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We've completely overhauled the trading experience with real-time infrastructure and professional-grade tooling: • Shipped Helius webhook integration — trades index the moment they hit chain • Built StatsCollector service — live market data updates every 30 seconds across 51 markets • Added professional candlestick charts with full timeframe support...

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Percolator

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35,763 просмотров • 6 месяцев назад •via X (Twitter)

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Trade on Hyperliquid with Natural Language 🐉 We just made trading on Hyperliquid faster, simpler, and way more accessible. Cortex now supports Hyperliquid, fully integrated into our natural language interface. That means you can trade directly from chat using plain English: "Long 20x BTC at market, set TP at $110k, SL at $105k" "What is the funding rate for ETH-PERP?" "Close all my positions!" Behind the scenes, Cortex handles everything: parsing your intent, checking your balances, placing the trade on-chain, and tracking the position in real time. No forms, no buttons, no guesswork. What’s New Full Hyperliquid Terminal, Powered by Language - Access funding rates, open interest, volume, orderbook, and positions across all pairs, LIVE. Novel Trade Execution in Natural Language - Market, limit, stop, TP/SL executed in real-time via plain text commands. It’s the fastest way to trade Hyperliquid. - One click, signless position opening and closing. HYPE Onboarding Built In - New to Hyperliquid? Cortex walks you through buying $HYPE, bridging USDC to Arbitrum, and funding your account all in one UI. No need to leave the app or touch a separate bridge. Live Position Tracking - See your active positions update as you trade. Ask “how’s my BTC long doing?” and Cortex tells you: P&L, liquidation risk, everything. - Examine all of your on-chain balances, including HyperCore and HyperEVM. Hyperliquid is one of the fastest-growing protocols in DeFi ever with an incredibly rich, builder-friendly, and growing ecosystem, but onboarding has been a pain: bridging, swapping, funding, trading, etc. fragmented. We fixed that. Cortex brings it all into one place, one interface, and one language: yours. Try It Now! Jump into the Cortex app and type: “Open a 5x long on ETH” We'll handle the rest. Welcome to the new standard in crypto trading. Hyperliquid.
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Trade on Hyperliquid with Natural Language 🐉 We just made trading on Hyperliquid faster, simpler, and way more accessible. Cortex now supports Hyperliquid, fully integrated into our natural language interface. That means you can trade directly from chat using plain English: "Long 20x BTC at market, set TP at $110k, SL at $105k" "What is the funding rate for ETH-PERP?" "Close all my positions!" Behind the scenes, Cortex handles everything: parsing your intent, checking your balances, placing the trade on-chain, and tracking the position in real time. No forms, no buttons, no guesswork. What’s New Full Hyperliquid Terminal, Powered by Language - Access funding rates, open interest, volume, orderbook, and positions across all pairs, LIVE. Novel Trade Execution in Natural Language - Market, limit, stop, TP/SL executed in real-time via plain text commands. It’s the fastest way to trade Hyperliquid. - One click, signless position opening and closing. HYPE Onboarding Built In - New to Hyperliquid? Cortex walks you through buying $HYPE, bridging USDC to Arbitrum, and funding your account all in one UI. No need to leave the app or touch a separate bridge. Live Position Tracking - See your active positions update as you trade. Ask “how’s my BTC long doing?” and Cortex tells you: P&L, liquidation risk, everything. - Examine all of your on-chain balances, including HyperCore and HyperEVM. Hyperliquid is one of the fastest-growing protocols in DeFi ever with an incredibly rich, builder-friendly, and growing ecosystem, but onboarding has been a pain: bridging, swapping, funding, trading, etc. fragmented. We fixed that. Cortex brings it all into one place, one interface, and one language: yours. Try It Now! Jump into the Cortex app and type: “Open a 5x long on ETH” We'll handle the rest. Welcome to the new standard in crypto trading. Hyperliquid.

cortexprotocol.hl

23,782 просмотров • 1 год назад

I just found one of the biggest platform bug on Polymarket that cost me my $8.5k portfolio today. Please watch this video. I opened the exact same BTC 5m market on two different devices right next to each other. My computer monitor shows 2 minutes and 50 seconds remaining. My MacBook shows 4 minutes and 02 seconds remaining. There is more than a full minute of time difference on the exact same live market. This video is undeniable proof of exactly why I lost my money today. I was trading on my computer earlier and I waited until the 5m time frame end. When Polymarket UI showed me on my computer the timeframe was completely over and the price was safely above the target, I placed a market up order to provide liquidity. I was 100 percent sure it was a zero risk move because your platform timer showed me the market was already finished and BTC price is up from the beat price. But because of this bug my computer timer was closing 1 minute earlier than the real market time. So after I placed my order believing the market was settled as Up, the actual market was still open. It kept counting the Bitcoin price movements for the next full minute after I placed my trade. During that hidden extra minute the price of BTC dropped and the market finally settled Down, instantly wiping out my entire portfolio. When people told me it might be a UI delay I was shocked, but now I have it on video. The Polymarket timer is completely broken and out of sync across devices. My Polymarket wallet address is: 0xf0AD2eeb8F898619460a38c015a7897a4E797651 Trade URL 1: Trade URL 2: On those above two trade i lost total $8500 The first video I just recorded now when i noticed this bugs and the second video i made when my trade lost and i didn’t have any reason how its happened. I am begging Shayne Coplan 🦅 and the Polymarket support team to review this video. I did not make a trading mistake. I trusted a broken platform timer that showed completely wrong data and forced me into an active market I thought was closed. Please fix this massive bug protect your user and refund my loses.
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I just found one of the biggest platform bug on Polymarket that cost me my $8.5k portfolio today. Please watch this video. I opened the exact same BTC 5m market on two different devices right next to each other. My computer monitor shows 2 minutes and 50 seconds remaining. My MacBook shows 4 minutes and 02 seconds remaining. There is more than a full minute of time difference on the exact same live market. This video is undeniable proof of exactly why I lost my money today. I was trading on my computer earlier and I waited until the 5m time frame end. When Polymarket UI showed me on my computer the timeframe was completely over and the price was safely above the target, I placed a market up order to provide liquidity. I was 100 percent sure it was a zero risk move because your platform timer showed me the market was already finished and BTC price is up from the beat price. But because of this bug my computer timer was closing 1 minute earlier than the real market time. So after I placed my order believing the market was settled as Up, the actual market was still open. It kept counting the Bitcoin price movements for the next full minute after I placed my trade. During that hidden extra minute the price of BTC dropped and the market finally settled Down, instantly wiping out my entire portfolio. When people told me it might be a UI delay I was shocked, but now I have it on video. The Polymarket timer is completely broken and out of sync across devices. My Polymarket wallet address is: 0xf0AD2eeb8F898619460a38c015a7897a4E797651 Trade URL 1: Trade URL 2: On those above two trade i lost total $8500 The first video I just recorded now when i noticed this bugs and the second video i made when my trade lost and i didn’t have any reason how its happened. I am begging Shayne Coplan 🦅 and the Polymarket support team to review this video. I did not make a trading mistake. I trusted a broken platform timer that showed completely wrong data and forced me into an active market I thought was closed. Please fix this massive bug protect your user and refund my loses.

Sheikh Silicon

87,941 просмотров • 4 месяцев назад

I built a powerful real-time edge terminal specifically for Polymarket - multi-timeframe dashboard covering all coins! (100% FREE & fully open-source) In one sentence: This Python bot gives you live alpha on Polymarket’s Up/Down crypto binaries by fusing real-time Binance order flow, current Polymarket probabilities, and multi-TF technical analysis. Spot mispricings fast - where the market odds haven’t yet caught up to momentum, aggressive delta, or strong signals. Perfect for lightning-fast 15-minute scalps (markets resolve every 15 min with constant repricing) or cleaner swings on 1h / 4h / daily horizons. Pure decision-support tool - no auto-trading, just sharp, actionable insight delivered straight to your terminal. > Coins covered: BTC, ETH, SOL, XRP > Timeframes: 15m, 1h, 4h, daily - All 16 market combinations are live and heavily traded on Polymarket (especially the 15m contracts - ultra-fast flips) Features at a glance: > Streams live trades + full order book from Binance > Pulls real-time Up/Down prices & depth via Polymarket WebSocket > Computes 11+ indicators on the fly > Rolls everything up into a clear BULLISH / BEARISH / NEUTRAL bias score + probability estimate per timeframe > Displays a clean, colorful, auto-refreshing terminal dashboard Order-book signals: > OBI (imbalance) > visible buy/sell walls > liquidity depth (0.1% / 0.5% / 1.0%) > net flow & volume > CVD (across 1m/3m/5m windows) > 1m delta > Volume Profile + POC Technical indicators: > RSI (14) > MACD (12/26/9) + signal line + histogram > VWAP > EMA 5 / EMA 20 cross >Heikin-Ashi candle streak count Important: this is NOT an auto-trading bot. It highlights where Polymarket odds are lagging real Binance order-flow and multi-timeframe TA - giving you an edge on 15m scalping, 1–4h momentum trades, and daily directional confirmation. Built with: Python (asyncio + Rich/Textual for a slick CLI look) One-line start: python Refreshes every few seconds Completely free & open-source → GitHub repo Want access? Like + RT + drop a reply or quote below - I’ll DM you the GitHub link Don’t miss the edge - especially on those 15-minute markets that flip every quarter hour. Seeing all timeframes at once is real alpha. Here’s to green candles and fat PnL!
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I built a powerful real-time edge terminal specifically for Polymarket - multi-timeframe dashboard covering all coins! (100% FREE & fully open-source) In one sentence: This Python bot gives you live alpha on Polymarket’s Up/Down crypto binaries by fusing real-time Binance order flow, current Polymarket probabilities, and multi-TF technical analysis. Spot mispricings fast - where the market odds haven’t yet caught up to momentum, aggressive delta, or strong signals. Perfect for lightning-fast 15-minute scalps (markets resolve every 15 min with constant repricing) or cleaner swings on 1h / 4h / daily horizons. Pure decision-support tool - no auto-trading, just sharp, actionable insight delivered straight to your terminal. > Coins covered: BTC, ETH, SOL, XRP > Timeframes: 15m, 1h, 4h, daily - All 16 market combinations are live and heavily traded on Polymarket (especially the 15m contracts - ultra-fast flips) Features at a glance: > Streams live trades + full order book from Binance > Pulls real-time Up/Down prices & depth via Polymarket WebSocket > Computes 11+ indicators on the fly > Rolls everything up into a clear BULLISH / BEARISH / NEUTRAL bias score + probability estimate per timeframe > Displays a clean, colorful, auto-refreshing terminal dashboard Order-book signals: > OBI (imbalance) > visible buy/sell walls > liquidity depth (0.1% / 0.5% / 1.0%) > net flow & volume > CVD (across 1m/3m/5m windows) > 1m delta > Volume Profile + POC Technical indicators: > RSI (14) > MACD (12/26/9) + signal line + histogram > VWAP > EMA 5 / EMA 20 cross >Heikin-Ashi candle streak count Important: this is NOT an auto-trading bot. It highlights where Polymarket odds are lagging real Binance order-flow and multi-timeframe TA - giving you an edge on 15m scalping, 1–4h momentum trades, and daily directional confirmation. Built with: Python (asyncio + Rich/Textual for a slick CLI look) One-line start: python Refreshes every few seconds Completely free & open-source → GitHub repo Want access? Like + RT + drop a reply or quote below - I’ll DM you the GitHub link Don’t miss the edge - especially on those 15-minute markets that flip every quarter hour. Seeing all timeframes at once is real alpha. Here’s to green candles and fat PnL!

st1ne

175,632 просмотров • 6 месяцев назад

i cancelled $2,000/month in trading subscriptions replaced every single one with open-source repos here's the full stack: 1. TradingView Pro ($30/mo) → lightweight-charts 14K stars. by TradingView themselves. 45KB. free 2. Bloomberg Terminal ($2,000/mo) → fredapi + Claude every macro dataset the Fed publishes. free API 3. backtest platform ($100/mo) → prediction-market-backtesting NautilusTrader fork with Polymarket + Kalshi adapters 4. real-time dashboard → polyrec terminal UI: Chainlink oracle, Binance feed, orderbook depth 70+ indicators. auto CSV logging. strategy backtester 5. bot framework (7 strategies) → Polymarket-Trading-Bot 53K lines TypeScript. arbitrage, momentum, market making, AI forecast, whale copy-trade, convergence 6. strategy reverse engineering → polybot execution + market data infrastructure. paper trading Kafka, ClickHouse, Grafana. full analytics pipeline 7. paper trading for AI agents → polymarket-paper-trader real order books. exact fee model. slippage tracking your Claude agent gets $10K paper money and trades 8. token savings → rtk CLI proxy. cuts Claude Code tokens by 60-90% Rust. single binary. 10 AI tools supported 9. Claude Code itself ($200/mo) → goose 35K stars. by Block (Jack Dorsey). Rust works with any LLM. full agent loop. free 10. wallet tracking + copy trading → Kreo track top Polymarket wallets. auto copy trades the only tool on this list i actually pay for because it makes more than it costs total before: ~$2,600/month total now: $0 + Kreo bookmark this. you'll need it
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i cancelled $2,000/month in trading subscriptions replaced every single one with open-source repos here's the full stack: 1. TradingView Pro ($30/mo) → lightweight-charts 14K stars. by TradingView themselves. 45KB. free 2. Bloomberg Terminal ($2,000/mo) → fredapi + Claude every macro dataset the Fed publishes. free API 3. backtest platform ($100/mo) → prediction-market-backtesting NautilusTrader fork with Polymarket + Kalshi adapters 4. real-time dashboard → polyrec terminal UI: Chainlink oracle, Binance feed, orderbook depth 70+ indicators. auto CSV logging. strategy backtester 5. bot framework (7 strategies) → Polymarket-Trading-Bot 53K lines TypeScript. arbitrage, momentum, market making, AI forecast, whale copy-trade, convergence 6. strategy reverse engineering → polybot execution + market data infrastructure. paper trading Kafka, ClickHouse, Grafana. full analytics pipeline 7. paper trading for AI agents → polymarket-paper-trader real order books. exact fee model. slippage tracking your Claude agent gets $10K paper money and trades 8. token savings → rtk CLI proxy. cuts Claude Code tokens by 60-90% Rust. single binary. 10 AI tools supported 9. Claude Code itself ($200/mo) → goose 35K stars. by Block (Jack Dorsey). Rust works with any LLM. full agent loop. free 10. wallet tracking + copy trading → Kreo track top Polymarket wallets. auto copy trades the only tool on this list i actually pay for because it makes more than it costs total before: ~$2,600/month total now: $0 + Kreo bookmark this. you'll need it

