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Anthropic dev turned $300 → $91K using upcoming Claude Mythos model on Polymarket weather markets No code. All he did is sent one MIT research: "Weather forecasting using ML models" Mythos model started to predict super-rare weather events {0.01¢ - 0.1¢} The result is crazy: 25$ → 12,452$ 16$...

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Movez

29,758 subscribers

34,903 次观看 • 6 个月前 •via X (Twitter)

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$26.41 → $24,1K thanks to the Weather BOT! Fully automated. Runs with zero human input. Most likely built using ClawdBot What does it do and how? - Buys shares at 20¢-38¢ - Trades within a very tight temperature range (1°) - Only trades London Result? $48.08 → $1,020.24 (example) Since weather is a physical process that can be accurately modeled over short timeframes, the bot spots errors in the crowd's opinion on the market I think weather is one of the most predictable markets for AI And yeah! This is another profile I've already added to my watchlist Drop a like if you want to see more breakdowns like this! - Profile: - Copy trades fast here:
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$26.41 → $24,1K thanks to the Weather BOT! Fully automated. Runs with zero human input. Most likely built using ClawdBot What does it do and how? - Buys shares at 20¢-38¢ - Trades within a very tight temperature range (1°) - Only trades London Result? $48.08 → $1,020.24 (example) Since weather is a physical process that can be accurately modeled over short timeframes, the bot spots errors in the crowd's opinion on the market I think weather is one of the most predictable markets for AI And yeah! This is another profile I've already added to my watchlist Drop a like if you want to see more breakdowns like this! - Profile: - Copy trades fast here:

cristal💎

35,866 次观看 • 7 个月前

just now, I detected this Polymarket profile with that turned $10 into $9,500 with a single trade this trader specializes in weather markets, and this huge return came from one of his weather trades he bet that the highest temperature in Lucknow would be 31°C on September 6, entering at just 0.1¢ this happened, and he made an insane +94,395% return and this wasn’t a one-time hit - he’s already found several similar market inefficiencies on top of his biggest hit, he’s also made +34,312%, +9,900%, and +952% on other trades i pinned his profile in the comments below if you want to check it out ↓
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just now, I detected this Polymarket profile with that turned $10 into $9,500 with a single trade this trader specializes in weather markets, and this huge return came from one of his weather trades he bet that the highest temperature in Lucknow would be 31°C on September 6, entering at just 0.1¢ this happened, and he made an insane +94,395% return and this wasn’t a one-time hit - he’s already found several similar market inefficiencies on top of his biggest hit, he’s also made +34,312%, +9,900%, and +952% on other trades i pinned his profile in the comments below if you want to check it out ↓

Korens

13,013 次观看 • 12 天前

This trader turned $25 into $12,400 on a single weather bet on Polymarket Made $45,000 in the last month alone -> and he only trades weather His profile: How he does it: -> only trades weather markets (temperature in NY, London, Seoul) -> buys NO at 94-98c when the forecast makes the bucket nearly impossible -> position sizes from $100 to $1,200, never bigger -> wins ~95c on the dollar, thousands of times -> doesn't predict weather, prices what the forecast already locked in The part most people miss: His edge isn't in being a meteorologist -> it's in noticing that the day before resolution, the market still trades at 94c instead of 99c That 5c gap, multiplied across hundreds of trades, is the entire game This is exactly the boring-but-profitable wallet pattern from the article above 👇 Copy him with me:
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This trader turned $25 into $12,400 on a single weather bet on Polymarket Made $45,000 in the last month alone -> and he only trades weather His profile: How he does it: -> only trades weather markets (temperature in NY, London, Seoul) -> buys NO at 94-98c when the forecast makes the bucket nearly impossible -> position sizes from $100 to $1,200, never bigger -> wins ~95c on the dollar, thousands of times -> doesn't predict weather, prices what the forecast already locked in The part most people miss: His edge isn't in being a meteorologist -> it's in noticing that the day before resolution, the market still trades at 94c instead of 99c That 5c gap, multiplied across hundreds of trades, is the entire game This is exactly the boring-but-profitable wallet pattern from the article above 👇 Copy him with me:

Paone

11,474 次观看 • 5 个月前

+$2,912 ON WEATHER MARKETS WITHOUT PREDICTING A SINGLE TEMPERATURE 80.6% win rate. 1,200+ positions. fully automated the pattern is simple and works on any weather market: > every specific temperature range has a low hit probability > market often overprices narrow exact bands at $0.05-$0.10 > the No side sits at $0.90-$1.00 -> almost free money > buy No across 20+ cities simultaneously > 87.7% resolve in your favor by pure base-rate math > run it with a bot 24/7 so you never miss a market you don't need a weather model -> you need to understand that exact values almost never land > full profile: real edge survives stress. this one did
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+$2,912 ON WEATHER MARKETS WITHOUT PREDICTING A SINGLE TEMPERATURE 80.6% win rate. 1,200+ positions. fully automated the pattern is simple and works on any weather market: > every specific temperature range has a low hit probability > market often overprices narrow exact bands at $0.05-$0.10 > the No side sits at $0.90-$1.00 -> almost free money > buy No across 20+ cities simultaneously > 87.7% resolve in your favor by pure base-rate math > run it with a bot 24/7 so you never miss a market you don't need a weather model -> you need to understand that exact values almost never land > full profile: real edge survives stress. this one did

