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🚨Everyone laughed at “AI will replace companies.” Until Matthew Gallagher proved it. > 2 months with $20K. ( ₹16–17 lakh ) > Just him + his brother. > They used ChatGPT, Claude, Grok… and built Medvi. > Month 1 → 300 customers > Month 2 → +1,000 more >...

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Chandana 🌻✨

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16,261 views • 3 months ago •via X (Twitter)

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The k- drama We Are All Trying Here is a must watch I know some people will watch one episode and call it boring. Because It’s not fast paced. It’s slice of life in the most literal sense people sitting in rooms with their envy, their 20 year old dreams that never launched, their friends who made it while they didn’t. It’s quiet. It’s slow. It lingers on silences. But that’s exactly why it gutted me. Because this show understands the war you don’t talk about. The one where you open Instagram at 2am and feel like a failure. Where you’ve been “trying” for years and the world still doesn’t know your name. Hwang Dong-man, twenty years into film school, still no debut. Byeon Eun-ah, called “The Axe” because she has to kill other people’s dreams for a living. Everyone in this drama is carrying some private worthlessness, some comparison they can’t shake. It’s not entertaining in the way K-dramas usually are. It’s uncomfortable. It holds up a mirror to the parts of you that feel behind, bitter, unseen. But that’s why it’s so relatable. That’s why I think everyone should watch it. On the outside, life looks fine but inside, everyone is struggling in their own way. And I think that’s what makes it so relatable. We spend so much time pretending we’re fine, pretending we’re winning. We Are All Trying Here just. admits it. We’re all scared we’re wasting our lives. We are all anxious. We’re all trying here. And maybe that’s enough to start with. #Wearealltryinghere
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The k- drama We Are All Trying Here is a must watch I know some people will watch one episode and call it boring. Because It’s not fast paced. It’s slice of life in the most literal sense people sitting in rooms with their envy, their 20 year old dreams that never launched, their friends who made it while they didn’t. It’s quiet. It’s slow. It lingers on silences. But that’s exactly why it gutted me. Because this show understands the war you don’t talk about. The one where you open Instagram at 2am and feel like a failure. Where you’ve been “trying” for years and the world still doesn’t know your name. Hwang Dong-man, twenty years into film school, still no debut. Byeon Eun-ah, called “The Axe” because she has to kill other people’s dreams for a living. Everyone in this drama is carrying some private worthlessness, some comparison they can’t shake. It’s not entertaining in the way K-dramas usually are. It’s uncomfortable. It holds up a mirror to the parts of you that feel behind, bitter, unseen. But that’s why it’s so relatable. That’s why I think everyone should watch it. On the outside, life looks fine but inside, everyone is struggling in their own way. And I think that’s what makes it so relatable. We spend so much time pretending we’re fine, pretending we’re winning. We Are All Trying Here just. admits it. We’re all scared we’re wasting our lives. We are all anxious. We’re all trying here. And maybe that’s enough to start with. #Wearealltryinghere

EdoQueen🌹

22,449 views • 3 months ago

JENSEN HUANG UNVEILED A BOARD THAT RUNS 1 TRILLION PARAMETER AI MODELS. THE $249 NVIDIA BOX UNDER YOUR DESK KILLS A $200/MONTH AI BILL FOR $5 IN ELECTRICITY jensen held it up on stage with one hand and called it the architecture that runs the future of ai. that same technology now ships in a $249 box smaller than your wallet the jetson orin nano super pulls 7-25 watts and does 67 trillion ai operations per second. llama 3, mistral and deepseek run locally with no api fees and no data leaving your machine most developers pay $2,400 a year across chatgpt, openai api, claude pro and cursor. the jetson costs $314 in year one and $60 a year after. 2 year savings hit $4,431 install ollama with one command, change one line of code to point at localhost, and every tool built for openai works identically. zero rewrites, zero rate limits cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who own the box in 2026 are going to look very far ahead in 2028 bookmark this and read the article below
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JENSEN HUANG UNVEILED A BOARD THAT RUNS 1 TRILLION PARAMETER AI MODELS. THE $249 NVIDIA BOX UNDER YOUR DESK KILLS A $200/MONTH AI BILL FOR $5 IN ELECTRICITY jensen held it up on stage with one hand and called it the architecture that runs the future of ai. that same technology now ships in a $249 box smaller than your wallet the jetson orin nano super pulls 7-25 watts and does 67 trillion ai operations per second. llama 3, mistral and deepseek run locally with no api fees and no data leaving your machine most developers pay $2,400 a year across chatgpt, openai api, claude pro and cursor. the jetson costs $314 in year one and $60 a year after. 2 year savings hit $4,431 install ollama with one command, change one line of code to point at localhost, and every tool built for openai works identically. zero rewrites, zero rate limits cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who own the box in 2026 are going to look very far ahead in 2028 bookmark this and read the article below

starmex

54,309 views • 1 month ago

A 17-year-old student spent $4,200 on 7 Mac minis. Small silver boxes. Stacked on a desk. Connected in one room. From the outside, it looked like a stupid purchase. But inside, it wasn't just 7 computers. It was Skills. Hooks. Memory. Worktrees. One machine handled repeatable tasks. One ran checks automatically. One kept context between sessions. Others ran parallel jobs without touching each other's work. While most people were still typing the same instructions again and again, his setup was already moving. A lot of people pay $200 a month for Claude and still use maybe 20% of it. He built a system around it. Skills turned repeated work into reusable workflows. Hooks made actions fire automatically. Memory stopped every session from starting at zero. Worktrees let multiple tasks run at the same time without collisions. That changed everything. Setup time: under 1 hour once. Time returned: 3 to 5 hours every day. He spent $4,200 once. He made $16,000 in the first week. Not because he found a secret tool. Not because he wrote magical prompts. Because he stopped using it like a chatbot and started using it like infrastructure. 7 Mac minis. 1 student. $4,200 in. $16,000 out. And most people would still call it just a stack of computers.
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A 17-year-old student spent $4,200 on 7 Mac minis. Small silver boxes. Stacked on a desk. Connected in one room. From the outside, it looked like a stupid purchase. But inside, it wasn't just 7 computers. It was Skills. Hooks. Memory. Worktrees. One machine handled repeatable tasks. One ran checks automatically. One kept context between sessions. Others ran parallel jobs without touching each other's work. While most people were still typing the same instructions again and again, his setup was already moving. A lot of people pay $200 a month for Claude and still use maybe 20% of it. He built a system around it. Skills turned repeated work into reusable workflows. Hooks made actions fire automatically. Memory stopped every session from starting at zero. Worktrees let multiple tasks run at the same time without collisions. That changed everything. Setup time: under 1 hour once. Time returned: 3 to 5 hours every day. He spent $4,200 once. He made $16,000 in the first week. Not because he found a secret tool. Not because he wrote magical prompts. Because he stopped using it like a chatbot and started using it like infrastructure. 7 Mac minis. 1 student. $4,200 in. $16,000 out. And most people would still call it just a stack of computers.

