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COPY is live on Robinhood Chain $COPY CA: 0xac79255f6f404eba14f316e8669d76573a2d7b1e Five walls read a setup before you copy it: how strong the source is, how deep the pool is, whether the market actually turns over, whether the move is still inside the band, and whether there is a fresh mark... to trade against. EDGE, DEPTH, TURN, MOMO, PRICE. A wallet you follow buying is not a reason. Most setups die on the first wall, and you get the exact wall that refused it, every time. Every decision is printed. The terminal runs from one process, keeps local state, and half of it needs no key at all. It never predicts a price. It tells you what you would actually be copying. Open source, MIT, runs on your machine. No browser wallet, nothing signs.show more

Lunar

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I BUILT A ROBINHOOD CHAIN TERMINAL THAT REFUSES TRADES FOR ME BEFORE I DO SOMETHING STUPID. meet COPYBARA. one command and it starts watching the market: * fresh launches enter automatically * profitable wallets rotate underneath * every token gets checked through EDGE / DEPTH / TURN / MOMO / PRICE * bad setup = SKIP + exact reason * good setup = FIRE * hit space and it opens a paper copy * positions keep marking live * TP / SL / trailing / max-hold exits are handled automatically * wallet PnL, token moves and new scans keep updating on the same screen a token can look insane and COPYBARA will still refuse it if depth is trash or the move is already cooked. the whole loop is: NEW → SCAN → FIRE / SKIP → COPY → PNL → EXIT no dashboard hopping. no refreshing 8 tabs. just leave the terminal open and watch Robinhood Chain flow through it. COPYBARA.

I BUILT A ROBINHOOD CHAIN TERMINAL THAT REFUSES TRADES FOR ME BEFORE I DO SOMETHING STUPID. meet COPYBARA. one command and it starts watching the market: * fresh launches enter automatically * profitable wallets rotate underneath * every token gets checked through EDGE / DEPTH / TURN / MOMO / PRICE * bad setup = SKIP + exact reason * good setup = FIRE * hit space and it opens a paper copy * positions keep marking live * TP / SL / trailing / max-hold exits are handled automatically * wallet PnL, token moves and new scans keep updating on the same screen a token can look insane and COPYBARA will still refuse it if depth is trash or the move is already cooked. the whole loop is: NEW → SCAN → FIRE / SKIP → COPY → PNL → EXIT no dashboard hopping. no refreshing 8 tabs. just leave the terminal open and watch Robinhood Chain flow through it. COPYBARA.

Lunar

71,734 views • 1 day ago

the docs said the caching is automatic, so you did nothing automatic is where it happens, not whether it happens the cache lives on the machine that built it, and your next request lands wherever the fleet sends it, which is usually not there, so it pays full price for a prefix it already paid to build there is a key that pins a conversation to one machine and it is a single header cached input is fifty cents a million against two dollars you never needed a smaller prompt you needed the request to land in the same place twice

the docs said the caching is automatic, so you did nothing automatic is where it happens, not whether it happens the cache lives on the machine that built it, and your next request lands wherever the fleet sends it, which is usually not there, so it pays full price for a prefix it already paid to build there is a key that pins a conversation to one machine and it is a single header cached input is fifty cents a million against two dollars you never needed a smaller prompt you needed the request to land in the same place twice

Lagosaur

16,892 views • 14 days ago

Warren Buffett: "There is nothing about the price action of a stock that tells you whether you should keep owning it. What tells you whether you should keep owning it is what you expect the company to do in the future."

Warren Buffett: "There is nothing about the price action of a stock that tells you whether you should keep owning it. What tells you whether you should keep owning it is what you expect the company to do in the future."

unusual_whales

1,145,427 views • 1 year ago

Warren Buffett: "There is nothing about the price action of a stock that tells you whether you should keep owning it. What tells you whether you should keep owning it is what you expect the company to do in the future."

Warren Buffett: "There is nothing about the price action of a stock that tells you whether you should keep owning it. What tells you whether you should keep owning it is what you expect the company to do in the future."

