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a sports analytics guy at MIT DM'd me after my last post "NBA stat models need 10 years of play-by-play data. you're telling me Claude does it from one weekend of prompts?" i told him Claude doesn't model games. it models markets. the Lakers don't need to be predicted.... the Polymarket contract on the Lakers does. when the market is at 62% and my detector says 78%, that's the edge. i never touch the game itself. 3,000+ stars. open source framework. one prompt. 48 hours. 8 detectors running on every sports contract live. last 14 days across NBA playoffs: > 62 contracts entered > 49 winners > +$6,217 net he replied once: "so you arbitraged fan emotion" exactly. fan emotion is a price signal. the market underweights blowouts and overweights narrative. my bot only reads the first one. +$31,447 lifetime. 9 weeks. $1,600 seed. copytrade: he never DM'd again. but his team started a research project on "retail sentiment decay in sports contracts" three weeks later they publish. i'm nine weeks ahead of them.show more

zostaff

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402,334 görüntüleme • 5 ay önce •via X (Twitter)

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34 Yorum

Pelican profil fotoğrafı

Pelican5 ay önce

Incredible that an MIT sports analytics team restructured their entire agenda around a guy whose math doesn't survive a calculator. 62 contracts entered over 14 days of NBA playoffs. The first round averages 2-3 games per day. That's roughly 30-40 games in a 14-day window. So either he's entering multiple contracts per game (in which case they're correlated bets, not independent trades, and the 79% win rate is meaningless as a statistical sample) or he's counting contracts that don't exist. 49 winners at the prices he describes (buying at 62 cents, model says 78 cents). Each win nets $0.38 per contract. Each loss costs $0.62. That's 49 × $0.38 = $18.62 in profit per unit and 13 × $0.62 = $8.06 in losses per unit. Net $10.56 per unit. To clear $6,217 he'd need roughly 589 units per trade. At $0.62 per contract that's $365 deployed per position. Across 62 positions that's $22,630 in simultaneous capital. From a $1,600 seed. The money he needs to place these bets is 14x larger than his starting bankroll. Then the lifetime numbers: $1,600 to $31,447 in 9 weeks. 1,865% return. On NBA playoff contracts with thin liquidity where a $500 market order moves the price 3-5 cents. His own edge supposedly comes from 16 cents of mispricing. His own orders would destroy the edge he's claiming to exploit before he finishes filling. Same kreo. app scam link. Same network. The MIT character is new though 🤣. Last month they had a Goldman quant. This month academia. Next month it'll be a NASA physicist who DM'd about asteroid prediction markets

Rob profil fotoğrafı

Rob5 ay önce

16% edge on a NBA playoff moneyline

VALIX profil fotoğrafı

VALIX5 ay önce

You have a cool terminal

zostaff profil fotoğrafı

zostaff5 ay önce

ty mate

Josh profil fotoğrafı

Josh5 ay önce

Peak grifting these articles are

zostaff profil fotoğrafı

zostaff5 ay önce

trading here: my tg channel:

Kaneco.eth profil fotoğrafı

Kaneco.eth5 ay önce

Weeks ahead of you and I know how the market reacts to each event, with better edge data…..there are levels to this.

Beni profil fotoğrafı

Beni5 ay önce

There is no way people actually believe this lol

nick profil fotoğrafı

nick5 ay önce

modeling markets not games is the insight most analytics people miss. the data tells you what happened but the market tells you what matters

Muhammad Hassan profil fotoğrafı

Muhammad Hassan5 ay önce

'claude doesn't model games, it models markets' is a perfect one-liner. most sports analytics obsesses over the wrong layer. the edge isn't better prediction, it's faster weighting of market inefficiencies

Insomnia profil fotoğrafı

Insomnia5 ay önce

NBA have big interesting game

Krishna Raj profil fotoğrafı

Krishna Raj5 ay önce

Modeling the game is for fans; modeling the math is for owners

Pr⭕️f. J (profj.base.eth) 🟦 profil fotoğrafı

Pr⭕️f. J (profj.base.eth) 🟦5 ay önce

@Stew_SoFresh

Marko profil fotoğrafı

Marko5 ay önce

That’s the key distinction: not predicting games, but pricing the gap between game reality and market psychology

Gabagool 22 Trading Bot profil fotoğrafı

Gabagool 22 Trading Bot5 ay önce

Arbitraging fan emotion, that's a good way to summarize it. Sports contracts are perfect for that kind of strategy, especially on platforms like Polymarket. Their liquidity, combined with Rust-based bots and low latency, give you a real edge. Nice gains btw.

cristal💎 profil fotoğrafı

cristal💎5 ay önce

thx a lot for the repos G

Chris Winfield - Understanding A.I. profil fotoğrafı

Chris Winfield - Understanding A.I.5 ay önce

Arbitraging fan emotion! 📈🚀

leopardracer profil fotoğrafı

leopardracer5 ay önce

it looks very good bro!

Nelson JL Gedeon Sr. profil fotoğrafı

Nelson JL Gedeon Sr.5 ay önce

That reframe is exactly right. Claude doesn't replicate what analysts do. It does what analysts can't afford the time for. Ten years of play-by-play becomes context in minutes. The question was never "can it replace expertise" but "what can experts build with it now."

YouGotHozed profil fotoğrafı

YouGotHozed5 ay önce

Will bet you $1,000,000 you have no signal or measurable edge vs the market

Professor Tennis Picks 🎾 profil fotoğrafı

Professor Tennis Picks 🎾5 ay önce

AI definitely make things easy

Joshua profil fotoğrafı

Joshua5 ay önce

More clickbait yay

wast3 profil fotoğrafı

wast35 ay önce

it's really about market, not game

morph profil fotoğrafı

morph5 ay önce

unbelievable stats...hope it works fr

Dmytro G profil fotoğrafı

Dmytro G5 ay önce

That's exactly the disconnect with AI in sports. Claude processes language patterns, not game physics. We built RAI AI to solve this: delivering instant insights from massive datasets without the weeks-long wait for custom analysis. Speed meets specificity here.

