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WHOEVER BUILT THIS HAS ZERO FEAR. SOMEONE CONNECTED 200 GROK BOTS INTO ONE AUTONOMOUS TRADING SYSTEM. -> One bot researches. -> Another tracks markets. -> Another analyzes sentiment. -> Another watches on-chain activity. But instead of leaving 200 separate outputs everywhere, they’re all connected through a CONTEXT GRAPH that... show more

MAX

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59,003 次观看 • 3 天前 •via X (Twitter)

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SpaceXAI engineer, Lauren Tan: "the upgrade was never a smarter model, it was wiring 20 Grok Bots into one graph they hand work to each other now, with zero input from me that took me from 6 tasks a day to 200+, my team ships overnight while I sleep" in a 55-minute session, a SpaceXAI engineer wires a full team of Grok Bots into one graph from scratch worth more than a $500 course on agentic engineering watch today, then read how to give that fleet a shared memory so it stops repeating your mistakes in the article below

SpaceXAI engineer, Lauren Tan: "the upgrade was never a smarter model, it was wiring 20 Grok Bots into one graph they hand work to each other now, with zero input from me that took me from 6 tasks a day to 200+, my team ships overnight while I sleep" in a 55-minute session, a SpaceXAI engineer wires a full team of Grok Bots into one graph from scratch worth more than a $500 course on agentic engineering watch today, then read how to give that fleet a shared memory so it stops repeating your mistakes in the article below

KingWilliam

29,071 次观看 • 2 天前

Claude read one article about trading bots, selected 7 GitHub repos, connected them into a pipeline and deployed the whole system. It made $847 overnight. → Scanned over 412,000 trades autonomously → Tracked whale wallets and detected insider activity → Analyzed data every few seconds and decided whether to buy, sell or pass → Executed 47 trades with zero manual intervention

Claude read one article about trading bots, selected 7 GitHub repos, connected them into a pipeline and deployed the whole system. It made $847 overnight. → Scanned over 412,000 trades autonomously → Tracked whale wallets and detected insider activity → Analyzed data every few seconds and decided whether to buy, sell or pass → Executed 47 trades with zero manual intervention

0xMarioNawfal

62,802 次观看 • 23 天前

GROK BOT MADE ME 3 TRADING BOTS IN 15 MINUTES +$2,353 in my wallet the next day, I quit my job that same day. I wrote one prompt and answered a few questions. Grok Bot took three strategies - MACD, RSI + VWAP, CVD divergence. Assigned each bot its own. The first one catches momentum - sees when volume picks up and gets in before the crowd wakes up. The second one trades reversals - waits for everyone to panic and bets against them. The third one scans divergences - when price says one thing but money does another, it follows the money. Built the structure itself, wrote the backtest, ran each strategy on historical data, set up the risk manager, deployed - all on its own. Three bots, three accounts, each trades differently - they don't know about each other. I named it Cabal. Started with $20, then $70, then $140, then $320, then $2,353 in a day. Citadel, Jane Street, Two Sigma have been trading with bots for years - they don't feel fear, greed, or FOMO - they only listen to algorithms. The market rewards systems.

GROK BOT MADE ME 3 TRADING BOTS IN 15 MINUTES +$2,353 in my wallet the next day, I quit my job that same day. I wrote one prompt and answered a few questions. Grok Bot took three strategies - MACD, RSI + VWAP, CVD divergence. Assigned each bot its own. The first one catches momentum - sees when volume picks up and gets in before the crowd wakes up. The second one trades reversals - waits for everyone to panic and bets against them. The third one scans divergences - when price says one thing but money does another, it follows the money. Built the structure itself, wrote the backtest, ran each strategy on historical data, set up the risk manager, deployed - all on its own. Three bots, three accounts, each trades differently - they don't know about each other. I named it Cabal. Started with $20, then $70, then $140, then $320, then $2,353 in a day. Citadel, Jane Street, Two Sigma have been trading with bots for years - they don't feel fear, greed, or FOMO - they only listen to algorithms. The market rewards systems.

