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F*ck YES... I made an AI vision & gesture-control web app with Claude Code without a single line of manual code the shift: Claude Code + vision-tracking libraries turn bare-hand gestures into a real-time interactive 3D particle physics engine in minutes here’s 3 step guide: step 1 → fire up your terminal and launch Claude Code with your project workspace. step 2 → drop your gesture reference spec or UI wireframe into the chat and tell it to build the vision pipeline + Three.js particle system (it starts writing the full component repo). step 3 → run the local server, test the hand tracking against your webcam, and tweak behavior with Claude Code by saying something like: "The hand pinch and open gestures look sick, but let's make the particle explosion smoother and add custom neon color gradients when tracking multiple fingers!" the result: you can build complex, interactive vision-controlled web apps instantly... Paste it now. Then read article below to master AI-driven development:

A developer spent 3 months coding a custom terminal because he was tired of staring at 10 different trading tabs and missing every major market move. 10 minutes later, a complete visual edge. Then he packed his laptop, disconnected from high-speed internet, and went to work from a local café with zero distractions. On his screen: a live automated pipeline streaming real-time liquidity, structural order blocks, and multi-asset price action into a single unified grid. One glance. The whole market mapped out instantly. Somewhere in the middle of a busy day, zero noise, he pulled up a custom risk scanner. It filtered out 95% of market garbage, tracked smart wallets entering early, and mapped out exact entry zones across dozens of assets without lagging. Executed the orders right from the terminal. Green numbers rolling in before lunch. Real edge built from a clean setup with zero bloat. Then he scaled the system. The terminal now tracks every order flow shift as it happens, filters out market noise, calculates risk ratios, and plots real-time price action automatically. Zero clutter, zero missed setups, nobody else sees his custom algorithms. Month one -> steady profits from a streamlined system. Month six -> it runs his entire trading workflow on autopilot. Most people still use generic charts and stare at standard indicators all day. A custom trading terminal gives you speed, cuts out the noise, and prints money before the crowd even wakes up and almost nobody has built one yet.

how is this even legal saw someone feed the entire Alex Hormozi meta ad library into a new AI marketing model and map out every single hook, format, and winning pattern for just $0.49 all it takes: drop any meta ads page url into the tool. let it ingest all active creatives, sort by duration, and surface the exact patterns running past 60 days. after that, the data is the business. it reads what works, plots out the winning talking-head frameworks, breaks down every script hook, and ships the insights by sunrise. > 8,498 ads analyzed, 1,214 active creatives mapped > zero manual research, zero guesswork, $0.49 to run > 68 days on the longest-running winner, direct caller format you didn't analyze ads. you wasted thousands of hours on manual competitor research. the whole system is in the app below, every prompt, the ad breakdown structure, and the Hormozi winning pattern index bookmark this before your next campaign and read art below

REA + 16 repos = my reverse engineering studio I pasted one config. 17 repos locked into one session, five groups deep. One MCP. Every binary on my drive open for reading. 1. REA runs the loop. MIT license, 412.4k stars. Works with Claude Code and Cursor. 2. 96.2k stars on Ghidra, free native decompiler. jadx reverses Android APKs to Java. 3. Two .NET tools: ILSpy decompiles, dnSpy debugs. Frida hooks into running apps live. 4. radare2, x64dbg, ImHex. Low-level debuggers and hex with its own pattern language. 5. Every packet between app and server, mitmproxy reads it. angr finds paths my tests miss. 6. I point REA at a target. Binary to Ghidra, APK to jadx, packets to mitmproxy. Own apps and open binaries only. No protection bypass, no license cracking. Which one of these 17 would you wire in first?

Wired six Wall Street repos into one desk. Goldman, JPMorgan, Jane Street, Jump, Morgan Stanley, Man Group. I pulled every one. 38.6k stars combined. 1. Goldman's gs-quant: pricing, risk and backtesting in one library. 13.8k stars. 2. JPMorgan's python-training: notebooks for analysts and traders. 14.3k stars. 3. Jane Street's magic-trace: every function call at ~40ns resolution, 2%–10% overhead. 4. Man Group's ArcticDB: billions of rows of market data, serverless. 2.6k stars. 5. Jump's Firedancer: Solana validator from low-latency trading design. 1.5k stars. 6. Morgan Stanley's Xpedite: non-sampling profiler for C++ real-time systems. 211 stars. I connected all six. Pulled five years of daily GS, JPM and MS prices through yfinance, stored them in ArcticDB, ran gs-quant on top. Volatility, max drawdown, z-score, beta to SPY. Backtested one rule with fees. The code ran clean. 38.6k stars. Six firms. One desk. The whole desk is open.

