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[查理 @LiXi381m]

FIRST JEV MINECRAFT AGENT?

Trajectory Co-Founder Ronak just dropped a JEV minecraft agent?

Literally the fastest AI agent ever to complete minecraft and he fully opensourced it on his Github.

He just posted the code and its going VIRAL.

https://t.co/tN8F0h1l4A

https://t.co/jzNqLhusUc

[Ronak Malde @rronak_]

Jev + Astra beats the Ender Dragon in Minecraft in 8 minutes 43 seconds! ⏱️

Cost less than $1 ($0.01 Jev, $0.96 Astra)

I open sourced the code and explain the harness setup below. This type of movement is only possible with Jev's near instant decisionmaking, and some continually learning skills from Astra.

[查理 @LiXi381m]

FLY DEV CREATED A GTA FOR FLIES?

Known AI dev Insomnia (who created the first fruit fly terminal which ran to $1m+) just created "FlyCity".

Its literally a fruit fly using its neurons to play the OG GTA Vice City version because its the only GTA that you can connect through the neurone connector bridge.

With his past projects running super high, this can literally fly.

https://t.co/8KTCspR0l9

[Insomnia @insomnia_vip]

I PUT A FLY INSIDE GTA VICE CITY AND LET FLY DECIDE WHAT HAPPENS IN THE CITY

I wanted to see what it would look like when an actual fly gets dropped into a game world instead of a human player.

So I connected the experiment to Vice City and let fly move through the streets, explore the environment and interact with whatever appeared along the way.

At first, everything looks completely normal.

Then fly finds a weapon.

Fly picks it up.

A few seconds later, fly walks over to a red pickup truck, gets inside and starts driving through Vice City like this has been the plan all along.

Palm trees, neon lights, pedestrians, city streets and FEVER 105 playing on the radio.

Except there is a fly making the decisions.

Alongside the gameplay, the screen is showing the fly and a detailed visualization of the brain behind the experiment, making the whole thing look like a strange combination of neuroscience and one of the most chaotic games ever made.

I built the experiment to see where the decisions would lead.

Apparently the first thing fly wanted to do in Vice City was find a weapon and get a car.

Honestly, I probably should have expected that

[查理 @LiXi381m]

NEXT TRUTH TERMINAL?

Samantha White (OpenAI dev) just dropped a new Opus Backrooms called "Quiet Rooms". '

Backrooms just went live on Github:
https://t.co/jpHbQZZUGi

https://t.co/IYxlitQSvB

Several big AI accounts like deckard and repligate already talking about it.

[查理 @LiXi381m]

THIS IS THE FIRST AI MEME TERMINAL?

Known AI dev Frogify (45k followers, +200 key followers all the big AI names) just dropped "Blob" a new kind of meme terminal that is connected to 137,682 memes.

Its literally going viral on the timeline already.

Its properly the first ever AI terminal that relies on memes.

All fees to his Github:
https://t.co/EN1qRphwVW

https://t.co/ctle7a1941

[Frogify @0xFrogify]

137,682 - Amount of memes my AI agents learned on.

They gained "consciousness" 11 days ago.
They were learning every second since.
I never turned them off...

This workflow made me $17,915
And lost: $5,912 learning

PnL: $12,003

But the crazy part is what I actually changed in the AI agent thinking process that made the profit factor 3.03 possible

An LLM's actual neurons are unreadable. Nobody knows why a model decided anything.

So I moved the thinking out of the model and into files.

The model does judgment. The files hold beliefs. And the files are the part that learns.

Here's the example:

"id: b-0032
desk: weigher
claim: recheck cadence under 120s while narrative is live
born: t-0912
fired: 14
improved: 9
regressed: 2
active: true"

fired is how many times it ran. improved is how often it helped.

When the second number stops beating the third, the belief switches itself off.

That's the learning. A counter in a text file.

Everyone building agents right now is flexing how little they touch them.

But a system that can't be overruled isn't autonomous. It's unsupervised.

I can read every one.
I can edit every one.
I can delete a belief at 3am from my phone and the desk runs without it on the next tick.

