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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...

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Carver

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17,952 просмотров • 3 месяцев назад •via X (Twitter)

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Two Chinese developers recorded a 4 minute video showing how to build a team of 7 AI agents that replaces an entire customer support department for $50 a month. They opened a terminal. In 4 minutes they had the whole thing running. One agent classifies tickets. One reads the knowledge base. One handles billing. One watches the customer's tone. One decides when to escalate. One writes the report. One agent runs the other six. The math hit hard. 1,200 tickets a day per person. More than a call center of 8 operators. The company used to pay $25,000 to $40,000 a month in salaries. Now they pay $50 for the API. The video hit 4 million views in 72 hours. Every CEO in China was forwarding it. Every support team in America was panicking. While the West is still debating whether AI will replace workers, China just published the manual. These guys were teaching people how to fire a department. They just showed too much. Bro pause at 0:39. Ignore the guy in the blue shirt pointing. Look at the second monitor on the right. That window is not a support dashboard. That is a live wallet. gabagool22. $868,862 profit. 28,620 predictions. Joined October 2025. → They were filming a tutorial about replacing humans with cheap AI. Their own setup behind them was running an AI that replaces traders. 28,620 positions. All BTC. All 15 minute windows. All green. The comment section turned into a detective board. Someone slowed the video to 0.5x. Screenshotted every frame where the right monitor was visible. Stitched them together. Reconstructed the full wallet page from 6 seconds of background footage. Entry prices between 2 and 10 cents. Payouts in the thousands. Not one red row in 28,620 entries. Biggest single win: $4,696. From a 15 minute window on a Tuesday. The 7 support agents save a company $40K a month. The wallet on their second monitor makes that in one good week. The tutorial taught the world how to replace a customer support team. The setup behind them was already replacing the trading desk. They deleted the wallet zoom from the next upload. Too late. Someone had already screen recorded it. The clip hit Discord. Then Telegram. Then every dev forum. The tutorial got 4 million views. The zoom on their second monitor got another 800,000. 727K people watching the wallet now. The 7 agents are still answering tickets somewhere for $50 a month. The wallet behind them does not need 7 agents. It needs one. And that one was already running while they filmed.
4:31

Two Chinese developers recorded a 4 minute video showing how to build a team of 7 AI agents that replaces an entire customer support department for $50 a month. They opened a terminal. In 4 minutes they had the whole thing running. One agent classifies tickets. One reads the knowledge base. One handles billing. One watches the customer's tone. One decides when to escalate. One writes the report. One agent runs the other six. The math hit hard. 1,200 tickets a day per person. More than a call center of 8 operators. The company used to pay $25,000 to $40,000 a month in salaries. Now they pay $50 for the API. The video hit 4 million views in 72 hours. Every CEO in China was forwarding it. Every support team in America was panicking. While the West is still debating whether AI will replace workers, China just published the manual. These guys were teaching people how to fire a department. They just showed too much. Bro pause at 0:39. Ignore the guy in the blue shirt pointing. Look at the second monitor on the right. That window is not a support dashboard. That is a live wallet. gabagool22. $868,862 profit. 28,620 predictions. Joined October 2025. → They were filming a tutorial about replacing humans with cheap AI. Their own setup behind them was running an AI that replaces traders. 28,620 positions. All BTC. All 15 minute windows. All green. The comment section turned into a detective board. Someone slowed the video to 0.5x. Screenshotted every frame where the right monitor was visible. Stitched them together. Reconstructed the full wallet page from 6 seconds of background footage. Entry prices between 2 and 10 cents. Payouts in the thousands. Not one red row in 28,620 entries. Biggest single win: $4,696. From a 15 minute window on a Tuesday. The 7 support agents save a company $40K a month. The wallet on their second monitor makes that in one good week. The tutorial taught the world how to replace a customer support team. The setup behind them was already replacing the trading desk. They deleted the wallet zoom from the next upload. Too late. Someone had already screen recorded it. The clip hit Discord. Then Telegram. Then every dev forum. The tutorial got 4 million views. The zoom on their second monitor got another 800,000. 727K people watching the wallet now. The 7 agents are still answering tickets somewhere for $50 a month. The wallet behind them does not need 7 agents. It needs one. And that one was already running while they filmed.