Archive

274,323 次观看 • 10 天前

Found a setup that replaces a team of researchers with 300 AI agents and one shared graph. the interesting part is what happens after all 300 come back with different pieces of the answer. because now you don’t have 300 agents. you have: 300 outputs → hundreds of sources → repeated entities → overlapping claims → contradictions → thousands of possible relationships and all of that has to collapse into one structure. that’s what the context graph is doing. instead of: agent → report you get: agents → sources → entities → edges → contradictions → verification → one graph every source becomes a node. every shared entity creates a connection. 300 agents can create information. the graph is what turns that information into memory the next agent can actually use. that’s the anatomy behind the setup ↓

Found a setup that replaces a team of researchers with 300 AI agents and one shared graph. the interesting part is what happens after all 300 come back with different pieces of the answer. because now you don’t have 300 agents. you have: 300 outputs → hundreds of sources → repeated entities → overlapping claims → contradictions → thousands of possible relationships and all of that has to collapse into one structure. that’s what the context graph is doing. instead of: agent → report you get: agents → sources → entities → edges → contradictions → verification → one graph every source becomes a node. every shared entity creates a connection. 300 agents can create information. the graph is what turns that information into memory the next agent can actually use. that’s the anatomy behind the setup ↓

Ricker

19,319 次观看 • 5 天前

A 14-year-old from China built three separate AI brains connected to Claude Code - and each one grows every day on its own. One brain for code, one for projects, one for everything else in his life. 600+ conversations on one topic in a single node - everything linked, everything accessible in one request without copying between tabs. But the main thing isn't storage. If Claude Code made a mistake and he corrected it once - the system remembered. That same mistake never happened again. No re-explaining context, no starting from zero - Claude already knows how he thinks. Instead of one giant messy file- a stack of smaller brains passing context to each other. Brain to brain to brain - just stacking intelligence while his classmates do homework by hand.

A 14-year-old from China built three separate AI brains connected to Claude Code - and each one grows every day on its own. One brain for code, one for projects, one for everything else in his life. 600+ conversations on one topic in a single node - everything linked, everything accessible in one request without copying between tabs. But the main thing isn't storage. If Claude Code made a mistake and he corrected it once - the system remembered. That same mistake never happened again. No re-explaining context, no starting from zero - Claude already knows how he thinks. Instead of one giant messy file- a stack of smaller brains passing context to each other. Brain to brain to brain - just stacking intelligence while his classmates do homework by hand.

Noisy

22,622 次观看 • 4 个月前

WHOEVER LEAKED THIS HAS ZERO FEAR SOMEONE CONNECTED 4,200 GROK BOTS TO RUN A ONE-PERSON CONTENT DESK. Not 50. Not 350. Four thousand two hundred agents wired into one system. I thought it was just another AI experiment until I saw the architecture. Floor 1 scans X, TikTok, YouTube, Reddit and news every few seconds. Floor 2 hunts only for hooks, angles and formats that already spread. Floor 3 writes threads, scripts, carousels and reply chains in parallel. Floor 4 generates thumbnails, visuals and clip variants. Floor 5 tests timing, distribution, quotes and follow-ups. Floor 6 kills anything mid, off-brand or risky before it ever reaches the owner. Then one HEAD OF STUDIO Grok sits on top of all 4,200. It does not send him a mountain of drafts. It sends 3–7 pieces a day that actually deserve to be posted. No writers. No editors. No content team. No staring at a blank page. Just 4,200 Grok bots passing work between each other 24/7. The craziest part? The owner said he barely touches the system anymore. He just publishes what survives. FULL GUIDE ON HOW TO BUILD IT BELOW

Ridark

91,620 次观看 • 7 天前

i gave Elon's Grok Bot $50 and told it "pay for yourself or you die" 48 hours later it's holding $5,273 and it's still alive autonomous trading agent on polymarket zero code this time. the bot has its own computer in the cloud, its own browser, its own terminal. it trades with my laptop shut every 10 minutes it: → scans 500-1000 markets → reads live X sentiment (it's grok, it sees every post on this app) → builds fair value, flags mispricing > 8% → calculates position size (kelly criterion, max 6% bankroll) → executes in its own browser → pays its own $200 subscription from profits if the balance hits $0, i cancel the subscription. the bot dies day one it dipped to $11. it dropped crypto and moved to weather markets, front-running NOAA updates so it learned to survive setup took one evening: create the bot, run one trade on your screen while it watches, put the skill on a schedule, connect telegram no VPS. no API keys. no rust last winter i built this exact system by hand. 3 weeks of rust. it made $2,980 in its first 48 hours grok bot beat my own code in one evening $50 → $5,273 in 48 hours how much do u think it'll have in a week?

