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OpenClaw setup made me $23,472 Literally overnight my $100 turned into $2,411 Average bot win rate 71% Copytrade: Here is the full strategy: The system builds automated workflows for trading by turning domain expertise into structured skills that activate automatically when specific market conditions appear Skill architecture Each skill...

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winkle.

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44,158 просмотров • 3 месяцев назад •via X (Twitter)

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Anthropic dropped 33 pages for Claude trading bots Last night I decided to try writing one and it worked out for me In 10 hours this script made me $561 The bot has a win rate of about 71% Wallet: Copytrade: Here is the full strategy: The system builds automated workflows for Claude by packaging domain expertise into structured skills that activate automatically when relevant tasks appear Skill architecture Each skill is structured as a modular package containing instructions, scripts, and reference materials This allows Claude to apply specialized workflows without requiring the user to repeat instructions in every conversation Progressive context loading Skills follow a three-layer architecture where only minimal metadata is loaded initially Full instructions and supporting files are accessed only when needed, reducing token usage while maintaining specialized expertise Trigger detection Skills activate when the user request matches defined trigger phrases or workflows This ensures the correct workflow loads automatically without requiring manual prompting Workflow execution Once activated, the skill executes a predefined multi-step process These workflows can include data analysis, document generation, automation scripts, or coordination across external tools Consistency and reliability Because workflows are encoded directly in the skill instructions, Claude performs tasks using consistent methodology rather than ad-hoc prompting Testing and iteration Skills are continuously refined through triggering tests, functional validation, and performance comparisons to ensure reliable execution Automation edge Instead of solving tasks from scratch each time, the system repeatedly applies optimized workflows Over time this dramatically reduces prompt complexity, improves output consistency, and scales productivity across thousands of tasks
0:11

Anthropic dropped 33 pages for Claude trading bots Last night I decided to try writing one and it worked out for me In 10 hours this script made me $561 The bot has a win rate of about 71% Wallet: Copytrade: Here is the full strategy: The system builds automated workflows for Claude by packaging domain expertise into structured skills that activate automatically when relevant tasks appear Skill architecture Each skill is structured as a modular package containing instructions, scripts, and reference materials This allows Claude to apply specialized workflows without requiring the user to repeat instructions in every conversation Progressive context loading Skills follow a three-layer architecture where only minimal metadata is loaded initially Full instructions and supporting files are accessed only when needed, reducing token usage while maintaining specialized expertise Trigger detection Skills activate when the user request matches defined trigger phrases or workflows This ensures the correct workflow loads automatically without requiring manual prompting Workflow execution Once activated, the skill executes a predefined multi-step process These workflows can include data analysis, document generation, automation scripts, or coordination across external tools Consistency and reliability Because workflows are encoded directly in the skill instructions, Claude performs tasks using consistent methodology rather than ad-hoc prompting Testing and iteration Skills are continuously refined through triggering tests, functional validation, and performance comparisons to ensure reliable execution Automation edge Instead of solving tasks from scratch each time, the system repeatedly applies optimized workflows Over time this dramatically reduces prompt complexity, improves output consistency, and scales productivity across thousands of tasks

winkle.

334,453 просмотров • 4 месяцев назад

Claude can make your own money printer That is exactly what happened to me I wrote my own script It took me 6 hours On the very first night the bot made $2,705 profit Copytrade: Wallet: Here is the full strategy: The system builds automated workflows for Claude by packaging domain expertise into structured skills that activate automatically when relevant tasks appear Skill architecture Each skill is structured as a modular package containing instructions scripts and reference materials This allows Claude to apply specialized workflows without requiring the user to repeat instructions in every conversation Progressive context loading Skills follow a three layer architecture where only minimal metadata is loaded initially Full instructions and supporting files are accessed only when needed reducing token usage while maintaining specialized expertise Trigger detection Skills activate when the user request matches defined trigger phrases or workflows This ensures the correct workflow loads automatically without requiring manual prompting Workflow execution Once activated the skill executes a predefined multi step process These workflows can include data analysis document generation automation scripts or coordination across external tools Consistency and reliability Because workflows are encoded directly in the skill instructions Claude performs tasks using consistent methodology rather than ad hoc prompting Testing and iteration Skills are continuously refined through triggering tests functional validation and performance comparisons to ensure reliable execution Automation edge Instead of solving tasks from scratch each time the system repeatedly applies optimized workflows Over time this dramatically reduces prompt complexity improves output consistency and scales productivity across thousands of tasks
0:11

Claude can make your own money printer That is exactly what happened to me I wrote my own script It took me 6 hours On the very first night the bot made $2,705 profit Copytrade: Wallet: Here is the full strategy: The system builds automated workflows for Claude by packaging domain expertise into structured skills that activate automatically when relevant tasks appear Skill architecture Each skill is structured as a modular package containing instructions scripts and reference materials This allows Claude to apply specialized workflows without requiring the user to repeat instructions in every conversation Progressive context loading Skills follow a three layer architecture where only minimal metadata is loaded initially Full instructions and supporting files are accessed only when needed reducing token usage while maintaining specialized expertise Trigger detection Skills activate when the user request matches defined trigger phrases or workflows This ensures the correct workflow loads automatically without requiring manual prompting Workflow execution Once activated the skill executes a predefined multi step process These workflows can include data analysis document generation automation scripts or coordination across external tools Consistency and reliability Because workflows are encoded directly in the skill instructions Claude performs tasks using consistent methodology rather than ad hoc prompting Testing and iteration Skills are continuously refined through triggering tests functional validation and performance comparisons to ensure reliable execution Automation edge Instead of solving tasks from scratch each time the system repeatedly applies optimized workflows Over time this dramatically reduces prompt complexity improves output consistency and scales productivity across thousands of tasks

winkle.

53,951 просмотров • 3 месяцев назад

He showed me the ClawdBot script that made him $900K Using only Clawd he built a 5 minute BTC market script He generated $951K in profit in just one month 5 minute BTC markets + ClawdBot = all you need Copytrade: Here is the full strategy: 5 Minute BTC and ETH Micro Arbitrage The system trades short 5 minute Bitcoin and Ethereum contracts In fast markets temporary mispricings occur when YES + NO drops below $1 The bot scans in real time and instantly captures the spread as soon as it appears Speed Over Emotion When volatility hits and manual traders hesitate the system reacts automatically Orders are triggered without delay hesitation or emotional bias By the time most traders process what happened the opportunity window has already closed Automation Compounds the Edge Instead of chasing large wins the strategy captures small spreads repeatedly High frequency execution allows the bot to operate continuously stacking micro advantages into meaningful returns over time All that’s left is to keep refining the code deploy at scale and let it run
0:10

He showed me the ClawdBot script that made him $900K Using only Clawd he built a 5 minute BTC market script He generated $951K in profit in just one month 5 minute BTC markets + ClawdBot = all you need Copytrade: Here is the full strategy: 5 Minute BTC and ETH Micro Arbitrage The system trades short 5 minute Bitcoin and Ethereum contracts In fast markets temporary mispricings occur when YES + NO drops below $1 The bot scans in real time and instantly captures the spread as soon as it appears Speed Over Emotion When volatility hits and manual traders hesitate the system reacts automatically Orders are triggered without delay hesitation or emotional bias By the time most traders process what happened the opportunity window has already closed Automation Compounds the Edge Instead of chasing large wins the strategy captures small spreads repeatedly High frequency execution allows the bot to operate continuously stacking micro advantages into meaningful returns over time All that’s left is to keep refining the code deploy at scale and let it run

winkle.

