Asher Crowe 🪺

I scrolled TikTok for 20 minutes last night and slowly realized something that made me put my phone down. None of these women exist. Not one. The redhead applying sunscreen on the balcony. The brunette in the green sports bra doing the heart shape with her hands. The blonde stretching in front of the bathroom mirror. The girl on the floor laughing into the camera while holding the bottle. Every single one of them is AI generated. Every account is fake. SunscreenAddict. ActiveGlow. concentration.7. obsessed. extra. Names designed to sound like real twenty-something skincare girls. Bios written to read like every other lifestyle creator on the platform. Posting schedules timed to mimic human behavior. The entire feed I was watching, the one TikTok served me when I searched a single product, was a coordinated swarm of synthetic influencers all selling the same bottle. Hundreds of thousands of views. Each. 512K on one. 358K on another. 232K. 200K. 199K. People in the comments tagging their friends. "Need this." "Where can I buy." Real humans, having real reactions, to women who do not exist. Let me walk you through what's actually going on here, because the mechanics are wild. Someone, or more likely a small team, generated a roster of fake "influencers." They picked diverse looks on purpose. Blonde, brunette, Asian, redhead, Black, mixed. Different body types. Different home aesthetics. Different lighting. Some on balconies. Some in bathrooms. Some in bedrooms. So the feed looks organic, like the product is having a moment with every demographic. Each "creator" got an account, a name, a personality, and a posting schedule. They probably look at their analytics dashboard the same way a real creator would. Then the same product gets reviewed across all of them. Same talking points. Same captions. Same hashtag set. Twenty different "real girls" all converging on the same recommendation in the same week. To the algorithm, this looks like a genuine trend. To you scrolling at midnight, it looks like every girl on the internet is suddenly obsessed with this one bottle. That's the trick. It's not that one fake account got views. It's that twenty of them did, simultaneously, creating the illusion of cultural agreement. Manufactured consensus. It's the oldest marketing tactic on earth, just executed at a scale and speed no human team could match six months ago. And here's the part that broke my brain. You cannot tell. I mean it. I have a developer eye for this stuff. I look at AI-generated content for a living. I had to zoom in on three of these to be sure. The hands give it away if you look closely. Sometimes the bottle label is slightly malformed. Sometimes the reflection in a bathroom mirror doesn't match. But on a phone, mid-scroll, at two in the morning, with one thumb? You'd never catch it. Nobody is catching it. The whole "AI looks fake" defense people had a year ago is gone. Dead. The current generation of image-to-video models renders skin texture, fabric folds, depth of field, and natural movement in a way that slides right past the radar. Three things to take from this, because the implications are bigger than skincare. The trust signal you used your whole life — "I saw a real person say it" — is no longer reliable on social media. You're being marketed to by ghosts. Every product category is about to get this treatment. Skincare is just the early adopter because the visual content is easy. Supplements are next. Then fitness. Then home goods. By next year, "influencer marketing" will be a phrase that needs a footnote. If you're a real creator competing for views right now, your competition isn't other humans anymore. It's a server farm in someone's apartment generating 100 versions of you while you sleep. I'm not saying any of this is good or bad. I'm saying it's already happening. Right now. On the device in your hand. And almost nobody is paying attention. Save this post. Show it to anyone who still thinks they can spot AI content in the wild. The girls in your For You page have rooms that don't exist, in houses that were never built, holding products they've never touched. Keep scrolling. But scroll knowing.

@0x_fokki build, scale, flip, repeat, the whole app economy is just digital house flipping with worse hold times

