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someone built a virtual office right inside their terminal a guy deployed 20 autonomous ai agents to simulate an entire agency using claude opus 5 as the brain for every single workstation one weak laptop and local pipelines. clients thought he hired a whole floor of senior managers he entered one prompt, built the floor plan and went to sleep by morning the agents checked 45 pull requests, deployed 12 features, sorted client emails and left one note: stanley tried to poison the coffee again the consulting agency he competes with charges 14500 dollars a month for the same sprint volume he spent 12 dollars and 40 cents on this right now millions of agencies work manually and keep paying monthly for the work that agents finish overnight and fewer than 70 thousand people on earth know how to set this up. that is millions of businesses for every one of them i told you about one of those below

a founder just built a company of 27 AI agents on a Mac Mini that runs his entire business without him it’s broken up across 6 different departments: communications, sales, finances, clients, marketing/growth, and tech running his daily operations these aren't just visual art, they are real functional AI agents you can click into to see every single skill and SOP being run in the middle sits his full company knowledge base built on G-Brain, handling everything in the company through a simple directory every workflow is connected to whatever AI agents and humans are necessary, whether human-led, human-assisted, or fully autonomous the best part: he has this whole thing hosted on his Mac Mini so he can run it on the go thousands of traditional companies are still doing everything manually, waiting for someone to build a full AI agent enterprise

Opus 5.5 dropped into Roblox Studio and three games ship every week A 22-year-old in Lisbon pulls $9,700 a month running this exact same stack. Every line on the cost sheet: Opus 5.5 Max plan. $100 a month. Roblox Studio. Free. DevEx cashout. 0.0038 per Robux. Floor payout. 30,000 Robux, $114. One prompt opens the agent session. Code scrolls, Studio loads the build. Four playtests run. Clicker, tycoon, egg hatch, arena. Red errors in the output log. Next build loads. Three games a week. One plan.

Anthropic. buried. this. in the docs. A three-model split killed my costs. I was feeding Opus 5.5 every task. Every grep, every search, every diff audit. The priciest context window in the stack, burning on work that needed seconds. Then I found one flag. claude --model sonnet --advisor opus Sonnet 5.5 took the main seat. Wrote code, applied fixes, coordinated the build. I set three Haiku 5.5 subagents loose on the repo: → search mapped modules → grep found call sites → audit checked the diff All three ran in parallel, read-only, in throwaway worktrees. Opus 5.5 never touched a file. It sat on call as advisor and only stepped in at three moments: 1. Before a plan locked 2. Same error showed up twice 3. Before calling it done Routine tokens landed on the cheapest model that could carry them. Every judgment call went to the one built for it. Sonnet 4.6 with an Opus 4.6 advisor scored 2.7 points higher on SWE-bench Multilingual. Cost per task dropped 11.9%. The 5.5 generation runs the same advisor split on a single flag. The advisor is experimental, Anthropic API only, and every advisor token bills on top.

Door + Grok + $25 ticket... Fictional run wrecked me. +$57.30 net. 6 seats. $44.30 to Grok. 463 → 31 → 6 dev sells. 1. Scan 2. Door 3. Grok 4. Snapshot 5. Watch 6. Exit 5 stopped. 5 timed out. Median drop after my exit: 71%. Paper money at screen prices.

A free gist turned Obsidian into a self-rewriting vault Karpathy's llm-wiki.md defines three operations. Ingest is the one that rewires everything. Every note app gives you a vault. None of them rewrite the vault when new data lands. Ingest has one job. Read a new source, build a summary, rewrite every connected page in the vault. Not "sort my files." Not "add some tags." One job: fold new material into the knowledge base so nothing contradicts and every cross-link holds. 1. A raw file drops in 2. The model reads it and writes a summary page 3. Every page touching the same topic gets rewritten 4. Cross-links between updated pages regenerate on save 5. log.md records the change 6. Lint catches contradictions on the next pass claude-obsidian runs this loop at 15.9k stars. mcp-obsidian opens 7 tools to read, search, patch and delete across the vault, 4.5k stars. One operation, one job. The vault stays current without a single manual edit. One gist. The vault rewrites itself.