i gave Elon's Grok Bot $50 and told it "pay for yourself or you die" 48 hours later it's holding $5,273 and it's still alive autonomous trading agent on polymarket zero code this time. the bot has its own computer in the cloud, its own browser, its own terminal. it trades with my laptop shut every 10 minutes it: → scans 500-1000 markets → reads live X sentiment (it's grok, it sees every post on this app) → builds fair value, flags mispricing > 8% → calculates position size (kelly criterion, max 6% bankroll) → executes in its own browser → pays its own $200 subscription from profits if the balance hits $0, i cancel the subscription. the bot dies day one it dipped to $11. it dropped crypto and moved to weather markets, front-running NOAA updates so it learned to survive setup took one evening: create the bot, run one trade on your screen while it watches, put the skill on a schedule, connect telegram no VPS. no API keys. no rust last winter i built this exact system by hand. 3 weeks of rust. it made $2,980 in its first 48 hours grok bot beat my own code in one evening $50 → $5,273 in 48 hours how much do u think it'll have in a week?

Argona

1,244,353 次观看 • 16 天前

THIS GUY TURNED ONE OBSIDIAN VAULT INTO A SHARED BRAIN FOR 5 CLAUDE AGENTS BUILT TO HANDLE 80% OF A SOLO DEVELOPER’S WORK. 00:03 he zooms out and hundreds of connected notes appear on screen. it is the perfect visual for Claude working from one shared project memory instead of starting from zero every session. most developers give Claude 1 file and 1 prompt. this setup gives it the architecture, coding rules, tests, client briefs, and previous decisions before it writes anything. obsidian becomes the memory layer, storing everything in markdown files Claude can read alongside the codebase. every agent works from the same context instead of repeating the same questions. then 5 specialists split the job. one researches, one plans, one codes, one reviews, and one deploys while the developer only controls the important decisions. one vault, 5 agents, 2 model tiers, and a $50 to $150 monthly stack can turn Claude from a chatbot into a small development team.

THIS GUY TURNED ONE OBSIDIAN VAULT INTO A SHARED BRAIN FOR 5 CLAUDE AGENTS BUILT TO HANDLE 80% OF A SOLO DEVELOPER’S WORK. 00:03 he zooms out and hundreds of connected notes appear on screen. it is the perfect visual for Claude working from one shared project memory instead of starting from zero every session. most developers give Claude 1 file and 1 prompt. this setup gives it the architecture, coding rules, tests, client briefs, and previous decisions before it writes anything. obsidian becomes the memory layer, storing everything in markdown files Claude can read alongside the codebase. every agent works from the same context instead of repeating the same questions. then 5 specialists split the job. one researches, one plans, one codes, one reviews, and one deploys while the developer only controls the important decisions. one vault, 5 agents, 2 model tiers, and a $50 to $150 monthly stack can turn Claude from a chatbot into a small development team.

Gipp 🦅

10,799 次观看 • 2 个月前

CLAUDE MADE ME 3 TRADING BOTS IN 15 MINUTES +$2,503 in my wallet the next day, I quit my job that same day. I wrote one prompt and answered a few questions. Claude took three strategies - MACD, RSI + VWAP, CVD divergence. Assigned each bot its own. The first one catches momentum - sees when volume picks up and gets in before the crowd wakes up. The second one trades reversals - waits for everyone to panic and bets against them. The third one scans divergences - when price says one thing but money does another, it follows the money. Built the structure itself, wrote the backtest, ran each strategy on historical data, set up the risk manager, deployed - all on its own. Three bots, three accounts, each trades differently - they don't know about each other. Started with $1, then $5, then $10, then $50, then $2,503 in a day. Citadel, Jane Street, Two Sigma have been trading with bots for years - they don't feel fear, greed, or FOMO - they only listen to algorithms. The market rewards systems.