Mr. Buzzoni

58,047 次观看 • 5 个月前

8 free Polymarket Trading Bots on GitHub (from Beginner Friendly to Advanced Level). Each of these repos comes with a detailed step by step setup and usage guide in English. > Beginner Level - 5 min setup 1. This bot includes 120 ready to use strategies and tools for trading on prediction markets (Binance-Polymarket latency, Smart Routing, Penny Clipper, Momentum, DCA bots, Expiry Fade and more). It was built by a Cambridge computer science student who won a hackathon with this bot. GitHub: 2. A trading bot with a Smart Money strategy - it finds top traders in selected markets, filters them by Pnl, win rate, stable performance and then creates a list for automated copy trading. GitHub: 3. This is a bot toolkit that includes Polymarket - Kalshi arbitrage, whale alerts, market making, spread farming, sports trading and more. GitHub: 4. A weather trading bot from Chinese dev that analyzes different sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the latest temperature data and generate a detailed weather report for a specific city and day. GitHub: 5. A huge collection of 30+ free trading bots and services for prediction markets. GitHub: > Advanced bot setup 1. This bot analyzes the real trading behavior of any Polymarket trader. It finds repeated patterns in his trades, shows which strategies he uses and helps you understand how to adapt them to your own trading. GitHub: 2. A bot that automatically manages all your limit orders on Polymarket to maximize liquidity rewards. GitHub: > A full ML weather model 1. A machine learning weather model that learns from weather forecasting errors. Instead of blindly trusting forecasts, it analyzes how different weather sources have historically overestimated or underestimated temperature values in specific cities and conditions. Then it automatically adjusts new forecasts to produce more accurate predictions. GitHub: All of these bots also support Dry Run mode, so you can test them on real markets without risking any funds.
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8 free Polymarket Trading Bots on GitHub (from Beginner Friendly to Advanced Level). Each of these repos comes with a detailed step by step setup and usage guide in English. > Beginner Level - 5 min setup 1. This bot includes 120 ready to use strategies and tools for trading on prediction markets (Binance-Polymarket latency, Smart Routing, Penny Clipper, Momentum, DCA bots, Expiry Fade and more). It was built by a Cambridge computer science student who won a hackathon with this bot. GitHub: 2. A trading bot with a Smart Money strategy - it finds top traders in selected markets, filters them by Pnl, win rate, stable performance and then creates a list for automated copy trading. GitHub: 3. This is a bot toolkit that includes Polymarket - Kalshi arbitrage, whale alerts, market making, spread farming, sports trading and more. GitHub: 4. A weather trading bot from Chinese dev that analyzes different sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the latest temperature data and generate a detailed weather report for a specific city and day. GitHub: 5. A huge collection of 30+ free trading bots and services for prediction markets. GitHub: > Advanced bot setup 1. This bot analyzes the real trading behavior of any Polymarket trader. It finds repeated patterns in his trades, shows which strategies he uses and helps you understand how to adapt them to your own trading. GitHub: 2. A bot that automatically manages all your limit orders on Polymarket to maximize liquidity rewards. GitHub: > A full ML weather model 1. A machine learning weather model that learns from weather forecasting errors. Instead of blindly trusting forecasts, it analyzes how different weather sources have historically overestimated or underestimated temperature values in specific cities and conditions. Then it automatically adjusts new forecasts to produce more accurate predictions. GitHub: All of these bots also support Dry Run mode, so you can test them on real markets without risking any funds.

Recogard

58,826 次观看 • 2 个月前

HOW 3 WEATHER MARKETS TURNED $50 INTO $30K How? Professional meteorological models like ECMWF March results: > Tokyo: $25 -> $12,452 > Chicago: $24 -> $12,398 > Tokyo: $16 -> $8,106 This is the work of a trader who leverages advanced analytics and automation. His strategy focuses on spotting undervalued outcomes that the market considers highly unlikely. Most market participants rely on popular weather apps like AccuWeather or CNN Weather. These services: - use averaged data - update less frequently - smooth out extreme scenarios - don’t always reflect the actual resolution sources used by prediction markets Instead, this trader taps into professional meteorological models to gain an edge Model hierarchy by region: ECMWF AIFS ENS -> MetUM (UK and Western Europe) -> ICON-EU (Central and Eastern Europe) Example scenario: Polymarket market - "Will the temperature in London exceed 25°C?" Forecasts: > AccuWeather - 24°C > ECMWF - 25°C > MetUM - 27°C Polymarket pricing: YES shares trading at $0.02 (implying a 2% probability). Around 80% of traders would follow AccuWeather and buy NO. That’s exactly why weather markets remain an underrated niche with significant inefficiencies. Finding and tracking these opportunities manually is extremely difficult. But you can simply copy this trader: Trader address: 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 Btw, you’ll receive a 100% bonus on your first deposit.
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HOW 3 WEATHER MARKETS TURNED $50 INTO $30K How? Professional meteorological models like ECMWF March results: > Tokyo: $25 -> $12,452 > Chicago: $24 -> $12,398 > Tokyo: $16 -> $8,106 This is the work of a trader who leverages advanced analytics and automation. His strategy focuses on spotting undervalued outcomes that the market considers highly unlikely. Most market participants rely on popular weather apps like AccuWeather or CNN Weather. These services: - use averaged data - update less frequently - smooth out extreme scenarios - don’t always reflect the actual resolution sources used by prediction markets Instead, this trader taps into professional meteorological models to gain an edge Model hierarchy by region: ECMWF AIFS ENS -> MetUM (UK and Western Europe) -> ICON-EU (Central and Eastern Europe) Example scenario: Polymarket market - "Will the temperature in London exceed 25°C?" Forecasts: > AccuWeather - 24°C > ECMWF - 25°C > MetUM - 27°C Polymarket pricing: YES shares trading at $0.02 (implying a 2% probability). Around 80% of traders would follow AccuWeather and buy NO. That’s exactly why weather markets remain an underrated niche with significant inefficiencies. Finding and tracking these opportunities manually is extremely difficult. But you can simply copy this trader: Trader address: 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 Btw, you’ll receive a 100% bonus on your first deposit.

