An American TV crew filmed a 24 year old Chinese engineer in his San Francisco apartment for a feature on remote workers who never leave home. He had not been to an office in eight months. AI handled his calls, his messages and every reply his bosses got, while he collected a salary from five companies at once. On camera he said the line everyone screenshotted: going to five morning calls would be exhausting, so I push them all into AI and stay in VR. His story was simple. Meta hired him from a research lab. The job was remote. He preferred meetings in VR. So he wore the headset all day. So nobody saw him. The crew thought that was the story. It was not. Pause at 0:25. The camera holds on the wall behind his desk for four seconds. Look at the shelf above it. Everyone saw one laptop. Almost nobody saw the other four. The four were not backups. The four were jobs. Each laptop runs an AI trained on the way he writes. Each one joins the morning calls in his voice. They talk to each other so the same work never gets done twice. He sits in the VR headset and watches the five jobs unfold around him. For months all five teams have been thanking him for being so responsive. None of them has ever been in the same call as another. He still wears the same headset every morning. He still sits in the same chair. He still passes every review. He still has not told his mom about the other four jobs. The crew came to film a remote worker who lived on a mattress on the floor. They left with a man who had not done a single day of work himself in eight months, while five American companies kept thanking him. His AI replied to all five morning calls again today. He watched. They thought: he is really trying.

Google's former CEO just said what everyone in AI already knows Building wealth is getting easier if you actually learn the tools Not by scrolling AI threads By understanding agents, Codex Code, prompts, memory, skills, MCP, and routines Save this before it disappears from your feed Everything below is free: ChatGPT basics help.openai.com/en/articles/… OpenAI Academy academy.openai.com/ Prompt engineering developers.openai.com/api/do… GPT-5.5 prompting guide developers.openai.com/api/do… OpenAI API docs developers.openai.com/api/do… Responses API developers.openai.com/api/do… Agents SDK developers.openai.com/api/do… Agents SDK quickstart developers.openai.com/api/do… Tools function calling developers.openai.com/api/do… Structured outputs developers.openai.com/api/do… Conversation state developers.openai.com/api/do… ChatGPT memory help.openai.com/en/articles/… ChatGPT projects help.openai.com/en/articles/… Custom GPTs help.openai.com/en/articles/… Tasks in ChatGPT help.openai.com/en/articles/… Codex overview developers.openai.com/codex Codex quickstart developers.openai.com/codex/… Codex CLI developers.openai.com/codex/… Codex GitHub repo github.com/openai/codex Codex best practices developers.openai.com/codex/… AGENTS.md developers.openai.com/codex/… Codex skills developers.openai.com/codex/… Codex MCP developers.openai.com/codex/… Codex subagents developers.openai.com/codex/… ChatGPT Apps SDK developers.openai.com/apps-s… Apps SDK quickstart developers.openai.com/apps-s… ChatGPT developer mode MCP developers.openai.com/api/do… OpenAI Cookbook github.com/openai/openai-coo… All of this costs $0 Most people will keep asking AI one question at a time Save this and start learning the stack

Someone cloned Netflix. Then cloned Spotify. Then cloned Instagram. Then cloned Airbnb. Then cloned WhatsApp. Then cloned TikTok. Then cloned Amazon. Then put the source code for all of them on GitHub. For free. Not one app. Not ten. Over 100 open source clones of the biggest apps on Earth. With source code. With demos. With tech stacks listed. It is called Clone-Wars. 34,555 stars on GitHub. Built by an Indian-origin developer named Gourav Goyal. He started collecting open source clones of popular apps into one list in December 2020. In March 2021, it went from 0 to 4,000 stars in 7 days. It was on GitHub Trending for 5 days straight. Someone posted it to Hacker News and it hit #1 on the front page. Here is what is inside. Netflix clones. React, TMDB API, full streaming UI. Spotify clones. Music player, playlists, search, albums. Instagram clones. Feed, stories, likes, comments, DMs. WhatsApp clones. Real-time messaging, read receipts, group chats. Airbnb clones. Search, booking, maps, payments. Amazon clones. Products, cart, checkout, Stripe payments. TikTok clones. Short video feed, upload, likes. Twitter clones. Feed, follow, tweet, retweet. Slack clones. Channels, threads, real-time chat. Trello clones. Boards, cards, drag and drop. YouTube clones. Video player, search, comments. And 90 more. Every clone has source code, a live demo, and the tech stack listed. React, Next.js, Node, Firebase, MongoDB, GraphQL, Tailwind. Every modern stack represented. Here is why this matters. Coding bootcamps charge $10,000 to $20,000 to teach you how to build apps like these. Udemy courses charge $50 to $200 each. One app at a time. One framework at a time. This repo gives you 100 fully built apps with source code you can read, fork, and learn from. For $0. Here is the wildest part. The best way to learn to build Netflix is to look at someone who already built Netflix. Not a tutorial that teaches you one feature at a time. A complete, working clone with every feature connected. You do not learn architecture from tutorials. You learn architecture from reading real projects. 100 apps. 100 demos. 100 source codes. One repo. Bootcamp: $10,000 to $20,000. Teaches 2 to 3 projects. Udemy: $50 to $200 per course. One project each. Clone-Wars: $0. 100 projects. Every big app cloned. 34,555 stars. AGPL-3.0 licensed. Every app you use. Cloned. Open sourced. Free to learn from. (Link in the comments)