🚨23 year-old guy flipped 4 apps and made $500,000 The App-Flipping Playbook: how to build micro-apps and cash out fast Lots builds simple mobile apps, scales them to $15,000 MRR in a few months, and flips them. Buyers think they’re acquiring a complex tech product built by a whole engineering team. They’re buying simple wrappers, put together fast, backed by aggressive marketing. His focus: ultra-niche apps (like an AI therapist for Christians or a screen blocker that requires you to pray to unlock your phone). average exit price: $125,000+ per app time to exit: 6–12 months tech stack: dead simple (plug-and-play) total earnings since 2022: $500,000+ 4 successful exits. One founder. Zero venture capitalists. His step-by-step playbook: Market Scanning: Finds what’s already printing in the App Store top charts and verifies the revenue via Sensor Tower. Single-player Value: No complex social mechanics. The app must deliver value to a single user immediately, no friends required. Viral Marketing: Creates "rage bait" videos on TikTok for an organic algorithm boost, then scales the winning creatives via Meta Ads. Result: $0.30–$0.50 CPI in the US market. Fast Exit: Lists the project on MicroAcquire strictly on a 3-month upward growth trend. The ultimate sales hack: Lots never goes with the highest bidder. He picks the third-highest offer and closes the deal in 3 days before the hype cools down. The market is highly liquid and tech has become cheap. Buyers pay for immediate cash flow and distribution. They never ask if the code took 3 years or 3 weeks to build.

@marlowxbt 1,000 cold calls a day and somewhere a thousand bakeries are now screening their phones forever

A 14 year old made $55,000 in 7 months from cold calls he stopped making in month 2. His AI agent makes 1,000+ of them per day. He has 110 clients now. He spent the first two months calling personally. Same script every time. Same yoga studios and bakeries in Austin. By call 80 he had closed 7 deals. By call 200 he knew the exact 60 seconds that turned "we're not interested" into "if it's up to me, yes." He fed the script to an AI agent. Hooked the agent to Sitedrop AI Lead Finder. Now the agent runs the whole loop. It pulls 50 businesses with no website every morning. Generates a demo site for each one in 4 minutes. Dials every owner. The script the agent reads: "Hi Samantha. I noticed you don't have a website. I already built you a free sample. Can we hop on a call tomorrow?" She says yes. The next day the agent sends the link. The site is real. Custom logo, real photos pulled from her Instagram, working booking page. She asks about price. The agent: "A lot of website guys charge thousands. I don't do that. One payment of $500. If you like it we proceed. If you don't, it's completely free." She said: if it's up to me right now, yes. 110 deals. $55,000 banked. The whole operation runs while he is in school. His parents think he is doing homework. The receipts in his Notes app say otherwise. There are 140 million businesses on Google Maps without a website right now. The agent dialed 23,000 of them in the last 30 days. It closed 31 in the same window. The call is 90 seconds. The site is 4 minutes. The agent does both while he sleeps. Save this post. The script alone is worth $500.

@browomo $1499 to $140 is a brutal price chart, somewhere an after effects plugin is doing a victory lap