CLAUDE MADE ME 3 TRADING BOTS IN 15 MINUTES +$2,503 in my wallet the next day, I quit my job that same day. I wrote one prompt and answered a few questions. Claude took three strategies - MACD, RSI + VWAP, CVD divergence. Assigned each bot its own. The first one catches momentum - sees when volume picks up and gets in before the crowd wakes up. The second one trades reversals - waits for everyone to panic and bets against them. The third one scans divergences - when price says one thing but money does another, it follows the money. Built the structure itself, wrote the backtest, ran each strategy on historical data, set up the risk manager, deployed - all on its own. Three bots, three accounts, each trades differently - they don't know about each other. Started with $1, then $5, then $10, then $50, then $2,503 in a day. Citadel, Jane Street, Two Sigma have been trading with bots for years - they don't feel fear, greed, or FOMO - they only listen to algorithms. The market rewards systems.

zostaff

1,949,166 次观看 • 5 个月前

THIS GUY TURNED OBSIDIAN INTO A DIGITAL TWIN OF HIS OWN BRAIN, 400 PLUS NODES, 6 KNOWLEDGE CLUSTERS, 1 LOCAL VAULT, AND A MAP THAT GETS SMARTER WITH EVERY NOTE 00:05 the graph begins as one dense sphere, then individual paths light up across the screen, showing how a single note can connect to dozens of ideas instead of disappearing inside another folder. most people store information in straight lines, one file after another. his vault grows like a network, research connects to projects, projects connect to decisions, and old notes keep feeding new work months later. after 100 notes, it still feels like storage. around 300, clusters begin exposing repeated interests, unfinished threads, and topics that keep returning even after he stops thinking about them. with claude connected, the network becomes usable context. instead of pasting 20 files into one chat, an agent can follow 5 linked notes, pull original sources, compare old decisions, and write the result back into the same vault. a real second brain is not the pretty graph. it is a local system where every new thought strengthens old connections, buried ideas come back when needed, and knowledge keeps compounding without leaving your machine.

THIS GUY TURNED OBSIDIAN INTO A DIGITAL TWIN OF HIS OWN BRAIN, 400 PLUS NODES, 6 KNOWLEDGE CLUSTERS, 1 LOCAL VAULT, AND A MAP THAT GETS SMARTER WITH EVERY NOTE 00:05 the graph begins as one dense sphere, then individual paths light up across the screen, showing how a single note can connect to dozens of ideas instead of disappearing inside another folder. most people store information in straight lines, one file after another. his vault grows like a network, research connects to projects, projects connect to decisions, and old notes keep feeding new work months later. after 100 notes, it still feels like storage. around 300, clusters begin exposing repeated interests, unfinished threads, and topics that keep returning even after he stops thinking about them. with claude connected, the network becomes usable context. instead of pasting 20 files into one chat, an agent can follow 5 linked notes, pull original sources, compare old decisions, and write the result back into the same vault. a real second brain is not the pretty graph. it is a local system where every new thought strengthens old connections, buried ideas come back when needed, and knowledge keeps compounding without leaving your machine.

Gipp 🦅

20,823 次观看 • 1 个月前

This guy built a trading bot with Claude and made $87,000 on Polymarket His bot trades the microstructure of short-term crypto Up/Down markets using high-frequency scalping, with elements of swing arbitrage and hedged trading His strategy is simple: > Compares the underlying asset price with the price on Polymarket and trades mispricings > First buys one side, then after the price moves, buys the opposite side so that Up + Down stays below $1 > Uses asymmetric sizing: small size on cheap tails, while most of the volume goes into the 60-97c range This guy’s Polymarket account: Using this strategy and clean execution, he turned $19.7k into $87.1k in one month of trading

This guy built a trading bot with Claude and made $87,000 on Polymarket His bot trades the microstructure of short-term crypto Up/Down markets using high-frequency scalping, with elements of swing arbitrage and hedged trading His strategy is simple: > Compares the underlying asset price with the price on Polymarket and trades mispricings > First buys one side, then after the price moves, buys the opposite side so that Up + Down stays below $1 > Uses asymmetric sizing: small size on cheap tails, while most of the volume goes into the 60-97c range This guy’s Polymarket account: Using this strategy and clean execution, he turned $19.7k into $87.1k in one month of trading

