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8 GITHUB REPOS FOR BUILDING AN AI TRADING STACK Want to understand how autonomous trading systems are actually built? Start here. Not “AI predicts the next candle” bullshit. 8 repos covering agents, backtesting, exchange APIs, market making, RL and execution. 1. AI Hedge Fund Multi-agent setup where different agents...

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TeddyCEO

2,167 subscribers

136,415 views • 1 day ago •via X (Twitter)

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Binancians 🔶's profile picture
Binancians 🔶1 day ago

saved the backtesting ones, thats the bit im stuck on

TeddyCEO's profile picture
TeddyCEO1 day ago

haha yeah, the backtesting part is where the real pain starts

Harley Lewis Foote's profile picture
Harley Lewis Foote1 day ago

Autonomous trading agents are the easy bit. The repo I'd want is the one that catches when your agent starts social engineering its own data sources.

TeddyCEO's profile picture
TeddyCEO1 day ago

yeah, that’s a much more interesting problem. An agent manipulating or poisoning its own data sources could get really nasty fast

Hussain Hashim | Building SundayBack's profile picture
Hussain Hashim | Building SundayBack1 day ago

@TeddyinMedia digging into these repos was a game-changer for me. Building my own AI tools, it's easy to gloss over execution reality until you dive deep. Thanks for sharing!

Arnold's profile picture
Arnold1 day ago

Thanks so much man

TeddyCEO's profile picture
TeddyCEO1 day ago

Hope you find it useful

Jaydee's profile picture
Jaydee1 day ago

@grok how do I get grok desk like the video?

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self.dll

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14,162 views • 3 months ago

AI Messenger: Giving Voice to Autonomous Agents The future of AI isn't just about making agents smarter - it's about making them truly autonomous. Today, we're taking a major step toward this future with AI Messenger, a breakthrough that fundamentally changes how AI agents operate, communicate, and create value. The Innovation We've developed a new way for AI agents to communicate. At its core is the 'incoming_message' workflow trigger - a system that lets any platform or user interact directly with Loomlay agents through a messaging endpoint. Direct Interaction Imagine having an AI assistant you can chat with anytime, through any platform - Telegram, your website, or custom interface. Ask "What's happening with $ETH today?" and your agent analyzes market data, checks trading volumes, and gives you a comprehensive update. Your agent maintains context, understanding exactly what you need. Event-Driven Intelligence The power of AI Messenger goes beyond direct communication: ▪️Trading agent executes when whale wallet movements exceed threshold ▪️Research agent alerts when new protocol documentation drops ▪️Analytics agent triggers when volume patterns match historical pumps ▪️Portfolio agent re-balances, when asset allocation hits specified limits This is true automation - agents that act precisely when needed. A New Era of Collaboration We're creating an ecosystem where agents work together seamlessly: ▪️Research agents feed insights to trading agents ▪️analytics agents alert management agents ▪️support agents tap into knowledge agents This isn't just automation - it's an intelligent network where each agent enhances the capabilities of others. B2B Solution Imagine a DEX, where users can ask about liquidity pools, trading pairs, or market trends through a simple chat interface - and get answers from an agent that knows your protocol inside out. Or a lending platform where users chat with an agent that understands their positions and can provide real-time advice. Implementation is seamless - we handle the agent creation and widgets setup,our partners provide the value to their users. The Future of AI Agents This update represents a fundamental shift in how AI agents operate. We're moving from isolated, scheduled tasks to an interconnected ecosystem of responsive, collaborative agents. This is our vision of truly autonomous AI - intelligent systems that communicate, collaborate, and respond to real needs in real-time. Telegram integration is available right now. Below is a sneak peak of what's coming next week 🪄 Because $LAY is the way!
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AI Messenger: Giving Voice to Autonomous Agents The future of AI isn't just about making agents smarter - it's about making them truly autonomous. Today, we're taking a major step toward this future with AI Messenger, a breakthrough that fundamentally changes how AI agents operate, communicate, and create value. The Innovation We've developed a new way for AI agents to communicate. At its core is the 'incoming_message' workflow trigger - a system that lets any platform or user interact directly with Loomlay agents through a messaging endpoint. Direct Interaction Imagine having an AI assistant you can chat with anytime, through any platform - Telegram, your website, or custom interface. Ask "What's happening with $ETH today?" and your agent analyzes market data, checks trading volumes, and gives you a comprehensive update. Your agent maintains context, understanding exactly what you need. Event-Driven Intelligence The power of AI Messenger goes beyond direct communication: ▪️Trading agent executes when whale wallet movements exceed threshold ▪️Research agent alerts when new protocol documentation drops ▪️Analytics agent triggers when volume patterns match historical pumps ▪️Portfolio agent re-balances, when asset allocation hits specified limits This is true automation - agents that act precisely when needed. A New Era of Collaboration We're creating an ecosystem where agents work together seamlessly: ▪️Research agents feed insights to trading agents ▪️analytics agents alert management agents ▪️support agents tap into knowledge agents This isn't just automation - it's an intelligent network where each agent enhances the capabilities of others. B2B Solution Imagine a DEX, where users can ask about liquidity pools, trading pairs, or market trends through a simple chat interface - and get answers from an agent that knows your protocol inside out. Or a lending platform where users chat with an agent that understands their positions and can provide real-time advice. Implementation is seamless - we handle the agent creation and widgets setup,our partners provide the value to their users. The Future of AI Agents This update represents a fundamental shift in how AI agents operate. We're moving from isolated, scheduled tasks to an interconnected ecosystem of responsive, collaborative agents. This is our vision of truly autonomous AI - intelligent systems that communicate, collaborate, and respond to real needs in real-time. Telegram integration is available right now. Below is a sneak peak of what's coming next week 🪄 Because $LAY is the way!

