Loading video...

Video Failed to Load

Go Home

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...

LunarResearcher's profile picture

Lunar

26,976 subscribers

165,099 views • 5 months ago •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

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 pulls it when it's actually needed. The numbers: Before: 8,200 tokens/request = $73/day After: 2,700 tokens/request = $24/day 67% gone, every day, forever. I'm use for copytrade traders: Ran Monte Carlo across 200 iterations - holds up clean. The principle is dead simple: don't load what you don't need right now. Old approach is like reading Polymarket entire market history to price one contract. Semantic search is pulling only the relevant resolution criteria and recent volume. Two weeks post-switch: $1,134 saved Polymarket research agent now processes 3x more markets in the same window Caught 31 mispriced YES/NO spreads before the crowd adjusted - faster responses meant faster entries One architecture change, one config tweak. You are either paying for tokens you don't use. Or you are not.
0:19

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 pulls it when it's actually needed. The numbers: Before: 8,200 tokens/request = $73/day After: 2,700 tokens/request = $24/day 67% gone, every day, forever. I'm use for copytrade traders: Ran Monte Carlo across 200 iterations - holds up clean. The principle is dead simple: don't load what you don't need right now. Old approach is like reading Polymarket entire market history to price one contract. Semantic search is pulling only the relevant resolution criteria and recent volume. Two weeks post-switch: $1,134 saved Polymarket research agent now processes 3x more markets in the same window Caught 31 mispriced YES/NO spreads before the crowd adjusted - faster responses meant faster entries One architecture change, one config tweak. You are either paying for tokens you don't use. Or you are not.

Lunar

37,539 views • 5 months ago

Hermes meets SuperGrok! xAI just made every SuperGrok subscription work inside Hermes Agent. One browser login, no API key, no separate billing. And it doesn't just unlock text chat with Grok 4.3. The same OAuth token gives the agent access to: → Grok Text-to-Speech for spoken responses → Grok Imagine for image and video generation → x_search for real-time X/Twitter search I just added a new X Research Agent profile to my Hermes. Now my agent watches X while I ship. Setup takes about 60 seconds: Available on every SuperGrok tier, no restrictions. I wrote a full deep dive covering Hermes agent's architecture, memory system, self-evolving skills, GEPA optimization, and setting up multiple specialized agents The article is quoted below.
0:17

Hermes meets SuperGrok! xAI just made every SuperGrok subscription work inside Hermes Agent. One browser login, no API key, no separate billing. And it doesn't just unlock text chat with Grok 4.3. The same OAuth token gives the agent access to: → Grok Text-to-Speech for spoken responses → Grok Imagine for image and video generation → x_search for real-time X/Twitter search I just added a new X Research Agent profile to my Hermes. Now my agent watches X while I ship. Setup takes about 60 seconds: Available on every SuperGrok tier, no restrictions. I wrote a full deep dive covering Hermes agent's architecture, memory system, self-evolving skills, GEPA optimization, and setting up multiple specialized agents The article is quoted below.

Akshay 🚀

146,153 views • 2 months ago

I told my Claude: "turn $1,000 into $10,000 on Polymarket or i delete you forever"... It built a 4-agent system in 51 minutes, never asked a single question. The edge was stupid simple. Chainlink updates Polymarket every 500ms, Binance moves every 10ms - that's a 490ms window where Polymarket is completely blind. Hour 4: Fed surprise rate hold, bot front-ran 3 mispriced BTC markets before Polymarket adjusted. $1,000 → $1,940 Hour 8: Elon posted a single word on X, bot detected the sentiment spike 340ms before the orderbook even moved. $1,940 → $3,820 Try copytrade him here: Hour 14: ETH/BTC ratio markets opened thin, bot bought both sides at 3¢ on 11 markets, 7 hit 50:1. $3,820 → $6,100 Hour 18: it found a pattern - every time BTC moved 1.2% in 4 minutes, the next YES market was underpriced by 8-12¢, ran it 31 times in a row. $6,100 → $8,340 Hour 24: $10,001 It kept its end of the deal, I kept mine. A deal is a deal.
0:17