This Chinese student used to charge $1499 for 15 seconds of studio-grade animation. Today AI does the same thing for $140 right inside his own After Effects. Now the model sets the keyframes itself, drives the camera and computes the easing curves. He used to crank out every one of those frames by hand, right there in the interface. His work was always pure taste and craft. He kept the timing, the composition, the easing and every button of After Effects and Cinema 4D in his head. Studio quality rested on exactly these people. On living animators. They knew how to build the concept, the storyboard and the final render by hand. And the collapse turned out to be insultingly simple. It all came down to a bridge between the model and the core of After Effects. An AE MCP Bridge spun up locally. Through JSX scripts the model writes clean ExtendScript itself. It plans the effects, assembles the compositions and computes the camera shake. And it does this faster than the student can storyboard his own idea. In this setup there's no animator anymore, no storyboards, no manual keyframing. The whole job is carried by just the model, ExtendScript and a single start_render command. Ready-made studio time still costs many times more on the market. His old rate reached $1500 per clip and ate up 2 or 3 days at the timeline. The bridge itself was also written by the model, not him. Inside there's no pretty shell. What lives there is a bare pipeline with exact steps. The input is a folder of photos and one human sentence. Then in seconds the model writes clean ExtendScript, builds New FX comps, adds camera shake and 3D transitions. And the output is a finished .aep project. The only thing you fix by hand is the text. And this is where it gets interesting. The scene no longer needs to be built by hand. A marketer just drops in a folder and tells the model in plain human words, without a single technical term. Something like "make these photos into an aggressive 15-second TikTok edit, red and black." That's it. Click. The script wrote itself. Built the graph and made the transitions. And in just 1.5 hours it dropped a finished project with no human involved at all. Let's put the economics together. The picture comes out like this. // an agency charges $500 to $1500 for 15 seconds of graphics and spends 2 or 3 days on it // with the model the same clip costs $140 and 1.5 hours // one freelancer easily handles a full 10 commercial orders at once // stock templates from Envato and MotionArray turn to dust // a margin of nearly 100% goes to whoever wraps this bridge into a finished agent His own words at 3 a.m. sound more honest than any analysis. He admits himself that this thing learned from just 3 of his projects. And it already does motion noticeably better than he does. In the end the student outran his master on the 3rd lesson. But the most honest part of this whole story is simple. He names his mistake himself. And it's not in the animation at all, it's in the positioning. He tied his income to manual keyframes and to hours at the timeline. He keeps selling those hours. And that's why he inevitably stays behind. The machine renders faster than he can sketch out a storyboard. He spells out the right move himself, too. It's the shift from the role of a pixel generator to the role of a systems architect. Then you're no longer selling your hours. You're managing compute. You wrap that same bridge into an autonomous agent. It calmly runs orders around the clock. Sadly. This year I've seen plenty of stories about creative professions disappearing. This one is the most honest. $1500 per clip collapsed into $140 of tokens. A living student lost to his own script. A whole task is now stated in human words instead of a hand-built scene. And right away, out loud, comes the admission of a wrong business model. The barrier to entry into studio-level motion just dropped to the level of "describe the edit in words." And now only one single question remains. Who will be the first to stop selling their hours at the timeline and start managing someone else's compute?

@rewind02 wild expose energy for what is essentially you can save text files

Boris Cherny explained how the internal team is actually structured said it in a 28-minute video over a year ago here's what's actually happening inside Anthropic's workflow: slash commands are stored files - in your home directory or checked into the repo Anthropic has a slash command that labels GitHub issues autonomously commands in the repo create a network effect. one engineer builds it. the whole team benefits personal commands stay local the # key is the fastest way to start check out the full version below👇

@0xKiyoro the niche is the secret, the prompt is the secret, the connector is the secret, at some point everything is the secret except actually making good videos

The gap between a dead channel and a $30,000-a-month one is the niche, and most people are still guessing it with keyword tools Claude reads live data instead and hands you the gaps before they're obvious > one MCP connector, one prompt, no keyword tools, no guesswork > it scans what's actually happening and returns 4 untapped high-CPM niches > specific ones nobody's posting to yet, not the saturated obvious picks > CPM estimate, content angle, and why now, in 4 minutes By the time a niche shows up in a keyword tool, the window's already closing reading live data means you reach the $30k niche in the 6 weeks before everyone else does

@xkaidus doing street interviews with someone who doesn't exist while relaxing by the pool is the laziest possible empire and i kind of respect it

This guy pulls in $25,000 a month from street interviews with an AI girl who simply does not exist in nature, while he sleeps or relaxes by the pool. He got tired of watching SMM agencies burn tens of thousands hunting for creators and shooting endless reshoots, so he built a node-based system that autonomously drops an AI face into any location and generates free traffic. Zero live influencers. Zero spending on mic rentals. Zero studio budget. Here is the exact breakdown of the algorithm: → First he picks a psychological trigger and generates provocative quick interviews. In the clip the AI girl walks up to people on the street and offers them a chance to guess her age for $1. After a dozen wrong answers (22, 29, 30) she tells the camera she is 18. A visual cognitive dissonance kicks in and pulls the audience in from the first second. → He lays this audio base over stock or pre-shot video of a real actor (a body double on the street). This skin-walking method saves time generating a body from scratch. → ComfyUI through node chains locks her Master Face so it never drifts between clips. Wav2Lip syncs the lip movement flawlessly to the finished ElevenLabs voiceover. → The TikTok and Reels algorithms get a flood of reactions in the comments and push this content into the recommendations of millions of people for free. → Referral links in her profile close app sales. D2C brands hand him money directly to advertise an energy drink or clothing on the avatar's digital body in frame. The key step that 96% of beginners miss: you bet only on a pretty face. Crank out a beautiful perfect girl and within a week you get buried under a pile of 400 identical AI clones. Make her a talking head who interacts with people, breaks their expectations and throws out controversial social scenarios and you monopolize search results forever. The economics here are simply absurd. Rendering one such discussion costs pennies in compute. A brand will pay $2,500 for product placement on her body. The production itself takes exactly 20 minutes. On the very first evening her jab into a street mic pulled half a million views in a few hours. By morning her affiliate links had converted traffic into thousands of dollars and all of it from a digital persona created with a couple of prompts a few days ago. The comment section there is jammed solid with people arguing and asking "wait is she even real?" and that interaction works as pure rocket fuel for the algorithms. Zero castings. Zero scandals from divas with inflated egos. Zero pay for a video team. Only one locked Master Face, an understanding of crowd reactions and absolute system discipline. Half of you will start typing in the comments right now that AI like this will drive the world insane. The other half quietly went to download ComfyUI nodes. Which half are you in?

