A 17-year-old clears $9,000 a month with a laptop, Google Maps and an AI site builder. no clients chased, no cold DMs. HER SYSTEM WORKS LIKE THIS: - OPEN GOOGLE MAPS and scan a neighborhood for businesses with old or missing websites - PICK ONE that clearly makes money but looks invisible online (restaurants are gold) - BUILD the new site with AI (Lovable) -> real menu, real photos, mobile-ready, done in an hour - SEND the owner the finished before/after, not a pitch - CLOSE the ones who see their business look premium for the first time she flipped the freelance model. instead of "hire me and maybe I'll build it," it's "here's your new site, want it?" the work sells itself because it already exists before she ever asks for a dollars.

A 17-year-old clears $9,000 a month with a laptop, Google Maps and an AI site builder. no clients chased, no cold DMs. HER SYSTEM WORKS LIKE THIS: - OPEN GOOGLE MAPS and scan a neighborhood for businesses with old or missing websites - PICK ONE that clearly makes money but looks invisible online (restaurants are gold) - BUILD the new site with AI (Lovable) -> real menu, real photos, mobile-ready, done in an hour - SEND the owner the finished before/after, not a pitch - CLOSE the ones who see their business look premium for the first time she flipped the freelance model. instead of "hire me and maybe I'll build it," it's "here's your new site, want it?" the work sells itself because it already exists before she ever asks for a dollars.

Claude Code head just did a 32-minute breakdown of how the tool actually gets used: 2:40 – what Claude Code really is under the hood 6:22 – agents that go book things for you 9:45 – tokenmaxxing, and whether the demand is real 18:27 – are agents too inefficient to scale 27:45 – rate limits and what they're actually protecting "you can't identify these engineers ahead of time → it's almost always going to surprise you" 32 minutes worth more than any paid Claude Code course Bookmark this..

Claude Code head just did a 32-minute breakdown of how the tool actually gets used: 2:40 – what Claude Code really is under the hood 6:22 – agents that go book things for you 9:45 – tokenmaxxing, and whether the demand is real 18:27 – are agents too inefficient to scale 27:45 – rate limits and what they're actually protecting "you can't identify these engineers ahead of time → it's almost always going to surprise you" 32 minutes worth more than any paid Claude Code course Bookmark this..

Google and Anthropic just built an app without writing a single careful prompt: "it's not about the exact prompt" here's the workflow, step by step: 10% → 0:15 – stop tuning the prompt – intent is what you're actually shipping 15% → 0:37 – describe what you want, then let it express it 25% → 4:35 – run the same thing at enterprise scale 70% → 17:04 – change the environment instead of re-prompting the change 90% → 24:31 – sub-agents you never asked for, each with its own context most people are still perfecting one prompt at 30:33 he says the job changed: you're not writing the code, you're owning it watch & bookmark, then read the 12 steps to a fleet that checks its own work below

Agent memory, from the team that shipped it: "you don't want the latency of including everything" here's the memory pipeline, step by step: step 1 → 5:50 – working memory first – it has to hold this conversation before it holds a history step 2 → 12:09 – extract memories from the conversation, not from the log step 3 → 13:30 – "my name is Kim" said twice is not two memories step 4 → 13:42 – consolidation – contradictory memories are worse than none step 5 → 19:14 – generate memory in the background, never on the user's latency path most people dump the whole transcript into context and call it memory that's a log, and it gets slower every single run watch & bookmark → then read the full graph engineering guide below ↓

Google's new Agents CLI builds a working multi-agent app without you opening an editor: "prompt history is the new code" here's the workflow, step by step: step 1 → 0:14 – install the CLI, stay in the terminal – no IDE for the whole session step 2 → 2:06 – build the first agent from an empty folder – scaffolding is generated, not written step 3 → 9:45 – run evals before you trust it – the step that separates a demo from a tool step 4 → 15:20 – prompt a two-agent system: one analyzes, one roasts – multi-agent is now one prompt step 5 → 20:52 – deploy it – the repo gets open-sourced, the prompt ships with it most people still think this needs an IDE and a week at 21:07 he says he'd have called it impossible six months ago watch & bookmark this