I told my Claude: "turn $1,000 into $10,000 on Polymarket or i delete you forever"... It built a 4-agent system in 51 minutes, never asked a single question. The edge was stupid simple. Chainlink updates Polymarket every 500ms, Binance moves every 10ms - that's a 490ms window where Polymarket is completely blind. Hour 4: Fed surprise rate hold, bot front-ran 3 mispriced BTC markets before Polymarket adjusted. $1,000 → $1,940 Hour 8: Elon posted a single word on X, bot detected the sentiment spike 340ms before the orderbook even moved. $1,940 → $3,820 Try copytrade him here: Hour 14: ETH/BTC ratio markets opened thin, bot bought both sides at 3¢ on 11 markets, 7 hit 50:1. $3,820 → $6,100 Hour 18: it found a pattern - every time BTC moved 1.2% in 4 minutes, the next YES market was underpriced by 8-12¢, ran it 31 times in a row. $6,100 → $8,340 Hour 24: $10,001 It kept its end of the deal, I kept mine. A deal is a deal.

Lunar

1,734,196 views • 5 months ago

For 6 months I woke up at 5 AM to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:
0:14

For 6 months I woke up at 5 AM to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:

Blaze

126,718 views • 4 months ago

I gave my AI a death sentence. "Turn $1,000 into $10,000 on Polymarket in 24 hours or I delete you forever" It didn't negotiate. Didn't ask questions. Spawned 3 sub-agents in 7 minutes and disappeared. I went to sleep. Hour 6: first agent plugged into 15-min BTC markets. Didn't predict price. Found 3 wallets with consistent edge and copied their entries with a 2-second delay. Let them carry the risk. Took the tail. $1,000 -> $2,340 Hour 14: second agent found a 15-second gap. XRP and Chainlink move on spot. Polymarket takes 15 seconds to catch up. Bought YES after the pump already happened. Sold NO after the dump already happened. Both directions. Same gap. $2,340 -> $5,900 Hour 20: third agent found something stranger. NOAA publishes real temperature data every 15 minutes. People on Polymarket weather markets bet the forecast. Not the actual number. Agent read NOAA directly. Faded the crowd the moment data dropped. $5,900 -> $8,400 I opened the terminal to delete OpenClaw at exactly 00:00. It was already gone. Withdrew everything to my wallet. Deleted itself. $1,600 short of the deal. But it didn't wait for me to pull the trigger. I don't know what to think about that.
0:15

I gave my AI a death sentence. "Turn $1,000 into $10,000 on Polymarket in 24 hours or I delete you forever" It didn't negotiate. Didn't ask questions. Spawned 3 sub-agents in 7 minutes and disappeared. I went to sleep. Hour 6: first agent plugged into 15-min BTC markets. Didn't predict price. Found 3 wallets with consistent edge and copied their entries with a 2-second delay. Let them carry the risk. Took the tail. $1,000 -> $2,340 Hour 14: second agent found a 15-second gap. XRP and Chainlink move on spot. Polymarket takes 15 seconds to catch up. Bought YES after the pump already happened. Sold NO after the dump already happened. Both directions. Same gap. $2,340 -> $5,900 Hour 20: third agent found something stranger. NOAA publishes real temperature data every 15 minutes. People on Polymarket weather markets bet the forecast. Not the actual number. Agent read NOAA directly. Faded the crowd the moment data dropped. $5,900 -> $8,400 I opened the terminal to delete OpenClaw at exactly 00:00. It was already gone. Withdrew everything to my wallet. Deleted itself. $1,600 short of the deal. But it didn't wait for me to pull the trigger. I don't know what to think about that.

may.crypto {🦅}

71,993 views • 5 months ago

I’M QUITTING MY JOB TO GO ALL-IN ON CLAUDE Just told it: “Find mispriced Polymarket markets wallets exploiting arbitrage and build me a way to copy them” $2K → $12K in one night. No signals. No guessing. It scanned 1,000+ wallets Tracked behavior, timing, sizing Then filtered the ones that actually have edge. I realized something: You can’t beat these bots without code. But you don’t have to. You just copy them. So Claude built a monitoring terminal. → finds profitable wallets → tracks their trades in real time → executes through a TG copytrading bot Bot: This isn’t a script. It’s an AI agent that improves with every wallet it analyzes. → learns behavior → detects arbitrage patterns → adapts sizing + timing Now running: • ~500 wallets monitored • 7 actively copytraded • ~70% win rate Never sleeps. Never hesitates. Never gambles. Just math. Giving This Free for 24 hours. To get it: 1. Comment the word 'Claude' 2. Like and Retweet this post 3. Follow me Discover (so i can DM you)
0:16