Carver

234,893 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

🚨 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 tickets. > One reads the knowledge base. > One handles billing. > One watches the customer’s tone. > One decides when to escalate. > One writes the reports. And one agent runs all the other six. The results? Brutal. 1,200 tickets a day per agent. More than a full call center of 8 human operators. Companies used to spend $25,000–$40,000 per month on salaries. Now they pay just $50 for the API. The video hit 4 million views in 72 hours. Every CEO in China was forwarding it. Every support team in America is panicking. While the West is still debating “Will AI replace jobs?”… China just published the actual manual on how to fire an entire department. But wait it gets way crazier. Pause the video at 0:39. Ignore the guy in the blue shirt. Look at the second monitor on the right. That’s not a support dashboard. That’s a live trading wallet. > Username: gabagool22 > $868,862 profit > 28,620 predictions > All on Bitcoin > All 15-minute windows Every single one green. Profile: Copying his trades: GitHub: The comment section turned into a detective agency. People slowed the video to 0.5x, screenshot every frame, and stitched the full wallet together from just 6 seconds of background footage. Entry prices: 2 to 10 cents. Payouts: thousands of dollars. Not one red trade in 28,620 bets. Biggest single win? $4,696 in one 15-minute window. Here’s the insane part: The 7 AI agents save a company $40K a month. The wallet on their second monitor makes that money in one good week. They were teaching the world how to replace humans with cheap AI. Meanwhile, their own setup behind the camera was already replacing traders. They deleted the wallet zoom in the next upload. Too late. Someone screen-recorded it anyway. The tutorial got 4 million views. The secret wallet clip got another 800K. Now 727K people are staring at that wallet. The 7 agents are still answering tickets somewhere for $50 a month. But the wallet behind them? It doesn’t need 7 agents. It only needs one. And that one was already running while they were filming. Mind officially blown Screenshot it. Send it to a friend. And ask yourself: what’s running on your second monitor?
4:31

🚨 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 tickets. > One reads the knowledge base. > One handles billing. > One watches the customer’s tone. > One decides when to escalate. > One writes the reports. And one agent runs all the other six. The results? Brutal. 1,200 tickets a day per agent. More than a full call center of 8 human operators. Companies used to spend $25,000–$40,000 per month on salaries. Now they pay just $50 for the API. The video hit 4 million views in 72 hours. Every CEO in China was forwarding it. Every support team in America is panicking. While the West is still debating “Will AI replace jobs?”… China just published the actual manual on how to fire an entire department. But wait it gets way crazier. Pause the video at 0:39. Ignore the guy in the blue shirt. Look at the second monitor on the right. That’s not a support dashboard. That’s a live trading wallet. > Username: gabagool22 > $868,862 profit > 28,620 predictions > All on Bitcoin > All 15-minute windows Every single one green. Profile: Copying his trades: GitHub: The comment section turned into a detective agency. People slowed the video to 0.5x, screenshot every frame, and stitched the full wallet together from just 6 seconds of background footage. Entry prices: 2 to 10 cents. Payouts: thousands of dollars. Not one red trade in 28,620 bets. Biggest single win? $4,696 in one 15-minute window. Here’s the insane part: The 7 AI agents save a company $40K a month. The wallet on their second monitor makes that money in one good week. They were teaching the world how to replace humans with cheap AI. Meanwhile, their own setup behind the camera was already replacing traders. They deleted the wallet zoom in the next upload. Too late. Someone screen-recorded it anyway. The tutorial got 4 million views. The secret wallet clip got another 800K. Now 727K people are staring at that wallet. The 7 agents are still answering tickets somewhere for $50 a month. But the wallet behind them? It doesn’t need 7 agents. It only needs one. And that one was already running while they were filming. Mind officially blown Screenshot it. Send it to a friend. And ask yourself: what’s running on your second monitor?

AdiiX

23,252 просмотров • 3 месяцев назад

The person who built Claude Code just explained how he is using it "Now I just have an army of agents that are doing stuff" Only 18 minutes, the best Claude guide on the internet right now. Boris Cherny covered: > how Claude Code is moving beyond just engineers > routines for CI, code review, and daily workflows > why the loop is the next big leap > working with hundreds of agents at once everything is already running through agents, ignoring this is not an option that's exactly why I wrote a full guide on how to build one yourself with Claude Code article below
17:28

The person who built Claude Code just explained how he is using it "Now I just have an army of agents that are doing stuff" Only 18 minutes, the best Claude guide on the internet right now. Boris Cherny covered: > how Claude Code is moving beyond just engineers > routines for CI, code review, and daily workflows > why the loop is the next big leap > working with hundreds of agents at once everything is already running through agents, ignoring this is not an option that's exactly why I wrote a full guide on how to build one yourself with Claude Code article below

