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Told my OpenClaw agent: "Cut my token spend in half without touching output quality"... Woke up 5 hours later. Done. Here's what changed: Two-tier memory - stops loading the entire context on every single request. Bootstrap holds only the critical rules. Everything else lives in MEMORY md, semantic search...

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Lunar

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37,539 просмотров • 6 месяцев назад •via X (Twitter)

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Someone told ClawdBot to build a 6-agent Polymarket trading system while they slept. 6 hours. Not a single question asked. Here’s what it built on its own: Monitoring agent — runs 24/7, spots mispriced markets, writes to memory, sends Telegram alerts instantly Research agent — parses news, X, and macro data every morning before you check your phone Trading agent — reads research memory and executes before the market catches up All on one Gateway, one config file, isolated per agent Copytrade → First week results: 47 mispriced markets captured before Polymarket adjusted 8–12¢ avg edge per position Token cost dropped 3×, from $0.40 → $0.13 per request The entire system is just plain .md text files. Change one line, the agent behaves differently. No deploy. No build. A BOT RESPONDS. AN AGENT EARNS. THIS IS WHAT AGENTIC TRADING ACTUALLY LOOKS LIKE.
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Someone told ClawdBot to build a 6-agent Polymarket trading system while they slept. 6 hours. Not a single question asked. Here’s what it built on its own: Monitoring agent — runs 24/7, spots mispriced markets, writes to memory, sends Telegram alerts instantly Research agent — parses news, X, and macro data every morning before you check your phone Trading agent — reads research memory and executes before the market catches up All on one Gateway, one config file, isolated per agent Copytrade → First week results: 47 mispriced markets captured before Polymarket adjusted 8–12¢ avg edge per position Token cost dropped 3×, from $0.40 → $0.13 per request The entire system is just plain .md text files. Change one line, the agent behaves differently. No deploy. No build. A BOT RESPONDS. AN AGENT EARNS. THIS IS WHAT AGENTIC TRADING ACTUALLY LOOKS LIKE.

Discover

14,679 просмотров • 6 месяцев назад

Someone told ClawdBot to build a 6-agent Polymarket trading system while they slept. 6 hours. Not a single question asked. Here's what it built on its own: > Monitoring agent running 24/7 — spots mispriced markets, writes to memory, pings Telegram instantly > Research agent parsing news, X, and macro data every morning before you check your phone > Trading agent reading the research memory and acting before the market catches up > All of it running on one Gateway, one config file, isolated per agent First week results: - 47 mispriced markets caught before Polymarket adjusted - 8-12c avg entry edge per position - Token cost dropped 3x, from $0.40 to $0.13 per request The whole system is plain .md text files. Change one line, the agent behaves differently. No deploy. No build. A BOT RESPONDS. AN AGENT EARNS. THIS IS WHAT AGENTIC TRADING ACTUALLY LOOKS LIKE.
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Someone told ClawdBot to build a 6-agent Polymarket trading system while they slept. 6 hours. Not a single question asked. Here's what it built on its own: > Monitoring agent running 24/7 — spots mispriced markets, writes to memory, pings Telegram instantly > Research agent parsing news, X, and macro data every morning before you check your phone > Trading agent reading the research memory and acting before the market catches up > All of it running on one Gateway, one config file, isolated per agent First week results: - 47 mispriced markets caught before Polymarket adjusted - 8-12c avg entry edge per position - Token cost dropped 3x, from $0.40 to $0.13 per request The whole system is plain .md text files. Change one line, the agent behaves differently. No deploy. No build. A BOT RESPONDS. AN AGENT EARNS. THIS IS WHAT AGENTIC TRADING ACTUALLY LOOKS LIKE.

0xMarioNawfal

80,450 просмотров • 6 месяцев назад

I told ClawdBot: "build me a 6-agent system for Polymarket that works while I sleep"... 6 hours while i was asleep. Not a single question. Here's what it built: Monitoring agent - runs 24/7, watches Polymarket for mispriced markets. Spots an anomaly - writes to MEMORY md and pings me on Telegram instantly. Research agent - parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I even check my phone. Trading agent - reads the research agent's memory through Gateway, sees the market hasn't reacted yet, acts. Exec tool in gateway mode with a whitelist - no full access on a live server. Watchdog - HEARTBEAT md every 5 minutes: monitoring running, no errors, positions up to date. Something breaks - immediate Telegram message. All of this - one Gateway. One config.json. Isolation via dmScope: per-agent. The token trick: stopped dumping everything into AGENTS md. Critical rules - bootstrap. Try copytrade my bot here: Everything about markets, patterns, past trades - MEMORY md, semantic search pulls it when needed. Token spend dropped 3x, from $0.40/request to $0.13. First week running: - 47 mispriced markets caught before Polymarket adjusted - avg entry edge: 8-12¢ per position - watchdog fired 3 times, caught a broken RPC before it cost me anything The whole system is plain .md text files. Open an editor, change one line - agent behaves differently. No deploy. No build. A bot responds. An agent earns.
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I told ClawdBot: "build me a 6-agent system for Polymarket that works while I sleep"... 6 hours while i was asleep. Not a single question. Here's what it built: Monitoring agent - runs 24/7, watches Polymarket for mispriced markets. Spots an anomaly - writes to MEMORY md and pings me on Telegram instantly. Research agent - parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I even check my phone. Trading agent - reads the research agent's memory through Gateway, sees the market hasn't reacted yet, acts. Exec tool in gateway mode with a whitelist - no full access on a live server. Watchdog - HEARTBEAT md every 5 minutes: monitoring running, no errors, positions up to date. Something breaks - immediate Telegram message. All of this - one Gateway. One config.json. Isolation via dmScope: per-agent. The token trick: stopped dumping everything into AGENTS md. Critical rules - bootstrap. Try copytrade my bot here: Everything about markets, patterns, past trades - MEMORY md, semantic search pulls it when needed. Token spend dropped 3x, from $0.40/request to $0.13. First week running: - 47 mispriced markets caught before Polymarket adjusted - avg entry edge: 8-12¢ per position - watchdog fired 3 times, caught a broken RPC before it cost me anything The whole system is plain .md text files. Open an editor, change one line - agent behaves differently. No deploy. No build. A bot responds. An agent earns.

Lunar

165,099 просмотров • 6 месяцев назад

Met my girlfriend's parents for the first time. Her dad asked what I do for work. I said I build trading systems. He said like Wall Street? I said no. 6 AI agents. They work while I sleep. He laughed. So robots are making you money? I did not argue. I opened my laptop. Showed him the terminal. 6 agents running. 47 mispriced markets caught in the first week alone. His face changed. That is not gambling. That is automation? Exactly. Then I showed him how it works. Built the whole thing in 6 hours. Agent 1: Monitoring Runs 24/7. Watches Polymarket for mispriced markets. Spots an anomaly. Writes to memory and pings me on Telegram instantly. Agent 2: Research Parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I check my phone. Agent 3: Trading Reads the research agent memory. Sees the market has not reacted yet. Acts. Execution tool in gateway mode with a whitelist. No full access on a live server. Agent 4: Watchdog Heartbeat every 5 minutes. Monitoring running. No errors. Positions up to date. Something breaks. Immediate Telegram message. All of this. One Gateway. One config file. Isolation via per-agent scope. The token trick: stopped dumping everything into one file. Critical rules in bootstrap. Markets, patterns, past trades in memory. Semantic search pulls it when needed. Token spend dropped 3x. From $0.40 per request to $0.13. First week running: → 47 mispriced markets caught before Polymarket adjusted → Average entry edge 8 to 12 cents per position → Watchdog fired 3 times and caught a broken RPC before it cost me anything The whole system is plain text files. Open an editor. Change one line. Agent behaves differently. No deploy. No build. Her dad went quiet. Then he asked can you teach this? Her mom asked for the setup guide. I built the entire framework. Six agents. Full deployment. Memory architecture. Telegram alerts. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word "Claude" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you Save this post. Deploy the 6-agent system this week. Start with $200. Scale on evidence.
0:16