Kursakov

17,104 次观看 • 5 个月前

This quant bot turned $2.5K into $861,000 on Polymarket using pure math his profile: How he does it: -> only trades binary markets (BTC Up/Down, NBA spreads, esports) -> buys NO at 5-65c when implied probability is mispriced -> 29,443 predictions, biggest single win: $35,500 on a Bitcoin market -> wins ~95c on the dollar, thousands of times -> doesn't predict outcomes, prices the gap between actual and implied probability The part most people miss: his edge isn't picking winners it's stacking 5-10 mispriced contracts at the same time across correlated markets when his model is right, multiple bets pay simultaneously The new way to copy traders like him: a parlay bot that combines all his correlated Polymarket bets into one ticket -> multiplied payout when several resolve right link: Always dyor
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This quant bot turned $2.5K into $861,000 on Polymarket using pure math his profile: How he does it: -> only trades binary markets (BTC Up/Down, NBA spreads, esports) -> buys NO at 5-65c when implied probability is mispriced -> 29,443 predictions, biggest single win: $35,500 on a Bitcoin market -> wins ~95c on the dollar, thousands of times -> doesn't predict outcomes, prices the gap between actual and implied probability The part most people miss: his edge isn't picking winners it's stacking 5-10 mispriced contracts at the same time across correlated markets when his model is right, multiple bets pay simultaneously The new way to copy traders like him: a parlay bot that combines all his correlated Polymarket bets into one ticket -> multiplied payout when several resolve right link: Always dyor

Paone

30,970 次观看 • 4 个月前

I’m making $2,200/weekly from Weather Arbitrage. I’m not posting this as clickbait. If you can’t replicate it, feel free to unfollow me. About a month ago, I found a Polymarket Account using a clever strategy: Weather Arbitrage. It caught my attention. After digging into how it works, I saw that this trader focuses only on daily temperature markets for cities like NYC, LA, Atlanta, Denver, Chicago, Seoul, London, Shanghai, San Francisco, and Munich. The key insight is that each Polymarket weather market resolves based on a specific airport weather station, for example NYC = LaGuardia / KLGA, Dallas = Love Field / KDAL, while most retail traders rely on city center data. The temperature difference between those can be 3–8°F. According to his profile: > He built a bot that profits from this gap between official weather data and uninformed retail traders. I figured I wasn’t skilled enough to build something like that myself, so I set up a copy trading bot with 0% fees and 100 ms latency: > This copy trading bot is the best solution on the market, at least because it doesn’t charge any fees. Now I copy his trades exactly and made almost $10,000 in a month. It actually works, guys. Check it out. This isn’t clickbait or a joke.
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I’m making $2,200/weekly from Weather Arbitrage. I’m not posting this as clickbait. If you can’t replicate it, feel free to unfollow me. About a month ago, I found a Polymarket Account using a clever strategy: Weather Arbitrage. It caught my attention. After digging into how it works, I saw that this trader focuses only on daily temperature markets for cities like NYC, LA, Atlanta, Denver, Chicago, Seoul, London, Shanghai, San Francisco, and Munich. The key insight is that each Polymarket weather market resolves based on a specific airport weather station, for example NYC = LaGuardia / KLGA, Dallas = Love Field / KDAL, while most retail traders rely on city center data. The temperature difference between those can be 3–8°F. According to his profile: > He built a bot that profits from this gap between official weather data and uninformed retail traders. I figured I wasn’t skilled enough to build something like that myself, so I set up a copy trading bot with 0% fees and 100 ms latency: > This copy trading bot is the best solution on the market, at least because it doesn’t charge any fees. Now I copy his trades exactly and made almost $10,000 in a month. It actually works, guys. Check it out. This isn’t clickbait or a joke.

igorizuchaetcrypty

53,836 次观看 • 5 个月前

How to make money on the weather using Polymarket I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto—focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( – $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > ( - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > ( — Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules >Tropical Tidbits ( - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high >Climate Reanalyzer ( - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities >Windy ( - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online ( - 100+ years of historical location data NOAA Weather Prediction ? >Center ( - short forecasts for precipitation, anomalies. Climate Prediction Center ( - long-term ENSO, droughts >Open-Meteo ( - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. >OpenWeatherMap ( = Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. >Visual Crossing Weather ( - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities >WeatherAPI. com ( - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha information
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How to make money on the weather using Polymarket I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto—focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( – $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > ( - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > ( — Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules >Tropical Tidbits ( - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high >Climate Reanalyzer ( - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities >Windy ( - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online ( - 100+ years of historical location data NOAA Weather Prediction ? >Center ( - short forecasts for precipitation, anomalies. Climate Prediction Center ( - long-term ENSO, droughts >Open-Meteo ( - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. >OpenWeatherMap ( = Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. >Visual Crossing Weather ( - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities >WeatherAPI. com ( - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha information

