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Pacifica x Robonet AMA
Recorded: Feb. 24, 2026 Duration: 0:50:12Space Recording
Full Transcription
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Music Music Music Music Music Music Music Music Music Music Oh I'm going to go to the next video. I Thank you. Music Thank you. I'm Music Oh Oh The Oh
Oh I'm going to go to the next video. Hello, hello.
Hopefully everyone can hear me fine here.
Hello, hello. Can you guys hear me well?
I can. Can you hear me?
Yes, loud and clear, loud and clear.
Awesome.
Okay, sweet. Well, hello everyone.
Welcome to today's AMA. It's been, I think, about two
weeks since we've done an AMA or Town Hall, so it's very nice to be back. A lot of stuff
has been happening behind the scenes, and one of those things has also been happening
at Robonauts. So that's what we're going to talk about today. So before we get
started, just a quick introduction today from the Pacifica team. We have I myself as well
as Intern. So yeah, we'll give a quick info. I myself, I'm Greg, I'm the head of growth
here at Pacifica. I primarily take care of all the non-technical side of things,
our affiliate programs, our builder programs, more and more into ecosystem as we're developing
RL1 and well, a lot of stuff in general.
So yeah, we definitely keep ourselves pretty busy, especially with all the things coming um
so um yeah i'll let uh intern introduce himself as well yeah uh hey jam everyone um intern here um
my official title is head of institutional so um uh it's my job to make sure that there's plenty of liquidity in the order books for everyone to trade with. So yeah, great to meet everyone.
Can't wait to see what Robonet has.
Amazing.
I guess I'll take the turn and introduce myself if that's why.
Yes, cheers.
Awesome.
Gus here, the go-to-market for Robonet.
market for Bobanet. It's spent some time working in the industry focused on interoperability,
focused on bridging, solving a lot of different complexities and later found myself working
on the intents, fully focused on empowering users, no matter what sort of technical capabilities they have or what sort of kind of, let's put it like,
quantitative information they have,
giving them tools and platform to innovate the intents
and ideas into performing strategies that generate profits.
Okay, sweet.
Well, thanks for the intro Gustavs. And I guess for those who don't know what RoboNet is, why Pacifica, I guess it would be great to kind of get a little bit of a background story on RoboNet, what it has to do with Pacifica, what it is you guys are building. Yeah, so just a full well-rounded introduction
to what you guys are doing would be great.
Absolutely.
Yeah, so RoboNet is, I think probably like
the shortest version would be like a quant desk
that your protocol can basically integrate.
And kind of like a medium to longer version
would be that it's a full stack
a training infrastructure layer
that allows a new user
to convert their thoughts and ideas, i.e. kind of convert natural language strategies
and descriptions into executable Python codes, which then can be automated through on-chain
trading agents. So all in all, like the goal of Robonet is to allow users to automate strategies with their own capital that are trading 24-7 without fatigue.
It kind of helps you to manage your positions, manage the risks whenever you're, for example, sleeping or you're away from your computer when you're not actively trading.
users to basically solve that issue in the pane where regardless of the technical backgrounds
is anyone can describe trading strategies, they can backtest them, they can validate them,
they can paper trade them. And once they build enough of conviction, they can actually deploy
those strategies live into execution venues. And one of those is specifically Pacifica.
The reason for Pacifica, I think like you guys built a very interesting protocol, especially you're the powerhouse within the Solana ecosystem.
You are very focused on the agentic tooling.
You are very kind of like adjacent towards that path.
There isn't like a clear path forward for API trading on the Pacifica. And we've seen a couple of people already in a couple of communities trading via API on Pacifica
and building like their own trade in Telegram bots,
building their own trading mechanism,
building their own custom infrastructure.
But the goal is here to allow users to essentially
have this full end-to-end platform solution
that allows them to take care of the strategies,
validate them, build them, deploy them onto Pacifica, and then see them perform live
as they roll out and they continuously automate
the trading for the user.
