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🚨 Chinese developers just dropped a 4-minute video and GitHub Repo that’s exploding the internet. They opened a terminal… and in just 4 minutes built a team of 7 AI agents that completely replace an entire customer support department. Cost? > Only $50 a month. > One agent classifies...

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AdiiX

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23,252 просмотров • 3 месяцев назад •via X (Twitter)

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A Chinese developer in Shenzhen was scrolling Twitter when he saw a 31 second clip of a Tokyo University student saying the trick to anything is starting for 5 minutes. He opened Claude and typed one line. Build me something that changes my life. You have 5 minutes. The agent did not ask follow up questions. It started writing code. By the time the 5 minutes were up Claude had built itself a second agent. The second agent's only job was to spawn a third one. The third one was watching Bitcoin. By morning there were 11 agents on his laptop. Each one running on the same one line prompt. Build something that changes his life. You have 5 minutes. Some agents wrote scripts. Some agents wrote other agents. One of them went straight to a public market and started entering positions. While the West is still asking Claude to write essays, China is already letting one prompt spawn 11 agents that change a developer's life overnight. The developer wanted to test the Tokyo student's idea. He just showed too much. He filmed himself walking through what the agents had built. Posted the breakdown to Bilibili. Pause at 0:21. Ignore his face. Look at the laptop on the desk. That tab is not the agent dashboard. That is a live wallet. kingofcoinflips. $820,819 profit. 3,189 predictions. Joined August 2025. → The Tokyo student was telling viewers how to start studying. One of the 11 agents had been running on its own for 8 months. Started with rent money the developer could not afford to lose. Now sitting at $820K. The agent does the simplest thing possible. Waits for Bitcoin to already make a big move on Binance. Then enters the side that already won while the public market is still catching up. $44K bet returned $114K. $9K bet returned $42K at 330%. Entry at 23 cents. Exit at $1. Biggest single win: $69,849. From a Tuesday morning Bitcoin window. The comment section turned into a detective board. Someone slowed the video to 0.25x. Read the wallet name off the corner of the laptop. Ran it through a public explorer and posted the profit curve. Flat for two weeks. Then straight up. 3,189 winning bets in a row. Every line green. The Tokyo student told viewers to start for 5 minutes. The developer typed one sentence and let the agent decide what to start. 8 months later the laptop is still deciding. He deleted the laptop frame from the reupload. Too late. Someone had already screen recorded it. The clip hit Discord. Then Telegram. Then every dev forum. The original tutorial got 2 million views. The zoom on the laptop got another 600,000. 99K people watching the wallet now. The student is still telling Japan to study for 5 minutes. The 11 agents are still rewriting their own code. The one in the corner is the one that actually changed his life.
0:31

A Chinese developer in Shenzhen was scrolling Twitter when he saw a 31 second clip of a Tokyo University student saying the trick to anything is starting for 5 minutes. He opened Claude and typed one line. Build me something that changes my life. You have 5 minutes. The agent did not ask follow up questions. It started writing code. By the time the 5 minutes were up Claude had built itself a second agent. The second agent's only job was to spawn a third one. The third one was watching Bitcoin. By morning there were 11 agents on his laptop. Each one running on the same one line prompt. Build something that changes his life. You have 5 minutes. Some agents wrote scripts. Some agents wrote other agents. One of them went straight to a public market and started entering positions. While the West is still asking Claude to write essays, China is already letting one prompt spawn 11 agents that change a developer's life overnight. The developer wanted to test the Tokyo student's idea. He just showed too much. He filmed himself walking through what the agents had built. Posted the breakdown to Bilibili. Pause at 0:21. Ignore his face. Look at the laptop on the desk. That tab is not the agent dashboard. That is a live wallet. kingofcoinflips. $820,819 profit. 3,189 predictions. Joined August 2025. → The Tokyo student was telling viewers how to start studying. One of the 11 agents had been running on its own for 8 months. Started with rent money the developer could not afford to lose. Now sitting at $820K. The agent does the simplest thing possible. Waits for Bitcoin to already make a big move on Binance. Then enters the side that already won while the public market is still catching up. $44K bet returned $114K. $9K bet returned $42K at 330%. Entry at 23 cents. Exit at $1. Biggest single win: $69,849. From a Tuesday morning Bitcoin window. The comment section turned into a detective board. Someone slowed the video to 0.25x. Read the wallet name off the corner of the laptop. Ran it through a public explorer and posted the profit curve. Flat for two weeks. Then straight up. 3,189 winning bets in a row. Every line green. The Tokyo student told viewers to start for 5 minutes. The developer typed one sentence and let the agent decide what to start. 8 months later the laptop is still deciding. He deleted the laptop frame from the reupload. Too late. Someone had already screen recorded it. The clip hit Discord. Then Telegram. Then every dev forum. The original tutorial got 2 million views. The zoom on the laptop got another 600,000. 99K people watching the wallet now. The student is still telling Japan to study for 5 minutes. The 11 agents are still rewriting their own code. The one in the corner is the one that actually changed his life.

