn't
have IC like nothing against coins, but those investors are
not patient as you know, ICO investors are not patient.
So, you know, and so by having patient capital on the balance
sheet, we could go for years and years without, you know,
worrying about any return in the short term.
And, and I think that that helped a lot.
OK, so now I'll tell you. There before before so you know,
we had sort of decided well, Coinbase is the right partner.
We were also talking to others. I mean, as you know, you know,
and, and assisted with the like my people like Jim Megdal at
Coinbase, we're trying to bring people into the central
consortium. And there were very serious
conversations we had before Coinbase that it didn't work
out, but very large, you know, players when ultimately you, you
leaned in and others at, at Coinbase.
I always wondered internally, did Brian have to be convinced
to to to go this path? It's a great question.
So, so now, now the story can be told right.
So it actually, so again, of course, you know, everything
that happened on the Circle side, I can describe it happened
on the on the Coinbase side. So there was essentially a big
conversation internally, which was build versus buy versus
partner, right? And I wanted to buy would have
been like buy an expensive stable coin or something like
that. And I also felt that wasn't
really in tune with crypto because crypto is about
decentralization and so on and so forth.
And so I wanted to part first of all, partnering would have been
you guys had my, my view on, on what you guys had.
You had an audited smart contract at a time when that was
actually a relatively very scarce thing, right?
Because a trail of bits and what have you had?
You know, they were, they're still, I think they're still
good, but they were backlogged. And you know, there weren't that
many people who knew how to do audited smart contracts at that
time. So I knew that that would take
us months to get to level that I felt that we could put hundreds
of millions or billions of dollars into it, right.
Like an audit of our contract is no, no small thing, right?
There's that. And also, you know, the fact
that you guys were reputable. You'd been around for a long
time. Jeremy had had an exit before
with the his video company. Gosh, I'm forgetting the name of
it, but it was Brightcove. Brightcove.
Exactly. That's right.
Look, streaming stream video company.
And actually we had met you. I don't know if you remember
this when I was partnered Anderson all the way at the very
beginning in 2013 when you guys were starting circle, you know,
so, so we, so I, I, we had game filled on you, right?
And, and obviously I think there's mutual respect.
And then the so my view was a partner B user balance sheet.
And essentially the question was partner versus build, right?
And I felt that partner was the right approach because crypto is
like I'm AI think I'd like to be or we'd like to be win, win
people. And, and, and there's more that
can be done together. And I felt that would be an
organic partnership since you guys were also crypto first and
you've been in the space for a long time and everybody who's in
the class of 2013, we all have our Grays, right?
But that was like the first time that a bunch of venture, you
know, Eric Voorhees of shape shift really got his start back
then, right? I think blockchain at info
really got going. Then, you know, block stream got
funded around that time. So I think quite quite a few
companies, as you may recall, the Coindesk and so on really
got going. So I think some of the really
foundational companies in the space got going at that time.
And what you'd been in the space for the right reasons.
You weren't like a Johnny come lately.
And I mean, it's all obvious stuff, but these are just
explaining what, what our thinking was.
So I felt you'd be a good long term partner for this.
And so that's, that was part of the reasoning on, on our side.
And then what I, what I did, which you, you guys don't care
about, but we, we had just really three or four people on
our side, Jim Mcdole, who you met, Jacob Horn, who's the
product manager, and then Maxim and Mija, who are the two lead
engineers. And then there's several other
people, you know, in design. And so sort of those are, I
think the four principal people. Maybe there's something I'm
forgetting, but I think there's the four principles and the
biggest, one of the hardest things was just clearing
everything off of Maxim and Miha's schedule so they could
just code 24/7 and it block all the HR people and so and so
forth. So no, I just fill out their
forms and we shipped it really fast.
October 23rd, 2018. Go ahead.
Yeah, yeah, I think that's right.
And Jacob, by the way, also, I always felt he was a great
champion for us internally at class and, you know, really,
really enjoyed working with him. We had Joao Reganado, It was PM
on our side, but our heat is really small, too.
It was a handful of people. I mean, the, the tech, obviously
it needed to be secure. It needed to be a strong
actually we we launched on Ethereum.
It's now in like 20 on everything.
It's on everything, but it has to be secure into the, the code
mattered a lot, but there's not a whole lot of tech there.
I think the, the partnerships and the distribution, you know,
obviously trying to, to clear the liquidity mode, which is
still, you know, they're, they're only two, you know,
dollar stables that have any meaningful liquidity right now,
because that liquidity mode is really difficult to clear.
Like all of these things were at least as important as, you know,
the the pure engineering. That's right.
And I think they're the reason on the engineering side, it
wasn't so much, it was hard because it wasn't a lot of code,
but it had to be extremely correct because, you know, smart
cut, you know, re entrancy bugs, there's all kinds of these
things that can get you. There are two early things that
I remember at the time that really important.
First was that a lot of other people had been doing stable
coins backed by what I call plutonium, right?
A very unstable thing over here. And you didn't know what the
value is because it jumped up and down all the time.
And nothing against Heather. They've proven themselves.
They've executed over the last X number of years, right?