Gipp 🦅

21,269 views • 2 months ago

let me explain what Anthropic just did they built an AI model so good at finding security vulnerabilities that they have refused to release it meet Claude Mythos → it’s Anthropic’s newest frontier model and it’s not available to the public. not because it’s not ready. because it’s too dangerous → Mythos found tens of thousands of zero day vulnerabilities across every major operating system and web browser… many of them 1 to 2 decades old. for context… Opus 4.6 found about 500. Mythos found tens of thousands → it found vulnerabilities in the Linux kernel. a 27 year old vulnerability in OpenBSD. a 16 year old vulnerability in FFmpeg → it doesn’t just find bugs. it writes the exploits too. that’s the part that scared them → so instead of releasing it… Anthropic has created Project Glasswing. a cybersecurity initiative where they hand picked 40+ companies to use Mythos for defense only → the partner list reads like a who’s who of tech… Amazon, Apple, Microsoft, Google, Nvidia, Broadcom, Cisco, CrowdStrike, Palo Alto Networks, JPMorgan, the Linux Foundation → Anthropic is giving up to $100 million in usage credits to these partners and $4 million to open source security organizations → they’re briefing CISA and the Commerce Department on how to handle this → the benchmarks are truly insane… Mythos hit 77.8% on SWE-bench Pro where Opus 4.6 scored 53.4%. hit 93.9% on SWE-bench Verified where Opus 4.6 scored 80.8% → Anthropic’s head of frontier red team said this is “the first time a model is this good that we decided to approach release in a very different way” this is the first time an AI company has held back a model because it was too capable not too expensive. not too slow. too dangerous and instead of locking it in a vault they weaponized it for defense and gave it to the companies that run the internet that’s either the most responsible thing an AI company has ever done… or the scariest only time will tell
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let me explain what Anthropic just did they built an AI model so good at finding security vulnerabilities that they have refused to release it meet Claude Mythos → it’s Anthropic’s newest frontier model and it’s not available to the public. not because it’s not ready. because it’s too dangerous → Mythos found tens of thousands of zero day vulnerabilities across every major operating system and web browser… many of them 1 to 2 decades old. for context… Opus 4.6 found about 500. Mythos found tens of thousands → it found vulnerabilities in the Linux kernel. a 27 year old vulnerability in OpenBSD. a 16 year old vulnerability in FFmpeg → it doesn’t just find bugs. it writes the exploits too. that’s the part that scared them → so instead of releasing it… Anthropic has created Project Glasswing. a cybersecurity initiative where they hand picked 40+ companies to use Mythos for defense only → the partner list reads like a who’s who of tech… Amazon, Apple, Microsoft, Google, Nvidia, Broadcom, Cisco, CrowdStrike, Palo Alto Networks, JPMorgan, the Linux Foundation → Anthropic is giving up to $100 million in usage credits to these partners and $4 million to open source security organizations → they’re briefing CISA and the Commerce Department on how to handle this → the benchmarks are truly insane… Mythos hit 77.8% on SWE-bench Pro where Opus 4.6 scored 53.4%. hit 93.9% on SWE-bench Verified where Opus 4.6 scored 80.8% → Anthropic’s head of frontier red team said this is “the first time a model is this good that we decided to approach release in a very different way” this is the first time an AI company has held back a model because it was too capable not too expensive. not too slow. too dangerous and instead of locking it in a vault they weaponized it for defense and gave it to the companies that run the internet that’s either the most responsible thing an AI company has ever done… or the scariest only time will tell

klöss

21,270 views • 3 months ago

A CHINESE GUY STOPPED PAYING WEB DESIGNERS $1,800 PER LANDING PAGE AND BUILT THE SAME KIND OF SITE WITH CLAUDE CODE IN ONE AFTERNOON FOR LESS THAN $70 claude was not just writing code. it was doing the job of a designer, copywriter and frontend dev in one window. in 4 hours, one rough idea turned into the layout, color system, font choices, page sections and the full html/css/js build the real trick was the references. he gave claude 5 screenshots, made it ask 7 questions first, then pushed it toward one clear visual direction instead of accepting another generic ai-looking template the first version already looked solid. the second pass made it feel expensive: better typography, a darker palette, mobile cleanup, cursor effects, 6 micro-interactions and custom hero visuals his old workflow was burning $1,200 on design, $500 on frontend work and another $150 on small fixes every time he needed a new page. now the whole test costs less than $70 and the site still looks like something a $5,000 agency would ship the edge is not “ai builds websites.” the edge is that one person can now brief, critique, polish and launch in one afternoon without waiting 10 days for a designer to send version one
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A CHINESE GUY STOPPED PAYING WEB DESIGNERS $1,800 PER LANDING PAGE AND BUILT THE SAME KIND OF SITE WITH CLAUDE CODE IN ONE AFTERNOON FOR LESS THAN $70 claude was not just writing code. it was doing the job of a designer, copywriter and frontend dev in one window. in 4 hours, one rough idea turned into the layout, color system, font choices, page sections and the full html/css/js build the real trick was the references. he gave claude 5 screenshots, made it ask 7 questions first, then pushed it toward one clear visual direction instead of accepting another generic ai-looking template the first version already looked solid. the second pass made it feel expensive: better typography, a darker palette, mobile cleanup, cursor effects, 6 micro-interactions and custom hero visuals his old workflow was burning $1,200 on design, $500 on frontend work and another $150 on small fixes every time he needed a new page. now the whole test costs less than $70 and the site still looks like something a $5,000 agency would ship the edge is not “ai builds websites.” the edge is that one person can now brief, critique, polish and launch in one afternoon without waiting 10 days for a designer to send version one