I think generally like the problem that Robonet set out
to solve is that generally like the DEX market usually
has a bit of a structural like liquidity gap, I think that nobody has yet fully solved.
So on one side, it would have sophisticated traders,
it would have quants, prop desks, systematic funds
that are trading through their own custom infrastructure.
They know exactly what they want to execute,
but have built like, you know, as I said,
like kind of custom infrastructure to do it.
But every time they want to do a new strategy,
it's an entirely new engineering project.
It's hard to kind of like carry it over to new ecosystems and like basically automate them kind of composably.
And on the other side, you'll have retail users who have capital, they have market views, they have strategy intuitions, but they don't necessarily have the ability to execute them systematically.
to execute them systematically.
You know, sometimes we see retail users
trading manually, getting affected by Black Swan events,
you know, kind of getting gouged by the emotion
and seeing certain inconsistencies.
And the goal of, you know, the result,
what we're seeing with Robonet essentially
is that there's a massive pool of laden capital
sitting idle and there are users
who want systematic exposure to crypto markets but lack the infrastructure
to achieve it.
And then Robonet is in this position to close this gap entirely and give retail users the
power user capabilities to execute what a hedge fund could do in 20 years ago.
If you're thinking about Renaissance technologies,, building like a custom strategy, like mean reversion strategy, it used to take them, you know, you know, from five to 10 million over six months, a team of 10 quants and different software architecture engineers.
Today, you can actually do that. And with your keyboard, like at the, like all of these strategies are actually holding at your fingertips.
So we want to empower users to essentially take the leverage of these of these platforms and essentially automate trading onto the Pacifica.
Great. I mean, it's pretty interesting. And I think as well, Gustav and I were speaking earlier
today, actually, and I guess piggybacking off what we were speaking
there are a lot of people within the market which think like yourself that believe that there's
definitely a gap here and like you said elevate a lot of people's experiences throughout whether
it's directly trading or helping them manage and keeping things in track when they're not present.
So I guess from your perspective, I would like to understand why RobotNet?
What makes you guys different?
What makes you confident that you have an edge in this market that others don't and
your product, I don't want to say superior, but your product has this edge that others don't.
Yeah, I think it can be layered into like three pieces.
All in all, I think like the very first section is as a kind of distinguishing the problem.
I think the very top and the very like prominent, the base layer is like what we call the strategy layer, right?
So like it's ability to convert natural language of any language um to executable python logic right so it's it's it's
an entry point for any roadmap user it's a strategy intent um you describe what you want in plain
english something for example like you know run the momentum strategy on ephburps with you know
free x leverage rebalance daily cut the position if drawdowns exceed like
to you know beyond the eight percent and then this natural language kind of instruction gets
converted into entry exit risk management like entry and all of these logics and then essentially
robin a strategy engine takes that input interprets the logic structure into these
executable parameters backs back tested uh against against historical data before even like a single
life trade is yet placed, right? So like you are able to build conviction before you risk any dollar.
So I think being able to build up your conviction and trust in the strategy that you're developing
is very important. I think that's giving a certain edge for what Robinet is doing and bringing to the market. The other layer, I think, is this intelligence layer that we are
kind of claiming from, you know, we are built on top of Allura
and Allura is giving us very sophisticated data
data sources through the ML forecasting.
So this layer, I would say, separates Robonet
from every other automation tool as, let's say, Telegram bots or any other kind of like automated trading systems that are more like kind of just trading systems as opposed to like giving you like the full stack.
I think it's worth spending some time here.
So when any strategy is composed, users have the optionality to choose to run with Allura alongside the strategy.
So if they do choose to integrate it, in that case, these strategies have the Allura inferences
locked into the strategy code that once they are deployed, they no longer kind of change,
right?
So that once strategy is deployed, it doesn't drift.