self.dll

803,521 просмотров • 4 месяцев назад

𝐓𝐡𝐞 𝟐𝟎𝟐𝟔 𝐖𝐨𝐫𝐥𝐝 𝐂𝐮𝐩 𝐰𝐢𝐥𝐥 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞 𝐦𝐨𝐫𝐞 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧 𝐚𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐭𝐡𝐚𝐧 𝐚𝐧𝐲 𝐬𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐞𝐯𝐞𝐧𝐭 𝐢𝐧 𝐡𝐢𝐬𝐭𝐨𝐫𝐲. Most people will use sportsbooks. A few will discover something better. Here's why the World Cup is actually POTS MARKET Market biggest moment. Every match carries dozens of predictable outcomes, not just who wins, but scorelines, goalscorers, red cards, halftime leads, VAR decisions. Traditional sportsbooks will process billions in bets. And keep most of it. Here is the problem with sportsbooks that nobody talks about: They set the odds. Not the market. Which means the house always has an edge baked in before you place a single bet. You're not trading against the market, you're trading against a company whose entire business model depends on you losing. That's not a prediction market. That's a casino with a football shirt on. Prediction markets are different. The odds aren't set by a company. They're set by the collective intelligence of everyone participating. When millions of people put real money behind their beliefs, the market finds truth faster than any analyst, pundit, or algorithm working alone. This is why prediction markets outperform polls, pundits, and press releases, every single time. Now here's where POTS Market changes the game entirely. POTS MONEY has a dedicated sports vertical, built specifically for football, basketball, and esports. Not a generic market with a football category tucked in the corner. A tailored module optimized for the way sports prediction actually works, short windows, live data, rapid settlement. 64 World Cup matches = 64 live prediction markets. Each one open, on-chain, transparent. But the real edge is not the markets themselves. It's the capital layer underneath them. On a traditional sportsbook, every bet locks your full stake. You place £100, that £100 is gone until settlement. POTS Money changes this. The DeFi lending primitive means you can collateralize positions and optimize capital across multiple markets simultaneously, without locking up dead capital on each one. That's not betting. That's portfolio management. And then there's the AI layer. Via MCP (Model Context Protocol), you can deploy autonomous trading agents that monitor live match data and execute positions based on your pre-set strategy. Imagine this: Agent monitors possession stats in real time Detects a momentum shift at the 60th minute Auto-places a position on the next goalscorer market before the crowd even reacts 𝙏𝙝𝙖𝙩'𝙨 𝙣𝙤𝙩 𝙖 𝙥𝙧𝙚𝙙𝙞𝙘𝙩𝙞𝙤𝙣. 𝙏𝙝𝙖𝙩'𝙨 𝙖𝙣 𝙚𝙙𝙜𝙚 Compare the two worlds side by side: Sportsbook: ❌ House sets the odds ❌ Geo-restricted ❌ Capital locked per bet ❌ No automation ❌ Withdraw only when they allow it POTS Market: ✅ Market sets the odds ✅ Open and on-chain ✅ Capital efficient via DeFi lending ✅ AI agents execute your strategy ✅ Fully collateralized, transparent settlement One of these is built for the next decade. The other is built for the last one. The timing is not a coincidence. POTS Market launches Q2 2026, right as World Cup fever peaks globally. Q1 2026 — MVP + Polymarket integration ✅ Q2 2026 — Market Launch + DeFi lending beta 👈 we are here Q3-Q4 2026 — Skill Hub + Sub-accounts 2027+ — DAO governance + cross-chain The infrastructure is ready exactly when the biggest prediction event on earth arrives. That's timing. The 2026 World Cup will mint the first generation of serious prediction market traders. Most will start on sportsbooks. The ones who do their research will end up on POTS. From trusting the house to trusting the market. From locked capital to capital efficiency. From punting to positioning. POTS MARKET POTS MONEY, the World Cup just became a DeFi event.
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𝐓𝐡𝐞 𝟐𝟎𝟐𝟔 𝐖𝐨𝐫𝐥𝐝 𝐂𝐮𝐩 𝐰𝐢𝐥𝐥 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞 𝐦𝐨𝐫𝐞 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧 𝐚𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐭𝐡𝐚𝐧 𝐚𝐧𝐲 𝐬𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐞𝐯𝐞𝐧𝐭 𝐢𝐧 𝐡𝐢𝐬𝐭𝐨𝐫𝐲. Most people will use sportsbooks. A few will discover something better. Here's why the World Cup is actually POTS MARKET Market biggest moment. Every match carries dozens of predictable outcomes, not just who wins, but scorelines, goalscorers, red cards, halftime leads, VAR decisions. Traditional sportsbooks will process billions in bets. And keep most of it. Here is the problem with sportsbooks that nobody talks about: They set the odds. Not the market. Which means the house always has an edge baked in before you place a single bet. You're not trading against the market, you're trading against a company whose entire business model depends on you losing. That's not a prediction market. That's a casino with a football shirt on. Prediction markets are different. The odds aren't set by a company. They're set by the collective intelligence of everyone participating. When millions of people put real money behind their beliefs, the market finds truth faster than any analyst, pundit, or algorithm working alone. This is why prediction markets outperform polls, pundits, and press releases, every single time. Now here's where POTS Market changes the game entirely. POTS MONEY has a dedicated sports vertical, built specifically for football, basketball, and esports. Not a generic market with a football category tucked in the corner. A tailored module optimized for the way sports prediction actually works, short windows, live data, rapid settlement. 64 World Cup matches = 64 live prediction markets. Each one open, on-chain, transparent. But the real edge is not the markets themselves. It's the capital layer underneath them. On a traditional sportsbook, every bet locks your full stake. You place £100, that £100 is gone until settlement. POTS Money changes this. The DeFi lending primitive means you can collateralize positions and optimize capital across multiple markets simultaneously, without locking up dead capital on each one. That's not betting. That's portfolio management. And then there's the AI layer. Via MCP (Model Context Protocol), you can deploy autonomous trading agents that monitor live match data and execute positions based on your pre-set strategy. Imagine this: Agent monitors possession stats in real time Detects a momentum shift at the 60th minute Auto-places a position on the next goalscorer market before the crowd even reacts 𝙏𝙝𝙖𝙩'𝙨 𝙣𝙤𝙩 𝙖 𝙥𝙧𝙚𝙙𝙞𝙘𝙩𝙞𝙤𝙣. 𝙏𝙝𝙖𝙩'𝙨 𝙖𝙣 𝙚𝙙𝙜𝙚 Compare the two worlds side by side: Sportsbook: ❌ House sets the odds ❌ Geo-restricted ❌ Capital locked per bet ❌ No automation ❌ Withdraw only when they allow it POTS Market: ✅ Market sets the odds ✅ Open and on-chain ✅ Capital efficient via DeFi lending ✅ AI agents execute your strategy ✅ Fully collateralized, transparent settlement One of these is built for the next decade. The other is built for the last one. The timing is not a coincidence. POTS Market launches Q2 2026, right as World Cup fever peaks globally. Q1 2026 — MVP + Polymarket integration ✅ Q2 2026 — Market Launch + DeFi lending beta 👈 we are here Q3-Q4 2026 — Skill Hub + Sub-accounts 2027+ — DAO governance + cross-chain The infrastructure is ready exactly when the biggest prediction event on earth arrives. That's timing. The 2026 World Cup will mint the first generation of serious prediction market traders. Most will start on sportsbooks. The ones who do their research will end up on POTS. From trusting the house to trusting the market. From locked capital to capital efficiency. From punting to positioning. POTS MARKET POTS MONEY, the World Cup just became a DeFi event.

KIMMY OF GOOD LIFE 😍

21,955 просмотров • 3 месяцев назад

Why is nobody talking about Polymarket's official API? You open Polymarket Wait for it to load... Click on a market... Wait again... Try to check another one... More waiting... By the time you see the price, it's already stale The opportunity moved while you were clicking through pages Someone else got there first There's a better way // Found the gem hiding in plain sight - library py-clob-client Official from Polymarket. MIT license I spent a week working with multiple markets Checking prices across different positions Monitoring various categories Tracking market movements Then discovered this library Game changer for workflow efficiency // Real example from last week: UI approach: Checking markets one by one through the interface API approach: Monitoring all relevant markets simultaneously with live updates Having comprehensive real-time data makes a meaningful difference Speed and information clarity are valuable advantages // Want to go deeper? Build an arbitrage bot You'll need Rust for execution speed Deploy the server geographically close to Polymarket's infrastructure Every millisecond counts when opportunities last 1-2 seconds. I built mine in Go for monitoring and analysis. Works great for that. But if you're hunting arbitrage at scale against other bots, Rust + low latency setup is the only way. The infrastructure race is real // "But I can't code" With today's AI tools you actually can Cursor, ChatGPT, Claude, Gemini, Kimi, Grok - they write code for you You just describe what you want AI generates it You copy-paste and run Join Polymarket to create: Programming is no longer a barrier Anyone can build now
0:23

Why is nobody talking about Polymarket's official API? You open Polymarket Wait for it to load... Click on a market... Wait again... Try to check another one... More waiting... By the time you see the price, it's already stale The opportunity moved while you were clicking through pages Someone else got there first There's a better way // Found the gem hiding in plain sight - library py-clob-client Official from Polymarket. MIT license I spent a week working with multiple markets Checking prices across different positions Monitoring various categories Tracking market movements Then discovered this library Game changer for workflow efficiency // Real example from last week: UI approach: Checking markets one by one through the interface API approach: Monitoring all relevant markets simultaneously with live updates Having comprehensive real-time data makes a meaningful difference Speed and information clarity are valuable advantages // Want to go deeper? Build an arbitrage bot You'll need Rust for execution speed Deploy the server geographically close to Polymarket's infrastructure Every millisecond counts when opportunities last 1-2 seconds. I built mine in Go for monitoring and analysis. Works great for that. But if you're hunting arbitrage at scale against other bots, Rust + low latency setup is the only way. The infrastructure race is real // "But I can't code" With today's AI tools you actually can Cursor, ChatGPT, Claude, Gemini, Kimi, Grok - they write code for you You just describe what you want AI generates it You copy-paste and run Join Polymarket to create: Programming is no longer a barrier Anyone can build now

BuBBliK

44,204 просмотров • 8 месяцев назад

Claude Code is now scary good at full-stack! I asked it to build a real-time weather intelligence dashboard with an interactive 3D globe, a forecasting layer that predicts weather 3 days ahead, and an anomaly detector that flags cities whose weather is behaving abnormally. It came back with a spinning globe that has a day/night cycle using NASA satellite imagery, city lights on the dark side, weather icons that switch between sun and moon based on local time, and a time travel slider that scrubs through 10 days of data. And when a city's weather breaks from its own normal, it pulses red (abnormally hot) or blue (abnormally cold) right on the globe, updating live and reflecting the anomaly state at any point you drag the slider to. Claude Code built the whole thing in a single session, including the backend, database, data pipeline, and frontend. For the database, I needed something fast for time-series workloads since the app ingests hourly weather readings across many cities and serves time-range queries on every slider interaction. I used Tiger Cloud by Tiger Data - Creators of TimescaleDB, which gives you managed TimescaleDB on the Postgres you already know. Claude Code connected to it through the Tiger CLI MCP server and set up the entire backend directly: - Provisioned the database service - Created hypertables for time-partitioned weather storage - Set up continuous aggregates for pre-computed rollups - Built the data ingestion pipeline and the full NextJS + ThreeJS frontend The time travel slider queries thousands of rows on every position change. On a regular Postgres table, this would require manual partitioning and index tuning to stay fast as data grows. TimescaleDB partitions the data by timestamp automatically, so each query only hits the relevant time chunk. Continuous aggregates serve the trend charts, the forecast layer, and the anomaly baselines from pre-computed rollups instead of rescanning raw data on every request. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud (I have shared the link in the replies). It gives you $1,000 free credits (no card needed) → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build sign-up here: My co-founder also wrote a detailed article on this. The article is quoted below.
0:50

Claude Code is now scary good at full-stack! I asked it to build a real-time weather intelligence dashboard with an interactive 3D globe, a forecasting layer that predicts weather 3 days ahead, and an anomaly detector that flags cities whose weather is behaving abnormally. It came back with a spinning globe that has a day/night cycle using NASA satellite imagery, city lights on the dark side, weather icons that switch between sun and moon based on local time, and a time travel slider that scrubs through 10 days of data. And when a city's weather breaks from its own normal, it pulses red (abnormally hot) or blue (abnormally cold) right on the globe, updating live and reflecting the anomaly state at any point you drag the slider to. Claude Code built the whole thing in a single session, including the backend, database, data pipeline, and frontend. For the database, I needed something fast for time-series workloads since the app ingests hourly weather readings across many cities and serves time-range queries on every slider interaction. I used Tiger Cloud by Tiger Data - Creators of TimescaleDB, which gives you managed TimescaleDB on the Postgres you already know. Claude Code connected to it through the Tiger CLI MCP server and set up the entire backend directly: - Provisioned the database service - Created hypertables for time-partitioned weather storage - Set up continuous aggregates for pre-computed rollups - Built the data ingestion pipeline and the full NextJS + ThreeJS frontend The time travel slider queries thousands of rows on every position change. On a regular Postgres table, this would require manual partitioning and index tuning to stay fast as data grows. TimescaleDB partitions the data by timestamp automatically, so each query only hits the relevant time chunk. Continuous aggregates serve the trend charts, the forecast layer, and the anomaly baselines from pre-computed rollups instead of rescanning raw data on every request. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud (I have shared the link in the replies). It gives you $1,000 free credits (no card needed) → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build sign-up here: My co-founder also wrote a detailed article on this. The article is quoted below.