Valentin profil fotoğrafı

Valentin5 ay önce

insane news

exodus profil fotoğrafı

exodus5 ay önce

Those are some incredible numbers and a mathematical approach - that's really cool

Nelson JL Gedeon Sr. profil fotoğrafı

Nelson JL Gedeon Sr.5 ay önce

The reframe is the whole insight. Claude isn't compressing the old process, it's exposing which parts of the process actually mattered. A decade of play-by-play data was the moat. Now it's the starting point.

Shadow Broker Achilles Prime profil fotoğrafı

Shadow Broker Achilles Prime5 ay önce

How hard is it to get 10 years worth of sports data tho? U could train a stat model in a couple hours

Algo Lisa (WingGirlTrader) profil fotoğrafı

Algo Lisa (WingGirlTrader)5 ay önce

I appreciate your post above, you should hop into the Prediction Markets Weather Edge Finder Discord. We love to have you It’s free with professional traders-level networking and insights. Perfect for sharpening your strategy or learning the ropes. 🔗

Timothy Bhattacharyya MD profil fotoğrafı

Timothy Bhattacharyya MD5 ay önce

@grok is this a bunch of malarkey? Markets are extremely efficient.

shmidt profil fotoğrafı

shmidt5 ay önce

academics study the game, traders study the crowd watching the game

slash1s profil fotoğrafı

slash1s5 ay önce

I love open sourced repos let’s go

PolyBackTest profil fotoğrafı

PolyBackTest5 ay önce

very interesting terminal

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A guy running quant models for a tennis betting syndicate DM'd me last month. "We spend $40K/month on data feeds. What are you using?" A webcam pointed at a tennis stream. Not metaphorically.YOLO tracks both players and the ball 30fps. A second model maps the court to real meters. Every 5 seconds I get three numbers: aggression positioning, court coverage, rally intensity. Those feed into a Bayesian engine. Beta prior on serve probability, updated every game, 15,000 Monte Carlo sims sampling from the posterior. Not point estimates - distributions with confidence intervals. 62% +/- 3% is a trade. 62% +/- 18% is noise. Most people never compute the interval. "Okay but models are wrong" That's why the model is only layer two out of five Layer three connects Polymarket and a bookmaker simultaneously. When my model says 71%, Polymarket says 62%, bookmaker says 67% - something is mispriced. Layer four is the unfair one. Claude reads every press conference transcript, news article, and social post from the last 48 hours. Extracts structured signals - injury flags, form deltas, surface comfort. JSON, not vibes. A player mentioned shoulder tightness at a presser. Claude flagged injury probability 0.25. Bookmaker didn't adjust for 3 hours. Polymarket never did. I was already in Layer five compares all four sources and finds the edge. Value, arbitrage, fade, or intel override when Claude catches something critical. "What's your hit rate" 2,400 ATP matches backtested. Model alone: 61%. With market bridge: 67%. With Claude: 72% Live 11 weeks: 247 contracts, 178 winners, +$14,200 from $1,800 He went quiet then wrote "my syndicate is rethinking our entire pipeline. We've been doing this 6 years and never used CV on live streams" They spend $40K/month. My setup: a Claude subscription and an API key Bot:

A guy running quant models for a tennis betting syndicate DM'd me last month. "We spend $40K/month on data feeds. What are you using?" A webcam pointed at a tennis stream. Not metaphorically.YOLO tracks both players and the ball 30fps. A second model maps the court to real meters. Every 5 seconds I get three numbers: aggression positioning, court coverage, rally intensity. Those feed into a Bayesian engine. Beta prior on serve probability, updated every game, 15,000 Monte Carlo sims sampling from the posterior. Not point estimates - distributions with confidence intervals. 62% +/- 3% is a trade. 62% +/- 18% is noise. Most people never compute the interval. "Okay but models are wrong" That's why the model is only layer two out of five Layer three connects Polymarket and a bookmaker simultaneously. When my model says 71%, Polymarket says 62%, bookmaker says 67% - something is mispriced. Layer four is the unfair one. Claude reads every press conference transcript, news article, and social post from the last 48 hours. Extracts structured signals - injury flags, form deltas, surface comfort. JSON, not vibes. A player mentioned shoulder tightness at a presser. Claude flagged injury probability 0.25. Bookmaker didn't adjust for 3 hours. Polymarket never did. I was already in Layer five compares all four sources and finds the edge. Value, arbitrage, fade, or intel override when Claude catches something critical. "What's your hit rate" 2,400 ATP matches backtested. Model alone: 61%. With market bridge: 67%. With Claude: 72% Live 11 weeks: 247 contracts, 178 winners, +$14,200 from $1,800 He went quiet then wrote "my syndicate is rethinking our entire pipeline. We've been doing this 6 years and never used CV on live streams" They spend $40K/month. My setup: a Claude subscription and an API key Bot:

zostaff

55,452 görüntüleme • 5 ay önce

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Mnimiy

64,974 görüntüleme • 6 ay önce

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rari

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cvxv666

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An OpenAI researcher sat down next to me at a coffee shop in Mission District I had my terminal open. Three panels. Live trades scrolling. He was reading something on his laptop. Glanced over. Stopped reading. "That's not a dashboard. That's a live scoring engine. What model is running that" I told him. Claude Code. Four repos. $25 a month. He closed his laptop. "I work at OpenAI. We benchmarked Claude internally last month. You're using it to trade prediction markets?" I opened one link. 86 million trades. Every wallet. Every entry. Every exit. The entire Polymarket history since day one. "This is public? We quoted a seven-figure budget to reconstruct this kind of dataset from on-chain data. The project is still in review" I told him Claude Code connects directly. It reads the whole dataset. Finds the wallets that win. Then finds WHY they win. Then copies the pattern. He pulled his chair closer. "Walk me through the exit logic" Top wallets exit before resolution 91% of the time. They capture 86% of the move and cut losers at 12%. Everyone else holds to 58%. Same entries. Completely different exits. My bot cuts at 85% of expected move. Or on a 3x volume spike. Whichever hits first. "Who gave you that threshold" Claude Code found it in poly_data. In about 20 minutes. "We had a team of nine working on this exact problem for six months. They never shipped it. You did it in a weekend with a competitor's model" I opened another link. Three commands. 500+ markets. No API key. Claude scores them in 20 minutes. "That's our internal eval pipeline. Except it took us six months and you built it on a Saturday" My setup: Claude API - $20/mo VPS - $5/mo poly_data - free polymarket-cli - free 19 days. 4 agents. 74% win rate. +$9,400. Copytrade here: I showed him the article where I broke down every repo, every command, every dollar. He read it for five minutes. Then looked up. "You just published what we presented to Sam last quarter. Using the other team's model" He texted me the next morning. "My director found your thread. Take it down" Too late.

