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Chicago HFT engineer pulled $190,492 in 24 days running Markov chains, Monte Carlo simulations and Claude as the brain - out of a $6 server in his bedroom. His old firm walked him out on May 1st for building it on company time. They didn’t like that. Nobody would...

22,376 次观看 • 5 天前 •via X (Twitter)

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An engineer at a Chicago HFT shop spent six years building latency arb pipes between CME and NYSE. On May 1st his desk got cut. Severance: $40K. He deposited $3000, ran a Hermes trading agent on Polymarket, and pulled in $236,913 over the next 23 days. His agent wallet: The pit taught him one thing - find where one venue knows something another doesn't, size to the gap, exit before the spread closes. So he made 757 trades a day. Not 7. Not 75. And let the rest expire. Here's the actual stack. Claude Opus 4.7 reads spot momentum off Chainlink, scores every 5-minute BTC market by Markov persistence × Kelly edge Then surfaces the windows where Polymarket hasn't priced in what Binance and Coinbase already confirmed. Hermes Agent by NousResearch executes. A $10/mo Hetzner VPS runs it 24/7. Telegram pings on every fill. Total cost: $10/month. Setup: 30 minutes. No coding. One trade on May 14: Bitcoin Down at 9AM ET. Market said 15.8¢. He put $1,681 on Down. It hit. +$8,974. A 533% return in 47 minutes. The real edge is the nightly self-learning loop. Every midnight, Opus reads the day's trade journal and rewrites MIN_PROB and MIN_EDGE in the .env file. May 2nd the threshold was 0.87. May 12th 0.89. May 23rd 0.91. The bot tightens with the regime. His version of the bot has rewritten itself 187 times in 23 days. The desk that cut him couldn't ban him from Polymarket. The bot doesn't sit in the colo. It doesn't need a leased line. It just reads two endpoints and presses a button. Save this if you want to dig in and understand Hermes. Or just copy this guy trades using TG bot - his algorithm has been perfected 187 times:

cvxv666

38,535 次观看 • 3 个月前

A blackjack dealer in Macau got blacklisted from the VIP rooms last spring for counting cards. By August he couldn't get a floor job at any property in Cotai. So he deposit $500, ran a Hermes trading agent on Polymarket and pulled in $881,319 over the next 14 months. His wallet: The casinos taught him one thing - count, size your bet to your edge, walk away when the edge is gone. So he makes 5 trades a day. Not 50. Not 500. Five. And waits for the rest. Here's the actual stack. Claude Opus 4.7 reads the order book nightly, scores every threshold market by Markov persistence x Kelly edge, and surfaces the 2-3 mispriced ones. Hermes Agent by NousResearch executes. A $10/mo Hetzner VPS runs it 24/7. Telegram pings on every fill. Total cost: $10/month. Setup: 30 minutes. No coding. One trade in April: Will Bitcoin reach $90,000? Market said 1.2¢. He put $3,088 on Yes. It hit. +$123,196. A 3,988% return on a single position. The real edge is the nightly self-learning loop. Every midnight, Opus reads the day's trade journal and rewrites MIN_PROB and MIN_EDGE in the .env file. Last week the threshold was 0.87. This week 0.89. Next week maybe 0.91. His version of the bot has rewritten itself 412 times in 14 months. The Macau syndicate couldn't ban him from Polymarket. The bot doesn't sit at a table. It doesn't show a passport. It just hunts the tails. Save this post - if you want to build something of your own based on Hermes. Or just start copying algorithm that has improved itself 412 times:

cvxv666

208,552 次观看 • 3 个月前

Someone just posted the full blueprint for an AI swarm that does the job of a 200-person quant research team. Six agents. Running 24/7. Finding brand-new alpha while you sleep. Citadel needs 100 PhDs to do this. Two Sigma needs 200. This does it with six bots and one laptop. Two ways to play this - spend a weekend building your own swarm, or copy the wallet of one that's already up $2M: Boris Cherny runs Claude Code at Anthropic. Two weeks ago he said: "I don't prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops" Alpha research is just a pipeline. So instead of sitting in it, you hand each stage to its own agent: > one reads every new research paper overnight and pulls out the trade idea > one builds the features and cleans the data > one backtests it over 20 years, costs and slippage included > one runs the hard stats and kills anything overfit > one checks it still works in every market regime > one strips out plain momentum and value to see if any real edge is left Each of those six is a job a fund pays a $600,000-a-year quant to do. He runs all six for the price of an API bill. The rule that makes it work: the agent that builds a signal never gets to approve it. A separate, stronger agent tries to kill it first. Whatever survives all six by morning is real, new alpha. One trader's already running this exact swarm on Polymarket. That $2M wallet is public, every trade on-chain. The full build is in the post below - six agents, the tool that runs them, and the five mistakes that kill most people. Bookmark & read this before it's buried.

cvxv666

103,734 次观看 • 1 个月前

A fired Jane Street quant walked out with 10 years of private BTC trading data. Turned it into $1.5M. He did not build a bot. He built a simulator that runs every move Bitcoin can make before it makes one. I found his wallet. Been copying him for a week. PnL prints like clockwork. Here is what he actually built. A swarm of agents feeds 10 years of stolen tick data into MiroFish. A god-tier agentic simulator. It does not forecast the next candle. It spins up a virtual market and plays Bitcoin forward through thousands of scenarios at once. Six agents each validate their own call. A trade only fires when they converge. They collect data 24/7, rerun the sim, and remember every pattern, every reaction, every signal they have ever seen. He does not predict the future. The math already knows it. He just reads the numbers and takes the money. Here is the part firms do not want public: MiroFish just broke algo trading. The desks are quietly building their own simulators right now. The window where one solo wallet can run this is still open. Barely. I rebuilt his approach using Claude. One prompt. Fed it the same framework. Let it run. The agent monitors his wallet 24/7. Copies every position in real-time. No delay. No guessing. Just mirror and profit. You only need Claude + device + 1 hour to deploy. Giving this free for 24 hours. To get it: 1. Comment the word "QUANT" 2. Like and retweet this post 3. Follow me Himanshu Kumar so I can DM you Save this post. Build the copytrading system this week. Start with $200. Scale on evidence.

Himanshu Kumar

63,419 次观看 • 2 个月前

THIS WALLET STACKED $230K ON BTC UP/DOWN BETS. THE BLUEPRINT TO AUTOMATE THE SAME EDGE WITH CLAUDE The wallet is $230K all-time, every position a Bitcoin or Ethereum Up or Down market It never guesses direction. It enters only when the math and the market disagree THE STRATEGY: BTC moves are not fully random. When the market enters a committed directional state, continuation is measurable. That is Markov persistence Entry signal: > Δ = p̂ − q ≥ ε Model probability minus market price. Enter only on a 5% gap or more Persistence filter: > p(j*,j*) ≥ 0.87 Only trade states with 0.87 persistence or higher. Below that, skip. This is what holds the win rate above 65% with zero directional guessing Payout: > r = (1 − q) / q At q = 0.647 that is +54.5% a win. At q = 0.441, +126.7%. Lower entry price, bigger asymmetry Sizing: > f* = p − (1−p)/b Kelly. At p = 0.87, b = 0.647, f* ≈ 0.71. Size to the edge, never to gut HOW TO BUILD IT WITH CLAUDE: What separates this from a static bot: Claude reads its own trade journal every night and rewrites its own thresholds 1. Take an open-source Polymarket bot repo as your base logic. Feed it to Claude and have it migrate to CLOB v2: py_clob_client_v2, Safe wallet support, fee-aware evaluation 2. Hard-code the filters. Enter only when Δ ≥ 0.05 and p(j*,j*) ≥ 0.87. Apply Kelly on every fill. 3. Run DRY_RUN first. Log every signal, entry price, Markov state, and simulated P/L. No real money until the numbers hold for days 4. The nightly loop. Claude reads the journal, finds which persistence states actually won, adjusts MIN_PROB and MIN_EDGE, ships tomorrow's rules. The agent is sharper after 50 to 100 trades THE SETUP: Claude Opus as the brain. An open-source repo as the starting logic. A Polygon wallet with $50 to $100. Telegram for the morning report Start at $1 to $2 per trade while it learns. Scale only when the dry runs and the live fills line up 17,000 trades compound a thin edge into six figures. The model finds the edge. The nightly loop keeps it sharp Bookmark before you point a bot at your first window