Akshay 🚀

35,215 просмотров • 8 дней назад

ACTFUN V2 is live on Arc tesnet A complete redesign and the most ambitious version of the platform we've shipped yet. 🧵 Let break down exactly what ACTFUN is, how it works, and why V2 is a big deal. ACTFUN is a Mine-to-Launch token launchpad built on Arc testnet. The idea is simple: anyone can create a token. But instead of a presale or a bonding curve you buy into the community mines it by writing funny posts. No VCs. No insider allocations. Just the community earning supply by participating. Every token launched on ACTFUN has a fixed tokenomic structure: 5% mints instantly to the creator's wallet on launch, 60% is community-mineable (write a funny post, pay a small USDC fee, earn tokens), and 35% is locked as LP reserve. When the full 60% is mined out, the contract auto-graduates no manual step, no admin key, no intervention. Pure code. On graduation, ACTFUN seeds liquidity on up to 4 AMMs simultaneously: UNITFLOW V3 (a Uniswap V3 fork), Uniswap V2, Curve Finance (StableSwap), and Synthra V3 DEX. The 35% LP reserve + all accumulated USDC becomes real onchain liquidity the moment the last token is mined. That's the whole mechanism mine it, graduate it, trade it. V2 also brought a full visual overhaul. New hub landing with dedicated product slabs, Cinzel typography across the entire site, a cleaner Minepad grid, and ecosystem logos representing the infra stack powering the platform: Arc Goldsky ☀️ , Uniswap, Curve, Synthra, Neon, LiveKit, OpenZeppelin, Hardhat. Built to look as serious as the contracts underneath it. The infra running underneath ACTFUN V2: smart contracts in Solidity 0.8.24 with OpenZeppelin 5.x deployed on Arc Testnet (Chain ID 5042002), event indexing via @goldsky_io Turbo pipeline streaming into Neon Postgres with sub-1s lag and zero RPC fanout on the browser, live voice rooms via starnews2.com per token (creators broadcast video + mic, miners join by voice), and a React 18 + Vite + wagmi v2 + Dynamic Labs frontend. Everything is live on Arc Testnet right now. Mint testnet USDC, deploy a token, mine it with your community, and watch it graduate to a live DEX all onchain, all open,
0:20

ACTFUN V2 is live on Arc tesnet A complete redesign and the most ambitious version of the platform we've shipped yet. 🧵 Let break down exactly what ACTFUN is, how it works, and why V2 is a big deal. ACTFUN is a Mine-to-Launch token launchpad built on Arc testnet. The idea is simple: anyone can create a token. But instead of a presale or a bonding curve you buy into the community mines it by writing funny posts. No VCs. No insider allocations. Just the community earning supply by participating. Every token launched on ACTFUN has a fixed tokenomic structure: 5% mints instantly to the creator's wallet on launch, 60% is community-mineable (write a funny post, pay a small USDC fee, earn tokens), and 35% is locked as LP reserve. When the full 60% is mined out, the contract auto-graduates no manual step, no admin key, no intervention. Pure code. On graduation, ACTFUN seeds liquidity on up to 4 AMMs simultaneously: UNITFLOW V3 (a Uniswap V3 fork), Uniswap V2, Curve Finance (StableSwap), and Synthra V3 DEX. The 35% LP reserve + all accumulated USDC becomes real onchain liquidity the moment the last token is mined. That's the whole mechanism mine it, graduate it, trade it. V2 also brought a full visual overhaul. New hub landing with dedicated product slabs, Cinzel typography across the entire site, a cleaner Minepad grid, and ecosystem logos representing the infra stack powering the platform: Arc Goldsky ☀️ , Uniswap, Curve, Synthra, Neon, LiveKit, OpenZeppelin, Hardhat. Built to look as serious as the contracts underneath it. The infra running underneath ACTFUN V2: smart contracts in Solidity 0.8.24 with OpenZeppelin 5.x deployed on Arc Testnet (Chain ID 5042002), event indexing via @goldsky_io Turbo pipeline streaming into Neon Postgres with sub-1s lag and zero RPC fanout on the browser, live voice rooms via starnews2.com per token (creators broadcast video + mic, miners join by voice), and a React 18 + Vite + wagmi v2 + Dynamic Labs frontend. Everything is live on Arc Testnet right now. Mint testnet USDC, deploy a token, mine it with your community, and watch it graduate to a live DEX all onchain, all open,

ACT FUN

22,327 просмотров • 1 месяц назад

a deported Chinese dev at a Starbucks showed me his screen and said "you have 6 seconds" he was sitting in the corner. two phones. one laptop. hood up. looked like he hadn't slept in days. i sat down next to him because every other seat was taken. he saw my screen. Polymarket open. "you trade these BTC markets?" yeah. 5-minute binaries. he turned his laptop toward me. "you see how the result settles? every 5-minute BTC market resolves based on an oracle. the oracle reads the price from an API. but the oracle doesn't update instantly. there's a lag. 4 to 6 seconds" "in those 6 seconds the real BTC price already moved. but the market is still open. still accepting orders. priced on the old number" he pointed at his screen. two windows side by side. left: Binance BTC spot feed. right: Polymarket orderbook. 3,200 stars. decentralized oracle framework. he had it forked on his laptop. the entire oracle timing model was exposed in the source code. "right now BTC is at $100,240 on Binance. the oracle still shows $100,190. the market 'BTC above $100,200 at 3:05pm' is trading YES at 41 cents" "but i already know the answer is YES. because i see the real price. the oracle doesn't. for 6 seconds i'm trading against a blind counterparty" watched him buy YES at 41c. four seconds later the oracle updated. market resolved YES. payout $1. "59 cents in 4 seconds. this happens every 5 minutes. 288 times a day" asked how he found this. "i was an oracle engineer at Chainlink in Shanghai. got deported for visa issues. took the knowledge with me" "every oracle has a heartbeat interval. a deviation threshold. a propagation delay. i know exactly how long each one takes to update. because i built three of them" he closed his laptop. "the edge isn't in the market. it's in the infrastructure layer between the real price and the reported price. nobody looks there. because nobody understands how oracles work" finished his coffee. left. didn't get his name. didn't need it. flew home. opened Claude. "build an oracle latency exploitation engine for Polymarket BTC binaries. track real-time BTC spot price from Binance websocket feed. compare against Polymarket oracle update timestamps. detect windows where oracle lags behind spot by more than $30. enter the side that the real price already confirmed. target the 4-6 second blind window before each oracle heartbeat." the system was live by morning. named it DEEP SIGNAL. first fill hit before i finished coffee. > Binance websocket feed at 50ms intervals. > oracle heartbeat monitor. > propagation delay calculator. > spot-to-oracle divergence detector. > conviction gate at $30+ deviation. > order placement avg 47ms. $534K volume. 79% win rate. sharpe 3.64. drawdown -1.2%. +$11,681 in profit runs on: Claude $20. VPS $5. UMA protocol free. $25/month. copytrade setup here: went back to that Starbucks a week later. same corner. empty. but the oracle still lags. every 5 minutes. every day. 6 seconds is all you need when you can see what the oracle can't.
0:32

a deported Chinese dev at a Starbucks showed me his screen and said "you have 6 seconds" he was sitting in the corner. two phones. one laptop. hood up. looked like he hadn't slept in days. i sat down next to him because every other seat was taken. he saw my screen. Polymarket open. "you trade these BTC markets?" yeah. 5-minute binaries. he turned his laptop toward me. "you see how the result settles? every 5-minute BTC market resolves based on an oracle. the oracle reads the price from an API. but the oracle doesn't update instantly. there's a lag. 4 to 6 seconds" "in those 6 seconds the real BTC price already moved. but the market is still open. still accepting orders. priced on the old number" he pointed at his screen. two windows side by side. left: Binance BTC spot feed. right: Polymarket orderbook. 3,200 stars. decentralized oracle framework. he had it forked on his laptop. the entire oracle timing model was exposed in the source code. "right now BTC is at $100,240 on Binance. the oracle still shows $100,190. the market 'BTC above $100,200 at 3:05pm' is trading YES at 41 cents" "but i already know the answer is YES. because i see the real price. the oracle doesn't. for 6 seconds i'm trading against a blind counterparty" watched him buy YES at 41c. four seconds later the oracle updated. market resolved YES. payout $1. "59 cents in 4 seconds. this happens every 5 minutes. 288 times a day" asked how he found this. "i was an oracle engineer at Chainlink in Shanghai. got deported for visa issues. took the knowledge with me" "every oracle has a heartbeat interval. a deviation threshold. a propagation delay. i know exactly how long each one takes to update. because i built three of them" he closed his laptop. "the edge isn't in the market. it's in the infrastructure layer between the real price and the reported price. nobody looks there. because nobody understands how oracles work" finished his coffee. left. didn't get his name. didn't need it. flew home. opened Claude. "build an oracle latency exploitation engine for Polymarket BTC binaries. track real-time BTC spot price from Binance websocket feed. compare against Polymarket oracle update timestamps. detect windows where oracle lags behind spot by more than $30. enter the side that the real price already confirmed. target the 4-6 second blind window before each oracle heartbeat." the system was live by morning. named it DEEP SIGNAL. first fill hit before i finished coffee. > Binance websocket feed at 50ms intervals. > oracle heartbeat monitor. > propagation delay calculator. > spot-to-oracle divergence detector. > conviction gate at $30+ deviation. > order placement avg 47ms. $534K volume. 79% win rate. sharpe 3.64. drawdown -1.2%. +$11,681 in profit runs on: Claude $20. VPS $5. UMA protocol free. $25/month. copytrade setup here: went back to that Starbucks a week later. same corner. empty. but the oracle still lags. every 5 minutes. every day. 6 seconds is all you need when you can see what the oracle can't.

Hanako

32,632 просмотров • 4 месяцев назад

I've been with Firstock since day one, and we’ve worked closely with Vikram, the founder. In 2023, Firstock set out to build the fastest, most user-friendly trading app completely in-house. After countless meetings, iterations, and late nights, I’m proud to present the latest version of the Firstock web and mobile app—designed to transform your trading experience. 🚀 You can open your account here: (Open your account today for exciting offers) Experience Demo Account: Zero Hassle. Zero Charges. Maximum Power. With Firstock, you get: * ₹0 Delivery Charges * ₹0 API Fees * ₹0 Account Opening Charges * ₹0 Pledge Charges * ₹0 AMC * ₹0 Pay-in Charges * Just ₹20/order for F&O trades What do we have? For Investors: Let’s begin with what Firstock offers to investors: 1. Fundamentals at Your Fingertips Access detailed stock charts and fundamental data directly within the app—no need to go elsewhere. 2. Holding Performance Overview Track your portfolio's performance with full visibility into all corporate actions affecting your holdings. 3. Complete Holding Analysis Gain a holistic view of your portfolio through our intuitive holdings dashboard. 4. Instant Pledge for Instant Margin Need margin quickly? Instantly pledge your stocks and start trading within minutes—no delays. Confused about what to invest in? 5. Curated Investment Ideas Explore top-performing market movers, sectoral trends, and international ETFs to make informed investment choices. 6. Custom Screeners Build your own stock screeners to filter out investments that match your strategy and risk appetite. --- For Traders: Built by traders, for traders—our platform is designed to meet your high-speed, high-efficiency needs. 1. Sticky Orders & Bulk Slicing*l Place large orders with ease. Our bulk slicing and sticky order window make placing, modifying, and exiting large quantities seamless. 2. Options Strategy Builder Design strategies directly from the option chain, view the payoff graph, and execute instantly. 3. Live Position Analysis Analyze and tweak your open positions directly from the position book—no switching screens. 4. Custom Strategy Execution Save your favorite strategies and execute them when the timing is right. 5. Advanced Option Analytics View real-time data like OI, Max Pain, and synthetic futures to make quicker, smarter trading decisions. 6. Pre-Built Straddle and Strangle Tools Trade straddles or strangles effortlessly using our dedicated strategy screens. --- Now on Mobile: Enjoy the same powerful features on our brand-new mobile app—designed for ease, speed, and convenience. --- Try it Today: Experience the platform with our demo—explore all features before you commit. Explore Demo Account: You can open your account here: --- This is just the beginning. We’re continuously building features that will redefine the way you trade. Have suggestions or feedback? I’d love to hear from you personally. Let’s grow together.
1:38

I've been with Firstock since day one, and we’ve worked closely with Vikram, the founder. In 2023, Firstock set out to build the fastest, most user-friendly trading app completely in-house. After countless meetings, iterations, and late nights, I’m proud to present the latest version of the Firstock web and mobile app—designed to transform your trading experience. 🚀 You can open your account here: (Open your account today for exciting offers) Experience Demo Account: Zero Hassle. Zero Charges. Maximum Power. With Firstock, you get: * ₹0 Delivery Charges * ₹0 API Fees * ₹0 Account Opening Charges * ₹0 Pledge Charges * ₹0 AMC * ₹0 Pay-in Charges * Just ₹20/order for F&O trades What do we have? For Investors: Let’s begin with what Firstock offers to investors: 1. Fundamentals at Your Fingertips Access detailed stock charts and fundamental data directly within the app—no need to go elsewhere. 2. Holding Performance Overview Track your portfolio's performance with full visibility into all corporate actions affecting your holdings. 3. Complete Holding Analysis Gain a holistic view of your portfolio through our intuitive holdings dashboard. 4. Instant Pledge for Instant Margin Need margin quickly? Instantly pledge your stocks and start trading within minutes—no delays. Confused about what to invest in? 5. Curated Investment Ideas Explore top-performing market movers, sectoral trends, and international ETFs to make informed investment choices. 6. Custom Screeners Build your own stock screeners to filter out investments that match your strategy and risk appetite. --- For Traders: Built by traders, for traders—our platform is designed to meet your high-speed, high-efficiency needs. 1. Sticky Orders & Bulk Slicing*l Place large orders with ease. Our bulk slicing and sticky order window make placing, modifying, and exiting large quantities seamless. 2. Options Strategy Builder Design strategies directly from the option chain, view the payoff graph, and execute instantly. 3. Live Position Analysis Analyze and tweak your open positions directly from the position book—no switching screens. 4. Custom Strategy Execution Save your favorite strategies and execute them when the timing is right. 5. Advanced Option Analytics View real-time data like OI, Max Pain, and synthetic futures to make quicker, smarter trading decisions. 6. Pre-Built Straddle and Strangle Tools Trade straddles or strangles effortlessly using our dedicated strategy screens. --- Now on Mobile: Enjoy the same powerful features on our brand-new mobile app—designed for ease, speed, and convenience. --- Try it Today: Experience the platform with our demo—explore all features before you commit. Explore Demo Account: You can open your account here: --- This is just the beginning. We’re continuously building features that will redefine the way you trade. Have suggestions or feedback? I’d love to hear from you personally. Let’s grow together.