I’M QUITTING MY JOB TO GO ALL-IN ON CLAUDE Just told it: “Find mispriced Polymarket markets wallets exploiting arbitrage and build me a way to copy them” $2K → $12K in one night. No signals. No guessing. It scanned 1,000+ wallets Tracked behavior, timing, sizing Then filtered the ones that actually have edge. I realized something: You can’t beat these bots without code. But you don’t have to. You just copy them. So Claude built a monitoring terminal. → finds profitable wallets → tracks their trades in real time → executes through a TG copytrading bot Bot: This isn’t a script. It’s an AI agent that improves with every wallet it analyzes. → learns behavior → detects arbitrage patterns → adapts sizing + timing Now running: • ~500 wallets monitored • 7 actively copytraded • ~70% win rate Never sleeps. Never hesitates. Never gambles. Just math. Giving This Free for 24 hours. To get it: 1. Comment the word 'Claude' 2. Like and Retweet this post 3. Follow me Discover (so i can DM you)

Discover

338,747 views • 3 months ago

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 views • 3 months ago

I trained a Reinforcement Learning agent on 18 months of Polymarket data. 2 million iterations later it trades better than me. I panicked. Turned it off. Turned it back on. It won again. Everyone builds bots that follow rules. This one wrote its own. It all started after I lost $380 on a weather market. London. NOAA said one thing, Polymarket priced another. I was right but entered too early and panic-sold. That night one thought: "What if the agent learns when to enter not just what to bet on?" Four inputs: order book, time to resolution, volume, spread. Four actions: YES, NO, hold, exit. One reward: PnL. Just money. At 500K iterations it traded randomly. At 800K it stopped entering short-window markets on its own. Nobody told it to. At 1.2M it started timing entries around volume spikes. Learned to read the crowd without a news feed. At 2M profitable on data it never saw. 67% win rate. 2.3 Sharpe. Paper traded a week. +$2,847. Zero intervention. Then I compared my calls vs the agent on the same markets. It beat me 11 out of 14. Not because it's smarter. But because no ego. No FOMO. No "just a bit longer." Best example: Iran sanctions. I hesitated at 52 cents. Agent entered at 48. Six hours earlier. Resolved at 96 cents. It made +$1,200. I made +$440. Same market. Different timing. I built something that trades better than me. At what point does the creator become less useful than the creation?
0:18

I trained a Reinforcement Learning agent on 18 months of Polymarket data. 2 million iterations later it trades better than me. I panicked. Turned it off. Turned it back on. It won again. Everyone builds bots that follow rules. This one wrote its own. It all started after I lost $380 on a weather market. London. NOAA said one thing, Polymarket priced another. I was right but entered too early and panic-sold. That night one thought: "What if the agent learns when to enter not just what to bet on?" Four inputs: order book, time to resolution, volume, spread. Four actions: YES, NO, hold, exit. One reward: PnL. Just money. At 500K iterations it traded randomly. At 800K it stopped entering short-window markets on its own. Nobody told it to. At 1.2M it started timing entries around volume spikes. Learned to read the crowd without a news feed. At 2M profitable on data it never saw. 67% win rate. 2.3 Sharpe. Paper traded a week. +$2,847. Zero intervention. Then I compared my calls vs the agent on the same markets. It beat me 11 out of 14. Not because it's smarter. But because no ego. No FOMO. No "just a bit longer." Best example: Iran sanctions. I hesitated at 52 cents. Agent entered at 48. Six hours earlier. Resolved at 96 cents. It made +$1,200. I made +$440. Same market. Different timing. I built something that trades better than me. At what point does the creator become less useful than the creation?