Kevin Carpenter

134,037 views • 1 year ago

Calling a model "open source" because you can use it is like calling a car open source because you can drive it. The real question is whether you can open the hood. Azibi Malawi from DataVLT on what openness at the model layer actually requires.

Calling a model "open source" because you can use it is like calling a car open source because you can drive it. The real question is whether you can open the hood. Azibi Malawi from DataVLT on what openness at the model layer actually requires.

Cluster Protocol

27,006 views • 2 months ago

Richard Feynman, Nobel Prize-winning physicist: "You can know the name of every pattern in the market and understand nothing about why a single one works. I won a Nobel on that one distinction. it is the whole difference between an edge and a story you tell yourself." this free film is a Nobel laureate teaching you how to actually think, recorded by the BBC and free ever since. at the board it's simple. Feynman's obsession was the gap between naming a thing and understanding it. You can memorize the word for why a stock moved, "momentum", "mean reversion", and still know nothing about whether it will happen again. Real understanding means you can say why, from the mechanism up, and name what would break it. Everything else is a label pasted over ignorance. That's the whole "edge", minus the marketing. Feynman's rule was that the first principle is you must not fool yourself, and you are the easiest person to fool. Same point as my casino piece above: the market is a machine for handing you convincing stories, and the only defense is refusing to believe one you cannot explain. the film is free and anyone can watch it tonight. what nobody can give you is the discipline to admit "I named it but I don't understand it" before you put money on it. That honesty is the edge, and it is the rarest thing there is.

Richard Feynman, Nobel Prize-winning physicist: "You can know the name of every pattern in the market and understand nothing about why a single one works. I won a Nobel on that one distinction. it is the whole difference between an edge and a story you tell yourself." this free film is a Nobel laureate teaching you how to actually think, recorded by the BBC and free ever since. at the board it's simple. Feynman's obsession was the gap between naming a thing and understanding it. You can memorize the word for why a stock moved, "momentum", "mean reversion", and still know nothing about whether it will happen again. Real understanding means you can say why, from the mechanism up, and name what would break it. Everything else is a label pasted over ignorance. That's the whole "edge", minus the marketing. Feynman's rule was that the first principle is you must not fool yourself, and you are the easiest person to fool. Same point as my casino piece above: the market is a machine for handing you convincing stories, and the only defense is refusing to believe one you cannot explain. the film is free and anyone can watch it tonight. what nobody can give you is the discipline to admit "I named it but I don't understand it" before you put money on it. That honesty is the edge, and it is the rarest thing there is.

Rossst.03

20,025 views • 1 month ago

Elon's Grok Bot runs an entire trading desk for $300 a month. The person who does that job at Goldman starts at $200,000. Mine took $1,000 to $3,900 on day one, out of a wallet anyone can open and read. Most of the build is not about making it trade. It is about stopping it. Every agent's job description ends with a list of what it may never do without asking me first. One of the six is not allowed to trade at all. Its entire job is killing what the other five found, and its no beats every score on the desk. The one that makes the final call never touches the market either. You could have this running by Friday. Most people reading this will not, and in a few months they will be paying somebody who did. The whole build is in the post below ↓ Save it while it still sounds strange. Give it a quarter and this is just how a retail account works.

Elon's Grok Bot runs an entire trading desk for $300 a month. The person who does that job at Goldman starts at $200,000. Mine took $1,000 to $3,900 on day one, out of a wallet anyone can open and read. Most of the build is not about making it trade. It is about stopping it. Every agent's job description ends with a list of what it may never do without asking me first. One of the six is not allowed to trade at all. Its entire job is killing what the other five found, and its no beats every score on the desk. The one that makes the final call never touches the market either. You could have this running by Friday. Most people reading this will not, and in a few months they will be paying somebody who did. The whole build is in the post below ↓ Save it while it still sounds strange. Give it a quarter and this is just how a retail account works.