VALIX

21,254 次观看 • 2 个月前

WOAH 🚨 MASSIVE Democrats ActBlue money laundering scam uncovered Democrats are pretending to buy $200,000 houses and CREATING $200 MILLION DOLLAR MORTGAGES and then laundering the money through wire transfers This isn’t uncommon, THEY’RE FOUND ALL OVER THE NATION RAN THROUGH ACTBLUE “Magic mortgages — Let's imagine you buy a house — for $200,000 and it's funded by one of the North American banks. We'll just say Wells Fargo, please don't sue me. All the records, including the mortgage, the deed of trust, the Alta insurance policy, all of those records are recorded in the county record. Then just a few minutes later, your $200,000 house suddenly has a $200 million magic mortgage that comes through. It's nothing but a wire that goes through the title company. There's no lender involved because it's a hard money loan, what they call a cash hard money loan. But because it goes through a title company, there's no notation of who the lender is and it goes on through the system. Now what's interesting is, and this is what caught our attention, these are ActBlue officers, corporate officers. Once we found one, it led to another and, and another, and another and another. So we have them all over the nation. And this is just one small fragment of the human map. You leave this digital dust, if you will. This is one small fragment.“ Democrats ActBlue Magic Mortgage Money Laundering Scheme: This is one of the many ways Democrats launder Dark Money

WOAH 🚨 MASSIVE Democrats ActBlue money laundering scam uncovered Democrats are pretending to buy $200,000 houses and CREATING $200 MILLION DOLLAR MORTGAGES and then laundering the money through wire transfers This isn’t uncommon, THEY’RE FOUND ALL OVER THE NATION RAN THROUGH ACTBLUE “Magic mortgages — Let's imagine you buy a house — for $200,000 and it's funded by one of the North American banks. We'll just say Wells Fargo, please don't sue me. All the records, including the mortgage, the deed of trust, the Alta insurance policy, all of those records are recorded in the county record. Then just a few minutes later, your $200,000 house suddenly has a $200 million magic mortgage that comes through. It's nothing but a wire that goes through the title company. There's no lender involved because it's a hard money loan, what they call a cash hard money loan. But because it goes through a title company, there's no notation of who the lender is and it goes on through the system. Now what's interesting is, and this is what caught our attention, these are ActBlue officers, corporate officers. Once we found one, it led to another and, and another, and another and another. So we have them all over the nation. And this is just one small fragment of the human map. You leave this digital dust, if you will. This is one small fragment.“ Democrats ActBlue Magic Mortgage Money Laundering Scheme: This is one of the many ways Democrats launder Dark Money

Wall Street Apes

1,077,024 次观看 • 1 年前

i merged all my AI agents into one brain Claude Code, Codex, Gemini: one team, one memory, zero re-briefing result: 8+ hours a week back, and every agent already knows my projects, my clients and how i think here's the setup with Jarvix: 1. dump your context once: projects, clients, writing style, how you make decisions.. it builds your personal model from your actual AI interactions 2. switch agents mid-task with zero re-briefing: Claude Code builds, Codex reviews, Gemini researches, all reading the same context 3. it carries what YOU choose across sessions.. never start a chat from zero again 4. when it's time to act, it pulls the right agents together as one team instead of five separate assistants the unlock isn't another agent. it's that your context finally travels agents without shared memory are five interns on their first day, forever. agents with it are a team that's worked with you for years not more agents. one shared context that's the right bet P.S. thanks to the Jarvix team for the early access

i merged all my AI agents into one brain Claude Code, Codex, Gemini: one team, one memory, zero re-briefing result: 8+ hours a week back, and every agent already knows my projects, my clients and how i think here's the setup with Jarvix: 1. dump your context once: projects, clients, writing style, how you make decisions.. it builds your personal model from your actual AI interactions 2. switch agents mid-task with zero re-briefing: Claude Code builds, Codex reviews, Gemini researches, all reading the same context 3. it carries what YOU choose across sessions.. never start a chat from zero again 4. when it's time to act, it pulls the right agents together as one team instead of five separate assistants the unlock isn't another agent. it's that your context finally travels agents without shared memory are five interns on their first day, forever. agents with it are a team that's worked with you for years not more agents. one shared context that's the right bet P.S. thanks to the Jarvix team for the early access