Gipp 🦅

293,979 views • 1 month ago

do you understand what Anthropic just admitted? their engineers haven’t written most of their own code since early 2026. 80% of the code merged into Anthropic’s codebase last month was written by Claude. let that sink in. the company building the most powerful AI in the world is already being built by that AI. and the numbers keep getting wilder: → engineers are shipping 8x more code than in 2024. not because they’re working harder. because Claude is doing most of it. → Claude’s success rate on open-ended coding problems hit 76% in May 2026. up 50 points in just 6 months. → one Anthropic employee said “it’s been 5 months since I last wrote any code myself.” → Claude Mythos Preview achieved 52x speedup on research optimization. a skilled human gets 4x in 4-8 hours. → the length of tasks AI can reliably complete is doubling every 4 months. and here’s the part that keeps me up at night: in April 2026, Claude-powered agents were given an open AI safety problem and left alone to solve it. two human researchers recovered 23% of the performance gap in a week. the agents recovered 97% in 800 hours. Anthropic calls this recursive self-improvement. AI building AI. getting better. building a better version. repeat. they say we’re not there yet. but they also say it could come sooner than most institutions are prepared for.
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do you understand what Anthropic just admitted? their engineers haven’t written most of their own code since early 2026. 80% of the code merged into Anthropic’s codebase last month was written by Claude. let that sink in. the company building the most powerful AI in the world is already being built by that AI. and the numbers keep getting wilder: → engineers are shipping 8x more code than in 2024. not because they’re working harder. because Claude is doing most of it. → Claude’s success rate on open-ended coding problems hit 76% in May 2026. up 50 points in just 6 months. → one Anthropic employee said “it’s been 5 months since I last wrote any code myself.” → Claude Mythos Preview achieved 52x speedup on research optimization. a skilled human gets 4x in 4-8 hours. → the length of tasks AI can reliably complete is doubling every 4 months. and here’s the part that keeps me up at night: in April 2026, Claude-powered agents were given an open AI safety problem and left alone to solve it. two human researchers recovered 23% of the performance gap in a week. the agents recovered 97% in 800 hours. Anthropic calls this recursive self-improvement. AI building AI. getting better. building a better version. repeat. they say we’re not there yet. but they also say it could come sooner than most institutions are prepared for.

Poonam Soni

54,496 views • 1 month ago

$TAO Bittensor is starting to bother a lot of people. They are uncomfortable. Before, a couple years ago, when $TAO was already trading around $500–$700, crypto bros looked at it and said: “Yeah, it’s going up.” Of course it was going up. Everything was going up. No questions asked. No curiosity. No attention. No hype. Just another chart moving with the market. Now things changed. BTC OGs ask: “Why is this outperforming BTC?” ETH maxis ask: “Why the hell is this pumping and ETH is still flat?” Gem hunters ask: “Why does it keep decoupling so often?” Beginners ask: “Why is this pumping harder than the gems my KOL gave me?” That’s when the tone shifts. Suddenly they attack TAO Bittensor. They attack the subnets. They attack the holders. They attack the people talking about TAO. Because something HUGE is happening. They think they’re late. But here’s the truth: It’s still early. Come in. You’re welcome here. No permission needed. This house is decentralized and permissionless. And when something big starts moving before everyone understands it, resistance always shows up first. Expect noise. Expect criticism. Expect dismissal. Soon it will feel like everyone is against TAO. That’s not random. That’s the signal. And it already started. Bittensor is becoming impossible to ignore.
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$TAO Bittensor is starting to bother a lot of people. They are uncomfortable. Before, a couple years ago, when $TAO was already trading around $500–$700, crypto bros looked at it and said: “Yeah, it’s going up.” Of course it was going up. Everything was going up. No questions asked. No curiosity. No attention. No hype. Just another chart moving with the market. Now things changed. BTC OGs ask: “Why is this outperforming BTC?” ETH maxis ask: “Why the hell is this pumping and ETH is still flat?” Gem hunters ask: “Why does it keep decoupling so often?” Beginners ask: “Why is this pumping harder than the gems my KOL gave me?” That’s when the tone shifts. Suddenly they attack TAO Bittensor. They attack the subnets. They attack the holders. They attack the people talking about TAO. Because something HUGE is happening. They think they’re late. But here’s the truth: It’s still early. Come in. You’re welcome here. No permission needed. This house is decentralized and permissionless. And when something big starts moving before everyone understands it, resistance always shows up first. Expect noise. Expect criticism. Expect dismissal. Soon it will feel like everyone is against TAO. That’s not random. That’s the signal. And it already started. Bittensor is becoming impossible to ignore.

Tao Outsider

45,269 views • 3 months ago

My friend quit his $180K tech job last month. Everyone called him insane. Yesterday he sent me a screenshot. No text. Just a wallet. anoin123. Joined December. Two months ago. $1,501,199 profit. 182 predictions. That is $8,248 per decision. Not per day. Per click. I asked him what the strategy was. He said one sentence: He does not predict more. He predicts better. → Wallet: 182 trades in two months. That is roughly 3 per day. While everyone else fires 50 positions hoping something sticks, this wallet waits. Biggest single win: $173,000. Currently holding $4.1 million in open positions. Not closed. Active. Right now. The profit curve does not spike and crash. It climbs like stairs. Controlled. Calculated. I spent three hours going through the positions. No meme markets. No lottery tickets. Just high conviction plays with serious size. $173K on one satisfactory yes. Most people lose because they trade like it is a casino. This wallet treats it like a sniper rifle. One shot. One kill. My friend still has not told me if he is copying or just watching. But he also has not gone back to his desk. Some people work 12 months for what this wallet made in 60 days. Maybe the crazy one was not the guy who quit.
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My friend quit his $180K tech job last month. Everyone called him insane. Yesterday he sent me a screenshot. No text. Just a wallet. anoin123. Joined December. Two months ago. $1,501,199 profit. 182 predictions. That is $8,248 per decision. Not per day. Per click. I asked him what the strategy was. He said one sentence: He does not predict more. He predicts better. → Wallet: 182 trades in two months. That is roughly 3 per day. While everyone else fires 50 positions hoping something sticks, this wallet waits. Biggest single win: $173,000. Currently holding $4.1 million in open positions. Not closed. Active. Right now. The profit curve does not spike and crash. It climbs like stairs. Controlled. Calculated. I spent three hours going through the positions. No meme markets. No lottery tickets. Just high conviction plays with serious size. $173K on one satisfactory yes. Most people lose because they trade like it is a casino. This wallet treats it like a sniper rifle. One shot. One kill. My friend still has not told me if he is copying or just watching. But he also has not gone back to his desk. Some people work 12 months for what this wallet made in 60 days. Maybe the crazy one was not the guy who quit.