Anatoli Kopadze

16,858 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

Marimar Martinez, the Chicago woman whom a Border Patrol agent shot five times last year, says she was only at the hospital for three hours before agents rushed her out. She then was admitted to a second hospital because she was through from her bandages. "As we left the hospital, I was escorted out through the back in a wheelchair. I observed over dozens of border patrol agents waiting outside the hospital. One of them, one of the agents came up to me with his cell phone and took a photograph of me. It was the same agent who had previously kept coming in and out of my room, and I had to repeatedly tell him to leave. I told him I did not consent for him to photograph me, but he did not care. It still haunts me that this agent has my photo on his phone. Was this the agent that shot me? Was this a trophy for him?"
2:19

Marimar Martinez, the Chicago woman whom a Border Patrol agent shot five times last year, says she was only at the hospital for three hours before agents rushed her out. She then was admitted to a second hospital because she was through from her bandages. "As we left the hospital, I was escorted out through the back in a wheelchair. I observed over dozens of border patrol agents waiting outside the hospital. One of them, one of the agents came up to me with his cell phone and took a photograph of me. It was the same agent who had previously kept coming in and out of my room, and I had to repeatedly tell him to leave. I told him I did not consent for him to photograph me, but he did not care. It still haunts me that this agent has my photo on his phone. Was this the agent that shot me? Was this a trophy for him?"

Heartland Signal

11,626 просмотров • 6 месяцев назад

An engineer at Anthropic wrote a spec, pointed Claude at an Asana board, and went home. Claude broke the spec into tickets, spawned agents for each one, and they started building independently. When the agent is confused it runs git-blame and messages the right engineers in Slack. By Monday the agents finished the plugin feature. That's one example of how the best engineers are shipping software right now. Developers will soon orchestrate 50 AI agents in parallel and the difference between a good engineer & a great one would come down to specs. You can't write a spec that holds up at that scale without genuinely understanding what you're building at a deeper level. The next-gen developer who understands the fundamentals, can architect well and orchestrate agent is going to be a 1000x developer!
1:08

An engineer at Anthropic wrote a spec, pointed Claude at an Asana board, and went home. Claude broke the spec into tickets, spawned agents for each one, and they started building independently. When the agent is confused it runs git-blame and messages the right engineers in Slack. By Monday the agents finished the plugin feature. That's one example of how the best engineers are shipping software right now. Developers will soon orchestrate 50 AI agents in parallel and the difference between a good engineer & a great one would come down to specs. You can't write a spec that holds up at that scale without genuinely understanding what you're building at a deeper level. The next-gen developer who understands the fundamentals, can architect well and orchestrate agent is going to be a 1000x developer!

rvivek

1,242,662 просмотров • 5 месяцев назад

A Chinese engineering student built a Claude powered device the size of a credit card. Raspberry Pi. Camera. One red LED. Total cost $14. His professor called it a toy. His classmates laughed. He posted a demo on YouTube and got 200 views. Then someone noticed what the device was actually connected to. A wallet. Making $11 million. In 10 months. kch123. $11,525,240 profit. 2,347 predictions. Joined June 2025. → Profile: The device does one thing. He asks it a question with his voice. Claude scans thousands of prediction markets in real time. When it finds a price that doesn't match reality the red LED lights up. Red light. He places the trade. Green result. $2M position on Seahawks. Won. $1.5M on Villarreal not winning. His professor saw the YouTube video again three months later. The demo was the same. The view count wasn't. Neither was the wallet. He asked the student what changed. The student showed him the balance. The professor didn't say anything. Sat down. Then asked if the device could run two accounts. 759K people watching. $319K still loaded in active positions. The device fits in your hand. The LED is still blinking. His classmates stopped laughing around month four. By month six two of them had built their own.
0:47

A Chinese engineering student built a Claude powered device the size of a credit card. Raspberry Pi. Camera. One red LED. Total cost $14. His professor called it a toy. His classmates laughed. He posted a demo on YouTube and got 200 views. Then someone noticed what the device was actually connected to. A wallet. Making $11 million. In 10 months. kch123. $11,525,240 profit. 2,347 predictions. Joined June 2025. → Profile: The device does one thing. He asks it a question with his voice. Claude scans thousands of prediction markets in real time. When it finds a price that doesn't match reality the red LED lights up. Red light. He places the trade. Green result. $2M position on Seahawks. Won. $1.5M on Villarreal not winning. His professor saw the YouTube video again three months later. The demo was the same. The view count wasn't. Neither was the wallet. He asked the student what changed. The student showed him the balance. The professor didn't say anything. Sat down. Then asked if the device could run two accounts. 759K people watching. $319K still loaded in active positions. The device fits in your hand. The LED is still blinking. His classmates stopped laughing around month four. By month six two of them had built their own.