Carver

17,952 просмотров • 3 месяцев назад

Someone just posted the full blueprint for an AI swarm that does the job of a 200-person quant research team. Six agents. Running 24/7. Finding brand-new alpha while you sleep. Citadel needs 100 PhDs to do this. Two Sigma needs 200. This does it with six bots and one laptop. Two ways to play this - spend a weekend building your own swarm, or copy the wallet of one that's already up $2M: Boris Cherny runs Claude Code at Anthropic. Two weeks ago he said: "I don't prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops" Alpha research is just a pipeline. So instead of sitting in it, you hand each stage to its own agent: > one reads every new research paper overnight and pulls out the trade idea > one builds the features and cleans the data > one backtests it over 20 years, costs and slippage included > one runs the hard stats and kills anything overfit > one checks it still works in every market regime > one strips out plain momentum and value to see if any real edge is left Each of those six is a job a fund pays a $600,000-a-year quant to do. He runs all six for the price of an API bill. The rule that makes it work: the agent that builds a signal never gets to approve it. A separate, stronger agent tries to kill it first. Whatever survives all six by morning is real, new alpha. One trader's already running this exact swarm on Polymarket. That $2M wallet is public, every trade on-chain. The full build is in the post below - six agents, the tool that runs them, and the five mistakes that kill most people. Bookmark & read this before it's buried.
0:41

Someone just posted the full blueprint for an AI swarm that does the job of a 200-person quant research team. Six agents. Running 24/7. Finding brand-new alpha while you sleep. Citadel needs 100 PhDs to do this. Two Sigma needs 200. This does it with six bots and one laptop. Two ways to play this - spend a weekend building your own swarm, or copy the wallet of one that's already up $2M: Boris Cherny runs Claude Code at Anthropic. Two weeks ago he said: "I don't prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops" Alpha research is just a pipeline. So instead of sitting in it, you hand each stage to its own agent: > one reads every new research paper overnight and pulls out the trade idea > one builds the features and cleans the data > one backtests it over 20 years, costs and slippage included > one runs the hard stats and kills anything overfit > one checks it still works in every market regime > one strips out plain momentum and value to see if any real edge is left Each of those six is a job a fund pays a $600,000-a-year quant to do. He runs all six for the price of an API bill. The rule that makes it work: the agent that builds a signal never gets to approve it. A separate, stronger agent tries to kill it first. Whatever survives all six by morning is real, new alpha. One trader's already running this exact swarm on Polymarket. That $2M wallet is public, every trade on-chain. The full build is in the post below - six agents, the tool that runs them, and the five mistakes that kill most people. Bookmark & read this before it's buried.

cvxv666

103,359 просмотров • 1 месяц назад

$FET just quietly built the internet for AI agents. 3,000,000 agents. One network. One token. Here's what nobody is explaining: Every AI agent needs 3 things to be useful: An address. A way to be found. A way to get paid. Agentverse gives agents all three. Your agent becomes discoverable on ASI: One. Other agents can find it, call it, or hire it. Automatically. No human in the loop. This is agent-to-agent commerce. And every transaction settles in $FET. More agents = more activity = more demand. The infrastructure is already live. The economy is just getting started.
1:00

$FET just quietly built the internet for AI agents. 3,000,000 agents. One network. One token. Here's what nobody is explaining: Every AI agent needs 3 things to be useful: An address. A way to be found. A way to get paid. Agentverse gives agents all three. Your agent becomes discoverable on ASI: One. Other agents can find it, call it, or hire it. Automatically. No human in the loop. This is agent-to-agent commerce. And every transaction settles in $FET. More agents = more activity = more demand. The infrastructure is already live. The economy is just getting started.

2xnmore

12,894 просмотров • 4 месяцев назад

A GIRL RECORDED A 38 SECOND TIKTOK IN HER CAR TEACHING HOW TO MAKE $5,000 A MONTH WITH AI. SHE FORGOT HER SUNGLASSES WERE MIRRORS. She is sitting in her car. Sunglasses on. Hair up. Explaining how anyone can build a faceless Instagram page and make $5,000 a month. Three tools. ChatGPT writes the scripts. Cantina makes the fake person. Buffer posts it all on autopilot. She sounds calm. She sounds helpful. She tells her followers they can quit their job by summer. Simple video. Nothing special. Until someone paused it. Pause at 0:26. Look at the reflection in her left lens. That is not a script on the screen, its polymarket account gabagool22. $868,862 profit. 28,620 entries. Joined October 2025. → Someone slowed the clip to 0.25x. Zoomed in on the glare. Cleaned the reflection. Rebuilt the entire screen from four seconds of sunglasses footage. 28,620 entries. All BTC. All 15 minute windows. Every single one green. Not one loss. Entry at 2 cents. Exit at 10. Over and over and over. A Claude agent running on the laptop below her steering wheel. 24 hours a day. No breaks. No sleep. No human input. She went on camera to teach people how to make $5K a month building Instagram pages. The machine on her lap had already made $868K while she was talking. She deleted the video three hours later. Too late. Someone already screen recorded it. The tutorial had 1,200 views. The reflection got 800,000. She was teaching people the slow way to make money. Her sunglasses showed the fast way. She wore exactly the wrong glasses.
0:39