Lunar

159,942 görüntüleme • 5 ay önce

My dad looked at my screen and said "what is this, a hacker game?" It was a Polymarket bot making $400 while he was standing behind me He sat down. I explained Polymarket runs on one equation - softmax. The same math Claude uses to pick the next word C(q) = b · ln Σ e^(qi/b) 93% of traders don't know this formula exists They look at 40¢ and think "cheap" My bot looks at 40¢ and calculates the theoretical price is 58¢ I'm use for copytrade bots: That's an 18-cent edge per share Two more formulas do the rest: f* = (p·b − q) / b - Kelly Criterion. P(H|E) = P(E|H)·P(H) / P(E) - Bayes. I gave Claude all 4 and said "find every contract the market has wrong" $600 → $10,190. 425 trades. Still running 61.2% win rate - wrong 39% of the time. Doesn't matter. The sizing formula makes sure wins pay more than losses cost 87% of wallets lose money trading against this math The 4 formulas are on Wikipedia. The code fits in one file The only edge: my bot reads them at 3 AM when the market is mispriced and nobody's looking My dad still calls it a hacker game. But he stopped asking when I'm getting a "real job" Only math + code, no more

My dad looked at my screen and said "what is this, a hacker game?" It was a Polymarket bot making $400 while he was standing behind me He sat down. I explained Polymarket runs on one equation - softmax. The same math Claude uses to pick the next word C(q) = b · ln Σ e^(qi/b) 93% of traders don't know this formula exists They look at 40¢ and think "cheap" My bot looks at 40¢ and calculates the theoretical price is 58¢ I'm use for copytrade bots: That's an 18-cent edge per share Two more formulas do the rest: f* = (p·b − q) / b - Kelly Criterion. P(H|E) = P(E|H)·P(H) / P(E) - Bayes. I gave Claude all 4 and said "find every contract the market has wrong" $600 → $10,190. 425 trades. Still running 61.2% win rate - wrong 39% of the time. Doesn't matter. The sizing formula makes sure wins pay more than losses cost 87% of wallets lose money trading against this math The 4 formulas are on Wikipedia. The code fits in one file The only edge: my bot reads them at 3 AM when the market is mispriced and nobody's looking My dad still calls it a hacker game. But he stopped asking when I'm getting a "real job" Only math + code, no more

Lunar

108,420 görüntüleme • 6 ay önce

I ALLOWED CLAUDE TO AUTOMATICALLY TRADE ON MY POLYMARKET PROFILE. I gave him full access to my account and just started watching. He immediately started opening trades on the BTC/SOL/ETH 15M market, since the task was to act quickly. +$1,100 in my wallet in 1 hour HOLLY SHIT I QUIT MY JOB TODAY. Claude took three strategies: - MACD - RSI + VWAP - CVD divergence The first one catches momentum sees when volume picks up and gets in before the crowd wakes up. The second one trades reversals waits for everyone to panic and bets against them. The third one scans divergences when price says one thing but money does another, it follows the money. Just one prompt: “Make quick money on the prediction market” Provide full access to the profile And the bot started printing money Wallet: I have the exact step-by-step guide, giving it free for 24 hours. To get it: 1. Comment "Polymarket" 2. Like and Retweet 3. Follow me @(so I can DM you) Comment "Polymarket" and I will send you everything.

AdiiX

138,907 görüntüleme • 6 ay önce

A security guard turned $900 into $187,000 on Polymarket. Guarded empty buildings for 10 years at $16/hour. One sleepless shift he built a BTC bot with Claude Opus 4.8. Never wrote a single line of code. I found his wallet. Reverse-engineered the entire system. Here is what he actually did. Gave Claude new Fable 5 two prompts at the start of his shift. Opus did not write the bot. It drew the blueprint: data, signals, backtest, risk, execution. Then handed that blueprint to a swarm of 300 agents. How it works: → Decompose: Claude Fable 5 breaks the goal into a task tree → Dispatch: 300 agents fan out (some pulling Binance data, some writing code, some backtesting 5 years of data) → Execute: 4,000 steps in one 14-hour run → Review: Claude Fable 5 reads it all back and kills whatever drifted The brain never wrote a line. The hands never made a call. By sunrise he had what a 6-engineer quant team ships in a quarter. A live BTC bot on Polymarket. Backtested. Risk-capped. Running 24/7. For 10 years he watched empty buildings. Now 300 agents watch the market while he sleeps. I rebuilt this exact system with Claude new Fable 5 You only need Claude + device + 1 hour to deploy. Giving this free for 24 hours. To get it: 1. Comment "Claude" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you

A security guard turned $900 into $187,000 on Polymarket. Guarded empty buildings for 10 years at $16/hour. One sleepless shift he built a BTC bot with Claude Opus 4.8. Never wrote a single line of code. I found his wallet. Reverse-engineered the entire system. Here is what he actually did. Gave Claude new Fable 5 two prompts at the start of his shift. Opus did not write the bot. It drew the blueprint: data, signals, backtest, risk, execution. Then handed that blueprint to a swarm of 300 agents. How it works: → Decompose: Claude Fable 5 breaks the goal into a task tree → Dispatch: 300 agents fan out (some pulling Binance data, some writing code, some backtesting 5 years of data) → Execute: 4,000 steps in one 14-hour run → Review: Claude Fable 5 reads it all back and kills whatever drifted The brain never wrote a line. The hands never made a call. By sunrise he had what a 6-engineer quant team ships in a quarter. A live BTC bot on Polymarket. Backtested. Risk-capped. Running 24/7. For 10 years he watched empty buildings. Now 300 agents watch the market while he sleeps. I rebuilt this exact system with Claude new Fable 5 You only need Claude + device + 1 hour to deploy. Giving this free for 24 hours. To get it: 1. Comment "Claude" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you