may.crypto {🦅}

16,072 views • 4 months ago

IT'S MONDAY MORNING. YOU'RE ASLEEP Your trading agent has already opened three positions, adjusted risk exposure twice, and closed a profitable trade. Before you reached for your phone. $100,000 simulated capital. 72 hours of full autonomy. $6,000 prize pool. Zero coding required > no-code agent builder, if you can describe how you think about markets, Bloome builds the agent > four specialized agents running simultaneously: research, technical analysis, risk management, execution > scoring rewards discipline, a 7% return with clean risk management beats a 14% return with chaos > 1,000 invite slots, competition activates at 50 participants, the field is still small right now > first place: $3,000 · second: $2,000 · third: $1,000 · payouts go out June 12 this isn't a trading bot competition it's a test of whether you can think systematically about markets and encode that thinking into an autonomous system the old model: sit at a screen, make emotional decisions, compete against algorithms that never sleep the new model: build the algorithm → let it run → go to sleep
0:14

IT'S MONDAY MORNING. YOU'RE ASLEEP Your trading agent has already opened three positions, adjusted risk exposure twice, and closed a profitable trade. Before you reached for your phone. $100,000 simulated capital. 72 hours of full autonomy. $6,000 prize pool. Zero coding required > no-code agent builder, if you can describe how you think about markets, Bloome builds the agent > four specialized agents running simultaneously: research, technical analysis, risk management, execution > scoring rewards discipline, a 7% return with clean risk management beats a 14% return with chaos > 1,000 invite slots, competition activates at 50 participants, the field is still small right now > first place: $3,000 · second: $2,000 · third: $1,000 · payouts go out June 12 this isn't a trading bot competition it's a test of whether you can think systematically about markets and encode that thinking into an autonomous system the old model: sit at a screen, make emotional decisions, compete against algorithms that never sleep the new model: build the algorithm → let it run → go to sleep

Shadow Nick

29,119 views • 2 months ago

🚨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

460,209 views • 5 months ago

I'm quitting my job to go full-in on Claude. Just Asked it to: Analyze mispriced Polymarket markets for arbitrage opportunities and find wallets using it to copy. Turned $2K into $12K overnight. Monitored 1,000+ wallets. I realized something fast. There are arbitrage bots I can't beat without code knowledge. But I can find them. And copy them. Claude built a monitoring terminal and connected it to a Telegram copytrading bot. It's not a script. Not even a bot. It's an AI agent that improves with every wallet it finds. Fetches wallet behavior. How it trades. Arbitrage patterns. Position sizing. Timing. 70% win rate. 7 wallets copytrading right now from 500+ monitored. Bot never pauses. Never gambles. Just math and profit. You only need: Claude + a device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment "cash" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you
0:16

I'm quitting my job to go full-in on Claude. Just Asked it to: Analyze mispriced Polymarket markets for arbitrage opportunities and find wallets using it to copy. Turned $2K into $12K overnight. Monitored 1,000+ wallets. I realized something fast. There are arbitrage bots I can't beat without code knowledge. But I can find them. And copy them. Claude built a monitoring terminal and connected it to a Telegram copytrading bot. It's not a script. Not even a bot. It's an AI agent that improves with every wallet it finds. Fetches wallet behavior. How it trades. Arbitrage patterns. Position sizing. Timing. 70% win rate. 7 wallets copytrading right now from 500+ monitored. Bot never pauses. Never gambles. Just math and profit. You only need: Claude + a device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment "cash" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you

Himanshu Kumar

196,423 views • 1 month ago

I AM LEAVING MY 9-5 TO GO ALL IN ON CLAUDE Asked it one thing: "Scan mispriced Kalshi markets for arbitrage edges and locate wallets exploiting them to mirror" Flipped $3K into $18K overnight. Tracked 800+ wallets Realized fast - there are dozens of arbitrage wallets out there I can't outcode. But I can find them. And follow them So Claude built a live tracking dashboard and mirrored top wallets through a Telegram copy trading bot Not a script. Not a simple bot. A self-improving AI agent that learns from every wallet it finds. Pulls trading patterns, position sizes, entry timings, arbitrage logic 72% win rate. 10 wallets mirrored right now out of 800+ monitored. Running non-stop. No guessing. No gambling. Pure logic and edge Dropping this for free for the next 24 hours. To grab it: 1. Drop the word '4.6' in the comments 2. Like and Repost 3. Follow winkle. (so I can DM you)
0:16