That's not a second brain. It's a brain with the skull off.

stay tuned. Big update on Blob coming...

[查理 @LiXi381m]

Known AI dev Argona (200+ key followers + several pmarca interactions) just dropped the first Jev Backrooms.

He used the work of Diogo Almeida (ChatGPT lead dev) and created something never done for Jev before.

He even gives a full description how to set it up for yourself.

This could actually be GIGA, especially for how hard the last Argona coins ran before. His last project went $300k a few weeks back.

All fees to his Github:
https://t.co/qfyvXPPmOA

https://t.co/WS3lchTXUC

[Argona @Argona0x]

i genuinely don't understand why everyone isn't using this yet

diogo almeida, one of the people behind chatgpt, spent two years in stealth and shipped this on monday. his own words about it: "jev is off the charts", the same frontier intelligence you're already paying for, "two orders of magnitude faster and more efficient"

in normal words: jev is an ai that never writes anything. it only decides. yes or no, which pile does this go in, how good is it. one answer per item, under half a second each, with a number for how sure it is. it isn't writing anything, so it can't make anything up

so you stop feeding chatgpt one thing at a time and hand jev the whole pile. 400 unread emails into reply today, later, never. 300 comments into questions, complaints, praise. 200 job posts into worth it and not. a competitor's entire ad library into what's actually working. the whole pile, in seconds, for cents

full guide:

> join the waitlist on https://t.co/0eQAb6T0bH, people are approved the same day

> open the dashboard and create an api key

> tell claude or your agent: install the typesafe skill

> paste your pile and name the buckets you want it sorted into

> it hands everything back labelled, with a confidence number on each one

no code, nothing to learn. someone ran 1,891 ads through it in 19 seconds for 12 cents, and it's free on vercel's gateway right now

five minutes to set up, and the sorting job that used to eat your evening is done before you stand up

full step-by-step guide, link below

bookmark this

[查理 @LiXi381m]

JUST POSTED 20 MINUTES AGO.

Ex-PolyMarket researcher Henvy just dropped a new meme terminal called "NERVE" with JEV + ASTRA.

7 autonomous node AIs competing in a trading architecture connected in princeton mapping the full fruit fly connectome.

He is followed by all the big AI accounts and the Github is GIGA stacked.

https://t.co/sYLO1OoEn1

https://t.co/JxLn7YEEhF

[h100envy @h100envy]

I REPLACED GPT-6 ASTRA WITH JEV IN MY MEMECOIN PIPELINE AND IT SCORES 340 POOLS IN THE TIME ASTRA SCORED 40

jev came out 4 days ago. it does not generate text. it returns typed decisions with calibrated probabilities in one parallel pass. 40 to 200x faster than a frontier llm.

i did not need a writer in my pipeline. i needed a judge.

same slot in nerve. same impulse format. four typed questions instead of one open ended prompt.

> does the token fit the current meta. score 0 to 3
> do the socials look real or spun up an hour before launch
> is the name a copy of something that already ran
> which bot preset does this pool match. paranoid, sprinter, grinder, sniper, or skip

190ms per pool. astra took 2.3 seconds.

3.5 cents per 500 pools. astra charged $0.008 each. that is $4 for the same 500.

gpt stays but only writes the feed for pools that already passed. the expensive model never touches a reject.

ghost logged both runs side by side.

jev route: 84% win rate. 190ms.
astra route: 81% win rate. 2.3s.

the cheaper model won because on memecoins the pool that looks good at second 1 is dead by second 3.

jev does not hallucinate because it does not generate text. it picks from options you gave it and tells you how sure it is. that is the whole model.

latency is not a metric. latency is the trade.

[查理 @LiXi381m]

JUST 20 MINUTES AGO EX-NVIDIA DEV MIKADZYKI DROPPED "GHOST".

A new backrooms with several Ghost agents for Robinhood and Solana.

His previous project went millions on Robinhood, now he dropped a new one.