A 23-year-old makes $11,000 a month building full arcade games from a single AI prompt he doesn't design games. he describes them. he points Claude Opus 5 at one instruction: -> "build a playable Rocket League in the browser, make the assets, wire the game loop, check for errors until it runs" -> and it ships a finished game on localhost. he's done it with a Rocket League clone, a Stardew-style farm, a Plants vs Zombies. then he turns the clips and the games into caps: - the "one prompt built this entire game" videos -> millions of views, sponsor slots from AI tools - the games dropped on web-game portals -> paid per thousand plays, no store, no publisher - a prompt pack + "build a game in an afternoon" guide -> sold to everyone who wants in - playable-ad mini-games for brands -> delivered in a day, near-100% margin $11,000 a month, and the hardest part was writing one good paragraph. he didn't learn Unity. he learned to describe a game precisely enough that a model builds it for him.

Factory is migrating 40-million-line codebases with agents. Their FDE lead showed how: "migrating 30, 40, 50 million plus line codebases fully autonomously" 10% → 3:33 -- the ROI story, and what the software factory is 30% → 5:27 -- why you have to own the agent harness 55% → 8:38 -- the teach-the-model step everyone skips 70% → 10:35 -- what you only discover inside a real codebase 100% → 13:23 -- 40 million lines, migrated autonomously everyone selling agents claims full autonomy at 16:54 he says his own company runs at 15-20% and that's the honest number watch & bookmark.

How to get AI to generate luxury ads without "floating" geometry The main problem with video generators is blurry logos and distorted details. A visual breakdown of the second-by-second prompt for a Hublot watch in Seedance: [00:00] Macro shot of the strap under grazing side light. [00:03] Camera pans over the dial and movement components. [00:07] The case emerges from the darkness on a red rocky surface. A clear timeline in the prompt is the only way to achieve studio-quality physics and 100% product consistency.

one of the richest men on earth talked for 26 minutes at Stanford, no script, no PR, for free.. i've seen $300 courses teach less.. the whole thing lands on one idea: "if you're still writing prompts, stop, and build loops instead." why it's worth the 26min: -> it's the same argument he makes to boardrooms, said plainly to students -> no upsell, no funnel, no "link in bio" -> just the thesis and the reasoning -> it reframes AI from a thing you chat with into a thing you engineer don't just watch it. build one loop after -> the smallest task you'd normally repeat by hand, wrapped so it runs itself. the talk is free. the people who act on it are the whole point. Save and Watch this video..

the shift Jensen Huang keeps pointing at, in one line: the job stopped being writing prompts. it's building loops.. a prompt is one shot. you type, it answers, you babysit. a loop runs. it plans, acts, checks itself, tries again, keeps going while you sleep. everyone's still perfecting the sentence. the edge moved to the system around the sentence. prompts are the typing. loops are the leverage..

A 25-year-old guy from China built a bot that trades prediction markets and cleared $9,000, without betting on gut once.. -> He'd blown up small accounts guessing. -> So he stopped guessing and built a system. pm-agent runs several LLMs (Gemini, DeepSeek, GPT, Qwen) in parallel, each reading live signals, BTC price, order book, MACD, RSI, and outputting a structured buy/no with a confidence score. The discipline is the whole thing: > it only enters when the market price is well below the modeled probability > win rate over the last 24 rounds -> 62.5%, not 100 > hard stop-losses and small sizing, because prediction markets take everything from people who over-bet > he tested in simulation for 50+ rounds before a single real cap Save this..