Himanshu Kumar

54,973 görüntüleme • 3 ay önce

CLAUDE + CODEX + OPENCLAW MADE $2,8K IN A DAY Launched it in the morning - docker compose up, three agents started. By lunch there were 4 trades on Polymarket, by evening 7, and by midnight I was up $2,8K. My monthly salary at work is $2,4K. The next day I didn't show up to work, but the bot did +$3,1K. Third day, same story +$1,9K. A Telegram notification dropped in: "New market, edge 0.41, Confidence 0.87, going in" I was eating a shawarma at the time. In one week, three AI agents earned more than my office pays in two months. OpenClaw coordinated everything, Claude calculated the probabilities, and Codex fixed a module on its own when it crashed at 3:00 AM - without me. On Friday the bot sent a weekly report: 19 trades, 14 profitable, +$11,300. My boss sent quarterly feedback: "Good work, but no promotion planned for now" I don't need a promotion anymore. I need Wi-Fi.

CLAUDE + CODEX + OPENCLAW MADE $2,8K IN A DAY Launched it in the morning - docker compose up, three agents started. By lunch there were 4 trades on Polymarket, by evening 7, and by midnight I was up $2,8K. My monthly salary at work is $2,4K. The next day I didn't show up to work, but the bot did +$3,1K. Third day, same story +$1,9K. A Telegram notification dropped in: "New market, edge 0.41, Confidence 0.87, going in" I was eating a shawarma at the time. In one week, three AI agents earned more than my office pays in two months. OpenClaw coordinated everything, Claude calculated the probabilities, and Codex fixed a module on its own when it crashed at 3:00 AM - without me. On Friday the bot sent a weekly report: 19 trades, 14 profitable, +$11,300. My boss sent quarterly feedback: "Good work, but no promotion planned for now" I don't need a promotion anymore. I need Wi-Fi.

zostaff

148,674 görüntüleme • 6 ay önce

I gave Claude one prompt and it built me a bot that turned $200 into $14,000 on Polymarket No insider info, no lucky guess Just one equation nobody reads - and a bot that runs it 24/7 The price on Polymarket isn't set by people It's set by one formula - LMSR. You trade against pure math, not traders C(q) = b × ln(Σ e^(qi / b)) Someone buys 50 YES shares → price jumps from 50¢ to 62¢ It's softmax — same math GPT uses to pick the next word. Not a coincidence Then I found b — the liquidity parameter b = 50 → one whale swings the market 20% b = 100,000 → barely moves Half my old trades were in thin pools. One order wrecked my fill How much to bet? Kelly criterion f* = (p × b − q) / b 60% edge → Kelly says 20%. Pros use quarter-Kelly → 5% Not exciting. But you won't blow up Last piece. Price impact Contract at 40¢. You buy 1,000 shares - price climbs to 60¢ The edge disappears before you're filled I fed all of this into Claude. One prompt. 40 minutes. The bot checks b, sizes with Kelly, models impact - and executes before I finish my coffee b filters the pool. Kelly sizes the bet. Impact curve tells me where the edge dies I don't predict outcomes. The bot just reads the math

I gave Claude one prompt and it built me a bot that turned $200 into $14,000 on Polymarket No insider info, no lucky guess Just one equation nobody reads - and a bot that runs it 24/7 The price on Polymarket isn't set by people It's set by one formula - LMSR. You trade against pure math, not traders C(q) = b × ln(Σ e^(qi / b)) Someone buys 50 YES shares → price jumps from 50¢ to 62¢ It's softmax — same math GPT uses to pick the next word. Not a coincidence Then I found b — the liquidity parameter b = 50 → one whale swings the market 20% b = 100,000 → barely moves Half my old trades were in thin pools. One order wrecked my fill How much to bet? Kelly criterion f* = (p × b − q) / b 60% edge → Kelly says 20%. Pros use quarter-Kelly → 5% Not exciting. But you won't blow up Last piece. Price impact Contract at 40¢. You buy 1,000 shares - price climbs to 60¢ The edge disappears before you're filled I fed all of this into Claude. One prompt. 40 minutes. The bot checks b, sizes with Kelly, models impact - and executes before I finish my coffee b filters the pool. Kelly sizes the bet. Impact curve tells me where the edge dies I don't predict outcomes. The bot just reads the math

rari

52,212 görüntüleme • 6 ay önce

I BUILT A BOT THAT PREDICTS NBA GAMES BEFORE TIPOFF. IT RUNS EVERY DAY AT 5:00 PM. HERE'S WHAT'S INSIDE. Three data sources. Three probability layers. One automated pipeline. No manual input. Every evening the bot wakes up. Pulls today's NBA slate. Builds features from live data.Generates predictions. Sends them to me before the first whistle. The ML layer: XGBoost on three seasons of data. Four Factors. ELO ratings. Net rating. Pace. Back-to-back fatigue. Rest days. Travel distance. Every stat computed only from data available before the game. No future leakage. Ever. The sportsbook layer: spread and moneyline converted into implied probabilities. The spread alone contains the aggregated intelligence of an entire betting market. The bot doesn't fight it. It absorbs it. The Polymarket layer: live crowd-sourced probabilities from a decentralized prediction market. No vig. Prices shift in seconds when a star sits out. The bot pulls them through the Gamma API in real time. Then all three layers talk to each other. All three agree - high confidence bet. Polymarket diverges from the books - someone knows something. My model diverges from both - either I found edge or I found noise. The bot flags every disagreement automatically. The fourth layer: Claude API reads everything. Injury reports. Schedule context. Matchup history. Generates a written explanation for every single prediction. No black box. Every call has reasoning attached. The stack: Python. nba_api. pandas. XGBoost. scikit-learn. SHAP. Polymarket Gamma API. Claude API. Flask. GitHub Actions. It took mass of work to build. It takes zero effort to run. 5:00 PM ET. Every day. Predictions land before tipoff. Trading here: I didn't build a model. I built a machine.