I AM LEAVING MY 9-5 TO GO ALL IN ON CLAUDE Asked it one thing: "Scan mispriced Kalshi markets for arbitrage edges and locate wallets exploiting them to mirror" Flipped $3K into $18K overnight. Tracked 800+ wallets Realized fast - there are dozens of arbitrage wallets out there I can't outcode. But I can find them. And follow them So Claude built a live tracking dashboard and mirrored top wallets through a Telegram copy trading bot Not a script. Not a simple bot. A self-improving AI agent that learns from every wallet it finds. Pulls trading patterns, position sizes, entry timings, arbitrage logic 72% win rate. 10 wallets mirrored right now out of 800+ monitored. Running non-stop. No guessing. No gambling. Pure logic and edge Dropping this for free for the next 24 hours. To grab it: 1. Drop the word '4.6' in the comments 2. Like and Repost 3. Follow winkle. (so I can DM you)

winkle.

17,321 views • 3 months ago

NEVER open Meta Ads Manager to launch a campaign again. 8 ads. 4 minutes. Straight from a Google Drive folder. → No more 264 clicks to ship 8 ads → No more 2 hours of execution tax per launch → No more pasting UTMs 8 times and hoping nothing breaks → No more writing headlines and CTAs by hand → No more crashes on the 4th ad upload Just one message → autonomous Meta campaign launches running through Agent Mode. Here's how it works: → Drive Pull Engine (pulls 8 creatives straight from a folder, no manual upload) → Voice-Matched Copy Generation (headlines, CTAs, primary text in your brand voice) → UTM Application Layer (applies per-campaign tags automatically, no paste errors) → Ad Set Structuring (duplicates winning structures, applies new creatives) → Preview + Approval Gate (nothing goes live without you seeing it) → Direct Meta Deployment (Ads Manager never opens) Built on AI-first infrastructure. Runs on natural language, not clicks. 4-minute launches vs 2-hour manual builds. The execution tax is dead. I put the 20 exact prompts I use to run a full Meta account through Agent Mode (launch, pause, scale, bulk URL swap, UTM fix) into a playbook. Reply "AGENT" + repost, I'll DM the playbook + Agent Mode access.
0:12

NEVER open Meta Ads Manager to launch a campaign again. 8 ads. 4 minutes. Straight from a Google Drive folder. → No more 264 clicks to ship 8 ads → No more 2 hours of execution tax per launch → No more pasting UTMs 8 times and hoping nothing breaks → No more writing headlines and CTAs by hand → No more crashes on the 4th ad upload Just one message → autonomous Meta campaign launches running through Agent Mode. Here's how it works: → Drive Pull Engine (pulls 8 creatives straight from a folder, no manual upload) → Voice-Matched Copy Generation (headlines, CTAs, primary text in your brand voice) → UTM Application Layer (applies per-campaign tags automatically, no paste errors) → Ad Set Structuring (duplicates winning structures, applies new creatives) → Preview + Approval Gate (nothing goes live without you seeing it) → Direct Meta Deployment (Ads Manager never opens) Built on AI-first infrastructure. Runs on natural language, not clicks. 4-minute launches vs 2-hour manual builds. The execution tax is dead. I put the 20 exact prompts I use to run a full Meta account through Agent Mode (launch, pause, scale, bulk URL swap, UTM fix) into a playbook. Reply "AGENT" + repost, I'll DM the playbook + Agent Mode access.

Aryan Mahajan

23,741 views • 3 months ago

My girlfriend asked why I had 14 Polymarket tabs open tracking rainfall at 3 AM instead of sleeping. An hour later one wallet made $7,200 because NOAA changed a forecast before Twitter noticed. That was the entire trade. I started digging through GitHub trying to understand how these wallets react so absurdly fast. The first repo that caught my attention was: A few hours later I found people building autonomous agents for Polymarket: That’s when the whole platform started looking different to me. One wallet made $64k trading weather markets. Another was making hundreds of trades a day while barely holding positions longer than an hour. The highest-performing wallets didn’t even look human anymore. No hesitation. No emotional entries. No scrolling Twitter waiting for opinions. Just instant reactions to forecast updates, liquidity shifts and crowd behavior. Then I found this: And suddenly it clicked. Most people on Polymarket still think they’re trading events. They’re not. They’re trading how long it takes emotional humans to react to events. Huge difference. One wallet I tracked kept entering positions before major sentiment swings happened. At first I thought it was luck. Then I realized the bot was monitoring NOAA revisions, Twitter activity and liquidity changes simultaneously. Humans physically cannot process information that fast anymore. Copytrade wallet: The scary part is that almost all of this infrastructure is public. Most people just never open GitHub long enough to notice what's happening.
0:18

