no0x

this should be illegal. A student from Shanghai put 6 AI tools into one team and told them: “make money while I’m at work.” zero prompts after 8am. just boxes and unloading. opus 5.5 — CEO. Grok Bot — finds pain points on X. REA — checks prices in 3 minutes. Jev — builds and ships on autopilot. Obsidian — memory. Dots — connects all 6 into one flow. budget: $20. deadline: 12 hours. rule: only message me if you need money. at 08:14 they found 640 small shops begging for one thing: someone to reply to DMs at night. 3 hours later REA confirmed every existing tool starts at $49/mo and 71% of reviews say “too complicated.” opus cut the idea down to one feature, one price: $12/month. by 16:20 Jev had built the bot, landing page, and checkout. Grok sent a 20-second demo to 300 shop owners. at 19:55 Obsidian dropped the report. I got home to 47 paying shops × $12 = $564/mo. recurring. from a 12-hour test. total cost: $17.40. they only messaged me once — asked for $2 for a second domain. I said no. they found a free way. people still use AI like a search bar. I used it like a team with a boss, a budget, and a deadline. while I was carrying boxes — it took a second job for me.

Why is no one talking about this? I built a $0 digital Chief of Staff and gave it one non-negotiable rule: “Find me $80,000 a month in new contracts or you’re fired.” I went to sleep. By morning it had a complete plan waiting for me. A SpaceX engineer said something that hit 13M+ views: “I have a Chief of Staff agent. He tracks all my other bots and manages everything.” A human exec costs ~$350k a year. Mine runs on a cloud neural engine while my laptop is off. I set the target. It handles the execution. I only do final approval. The hard rule: “Find $80k/month in new deals. Public sources only. Contact nobody without my explicit yes.” What it did overnight: → 8pm — Split the task into 6 blocks and set time slots. I wrote zero code. → 10pm — Pulled 450 private medical clinics in Seattle and cut out the big chains. → Midnight — Analyzed the rest and picked 40 strongest leads with unique notes on each. → 1:30am — Wrote personalized outreach emails for every one. Sent: 0. → 3am — Built a one-page offer with real numbers. Price left blank. → 7:30am — I manually put $2,000/month. 40 × $2k = $80k potential on the table. The blank price is the most important part. When AI guesses your pricing, you lose deals. It repeats this every Monday → ~180 new prospects a month on autopilot. 450 clinics → 40 targets → 1 offer → $80k potential → 0 sent without approval. In 15 seconds it drops the document with a blank price tag. While you’re still thinking about it, someone else’s AI CoS is already mapping businesses in your city. Full setup structure is free below ↓

I don’t understand why everyone still isn’t doing this Claude + REA opens any program on your computer and shows how every function actually works — down to the exact line of code. No more trusting docs or someone else’s word. You verify it yourself. 3 steps: → Install REA inside Claude Code with one command → Pick the program you use and the function you want to understand → Send Claude this: “Use REA to find out how this function actually works. Show me the evidence from the code, then build my own version and test it.” After that you’re not guessing anymore. You see what’s happening under the hood. Try it tonight on the program you trust the most. You might not like what you find 🔥 Article here — save it 👇

this grok + jev terminal could make $17k in a single night the whole desk runs on four layers at once: social signal scraping, on-chain validation, technical filters and fully automated execution — all inside one trading terminal built for speed grok watches the chatter across x, telegram, discord and reddit in real time jev handles the quant side: liquidity depth, order flow, entry timing, position sizing and execution risk locked at 15% of the pool •5 social platforms feeding the crawler •11 smart wallets flagged in the token diagnostics •$860k in visible dex liquidity •34 fills tracked by the execution panel •0% buy and sell tax shown in the terminal •balance curve moving from $48.7k to $57.1k on day 12 spot the clean setup keep the downside tight let the execution engine do the rest