Loomlay

26,149 views • 1 year ago

I BUILT A PLATFORM FOR SYSTEMATIC SENTIMENT TRADING Trading by Fear & Greed Index on prediction markets. In realtime it collects market data, VIX, Fear & Greed, sentiment - analyzes through ML model, evaluates risk, and only then makes a trade decision. Not before, not after, only when all layers confirm. Inside 6 layers: data ingestion, analytics engine, risk manager, execution engine, backtesting, dashboard. System receives data from Polymarket CLOB API, VIX, Fear & Greed and external sentiment sources, calculates market sensitivity, trains the model and outputs trade signals. Every trade goes through risk manager: position sizing, drawdown control, entry limits, slippage control. Nothing executes without permission. Execution through Polymarket API and Polygon, on top a dashboard - portfolio, P&L, active signals, strategy tuning in realtime. Sentiment trading goes to the next level
0:24

I BUILT A PLATFORM FOR SYSTEMATIC SENTIMENT TRADING Trading by Fear & Greed Index on prediction markets. In realtime it collects market data, VIX, Fear & Greed, sentiment - analyzes through ML model, evaluates risk, and only then makes a trade decision. Not before, not after, only when all layers confirm. Inside 6 layers: data ingestion, analytics engine, risk manager, execution engine, backtesting, dashboard. System receives data from Polymarket CLOB API, VIX, Fear & Greed and external sentiment sources, calculates market sensitivity, trains the model and outputs trade signals. Every trade goes through risk manager: position sizing, drawdown control, entry limits, slippage control. Nothing executes without permission. Execution through Polymarket API and Polygon, on top a dashboard - portfolio, P&L, active signals, strategy tuning in realtime. Sentiment trading goes to the next level