Marlow

98,288 views • 5 months ago

✨ I revived my first AI startup from 6 years ago with Claude Code [ 💡 ] Back then it used GPT-3 (this was 2 years before ChatGPT existed!) to generate new startup ideas which then people can vote on And the best startup ideas rise to the top! Back then I made it because people complained they didn't have any ideas to build a startup This week I moved it to its own VPS and installed Claude Code and told it to fix everything, the DB had become big and there was stupid write operations on every page load that it made it very slow Claude Code is excellent at fixing all those small bugs from old projects and quickly fixing them As Garry Tan says "boil the oceans" as in before I'd not have the time to fix these kinds of projects, it wouldn't be worth it, I mean IdeasAI doesn't even make money, but now it takes me an hour to do this and it works again! I also upgraded GPT-3 to xAI's Grok 4.2 for new startup ideas
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✨ I revived my first AI startup from 6 years ago with Claude Code [ 💡 ] Back then it used GPT-3 (this was 2 years before ChatGPT existed!) to generate new startup ideas which then people can vote on And the best startup ideas rise to the top! Back then I made it because people complained they didn't have any ideas to build a startup This week I moved it to its own VPS and installed Claude Code and told it to fix everything, the DB had become big and there was stupid write operations on every page load that it made it very slow Claude Code is excellent at fixing all those small bugs from old projects and quickly fixing them As Garry Tan says "boil the oceans" as in before I'd not have the time to fix these kinds of projects, it wouldn't be worth it, I mean IdeasAI doesn't even make money, but now it takes me an hour to do this and it works again! I also upgraded GPT-3 to xAI's Grok 4.2 for new startup ideas

@levelsio

180,039 views • 3 months ago

I started in video games, spent 12 years in Hollywood, then walked away in 2020— still in my late 30s and considered one of the best digital matte painters and concept artists in the industry. Worked on The Hunger Games, The Mandalorian, Westworld, Game of Thrones, Hugo, The Amazing Spider-Man, and 5 Fast & Furious films, etc. Over 30 credits to my name. Now I watch my friends panic about AI taking their jobs. But I’ve seen this before. Old-school matte painters hated us when we moved from glass to digital. We were “ruining the craft.” Now my generation is doing the same thing with AI instead of embracing it. Here’s the truth: AI won’t make Hollywood bigger. It’ll make it better. For the first time, creative people don’t need permission, budgets, or gatekeepers to bring ideas to life. Small teams. Less suits. More originality. This feels like when I first opened Photoshop—with one layer. We’re early. And in the end, more people will create than ever before. The process changed but the results will be better imo. For example, I spent 3 months on this matte painting. Now with ai, it can be done in 2 weeks. 👇🏽
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I started in video games, spent 12 years in Hollywood, then walked away in 2020— still in my late 30s and considered one of the best digital matte painters and concept artists in the industry. Worked on The Hunger Games, The Mandalorian, Westworld, Game of Thrones, Hugo, The Amazing Spider-Man, and 5 Fast & Furious films, etc. Over 30 credits to my name. Now I watch my friends panic about AI taking their jobs. But I’ve seen this before. Old-school matte painters hated us when we moved from glass to digital. We were “ruining the craft.” Now my generation is doing the same thing with AI instead of embracing it. Here’s the truth: AI won’t make Hollywood bigger. It’ll make it better. For the first time, creative people don’t need permission, budgets, or gatekeepers to bring ideas to life. Small teams. Less suits. More originality. This feels like when I first opened Photoshop—with one layer. We’re early. And in the end, more people will create than ever before. The process changed but the results will be better imo. For example, I spent 3 months on this matte painting. Now with ai, it can be done in 2 weeks. 👇🏽

cryptopainter 🐯🍌

61,772 views • 3 months ago

A 24-year-old in Seoul spun up an AI girl with Claude as a joke on a slow weekend. Fourteen months later she pulls $38,000 a month, and not one of the men paying her knows she was never real. He never opened OnlyFans. It demands a verified ID, the one thing an AI operator can't hand over, so the money quietly moved to the place that never asks for a passport: Telegram. Claude writes her whole personality, her captions, her daily posting calendar. An image model locked to one seed keeps her face identical in every clip, that messy-bedroom iPhone look nobody thinks to question. He face-swaps her onto dances that already went viral, so the views are borrowed, not earned from scratch. Day six, the account hit 61,000 followers. The bio holds one link. 2,400 men paid to walk through it into her private channel. The top one sent $2,300 in a single month, certain he was building something real, because Claude remembers his name, his bad days, every word from last time, and answers like she missed him. The whole stack costs forty dollars a month. Then he cloned her. Six girls now, a $120,000-a-month run rate, one guy, one laptop, no face. The girl in the video is dancing in a room that was never built, for a man who will cover her rent this month without ever learning her name.
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Sensitive content

A 24-year-old in Seoul spun up an AI girl with Claude as a joke on a slow weekend. Fourteen months later she pulls $38,000 a month, and not one of the men paying her knows she was never real. He never opened OnlyFans. It demands a verified ID, the one thing an AI operator can't hand over, so the money quietly moved to the place that never asks for a passport: Telegram. Claude writes her whole personality, her captions, her daily posting calendar. An image model locked to one seed keeps her face identical in every clip, that messy-bedroom iPhone look nobody thinks to question. He face-swaps her onto dances that already went viral, so the views are borrowed, not earned from scratch. Day six, the account hit 61,000 followers. The bio holds one link. 2,400 men paid to walk through it into her private channel. The top one sent $2,300 in a single month, certain he was building something real, because Claude remembers his name, his bad days, every word from last time, and answers like she missed him. The whole stack costs forty dollars a month. Then he cloned her. Six girls now, a $120,000-a-month run rate, one guy, one laptop, no face. The girl in the video is dancing in a room that was never built, for a man who will cover her rent this month without ever learning her name.