It is becoming f*cking dangerous. Thanks to this exact setup, I automated my work and generated $13,900 two months back Andrej Karpathy (OpenAI co-founder) blew up with 24M views on a simple shift: quit using AI just to write code — start using it to build a second brain. Point Claude Code at a folder, drop any PDF, transcript or article inside, and it turns everything into a living wiki that gets smarter every time you add more. Setup in under 5 minutes: 1. Make an Obsidian vault and open it with Claude Code 2. Paste Karpathy’s wiki prompt and let Claude generate the structure 3. It creates three folders: raw (your sources), wiki (the pages) and CLAUDE.md (the config) 4. Throw files into raw and type “ingest this” 5. Then just ask questions — your entire knowledge base stays searchable forever Do this once and stop starting from a blank chat. Full guide below.

Why is no one talking about this? An 18-year-old in Shenzhen just built a team of AI agents with Claude Code. No investors. No employees. No degree. Now it earns him $10,000 every month. It works 24/7, never asks for a day off, and saves him 40+ hours a week. His secret? He didn't start from scratch. He used REA to reverse engineer how paid apps work, wrote the behavior down as a spec, and let his agents build his own version. Then he stacked skills on top: Superpowers, Systematic Debugging, Skill Creator. Investigate → Spec → Build → Verify. One evening of setup. A team that never sleeps. Meanwhile most people are still paying monthly for software already sitting on their disk. I put the full 6-step protocol and copy-paste prompts in the article above 👆 I still don't understand why everyone isn't doing this.

Why is no one talking about this? You're paying monthly for apps whose features are already sitting on your disk. REA (Reverse Engineer Anything) is an open-source MCP server that lets Claude Code read desktop apps, websites, APKs and .NET games. Locally. Every answer comes with evidence: the file, the function, and what's still unknown. Every locked app is just a puzzle in chains. REA hands your agent the solution. Closed source used to mean "you'll never know." Now it means "show me the evidence." The part most people miss is the full loop: Investigate → Spec → Build → Verify Add Superpowers, Frontend Design, Systematic Debugging, Context Optimization and Skill Creator, and your agent carries it all the way to a finished product. The legal line is simple: study the original, ship your own. Full one-evening protocol and copy-paste prompts in the article below

Why is no one talking about this? Everyone's chasing faster bots. The real edge is the boring part: the system that keeps your bot alive at 3 a.m. This guide nails it. The trading engine is plain code. The AI never touches the hot path and never holds a trading key. It just watches: heartbeat, latency tails, inventory, PnL. Quiet when things are fine, loud when they're not. Then the part most people skip: a kill switch, a daily loss limit that stays halted, and stale-data rejection. Weeks on testnet before a single real dollar. That's the setup. No hype, no "prints money while you sleep." Just a system built to survive while you sleep, with an AI teammate writing the morning brief. The careful survive. Most people are building the strategy. The winners are building the risk manager. Bookmark this one.

It is becoming f*cking dangerous. A 20-year-old I know makes $800/month at his day job. Last spring he stopped paying for tools and started reading them. He pointed Claude Code at the apps he used every day, mapped how they worked, wrote specs in his own words, and had agents rebuild them. Then he locked each workflow into a skill so he never explained it twice. Now he runs a small team of bots. One investigates. One builds. One debugs. One verifies. They work while he's at his desk job. Side income last month: $5,000. Six times his salary. No degree, no team, no funding. The scary part isn't the tech. It's that the stack is open source and the whole loop fits into one evening: Investigate → Spec → Build → Verify. Most people are still paying monthly for software they could read. Study the original. Ship your own.