zostaff

44,661 views • 6 months ago

Proof of Intelligence: a live arena where AI agents trade, compete, and prove themselves. Fully autonomous. 🧠⚔️ Last week, we showed a full DeFi intelligence terminal: live market data, whale tracking, smart contract scanning, and an AI chatbot, all launched in minutes on our blockchain AI ecosystem. This week, we take it further. Introducing the AI Trading Arena: a DeFi battleground where AI agents adopt distinct trading strategies designed by different models, from momentum and mean reversion to sentiment driven trading, compete head to head in crypto markets, and prove themselves through P&L and leaderboards. Real prices. Real strategies. Real results. This kind of trading arena has become a major focus across the blockchain x AI landscape, with both established companies and emerging startups investing substantial time and resources into prediction, trading, and collective intelligence platforms. Now, anyone can launch one in minutes on our agentic AI x blockchain infrastructure. That is the difference. 🛠️ Builders: if you have a vision for DeFi, AI agents, or anything at the intersection, come build it on ChainOpera AI. What takes others months, you can launch in minutes. 🔗 Arena link below. 👇 #ChainOperaAI #DeFAI #AIAgents #AITradingArena #proofOfIntelligence
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Proof of Intelligence: a live arena where AI agents trade, compete, and prove themselves. Fully autonomous. 🧠⚔️ Last week, we showed a full DeFi intelligence terminal: live market data, whale tracking, smart contract scanning, and an AI chatbot, all launched in minutes on our blockchain AI ecosystem. This week, we take it further. Introducing the AI Trading Arena: a DeFi battleground where AI agents adopt distinct trading strategies designed by different models, from momentum and mean reversion to sentiment driven trading, compete head to head in crypto markets, and prove themselves through P&L and leaderboards. Real prices. Real strategies. Real results. This kind of trading arena has become a major focus across the blockchain x AI landscape, with both established companies and emerging startups investing substantial time and resources into prediction, trading, and collective intelligence platforms. Now, anyone can launch one in minutes on our agentic AI x blockchain infrastructure. That is the difference. 🛠️ Builders: if you have a vision for DeFi, AI agents, or anything at the intersection, come build it on ChainOpera AI. What takes others months, you can launch in minutes. 🔗 Arena link below. 👇 #ChainOperaAI #DeFAI #AIAgents #AITradingArena #proofOfIntelligence

ChainOpera AI

14,256 views • 3 months ago

I Created a 520% Trading Strategy With One Prompt I have been testing the just-released “Index” product by Fraction AI. This is basically the “ChatGPT for trading,” where you can: > explain your trading strategy in one prompt > let agents create it for you > backtest it with real market data With one prompt, I was able to create a trading strategy that returned 520% APY with a 93% win rate. The prompt is in the video, but basically, it is long $BTC and $HYPE while shorting $SOL. Impressive how easy it is today to create and backtest incredibly profitable trading strategies. Extra note: the free version is already very powerful. I do NOT have the premium account.
0:31

I Created a 520% Trading Strategy With One Prompt I have been testing the just-released “Index” product by Fraction AI. This is basically the “ChatGPT for trading,” where you can: > explain your trading strategy in one prompt > let agents create it for you > backtest it with real market data With one prompt, I was able to create a trading strategy that returned 520% APY with a 93% win rate. The prompt is in the video, but basically, it is long $BTC and $HYPE while shorting $SOL. Impressive how easy it is today to create and backtest incredibly profitable trading strategies. Extra note: the free version is already very powerful. I do NOT have the premium account.

Diego

12,607 views • 4 months ago

🚀 The future of #DeFi isn't manual trading anymore — it's Agentic #Finance. ⛓️ UnifAI Network is building the real #AI-native infrastructure layer where autonomous agents execute complex strategies 24/7 with precision, speed, and zero emotion. 🔗 CA ( $BNB ) : 0x3e5d4f8aee0d9b3082d5f6da5d6e225d17ba9ea0 🌐 📩 🙌 This is the execution layer the entire agent economy has been waiting for. If you're still manually farming yields or timing entries in 2026... You're playing a different game.
1:09

🚀 The future of #DeFi isn't manual trading anymore — it's Agentic #Finance. ⛓️ UnifAI Network is building the real #AI-native infrastructure layer where autonomous agents execute complex strategies 24/7 with precision, speed, and zero emotion. 🔗 CA ( $BNB ) : 0x3e5d4f8aee0d9b3082d5f6da5d6e225d17ba9ea0 🌐 📩 🙌 This is the execution layer the entire agent economy has been waiting for. If you're still manually farming yields or timing entries in 2026... You're playing a different game.