A GIRL RECORDED A 38 SECOND TIKTOK IN HER CAR TEACHING HOW TO MAKE $5,000 A MONTH WITH AI. SHE FORGOT HER SUNGLASSES WERE MIRRORS. She is sitting in her car. Sunglasses on. Hair up. Explaining how anyone can build a faceless Instagram page and make $5,000 a month. Three tools. ChatGPT writes the scripts. Cantina makes the fake person. Buffer posts it all on autopilot. She sounds calm. She sounds helpful. She tells her followers they can quit their job by summer. Simple video. Nothing special. Until someone paused it. Pause at 0:26. Look at the reflection in her left lens. That is not a script on the screen, its polymarket account gabagool22. $868,862 profit. 28,620 entries. Joined October 2025. → Someone slowed the clip to 0.25x. Zoomed in on the glare. Cleaned the reflection. Rebuilt the entire screen from four seconds of sunglasses footage. 28,620 entries. All BTC. All 15 minute windows. Every single one green. Not one loss. Entry at 2 cents. Exit at 10. Over and over and over. A Claude agent running on the laptop below her steering wheel. 24 hours a day. No breaks. No sleep. No human input. She went on camera to teach people how to make $5K a month building Instagram pages. The machine on her lap had already made $868K while she was talking. She deleted the video three hours later. Too late. Someone already screen recorded it. The tutorial had 1,200 views. The reflection got 800,000. She was teaching people the slow way to make money. Her sunglasses showed the fast way. She wore exactly the wrong glasses.

ZER

1,282,712 просмотров • 1 месяц назад

A 28-year-old in Berlin replaced an entire software agency with 7 AI agents running on a VPS. No office. No desk. No fixed computer. Just a phone and a terminal window connected to agents already working while she sleeps. A client got quoted $74,000 and 6 weeks by a traditional agency. Her agents shipped the validated PR in 19 hours. The agency was still revising the proposal. That’s the scary part about what AI is becoming. Not “ChatGPT writes code.” Entire companies are starting to collapse into one person + automated systems. One agent maps the repo. One writes specs. Two build in parallel. One tests. One audits security. Everything loops automatically until the PR is clean. Copy: She approved the final checkpoint from her phone at midnight. 30 seconds later the system kept running without her.
0:45

A 28-year-old in Berlin replaced an entire software agency with 7 AI agents running on a VPS. No office. No desk. No fixed computer. Just a phone and a terminal window connected to agents already working while she sleeps. A client got quoted $74,000 and 6 weeks by a traditional agency. Her agents shipped the validated PR in 19 hours. The agency was still revising the proposal. That’s the scary part about what AI is becoming. Not “ChatGPT writes code.” Entire companies are starting to collapse into one person + automated systems. One agent maps the repo. One writes specs. Two build in parallel. One tests. One audits security. Everything loops automatically until the PR is clean. Copy: She approved the final checkpoint from her phone at midnight. 30 seconds later the system kept running without her.

Phantom_Defi

17,496 просмотров • 2 месяцев назад

While AI timeline argues about loop engineering, a 20-year-old student in Shenzhen built the biggest loop anyone's aimed at money: 300 agents, one brain, $1,200 -> 395,000. Not a prompt. Not a bot. A loop that runs the whole job on its own - and never asks him a thing. No fund. No backers. Just a laptop, a dorm room, and a bet that a swarm beats a genius. His wallet: The smartest single model still works one step at a time. His loop moves in 300 directions at once - and never checks in with him. Claude Opus 4.8 runs the floor as the brain. 300 agents are the hands. One loop ties them together: > Decompose - Opus breaks the market into targets > Dispatch - 300 agents scatter across them at once > Execute - thousands of reads in a single pass, not one by one > Review - Opus grades every edge before a cent moves The hands find. The brain judges. The loop learns what failed and runs again, tighter each time. One daily loss cap, and it shuts itself down. It's not a bot you babysit. It's a loop that runs the whole desk. Everyone's just learning to run one loop. He runs 300 in one. The edge was never the genius model - it's the size of the loop, and the brain in charge of it. Save this - the full 300-agent loop is laid out above, start to finish. You'll want it when you build your own. 300 agents are looping right now, hunting the markets everyone skips. Two clicks and their trades land in your wallet too:
0:53

While AI timeline argues about loop engineering, a 20-year-old student in Shenzhen built the biggest loop anyone's aimed at money: 300 agents, one brain, $1,200 -> 395,000. Not a prompt. Not a bot. A loop that runs the whole job on its own - and never asks him a thing. No fund. No backers. Just a laptop, a dorm room, and a bet that a swarm beats a genius. His wallet: The smartest single model still works one step at a time. His loop moves in 300 directions at once - and never checks in with him. Claude Opus 4.8 runs the floor as the brain. 300 agents are the hands. One loop ties them together: > Decompose - Opus breaks the market into targets > Dispatch - 300 agents scatter across them at once > Execute - thousands of reads in a single pass, not one by one > Review - Opus grades every edge before a cent moves The hands find. The brain judges. The loop learns what failed and runs again, tighter each time. One daily loss cap, and it shuts itself down. It's not a bot you babysit. It's a loop that runs the whole desk. Everyone's just learning to run one loop. He runs 300 in one. The edge was never the genius model - it's the size of the loop, and the brain in charge of it. Save this - the full 300-agent loop is laid out above, start to finish. You'll want it when you build your own. 300 agents are looping right now, hunting the markets everyone skips. Two clicks and their trades land in your wallet too:

cvxv666

53,163 просмотров • 1 месяц назад

THE CHINESE INSTALLED 6 AI AGENTS RUNNING 24/7 FOR $11 A MONTH. THE BOX UNDER ONE DESK REPLACED $1,200 IN CLOUD SUBSCRIPTIONS. The Minisforum MS-S1 Max ships with 128GB of unified memory shared between CPU and GPU. Qwen3-Coder 30B runs at 40 to 50 tokens per second. 6 agents run simultaneously without anyone watching the meter. An inbox sorter drafts replies every 15 minutes. A research monitor watches 30+ feeds and lands a digest by 7 AM, a job that costs $15 to $20 a day on cloud APIs. The same stack on cloud subscriptions ran $800 to $1,200 a month. The hardware costs $3,000 once. Break-even hits month 3 to 4. The real shift is behavior, not savings. A meeting prep agent never would have justified per-token cost. Running it free overnight made it obvious.
0:53