So what that creates is that every robot and agent that then runs the strategy logic has embedded real-time
machine learning inference from Allura, which is giving certain predictions, right? Like in terms of
what is the, you know, what is the future price volatility of Bitcoin in the next, let's say,
one day and give me like at every one hour, what is the you know volatility of like the market like
what is the predictable utility environment that the agent is operating in like what is the current
ml consensus say about the near-term price direction of the asset of the strategy so like
this layer of intelligence is driving a lot of um edge for robot strategies because it optimizes the
order placement it has better dynamic position sizing.
In the same kind of corresponding logic, it also has like better understanding of when
to time the entries and when to time the exits.
So this is the second layer where I think like a lot of like the modes is being built
around RoboNet itself.
And the third part of the thing like the main, the most important, the most important that
I want to touch upon is that the execution layer right so that the mcp the robot mcp the core infrastructure the brain of what robinet is today
um it is where the strategies are getting defined this is where the intelligence layer is running
this is where the execution um happens so robinet integrates any training venues via this mcp the
model concept protocol and think of this as like like a standardized API interface that lets all of the Robonet agents
communicate with any compatible venue without kind of building out like a custom backend
development on either side.
So for example, for Pacifica, that would mean, you know, direct order book access, you know,
so where Robonets can, you know, directly place orders into Pacifica's order book on behalf
of the users, it's non-custodial, it immutable it's auditable and chain where every execution is essentially verifiable the
goal of Robonet is to provide this transparency so that you are aware of like what the system is
doing so like the goal of Robonet to be as transparent as possible not to allude to the
black box analogy here but yeah the goal of this is to provide any user with the capacity and the tools
to build strategies in any form, in any way that they like to interact with the platform. So we
have the RoboNet UI where retail users, if they want to go there, they can do that. They can
experiment through the UI. You can also call the MC through the, you can call the MCP through the RoboNet API,
which now allows you then to run these strategies
and build them up programmatically in cursor.
You can build them in codecs,
you can build them in, you know, cloud code,
wherever you like.
And then the last part, I think what's very interesting
is I know activation through OpenClock, like agents,
like running something like what we've seen,
like with the explosion of Moldbook
and like all of these like self-governing agents.
That's a possibility in the future
where I think some of the participation is heading.
So focus of Robonet MCP is to be kind of agent first
and human compatible platform.
And you mentioned how RoboNet can help users to develop these trading strategies.
I guess it would be good to hear in a little bit more detail what kind of strategies you
guys for example have tested internally.
What kind of strategies do you see others running already and testing on?
Could you give us a bit more context into that? Yeah, absolutely.
I actually have a really good example of a strategy
we recently launched onto another exchange.
It's, for example, it's what we call Agent XYZ strategy.
It's been built in collaboration with the Allura team.
It uses the Allura inferences. It rebalances every eight hours, and it's basically trading E collaboration with the allora team it uses the allora inferences it
rebalances every eight hours um and it's basically trading eve ptc and soul um when it rebalances it
always makes sure to place a position whether it's a long or short for either market and the goal of
this is like a kind of like a long burning candle right so like it takes time to build up the momentum
but the most recent for, strategy that we've seen
on one of these venues performing,
and it has been running for 64 days and has a 60% APR,
which is significant in terms of how these agents
are able to automate.
So with only 1,000 of capital,
the strategy itself managed to generate
over 60, 000 of volume
over 64 days so like it's trading at least of uh you know 1.2k a day in volume
from placing all of these different trades so that's one example the other strategies that
we're currently working through is uh what we call like candle gpt but it's it's more of like
kind of like focused high frequency strategy that trades on like one minute candles.
And that's something I think like that will be very attractive
for Pacifica community, especially for high frequency traders.
And after this call, and as we are developing through this,
I believe we'll be able to share more of this information
to you guys in the next week,
as we're opening up to the broader
market. But to come back to the general capabilities of the platform, so there are different
kinds of strategies that users can build. There are mean reversion strategies, there are trend
following strategies. Essentially, any class of strategy that the user wants to build, it's available and accessible
to be built on your robot net.
Obviously we are scaling this out.
There are certain parameters where we are adding new venues and adding new classes of
strategies.
However, the current platform is mostly geared up for perpetual exchanges.
