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Paid AI trading bots just got cooked,, While everyone’s paying $99/mo for bots that still need babysitting, one open-source thing on GitHub is already running real trades for free. OpenClaw🦞 (June 2026 update) lets you spin up agents that: - Copy-trade big wallets automatically - Scan viral narratives 24/7...

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Rifat Ahmed

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54,312 Aufrufe • vor 1 Monat •via X (Twitter)

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Claude will replace manual traders in 2026. New update lets you give it full control of your computer. That's why I decided to test it with $100 and total access. Asked to turn it into $1,000 on Polymarket or I shut it down. 3 hours later it was scanning every wallet on Polymarket for copy trading opportunities. It found best wallets and started testing them through this bot: At first, it lost $73 trying each wallet to understand which ones were profitable. Then it picked 7 wallets, executed copy trades automatically and did something i don't believe even now. $3,467 profit in 24 hours. Automatically. With no monitoring. What’s insane is how it works: • Claude monitors hundreds of wallets 24/7 • Evaluates win rates, market timing and sizing • Tests micro trades to find the best strategy • Executes automatically with AL and TP rules This is why AI is mandatory in 2026. Markets move faster than humans, I've been telling it for months. Your edge is speed, analysis, and execution. Anyone still clicking buttons manually will lose edge within months. I just reinvested the profits and let Claude keep copy trading. This is the future. Manual trading is probably dead FOREVER.

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HERMES JUST GOT A CHATGPT INTERFACE AND IT IS COMPLETELY FREE. No terminal. No command line. No technical setup that takes half a day to figure out. Here is what just became possible. You can now run Hermes, DeepSeek, Ollama, and OpenClaw from a single clean chat interface. Switch between them in one click. Upload files directly. Attach knowledge bases and notes. Preview code without touching the terminal once. Use it on mobile. Make voice and video calls. All of it. Free. Open source. The setup took one conversation with Hermes itself. Pasted the GitHub link in. Hermes installed Open Web UI in Docker on its own. Connected the API server and gateway automatically. A clean ChatGPT-level interface running entirely on local hardware was live in minutes. No subscription. No data leaving your machine. No API bill at the end of the month. The people who set this up this weekend will have a local AI stack that rivals what most companies are paying $2,000 a month for in cloud infrastructure. The people who wait will keep paying for tools that send their data somewhere they cannot see. Both tools are free. Both are open source. The only thing between you and this setup is the next 30 minutes. Follow CyrilXBT for the exact config, setup steps, and local AI workflows I use to run a full stack without spending a dollar on cloud inference.

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37,120 Aufrufe • vor 3 Monaten

You need to try Hermes RIGHT NOW. OpenClaw was the breakthrough. Hermes feels like the evolution. Here’s why AI power users are quietly switching: • Hermes learns from you over time • It creates its own reusable skills • Memory stays curated instead of bloated • Agents improve every 10 turns automatically • It actually feels stable on day 30 The wildest part: Hermes agents build workflows from your behavior. One user asked their agent to configure Twingate once. The agent: → learned the process → created a reusable skill → stored it for future tasks → improved its own workflow automatically That’s not prompt engineering anymore. That’s agent evolution. Meanwhile most people are still babysitting broken OpenClaw setups and manually importing marketplace skills. Hermes took a different path: Less clutter. Less tweaking. More autonomy. And it’s working. It already flipped OpenClaw in OpenRouter token usage and became one of the fastest-growing AI repos on GitHub. The bigger shift: We’re entering the era where the model matters less than the harness around it. GPT-5.5, Grok, Qwen: They’re already powerful enough. The real edge now is: • memory systems • self-improvement loops • skill creation • agent orchestration Hermes understands that. Most people still think AI agents are glorified chatbots. The people using Hermes are building AI teammates.
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You need to try Hermes RIGHT NOW. OpenClaw was the breakthrough. Hermes feels like the evolution. Here’s why AI power users are quietly switching: • Hermes learns from you over time • It creates its own reusable skills • Memory stays curated instead of bloated • Agents improve every 10 turns automatically • It actually feels stable on day 30 The wildest part: Hermes agents build workflows from your behavior. One user asked their agent to configure Twingate once. The agent: → learned the process → created a reusable skill → stored it for future tasks → improved its own workflow automatically That’s not prompt engineering anymore. That’s agent evolution. Meanwhile most people are still babysitting broken OpenClaw setups and manually importing marketplace skills. Hermes took a different path: Less clutter. Less tweaking. More autonomy. And it’s working. It already flipped OpenClaw in OpenRouter token usage and became one of the fastest-growing AI repos on GitHub. The bigger shift: We’re entering the era where the model matters less than the harness around it. GPT-5.5, Grok, Qwen: They’re already powerful enough. The real edge now is: • memory systems • self-improvement loops • skill creation • agent orchestration Hermes understands that. Most people still think AI agents are glorified chatbots. The people using Hermes are building AI teammates.