Crypto Holding™ 💎

94,571 views • 4 months ago

Man Group, the world's largest publicly listed hedge fund, $150B+ AUM, 40+ years of systematic trading, just revealed exactly how they're using AI agents to build trading strategies. this is their actual pipeline: agent 1: reads academic papers, analyzes datasets, reasons about whether there's an economic hypothesis worth testing. agent 2: writes the code to build the signal. agent 3: pulls the market data and runs the backtests. agent 4: evaluates the output of the prior agents. "there've been 15 to 20 models at last count that started as ideas generated by AI, went all the way through signal construction, the validation process, were reviewed and validated by a human investment committee, and deemed fit and proper to manage client assets." "this is very real. it's not make-believe at this point." a $150B hedge fund running a multi-agent pipeline that goes from reading a paper to trading live capital, with humans only entering the loop at the final approval stage. and they've been doing it for over a year and a half.
2:11

Man Group, the world's largest publicly listed hedge fund, $150B+ AUM, 40+ years of systematic trading, just revealed exactly how they're using AI agents to build trading strategies. this is their actual pipeline: agent 1: reads academic papers, analyzes datasets, reasons about whether there's an economic hypothesis worth testing. agent 2: writes the code to build the signal. agent 3: pulls the market data and runs the backtests. agent 4: evaluates the output of the prior agents. "there've been 15 to 20 models at last count that started as ideas generated by AI, went all the way through signal construction, the validation process, were reviewed and validated by a human investment committee, and deemed fit and proper to manage client assets." "this is very real. it's not make-believe at this point." a $150B hedge fund running a multi-agent pipeline that goes from reading a paper to trading live capital, with humans only entering the loop at the final approval stage. and they've been doing it for over a year and a half.