Madness that your coding agent still can't file a ticket Claude Code starts at $20 a month. every server below gives it hands outside the terminal. tickets, workflows, diagrams, live web. no more copy-paste. Microsoft shipped the stable MCP C# SDK 2.0 this week on the new stateless HTTP spec. 10 GitHub repos giving your coding agent hands: 01 github-mcp-server → official GitHub server in Go. reads repos, runs issues, PRs and Actions so you stop switching tabs for a single ticket github.com/github/github-mcp… 02 servers → 7 reference servers, 13 archived and 10 SDKs in one place. start here before building your own github.com/modelcontextproto… 03 fastmcp → ships your own Python MCP server in a few lines. a million downloads a day. runs behind 70% of MCP servers github.com/PrefectHQ/fastmcp 04 n8n-mcp → feeds the agent 3,143 n8n node docs and 2,352 workflow templates. it builds automations instead of you reading the docs by hand github.com/czlonkowski/n8n-m… 05 next-ai-draw-io → the agent draws and edits draw.io diagrams from the chat. 25 model providers, runs as web, desktop or MCP server github.com/DayuanJiang/next-… 06 gitlab-mcp → 278 GitLab tools, 40 on by default at 12,671 tokens. the full set burns 71,420. keep it lean or context explodes github.com/zereight/gitlab-m… 07 mcp-atlassian → 98 tools for Jira and Confluence. your agent reads tickets, updates boards and pulls wiki pages. no more tab switching github.com/sooperset/mcp-atl… 08 tavily-mcp → search, extract, map and crawl the live web. your agent pulls fresh data instead of guessing from stale training knowledge github.com/tavily-ai/tavily-… 09 exa-mcp-server → web search and full-page fetch in one connection. two tools by default, two optional, two skills for deeper research github.com/exa-labs/exa-mcp-… 10 mcphub → self-hosted gateway for every server above. control panel on port 3000, five-minute setup, one entry point instead of ten github.com/samanhappy/mcphub Start with one. wire the ticket server into your session and file an issue from the terminal. agent asks → gateway routes the call → ticket server reads issues → workflow server builds the flow → search pulls live context → diagram server draws the result Every server is open source and free to install. running them still uses your plan's tokens and any third-party API keys the server needs. Open your config and add one server entry tonight.

Pure f*cking gold for ten dollars Stockfish rates above 3,600 Elo. This pipeline puts it behind a pair of smart glasses and a WhatsApp call. You want a board analyzer that works by sight. No typing positions, no copying FEN strings. The glasses watch the board, the engine speaks the best move back. One Mac, one WhatsApp call, and Ray-Ban Meta glasses. Everything else runs on its own. 1. The glasses stream the board to your Mac through a live video call 2. The Mac grabs frames from the call window, about one per second 3. A cheap filter checks every frame. Board readable, no hand in the way, piece moved 4. Nothing changed, no model call fired. Only real moves hit the expensive step 5. The vision model reads the new board state 6. The app checks it against the last known position. Only legal moves pass 7. Stockfish picks the best reply. About ten seconds from board change to spoken answer 8. The Mac speaks it through a virtual mic into the call Default model runs at 1.4 cents per frame. Opus 5.5 costs about 4 cents. The whole game sits under a ten dollar cap. The full pipeline is open source. MIT licence. The glasses camera runs through WhatsApp's built-in video share. No firmware, no jailbreak. But in any rated game against a human, this is cheating. Platforms ban for it. Bookmark this.

this guy is a certified freak A full futures terminal running inside a Minecraft house. TopstepX platform, Nasdaq-100 chart, candles ticking on a wall screen. The player walks up with a diamond pickaxe and starts working a live order ticket. Look at what is on that screen: 1. NQU26 Nasdaq-100 contract on a 1-minute chart with active candles and a blue trend line, price ladder reading 29,530 to 29,550 2. Market order execution with BUY +3 MARKET and SELL -3 MARKET buttons, JOIN BID and JOIN ASK right next to them 3. Full position controls including CLOSE POSITION and FLATTEN ALL live on the same ticket 4. Topstep Trading Combine where a 50K account carries a $2,000 max loss limit before the whole thing blows Prop futures from a block game. Trading desk and game world just collapsed into the same wall. Save this. The full clip runs below ↓