Met my girlfriend's parents for the first time. Her dad asked what I do for work. I said I build trading systems. He said like Wall Street? I said no. 6 AI agents. They work while I sleep. He laughed. So robots are making you money? I did not argue. I opened my laptop. Showed him the terminal. 6 agents running. 47 mispriced markets caught in the first week alone. His face changed. That is not gambling. That is automation? Exactly. Then I showed him how it works. Built the whole thing in 6 hours. Agent 1: Monitoring Runs 24/7. Watches Polymarket for mispriced markets. Spots an anomaly. Writes to memory and pings me on Telegram instantly. Agent 2: Research Parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I check my phone. Agent 3: Trading Reads the research agent memory. Sees the market has not reacted yet. Acts. Execution tool in gateway mode with a whitelist. No full access on a live server. Agent 4: Watchdog Heartbeat every 5 minutes. Monitoring running. No errors. Positions up to date. Something breaks. Immediate Telegram message. All of this. One Gateway. One config file. Isolation via per-agent scope. The token trick: stopped dumping everything into one file. Critical rules in bootstrap. Markets, patterns, past trades in memory. Semantic search pulls it when needed. Token spend dropped 3x. From $0.40 per request to $0.13. First week running: → 47 mispriced markets caught before Polymarket adjusted → Average entry edge 8 to 12 cents per position → Watchdog fired 3 times and caught a broken RPC before it cost me anything The whole system is plain text files. Open an editor. Change one line. Agent behaves differently. No deploy. No build. Her dad went quiet. Then he asked can you teach this? Her mom asked for the setup guide. I built the entire framework. Six agents. Full deployment. Memory architecture. Telegram alerts. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word "Claude" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you Save this post. Deploy the 6-agent system this week. Start with $200. Scale on evidence.

Himanshu Kumar

47,275 просмотров • 2 месяцев назад

Every night at 2 AM someone clicks a button and makes $49,000. The wallet is 57 days old. ClawdBot flagged it before my morning coffee. Now I can't stop checking. I showed anoin123 to a friend who trades professionally. He asked if I photoshopped the screenshot. $1,613,408 profit on Polymarket. Not in a year. In under two months. That's hedge fund performance from a browser tab. Dug into the timeline. The entries don't fire randomly. Almost every trade lands between 2-4 AM EST when volume is dead and most traders are asleep. Whatever signal this wallet follows, it only speaks at night. Changed the ClawdBot filter: profit above $500K, wallet age under 90 days. Three results. Total. On the entire platform. Under 20 wallets in Polymarket history have ever crossed $1M. This one did it faster than most people finish a trading course. My quant friend stopped laughing. Now he's asking how to set up alerts. → No - US strikes Iran by February 13, 2026
0:10

Every night at 2 AM someone clicks a button and makes $49,000. The wallet is 57 days old. ClawdBot flagged it before my morning coffee. Now I can't stop checking. I showed anoin123 to a friend who trades professionally. He asked if I photoshopped the screenshot. $1,613,408 profit on Polymarket. Not in a year. In under two months. That's hedge fund performance from a browser tab. Dug into the timeline. The entries don't fire randomly. Almost every trade lands between 2-4 AM EST when volume is dead and most traders are asleep. Whatever signal this wallet follows, it only speaks at night. Changed the ClawdBot filter: profit above $500K, wallet age under 90 days. Three results. Total. On the entire platform. Under 20 wallets in Polymarket history have ever crossed $1M. This one did it faster than most people finish a trading course. My quant friend stopped laughing. Now he's asking how to set up alerts. → No - US strikes Iran by February 13, 2026

Carver

44,466 просмотров • 6 месяцев назад

🚨BREAKING... I gave OpenClaw a choice: turn $500 into $5,000 on Polymarket within 24 hours, or I'd wipe its entire directory and terminate the instance forever NOT engagement bait. NOT fiction If you're trading on Polymarket, READ this carefully So👇 It didn't argue. It didn't ask for clarification Within 50 minutes, it deployed a 4-agent autonomous swarm that found a massive technical "blind spot" in the prediction markets The Strategy: Exploiting the 290ms Latency Gap The edge was pure physics. Chainlink updates Polymarket roughly every 300ms. Binance moves in 10ms. That creates a 290ms window where Polymarket is effectively trading on "stale" data. OpenClaw built a bridge to exploit that lag. The Timeline: - Hour 4: The Fed drops a surprise rate hold. While the Polymarket oracle was still processing, the bot front-ran 3 mispriced BTC markets before the order book could react Balance: $934.78 - Hour 8: Elon posts a cryptic one-word tweet. OpenClaw’s sentiment agent caught the spike 340ms before the first major buy order hit the books Balance: $1,827.49 - Hour 14: It targeted thin ETH/BTC ratio markets. The bot scooped up "Yes" shares at 3¢ across 11 different markets; 7 of them hit a 50:1 payout Balance: $3,475.52 - Hour 18: The pattern recognition kicked in. It identified that every time BTC moved 1.2% in under 4 minutes, the next "YES" market was undervalued by 8-12¢. It looped this trade 31 times without a single miss Balance: $4,296.53 - Hour 24: The dust settled at $5,034.85 I've been running this publicly now so others can follow the same trades in real time If you want in: OpenClaw held up its end of the bargain. I held up mine The delete button stays untouched... for now
0:12

🚨BREAKING... I gave OpenClaw a choice: turn $500 into $5,000 on Polymarket within 24 hours, or I'd wipe its entire directory and terminate the instance forever NOT engagement bait. NOT fiction If you're trading on Polymarket, READ this carefully So👇 It didn't argue. It didn't ask for clarification Within 50 minutes, it deployed a 4-agent autonomous swarm that found a massive technical "blind spot" in the prediction markets The Strategy: Exploiting the 290ms Latency Gap The edge was pure physics. Chainlink updates Polymarket roughly every 300ms. Binance moves in 10ms. That creates a 290ms window where Polymarket is effectively trading on "stale" data. OpenClaw built a bridge to exploit that lag. The Timeline: - Hour 4: The Fed drops a surprise rate hold. While the Polymarket oracle was still processing, the bot front-ran 3 mispriced BTC markets before the order book could react Balance: $934.78 - Hour 8: Elon posts a cryptic one-word tweet. OpenClaw’s sentiment agent caught the spike 340ms before the first major buy order hit the books Balance: $1,827.49 - Hour 14: It targeted thin ETH/BTC ratio markets. The bot scooped up "Yes" shares at 3¢ across 11 different markets; 7 of them hit a 50:1 payout Balance: $3,475.52 - Hour 18: The pattern recognition kicked in. It identified that every time BTC moved 1.2% in under 4 minutes, the next "YES" market was undervalued by 8-12¢. It looped this trade 31 times without a single miss Balance: $4,296.53 - Hour 24: The dust settled at $5,034.85 I've been running this publicly now so others can follow the same trades in real time If you want in: OpenClaw held up its end of the bargain. I held up mine The delete button stays untouched... for now

cristal💎

460,335 просмотров • 6 месяцев назад

🚨 Do you understand what Claude just quietly dropped while everyone was distracted? 1 million tokens. Let me explain what that actually means because the number alone doesn't hit right. > A senior engineer joins a company and spends 3 to 6 months just reading code.. Understanding how things connect. Learning where the bugs hide. Why that one file nobody touches exists. It takes months because a codebase is massive and human memory is small. > Claude just loaded the entire thing in one prompt. 30 seconds. Every file, Every function, Every line. All of it. Sitting in memory like it's been working there for years. And it scored highest among every single frontier model. Not GPT.. Not Gemini, Nobody. > Yesterday Amazon's AI nuked production because it couldn't see the full picture - it made a decision with partial context and deleted everything. Today an AI can hold 1 million tokens of context at once. That's the fix. That's the "before and after" moment for AI coding. > 600 images in one request. Entire PDFs. Full repos. And they dropped it on a Friday on all plans like it was a patch note. The scariest AI updates aren't the ones with press conferences. They're the ones that drop in a tweet at 6pm and change everything by Monday morning.
0:15

🚨 Do you understand what Claude just quietly dropped while everyone was distracted? 1 million tokens. Let me explain what that actually means because the number alone doesn't hit right. > A senior engineer joins a company and spends 3 to 6 months just reading code.. Understanding how things connect. Learning where the bugs hide. Why that one file nobody touches exists. It takes months because a codebase is massive and human memory is small. > Claude just loaded the entire thing in one prompt. 30 seconds. Every file, Every function, Every line. All of it. Sitting in memory like it's been working there for years. And it scored highest among every single frontier model. Not GPT.. Not Gemini, Nobody. > Yesterday Amazon's AI nuked production because it couldn't see the full picture - it made a decision with partial context and deleted everything. Today an AI can hold 1 million tokens of context at once. That's the fix. That's the "before and after" moment for AI coding. > 600 images in one request. Entire PDFs. Full repos. And they dropped it on a Friday on all plans like it was a patch note. The scariest AI updates aren't the ones with press conferences. They're the ones that drop in a tweet at 6pm and change everything by Monday morning.