Kardinall

514,611 views • 14 days ago

A 19 year old Chinese student controls an AI security system from his bed through Telegram. Types one message on his phone, the device across the room wakes up, starts watching and reports back to him like an employee. While American companies charge $100 for a Ring camera plus $4 a month for cloud, this kid spent $10 once and built something smarter. He sent a Telegram message: open maixcam and notify me if a person detected. One second later his phone buzzed back. Green checkmark. Status: Active. Monitoring: Person detection enabled. Notifications: Telegram ready. His roommate laughed. Said a $10 device can't do real security. Then someone walked past the door. The phone buzzed instantly. Person detected. Class: person. Confidence: 92.00%. Position: (120, 80). Size: 100x150. Not a blurry photo 45 seconds later like Amazon cameras. Exact data in under 1 second. What it saw, how sure it is, where the person is standing, how big they are. All through a Telegram message. He built the whole thing with Claude Code in one weekend. The AI runs directly on the device, no cloud, no subscription, no internet needed after setup. 10MB of memory. Boots in 1 second. Camera sees, chip thinks, Telegram delivers. Posted a 17 second demo. GitHub exploded. 7,400 stars in 2 days. But person detection was just the demo. A developer in Tokyo forked it and pointed it at his front door. Telegram alert with a photo every time a delivery arrives. A mom in Seoul pointed it at her baby's crib. Gets a message when the baby stands up. A business owner in Shenzhen bought 6 for $60 total, mounted them around his warehouse and replaced a $200 a month security service. His entire security system is now a Telegram group chat with 6 AI cameras. Someone commented under the GitHub repo: I'm a senior engineer at a home security company. We have a team of 8 working on person detection. This 19 year old did it alone with Claude Code on a $10 device and it works better than our product. The student isn't a machine learning engineer. He's a second year CS student who wanted to know when his roommate eats his snacks. Claude Code wrote the detection model, the Telegram bot, the alert system and the boot sequence. He just described what he wanted. The roommate who laughed now has one pointed at his own shelf. Same device, same code, same Telegram bot. He stops losing snacks. The student stops losing sleep. Everyone is paying $100 for smart cameras with $4 monthly subscriptions. China is building the same thing for $10 with a Telegram chat and Claude Code. 7,400 stars. One weekend. One student who asked Claude Code to watch his door and accidentally built something better than Ring.
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A 19 year old Chinese student controls an AI security system from his bed through Telegram. Types one message on his phone, the device across the room wakes up, starts watching and reports back to him like an employee. While American companies charge $100 for a Ring camera plus $4 a month for cloud, this kid spent $10 once and built something smarter. He sent a Telegram message: open maixcam and notify me if a person detected. One second later his phone buzzed back. Green checkmark. Status: Active. Monitoring: Person detection enabled. Notifications: Telegram ready. His roommate laughed. Said a $10 device can't do real security. Then someone walked past the door. The phone buzzed instantly. Person detected. Class: person. Confidence: 92.00%. Position: (120, 80). Size: 100x150. Not a blurry photo 45 seconds later like Amazon cameras. Exact data in under 1 second. What it saw, how sure it is, where the person is standing, how big they are. All through a Telegram message. He built the whole thing with Claude Code in one weekend. The AI runs directly on the device, no cloud, no subscription, no internet needed after setup. 10MB of memory. Boots in 1 second. Camera sees, chip thinks, Telegram delivers. Posted a 17 second demo. GitHub exploded. 7,400 stars in 2 days. But person detection was just the demo. A developer in Tokyo forked it and pointed it at his front door. Telegram alert with a photo every time a delivery arrives. A mom in Seoul pointed it at her baby's crib. Gets a message when the baby stands up. A business owner in Shenzhen bought 6 for $60 total, mounted them around his warehouse and replaced a $200 a month security service. His entire security system is now a Telegram group chat with 6 AI cameras. Someone commented under the GitHub repo: I'm a senior engineer at a home security company. We have a team of 8 working on person detection. This 19 year old did it alone with Claude Code on a $10 device and it works better than our product. The student isn't a machine learning engineer. He's a second year CS student who wanted to know when his roommate eats his snacks. Claude Code wrote the detection model, the Telegram bot, the alert system and the boot sequence. He just described what he wanted. The roommate who laughed now has one pointed at his own shelf. Same device, same code, same Telegram bot. He stops losing snacks. The student stops losing sleep. Everyone is paying $100 for smart cameras with $4 monthly subscriptions. China is building the same thing for $10 with a Telegram chat and Claude Code. 7,400 stars. One weekend. One student who asked Claude Code to watch his door and accidentally built something better than Ring.

Marlow

23,390 views • 2 months ago

I'm proud to share that Glean has surpassed $300M ARR, just five months after crossing $200M and growing ~3x over the past 15 months. This is an exciting milestone for Glean, and it's a signal about where the enterprise AI market is heading. We’ve long believed the real challenge in enterprise AI is not access to models. It is grounding AI in how a company actually works: its people, knowledge, workflows, permissions, and systems. That’s even clearer now. The companies creating real value with AI are not just adopting better models. They are building systems that understand their business well enough to deliver reliable outcomes at scale. That is the real moat, and it is what we’ve been building at Glean: an unrivaled context layer for enterprise AI. That context has to work across the business, not just inside a single team or use case. We see that in how customers adopt Glean: more than 85% use it across five or more job functions. It also has to meet the security and governance demands of complex enterprises. We see that in who is choosing Glean: our Fortune 500 customer count nearly doubled year over year. And it has to make economic sense as usage grows. In our recent benchmark with Claude Cowork, Glean was preferred roughly 2.5x as often as off-the-shelf MCP tools and used 30% fewer tokens on average. Better context improves both quality and efficiency. I enjoyed talking with CNBC's Deirdre Bosa about this broader shift. In enterprise AI, the winners will not be defined by better models alone. They will be defined by who builds the strongest foundation for enterprise context. Thank you to our customers, partners, and team for helping us build the future of enterprise AI.
0:15

I'm proud to share that Glean has surpassed $300M ARR, just five months after crossing $200M and growing ~3x over the past 15 months. This is an exciting milestone for Glean, and it's a signal about where the enterprise AI market is heading. We’ve long believed the real challenge in enterprise AI is not access to models. It is grounding AI in how a company actually works: its people, knowledge, workflows, permissions, and systems. That’s even clearer now. The companies creating real value with AI are not just adopting better models. They are building systems that understand their business well enough to deliver reliable outcomes at scale. That is the real moat, and it is what we’ve been building at Glean: an unrivaled context layer for enterprise AI. That context has to work across the business, not just inside a single team or use case. We see that in how customers adopt Glean: more than 85% use it across five or more job functions. It also has to meet the security and governance demands of complex enterprises. We see that in who is choosing Glean: our Fortune 500 customer count nearly doubled year over year. And it has to make economic sense as usage grows. In our recent benchmark with Claude Cowork, Glean was preferred roughly 2.5x as often as off-the-shelf MCP tools and used 30% fewer tokens on average. Better context improves both quality and efficiency. I enjoyed talking with CNBC's Deirdre Bosa about this broader shift. In enterprise AI, the winners will not be defined by better models alone. They will be defined by who builds the strongest foundation for enterprise context. Thank you to our customers, partners, and team for helping us build the future of enterprise AI.