I don’t understand why everyone isn’t doing this yet. Anthropic released a workflow for Claude Code that turns it into a read-only mobile security auditor, auditing your entire phone in 5 minutes while burning a fraction of the effort. Main Idea: Read-Only Phone Audit via Claude Code Instead of guessing what is tracking you or paying for bloated security apps, tasks are executed through a single paste-once prompt with zero writes to the device: > Role Setup (Mobile Privacy & Security Auditor): Sets strict constraints, read-only access, no modifications, and skips any step requiring a write. > Five Check Areas: Automatically scans apps (including hidden ones), deep control (accessibility/MDM profiles), permissions, persistence, and network behavior. > Severity Grading: Categorizes every finding into Low, Medium, or High signals so you know exactly how to respond. > Actionable Verdict & Lists: Ends with a clean/compromised verdict, followed by three sorted lists (Safe, Worth removing, Needs a professional). > Critical Safety Protocol: Instructs you not to delete high-severity threats immediately, preventing data loss or alerting an attacker, and advises changing passwords from a separate clean device. Launch the audit via terminal: claude --prompt "Run mobile privacy audit in read-only mode" Configure your Claude Code workspace for security audits: > In ~/.claude/settings.json, set strict boundaries and lock session limits to effortLevel: high. > In CLAUDE.md, add a rule requiring safety checks before suggesting any app removal or modification. > Keep your device connected via adb (Android) or standard diagnostics (iPhone) for read-only access. Crucial Rule* If something is found, do not delete first. Keep the app installed, save the full audit report, change your credentials on a *second* device, and hand the report to a professional if it's a high-severity threat. > code.claude.com/docs/en/secu…

It is becoming f*cking dangerous: AI agents connected via MCP just turned an open-source world map and a paper brokerage into an automated geopolitical trading floor. World Events Agent wires an 89.4k GitHub star intelligence dashboard directly into Alpaca's trading system, giving a single LLM 160 real-time tools to trade global chaos on virtual money 24/7. The setup constantly scans conflicts, shipping lanes, subsea cables, flights, and market feeds, evaluating trade opportunities every few minutes without human intervention. The main danger lies in the fact that paper trading hides every real-market friction, latency, slippage, and liquidity don't exist in simulation, making early "wins" dangerously deceiving. Here is how this automated geopolitical trading stack is built: > analysts pull 469 news & OSINT feeds across 773 providers to track 29 scored hotspots and 31 instability indexes > mapping agents link global events to specific energy stocks, gold, or crypto assets > crowd gates check X chatter, Polymarket, and Kalshi odds to confirm if the market already priced the event in > execution tools push trade orders to an Alpaca paper account with $100k in virtual funds Before any order lands, the system runs a three-step validation to filter out noise: > Written triggers: Plain-English rules (e.g., oil supply risk spikes → watch energy stocks). > Isolated mapping: A separate model identifies exactly which assets are affected. > Crowd gate: Passes on trades if public prediction markets already moved. The real trap is the false sense of security. The dashboard is completely free to open, but running MCP data calls starts at $39.99/month, plus LLM API costs. More importantly, setting ALPACA_PAPER_TRADE=false flips the entire 160-tool system directly to live, real-money execution without extra confirmations or cooldowns. If you want to test this stack safely on paper, keep these key setup steps in mind: 1. Connect the dual MCP servers: Load the 95 tools from World Monitor and 65 tools from Alpaca into your agent framework (uvx alpaca-mcp-server). 2. Implement strict crowd gates: Force the agent to cross-reference X and prediction markets so it stops firing on stale, already-priced news. 3. Audit the output, not the PnL: Evaluate performance purely by counting how many trades fired on absorbed events rather than paper profit. 4. Scale carefully: Run the setup on virtual money for weeks to study false triggers before ever considering switching the environment flag. Before this stack, event-driven trading required a bloomberg terminal, a news desk, and an entire research team. Today, it runs on two MCP servers, a prompt file, and a script.