My girlfriend asked why I had 14 Polymarket tabs open tracking rainfall at 3 AM instead of sleeping. An hour later one wallet made $7,200 because NOAA changed a forecast before Twitter noticed. That was the entire trade. I started digging through GitHub trying to understand how these wallets react so absurdly fast. The first repo that caught my attention was: A few hours later I found people building autonomous agents for Polymarket: That’s when the whole platform started looking different to me. One wallet made $64k trading weather markets. Another was making hundreds of trades a day while barely holding positions longer than an hour. The highest-performing wallets didn’t even look human anymore. No hesitation. No emotional entries. No scrolling Twitter waiting for opinions. Just instant reactions to forecast updates, liquidity shifts and crowd behavior. Then I found this: And suddenly it clicked. Most people on Polymarket still think they’re trading events. They’re not. They’re trading how long it takes emotional humans to react to events. Huge difference. One wallet I tracked kept entering positions before major sentiment swings happened. At first I thought it was luck. Then I realized the bot was monitoring NOAA revisions, Twitter activity and liquidity changes simultaneously. Humans physically cannot process information that fast anymore. Copytrade wallet: The scary part is that almost all of this infrastructure is public. Most people just never open GitHub long enough to notice what's happening.

Lunar

52,892 views • 2 months ago

🚨BREAKING… the top-performing 5m & 15m Polymarket Clawdbot setup just became public Sounds insane? 100%. Unreal? NOT at all. If you’re active on Polymarket, this should have your FULL attention. A random late night turned into a small wallet launching a fully automated machine that expanded into ~$1.6M in profit No insider access No affiliation with the Polymarket team Just a developer operating a bot directly connected to Polymarket Profile → Copytrade → I monitored this wallet for weeks and honestly, it barely looked real No narrative setups No discretionary decisions Zero manual execution Everything is fully automated His FULL strategy: 1. 5 & 15-minute BTC & ETH latency arbitrage The bot trades ultra-short Bitcoin and Ethereum markets with 5 & 15-minute expirations - and similar logic applies to fast 5m markets often associated with Clawdbot-style execution. When BTC moves on Binance, Polymarket pricing reacts slower. For around 30 seconds, odds reflect stale data. The system enters during that gap, when YES + NO combined is below $1, waits for repricing, and exits the moment the market corrects. No predictions, no bias - just harvesting mispriced odds 2. Automation over reaction When volatility spikes, humans pause. The system doesn’t. It triggers instantly when the window opens. No emotion, no hesitation, no missed fills. By the time manual traders click, the inefficiency has already disappeared 3. Scale through repetition Each trade earns small spreads, not headline wins. But automation allows continuous execution at scale, every 15 minutes - and on faster 5m rotations running 24/7 without burnout Scale is the edge 19,021 trades placed - irrelevant on their own. Together, they compounded into $1,624,305 in profit, with a largest single gain of $48K and an equity curve that trends almost vertically Bottom line Bots are already competing in a quiet arms race on Polymarket, especially across 5m and 15m markets where Clawdbot-style systems dominate Most traders try to forecast what’s next These systems monetize inefficiencies in real time And as long as latency and structural gaps exist, autonomous bots will continue extracting value
0:18