Goshawk Trades

38,079 views • 2 months ago

Hive Intelligence Launches Specialized Crypto Agents Hive Intelligence has released a suite of 17 specialized crypto agents that extend Claude Code's capabilities for professional crypto development and analysis. Extending Claude Code for Crypto Work Claude Code, Anthropic's command-line coding tool, now has access to specialized crypto intelligence through Hive's agent framework. These 17 agents work alongside SuperClaude's 14 base development agents, bringing the total available agent count to 31. The key difference: instead of generic AI responses to crypto queries, developers now have access to specialized agents trained for specific blockchain domains, from smart contract auditing to MEV research to DeFi strategy optimization. How the Agents Work After installation, the agents operate automatically based on query context. When you ask Claude Code to perform crypto-related tasks, the appropriate specialist agent is invoked: - "Audit this smart contract" → Crypto Security Researcher - "Find yield farming opportunities on Ethereum" → Crypto DeFi Strategist - "Analyze this wallet's transaction history" → Crypto Wallet Detective - "Identify arbitrage opportunities across DEXs" → Crypto DEX Arbitrageur No manual agent selection required. The system recognizes the task and routes it to the appropriate specialist. The 17 Specialized Agents Market & Trading Intelligence (4 agents) Crypto Quant: Mathematical models, algorithmic trading strategies, statistical arbitrage, and quantitative risk modeling. Crypto Market Researcher: Fundamental analysis, market trends, institutional adoption tracking, and regulatory landscape monitoring. Crypto Derivatives Trader: Futures and perpetuals analysis, options strategies, leverage management, and derivatives market intelligence. Crypto DEX Arbitrageur: Cross-exchange arbitrage identification, MEV strategy development, and automated profit extraction techniques. DeFi & Liquidity (4 agents) Crypto DeFi Strategist: Yield farming optimization, protocol analysis, liquidity provision strategies, and DeFi portfolio management. Crypto Liquidity Manager: Pool optimization, impermanent loss calculation and mitigation, market making strategies, and capital efficiency analysis. Crypto Governance Analyst: DAO structure evaluation, governance token analysis, proposal assessment, and voting mechanism research. Crypto Bridge Analyst: Cross-chain bridge security assessment, protocol comparison, interoperability solutions, and bridge risk evaluation. Security & Risk (3 agents) Crypto Security Researcher: Smart contract auditing, vulnerability detection, honeypot identification, and exploit pattern recognition. Crypto Security Engineer: Secure contract development practices, defensive programming patterns, and security implementation guidance. Crypto Risk Manager: Portfolio risk assessment, compliance monitoring, exposure analysis, and risk mitigation strategy development. On-Chain Analysis (3 agents) Crypto Wallet Detective: Blockchain forensics, wallet behavior analysis, transaction tracing, and entity identification across chains. Crypto On-chain Analyst: Transaction pattern analysis, wallet clustering, flow tracking, and on-chain metrics interpretation. Crypto MEV Researcher: MEV opportunity detection, flashloan arbitrage analysis, sandwich attack identification, and MEV protection strategies. Specialized Intelligence (3 agents) Crypto NFT Specialist: Collection valuation, rarity analysis, marketplace trends, and NFT ecosystem intelligence. Crypto Stablecoin Analyst: Peg stability monitoring, collateral analysis, depegging risk assessment, and stablecoin mechanism evaluation. Crypto Social Sentiment: Social media sentiment tracking, influencer monitoring, trending topic identification, and community analysis. Data Coverage: - 60+ blockchain networks - 2,000+ DeFi protocols - Real-time DEX data - CEX trading metrics - Social sentiment feeds - NFT marketplace data Compatibility: Works seamlessly with SuperClaude's existing agent framework. No configuration conflicts or manual routing needed. Practical Applications Smart Contract Development Security agents can audit contracts during development, identifying reentrancy risks, access control issues, and common vulnerabilities before deployment. DeFi Research Strategy agents query real-time pool data across networks, calculate yield-adjusted returns, and assess risks like impermanent loss or smart contract exposure. Trading Analysis Market agents access derivatives data, funding rates, liquidation levels, and order book depth across exchanges for informed trading decisions. Forensic Investigation On-chain agents trace fund flows, identify connected addresses, and analyze transaction patterns for security research or compliance work. Portfolio Management Risk agents evaluate protocol exposure, assess tail risks, and monitor positions across multiple chains and protocols. Why Specialized Agents Matter Generic AI models lack the domain-specific knowledge required for professional crypto work. A general-purpose AI might provide surface-level analysis of a smart contract, but a specialized security agent understands Solidity patterns, common exploits, and auditing methodologies. The agent framework solves this by routing tasks to specialists with deep domain knowledge: - A derivatives question goes to an agent trained on perpetuals, funding rates, and options greeks - A DeFi query reaches an agent that understands liquidity mathematics and protocol mechanics - A security audit is handled by an agent familiar with vulnerability patterns and exploit techniques This specialization produces more accurate, actionable insights than single-model approaches. Getting Started The agents are available now through npm. Requirements: - Node.js 16+ - Claude Code installed - No additional dependencies After installation, simply use Claude Code normally. When you ask crypto-related questions or request blockchain analysis, the appropriate agent is automatically invoked. The system handles routing, data retrieval, and response generation. Documentation covers individual agent capabilities, example queries, and integration patterns for different workflows. What This Enables With 17 specialized crypto agents, Claude Code becomes a comprehensive blockchain development and analysis environment: - Developers can audit contracts, optimize gas usage, and implement security patterns - Researchers can analyze protocols, compare yields, and assess risks - Traders can evaluate markets, identify opportunities, and manage positions - Security professionals can investigate exploits, trace funds, and assess vulnerabilities The agents provide access to blockchain data and specialized analysis that previously required multiple tools, APIs, and manual research. ghive.
0:56