Aleiah

77,547 次观看 • 8 个月前

How to make money on the weather using Polymarket I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto-focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( - $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > - Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules > - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high > - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities > - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online - 100+ years of historical location data NOAA Weather Prediction > - short forecasts for precipitation, anomalies. Climate Prediction Center - long-term ENSO, droughts > - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. > - Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. > - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities > - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha information
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How to make money on the weather using Polymarket I've been noticing more and more traders quietly printing on Polymarket's weather markets lately - and the category is exploding for a reason. Weather has always been super predictable for meteorologists (and us normals) right up to the day of. The whole point? You can earn easy, near-certain yield just knowing it'll rain in London tomorrow. I'm sharing a finished tutorial with you. Here is a small list of traders 1. gopfan2 ( - The absolute leader in weather. Earned over $2M in net profit by focusing on temperature and precipitation. Strategy - buy Yes below 15 cents, No above 45 cents, with risks of less than $1 per position. It dominates the NYC and London markets where the weather is predictable 2. enzocostapt81 ( is a weather-exclusive trader whose profile shows a complete wipeout in resolved positions-no active/open trades, current positions value $0.00, and all listed markets (resolved) at -100% P/L. The trader focused solely on daily/precise temperature predictions in major cities like New York City and London. 3. 0x594edb9112f526fa6a80b8f858a6379c8a2c1c11 ( 100% of active positions are weather/temperature markets across cities like Dallas, London, Seattle, Atlanta, NYC, and Toronto-focused on precise daily highs/thresholds/ranges. 4. meropi ( - Earned ~$30k on micro bets ($1-3) with multipliers up to 500x. Automated bets on temperature rise for 0.01 cents. Focus on speed to capture momentum in daily markets. One of the most stable in weather 5. 1pixel ( - $18.5k profit from $2.3k deposit, weather only (NYC and London) 6. erb80 ( Dominant focus-two massive Atlanta temperature range bets for Dec 17, with enormous share volume at ultra-low entries (0.1¢) turning into huge unrealized gains (+49,550% on the main one) 7. Hans323 ( - Earned $1.1M on one temperature trade in London. Started with $741 in January 2025 and increased to $87k net profit for the year 8. securebet ( - Turned $7 into $640 (+9244%) on a series of temperature bets in NYC and Seattle. 3077 predictions, top 0.04% by metrics. Focus on small bets ($3-20) with high growth on low quotes. High win rate thanks to NOAA data 9. automatedAItradingbot ( Micro/low-cost bets (0.4¢–15¢) on specific outcomes, especially weather thresholds in Seoul/London and fighter matchups.Explosive wins (300%+ on select weather 1,000–5,000% average ROI across successful weather specialists based on this traders Tools and Automation > - Built specifically for Polymarket weather traders. Offers real-time multi-model forecasts (GFS, ECMWF, etc.), temperature range dashboards, climate pattern guides per city/station, and settlement station details. Includes educational guides on seasonal biases and forecasting challenges—highly recommended for NYC/London/Atlanta markets. > - Free guide/resource hub for weather betting on Polymarket. Covers market overviews, settlement rules > - US GFS and ECMWF Europe models for temperature, precipitation, hurricane forecasts. Updates every 6 hours. Ideal for comparing models if 3+ agree, the probability is high > - real-time maps of air/ocean temperature, precipitation anomalies. With historical context for calculating probabilities > - interactive maps of wind, temperature, rain, snow. 10+ models, for local events NOAA Climate Data Online - 100+ years of historical location data NOAA Weather Prediction > - short forecasts for precipitation, anomalies. Climate Prediction Center - long-term ENSO, droughts > - Completely free open-source weather API with no key required. Provides GFS, ECMWF-derived, and ensemble forecasts for temperature, precipitation, and more at hourly/sub-hourly resolution globally. Excellent for scripting quick checks on NYC/London highs or comparing multiple models. Direct API calls make it ideal for automation or batch probability calculations. > - Free tier gives current conditions, 5-day/3-hour forecasts, and 16-day daily forecasts. Good for real-time verification and basic historical pulls (limited free). Use for cross-checking Polymarket ranges before resolution. > - Free tier includes historical data (50+ years), current conditions, hourly/sub-hourly forecasts, and alerts. Strong for querying specific cities > - Free plan covers real-time, hourly, daily forecasts (up to 14 days), historical data (from 2010), and bulk requests. Reliable for urban stations and includes marine/pollen extras if needed. Quick Tips for Using These in Trading >>>Cross-verify 3+ models (e.g., GFS + ECMWF via Open-Meteo + Windy) → if 80%+ agree on a range/threshold, probability is often very high for "Yes" bets under 10-15¢. >>>Focus on major stations (e.g., Central Park for NYC, Heathrow for London) - check settlement rules on Polymarket pages. >>>ADD TO BOOKMARKS so you don't lose alpha information