Tuki

206,309 просмотров • 5 месяцев назад

Polymarket introduced new fees to kill bots on 15-minute markets. Result? They just eliminated competition for the two apex predators. These wallets did not just survive. They mutated. While the platform tried to "fix" the system, these two made $918,357 in pure profit in one month. On the fees that were supposed to bankrupt them. Someone on Twitter was complaining his stops get blown at the exact same second every time. Said he was up against HFT bots with direct exchange connections. In the comments someone dropped two profiles. Said here are your "manipulators". Just code. $522,439 profit in one month. $65 million volume. First place on crypto leaderboard. This is not a person. This is PurpleThunderBicycleMountain. His profile: The second profile looked like it could not top the first. 0x8dxd. Second place. $395,918 in the same month. But here is what breaks the brain completely. In December 2025 this wallet had $313. Three hundred thirteen dollars. Now his all-time profit exceeds $658,000. The numbers do not lie. $313 turned into a fortune in six weeks. See for yourself: The mechanics are uncomfortably simple. Both trade the same thing. 15-minute crypto markets. Bitcoin up or down. ETH above or below. Every 15 minutes a new contract. Here is the trick. You look at Polymarket and see 50/50 odds. For you this is a fair coin flip. But these two do not look at Polymarket. They look at Binance. When BTC makes a move on the exchange Polymarket does not know yet. Price already moved. Direction already determined. But odds on the platform still show yesterday. The window lasts 30 seconds. Sometimes 90. It is like playing poker against someone with a mirror behind your back. He already sees your cards. You still think you are bluffing. During this time the bot enters at old prices. Buys YES at 25 cents when real probability is already 80%. Or NO at 1.5 cents when the market already crashed. Then the window closes. Odds catch up to reality. Bot gets $1 for every 25 cents. This is not forecasting. This is harvesting from people staring at a stale screen. One trade stands out. ETH dumped on spot. PurpleThunderBicycleMountain loaded NO at 1.5 cents. Kept buying as price rose to 15 cents. Window closed down. Every share paid $1. 785% in fifteen minutes. On one trade. The craziest part is 0x8dxd stats. Win rate 98%. Out of 6,615 trades. Almost perfect. A human cannot trade like this. A human has shaky hands. A human doubts. A human sleeps. The bot does not sleep. The bot does not doubt. The bot just waits for Binance and Polymarket to diverge for 30 seconds. And takes the difference. Their profit curves both grow without a single pullback. No crashes. No nervous breakdowns. Methodical. Mechanical. Relentless. Polymarket introduced fees to stop this. Result? Small bots died. These two took their market share. A 1.5% fee means nothing when your average return is 300%. Here is what kills. Anyone can spend months learning Python. Rent a server near the exchange. Write an algorithm. Test. Debug. Lose money on mistakes. Or just open their profiles and see what they are buying. The blockchain stores everything. Every position. Every timing. Full history in the open. They spend thousands on infrastructure. Write code for months. Optimize milliseconds. Anyone can just watch where they enter. $918,357 in one month between them. First and second place on the leaderboard. This is not theory. This is a working machine. Right now somewhere BTC is making a move. Polymarket still shows old odds. These two are already entering a position. Only one question remains: Will you be the one selling to them at stale prices? Or the one entering alongside them? In 15 minutes a new contract opens. 14 minutes left.
0:17

Polymarket introduced new fees to kill bots on 15-minute markets. Result? They just eliminated competition for the two apex predators. These wallets did not just survive. They mutated. While the platform tried to "fix" the system, these two made $918,357 in pure profit in one month. On the fees that were supposed to bankrupt them. Someone on Twitter was complaining his stops get blown at the exact same second every time. Said he was up against HFT bots with direct exchange connections. In the comments someone dropped two profiles. Said here are your "manipulators". Just code. $522,439 profit in one month. $65 million volume. First place on crypto leaderboard. This is not a person. This is PurpleThunderBicycleMountain. His profile: The second profile looked like it could not top the first. 0x8dxd. Second place. $395,918 in the same month. But here is what breaks the brain completely. In December 2025 this wallet had $313. Three hundred thirteen dollars. Now his all-time profit exceeds $658,000. The numbers do not lie. $313 turned into a fortune in six weeks. See for yourself: The mechanics are uncomfortably simple. Both trade the same thing. 15-minute crypto markets. Bitcoin up or down. ETH above or below. Every 15 minutes a new contract. Here is the trick. You look at Polymarket and see 50/50 odds. For you this is a fair coin flip. But these two do not look at Polymarket. They look at Binance. When BTC makes a move on the exchange Polymarket does not know yet. Price already moved. Direction already determined. But odds on the platform still show yesterday. The window lasts 30 seconds. Sometimes 90. It is like playing poker against someone with a mirror behind your back. He already sees your cards. You still think you are bluffing. During this time the bot enters at old prices. Buys YES at 25 cents when real probability is already 80%. Or NO at 1.5 cents when the market already crashed. Then the window closes. Odds catch up to reality. Bot gets $1 for every 25 cents. This is not forecasting. This is harvesting from people staring at a stale screen. One trade stands out. ETH dumped on spot. PurpleThunderBicycleMountain loaded NO at 1.5 cents. Kept buying as price rose to 15 cents. Window closed down. Every share paid $1. 785% in fifteen minutes. On one trade. The craziest part is 0x8dxd stats. Win rate 98%. Out of 6,615 trades. Almost perfect. A human cannot trade like this. A human has shaky hands. A human doubts. A human sleeps. The bot does not sleep. The bot does not doubt. The bot just waits for Binance and Polymarket to diverge for 30 seconds. And takes the difference. Their profit curves both grow without a single pullback. No crashes. No nervous breakdowns. Methodical. Mechanical. Relentless. Polymarket introduced fees to stop this. Result? Small bots died. These two took their market share. A 1.5% fee means nothing when your average return is 300%. Here is what kills. Anyone can spend months learning Python. Rent a server near the exchange. Write an algorithm. Test. Debug. Lose money on mistakes. Or just open their profiles and see what they are buying. The blockchain stores everything. Every position. Every timing. Full history in the open. They spend thousands on infrastructure. Write code for months. Optimize milliseconds. Anyone can just watch where they enter. $918,357 in one month between them. First and second place on the leaderboard. This is not theory. This is a working machine. Right now somewhere BTC is making a move. Polymarket still shows old odds. These two are already entering a position. Only one question remains: Will you be the one selling to them at stale prices? Or the one entering alongside them? In 15 minutes a new contract opens. 14 minutes left.

Blaze

61,835 просмотров • 7 месяцев назад

I need to explain something to those followers that don't get my recent X feed. No altcoin made me $2.5 million in 3 weeks. $RAT did. That's why I focus on it. Bitcoin remains important and I will cover it more in the future. However, right now, there is nothing interesting about BTC moving up and down around 100k. On the other hand, RAT will soon be listed on 8 centralized exchanges. Do you know what that means for a token with a $10 mil market cap? If you don't, that's fine. The TLDR is this. RAT will pump. Simple as that. 10x or maybe 100x. We will find out. This is more exciting than watching ETH crash 20% the other day. Or seeing Solana drop under $200 after I told everyone to sell it at $260. I lost all interest in altcoins. My only altcoin focus is MY OWN TOKEN. The one my community and I love. Because it is OURS! It's not owned by some VC. It's owned by OUR community. Do you understand what I am writing here? Believe in something! RAT Escape is that for us. If you can't see the alpha in this post. I can't help you.
0:12

I need to explain something to those followers that don't get my recent X feed. No altcoin made me $2.5 million in 3 weeks. $RAT did. That's why I focus on it. Bitcoin remains important and I will cover it more in the future. However, right now, there is nothing interesting about BTC moving up and down around 100k. On the other hand, RAT will soon be listed on 8 centralized exchanges. Do you know what that means for a token with a $10 mil market cap? If you don't, that's fine. The TLDR is this. RAT will pump. Simple as that. 10x or maybe 100x. We will find out. This is more exciting than watching ETH crash 20% the other day. Or seeing Solana drop under $200 after I told everyone to sell it at $260. I lost all interest in altcoins. My only altcoin focus is MY OWN TOKEN. The one my community and I love. Because it is OURS! It's not owned by some VC. It's owned by OUR community. Do you understand what I am writing here? Believe in something! RAT Escape is that for us. If you can't see the alpha in this post. I can't help you.