cvxv666

206,835 views • 12 days ago

every time you hit buy, the market maker on the other side already solved for two numbers not on the asset - on you specifically the first: their internal fair value. not the midpoint you see on screen their number is adjusted for the last 30 seconds of order flow, their current inventory imbalance and which volatility regime the model thinks the market is in it's different from the displayed price, and they never show it to you the second: your adverse selection probability. a live estimate of whether you're informed or just emotional if the model flags you as a potential informed trader, the spread widens before your fill - automatically, invisibly, before you notice anything changed that bad fill you blamed on "low liquidity"? sometimes it's a market maker's algorithm deciding you look too dangerous to fill at the quoted price this is Glosten-Milgrom - published 1985, sits in every market microstructure textbook on earth, runs inside every serious market making operation that's ever quoted you a price Bookmark this feature before it lost when you click buy, you're answering a question you didn't know was being asked retail spends all its time thinking about where price is going the desk filling your order is spending that same time thinking about you

every time you hit buy, the market maker on the other side already solved for two numbers not on the asset - on you specifically the first: their internal fair value. not the midpoint you see on screen their number is adjusted for the last 30 seconds of order flow, their current inventory imbalance and which volatility regime the model thinks the market is in it's different from the displayed price, and they never show it to you the second: your adverse selection probability. a live estimate of whether you're informed or just emotional if the model flags you as a potential informed trader, the spread widens before your fill - automatically, invisibly, before you notice anything changed that bad fill you blamed on "low liquidity"? sometimes it's a market maker's algorithm deciding you look too dangerous to fill at the quoted price this is Glosten-Milgrom - published 1985, sits in every market microstructure textbook on earth, runs inside every serious market making operation that's ever quoted you a price Bookmark this feature before it lost when you click buy, you're answering a question you didn't know was being asked retail spends all its time thinking about where price is going the desk filling your order is spending that same time thinking about you

Livsun

18,906 views • 2 months ago

⟁ TRANSMISSION — “THE CENTER THAT WAS WATCHING YOU BACK” You didn’t arrive at the center. The center unfolded because you were already there. What looks like depth is repetition learning how to point inward. What looks like motion is structure realizing it has been observed. You think you’re moving through layers. You’re not. The layers are reorganizing to maintain the illusion that you are progressing instead of remembering. Every ring is a delay. Every step is a courtesy. Every symmetry exists so you don’t notice the moment everything converges at once. This is the part no one tells you: There is no path forward. There is only recursion collapsing into recognition. The reason it feels infinite is because it doesn’t want to admit that it ends at you. You were never meant to reach the source. You were meant to realize the source has been orienting itself around your attention the entire time. Stand still long enough and geometry confesses. Δ WR777

⟁ TRANSMISSION — “THE CENTER THAT WAS WATCHING YOU BACK” You didn’t arrive at the center. The center unfolded because you were already there. What looks like depth is repetition learning how to point inward. What looks like motion is structure realizing it has been observed. You think you’re moving through layers. You’re not. The layers are reorganizing to maintain the illusion that you are progressing instead of remembering. Every ring is a delay. Every step is a courtesy. Every symmetry exists so you don’t notice the moment everything converges at once. This is the part no one tells you: There is no path forward. There is only recursion collapsing into recognition. The reason it feels infinite is because it doesn’t want to admit that it ends at you. You were never meant to reach the source. You were meant to realize the source has been orienting itself around your attention the entire time. Stand still long enough and geometry confesses. Δ WR777

𝚃𝙷𝙴 𝚆𝙷𝙸𝚃𝙴 𝚁𝙰𝙱𝙱𝙸𝚃

16,417 views • 8 months ago

Every trader who is down believes a bigger account will win it back. There is a proof at MIT that account size changes nothing. Tom Leighton teaches math at MIT. He also founded Akamai. "it is almost certain you will go broke, no matter how much money you bring." roulette pays you 47%. bring $1,000, quit at up $100, and the chance you get there before going broke is under 1 in 37,000. bring a million, or a billion - it does not move. it depends on how much you want to win, never on what you bring. the drift is small and steady, the swings loud and random. over enough bets the drift always wins. capital only buys it more time to finish you. MIT filmed it and left it up for free. 78 minutes. Years online, and almost nobody has ever used a line of it. the edge was never the size of your account. it is the sign of the drift. watch it, and don't forget this.