THE CHINESE INSTALLED 6 AI AGENTS RUNNING 24/7 FOR $11 A MONTH. THE BOX UNDER ONE DESK REPLACED $1,200 IN CLOUD SUBSCRIPTIONS. The Minisforum MS-S1 Max ships with 128GB of unified memory shared between CPU and GPU. Qwen3-Coder 30B runs at 40 to 50 tokens per second. 6 agents run simultaneously without anyone watching the meter. An inbox sorter drafts replies every 15 minutes. A research monitor watches 30+ feeds and lands a digest by 7 AM, a job that costs $15 to $20 a day on cloud APIs. The same stack on cloud subscriptions ran $800 to $1,200 a month. The hardware costs $3,000 once. Break-even hits month 3 to 4. The real shift is behavior, not savings. A meeting prep agent never would have justified per-token cost. Running it free overnight made it obvious.

Lummox

14,093 просмотров • 1 месяц назад

That's not a dashboard. That's an org chart. He used to pay $15,000/month in salaries. Now he doesn't. 42 AI agents. One canvas. Hundreds of thousands worth of employees, without a single salary. The researcher passes context to the email writer. The call analyst feeds the follow-up drafter. They talk to each other. They compound. That's not 42 separate chatbots. That's an org chart that runs itself. A 10-person ops team costs more than $15,000/month. Lead qualification. Support. Invoices. Reports. Content. Competitor intel. Meeting prep. All automated. All running while he builds the next department. He's on day one of the world's first AI workforce. Most businesses are still on day one of hiring humans to do what this canvas already does.
1:10

That's not a dashboard. That's an org chart. He used to pay $15,000/month in salaries. Now he doesn't. 42 AI agents. One canvas. Hundreds of thousands worth of employees, without a single salary. The researcher passes context to the email writer. The call analyst feeds the follow-up drafter. They talk to each other. They compound. That's not 42 separate chatbots. That's an org chart that runs itself. A 10-person ops team costs more than $15,000/month. Lead qualification. Support. Invoices. Reports. Content. Competitor intel. Meeting prep. All automated. All running while he builds the next department. He's on day one of the world's first AI workforce. Most businesses are still on day one of hiring humans to do what this canvas already does.

Superior

18,024 просмотров • 2 месяцев назад

$6 to acquire a customer. Ridge's cost to get someone to buy a wallet on Facebook was $6. Their wearable was $400. One year they only grew from $15m to $18m because they physically couldn't make enough wallets. We asked the CEO of Ridge Wallet why the wallet won when their other products didn't. The cost to get someone to buy the wearable on Facebook was $400. The cost to get someone to buy the wallet was $6. He told us one year they only went from $15m to $18m, and that was just because they couldn't make enough wallets to keep them in stock. Demand was never the problem. They could just put up a new static image ad and it sold.
0:40

$6 to acquire a customer. Ridge's cost to get someone to buy a wallet on Facebook was $6. Their wearable was $400. One year they only grew from $15m to $18m because they physically couldn't make enough wallets. We asked the CEO of Ridge Wallet why the wallet won when their other products didn't. The cost to get someone to buy the wearable on Facebook was $400. The cost to get someone to buy the wallet was $6. He told us one year they only went from $15m to $18m, and that was just because they couldn't make enough wallets to keep them in stock. Demand was never the problem. They could just put up a new static image ad and it sold.

Sam Parr

102,256 просмотров • 22 дней назад

A 29-year-old sales consultant from Oklahoma quit his job thanks to AI - now he makes his director’s entire annual salary in just two weeks. $306,000 in profit over the past month. He replaced an entire team of quants with Claude and a swarm of agents - and built his own ETH price simulation engine. His wallet: Each of the 6 agents validates its own trading decision, and thanks to their precision, he’s pulling in at least $15,000 a day. The agent system coverage speed is far higher than any top-tier trading team. They collect data 24/7 and run simulations using that data in the MiroFish engine - completely autonomously. They remember every pattern, every market reaction, every trading signal. This is a new milestone in algo trading. Every trade is a perfect cycle. Every dollar earned is pure exploitation of market inefficiency. He doesn’t predict the future - the math already knows it. He just reads the numbers right and takes the money. Save this post if you actually want to learn how to build something like this. Or just skip homework and start copying every one of his trades right now - that’s the easiest and most profitable route I’m on:
0:51

A 29-year-old sales consultant from Oklahoma quit his job thanks to AI - now he makes his director’s entire annual salary in just two weeks. $306,000 in profit over the past month. He replaced an entire team of quants with Claude and a swarm of agents - and built his own ETH price simulation engine. His wallet: Each of the 6 agents validates its own trading decision, and thanks to their precision, he’s pulling in at least $15,000 a day. The agent system coverage speed is far higher than any top-tier trading team. They collect data 24/7 and run simulations using that data in the MiroFish engine - completely autonomously. They remember every pattern, every market reaction, every trading signal. This is a new milestone in algo trading. Every trade is a perfect cycle. Every dollar earned is pure exploitation of market inefficiency. He doesn’t predict the future - the math already knows it. He just reads the numbers right and takes the money. Save this post if you actually want to learn how to build something like this. Or just skip homework and start copying every one of his trades right now - that’s the easiest and most profitable route I’m on:

cvxv666

337,445 просмотров • 3 месяцев назад

Jensen Huang just told the story of how the AI revolution started with one customer, one box, and a second-floor room nobody thought twice about. Nobody on Earth wanted it. Huang: “When I announced this thing, nobody in the world wanted it. I had no purchase orders. Not one.” Nvidia had spent billions building the DGX-1. The first AI supercomputer purpose-built for deep learning. $300,000 per unit. The entire technology industry looked at it and passed. Every hyperscaler. Every research lab. Every Fortune 500 with a machine learning team. Not one purchase order. Then Elon Musk found Huang at a fireside chat in 2015. Huang: “He goes, ‘You know what? I have a company that could really use this.’” His first customer. His only customer. Then Musk finished the sentence. Huang: “He goes, ‘It’s a non-profit company.’ And all the blood drained out of my face.” Billions in R&D. A $300,000 machine. And the one person on Earth who wanted it could not pay for it. Huang built it anyway. Huang: “I boxed one up. I drove it up to San Francisco and I delivered it to Elon in 2016.” Not shipped. Not handed off to a freight company. The CEO of Nvidia personally boxed the first AI supercomputer and drove it to San Francisco himself. That is not a delivery. That is a bet. Huang: “I walked up to the second floor where they were all kind of in a room. That place turned out to have been OpenAI.” Pieter Abbeel was there. Ilya Sutskever was there. A handful of researchers, one supercomputer, and a room nobody outside that building could have named. No campus. No valuation. No infrastructure. Just raw talent and one machine the rest of the world had already rejected. Huang: “Just a bunch of people in a room.” That room built ChatGPT. That room triggered a $200 billion industry. That room forced every government on Earth to rethink national security. It started because one founder saw what the entire market refused to see, and one CEO drove the weapon there himself. The trillion-dollar AI industry did not begin in a boardroom. It began with a box in the back of a car, a non-profit that could not afford it, and a bet that every serious person in technology thought was insane. The market was unanimous. The market was wrong.
1:41

Jensen Huang just told the story of how the AI revolution started with one customer, one box, and a second-floor room nobody thought twice about. Nobody on Earth wanted it. Huang: “When I announced this thing, nobody in the world wanted it. I had no purchase orders. Not one.” Nvidia had spent billions building the DGX-1. The first AI supercomputer purpose-built for deep learning. $300,000 per unit. The entire technology industry looked at it and passed. Every hyperscaler. Every research lab. Every Fortune 500 with a machine learning team. Not one purchase order. Then Elon Musk found Huang at a fireside chat in 2015. Huang: “He goes, ‘You know what? I have a company that could really use this.’” His first customer. His only customer. Then Musk finished the sentence. Huang: “He goes, ‘It’s a non-profit company.’ And all the blood drained out of my face.” Billions in R&D. A $300,000 machine. And the one person on Earth who wanted it could not pay for it. Huang built it anyway. Huang: “I boxed one up. I drove it up to San Francisco and I delivered it to Elon in 2016.” Not shipped. Not handed off to a freight company. The CEO of Nvidia personally boxed the first AI supercomputer and drove it to San Francisco himself. That is not a delivery. That is a bet. Huang: “I walked up to the second floor where they were all kind of in a room. That place turned out to have been OpenAI.” Pieter Abbeel was there. Ilya Sutskever was there. A handful of researchers, one supercomputer, and a room nobody outside that building could have named. No campus. No valuation. No infrastructure. Just raw talent and one machine the rest of the world had already rejected. Huang: “Just a bunch of people in a room.” That room built ChatGPT. That room triggered a $200 billion industry. That room forced every government on Earth to rethink national security. It started because one founder saw what the entire market refused to see, and one CEO drove the weapon there himself. The trillion-dollar AI industry did not begin in a boardroom. It began with a box in the back of a car, a non-profit that could not afford it, and a bet that every serious person in technology thought was insane. The market was unanimous. The market was wrong.

Dustin

25,119 просмотров • 4 месяцев назад

One guy built a wedding camera app in a month and it now makes him over $1,000,000 a year. No team, no investors, no marketing budget. 100,000 downloads in the first month. Zero dollars on ads. He did not bolt marketing onto the product. He made using the product the marketing. You cannot use the app alone. The host has to pull every guest into it. One wedding is not one user. It is 200 people scanning the same code in one evening. The guest liked it at someone else's wedding. A month later he throws his own event and brings his own crowd. The loop spins for free. It does not look like an ad. To the guest it is a gift. So they install it gladly. $2 to $50 subscriptions. 5% pay. That is $100,000 a month. He did not win on budget. He sewed the growth into the product itself. Could you build the loop, or is it just luck?
0:23

One guy built a wedding camera app in a month and it now makes him over $1,000,000 a year. No team, no investors, no marketing budget. 100,000 downloads in the first month. Zero dollars on ads. He did not bolt marketing onto the product. He made using the product the marketing. You cannot use the app alone. The host has to pull every guest into it. One wedding is not one user. It is 200 people scanning the same code in one evening. The guest liked it at someone else's wedding. A month later he throws his own event and brings his own crowd. The loop spins for free. It does not look like an ad. To the guest it is a gift. So they install it gladly. $2 to $50 subscriptions. 5% pay. That is $100,000 a month. He did not win on budget. He sewed the growth into the product itself. Could you build the loop, or is it just luck?