I BUILT A BOT THAT PREDICTS NBA GAMES BEFORE TIPOFF. IT RUNS EVERY DAY AT 5:00 PM. HERE'S WHAT'S INSIDE. Three data sources. Three probability layers. One automated pipeline. No manual input. Every evening the bot wakes up. Pulls today's NBA slate. Builds features from live data.Generates predictions. Sends them to me before the first whistle. The ML layer: XGBoost on three seasons of data. Four Factors. ELO ratings. Net rating. Pace. Back-to-back fatigue. Rest days. Travel distance. Every stat computed only from data available before the game. No future leakage. Ever. The sportsbook layer: spread and moneyline converted into implied probabilities. The spread alone contains the aggregated intelligence of an entire betting market. The bot doesn't fight it. It absorbs it. The Polymarket layer: live crowd-sourced probabilities from a decentralized prediction market. No vig. Prices shift in seconds when a star sits out. The bot pulls them through the Gamma API in real time. Then all three layers talk to each other. All three agree - high confidence bet. Polymarket diverges from the books - someone knows something. My model diverges from both - either I found edge or I found noise. The bot flags every disagreement automatically. The fourth layer: Claude API reads everything. Injury reports. Schedule context. Matchup history. Generates a written explanation for every single prediction. No black box. Every call has reasoning attached. The stack: Python. nba_api. pandas. XGBoost. scikit-learn. SHAP. Polymarket Gamma API. Claude API. Flask. GitHub Actions. It took mass of work to build. It takes zero effort to run. 5:00 PM ET. Every day. Predictions land before tipoff. Trading here: I didn't build a model. I built a machine.

zostaff

48,649 görüntüleme • 5 ay önce

Someone trained a swarm model on 3 years of NBA data and let it loose on Polymarket The result: $1.49M. He didn't build a better model. He built a better crowd. Here's how the system actually works. He takes MiroFish - an open-source engine that simulates thousands of AI agents and feeds it raw sports data. The actual building blocks: > Player stat vectors: points, rebounds, assists, eFG%, usage rate across 3 full seasons > Team form tensors: last 10 games, home/away splits, pace-of-play, defensive rating > Matchup history: head-to-head records, positional mismatches, referee tendencies > Injury probability models: medical staff reports weighted by recovery timelines > Line movement tracking: where the sharp money flows before tip-off Check how this wallet works: MiroFish generates 4,096 agents - analysts, bettors, insiders, oddsmakers - each with different reasoning. They argue, form clusters, shift opinions. Consensus emerges. He pipes that consensus into a 12-layer transformer trained on the full history of his 16,695 predictions. The model compares MiroFish output against live Polymarket odds. When the gap exceeds his Kelly criterion threshold, it enters. Lakers at 40 cents. MiroFish said 62%. One position: $190,823. The edge isn't data. Every sharp has data. The edge is simulating how 4,000 fake humans process it - before the real crowd does.

Someone trained a swarm model on 3 years of NBA data and let it loose on Polymarket The result: $1.49M. He didn't build a better model. He built a better crowd. Here's how the system actually works. He takes MiroFish - an open-source engine that simulates thousands of AI agents and feeds it raw sports data. The actual building blocks: > Player stat vectors: points, rebounds, assists, eFG%, usage rate across 3 full seasons > Team form tensors: last 10 games, home/away splits, pace-of-play, defensive rating > Matchup history: head-to-head records, positional mismatches, referee tendencies > Injury probability models: medical staff reports weighted by recovery timelines > Line movement tracking: where the sharp money flows before tip-off Check how this wallet works: MiroFish generates 4,096 agents - analysts, bettors, insiders, oddsmakers - each with different reasoning. They argue, form clusters, shift opinions. Consensus emerges. He pipes that consensus into a 12-layer transformer trained on the full history of his 16,695 predictions. The model compares MiroFish output against live Polymarket odds. When the gap exceeds his Kelly criterion threshold, it enters. Lakers at 40 cents. MiroFish said 62%. One position: $190,823. The edge isn't data. Every sharp has data. The edge is simulating how 4,000 fake humans process it - before the real crowd does.

BuBBliK

504,921 görüntüleme • 6 ay önce

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

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

zostaff

1,951,025 görüntüleme • 6 ay önce

Anthropic engineer stops me in a hallway at a conference and points at my screen. "Are you the one running the Polymarket bot on Claude Code?" I say maybe. He looks back at the terminal. "This thing is live?" Yeah. He laughs. "We built Claude to write code. You people immediately turned it into a market animal." I ask what gave it away. "The layout," he says. "Official CLI on one side. Orderbook on the other. You’re not paper trading." He was right. I show him the stack. - official CLI. Rust. Scanning markets, placing orders, no UI tax. Claude Code on top of it. No giant infra. No team. Just prompts, a terminal, and a model that’s better at reading weird edge cases than most interns. "What’s the loop," he asks. "Short horizon only," I tell him. "Scan for contracts under 48h. Pull structure. Look for mispriced panic. Feed the market state to Claude. Let it decide if the crowd is overreacting or just early." "And execution?" "Three commands and the order is live." He nods. Profile bot: "That’s the part people miss. Everyone thinks the alpha is the model. The alpha is the model plus an execution path short enough that you don’t talk yourself out of the fill." A market flips while we’re standing there. +118. He sees it print. "Jesus." I keep going. "Most people use Claude Code to save time writing wrappers. Fine. But the real trick is that it reads messy market context better than brittle rule systems. News fragments. weird phrasing. half-broken incentives. Retail panic. You can feel the model noticing when the tape smells wrong." He smiles at that. "So what’s the cost." "$25 a month." He laughs again. "We spend more than that on lunch." Copytrade here: I show him the numbers. 214 trades. 74% win rate. +$9,437 in 19 days. He goes quiet for a second. "OpenAI people will say use Codex. Quant guys will say build a proper system. Old traders will say this isn’t robust." I shrug. "It placed the order." That’s when he gives me the line I kept. "Anthropic made Claude. GitHub did the rest." Then he taps the CLI window one more time. "Keep it ugly," he says. "The second you wrap this in a beautiful dashboard, someone upstairs will understand how little infrastructure the edge actually needed."