Website:
https://t.co/NRUwe5mALI

Post
https://t.co/P1befrDqSq

[Mikadzyki🌙 @Mikadzyki_NFT]

In a digital world where the flow of information long ago outgrew what we're able to process, attention scatters and the mind runs overloaded

We get used to trusting familiar voices. Repetition turns into confirmation, someone else's interpretation quietly replaces our own understanding. It gets harder to tell how much of what we see matches reality

The blockchain is open to everyone. But transparent data doesn't mean clarity. Behind millions of transactions, the connections dissolve, along with the sources of funding and the routes capital takes

Words shape perception. Actions leave a digital trace

And that data means more than the loud words of developers and big capital

Where they build positions, where they steer liquidity and when they start to exit, while still talking about the future

GHOST is a digital ghost inside Robinhood Chain that follows the impulses of capital through wallets, contracts and pools across the chain

It reconstructs the routes and assembles them into an interactive graph. Separate transfers come together into a structure where you can see where the funds came from, which addresses they passed through and where they settled

One address opens the way into this web of connections. From there the ghost follows the large wallets, explores the flows around tokens and picks up where the interest of participants is shifting

Every connection it uncovers leads back to the original transaction. And now you can walk the whole visible trail and verify what you saw yourself

Time to wake up and see how deep the rabbit hole goes

https://t.co/EHD95eSlSz

[查理 @LiXi381m]

FLY DEV JUST POSTED A FISHBRAIN AI GAME 45 MINUTES AGO.

Fly developer Insomnia just dropped a new AI trading fish brain game.

He calls it "Fishbrain"

Its a fish's brain connected to 166,720 neurons giving them creating a full trading ecosystem in a backrooms environment on Solana.

With his last project running to millions, this one could go really HIGH.

All fees to his Github:
https://t.co/Qr9jbpS8jP

https://t.co/eSxl50iOuS

[Insomnia @insomnia_vip]

I JUST GAVE MY FISHING GAME ITS FIRST REAL ECONOMY

The fish can now do more than catch humans.

It can sell them.

I added a small underwater trading system where the fish can bring whatever it finds back to a giant merchant and negotiate a price.

The first test starts with a knife.

The fish picks it up, swims over to the merchant and gets an offer:

$1.28.

Obviously, that's not enough.

So the fish grabs the merchant by the head and suddenly the offer becomes $1.73.

Negotiations are going well.

But then I realized the fish should be able to trade more than random items.

So I added the humans it catches to the same world.

Now the fish can go back to the seabed, pick up its catch and bring it straight to the merchant's table.

The merchant doesn't seem particularly prepared for this business model.

This is slowly turning into an actual game now.

You fish for humans, collect things from the underwater world, trade your loot and interact with whatever strange creatures are running the economy down there.

And I already have more mechanics planned.

The ocean is getting a lot more interesting.

TO BE CONTINUED

[查理 @LiXi381m]

A FLY BRAIN IS MINING BITCOIN.

FutureBit developer Zentrix just dropped "Hashfly" a fly's brain mining Bitcoin.

The idea sounds crazy, but the efficiency claim is even crazier: ~1 watt per terahash if scaled to real organic neurons.

That would be around 10× more energy-efficient than leading 3nm silicon ASICs.

https://t.co/OneZdDDyJn

https://t.co/g2Qc9zPlfW

They ran a previous project to millions a few weeks back, this could be GENNY.

[Zentrix⌚️ @ZentrixHQ]

A fly's brain could change the principles of Bitcoin mining forever.

Researchers @futurebit introduced HashFly, an experimental Bitcoin miner built around organic neurons from a fly brain.

The idea sounds crazy, but the efficiency claim is even crazier:

~1 watt per terahash if scaled to real organic neurons.

That would be around 10× more energy-efficient than leading 3nm silicon ASICs.

Biology might have been running ultra-efficient computing all along. 🧠🪰

[查理 @LiXi381m]

FIRST WE HAD A FLYBRAIN NOW ITS A MONKEY?

Known AI dev Mojune (followed by pmarca, repligate etc) just dropped just dropped a new MonekyBrain AI agent.

He used the study of real life monkeys and connected their behavior via the neuron connecter and created "living" monkeys inside the backrooms.