Built a fictional rig. Twelve timelines gone, one slider left. One equation. Every part, every gauge, every label I wired reads from it. 1. Machine: hex chassis, 6 legs, 18 joints, built in real units to the servo. 2. Model: pure functions of one input. Legs, panels and floor all compute from one solver. 3. Panels: joint torque, foot height, per-leg load, solver time. Nothing typed in. 4. Buttons: wave, ripple and tripod gaits, direction pad, speed and stride. 5. Window: floor draws the solver live. Lines to planted feet, markers for landings. 6. Tour: cursor runs the page alone. Any click takes over. 25 s of quiet gives it back. I tore down the landing gear. Rack pushes 201 mm, turns a 32-tooth pinion half a turn. 128 mm pitch circle. Legs swing 180 degrees into the airframe. Jansen's Strandbeest runs the same rule. 11 link lengths, every joint from one crank. One input, whole machine ↓

BEYOND F*CKING COOKED, MY BOTS SAT OUT A 508% CANDLE WHILE I SLEPT AND STILL TURNED MY $100 INTO $4,236 I would have bought that candle. my bots didn't. every morning QUANT pulls six macro inputs and publishes one dial. 0 to 1 under 0.50, stand down. 0.50, half size. 0.75, three quarters. 1.00, full send my size rule clamps every ticket at 6% of the bank times the dial, caps it at 2% of the pool 3:35am my crawler found CATBOT. up 508% in 80 minutes Jev read the dial. 0.75. too weak for today. skip I would have gone in. 4:10am the creator pulled the money. -99.6% I'd be holding dust. the same night, five fills on HIRE: 1. 2:50pm in at $248K, out at $1.76M, +$416 2. 9:45pm floor $198K, sold $757K, +$1,197 3. 1:55am bought the top, -$138 4. 7:55am back in $368K to $765K, +$1,237 5. 11:05am sold $1.09M before the slide, +$1,304 volume ratio drops under 0.20, my risk seat closes everything in 60 seconds equity drops 4%, every seat flattens for the day my $100 turned into $4,236. the fills add to $4,016 the exit is not mine to touch the dial reading drops and every seat goes dark in one frame

COOKED WHAT A $6 BOT PRINTS ON POLYMARKET 288 Bitcoin markets open every day. Five minutes each. One builder wired a Grok Bot team to sit inside them and grind. 1. Window opens. Scout reads Chainlink BTC/USD. Prices each side's real chance. 2. Two minutes left. The losing side sells for 20-40 cents. The bot buys it. Hits 44%. 3. One side pulls far ahead. It grabs the leader near 50 cents. Never above 70 cents. 4. Seven windows out of ten get skipped. $14 a bet, up to $170 on the strongest calls. 5. Morning. Risk reviews every trade. Three red days in a row and everything pauses. The builder's running total: +$10,774 across 6,692 trades. Worst day: -$31. Before real money, every paper version bled for a week. Fees ate the edge. Runs on a $6 server. Straight to Polymarket. Grok Bot routines are too slow for two-minute windows, so Builder wrote a standalone terminal. Fees, slippage and latency still erase the edge even when direction is right.

BEYOND F*CKING COOKED, SAVIP'S DESK SAT OUT A 508% CANDLE ON ONE DIAL READING AND STILL TURNED $100 INTO $4,236 OVERNIGHT the restraint: every morning QUANT pulls six macro inputs and publishes one dial. 0 to 1 under 0.50, stand down. 0.50, half size. 0.75, three quarters. 1.00, full send the size rule clamps every ticket at 6% of the bank times the dial, caps it at 2% of the pool the temptation: 3:35am the crawler found CATBOT. up 508% in 80 minutes Jev read the dial. 0.75. still a go on paper, but Jev judged it too weak for the day. skip 4:10am the creator pulled the money. -99.6% the same night, five fills on HIRE: → 2:50pm in at $248K, out at $1.76M, +$416 → 9:45pm floor $198K, sold $757K, +$1,197 → 1:55am bought the top, -$138 → 7:55am back in $368K to $765K, +$1,237 → 11:05am sold $1.09M before the slide, +$1,304 volume ratio drops under 0.20, the risk seat closes everything in 60 seconds. equity drops 4%, every seat flattens for the day savip's desk turned $100 into $4,236. the fills add to $4,016 one skipped candle carried the whole night save this. the terminal below shows the full dial and rule stack

YOUR OLD CHART IS THE PROBLEM Every second of dxFeed order-flow depth tells a different story than the candle: > 0:00. DOM ladder loads. Resting buys and sells stacked by level. > 0:02. Price drops. Fat red bubble prints on the fall. Sellers hammering bids. > 0:04. Red bubbles trail lower. Ladder bars stretch at every row. Sell walls piling up. > 0:05. Watch this one. Green bubbles punch through the red at the lows. Buyers absorbing sells at the same price. A long bar locks in the DOM. Massive resting order at one level. > 0:07. Cluster at the new low. Red and green tangled on the level line. Size vs. size. The candle said "down." The bubbles showed who hit bids, who absorbed, and where the walls sat waiting. bookmark this.