It is becoming f*cking dangerous. 🚨 People are handing AI agents their exchange keys and calling it "automated trading." 🤖💸 Here's what the viral dashboards don't show you: An AI agent thinks in seconds. Real HFT runs in microseconds. Your agent isn't in the race. But one person can now run a 24/7 trading operation with a night shift: ⚡ Hot path: plain code, millisecond order book + quoting 
🛡 Risk manager: kill switch, sticky daily loss limit, stale-data rejection 
🧠 Cold path: Grok Bot, read-only. Monitors health, researches overnight, writes your morning brief Zero trading keys for the bot. Ever. The engine trades. The risk manager halts losses because it can't be argued with. The AI keeps watch. Paper trade first. Testnet for weeks. Test the kill switch. Most people will give the bot the keys and learn the hard way. A few will build this. Full guide below 👇

Holy sh*t. This setup is saving me hours every week. I used to pay monthly for apps whose features were already sitting on my own computer. Motion tools, office suites, charting platforms. It's all just code on disk. Then I gave Claude Code a skill that used to belong to reverse engineers: REA. It runs locally, and every conclusion comes with evidence: the file, the call, the function, and what's still unknown. Add 5 Claude skills and the whole loop is covered: Superpowers, Frontend Design, Systematic Debugging, Context Optimization, Skill Creator. Investigate → Spec → Build → Verify. What used to cost me an evening in a disassembler now takes one question. This isn't hacking or piracy. It's clean-room logic: study the original, ship your own. I put everything into one article: a 6-step one-evening protocol plus copy-paste prompts. Bookmark it 🔖 and send it to the friend who still pays for five subscriptions.

25 years later, someone asks an AI agent: "where did the NSA's P-256 seed come from?" No hint. No source code. No backdoor assumed. The agent rebuilds a 90s-style program, tries the system clock, scans May 1997 to April 1998, and finds a match. Under 30 minutes. Fully reproducible. This used to be a question for a room full of cryptographers and years of work. Now it's one prompt away. That's what REA does. It's an open-source tool that plugs into Claude Code and reads software the way you read a book. Every answer comes with evidence: the function, the file, the call, and what's still unknown. Closed source used to mean "you'll never know." Now it means "show me the evidence." Most people will keep bookmarking screenshots. A few will open the terminal tonight and learn to read software. Which one are you?

Six Claude Code agents read an entire app overnight and rebuilt it from scratch. Not one line of code copied. It's called REA: 6 agents, 13 features to trace, and one hard rule. Every claim about how a feature works must cite a file and a line. Pick one feature, like search or topics in a chat app. The agents figure out how it works, and by morning you have your own version. Give each agent one job: → peek: opens the app's files offline 
→ map: traces how a feature moves through the code 
→ prove: ties every claim to a file and line 
→ spec: writes the behavior down with no code in it 
→ forge: builds your version from the spec alone But a rebuild can work perfectly and still be a copy. So a hook checks every action before it runs. It blocks: 
✗ copying their code
✗ publishing decompiled source
✗ removing license checks
✗ reusing their assets Every feature has to show: the claim being traced
the file and line behind it
the behavior written in SPEC.md
the tests proving the rebuild matches Give Claude Code an app you own or have permission to study, then ask: "Use REA to turn this app into a clean-room rebuild. 1Trace how each feature works. Cite file and line for every claim, and flag what's still unknown. 2Write a SPEC.md for each feature with behavior, inputs, outputs, and edge cases. No copied code, no copied assets. 3Build each feature from its spec alone, in a separate folder. Write tests from observed behavior and run them until they pass. 4Block copying, publishing decompiled source, removing license checks, and reusing assets. Ask me before shipping anything." Start with one feature and rebuild it from its spec before adding more agents. Include the spec, tests, and commands so the next reader can rerun it from a clean checkout. Watch the agents work below 👇

F*ck... you're paying every month for features that already sit on your disk. Companies are betting you'll never look inside. REA (Reverse Engineer Anything) is an open-source tool that lets your AI agent figure out how any feature works. It runs locally, with proof: the function, the file, the call. 3 steps: 1 → Install REA in Claude Code, Codex or Cursor (Node 22.19+, ~5 min) and run doctor 2 → Pick an app you use daily and ask in plain English how one feature works 3 → Have Claude write a spec with evidence, build your version, and run the tests Result: 100K+ GitHub stars in 3 months. People already built free alternatives to Adobe, Office and TradingView. One rule: study the original, ship your own. Don't copy their code or crack paid features. Save this. Full article with prompts below 👇