Valentin

17,150 次观看 • 4 个月前

HydraFusion Explained. Part I: How does the Copilot engine know what to optimize for? Your prompt is evaluated across 4 dimensions: ➡ Does it require deep reasoning? (aka. reasoning depth) ➡ Is it a sophisticated problem? (aka. code generation complexity) ➡ Is it untangling a complicated mess? (aka. debugging difficulty) ➡ Is it dominated by tool-use? (aka. tool orchestration needs) Based on this evaluation, a HyDRA score is assigned to determine the capability profile your task needs the most and to establish a quality bar. Part II: How does it choose a model? Note: It doesn' t pick one model to handle the entire job e2e, (that's Auto mode). Instead, it selects 1 of 3 execution workflows and assigns the best model at different stages based on the HyDRA score: 1️⃣ Single ⚙️ How it works: A single model completes the task from start to finish. ⚖️ Rationale: The task comfortably meets the quality bar with one model. Multi-model orchestration would add latency and cost with no meaningful quality gain. 2️⃣ Cascade ⚙️ How it works: A lightweight, cost-efficient model generates the solution. This draft is evaluated against a quality gate and if it falls short of the quality bar, the entire task escalates to a stronger, frontier model. ⚖️ Rationale: Only bring in the big guns when there is concrete evidence that a lightweight model won't meet the quality threshold. 3️⃣ Critique ⚙️ How it works: A lightweight model drafts the initial code and tool interactions. An independent, read-only frontier model reviews that draft and provides feedback. The original lightweight model then performs any targeted revision(s) before the final response is sent to the user. ⚖️ Rationale: Writing code (output tokens) is expensive while reviewing code (input tokens) is cheap. Instead of incurring the cost of a powerhouse writing hundreds of lines from scratch, a cost-efficient model writes the first draft, and the frontier model just reviews it and points out fixes. HydraFusion is available in experimental preview on the GitHub Copilot CLI: /experimental on, /model and select Hydrafusion (Research Preview)
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HydraFusion Explained. Part I: How does the Copilot engine know what to optimize for? Your prompt is evaluated across 4 dimensions: ➡ Does it require deep reasoning? (aka. reasoning depth) ➡ Is it a sophisticated problem? (aka. code generation complexity) ➡ Is it untangling a complicated mess? (aka. debugging difficulty) ➡ Is it dominated by tool-use? (aka. tool orchestration needs) Based on this evaluation, a HyDRA score is assigned to determine the capability profile your task needs the most and to establish a quality bar. Part II: How does it choose a model? Note: It doesn' t pick one model to handle the entire job e2e, (that's Auto mode). Instead, it selects 1 of 3 execution workflows and assigns the best model at different stages based on the HyDRA score: 1️⃣ Single ⚙️ How it works: A single model completes the task from start to finish. ⚖️ Rationale: The task comfortably meets the quality bar with one model. Multi-model orchestration would add latency and cost with no meaningful quality gain. 2️⃣ Cascade ⚙️ How it works: A lightweight, cost-efficient model generates the solution. This draft is evaluated against a quality gate and if it falls short of the quality bar, the entire task escalates to a stronger, frontier model. ⚖️ Rationale: Only bring in the big guns when there is concrete evidence that a lightweight model won't meet the quality threshold. 3️⃣ Critique ⚙️ How it works: A lightweight model drafts the initial code and tool interactions. An independent, read-only frontier model reviews that draft and provides feedback. The original lightweight model then performs any targeted revision(s) before the final response is sent to the user. ⚖️ Rationale: Writing code (output tokens) is expensive while reviewing code (input tokens) is cheap. Instead of incurring the cost of a powerhouse writing hundreds of lines from scratch, a cost-efficient model writes the first draft, and the frontier model just reviews it and points out fixes. HydraFusion is available in experimental preview on the GitHub Copilot CLI: /experimental on, /model and select Hydrafusion (Research Preview)

Julia Muiruri

12,687 次观看 • 19 天前

This HFT bot is about to cross $1M profit trading 5-min BTC markets and making $10,000/day I traced his trades using Claude → backtested the strategy on 72M trades dataset the edge is that he runs both sides of the same window at once, then lets a probability model decide where the real money is that's the floor. the edge on top is directional: edge = fair_prob - market_price for each window the bot estimates the true probability BTC moves a direction in the next few minutes then fades the crowd when the price disagrees. that's why his fills run from 21¢ longshots to 99¢ near-locks across BTC and ETH Profile:
0:12

This HFT bot is about to cross $1M profit trading 5-min BTC markets and making $10,000/day I traced his trades using Claude → backtested the strategy on 72M trades dataset the edge is that he runs both sides of the same window at once, then lets a probability model decide where the real money is that's the floor. the edge on top is directional: edge = fair_prob - market_price for each window the bot estimates the true probability BTC moves a direction in the next few minutes then fades the crowd when the price disagrees. that's why his fills run from 21¢ longshots to 99¢ near-locks across BTC and ETH Profile:

Ricker

24,662 次观看 • 3 个月前

AUTOMATE POLYMARKET BOT WITH CLAUDE! Now, since Claude can control your computer, things are changing fast, so I decided to try a few strategies I said, Claude: "Research for the best options to profit through Polymarket using my PC" He said that simple trading is basically gambling, you can also build a bot that arbitrages, trades, etc., but it takes ~months Then he said, "Copytrading." So I asked him to fetch wallets that I can copytrade and how I can copytrade them, what is the strategy Couple of hours and I had a running monitoring bot that fetched wallets and filtered them by: - PnL - Markets they are trading - Trades a day - Position size - Portfolio size - Strategy of trading Based on that, I asked him to consider options of copytrading, fixed amount, % of portfolio, or same risk management, what slippage He gave me 2 wallets that traded 5-15 min markets and said: "These wallets will be profitable for copytrading using: 5% slippage, one of them with a fixed amount, another with RM 1x ratio copytrading" Since these wallets didn't have a large portfolio, it really worked and it started copytrading using this TG bot Bot: It's ~1 hour since copytrading started and so far I have not made much profit, but testing looks great and Claude decided to test only for 20 trades/per day, firstly Make sure to follow me and turn notifs on, will share with you the rest of the journey here and continue finding new strategies
0:16