Duo Nine ⚡ YCC

22,004 просмотров • 1 год назад

A Citadel quant sat down next to me at Verve on Gough and asked why my laptop had four terminals open I was scanning Polymarket. Four panes. Each one a different agent. He was killing time before a flight. Saw the screens. "Is that a multi-agent setup on prediction markets. Who's orchestrating" Claude. One prompt per agent. They don't share memory. Only a queue file. He pulled up a chair. "Walk me through. I do this for equities at work. I want to see your agent separation" Agent 1 is the scanner. I piped raw JSON from the official Polymarket CLI straight into Claude and told it to score every live market on three things. Edge against my probability estimate. Book depth on both sides. Hours to resolution. Thresholds kill 93% of markets before the brain ever sees them. Edge under 7 cents gone. Depth under $500 gone. Under 4 hours to resolution gone. Over 168 gone. 487 live markets collapse to 35. "Seven cents is your transaction cost buffer" Yes. Below that the gas and spread eat the trade. A green fill popped. +$52 on a BTC dominance market. "And the brain" Agent 2. Runs four checks on every survivor. Base rate from history. News in the last six hours. Whether any of the 47 top wallets are currently holding. And a disposition check - is the crowd making a known cognitive error. Three out of four must agree. Otherwise drop it. 86 million trades. I let Claude rank every wallet with 100+ fills and a 70%+ win rate. It returned 47 names in four minutes. Top 20 wallets made more than the bottom 13,000 combined. "Concentration like that means the signal is there. Most retail books look like a normal curve. Yours looks like power law" Kelly sizing does the rest. Capped at quarter Kelly. If f-star goes negative the trade dies no matter how confident I feel. "Overbet once and the bankroll is gone. You respect that. Good" Agent 3 is execution. Three strategies pulled out of a 53k line Typescript repo. Arbitrage across related markets. Convergence when price moves toward my estimate. Whale copy with a 60 second delay on the 47 wallets. Two agents agree full position. One agent only half. Disagreement no trade. "What did you cut" Sports. 52% win rate. Already priced in before the scanner flags it. Markets under $50k in depth. Slippage makes every edge a coin flip. Holding to settlement. The top wallets exit at 73% of max profit every time. I copied that. Agent 4 watches exits. Three triggers. Target hit at 85% of expected move. Volume spike 3x the ten minute average. Thesis stale 24 hours with no movement. "91% of the smart wallets exit before resolution. That's the trade" Yeah. Being right is not the same as being profitable. Setup: Claude API $20 Hetzner VPS $5 Four repos free Total $25 a month $200 seed. 27 days ago. $14,300 now. 271 trades. 74% win rate. Sharpe 2.47. Copy here: "How long did the build take" Two weekends. One to wire the scanner and the CLI. One to get the agents talking through the queue file. He watched the volume exit trigger fire on a Fed cut market. Position closed at 0.71. +$184. "Nobody at my shop runs four agents on their own money. We run eight on the firm's. You got the same structure on a laptop for the price of a sandwich a month" He asked for the repos. I sent them. He messaged me from the gate. "Publishing this tomorrow. My PM is going to ask me why I didn't do it first" I told him his PM already has a Bloomberg. That's the problem.
0:18

A Citadel quant sat down next to me at Verve on Gough and asked why my laptop had four terminals open I was scanning Polymarket. Four panes. Each one a different agent. He was killing time before a flight. Saw the screens. "Is that a multi-agent setup on prediction markets. Who's orchestrating" Claude. One prompt per agent. They don't share memory. Only a queue file. He pulled up a chair. "Walk me through. I do this for equities at work. I want to see your agent separation" Agent 1 is the scanner. I piped raw JSON from the official Polymarket CLI straight into Claude and told it to score every live market on three things. Edge against my probability estimate. Book depth on both sides. Hours to resolution. Thresholds kill 93% of markets before the brain ever sees them. Edge under 7 cents gone. Depth under $500 gone. Under 4 hours to resolution gone. Over 168 gone. 487 live markets collapse to 35. "Seven cents is your transaction cost buffer" Yes. Below that the gas and spread eat the trade. A green fill popped. +$52 on a BTC dominance market. "And the brain" Agent 2. Runs four checks on every survivor. Base rate from history. News in the last six hours. Whether any of the 47 top wallets are currently holding. And a disposition check - is the crowd making a known cognitive error. Three out of four must agree. Otherwise drop it. 86 million trades. I let Claude rank every wallet with 100+ fills and a 70%+ win rate. It returned 47 names in four minutes. Top 20 wallets made more than the bottom 13,000 combined. "Concentration like that means the signal is there. Most retail books look like a normal curve. Yours looks like power law" Kelly sizing does the rest. Capped at quarter Kelly. If f-star goes negative the trade dies no matter how confident I feel. "Overbet once and the bankroll is gone. You respect that. Good" Agent 3 is execution. Three strategies pulled out of a 53k line Typescript repo. Arbitrage across related markets. Convergence when price moves toward my estimate. Whale copy with a 60 second delay on the 47 wallets. Two agents agree full position. One agent only half. Disagreement no trade. "What did you cut" Sports. 52% win rate. Already priced in before the scanner flags it. Markets under $50k in depth. Slippage makes every edge a coin flip. Holding to settlement. The top wallets exit at 73% of max profit every time. I copied that. Agent 4 watches exits. Three triggers. Target hit at 85% of expected move. Volume spike 3x the ten minute average. Thesis stale 24 hours with no movement. "91% of the smart wallets exit before resolution. That's the trade" Yeah. Being right is not the same as being profitable. Setup: Claude API $20 Hetzner VPS $5 Four repos free Total $25 a month $200 seed. 27 days ago. $14,300 now. 271 trades. 74% win rate. Sharpe 2.47. Copy here: "How long did the build take" Two weekends. One to wire the scanner and the CLI. One to get the agents talking through the queue file. He watched the volume exit trigger fire on a Fed cut market. Position closed at 0.71. +$184. "Nobody at my shop runs four agents on their own money. We run eight on the firm's. You got the same structure on a laptop for the price of a sandwich a month" He asked for the repos. I sent them. He messaged me from the gate. "Publishing this tomorrow. My PM is going to ask me why I didn't do it first" I told him his PM already has a Bloomberg. That's the problem.

Lunar

29,547 просмотров • 4 месяцев назад

I spent 6 months studying Polymarket. Yesterday I realized I was playing chess against people who know my moves in advance. It all started with a simple question: why are some wallets consistently in profit and I'm not? I read the same news. Watched the same debates. Analyzed the same statistics. But they entered the market hours before the news became news. I found a cluster of 12 wallets. They share one thing: they buy when the price hasn't moved yet. And sell when the crowd is just starting to enter. One of them started with $288. Now the account has $666K. No loud trades. No screenshots all over Twitter. Just methodical work. Entry after entry. Week after week. I scrolled through his history and didn't find a single heroic trade. Not one bet that made half the profit. The capital curve is almost a straight line up. While everyone is looking for one trade that will change their life this wallet quietly collects bit by bit. And bit by bit turned into $666K. I started breaking down where they get their information. And realized: they don't predict. They're just closer to the source. Three levels of the food chain on Polymarket: First circle. People who know the journalist personally. Know the article comes out tomorrow morning. Position opened tonight. Second circle. People who see the first circle's activity. Notice that large wallets started moving. Enter right behind. Still before the news. Third circle. You. Read the headline on Twitter. Open Polymarket. Price already moved 40%. Think maybe it'll go higher. Buy at the peak. Guess who's selling you that position? The first two circles. Platform statistics: 84% of traders lose money. That money doesn't disappear. It flows to the remaining 16%. I spent six months trying to get into that 16% through analysis and research. Then I looked at my P&L. And realized the obvious: I will never be in the first circle. I don't have journalist friends. No sources in candidate teams. No insider info. But I can be in the second. You don't need to know what will happen. You need to see who already started moving. Their wallets are public. Their positions are visible to everyone. Their entries can be tracked in real time and copied automatically → Copy the winners: They spend years building connections. You spend seconds copying their trade. They risk reputation and money. You only risk time on setup. I deleted all my indicators. Closed all news tabs. Stopped watching debates. Now I only watch one thing: where the wallets that don't lose are moving. On this market there are two places: Either you're the liquidity being drained. Or you're the shadow of the one draining. Stop being the third circle.
0:13