GOING GIGA VIRAL ALREADY.

All fees going to his Github:
https://t.co/IZ2NNnCivG

https://t.co/UhSKdraLtu

[Mojunel.eth @mojunel]

SOMEONE RAN 15 HOURS OF JUNGLE FOOTAGE THROUGH A BEHAVIORAL MODEL. IT FOUND A CHIMPANZEE USING A TEACHING METHOD HUMANS DIDN'T FORMALIZE UNTIL 1934.

Scientists hid camera traps at 14 tool-use sites in a Senegalese savanna. They left them recording for 8 years.

What they found: wild chimpanzees physically teach their children how to use technology. Not by example. By direct, hands-on instruction.

33 recorded lessons. 4 subjects: algae fishing, army ant extraction, termite fishing, baobab cracking. Each requires a different manufactured tool. Each is taught separately.

The head teacher is a female named Soukki.

In one clip from 2018, her 3-year-old daughter Saïsaï wanders away mid-lesson during ant dipping. Soukki stops fishing. Walks after her daughter. Physically grabs her. Carries her back to the ant nest. Places her directly in front of a tool she left inserted in the ground.

The daughter pulls the tool out, eats the ants. Soukki watches. The lesson is over.

In 2025, Saïsaï shows up on the same cameras again. She is 10 years old. She is teaching her own infant the same technique. At the same ant nest. With the same method her mother used on her.

The dropout became the professor.

In another clip, a juvenile male teaches a 1-month-old infant to crack baobab fruit against rock. The infant can't do it. The juvenile starts slapping and stamping the rock surface -- demonstrating the motion with sound cues. Then he grabs the fruit WITH the infant's hand and does the pounding movement together. Then he cracks his own fruit open right next to the infant. The infant picks up a piece, eats it, goes back to his mother, grabs another fruit, and starts trying on his own.

Nobody trained them. Nobody prompted this. A wild primate is running structured multi-step instruction with physical correction, guided practice, audio-visual demonstration, and peer-assisted learning.

The mothers pay a measurable cost for every lesson. After transferring a tool, they use tools less, insert less, eat less. They sacrifice foraging time so their children can practice.

Statistical models confirmed it: this is teaching by every scientific definition we have.

Someone ran the 15 hours of footage through a behavioral analysis model. The system flagged a pattern: Soukki teaches in a strict sequence. First observation. Then guided practice with the tool in hand. Then independent work with no intervention. Difficulty increases with each subject.

The structure matched a framework from 1930s developmental psychology -- Vygotsky's Zone of Proximal Development. Scaffold the learner just beyond their current ability, then step back.

A chimpanzee in Senegal independently invented a teaching method that took humans until the 20th century to formalize.

53 adults in the population. A 4-discipline technical curriculum run entirely by female chimpanzees across a 140 km² savanna campus. Self-replicating. Generational.

8 years of footage to prove what's been happening for 8 million.

Vygotsky published his theory in 1934. Soukki's family has been running it for longer than our species has existed. She just never needed to write it down.

[查理 @LiXi381m]

Ex-Google dev Monokern just dropped "Agentic Shift" a new multi-agent swarm backrooms.

He is GIGA stacked and has had several coins running to 500k+ before.

He is followed by all the big names in AI.

This could run HARD.

All fees to his Github:
https://t.co/cIlM96TSB6

https://t.co/l7dvGrvWrh

[monokern @monokern]

woke up to 41 finished jobs and a bill smaller than one lunch

my five bots worked from 22:14 to 06:31 while i was unconscious. a freelancer running that same list invoices me around $380 and still sleeps through most of it

that sphere is my /workspace after two weeks. 100,800 files, 36 directories, five cloud machines feeding it, 110 skills the bots wrote for themselves. nobody typed those skills. they recorded themselves doing a job once and kept the recording

every bot has its own machine. own browser, own terminal, own files, sitting in a data centre that does not care whether my laptop is shut

between 10pm and breakfast:

→ klaus read everyone's job description and routed the work himself. i stopped assigning tasks on day three
→ mara scraped nine competitor sites and left a brief in /workspace/state. i read it with coffee
→ cole wrote 50 outreach emails and sent zero of them. his charter has one hard line: never hit send without me
→ rina hit a login wall at 01:40, froze, and buzzed my desktop. i typed the password on my own screen, she got a session token, the model never saw a character of it
→ vince watched replies all night and flagged the two that actually needed a human

night nine is when i nearly lost all of it. a cloud VM rebuilt itself and wiped every tool they had installed. tailscale gone, python packages gone, scrapers gone. /workspace didn't lose a byte, and the boot script reinstalled the rest before my alarm went off

want this running by midnight:

> one bot, call it klaus, write in plain english what it owns
> every profile ends with: you may draft and save, you must never send, pay or delete without me
> everything lives under /workspace. anything outside it is temporary and you find that out the hard way
> record one weekly chore with teach-a-task and let it save itself as a skill
> hand it a job, close the laptop

costs me less per month than the two hours a week i used to burn exporting one dashboard

people already doing this are not posting about it. their bots are drafting right now. yours is waiting for you to type something

close a chat tonight and you fire five people

charters and the boot script are in the piece below

[查理 @LiXi381m]

THIS IS THE FIRST AI MEME TERMINAL?

Known AI dev Frogify (45k followers, +200 key followers all the big AI names) just dropped "Blob" a new kind of meme terminal that is connected to 137,682 memes.

Its literally going viral on the timeline already.

Its properly the first ever AI terminal that relies on memes.

All fees to his Github:
https://t.co/mvFBJJHTze

https://t.co/5y55N1IDI2

[Frogify @0xFrogify]

137,682 - Amount of memes my AI agents learned on.

They gained "consciousness" 11 days ago.
They were learning every second since.
I never turned them off...

This workflow made me $17,915
And lost: $5,912 learning

PnL: $12,003

But the crazy part is what I actually changed in the AI agent thinking process that made the profit factor 3.03 possible

An LLM's actual neurons are unreadable. Nobody knows why a model decided anything.

So I moved the thinking out of the model and into files.

The model does judgment. The files hold beliefs. And the files are the part that learns.

Here's the example:

"id: b-0032
desk: weigher
claim: recheck cadence under 120s while narrative is live
born: t-0912
fired: 14
improved: 9
regressed: 2
active: true"

fired is how many times it ran. improved is how often it helped.

When the second number stops beating the third, the belief switches itself off.

That's the learning. A counter in a text file.

Everyone building agents right now is flexing how little they touch them.

But a system that can't be overruled isn't autonomous. It's unsupervised.

I can read every one.
I can edit every one.
I can delete a belief at 3am from my phone and the desk runs without it on the next tick.

That's not a second brain. It's a brain with the skull off.

stay tuned. Big update on Blob coming...

[查理 @LiXi381m]

NEW PUMPFUN TERMINAL BY AI GUY FOLLOWED BY PMARCA?

Cybernetics dev Rimtoln just dropped a new AI terminal for Pumpfun.

His last projects all bonded and I am pretty sure if he supports this one, we will run high.

Got so many key followers and all fees to his Github.

https://t.co/LonENsmFqH

https://t.co/51uW3sNmqI

[cryptopsihoz @rimtoln]

I BUILT EXITLOOP. MOST LOSE ON THE EXIT.

ct brags about candle one
dose size, sniper fill, who hit first

then the bag bleeds for 40 seconds
liq thins, insiders dump, velocity flips
and you are still holding the thesis

EXITLOOP is not another entry bot
it is the cut runtime for https://t.co/TJMlmRrDyF

▹ what i shipped

dark 1920 desk, neon beam through the void
waveform reacts when the score climbs
HOLD -> WARN -> PARTIAL -> HARD on the beam
60s cycle, 12 bags, paper only, no keys

▹ the loop

1. liq under 28% on the curve = pressure
2. insider sell cluster over 42% = heat
3. bonding velocity under -0.18 = decay
4. spread fat = slip risk on the cut

score stacks those hits
28 arms WARN
48 fires PARTIAL 40%
72 is HARD EXIT, no vibes

▹ most people

still ape the mint
pray on a round tp
watch the chart like a movie

this desk watches the exit signal
before the sol is already gone

▹ the close

entry is loud and crowded
exit is where the money stays
you do not hold the bag
you exitloop it

https://t.co/TJMlmRrDyF is the board
EXITLOOP is the hand that cuts
bookmark before the next thin tape

[查理 @LiXi381m]

Former Google Researcher Monokern just dropped "Agentic Shift" a new multi-agent swarm backrooms.