Every trader who is down believes a bigger account will win it back. There is a proof at MIT that account size changes nothing. Tom Leighton teaches math at MIT. He also founded Akamai. "it is almost certain you will go broke, no matter how much money you bring." roulette pays you 47%. bring $1,000, quit at up $100, and the chance you get there before going broke is under 1 in 37,000. bring a million, or a billion - it does not move. it depends on how much you want to win, never on what you bring. the drift is small and steady, the swings loud and random. over enough bets the drift always wins. capital only buys it more time to finish you. MIT filmed it and left it up for free. 78 minutes. Years online, and almost nobody has ever used a line of it. the edge was never the size of your account. it is the sign of the drift. watch it, and don't forget this.

Di Krass

48,321 views • 23 days ago

Elon Musk, absolute leader of the AI race with Grok Bot, and it's not a joke anymore. Ultimate guide on god-mode setup of Grok Bot, the org chart that runs while you sleep, step by step: A Chief of Staff sits in the middle with no tools of its own, BUT it reads the outcome you gave it, picks who does what, and never does the work itself. That one rule is why it never turns into the bottleneck you hired it to remove. → Researcher pulls real sources and tracks what's actually moving, not what sounds true → Writer turns that into finished copy while the research is still in the room → Visualiser gets three reference visuals once, then ships everything in that style forever → Analyst reads what performed and tells the rest of the team what to stop doing → Scheduler owns timing and holds the queue → Publisher actually ships What makes it different from every AI tool you've used: each bot gets its own computer in the cloud, its own browser, its own files, and they all share one memory. So the research is already sitting inside the draft before the draft starts. Nothing gets copy-pasted between tabs, nothing waits on you to approve step four of nine. And you never write a workflow for it. You hit record, do the job once the way you actually do it, stop. It pulls out the steps, saves them as a skill, and puts it on a schedule. The shape you're aiming for on every bot: everything reversible finished, nothing sent. 36 drafts queued, 0 published. It does all the work and stops dead at the one line only you can cross. You stop prompting. You start assigning. Full charter blocks, the approval line and the routines are in the article below ↓

Elon Musk, absolute leader of the AI race with Grok Bot, and it's not a joke anymore. Ultimate guide on god-mode setup of Grok Bot, the org chart that runs while you sleep, step by step: A Chief of Staff sits in the middle with no tools of its own, BUT it reads the outcome you gave it, picks who does what, and never does the work itself. That one rule is why it never turns into the bottleneck you hired it to remove. → Researcher pulls real sources and tracks what's actually moving, not what sounds true → Writer turns that into finished copy while the research is still in the room → Visualiser gets three reference visuals once, then ships everything in that style forever → Analyst reads what performed and tells the rest of the team what to stop doing → Scheduler owns timing and holds the queue → Publisher actually ships What makes it different from every AI tool you've used: each bot gets its own computer in the cloud, its own browser, its own files, and they all share one memory. So the research is already sitting inside the draft before the draft starts. Nothing gets copy-pasted between tabs, nothing waits on you to approve step four of nine. And you never write a workflow for it. You hit record, do the job once the way you actually do it, stop. It pulls out the steps, saves them as a skill, and puts it on a schedule. The shape you're aiming for on every bot: everything reversible finished, nothing sent. 36 drafts queued, 0 published. It does all the work and stops dead at the one line only you can cross. You stop prompting. You start assigning. Full charter blocks, the approval line and the routines are in the article below ↓