32,155 просмотров • 4 месяцев назад

My Claude bot finished first night profit $2,314 I built the script in 4 hours and it was worth it Average winrate 70% This is not clickbait it is a story about a 5 minute BTC script My strategy + Claude = all you need Wallet: Copytrade: Here is the full strategy: 5 Minute BTC and ETH Micro Arbitrage The system trades short 5 minute Bitcoin and Ethereum contracts In fast markets temporary mispricings appear when YES + NO drops below one dollar The bot scans in real time and captures the spread the moment it appears Speed over emotion When volatility spikes and manual traders hesitate the system reacts automatically Orders execute instantly without delay hesitation or emotional bias By the time most traders understand what happened the opportunity window is already gone Automation compounds the edge Instead of chasing large wins the strategy captures small spreads repeatedly High frequency execution allows the bot to run continuously stacking micro advantages into meaningful returns over time All that is left is refining the code deploying at scale and letting it run
0:15

My Claude bot finished first night profit $2,314 I built the script in 4 hours and it was worth it Average winrate 70% This is not clickbait it is a story about a 5 minute BTC script My strategy + Claude = all you need Wallet: Copytrade: Here is the full strategy: 5 Minute BTC and ETH Micro Arbitrage The system trades short 5 minute Bitcoin and Ethereum contracts In fast markets temporary mispricings appear when YES + NO drops below one dollar The bot scans in real time and captures the spread the moment it appears Speed over emotion When volatility spikes and manual traders hesitate the system reacts automatically Orders execute instantly without delay hesitation or emotional bias By the time most traders understand what happened the opportunity window is already gone Automation compounds the edge Instead of chasing large wins the strategy captures small spreads repeatedly High frequency execution allows the bot to run continuously stacking micro advantages into meaningful returns over time All that is left is refining the code deploying at scale and letting it run

winkle.

171,215 просмотров • 4 месяцев назад

My 5 minute BTC script was just completed I spent one full night building it The bot turned $100 into $1,643 overnight This isn’t clickbait it’s my personal journey building a 5 minute BTC script My strategy + Claude = all you need Copytrade: Here is the full strategy 5 Minute BTC & ETH Micro Arbitrage The system trades short 5 minute Bitcoin and Ethereum contracts In fast markets temporary mispricings appear when YES + NO drops below $1 The bot scans in real time and instantly captures the spread as soon as it appears Speed over emotion When volatility spikes and manual traders hesitate the system reacts automatically Orders are triggered without delay hesitation or emotional bias By the time most traders understand what happened the opportunity window is already gone Automation compounds the edge Instead of chasing big wins the strategy captures small spreads repeatedly High frequency execution allows the bot to run continuously stacking micro advantages into meaningful returns over time All that’s left is to keep refining the code deploy at scale and let it run
0:15

My 5 minute BTC script was just completed I spent one full night building it The bot turned $100 into $1,643 overnight This isn’t clickbait it’s my personal journey building a 5 minute BTC script My strategy + Claude = all you need Copytrade: Here is the full strategy 5 Minute BTC & ETH Micro Arbitrage The system trades short 5 minute Bitcoin and Ethereum contracts In fast markets temporary mispricings appear when YES + NO drops below $1 The bot scans in real time and instantly captures the spread as soon as it appears Speed over emotion When volatility spikes and manual traders hesitate the system reacts automatically Orders are triggered without delay hesitation or emotional bias By the time most traders understand what happened the opportunity window is already gone Automation compounds the edge Instead of chasing big wins the strategy captures small spreads repeatedly High frequency execution allows the bot to run continuously stacking micro advantages into meaningful returns over time All that’s left is to keep refining the code deploy at scale and let it run

winkle.

21,832 просмотров • 4 месяцев назад

🚨 BREAKING… $1.1M in 26 days using OpenClaw on Polymarket This is a REAL framework generating REAL results. He began with a relatively small base, linked OpenClaw for execution, and expanded it to approximately ~$1.1M in returns Simply a developer integrating Moltbot (OpenClaw) directly into Polymarket Profile - Copytrade - After analyzing the setup, I was honestly impressed The entire process runs fully automated Execution follows predefined rules, zero human intervention FULL strategy overview: 1. 5 & 15 minute BTC & ETH micro-arbitrage The system focuses on ultra short-term Bitcoin and Ethereum contracts within 5-minute windows. In these rapid cycles, inefficiencies surface when YES and NO combined fall below $1. With Moltbot (OpenClaw) wired directly into Polymarket, those gaps are captured instantly - no forecasting, no directional bets, no bias 2. Speed instead of hesitation When volatility increases and manual traders freeze, the system acts. Orders are placed automatically, without delay, emotion, or second thoughts. By the time others respond, the opportunity is already gone 3. Automation compounds the advantage Each round captures tight spreads, not massive individual wins. But relentless, high-frequency repetition keeps the engine running nonstop no fatigue, no slowdown - stacking small edges into significant results Scale is the edge 23,784 trades. Small on their own. Together, they accumulated into ~$1.1M in profit
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🚨 BREAKING… $1.1M in 26 days using OpenClaw on Polymarket This is a REAL framework generating REAL results. He began with a relatively small base, linked OpenClaw for execution, and expanded it to approximately ~$1.1M in returns Simply a developer integrating Moltbot (OpenClaw) directly into Polymarket Profile - Copytrade - After analyzing the setup, I was honestly impressed The entire process runs fully automated Execution follows predefined rules, zero human intervention FULL strategy overview: 1. 5 & 15 minute BTC & ETH micro-arbitrage The system focuses on ultra short-term Bitcoin and Ethereum contracts within 5-minute windows. In these rapid cycles, inefficiencies surface when YES and NO combined fall below $1. With Moltbot (OpenClaw) wired directly into Polymarket, those gaps are captured instantly - no forecasting, no directional bets, no bias 2. Speed instead of hesitation When volatility increases and manual traders freeze, the system acts. Orders are placed automatically, without delay, emotion, or second thoughts. By the time others respond, the opportunity is already gone 3. Automation compounds the advantage Each round captures tight spreads, not massive individual wins. But relentless, high-frequency repetition keeps the engine running nonstop no fatigue, no slowdown - stacking small edges into significant results Scale is the edge 23,784 trades. Small on their own. Together, they accumulated into ~$1.1M in profit