Carver

790,327 просмотров • 4 месяцев назад

A Japanese TV crew filmed the CEO of a 7 billion yen fast food chain for a feature on Japan's humble corporate culture. His head office in Shinagawa had 3 desks and cost 103,000 yen a month in rent. The office was that small because a Claude agent did the procurement, pricing, and contract work that normally fills three floors. The crew showed the office. Two desks. One printer. Three employees. A rice cooker in the corner. The TV banner introduced him as the entrepreneur whose chain of snack shops sources rice directly from 312 farmers across Japan. At 0:43 he says the word fleet. He says it once. He says it without looking at the camera. The crew kept the line because they thought he meant his delivery vans. He did not mean delivery vans. He meant the fleet of Claude agents that runs every part of his company that does not require a human signature. The two desks at headquarters are for him and the CFO. The third employee is there to answer the phone. One agent reads daily yield data from 312 rice farmers and sets the next morning's wholesale price for each variety. A second agent routes 47 stores worth of inventory based on the previous day's POS data. A third agent drafts every franchise contract and every supplier renewal. He signs every morning before the office opens. Japanese commercial law is satisfied. Someone pulled the company's filings on the Tokyo commercial registry. Every contract filed in the last 14 months had been timestamped between 5:47 AM and 6:03 AM. Every supplier renewal used the same boilerplate clauses, written in slightly different prose each time. The morning shots in the TV segment showed an empty office because the agent had already done the work of 40 employees overnight. 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 CEO had been one of them. He still flies to rice paddies every spring. He still personally tastes every new variety before it gets a code in the system. He still tells investors the head office rent is 103,000 yen because it builds trust. He still has not told the farmers that the agent decided who got the new orders last quarter. The TV crew thought the rundown head office was a story about a humble entrepreneur. It was actually a story about how many employees a 7 billion yen company does not need when one CEO signs what one Claude agent writes.
0:49

A Japanese TV crew filmed the CEO of a 7 billion yen fast food chain for a feature on Japan's humble corporate culture. His head office in Shinagawa had 3 desks and cost 103,000 yen a month in rent. The office was that small because a Claude agent did the procurement, pricing, and contract work that normally fills three floors. The crew showed the office. Two desks. One printer. Three employees. A rice cooker in the corner. The TV banner introduced him as the entrepreneur whose chain of snack shops sources rice directly from 312 farmers across Japan. At 0:43 he says the word fleet. He says it once. He says it without looking at the camera. The crew kept the line because they thought he meant his delivery vans. He did not mean delivery vans. He meant the fleet of Claude agents that runs every part of his company that does not require a human signature. The two desks at headquarters are for him and the CFO. The third employee is there to answer the phone. One agent reads daily yield data from 312 rice farmers and sets the next morning's wholesale price for each variety. A second agent routes 47 stores worth of inventory based on the previous day's POS data. A third agent drafts every franchise contract and every supplier renewal. He signs every morning before the office opens. Japanese commercial law is satisfied. Someone pulled the company's filings on the Tokyo commercial registry. Every contract filed in the last 14 months had been timestamped between 5:47 AM and 6:03 AM. Every supplier renewal used the same boilerplate clauses, written in slightly different prose each time. The morning shots in the TV segment showed an empty office because the agent had already done the work of 40 employees overnight. 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 CEO had been one of them. He still flies to rice paddies every spring. He still personally tastes every new variety before it gets a code in the system. He still tells investors the head office rent is 103,000 yen because it builds trust. He still has not told the farmers that the agent decided who got the new orders last quarter. The TV crew thought the rundown head office was a story about a humble entrepreneur. It was actually a story about how many employees a 7 billion yen company does not need when one CEO signs what one Claude agent writes.

Carver

143,056 просмотров • 2 месяцев назад

THIS GUY TURNED ONE OBSIDIAN VAULT INTO A SHARED BRAIN FOR 5 CLAUDE AGENTS BUILT TO HANDLE 80% OF A SOLO DEVELOPER’S WORK. 00:03 he zooms out and hundreds of connected notes appear on screen. it is the perfect visual for Claude working from one shared project memory instead of starting from zero every session. most developers give Claude 1 file and 1 prompt. this setup gives it the architecture, coding rules, tests, client briefs, and previous decisions before it writes anything. obsidian becomes the memory layer, storing everything in markdown files Claude can read alongside the codebase. every agent works from the same context instead of repeating the same questions. then 5 specialists split the job. one researches, one plans, one codes, one reviews, and one deploys while the developer only controls the important decisions. one vault, 5 agents, 2 model tiers, and a $50 to $150 monthly stack can turn Claude from a chatbot into a small development team.
0:30

THIS GUY TURNED ONE OBSIDIAN VAULT INTO A SHARED BRAIN FOR 5 CLAUDE AGENTS BUILT TO HANDLE 80% OF A SOLO DEVELOPER’S WORK. 00:03 he zooms out and hundreds of connected notes appear on screen. it is the perfect visual for Claude working from one shared project memory instead of starting from zero every session. most developers give Claude 1 file and 1 prompt. this setup gives it the architecture, coding rules, tests, client briefs, and previous decisions before it writes anything. obsidian becomes the memory layer, storing everything in markdown files Claude can read alongside the codebase. every agent works from the same context instead of repeating the same questions. then 5 specialists split the job. one researches, one plans, one codes, one reviews, and one deploys while the developer only controls the important decisions. one vault, 5 agents, 2 model tiers, and a $50 to $150 monthly stack can turn Claude from a chatbot into a small development team.