Dami-Defi

17,062 Aufrufe • vor 2 Monaten

I’M DROPPING EVERYTHING AND GOING ALL-IN ON CLAUDE Just asked him to: “Look for mispriced Polymarket markets to profit from arbitrage, and spot wallets that copy these trades” Turned $600 into $10K in one 2 day Monitored ~1k+ wallets I looked at the wallets that he scans and was shocked, here is one of them: $120 → $1.4M 1,947 trades. Win rate 55%. I just realized that there are many arbitrage bots that I can't beat without code knowledge But I can find them and copy So Claude created a monitoring terminal and copytraded found wallets using Ares copytrading. It’s not a script and not even the bot, it’s an AI agent that automatically adds top wallets to the leaderboard, and you can simply start copying them and earning. Nothing complicated: - choose a trader - choose PRIORITY MODE (the fastest bot for copytrading) - press the start button That’s all you need to consistently earn. If you’re curious about how to write your own bot, I will send you a step-by-step guide on how to create your bot from scratch. I’ve already helped more than a dozen people achieve stable income. I don’t promise huge sums, I promise stability. Just: 1. Comment the word ‘CLAUDE’ 2. Like and Retweet this post 3. Follow me Marry Evan (so that I can message you)
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I’M DROPPING EVERYTHING AND GOING ALL-IN ON CLAUDE Just asked him to: “Look for mispriced Polymarket markets to profit from arbitrage, and spot wallets that copy these trades” Turned $600 into $10K in one 2 day Monitored ~1k+ wallets I looked at the wallets that he scans and was shocked, here is one of them: $120 → $1.4M 1,947 trades. Win rate 55%. I just realized that there are many arbitrage bots that I can't beat without code knowledge But I can find them and copy So Claude created a monitoring terminal and copytraded found wallets using Ares copytrading. It’s not a script and not even the bot, it’s an AI agent that automatically adds top wallets to the leaderboard, and you can simply start copying them and earning. Nothing complicated: - choose a trader - choose PRIORITY MODE (the fastest bot for copytrading) - press the start button That’s all you need to consistently earn. If you’re curious about how to write your own bot, I will send you a step-by-step guide on how to create your bot from scratch. I’ve already helped more than a dozen people achieve stable income. I don’t promise huge sums, I promise stability. Just: 1. Comment the word ‘CLAUDE’ 2. Like and Retweet this post 3. Follow me Marry Evan (so that I can message you)

Marry Evan

19,800 Aufrufe • vor 4 Monaten

🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.
1:15

🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.

MIKE

38,108 Aufrufe • vor 1 Monat

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10 repos blowing up on GitHub this week that replace $1,500/month in AI tools 1. andrej-karpathy-skills → replaces paid Claude Code courses one CLAUDE.md file from Karpathy's LLM coding observations 48,965 stars. 7,939 stars TODAY 2. claude-mem → replaces paid context/memory tools auto-captures everything Claude does across sessions compresses with AI and injects into future sessions 59,373 stars. 1,907 stars today 3. voicebox → replaces ElevenLabs ($22/mo) open-source voice synthesis studio 18,963 stars. 887 stars today 4. open-agents → replaces paid agent platforms ($200/mo) open-source template for building cloud agents. by Vercel 3,105 stars. 735 stars today 5. cognee → replaces paid knowledge bases ($50/mo) AI agent memory engine in 6 lines of code 15,733 stars 6. magika → replaces paid file detection tools AI file content type detection. by Google 14,603 stars 7. GenericAgent → replaces paid agent infra ($100/mo) self-evolving agent. grows skill tree from 3.3K-line seed 6x less token consumption than standard agents 2,661 stars. 883 stars today 8. omi → replaces Rewind AI ($25/mo) AI that sees your screen + listens to conversations tells you what to do next 8,952 stars. 488 stars today 9. evolver → replaces manual agent optimization self-evolution engine for AI agents genome evolution protocol 3,074 stars. 866 stars today 10. wallet tracking + copy trading → Kreo tracks top Polymarket wallets. auto copies trades the only tool on this list i actually pay for because it makes more than it costs → total before: ~$1,500/month in AI subscriptions total now: $0 + Kreo like + bookmark you'll need this