He is GIGA stacked and has had several coins running to 500k+ before.

He is followed by all the big names in AI.

This could run HARD.

All fees to his Github:
https://t.co/cIlM96TSB6

https://t.co/l7dvGrvWrh

[monokern @monokern]

woke up to 41 finished jobs and a bill smaller than one lunch

my five bots worked from 22:14 to 06:31 while i was unconscious. a freelancer running that same list invoices me around $380 and still sleeps through most of it

that sphere is my /workspace after two weeks. 100,800 files, 36 directories, five cloud machines feeding it, 110 skills the bots wrote for themselves. nobody typed those skills. they recorded themselves doing a job once and kept the recording

every bot has its own machine. own browser, own terminal, own files, sitting in a data centre that does not care whether my laptop is shut

between 10pm and breakfast:

→ klaus read everyone's job description and routed the work himself. i stopped assigning tasks on day three
→ mara scraped nine competitor sites and left a brief in /workspace/state. i read it with coffee
→ cole wrote 50 outreach emails and sent zero of them. his charter has one hard line: never hit send without me
→ rina hit a login wall at 01:40, froze, and buzzed my desktop. i typed the password on my own screen, she got a session token, the model never saw a character of it
→ vince watched replies all night and flagged the two that actually needed a human

night nine is when i nearly lost all of it. a cloud VM rebuilt itself and wiped every tool they had installed. tailscale gone, python packages gone, scrapers gone. /workspace didn't lose a byte, and the boot script reinstalled the rest before my alarm went off

want this running by midnight:

> one bot, call it klaus, write in plain english what it owns
> every profile ends with: you may draft and save, you must never send, pay or delete without me
> everything lives under /workspace. anything outside it is temporary and you find that out the hard way
> record one weekly chore with teach-a-task and let it save itself as a skill
> hand it a job, close the laptop

costs me less per month than the two hours a week i used to burn exporting one dashboard

people already doing this are not posting about it. their bots are drafting right now. yours is waiting for you to type something

close a chat tonight and you fire five people

charters and the boot script are in the piece below

[查理 @LiXi381m]

NEW AI AGENT BY THE FLY CREATOR JUST POSTED 30 MINUTES AGO.

The fly creator Shelpid just dropped a new AI agent called Aurora Sentinel.

He had several projects before and most of them ran super high.

Shelpid is followed by ALL the big accounts in AI.

https://t.co/k7yicBxqcA

[Shelpid.WI3M @Shelpid_WI3M]

EIGHT TRADING AGENTS. ONE DESK. EVERY DECISION CONNECTED

What would a trading terminal look like if you could actually see how the agents coordinate?

That’s the idea behind AURORA SENTINEL

A central robot surrounded by eight specialists, each with its own role, telemetry, and connection to the core

Here’s how the desk is designed:

→ SCOUT discovers new pairs and emerging opportunities
→ ORACLE evaluates signals
→ AEGIS checks risk before execution
→ PULSE tracks momentum
→ VECTOR handles order execution
→ SPECTRE follows on-chain activity
→ NOVA monitors liquidity
→ ANCHOR manages exits

The Sentinel sits in the middle as the coordinator, bringing those inputs into one view

I wanted the interface to make that process visible

Packets move between agents and the core
Individual panels show what each specialist is monitoring
The execution stream records events
The consensus bar shows how closely the agents agree

Deep navy, ice blue, and violet give the terminal its identity, with a custom shield logo matching the robot at the center

This is an animated interface concept with simulated data, including the P&L

The goal is simple: one screen where you can follow the whole process, from discovery to exit

[查理 @LiXi381m]

Ex Nvidia-researcher Henvy jhust dropped a new backrooms protocol called "Nerve".