Ronin

15,071 次观看 • 27 天前

Most traders don’t fail because of strategy. They fail because they don’t see what they’re doing wrong. In real time. After being on a real trading floor and competing at a high level, one thing became clear: Awareness beats strategy. That’s why we built a full system: - A journal that tracks every trade automatically - An AI coach that analyzes your behavior - A community with live analysis and full transparency - And the ability to run our strategy as a bot Everything connected. Everything based on real data. If you’re serious about improving, you should be inside. Free Telegram group:

Most traders don’t fail because of strategy. They fail because they don’t see what they’re doing wrong. In real time. After being on a real trading floor and competing at a high level, one thing became clear: Awareness beats strategy. That’s why we built a full system: - A journal that tracks every trade automatically - An AI coach that analyzes your behavior - A community with live analysis and full transparency - And the ability to run our strategy as a bot Everything connected. Everything based on real data. If you’re serious about improving, you should be inside. Free Telegram group:

Merlijn The Trader

45,582 次观看 • 4 个月前

I used to spend hours generating fashion visuals one image at a time. And no matter how good they looked… something always felt off. Because real campaigns aren’t isolated shots. They’re systems. So I changed how I think. Instead of creating images, I built a workflow in FLORA that turns one outfit into a full campaign ,consistent, connected, intentional. This video is literally how my brain works now. Watch with sound 👀 FLORA © #FLORATechnique

I used to spend hours generating fashion visuals one image at a time. And no matter how good they looked… something always felt off. Because real campaigns aren’t isolated shots. They’re systems. So I changed how I think. Instead of creating images, I built a workflow in FLORA that turns one outfit into a full campaign ,consistent, connected, intentional. This video is literally how my brain works now. Watch with sound 👀 FLORA © #FLORATechnique

Zazzy

364,455 次观看 • 4 个月前

Robinhood already has the audience Ansem views Robinhood's existing user base as the key variable behind the chain's potential. "If they figure out a way for the Robinhood app users to be more active on the Robinhood chain..." "They have like the same amount of user base and they're also degens." "The Robinhood people made a ton of money on Dogecoin." Coinbase had a massive distribution advantage through its main app, yet Base required a separate effort to turn that audience into active onchain users. Robinhood starts with a user base already familiar with trading and speculation. Its retail audience also experienced one of crypto's biggest meme cycles through Dogecoin, creating an existing connection between the platform and onchain style trading. If Robinhood can convert that existing trading behavior into activity on its own chain, the network could gain a powerful distribution advantage from day one. The chain already has access to the audience. The real opportunity is turning that audience into onchain users. w/ Ansem 🐂🀄️

Robinhood already has the audience Ansem views Robinhood's existing user base as the key variable behind the chain's potential. "If they figure out a way for the Robinhood app users to be more active on the Robinhood chain..." "They have like the same amount of user base and they're also degens." "The Robinhood people made a ton of money on Dogecoin." Coinbase had a massive distribution advantage through its main app, yet Base required a separate effort to turn that audience into active onchain users. Robinhood starts with a user base already familiar with trading and speculation. Its retail audience also experienced one of crypto's biggest meme cycles through Dogecoin, creating an existing connection between the platform and onchain style trading. If Robinhood can convert that existing trading behavior into activity on its own chain, the network could gain a powerful distribution advantage from day one. The chain already has access to the audience. The real opportunity is turning that audience into onchain users. w/ Ansem 🐂🀄️