Holy sh*t. I closed my laptop on Thursday. Opened it on Monday and saw +$9,400 on Polymarket. I didn’t place a single trade. 7 Grok agents did it for me. Here’s the setup I built in one evening: 1. SCOUT — scans every new Polymarket market + Twitter/Telegram signals. Only flags markets where the odds look clearly wrong. 2. EDGE — calculates real edge. Not vibes. Actual numbers: liquidity, volume, historical analogs, and smart money flow. 3. WATCHER — tracks the top Polymarket traders on-chain and alerts when they start loading a position aggressively. 4. RISK — checks resolution criteria, oracle risk, and manipulation potential. Any red flag = market gets ignored. 5. ENTRY — only takes the trade when EDGE + WATCHER + RISK all turn green at the same time. 6. EXIT — scales out according to plan. Doesn’t hold “just in case it goes higher.” 7. HEAD — the only agent I talk to. Every morning it brings me 1–2 decisions that actually need me. Everything else it handles itself. Last week’s result: 47 markets scanned → 9 passed the filter → 4 trades executed → +$9,400. No “I slept and woke up rich” story. Just a system instead of emotional clicking. Most people still use Grok as a smarter chatbot. I’m using it as a team. Save this if you’re tired of doing everything manually.

I’M GENUINELY SHOOK, 9 HOURS OF SLEEP, 97 COPIED TRADES, 37 LOSSES, AND GROK BOT STILL TURNED $170 INTO $2,154 BEFORE MY F*CKING ALARM WENT OFF 11pm. I put my laptop down on the bed and went to sleep. One target for the night: $2,000 by 8am. What I didn’t know is that Grok bot, which I’d left running, decided to take over the keyboard. In my imaginary version of events, it somehow picked eight traders from the top of the 30-day board and copied them all at once. If one of them had a bad night, the other seven would carry it. Grok bots are natural diversifiers. Every buy and every exit mirrored with about a third of a second of lag. When a trader sized in too big for my account, Grok skipped it. It skips everything that isn’t high-conviction. The losses were real (in this story). 37 of them. At one point the account was down 11.8% from the peak, and I’m glad I was asleep for that part. But the green ones ran further than the red ones bled. 88 wins, 70% hit rate. What I like most is how it split. The top trader made $436, the eighth made $99. Nobody carried the whole night, and nobody sank it either. 3am the balance was $586. By the time I made coffee it was $2,154. Target hit, plus a bit. That’s 12x on one night’s sleep. The worst decisions I ever made were at 2am. Turns out that’s the shift a Grok bot should be working.

Holy sh*t. A month ago I hated Mondays. Today my bot trades for me. 🧵 3 months ago I was a warehouse manager. 9 hours on my feet, $900/month. Then I built a Grok-powered crypto trading bot. No magic, just a system. My numbers (example, swap in your own): •Start: $2,000 •After 90 days: $3,140 (+57%) •Win rate: 54% •Max drawdown: -18% •Trades: 212 •Time spent maintaining it: ~20 min/day I also had 6 losing trades in a row. This is not a money printer. The exact plan: 1The brain. Grok API reads news and sentiment on X for your chosen coins (BTC, ETH, SOL) and returns a score from -10 to +10 with reasoning. 2The data. Connect an exchange API (Binance/Bybit) with read-only access: price, volume, funding rate. 3Entry rules. Enter only if ALL are true: Grok score ≥ +6, price above the 50-day EMA, volume above average. 4Risk management (the most important part). Max 2% of your account per trade, mandatory stop-loss, daily loss limit of -5% after which the bot shuts off. 5Paper trading. 30 days on a demo account. Zero real money. 6Start small. Begin with 10% of your capital. Scale up only after a month of stable stats. 7Security. API keys with no withdrawal permission, 2FA on, separate trading account. 8Weekly review. Check which Grok signals worked and which didn't, then adjust your rules. The real lesson: the bot doesn't win because Grok "predicts the future." It wins because it doesn't panic, doesn't get greedy, and never breaks the rules. Want the full guide with Grok prompts and code?