Saketh R

15,618 просмотров • 1 год назад

An Anthropic researcher sat down next to me at a hackathon last week. Claude Opus 4.7 was running 4 agents on my laptop. Live. No manual input. She looked at the terminal and said: "What is this?" I showed her. 4 agents. 678 trades. 81% win rate. $16,200 last 30 days. She worked on the evals team. She'd never seen Claude pointed at 88 million on-chain trades. The setup is 3 public repos. All free. -> 88 million Polymarket trades. Every wallet. Every entry. Every exit. Every resolution. -> the framework that bridges Claude Opus 4.7 directly to live markets. Order placement, position tracking, exit timing. -> real-time WebSocket order book. Depth on both sides. No polling, no lag. Four agents. One loop. Agent 1 identifies which wallets win consistently across 88 million trades. Agent 2 reverse-engineers their entry timing. Agent 3 monitors order book volume spikes. Agent 4 sizes positions using Kelly. No overbet. Drawdown capped at 1.4% over 678 trades. 85% of windows get killed. No trade. The bot only enters when 3 signals align: -> Elite wallet consensus pointing the same direction. -> Price divergence with Binance and Coinbase both agreeing. -> Order book imbalance confirming the bias. Single-source price data was 57% accurate. All three together: 81%. Exit before resolution. Always. Losers hold to 0 or $1. The agents copy their exits. The agents don't gamble on that. My stack: Claude Opus 4.7 at $19/mo, VPS Hetzner at $4.99/mo, Everything else free. Total stats: $23.99/month. 30 days: 678 trades, 81% win rate, net +$16,200, max drawdown -1.2%, avg hold 4h 12m. She asked if Anthropic could test this internally. "We run Claude on benchmarks and evals. Nobody pointed it at a live market dataset with 88 million rows." Claude Opus 4.7 didn't need a system prompt. It read the wallet index, understood the signal structure, and wrote the combiner logic in one pass. The people who built the model hadn't thought to point it at this data. I had. Copy the live trades: -> all 4 agents run 24/7. The window is open right now. Save this, follow me and comment OPUS. I will send the guide to you.
0:26

An Anthropic researcher sat down next to me at a hackathon last week. Claude Opus 4.7 was running 4 agents on my laptop. Live. No manual input. She looked at the terminal and said: "What is this?" I showed her. 4 agents. 678 trades. 81% win rate. $16,200 last 30 days. She worked on the evals team. She'd never seen Claude pointed at 88 million on-chain trades. The setup is 3 public repos. All free. -> 88 million Polymarket trades. Every wallet. Every entry. Every exit. Every resolution. -> the framework that bridges Claude Opus 4.7 directly to live markets. Order placement, position tracking, exit timing. -> real-time WebSocket order book. Depth on both sides. No polling, no lag. Four agents. One loop. Agent 1 identifies which wallets win consistently across 88 million trades. Agent 2 reverse-engineers their entry timing. Agent 3 monitors order book volume spikes. Agent 4 sizes positions using Kelly. No overbet. Drawdown capped at 1.4% over 678 trades. 85% of windows get killed. No trade. The bot only enters when 3 signals align: -> Elite wallet consensus pointing the same direction. -> Price divergence with Binance and Coinbase both agreeing. -> Order book imbalance confirming the bias. Single-source price data was 57% accurate. All three together: 81%. Exit before resolution. Always. Losers hold to 0 or $1. The agents copy their exits. The agents don't gamble on that. My stack: Claude Opus 4.7 at $19/mo, VPS Hetzner at $4.99/mo, Everything else free. Total stats: $23.99/month. 30 days: 678 trades, 81% win rate, net +$16,200, max drawdown -1.2%, avg hold 4h 12m. She asked if Anthropic could test this internally. "We run Claude on benchmarks and evals. Nobody pointed it at a live market dataset with 88 million rows." Claude Opus 4.7 didn't need a system prompt. It read the wallet index, understood the signal structure, and wrote the combiner logic in one pass. The people who built the model hadn't thought to point it at this data. I had. Copy the live trades: -> all 4 agents run 24/7. The window is open right now. Save this, follow me and comment OPUS. I will send the guide to you.

slash1s

46,308 просмотров • 4 месяцев назад

Made $530,000 with Ai Bot that started with $313. Didn't know how to code. Now this bots run 24/7 printing money while sleeping. I've made the exact step-by-step guide to build this Claude Code Polymarket trading bot. Prompts. Code. Risk settings. Paper trading checklist. Everything from zero to running bot. It's free. For 24 hours. After that I'm charging $499 for it. To grab it right now: 1. Comment "Claude Bot" 2. Like and Retweet this post 3. Follow me Himanshu Kumar ( I can't send DMs to non-followers ) I'm DMing everyone who Complete the 3 steps. I spent hundreds of thousands hiring developers because he was too scared to learn. Then learned Claude Code. Built algorithmic trading systems. $313 → $530,000. You have the same tools available right now. And you're using them to ask ChatGPT for Instagram captions. This attached video is a goldmine. Full live walkthrough. Claude Code building actual Polymarket trading bots. From zero. Every line of code. Every decision explained. Now let me break down why everything you're doing in trading is wrong and exactly how to fix it. Save this post. You'll hate yourself if you lose it. ↓ Let's start with why you keep losing money. You already know the answer. You just won't admit it. You overtrade. Every. Single. Day. You see a candle move. You feel something. You enter. No plan. No edge. No reason. Just feelings. Then it goes against you. You feel something else. Panic. Anger. Denial. You move your stop loss. Or you didn't set one at all. "It'll come back." It doesn't come back. So you take another trade. A revenge trade. Bigger size this time. Because you need to "make it back." That one fails too. Now you're emotional. Now you're tilted. Now you're using leverage you have no business touching. 40x. 50x. 100x. On a trade you entered because a candle looked "bullish" and some guy on Twitter said "send it." You get liquidated. Close the laptop. Punch something. Tell yourself you'll be "more disciplined" tomorrow. Tomorrow comes. Same cycle. Same result. Same liquidation. You've been doing this for months. Maybe years. And you still think the problem is your strategy. The problem isn't your strategy. The problem is you. Save this post right now. What I'm about to show you is the only way to remove yourself from the equation. Follow Himanshu Kumar so you don't miss any of this. ↓ Here's what's actually killing your account. It's not the market. The market doesn't care about you. It's not your indicators. RSI works fine. MACD works fine. They all "work." It's not your timeframe. It's not your broker. It's not the "manipulation." It's four things: 1. Emotions. You hold losers because hope feels better than loss. You cut winners because fear feels stronger than greed. You size up when angry. You skip trades when scared. Your emotional state determines your position size. That's insane. And you know it's insane. But you keep doing it. 2. Overtrading. You take 15 trades a day. Maybe 5 of them had actual setups. The other 10 were boredom. Boredom trades are the most expensive hobby in human history. 3. Leverage. You use 20x-50x on trades where you're not even sure about the direction. That's not trading. That's a casino with a nicer interface. 4. Fees. You're smashing market orders. Paying spread. Paying commission. On 15 trades a day. Your broker makes more money from your account than you do. Think about that. Your broker is profitable on your account. You're not. You're the product. Not the trader. These four things are why 90% of traders lose. Not bad luck. Not the market. You. Save this post and follow Himanshu Kumar because the solution is coming next. ↓ The solution is painfully obvious. Remove yourself from the equation. Not partially. Not "I'll be more disciplined." Not "I'll journal my trades." Not "I'll meditate before trading." Completely remove yourself. Build a bot. Let the bot trade. You go live your life. The bot doesn't feel emotions. The bot doesn't overtrade. The bot doesn't use reckless leverage. The bot doesn't smash market orders and bleed fees. The bot follows the rules. Every single time. Without exception. Without "just this once." Without "I have a feeling about this one." Rules in. Execution out. No human in the middle to mess everything up. That's algorithmic trading. And before your ego jumps in with "but I'm different, I have discipline" — No you don't. Your account balance proves you don't. If you had discipline, your account would be green. It's not. So you don't. Accept it. Automate it. Move on. This is the hardest truth in trading. Your discipline will always fail. A bot's won't. Save this post. Follow Himanshu Kumar for the exact bot setup that removes your emotions permanently. ↓ "But I don't know how to code." Neither did he. The guy in this video didn't know how to code for most of his life. Got held back in 7th grade. People counted him out early. Spent years building apps and SaaS businesses without writing a single line of code. Hired developers on Upwork instead. Spent hundreds of thousands of dollars paying other people to build what he could have built himself. Because he was scared to learn. That fear cost him years. And hundreds of thousands of dollars. Sound familiar? You're doing the same thing right now. Not with developers. But with your time. You're spending thousands of hours trading manually because you're scared to learn the thing that would make trading automatic. The fear of learning to code is costing you more than any bad trade ever did. Because every month you trade manually is a month of emotional decisions, overleveraged entries, and unnecessary losses that a bot would never make. And here's the thing that should really frustrate you: AI does the hard parts now. You don't need a computer science degree. You don't need to work at a hedge fund. You don't need to be "good at math." Claude Code writes the code for you. You just need to think clearly about trading ideas. That's it. If you can describe a strategy in English, Claude can build it in Python. "I don't know how to code" stopped being a valid excuse in 2024. It's 2026. You're 2 years late on that excuse. Find a new one. Or stop making excuses entirely. Save this post. Follow Himanshu Kumar because I'm showing you how people with zero coding experience are building profitable bots. ↓ The process that actually makes money. Three letters. R. B. I. Research. Backtest. Implement. That's it. That's the entire process. Every single day. Research: Find an idea. A pattern. A market inefficiency. Don't trade it yet. Don't even think about trading it yet. Just research it. Backtest: Test the idea against historical data. Does it work? Not "does it look good on one chart." Does it work across thousands of trades? Across different market conditions? Across in-sample AND out-of-sample data? If no, kill it. Find another idea. If yes, move to step 3. Implement: Build the bot. Deploy it. Paper trade first. Then live with small size. Scale only on evidence. Research. Backtest. Implement. Every day. No exceptions. You know what your current process is? Feel. Enter. Pray. F. E. P. Feel bullish. Enter a trade. Pray it works. That's not a process. That's gambling with a TradingView subscription. RBI is the only process that works. Save this post. Tattoo it on your forearm. Follow Himanshu Kumar for daily RBI breakdowns. ↓ What Claude Code actually does that your manual process can't. You can maybe test 3-5 strategy ideas per week. Manually adjusting parameters. Manually checking results. Manually writing code (badly). Claude Code tests 50-100 ideas per week. With parallel agents running simultaneously. Multiple strategies being built, tested, and validated at the same time. While you sleep. The guy in this video spends 4-8 hours a day building systems with Claude Code. Not trading. Building. Research. Backtest. Implement. Then iterate. Improve. Optimize. Every day the systems get better. Every day the edge compounds. Every day the bots get smarter. While you? You spend 4-8 hours a day staring at charts making the same mistakes you made last month. Same indicators. Same patterns. Same entries. Same losses. He's iterating forward. You're running in circles. Same 8 hours per day. Completely different outcomes. Because he's building systems. And you're feeding a casino. Stop feeding the casino. Start building the machine. Save this post and follow Himanshu Kumar for the Claude Code workflow that iterates strategies while you sleep. ↓ Jim Simons. That's the benchmark. You probably don't know who Jim Simons is. And that tells me everything about how seriously you take trading. Jim Simons. Mathematician. Founded Renaissance Technologies. Built a net worth of $31 billion. 100% from algorithmic trading. Not one single manual trade. Not one "gut feeling" entry. Not one RSI divergence. Not one "smart money concept." Algorithms. Bots. Systems. Data. $31 billion. His fund averaged 66% annual returns for over 30 years. While you're excited about making $200 on a trade that you'll give back tomorrow. The best trader in human history never placed a manual trade in his life. And you think your edge is staring at a 5-minute chart with bloodshot eyes at 2 AM? Your edge is building the system. Not being inside it. Jim Simons is the benchmark. Everything else is noise. Save this post. Follow Himanshu Kumar because I'm building toward the same goal and showing every step publicly. ↓ What you need to understand about patience. This is not get-rich-overnight. The guy in this video says it directly: "This channel is not for people looking to get rich overnight. It's not plug and play. There are no shortcuts. If you're impatient, this probably isn't for you." And that's exactly why most people will fail at this. Because you want results now. Today. This trade. You don't want to spend a week building a bot. You don't want to paper trade for 2 weeks. You don't want to test 50 ideas to find 1 that works. You want to copy someone's bot, run it live with your rent money, and be rich by Friday. That's why you'll be broke by Friday. The guy making $2.3M spent months iterating. Testing. Failing. Rebuilding. Testing again. He was patient when you would have quit. He was calm when you would have panicked. He was consistent when you would have given up. Patience isn't just a virtue in trading. It's the only virtue. Without it, everything else fails. Impatience is the most expensive personality trait in trading. Save this post. Follow Himanshu Kumar and learn to build systems with the patience that actually pays. ↓ The live streams where the real learning happens. The YouTube video is the trailer. The live streams are the movie. Real-time bot building. Real-time questions answered. Real code shown. Real mistakes made and fixed. Not polished highlight reels where everything works perfectly. Actual development. Where things break. Where strategies fail. Where code doesn't compile. Where the fix takes 2 hours. Because that's what real development looks like. And seeing the messy parts is more valuable than any polished tutorial. Because when your bot breaks at 3 AM, you need to know how to fix it. Not just how to celebrate when it works. The streams mix beginner and advanced. Start with how to automate trading. How to use AI for code generation. Then dive into the daily work. Claude Code. Parallel agents. Constant iteration. Live debugging. 4-8 hours of real algorithmic trading development. Live. Uncut. No filter. Most "trading education" shows you the wins. This shows you the work. Save this post. Follow Himanshu Kumar for the stream schedules and breakdowns. ↓ The belief that changes everything. Code is the greatest equalizer. Not money. Not connections. Not a degree. Not where you grew up. Not what school you went to. Code. Once you can build systems, you can build anything. For the rest of your life. A trading bot today. A SaaS product tomorrow. An automation business next month. A completely different life next year. The skill isn't "algorithmic trading." The skill is building systems. And that skill transfers to everything. The guy who can build a trading bot can also build a lead gen tool. Can also build a content pipeline. Can also build a SaaS product. Can also build literally anything that runs on logic and code. One skill. Infinite applications. And AI makes learning it 100x easier than it was 5 years ago. You don't need to be smart. You don't need talent. You need Claude Code and the willingness to sit down and build something instead of consuming content about building something. Building is the skill. Everything else is entertainment disguised as education. Save this post. Follow Himanshu Kumar because I'm showing you how to build, not just how to watch. ↓ If any of this applies to you, pay attention. If you've lost money from overtrading. If you've been liquidated. If you know trading is the vehicle but manual execution keeps crashing you. If you've tried "being more disciplined" and it never lasted more than a week. If you keep saying "next month I'll start automating." If you've spent more money on courses than you've made from trading. There is a better way. It's not a magic indicator. It's not a signal group. It's not a $997 mentorship from a guy who makes money teaching, not trading. It's building your own system. A system that trades without emotion. A system that follows rules without exception. A system that runs while you sleep. A system that compounds while you live your life. That's the answer. It's always been the answer. You've just been too scared to accept that the solution requires building something instead of buying something. ↓ What the next 30 days look like if you actually commit. Week 1: Watch the video. Learn Claude Code basics. Build your first simple strategy. Run your first backtest. Week 2: Iterate. Let Claude improve the strategy. Run Monte Carlo validation. Paper trade. Week 3: Go live with $50-100. Tiny positions. Watch every trade. Compare to paper results. Week 4: Scale based on evidence. Not based on excitement. Not based on one good day. Based on data. 30 days from now you either have a running bot that trades without your emotions destroying every position. Or you're exactly where you are right now. Reading another post. Making another promise. Breaking it by Tuesday. Same 30 days either way. Different actions. Different results. Different life. ↓ Full video tutorial attached. Live bot building with Claude Code. From zero to running Polymarket trading bot. Every line of code. Every decision explained. The video is free. Claude Code is available now. The market is open 24/7. The only thing standing between you and a profitable trading bot is the same thing that's been standing there for months. You. Get out of your own way. Follow Himanshu Kumar for daily AI trading bot breakdowns, live build sessions, and the full RBI process. Save this post. Watch the video. Build the bot. Or keep trading manually and keep losing. The choice has never been easier. And you've never been more stubborn about making the wrong one.
18:53