So you can see a lot of the strategies geared towards directional strategies, like long
short with 5 to ten x leverage possible nice um yeah um i'm wondering
um what strategies right now are the most sort of popular among your users
um most recently i saw like a very exciting there's a lot of creative space um to be honest
like the reason why i'm laughing is that i I saw a person who created a strategy in our community.
He created a Bitcoin mean reversion strategy and paired entry and exit logic with finished calendar.
And for some reason, that strategy was performing 20% in the past three months.
So it has been like, there's, there, there's certainly creative space that,
you know, users are exploring, exploring, but generally what we're seeing, like
the trend is, you know, developing, um, mid reversion strategies, I would say
is probably the most popular, but being able to kind of mix different types of
elements, uh, because you're able to choose like from 200 plus different indicators
to build up strategies as you wish right so
so if any user essentially has the power like like to build whatever they are uh want like
whatever whatever they want to build they're a they're capable to do that and like the platform
is able to support them.
There are certain limitations, as I mentioned, but like mean reversion,
trend following are probably the most popular.
We've seen users who are, you know, maximizing the leverage
and it's actually performing well for them.
But obviously, like if you're maximizing leverage, there is a high risk of the drawdown.
So all of these kind of like parameters, like the build context is as you're walking through the process you're able to basically
get reasoning and logic for how your agent would have performed on like historical structure data
so let's say if and i build like a btc you, mean reversion strategy. And I backtest it in the last six months.
And if it has done like over 300 trades,
I can better understand every single trade in the context.
Like what was the reason?
Like what was the entry?
And help me better understand like and refine the strategy by like single trained.
Right, right.
Makes sense, makes sense.
And I guess sort of like building on top of that.
So like it's fantastic, you know, the sweeter features that Robinet has right now. Like
where do you see you guys going from here? You know, like what's next for you guys and
where would you see sort of the biggest growth?
Yeah, I would say I would start here that, you know, first of all, Robonet still includes
beta.
We are currently running in this kind of like invite code system.
We are looking to open this platform publicly at the start of next week.
Where we are looking for open at the scale is to activate a lot of like kind of users. We want to
get as much feedback as possible as early as possible. We currently have around 300 users
that have been actively trading and giving a lot of intimate feedback to how the
strategies are performing. So we are looking to kind of upscale this looking like moving forward.
We want to iterate together with the community. We want to build this product for the community.
So that's an important step I want to highlight. The other part is when users are deploying
strategies, there are two ways you can deploy it, right? So like if you have a strategy that's performing well on the backtest and you want to deploy it live, for example, onto Pacifica, you're able to choose between two pathways, right?
So like you're able to deploy it as an EOA, which would mean like it's your own private funds, it's your own private capital.
So one wallet, one strategy essentially.
So one wallet, one strategy, essentially.
And the other option is obviously like also depends on the architecture and the infrastructure
of Pacifica, but ability for users to deploy the strategies as vaults.
And as users deploy strategies as vaults, they're able to charge performance fees and
essentially create this network effect.
If additional LPs are joining the vault and kind
of inputting capital into the strategy that's performing well, these users that are sharing
the alpha, they're able to monetize that alpha and they're able to earn like this revenue source
through the performance fees. And this is absolutely like all in the ownership of the
strategy creator, right? So when you create any new strategy,
like that becomes your intellectual property
to the wallet that's authenticated.
So moving forward, the strategy becomes your own.
That's the only reason why as you deploy it as a bold,
you should be able to monetize it as well, right?
So we do see like scalability in terms of feedback and users. We do see the path of
additional strategies being deployed and the kind of like the horizontal expansion of Robonet and
more product depth in terms of like new asset classes and new strategy classes that make it
more expansive. And I would say like probably the biggest angle that I'm very excited about is enabling multi-asset
trading strategies, multi-venue strategy. So you're able to trade, for example, like a portfolio,
let's say, for example, you have 10 million, maybe you want to put in like a high risk,
like, or let's say medium risk, 20% into prediction markets, maybe 50% into like yield
rotation that generates you like seven, 8%.