I spent 6 months studying Polymarket. Yesterday I realized I was playing chess against people who know my moves in advance. It all started with a simple question: why are some wallets consistently in profit and I'm not? I read the same news. Watched the same debates. Analyzed the same statistics. But they entered the market hours before the news became news. I found a cluster of 12 wallets. They share one thing: they buy when the price hasn't moved yet. And sell when the crowd is just starting to enter. One of them started with $288. Now the account has $666K. No loud trades. No screenshots all over Twitter. Just methodical work. Entry after entry. Week after week. I scrolled through his history and didn't find a single heroic trade. Not one bet that made half the profit. The capital curve is almost a straight line up. While everyone is looking for one trade that will change their life this wallet quietly collects bit by bit. And bit by bit turned into $666K. I started breaking down where they get their information. And realized: they don't predict. They're just closer to the source. Three levels of the food chain on Polymarket: First circle. People who know the journalist personally. Know the article comes out tomorrow morning. Position opened tonight. Second circle. People who see the first circle's activity. Notice that large wallets started moving. Enter right behind. Still before the news. Third circle. You. Read the headline on Twitter. Open Polymarket. Price already moved 40%. Think maybe it'll go higher. Buy at the peak. Guess who's selling you that position? The first two circles. Platform statistics: 84% of traders lose money. That money doesn't disappear. It flows to the remaining 16%. I spent six months trying to get into that 16% through analysis and research. Then I looked at my P&L. And realized the obvious: I will never be in the first circle. I don't have journalist friends. No sources in candidate teams. No insider info. But I can be in the second. You don't need to know what will happen. You need to see who already started moving. Their wallets are public. Their positions are visible to everyone. Their entries can be tracked in real time and copied automatically → Copy the winners: They spend years building connections. You spend seconds copying their trade. They risk reputation and money. You only risk time on setup. I deleted all my indicators. Closed all news tabs. Stopped watching debates. Now I only watch one thing: where the wallets that don't lose are moving. On this market there are two places: Either you're the liquidity being drained. Or you're the shadow of the one draining. Stop being the third circle.

Blaze

11,624 просмотров • 7 месяцев назад

Claude and a free weather API will earn you $100k+. Success rate for beginners: 80%. Complete guide and algorithm for building Polymarket weather trading bot. Simple logic, a low entry budget and high ROI -that’s why weather bots are so clean. Onchain proof these bots exist: 1st bot: 2nd bot: I verified their profitability by myself copying every trade - each bot's win rate over time ranges from 80 to 90%. I grew my starting capital by +40% in just one week. You can copy their trades and see for yourself in two clicks through this bot: The alpha is simple: you're not trading weather. You're trading other people's ignorance. Gap between what the crowd prices and what 51 ensemble models say. Polymarket asks: "Will Atlanta hit 95°F tomorrow?" Normies bet on vibes. You bet on math. The core tool: Open-Meteo API. Free. No key needed. 51-model ensemble. Clean JSON. Cooked and ready. Update every 30 min. Hardcode your city coordinates - don't waste time on geocoding at runtime. This single endpoint beats most paid tools for what Polymarket actually needs. The edge in one sentence: Market is heavy on 16°C. Your 51-model ensemble points at 19°C. That's your trade. Find that gap systematically across every city market, every day - and you have a scanner. That's what separates consistent traders from gamblers. How to start: - Week 1: Open-Meteo + tropicaltidbits. Pick one city market. Track model vs market price daily. Don't trade yet — just watch where you'd have been right. - Weeks 2–3: Automate the pull. Log ensemble divergences. Build the scanner. - Week 4: Now you have an edge. Trade it. Most people want to skip to week 4. That's exactly why most people lose. Now you have the algorithm framework plus a complete guide to get started. All that's left is to actually do it. Bookmark this post so you can come back to it when you start building the bot.
0:14

Claude and a free weather API will earn you $100k+. Success rate for beginners: 80%. Complete guide and algorithm for building Polymarket weather trading bot. Simple logic, a low entry budget and high ROI -that’s why weather bots are so clean. Onchain proof these bots exist: 1st bot: 2nd bot: I verified their profitability by myself copying every trade - each bot's win rate over time ranges from 80 to 90%. I grew my starting capital by +40% in just one week. You can copy their trades and see for yourself in two clicks through this bot: The alpha is simple: you're not trading weather. You're trading other people's ignorance. Gap between what the crowd prices and what 51 ensemble models say. Polymarket asks: "Will Atlanta hit 95°F tomorrow?" Normies bet on vibes. You bet on math. The core tool: Open-Meteo API. Free. No key needed. 51-model ensemble. Clean JSON. Cooked and ready. Update every 30 min. Hardcode your city coordinates - don't waste time on geocoding at runtime. This single endpoint beats most paid tools for what Polymarket actually needs. The edge in one sentence: Market is heavy on 16°C. Your 51-model ensemble points at 19°C. That's your trade. Find that gap systematically across every city market, every day - and you have a scanner. That's what separates consistent traders from gamblers. How to start: - Week 1: Open-Meteo + tropicaltidbits. Pick one city market. Track model vs market price daily. Don't trade yet — just watch where you'd have been right. - Weeks 2–3: Automate the pull. Log ensemble divergences. Build the scanner. - Week 4: Now you have an edge. Trade it. Most people want to skip to week 4. That's exactly why most people lose. Now you have the algorithm framework plus a complete guide to get started. All that's left is to actually do it. Bookmark this post so you can come back to it when you start building the bot.

cvxv666

50,799 просмотров • 4 месяцев назад

here's how the whole thing works. claude code doesn't care what's behind the API. it just sends requests and expects responses. so i pointed it at my own machine instead of anthropic's servers. llama-server runs the model locally. LiteLLM sits in between and translates the API format. claude code thinks it's talking to claude. it's talking to qwen on localhost. the setup: 2x 3090s, 38 layers on GPU, 10 on CPU. 128K context window. generation is only 7 tok/s but the tradeoff is worth it. 128K means the agent can hold an entire project in memory without losing context midtask. claude code alone loads a 17.5K token system prompt on every request. tool definitions, safety rules, agent behavior. that's your baseline before you even say hello. pushed as far as i could tonight. what surprised me most wasn't the speed. it was the iteration quality. first prompt gave me a working particle sim. second prompt, the model read its own 564 lines, understood the architecture, and added trails, explosions, gravity wells, bloom effects. no handholding. 4bit quantized. 45GB on two consumer cards. running a full coding agent autonomously. detailed article coming. full benchmarks, hardware breakdowns, engine debugging, code quality. everything from setup to what broke and why.
0:12

here's how the whole thing works. claude code doesn't care what's behind the API. it just sends requests and expects responses. so i pointed it at my own machine instead of anthropic's servers. llama-server runs the model locally. LiteLLM sits in between and translates the API format. claude code thinks it's talking to claude. it's talking to qwen on localhost. the setup: 2x 3090s, 38 layers on GPU, 10 on CPU. 128K context window. generation is only 7 tok/s but the tradeoff is worth it. 128K means the agent can hold an entire project in memory without losing context midtask. claude code alone loads a 17.5K token system prompt on every request. tool definitions, safety rules, agent behavior. that's your baseline before you even say hello. pushed as far as i could tonight. what surprised me most wasn't the speed. it was the iteration quality. first prompt gave me a working particle sim. second prompt, the model read its own 564 lines, understood the architecture, and added trails, explosions, gravity wells, bloom effects. no handholding. 4bit quantized. 45GB on two consumer cards. running a full coding agent autonomously. detailed article coming. full benchmarks, hardware breakdowns, engine debugging, code quality. everything from setup to what broke and why.