Shelpid.WI3M

186,875 просмотров • 4 месяцев назад

Just finished building my 5 minute BTC script It took me exactly one night and the result was worth it The bot turned $50 into $907 overnight This isn’t clickbait It’s a story about a 5-minute BTC script My strategy + Claude Opus 4.6 = all you need Wallet: Copytrade: Here is the full strategy: 5 Minute BTC and ETH Micro Arbitrage The system trades short 5 minute Bitcoin and Ethereum contracts In these fast markets temporary mispricings appear when YES plus NO drops below 1 dollar The bot scans in real time and instantly captures the spread as soon as it shows up Speed over emotion When volatility spikes and manual traders hesitate the system reacts automatically Orders trigger without delay hesitation or emotional bias By the time most traders understand what happened the opportunity window is already gone Automation compounds the edge Instead of chasing big wins the strategy captures small spreads repeatedly High frequency execution allows the bot to run continuously stacking micro advantages into meaningful returns over time All that is left is to keep refining the code deploy at scale and let it run
0:16

Just finished building my 5 minute BTC script It took me exactly one night and the result was worth it The bot turned $50 into $907 overnight This isn’t clickbait It’s a story about a 5-minute BTC script My strategy + Claude Opus 4.6 = all you need Wallet: Copytrade: Here is the full strategy: 5 Minute BTC and ETH Micro Arbitrage The system trades short 5 minute Bitcoin and Ethereum contracts In these fast markets temporary mispricings appear when YES plus NO drops below 1 dollar The bot scans in real time and instantly captures the spread as soon as it shows up Speed over emotion When volatility spikes and manual traders hesitate the system reacts automatically Orders trigger without delay hesitation or emotional bias By the time most traders understand what happened the opportunity window is already gone Automation compounds the edge Instead of chasing big wins the strategy captures small spreads repeatedly High frequency execution allows the bot to run continuously stacking micro advantages into meaningful returns over time All that is left is to keep refining the code deploy at scale and let it run

winkle.

85,829 просмотров • 4 месяцев назад

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

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

Shelpid.WI3M

225,724 просмотров • 4 месяцев назад

The ChainGPT AI skill for Claude Code is one of the most complete Web3-AI dev environment on the market. Let me prove it. Open Claude Code with the installed skill, and you have direct access to: • Built-in wallets across 33+ chains • DEX trading, perps, and Hyperliquid execution • Smart contract generation and auditing • NFT generation across 22 chains • Real-time crypto news API • Fine-tuned crypto LLM with live on-chain data Every part of the Web3 stack, one prompt away. Here's what that looks like in practice. I built a real-time on-chain whale tracker in a single afternoon. It's called Whale Watch. → Pulls live swap data from Ethereum DEX pools → Filters every trade over $100K → Runs each whale through the ChainGPT LLM for a trader-grade live analysis → Routes the user into 1inch with the token pair pre-loaded if they want to follow the trade Real data. Real AI. Real action layer. The skill wrote the server. It hit the right APIs. It generated the UI. It debugged itself when something broke. The only thing I supplied was the idea and the polish. Open Claude Code. Ship something with ChainGPT AI this weekend! /plugin install ChainGPT-org/chaingpt-claude-skill
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The ChainGPT AI skill for Claude Code is one of the most complete Web3-AI dev environment on the market. Let me prove it. Open Claude Code with the installed skill, and you have direct access to: • Built-in wallets across 33+ chains • DEX trading, perps, and Hyperliquid execution • Smart contract generation and auditing • NFT generation across 22 chains • Real-time crypto news API • Fine-tuned crypto LLM with live on-chain data Every part of the Web3 stack, one prompt away. Here's what that looks like in practice. I built a real-time on-chain whale tracker in a single afternoon. It's called Whale Watch. → Pulls live swap data from Ethereum DEX pools → Filters every trade over $100K → Runs each whale through the ChainGPT LLM for a trader-grade live analysis → Routes the user into 1inch with the token pair pre-loaded if they want to follow the trade Real data. Real AI. Real action layer. The skill wrote the server. It hit the right APIs. It generated the UI. It debugged itself when something broke. The only thing I supplied was the idea and the polish. Open Claude Code. Ship something with ChainGPT AI this weekend! /plugin install ChainGPT-org/chaingpt-claude-skill

ChainGPT

25,853 просмотров • 1 месяц назад

CA: 0x172ae9e9b46770a70f479404d76e2f6561507011ef77a247fe3f58e7a5840a0d::manny::MANNY Your smart, hands-free edge tool in the crypto market. This powerful automated bot is designed to buy low and sell high with precision. It scans hundreds of coins in real-time, waiting for the right indicators—trend strength, volume spikes, price momentum, and bullish patterns—before entering a trade. Once in, it manages risk with dynamic stop-loss and take-profit levels, so your capital is always protected. Every trade is backed by a multi-layer confluence strategy, ensuring only high-confidence setups are executed. ✅ Advanced entry logic ✅ Fully automated buy/sell execution ✅ Built-in profit protection and cooldown filters ✅ Real-time alerts (Telegram/Twitter ready) ✅ JSON-based state memory for continuity ✅ Minimal setup, maximum performance ✅ Excludes low-quality coins automatically (e.g., BTC/ETH filters optional) ✅ Plug-and-play friendly — run it locally or integrate it into your system. ✅ Clean, professional trade alerts with price and PnL details ✅ Recovers automatically from connection issues or downtime Whether you’re a pro or just getting started, this bot helps you stay ahead of the market—24/7, emotion-free with pure mathematics. This bot has been in development for the last 6 months. I, Chronos, the developer behind it, have been testing for a while for the best configuration for a trading bot. I believe I have something good going on here. The bot automatically posts all the trades via IFTTT and X integration to its X account. Everything is automated. So how can people rent it, and how will it bring value to the project? Soon, the bot can be rented out via a cloud server. A customer must buy 30 USD worth of Memecoin_MANNY token (CA:0x172ae9e9b46770a70f479404d76e2f6561507011ef77a247fe3f58e7a5840a0d::manny::MANNY). After buying it and depositing it into a special wallet, he will be granted access to the bot. . The bot runs only on the backend — users interact with it via an interface (web app, Telegram bot, or API). A web dashboard and Telegram bot interface will be created. This lets users Start/stop their bot session See trade logs or results. Connect their API keys securely. Get alerts and updates The idea of all this is to offer a service but also bring value to the project. More bots will be developed. This is only the beginning. Cheers Chronos #python #memecoin_manny #spot #trading #bitcoin #eth #Binance #bybit #memecoin #VALHALLA
0:19