This is getting wild: I am genuinely surprised more people aren't using this. With this exact framework, I scaled my monthly revenue to $10,000 just two months back. OpenAI co-founder Andrej Karpathy shared a game-changing concept that went viral with over 24M views. His takeaway? Quit using AI as just a code helper and transform it into your main intelligence hub. The core mechanic: target a specific folder with Claude Code, throw in all your raw files (PDFs, meeting notes, articles) and let Claude process, connect, and organize them into a self-updating knowledge network. It scales like compound interest, boosting its total value with every file added. Step-by-step setup: 1. Create a clean Obsidian vault and launch Claude Code inside it 2. Give Claude Karpathy's architecture prompt to set up the system framework 3. Claude automatically builds three main components: a raw directory for uploads, a wiki area for processed insights, and a central CLAUDE.md file 4. Place any document into the raw directory and run the "ingest this" prompt 5. Interrogate your compiled knowledge base at any moment with zero delay The setup process takes under 5 minutes, which means you'll never start from a blank screen ever again Click the link below to get the full setup guide Save this post so you don't lose it

GENUINELY UNHINGED. TERMINAL TURNED 65 TRADES INTO $1,599. Someone filmed a green terminal off their monitor with a phone. No name anywhere. Panels just numbered 5 through 8. Full session log: 1. Order book loads ETHUSDT. Bids and asks stacked from 2,476 to 2,482. 2. Radar gates every trade through four checks. Flow, book, speed, trend. Starts at 2/4. 3. All four pass. Ready long. Bracket auto-sizes at 40 ETH. 4. Hold lasts 22 seconds average. Then it fires again. 65 trades that session. 26 per hour. 66% win rate. Average win $72.88. Average loss $69.76. Profit factor 2.04. Expectancy +$24.60 per trade. Latency sat between 35 and 43ms the whole time. Session P&L hit $1,599, net of fees. Four numbered panels and a four-check gate that fires a bracket every time all signals line up. What are your four checks before entry?

builders burn weekends starting from zero. 304 projects mapped, AutoGen in maintenance. AutoGen at 61k stars runs on patches only. Agent Framework picks up at 14k. awesome-ai-agents maps the full set. MIT, 24 categories in the README, 36 in the YAML. DSPy at 38k, Cognee at 31k, Serena at 30k, all on the same list. PICK a category from the map CHECK which of three still ships commits BUILD on the winner, pull the data as JSON Dead-repo pick costs months. The full map runs below ↓

THIS IS F*CKING DANGEROUS 76x cheaper per scored setup smartmoneyconcepts. one MIT indicator marks order blocks, fair value gaps, break of structure and the liquidity sweeps where stops collect. 2.1k stars on GitHub, pandas and numba underneath. the system stacks six layers on that single install. > INSTALL - pip install smartmoneyconcepts. computes zones and structure, executes nothing > CONNECT - Opus 5.5 reads live price data. 4h chart for direction, 15m for entries > MARK - order blocks, FVG, BOS and every trap level flagged across the pair > SCORE - Jev rates each setup at $0.0004 per case. a frontier model runs $0.0304 for the same job. 76x the cost gap > TEST - backtest on Sharpe, max drawdown and win rate. failures stay on paper > FIRE - only scored and tested setups go live. Telegram pings the phone the indicator marks zones. no execution, no exchange keys, no latency engine. everything past the markup is the builder's own pipeline. without the gate before live, every scored setup fires. cheap scoring means nothing if weak setups eat capital at the same speed. one independent Jev trial ran 15 trades over 17 days and closed at net -4.5R. the gate is where the system lives or dies. the terminal below maps it. order block, trap sweep, price flip, scored entry through the gate ↓

Why isn't everyone using this yet? Roblox Studio ships a built-in MCP server. Opus 5.5 plugs in at $4 per million input tokens. The agent edits a clicker game in real time. Chat prompt in, one pass: 426 parts switched off under the map, buttons resized. 1. TYPE a plain edit into the agent chat 2. AGENT reports what changed, area by area 3. STUDIO shows the result. Red lines in the output panel 4. TEST the build. Power, Wins, combat bars, stages all functional One build pulls 5k a month. Do the math: DevEx pays $0.0038 per Earned Robux. 5,000 / 0.0038 = 1,315,789 Earned Robux a month. Minimum cash-out is 30,000 Robux = $114. One withdrawal per month, verified account and W-9 on file. Full chain in the HUD below: prompt to MCP to Studio to Robux to cash ↓

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 ↓