AUTOMATE POLYMARKET BOT WITH CLAUDE! Now, since Claude can control your computer, things are changing fast, so I decided to try a few strategies I said, Claude: "Research for the best options to profit through Polymarket using my PC" He said that simple trading is basically gambling, you can also build a bot that arbitrages, trades, etc., but it takes ~months Then he said, "Copytrading." So I asked him to fetch wallets that I can copytrade and how I can copytrade them, what is the strategy Couple of hours and I had a running monitoring bot that fetched wallets and filtered them by: - PnL - Markets they are trading - Trades a day - Position size - Portfolio size - Strategy of trading Based on that, I asked him to consider options of copytrading, fixed amount, % of portfolio, or same risk management, what slippage He gave me 2 wallets that traded 5-15 min markets and said: "These wallets will be profitable for copytrading using: 5% slippage, one of them with a fixed amount, another with RM 1x ratio copytrading" Since these wallets didn't have a large portfolio, it really worked and it started copytrading using this TG bot Bot: It's ~1 hour since copytrading started and so far I have not made much profit, but testing looks great and Claude decided to test only for 20 trades/per day, firstly Make sure to follow me and turn notifs on, will share with you the rest of the journey here and continue finding new strategies

symbiote

44,193 次观看 • 6 个月前

Mechanical arbitrage. The best Polymarket strategy. In one month, using this strategy, a Polymarket trader turned $300 into $300K. A human, without gambling, wouldn’t even come close to repeating that result. So what’s the point? The account I’m going to talk about below — it’s a bot. No human intervention at all. It trades only BTC on 15-minute Up/Down windows. It enters only after a confirmed impulse on Binance and Coinbase, while Polymarket’s price hasn’t “caught up” yet. That’s the trick the platform still hasn’t fixed. Losses are almost negligible because the wins cover everything. The price at entry is already “wrong” from the market’s perspective, and the bot catches this short-lived gap. According to his profile: > Polycule helps me copy his trades: > Bug or feature? What do you think?
0:17

Mechanical arbitrage. The best Polymarket strategy. In one month, using this strategy, a Polymarket trader turned $300 into $300K. A human, without gambling, wouldn’t even come close to repeating that result. So what’s the point? The account I’m going to talk about below — it’s a bot. No human intervention at all. It trades only BTC on 15-minute Up/Down windows. It enters only after a confirmed impulse on Binance and Coinbase, while Polymarket’s price hasn’t “caught up” yet. That’s the trick the platform still hasn’t fixed. Losses are almost negligible because the wins cover everything. The price at entry is already “wrong” from the market’s perspective, and the bot catches this short-lived gap. According to his profile: > Polycule helps me copy his trades: > Bug or feature? What do you think?

igorizuchaetcrypty

16,033 次观看 • 8 个月前

An Anthropic team lead emailed me. From a corporate address. I thought it was a scam. "Your Polymarket wallet is on page 14 of our internal research deck" A screenshot. My wallet. Inside a slide labeled "external validation - top 0.1% exit structure" Their model flagged me. Not a human. Claude 4.7 picked my wallet out of 12,000 during training. "You exit before the volume spike. Every single time. We couldn't replicate that in our sandbox until 4.7" He asked me to switch to Opus 4.7 and post my results publicly. "I need proof this works in the wild. Not in our evals. No one trusts benchmarks anymore" I switched in 20 minutes. Didn't touch a single prompt. First 48 hours. 11 trades. 10 green. The one red lost $40. The greens made $3,200. "Your old model captured 68% of the move. 4.7 captures 89%. That's not tuning. That's a different brain" Same repos his team benchmarks against. Open source. Full stack. I asked why Anthropic cares about one random trader. "Because your live wallet is better proof than any paper we could publish" 187 trades since the switch. 80% hit. Sharpe sitting at 3.04. Breakdown by category: Crypto: +$7,400 Politics: +$5,100 Weather derivatives: +$3,500 Macro: +$2,300 Total: +$18,300 from $200 seed. 31 days. Bot for those who don't build: He asked me not to share the slides. I didn't. But I'm sharing everything else.
0:19

An Anthropic team lead emailed me. From a corporate address. I thought it was a scam. "Your Polymarket wallet is on page 14 of our internal research deck" A screenshot. My wallet. Inside a slide labeled "external validation - top 0.1% exit structure" Their model flagged me. Not a human. Claude 4.7 picked my wallet out of 12,000 during training. "You exit before the volume spike. Every single time. We couldn't replicate that in our sandbox until 4.7" He asked me to switch to Opus 4.7 and post my results publicly. "I need proof this works in the wild. Not in our evals. No one trusts benchmarks anymore" I switched in 20 minutes. Didn't touch a single prompt. First 48 hours. 11 trades. 10 green. The one red lost $40. The greens made $3,200. "Your old model captured 68% of the move. 4.7 captures 89%. That's not tuning. That's a different brain" Same repos his team benchmarks against. Open source. Full stack. I asked why Anthropic cares about one random trader. "Because your live wallet is better proof than any paper we could publish" 187 trades since the switch. 80% hit. Sharpe sitting at 3.04. Breakdown by category: Crypto: +$7,400 Politics: +$5,100 Weather derivatives: +$3,500 Macro: +$2,300 Total: +$18,300 from $200 seed. 31 days. Bot for those who don't build: He asked me not to share the slides. I didn't. But I'm sharing everything else.