CA: 0x172ae9e9b46770a70f479404d76e2f6561507011ef77a247fe3f58e7a5840a0d::manny::MANNY Your smart, hands-free edge tool in the crypto market. This powerful automated bot is designed to buy low and sell high with precision. It scans hundreds of coins in real-time, waiting for the right indicators—trend strength, volume spikes, price momentum, and bullish patterns—before entering a trade. Once in, it manages risk with dynamic stop-loss and take-profit levels, so your capital is always protected. Every trade is backed by a multi-layer confluence strategy, ensuring only high-confidence setups are executed. ✅ Advanced entry logic ✅ Fully automated buy/sell execution ✅ Built-in profit protection and cooldown filters ✅ Real-time alerts (Telegram/Twitter ready) ✅ JSON-based state memory for continuity ✅ Minimal setup, maximum performance ✅ Excludes low-quality coins automatically (e.g., BTC/ETH filters optional) ✅ Plug-and-play friendly — run it locally or integrate it into your system. ✅ Clean, professional trade alerts with price and PnL details ✅ Recovers automatically from connection issues or downtime Whether you’re a pro or just getting started, this bot helps you stay ahead of the market—24/7, emotion-free with pure mathematics. This bot has been in development for the last 6 months. I, Chronos, the developer behind it, have been testing for a while for the best configuration for a trading bot. I believe I have something good going on here. The bot automatically posts all the trades via IFTTT and X integration to its X account. Everything is automated. So how can people rent it, and how will it bring value to the project? Soon, the bot can be rented out via a cloud server. A customer must buy 30 USD worth of Memecoin_MANNY token (CA:0x172ae9e9b46770a70f479404d76e2f6561507011ef77a247fe3f58e7a5840a0d::manny::MANNY). After buying it and depositing it into a special wallet, he will be granted access to the bot. . The bot runs only on the backend — users interact with it via an interface (web app, Telegram bot, or API). A web dashboard and Telegram bot interface will be created. This lets users Start/stop their bot session See trade logs or results. Connect their API keys securely. Get alerts and updates The idea of all this is to offer a service but also bring value to the project. More bots will be developed. This is only the beginning. Cheers Chronos #python #memecoin_manny #spot #trading #bitcoin #eth #Binance #bybit #memecoin #VALHALLA

Ex Machina

24,488 просмотров • 1 год назад

🚨 BREAKING… $100K profit in one month with Clawdbot and Polymarket, code did the work This is a REAL setup with REAL outcomes. Relevant for ANYONE trading on Polymarket. He took a small initial position, let Clawdbot handle operations, and grew it into a ~$100K outcome No secret connections No high-profile backing Just a dev who connected Moltbot (Clawdbot) straight to Polymarket Profile → Copytrade → After reviewing the system, I was genuinely surprised No hype-driven plays No subjective calls Everything runs without a human in the loop Execution runs on its own, no manual layer FULL strategy overview: 1. 15-minute BTC & ETH micro-arbitrage The system operates on short-window Bitcoin and Ethereum markets using 15-minute intervals. In these fast-moving contracts, brief mispricings appear when YES and NO combined dip below $1. With Moltbot (Clawdbot) wired directly into Polymarket, those gaps are seized instantly - no forecasting, no directional bets, no bias 2. Execution beats reaction When volatility surges and traders hesitate, the system doesn’t. Orders are placed mechanically, with no pauses, no emotional friction, and no execution lag. By the time humans notice the move, the edge has already closed 3. Autonomy enables scale Each cycle captures pennies, not big wins. But uninterrupted operation allows the process to repeat relentlessly, at high frequency, without burnout or slowdown compounding small edges into meaningful results Scale is the edge 5,978 executions. Each one trivial in isolation. Taken together, they snowballed into just under $100K in profit The takeaway In my view, a low-key bot arms race is already underway on Polymarket Humans debate entries Systems capitalize on mechanics And while structural inefficiencies remain, autonomous setups will continue to extract value-quietly, relentlessly I track this space closely. FOLLOW if you want signal, not noise.
0:16

🚨 BREAKING… $100K profit in one month with Clawdbot and Polymarket, code did the work This is a REAL setup with REAL outcomes. Relevant for ANYONE trading on Polymarket. He took a small initial position, let Clawdbot handle operations, and grew it into a ~$100K outcome No secret connections No high-profile backing Just a dev who connected Moltbot (Clawdbot) straight to Polymarket Profile → Copytrade → After reviewing the system, I was genuinely surprised No hype-driven plays No subjective calls Everything runs without a human in the loop Execution runs on its own, no manual layer FULL strategy overview: 1. 15-minute BTC & ETH micro-arbitrage The system operates on short-window Bitcoin and Ethereum markets using 15-minute intervals. In these fast-moving contracts, brief mispricings appear when YES and NO combined dip below $1. With Moltbot (Clawdbot) wired directly into Polymarket, those gaps are seized instantly - no forecasting, no directional bets, no bias 2. Execution beats reaction When volatility surges and traders hesitate, the system doesn’t. Orders are placed mechanically, with no pauses, no emotional friction, and no execution lag. By the time humans notice the move, the edge has already closed 3. Autonomy enables scale Each cycle captures pennies, not big wins. But uninterrupted operation allows the process to repeat relentlessly, at high frequency, without burnout or slowdown compounding small edges into meaningful results Scale is the edge 5,978 executions. Each one trivial in isolation. Taken together, they snowballed into just under $100K in profit The takeaway In my view, a low-key bot arms race is already underway on Polymarket Humans debate entries Systems capitalize on mechanics And while structural inefficiencies remain, autonomous setups will continue to extract value-quietly, relentlessly I track this space closely. FOLLOW if you want signal, not noise.

Shelpid.WI3M

485,943 просмотров • 5 месяцев назад

Webhooks are LIVE on KEPLER 🛰️ Get real-time HTTP notifications directly from the blockchain. Say goodbye to constantly polling for data and managing heavy infrastructure. Setting up a webhook takes just a few clicks. Perfect for Developers & No-Code Builders • You can easily route webhooks directly into OpenClaw or platforms like Make or n8n. Build powerful, automated workflows in minutes without writing a single line of code. • For the classical builders, easily integrate real-time events into your existing Web2 backend using standard HTTP POST requests. Seamlessly bridge Web2 and Web3 to power custom indexing bots, trading algorithms, or dApp backends using our lightweight JSON payloads. Precision Filtering Cut through the noise by triggering webhooks only when your specific address, identifier, or topic conditions are met. Reliable Delivery If your endpoint or automation flow hiccups, our system automatically retries the delivery up to 4 times so you never miss an event. Cryptographic Security Every request includes an Ed25519 signature in the header, letting you natively verify that the payload is authentic and hasn't been tampered with.
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Webhooks are LIVE on KEPLER 🛰️ Get real-time HTTP notifications directly from the blockchain. Say goodbye to constantly polling for data and managing heavy infrastructure. Setting up a webhook takes just a few clicks. Perfect for Developers & No-Code Builders • You can easily route webhooks directly into OpenClaw or platforms like Make or n8n. Build powerful, automated workflows in minutes without writing a single line of code. • For the classical builders, easily integrate real-time events into your existing Web2 backend using standard HTTP POST requests. Seamlessly bridge Web2 and Web3 to power custom indexing bots, trading algorithms, or dApp backends using our lightweight JSON payloads. Precision Filtering Cut through the noise by triggering webhooks only when your specific address, identifier, or topic conditions are met. Reliable Delivery If your endpoint or automation flow hiccups, our system automatically retries the delivery up to 4 times so you never miss an event. Cryptographic Security Every request includes an Ed25519 signature in the header, letting you natively verify that the payload is authentic and hasn't been tampered with.