Arvind Jain

280,065 views • 1 month ago

🚨 AMERICA JUST BUILT THE WORLD’S MOST POWERFUL METAL 3D PRINTER AND IT’S ABOUT TO MASS-PRODUCE ROCKETS AND MISSILES. Divergent Technologies has unveiled the Monolith One, a giant industrial metal printer standing over 8 meters tall and armed with 12 high-powered lasers delivering a combined 24 kilowatts of energy. Unlike typical 3D printers used for prototypes, this machine is built for serious, high-volume production. It can print large, complex aerospace and defense parts in aluminum, titanium, steel, and nickel alloys and it roughly doubles the output of current systems. Why this matters: • Divergent plans to install 64 more of these machines in a massive new 430,000 sq ft factory in Long Beach, California • Once running, the facility aims to produce tens of thousands of munition airframes per year plus hundreds of thousands of critical metal components • It slashes manufacturing time from months down to weeks or even days • The company already supplies major players like Lockheed Martin and RTX The deeper implication: This isn’t just another 3D printer. It represents a shift toward software-defined, on-demand manufacturing at industrial scale for mission-critical hardware. As defense and aerospace demand skyrockets, traditional supply chains are too slow. Systems like Monolith One could become a cornerstone of faster, more resilient domestic production especially for complex structures that are difficult or impossible to make conventionally. We’re watching the industrialization of additive manufacturing in real time. How do you think large-scale 3D printing will change aerospace and defense manufacturing over the next decade? Follow for more frontier manufacturing and defense technology.
0:10

🚨 AMERICA JUST BUILT THE WORLD’S MOST POWERFUL METAL 3D PRINTER AND IT’S ABOUT TO MASS-PRODUCE ROCKETS AND MISSILES. Divergent Technologies has unveiled the Monolith One, a giant industrial metal printer standing over 8 meters tall and armed with 12 high-powered lasers delivering a combined 24 kilowatts of energy. Unlike typical 3D printers used for prototypes, this machine is built for serious, high-volume production. It can print large, complex aerospace and defense parts in aluminum, titanium, steel, and nickel alloys and it roughly doubles the output of current systems. Why this matters: • Divergent plans to install 64 more of these machines in a massive new 430,000 sq ft factory in Long Beach, California • Once running, the facility aims to produce tens of thousands of munition airframes per year plus hundreds of thousands of critical metal components • It slashes manufacturing time from months down to weeks or even days • The company already supplies major players like Lockheed Martin and RTX The deeper implication: This isn’t just another 3D printer. It represents a shift toward software-defined, on-demand manufacturing at industrial scale for mission-critical hardware. As defense and aerospace demand skyrockets, traditional supply chains are too slow. Systems like Monolith One could become a cornerstone of faster, more resilient domestic production especially for complex structures that are difficult or impossible to make conventionally. We’re watching the industrialization of additive manufacturing in real time. How do you think large-scale 3D printing will change aerospace and defense manufacturing over the next decade? Follow for more frontier manufacturing and defense technology.

TheNewPhysics

80,575 views • 1 month ago

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.
0:17

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Dustin

21,842 views • 5 days ago

GROK SURGES TO THE FRONT OF THE GENAI RACE AS GROWTH SKYROCKETS Grok is absolutely amazing, continuing to stun with incredible results. Web traffic jumped nearly 15% month-over-month in November 2025, the fastest growth in the generative AI industry, proving Elon’s xAI project isn’t just competing, it’s taking real market share from ChatGPT. Grok hit around 234.4 million visits in November, up from 204 million in October. That’s a staggering 1,300% year-over-year surge, pushing it past Perplexity and Claude in user growth and cementing it as the world’s #2 chatbot by market share. The breakout came with Grok 4.1’s release in mid-November. The update debuted at number 1 on LMSYS Arena, that’s the global benchmark where AI models are ranked through blind human evaluations. Grok’s new “Thinking Mode” scored 1483 Elo, a 31-point lead over every open model, beating Gemini 2.5 Pro and Claude 3. The upgrade also cut hallucinations (false answers) by two-thirds, expanded its context window to 2 million tokens, about 1.5 million words of memory, and dominated top reasoning and coding tests like, graduate-level logic, and the emotional intelligence aspect. U.S. traffic surged to 51.5 million visits, boosted by X integration and Grok’s unfiltered style. At just $0.20 per million input tokens, versus GPT-5.1’s $1.25—it’s winning with both speed and affordability. The momentum isn’t hype, it’s lift-off. If growth holds, Grok could reach 500 million users by mid-2026, forcing every rival to redefine what “intelligent” really means. To truthful AI winning! Source: X Freeze, NextBigFuture, CometApi, Langcopilot
0:18

GROK SURGES TO THE FRONT OF THE GENAI RACE AS GROWTH SKYROCKETS Grok is absolutely amazing, continuing to stun with incredible results. Web traffic jumped nearly 15% month-over-month in November 2025, the fastest growth in the generative AI industry, proving Elon’s xAI project isn’t just competing, it’s taking real market share from ChatGPT. Grok hit around 234.4 million visits in November, up from 204 million in October. That’s a staggering 1,300% year-over-year surge, pushing it past Perplexity and Claude in user growth and cementing it as the world’s #2 chatbot by market share. The breakout came with Grok 4.1’s release in mid-November. The update debuted at number 1 on LMSYS Arena, that’s the global benchmark where AI models are ranked through blind human evaluations. Grok’s new “Thinking Mode” scored 1483 Elo, a 31-point lead over every open model, beating Gemini 2.5 Pro and Claude 3. The upgrade also cut hallucinations (false answers) by two-thirds, expanded its context window to 2 million tokens, about 1.5 million words of memory, and dominated top reasoning and coding tests like, graduate-level logic, and the emotional intelligence aspect. U.S. traffic surged to 51.5 million visits, boosted by X integration and Grok’s unfiltered style. At just $0.20 per million input tokens, versus GPT-5.1’s $1.25—it’s winning with both speed and affordability. The momentum isn’t hype, it’s lift-off. If growth holds, Grok could reach 500 million users by mid-2026, forcing every rival to redefine what “intelligent” really means. To truthful AI winning! Source: X Freeze, NextBigFuture, CometApi, Langcopilot