self.dll

361,846 Aufrufe • vor 3 Monaten

Introducing Clips - 100% free, open source, agent-native alternative to Loom Unlike Loom, agent's can fully understand Clips just from a URL. Every Clip comes with APIs and metadata for agents to explore their contents. Agents can "see and hear" anything in a Clip - not just transcripts, but everything visually in the video at any timestamp. Easily share bug reports, feedback, analyses, or anything else in a way that you can easily pass to agents to use to improve products, reports, or more. Also unlike Loom, you own the software, so no one can jack up prices on you suddenly like Loom did to us. Clips is made to be customized. The built-in agent can customize its own code, so you can personalize the app to your needs and workflows. This, in my opinion, is the future of software. Open-source, forkable, customizable with agents, to make your own personal version of anything. You can also import Looms just from a URL and upload videos as well. I got so sick of telling people "don't send me feedback as looms, I can't pass those to agents, I need text and images" that I had to just solve this once and for all. There's a free hosted version you can use too, or fork and self host yourself. Will link to both in the replies.
0:35

Introducing Clips - 100% free, open source, agent-native alternative to Loom Unlike Loom, agent's can fully understand Clips just from a URL. Every Clip comes with APIs and metadata for agents to explore their contents. Agents can "see and hear" anything in a Clip - not just transcripts, but everything visually in the video at any timestamp. Easily share bug reports, feedback, analyses, or anything else in a way that you can easily pass to agents to use to improve products, reports, or more. Also unlike Loom, you own the software, so no one can jack up prices on you suddenly like Loom did to us. Clips is made to be customized. The built-in agent can customize its own code, so you can personalize the app to your needs and workflows. This, in my opinion, is the future of software. Open-source, forkable, customizable with agents, to make your own personal version of anything. You can also import Looms just from a URL and upload videos as well. I got so sick of telling people "don't send me feedback as looms, I can't pass those to agents, I need text and images" that I had to just solve this once and for all. There's a free hosted version you can use too, or fork and self host yourself. Will link to both in the replies.

Steve (Builder.io)

230,750 Aufrufe • vor 1 Monat

🚨 THIS GUY JUST PLUGGED CLAUDE STRAIGHT INTO HIS BROKERAGE ACCOUNT AND REBUILT $99/MO INDICATORS IN MINUTES!! No course. No bot promising 1000% gains. Not clickbait Just a dude in a flag hat wiring AI into his trading workflow from his kitchen The play: connect Claude to his account → ask it to recreate the indicators other people gatekeep and sell → done in minutes, not months It sounds like cope until you clock what actually happened: The secret strategy everyone's charging for? Rebuilt for free The locked "DM me for access" indicator? Cloned on the spot The edge was never the indicator, it's that nobody told you you could just build it Five-minute setup vs a $99/month subscription that does less. That's the whole trade His call: retail trading gets rewritten over the next 2-5 years. The ones putting in reps now eat. The ones waiting for it to get easy get left Bookmark this! The edge is now a chatbot and the will to actually use it
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🚨 THIS GUY JUST PLUGGED CLAUDE STRAIGHT INTO HIS BROKERAGE ACCOUNT AND REBUILT $99/MO INDICATORS IN MINUTES!! No course. No bot promising 1000% gains. Not clickbait Just a dude in a flag hat wiring AI into his trading workflow from his kitchen The play: connect Claude to his account → ask it to recreate the indicators other people gatekeep and sell → done in minutes, not months It sounds like cope until you clock what actually happened: The secret strategy everyone's charging for? Rebuilt for free The locked "DM me for access" indicator? Cloned on the spot The edge was never the indicator, it's that nobody told you you could just build it Five-minute setup vs a $99/month subscription that does less. That's the whole trade His call: retail trading gets rewritten over the next 2-5 years. The ones putting in reps now eat. The ones waiting for it to get easy get left Bookmark this! The edge is now a chatbot and the will to actually use it

