if u think the top of fomo leaderboard is insiders and devs, i'm begging u, read this. it's worse and better than that:

We need to have a serious conversation about overweight people flying on commercial airlines. I’m flying on @AmericanAir and after paying extra money to upgrade my seat, I got stuck next to a man who is 300+ pounds and stripped mid flight. None of the flight attendants wanted to confront him. He smells like 💩 and weed. He’s literally sitting in my seat and keeps touching me. For context, he’s literally 300+ pounds and I’m 120. Why does American Airlines think it’s acceptable to treat people this way?! I tried reaching out discreetly during the flight, but they have no avenues to do that.

MIT Researchers Built An AI Hedge Fund & released it 100% FREE this gives you full trading firm of AI agents, analysts, a bull vs bear debate, a trader and a risk manager that approves every trade i cloned it and plugged in Opus 5.5 as the brain and Jev as the fast decision layer (INSANE RESULTS) here is how to USE this repo: 1. clone the repo and install it, one command with pip or uv, it runs on your laptop in a few minutes 2. drop in your Anthropic key and set Opus 5.5 as the deep think model, so the whole agent firm reasons on the best brain available 3. launch the CLI, pick any ticker and a date, it works on every market Yahoo covers, US stocks, crypto and more 4. the fundamentals agent digs through the financials and the news agent reads every headline and macro event that could move the price 5. the sentiment agent reads the crowd on Reddit, StockTwits while the technical agent reads the charts, RSI, MACD, the patterns 6. every agent writes a clean structured report instead of loose chat, which is the trick that stops the signal getting distorted as it passes along 7. then a bull agent and a bear agent debate the trade over multiple rounds, and a facilitator reads the whole debate and picks the winning case 8. the trader agent turns that into an actual call, then the risk team and portfolio manager approve or reject it before anything fires, same as a real desk 9. backtest the full pipeline across a grid of tickers and dates, it scores every decision on real alpha against the benchmark and logs what worked so it gets sharper each run 10. the agent debate takes minutes, so wire Jev in as the fast layer - it'll makes the final live call in just milliseconds > this turns this research firm into a real self-improving 24/7 AI trading agent the full build of AI trading bot that makes it trade live is in my article below:

Holy sh*t, I wish I’d found this earlier. someone put 300+ AI agent projects into one free GitHub repo because half the time you think you need to build something new… someone already built it. agent memory? there. browser control? there. coding agents, sandboxes, evals, voice, multi-agent teams, local models? all there. so I went through the list and started connecting the pieces: > RUN - Ollama runs the model locally > BUILD - LangChain connects everything > CODE - Aider + Continue work inside your codebase > ORCHESTRATE - CrewAI + AutoGen manage the agent team > ACT - E2B + Composio give agents tools and somewhere safe to run > REMEMBER - Mem0 keeps memory between sessions > WATCH - AgentOps shows what your agents actually did > SHIP - Vercel AI SDK helps turn it into a real product but here’s what clicked for me: the list isn’t really a list. it’s a build-your-own-agent menu. model -> framework -> tools -> sandbox -> memory -> evals -> product missing something? don’t spend the weekend rebuilding it. find the category -> see what already exists -> grab 3 options -> check which one’s still alive -> start there. and if you want to build on top of the list itself, they even give you the ecosystem data in JSON + YAML. > no signup. > no paywall. > MIT licensed. > 300+ projects in one place. basically, before I build anything agent-related now, I’d check this repo first. I pulled out the projects I’d actually start with + the best stuff from each category below

Crypto is a group chat with a chart. Charm is where you actually meet the people. @TheCharmPad Scroll. Connect. Launch a coin together. Trade it on CharmPad. Meet. Launch together. Trade. Get paid. charmplay.io