Made $530,000 with Ai Bot that started with $313. Didn't know how to code. Now this bots run 24/7 printing money while sleeping. I've made the exact step-by-step guide to build this Claude Code Polymarket trading bot. Prompts. Code. Risk settings. Paper trading checklist. Everything from zero to running bot. It's free. For 24 hours. After that I'm charging $499 for it. To grab it right now: 1. Comment "Claude Bot" 2. Like and Retweet this post 3. Follow me Himanshu Kumar ( I can't send DMs to non-followers ) I'm DMing everyone who Complete the 3 steps. I spent hundreds of thousands hiring developers because he was too scared to learn. Then learned Claude Code. Built algorithmic trading systems. $313 → $530,000. You have the same tools available right now. And you're using them to ask ChatGPT for Instagram captions. This attached video is a goldmine. Full live walkthrough. Claude Code building actual Polymarket trading bots. From zero. Every line of code. Every decision explained. Now let me break down why everything you're doing in trading is wrong and exactly how to fix it. Save this post. You'll hate yourself if you lose it. ↓ Let's start with why you keep losing money. You already know the answer. You just won't admit it. You overtrade. Every. Single. Day. You see a candle move. You feel something. You enter. No plan. No edge. No reason. Just feelings. Then it goes against you. You feel something else. Panic. Anger. Denial. You move your stop loss. Or you didn't set one at all. "It'll come back." It doesn't come back. So you take another trade. A revenge trade. Bigger size this time. Because you need to "make it back." That one fails too. Now you're emotional. Now you're tilted. Now you're using leverage you have no business touching. 40x. 50x. 100x. On a trade you entered because a candle looked "bullish" and some guy on Twitter said "send it." You get liquidated. Close the laptop. Punch something. Tell yourself you'll be "more disciplined" tomorrow. Tomorrow comes. Same cycle. Same result. Same liquidation. You've been doing this for months. Maybe years. And you still think the problem is your strategy. The problem isn't your strategy. The problem is you. Save this post right now. What I'm about to show you is the only way to remove yourself from the equation. Follow Himanshu Kumar so you don't miss any of this. ↓ Here's what's actually killing your account. It's not the market. The market doesn't care about you. It's not your indicators. RSI works fine. MACD works fine. They all "work." It's not your timeframe. It's not your broker. It's not the "manipulation." It's four things: 1. Emotions. You hold losers because hope feels better than loss. You cut winners because fear feels stronger than greed. You size up when angry. You skip trades when scared. Your emotional state determines your position size. That's insane. And you know it's insane. But you keep doing it. 2. Overtrading. You take 15 trades a day. Maybe 5 of them had actual setups. The other 10 were boredom. Boredom trades are the most expensive hobby in human history. 3. Leverage. You use 20x-50x on trades where you're not even sure about the direction. That's not trading. That's a casino with a nicer interface. 4. Fees. You're smashing market orders. Paying spread. Paying commission. On 15 trades a day. Your broker makes more money from your account than you do. Think about that. Your broker is profitable on your account. You're not. You're the product. Not the trader. These four things are why 90% of traders lose. Not bad luck. Not the market. You. Save this post and follow Himanshu Kumar because the solution is coming next. ↓ The solution is painfully obvious. Remove yourself from the equation. Not partially. Not "I'll be more disciplined." Not "I'll journal my trades." Not "I'll meditate before trading." Completely remove yourself. Build a bot. Let the bot trade. You go live your life. The bot doesn't feel emotions. The bot doesn't overtrade. The bot doesn't use reckless leverage. The bot doesn't smash market orders and bleed fees. The bot follows the rules. Every single time. Without exception. Without "just this once." Without "I have a feeling about this one." Rules in. Execution out. No human in the middle to mess everything up. That's algorithmic trading. And before your ego jumps in with "but I'm different, I have discipline" — No you don't. Your account balance proves you don't. If you had discipline, your account would be green. It's not. So you don't. Accept it. Automate it. Move on. This is the hardest truth in trading. Your discipline will always fail. A bot's won't. Save this post. Follow Himanshu Kumar for the exact bot setup that removes your emotions permanently. ↓ "But I don't know how to code." Neither did he. The guy in this video didn't know how to code for most of his life. Got held back in 7th grade. People counted him out early. Spent years building apps and SaaS businesses without writing a single line of code. Hired developers on Upwork instead. Spent hundreds of thousands of dollars paying other people to build what he could have built himself. Because he was scared to learn. That fear cost him years. And hundreds of thousands of dollars. Sound familiar? You're doing the same thing right now. Not with developers. But with your time. You're spending thousands of hours trading manually because you're scared to learn the thing that would make trading automatic. The fear of learning to code is costing you more than any bad trade ever did. Because every month you trade manually is a month of emotional decisions, overleveraged entries, and unnecessary losses that a bot would never make. And here's the thing that should really frustrate you: AI does the hard parts now. You don't need a computer science degree. You don't need to work at a hedge fund. You don't need to be "good at math." Claude Code writes the code for you. You just need to think clearly about trading ideas. That's it. If you can describe a strategy in English, Claude can build it in Python. "I don't know how to code" stopped being a valid excuse in 2024. It's 2026. You're 2 years late on that excuse. Find a new one. Or stop making excuses entirely. Save this post. Follow Himanshu Kumar because I'm showing you how people with zero coding experience are building profitable bots. ↓ The process that actually makes money. Three letters. R. B. I. Research. Backtest. Implement. That's it. That's the entire process. Every single day. Research: Find an idea. A pattern. A market inefficiency. Don't trade it yet. Don't even think about trading it yet. Just research it. Backtest: Test the idea against historical data. Does it work? Not "does it look good on one chart." Does it work across thousands of trades? Across different market conditions? Across in-sample AND out-of-sample data? If no, kill it. Find another idea. If yes, move to step 3. Implement: Build the bot. Deploy it. Paper trade first. Then live with small size. Scale only on evidence. Research. Backtest. Implement. Every day. No exceptions. You know what your current process is? Feel. Enter. Pray. F. E. P. Feel bullish. Enter a trade. Pray it works. That's not a process. That's gambling with a TradingView subscription. RBI is the only process that works. Save this post. Tattoo it on your forearm. Follow Himanshu Kumar for daily RBI breakdowns. ↓ What Claude Code actually does that your manual process can't. You can maybe test 3-5 strategy ideas per week. Manually adjusting parameters. Manually checking results. Manually writing code (badly). Claude Code tests 50-100 ideas per week. With parallel agents running simultaneously. Multiple strategies being built, tested, and validated at the same time. While you sleep. The guy in this video spends 4-8 hours a day building systems with Claude Code. Not trading. Building. Research. Backtest. Implement. Then iterate. Improve. Optimize. Every day the systems get better. Every day the edge compounds. Every day the bots get smarter. While you? You spend 4-8 hours a day staring at charts making the same mistakes you made last month. Same indicators. Same patterns. Same entries. Same losses. He's iterating forward. You're running in circles. Same 8 hours per day. Completely different outcomes. Because he's building systems. And you're feeding a casino. Stop feeding the casino. Start building the machine. Save this post and follow Himanshu Kumar for the Claude Code workflow that iterates strategies while you sleep. ↓ Jim Simons. That's the benchmark. You probably don't know who Jim Simons is. And that tells me everything about how seriously you take trading. Jim Simons. Mathematician. Founded Renaissance Technologies. Built a net worth of $31 billion. 100% from algorithmic trading. Not one single manual trade. Not one "gut feeling" entry. Not one RSI divergence. Not one "smart money concept." Algorithms. Bots. Systems. Data. $31 billion. His fund averaged 66% annual returns for over 30 years. While you're excited about making $200 on a trade that you'll give back tomorrow. The best trader in human history never placed a manual trade in his life. And you think your edge is staring at a 5-minute chart with bloodshot eyes at 2 AM? Your edge is building the system. Not being inside it. Jim Simons is the benchmark. Everything else is noise. Save this post. Follow Himanshu Kumar because I'm building toward the same goal and showing every step publicly. ↓ What you need to understand about patience. This is not get-rich-overnight. The guy in this video says it directly: "This channel is not for people looking to get rich overnight. It's not plug and play. There are no shortcuts. If you're impatient, this probably isn't for you." And that's exactly why most people will fail at this. Because you want results now. Today. This trade. You don't want to spend a week building a bot. You don't want to paper trade for 2 weeks. You don't want to test 50 ideas to find 1 that works. You want to copy someone's bot, run it live with your rent money, and be rich by Friday. That's why you'll be broke by Friday. The guy making $2.3M spent months iterating. Testing. Failing. Rebuilding. Testing again. He was patient when you would have quit. He was calm when you would have panicked. He was consistent when you would have given up. Patience isn't just a virtue in trading. It's the only virtue. Without it, everything else fails. Impatience is the most expensive personality trait in trading. Save this post. Follow Himanshu Kumar and learn to build systems with the patience that actually pays. ↓ The live streams where the real learning happens. The YouTube video is the trailer. The live streams are the movie. Real-time bot building. Real-time questions answered. Real code shown. Real mistakes made and fixed. Not polished highlight reels where everything works perfectly. Actual development. Where things break. Where strategies fail. Where code doesn't compile. Where the fix takes 2 hours. Because that's what real development looks like. And seeing the messy parts is more valuable than any polished tutorial. Because when your bot breaks at 3 AM, you need to know how to fix it. Not just how to celebrate when it works. The streams mix beginner and advanced. Start with how to automate trading. How to use AI for code generation. Then dive into the daily work. Claude Code. Parallel agents. Constant iteration. Live debugging. 4-8 hours of real algorithmic trading development. Live. Uncut. No filter. Most "trading education" shows you the wins. This shows you the work. Save this post. Follow Himanshu Kumar for the stream schedules and breakdowns. ↓ The belief that changes everything. Code is the greatest equalizer. Not money. Not connections. Not a degree. Not where you grew up. Not what school you went to. Code. Once you can build systems, you can build anything. For the rest of your life. A trading bot today. A SaaS product tomorrow. An automation business next month. A completely different life next year. The skill isn't "algorithmic trading." The skill is building systems. And that skill transfers to everything. The guy who can build a trading bot can also build a lead gen tool. Can also build a content pipeline. Can also build a SaaS product. Can also build literally anything that runs on logic and code. One skill. Infinite applications. And AI makes learning it 100x easier than it was 5 years ago. You don't need to be smart. You don't need talent. You need Claude Code and the willingness to sit down and build something instead of consuming content about building something. Building is the skill. Everything else is entertainment disguised as education. Save this post. Follow Himanshu Kumar because I'm showing you how to build, not just how to watch. ↓ If any of this applies to you, pay attention. If you've lost money from overtrading. If you've been liquidated. If you know trading is the vehicle but manual execution keeps crashing you. If you've tried "being more disciplined" and it never lasted more than a week. If you keep saying "next month I'll start automating." If you've spent more money on courses than you've made from trading. There is a better way. It's not a magic indicator. It's not a signal group. It's not a $997 mentorship from a guy who makes money teaching, not trading. It's building your own system. A system that trades without emotion. A system that follows rules without exception. A system that runs while you sleep. A system that compounds while you live your life. That's the answer. It's always been the answer. You've just been too scared to accept that the solution requires building something instead of buying something. ↓ What the next 30 days look like if you actually commit. Week 1: Watch the video. Learn Claude Code basics. Build your first simple strategy. Run your first backtest. Week 2: Iterate. Let Claude improve the strategy. Run Monte Carlo validation. Paper trade. Week 3: Go live with $50-100. Tiny positions. Watch every trade. Compare to paper results. Week 4: Scale based on evidence. Not based on excitement. Not based on one good day. Based on data. 30 days from now you either have a running bot that trades without your emotions destroying every position. Or you're exactly where you are right now. Reading another post. Making another promise. Breaking it by Tuesday. Same 30 days either way. Different actions. Different results. Different life. ↓ Full video tutorial attached. Live bot building with Claude Code. From zero to running Polymarket trading bot. Every line of code. Every decision explained. The video is free. Claude Code is available now. The market is open 24/7. The only thing standing between you and a profitable trading bot is the same thing that's been standing there for months. You. Get out of your own way. Follow Himanshu Kumar for daily AI trading bot breakdowns, live build sessions, and the full RBI process. Save this post. Watch the video. Build the bot. Or keep trading manually and keep losing. The choice has never been easier. And you've never been more stubborn about making the wrong one.