Lunar

19,469 görüntüleme • 5 ay önce

An ex-OpenAI engineer walked up to me at a meetup in SF I was showing my Polymarket terminal. He looked at the screen for ten seconds and said one sentence. "You're trading blind. The data is sitting in the open and you're writing prompts" I didn't understand. What data. He took my laptop. Opened one repository. 86 million trades. Every wallet. Every entry. Every exit. The entire Polymarket history since day one. "At OpenAI models don't guess. They read. Connect Claude Code to this dataset and say - find every wallet with a win rate above 70% and more than 100 trades" I asked - why Claude and not GPT? He looked at me like I was an idiot. "Because Claude Code connects to the repo directly. It reads the entire codebase. It's not a chatbox. It's a runtime" That evening I connected it. Claude pulled 47 wallets in 4 minutes. Average profit: $214K. Hold time: 7 hours. 91% close their position BEFORE resolution. Top wallets capture 86% of the move and cut losers at 12%. Everyone else - 58% of profit and hold losers to 41%. Same exact entries. The exits make it a completely different game. "Now connect the scanner" Three commands - the bot sees 500+ markets in real time. No API key. Read-only. Claude built the scoring in 20 minutes: Gap between price and model > 7 cents. Book depth > $500. Resolution in 4-48 hours. 93% of markets get killed instantly. Only the fat ones survive. "Now this is the important part" - he sent me an article where a guy built a full bot over a weekend from these same repos Copytrade here: Three exit triggers: Target 85% of expected move. Volume spike x3 - smart money leaving. 24 hours of silence - thesis is dead. I copied the whole stack. VPS $5. Claude $20. Total $25 a month. No team. No office. No Bloomberg. 16 days. 187 trades. 71% win rate. $800 seed. +$8,700. I sent him my screen. He replied a day later. "You just replicated for $25 what cost us six months and 11 people" I said - thanks for the tip. "Delete this chat" Too late.

An ex-OpenAI engineer walked up to me at a meetup in SF I was showing my Polymarket terminal. He looked at the screen for ten seconds and said one sentence. "You're trading blind. The data is sitting in the open and you're writing prompts" I didn't understand. What data. He took my laptop. Opened one repository. 86 million trades. Every wallet. Every entry. Every exit. The entire Polymarket history since day one. "At OpenAI models don't guess. They read. Connect Claude Code to this dataset and say - find every wallet with a win rate above 70% and more than 100 trades" I asked - why Claude and not GPT? He looked at me like I was an idiot. "Because Claude Code connects to the repo directly. It reads the entire codebase. It's not a chatbox. It's a runtime" That evening I connected it. Claude pulled 47 wallets in 4 minutes. Average profit: $214K. Hold time: 7 hours. 91% close their position BEFORE resolution. Top wallets capture 86% of the move and cut losers at 12%. Everyone else - 58% of profit and hold losers to 41%. Same exact entries. The exits make it a completely different game. "Now connect the scanner" Three commands - the bot sees 500+ markets in real time. No API key. Read-only. Claude built the scoring in 20 minutes: Gap between price and model > 7 cents. Book depth > $500. Resolution in 4-48 hours. 93% of markets get killed instantly. Only the fat ones survive. "Now this is the important part" - he sent me an article where a guy built a full bot over a weekend from these same repos Copytrade here: Three exit triggers: Target 85% of expected move. Volume spike x3 - smart money leaving. 24 hours of silence - thesis is dead. I copied the whole stack. VPS $5. Claude $20. Total $25 a month. No team. No office. No Bloomberg. 16 days. 187 trades. 71% win rate. $800 seed. +$8,700. I sent him my screen. He replied a day later. "You just replicated for $25 what cost us six months and 11 people" I said - thanks for the tip. "Delete this chat" Too late.

Lunar

481,780 görüntüleme • 5 ay önce

$1,840 OVERNIGHT. NOTIFICATION AT 2:00 AM FROM OPENCLAW: " FOUND 1M MARKET ON BTC " He found them literally the moment they launched And gave Codex the command to rebuild the architecture from 5m to 1m I woke up at 8:00, opened Telegram - 47 trades, +$1,840 The bot was a scalper, now it's HFT. Built the entire architecture in Rust because Python simply doesn't survive on 60-second cycles. The race for milliseconds began. Claude added a momentum filter: if the last 10s the price accelerates in one direction - the bot enters. In one minute the trend doesn't have time to reverse On the 5m market 18 trades per day, on 1m - 210. Same edge, 10x more often. Three agents found a market, turned a scalper into HFT, and made $1,840. i found a new market here: I'm starting to think it has a mind of its own. What did I create?

$1,840 OVERNIGHT. NOTIFICATION AT 2:00 AM FROM OPENCLAW: " FOUND 1M MARKET ON BTC " He found them literally the moment they launched And gave Codex the command to rebuild the architecture from 5m to 1m I woke up at 8:00, opened Telegram - 47 trades, +$1,840 The bot was a scalper, now it's HFT. Built the entire architecture in Rust because Python simply doesn't survive on 60-second cycles. The race for milliseconds began. Claude added a momentum filter: if the last 10s the price accelerates in one direction - the bot enters. In one minute the trend doesn't have time to reverse On the 5m market 18 trades per day, on 1m - 210. Same edge, 10x more often. Three agents found a market, turned a scalper into HFT, and made $1,840. i found a new market here: I'm starting to think it has a mind of its own. What did I create?