I HAD A 74% WIN RATE AND LOST $11,400 IN TWO YEARS. CLAUDE SAID ONE SENTENCE AND I MADE $8,900 IN 6 WEEKS "you take profits like a coward and losses like a hero" i laughed. then i opened my trade history and stopped laughing my average win was +$140. my average loss was -$610. i was right three times out of four and still bleeding, because every time i was wrong i held it like a religion this is the thing nobody on this app wants to hear. win rate is a vanity metric. the only number that matters is expectancy: what you make when you're right times how often, minus what you lose when you're wrong times how often mine was negative. a 74% win rate with negative expectancy is just a slower way to go broke so i stopped letting myself manage exits. claude reads every open position and jev decides one thing: is the reason i entered still true. the moment that drops below 0.80, the position is gone. no hoping, no averaging down, no "it'll come back" my win rate fell to 51%. my average loss went from -$610 to -$95 six weeks later i'm up $8,900. two years of being right never paid me once being right feels amazing. being paid feels different what's your win rate? i'll tell you if it's lying to you

Sam Altman (CEO of OpenAI) just revealed how he uses Dots: at DevDay, he recounted how he spent 10–20 minutes searching Slack and couldn't find what he needed Dotty kept searching overnight the next day: it found the missing screenshot that's one part of his setup: → protects his mornings by filtering noise and surfacing urgent issues → catches urgent decisions in the gaps between meetings → builds 5–6 feature versions from raw notes → keeps a business dashboard updated around his changing priorities the move: give your dot a responsibility it can keep owning paste this into your dot ↓ Protect my morning focus. Surface urgent decisions with context. Keep a live dashboard of my priorities. Turn rough feature ideas into local prototypes for review. Ask before sending messages or changing shared systems capture the idea → let work continue → review what comes back study the entire system, then build your company with Dots ⭣

THIS IS HECKING INSANE! free gold for anyone who wants an OpenAI Dots-style agent but don’t want to pay for $200 subscription. i found a repo with 2.4K stars in 3 days that gives you an open-source AI agent with its own browser. it runs on your machine and works with any model you want. it's called dots, and the idea behind it is smarter than most agent projects i've seen this year. here's the breakdown: → the insight that started it all. - most people think web agents fail because the model isn't smart enough. the author argues the opposite: the model is rarely the problem. the page never loaded, a challenge popped up, the login expired, the click didn't land. all of that happens in the browser, before the model even gets to think. so instead of chasing a better model, they rebuilt the browser. → a real browser engine, not a wrapper. - most agent tools drive Chrome through automation hooks and then try to hide those hooks with JavaScript patches. dots doesn't. it uses a real Firefox engine patched at the C++ level, so the browser's fingerprint is set inside the engine itself. there's nothing painted on top for a page to inspect. → one consistent identity. - screen size, fonts, GPU, timezone and language all match each other, like a real device would. pass the same seed and you get the exact same "person" on every run, so logins and sessions keep working instead of starting from zero each time. → nothing that screams "bot". - no WebDriver flag, no DevTools protocol, no automation globals sitting in the page. most automation stacks leak these signals by default. → it moves like a person. - the pointer actually travels to what it clicks, and keys are pressed one at a time. every event the page receives looks like it came from a real user. → the model is swappable. - you plug in an OpenRouter key and choose the model with one flag. today's best model, tomorrow's cheaper one, or an open-source one: the agent doesn't care, because the hard part lives in the browser. → setup is one command. - one uvx line on Windows or Linux, then open localhost in your browser. the conversation is on the left and the live browser is on the right, so you watch every click as it happens. OpenAI ships Dots as a closed product inside a paid plan. this is open source, runs locally, and you own the whole stack. i dig up repos like this every week before they hit the timeline. stay tuned so you catch the next one early, and show it to the friend who's still paying for agents they can't look inside. so be honest: if the browser is the real bottleneck, are we wasting our time arguing over which model is best?

زوجان حاولا معرفة جنس الجنين أثناء فحص الأشعة، لكن الصغير داخل البطن قرر يكشف الإجابة بنفسه وبكل ثقة.. واضح أنه كان «متباهيًا» من بدري!