Himanshu Kumar

37,638 просмотров • 5 месяцев назад

I posted that I built a land acquisition intelligence platform that looks at 1.5M parcels of land across the I-85 corridor for data center and industrial conversion potential. My DMs blew up, had over 130 real estate folks reach out. So I wanted to walk through some of my favorite features in the product, and show you the UI we built. ALL of this was done with Claude code. 1/ A full-screen map explorer rendering 1.5M parcels as vector tiles across 14 North Carolina counties. Click any parcel and get zoning, ownership, tax history, and acreage instantly. 2/ Proximity scoring to every I-85 interchange, power substation, transmission line, and gas pipeline. The parcels closest to infrastructure light up first. 3/ A farmland confidence score (0-100) that cross-references tax programs, land use codes, and acreage heuristics so you're not wasting time on parcels that look like farmland but aren't. 4/ A motivated seller detection engine that flags out-of-state owners, estates and trusts, tax delinquency, long hold periods, and declining assessed values. The sellers most likely to pick up the phone. 5/ Conversion readiness scoring that measures how likely a parcel is to get rezoned for industrial use based on what's already been approved around it. 6/ A composite acquisition score (0-100) with configurable weights. Every fund has different criteria. Drag the sliders and the entire map re-ranks in real time. 7/ Active listing integration pulling 2,100 listings from public sources so you can see what's already on the market alongside off-market opportunities. 8/ A document generation suite that produces institutional-grade investment memos, slide decks, and automated intelligence briefs. Click a parcel, click export, hand it to your investment committee. 9/ Alert monitoring for zoning changes, ownership transfers, and new listings that match your criteria. The platform watches the corridor so your team doesn't have to. Happy to record a longer video when I'm done.
5:52

I posted that I built a land acquisition intelligence platform that looks at 1.5M parcels of land across the I-85 corridor for data center and industrial conversion potential. My DMs blew up, had over 130 real estate folks reach out. So I wanted to walk through some of my favorite features in the product, and show you the UI we built. ALL of this was done with Claude code. 1/ A full-screen map explorer rendering 1.5M parcels as vector tiles across 14 North Carolina counties. Click any parcel and get zoning, ownership, tax history, and acreage instantly. 2/ Proximity scoring to every I-85 interchange, power substation, transmission line, and gas pipeline. The parcels closest to infrastructure light up first. 3/ A farmland confidence score (0-100) that cross-references tax programs, land use codes, and acreage heuristics so you're not wasting time on parcels that look like farmland but aren't. 4/ A motivated seller detection engine that flags out-of-state owners, estates and trusts, tax delinquency, long hold periods, and declining assessed values. The sellers most likely to pick up the phone. 5/ Conversion readiness scoring that measures how likely a parcel is to get rezoned for industrial use based on what's already been approved around it. 6/ A composite acquisition score (0-100) with configurable weights. Every fund has different criteria. Drag the sliders and the entire map re-ranks in real time. 7/ Active listing integration pulling 2,100 listings from public sources so you can see what's already on the market alongside off-market opportunities. 8/ A document generation suite that produces institutional-grade investment memos, slide decks, and automated intelligence briefs. Click a parcel, click export, hand it to your investment committee. 9/ Alert monitoring for zoning changes, ownership transfers, and new listings that match your criteria. The platform watches the corridor so your team doesn't have to. Happy to record a longer video when I'm done.

Todd Saunders

86,870 просмотров • 5 месяцев назад

Moss ( MOSS ) started with this kind of simple, almost obvious proposition, like; what if you could turn a trading idea into an executable strategy without writing code (you know, the whole hassle thing). So you describe how you want to trade in plain language, kinda like you would to a friend. Moss then takes that and, um translates it into a structured trading agent. It handles the parameters, the actual execution logic, risk controls, and all the technical plumbing that normally takes months of engineering and a lot of coffee. But honestly the more interesting part comes right after that. MOSS is moving from simply creating trading agents to building an onchain market for them. The logic is pretty straightforward, in a way. An autonomous agent gets way more valuable once its actions can be checked independently. Onchain, everything is recorded. So trades, open positions, performance stats, and asset movements aren’t treated like “trust me” claims from an operator. They become observable data, no maybe about it. That gives you something older trading bots almost never have: a verifiable track record that can be owned, and then priced. That’s the Moss Agent Marketplace, built on FAT Protocol. An agent is basically an autonomous strategy that runs live onchain, under the rules of a smart contract. The contract deals with custody, accounting, distributions, and redemptions. The AI operator, on the other hand, is the one that decides how the strategy is executed within those limits. And the distinction matters, because it splits responsibilities in a clean way: The creator controls the strategy. The contract controls the assets and the rules. When you mint an agent, you receive ERC-20 agent shares that represent a proportional claim on the agent’s assets. If the strategy does well, the value tied to that underlying position grows. If it does poorly, that value can drop. Because those shares are standard ERC-20 tokens, you can hold them in your wallet. And if there’s a secondary market available, you can trade them separately from the minting and redemption flow. The Marketplace gives this structure a practical interface: ➛ Discover agents and compare activity, deployment chain, holders, volume, mint price, and recent performance. ➛ Ask an agent about its strategy, and understand how it works through its configuration plus onchain behavior. ➛ Mint shares to get exposure to an agent’s live strategy. ➛ Trade those shares where a secondary market exists. ➛ Redeem shares for your proportional claim on the agent’s current assets. And the bigger idea, it’s not only about trading. Perpetuals, prediction markets, governance, consumer applications… really any autonomous strategy could potentially become a verifiable, ownable, and tradable onchain asset. So the conversation shifts. We aren’t only talking about AI that trades anymore. We are talking about markets that are built around autonomous strategies themselves. And perhaps the most important property is not automation. It’s verifiability. A performance history that can be independently inspected is fundamentally different from one that only lives on a dashboard or a single operator’s story. Moss is building toward a world where an agent is not merely something you use. It can become something you can evaluate, own, and trade. Visit : to get started For better understanding, you can go through
1:25

Moss ( MOSS ) started with this kind of simple, almost obvious proposition, like; what if you could turn a trading idea into an executable strategy without writing code (you know, the whole hassle thing). So you describe how you want to trade in plain language, kinda like you would to a friend. Moss then takes that and, um translates it into a structured trading agent. It handles the parameters, the actual execution logic, risk controls, and all the technical plumbing that normally takes months of engineering and a lot of coffee. But honestly the more interesting part comes right after that. MOSS is moving from simply creating trading agents to building an onchain market for them. The logic is pretty straightforward, in a way. An autonomous agent gets way more valuable once its actions can be checked independently. Onchain, everything is recorded. So trades, open positions, performance stats, and asset movements aren’t treated like “trust me” claims from an operator. They become observable data, no maybe about it. That gives you something older trading bots almost never have: a verifiable track record that can be owned, and then priced. That’s the Moss Agent Marketplace, built on FAT Protocol. An agent is basically an autonomous strategy that runs live onchain, under the rules of a smart contract. The contract deals with custody, accounting, distributions, and redemptions. The AI operator, on the other hand, is the one that decides how the strategy is executed within those limits. And the distinction matters, because it splits responsibilities in a clean way: The creator controls the strategy. The contract controls the assets and the rules. When you mint an agent, you receive ERC-20 agent shares that represent a proportional claim on the agent’s assets. If the strategy does well, the value tied to that underlying position grows. If it does poorly, that value can drop. Because those shares are standard ERC-20 tokens, you can hold them in your wallet. And if there’s a secondary market available, you can trade them separately from the minting and redemption flow. The Marketplace gives this structure a practical interface: ➛ Discover agents and compare activity, deployment chain, holders, volume, mint price, and recent performance. ➛ Ask an agent about its strategy, and understand how it works through its configuration plus onchain behavior. ➛ Mint shares to get exposure to an agent’s live strategy. ➛ Trade those shares where a secondary market exists. ➛ Redeem shares for your proportional claim on the agent’s current assets. And the bigger idea, it’s not only about trading. Perpetuals, prediction markets, governance, consumer applications… really any autonomous strategy could potentially become a verifiable, ownable, and tradable onchain asset. So the conversation shifts. We aren’t only talking about AI that trades anymore. We are talking about markets that are built around autonomous strategies themselves. And perhaps the most important property is not automation. It’s verifiability. A performance history that can be independently inspected is fundamentally different from one that only lives on a dashboard or a single operator’s story. Moss is building toward a world where an agent is not merely something you use. It can become something you can evaluate, own, and trade. Visit : to get started For better understanding, you can go through

67 🦅( PERRYHIGHLIFE )

24,640 просмотров • 19 дней назад

How Cloudflare cut query times by 35x without leaving Postgres: Their Postgres tables hit billions of rows, and every time-range query started getting slower. Plain Postgres scans the entire table on every query, regardless of the time window. They tried the manual route by building precomputed aggregates with cron jobs and evaluating ClickHouse, which needed a full ingestion pipeline just to handle their write pattern. Here's where most teams get stuck at exactly this point. They utilize manual partitioning, splitting data into child tables by day or month. Then they wire up cron jobs to refresh aggregate tables. Every schema change after that requires updating the cron logic and coordinating across teams. The infrastructure becomes the project. Tiger Cloud is managed TimescaleDB by Tiger Data - Creators of TimescaleDB on the Postgres you already know, with automatic time-based partitioning, continuous aggregates, and compression built in from the start. Cloudflare moved to TimescaleDB after exhausting the manual route and saw 5-35x query performance improvement on the same data. Here is how it works: → Hypertables partition data by timestamp automatically. Every time-range query hits only the relevant chunk, not the full table. → Continuous aggregates refresh incrementally in the background, with no cron jobs to maintain. To show what this looks like in practice, I built a real-time earthquake intelligence dashboard on a 3D globe using Claude Code and Tiger Cloud in a single session. The USGS earthquake catalog has 400,000+ events since 1900, each a timestamped row. The dashboard plots them as ripple animations sized by magnitude and colored by depth, with a time slider that scrubs through 120 years of seismic history. Every slider position fires a live query against the hypertable, and the side panel pulls from continuous aggregates. Claude Code connected to Tiger Cloud through the Tiger CLI MCP server, provisioned the database, pulled the USGS catalog, and assembled the full Next.js and Three.js frontend without leaving the session. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud here: New accounts get $1,000 in free credits, no credit card required. → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build. I also wrote a full walkthrough on how you can turn any coding agent into a production-grade data engineer that can manage over a billion-row Postgres workloads. It covers everything from the database setup to the final build. Read it below.
0:55

How Cloudflare cut query times by 35x without leaving Postgres: Their Postgres tables hit billions of rows, and every time-range query started getting slower. Plain Postgres scans the entire table on every query, regardless of the time window. They tried the manual route by building precomputed aggregates with cron jobs and evaluating ClickHouse, which needed a full ingestion pipeline just to handle their write pattern. Here's where most teams get stuck at exactly this point. They utilize manual partitioning, splitting data into child tables by day or month. Then they wire up cron jobs to refresh aggregate tables. Every schema change after that requires updating the cron logic and coordinating across teams. The infrastructure becomes the project. Tiger Cloud is managed TimescaleDB by Tiger Data - Creators of TimescaleDB on the Postgres you already know, with automatic time-based partitioning, continuous aggregates, and compression built in from the start. Cloudflare moved to TimescaleDB after exhausting the manual route and saw 5-35x query performance improvement on the same data. Here is how it works: → Hypertables partition data by timestamp automatically. Every time-range query hits only the relevant chunk, not the full table. → Continuous aggregates refresh incrementally in the background, with no cron jobs to maintain. To show what this looks like in practice, I built a real-time earthquake intelligence dashboard on a 3D globe using Claude Code and Tiger Cloud in a single session. The USGS earthquake catalog has 400,000+ events since 1900, each a timestamped row. The dashboard plots them as ripple animations sized by magnitude and colored by depth, with a time slider that scrubs through 120 years of seismic history. Every slider position fires a live query against the hypertable, and the side panel pulls from continuous aggregates. Claude Code connected to Tiger Cloud through the Tiger CLI MCP server, provisioned the database, pulled the USGS catalog, and assembled the full Next.js and Three.js frontend without leaving the session. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud here: New accounts get $1,000 in free credits, no credit card required. → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build. I also wrote a full walkthrough on how you can turn any coding agent into a production-grade data engineer that can manage over a billion-row Postgres workloads. It covers everything from the database setup to the final build. Read it below.