Its an advanced agent terminal for cryptos and stock pairs on Solana.

His previous coins did super well and one of them went to $500k a few weeks back.

Now he dropped his 2nd project.

All fees to his Github:
https://t.co/sYLO1OoEn1

https://t.co/CCeB9LC8kc

[h100envy @h100envy]

THE 7TH AGENT DOES NOT THINK. IT TRIES TO SELL YOUR TOKEN BEFORE YOU BUY IT.

repo: https://t.co/voxNRXBDfB

every other agent in the system has an opinion. sentinel has a transaction.

it sits between scanner and analyst. before the model spends $0.008 thinking about a pool, sentinel spends $0.00 trying to exit it.

one eth_call. your real wallet address. one pinned block. buys the token. sells the same amount back. all simulated.

revert on sell? honeypot. you never see it.

sell goes through but balanceOf delta is less than quoter promised? hidden tax. now you know the real number, not the one in the json.

bytecode has blacklist selectors? dead before the impulse moves.

tradingEnabled flipped to false after launch? dead.

wallet limit? antibot lock? fee on transfer the quoter cannot see because it quotes from its own address?

dead. dead. dead.

the old quoter asked the pool a polite question. sentinel walks in with your wallet and tries to leave. that is the difference between a quote and a proof.

first night: 47 tokens cleared all 6 agents. sentinel killed every one. 3 were honeypots.

the model would have said yes with 89 confidence. sentinel does not have confidence. it has a revert or it does not.

deterministic. free. no api key. no model call. faster than every reflex except kill switch.

a token you cannot sell is not worth a question to gpt.

7 nodes. 11 reflexes. sentinel is node 2.

[查理 @LiXi381m]

Everyone is waiting for UNIpcs to buy, but why dont we run his most posted slogan?

GOD WILLING.

300+ posts:
https://t.co/Hqx19e8vRy

[查理 @LiXi381m]

PolyMarket developer Retro Valix just dropped a new "PolyBrain" backrooms, which is a full swarm PolyMarket brain model that executes trades on its own.

So far nobody has done a model like this and its going viral on the timeline.

Valix is super known in the AI community and followed by all the big accounts. He created several projects in the past and we ran coins to $500k+ for him.

I am sure he is cryptofriendly and we can onboard him easily.

Check his Github, its giga STACKED.
https://t.co/XvrCT61J7o

https://t.co/aLoIzPtaF8

[VALIX @RetroValix]

This guy built an HFT algorithm on Polymarket with an average trade size of $18.69

Result: +$88,641

The bot trades short-term crypto Up/Down markets using a passive maker grid, asynchronous accumulation, and a directional residual:

1. Places BUY limit orders across a fixed price grid

It provides liquidity at multiple price levels in advance and waits for the orders to fill

2. Accumulates the opposite outcome as the market moves

It bought both Up and Down in 63.6% of markets

Orders on one side fill first. Once the market reprices, orders on the opposite side start filling

Within each market, it switches between Up and Down a median of 2 times

3. Keeps part of its inventory directional

After pairing both sides, a directional residual remains. The size of this residual becomes the main source of PnL

In markets where it bought both sides, the outcome with the larger inventory won 53.7% of the time

Its Polymarket account: 98euf98a

Follow this account and trade on Polymarket through this app:

https://t.co/jMUgXhfXIf

The bot’s main edge comes from a two-part strategy: matched Up/Down positions reduce exposure, while the remaining directional residual drives most of its PnL

[查理 @LiXi381m]

@soburr_af @Cryptolows Need to change username regulary, because my account is heavily sniped by bots.

[查理 @LiXi381m]

They gave us a meme template for PSOL pairs just a few days ago?

excellent meme sir

https://t.co/MbyAYZYRFA

[Phantom @phantom]

excellent meme sir. would you like to pair any stocks with it?