But at the time it wasn't known that, you know, they're, that
they're, they had enough paper to back what their outstanding
assets were and so and so forth, right.
And then there are other people, not even Tether, who are doing
algorithmic table coins, some of which, as you know, you know,
blew up later. And so one big thing for us was
using the banking relationships to get $1.00 on chain back by
$1.00 off chain and do it in a, in a dumb.
But like, you know, it's simple is hard and, and good, right?
Like, you know, so the simple thing of just one currency off
chain, 1 currency on chain, that was one big piece.
The second big piece, if if you may recall, is you know, and
this is a big debate with those banks, right?
Was would people have to KYC to send to somebody?
Or would it be blacklist rather than whitelist, right?
Meaning would we maintain so we had to have some compliance type
stuff and so and so for somebody that misused it.
So we eventually agreed that freeze and you know, in, in, in
extreme circumstances, freeze or reverse transactions in, in the
contract was better than having every single address have to pre
verify in KYC beforehand, which would defeat the whole point of
it, right? So once we, I think that was
another key thing is we got enough banking partners to agree
a, OK with a warrant you can freeze or, or seize or, or, or
reverse transactions just like you can with wires.
And B, you can also guard the, the egress and ingress at the
exchanges when USDC is being swapped for USD, right?
And so given that, then you otherwise have fun on chain and
do what you need to do, right? And I think that actually now
opened up the door for, among other things, something you and
I have both thought a lot about kind of your new company, which
is Cortana, right? Because by doing that, since,
you know, if you had to KYC every address, you couldn't have
a program generate 100 new addresses because they'd all
have to be KYC by like the human and some photograph or something
like that. Too much friction on being.
Possible. That'd be impossible, right?
So that brings us to the unlock of machine to machine payments.
So why don't you talk about your new thing, Cortana?
Yeah. So I I also say something on the
the, the, the way that the sort of funds freeze happens.
I was still never honestly, I I always felt like we could have
we could have innovative there a bit more past just address, you
know, management and you and I talked at the time about the
things that were more sophisticated probably would not
have been executable then, but this like governance.
Contracts that like, yeah. Like risk and reputation on
chain to, you know, sort of handle these these sorts of
things. And it turned out that you're
right. The simple approach was, was the
one that was going to work, you know, But I still always felt
like, you know, there's something there.
And it's the, you know, one of the things that always nagged me
about the Internet is there's no real like, like really, you
know, distributed identity layer or people can sort of manage
their own credentials effectively and, and not have
to, to lean on a Google or, or whatever.
And I, I was sort of like the remnants of that.
I wanted to somehow figure out maybe how we could incorporate
it. But at the end of the day, it
was all about not even getting the regulators comfortable, but
our de facto regulators, which are our bank partners.
And this, the simple approach, was the one that was going to
win there for both settlement and Reserve Bank partners.
Yes. And, and I think that basically
you know, like you, so I think today it's, it's possible to
innovate on that, right. But you know, my, my view on a
lot of things like this is sort of like minimum necessary
innovation, right. So no coin, we just did off the
balance sheet, no plutonium, we just did 1 to 1 backing, you
know, USD for USCC, no coin governance.
We just had rude access to the contract.
We had the minimum size of the consortium of the game was just
two and and we just minimized all complexity and was still not
a completely trivial thing to scale and build this thing over
the last few years. But but it was awesome.
And you know, really, you know, it's funny, you do 20 things and
it's interesting as to what things actually turn out to be
really big. You know, it's kind of like for,
you know, they're they're like 50 investments I do did in a
year. And then one of them is like
Ethereum or one of them is salon or something like that.
And then it's like, oh, OK, well, that one, you know, that
goes really big, right? And it it's interesting because
a year later or two years later USTC was useful, but it is it is
after I think Zerp ended that it really went boom like this and
became as material as it is now, right.
And it's funny. So I'll tell you another
discussion that not public, but I think, you know, there was a
discussion internally as to how much to out, you know, like
resources to allocate towards USDC.
And unusually see, most of the time you know, good advice of a
company is like ignore macro. But in this case, you couldn't
ignore macro because 100% decision was what is the Fed
going to do, right? Because it's like, is it going
to increase rates or is it going to keep them down or is it going
to go wiggle like this or what? What is it going to do?
And like, it felt actually it was much more Wall Street than
I'm used to in tech because completely 100% of the decision
was your mental model of the Fed.
I I don't know if you have any thoughts on that, then we can go
to Cantina over there. Yeah, yeah, yeah, yeah, yeah.
No, that's true. I mean, I think that my
recollection is that even after we had, we had decided on most
of the structural pieces in terms of governance and and
attack and we had, you know, lined up the banking partners.
And this was also Speaking of banking partners.
This was also just barely after the era when there's only really
one bank in the world that would bank Coinbase or Circle.
Yeah. So the making partner piece,
which you mentioned was it was a huge negotiation and discussion
because things are different now.
You know, we have, you know, Bony Melon and BlackRock and you
know, you know, but it was not like that then a short time ago.
So. So yeah.