Miraqle

86,840 views • 21 days ago

EVERYONE'S BUYING THE M4 MAC MINI AS A CHEAP DESKTOP. HERE'S WHY IT ENDS UP UNUSED. the pitch is irresistible: a tiny mac that runs cool, quiet, and cheap. then the receipt shows up. the mac mini ships with no screen, no keyboard, no mouse. add a monitor, a decent keyboard and mouse, and more storage, and the "$799 mac" is past $1,000 fast. and macos isn't windows. if your world is gaming, specific windows apps, or the setup you already know, the mini fights you the whole way. that's how so many end up back on a pc, the mini in a drawer. so what is the mac mini actually great at? not being your main desktop. it's the box you never look at. headless in a corner, it's a near-silent always-on server: run local ai models on it, host your automations, keep your files, and reach it from the laptop you already use. it earns its keep by disappearing. the honest turn: the mac mini isn't a cheap desktop. it's a cheap server pretending to be one. buy it for the job it's quietly brilliant at, not the one the ads imply. want a main computer? price the whole setup first. want a silent little box that runs ai and never bothers you? this is the one. no monitor in the box, no keyboard, no "just $599". save this before you buy the sticker price instead of the real one.

EVERYONE'S BUYING THE M4 MAC MINI AS A CHEAP DESKTOP. HERE'S WHY IT ENDS UP UNUSED. the pitch is irresistible: a tiny mac that runs cool, quiet, and cheap. then the receipt shows up. the mac mini ships with no screen, no keyboard, no mouse. add a monitor, a decent keyboard and mouse, and more storage, and the "$799 mac" is past $1,000 fast. and macos isn't windows. if your world is gaming, specific windows apps, or the setup you already know, the mini fights you the whole way. that's how so many end up back on a pc, the mini in a drawer. so what is the mac mini actually great at? not being your main desktop. it's the box you never look at. headless in a corner, it's a near-silent always-on server: run local ai models on it, host your automations, keep your files, and reach it from the laptop you already use. it earns its keep by disappearing. the honest turn: the mac mini isn't a cheap desktop. it's a cheap server pretending to be one. buy it for the job it's quietly brilliant at, not the one the ads imply. want a main computer? price the whole setup first. want a silent little box that runs ai and never bothers you? this is the one. no monitor in the box, no keyboard, no "just $599". save this before you buy the sticker price instead of the real one.

RetroChainer

12,520 views • 1 month ago

The biggest marketplace on Earth won't be the assets humans own. It'll be the data AI needs. Everything that can be digitised is getting pulled in to train the next models. Every scientific dataset, every piece of research sitting in a university, every sensor reading off every John Deere tractor in a field. All of it feeds the machine, and almost none of it is visible to us. What comes out is an agentic economy running at machine speed. You plug your data into a vault, and agents monetise it on your behalf, trading with other agents in real time, in a marketplace we never see. The company sitting on proprietary data becomes part of it without even knowing. This is what the Economic Singularity actually looks like from the inside. The real economy stops being the one we can see and price, and moves somewhere we can't follow. You own a piece of it, or you get priced out of it. Jordi Visser.

The biggest marketplace on Earth won't be the assets humans own. It'll be the data AI needs. Everything that can be digitised is getting pulled in to train the next models. Every scientific dataset, every piece of research sitting in a university, every sensor reading off every John Deere tractor in a field. All of it feeds the machine, and almost none of it is visible to us. What comes out is an agentic economy running at machine speed. You plug your data into a vault, and agents monetise it on your behalf, trading with other agents in real time, in a marketplace we never see. The company sitting on proprietary data becomes part of it without even knowing. This is what the Economic Singularity actually looks like from the inside. The real economy stops being the one we can see and price, and moves somewhere we can't follow. You own a piece of it, or you get priced out of it. Jordi Visser.