And then the rest of that kind of like portfolio, maybe you want to play around and like,
but as capital into Pacifica and do some sort of like specialized strategies on the Pacifica.
So like the goal is to provide these like kind of meta strategies that basically act
as your kind of portfolio advisors, in a sense, and automate a lot of that P&L for you automatically.
Fantastic, fantastic.
And yeah, so whenever I hear like automated trading strategy
and sort of like AI,
like I'm both very, very curious and very excited on one end, but also quite scared on the other
because we all know AI's propensity to sometimes get things wrong and hallucinate and whatnot.
And for those who pay a lot of attention to the autobooks, a few weeks ago, we saw that
market maker bought on Bybit that went crazy and started buying, selling, buying, selling ETH.
And yeah, probably like burned through like a few million dollars in like under an hour.
So yeah, like, you know, how do I get the peace of mind when I'm, you know, like using like a strategy that, you know, that was built by AI?
using like a strategy that was built by AI,
especially if let's say I don't really know how to code
and I can only sort of like take what the AI has built
for me at sort of like the natural language sort of value.
Makes sense.
I would probably split like into two sections, right?
So part of the robot at
mcp we have certain tools where it requires um ai reasoning right so um to use the air reasoning we
are we are setting it up on so whenever you ask like for example create a strategy or
um generate ideas it will use llm reasoning which is built on office 4.6 and it's also like we are
integrating additional models to allow users to just have some sort of like choice between the different models.
And also like as a backup in case like one of those goes down. Right.
But so this is where like you are creating the strategy so that strategy is still like fluid. Right.
Like it's not yet final. It's not hasn't yet been locked security scan and like deployed live.
So until you do that, a lot of that kind of reasoning,
there's a lot of like freedom and creative space that you're able to like
completely like continue iterating and iterating and you can actually deploy it as paper trading.
So you can actually like see how the
like how the strategy would be able to perform in real market, not fully overfitting on like historical backtest data,
but you
should be able to also see like how it paper trains and like active market data, right?
So let it marinate for like two weeks, build up more conviction.
And this is that part of like the AI where like it helps to reason, right?
And this also like, this is the angle which unlocks like different languages.
Like, and I've seen people prompting in Italian, I've seen people prompting in Mandarin, I've
seen people, you know, prompting in so many different languages already.
And this is like a unique skill that we get just from building on top of these LLM models, right?
But they're purely for kind of giving the contextual sense and helping users to iterate through the process.
So when the strategy is kind of finalized, then this is the second part where once the strategy is locked, it's security scan.
And when it gets deployed, it can no longer be changed. Right.
So like it's it cannot drift in the current form that we have constructed it to avoid these hallucinations.
We basically have a deterministic policy for an agent which is
hosted on by Robonet on Pacifica for example to execute that deterministic logic right so
if the entry says like enter like above 60 um and it's it you know it will not enter like if it's on
like 59 right so like it will have very clear kind of guardrails and and you can kind of build up
like that peace of mind for yourself that it won't execute something that doesn't exist in the strategy. So it becomes like
you move from like a quantitative strategy that's still kind of fluid, you're kind of historically
testing and then it becomes super locked and it can no longer drift. So that's I think like that
point that I want to make is that it becomes in a sense a bit on the spectrum of immutability, right?
So like it can no longer be affected once it's deployed live.
And of course the user always maintains the controls of the strategy.
So if they do want to pause the agent, they are always able to do that.
If they want an emergency stop, they are always able to do that.
And if there's in some sense, they want to just like pause it and resume in a week, they're also able to do that. And, you know, if there's in some sense, they want to just like pause it and, you know, resume in a week, they're also able to do that.
So there are a lot of functionalities built into that automation for the users.
It's not like, you know, the case would be seen like last week.
I would say it's a bit of a different case where you have like an agent running like loosely and then kind of hallucinating its own strategies.