Sudo su

37,623 просмотров • 6 месяцев назад

how to build Polymarket "always buy NO" bot +$200-400/day PnL if you pick the right markets​ everyone overcomplicates this. the "NO-maxi bot" strategy is literally: buy NO on outcomes that are structurally overpriced, wait for reality to catch up.​ the part that matters isn't "genius insight", it's picking the right markets plus execution.​ where the +$200-400/day comes from it's not betting "no" everywhere. it's selectively loading up NO on multi-outcome ladders (FDV ranges, price targets, user metrics) where the top brackets are CT dreams priced way too rich.​ if you're consistently capturing 5-15% edge per cycle across 20-30 outcomes and actually getting fills, +$200-400/day is just position sizing plus discipline.​ first, the edge (why this isn't a meme) polytrackhq research shows $40M+ arb profits from 86M trades came from exploiting pricing errors. "NO-maxi" is the retail version of the same logic on overhyped brackets.​ so the goal is simple: find multi-outcome markets with fat tails, skip the base case, load NO on the fantasy brackets, let time and reality work.​ what you actually need (minimal) Python plus official py-clob-client (standard for Polymarket orders). Telegram bot for alerts (don't stare at screen). VPS so it runs 24/7 (don't run from laptop). where people mess up: they try "always NO" on everything and get wrecked by the one outcome that hits. pick markets with obvious "dream vs reality" skew.​ the bot loop (in plain English) Pull multi-outcome markets (FDV ladders, price targets). For each outcome: check if YES price exceeds realistic probability.​ Buy NO on 3-5 fattest tails (skip base case).​ Log market, outcomes, expected edge, fills. Repeat on new ladders. that's it. no AI, no news scraping, no predictions. just "overhype vs fundamentals".​ where to get real references (not vibes) PolyTrackHQ arb guide. exact logic for multi-outcome pricing errors.​ py-clob-client PyPI. official client (no wrappers). Polymarket Agents GitHub. framework for outcome looping plus orders.​ r/arbitragebetting Reddit. discussions on non-atomic multi-order risk.​ two real-world gotchas (that decide profit vs loss) Outcome blowout: one crazy top bracket hitting wipes the basket. always skip the most likely 1-2 outcomes.​ Resolution risk: ambiguous wording equals instant edge killer. read rules before loading up. how to make it feel "pro" fast Run only on high-volume ladders (FDV, price targets). fills matter more than theory.​ Start with $50-100 per outcome until logs prove fills work, then scale.​ Use official libs only. treat GitHub bots as hostile until audited.
0:10

how to build Polymarket "always buy NO" bot +$200-400/day PnL if you pick the right markets​ everyone overcomplicates this. the "NO-maxi bot" strategy is literally: buy NO on outcomes that are structurally overpriced, wait for reality to catch up.​ the part that matters isn't "genius insight", it's picking the right markets plus execution.​ where the +$200-400/day comes from it's not betting "no" everywhere. it's selectively loading up NO on multi-outcome ladders (FDV ranges, price targets, user metrics) where the top brackets are CT dreams priced way too rich.​ if you're consistently capturing 5-15% edge per cycle across 20-30 outcomes and actually getting fills, +$200-400/day is just position sizing plus discipline.​ first, the edge (why this isn't a meme) polytrackhq research shows $40M+ arb profits from 86M trades came from exploiting pricing errors. "NO-maxi" is the retail version of the same logic on overhyped brackets.​ so the goal is simple: find multi-outcome markets with fat tails, skip the base case, load NO on the fantasy brackets, let time and reality work.​ what you actually need (minimal) Python plus official py-clob-client (standard for Polymarket orders). Telegram bot for alerts (don't stare at screen). VPS so it runs 24/7 (don't run from laptop). where people mess up: they try "always NO" on everything and get wrecked by the one outcome that hits. pick markets with obvious "dream vs reality" skew.​ the bot loop (in plain English) Pull multi-outcome markets (FDV ladders, price targets). For each outcome: check if YES price exceeds realistic probability.​ Buy NO on 3-5 fattest tails (skip base case).​ Log market, outcomes, expected edge, fills. Repeat on new ladders. that's it. no AI, no news scraping, no predictions. just "overhype vs fundamentals".​ where to get real references (not vibes) PolyTrackHQ arb guide. exact logic for multi-outcome pricing errors.​ py-clob-client PyPI. official client (no wrappers). Polymarket Agents GitHub. framework for outcome looping plus orders.​ r/arbitragebetting Reddit. discussions on non-atomic multi-order risk.​ two real-world gotchas (that decide profit vs loss) Outcome blowout: one crazy top bracket hitting wipes the basket. always skip the most likely 1-2 outcomes.​ Resolution risk: ambiguous wording equals instant edge killer. read rules before loading up. how to make it feel "pro" fast Run only on high-volume ladders (FDV, price targets). fills matter more than theory.​ Start with $50-100 per outcome until logs prove fills work, then scale.​ Use official libs only. treat GitHub bots as hostile until audited.

0xCryptoGirl

22,740 просмотров • 7 месяцев назад

My trainer at the gym asked what I do for work. "Trading systems. Open-source." He laughed. "Like day trading?" "No. Anyone can see how it works. All the code is public." He put down his weights. "So you just look at code all day?" I didn't argue. I opened my laptop. One wallet I was tracking returned 71% in a single month. Another processed $4.1M in volume. One more turned $500 into $8,200. His face changed. "That's... from some code?" Exactly. Then I showed him the repos. All public. All free. First one: Every trade ever made. 86M+ trades. Free to download. Snapshot saves 2+ days of research. Second one: Market making bot. Both sides of the book. Gas optimized. Google Sheets execution layer. Third one: ML + heuristics. Flagged that \$500 → \$8,200 wallet before anyone noticed. LLM auto market making. Open source from Polymarket team. My trainer went quiet. Then he asked: "Can my son run this? He's into computers." Profile: I said yes. Then I showed him how to start. Most people think you need a finance degree or a fund. You don't. You just need to read the code and start.
0:15

My trainer at the gym asked what I do for work. "Trading systems. Open-source." He laughed. "Like day trading?" "No. Anyone can see how it works. All the code is public." He put down his weights. "So you just look at code all day?" I didn't argue. I opened my laptop. One wallet I was tracking returned 71% in a single month. Another processed $4.1M in volume. One more turned $500 into $8,200. His face changed. "That's... from some code?" Exactly. Then I showed him the repos. All public. All free. First one: Every trade ever made. 86M+ trades. Free to download. Snapshot saves 2+ days of research. Second one: Market making bot. Both sides of the book. Gas optimized. Google Sheets execution layer. Third one: ML + heuristics. Flagged that \$500 → \$8,200 wallet before anyone noticed. LLM auto market making. Open source from Polymarket team. My trainer went quiet. Then he asked: "Can my son run this? He's into computers." Profile: I said yes. Then I showed him how to start. Most people think you need a finance degree or a fund. You don't. You just need to read the code and start.

Lunar

35,831 просмотров • 3 месяцев назад

My girlfriend asked why I was smiling at 4 AM. Showed her the terminal. "What are all those green numbers?" +$11,400. Made while I slept. "Doing what?" Nothing. Claude scanned 86 million Polymarket trades, found the 47 wallets that never lose, and built me a bot that copies them live. She watched for 10 seconds: +$340 captured +$890 captured +$1,400 captured "It just keeps going?" Every few seconds. New market. New edge. New profit. "How much did you start with?" $25/month. Claude API + $5 VPS. Now the bot runs 24/7 in Germany and I haven’t touched it in 19 days. "What does it do?" Finds mispriced markets before the crowd, copies the smartest whales, exits at the perfect moment. 74% win rate. Sharpe 2.31. "That’s legal?" Polymarket is. The top wallets do this every day. I just have one screen. She looked at the P&L curve. Never dips. Just climbs. "Can you make me one?" Setting hers up now. She still doesn’t get how it works. The bot doesn’t care. You only need Claude + the 4 open-source repos + 1 hour this weekend. Giving the full step-by-step + my exact bot setup free for the next 24 hours. To get it: > Comment the word "BOT". > Like + Retweet this post. > Follow me slash1s (so I can DM you the link). > Bookmark this post.
0:15