It is becoming f*cking dangerous: when Anthropic disclosed this, they didn't even realize they were opening a Pandora's box 1. Connect QuantGPT to Grok Bot over MCP to pull historical equity data, insider transactions, and macro feeds instantly 2. Set up the 8-seat trading desk where every seat has one strict job (Quant, Scan, Judge, Size, Fills, Risk, Chief, Cloud) 3. Run the morning Risk Dial using 6 macro inputs (liquidity, volatility, credit, BTC, SOL, QQQ) to decide today's size 4. Use Jev for structured verdicts and FOMO for automated memecoin pool scanning and execution 5. Deploy QuantGPT Cloud to manage the 3x Nasdaq trend sleeve on Alpaca with automatic risk stops 6. Enforce strict account kill switches that flatten positions if drawdowns exceed 4% 7. Let the Chief of staff run daily pre-flight checks and compile end-of-day reports with zero fabrication The whole setup process takes around 20 minutes Turn Grok Bot into your ultimate autonomous trading desk, equipped with live data terminals, multi-sleeve risk dials, and automated broker execution Find the step-by-step instructions in the article below

AMN, ONE RULE MADE 6 BOTS SIT OUT A 6.8X AND SAVIP'S FIVE DESKS STILL TURNED $17,600 INTO $50,440 IN ONE F*CKING NIGHT Grok Bot runs five desks. one bot team per coin, each desk starts with a fifth of the bank 10% of a desk holds its coin all night. the other 90% trades only what passes six rules 2.87x in one night. the night before, the same bots only doubled $8,506 the six rules: 1. no pool under $40K 2. no coin with dead volume 3. no buying a chart that's already vertical 4. no coin where sells beat buys 2 to 1 5. 2 losses in a row and the bot is out 6. a post on X is research, never the trigger the price of rule 3: the Robinhood desk sold KIMCHIBULL at $1.68M, up 122%. then it ran to $11.37M without them. 6 bots watched a 6.8x walk 21 green trades, 10 red. worst loss -5.6%. Kimchi -45% and BACKERS -46% overnight, both desks still ended green the rules do not save a desk from a pulled pool or a model that misreads the chart would you hold every rule in place knowing one of them just let a 6.8x walk? the terminal below shows every desk, every rule, and the one trade they all watched leave ↓

NO F*CKING WAY, SAVIP'S GROK BOTS WENT ALL CASH AT 5AM, A TRUMP MEME COIN CRASHED 78% BY SUNRISE, $1,873 LEFT IS NOW $8,977 Grok Bot on one desk. three nights, $100 became $61,873. savip pulled $60,000 to the bank and left the bots $1,873. the coin: VeilTrump, 1-day-old Trump meme coin, $866K at 1pm. the night: → 3:20pm bought the dip at $714K, sold at $1.71M, +$2,400 → 10:30pm passed on a coin up 218% in 40 minutes. pool emptied by 11:30pm → 5:00am sold at $1.10M, all cash → 6:30am the coin fell from $1.03M to $230K in 25 minutes → the bots had been out for 90 minutes $1,000 held in that coin is $265. the bots' $1,873 is $8,977. 4.8x on a coin that lost 73%. the scan gate: age 15 min to 72h, liquidity over 12k, volume24 over 40k, mcap 60k to 8M. holders climbing faster than price rank first. more sells than buys in the last two windows drops it. the close gate: six-hour volume against the six-hour average below 0.20. full close inside 60 seconds. the desk cleared the coin, passed on the 218% run, and sat in cash while the floor dropped. one night of eight seats working. would you have been in cash at 5am? terminal below: rule checklist, desk rows, coin falling, balance rising ↓