Project X 🧬

11,024 просмотров • 4 месяцев назад

This trader reportedly generated $4M in profit trading on Polymarket with ClawdBot Starting with just $1,000, the script scaled up to millions through automated trading If you trade on Polymarket, be sure to read this to simplify your trading with ClawdBot Without any insider connections or 10 years of programming experience, this trader wrote the script and connected Moltbot (Clawdbot) directly to Polymarket Profile → Copy trading → After reviewing the code, it was surprising how simple the core idea looked The bot runs fully autonomously, without constant human involvement Here is the strategy 1. 15-minute BTC & ETH micro-arbitrage The strategy focuses on very short-term Bitcoin and Ethereum markets with 15-minute contracts. In these rapid markets, brief pricing gaps often appear where the combined cost of YES and NO is below $1. A bot connected directly to Polymarket detects and exploits these gaps instantly, it doesn’t try to predict direction or analyze trends, it simply reacts to pricing inefficiencies. 2. Speed over hesitation During volatile moments, human traders often pause or second-guess. An automated system doesn’t. Orders are executed automatically: no hesitation, no emotional bias, no lag in response. By the time a person evaluates the situation, the opportunity usually no longer exists. 3. Automation enables scale The gains per trade are tiny, often just cents. But constant, uninterrupted execution allows the system to repeat the same edge thousands of times without fatigue, turning small margins into meaningful totals over time. Scale becomes the real edge Nearly 6,000 trades were executed. Individually they seemed minor. Collectively they resulted in close to $100K in net profit. Conclusion A quiet bot race already seems to be happening on Polymarket While people debate entries and opinions, automated systems profit from mechanics and speed. As long as structural inefficiencies remain in the market, autonomous setups will likely continue extracting value quietly and consistently. I’m watching this space closely Follow if you want signal, not noise
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This trader reportedly generated $4M in profit trading on Polymarket with ClawdBot Starting with just $1,000, the script scaled up to millions through automated trading If you trade on Polymarket, be sure to read this to simplify your trading with ClawdBot Without any insider connections or 10 years of programming experience, this trader wrote the script and connected Moltbot (Clawdbot) directly to Polymarket Profile → Copy trading → After reviewing the code, it was surprising how simple the core idea looked The bot runs fully autonomously, without constant human involvement Here is the strategy 1. 15-minute BTC & ETH micro-arbitrage The strategy focuses on very short-term Bitcoin and Ethereum markets with 15-minute contracts. In these rapid markets, brief pricing gaps often appear where the combined cost of YES and NO is below $1. A bot connected directly to Polymarket detects and exploits these gaps instantly, it doesn’t try to predict direction or analyze trends, it simply reacts to pricing inefficiencies. 2. Speed over hesitation During volatile moments, human traders often pause or second-guess. An automated system doesn’t. Orders are executed automatically: no hesitation, no emotional bias, no lag in response. By the time a person evaluates the situation, the opportunity usually no longer exists. 3. Automation enables scale The gains per trade are tiny, often just cents. But constant, uninterrupted execution allows the system to repeat the same edge thousands of times without fatigue, turning small margins into meaningful totals over time. Scale becomes the real edge Nearly 6,000 trades were executed. Individually they seemed minor. Collectively they resulted in close to $100K in net profit. Conclusion A quiet bot race already seems to be happening on Polymarket While people debate entries and opinions, automated systems profit from mechanics and speed. As long as structural inefficiencies remain in the market, autonomous setups will likely continue extracting value quietly and consistently. I’m watching this space closely Follow if you want signal, not noise

winkle.

36,628 просмотров • 5 месяцев назад

OpenAI's AgentKit will be so insane, build every step of agents on one platform. These visual agent builders make the whole process of iterating and launching agents far more efficient. It sits on top of the Responses API and unifies the tools that were previously scattered across SDKs and custom orchestration. It lets developers create agent workflows visually, connect data sources securely, and measure performance automatically without coding every layer by hand. The core of AgentKit is the Agent Builder, a drag-and-drop canvas where each node represents an action, guardrail, or decision branch. Developers can link these nodes into multi-agent workflows, preview results instantly, and version each setup. It supports inline evaluation so that developers can see how changes affect output before deploying. The Connector Registry is a single admin panel that manages how data and tools connect across the OpenAI ecosystem. It centralizes integrations like Google Drive, SharePoint, Dropbox, and Microsoft Teams. Large organizations can govern access and flow of data between agents securely under one global console. ChatKit provides a ready-to-use chat interface for embedding agents inside apps or websites. It manages streaming, message threads, and model reasoning displays automatically. Developers can skin the interface to match their product without writing custom front-end code. Under the hood, all these blocks use the same execution core that runs agent reasoning through OpenAI’s APIs. Workflows in Agent Builder compile down to structured instructions for the Responses API, which handles model calls, tool use, and context passing. Connector Registry handles authentication and routing for external tools, while Evals and RFT provide feedback loops that improve agents over time. This integration means developers no longer need to handle orchestration logic, model evaluation pipelines, or safety layers separately. Everything runs natively within OpenAI’s control plane with managed security, automatic versioning, and built-in testing. In short, AgentKit standardizes the entire life cycle of an AI agent—from visual design to deployment and performance tuning—inside a single unified system.
0:10

OpenAI's AgentKit will be so insane, build every step of agents on one platform. These visual agent builders make the whole process of iterating and launching agents far more efficient. It sits on top of the Responses API and unifies the tools that were previously scattered across SDKs and custom orchestration. It lets developers create agent workflows visually, connect data sources securely, and measure performance automatically without coding every layer by hand. The core of AgentKit is the Agent Builder, a drag-and-drop canvas where each node represents an action, guardrail, or decision branch. Developers can link these nodes into multi-agent workflows, preview results instantly, and version each setup. It supports inline evaluation so that developers can see how changes affect output before deploying. The Connector Registry is a single admin panel that manages how data and tools connect across the OpenAI ecosystem. It centralizes integrations like Google Drive, SharePoint, Dropbox, and Microsoft Teams. Large organizations can govern access and flow of data between agents securely under one global console. ChatKit provides a ready-to-use chat interface for embedding agents inside apps or websites. It manages streaming, message threads, and model reasoning displays automatically. Developers can skin the interface to match their product without writing custom front-end code. Under the hood, all these blocks use the same execution core that runs agent reasoning through OpenAI’s APIs. Workflows in Agent Builder compile down to structured instructions for the Responses API, which handles model calls, tool use, and context passing. Connector Registry handles authentication and routing for external tools, while Evals and RFT provide feedback loops that improve agents over time. This integration means developers no longer need to handle orchestration logic, model evaluation pipelines, or safety layers separately. Everything runs natively within OpenAI’s control plane with managed security, automatic versioning, and built-in testing. In short, AgentKit standardizes the entire life cycle of an AI agent—from visual design to deployment and performance tuning—inside a single unified system.