cristal

84,063 Aufrufe • vor 1 Monat

Reachy Mini just got a new Brain! We released a fully open-source backend for talking to Reachy Mini. In the last 48 hours, 3,000+ robots have already hit the version deployed on Hugging Face's infra. Until today, if you wanted a real-time voice agent in your robot, you were looking at $20+ a day. Realtime APIs are expensive because every second the connection is up, you are being charged! But with our approach, you can run the audio models locally and use your OpenAI or Claude subscription for the LLM, at no extra costs. The audio pipeline is very efficient; in the video, it's running on the cheapest Mac mini, 16GB of RAM (the one that sold out a couple of months back when people were buying them up for openclaws setups). Tutorials coming in the next few weeks: how to run your robot fully locally, or with your favorite agent. Stay tuned!
1:50

Reachy Mini just got a new Brain! We released a fully open-source backend for talking to Reachy Mini. In the last 48 hours, 3,000+ robots have already hit the version deployed on Hugging Face's infra. Until today, if you wanted a real-time voice agent in your robot, you were looking at $20+ a day. Realtime APIs are expensive because every second the connection is up, you are being charged! But with our approach, you can run the audio models locally and use your OpenAI or Claude subscription for the LLM, at no extra costs. The audio pipeline is very efficient; in the video, it's running on the cheapest Mac mini, 16GB of RAM (the one that sold out a couple of months back when people were buying them up for openclaws setups). Tutorials coming in the next few weeks: how to run your robot fully locally, or with your favorite agent. Stay tuned!

Andi Marafioti

56,158 Aufrufe • vor 3 Monaten

💡 Most people still just HODL their Bitcoin and wait for the next pump. But what if your BTC could actually work for you instead of just sitting idle? That is where BOB comes in. BOB is a hybrid chain that takes Bitcoin's security and plugs it into Ethereum's flexibility. With BitVM and zkStack you get to use native BTC directly, no wrapped tokens or shady shortcuts. On BOB your BTC can finally move: 👉 Stake and earn yield 👉 Borrow stables when you need liquidity 👉 Trade across ETH, SOL, SUI without friction 👉 Pay instantly with BTC, no gas headaches And for builders it is a full EVM environment with account abstraction, zero gas fees and backed by Bitcoin liquidity. This is not just an experiment. BOB is becoming the real gateway for Bitcoin DeFi. Your BTC is no longer passive digital gold, it is becoming the fuel for the next wave of on-chain finance. 🚀 GBOB fam, the future is being built right now.
0:59

💡 Most people still just HODL their Bitcoin and wait for the next pump. But what if your BTC could actually work for you instead of just sitting idle? That is where BOB comes in. BOB is a hybrid chain that takes Bitcoin's security and plugs it into Ethereum's flexibility. With BitVM and zkStack you get to use native BTC directly, no wrapped tokens or shady shortcuts. On BOB your BTC can finally move: 👉 Stake and earn yield 👉 Borrow stables when you need liquidity 👉 Trade across ETH, SOL, SUI without friction 👉 Pay instantly with BTC, no gas headaches And for builders it is a full EVM environment with account abstraction, zero gas fees and backed by Bitcoin liquidity. This is not just an experiment. BOB is becoming the real gateway for Bitcoin DeFi. Your BTC is no longer passive digital gold, it is becoming the fuel for the next wave of on-chain finance. 🚀 GBOB fam, the future is being built right now.