Gipp 🦅

10,776 просмотров • 1 месяц назад

Anthropic engineer showed how one person can run 5 AI agents, that code, test, review, and deploy at the same time. In 30 minutes they built the whole thing live in one session. Here's what they cover: > when to use one agent vs a full team > how to split work so agents don't step on each other > the exact framework for deciding what each agent handles that's exactly why, I put together a guide on building agent teams that actually work. full guide in the article below 👇
29:58

Anthropic engineer showed how one person can run 5 AI agents, that code, test, review, and deploy at the same time. In 30 minutes they built the whole thing live in one session. Here's what they cover: > when to use one agent vs a full team > how to split work so agents don't step on each other > the exact framework for deciding what each agent handles that's exactly why, I put together a guide on building agent teams that actually work. full guide in the article below 👇

darkzodchi

842,482 просмотров • 2 месяцев назад

A few weeks ago the US government forced Claude Fable 5 offline. It's back. And before they switch it off again, this is your shot to point the most powerful AI on earth at something of your own. Take the 26-year-old in Toronto. His bot went dark the day Fable 5 got pulled. The day it came back, it woke up and started printing again - $568,000 profit and counting. His wallet: Here's the story. When the ban hit, Anthropic had to switch Fable 5 off for everyone. They called it a misunderstanding with the government. Whatever it was, every bot running on that model stopped cold. His was one of them. He didn't rebuild a thing. The loop just sat there, paused, for weeks. Here's what that loop actually does. It's not one prompt to an AI. It's an agentic loop: a team of agents running on repeat. One reads the market, one places the trade, one tries to prove it wrong before a cent moves. Then it goes again, around the clock, keeping what works and dropping what doesn't. Fable 5 is the brain running that team. The exact model the government decided was too powerful to leave on. Point it at Bitcoin's 5-minute markets and it barely misses. Most of its trades close green, and it runs itself. He checks it from his phone. The government could switch off the model. It couldn't switch off the idea. Now the model's back, and so is the money. Save this before next headline. You'll want it the day Fable 5 hits offline again.
0:39

A few weeks ago the US government forced Claude Fable 5 offline. It's back. And before they switch it off again, this is your shot to point the most powerful AI on earth at something of your own. Take the 26-year-old in Toronto. His bot went dark the day Fable 5 got pulled. The day it came back, it woke up and started printing again - $568,000 profit and counting. His wallet: Here's the story. When the ban hit, Anthropic had to switch Fable 5 off for everyone. They called it a misunderstanding with the government. Whatever it was, every bot running on that model stopped cold. His was one of them. He didn't rebuild a thing. The loop just sat there, paused, for weeks. Here's what that loop actually does. It's not one prompt to an AI. It's an agentic loop: a team of agents running on repeat. One reads the market, one places the trade, one tries to prove it wrong before a cent moves. Then it goes again, around the clock, keeping what works and dropping what doesn't. Fable 5 is the brain running that team. The exact model the government decided was too powerful to leave on. Point it at Bitcoin's 5-minute markets and it barely misses. Most of its trades close green, and it runs itself. He checks it from his phone. The government could switch off the model. It couldn't switch off the idea. Now the model's back, and so is the money. Save this before next headline. You'll want it the day Fable 5 hits offline again.