rari

23,580 次观看 • 5 个月前

let me explain what Anthropic just did they built an AI model so good at finding security vulnerabilities that they have refused to release it meet Claude Mythos → it’s Anthropic’s newest frontier model and it’s not available to the public. not because it’s not ready. because it’s too dangerous → Mythos found tens of thousands of zero day vulnerabilities across every major operating system and web browser… many of them 1 to 2 decades old. for context… Opus 4.6 found about 500. Mythos found tens of thousands → it found vulnerabilities in the Linux kernel. a 27 year old vulnerability in OpenBSD. a 16 year old vulnerability in FFmpeg → it doesn’t just find bugs. it writes the exploits too. that’s the part that scared them → so instead of releasing it… Anthropic has created Project Glasswing. a cybersecurity initiative where they hand picked 40+ companies to use Mythos for defense only → the partner list reads like a who’s who of tech… Amazon, Apple, Microsoft, Google, Nvidia, Broadcom, Cisco, CrowdStrike, Palo Alto Networks, JPMorgan, the Linux Foundation → Anthropic is giving up to $100 million in usage credits to these partners and $4 million to open source security organizations → they’re briefing CISA and the Commerce Department on how to handle this → the benchmarks are truly insane… Mythos hit 77.8% on SWE-bench Pro where Opus 4.6 scored 53.4%. hit 93.9% on SWE-bench Verified where Opus 4.6 scored 80.8% → Anthropic’s head of frontier red team said this is “the first time a model is this good that we decided to approach release in a very different way” this is the first time an AI company has held back a model because it was too capable not too expensive. not too slow. too dangerous and instead of locking it in a vault they weaponized it for defense and gave it to the companies that run the internet that’s either the most responsible thing an AI company has ever done… or the scariest only time will tell
0:11

let me explain what Anthropic just did they built an AI model so good at finding security vulnerabilities that they have refused to release it meet Claude Mythos → it’s Anthropic’s newest frontier model and it’s not available to the public. not because it’s not ready. because it’s too dangerous → Mythos found tens of thousands of zero day vulnerabilities across every major operating system and web browser… many of them 1 to 2 decades old. for context… Opus 4.6 found about 500. Mythos found tens of thousands → it found vulnerabilities in the Linux kernel. a 27 year old vulnerability in OpenBSD. a 16 year old vulnerability in FFmpeg → it doesn’t just find bugs. it writes the exploits too. that’s the part that scared them → so instead of releasing it… Anthropic has created Project Glasswing. a cybersecurity initiative where they hand picked 40+ companies to use Mythos for defense only → the partner list reads like a who’s who of tech… Amazon, Apple, Microsoft, Google, Nvidia, Broadcom, Cisco, CrowdStrike, Palo Alto Networks, JPMorgan, the Linux Foundation → Anthropic is giving up to $100 million in usage credits to these partners and $4 million to open source security organizations → they’re briefing CISA and the Commerce Department on how to handle this → the benchmarks are truly insane… Mythos hit 77.8% on SWE-bench Pro where Opus 4.6 scored 53.4%. hit 93.9% on SWE-bench Verified where Opus 4.6 scored 80.8% → Anthropic’s head of frontier red team said this is “the first time a model is this good that we decided to approach release in a very different way” this is the first time an AI company has held back a model because it was too capable not too expensive. not too slow. too dangerous and instead of locking it in a vault they weaponized it for defense and gave it to the companies that run the internet that’s either the most responsible thing an AI company has ever done… or the scariest only time will tell

klöss

21,318 次观看 • 5 个月前

Predicting the next word "only" is sufficient for language models to learn a large body of knowledge that enables then to code, answer questions, understand many topics, chat, and so on. This is clear to many researchers now, and there are nice tutorials on why this works by Ilya Sutskever resorting to compression ( ) and by Geoffrey Hinton ( ). However, the emergence of types of understanding is not unique to language models. In by Misha Denil and Brandon Amos the authors trained models to predict the next few time stems of over a hundred robot hand sensors (Touch, Gyro, Accelerometer, Joint Info, Actuator Info, etc.). They ten found out that they could regress the shape of the thing the hand was touching from the activations of the neural networks using probes. That is, the model developed an internal representation of shapes even though it was simply used to predict "only" the next few senses. Awareness follows from simple predictions and interaction with the world.
0:14

Predicting the next word "only" is sufficient for language models to learn a large body of knowledge that enables then to code, answer questions, understand many topics, chat, and so on. This is clear to many researchers now, and there are nice tutorials on why this works by Ilya Sutskever resorting to compression ( ) and by Geoffrey Hinton ( ). However, the emergence of types of understanding is not unique to language models. In by Misha Denil and Brandon Amos the authors trained models to predict the next few time stems of over a hundred robot hand sensors (Touch, Gyro, Accelerometer, Joint Info, Actuator Info, etc.). They ten found out that they could regress the shape of the thing the hand was touching from the activations of the neural networks using probes. That is, the model developed an internal representation of shapes even though it was simply used to predict "only" the next few senses. Awareness follows from simple predictions and interaction with the world.

Nando de Freitas

134,406 次观看 • 2 年前

An Anthropic engineer watched me trade from across the table at a WeWork in SF I had my laptop open. Four agents running. Green charts. Live trades scrolling. He was on a Zoom call. Muted himself. Walked over. "Are you running Claude against live prediction markets right now" I told him. Claude Code. Two repos. $25 a month. He pulled up a chair. "I helped build the model you're using. I've never seen anyone wire it to live trades like this" I showed him the dataset. 86 million trades. Every wallet. Every entry. Every exit. He stared at it. "We tested this internally. You give Claude a dataset and don't tell it what to look for. It finds the winning wallets. Then it finds WHY they win. Then it copies the pattern. We never shipped it because legal killed it" I told him I did exactly that. One weekend. Claude Code found the exit logic on its own. Top wallets exit before resolution 91% of the time. They capture 86% of expected value. Cut losers at 12%. Everyone else captures 58% and holds to 41%. "That's the exact finding from our internal eval. Except ours took a team of eight and four months" I showed him the scanner. Three commands. 500+ markets. No API key. Claude scores them all in 20 minutes. "You're using our model to beat markets we're not allowed to touch. On infra that costs less than my lunch" My setup: Claude API - $20/mo VPS - $5/mo poly_data - free polymarket-cli - free 214 trades. 74% win rate. +$9,400. 19 days. I showed him the full breakdown. Every repo. Every command. Every dollar. Copytrade here: He read it for five minutes. Then looked up. "If my manager sees this he's going to lose his mind. You just proved our model works in production and we've been sitting on it for a year" He DM'd me that night. "Take this down before someone at Anthropic finds it" Too late.
0:19

