🧵
@metricxyz reached $1.2B in trading volume just 5 days after launch.
$11M TVL
$500M in tokenized stock trading volume
let's take a look at what they're building and how it works ↓
🤟🏻🤟🏻🤟🏻 @ambient_xyz
1/ For the past 20 weeks, the Ambient community has been doing much more than testing a testnet.
They challenged assumptions, found edge cases, questioned how things work, and helped identify where the network needed to improve.
It's pretty incredible how much of the journey has been shaped by community feedback.
Here's some highlights.
better models solve one problem.
they also create new ones.
serving them efficiently and making inference verifiable may be just as important as the models themselves.
@ambient_xyz is building the infrastructure to solve both.
ixela™ retweeted
Excited to share another special guest at Cortex Connex Global Tech Fest this weekend.
In the moment of convergence of Blockchain and AI, @ambient_xyz is emerging at the leader.
Co Founder @IridiumEagle will join us to share a little about what they are doing.
Registrations still open
luma.com/vcdd20wc
as many already know, @ambient_xyz is building infrastructure for verified AI inference, autonomous agents and an economy where AI systems can actually interact and make decisions onchain.
but for any ecosystem like this to work at scale, it also needs markets, liquidity and tools for moving value around safely.
this is where @getonyxnow becomes very important for Ambient.
if explained simply, Onyx is the liquidity and market layer for PoW AI ecosystems.
it helps solve one of the biggest problems early AI networks usually face:
fragmented liquidity, weak price discovery, difficult access to tokens and almost no proper risk management tools.
with Onyx, the Ambient ecosystem gets:
>onchain token swaps
>liquidity infrastructure
>bridging between networks
>future perps and hedging tools
>cleaner and more accessible markets around AI assets
and honestly, this is one of those pieces that many people underestimate.
because AI ecosystems cannot fully function only around models and inference.
if agents, miners, users and protocols are going to interact economically, there must also be a strong market layer underneath them.
and that’s exactly the direction this integration is moving toward.
🤝 Paid partnership · 🤖 Made with AI
ixela™ retweeted
Milestone announcement: We are partnering with @GrandCroixAI to launch the first native DEX for the Ambient ecosystem.
This will be a full DeFi stack built specifically for the people in this network: an optimized AMM for a native cross-chain bridge live at launch (no third-party bridge, no workarounds) and an LP dashboard designed for retail. Ambient was always going to need a financial layer commensurate with what's being built at the infrastructure level. This is that layer.
GrandCroix is also seeding day-one liquidity from their own mining treasury. They have been in the network, earning and they are putting it to work.
-Q3 will bring limit orders and a programmatic trading API.
-Q4 will brings community governance with onchain voting for fee parameters and new pair listings.
We are actively building toward something where participants actively own the economic engines they run on. The intelligence is already onchain and we just opened the economy.
Full announcement below.
is today’s payment infrastructure actually built for ai agents?
@PiSquared recently published an article
“AI Agents Don’t Click ‘Pay Now’”
and it clearly shows where the real problems start
most payment systems were designed for humans
when there is an explicit action
a confirmation
context
and a pause before paying
for a human this is fine
for an ai agent - it isn’t
an agent executes a task end to end
and payment for it is just one step in the process
no pauses
no second checks
as long as the system allows it
so the real question isn’t
whether ai agents can make payments
but whether the infrastructure itself is ready for this scenario
especially when it comes to frequent and small payments
between services
agents
or inside automated workflows
the pi article explains well
why simply “giving access to a pay button” is not enough
you need clear limits
explicit rules
and programmable logic that defines
what an agent can do with money and within which boundaries
from this perspective, their architecture makes sense
it assumes from the start
that the participant of the system may not be a human
but software with predefined permissions
no intuition
no emotions
only rules
i recommend reading the article itself
it helps clarify why agent payments are not an abstraction
but a very real and practical problem already today
gm cx. how are you doing emotionally and physically these days? maybe your feed looks different, but mine has turned into pure trash. epstein, binance, endless noise and accusations. is it the same for you?
i have a strong feeling that all this noise is being fed to us on purpose. there are no right or left sides here. the goal is simple. to throw dust in our eyes. while you’re wiping your eyes, someone else is calmly doing their thing. i don’t fully understand what exactly they’re doing, but i’m convinced it’s happening.
in times like this, i think it’s more important not to polish cz’s glasses from hate or dive deep into epstein documents, but to stay grounded. to look for ideas, strategies, ways to earn and survive in this market. opportunities exist. the @Polymarket market alone is full of speculation where you can make money, but if you’re not using your head, you can lose it just as fast.
and maybe during such dumb periods the best decision is to step away from the screen and spend time with your family, with people close to you. sometimes that’s the most rational choice.
at the same time, there’s still a simple, naive, but important idea living inside me. a world without borders, without skin color, without passports and papers. a world where crypto is a choice, not a permission. where we don’t constantly run into politics, bans, and attempts to kill anonymity and decentralization.
every cryptocurrency should be a personal choice. if someone chooses tornado cash, dash, monero, zcash, that’s their right. without fear of consequences or persecution.
peace for the whole world is the baseline. maybe these are just my wet dreams. but as one Russian entrepreneur once said: «мне похуй юра, я так чувствую».
i’m not chasing popularity. i’m trying to find people who feel the same way. and honestly, i don’t really care about x anymore. they took away my blue subscription a month or two after i paid for it. no email replied, no support account answered. i bought premium, got hit with artificial engagement, and now, judging by my before and after activity, i’m sitting in a shadowban.
that’s the time we’re in. that’s the market. that’s the internet. curious who else feels it the same way.
scrolling through x , as usual.
news about AI, constant “breakthroughs”, talks about AGI.
at the same time, more and more discussions about the problems of centralized AI
and the idea that model outputs should actually be verifiable.
this narrative is showing up more often.
and over time, you start to understand why.
when AI influences decisions, money, processes, and people,
trusting results purely “on faith” starts to feel strange and risky.
for a long time, even for me, this stayed at the level of stereotypes.
closed models work this way, that’s just how it is.
if a big company says so, then it must be true.
and only through the @ambient_xyz account did I really start to see
the root of the problem with closed models.
not through loud slogans, but through calm, honest posts
that actually break things down.
before that, the picture felt fragmented. now it feels coherent.
it’s clear there’s an idea-driven team behind ambient.
people who aren’t just building a product,
but are digging deeply into the core problem of our time and the near future.
and ambient exists specifically to address that.
in short:
ambient is an AI network where the answer itself isn’t enough.
what matters is the ability to verify how the model arrived at it.
not trust by default, but a verifiable process.
the project is currently running a public testnet,
and you can already see how this works in practice.
i’d recommend simply keeping an eye on ambient
and reading their posts.
they talk openly about issues many others prefer to ignore,
and they do it calmly and without noise.
Devs are clueless about how to solve the hidden tax of modern AI services. When a model feels slower, weirder, or suddenly less accurate, support gets a vague ticket on the lines of: 'It broke yesterday.' The provider answers with a shrug: 'We cannot reproduce it'...and now you are arguing over feelings because you do not have a replayable trace of what the system actually did.
If you cannot replay the job, you cannot debug the job.
A proper AI service should ship with receipts. A receipt is a compact record of the exact conditions that produced an answer: which model, which safety policy, which route through the infrastructure, which latency target, and what was returned. With that, you can rerun the same request under the same constraints and see whether the failure was model drift, routing, congestion or a broken policy.
Ambient is built to make this happen where you can pick one flaky workflow, store receipts, replay the top failures, fix in hours.