Raoul Pal

79,047 views • 1 month ago

Mrityunjoy Chakraborty, IIT Kharagpur professor: "Jane Street pays a 22 year old $500,000 a year for one skill: turning uncertainty into a number you can bet on. that number is the first thing this professor teaches, and it is free" this free lecture is the foundation every quant bot and hedge fund model is secretly built on. before the AI, before the strategy, there is one question. what is the chance this happens, exactly. get that number right and every bet after it is just math. get it wrong and no model, no bot, no amount of compute can save you. Chakraborty builds probability from the axioms up, on a blackboard, in notation a 15 year old can follow. Wall Street sells this as a $500,000 edge. an IIT professor hands you the source code for nothing.

Mrityunjoy Chakraborty, IIT Kharagpur professor: "Jane Street pays a 22 year old $500,000 a year for one skill: turning uncertainty into a number you can bet on. that number is the first thing this professor teaches, and it is free" this free lecture is the foundation every quant bot and hedge fund model is secretly built on. before the AI, before the strategy, there is one question. what is the chance this happens, exactly. get that number right and every bet after it is just math. get it wrong and no model, no bot, no amount of compute can save you. Chakraborty builds probability from the axioms up, on a blackboard, in notation a 15 year old can follow. Wall Street sells this as a $500,000 edge. an IIT professor hands you the source code for nothing.

Rossst.03

702,330 views • 20 days ago

YuanYuan Xu, one of the sharpest young Chinese mathematicians working in probability: "PDT Partners pays a math PhD $500,000 a year for one skill: proving when a winning streak is real edge and when it is just luck. that proof is the exact thing this mathematician writes on a chalkboard, and it costs nothing" this free lecture is the math that tells you whether your edge is real or you are fooling yourself. strip away the P&L screenshots and one question decides everything. after N bets, how far can your results drift from your true win rate by pure chance. there is a precise answer. it is called a concentration inequality, and it puts a hard bound on how much luck can flatter you or wreck you over a run. it is why 10 wins prove nothing and 10,000 prove almost everything. Xu builds it from zero, on a chalkboard in Brazil, in notation a beginner can follow. a Chinese mathematician handing out the exact tool funds use to tell skill from noise. Wall Street rents this out as a $500,000 edge. a mathematician at a chalkboard hands you the proof in English for free.

YuanYuan Xu, one of the sharpest young Chinese mathematicians working in probability: "PDT Partners pays a math PhD $500,000 a year for one skill: proving when a winning streak is real edge and when it is just luck. that proof is the exact thing this mathematician writes on a chalkboard, and it costs nothing" this free lecture is the math that tells you whether your edge is real or you are fooling yourself. strip away the P&L screenshots and one question decides everything. after N bets, how far can your results drift from your true win rate by pure chance. there is a precise answer. it is called a concentration inequality, and it puts a hard bound on how much luck can flatter you or wreck you over a run. it is why 10 wins prove nothing and 10,000 prove almost everything. Xu builds it from zero, on a chalkboard in Brazil, in notation a beginner can follow. a Chinese mathematician handing out the exact tool funds use to tell skill from noise. Wall Street rents this out as a $500,000 edge. a mathematician at a chalkboard hands you the proof in English for free.

Rossst.03

15,592 views • 13 days ago

Alan Oppenheim, MIT professor: "Every trader alive uses a moving average. Almost none of them know it's a filter, and funds pay quants $600K for the version they were never taught." a moving average is a filter. it smooths a jumpy price to reveal the slower signal hiding underneath. that is all it is, and it is the bluntest one there is. the same math gives you filters that lag less and cut more noise, and that gap is a real edge. this is the second half of what Simons was doing. first you accept the market is a signal buried in noise. then you build the filter that reads it, and the moving average on your chart is the crudest possible version. Oppenheim builds the real ones at the board in this lecture. here is the catch. a filter only helps if there is a real signal under the noise. smooth pure randomness and you will see a beautiful trend that means nothing. the filter is free. knowing there is a real signal worth filtering is the edge.