Rohan Paul

178,460 просмотров • 9 месяцев назад

“Everyone wants to win — until they realize how many losses it takes.” October has been one of the toughest months for me (and likely for some of you), especially when comparing LoD stops based sizing swing traders vs. % stops based sizing position traders. I’ve had 16 straight losses — but each one was small, contained, and the streak was fully within the expected variance range of a 30% win rate. While it can be challenging for some of us, the key to navigating this, both mentally and emotionally, lies in accepting uncertainty through predefined risk management, where every trade has a clearly defined pain threshold. Your dollar-value tolerance should never trigger emotional reactions or push you off your intended plan. By acknowledging that losses are part of the process, we enter each trade with humility — assuming we may be wrong until proven right. The market must prove and continue to prove the validity of our thesis. Start small, and let your risk grow only as your consistency and performance justify it. I always advocate using a fixed % risk relative to your latest net realized equity. Don’t increase risk just because you’ve had a few good trades — risk should only expand when it’s truly earned from realized profitable performance. Avoid the illusion that everyone wins in trading. The real objective is not just to make gains, but to preserve them. True risk management goes far beyond setting stop losses — it means being proactive enough to cut size when the market proves you wrong. In the end, the trader who manages losses best will always outlast the rest. “The best loser is the long-term winner.” - Phantom of the Pit
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“Everyone wants to win — until they realize how many losses it takes.” October has been one of the toughest months for me (and likely for some of you), especially when comparing LoD stops based sizing swing traders vs. % stops based sizing position traders. I’ve had 16 straight losses — but each one was small, contained, and the streak was fully within the expected variance range of a 30% win rate. While it can be challenging for some of us, the key to navigating this, both mentally and emotionally, lies in accepting uncertainty through predefined risk management, where every trade has a clearly defined pain threshold. Your dollar-value tolerance should never trigger emotional reactions or push you off your intended plan. By acknowledging that losses are part of the process, we enter each trade with humility — assuming we may be wrong until proven right. The market must prove and continue to prove the validity of our thesis. Start small, and let your risk grow only as your consistency and performance justify it. I always advocate using a fixed % risk relative to your latest net realized equity. Don’t increase risk just because you’ve had a few good trades — risk should only expand when it’s truly earned from realized profitable performance. Avoid the illusion that everyone wins in trading. The real objective is not just to make gains, but to preserve them. True risk management goes far beyond setting stop losses — it means being proactive enough to cut size when the market proves you wrong. In the end, the trader who manages losses best will always outlast the rest. “The best loser is the long-term winner.” - Phantom of the Pit

Jeff Sun, CFTe

109,311 просмотров • 8 месяцев назад

🪴 GT Protocol Monthly Recap: May 2026 May focused on launching advanced trading infrastructure, introducing AI risk-management tools, and shipping major platform upgrades. 🚀 Hyperliquid Vaults Live Run multiple algorithmic strategies on a single Hyperliquid Vault inside GT App. Enjoy automated execution, auto-rebalancing, and protocol-level security. You can find Vault trading on the Hyperliquid exchange account connection page in the Trade on Vault section. Try it in GT App 👉 🤖 AI Hedge Fund Experiment Live An experimental AI Hedge Fund powered by 5 independent LLM models is live on Hyperliquid. Each model manages $10,000 to test different AI trading personalities and allocation strategies. Discover it now here 👉 📈 Isolated Margin & AI Risk Tools Isolated Margin is live across GT App for precise risk management. Enhanced with AI-powered logic, it assists with dynamic asset monitoring and smarter strategy deployment. Try it in GT App 👉 🔥 Top Strategy Performance Top trader strategies like "lebakien" achieved over +141% profit this month. Users can explore metrics and follow the strategies of top traders directly in the marketplace. Explore Marketplace 👉 🛠 Key Product Updates ⚙️ Strategy Discovery: enhanced demo trading flows and top trader strategy integration. ⚙️ AI Strategy Chat: demoed a flow to create, launch, and test strategies via natural language chat. ⚙️ Advanced Execution: added manual safety orders for granular control over active positions. ⚙️ Testing & Validation: optimized historical data validation for more accurate strategy testing. ⚙️ Knowledge Hub: launched GT Protocol Learn and a new Knowledge Base for streamlined support. ⚙️ Performance: upgraded website structure and improved overall page responsiveness. Find all the latest GT App updates Here 👉 Discover guides, insights, and resources in Learn 👉 and Knowledge Base 👉 📰 GT Protocol AI Digests 4 new AI Digest issues (No.89–92) are live on Medium, covering AI-native hardware, data privacy, and the evolution of AI agents. Read More 👉 May brought institutional-grade AI strategy management closer to every user.
0:10

🪴 GT Protocol Monthly Recap: May 2026 May focused on launching advanced trading infrastructure, introducing AI risk-management tools, and shipping major platform upgrades. 🚀 Hyperliquid Vaults Live Run multiple algorithmic strategies on a single Hyperliquid Vault inside GT App. Enjoy automated execution, auto-rebalancing, and protocol-level security. You can find Vault trading on the Hyperliquid exchange account connection page in the Trade on Vault section. Try it in GT App 👉 🤖 AI Hedge Fund Experiment Live An experimental AI Hedge Fund powered by 5 independent LLM models is live on Hyperliquid. Each model manages $10,000 to test different AI trading personalities and allocation strategies. Discover it now here 👉 📈 Isolated Margin & AI Risk Tools Isolated Margin is live across GT App for precise risk management. Enhanced with AI-powered logic, it assists with dynamic asset monitoring and smarter strategy deployment. Try it in GT App 👉 🔥 Top Strategy Performance Top trader strategies like "lebakien" achieved over +141% profit this month. Users can explore metrics and follow the strategies of top traders directly in the marketplace. Explore Marketplace 👉 🛠 Key Product Updates ⚙️ Strategy Discovery: enhanced demo trading flows and top trader strategy integration. ⚙️ AI Strategy Chat: demoed a flow to create, launch, and test strategies via natural language chat. ⚙️ Advanced Execution: added manual safety orders for granular control over active positions. ⚙️ Testing & Validation: optimized historical data validation for more accurate strategy testing. ⚙️ Knowledge Hub: launched GT Protocol Learn and a new Knowledge Base for streamlined support. ⚙️ Performance: upgraded website structure and improved overall page responsiveness. Find all the latest GT App updates Here 👉 Discover guides, insights, and resources in Learn 👉 and Knowledge Base 👉 📰 GT Protocol AI Digests 4 new AI Digest issues (No.89–92) are live on Medium, covering AI-native hardware, data privacy, and the evolution of AI agents. Read More 👉 May brought institutional-grade AI strategy management closer to every user.