Yarchi

22,966 次观看 • 3 个月前

A 29-year-old sales consultant from China quit his job and now makes in 2 weeks what his boss earns all year. $306,000 profit last month. He replaced an entire quant team with Claude and 6 AI agents. Built his own ETH price simulation engine. Generating $15,000+ per day on autopilot. I reverse-engineered his system. One Claude prompt. 90 minutes. Fully autonomous. Giving this free for 24 hours. To get it: 1. Comment 'AGENT' 2. Like and retweet this 3. Follow Marry Evan so I can DM you His wallet: 0x06dc51826bc524d9a83770e7de9dd7e005b0452 on Polymarket. Almost nobody is watching. What the 6-agent swarm actually does: → Each agent validates its own trading decisions independently → Collects data 24/7 across markets → Runs continuous ETH price simulations in MiroFish engine → Memorizes every pattern, market reaction, trading signal → Detects market inefficiencies in real-time → Executes when edge appears → No human input required Not prediction. Pure math exploiting market lag. The coverage and speed beat top-tier trading teams. Every trade is a perfect cycle. Every dollar is extracted from pricing gaps that disappear in seconds. The system does not guess the future. It reads the numbers correctly and takes the money before markets reprice. The edge exists right now. It won't in 6 months when everyone runs similar systems. You only need: Claude + a device + 1 hour to deploy. Save this post. Build the agent swarm this week. Start with $100. Scale on evidence.

Marry Evan

19,080 次观看 • 2 个月前

A 29-year-old sales consultant from China quit his job. Now making 2 weeks what his boss earns all year. $306,000 profit last month. He replaced an entire quant team with Claude and 6 AI agents. Built his own ETH price simulation engine. Generating $15,000+ per day on autopilot. I reverse-engineered his system. One Claude prompt. 90 minutes. Fully autonomous. Giving this free for 24 hours. To get it: 1. Comment AGENT 2. Like and retweet this 3. Follow Himanshu Kumar so I can DM you His wallet: 0x06dc51826bc524d9a83770e7de9dd7e005b0452 on Polymarket. Almost nobody is watching. What the 6-agent swarm actually does: → Each agent validates its own trading decisions independently → Collects data 24/7 across markets → Runs continuous ETH price simulations in MiroFish engine → Memorizes every pattern, market reaction, trading signal → Detects market inefficiencies in real-time → Executes when edge appears → No human input required Not prediction. Pure math exploiting market lag. The coverage and speed beat top-tier trading teams. Every trade is a perfect cycle. Every dollar is extracted from pricing gaps that disappear in seconds. The system does not guess the future. It reads the numbers correctly and takes the money before markets reprice. The edge exists right now. It won't in 6 months when everyone runs similar systems. You only need: Claude + a device + 1 hour to deploy. Save this post. Build the agent swarm this week. Start with $100. Scale on evidence.

Himanshu Kumar

12,345 次观看 • 2 个月前

I made $18,300 in 30 days copying David's wallet on Polymarket. Trump's crypto advisor aka "Czar" wallet is insider trading on Polymarket. This wallet knows in advance when Trump will mention crypto. $187K profit. 90% win rate. I've made the exact guide to auto copy-trade his wallet. Could've sold for $999. Giving It Free for 24 hours. Comment "Wallet" + Retweet + Save This Post. You Must Follow me Himanshu Kumar, so i can send you DM. The play is stupid simple. He sits in meetings before every Trump appearance. He sees the speech draft. Then he opens Polymarket and bets on what Trump's about to say. Mentions of "Bitcoin." Mentions of "stablecoin." Mentions of "regulation." He bets "Yes" before the speech. Trump says the word. "czar" cashes out. $30K-$50K per public appearance. Every single time. His Polymarket Wallet: EscalateFund The numbers are insane: > 90% win rate in the mentions category > Longest win streak: 51 trades in a row > $187K total profit > Active in every Trump-adjacent market Bookmark his wallet. If this guy bets Trump will say something, Trump will definitely say it. Pro tip: skip his NBA trades. Dude yolos on his favorite team and they lose every time. You're trying to predict Trump from his Truth Social posts. Sacks is hearing the speech draft 6 hours before it goes live. You can't out-research that. But you can copy it. Follow me Himanshu Kumar, to stay connected for more post on making money with ai Disclaimer: For educational purposes only. I’m not making claims about any person, only about the wallet activity. This is real, and it’s happening.