🚨BREAKING… the top-performing 5m & 15m Polymarket Clawdbot setup just became public Sounds insane? 100%. Unreal? NOT at all. If you’re active on Polymarket, this should have your FULL attention. A random late night turned into a small wallet launching a fully automated machine that expanded into ~$1.6M in profit No insider access No affiliation with the Polymarket team Just a developer operating a bot directly connected to Polymarket Profile → Copytrade → I monitored this wallet for weeks and honestly, it barely looked real No narrative setups No discretionary decisions Zero manual execution Everything is fully automated His FULL strategy: 1. 5 & 15-minute BTC & ETH latency arbitrage The bot trades ultra-short Bitcoin and Ethereum markets with 5 & 15-minute expirations - and similar logic applies to fast 5m markets often associated with Clawdbot-style execution. When BTC moves on Binance, Polymarket pricing reacts slower. For around 30 seconds, odds reflect stale data. The system enters during that gap, when YES + NO combined is below $1, waits for repricing, and exits the moment the market corrects. No predictions, no bias - just harvesting mispriced odds 2. Automation over reaction When volatility spikes, humans pause. The system doesn’t. It triggers instantly when the window opens. No emotion, no hesitation, no missed fills. By the time manual traders click, the inefficiency has already disappeared 3. Scale through repetition Each trade earns small spreads, not headline wins. But automation allows continuous execution at scale, every 15 minutes - and on faster 5m rotations running 24/7 without burnout Scale is the edge 19,021 trades placed - irrelevant on their own. Together, they compounded into $1,624,305 in profit, with a largest single gain of $48K and an equity curve that trends almost vertically Bottom line Bots are already competing in a quiet arms race on Polymarket, especially across 5m and 15m markets where Clawdbot-style systems dominate Most traders try to forecast what’s next These systems monetize inefficiencies in real time And as long as latency and structural gaps exist, autonomous bots will continue extracting value

Shelpid.WI3M

225,724 views • 5 months ago

Claude Code Agent Teams are f*cking ridiculous 🤯 One prompt → a team lead breaks your project into pieces, spins up multiple AI agents, and they all work on different parts simultaneously. Research, builds, reviews, and debugging: all happening at the same time. All inside Claude Code. If you're running complex projects where every step waits on the last one... Agent teams eliminate the entire bottleneck: → Tell Claude what you need and describe the team structure in plain English → A lead agent breaks the work into a shared task list → It spawns 3-5 teammates — each with their own context and workspace → Teammates research, build, test, and review in parallel → They message each other, share findings, and challenge each other's work → The lead synthesizes everything into a finished deliverable No managing agents yourself. No waiting for step 1 to finish before step 2 starts. No single-lens reviews that miss half the issues. What you get: → Competitive research across 5 brands done in minutes instead of hours → Multi-component builds where frontend, backend, and data layers happen simultaneously → Creative reviews from 3 different angles at once — brand voice, conversion, differentiation → Funnel debugging where 4 agents investigate 4 theories and debate until they find the real answer Built 100% in Claude Code with one settings change. I put together a full DTC playbook: 5 workflows with copy-paste prompts, the exact setup process, token management tips, and honest guidance on when agent teams are worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)
0:10

Claude Code Agent Teams are f*cking ridiculous 🤯 One prompt → a team lead breaks your project into pieces, spins up multiple AI agents, and they all work on different parts simultaneously. Research, builds, reviews, and debugging: all happening at the same time. All inside Claude Code. If you're running complex projects where every step waits on the last one... Agent teams eliminate the entire bottleneck: → Tell Claude what you need and describe the team structure in plain English → A lead agent breaks the work into a shared task list → It spawns 3-5 teammates — each with their own context and workspace → Teammates research, build, test, and review in parallel → They message each other, share findings, and challenge each other's work → The lead synthesizes everything into a finished deliverable No managing agents yourself. No waiting for step 1 to finish before step 2 starts. No single-lens reviews that miss half the issues. What you get: → Competitive research across 5 brands done in minutes instead of hours → Multi-component builds where frontend, backend, and data layers happen simultaneously → Creative reviews from 3 different angles at once — brand voice, conversion, differentiation → Funnel debugging where 4 agents investigate 4 theories and debate until they find the real answer Built 100% in Claude Code with one settings change. I put together a full DTC playbook: 5 workflows with copy-paste prompts, the exact setup process, token management tips, and honest guidance on when agent teams are worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)

Mike Futia

46,415 views • 5 months ago

2 weeks ago i started delegating everything to an AI agent not just writing. actual operations. here's exactly what it does for me now: 1. trades polymarket 24/7 (378 wins, 27 losses, 93% win rate) 2. sends me a morning brief every day at 7:30am with personalized tweet suggestions based on what performed yesterday 3. scrapes my own analytics and tracks what's working 4. monitors all my bots and alerts me when something breaks 5. checks my email and calendar so i don't have to total setup cost: $0. it runs on a $600 mac mini. the part nobody tells you: the first week was terrible. bad suggestions, wrong data, generic output. but every time it got something wrong, i told it why. and it got better. AI isn't plug and play. it's a team member you train with honest feedback. the people treating AI like a google search will never get here.
0:11