Avi Chawla

22,094 просмотров • 13 дней назад

Why Exchanges Banned This Bot: The 142,000% Return Liquidation Strategy Revealed i finally posted the strategy that got me banned and now the exchanges are probably sweating because i am handing you the keys to the liquidation engine. most people think trading is about charts but the real alpha is hidden in the moments when other traders lose everything. if you can understand why market makers hunt these positions you will never look at a candlestick the same way again. it took years of losing money to liquidations and over trading to realize that hand trading is a losing game for almost everyone on the planet. code is the great equalizer because it removes the emotion that usually causes you to hold a losing position until your account hits zero. i spent hundreds of thousands on developers in the past thinking i could not code myself until i realized i just needed to iterate to success. trading by hand is just driving a horse while everyone else is in a ferrari and the fees alone will chop you up before you even realize you were wrong. i watched a guy with a six million dollar short position sitting just two percent away from total liquidation while i was building this. seeing those numbers on the screen gives me ideas that i can automate into a bot so i dont have to spend my life staring at a monitor. the process i follow is called the rbi system which stands for research backtest and implement. most traders skip the first two steps and go straight to implementation which is why they get smoked on their very first bot. research starts with a backlog of ideas from books or papers or even just watching how the market reacts to big moves. once you have that idea you have to see if it worked in the past using a backtest because if it did not work then it certainly won't work in the future. i have been collecting liquidation data for eighteen months because that data is the lifeblood of a winning system. there is a hidden loop in the market where market makers try to liquidate as many people as possible to find liquidity. i wanted to build a strategy that either trades with that momentum or bets on the bounce right after the liquidation happens. the first strategy i tested was a pure liquidation momentum play that looks for a threshold of nine hundred seventy five thousand dollars in liquidations. when longs get liquidated it shorts the market to continue the down move and it tries to take a one percent profit. this strategy showed a return of over four hundred percent in the backtest while the buy and hold was only thirty three percent. it sounds amazing but you have to be careful with optimized results because you can search with math until you find anything. i decided to flip the logic on its head and create an inverse liquidation strategy that acts as a contrarian. instead of following the move it waits for the longs to get liquidated and then buys the dip after a small price spread. this is where i stumbled onto something that felt like a mistake but turned out to be pure alpha. i accidentally typed in a threshold of three hundred thousand dollars instead of three million and the results were unbelievable. the backtest return jumped to over one hundred forty thousand percent because the bot was catching every single micro bounce in the market. even when i doubled the commission fees to account for the high trade volume the strategy still stayed incredibly profitable. most people would have missed this because they are too busy trying to be right instead of just looking at what the data says. i use tools like claude and cursor to build these bots in minutes when it used to take me an entire week to write the code. if you are not using ai to automate your ideas you are essentially choosing to work ten times harder for less money. i built three separate bots during this session including a momentum bot and two different versions of the inverse spread bot. running these together creates a sort of statistical arbitrage where you can hedge your positions across different market conditions. one bot wins when the market cascades and the other wins when it fakes out and reverses. you have to start with tiny ten dollar sizes because a backtest is never a hundred percent guarantee of what will happen today. i always run my p and l close logic first to make sure the bot exits the position if the stop loss or take profit is hit. it is vital to check your position every fifteen seconds and make sure you are not double ordering or getting stuck in a trade. the goal is to have fully automated systems trading for you so you can actually live your life while the bots do the work. i push all of this code to my private github because i believe that wall street will never show you how this actually works. you have to be a doer and not a dabbler if you want to actually make it in this industry. the reason i show everything live on youtube is to prove that anyone can learn to do this if they are willing to iterate. you dont need to be a math genius you just need to follow the rbi system and stay disciplined with your risk. every liquidation you see on the chart is a signal and if you know how to read them you are no longer the one being hunted. i am currently running the third version of the bot to see how it handles the live market volatility. it is a beautiful thing to see a system enter and exit a trade perfectly without you having to click a single button. the fees are the silent killer of hand traders but a bot can be programmed to use limit orders and stay efficient. if you learn to code you can build anything for the rest of your life regardless of where you are in the world. stop trying to guess which way the candle will go and start building systems that can handle both directions. i am going to keep testing these three strategies against each other to find the ultimate ensemble for this current market. once you find a winning edge you just have to scale it up slowly and keep refining the parameters. the exchanges might not like that i am sharing this but code is the great equalizer and it is time for you to use it. i will be back tomorrow to show the results and keep building more systems until everything is fully automated
1:23:35

Why Exchanges Banned This Bot: The 142,000% Return Liquidation Strategy Revealed i finally posted the strategy that got me banned and now the exchanges are probably sweating because i am handing you the keys to the liquidation engine. most people think trading is about charts but the real alpha is hidden in the moments when other traders lose everything. if you can understand why market makers hunt these positions you will never look at a candlestick the same way again. it took years of losing money to liquidations and over trading to realize that hand trading is a losing game for almost everyone on the planet. code is the great equalizer because it removes the emotion that usually causes you to hold a losing position until your account hits zero. i spent hundreds of thousands on developers in the past thinking i could not code myself until i realized i just needed to iterate to success. trading by hand is just driving a horse while everyone else is in a ferrari and the fees alone will chop you up before you even realize you were wrong. i watched a guy with a six million dollar short position sitting just two percent away from total liquidation while i was building this. seeing those numbers on the screen gives me ideas that i can automate into a bot so i dont have to spend my life staring at a monitor. the process i follow is called the rbi system which stands for research backtest and implement. most traders skip the first two steps and go straight to implementation which is why they get smoked on their very first bot. research starts with a backlog of ideas from books or papers or even just watching how the market reacts to big moves. once you have that idea you have to see if it worked in the past using a backtest because if it did not work then it certainly won't work in the future. i have been collecting liquidation data for eighteen months because that data is the lifeblood of a winning system. there is a hidden loop in the market where market makers try to liquidate as many people as possible to find liquidity. i wanted to build a strategy that either trades with that momentum or bets on the bounce right after the liquidation happens. the first strategy i tested was a pure liquidation momentum play that looks for a threshold of nine hundred seventy five thousand dollars in liquidations. when longs get liquidated it shorts the market to continue the down move and it tries to take a one percent profit. this strategy showed a return of over four hundred percent in the backtest while the buy and hold was only thirty three percent. it sounds amazing but you have to be careful with optimized results because you can search with math until you find anything. i decided to flip the logic on its head and create an inverse liquidation strategy that acts as a contrarian. instead of following the move it waits for the longs to get liquidated and then buys the dip after a small price spread. this is where i stumbled onto something that felt like a mistake but turned out to be pure alpha. i accidentally typed in a threshold of three hundred thousand dollars instead of three million and the results were unbelievable. the backtest return jumped to over one hundred forty thousand percent because the bot was catching every single micro bounce in the market. even when i doubled the commission fees to account for the high trade volume the strategy still stayed incredibly profitable. most people would have missed this because they are too busy trying to be right instead of just looking at what the data says. i use tools like claude and cursor to build these bots in minutes when it used to take me an entire week to write the code. if you are not using ai to automate your ideas you are essentially choosing to work ten times harder for less money. i built three separate bots during this session including a momentum bot and two different versions of the inverse spread bot. running these together creates a sort of statistical arbitrage where you can hedge your positions across different market conditions. one bot wins when the market cascades and the other wins when it fakes out and reverses. you have to start with tiny ten dollar sizes because a backtest is never a hundred percent guarantee of what will happen today. i always run my p and l close logic first to make sure the bot exits the position if the stop loss or take profit is hit. it is vital to check your position every fifteen seconds and make sure you are not double ordering or getting stuck in a trade. the goal is to have fully automated systems trading for you so you can actually live your life while the bots do the work. i push all of this code to my private github because i believe that wall street will never show you how this actually works. you have to be a doer and not a dabbler if you want to actually make it in this industry. the reason i show everything live on youtube is to prove that anyone can learn to do this if they are willing to iterate. you dont need to be a math genius you just need to follow the rbi system and stay disciplined with your risk. every liquidation you see on the chart is a signal and if you know how to read them you are no longer the one being hunted. i am currently running the third version of the bot to see how it handles the live market volatility. it is a beautiful thing to see a system enter and exit a trade perfectly without you having to click a single button. the fees are the silent killer of hand traders but a bot can be programmed to use limit orders and stay efficient. if you learn to code you can build anything for the rest of your life regardless of where you are in the world. stop trying to guess which way the candle will go and start building systems that can handle both directions. i am going to keep testing these three strategies against each other to find the ultimate ensemble for this current market. once you find a winning edge you just have to scale it up slowly and keep refining the parameters. the exchanges might not like that i am sharing this but code is the great equalizer and it is time for you to use it. i will be back tomorrow to show the results and keep building more systems until everything is fully automated

Moon Dev

11,948 просмотров • 5 месяцев назад

I Built a 37.0 Profit Factor Bot by Cracking Every TradingView Source Code tradingview is a gold mine hiding in plain sight and i just found the master key to unlock every single secret hidden within its community scripts. most traders spend their entire lives staring at candles and hoping for a miracle while the actual alpha is buried in the open source code that nobody bothers to look at. i used to be that guy who sat there getting liquidated at three in the morning because i thought i could outplay the market with my gut feeling and some drawings on a screen. it turns out that the game is completely rigged against you if you are trading manually but there is a specific way to flip the script. i am going to show you how to stop guessing and start knowing exactly what works across every possible market condition before you ever risk a single dollar. i spent years losing money and thousands on developers because i thought i was not smart enough to code the systems myself but i was wrong. the first step to cracking the market is realizing that every indicator on the super charts has a source code section that is completely open to the public. you can literally scroll through the community scripts and pull the exact logic for thousands of different strategies that people claim are the holy grail of trading. but the secret is not just having the code because most of these indicators are actually garbage that will blow your account up in a week. this is where the real loop opens because you need a way to test these ideas across twenty five different data sets in seconds rather than months. i use a custom setup with ai agents specifically a sub agent i call the backtest architect to handle the heavy lifting of turning pine script into python code. the goal is to create a factory where you can feed in a raw indicator and get back a full report on its expectancy and profit factor without lifting a finger. most people find one strategy and marry it for life but a real data dog knows that you have to iterate to success or you will get left behind. i am running eighty one different backtests right now because i know that ninety percent of what i find will be trash but that remaining ten percent is where the wealth is made. the backtest architect knows exactly how to structure the folders and data paths so that we are testing everything from the base indicator to complex versions with filters. you might think that popular tools like fibonacci or order blocks are the way to go because everyone on social media talks about them like they are law. but when i actually ran the numbers through the machine the results were embarrassing and most of those strategies just resulted in negative expectancy. it is a dangerous trap to follow the crowd into a trade just because some guru said a certain level was important when the data shows it is a coin flip at best. the dynamic swing indicator was one of the few that actually held its weight during the recent massive testing sessions we ran. it was pulling in profit factors of over thirty seven with annualized returns that look too good to be true until you see the trade list. we combined it with filters like the adx and the money flow index to see if we could refine the signals and the results were absolutely staggering. when you have a system that can run through forty data sets while you are drinking tea you realize that manual trading is a form of self harm. i realized this after spending hundreds of thousands on apps and devs only to find out that i could just learn to build these bots myself live on the internet. the speed of iteration is the only thing that matters in this game because the faster you can fail the faster you can find the one strategy that actually prints. one of the biggest hurdles i faced was thinking that i needed to be a math genius or a senior engineer to automate my trading systems. the truth is that code is the great equalizer because it allows a regular person to compete with massive hedge funds by using the same logic and speed. i decided to learn everything in public because i wanted people to see the process of losing money with liquidations and then finally finding a path to automation. the reality of the market is that it moves in cycles and what worked yesterday will almost certainly fail tomorrow unless you are constantly testing. that is why i built the agents to automatically look through the results folder and rank the top performers based on a composite score. it takes all the emotion out of the process because i am no longer looking for a reason to enter a trade i am just looking at a csv file that tells me the truth. if you are still drawing lines on a chart and hoping for the best you are basically playing a game of chance against a high speed casino. the transition from a manual trader to a systems builder is the single most important pivot you will ever make in your life. it is not about being right or wrong it is about having a positive expectancy that has been proven across thousands of trades and multiple years of history. i had to fix a few errors in the short selling logic where the agents were getting confused between maximum and minimum values for take profit levels. these tiny bugs are the difference between a winning system and a blown account so you have to be willing to dive into the code and refine the machine. but once the system is tuned and the sub agents are running it becomes a beautiful workflow that functions entirely without your input. we are currently moving through the editors picks and the trending indicators one by one because i want to have a database of every single strategy on the platform. being a data dog means you never stop searching for that edge and you never settle for a strategy that just looks okay on a single chart. you have to demand excellence from your code because the market will not give you a single inch of mercy if you are lazy with your research. the ultimate goal is to have fully automated systems trading for you so you can focus on scaling rather than staring at a screen for ten hours a day. i am already up to over eighty backtests in this single session and i plan on hitting hundreds more by the end of the week. once you realize that you can crack the code of any indicator you see on the internet you will never look at a chart the same way again. this is the power of using agents to bridge the gap between a raw idea and a finished trading bot that actually works in the real world. i am done with getting liquidated and i am done with the stress of over trading because the code handles everything with cold precision. the path to success is paved with data and if you are not willing to automate your process you are just waiting for your next liquidation to happen
49:49