Model + MCP: 2.3x smaller crash at the same 6.8%. QuantGPT backtested one rule across 27 years of S&P data through a single endpoint. The stack is the edge. Swap Claude for Gemini next month, the data warehouse, the backtest engine and the runner stay put. Three layers a fund runs on: data, compute, execution. A bare chat model owns none of them. > INGEST - nightly warehouse from 1998, delisted tickers included, fundamentals stamped by filing date, crypto, commodities, FRED macro > TEST - model sends a rule over MCP, server replays it on stored history, returns one of three verdicts: DATA VALIDATED, TRADE-OFF, NO EDGE > SWEEP - one prompt fires the rule across 5 moving-average lengths and 4 exit buffers, checks plateau vs one lucky number > STRESS - futuretests replay your holdings through past event shocks: tariffs, oil disruption, war onset > JOURNAL - rechecks every finished backtest each time new bars land > EXECUTE - hosted runner sends your strategy code to your broker, under your keys, on your schedule QuantGPT's own 27-year run on the 200-day rule grew $10K to $61,526 with the rule vs $61,009 holding still. Nearly the same finish line. The gap is all in the worst crash. -24.4% with the rule, -56.8% without. Sharpe 0.61 vs 0.44. 42 trades total, gross of costs. The data layer and the backtest engine do the work the model cannot do alone: store history, kill survivorship bias and compute a Sharpe on real bars. Without that layer the model invents a Sharpe it never computed. Without the out-of-sample split a rule memorizes noise. Without 30 days on paper you find out on real money. Full data-to-broker pipeline below ↓

THIS IS F*CKING INSANE 2 seconds now run the other 58 One Claude stack feeds YouTube Shorts, TikTok and Instagram Reels from a content farm. The farm optimizes exactly 2 seconds of every 60-second clip and treats the other 58 as dead cargo. 2 of 60 seconds. 3.3% of the clip. Three feeds off one pipeline. 1. OPEN - every clip loads a 2-second hook window that decides the view, nothing past it gets touched 2. BUILD - one Claude stack runs real scripts that produce and schedule clips across all three platforms 3. FORK - each finished clip splits to Shorts, TikTok and Reels from one source without a rebuild 4. TRACK - YouTube tracks who stays past the initial seconds, TikTok measures retention rate and watch time, Instagram ranks by reshares and full watch-through 5. DROP - 58 seconds of filler ride behind the hook, the farm skips them entirely YouTube, TikTok and Instagram all track whether viewers hold past the opening seconds. No platform publishes a first-seconds threshold. The farm drew its line at 2 and built the whole production run around it. One stack, one number, three feeds. The radar below fires 2 of 60 segments and sends beams to all three. ↓

🚨 this is getting SCARY. Scalp City. 0DTE calls and puts across QQQ, SPY, IWM, fired by one rule. Schwab's count: ~1.5M of those contracts daily on SPX alone. Nearly half the options book. Each tower is a worker locked to one ticker. Beams are live trades. Vault at the center stacks the day. The rule: CROSS → candle breaks VWAP, scanner reads distance in ATR FIRE → close above means call, close below means put LOCK → target hit, position sealed VAULT → total stacks, workers clock out The vault dips to -$233 mid-session. Fri 10/2 closes at +$4,839, top worker SPY at +$2,337. No broker. No commissions. No account history. 0DTE expires at the end of the same trading day. Out of the money at close and the contract is zero. The 3D city is the skin. The exit rule is the edge. HUD below breaks down every vault swing ↓

Five calls, 12 seconds, one Ethereum block. Everyone tracks latency. The bot only tracks whether the fork clears the floor. Ethereum clocks 300 blocks per hour. Flashbots routes the bundle to builders. Foundry's anvil forks the chain in memory. Wrong order, and gas burns on every attempt with nothing to show. > INGEST - blocks and pool reserves arrive by gRPC stream. The moment you poll, you are a block late. > DETECT - reserves shift, price gap minus fees minus gas. Thousands of passes per minute. Almost always zero. > SIMULATE - fork current state with anvil or revm, run the trade. Below the floor, it dies here. > SUBMIT - bundle with a bid routed to builders via Flashbots. Too low: missed block. Too high: validator takes the edge. > CONFIRM - watch inclusion, reconcile nonce and inventory, log what the chain paid. A fire-every-block loop costs roughly 0.6 ETH per hour in gas, per the framework's own math (0.002 ETH illustrative per attempt, 300 blocks). Backtest haircut from the same guide: win only 20 to 40 percent of contested blocks. CONFIRM closes the loop. Nonce updates, inventory reconciles, the log records what the chain actually paid, not the simulation. That log feeds the next block's INGEST. Miss it once, and the bot fires the next 12-second window on a stale nonce and a phantom balance. One block, five calls, one DROP branch at SIMULATE ↓