Like this wouldn't happen here in the sense where once it's deployed live,
it cannot be changed.
Got it.
Got it.
That that's great to hear.
Which I think one more thing I want to add if, um, you know, um, these
strategies that are, you know, obviously you're generating data.
So when you're coming back and you're kind of learning from the experience of what the strategy, how it has been performing, you're able to iterate and build new versions on top of the strategy.
Right. So like if you have like that version free of like, let's say, you know, some sort of trend following strategy for Solana.
For Sol token, for Sol market, and then you've seen how it's performing, but you want to do like additional iterations.
You can go back to the drawing board.
You can like spin up like new version four, version five,
like iterate, optimize them and essentially deploy them
as a new, if that makes sense.
Yep, understood, understood.
That's awesome.
I actually have a follow up question.
You know, as someone that primarily does arbitrage funding rate, I'm assuming that, well, you
guys also allow users to develop cross-exchange strategies, right?
Yeah, this is coming. This is like that part of where your intern asked about what's exciting for the future
of Robinet, right?
So this is coming with new kind of strategy classes and we are looking to develop this
out in the next month.
But yeah, we've seen a lot of attention and there's a lot of curiosity around these funding
rate arbitrage strategies and they're more seen less of like
directional or more kind of like towards like the spectrum of market neutral right in a sense
okay nice nice that's good to hear um it feels like you uh you cover all the all the areas
pretty much a lot of the things that other people are building. So it's definitely pretty cool.
And I think you guys have this malleable edge where I guess the product kind of adapts to whatever the user needs at the end of the day.
It's pretty cool to see.
Thanks for going over all the more finer details.
over all the more finer details. We actually have some people in our community which are
texting us in Discord saying that they were actually looking for some sort of Allura-based
tool. So here you go. I guess moving away from the technicals specifically, I would
like to know a little bit more about yourself and your team. How did it come to be? How long is it that you guys have been building? And intern
already asked a little bit as to, you know, what you guys see yourself doing further on.
I guess if you could also expand on, do you have any other ideas that you haven't mentioned
yet or any things coming in the near future that you want to mention?
Yeah, absolutely.
Yeah, I guess I can recap.
So just a bit about myself is that I spent over two years working with Stargate.
It was the bridge protocol that was built on top of Layer zero which later got um assumed into the into the
layer zero um product stack um so spend a lot of time scaling to different ecosystems working with
different protocols in those ecosystems kind of automating the the actions for users and
basically trying to compose let's say if user wanted to bridge deposit and then you know get
a derivative and then stick that derivative on another platform.
So if you have like four different separate actions with four different like gas costs,
like for the user, that could be like, you know, four different friction points.
So like the always the goal was to automate this into like a one click experience, like
you only sign transaction once and you get like the execution done for you.
So I spent a lot of time like building that stuff.
And obviously a lot of that started iterating when it came to the intent.
And then we came, you know,
a lot of these intent bridges came along, right?
So like you had the cross, you had the bridge,
which basically had a more simple solution
in how to automate these systems
and provide users even like a faster experience
in transferring the assets.
And this really like sparked a lot of interest in my mind. Where can this intense space go to?
Like what is the design space? Ideally, like what we're seeing today is where I think in the very
near future, we'll go to applications. We'll just like ask for, you know, part of the protocol,
like there'll probably be like a chatbot where you just like type in like, oh, I need like this feature and it will be built specifically for you.
Like it will personalize the platform for you.
So like a lot of that intent design space, I think there's like is heading towards that path.
And, and I think that's where like Robinette should be just kind of gearing towards in terms of like the financial sector, we want to kind of see what is possible to achieve with the product that we built for, for RoboNet.
And I think generally like the ability for RoboNet to cover horizontally, let's say like 100 protocols in the space and then allow users to tap into like their creative part and then deploy these strategies as creatively as they want.
I think that's like a big path that we're seeing for Robonet. And obviously also like
with the power of Robonet team and together we're very collaborative, Alora team kind of building a
lot of these in-house strategies. And quite a few of them will come out in coming three weeks.