But my recollection is the the the most, I would say difficult
but time consuming hardest pieces to put together were the
economics. It was the macro situation, a
sort of analysis, but also micro.
Is this what what are the what should the economics be if we
have a consortium not of 100 people, but of a small number
starting with two, What what should what does that look like?
And there's a lot of discussion. It's been revised, you know,
since since our time, you know, focused on that.
But but yeah, absolutely. I think that that was the big
puzzle. And and even then I remember we
had people talking about, you know, maybe can you do JPY
stable coin or like negative interest rates or this doesn't
you? Know all that is now happening,
Yeah. Absolutely, yeah, Yeah, so, so
that's right. So, so you asked about Capena
and I keep going back to USDC because it's fun to chat with
you about it. But you know, one of the one of
the nice things about about machine native money is that
it's it's very reliable for machines to use it.
So, so when we have these orchestrated workflows called a
mate and no one can agree on what an agent is, but sort of
workflows with alolim intelligence involved in making
decisions, then as those workflows become economic
actors, they need to be able to transact.
They need to be able to hold money.
They need to be able to send money.
They need to be able to make, you know, treasury effects
decisions, potentially with, you know, all within guardrails and
humans in the loop where necessary.
But simply tacking AI intelligence on to the edges of
say a credit card flow is just aside from the economics, it is
not reliable. It's really difficult to make
those even the just the simple tool calls very reliable.
And, and so you, when you take a 5 to 7 to 9 party system and you
add a couple more parties on the edges of it, then, you know,
it's different than taking a, a stable coin, you know, point to
point transaction and, and you know, gentech work flows were
very good at signing cryptographic messages.
And, and so, and so, and then all of a sudden, you know, you
sort of unlock the capability of transacting in fractional
amounts in like streaming payments in real time.
All these things we've been talking about for 20 years that
have really never been economically possible or
technically possible until we have the combination of machines
becoming economic actors and stable coins.
I don't know if we keep calling them stable coins, but it's a,
you know, money. Yes, that's right.
Well, so because this is funny because, you know, 10 years ago,
I also took a crack at the machine payable web and machine
micro payments and 402. And the issue was that Bitcoin
at the time, see Gavin Anderson, if you recall, had published a
road map for scaling to huge numbers of transactions of big
blocks and so on. And then the Bitcoin civil war
happened and became small blocks and fine, but that just
basically meant that you couldn't scale on Bitcoin in the
way that, you know, lots of transactions.
So everything had to move to other chains.
And so, and, and frankly, you know, it's funny now today in
retrospect, now that we have Solana and Bass and we have USDC
and we had to have Ethereum and we had to have Bitcoin and we
also had to like win this gigantic political battle, right
after all of that. Now finally a lots of the pent
up innovation and also we have to be able to get on phones,
right, because you have to win this political battle because
this is something, it's a really interesting thing, which you
know, and I know so many people for some years, like where are
the crypto apps? Why aren't they on phones?
And the reason is that Apple especially, and to a lesser
extent, for real extent Android would nerf all kinds of apps
that use crypto on phones. Because there was some like
Apple payment, you know, the IAP thing, in app purchases thing,
all this kind of stuff where they've now actually lost some
cases on that, you know, and they're sort of being forced to
do that. And to be clear, look, Apple
does a lot of stuff well, but they're sort of genetically anti
crypto. And so there's a chicken and egg
thing where you just couldn't get.
And that's why crypto is actually developed as much more
of a web phenomenon than a mobile phenomenon.
We have to be choke point in a certain way where we're only web
rather than mobile, and we have to be choke pointed through the
banks in a certain way. And like you couldn't do equity
issuance, you can only do meme coins.
So this I think bank list also had a very similar observation.
Like there's all this pent up spring of innovation go Boeing
like this over the next 10 years that that that machine payable
machine payments are part of. Go ahead.
Yeah, yeah, absolutely. I mean, my thesis is that in the
future, the only actors that we will trust with our money and
our assets and the only actors that will be capable of of
generating competitive returns will be agentic.
Interesting. And and and I.
Only play the agentic or do you mean delegates of yourself?
So this isn't, that's a good question.
So right now there's a little bit of a of a battle, I would
say, between, you know, those who believe that agents will
always be, should be mapped to tasks that always get mapped to
some user to be, you know, business or consumer or
whatever. And those, those that believe
that may be true, but we'll also see semi autonomous or
autonomous agents that actually do have their own identity and
act on their own on, on not just a planning loop that can truly
act on their own behalf. And so there's debates on on
both sides of those things, but I, I think, you know, either
either way, you know, in terms of being able to make good
decisions rapidly enough with, with money, we will just not
want to trust anything other than.
I mean, it is hard to imagine now because people's anecdotal
experiences are that, you know, Claude or ChatGPT can't give
them a, a, you know, recipe for a brownie correctly because of
the, the sort of hallucinations. But it, but it is, I still have
strong conviction that it is the truth that we will see AI actors
that will be the most effective economic participants the
world's ever seen. And then we will want to, we use
those, but we will have no need to ever execute a transaction
ourselves. We will always be doing it
through some form of, you know, personal or or other AI.