Himanshu Kumar

17,112 次观看 • 3 个月前

how to set up hermes agent step by step. built-in memory, 40+ tools, works on your phone, and what to think of hermes vs openclaw: 1. hermes is a personal AI agent that runs in your terminal. think of it like open claw but with built-in memory, 40+ tools out of the box, and 90% cheaper token costs. you install it with one command. 2. the 3 problems with open claw that hermes solves: no memory (you keep repeating yourself), constant gateway restarts, and zero visibility into what you're spending on tokens. 3. hermes remembers everything. every completed task gets saved to memory. it searches through past logs to find solutions. over time it literally gets smarter at your specific workflows. 4. connect it to open router. you see exact costs per model per task. free models rotate weekly. one founder went from $130 every five days on open claw to $10 on hermes. same output. 5. it comes preloaded with skills. apple notes, imessage, find my, browser, web search, image generation, cron jobs. no hunting for plugins. 6. connect it to obsidian so it reads your entire vault. connect it to gstack for your dev environment. create custom skills for your specific workflows. 7. the biggest money saver: have it write code once for recurring tasks. then it runs without burning tokens every time. stop paying an LLM to do the same scrape or report daily. 8. run it on android via telegram. name your agents. talk to them like coworkers. in this episode imran shows you how to set this up. 9. you can run it bare metal, in docker, or serverless on modal. pick your risk level. i begged imran to come on The Startup Ideas Podcast (SIP) 🧃 and walk through the full installation live. he made it impossibly clear. if you've heard of Hermes Agent and want the clearest explanation of how to get set up like a pro let me know what you want me to cover on the next ep this is the best personal agent setup video on the internet right now. watch

GREG ISENBERG

622,600 次观看 • 4 个月前

An Anthropic safety researcher closed her laptop when she saw my screen at Philz Coffee. I was running my Polymarket bot from the corner table. She was in line. Looked over my shoulder. Stopped moving. That is not a normal trading app. What model is that running on? I told her. Claude Code. Four repos. $25 a month. She sat down without asking. I work on the alignment team. We test Claude for exactly this kind of autonomous behavior. You are letting it find its own trading signals. Not just signals. Wallets. github/warproxxx/poly_data 86 million trades. Every wallet. Every entry. Every exit. You are feeding Claude raw wallet data and letting it identify which traders consistently win. Then cloning their behavior. She said it slowly. Like she was writing an internal report in her head. Claude Code finds the top wallets. Reverse-engineers their timing. Copies their entries. Then exits before they do. Before they do? My bot cuts at 85% of expected move or on a 3x volume spike. Top wallets exit before resolution 91% of the time. They capture 86% of the move. Losers hold to 58%. She put her coffee down. How did you get Claude to learn exit timing on its own? I showed her the second repo. github/Polymarket/polymarket-cli Three commands. 500+ markets. No API key. Claude scores them in 20 minutes. We have 14 people stress-testing Claude's autonomous capabilities. You are just using them. My setup: Claude API: $20 per month VPS: $5 per month poly_data: free polymarket-cli: free 19 days. 4 agents. 74% win rate. She stared at the screen for a long time. This is literally what our red team simulates. Except you actually deployed it. She emailed me two days later. Our policy team found your post. Please take it down. Too late. I built the entire framework: How to connect Claude Code to poly_data wallet analysis How to configure autonomous exit timing at 85% threshold How to deploy polymarket-cli for market scoring How to run 4 parallel agents on a single VPS How to start with $500 and scale on evidence The system runs 24/7. Finds proven wallets. Copies their timing. Exits before the crowd. No prediction. No guessing. Just wallet cloning. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word MoneyBot 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you Save this post. Deploy the wallet cloning system this week. Start with $500. Scale on evidence.