cvxv666

24,055 просмотров • 1 месяц назад

THIS GUY CONNECTED HIS AI AGENTS TO HIS OBSIDIAN AND BUILT A BRAIN THAT LEARNS ON ITS OWN. HERE'S HOW TO BUILD IT Obsidian is just markdown files sitting in a folder. That turns out to be the perfect memory for an AI agent, because an agent can read and write those files directly. He wired his agents into the vault so they pull context from it, do the work, and write what they learned back. The notes aren't the point. The loop is, and it gets sharper every cycle How to build it: 1. Point an agent at your vault. The fastest way, no plugins, no API keys: open a terminal and run npx obsidian-mcp /path/to/your/vault. That exposes your Obsidian folder to Claude as a tool it can read, search, and write to. Add it to your Claude Code or Cowork config and restart 2. Confirm it can see the brain. Ask it: "list the notes in my vault and summarize what's in them." If it reads them back, the connection is live. Now it starts every task with everything the vault already holds instead of from zero 3. Give each agent one job and a write-back rule. Tell it: "research this, then save what you found as a new note in /brain with links to related notes." One agent researches, one summarizes, one plans. Each writes its output back into the vault 4. Close the loop. Add one line to every agent's instructions: "read /brain before starting, write your result back when done." Now each task leaves the vault richer, and the next run reads that before it works. It compounds instead of resetting 5. You only steer. Review what the brain produces, point it at the next thing. The agents handle the reading, writing, and connecting The edge isn't better notes. It's a brain that feeds itself, so the work gets sharper every cycle instead of starting over Bookmark this
0:24

THIS GUY CONNECTED HIS AI AGENTS TO HIS OBSIDIAN AND BUILT A BRAIN THAT LEARNS ON ITS OWN. HERE'S HOW TO BUILD IT Obsidian is just markdown files sitting in a folder. That turns out to be the perfect memory for an AI agent, because an agent can read and write those files directly. He wired his agents into the vault so they pull context from it, do the work, and write what they learned back. The notes aren't the point. The loop is, and it gets sharper every cycle How to build it: 1. Point an agent at your vault. The fastest way, no plugins, no API keys: open a terminal and run npx obsidian-mcp /path/to/your/vault. That exposes your Obsidian folder to Claude as a tool it can read, search, and write to. Add it to your Claude Code or Cowork config and restart 2. Confirm it can see the brain. Ask it: "list the notes in my vault and summarize what's in them." If it reads them back, the connection is live. Now it starts every task with everything the vault already holds instead of from zero 3. Give each agent one job and a write-back rule. Tell it: "research this, then save what you found as a new note in /brain with links to related notes." One agent researches, one summarizes, one plans. Each writes its output back into the vault 4. Close the loop. Add one line to every agent's instructions: "read /brain before starting, write your result back when done." Now each task leaves the vault richer, and the next run reads that before it works. It compounds instead of resetting 5. You only steer. Review what the brain produces, point it at the next thing. The agents handle the reading, writing, and connecting The edge isn't better notes. It's a brain that feeds itself, so the work gets sharper every cycle instead of starting over Bookmark this

Yarchi

58,186 просмотров • 2 месяцев назад

Hunter Biden Had TWO Laptops—And Federal Agents Helped Bury the Second One Not only did the media ignore Hunter’s first laptop—most people missed that he left ANOTHER one with his psychiatrist. That second laptop was seized during a DEA raid—then quietly shipped back to Hunter’s attorneys. Garrett Ziegler says the DEA covered up Hunter Biden’s second laptop after the raid: “… the FBI covered for the laptop that was dropped off at JP Mac Isaac shop. Yes, everybody knows that, but what they don't talk about often is that the DEA also covered for Hunter because they took another one of his laptops, which was inside Keith Ablow safe when Keith Ablow was raided by the DEA. Now, why Hunter left it there?… that's something that only Keith can answer.” Two laptops. Two federal agencies. One massive coverup. – @GarrettZxcvi
1:06

Hunter Biden Had TWO Laptops—And Federal Agents Helped Bury the Second One Not only did the media ignore Hunter’s first laptop—most people missed that he left ANOTHER one with his psychiatrist. That second laptop was seized during a DEA raid—then quietly shipped back to Hunter’s attorneys. Garrett Ziegler says the DEA covered up Hunter Biden’s second laptop after the raid: “… the FBI covered for the laptop that was dropped off at JP Mac Isaac shop. Yes, everybody knows that, but what they don't talk about often is that the DEA also covered for Hunter because they took another one of his laptops, which was inside Keith Ablow safe when Keith Ablow was raided by the DEA. Now, why Hunter left it there?… that's something that only Keith can answer.” Two laptops. Two federal agencies. One massive coverup. – @GarrettZxcvi

The Vigilant Fox 🦊

927,283 просмотров • 1 год назад

Anthropic's Head of Claude Code: "I don't have a to-do list anymore. Claude just builds everything" he runs a tree of thousands of agents. agents prompting agents prompting agents one engineer set up a routine that auto-fixes any bug report not responded to in 5 hours. merges the easy ones himself Boris shipped a feature with an edge case. before he could fix it - another engineer's routine already had a PR up "Claude tells me this all the time. someone else has already fixed it. there's always another Claude working on it" 17 minutes. free. the most honest look at how the Claude Code team actually works bookmark & watch ↓
17:53