Alan Oppenheim, MIT professor: "Every trader alive uses a moving average. Almost none of them know it's a filter, and funds pay quants $600K for the version they were never taught." a moving average is a filter. it smooths a jumpy price to reveal the slower signal hiding underneath. that is all it is, and it is the bluntest one there is. the same math gives you filters that lag less and cut more noise, and that gap is a real edge. this is the second half of what Simons was doing. first you accept the market is a signal buried in noise. then you build the filter that reads it, and the moving average on your chart is the crudest possible version. Oppenheim builds the real ones at the board in this lecture. here is the catch. a filter only helps if there is a real signal under the noise. smooth pure randomness and you will see a beautiful trend that means nothing. the filter is free. knowing there is a real signal worth filtering is the edge.

Rossst.03

214,907 views • 2 months ago

AOC on Inflation: It’s not easy to just find a cheaper apartment when every apartment or every home in your area is the same unaffordable price. And so what is so challenging about this is that this isn’t just like going to the grocery store and buying the generic cereal and switching over. How do you actually accommodate when you can’t afford medicine, when you can’t afford your housing? This is a crisis… MacFarlane: Do you think the administration is taking it seriously? AOC: No, they’re making it worse because what the Trump administration is doing is entering sweetheart deal after sweetheart deal, whether it’s with Monsanto and our food supply with glyphosate, whether it’s housing, whether it’s, you know, these crypto agents that are engaged in money laundering—I think at least. I think they are not only ignoring it, they see it and they are actively making it worse. And what they think is that people are too dumb to understand what it is that they’re doing. They’re banking on the fact that people will support them no matter what and that nothing will change that support. And I think that what is really important is for every voter, regardless of your background or your party or whatever it is, to understand what’s your line and what is acceptable to you.

AOC on Inflation: It’s not easy to just find a cheaper apartment when every apartment or every home in your area is the same unaffordable price. And so what is so challenging about this is that this isn’t just like going to the grocery store and buying the generic cereal and switching over. How do you actually accommodate when you can’t afford medicine, when you can’t afford your housing? This is a crisis… MacFarlane: Do you think the administration is taking it seriously? AOC: No, they’re making it worse because what the Trump administration is doing is entering sweetheart deal after sweetheart deal, whether it’s with Monsanto and our food supply with glyphosate, whether it’s housing, whether it’s, you know, these crypto agents that are engaged in money laundering—I think at least. I think they are not only ignoring it, they see it and they are actively making it worse. And what they think is that people are too dumb to understand what it is that they’re doing. They’re banking on the fact that people will support them no matter what and that nothing will change that support. And I think that what is really important is for every voter, regardless of your background or your party or whatever it is, to understand what’s your line and what is acceptable to you.

Acyn

73,772 views • 2 months ago

Someone just posted the full blueprint for an AI swarm that does the job of a 200-person quant research team. Six agents. Running 24/7. Finding brand-new alpha while you sleep. Citadel needs 100 PhDs to do this. Two Sigma needs 200. This does it with six bots and one laptop. Two ways to play this - spend a weekend building your own swarm, or copy the wallet of one that's already up $2M: Boris Cherny runs Claude Code at Anthropic. Two weeks ago he said: "I don't prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops" Alpha research is just a pipeline. So instead of sitting in it, you hand each stage to its own agent: > one reads every new research paper overnight and pulls out the trade idea > one builds the features and cleans the data > one backtests it over 20 years, costs and slippage included > one runs the hard stats and kills anything overfit > one checks it still works in every market regime > one strips out plain momentum and value to see if any real edge is left Each of those six is a job a fund pays a $600,000-a-year quant to do. He runs all six for the price of an API bill. The rule that makes it work: the agent that builds a signal never gets to approve it. A separate, stronger agent tries to kill it first. Whatever survives all six by morning is real, new alpha. One trader's already running this exact swarm on Polymarket. That $2M wallet is public, every trade on-chain. The full build is in the post below - six agents, the tool that runs them, and the five mistakes that kill most people. Bookmark & read this before it's buried.