Interesting. You don't think you'll ever need
to execute a transaction yourself?
That's interesting. That's a strong form version.
So where do you? When that happens when that
happens is a is a question. I always find that when the
hardest question for me to answer in this so I have
conviction around the what is it take three years to touch
certain domains before others? Or does it take two months?
Does it take 20 years? It's really difficult to say.
So 12 years ago, actually me and actually the Winklevoss's and
Neville, there's some panel and I remember thinking about
machine payments then. And my kind of example of
something Bitcoin could do that, you know, other currencies like
Fiat couldn't do is if you had two self driving cars on the
highway, one of them could pay the other to pass, for example,
right? And now that's just kind of a
made-up example, but the general concept is machines could
negotiate prioritization amongst themselves or what have you,
right? In practice, by the way, self
driving cars might just drive fast enough that they could
just, you know, boom, snap, snap onto each other and and and go,
right. But there's probably something
to that of machines being able to negotiate back and forth.
You know, for example, you could have a fully, you know, right
now, Waymo and and Tesla robotaxis just to drop off and
pick up. Finally, we have truly fully
self driving end to end cars. But you could have something
load food into it and then unload the food on their side,
like sidewalk robots exist, right, and drive thrus exist.
And you could have something where like the car pulls up, it
pays the robot, it it gets the food.
You know what I mean? Right.
So that's an example of machine to machine.
I don't know if now the thing about that is that's actually in
the physical real world, which is always hard because there's
other kinds of issues that Wi-Fi drop out, the Bluetooth drop.
So I wanted to know where you thought the first two or three
applications of machine payments would be for a.
Catina Yeah. So I'll see what we're seeing
today. What we're not seeing is true
agent to agent or machine to machine payments.
We're seeing AI workflows pay for access for, to resources,
content, data, paying for, you know, access to APIs.
There may be another agent on the other side of an API, but
the interface is not truly agent to agent yet.
And I think there are a lot of reasons for that that have
nothing to do with the payment side.
You know, there's no DNS for agents that we haven't really
figured out the right way to handle discovery.
You know, if you're, if you, if you're, if your agent
interfaces. Do talk about text fields, I
guess. But yeah, not really, because
agents don't have persistent domains either.
They can't, Yeah. I mean, they kind of do, but not
really. There are proposals for like
registry concepts. So Google has, for you know,
proposed something for a registry concept attached to
their A to a framework. Maybe.
Maybe there isn't. Really like a standard for it.
Maybe you could use ENS or SNS, the Solana name system for doing
that. Yeah, because that's a little
more flexible than DNS. Yeah, you can I.
Think we may see a little bit of fragmented approach, whether it
be, you know, multiple things that will need to be supported.
But in the meantime, it's sort of like, you know, if you and I
go build a website, we get a domain and we just deploy it or,
you know, there are lots of ways for it to be discovered in the
world. And there aren't really there's
not really that equivalent for agents working outside of their
ecosystems. And even when people build
agents, it's usually in a particular framework or in a
particular ecosystem. It's and it talks to other
agents in that same ecosystem, but it doesn't really span the
ecosystem. So if you build an agent that
you deploy, say you can build it and say you know a framework
like Lane graph. How does it make it self
discoverable outside of like a chat interface to an agent
deployed in like Salesforce or something?
So, so you know, there are smart contracts that are something,
something dot ETH, right. And so that, I mean, basically
the smart contract and the agent are the same thing potentially
and you just have an ENS name or an SNS name and that is that is
the registry. But but I like your framing of
it, which is smart contract registries and agent registries
should be the same thing. And that there should be like, I
think that itself is a business in its own right to just
register and discover agents, you know?
Yeah, I think that there's probably a, there's some form
of, you know, Verisign for agents company that wants to be
built. And just verification on them
too, yeah, because they could just take your funds and
something, yeah. Exactly because the real and
this is, you know, part of the thing part of the the work that
we have done at container so far is just this this foundational
layer of trying to address trust and policy.
The the issue that people have with agent took work flows is
not yet things related to price sensitivity or even largely data
privacy issues. It's just reliability.
How can you trust these things? Who's who's vouching for them
or, or when they, when they exceed their guardrails, who's
liable, you know, all these sorts of guardrail policy
reliability, really trust issues and so.
This is why, yeah, exactly. That's the thing.
The AI like, you know, I recognize that it's in like in
some sense a through of the Gartner Hype cycle.
Now it's weird because both there's tons of money going into
it, but also there's less energy than there was a year or two ago
in the sense of Oh my God, it's going to kill everybody and so
and so forth. Right.
But my view is, at least right now, as toy 25, AI requires a
lot of supervision to get anything non trivial done.
And the smarter you are, the smarter the AI is.
And it doesn't do it end to end. It doesn't middle to middle
right because the prompting and the verifying have to be done by
humans. And so it's great generating
reams and reams of text, but often a lot of that is filler.
And I can always tell when someone's used AI to do
something and even when you're using it.