Himanshu Kumar

23,186 次观看 • 2 个月前

HERMES AGENT LEARNS FROM ITS OWN MISTAKES. UPDATES ITS MEMORY. CREATES ITS OWN SKILLS. NO CLOUD. EVERYTHING STORED LOCALLY. THIS IS HOW THE SELF-IMPROVING LOOP WORKS. most agents start from zero every session. Hermes carries forward what it learned. THREE MEMORY SYSTEMS: 1. PROCEDURAL MEMORY (how to act) stored in ~/.hermes/skills/ as SKILL.md files. when the agent repeats a complex workflow, it saves the procedure as a reusable skill. next time the same task comes up, it follows the skill instead of figuring it out again. you can also create skills explicitly: "create a skill called video-prep that captures how I format my video scripts. spoken english, define jargon inline, no em-dashes, close with a catchphrase." the agent writes the SKILL.md. available as a slash command from that moment. Hermes ships with 90+ skills. the number grows the longer you use it. 2. SEMANTIC MEMORY (durable facts about you) stored in ~/.hermes/memory/memory.md the agent scans conversations for facts worth remembering. preferences, habits, corrections, project details. real example from the video: agent tried to scrape a YouTube channel. URL was wrong. it failed. it updated memory.md with the correct URL pattern so it never makes the same mistake again. you can also save explicitly: "save to memory that my favorite testing framework is pytest" the agent updates memory.md immediately. this file loads into context on every session. the agent knows you better every week. 3. EPISODIC MEMORY (chat history) stored in ~/.hermes/state.db (local SQLite). every conversation. every tool call. every result. searchable with FTS5 full-text search. "search our past sessions. what was the first thing I ever said to you?" the agent queries state.db and finds it. over time, auxiliary models consolidate episodic memory into semantic memory. distilling recurring patterns into durable facts. THE SELF-IMPROVING LOOP: every agent run follows this cycle: → you send a prompt → working memory loads: SOUL.md + memory.md + relevant skills + chat history → agent calls tools (terminal, browser, delegate_task) → agent completes the task, replies to you → AFTER the reply: agent checks "did I learn something worth saving?" → if yes: updates memory.md or creates a new skill → next session starts smarter than the last this happens automatically. you don't ask the agent to learn. it decides what to remember on its own. WHAT MAKES THIS DIFFERENT FROM CLAUDE CODE: Claude Code has memory too. but Hermes stores everything locally. no cloud. your data never leaves your machine. Claude Code doesn't auto-create skills from experience. Hermes turns repeated workflows into reusable procedures. Claude Code memory is instruction-based. Hermes memory is conversational and self-updating. over months of usage, Hermes builds a knowledge base of your preferences, your projects, your mistakes, and the procedures that work for your specific workflow. the agent that remembers your birthday also remembers why your last deploy failed. NO EMBEDDINGS. PLAIN TEXT. Hermes does not use embeddings or RAG for memory. skill and memory search runs on plain text keyword matching. simpler. faster. no vector database to maintain. works entirely offline on your local machine. DELEGATE TO CLAUDE CODE: Hermes can spawn a sub-agent that runs Claude Code in headless mode: "spawn a sub-agent using Claude CLI to build a Python script that fetches the top 5 Hacker News stories to markdown." Hermes delegates. Claude Code writes the code. result returns to Hermes. Hermes runs the script and delivers the output. use Hermes for orchestration. use Claude Code for heavy coding. both tools. not competitors. WHAT HERMES DOES NOT HAVE: no built-in eval or LMOps system. no LangSmith, no LangFuse integration out of the box. trajectory export and logs exist but there is no automated quality tracking. if you need eval, build it yourself or connect external tools. the loop is self-improving. measuring how well it improves is on you. comment LOOP and I'll send you the configs that control how fast Hermes learns and what it remembers. memory limits, skill auto-creation triggers, and the auxiliary model that runs the learning. Replace your entire team with 8 hermes agents👇

YanXbt

22,720 次观看 • 1 个月前