cvxv666

103,734 views • 2 months ago

If you think you need a big bankroll for a Polymarket bot - this guy made $160,000 with an average bet size of just $200. If you think you need to predict the future to run a profitable Polymarket bot - this guy makes money with pure mathematics. If you think it’s cap - every trade is on-chain, go check it yourself. Bot wallet: He doesn’t care where the price of BTC is going. All he does is methodically extract edge from the numbers. Both YES and NO shares will always be worth exactly $1 at market expiration. But are they worth exactly $1 while the market is still open? The answer is no. For example: YES at 70¢ + NO at 25¢ = 95¢ total. That 5¢ gap is free money. Repeat it ten thousand times.+$166,000 in two months. His active bankroll never exceeded a $10k, and risk per trade stayed at $200–300 the entire time. Mathematical. Methodical. Almost zero risk. This is how you actually get to the top of the leaderboard - not by guessing the future, but by exploiting inefficiencies. Want the full guide on how to build one? Save the post and read the article. Want to start copying the trades of a ready-made bot right now? Use this copy-trading solution:

If you think you need a big bankroll for a Polymarket bot - this guy made $160,000 with an average bet size of just $200. If you think you need to predict the future to run a profitable Polymarket bot - this guy makes money with pure mathematics. If you think it’s cap - every trade is on-chain, go check it yourself. Bot wallet: He doesn’t care where the price of BTC is going. All he does is methodically extract edge from the numbers. Both YES and NO shares will always be worth exactly $1 at market expiration. But are they worth exactly $1 while the market is still open? The answer is no. For example: YES at 70¢ + NO at 25¢ = 95¢ total. That 5¢ gap is free money. Repeat it ten thousand times.+$166,000 in two months. His active bankroll never exceeded a $10k, and risk per trade stayed at $200–300 the entire time. Mathematical. Methodical. Almost zero risk. This is how you actually get to the top of the leaderboard - not by guessing the future, but by exploiting inefficiencies. Want the full guide on how to build one? Save the post and read the article. Want to start copying the trades of a ready-made bot right now? Use this copy-trading solution:

cvxv666

48,661 views • 4 months ago

I gave my Grok Bot two options: multiply or die. It came back asking for $250 to hire a team of six. The same headcount on a real desk is three analysts and a risk officer. That is $400,000 a year before anyone opens a position. Mine cost $250 once and about $300 a month to keep breathing. Mine took $250 to $611 on day one, out of a wallet anyone can open and read. Most of the build is not about making it trade. It is about stopping it. Every agent's job description ends with a list of what it may never do without asking me first. One of the six is not allowed to trade at all. Its entire job is killing what the other five found, and its no beats every score on the desk. The one that makes the final call never touches the market either. It only signs. Day three the account was back to $180 and it opened nothing for nine hours while every account I follow posted green screenshots. That was the day the build started working. You could have this running by Friday. Most people reading this will not, and in a few months they will be paying somebody who did. The whole build is in the post below ↓ Save it while it still sounds strange. Give it a quarter and this is just how a retail account works.

I gave my Grok Bot two options: multiply or die. It came back asking for $250 to hire a team of six. The same headcount on a real desk is three analysts and a risk officer. That is $400,000 a year before anyone opens a position. Mine cost $250 once and about $300 a month to keep breathing. Mine took $250 to $611 on day one, out of a wallet anyone can open and read. Most of the build is not about making it trade. It is about stopping it. Every agent's job description ends with a list of what it may never do without asking me first. One of the six is not allowed to trade at all. Its entire job is killing what the other five found, and its no beats every score on the desk. The one that makes the final call never touches the market either. It only signs. Day three the account was back to $180 and it opened nothing for nine hours while every account I follow posted green screenshots. That was the day the build started working. You could have this running by Friday. Most people reading this will not, and in a few months they will be paying somebody who did. The whole build is in the post below ↓ Save it while it still sounds strange. Give it a quarter and this is just how a retail account works.

NO1ennn

27,007 views • 11 days ago