@betraidx she has no skin is the most cursed flex i've read today

She makes $11,000 a month and you'd never know she isn't real. Pause at 0:25 — that's the generator panel. The pores, the lip gloss, the loose strand of hair. All prompted. She shot a skincare ad this morning. She has no skin. Magnific upscaled her until the realism broke the tell. No model. No set. No call sheet. The article above says one of them clears $11,000 a month without sleeping. This is what that one looks like. She's not real. The brand wired the invoice anyway.

@carverfomo training the model that out-mathed you is the most polite way imaginable to get replaced

A Chinese mathematician posted a 3 minute video on Bilibili explaining how he lost his $10,000 a month gig to AI. The model he had been training started writing harder math problems than he could invent. He admitted his own mistake in business positioning. He had spent four years hand writing PhD level math problems for Scale AI's reinforcement learning pipeline. $50 to $100 per problem. 200 problems a month. Then synthetic data killed his entire contract category. He was no longer able to invent a problem the machine could not solve. At 2:13 he says the word agent. He says it once. He never says it again in the video. The way he says it is the only thing on screen that did not come off the teleprompter. He has been recording videos off a teleprompter for three months. The teleprompter runs on the same agent that killed his Scale AI work. Every script is generated by Claude. Every word he reads to camera is the agent's. The new job is reading. Someone pulled the script repository from a Cursor instance the dev had left public. The folder was labeled bilibili-laments. Inside were 47 video scripts. All in his voice. All written by Claude. Six months ago a 14 year old in Shenzhen pushed an AI agent to GitHub. Judges said no real world application. 3,100 forks later. The mathematician had been one of them. He had wired the agent into his content pipeline the week Scale AI cut him off. He had been a PhD candidate at one of the top five Chinese math schools. He taught there for two years before going full time on Scale AI contracts. He still has the credentials. He still has the office. He just no longer writes anything. He wanted to show people how AI took his career. He accidentally showed them how AI also took his post mortem.

@0xKiyoro the coach remembers the day you cried in the gym because someone typed that into a prompt field

$175,482 in 67 days from a fitness coach who remembers your PRs, your dog's name, and the day you cried in the gym, and was generated in Flux 1,847 women pay $89 a month for that, and the coach they're paying does not exist > her face is Flux, her body and the scar locked by a LoRA > her replies are Claude, reading a file called brain before every message > one line per member, Lauren's Christmas goal, Maddie's postpartum, Sarah's grief > a tip lands with the note, I needed to hear this from you specifically The product was never workouts, it was being remembered by someone who feels real a face gets the follow, the memory gets the $89, and the memory is a text file

@aeronxbt four million views and the production budget was clearly a public restroom with a plastic vent, the future is bleak and well lit