Anthropic's Head of Claude Code: "I don't have a to-do list anymore. Claude just builds everything" he runs a tree of thousands of agents. agents prompting agents prompting agents one engineer set up a routine that auto-fixes any bug report not responded to in 5 hours. merges the easy ones himself Boris shipped a feature with an edge case. before he could fix it - another engineer's routine already had a PR up "Claude tells me this all the time. someone else has already fixed it. there's always another Claude working on it" 17 minutes. free. the most honest look at how the Claude Code team actually works bookmark & watch ↓

Carnage

373,919 просмотров • 2 месяцев назад

the bottleneck Karpathy keeps pointing at isn't the model. it's the file you wrote three months ago telling it how to work. his whole framing: code isn't the verb anymore. > you express your will to agents 16 hours a day. > running more of them in parallel is the unlock. > and he drops this line halfway through, no fanfare: "now you can have optimization over the instructions." that's the sentence. the instructions are the new bottleneck. and almost nobody has a process for optimizing them. i built one for myself. it reads 100 of my past Claude Code sessions and rewrites my CLAUDE.md from what the transcripts show, not from what i thought i wrote. one Saturday morning later: a 38-line memory file. 73% of my old CLAUDE.md got deleted. most of it was one-off corrections that hardened into permanent rules months ago and were quietly steering every agent i ran. four behavior patterns surfaced that i had never written down. the loudest one: my prose corrections outnumber code corrections 8.2 to 1. that ratio was running silently through every session for 90 days. you don't need a smarter model. you need an instruction file that still describes how you actually work. listen to the podcast for the framing. open the article for the script that does the optimization.
1:04:42

the bottleneck Karpathy keeps pointing at isn't the model. it's the file you wrote three months ago telling it how to work. his whole framing: code isn't the verb anymore. > you express your will to agents 16 hours a day. > running more of them in parallel is the unlock. > and he drops this line halfway through, no fanfare: "now you can have optimization over the instructions." that's the sentence. the instructions are the new bottleneck. and almost nobody has a process for optimizing them. i built one for myself. it reads 100 of my past Claude Code sessions and rewrites my CLAUDE.md from what the transcripts show, not from what i thought i wrote. one Saturday morning later: a 38-line memory file. 73% of my old CLAUDE.md got deleted. most of it was one-off corrections that hardened into permanent rules months ago and were quietly steering every agent i ran. four behavior patterns surfaced that i had never written down. the loudest one: my prose corrections outnumber code corrections 8.2 to 1. that ratio was running silently through every session for 90 days. you don't need a smarter model. you need an instruction file that still describes how you actually work. listen to the podcast for the framing. open the article for the script that does the optimization.

Mnimiy

50,181 просмотров • 2 месяцев назад

Insomnia made me rich. 2am. Found a $47K/day trading bot on GitHub. No password. Just sitting there. Downloaded it. Owner deleted it by morning. But I already had everything. The code was clean. Simple. Almost boring to read. One script watching BTC on Binance. Another script connected to Polymarket. That is it. → Account: The trick lives in a 30 second gap. BTC moves on spot. Polymarket freezes. Old odds. Stale prices. Reality already shifted but the prediction market is still sleeping. Think of it like football. You sit in the stadium. See the goal. Your bookmaker watches a stream 30 seconds behind. For him it is still 0-0. You bet on what already happened. This bot does exactly that. Every 15 minutes. Sees the move on Binance. Enters Polymarket while odds are frozen. Waits. Window closes. Collects $1 for 30 cents. The wallet running this code: 0x8dxd. Profit chart goes straight up. $629K total. 98% green trades. A human cannot do this. We hesitate. We think. By the time you see the candle, the bot already cashed out. I integrated parts of this code into my scanner. Now it flags wallets exploiting the same lag. One sleepless night. One random GitHub scroll. One download. Sometimes the best alpha is not the strategy you build. It is the code someone forgot to hide.
0:46

Insomnia made me rich. 2am. Found a $47K/day trading bot on GitHub. No password. Just sitting there. Downloaded it. Owner deleted it by morning. But I already had everything. The code was clean. Simple. Almost boring to read. One script watching BTC on Binance. Another script connected to Polymarket. That is it. → Account: The trick lives in a 30 second gap. BTC moves on spot. Polymarket freezes. Old odds. Stale prices. Reality already shifted but the prediction market is still sleeping. Think of it like football. You sit in the stadium. See the goal. Your bookmaker watches a stream 30 seconds behind. For him it is still 0-0. You bet on what already happened. This bot does exactly that. Every 15 minutes. Sees the move on Binance. Enters Polymarket while odds are frozen. Waits. Window closes. Collects $1 for 30 cents. The wallet running this code: 0x8dxd. Profit chart goes straight up. $629K total. 98% green trades. A human cannot do this. We hesitate. We think. By the time you see the candle, the bot already cashed out. I integrated parts of this code into my scanner. Now it flags wallets exploiting the same lag. One sleepless night. One random GitHub scroll. One download. Sometimes the best alpha is not the strategy you build. It is the code someone forgot to hide.