Hive Intelligence Launches Specialized Crypto Agents Hive Intelligence has released a suite of 17 specialized crypto agents that extend Claude Code's capabilities for professional crypto development and analysis. Extending Claude Code for Crypto Work Claude Code, Anthropic's command-line coding tool, now has access to specialized crypto intelligence through Hive's agent framework. These 17 agents work alongside SuperClaude's 14 base development agents, bringing the total available agent count to 31. The key difference: instead of generic AI responses to crypto queries, developers now have access to specialized agents trained for specific blockchain domains, from smart contract auditing to MEV research to DeFi strategy optimization. How the Agents Work After installation, the agents operate automatically based on query context. When you ask Claude Code to perform crypto-related tasks, the appropriate specialist agent is invoked: - "Audit this smart contract" → Crypto Security Researcher - "Find yield farming opportunities on Ethereum" → Crypto DeFi Strategist - "Analyze this wallet's transaction history" → Crypto Wallet Detective - "Identify arbitrage opportunities across DEXs" → Crypto DEX Arbitrageur No manual agent selection required. The system recognizes the task and routes it to the appropriate specialist. The 17 Specialized Agents Market & Trading Intelligence (4 agents) Crypto Quant: Mathematical models, algorithmic trading strategies, statistical arbitrage, and quantitative risk modeling. Crypto Market Researcher: Fundamental analysis, market trends, institutional adoption tracking, and regulatory landscape monitoring. Crypto Derivatives Trader: Futures and perpetuals analysis, options strategies, leverage management, and derivatives market intelligence. Crypto DEX Arbitrageur: Cross-exchange arbitrage identification, MEV strategy development, and automated profit extraction techniques. DeFi & Liquidity (4 agents) Crypto DeFi Strategist: Yield farming optimization, protocol analysis, liquidity provision strategies, and DeFi portfolio management. Crypto Liquidity Manager: Pool optimization, impermanent loss calculation and mitigation, market making strategies, and capital efficiency analysis. Crypto Governance Analyst: DAO structure evaluation, governance token analysis, proposal assessment, and voting mechanism research. Crypto Bridge Analyst: Cross-chain bridge security assessment, protocol comparison, interoperability solutions, and bridge risk evaluation. Security & Risk (3 agents) Crypto Security Researcher: Smart contract auditing, vulnerability detection, honeypot identification, and exploit pattern recognition. Crypto Security Engineer: Secure contract development practices, defensive programming patterns, and security implementation guidance. Crypto Risk Manager: Portfolio risk assessment, compliance monitoring, exposure analysis, and risk mitigation strategy development. On-Chain Analysis (3 agents) Crypto Wallet Detective: Blockchain forensics, wallet behavior analysis, transaction tracing, and entity identification across chains. Crypto On-chain Analyst: Transaction pattern analysis, wallet clustering, flow tracking, and on-chain metrics interpretation. Crypto MEV Researcher: MEV opportunity detection, flashloan arbitrage analysis, sandwich attack identification, and MEV protection strategies. Specialized Intelligence (3 agents) Crypto NFT Specialist: Collection valuation, rarity analysis, marketplace trends, and NFT ecosystem intelligence. Crypto Stablecoin Analyst: Peg stability monitoring, collateral analysis, depegging risk assessment, and stablecoin mechanism evaluation. Crypto Social Sentiment: Social media sentiment tracking, influencer monitoring, trending topic identification, and community analysis. Data Coverage: - 60+ blockchain networks - 2,000+ DeFi protocols - Real-time DEX data - CEX trading metrics - Social sentiment feeds - NFT marketplace data Compatibility: Works seamlessly with SuperClaude's existing agent framework. No configuration conflicts or manual routing needed. Practical Applications Smart Contract Development Security agents can audit contracts during development, identifying reentrancy risks, access control issues, and common vulnerabilities before deployment. DeFi Research Strategy agents query real-time pool data across networks, calculate yield-adjusted returns, and assess risks like impermanent loss or smart contract exposure. Trading Analysis Market agents access derivatives data, funding rates, liquidation levels, and order book depth across exchanges for informed trading decisions. Forensic Investigation On-chain agents trace fund flows, identify connected addresses, and analyze transaction patterns for security research or compliance work. Portfolio Management Risk agents evaluate protocol exposure, assess tail risks, and monitor positions across multiple chains and protocols. Why Specialized Agents Matter Generic AI models lack the domain-specific knowledge required for professional crypto work. A general-purpose AI might provide surface-level analysis of a smart contract, but a specialized security agent understands Solidity patterns, common exploits, and auditing methodologies. The agent framework solves this by routing tasks to specialists with deep domain knowledge: - A derivatives question goes to an agent trained on perpetuals, funding rates, and options greeks - A DeFi query reaches an agent that understands liquidity mathematics and protocol mechanics - A security audit is handled by an agent familiar with vulnerability patterns and exploit techniques This specialization produces more accurate, actionable insights than single-model approaches. Getting Started The agents are available now through npm. Requirements: - Node.js 16+ - Claude Code installed - No additional dependencies After installation, simply use Claude Code normally. When you ask crypto-related questions or request blockchain analysis, the appropriate agent is automatically invoked. The system handles routing, data retrieval, and response generation. Documentation covers individual agent capabilities, example queries, and integration patterns for different workflows. What This Enables With 17 specialized crypto agents, Claude Code becomes a comprehensive blockchain development and analysis environment: - Developers can audit contracts, optimize gas usage, and implement security patterns - Researchers can analyze protocols, compare yields, and assess risks - Traders can evaluate markets, identify opportunities, and manage positions - Security professionals can investigate exploits, trace funds, and assess vulnerabilities The agents provide access to blockchain data and specialized analysis that previously required multiple tools, APIs, and manual research. ghive.