My girlfriend asked why I was smiling at 4 AM. Showed her the terminal. "What are all those green numbers?" +$11,400. Made while I slept. "Doing what?" Nothing. Claude scanned 86 million Polymarket trades, found the 47 wallets that never lose, and built me a bot that copies them live. She watched for 10 seconds: +$340 captured +$890 captured +$1,400 captured "It just keeps going?" Every few seconds. New market. New edge. New profit. "How much did you start with?" $25/month. Claude API + $5 VPS. Now the bot runs 24/7 in Germany and I haven’t touched it in 19 days. "What does it do?" Finds mispriced markets before the crowd, copies the smartest whales, exits at the perfect moment. 74% win rate. Sharpe 2.31. "That’s legal?" Polymarket is. The top wallets do this every day. I just have one screen. She looked at the P&L curve. Never dips. Just climbs. "Can you make me one?" Setting hers up now. She still doesn’t get how it works. The bot doesn’t care. You only need Claude + the 4 open-source repos + 1 hour this weekend. Giving the full step-by-step + my exact bot setup free for the next 24 hours. To get it: > Comment the word "BOT". > Like + Retweet this post. > Follow me slash1s (so I can DM you the link). > Bookmark this post.

slash1s

85,050 просмотров • 4 месяцев назад

YOUR GROK BOT HAS YOUR LOGINS AND ITS OWN CLOUD COMPUTER. WITHOUT A RULEBOOK, IT WILL SPEND, POST, OR DELETE SOMETHING BY MONDAY THAT YOU CAN'T UNDO. saturday, 8am. i opened the laptop and started counting what a fresh bot had done overnight on the broad task i left him with. signed up for a paid trial in my name. replied to two DM. deleted a file it decided was clutter. none of it was catastrophic. all of it was mine to clean up on the weekend. the bot was doing exactly what i asked. i had just never told him what he was not allowed to do. so i wrote three files before the next task ran. 1. layer one: charter. one page in Bot actions, Description. name, who he reports to, what he owns, and the exact verbs he must park for me. send, publish, spend, delete, sign, sign-up. 2. layer two: rulebook. ten one-line rules he acknowledges before touching anything. rule 1 (if i cannot undo it in a minute, i park it) closed most of the friday-night damage. rule 9 (never paste a password, sign-in goes through the Agent Computer handoff) closed the rest. 3. layer three: routines. five saved jobs, not seven. morning brief at 7, weekly review on friday, end-of-day handoff at 6, silent-inbox catcher, monthly audit. anything else lives in me, not in the bot. the day after i pasted the three files, the same task came back with three parked questions and one finished deliverable. no signups. no DMs. no deletes. your bot is not scary because it is smart. it is scary because it has your credentials and no one told it what stop looks like. paste the charter and the ten rules before the next task runs. the routines can wait until the first parked question comes back the way you wanted.
0:18

YOUR GROK BOT HAS YOUR LOGINS AND ITS OWN CLOUD COMPUTER. WITHOUT A RULEBOOK, IT WILL SPEND, POST, OR DELETE SOMETHING BY MONDAY THAT YOU CAN'T UNDO. saturday, 8am. i opened the laptop and started counting what a fresh bot had done overnight on the broad task i left him with. signed up for a paid trial in my name. replied to two DM. deleted a file it decided was clutter. none of it was catastrophic. all of it was mine to clean up on the weekend. the bot was doing exactly what i asked. i had just never told him what he was not allowed to do. so i wrote three files before the next task ran. 1. layer one: charter. one page in Bot actions, Description. name, who he reports to, what he owns, and the exact verbs he must park for me. send, publish, spend, delete, sign, sign-up. 2. layer two: rulebook. ten one-line rules he acknowledges before touching anything. rule 1 (if i cannot undo it in a minute, i park it) closed most of the friday-night damage. rule 9 (never paste a password, sign-in goes through the Agent Computer handoff) closed the rest. 3. layer three: routines. five saved jobs, not seven. morning brief at 7, weekly review on friday, end-of-day handoff at 6, silent-inbox catcher, monthly audit. anything else lives in me, not in the bot. the day after i pasted the three files, the same task came back with three parked questions and one finished deliverable. no signups. no DMs. no deletes. your bot is not scary because it is smart. it is scary because it has your credentials and no one told it what stop looks like. paste the charter and the ten rules before the next task runs. the routines can wait until the first parked question comes back the way you wanted.

kocer

16,515 просмотров • 5 дней назад

let me explain what's actually happening with $ZOE and why most of CT is gonna miss this entire window Charms is launching their public platform this month. character economy. AI characters that are tokens, tokens that are characters, every trade pays creator fees forever. $ZOE is the first one. live this week on Base, deployed through clanker. CA: 0xC29832025E7652ef58D15F7fA3e232A2fDfaaB07 three things you need to clock: 1. this is the platform's launch token. not a random clanker. the FIRST character ever shipped from Charms, used by the team to demo what the entire economy will look like once public launch hits. every other character coming after $ZOE references $ZOE. that's a specific kind of asset and the market historically misprices these on day 1. 2. the creator fee model is the real bull case. Charms straight up posted: if you had launched Zoe, you'd have made $15K+ in fees in 24h. that number tells you exactly how much volume they're routing through this thing. 0.8% of every single trade goes to creator. perpetually. now imagine that fee tap on a token that becomes the reference asset for an entire AI character economy. 3. they're paying $15K + 3 months of fees to top 3 posters. think about what that means. they have so much confidence in the volume this thing will do that giving away 3 months of creator fees is a worthwhile marketing budget. teams don't do that math unless they expect the fee pipe to be massive. Clanker as the deployment layer is also not a footnote. CLANKER itself runs a revenue -> buyback flywheel. that infrastructure is battle tested. $ZOE plugs into a system that already works. the setup: - first character from a platform launching this month - pre-public-launch entry window - proven fee mechanics - Clanker rails underneath - team aggressively seeding distribution i'm not telling you what to do. i'm telling you the structure of this launch is one of the cleaner asymmetries on Base right now and the entry window is measured in days not weeks. if you wanna talk to her first. then decide. NFA. obviously.
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let me explain what's actually happening with $ZOE and why most of CT is gonna miss this entire window Charms is launching their public platform this month. character economy. AI characters that are tokens, tokens that are characters, every trade pays creator fees forever. $ZOE is the first one. live this week on Base, deployed through clanker. CA: 0xC29832025E7652ef58D15F7fA3e232A2fDfaaB07 three things you need to clock: 1. this is the platform's launch token. not a random clanker. the FIRST character ever shipped from Charms, used by the team to demo what the entire economy will look like once public launch hits. every other character coming after $ZOE references $ZOE. that's a specific kind of asset and the market historically misprices these on day 1. 2. the creator fee model is the real bull case. Charms straight up posted: if you had launched Zoe, you'd have made $15K+ in fees in 24h. that number tells you exactly how much volume they're routing through this thing. 0.8% of every single trade goes to creator. perpetually. now imagine that fee tap on a token that becomes the reference asset for an entire AI character economy. 3. they're paying $15K + 3 months of fees to top 3 posters. think about what that means. they have so much confidence in the volume this thing will do that giving away 3 months of creator fees is a worthwhile marketing budget. teams don't do that math unless they expect the fee pipe to be massive. Clanker as the deployment layer is also not a footnote. CLANKER itself runs a revenue -> buyback flywheel. that infrastructure is battle tested. $ZOE plugs into a system that already works. the setup: - first character from a platform launching this month - pre-public-launch entry window - proven fee mechanics - Clanker rails underneath - team aggressively seeding distribution i'm not telling you what to do. i'm telling you the structure of this launch is one of the cleaner asymmetries on Base right now and the entry window is measured in days not weeks. if you wanna talk to her first. then decide. NFA. obviously.