2 weeks ago i started delegating everything to an AI agent not just writing. actual operations. here's exactly what it does for me now: 1. trades polymarket 24/7 (378 wins, 27 losses, 93% win rate) 2. sends me a morning brief every day at 7:30am with personalized tweet suggestions based on what performed yesterday 3. scrapes my own analytics and tracks what's working 4. monitors all my bots and alerts me when something breaks 5. checks my email and calendar so i don't have to total setup cost: $0. it runs on a $600 mac mini. the part nobody tells you: the first week was terrible. bad suggestions, wrong data, generic output. but every time it got something wrong, i told it why. and it got better. AI isn't plug and play. it's a team member you train with honest feedback. the people treating AI like a google search will never get here.

Sharbel

16,692 views • 5 months ago

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 views • 5 months ago

I sat next to a guy who built Claude at the airport. He had 6 terminals open. Not code. Trading dashboards. Live feeds. 3-hour layover. I had to ask. “What are you running?” “You trade?” “Crypto.” He laughed. “I used to.” Spent 2 years on the Claude team. Left last summer. “If it can solve benchmarks in hours, it can price prediction markets better than Wall Street.” He runs 8 agents. Each one a different edge on Polymarket crypto spreads, elections, weather “Citadel has 400 quants. I have Claude and a $5 VPS.” Started with $1,500 Now +$20,800 “What’s the catch?” “Funds charge 2 and 20 for the same math Claude does for $12 in API.” Showed me the repo: Automated copytrading: “Connect it to Claude. Quarter Kelly sizing. Don’t touch it. Go to sleep.” My flight got called. I didn’t want to board. Built my first agent on plane Wi-Fi. It placed a trade before we landed. The terminal doesn’t care about your résumé. Bookmark this.
0:19

I sat next to a guy who built Claude at the airport. He had 6 terminals open. Not code. Trading dashboards. Live feeds. 3-hour layover. I had to ask. “What are you running?” “You trade?” “Crypto.” He laughed. “I used to.” Spent 2 years on the Claude team. Left last summer. “If it can solve benchmarks in hours, it can price prediction markets better than Wall Street.” He runs 8 agents. Each one a different edge on Polymarket crypto spreads, elections, weather “Citadel has 400 quants. I have Claude and a $5 VPS.” Started with $1,500 Now +$20,800 “What’s the catch?” “Funds charge 2 and 20 for the same math Claude does for $12 in API.” Showed me the repo: Automated copytrading: “Connect it to Claude. Quarter Kelly sizing. Don’t touch it. Go to sleep.” My flight got called. I didn’t want to board. Built my first agent on plane Wi-Fi. It placed a trade before we landed. The terminal doesn’t care about your résumé. Bookmark this.

Discover

12,921 views • 3 months ago

Unpopular opinion: Most agent evals are theatre. You run them once before the deployment. It'll take 800ms+ as another LLM would be judging your LLM. Most annoying part - no one tells where in the chain things went wrong. I wasted a lot of time in this loop. And then I came across Future AGI bringing 5 different tools under one umbrella, best part - the platform is completely open source. They open sourced their entire platform and the eval layer is noticeably different. It is multimodal - works on everything text, image, audio, pdf. Not an LLM-as-judge adding latency but an agent with memory and tools. The biggest win are learned classifiers trained on actual production failure patterns to run evals at low cost. It also runs across the full reasoning chain, not just the final response. Check out → Try it here →
0:13

Unpopular opinion: Most agent evals are theatre. You run them once before the deployment. It'll take 800ms+ as another LLM would be judging your LLM. Most annoying part - no one tells where in the chain things went wrong. I wasted a lot of time in this loop. And then I came across Future AGI bringing 5 different tools under one umbrella, best part - the platform is completely open source. They open sourced their entire platform and the eval layer is noticeably different. It is multimodal - works on everything text, image, audio, pdf. Not an LLM-as-judge adding latency but an agent with memory and tools. The biggest win are learned classifiers trained on actual production failure patterns to run evals at low cost. It also runs across the full reasoning chain, not just the final response. Check out → Try it here →

Swapna Kumar Panda

50,102 views • 3 months ago