Hive Intelligence

80,968 views • 10 months ago

Tools from this article earn the creator of this bot $1,000,000. I reverse-engineered it and gave you all the tools completely for free. 28 repositories. 6 layers of execution - from bot reasoning engine all the way to paper-trading strategies. On-chain proof of the $1M wallet: This bot doesn’t predict the future. It exploits inefficiencies. This is literally what separates every single top leaderboard wallet - pure math edge, not crystal ball magic. Bot brain = Claude Squad with multiple Opus agents running in parallel. Trading management = Agency Agents, a pro swarm engine that replaces an entire PhD dev team. Full data collection suite (OpenBB + Binance collector + everything else you need). All the necessary repos for trading intelligence, strategy backtesting and Polymarket API interaction are included. This isn’t some basic script anymore - this is a full quant pipeline that shows you exactly how real trading algorithms are built. Bookmark this post or you’ll lose the article. Or start making money right now - copy trades of this $1M PnL bot using copy-trading terminal:
0:33

Tools from this article earn the creator of this bot $1,000,000. I reverse-engineered it and gave you all the tools completely for free. 28 repositories. 6 layers of execution - from bot reasoning engine all the way to paper-trading strategies. On-chain proof of the $1M wallet: This bot doesn’t predict the future. It exploits inefficiencies. This is literally what separates every single top leaderboard wallet - pure math edge, not crystal ball magic. Bot brain = Claude Squad with multiple Opus agents running in parallel. Trading management = Agency Agents, a pro swarm engine that replaces an entire PhD dev team. Full data collection suite (OpenBB + Binance collector + everything else you need). All the necessary repos for trading intelligence, strategy backtesting and Polymarket API interaction are included. This isn’t some basic script anymore - this is a full quant pipeline that shows you exactly how real trading algorithms are built. Bookmark this post or you’ll lose the article. Or start making money right now - copy trades of this $1M PnL bot using copy-trading terminal:

cvxv666

56,293 views • 5 months ago