And we will be doing some marketing around, but generally these strategies have been built
kind of with, you know, in-house engineers who have spent over 10 years in different sectors, maybe like
automated trading, quantitative sectors, but these strategies are performant.
And we do want to bring this value into the system, into the community.
We do believe that it's a bit of a new era.
I think we can now build like a, what Citadel is, what's Renaissance Technologies once was, build up these systems
and democratize them basically for retail for anyone without having like high barrier
cost to entry. So I think that that's one of the paths that Robonet is kind of gearing
towards. And yeah, generally, I think like in terms of the
team, I've been working with Robonet for the for the for the past five months, we have been building
a lot of these different things and pushing with the platform altogether. But Robonet itself as a
product has been around for just, you know, I would say close to two years. The first iteration
was was a bit different, like the goal of Robonaut was to become what virtuals is today,
but it had a bit of a differentiation. So what we saw in, I believe, 2025, we saw some AI sloppy.
We've seen agents having their own tokens, but they didn't really have ways to functionally
return value for investors. Those who are purchasing they didn't really have ways to functionally like return value
for the for investors, right? Like those who are purchasing tokens didn't have any like
interesting mechanisms to create like value for the user who's investing into that token.
And basically, the goal of Robinette, the initial version was to showcase that there
are possibilities for agents to do actually functional things. Functional as in raising capital for themselves and then deploying
that capital into different venues and being automated in a certain sense through different
like architecture patterns, right? So I think we have one proof like what we built previously
I can share like a bit about it. But Robinet previously built like this case study, it's called Poly, where
basically Poly was, I would say, one of the first production grade A trading agents for
Robonet. It was like an MVP with real capital deployed autonomously in a prediction market,
in Polymarket. And over three months, it managed to get to 14% in P&L, almost like 78% in APY, prorated, of course, here.
But it had zero exposure to the final market resolution because, well, it was rating on an event for the U.S. election,
but it gave back all of the funds to the investors the day before the market resolved.
all of the funds to the investors the day before the market resolved.
The reason why I did that is to showcase that the agents are actually very
powerful in a sense, how they become these new market class participants.
And we should treat them accordingly with caution and care, but also being like
aware of like where we can leverage these systems that they can actually deliver
more value for users at the end of the day.
Interesting. Okay.
Well, I mean, it certainly also seems
that you guys have a lot coming in store.
So I guess just before we ask my next question, I do want to let everyone in the audience
know that if you want to ask any questions, please feel free to request a speak and I'm
up on stage.
Alternatively, I know a lot of the people here listening are in our Discord.
Feel free to ask any questions on there happy to ask them here
myself too um and i guess uh yeah you guys are are gearing up to launching pretty soon correct
that is true um we are already live but we're in closed beta. So, you know, if anyone wants to try out the platform, you can guys ping me.
You can ping me as a DM on Twitter.
You can come into Robinette Discord.
I'll share some invite codes so you can access and play around
with the platform already.
But yeah, with the public getting launched, it's basically, yeah,
with the public launch, we're nearing in the next week to open
up to the public.
So there will no longer be any invite codes necessary.
But I think like one thing I wanted to say that, you know, we built in this system.
We want to reward early adopters.
So every user that comes in gets, you know, $25 worth of credits that are can be consumed to deploy and generate strategies to backtest them.
Right. So we value every single user. can be consumed to deploy and generate strategies to backtest them, right?
So we value every single user.
So we're kind of giving this as like a giveaway in return,
kind of selflessly expecting for robust feedback
on the platform and how it works for the users.
Yeah, I think undoubtedly something coming
from our side as well is that,
you know, feedback is definitely one of the most important things at the early stages
and pretty much at any stage of product development.
So, yeah, you'll be needing a lot of feedback, I'm sure of it.
And I guess you could also send me some invite codes.
You can also send me some invite coins.
I'm happy to send them over to our community as well.
I'm happy to send them over to our community as well.
But yeah, as soon as next week, you mentioned, you'll be open?