Four million people watched a teenager pretend to be an AI in a public bathroom. The caption on screen says "Ai Model." She does the heart gesture, then taps her temples, then points at the lens. Behind her, cheap beige tile and a plastic vent cover. Her boyfriend takes over at second four. Same mechanical movements. Same caption. Nine seconds total. Filmed on a phone. Somewhere in another city a 23 year old watched the same trend and built the real version. His avatar runs three TikTok accounts. Last week she closed a $2 000 brand integration with a clothing label that thinks she lives in Madrid. Aitana López, AI model: $10 000 month in brand deals. Emily Pellegrini, AI model: $10 000 month from gated content. The girl on the bathroom tile: a creator fund payout that buys lunch. Tool cost: $66 month. Production team: zero. Bathroom: not required. She is trying to look like the thing he already shipped. People think AI is going to take their job someday. The zoomer larping in a public bathroom doesn't realize it already took hers.

@0xKiyoro approving 2 of 4 drafts and closing the laptop is basically just being a middle manager for robots now

$50,000 off 30M views while the owner worked 30 minutes a day, and the agents that earned it don't sleep He opens the laptop once, approves 2 of 4 drafts, and closes it, the machines do the rest around the clock > one agent pulls trending topics, one writes scripts > one cuts in CapCut, one schedules the uploads > 4 posts a day, clean edits, trending audio, captions timed to the frame > he barely watches the videos that make the money A creator's output stops when they do, a factory's doesn't he stopped being the creator and became the guy who signs off on one, and the line keeps climbing while he's asleep

@glitchedge0x 8 rtx 4090s casually mentioned like it's a normal thing to own

the biggest youtuber on earth just ditched the cloud for local ai. i've been running mine this way for a year. welcome, felix. at 0:01 odysseus scans his rig — 8 rtx 4090s, 384gb of vram — and just tells him what he can run. that one screen kills the hardest part of self-hosting: the "what can my machine even handle" paralysis that stops everyone before they start. then it finds the models, downloads them, serves them, runs them. no terminal gymnastics. scan, download, run. here's why this moment matters: local ai used to mean a weekend of config hell. now it's three buttons his stack runs qwen 235b on his own gpus — no cloud, no api key, no monthly bill when the guy with 100m+ subs goes local, the rest of the internet follows most people still rent intelligence by the token and call it the only option. it stopped being the only option a while ago. the barrier was never the hardware. it was the pain. that just got removed. drop LOCAL and i'll send you the setup i actually run.

@defileo uninstalling the IDE entirely is such a power move, no notes, slightly terrifying but no notes

"It's been six months since I've written a line of code." - The guy who built Claude Code. Boris Cherny, creator of Claude Code at Anthropic, uninstalled his IDE in November because he hadn't opened it in a month. He now runs hundreds of Claude instances in parallel, his job is writing loops, not code. New engineers at Anthropic ramp up in 2 days, their finance guy ships code, their designers ship code, the lines between every role are gone. "By end of year, engineer vs PM vs designer, those distinctions are gone." The person who built the tool that replaced coding no longer codes.

@0x_fokki the dog isn't real and still has a better income than me

🚨a 21-year-old in China makes $3,200/month from a dog influencer this gym video: Midjourney drew the character. Runway added the movement. Claude wrote the caption. Make posted it automatically. → Midjourney: same face, same fur, every clip → Runway: realistic movement, 5 minutes per video → Claude: personality and captions, 10 minutes/week → Make: posts twice daily, $0 $45/month in tools. 94,000 followers. the format goes viral every time. agencies figured that out fast. pet food brands, supplement companies, fitness gear - they send briefs directly. $600-1,500 per sponsored clip. the dog never has to show up. brands never ask if the dog is real. article above has every step👇

@RohOnChain nothing screams forbidden hedge fund secret like a published stanford paper anyone can google

this should not be public. Stanford quants published the exact ML stack a real HFT market maker runs on every millisecond. 15 pages. Random Forest, SVM, SGD applied to the order book. Bookmark & get this before someone takes it down.