Crypto Sinan

14,831 Aufrufe • vor 10 Monaten

i cancelled $2,000/month in trading subscriptions replaced every single one with open-source repos here's the full stack: 1. TradingView Pro ($30/mo) → lightweight-charts 14K stars. by TradingView themselves. 45KB. free 2. Bloomberg Terminal ($2,000/mo) → fredapi + Claude every macro dataset the Fed publishes. free API 3. backtest platform ($100/mo) → prediction-market-backtesting NautilusTrader fork with Polymarket + Kalshi adapters 4. real-time dashboard → polyrec terminal UI: Chainlink oracle, Binance feed, orderbook depth 70+ indicators. auto CSV logging. strategy backtester 5. bot framework (7 strategies) → Polymarket-Trading-Bot 53K lines TypeScript. arbitrage, momentum, market making, AI forecast, whale copy-trade, convergence 6. strategy reverse engineering → polybot execution + market data infrastructure. paper trading Kafka, ClickHouse, Grafana. full analytics pipeline 7. paper trading for AI agents → polymarket-paper-trader real order books. exact fee model. slippage tracking your Claude agent gets $10K paper money and trades 8. token savings → rtk CLI proxy. cuts Claude Code tokens by 60-90% Rust. single binary. 10 AI tools supported 9. Claude Code itself ($200/mo) → goose 35K stars. by Block (Jack Dorsey). Rust works with any LLM. full agent loop. free 10. wallet tracking + copy trading → Kreo track top Polymarket wallets. auto copy trades the only tool on this list i actually pay for because it makes more than it costs total before: ~$2,600/month total now: $0 + Kreo bookmark this. you'll need it
0:49

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

self.dll

803,521 Aufrufe • vor 4 Monaten

You're Still Manually Trading in 2026. That's Why You're Broke. Everyone who's making money in markets right now built their own OpenClaw AI bots months ago. You're still staring at charts. I've made the exact step-by-step guide to build your own AI trading bots + indicators. No coding. Free. Giving it Free for 24 hours, To get it: 1. Comment "OpenClaw" 2. Like and Retweet 3. Follow me Himanshu Kumar (so i can DM you) While you're paying $200/month for some random guy's signals that don't work, people with zero coding skills are building their own bots in 30 minutes using ChatGPT. You don't need to code. You don't need experience. You just need to stop doing what's clearly not working. > Turn any TradingView indicator into a full strategy > AI indicators for scalping and day trading > Backtest everything before risking a single dollar > Works for forex, crypto, stocks Stop buying courses. Stop paying for signals. Stop watching others make money. Full video tutorial attached. This is the only guide you need. You Must Follow me Himanshu Kumar, so i can send you DM. Save this post to make sure you don't miss this one.
25:45

You're Still Manually Trading in 2026. That's Why You're Broke. Everyone who's making money in markets right now built their own OpenClaw AI bots months ago. You're still staring at charts. I've made the exact step-by-step guide to build your own AI trading bots + indicators. No coding. Free. Giving it Free for 24 hours, To get it: 1. Comment "OpenClaw" 2. Like and Retweet 3. Follow me Himanshu Kumar (so i can DM you) While you're paying $200/month for some random guy's signals that don't work, people with zero coding skills are building their own bots in 30 minutes using ChatGPT. You don't need to code. You don't need experience. You just need to stop doing what's clearly not working. > Turn any TradingView indicator into a full strategy > AI indicators for scalping and day trading > Backtest everything before risking a single dollar > Works for forex, crypto, stocks Stop buying courses. Stop paying for signals. Stop watching others make money. Full video tutorial attached. This is the only guide you need. You Must Follow me Himanshu Kumar, so i can send you DM. Save this post to make sure you don't miss this one.

Himanshu Kumar

54,599 Aufrufe • vor 4 Monaten

ANTHROPIC IS PREPARING TO RELEASE CLAUDE RS - AN AUTOMATED TRADING BOT FOR POLYMARKET Having already automated S&P500 and SPX trading , the company is now making its move into the crypto space. One standout case: a Polymarket bot that grew $1.98 into $1,031,000 over just 4 months. The account behind -> [BoneReader]: -> Mirror its trades like Claude does here: Just add his wallet and start earning: 0xd84c2b6d65dc596f49c7b6aadd6d74ca91e407b9 Here's the breakdown of how it operates: // --> The system tracks hundreds of wallets around the clock. --> It analyzes win rates, entry timing, and position sizing. --> Small test trades are run to identify the most effective strategy. --> Everything is executed automatically with pre-set SL and TP levels. // This is exactly why AI is no longer optional in 2026. Markets move at a pace no human can keep up with and I've been saying this for weeks ngl. Your real advantage lies in speed, deep analysis, and flawless execution. Anyone still trading manually will find their edge gone within months. This is where everything is headed imo. Manual trading is most likely dead and it's not coming back. Like, comment, retweet and I'll drop you an open GitHub link to a similar bot that helped me pull in $2,660 in just 5 days. Follow me so I can DM you directly. Also don't forget to SAVE THIS ALPHA.
0:20