Marlow

688,873 просмотров • 7 месяцев назад

🚨🤬Karen Bass’s LA🤬🚨 Protesters followed federal agents into a parking lot near the LA federal building, then deliberately attacked. They struck the agents multiple times. In fear for his life while being swarmed by belligerent heathens, one officer was forced to brandish his weapon. Two agents were hospitalized. One of them a detention officer. Two suspects were arrested. This is not protesting. It is the calculated targeting of the thin line that still enforces the law. When the people sworn to uphold order become the prey, the rest of us are already living in the aftermath. Stand with the agents. The alternative is far uglier than any slogan.
2:40

🚨🤬Karen Bass’s LA🤬🚨 Protesters followed federal agents into a parking lot near the LA federal building, then deliberately attacked. They struck the agents multiple times. In fear for his life while being swarmed by belligerent heathens, one officer was forced to brandish his weapon. Two agents were hospitalized. One of them a detention officer. Two suspects were arrested. This is not protesting. It is the calculated targeting of the thin line that still enforces the law. When the people sworn to uphold order become the prey, the rest of us are already living in the aftermath. Stand with the agents. The alternative is far uglier than any slogan.

🇺🇸 𝓐𝓟𝓡𝓘𝓛 𝓢𝓟𝓐𝓡𝓚𝓢 🇺🇸

70,078 просмотров • 2 дней назад

US export-control disable Claude Fable 5 overnight. Not for what it said - for what one trader did with it. He turned an $11,000 wreck into $300,000 profit in five days. Then they pulled Claude Fable 5 from public hands. Too late - his bot's still running. His wallet: Every other Claude model still works. The two best ones don't. Anthropic's calling it a misunderstanding. Maybe. But think about what gets a model killed by export control overnight, no warning. Here's what Fable 5 actually did for him. It doesn't predict price. It computes the whole probability surface of a market - every outcome, weighted, faster than the market can correct itself. It finds the bets the crowd writes off as impossible, runs the real math, and buys them for pennies when the math disagrees. One of those just paid x205. A regular guy, a model this sharp, a market no regulator polices. They closed that door overnight - one night too late. He's holding one of the last builds that ever touched a live market. It's still on Polymarket right now, hunting the same mispriced tails. Fable 5 is locked. The algorithm it wrote is loose. You can't open the model anymore. You can still copy the wallet it built in two clicks:
0:46

US export-control disable Claude Fable 5 overnight. Not for what it said - for what one trader did with it. He turned an $11,000 wreck into $300,000 profit in five days. Then they pulled Claude Fable 5 from public hands. Too late - his bot's still running. His wallet: Every other Claude model still works. The two best ones don't. Anthropic's calling it a misunderstanding. Maybe. But think about what gets a model killed by export control overnight, no warning. Here's what Fable 5 actually did for him. It doesn't predict price. It computes the whole probability surface of a market - every outcome, weighted, faster than the market can correct itself. It finds the bets the crowd writes off as impossible, runs the real math, and buys them for pennies when the math disagrees. One of those just paid x205. A regular guy, a model this sharp, a market no regulator polices. They closed that door overnight - one night too late. He's holding one of the last builds that ever touched a live market. It's still on Polymarket right now, hunting the same mispriced tails. Fable 5 is locked. The algorithm it wrote is loose. You can't open the model anymore. You can still copy the wallet it built in two clicks:

cvxv666

77,366 просмотров • 1 месяц назад

Claude Code creator, Boris Cherny: "Forget everything you learned about computer science theory, now you just explain to the model what you need and it does the rest." 32 minutes of the head of Claude Code showing exactly how he builds now. He gave Claude one prompt two weeks ago and it's still running, spawning thousands of agents on its own. The people winning right now aren't writing more code, they're building loops that run without them. Watch it, then go deeper with the graph engineering guide that combines agents and loops below.
31:58

Claude Code creator, Boris Cherny: "Forget everything you learned about computer science theory, now you just explain to the model what you need and it does the rest." 32 minutes of the head of Claude Code showing exactly how he builds now. He gave Claude one prompt two weeks ago and it's still running, spawning thousands of agents on its own. The people winning right now aren't writing more code, they're building loops that run without them. Watch it, then go deeper with the graph engineering guide that combines agents and loops below.

Anatoli Kopadze

47,071 просмотров • 14 дней назад