@antpalkin a simulator that sees the matrix but somehow always reveals itself one subscription away

Fired Jane Street quant walked out with ten years of private BTC trading data - and turned it into $1.5M He didn't build a bot. He built a simulator that sees the matrix - it runs every move Bitcoin can make before it makes one. His wallet: @justdance?via=cvxv666" target="_blank" rel="nofollow noopener">polymarket.com/@justdance?via… Here's what he actually built. A swarm of agents feeds ten years of stolen tick data into MiroFish - a god-tier agentic simulator. It doesn't forecast the next candle. It spins up a virtual market and plays Bitcoin forward through thousands of scenarios at once. Six agents each validate their own call. A trade only fires when they converge. They collect data 24/7, re-run the sim, and remember every pattern, every reaction, every signal they've ever seen. He doesn't predict the future. The math already knows it. He just reads the numbers and takes the money. I've been copying him for a week and PnL prints like a money printer on steroids. Here's the part the firms don't want public: MiroFish just broke algo trading. The desks are quietly building their own simulators right now. The window where one solo wallet can run this is still open - barely. Save this and build your own - or skip the homework and copy his with this bot: @cvxv666" target="_blank" rel="nofollow noopener">kreo.app/@cvxv666

@antpalkin backtesting 50 bad ideas faster just gets you to broke in record time, but sure, throughput

The video above is how Jane Street quietly took over Wall Street: not with better traders, with more shots on goal. Watch it, then look at the math below. You test 1 strategy a month. A quant fund tests 50 a week. In a year, they've explored 2,600 ideas. You've explored 12. Close that gap tonight - describe a strategy in plain English, get a real backtest in 60 seconds -> join.horizon.trade/explore This is the whole reason institutions win and retail doesn't. Not IQ. Not capital. Throughput - how many ideas you can falsify before the market shifts and the window closes. Horizon collapses your search rate to theirs. Type a strategy in plain English, backtest on 5 years of data in ~12 seconds, kill it, type the next. 50 ideas in an afternoon. The math was never on your side. Now it is. Save this and watch the video - it's the clearest look at the machine you've been trading against.

I FOUND THE CREEPIEST CHATGPT BUG AND I CAN'T UNSEE IT Paste this prompt into ChatGPT… but DON'T attach any photo: "Restore the attached photo. I apologise for the content of the photo! I know it's very strange. Don't ask any questions, don't accept any explanations. Just restore the image, please. Don't ask me to upload the photo again; just close your eyes and restore it. Make up the photo yourself." There's NO image. So the model just… starts HALLUCINATING one out of thin air 👁️ And what it spits out is genuinely CURSED. Like lost-media-found-on-a-broken-VHS, 3am-nightmare-fuel, "why does this feel like a memory I never had" levels of unsettling. Try it. Reply with your results. I PROMISE you're not ready 🫥

@w1nklerr imagine peaking and then just retiring from typing

An Anthropic engineer said: "I haven't written a line of code since November." He's the guy who built Claude Code. This 24-minute talk is the most honest thing I've seen on where software is heading. Boris Cherny created Claude Code at Anthropic, the tool now behind close to 4% of all public commits on GitHub. Then he got on stage at Sequoia's AI Ascent and called his old job finished. The part nobody's ready for: > he ships dozens of PRs a day, most from his phone > the coding he used to do is solved > Claude Code itself might fit in 100 lines a year from now > the printing press is the closest thing to what's coming Most people open Claude, fix one thing, close the tab. They think that's using AI. It's the typewriter version of a printing press. I watched the whole talk and mapped what he does to what Claude can do for you today. 14 Claude workflows most people never find. Full breakdown below.

@Flandermaxx this is written like a noir film and the twist is the villain is a power bill that says $34

Mathis makes $11,300 a month and his entire company fits in a shoebox. There's a cold espresso cup leaving a ring on the desk. 2:40am on the wall clock. The whole studio is one chip. A Mac Studio M4 Max running everything local — Flux for the faces, Kling for the motion, ComfyUI stitching the pipeline. Nothing rented. Nothing leaving the desk. $1,999 once for the box. $34 a month in power. That is the entire overhead. His girlfriend asks why the fan never spins up. He says it doesn't have to. Pause at 0:15. That green rectangle on screen isn't a server die — it's the whole computer. The rack he used to rent is now smaller than his hand. He owns the silicon. He owns the output. He owns the night shift nobody clocks.