Like I think the biggest thing for me whenever we use AI
internally is there's actually only relatively few kinds of
tasks which can truly tolerate non deterministic error prone
output. Images and video can, but back
in code can't. Like front end code is more
tolerant of those issues because we have our GPU's in our eyes
and we can instantly see it and verify that the widget is off.
But back end code is much more subtle and it's like much harder
to determine that it's off without like really going line
by line, you know, right. And and it's possible there's
some like visualization mechanism, you know, like a
Fourier transform or like an audio spectrogram can turn
something that's not visual into something visual.
So it's possible we might be able to turn some of these other
data structures like back end code into things that we can
just visually debug by eye, you know, like a state machine or
something like that, right. So it might be might be
something along those lines or it's in a domain with smart
contracts, for example. As you know, formal verification
finally became useful because these were such compact programs
and of such high value that all the compute for formal
verification actually became valuable.
Right. So maybe maybe that's the answer
is, you know, we, we have an only generate code that we can
do formal verification on or something along those lines.
But the reason I ask is where, you know, shopping seems to me
to be like the simple kind of thing of get me a good plane
ticket that satisfies my requirements.
Like from point A to point B that doesn't cost more than X
seems to me like a good place to start because that actually does
take a surprising amount of time to go and book tickets.
It's like actually kind of a pain still, right?
Oh, you're putting your name, blah, blah, blah, Fill in all
this stuff on every new, you know, airline site.
So that's like one thing, right? And I think the Max budget stops
it from totally screwing up too much, right?
And maybe you just assign it to get food or a book you like or
something like that. I don't know.
Maybe you have some thoughts on what it would buy for you first
or what you do with it first. Yeah, I so my belief is that
right now, I mean things could change by the time this
conversation is done. This space is very so quickly,
right. But right now I think consumer
retail shopping experiences will be one of the hardest nuts to
crack in terms of a, in terms of a full shopping flow.
So I think, you know, I can see it replacing search, which is
sort of already happened to content on the web in some way.
But the full flow, I think that'll be, I think we'll see B
to B or even B to B to B sort of agentic payment solutions happen
before we see some of the consumer use cases, but.
How about EC2 then compute auctions, right?
So Amazon has auctions of compute because you've got real
time pricing as demand goes up and down, right?
And you can get reserved instances versus real time.
Maybe somebody's already doing that, but that's an example of a
machine bidding on a resource used by a machine for an
algorithm where it's it's like a truly a machine economy.
I don't know, maybe you? Did yeah and, and, and use cases
like, you know, supply supply chains or another one where a
buyer agent and a seller agent can potentially negotiate.
So if you, I have 12 approved vendors for this, you know, this
piece that I need to acquire the, this sort of discovery,
negotiation and also handling, you know, things like the
fulfillment could be handled by agents on both sides and, and,
and in that case, the, the, the data may be known, but in many
cases, the data types themselves, the schemas may
vary. And so you have this need to
parse, you know, not necessarily unstructured, but not always,
you know, schema compliance structure data, which elements
can be quite good at. But to make that reliable, you,
you, you know, what we found so far to make that reliable, It's
not the AI that is actually executing the task for
interpreting the data and beginning to handle the
negotiation that requires human, you know, subject matter expert
alignment. It's actually the evaluating
sort of elements as jury sort of, you know, evaluators that
are other AIS just evaluating the output of those tasks
executors. It's that that layer that
requires human subject matter expert alignment in order to
make the the sort of upstream task like much more reliable and
effective. So, so actually, you know, just
poking on that for a little bit. The only thing about supply
chain is, you know, I actually ordered a lot of, you know, I, I
still, I still building network school.
So I actually, I'm constantly looking at bill of materials and
and so on and so forth for various physical things.
That is a manual in, in my view, a fairly manual process because
you're talking to the vendors you are.
I think an agent can help you with getting quotes.
Maybe that can be helpful, right, If it's hitting a bunch
of telegrams and Whatsapps and, and so that that actually could
be quite helpful. Like I have a spreadsheet and
I'm like, agent, get me, get me quotes on this stuff where it's
like only partially listed a little bit like OTC markets, you
know, where some stuff isn't listed that that's maybe
helpful. But a lot of those are like
large enough. And I also don't need it so fast
that I wouldn't review the purchase order before I hit
submit on it, you know? But that example would like EC2
compute is something where you might literally put that in a
subroutine of get me the best price on this, which people
already do for reserved instances and so on.
You know, so like that's kind of machine resources like getting
storage, getting compute that feels like where it's like kind
of native, you know, or I don't know, maybe go ahead.
Yeah, I think that, you know, as the the sort of business model
of the web transforms from from, you know, search and advertising
dominated into, you know, sort of data curation, this sort of
data curation flywheel that is beginning to emerge, which is
intelligence, whether it's agents or Ellen Foundation,
people providing agentic intelligence need data.
That data needs to be curated ultimately by humans, can be
synthetic data, but it ultimately needs to be curated
and sort of aligned by humans and humans need to be paid for
that job. So that creates a little bit
more of a data content service marketplace that has not
existed. And the services that are
helping to provide that data to the intelligence providers will
pay humans for that job. And so the, the sort of task of
a human begins to be curate these, this data content, these
services, so that the intelligence ultimately is
better for us. We can be more productive and we
get paid for, for doing that task.