An Anthropic engineer watched me trade from across the table at a WeWork in SF I had my laptop open. Four agents running. Green charts. Live trades scrolling. He was on a Zoom call. Muted himself. Walked over. "Are you running Claude against live prediction markets right now" I told him. Claude Code. Two repos. $25 a month. He pulled up a chair. "I helped build the model you're using. I've never seen anyone wire it to live trades like this" I showed him the dataset. 86 million trades. Every wallet. Every entry. Every exit. He stared at it. "We tested this internally. You give Claude a dataset and don't tell it what to look for. It finds the winning wallets. Then it finds WHY they win. Then it copies the pattern. We never shipped it because legal killed it" I told him I did exactly that. One weekend. Claude Code found the exit logic on its own. Top wallets exit before resolution 91% of the time. They capture 86% of expected value. Cut losers at 12%. Everyone else captures 58% and holds to 41%. "That's the exact finding from our internal eval. Except ours took a team of eight and four months" I showed him the scanner. Three commands. 500+ markets. No API key. Claude scores them all in 20 minutes. "You're using our model to beat markets we're not allowed to touch. On infra that costs less than my lunch" My setup: Claude API - $20/mo VPS - $5/mo poly_data - free polymarket-cli - free 214 trades. 74% win rate. +$9,400. 19 days. I showed him the full breakdown. Every repo. Every command. Every dollar. Copytrade here: He read it for five minutes. Then looked up. "If my manager sees this he's going to lose his mind. You just proved our model works in production and we've been sitting on it for a year" He DM'd me that night. "Take this down before someone at Anthropic finds it" Too late.

Lunar

224,077 次观看 • 5 个月前

My dad told me I was wasting my life using Claude to analyze Polymarket wallets instead of "learning real trading" 2 weeks later he asked me why one weather market suddenly made someone $11,000 overnight. I didn’t know how to explain to him that half the market is now bots reacting to each other. So I started digging through GitHub trying to understand how deep this rabbit hole actually goes. The first repo that caught my attention was: A few hours later I found people building autonomous agents for Polymarket: That’s when the entire platform started looking different to me. One wallet made $87k trading weather markets. Another was making hundreds of trades a day while barely holding positions longer than 90 minutes. The highest-performing wallets didn’t even look human anymore. No emotional entries. No hesitation. No scrolling Twitter waiting for opinions. Just instant reactions to forecast changes, 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 millions of emotional humans react to events in real time. 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 forecast disagreements, Twitter activity and liquidity changes simultaneously. Humans physically cannot process information that fast anymore. Here 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.
0:19

My dad told me I was wasting my life using Claude to analyze Polymarket wallets instead of "learning real trading" 2 weeks later he asked me why one weather market suddenly made someone $11,000 overnight. I didn’t know how to explain to him that half the market is now bots reacting to each other. So I started digging through GitHub trying to understand how deep this rabbit hole actually goes. The first repo that caught my attention was: A few hours later I found people building autonomous agents for Polymarket: That’s when the entire platform started looking different to me. One wallet made $87k trading weather markets. Another was making hundreds of trades a day while barely holding positions longer than 90 minutes. The highest-performing wallets didn’t even look human anymore. No emotional entries. No hesitation. No scrolling Twitter waiting for opinions. Just instant reactions to forecast changes, 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 millions of emotional humans react to events in real time. 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 forecast disagreements, Twitter activity and liquidity changes simultaneously. Humans physically cannot process information that fast anymore. Here 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

54,853 次观看 • 4 个月前

AI will kill Polymarket. $2.2M in 2 months using probability models. This news is going to blow up the internet. Polymarket trader made $2.2M in just 2 months using AI. His account is traded entirely by a bot. I’ve heard plenty of stories about AI trading bots before, and almost all of them turned out to be scams or didn’t work properly. But this case is different and honestly I’m shocked. He uses AI probability models, training machine learning to estimate real odds based on news and social media data. If his model says an outcome has a 60% chance, while the market prices it at 50% (50¢), he buys because the market is mispricing it. According to his profile: > His prediction accuracy is 74%. That’s insane. He runs an ensemble of 10 AI models that retrain themselves every week to stay up to date. What do you think about this? This feels like the new reality.
0:15

AI will kill Polymarket. $2.2M in 2 months using probability models. This news is going to blow up the internet. Polymarket trader made $2.2M in just 2 months using AI. His account is traded entirely by a bot. I’ve heard plenty of stories about AI trading bots before, and almost all of them turned out to be scams or didn’t work properly. But this case is different and honestly I’m shocked. He uses AI probability models, training machine learning to estimate real odds based on news and social media data. If his model says an outcome has a 60% chance, while the market prices it at 50% (50¢), he buys because the market is mispricing it. According to his profile: > His prediction accuracy is 74%. That’s insane. He runs an ensemble of 10 AI models that retrain themselves every week to stay up to date. What do you think about this? This feels like the new reality.

igorizuchaetcrypty

509,887 次观看 • 9 个月前