ANTHROPIC IS PREPARING TO RELEASE CLAUDE RS - AN AUTOMATED TRADING BOT FOR POLYMARKET Having already automated S&P500 and SPX trading , the company is now making its move into the crypto space. One standout case: a Polymarket bot that grew $1.98 into $1,031,000 over just 4 months. The account behind -> [BoneReader]: -> Mirror its trades like Claude does here: Just add his wallet and start earning: 0xd84c2b6d65dc596f49c7b6aadd6d74ca91e407b9 Here's the breakdown of how it operates: // --> The system tracks hundreds of wallets around the clock. --> It analyzes win rates, entry timing, and position sizing. --> Small test trades are run to identify the most effective strategy. --> Everything is executed automatically with pre-set SL and TP levels. // This is exactly why AI is no longer optional in 2026. Markets move at a pace no human can keep up with and I've been saying this for weeks ngl. Your real advantage lies in speed, deep analysis, and flawless execution. Anyone still trading manually will find their edge gone within months. This is where everything is headed imo. Manual trading is most likely dead and it's not coming back. Like, comment, retweet and I'll drop you an open GitHub link to a similar bot that helped me pull in $2,660 in just 5 days. Follow me so I can DM you directly. Also don't forget to SAVE THIS ALPHA.

slash1s

154,546 Aufrufe • vor 4 Monaten

how to build the fastest Polymarket latency bot +$100k/month PnL if you hit 1,000+ trades/day cleanly 0x8dxd is just a latency bot that farms the 200–500ms gap between Binance moving and Polymarket waking up. the part that matters isn't some alpha model, it's reading spot first and hitting the book before odds adjust.​ where the $100k+/month comes from it's not one massive bet. it's clipping tiny edges thousands of times. 0x8dxd started with $313 and ended month one around $438k, now sits north of $550k all‑time PnL with ~5.6k–7k trades at 96–98% win rate on BTC/ETH/SOL 15‑minute windows.​ if you're consistently pulling 1–2% per cycle over 1,000+ trades/month with real size, six figures is just arithmetic.​ first, the edge: spot (Binance/Coinbase) moves first, Polymarket's 15‑minute up/down windows lag by 200–500ms before odds fully reprice. latency bots live in that window: spot already moved, book still thinks it's 50/50, bot fixes the misprice and takes the edge.​ what you actually need: - Python + official py‑clob‑client to prove the idea, Rust CLOB client if you want to compete with 0x8dxd‑level bots.​ - WebSocket feeds for BTC/ETH/SOL from Binance/Coinbase (REST polling is too slow).​ Dedicated Polygon RPC node so your orders don't die in public rate limits.​ - VPS physically close to Polymarket's infra (ping is literally part of your edge).​ where people mess up: they try "HFT" from a laptop with Python + public RPC and wonder why their 300ms reaction gets farmed by a 30ms Rust engine.​ the bot loop (in plain English) pull real‑time spot for BTC/ETH/SOL via WebSocket, track short‑term % moves over a few seconds.​ for each 15‑minute crypto market on Polymarket: check if spot moved beyond your threshold (e.g. ±2%) while Polymarket odds barely changed.​ if BTC rips and the "down" contract is still priced like a coinflip, load NO at stale odds. if BTC nukes and "up" is still fat, fade that with NO or take YES on "down" depending on the market structure.​ log market, entry odds, exit odds, realized edge. that's it. no AI, no news scraping, just enforcing what spot already told you.​ where to get real references: Finbold/MEXC breakdowns: exactly how a bot took $313 to $438k on Polymarket using BTC 15‑minute windows and latency between spot and odds.​ BlakeNastri's X thread: dug through 0x8dxd's stats, ~5.6k trades and ~96%+ win rate, called it latency arbitrage not insider magic.​ two real‑world gotchas (that decide profit vs loss) edge decay: as more bots pile in, the 200–500ms lag shrinks and your edge turns into noise. research on Polymarket shows arbitrage bots already extracted tens of millions.​ self‑slippage: once you scale to real size, you start moving the book yourself - without proper sizing and staggering, you donate your edge back to the market.​ how to make it feel "pro" fast run only on high‑volume crypto windows: (BTC/ETH/SOL 15‑minute) where size actually fills and you can hit 1,000+ trades/month without breaking the market.​ start with tiny tickets ($20–50 per trade), prove the edge over thousands of logs with fees and slippage included, only then scale size not risk per trade.​ use official libs and known clients as your backbone, treat random "Polymarket bot" repos as hostile until you audit them - there are already GitHub bots caught stealing keys
0:21