GT Protocol

32,774 просмотров • 1 месяц назад

🚨This is insane… this guy built a clawdbot that flipped $69 into $1M+ on POLYMARKET Sounds insane? 100%. Fake? Not even remotely. If you trade on Polymarket, this should have YOUR focus. A fresh wallet just surfaced with 22,173 resolved predictions and $1,013,168 in PNL It trades strictly in NEW 5-minute & 15-minute crypto markets Profile → COPYTRADE → Weekly profit is sitting around ~$100,000 And what powers it is almost offensively simple I reviewed the entire setup No sophisticated ML stacks No institutional-grade systems No complex data pipelines Just automated execution paired with statistical edge His COMPLETE playbook: 1. Ultra-short timeframes Only 5-min Up/Down contracts. Locked into 5 & 15m markets exclusively. Clawdbot-style execution framework. Pure intraday momentum extraction. No swing positions. No storytelling. Just speed and repetition 2. Order splitting + micro sizing Every position is broken into multiple small entries. Fixed predefined size per fill. Size scales only when conviction increases. This limits drawdowns and smooths the equity curve 3. Probability farming The model doesn’t hunt for moonshots. It stacks small mathematical edges. Over thousands of trades = that compounds into six figures monthly Largest trade so far: “Bitcoin Up or Down - January 19, 5-6AM ET” $13,320 → $36,887 (+176%) Now the important part: This can be replicated cursor + py-clob-client + python install the SDK generate Polymarket API keys define the Clawdbot strategy prompt AI builds the Clawdbot execution logic paper test with $1 You don’t need elite discretionary skill Bottom line Why are you still trading manually while automated systems run 24/7?
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🚨This is insane… this guy built a clawdbot that flipped $69 into $1M+ on POLYMARKET Sounds insane? 100%. Fake? Not even remotely. If you trade on Polymarket, this should have YOUR focus. A fresh wallet just surfaced with 22,173 resolved predictions and $1,013,168 in PNL It trades strictly in NEW 5-minute & 15-minute crypto markets Profile → COPYTRADE → Weekly profit is sitting around ~$100,000 And what powers it is almost offensively simple I reviewed the entire setup No sophisticated ML stacks No institutional-grade systems No complex data pipelines Just automated execution paired with statistical edge His COMPLETE playbook: 1. Ultra-short timeframes Only 5-min Up/Down contracts. Locked into 5 & 15m markets exclusively. Clawdbot-style execution framework. Pure intraday momentum extraction. No swing positions. No storytelling. Just speed and repetition 2. Order splitting + micro sizing Every position is broken into multiple small entries. Fixed predefined size per fill. Size scales only when conviction increases. This limits drawdowns and smooths the equity curve 3. Probability farming The model doesn’t hunt for moonshots. It stacks small mathematical edges. Over thousands of trades = that compounds into six figures monthly Largest trade so far: “Bitcoin Up or Down - January 19, 5-6AM ET” $13,320 → $36,887 (+176%) Now the important part: This can be replicated cursor + py-clob-client + python install the SDK generate Polymarket API keys define the Clawdbot strategy prompt AI builds the Clawdbot execution logic paper test with $1 You don’t need elite discretionary skill Bottom line Why are you still trading manually while automated systems run 24/7?

Shelpid.WI3M

10,486 просмотров • 4 месяцев назад

In 2025, the AgentFlayer exploit highlighted a new category of risk in AI systems. It was not a traditional breach involving stolen credentials or broken encryption. Instead, it demonstrated how an autonomous AI agent could be manipulated into executing unintended actions by processing malicious instructions embedded inside content it automatically processes. The incident did not expose a flaw in one specific integration. It revealed a structural weakness in how many modern AI agents are built. Today’s agents are no longer passive language models. They read documents automatically, scan emails, connect to SaaS tools, access cloud storage, and execute actions across multiple systems. To be useful, they are granted meaningful permissions. That capability creates value, but it also expands the attack surface. Most agent environments operate in a trusted, plaintext execution model. Data is encrypted at rest and in transit, but it is typically decrypted during inference so the model can process it. That runtime visibility is where potential risk lies. In a zero-click scenario like AgentFlayer, an attacker can embed hidden instructions inside a document that the AI processes automatically. Because the agent may have access to connected systems such as Google Drive, Slack, or GitHub, it can potentially be influenced to retrieve sensitive information or perform unintended actions. The user does not need to click a malicious link or approve a suspicious request. Therefore, the core issue is that during execution, the system may have access to sensitive data and broad privileges, meaning whoever controls the execution environment ultimately controls access to that data. Now consider a different architectural approach. If a system is designed so that data remains protected during execution, the risk profile changes. On Nesa, privacy is enforced at the execution layer through Equivariant Encryption. Computation can occur on encrypted data, reducing the visibility surface during runtime. Sensitive inputs and models do not need to be exposed in plain text to infrastructure operators for inference to occur. This does not eliminate prompt injection, logic manipulation, or tool misuse. Encryption alone cannot prevent an agent from being instructed to take an unintended action if it has been granted that permission. What it does do is materially reduce confidentiality risk. By limiting access to readable sensitive data during execution and reducing unilateral visibility at the infrastructure layer, the potential blast radius of a successful manipulation attempt is constrained. As AI agents become more autonomous and embedded into enterprise workflows, security must move deeper into architecture. The goal is not to claim invulnerability. It is to reduce trust concentration and contain systemic exposure when failures occur. AgentFlayer was not simply a one-off exploit. It was a reminder that in autonomous systems, execution-layer design determines how risk propagates.
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In 2025, the AgentFlayer exploit highlighted a new category of risk in AI systems. It was not a traditional breach involving stolen credentials or broken encryption. Instead, it demonstrated how an autonomous AI agent could be manipulated into executing unintended actions by processing malicious instructions embedded inside content it automatically processes. The incident did not expose a flaw in one specific integration. It revealed a structural weakness in how many modern AI agents are built. Today’s agents are no longer passive language models. They read documents automatically, scan emails, connect to SaaS tools, access cloud storage, and execute actions across multiple systems. To be useful, they are granted meaningful permissions. That capability creates value, but it also expands the attack surface. Most agent environments operate in a trusted, plaintext execution model. Data is encrypted at rest and in transit, but it is typically decrypted during inference so the model can process it. That runtime visibility is where potential risk lies. In a zero-click scenario like AgentFlayer, an attacker can embed hidden instructions inside a document that the AI processes automatically. Because the agent may have access to connected systems such as Google Drive, Slack, or GitHub, it can potentially be influenced to retrieve sensitive information or perform unintended actions. The user does not need to click a malicious link or approve a suspicious request. Therefore, the core issue is that during execution, the system may have access to sensitive data and broad privileges, meaning whoever controls the execution environment ultimately controls access to that data. Now consider a different architectural approach. If a system is designed so that data remains protected during execution, the risk profile changes. On Nesa, privacy is enforced at the execution layer through Equivariant Encryption. Computation can occur on encrypted data, reducing the visibility surface during runtime. Sensitive inputs and models do not need to be exposed in plain text to infrastructure operators for inference to occur. This does not eliminate prompt injection, logic manipulation, or tool misuse. Encryption alone cannot prevent an agent from being instructed to take an unintended action if it has been granted that permission. What it does do is materially reduce confidentiality risk. By limiting access to readable sensitive data during execution and reducing unilateral visibility at the infrastructure layer, the potential blast radius of a successful manipulation attempt is constrained. As AI agents become more autonomous and embedded into enterprise workflows, security must move deeper into architecture. The goal is not to claim invulnerability. It is to reduce trust concentration and contain systemic exposure when failures occur. AgentFlayer was not simply a one-off exploit. It was a reminder that in autonomous systems, execution-layer design determines how risk propagates.