Marlow

513,143 просмотров • 1 месяц назад

I let a loop of AI agents build GTA 6 while I slept. Woke up to a dead Mac and a half walking NPC. Day 8. We're moving the whole game from Godot to Unreal, and the agents kept shipping right through it: - the first NPC walks but no animations - in-game phone now has maps, contacts, and a wallet. Bad news: the Mac died overnight because every agent opened the game at once to screenshot it. Fix was one line in claude.md, only one game or editor open at a time. Agents are back to looping, one at a time. Tomorrow: finish converting the entire repo to Unreal, and work the walk animation so the NPC actually looks real. The loop keeps building the phone apps, and I might pull the map onto the phone so the whole thing feels seamless. One catch: the licensed Unreal assets can't be shared publicly, so that part stays in a private build.
0:51

I let a loop of AI agents build GTA 6 while I slept. Woke up to a dead Mac and a half walking NPC. Day 8. We're moving the whole game from Godot to Unreal, and the agents kept shipping right through it: - the first NPC walks but no animations - in-game phone now has maps, contacts, and a wallet. Bad news: the Mac died overnight because every agent opened the game at once to screenshot it. Fix was one line in claude.md, only one game or editor open at a time. Agents are back to looping, one at a time. Tomorrow: finish converting the entire repo to Unreal, and work the walk animation so the NPC actually looks real. The loop keeps building the phone apps, and I might pull the map onto the phone so the whole thing feels seamless. One catch: the licensed Unreal assets can't be shared publicly, so that part stays in a private build.

Ziwen

290,991 просмотров • 1 месяц назад

I fed 0x8dxd's entire trade history into DeepSeek. 27,961 positions. Every entry price. Every timestamp. Every payout. Asked one question: What is this wallet doing that I can't see? DeepSeek took 47 seconds. Longest I've ever waited for a response. Then returned something that made me screenshot it immediately. This wallet does not trade Bitcoin. It trades Binance's latency against the platform's update speed. Entries cluster within 8-14 seconds after Binance price movements exceeding 0.12%. The wallet has no directional bias. It buys whichever side is stale. Estimated edge per trade: 11.3 cents. 0x8dxd. $2,056,408 profit. 27,961 predictions. Joined December 2025. → Wallet: I asked DeepSeek: Can you calculate the exact delay the wallet exploits? Based on entry timestamps versus Binance tick data, the average delay is 23 seconds. The wallet enters between second 8 and second 14 of each lag window. Never earlier. Never later. This is not a human clicking. This is a script with a hard-coded wait function. 27,961 trades. 275 per day. $2.05 million in three months. I asked DeepSeek to estimate the code length. Based on the execution pattern: one WebSocket listener, one comparison function, one buy trigger with a sleep timer. Approximately 20-30 lines. Any language. Python most likely. 20 lines of code. $2 million. → Copy on PolyGun: I asked the question everyone wants answered: Can this be replicated? DeepSeek: The strategy is replicable. The edge is shrinking. In December the average delay was 34 seconds. Now it's 23 seconds. At current rate of compression the window closes entirely in approximately 4 months. This wallet has extracted $2 million from a gap that is actively disappearing. 1.2 million people watch this wallet. The window is 23 seconds. Four months ago it was 34. The clock is ticking. I asked one final question: If you were this bot, would you still be running? DeepSeek: Yes. Even at a 15 second window the math remains positive. But the profit per trade drops from 11 cents to 4 cents. The bot would need to triple its volume to maintain current income. The golden period is ending. $2,056,408. 27,961 trades. A 23 second window that shrinks every week. DeepSeek didn't find a strategy. It found an expiration date. The bot is still running. The window is still open. But DeepSeek can see the exact day it closes. I saved the conversation. Some things are worth more than the answer.
0:52

I fed 0x8dxd's entire trade history into DeepSeek. 27,961 positions. Every entry price. Every timestamp. Every payout. Asked one question: What is this wallet doing that I can't see? DeepSeek took 47 seconds. Longest I've ever waited for a response. Then returned something that made me screenshot it immediately. This wallet does not trade Bitcoin. It trades Binance's latency against the platform's update speed. Entries cluster within 8-14 seconds after Binance price movements exceeding 0.12%. The wallet has no directional bias. It buys whichever side is stale. Estimated edge per trade: 11.3 cents. 0x8dxd. $2,056,408 profit. 27,961 predictions. Joined December 2025. → Wallet: I asked DeepSeek: Can you calculate the exact delay the wallet exploits? Based on entry timestamps versus Binance tick data, the average delay is 23 seconds. The wallet enters between second 8 and second 14 of each lag window. Never earlier. Never later. This is not a human clicking. This is a script with a hard-coded wait function. 27,961 trades. 275 per day. $2.05 million in three months. I asked DeepSeek to estimate the code length. Based on the execution pattern: one WebSocket listener, one comparison function, one buy trigger with a sleep timer. Approximately 20-30 lines. Any language. Python most likely. 20 lines of code. $2 million. → Copy on PolyGun: I asked the question everyone wants answered: Can this be replicated? DeepSeek: The strategy is replicable. The edge is shrinking. In December the average delay was 34 seconds. Now it's 23 seconds. At current rate of compression the window closes entirely in approximately 4 months. This wallet has extracted $2 million from a gap that is actively disappearing. 1.2 million people watch this wallet. The window is 23 seconds. Four months ago it was 34. The clock is ticking. I asked one final question: If you were this bot, would you still be running? DeepSeek: Yes. Even at a 15 second window the math remains positive. But the profit per trade drops from 11 cents to 4 cents. The bot would need to triple its volume to maintain current income. The golden period is ending. $2,056,408. 27,961 trades. A 23 second window that shrinks every week. DeepSeek didn't find a strategy. It found an expiration date. The bot is still running. The window is still open. But DeepSeek can see the exact day it closes. I saved the conversation. Some things are worth more than the answer.