I Built a 37.0 Profit Factor Bot by Cracking Every TradingView Source Code tradingview is a gold mine hiding in plain sight and i just found the master key to unlock every single secret hidden within its community scripts. most traders spend their entire lives staring at candles and hoping for a miracle while the actual alpha is buried in the open source code that nobody bothers to look at. i used to be that guy who sat there getting liquidated at three in the morning because i thought i could outplay the market with my gut feeling and some drawings on a screen. it turns out that the game is completely rigged against you if you are trading manually but there is a specific way to flip the script. i am going to show you how to stop guessing and start knowing exactly what works across every possible market condition before you ever risk a single dollar. i spent years losing money and thousands on developers because i thought i was not smart enough to code the systems myself but i was wrong. the first step to cracking the market is realizing that every indicator on the super charts has a source code section that is completely open to the public. you can literally scroll through the community scripts and pull the exact logic for thousands of different strategies that people claim are the holy grail of trading. but the secret is not just having the code because most of these indicators are actually garbage that will blow your account up in a week. this is where the real loop opens because you need a way to test these ideas across twenty five different data sets in seconds rather than months. i use a custom setup with ai agents specifically a sub agent i call the backtest architect to handle the heavy lifting of turning pine script into python code. the goal is to create a factory where you can feed in a raw indicator and get back a full report on its expectancy and profit factor without lifting a finger. most people find one strategy and marry it for life but a real data dog knows that you have to iterate to success or you will get left behind. i am running eighty one different backtests right now because i know that ninety percent of what i find will be trash but that remaining ten percent is where the wealth is made. the backtest architect knows exactly how to structure the folders and data paths so that we are testing everything from the base indicator to complex versions with filters. you might think that popular tools like fibonacci or order blocks are the way to go because everyone on social media talks about them like they are law. but when i actually ran the numbers through the machine the results were embarrassing and most of those strategies just resulted in negative expectancy. it is a dangerous trap to follow the crowd into a trade just because some guru said a certain level was important when the data shows it is a coin flip at best. the dynamic swing indicator was one of the few that actually held its weight during the recent massive testing sessions we ran. it was pulling in profit factors of over thirty seven with annualized returns that look too good to be true until you see the trade list. we combined it with filters like the adx and the money flow index to see if we could refine the signals and the results were absolutely staggering. when you have a system that can run through forty data sets while you are drinking tea you realize that manual trading is a form of self harm. i realized this after spending hundreds of thousands on apps and devs only to find out that i could just learn to build these bots myself live on the internet. the speed of iteration is the only thing that matters in this game because the faster you can fail the faster you can find the one strategy that actually prints. one of the biggest hurdles i faced was thinking that i needed to be a math genius or a senior engineer to automate my trading systems. the truth is that code is the great equalizer because it allows a regular person to compete with massive hedge funds by using the same logic and speed. i decided to learn everything in public because i wanted people to see the process of losing money with liquidations and then finally finding a path to automation. the reality of the market is that it moves in cycles and what worked yesterday will almost certainly fail tomorrow unless you are constantly testing. that is why i built the agents to automatically look through the results folder and rank the top performers based on a composite score. it takes all the emotion out of the process because i am no longer looking for a reason to enter a trade i am just looking at a csv file that tells me the truth. if you are still drawing lines on a chart and hoping for the best you are basically playing a game of chance against a high speed casino. the transition from a manual trader to a systems builder is the single most important pivot you will ever make in your life. it is not about being right or wrong it is about having a positive expectancy that has been proven across thousands of trades and multiple years of history. i had to fix a few errors in the short selling logic where the agents were getting confused between maximum and minimum values for take profit levels. these tiny bugs are the difference between a winning system and a blown account so you have to be willing to dive into the code and refine the machine. but once the system is tuned and the sub agents are running it becomes a beautiful workflow that functions entirely without your input. we are currently moving through the editors picks and the trending indicators one by one because i want to have a database of every single strategy on the platform. being a data dog means you never stop searching for that edge and you never settle for a strategy that just looks okay on a single chart. you have to demand excellence from your code because the market will not give you a single inch of mercy if you are lazy with your research. the ultimate goal is to have fully automated systems trading for you so you can focus on scaling rather than staring at a screen for ten hours a day. i am already up to over eighty backtests in this single session and i plan on hitting hundreds more by the end of the week. once you realize that you can crack the code of any indicator you see on the internet you will never look at a chart the same way again. this is the power of using agents to bridge the gap between a raw idea and a finished trading bot that actually works in the real world. i am done with getting liquidated and i am done with the stress of over trading because the code handles everything with cold precision. the path to success is paved with data and if you are not willing to automate your process you are just waiting for your next liquidation to happen

Moon Dev

26,234 просмотров • 5 месяцев назад

a 22-year-old who never filed taxes just got flagged by the IRS not for the $330K in polymarket bot profit but for 12,000 micro-transactions that looked like structuring 38 days of trading and he triggered the same alerts drug dealers do kid built a bot that trades 5-minute crypto resolution markets on polymarket - eth up or down, sol up or down, new scheduled 5-minute ETH/SOL up/down markets resolving via Chainlink data he didn't even know what structuring was the bot was placing mass volume to capture edge across dozens of active micro-markets and every single trade settled through USDC on-chain every 5 minutes the bot runs the same loop: → pulls live order books across dozens of active micro-markets → estimates fair value using Claude Sonnet 4.6 API inference → detects mispricing above 6% and sizes via kelly criterion → fires the trade, collects payout, rolls into the next market → repeats 288+ times per day without sleeping in 38 days it executed 12,247 transactions at an average size of $27 the problem is that pattern - thousands of small, rapid, sequential transactions flowing through crypto rails - is exactly what the bank secrecy act was written to catch under 31 USC 5324 that's called structuring and it carries civil penalties up to ~$400K or twice the transaction amount per violation, criminal up to 5-10 years and $250K-$500K in fines the bot doesn't know what the IRS is it just knew the expected value math worked: 65% win rate on binary contracts means +$0.10 per dollar risked, compounded across 12,000 trades that's $330K in pure edge his entire infra was a mac mini and a $4.50/month VPS with no accountant, no LLC, no tax software the IRS didn't find him through some sophisticated investigation - his bank's automated AML system flagged the deposit pattern and filed a suspicious activity report before he even knew there was a problem $330K in profit sitting in a wallet and the kid googled "do i need to pay taxes on polymarket" for the first time last tuesday the bot opened 6 new positions while he was on hold with a CPA his trading algorithm is mass accurate and his compliance strategy is mass nonexistent - and somewhere right now there are 50 more kids running the same bot who haven't been flagged yet
1:33

a 22-year-old who never filed taxes just got flagged by the IRS not for the $330K in polymarket bot profit but for 12,000 micro-transactions that looked like structuring 38 days of trading and he triggered the same alerts drug dealers do kid built a bot that trades 5-minute crypto resolution markets on polymarket - eth up or down, sol up or down, new scheduled 5-minute ETH/SOL up/down markets resolving via Chainlink data he didn't even know what structuring was the bot was placing mass volume to capture edge across dozens of active micro-markets and every single trade settled through USDC on-chain every 5 minutes the bot runs the same loop: → pulls live order books across dozens of active micro-markets → estimates fair value using Claude Sonnet 4.6 API inference → detects mispricing above 6% and sizes via kelly criterion → fires the trade, collects payout, rolls into the next market → repeats 288+ times per day without sleeping in 38 days it executed 12,247 transactions at an average size of $27 the problem is that pattern - thousands of small, rapid, sequential transactions flowing through crypto rails - is exactly what the bank secrecy act was written to catch under 31 USC 5324 that's called structuring and it carries civil penalties up to ~$400K or twice the transaction amount per violation, criminal up to 5-10 years and $250K-$500K in fines the bot doesn't know what the IRS is it just knew the expected value math worked: 65% win rate on binary contracts means +$0.10 per dollar risked, compounded across 12,000 trades that's $330K in pure edge his entire infra was a mac mini and a $4.50/month VPS with no accountant, no LLC, no tax software the IRS didn't find him through some sophisticated investigation - his bank's automated AML system flagged the deposit pattern and filed a suspicious activity report before he even knew there was a problem $330K in profit sitting in a wallet and the kid googled "do i need to pay taxes on polymarket" for the first time last tuesday the bot opened 6 new positions while he was on hold with a CPA his trading algorithm is mass accurate and his compliance strategy is mass nonexistent - and somewhere right now there are 50 more kids running the same bot who haven't been flagged yet

Argona

150,141 просмотров • 4 месяцев назад

SynkSwap Is About to Redefine Rewarded Swapping Since day one, Synk has been built around empowering users—never for glory or profit. Now, SynkSwap takes that promise further with the Synk Wheel, our reward engine designed to give back to every person who swaps. Here’s the secret: Every time you execute a swap, you immediately earn one ticket, which grants you a spin on the Synk Wheel—where prizes range from $10 up to $100,000. For the initial launch, we’re supplying the first $100,000 in prize capital; this is pre-funded by Synk, not pulled from development or treasury funds. After that, swap fees will keep the wheel spinning and the prizes coming, all through our own infrastructure. Why it matters: Most protocols funnel swap fees into development budgets or outside interests. We’re different. We believe that when you help grow SynkSwap, you deserve a real chance to win. It’s not a gimmick; it’s the core of our economic model. Our audited backend and infrastructure ensure fairness and transparency. Plus, you’ll be able to watch your ticket count grow in real time—completely anonymously—as you trade. What’s next: I’m a one-person development team. Every line of code, every server tweak, and every feature update comes from my keyboard. Yes, Synk is built solo—but it’s fueled by the trust and feedback of our entire community. Over the past weeks, I’ve finalized the Wheel’s integration, stress-tested the trade flows, and optimized our routing infrastructure to guarantee market-leading rates. Now, we’re ready to move into the launch phase. What to expect: • Final tests and infrastructure checks to ensure seamless operations when the Wheel goes live. • A detailed launch announcement next week—you’ll learn exactly how to earn tickets, spin the wheel, and claim prizes. • Full visibility into the prize pool and fee allocation process, so you understand how SynkSwap sustains rewards long term. We do this for the legacy of DOC K. We do this for the people. SynkSwap is more than a swap platform; it’s a new chapter in Synk DEOS’s history—an entire page in the story of decentralized finance—where each swap brings you closer to potentially life-changing rewards. Stay tuned—this is the beginning of something big. Get your tickets ready, because you’re about to experience swapping in a way no one else offers.
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SynkSwap Is About to Redefine Rewarded Swapping Since day one, Synk has been built around empowering users—never for glory or profit. Now, SynkSwap takes that promise further with the Synk Wheel, our reward engine designed to give back to every person who swaps. Here’s the secret: Every time you execute a swap, you immediately earn one ticket, which grants you a spin on the Synk Wheel—where prizes range from $10 up to $100,000. For the initial launch, we’re supplying the first $100,000 in prize capital; this is pre-funded by Synk, not pulled from development or treasury funds. After that, swap fees will keep the wheel spinning and the prizes coming, all through our own infrastructure. Why it matters: Most protocols funnel swap fees into development budgets or outside interests. We’re different. We believe that when you help grow SynkSwap, you deserve a real chance to win. It’s not a gimmick; it’s the core of our economic model. Our audited backend and infrastructure ensure fairness and transparency. Plus, you’ll be able to watch your ticket count grow in real time—completely anonymously—as you trade. What’s next: I’m a one-person development team. Every line of code, every server tweak, and every feature update comes from my keyboard. Yes, Synk is built solo—but it’s fueled by the trust and feedback of our entire community. Over the past weeks, I’ve finalized the Wheel’s integration, stress-tested the trade flows, and optimized our routing infrastructure to guarantee market-leading rates. Now, we’re ready to move into the launch phase. What to expect: • Final tests and infrastructure checks to ensure seamless operations when the Wheel goes live. • A detailed launch announcement next week—you’ll learn exactly how to earn tickets, spin the wheel, and claim prizes. • Full visibility into the prize pool and fee allocation process, so you understand how SynkSwap sustains rewards long term. We do this for the legacy of DOC K. We do this for the people. SynkSwap is more than a swap platform; it’s a new chapter in Synk DEOS’s history—an entire page in the story of decentralized finance—where each swap brings you closer to potentially life-changing rewards. Stay tuned—this is the beginning of something big. Get your tickets ready, because you’re about to experience swapping in a way no one else offers.

Kard

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