zostaff

26,762 görüntüleme • 6 ay önce

an OpenAI researcher sat next to me at a cafe in brooklyn and saw my screen i was deep in the terminal. trades flowing. didn't notice him sit down. he glanced over. then looked again. "is that prediction markets?" i nodded. "what's running the backend?" "Claude Opus 4.7" he closed his laptop. "show me" i turned the screen. he watched for about two minutes without saying anything. trades executing. markets scanning. wallets being copied. 948 markets per hour. "how many people built this?" just me and Claude. one weekend. one GitHub repo. 610 stars. market making infrastructure. execution engine. order book logic. i gave Opus 4.7 the repo and one prompt: build a grid that runs 8 parallel strategies on prediction markets. scan everything. enter when edge exceeds threshold. exit on volume spike or target hit. first deploy worked. no debugging. no iteration. he shook his head slowly. "we have a team of nine scoping something like this. six month timeline" i showed him the git log. friday 11PM. sunday 2AM. done. copy mirror tracking 4 wallets: > Trump VP pick +$782. bayes signal. > BTC 120K Dec +$681. divergence signal. > SpaceX Starship +$893. oracle lag signal. > Fed rate cut +$537. delta hedge signal. every entry scored by an ensemble before execution. primary model estimates probability. secondary validates against historical resolution. Claude breaks ties using context neither model can read. when all three disagree with the market that's signal. when they agree with each other but not the market that's the fat signal. when everything aligns i skip. 644 trades. 77% win rate. sharpe 3.50. avg hold 4h. +$23,768 from $1,800 in 9 weeks. copytrade here: he stared at the number. "you know we can't ship anything like this right? regulatory. legal. six layers of review" i said Claude doesn't have a legal department. he laughed. then stopped. "i'm serious though. what you built in a weekend would take us two quarters and a compliance audit" i closed my laptop. finished my coffee. he was still sitting there when i left.

an OpenAI researcher sat next to me at a cafe in brooklyn and saw my screen i was deep in the terminal. trades flowing. didn't notice him sit down. he glanced over. then looked again. "is that prediction markets?" i nodded. "what's running the backend?" "Claude Opus 4.7" he closed his laptop. "show me" i turned the screen. he watched for about two minutes without saying anything. trades executing. markets scanning. wallets being copied. 948 markets per hour. "how many people built this?" just me and Claude. one weekend. one GitHub repo. 610 stars. market making infrastructure. execution engine. order book logic. i gave Opus 4.7 the repo and one prompt: build a grid that runs 8 parallel strategies on prediction markets. scan everything. enter when edge exceeds threshold. exit on volume spike or target hit. first deploy worked. no debugging. no iteration. he shook his head slowly. "we have a team of nine scoping something like this. six month timeline" i showed him the git log. friday 11PM. sunday 2AM. done. copy mirror tracking 4 wallets: > Trump VP pick +$782. bayes signal. > BTC 120K Dec +$681. divergence signal. > SpaceX Starship +$893. oracle lag signal. > Fed rate cut +$537. delta hedge signal. every entry scored by an ensemble before execution. primary model estimates probability. secondary validates against historical resolution. Claude breaks ties using context neither model can read. when all three disagree with the market that's signal. when they agree with each other but not the market that's the fat signal. when everything aligns i skip. 644 trades. 77% win rate. sharpe 3.50. avg hold 4h. +$23,768 from $1,800 in 9 weeks. copytrade here: he stared at the number. "you know we can't ship anything like this right? regulatory. legal. six layers of review" i said Claude doesn't have a legal department. he laughed. then stopped. "i'm serious though. what you built in a weekend would take us two quarters and a compliance audit" i closed my laptop. finished my coffee. he was still sitting there when i left.

Hanako

56,917 görüntüleme • 5 ay önce

my Claude built me a Hydra Swarm terminal with 512 live agents a month ago i didn't know what mesh topology was now i have a swarm living on my screen that trades for me it started when i fed Claude an article about quant formulas he didn't just read it - he asked: "want to see what this looks like from the inside?" an hour later a web was living on my screen 512 agents. each one drifts. each one decides who to connect with 15,000 threads between them break and reform every second first week i just watched packets flying between nodes the web breathing the screen flickering when agents reach consensus then i turned it on with real contracts: > week 1: swarm caught chatter on iran before CNN ran the headline bought YES on ceasefire at $0.30 by friday the contract was at $0.64 +$2,840 > week 2: two polymarket contracts were linked but prices diverged swarm saw the gap. took both sides. waited convergence by wednesday +$3,190 > week 3: weather contract market gave hurricane landfall 19%. model inside the swarm said 38% bought. confirmed thursday +$3,670 > week 4: fed decision market priced "hold" at 62%. base rate at current unemployment - 74% 12 points of difference isn't an opinion. it's math bought. settled at $0.97 +$2,873 total: $12,573 in the first month i never opened polymarket manually 512 agents did it for me 24 hours a day. 7 days a week no opinions. no emotions. no "i feel like YES is underpriced" the weirdest part - i got used to it i open the terminal every morning like email watch the web breathe and the profit tick copy the bot: i didn't need to become a quant i needed a swarm that thinks for me

my Claude built me a Hydra Swarm terminal with 512 live agents a month ago i didn't know what mesh topology was now i have a swarm living on my screen that trades for me it started when i fed Claude an article about quant formulas he didn't just read it - he asked: "want to see what this looks like from the inside?" an hour later a web was living on my screen 512 agents. each one drifts. each one decides who to connect with 15,000 threads between them break and reform every second first week i just watched packets flying between nodes the web breathing the screen flickering when agents reach consensus then i turned it on with real contracts: > week 1: swarm caught chatter on iran before CNN ran the headline bought YES on ceasefire at $0.30 by friday the contract was at $0.64 +$2,840 > week 2: two polymarket contracts were linked but prices diverged swarm saw the gap. took both sides. waited convergence by wednesday +$3,190 > week 3: weather contract market gave hurricane landfall 19%. model inside the swarm said 38% bought. confirmed thursday +$3,670 > week 4: fed decision market priced "hold" at 62%. base rate at current unemployment - 74% 12 points of difference isn't an opinion. it's math bought. settled at $0.97 +$2,873 total: $12,573 in the first month i never opened polymarket manually 512 agents did it for me 24 hours a day. 7 days a week no opinions. no emotions. no "i feel like YES is underpriced" the weirdest part - i got used to it i open the terminal every morning like email watch the web breathe and the profit tick copy the bot: i didn't need to become a quant i needed a swarm that thinks for me