And then, and then we pay for the intelligence in turn.
And, and so whether it's machine resources for things like
compute or whether it's particular content or data or,
you know, services that can be quantified in like a data schema
or something, then that becomes a place where agents are passing
money, making payment decisions, but also actually executing, you
know, a binary payment task. So the thing where we where we
sort of move, you know, a little bit up the stack.
So we're still missing some primitives, by the way, to make
that reliable. Some of them are related to this
potential certification or identity layer that's necessary
for agents. There are many people who are
working on different versions of that, but it's kind of notion of
agentic identity and handling authentication effectively.
Even in the shopping example, if I'm do, if I'm shopping in
Amazon and I'm not just using a chatbot, I'm not on Amazon.com,
but I'm just, I'm interacting with the Amazon agent in some
other way, how do I be sure it's Amazon?
There isn't sort of this. Like, yeah, the authentication,
the verification, yeah, it's like whose whose dog is this?
Whose dog is this? And then, and then, and then,
you know, what are the new security and risk factors that
emerge when AI actors are the ones who are executing these
kinds of transactions or an agent on my behalf and an Amazon
agent on its behalf? What new risk factors emerge?
This is why ultimately we're, we decided to create a new
financial institution from the ground up using AI is because,
and we know this from circle, you know this from, from, you
know, building infrastructure to manage risk as well.
You know, classic finance and banking risk infrastructure is
designed to make sure no bots can ever use it.
You need to be a KYC or KYV, an individual.
What we actually need is completely the other way around.
Let's assume the only actors who will be using this system will
be bots or agents And, and how do we let the good ones in?
How do we keep the bad actors out?
How do we give them rules and policies so that they, they
can't exceed? How do they how do we tell them
to escalate to us as needed when they do exceed those policies?
How do we have insurance or sort of liability protections for
this? There's all these like these
problems have not been cracked. And so ultimately we decided.
Well, I mean, self-directed cars will be the first place where
this stuff is happening now in some ways.
Liability, all that kind of stuff.
Who's at fault? All that stuff.
Who's at fault exactly? And there is a path obviously
to, to have sort of, yeah, we're mostly at level 2.
I think there may be one Level 3 self driving in the US now.
But anyway, we're mostly at level 2.
There's sort of a path to get, you know, Level 3 self driving.
There isn't really a similar path for agents executing
financial transactions or or you know, aside from commerce doing
things like handling treasury management a really large sums
of money. And that is where we're headed.
Yes, Well, I think you might want to, I mean, obviously
agents and machine payments in crypto where an agent is trading
on crypto bots, that's like a place where you start with some
sometimes small, sometimes large amounts of money.
So that like people have been building some intuitions on this
for a while, right? But but I think you're right
that we could do, we could do a lot more.
OK. I wanted, I wanted to, unless
you had something else on this, I wanted to switch gears a
little bit and just ask about some different topics, if that's
all right. OK.
Go for it So. OK.
So what, what I've been thinking a lot about what I'm working on
is physical world crypto in a sense, right?
Because you have, I think after cryptocurrency there's different
directions you can take it. But I think crypto community is
a big part of it because we got all these conferences and a
conference, in my view, is actually like a it's an
important subroutine for our space because we're so digital.
And the conferences are where actually we all kind of come
together in the physical world. And so we've got this star
Society here off the coast of Singapore.
We're just taking over an island.
We've got thousands of people from around the world.
It's actually really cool. You should come and visit.
So I wanted to know what, you know, what do you think about
Star Societies Network states? We're we're showing on that.
Have you given any thought to that?
Yeah. I mean, I think we're already in
a case where many of the things that even 20 years ago were done
in a confined sort of Geo space, they're online now.
And so we, we've already, whether we want to formally sort
of give a name to it or not, we have informally formed our own
communities and our own societies.
And we're in multiple ones of those with different identities
that we present to those at different times.
Who'd be, you know, sort of a gamer society at 1 moment and
then something that is, you know, related to academia and
the next moment or, you know, family management in the next,
whatever it is, we're already in these multiple online societies,
much more than, you know, then we participate in the physical
space that we're in. So the next step beyond that is,
well, if we're already in these other spaces, then transforming
that to the physical space that we actually want to be.
And, you know, how did, how do we think about, you know,
forming actual real world corollaries to where we're
already spending our mental and, you know, time online today?
And so, you know, that's, that's the sort of transformation, I
think I think of a largely from the view of, you know, we're
creating a new kind of global hyper personalized bank that is
run entirely by a is, is a level of private banking that most
people would never have access to.
And that is enabled by stable coins, the Internet, AI, you
know, all of these things sort of coming together in, in in the
middle of this Venn diagram. And that sort of bank is that is
the new hyper personalized bank for people who are forming like
physically in this, in their, in their space, A version of the
society that they're already joining and already have joined
online. Interesting, yes.
And so let's say you, what is the Shawn Neville, you know,
people ask what kind of company would you start?