That is correct, yes.
Okay.
Obviously, I'll check with engineering.
I don't want to give like a hard date.
Usually there are some moving parts and we are building a lot of things and we're trying
to make sure that everything is reliable and stable so we can scale with thousands of people.
Yeah, makes sense. Makes sense. Yeah, I think we see eye to eye on this. It's best not to give any dates until it's 100% confirmed, you know?
Until you're live. Yeah.
Yeah, exactly. confirmed you know until your life yeah yeah exactly and um i've i've been seeing a lot of
like you know i've i've been seeing a lot of these training competitions happening on pacifica and
i'm just generally curious like about the participation how do you find them um yourself
and do you guys host them like particularly on like uh on uh on a very specific track record
like or do you guys do like these like cross venue competitions against other perfect changes?
Oh, so I mean, our competitions are just something that have been going on for for always. So if you go back on our Twitter or Discord on generally anything, really,
there will be more than one, two, three, four days
where there wasn't a competition going.
It's kind of one of the things that we've always been doing.
I think it adds a lot more to the dynamic of points as well
because participating in the competitions
is a pretty big part of all the points as well,
but also brings some more excitement to the trading.
And I guess just to clarify here, right?
Anyone that's trading through RoboNet
or anyone that's trading through any
of the builder platforms on Pacifica
automatically are also participating
in our trading competitions.
If you need to sign up, you still need to sign up to participate.
But for the ones that don't require sign up,
you're automatically already participating in these competitions,
whether you're trading on our front end or through any of our builders.
So yeah, I guess the type of competition changes a lot uh you know we've done some pretty
uh more basic ones i think from time to time it's good to to go back to basics uh then we go
on to some kind of like uh community competitions then we have some country versus country competitions
we have some country versus country competitions um and for example as of uh last week we started our
bulls versus bears competition so uh yeah just always a little bit of variety um and maybe we
have some new exciting stuff coming next week so yeah amazing fantastic yeah um yeah and obviously So yeah. Amazing. Fantastic. Yeah. Yeah. And obviously like RoboNet will be part of that excitement and want to be, you know,
closely, you know, iterating together with the Pacific community and see if what we built,
you know, with your integration actually delivers for what the users actually want.
Yeah.
Yeah, of course.
Of course. Yeah, of course. Of course.
Yeah, I guess I don't see any questions from our end.
So I guess we could get close to wrap up.
And before we do so, Gustaf, is there any last remarks that you may have?
Any comments on the near future?
Any last things that you would like to tell our community
i think a lot has been spoken already um um i think generally is you know being curious um and trying out new ways to to identify um as we're kind of braving through what comes out to be like
one of probably the most interesting areas um at current time where we're seeing a lot of these
different vectors and areas being kind
of identified right so i think being curious and just taking the leap um and trying out these
different ways how we can start interacting with the platforms and i think defy itself and then you
know different platforms that have been we have been building for the past years i think they'll
we are moving towards some sort of renaissance in my sense,
where we see a lot of the usage coming through programmatic commands.
So yeah, I'm very excited myself and yeah, I'm very curious what other people are building.
And always be curious and always try new things.
Amazing. Sweet.
Well, hey, it's been a pleasure having you on. For anyone that's listening,
please feel free to reach out to the RoboNet team on Twitter or any social media. They'll
get back to you and hopefully provide some codes to us as well for you guys to try it
out already. And yeah, it's been a pleasure having you guys on today.
We'll be sure to let the community know
with any of your guys' updates.
And yeah, I guess we'll catch you in the next one.
And we have some exciting stuff coming next week.
So we'll be seeing a little bit more about you then.
Amazing. Thank you, guys. Thank you for having me.
Amazing. Well, take care and see you on the next one.
And for the people listening in, see you in tomorrow's town hall.
I'll be there.
Amazing. I'll see you.
Awesome. Thanks for coming.
Take care, guys. See you. Take care. I'll see you awesome thanks for coming take care guys
see ya
take care Thank you.