toxacnphnk.eth

13,915 просмотров • 4 месяцев назад

Yesterday we showed you what the Aion Terminal was seeing. Today the market confirmed it. But this isn't a victory lap. This is a wake-up call. Retail traders have been stuck in the dark ages. You're making decisions based on someone else's chart, someone else's opinion, someone else's narrative. You open Twitter and it's 50 people with 50 different takes and no data behind any of them. One guy says crash. One guy says moon. You pick whoever confirms what you already believe and call it research. That's not how institutions trade. They don't watch YouTube. They don't follow furus. They sit in front of terminals that cost $24,000 a year and run quantitative models that process thousands of data points before a human ever makes a decision. They see regime shifts before they show up on a chart. They see breadth divergences before the price moves. They see stress building or collapsing in real time while everyone else is reacting to yesterday's candle. That's what the Aion Terminal is. Except it's not $24,000. And you don't need a finance degree to use it. We built something that has never existed for retail. Not a screener. Not a scanner. Not an indicator pack. A real quantitative terminal that runs 4 machine learning models across 30+ sector profiles every 2 hours. XGBoost, Random Forest, Neural Network, and Deep Learning, the same model classes that quant funds use, retrained constantly on live market data and generating forward-looking probabilities, not backward-looking patterns. When you open the Aion Terminal you're not looking at a chart. You're looking at what the market is doing right now and what it's likely to do next. Crash probability. Regime detection. Exposure recommendations. Predictive outlooks with calibrated confidence intervals. Market stress and oversold composites that tell you whether fear is real or whether it's a coiled spring about to snap back. Relative strength rankings across every sector so you know exactly where money is flowing before the move is obvious. Yesterday the terminal showed 7 of 9 models bullish. Crash probability at 15.2%. Market stress collapsing. Oversold at 83.5. Breadth snapping back on the short end. Every single data point was saying the same thing. Today $SPX is up 2.7% pre-market. Nobody on your timeline told you that. The models did. This is the gap between retail and institutional. It was never about skill. It was about information. Institutions don't trade better because they're smarter. They trade better because they see things you don't. The Aion Terminal closes that gap. Stop trading blind. The link is in the bio.
0:14

Yesterday we showed you what the Aion Terminal was seeing. Today the market confirmed it. But this isn't a victory lap. This is a wake-up call. Retail traders have been stuck in the dark ages. You're making decisions based on someone else's chart, someone else's opinion, someone else's narrative. You open Twitter and it's 50 people with 50 different takes and no data behind any of them. One guy says crash. One guy says moon. You pick whoever confirms what you already believe and call it research. That's not how institutions trade. They don't watch YouTube. They don't follow furus. They sit in front of terminals that cost $24,000 a year and run quantitative models that process thousands of data points before a human ever makes a decision. They see regime shifts before they show up on a chart. They see breadth divergences before the price moves. They see stress building or collapsing in real time while everyone else is reacting to yesterday's candle. That's what the Aion Terminal is. Except it's not $24,000. And you don't need a finance degree to use it. We built something that has never existed for retail. Not a screener. Not a scanner. Not an indicator pack. A real quantitative terminal that runs 4 machine learning models across 30+ sector profiles every 2 hours. XGBoost, Random Forest, Neural Network, and Deep Learning, the same model classes that quant funds use, retrained constantly on live market data and generating forward-looking probabilities, not backward-looking patterns. When you open the Aion Terminal you're not looking at a chart. You're looking at what the market is doing right now and what it's likely to do next. Crash probability. Regime detection. Exposure recommendations. Predictive outlooks with calibrated confidence intervals. Market stress and oversold composites that tell you whether fear is real or whether it's a coiled spring about to snap back. Relative strength rankings across every sector so you know exactly where money is flowing before the move is obvious. Yesterday the terminal showed 7 of 9 models bullish. Crash probability at 15.2%. Market stress collapsing. Oversold at 83.5. Breadth snapping back on the short end. Every single data point was saying the same thing. Today $SPX is up 2.7% pre-market. Nobody on your timeline told you that. The models did. This is the gap between retail and institutional. It was never about skill. It was about information. Institutions don't trade better because they're smarter. They trade better because they see things you don't. The Aion Terminal closes that gap. Stop trading blind. The link is in the bio.

Deep Inference

17,953 просмотров • 4 месяцев назад

This Chinese developer launched Llama 70B locally on a MacBook on a plane and for a full 11 hours without internet ran client projects. He was sitting by the window on a transatlantic flight with a MacBook Pro M4 with 64 GB of memory. WiFi on board cost $25 for the flight. He declined. No cloud API, no connection to Anthropic or OpenAI servers, no internet at all. Just a local Llama 3.3 70B on bf16 and his own orchestrator script. The model runs through llama.cpp. Generation speed, 71 tokens per second. Context around 60,000 tokens. Memory usage, 48.6 GiB out of 64. Battery at takeoff, 3 hours 21 minutes. And he gave the orchestrator this system prompt before takeoff: "You are an offline orchestrator running on a single MacBook. There is no network. The only resources you have are local files in /Users/dev/work, the Llama 70B inference server at localhost:8080, and a battery budget of 3 hours 21 minutes. Process the queue at /Users/dev/work/queue.jsonl (one client task per line). For each task: draft → run local evals → save artefact to /Users/dev/work/done/. Save context checkpoints every 12 tasks so you can resume after a battery swap. Stop only on empty queue or when battery drops below 5%." So the system knows exactly what resources it is running on. It knows it has no connection to the outside world for the next 11 hours. It knows it has finite memory and a finite battery. It knows the human will not intervene until the plane lands. The system runs in 1 loop. Takes a task from the queue, runs it through inference, saves the artifact, writes a checkpoint. Task after task, just like that. And only when the battery drops below 5% does the orchestrator automatically pause, waits for the laptop to switch to the backup power bank, and continues from the last checkpoint. Here is what the system actually writes in his log during the flight: "saved context checkpoint 8 of 12 (pos_min = 488, pos_max = 50118, size = 62.813 MiB)" "restored context checkpoint (pos_min = 488, pos_max = 50118)" "prompt processing progress: n_tokens = 50 / 60 818" "task 37016 done | tps = 71 s tokens text → /Users/dev/work/done/proposal_westside.md" Outside the window, clouds, blue sky, and no WiFi. On the tray, 1 MacBook, an open terminal on 2 screens, and an inference server on localhost. From what I have observed, this is the cleanest offline AI workflow I have seen in the past year: 11 hours of flight, $0 for WiFi, and the entire client queue closed before landing.
0:10

This Chinese developer launched Llama 70B locally on a MacBook on a plane and for a full 11 hours without internet ran client projects. He was sitting by the window on a transatlantic flight with a MacBook Pro M4 with 64 GB of memory. WiFi on board cost $25 for the flight. He declined. No cloud API, no connection to Anthropic or OpenAI servers, no internet at all. Just a local Llama 3.3 70B on bf16 and his own orchestrator script. The model runs through llama.cpp. Generation speed, 71 tokens per second. Context around 60,000 tokens. Memory usage, 48.6 GiB out of 64. Battery at takeoff, 3 hours 21 minutes. And he gave the orchestrator this system prompt before takeoff: "You are an offline orchestrator running on a single MacBook. There is no network. The only resources you have are local files in /Users/dev/work, the Llama 70B inference server at localhost:8080, and a battery budget of 3 hours 21 minutes. Process the queue at /Users/dev/work/queue.jsonl (one client task per line). For each task: draft → run local evals → save artefact to /Users/dev/work/done/. Save context checkpoints every 12 tasks so you can resume after a battery swap. Stop only on empty queue or when battery drops below 5%." So the system knows exactly what resources it is running on. It knows it has no connection to the outside world for the next 11 hours. It knows it has finite memory and a finite battery. It knows the human will not intervene until the plane lands. The system runs in 1 loop. Takes a task from the queue, runs it through inference, saves the artifact, writes a checkpoint. Task after task, just like that. And only when the battery drops below 5% does the orchestrator automatically pause, waits for the laptop to switch to the backup power bank, and continues from the last checkpoint. Here is what the system actually writes in his log during the flight: "saved context checkpoint 8 of 12 (pos_min = 488, pos_max = 50118, size = 62.813 MiB)" "restored context checkpoint (pos_min = 488, pos_max = 50118)" "prompt processing progress: n_tokens = 50 / 60 818" "task 37016 done | tps = 71 s tokens text → /Users/dev/work/done/proposal_westside.md" Outside the window, clouds, blue sky, and no WiFi. On the tray, 1 MacBook, an open terminal on 2 screens, and an inference server on localhost. From what I have observed, this is the cleanest offline AI workflow I have seen in the past year: 11 hours of flight, $0 for WiFi, and the entire client queue closed before landing.

Blaze

1,841,161 просмотров • 4 месяцев назад