And you have started a company which is, you know, Cortana and
you did circle before that. But I have a different question,
which is, and actually we also start a currency, which is who
started USDC. So we started companies who
started currencies. I have, I have a question on the
third kind of thing, which is not an intranet company or an
intranet currency, but an intranet community.
If Sean was starting the community, if you're starting,
you know, something, what would that community be about the
theme of it? Is there something you'd like to
see in the world? For example, Aladdin immersion,
right? Or you know, keto or something
like that, right? Keto, kosher.
OK, there's just examples, toy examples I've got, but you must
have something you'd like to see in the world.
What would be your ideal community if you could fork
Shawn and clone yourself and build something?
Yeah. I mean, for me it's about hyper
personalization, transparency and trust that doesn't require
relying on other human beings. And it's all coded, you know, so
one of the things that drew me to, you know, cryptocurrency in
the 1st place and Bitcoin specifically in, you know, in
2011. And, and it was this idea that
don't really need to rely on fallible humans or the
governance structures that they create that are sort of enforced
by courts. If you can code those things
crypto and then code those things cryptographically and
software. And so, you know, trust enforced
by software is, is just, it's a fundamental theme.
So one of the reasons I have such optimism about, although I
think you're absolutely right, we're in a little bit of the
trough of disillusionment in terms of, you know, people's
views, views of and this switched because nine months ago
people were really at least. They're beyond.
IOAI, yeah, but you couldn't mention stable coins to them
because especially in AI engineer communities, yeah,
yeah, they're they're they crypto is even more toxic than
it's another. Funny, you know what it is.
Actually, it's funny. Savior going to say, I was going
to say, go ahead, give a meme, you know, finish what you're
saying. I was going to say something.
Well, I was going to say that and it used to be that we would
bend over backwards, not to mention the fact that our agents
were using stable coins because, you know, people and I think of
circle in a good way, is probably the most boring company
in crypto because we have it's a dollar, it's a dollar, it's a
dollar. We went into the front door, we
got, we know all these sorts of things.
And yet people would be afraid to shake my hand because I was a
crypto, maybe a, you know, Ponzi schemer or something.
And it's completely put the other way now where people have
a lot of interest in stable coins, which over the last
several months, because of the genius act and other things have
really achieved escape velocity in the mainstream.
I mean, it was inconceivable 6-7 years ago that Stripe would
create a payment chain, you know, it's using and the Visa
would be leaning in and, and you know, and so on and so forth.
But it has flipped over the last few months where now people have
a lot of interest in, in hearing about various forms of uses of
stable coins, not even just as a currency, but as programmable
money and as, as sort of a platform to build on.
They really don't want to hear about the AI component as much.
We're right in the middle of both of those things.
But it is absolutely flipped the other direction.
It's it's like first it's AI and then crypto and now it's like
stable coins and a little bit, you know, it's just funny you
have to say, yeah, but it's there's there's one thing about
that, you know, the meme, which was the guy getting, you know,
hanged and he says like first time to their guy, you know,
like from it's, it's I will put them on the screen.
But so I thought about that because, you know, right around
the time when AI was really going vertical in late 2022 and
FTX was happening, right? So many people were like, AI is
the real innovation. The crypto stuff is all bogus.
So many people were saying something like that, right?
And you know, of course AI is a real innovation.
But what's what's interesting today and huge obviously, but
it's interesting today is I think in the fullness of time,
we see a couple of things. First is AI is actually for many
people in some contexts equivalent to fake AI scam.
Is that AI or is it real? You'll often hear people say
that, right? So it actually has in some ways
the same. It's got pulled into some of the
same issues that crypto has. Where is it a crypto scam?
Is an AI scam? Is that right?
So a lot of the AI guys, like lots of artists and so on, are
super mad about AI. And so it's OK, That's one
piece. The other thing that's
interesting is in many ways crypto is what AI can't do.
That's a deep point. Like I say, because AI is
probabilistic and crypto is deterministic.
AI can solve partial differential equations, but it
can't solve cryptographic equations.
And so because it cannot, you know, invert a hash function, a
cryptographic hash function, there's certain kinds of NP hard
problems. Obviously it can't, it literally
can't solve them without us changing.
But we know about computer science, you know, develop maybe
P equals NP, but we don't know that.
So without breakthroughs in theoretical computer science,
like AI cannot solve cryptographic equations.
And so that that means crypto is like a hard wall that can
constrain and bound AI, right? It can say I have a dollar and
the other AI or the human can say, OK, send it to me on chain.
And if it can't do that, then it's actually fake.
It's just emitting words. Your crypto is the actions and
AI is the words in many ways. And the actions speak louder
than words, right? So in a very deep sense, crypto
and AI are complementary technologies that you know, you
like what you're what you're doing is one example of I think
a useful synthesis of them with an AI agent that spends crypto,
right? But I think there's others as
well. When you start thinking of them
as sort of peanut butter and Jelly, like dual technologies,
dual to each other. Let me know your thoughts.
Yeah, no, I think that's right on.
And you know the exact form that it takes.
No one. I, I, I, this is like his face
where I think I heard somebody mentioned it's really difficult
to play chess strategically in AI because, you know, you just.