AMD CEO LISA SU HELD A MINI PC ON STAGE THAT RUNS A 235B MODEL AND REPLACES YOUR $440/MONTH AI STACK amd's ryzen ai max 395 is the first x86 chip that runs a 200 billion parameter model on one piece of silicon. cpu and gpu share 128gb of unified memory, no separate graphics card needed the gmktec evo-x2 runs qwen3 235b fully, deepseek v3 comfortably and llama 3.3 70b with headroom. on linux you get 110gb of usable vram out of 128gb amd claimed the chip beat an nvidia rtx 5080 by more than 3x on deepseek r1 inference. a lunchbox sized pc outrunning a $1,000 discrete gpu on a real ai workload a heavy ai user pays $200 for claude code max, $200 for chatgpt pro, $20 for cursor and $20 for gemini. that's $5,280 a year and the box pays itself off in 9 to 10 months install ollama, pull the model, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below

to mock on ur stupidity of course, what else 😆

🔥 STOP “VIBE CODING” — GITHUB BARU DROP TOOL GRATIS YANG UBAH CARA KITA BUILD SOFTWARE Sekarang GitHub ngerilis tool open-source yang konsepnya lumayan mindblowing: bikin ide jadi spesifikasi yang jelas sebelum lo mulai ngoding. Nama tool-nya: Spec Kit 💡 CARA KERJANYA: → Lo jelasin ide produk lo → AI ubah jadi spec yang rapi dan terstruktur → Dibikin juga rencana implementasi yang jelas → Baru dari situ bantu proses build projectnya ⚙️ YANG BERUBAH DARI CARA LAMA: Dulu orang langsung “vibe coding” — langsung ngoding tanpa arah jelas, sambil improvisasi terus. Sekarang konsepnya digeser jadi: → mulai dari requirement yang jelas → behavior system yang terdefinisi → outcome yang udah ditentukan dari awal 🚀 HASILNYA: → Lebih sedikit trial & error → Output lebih konsisten → Arah development lebih jelas → Gak gampang nyasar di tengah jalan 🧠 MENARIKNYA LAGI: → Bisa dipakai bareng berbagai AI agent populer → Jadi gak tergantung satu ekosistem aja → Open-source, jadi bisa dipakai siapa aja gratis 💥 INTINYA: Ini kayak “naik level” dari ngoding spontan jadi ngebangun software pakai blueprint yang bener-bener jelas dari awal. 🔥 REAL TALK: Kalau ini dipakai serius, cara orang bikin software bisa geser dari “asal jadi dulu” ke “desain dulu baru eksekusi”. github.com/github/spec-kit

I DON'T UNDERSTAND WHY PEOPLE STILL DON'T USE THESE CLAUDE SECRET CODES IN 2026 You can use them daily to learn and master any skill 10x faster and easier Here are 10 powerful codes (bookmark this now)👇

This guy used Claude Fable 5 to upgrade the Quant Bot that made $288,872 on Polymarket Since Apr 30, this wallet has been averaging roughly $6,878 in profit per day while putting up about 30 trades per hour on short Bitcoin “Up / Down” markets 30,670 predictions with a 56% win rate in 42 days This trader’s Polymarket account:polymarket.com/@0xce25e214d5… He started with a $54.3K deposit and is now up 531.8% ROI The bot strategy is simple: >It waits for short-term pricing to drift away from fair value >Gets in before the board fully reprices then reuses that same setup across a huge number of entries >The gain on any single trade is not the whole story, the real edge comes from running the same process over and over at scale Most profitable trades: $2,851 → $7,332 ( $4,480 157.13%) $881 → $4,756 ( $3,874 439.34%) $3,455 → $6,319 ( $2,864 82.9%) It is a repeatable short-window system that keeps converting small pricing errors into a steadily rising PnL curve

You can make $500 per day if you have: 1. A laptop 2. Wi-Fi 3. Time Here are 10 Claude Prompts that pay you daily:

Claude 5.0 built a Chinese girl a trading bot. skip to 0:08 look at her journal, bot easily earns your monthly salary in a couple of days. how it works: the bot runs mean reversion on s&p 500 and nasdaq on 15-min candles, catching the small overextensions indices make every few hours. on bitcoin it switches to momentum breakouts on the 1-hour crypto trends harder than indices, so you ride the move instead of fading it. gold and oil get a slower trend-following layer on the 4-hour, because commodities move in cleaner waves and you don't want noise from intraday whipsaws. position sizing is ATR-based per instrument, so a quiet day on gold gets a bigger size than a volatile day on bitcoin - risk stays constant even when volatility doesn't. every trade has a hard 1% stop, no exceptions, no "let me give it room." and there's a correlation filter on top: if s&p and nasdaq are already long, it won't pile into another risk-on asset and double the real exposure. claude code writes and updates the logic. the bot just executes. then claude cowork sends her two messages a day: - 7am: what's happening in the market - 9pm: how did the bot do that's the whole job. two messages. five instruments. zero screen time. manually she could only watch one chart at a time. this thing watches five. doesn't sleep. doesn't tilt. doesn't revenge trade at 2am. what used to need a team of quants and a $200k bloomberg terminal now runs on a laptop and claude. And your friend is still trading manually and is constantly in the red. save this and read the article in the comments below to write your own bot using Claude