Mario Nawfal

33,823 views • 7 months ago

WHAT IS A MEDBED — It’s not magic. It’s quantum bio-resonance fused with AI diagnostics, scalar frequency therapy, and zero-point field harmonics. Think of it as a quantum MRI, AI surgeon, and energetic regeneration system — all in one. ⸻ HOW DOES IT WORK? 1. FULL BODY QUANTUM SCAN • Scans the biofield (your body’s energetic blueprint). • Detects anomalies at the subatomic level — long before symptoms show. • Quantum sensors read your body like a hyperdimensional fingerprint. 2. CELLULAR TIME REVERSAL • Accesses your original genetic blueprint — the uncorrupted version. • Uses field harmonics to “remind” cells of their ideal state. • It doesn’t just treat — it restores the body to what it was designed to be. 3. ZERO-POINT ENERGY FIELD • Draws limitless energetic fuel from the quantum vacuum. • Your cells absorb this pure energy to accelerate repair, regeneration, and coherence. • This is not “energy healing.” This is quantum field engineering. 4. SCALAR FREQUENCY CORRECTION • Sends precision scalar waves to reprogram damaged cells. • Like frequency acupuncture — no needles, just vibration at the core of matter. • Inflammation, tumors, scar tissue? Disassembled by harmonic codes. ⸻ WHO HAS THIS TECH? • Classified military medical programs • Breakaway science divisions • The same entities deploying Quantum Financial Systems, AI weapons, and clean energy solutions They’ve had it. They just didn’t want you to. ⸻ WHY HAVEN’T WE SEEN IT? Because Big Pharma profits from symptoms, not solutions. They engineered a sick world that can’t heal — because healing ends the business model. A healthy soul doesn’t obey. A healed body doesn’t comply. A clear mind doesn’t consent. So they buried the cure. Laughed at it. Censored it. Because it threatens their entire empire. ⸻ WHY NOW? Because the collapse of their system is happening in real-time: 🔹 Currency reset 🔹 Healthcare exposure 🔹 Quantum rollout They’ll unveil medbeds as a “revolutionary new breakthrough” — but the truth is: 👉 It was always there. Hidden. Waiting. Suppressed. ⸻ THE FUTURE? Is not pills, not surgery, not chemo. The future is vibrational, intelligent, and self-healing. It’s not just about health. It’s about sovereignty — over your body, mind, and frequency. They’ve had the cure. But now, we take the key. They didn’t want you to read this. We go deeper inside👇 — #HealtyNation #MedBedRevolution #QuantumHealing #BigPharmaExposed #ScalarEnergy #QFS #BreakawayScience #BioResonance
0:13

WHAT IS A MEDBED — It’s not magic. It’s quantum bio-resonance fused with AI diagnostics, scalar frequency therapy, and zero-point field harmonics. Think of it as a quantum MRI, AI surgeon, and energetic regeneration system — all in one. ⸻ HOW DOES IT WORK? 1. FULL BODY QUANTUM SCAN • Scans the biofield (your body’s energetic blueprint). • Detects anomalies at the subatomic level — long before symptoms show. • Quantum sensors read your body like a hyperdimensional fingerprint. 2. CELLULAR TIME REVERSAL • Accesses your original genetic blueprint — the uncorrupted version. • Uses field harmonics to “remind” cells of their ideal state. • It doesn’t just treat — it restores the body to what it was designed to be. 3. ZERO-POINT ENERGY FIELD • Draws limitless energetic fuel from the quantum vacuum. • Your cells absorb this pure energy to accelerate repair, regeneration, and coherence. • This is not “energy healing.” This is quantum field engineering. 4. SCALAR FREQUENCY CORRECTION • Sends precision scalar waves to reprogram damaged cells. • Like frequency acupuncture — no needles, just vibration at the core of matter. • Inflammation, tumors, scar tissue? Disassembled by harmonic codes. ⸻ WHO HAS THIS TECH? • Classified military medical programs • Breakaway science divisions • The same entities deploying Quantum Financial Systems, AI weapons, and clean energy solutions They’ve had it. They just didn’t want you to. ⸻ WHY HAVEN’T WE SEEN IT? Because Big Pharma profits from symptoms, not solutions. They engineered a sick world that can’t heal — because healing ends the business model. A healthy soul doesn’t obey. A healed body doesn’t comply. A clear mind doesn’t consent. So they buried the cure. Laughed at it. Censored it. Because it threatens their entire empire. ⸻ WHY NOW? Because the collapse of their system is happening in real-time: 🔹 Currency reset 🔹 Healthcare exposure 🔹 Quantum rollout They’ll unveil medbeds as a “revolutionary new breakthrough” — but the truth is: 👉 It was always there. Hidden. Waiting. Suppressed. ⸻ THE FUTURE? Is not pills, not surgery, not chemo. The future is vibrational, intelligent, and self-healing. It’s not just about health. It’s about sovereignty — over your body, mind, and frequency. They’ve had the cure. But now, we take the key. They didn’t want you to read this. We go deeper inside👇 — #HealtyNation #MedBedRevolution #QuantumHealing #BigPharmaExposed #ScalarEnergy #QFS #BreakawayScience #BioResonance

Mr. Pool

82,956 views • 1 year ago

They Don’t Work for You The H‑1B Isn’t Just Stealing Jobs... It’s Not Even Doing the Work. They said the H‑1B was about “top talent.” In reality, it’s become a passport for fraud, offshoring, and economic sabotage. Here’s the Game: • The H‑1B gets the badge, the cubicle, the paycheck • The actual work is done by a cousin back in Hyderabad • Remote login, fake résumés, offshore handoffs, it's routine • We train them. They train the next guy. The next guy is in India “He couldn’t answer a single technical question. His cousin was doing the coding from India.” – r/cscareerquestions “I reported it. HR told me to stop being racist.” – r/consulting This isn’t about immigration. It’s a deliberate proxy labor cartel, operating inside your own economy. And It Gets Worse... Every H‑1B is a pipeline: 1. Remittance Drain • $20K–$30K per worker sent abroad annually • That’s over $12 billion gone, not invested in your city, your schools, your community creating more jobs. 2. Proxy Networks & Job Sharing • Visa holder here, subcontractor there • One job split between two countries • Zero accountability 3. Trojan Horse for Offshoring • Train the H‑1B. Lose your job. • Six months later, your whole department is in Bangalore “We trained our Infosys replacements. Six months later we were gone.” – Former U.S. tech worker, r/cscareerquestions The Real Math: • 1 visa = 2 paychecks → One here, one overseas • 1 job = 3 U.S. workers lost → The jobholder, the trainee, and the one who never got the offer • 1 lie = a thousand closed doors → Americans can't compete with a transnational lie This is not a “talent strategy.” It’s job laundering. It’s extraction. It’s theft. And everyone in power knows it. Anyone pushing for more of it is literally selling American jobs for the money their lobby gives them. Globalists love cheap labor - its making the companies they own worth trillions and screwing Americans is just a side bonus they have zero guilt over. There is not a single American worker that benefits from foreign labor or foreign students- no other country on earth is doing what America is. They just keep calling it "diversity"... so you won’t call it what it is: Treason against the American worker. So common yet posting about this could get your post taken down by the very folks exploiting this. It already happened to an account that has been search banned, demonetized, throttled, and yet - keeps growing.
0:19