Have to kind of go fast. Everything changes too fast.
The thing is to just keep marching the ponds down the
board right now. And so people are trying
different, different versions of that.
But they're great companies that are, you know, experimenting
with merging the two in ways that solve real world problems.
And there are many companies that large and small startups
and comments that have sort of realized, yeah, these these two
do fit. You know, there is a little bit
of a, there's the Crypto X AI piece, which I think has been a
little maybe a little over hyped, but there's reality there
in combining these two technologies at the same time,
so. That's right.
And in a sense, you know, this is another kind of parallel
financial system, which is it's the machine economy that is
booting up right now. Yeah.
Incentive perspective. Yeah, right.
So it's like another whole plane of where things are, you know,
trading back and forth. Absolutely.
I mean, I think ultimately Balji, I think it's going to
change everything. I mean, I, I know, you know, the
closest and the kind of analogy that we use are, well, there are
so many, you know, people who first experienced the Internet
on their devices that we sort of skipped the whole laptop error.
And then maybe there'll be other people who suddenly begin to
experience the Internet only through, you know, agentic
interfaces. And I don't think that's a great
analogy because I think the change is even bigger.
Are we still using web browsers to to interact with the Internet
if our interface is always going to be some series of agents?
We're not trying to crack the UX problem here, but these are the
kind of questions, you know that emerge.
I mean, replet is genuinely replet and chat CBT in codecs
and cloud code are genuinely new interfaces for, I mean, because
they can accept probabilistic input.
I like a lot of it, right? As opposed to, you know, it's
the exact opposite of how you type into a search engine.
A search engine you sort of invert and you find the least
frequent keywords in your head and you give the fewest
characters and boom, you've got a search query.
And with an agent, you just like you write a huge amount of text
and you're as detailed as possible and or necessarily a
huge amount, but like you can write quite a lot and it'll take
all of that and your vocabulary actually constrains the machine
and it's just completely different, you know, interface
in that sense. I mean, one other thought I had
for you, which is we, we didn't discuss this too much yet, but
there's a lot more robots of different form factors, not just
humanoid robots, but like robot dogs and drones and all kinds of
things coming out of China that you know, robot locks and so on
and so forth, right? That is another potential area
for machine to machine. For example, smart locks, like
here's an example, there's public you could have, for
example, in Singapore, there are these shipping containers that
have gyms like like fitness centers.
They're just in a shipping container.
OK. So you could in theory just go
up to it and go zip, zip like this and do a machine to machine
payment and open the the smart lock and have it debited, right?
That seems to me to be a pretty good application.
I mean, you can do it with Apple Pay, but it's lower cost if you
do it with machine to machine and it's cool, right?
And and you might be able to do things like that where you know
you've got a robot dog and it's sitting down and then you go
like this and it jumps up and it starts running around and doing
something right. I feel you might be able to do
some cool demos there. Let me know if you have.
Any yeah, yeah, yeah, yeah. It's a very cool idea.
I'm transforming this to the physical is just is is a great
space it's creative space to be thinking about regardless.
I do think in those kinds of examples, like you said, yes,
you can do this with Apple, but I think it's going to be very
important not to have vendor lock in in the next version of
this sort of agentic web. And, and you know, I, I think
that's one of the obviously is one of the things that kind of
the web was an amazing sort of culmination of many, many
partnerships and technologies and so on.
But we had also steered in certain direction that was not
the healthiest and, you know, did not.
And vendors. Exactly.
And like 5 companies that matter in terms of controlling
identity, you know, for, for instance.
And so the next version of this, when we, we are using agentic
interfaces, it ought to be much more broadly distributed.
And that's the way that it becomes more prosperous for more
people and, and sort of avoiding this, you know, yes, you could.
I trust Apple. I don't want to have to trust
that. And I, you know, obviously
respect Apple. I don't want to have to trust
them to get access to that gym. Yeah.
And, and the thing what's interesting is in some ways the
society where everything is, is computational trust actually
then loops around and becomes a high trust society again in some
circumstances, because you know, that person can't defraud you if
you checked it, right? So that means they don't have an
incentive to try, even try it. You know what I mean?
Right. So anyway, I, I think there's
something to that which is interesting.
Like if that their guy knows he can't get one over on somebody
because they'll check it. It doesn't even try, you know,
there's like a superior force, which is, you know, the the
blockchain like above them that is enforcing rule of code, you
know, between them, you know, so OK, cool.
I I enjoyed this. And if there's AI guess people
can go to Catina labs right now. It's join the team and
catinala-bs.com. Anything else you want to?
Yeah, I don't know, I'd say we've been, we've been pretty
open about some of the foundational sort of agent, you
know, identity and policy rules efforts that we're contributing
just open source code, been pretty quiet about the
commercial product offering. And so we we're hard work
building, we're really excited about it.
We're taking a big swing leverages all, all these
technologies. And so I'd say people are
interested from, you know, a partnership perspective,
learning more, working with us, potentially happy to have
conversations. Awesome, Great.
All right, Thank you very much, Sean, and thanks.
Pleasure. Great.