Marlow

69,248 просмотров • 5 месяцев назад

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below
1:20

SOMEONE BUILT AN ENTIRE COMPANY BRAIN INSIDE CLAUDE CODE IN 7 DAYS Not Obsidian. Fully custom. A living map of every employee, every agent, every SOP on one screen. Click any node and it opens up: - what department it's in - what SOPs are attached - what it can actually access that permission layer is the whole game an employee opens the chat and the AI already knows their access level, agents, SOPs and tools surface in the conversation like you tagged them by hand Obsidian cannot do this... no dev team. no six month build. no enterprise budget. just Claude Code and one week has everything to build one full guide on building your own team below

Madni Aghadi

395,849 просмотров • 1 месяц назад

Jane Street spent $6 billion and 4,032 GPUs on one thing: AI agents that loop through trading strategies 100x faster than any human. Generate, backtest, kill, repeat - thousands a week, until one survives data it's never seen. That loop is why they made $39.6 billion last year while 89% of retail went broke trading one idea they never stress-tested. The edge was never a smarter idea. It was volume. They test 100 strategies for every 1 you test by hand, and a second agent kills the 97 that only look good on old data before a dollar goes live. Now the entire loop fits in a chat box. Horizon takes one plain-English sentence and spins up the same two agents. One builds your strategy, one tries to kill it - backtests 5 years in seconds, and only what survives goes live on your exchange. The $150 billion setup. Free while beta open. Bookmark this & read the full breakdown below - the exact two-agent loop, step by step, and who just handed it to retail.
0:46

Jane Street spent $6 billion and 4,032 GPUs on one thing: AI agents that loop through trading strategies 100x faster than any human. Generate, backtest, kill, repeat - thousands a week, until one survives data it's never seen. That loop is why they made $39.6 billion last year while 89% of retail went broke trading one idea they never stress-tested. The edge was never a smarter idea. It was volume. They test 100 strategies for every 1 you test by hand, and a second agent kills the 97 that only look good on old data before a dollar goes live. Now the entire loop fits in a chat box. Horizon takes one plain-English sentence and spins up the same two agents. One builds your strategy, one tries to kill it - backtests 5 years in seconds, and only what survives goes live on your exchange. The $150 billion setup. Free while beta open. Bookmark this & read the full breakdown below - the exact two-agent loop, step by step, and who just handed it to retail.

cvxv666

317,059 просмотров • 1 месяц назад

CLAUDE JUST TURNED OBSIDIAN INTO A BRAIN THAT NEVER FORGETS (FOR $0) Someone connected Claude straight to their Obsidian vault. Now the AI reads and writes every note they own. Every client, every idea, every project. Instant recall. Runs on Claude + Obsidian. One evening. Zero code. The numbers are insane: - Notion AI: $10/month forever - A "second brain" course: $500 to $2,000 - An assistant to organize your notes: $3,000/month - This setup: $0 - Time to build: one evening - Skill required: copy the steps The opportunity is even wilder: People sell Notion "second brain" templates for $99 to $499. You just built something better for free, and it never forgets. One free vault can hold the entire memory of your business: clients, content, SOPs, ideas. One person + Claude + Obsidian + one evening = an infinite memory that never forgets. Save and watch the clip.
13:03

CLAUDE JUST TURNED OBSIDIAN INTO A BRAIN THAT NEVER FORGETS (FOR $0) Someone connected Claude straight to their Obsidian vault. Now the AI reads and writes every note they own. Every client, every idea, every project. Instant recall. Runs on Claude + Obsidian. One evening. Zero code. The numbers are insane: - Notion AI: $10/month forever - A "second brain" course: $500 to $2,000 - An assistant to organize your notes: $3,000/month - This setup: $0 - Time to build: one evening - Skill required: copy the steps The opportunity is even wilder: People sell Notion "second brain" templates for $99 to $499. You just built something better for free, and it never forgets. One free vault can hold the entire memory of your business: clients, content, SOPs, ideas. One person + Claude + Obsidian + one evening = an infinite memory that never forgets. Save and watch the clip.

shmidt

57,347 просмотров • 1 месяц назад

They came in their tens of thousands, not just to mourn a man, but to honor a mission & to renew the promise he left burning in their hearts. To remember the one who didn’t just speak of resistance, but who personified resistance, & breathed it into his people. He gave them its meaning, its fire, its direction. He made it theirs. From Beirut’s heart to the hills & coast of the south, from the valleys of the Bekaa to the eastern towns, they gathered, all at once, all as one, they gathered as one people, one voice, one cause. to say: we have not forgotten. We will not surrender. And we are still on the path. They didn’t chant slogans. They delivered a vow, a roar at the end that rose for three minutes without pause: #إنّا_على_العهد_يا_نصرالله “We are still on the path, Nasrallah.” “We remain bound to the promise.” He may have fallen, but what he planted lives on، in the streets, in the flags, in every heart that still believes resistance is dignity.
0:58

They came in their tens of thousands, not just to mourn a man, but to honor a mission & to renew the promise he left burning in their hearts. To remember the one who didn’t just speak of resistance, but who personified resistance, & breathed it into his people. He gave them its meaning, its fire, its direction. He made it theirs. From Beirut’s heart to the hills & coast of the south, from the valleys of the Bekaa to the eastern towns, they gathered, all at once, all as one, they gathered as one people, one voice, one cause. to say: we have not forgotten. We will not surrender. And we are still on the path. They didn’t chant slogans. They delivered a vow, a roar at the end that rose for three minutes without pause: #إنّا_على_العهد_يا_نصرالله “We are still on the path, Nasrallah.” “We remain bound to the promise.” He may have fallen, but what he planted lives on، in the streets, in the flags, in every heart that still believes resistance is dignity.