how to build the fastest Polymarket latency bot +$100k/month PnL if you hit 1,000+ trades/day cleanly 0x8dxd is just a latency bot that farms the 200–500ms gap between Binance moving and Polymarket waking up. the part that matters isn't some alpha model, it's reading spot first and hitting the book before odds adjust.​ where the $100k+/month comes from it's not one massive bet. it's clipping tiny edges thousands of times. 0x8dxd started with $313 and ended month one around $438k, now sits north of $550k all‑time PnL with ~5.6k–7k trades at 96–98% win rate on BTC/ETH/SOL 15‑minute windows.​ if you're consistently pulling 1–2% per cycle over 1,000+ trades/month with real size, six figures is just arithmetic.​ first, the edge: spot (Binance/Coinbase) moves first, Polymarket's 15‑minute up/down windows lag by 200–500ms before odds fully reprice. latency bots live in that window: spot already moved, book still thinks it's 50/50, bot fixes the misprice and takes the edge.​ what you actually need: - Python + official py‑clob‑client to prove the idea, Rust CLOB client if you want to compete with 0x8dxd‑level bots.​ - WebSocket feeds for BTC/ETH/SOL from Binance/Coinbase (REST polling is too slow).​ Dedicated Polygon RPC node so your orders don't die in public rate limits.​ - VPS physically close to Polymarket's infra (ping is literally part of your edge).​ where people mess up: they try "HFT" from a laptop with Python + public RPC and wonder why their 300ms reaction gets farmed by a 30ms Rust engine.​ the bot loop (in plain English) pull real‑time spot for BTC/ETH/SOL via WebSocket, track short‑term % moves over a few seconds.​ for each 15‑minute crypto market on Polymarket: check if spot moved beyond your threshold (e.g. ±2%) while Polymarket odds barely changed.​ if BTC rips and the "down" contract is still priced like a coinflip, load NO at stale odds. if BTC nukes and "up" is still fat, fade that with NO or take YES on "down" depending on the market structure.​ log market, entry odds, exit odds, realized edge. that's it. no AI, no news scraping, just enforcing what spot already told you.​ where to get real references: Finbold/MEXC breakdowns: exactly how a bot took $313 to $438k on Polymarket using BTC 15‑minute windows and latency between spot and odds.​ BlakeNastri's X thread: dug through 0x8dxd's stats, ~5.6k trades and ~96%+ win rate, called it latency arbitrage not insider magic.​ two real‑world gotchas (that decide profit vs loss) edge decay: as more bots pile in, the 200–500ms lag shrinks and your edge turns into noise. research on Polymarket shows arbitrage bots already extracted tens of millions.​ self‑slippage: once you scale to real size, you start moving the book yourself - without proper sizing and staggering, you donate your edge back to the market.​ how to make it feel "pro" fast run only on high‑volume crypto windows: (BTC/ETH/SOL 15‑minute) where size actually fills and you can hit 1,000+ trades/month without breaking the market.​ start with tiny tickets ($20–50 per trade), prove the edge over thousands of logs with fees and slippage included, only then scale size not risk per trade.​ use official libs and known clients as your backbone, treat random "Polymarket bot" repos as hostile until you audit them - there are already GitHub bots caught stealing keys

0xCryptoGirl

25,454 Aufrufe • vor 7 Monaten

At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.
2:38

At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

Tykoo

25,535 Aufrufe • vor 8 Monaten