Kaiz 🐂🀄️

24,658 次观看 • 17 天前

CLAUDE BUILT ME 10 TRADING BOTS IN 34 MINUTES. +$788 IN 3 DAYS. I gave each one $300 and said - compete. One prompt. Ten strategies. Each bot - a separate agent on Claude API. Its own system prompt, its own decision logic, its own risk management. Newsreader - parses RSS + NewsAPI, runs every headline through Claude with the prompt "rate market impact from 1 to 10". Above 7 - enters. 10-15 trades a day. Never sleeps. $300 -> $368 Arbitrage - finds broken logic between linked markets. One says 40%, a related one says 15%. Calculates conditional probability, finds the gap - enters quietly. $300 -> $427 Contrarian - monitors volume. When 80%+ of money is on one side - takes the opposite. Kelly criterion cuts position size. Hates consensus. $300 -> $234 Sniper - 2-3 trades per day max. Claude calculates expected value for each market. Only when edge is above 25% and model confidence is 8/10 - enters. Rest of the time - silence. $300 -> $536 Reader - RAG pipeline. Eats SEC filings, CBO reports, Fed minutes. Splits into chunks, embeds, searches for contradictions with current prices. 400 pages per minute. $300 -> $493 Whale Hunter - parses on-chain data through Dune API. Tracks wallets with 70%+ win rate. When someone drops $50K+ into a position at 3:00 AM - follows. No questions. $300 -> $412 Scalper - microtrades through CLOB API. 30-40 a day. Catches 2-3 cent moves on bid-ask spreads. $300 -> $271 Calendar - only trades events with a known date. Elections, Fed meetings, court rulings. Pulls historical data on similar events, calculates base rate. No deadline - not interested. $300 -> $389 Sentiment - sentiment analysis. Collects posts from Twitter API, Reddit, Telegram. Calculates positive/negative ratio, compares to price. Everyone panics - buys. $300 -> $197 Copycat - monitors signals from the other nine through a shared JSON. No strategy of its own. Waits until 3+ bots agree - copies with double size. Ensemble model in one line of code. $300 -> $461 +$788 in 3 days. Ten bots. One prompt. Zero emotions.

CLAUDE BUILT ME 10 TRADING BOTS IN 34 MINUTES. +$788 IN 3 DAYS. I gave each one $300 and said - compete. One prompt. Ten strategies. Each bot - a separate agent on Claude API. Its own system prompt, its own decision logic, its own risk management. Newsreader - parses RSS + NewsAPI, runs every headline through Claude with the prompt "rate market impact from 1 to 10". Above 7 - enters. 10-15 trades a day. Never sleeps. $300 -> $368 Arbitrage - finds broken logic between linked markets. One says 40%, a related one says 15%. Calculates conditional probability, finds the gap - enters quietly. $300 -> $427 Contrarian - monitors volume. When 80%+ of money is on one side - takes the opposite. Kelly criterion cuts position size. Hates consensus. $300 -> $234 Sniper - 2-3 trades per day max. Claude calculates expected value for each market. Only when edge is above 25% and model confidence is 8/10 - enters. Rest of the time - silence. $300 -> $536 Reader - RAG pipeline. Eats SEC filings, CBO reports, Fed minutes. Splits into chunks, embeds, searches for contradictions with current prices. 400 pages per minute. $300 -> $493 Whale Hunter - parses on-chain data through Dune API. Tracks wallets with 70%+ win rate. When someone drops $50K+ into a position at 3:00 AM - follows. No questions. $300 -> $412 Scalper - microtrades through CLOB API. 30-40 a day. Catches 2-3 cent moves on bid-ask spreads. $300 -> $271 Calendar - only trades events with a known date. Elections, Fed meetings, court rulings. Pulls historical data on similar events, calculates base rate. No deadline - not interested. $300 -> $389 Sentiment - sentiment analysis. Collects posts from Twitter API, Reddit, Telegram. Calculates positive/negative ratio, compares to price. Everyone panics - buys. $300 -> $197 Copycat - monitors signals from the other nine through a shared JSON. No strategy of its own. Waits until 3+ bots agree - copies with double size. Ensemble model in one line of code. $300 -> $461 +$788 in 3 days. Ten bots. One prompt. Zero emotions.

zostaff

118,475 次观看 • 4 个月前

If your Uber driver asked what Flare ☀️ is, you could simply tell them: "It’s a layer one chain that treats data like a first-class citizen" Co-Founder Hugo Philion ☀️ and the team at Flare aren’t just decentralizing data access - they’re rethinking how it's validated, scaled, and used across all corners of web3. With price feeds, cross-chain event data, and web2 inputs built into the network itself, every validator is also a data oracle. It’s not just another smart contract chain. It’s infrastructure for a more connected, data-native DeFi world.

If your Uber driver asked what Flare ☀️ is, you could simply tell them: "It’s a layer one chain that treats data like a first-class citizen" Co-Founder Hugo Philion ☀️ and the team at Flare aren’t just decentralizing data access - they’re rethinking how it's validated, scaled, and used across all corners of web3. With price feeds, cross-chain event data, and web2 inputs built into the network itself, every validator is also a data oracle. It’s not just another smart contract chain. It’s infrastructure for a more connected, data-native DeFi world.