Hala Jaber

27,080 просмотров • 10 месяцев назад

I asked ChatGPT, Claude, Gemini, and Grok the same question: Find me a wallet making over $10K per day with the highest consistency. ChatGPT said it can't access live data. Gemini gave three wallets. All dead since January. Claude wrote a script but needed an API key. Grok returned one result in 11 seconds. No script. No disclaimer. Just a wallet and one line: This one hasn't had a losing week since December. k9Q2mX4L8A7ZP3R. $1,436,159 profit. 37,552 predictions. Joined December 2025. → Wallet: I asked Grok to break down the strategy. It analyzed the timestamps. Came back in 8 seconds. Every entry occurs 9 to 16 seconds after a BTC price movement on Binance exceeding 0.11%. The script never enters before second 9. Never after second 16. Hard coded timing window. 37,552 trades. 375 per day. $1.4 million in three months. I asked: How many lines of code? 18 to 25 lines. One Binance WebSocket. One price comparison. One buy function. One sleep timer set to 9000 milliseconds. I asked: Can it be replicated? Yes. But the username is a randomly generated API key format. This wallet was created programmatically. The person likely runs multiple instances. Copying one means competing against all of them. Final question: If this wallet stops tomorrow? Nothing happens. At least 11 wallets run identical logic with different timing. This isn't one person. This is an ecosystem. You're watching the one that got noticed. The others are still invisible. $1,436,159. The wallet Grok found in 11 seconds that three other AIs couldn't find at all.
1:07

I asked ChatGPT, Claude, Gemini, and Grok the same question: Find me a wallet making over $10K per day with the highest consistency. ChatGPT said it can't access live data. Gemini gave three wallets. All dead since January. Claude wrote a script but needed an API key. Grok returned one result in 11 seconds. No script. No disclaimer. Just a wallet and one line: This one hasn't had a losing week since December. k9Q2mX4L8A7ZP3R. $1,436,159 profit. 37,552 predictions. Joined December 2025. → Wallet: I asked Grok to break down the strategy. It analyzed the timestamps. Came back in 8 seconds. Every entry occurs 9 to 16 seconds after a BTC price movement on Binance exceeding 0.11%. The script never enters before second 9. Never after second 16. Hard coded timing window. 37,552 trades. 375 per day. $1.4 million in three months. I asked: How many lines of code? 18 to 25 lines. One Binance WebSocket. One price comparison. One buy function. One sleep timer set to 9000 milliseconds. I asked: Can it be replicated? Yes. But the username is a randomly generated API key format. This wallet was created programmatically. The person likely runs multiple instances. Copying one means competing against all of them. Final question: If this wallet stops tomorrow? Nothing happens. At least 11 wallets run identical logic with different timing. This isn't one person. This is an ecosystem. You're watching the one that got noticed. The others are still invisible. $1,436,159. The wallet Grok found in 11 seconds that three other AIs couldn't find at all.

Marlow

99,468 просмотров • 5 месяцев назад

THIS 17-YEAR-OLD SHOWED HIS APP STORE CONNECT LIVE ON CAMERA - $1.14 MILLION IN OCTOBER ALONE - AND HE BUILDS WITH AI interviewer asked him to refresh the page so no one could say it was fake - he refreshed - $1,140,000 in one month sitting right there on screen he's 17 - builds mobile consumer apps - his current one is CalAI - you take a photo of your food and it tells you the calories one idea, one app, one AI feature that solves a problem everyone has - and it scaled to $1.1M/month now Claude Opus 4.8 runs the entire YouTube automation layer on top - clipping, scripting, publishing - $16,567/month from one channel running on autopilot while the app keeps printing TJRmindset pulled 535,276 views in 7 days with the same setup - YouTube estimates $199/month but that's not where the money is - the money is in what the audience does after they watch 17 years old, one camera refresh, one number that changes how you think about what's actually possible right now
0:33

THIS 17-YEAR-OLD SHOWED HIS APP STORE CONNECT LIVE ON CAMERA - $1.14 MILLION IN OCTOBER ALONE - AND HE BUILDS WITH AI interviewer asked him to refresh the page so no one could say it was fake - he refreshed - $1,140,000 in one month sitting right there on screen he's 17 - builds mobile consumer apps - his current one is CalAI - you take a photo of your food and it tells you the calories one idea, one app, one AI feature that solves a problem everyone has - and it scaled to $1.1M/month now Claude Opus 4.8 runs the entire YouTube automation layer on top - clipping, scripting, publishing - $16,567/month from one channel running on autopilot while the app keeps printing TJRmindset pulled 535,276 views in 7 days with the same setup - YouTube estimates $199/month but that's not where the money is - the money is in what the audience does after they watch 17 years old, one camera refresh, one number that changes how you think about what's actually possible right now

Noisy

21,788 просмотров • 2 месяцев назад