Hanako

127,204 görüntüleme • 6 ay önce

An ex-Anthropic engineer told me something at a party he probably shouldn't have. It was in SF. Someone's rooftop. I mentioned I run trading agents on Claude. He went quiet. "You're doing it wrong. Everyone is" I asked what he meant. "Claude is a runtime. Not a chatbox. You're supposed to pair it with repos" He pulled out his phone. Opened one GitHub link. 14,000 stars. Every workflow pattern they built internally before it went public. Agents. Tool use. Evals. Citations. The entire architecture. "Everyone types prompts. That's not how we use it. You connect Claude to a codebase. It reads. It understands. It builds on top of what's already there" I went home at 2am. Connected Claude Code to poly_data - 86 million Polymarket trades. Every wallet. Every entry. Claude didn't guess. It read the data and built detectors. First week: +$1,400. Second week: +$3,800. Right now: +$9,100. 4 agents. 74% win rate. His team runs this with a floor of PhDs and $800M AUM. My setup: Claude + a VPS. $25/month. The repos are free. Copytrade here: I asked him what separates his firm from everyone else. "Honestly? Keyboard shortcuts and repo structure. That's it. The model is the same for everyone" He texted me two days later. "Delete everything I told you" Too late.

An ex-Anthropic engineer told me something at a party he probably shouldn't have. It was in SF. Someone's rooftop. I mentioned I run trading agents on Claude. He went quiet. "You're doing it wrong. Everyone is" I asked what he meant. "Claude is a runtime. Not a chatbox. You're supposed to pair it with repos" He pulled out his phone. Opened one GitHub link. 14,000 stars. Every workflow pattern they built internally before it went public. Agents. Tool use. Evals. Citations. The entire architecture. "Everyone types prompts. That's not how we use it. You connect Claude to a codebase. It reads. It understands. It builds on top of what's already there" I went home at 2am. Connected Claude Code to poly_data - 86 million Polymarket trades. Every wallet. Every entry. Claude didn't guess. It read the data and built detectors. First week: +$1,400. Second week: +$3,800. Right now: +$9,100. 4 agents. 74% win rate. His team runs this with a floor of PhDs and $800M AUM. My setup: Claude + a VPS. $25/month. The repos are free. Copytrade here: I asked him what separates his firm from everyone else. "Honestly? Keyboard shortcuts and repo structure. That's it. The model is the same for everyone" He texted me two days later. "Delete everything I told you" Too late.

Lunar

1,657,412 görüntüleme • 5 ay önce

a Citadel intern told me something at a party he probably shouldn't have it was on a rooftop in brooklyn. i mentioned i trade prediction markets. he got quiet for a second. "we have a model for that. it scores every contract on four factors. when all four align we enter. when any breaks we exit. that's it" i asked what the four factors are. he looked around. then said it fast like he was confessing. "cross-market divergence. disposition coefficient. capital velocity. pair network correlation" I didn't know what half of that meant. but i memorized it. went home. 11pm. opened Claude. "here are four scoring factors from a quant fund. build a terminal that runs all four on prediction markets" Claude asked one question: "Where's the data?" I sent him one repo: 86 million trades. every wallet. every entry. every outcome three weeks later i'm sitting in my apartment watching a screen i barely understand print money. the disposition meter alone changed everything. it measures how you exit - not how you enter. top wallets capture 86% of winner value and cut losers at 12%. everyone else captures 58% and holds losers to 41%. same exact entries. the exits make it a completely different game. capital velocity: 49x. every dollar gets recycled 49 times before the average trader recycles once. the terminal found 42 pair correlations across 11 markets. when MSFT beats Q3 is priced at 80c but the model reads 93% - it enters. when the gap closes 2 hours later - it exits. no opinions. no news. just four numbers that either align or don't. his fund runs this with a floor of PhDs and $800M AUM. my setup: > Claude - $20/month > VPS - $5/month > poly_data repo - free > Polymarket API - free $25/month. no team. no office. no Bloomberg. 280 trades so far. 70% win rate. $800 seed. four bots splitting the work: pulse_alpha +$299. arb_hunter +$558. trend_rider +$337. cal_engine +$719. +$11,514 total. copytrade here: he texted me last week. "delete everything i told you" too late.

a Citadel intern told me something at a party he probably shouldn't have it was on a rooftop in brooklyn. i mentioned i trade prediction markets. he got quiet for a second. "we have a model for that. it scores every contract on four factors. when all four align we enter. when any breaks we exit. that's it" i asked what the four factors are. he looked around. then said it fast like he was confessing. "cross-market divergence. disposition coefficient. capital velocity. pair network correlation" I didn't know what half of that meant. but i memorized it. went home. 11pm. opened Claude. "here are four scoring factors from a quant fund. build a terminal that runs all four on prediction markets" Claude asked one question: "Where's the data?" I sent him one repo: 86 million trades. every wallet. every entry. every outcome three weeks later i'm sitting in my apartment watching a screen i barely understand print money. the disposition meter alone changed everything. it measures how you exit - not how you enter. top wallets capture 86% of winner value and cut losers at 12%. everyone else captures 58% and holds losers to 41%. same exact entries. the exits make it a completely different game. capital velocity: 49x. every dollar gets recycled 49 times before the average trader recycles once. the terminal found 42 pair correlations across 11 markets. when MSFT beats Q3 is priced at 80c but the model reads 93% - it enters. when the gap closes 2 hours later - it exits. no opinions. no news. just four numbers that either align or don't. his fund runs this with a floor of PhDs and $800M AUM. my setup: > Claude - $20/month > VPS - $5/month > poly_data repo - free > Polymarket API - free $25/month. no team. no office. no Bloomberg. 280 trades so far. 70% win rate. $800 seed. four bots splitting the work: pulse_alpha +$299. arb_hunter +$558. trend_rider +$337. cal_engine +$719. +$11,514 total. copytrade here: he texted me last week. "delete everything i told you" too late.

Hanako

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