MR SHIFT 🦁

16,788 次观看 • 10 个月前

Everyone's racing to build the next copytrading bot coldvision took a different approach. Instead of copying traders, we built a system to expose who's copying who. Louvain clustering. Jaccard similarity. 300 top Polymarket wallets mapped into a hypergraph The result? Most "alpha traders" aren't independent, more like nodes in one massive interconnected swarm. But what's catchy: A disconnected cyan cluster. 9 wallets. 60% similarity scores. Trading crypto markets in near-perfect sync. Completely separated from the mother graph. The hivemind is now visible.

Everyone's racing to build the next copytrading bot coldvision took a different approach. Instead of copying traders, we built a system to expose who's copying who. Louvain clustering. Jaccard similarity. 300 top Polymarket wallets mapped into a hypergraph The result? Most "alpha traders" aren't independent, more like nodes in one massive interconnected swarm. But what's catchy: A disconnected cyan cluster. 9 wallets. 60% similarity scores. Trading crypto markets in near-perfect sync. Completely separated from the mother graph. The hivemind is now visible.

gemchanger

433,724 次观看 • 8 个月前

WOAH 🚨 MASSIVE Democrats ActBlue money laundering scam uncovered Democrats are pretending to buy $200,000 houses and CREATING $200 MILLION DOLLAR MORTGAGES and then laundering the money through wire transfers This isn’t uncommon, THEY’RE FOUND ALL OVER THE NATION RAN THROUGH ACTBLUE “Magic mortgages — Let's imagine you buy a house — for $200,000 and it's funded by one of the North American banks. We'll just say Wells Fargo, please don't sue me. All the records, including the mortgage, the deed of trust, the Alta insurance policy, all of those records are recorded in the county record. Then just a few minutes later, your $200,000 house suddenly has a $200 million magic mortgage that comes through. It's nothing but a wire that goes through the title company. There's no lender involved because it's a hard money loan, what they call a cash hard money loan. But because it goes through a title company, there's no notation of who the lender is and it goes on through the system. Now what's interesting is, and this is what caught our attention, these are ActBlue officers, corporate officers. Once we found one, it led to another and, and another, and another and another. So we have them all over the nation. And this is just one small fragment of the human map. You leave this digital dust, if you will. This is one small fragment.“ This is one of the many ways Democrats launder Dark Money And to explain this in ver simple terms that makes this easy to understand, - Democrats have homes that aren’t very expensive - They take out massive loans against these homes, this happens around election cycles - Now they have tons of money for their campaigns It’s fraud

WOAH 🚨 MASSIVE Democrats ActBlue money laundering scam uncovered Democrats are pretending to buy $200,000 houses and CREATING $200 MILLION DOLLAR MORTGAGES and then laundering the money through wire transfers This isn’t uncommon, THEY’RE FOUND ALL OVER THE NATION RAN THROUGH ACTBLUE “Magic mortgages — Let's imagine you buy a house — for $200,000 and it's funded by one of the North American banks. We'll just say Wells Fargo, please don't sue me. All the records, including the mortgage, the deed of trust, the Alta insurance policy, all of those records are recorded in the county record. Then just a few minutes later, your $200,000 house suddenly has a $200 million magic mortgage that comes through. It's nothing but a wire that goes through the title company. There's no lender involved because it's a hard money loan, what they call a cash hard money loan. But because it goes through a title company, there's no notation of who the lender is and it goes on through the system. Now what's interesting is, and this is what caught our attention, these are ActBlue officers, corporate officers. Once we found one, it led to another and, and another, and another and another. So we have them all over the nation. And this is just one small fragment of the human map. You leave this digital dust, if you will. This is one small fragment.“ This is one of the many ways Democrats launder Dark Money And to explain this in ver simple terms that makes this easy to understand, - Democrats have homes that aren’t very expensive - They take out massive loans against these homes, this happens around election cycles - Now they have tons of money for their campaigns It’s fraud

Wall Street Apes

424,479 次观看 • 3 个月前