They Don’t Work for You The H‑1B Isn’t Just Stealing Jobs... It’s Not Even Doing the Work. They said the H‑1B was about “top talent.” In reality, it’s become a passport for fraud, offshoring, and economic sabotage. Here’s the Game: • The H‑1B gets the badge, the cubicle, the paycheck • The actual work is done by a cousin back in Hyderabad • Remote login, fake résumés, offshore handoffs, it's routine • We train them. They train the next guy. The next guy is in India “He couldn’t answer a single technical question. His cousin was doing the coding from India.” – r/cscareerquestions “I reported it. HR told me to stop being racist.” – r/consulting This isn’t about immigration. It’s a deliberate proxy labor cartel, operating inside your own economy. And It Gets Worse... Every H‑1B is a pipeline: 1. Remittance Drain • $20K–$30K per worker sent abroad annually • That’s over $12 billion gone, not invested in your city, your schools, your community creating more jobs. 2. Proxy Networks & Job Sharing • Visa holder here, subcontractor there • One job split between two countries • Zero accountability 3. Trojan Horse for Offshoring • Train the H‑1B. Lose your job. • Six months later, your whole department is in Bangalore “We trained our Infosys replacements. Six months later we were gone.” – Former U.S. tech worker, r/cscareerquestions The Real Math: • 1 visa = 2 paychecks → One here, one overseas • 1 job = 3 U.S. workers lost → The jobholder, the trainee, and the one who never got the offer • 1 lie = a thousand closed doors → Americans can't compete with a transnational lie This is not a “talent strategy.” It’s job laundering. It’s extraction. It’s theft. And everyone in power knows it. Anyone pushing for more of it is literally selling American jobs for the money their lobby gives them. Globalists love cheap labor - its making the companies they own worth trillions and screwing Americans is just a side bonus they have zero guilt over. There is not a single American worker that benefits from foreign labor or foreign students- no other country on earth is doing what America is. They just keep calling it "diversity"... so you won’t call it what it is: Treason against the American worker. So common yet posting about this could get your post taken down by the very folks exploiting this. It already happened to an account that has been search banned, demonetized, throttled, and yet - keeps growing.

Chief_Engineer

13,548 views • 4 months ago

Today, we're announcing a $60M Series B led by Battery Ventures, bringing our total funding to $85M in just under a year. Also joining the round are founders and operators who’ve built generational companies of the last two decades – tobi lutke (CEO, Shopify), arash ferdowsi (Dropbox), Claire Hughes Johnson (Stripe), and more. The round came together in 6 days. Here's why. Every major category in enterprise software is seeing multiple AI-native challengers. CRM, ERP, ITSM – all being rebuilt from scratch by a new generation of companies applying AI to solve persistent problems we couldn’t before. Employee Management (also known as HCM) is the exception. It’s the last frontier, and we believe the most important one. The operating layer to manage people, run payroll, benefits, compliance, and IT, for every company in the world, is still built on architecture that predates AI by decades. This fundraise is the story of how Warp is changing that. The average Warp customer is growing 5x faster than their peers, with 1/10th of the HR and admin overhead. We’re seeing a massive shift happening in how the best companies run their people operations. From the fastest-growing AI-startups to massive public companies, the winning teams are running lean: HR, finance, and ops generalists who automate as much as possible, and use their time instead for strategic work that AI can’t automate. Warp is the platform of choice for ambitious companies operating at this new pace. Legacy HCMs help humans track the work. Warp uses AI to proactively complete the work. Workday was built for the last era. We're building for the next one. And it’s working. We've – - Doubled ARR in Q1 - On track to $2B+ payroll volume this year - Signed enterprise customers with thousands of employees - Launched entire product lines back-to-back: Warp benefits brokerage and Warp Fabric (our AI-native IT automation suite built in-house). A few thank-yous: 1. Our customers, the fastest-growing companies in the world, who trust us with their most critical systems. We wouldn't be here without you. 2. Our team - 50+ people in NYC who've built this platform, taken on the hardest problems in business-critical software. We're just getting started. 3. Our investors doubling down in this round, and some of our earliest believers – Sound Ventures (ashton kutcher, Effie Epstein), Derek Grant, (Arnav Sahu), Harj Taggar at Y Combinator, Balaji, Kevin Hartz, Kyle Vogt, Amjad Masad, HOF Capital (Fady Yacoub), colinevans (OpenAI) We're here to arm ambitious American companies with Workday-grade power, but with the usability and delight of an Apple product. With this new funding, we plan to fund deeper AI agents, tax and compliance infrastructure, expand our product suite, and support even closely our fast-growing customers. Come join us.
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Today, we're announcing a $60M Series B led by Battery Ventures, bringing our total funding to $85M in just under a year. Also joining the round are founders and operators who’ve built generational companies of the last two decades – tobi lutke (CEO, Shopify), arash ferdowsi (Dropbox), Claire Hughes Johnson (Stripe), and more. The round came together in 6 days. Here's why. Every major category in enterprise software is seeing multiple AI-native challengers. CRM, ERP, ITSM – all being rebuilt from scratch by a new generation of companies applying AI to solve persistent problems we couldn’t before. Employee Management (also known as HCM) is the exception. It’s the last frontier, and we believe the most important one. The operating layer to manage people, run payroll, benefits, compliance, and IT, for every company in the world, is still built on architecture that predates AI by decades. This fundraise is the story of how Warp is changing that. The average Warp customer is growing 5x faster than their peers, with 1/10th of the HR and admin overhead. We’re seeing a massive shift happening in how the best companies run their people operations. From the fastest-growing AI-startups to massive public companies, the winning teams are running lean: HR, finance, and ops generalists who automate as much as possible, and use their time instead for strategic work that AI can’t automate. Warp is the platform of choice for ambitious companies operating at this new pace. Legacy HCMs help humans track the work. Warp uses AI to proactively complete the work. Workday was built for the last era. We're building for the next one. And it’s working. We've – - Doubled ARR in Q1 - On track to $2B+ payroll volume this year - Signed enterprise customers with thousands of employees - Launched entire product lines back-to-back: Warp benefits brokerage and Warp Fabric (our AI-native IT automation suite built in-house). A few thank-yous: 1. Our customers, the fastest-growing companies in the world, who trust us with their most critical systems. We wouldn't be here without you. 2. Our team - 50+ people in NYC who've built this platform, taken on the hardest problems in business-critical software. We're just getting started. 3. Our investors doubling down in this round, and some of our earliest believers – Sound Ventures (ashton kutcher, Effie Epstein), Derek Grant, (Arnav Sahu), Harj Taggar at Y Combinator, Balaji, Kevin Hartz, Kyle Vogt, Amjad Masad, HOF Capital (Fady Yacoub), colinevans (OpenAI) We're here to arm ambitious American companies with Workday-grade power, but with the usability and delight of an Apple product. With this new funding, we plan to fund deeper AI agents, tax and compliance infrastructure, expand our product suite, and support even closely our fast-growing customers. Come join us.

Ayush S

1,096,625 views • 25 days ago