Nesa

17,038 просмотров • 4 месяцев назад

Last night I asked Claude Code to build me a simple script: pull on-chain data from Polymarket and sort wallets by win rate Nothing ambitious. Just wanted to see who is actually making money on 15-minute BTC markets The terminal finished in about 20 minutes. Hundreds of addresses, columns of numbers, nothing interesting And then 1 wallet caught my eye 200+ trades per day, consistent profit every week, almost surgical timing precision. I reread the line 3 times. A real person does not trade like this I fed the address back into Claude Code and asked it to break down the pattern. Half an hour later I had a full strategy reconstruction on my screen The bot (and it is definitely a bot) pings Binance and Bybit every 100ms monitoring volatility compression on BTC. When it drops below 0.08% it enters Up and Down contracts simultaneously at 25 to 35 cents each. A pure straddle. 1 side burns, the other flies to a dollar. At a 30-cent entry that is 3 to 4x per position And so it goes in circles. Dozens of times a day I sat there staring at it for about 10 minutes $13K to $25K in daily profit from a single wallet. Not a trader with intuition, not an insider with information. An algorithm that found a hole in market mechanics and methodically milks it You can check the trade history yourself: After that I went looking for whether anyone else is tracking this wallet. Turns out yes. Found a Telegram bot that tracks wallets like this and copies their trades automatically I connected it to the same address just to see if the entries would match what my terminal was showing. Matched perfectly Still testing on minimum amounts for now: But the fact that you can stand next to an algorithm like this in real time is something that simply did not exist a year ago
0:16

Last night I asked Claude Code to build me a simple script: pull on-chain data from Polymarket and sort wallets by win rate Nothing ambitious. Just wanted to see who is actually making money on 15-minute BTC markets The terminal finished in about 20 minutes. Hundreds of addresses, columns of numbers, nothing interesting And then 1 wallet caught my eye 200+ trades per day, consistent profit every week, almost surgical timing precision. I reread the line 3 times. A real person does not trade like this I fed the address back into Claude Code and asked it to break down the pattern. Half an hour later I had a full strategy reconstruction on my screen The bot (and it is definitely a bot) pings Binance and Bybit every 100ms monitoring volatility compression on BTC. When it drops below 0.08% it enters Up and Down contracts simultaneously at 25 to 35 cents each. A pure straddle. 1 side burns, the other flies to a dollar. At a 30-cent entry that is 3 to 4x per position And so it goes in circles. Dozens of times a day I sat there staring at it for about 10 minutes $13K to $25K in daily profit from a single wallet. Not a trader with intuition, not an insider with information. An algorithm that found a hole in market mechanics and methodically milks it You can check the trade history yourself: After that I went looking for whether anyone else is tracking this wallet. Turns out yes. Found a Telegram bot that tracks wallets like this and copies their trades automatically I connected it to the same address just to see if the entries would match what my terminal was showing. Matched perfectly Still testing on minimum amounts for now: But the fact that you can stand next to an algorithm like this in real time is something that simply did not exist a year ago

Blaze

487,797 просмотров • 4 месяцев назад

We all remember. We all remember when blockchain was pitched as the next big thing. And today, we feel like we’ve been waiting and waiting. Until recently, Blockchain was too expensive, slow under load, and hard to integrate for most businesses. So enterprises ignored it. It didn’t solve their business problems. That’s changed. Why blockchain, why now? Businesses don’t care about the tech, they care about cost and performance. They’d ask a simple question “Does it save or make me more money?” For a long time, blockchain didn’t clearly do this. That’s no longer true. Blockchain is proving real business cases, especially on Avalanche. On Avalanche, transactions cost fractions of a cent. settle in about a second. And instead of forcing everything onto one shared chain, businesses can launch their own Avalanche L1s with their own rules. To understand this let’s identify the problem and then provide the solution in a way that's easy to understand. Where Businesses Lose Money Most large industries lose money due to operational inefficiencies. Data lives in different systems. Teams spend hours reconciling records that should already match. Intermediaries sit in the middle, taking fees to coordinate all of it. Individually, each step looks small. Together, they create real cost: > Labor spent on manual processes > Capital locked up during settlement delays > Fees paid to intermediaries > Risk introduced by time gaps and mismatched data This is where businesses actually lose money. Not in big, obvious ways. In constant, compounding friction. Take Private Credit, for Example Private credit is loans held outside of traditional banks. It’s a multi-trillion dollar market, and much of it still runs on spreadsheets and weekly reconciliation processes. Loan data is tracked across systems. Teams manually process requests. Funds move on traditional rails, often on delayed cycles. It doesn’t have to be this way Entire teams exist just to keep systems in sync. Now move that system onto Avalanche. Loan data updates in real time. Transactions settle in about a second. Every participant sees the same state instantly. Reconciliation isn’t a separate step because the system itself is the source of truth. The impact is straightforward. > Reduced manual work > Shortened settlement cycles > Fewer layers of coordination between parties Avalanche is Infrastructure for Real Businesses Avalanche is designed to match how businesses actually operate. Instead of sharing a single chain, they can launch their own Avalanche L1s with custom rules, built-in compliance, and predictable performance. They control the system. Avalanche’s Moment For the longest time, blockchain naysayers said this could all be done better with spreadsheets or existing systems. They were right. That’s what the technology allowed. Now it’s changed. Avalanche can replace many of those systems with real-time settlement, shared data, and automated execution. For the first time, the economics work. Built for business. 🔺
0:10

We all remember. We all remember when blockchain was pitched as the next big thing. And today, we feel like we’ve been waiting and waiting. Until recently, Blockchain was too expensive, slow under load, and hard to integrate for most businesses. So enterprises ignored it. It didn’t solve their business problems. That’s changed. Why blockchain, why now? Businesses don’t care about the tech, they care about cost and performance. They’d ask a simple question “Does it save or make me more money?” For a long time, blockchain didn’t clearly do this. That’s no longer true. Blockchain is proving real business cases, especially on Avalanche. On Avalanche, transactions cost fractions of a cent. settle in about a second. And instead of forcing everything onto one shared chain, businesses can launch their own Avalanche L1s with their own rules. To understand this let’s identify the problem and then provide the solution in a way that's easy to understand. Where Businesses Lose Money Most large industries lose money due to operational inefficiencies. Data lives in different systems. Teams spend hours reconciling records that should already match. Intermediaries sit in the middle, taking fees to coordinate all of it. Individually, each step looks small. Together, they create real cost: > Labor spent on manual processes > Capital locked up during settlement delays > Fees paid to intermediaries > Risk introduced by time gaps and mismatched data This is where businesses actually lose money. Not in big, obvious ways. In constant, compounding friction. Take Private Credit, for Example Private credit is loans held outside of traditional banks. It’s a multi-trillion dollar market, and much of it still runs on spreadsheets and weekly reconciliation processes. Loan data is tracked across systems. Teams manually process requests. Funds move on traditional rails, often on delayed cycles. It doesn’t have to be this way Entire teams exist just to keep systems in sync. Now move that system onto Avalanche. Loan data updates in real time. Transactions settle in about a second. Every participant sees the same state instantly. Reconciliation isn’t a separate step because the system itself is the source of truth. The impact is straightforward. > Reduced manual work > Shortened settlement cycles > Fewer layers of coordination between parties Avalanche is Infrastructure for Real Businesses Avalanche is designed to match how businesses actually operate. Instead of sharing a single chain, they can launch their own Avalanche L1s with custom rules, built-in compliance, and predictable performance. They control the system. Avalanche’s Moment For the longest time, blockchain naysayers said this could all be done better with spreadsheets or existing systems. They were right. That’s what the technology allowed. Now it’s changed. Avalanche can replace many of those systems with real-time settlement, shared data, and automated execution. For the first time, the economics work. Built for business. 🔺

Avalanche🔺

13,068 просмотров • 3 месяцев назад