150 AI agents. 15,000 steps. 522 claims, 890 pieces of evidence. One prompt, 39 minutes flat. All of it aimed at one job: find where a live Bitcoin market is mispriced. It found it - a bet trading at 83 cents that had already won. That is a hedge fund research desk, run from a text box. Last year the same job needed 28 tools and a team you had to hire. The call settled four days later, exactly as it read - Bitcoin ripped past $66,000 on July 22 while sellers dumped the contract at 83 cents. It also ranks #1# on FutureX, the live prediction board scored by Stanford, Princeton and ByteDance - on its smallest model, not its biggest. The guy behind it put $1 billion into science and now hands research labs $100,000 a month of this compute for nothing. Full breakdown below - read & bookmark it.

A 23-year-old turned a school diploma project into $1,000. It's a trash can that sorts itself.. HIS BUILD WORKS LIKE THIS: - A MICROCONTROLLER + camera + display + Bluetooth - 4 MINI-BINS for the categories: recyclable, organic,hazardous, other - PRESS A BUTTON -> a servo pops open the right bin - one clean, filmable, "smart" device out of $30 of parts Then he sold it every way it monetizes: > DIY "build it yourself" kits -> students and hobbyists on Etsy > Shorts of the sorting in action -> millions of views, affiliate links to the parts > the code + 3D-print files -> Patreon, Gumroad, Thingiverse He didn't invent recycling. He packaged a diploma project people would pay to build. Bookmark this..

A 26-year-old makes $11,000 a month building AI agents on a model that costs him almost nothing. His setup is a "harness swap": -> Codex is the control system -> DeepSeek is the model 1 goal, typed once → Codex plans and executes it step by step → a local agent reads his files, keeps context, writes and runs the code → DeepSeek powers it all for a fraction of an OpenAI subscription. 3 ways he turns it into caps: > sell the config packs and system prompts as a paid guide > build MVPs and parsers for clients in a fraction of the usual time > drop the same AI agents into small businesses that can't afford OpenAI prices He doesn't ping a chatbot. He runs an autonomous coder on the cheapest model that works.

He is 63. His net worth is valued at $170 billion. Jensen Huang walked on stage and pulled what looked like a whole computer out of his pocket. everyone's asking the wrong two questions. NVIDIA crammed a CPU, a Blackwell-class GPU and up to 128GB of memory into one tiny machine and framed it as the end of the PC as we know it. -> a 20-core Grace CPU plus a GPU in the RTX 5070 tier, in a 14mm body -> claims of 100+ FPS at 1440p, on battery -> it runs a 120-billion-parameter model locally, no cloud -> vendors reportedly already have 30+ laptops lined up around it the whole internet is arguing about two things: is it real, and how much. nobody's asking the third: if one pocket-sized box does all of that, what happens to every other chipmaker that sells the pieces separately??

Turning $1,000 into $72,000 off a single ticket isn’t luck anymore. Here’s why I’m telling you this… Polymarket is handing out $25,000 daily for the best combo, and the current leader just pulled a 72x on a single slip. We’re talking a 15-leg deep parlay where one mistake wipes out everything, you don't need intuition here, you need precision engineering. That’s exactly why the "Sides" agent does the heavy lifting for you: it scans correlations across all sports, cuts out the landmine legs, and packages the rest into a ready-to-go ticket you confirm in a single tap. While most people just throw together five of their favorite teams and pray, the agent engineers a coupon built to actually survive all 15 legs. Just type "build me a combo" to the bot or in any group chat.

Still baffled that one developer can build an entire indie game alone, then get quoted $5,000-12,000 just to make people notice it this solo dev is already building the world, combat and new abilities himself. the game can cost months of work, while a basic trailer still starts around $1,000-3,000 before it even looks cinematic. somewhere a studio is preparing a five-figure invoice while the same developer can connect Higgsfield MCP to Claude and turn one strong gameplay moment into a reveal shot in under a minute. it’s the same trailer pipeline, compressed into one chat: ＞ key art + 4K upscale for 4 credits ＞ 8-second cinematic clips for 16-72 credits ＞ roughly 60-300 credits for a 30-second trailer ＞ new lighting, camera moves and pacing through one follow-up prompt bookmark this before your indie game is finished and the trailer costs more than the game.