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18 / ai workflows print money / vibe coding / dm open

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HE STRAPPED A BATTERY TO A $599 MAC MINI AND TURNED A DESK COMPUTER INTO A 14-HOUR PORTABLE AI WORKSTATION 00:03 the battery slides onto the side of the mac mini and the whole setup stops behaving like a desk machine. now it can run from a backpack, power a screen, hold local files and keep working without asking for an outlet. that changes the use case completely. instead of renting another cloud box, one silent computer can handle research dumps, meeting notes, scraped pages, voice transcripts and small automation jobs from almost anywhere. with claude connected, it becomes a moving command center. 45-minute calls become summaries, 120 saved links become organized notes, and messy project folders get cleaned while the machine quietly keeps working in the background. the interesting number is not the battery size. it is the avoided rent. one portable local box can replace $25 storage, $39 automation, $20 transcription and another $30 vps bill if the workflow is built correctly. this is no longer just a desktop. it becomes a portable ai machine that keeps working long after you leave the desk. bookmark this before portable ai becomes the new normal.

HE STRAPPED A BATTERY TO A $599 MAC MINI AND TURNED A DESK COMPUTER INTO A 14-HOUR PORTABLE AI WORKSTATION 00:03 the battery slides onto the side of the mac mini and the whole setup stops behaving like a desk machine. now it can run from a backpack, power a screen, hold local files and keep working without asking for an outlet. that changes the use case completely. instead of renting another cloud box, one silent computer can handle research dumps, meeting notes, scraped pages, voice transcripts and small automation jobs from almost anywhere. with claude connected, it becomes a moving command center. 45-minute calls become summaries, 120 saved links become organized notes, and messy project folders get cleaned while the machine quietly keeps working in the background. the interesting number is not the battery size. it is the avoided rent. one portable local box can replace $25 storage, $39 automation, $20 transcription and another $30 vps bill if the workflow is built correctly. this is no longer just a desktop. it becomes a portable ai machine that keeps working long after you leave the desk. bookmark this before portable ai becomes the new normal.

1,788,765 次观看

THIS GUY BOUGHT A $31 TOY DRONE AND TURNED CLAUDE OPUS 4.8 INTO ITS ENGINEER he plugged it into a laptop, explained the control logic in plain english and let Claude build the flight interface by the end of the session it had calibration, live controls and a browser cockpit moving the drone in real time most people will use Opus 4.8 to save 12 minutes on emails. he used it to turn cheap plastic into a working demo the crazy part isn’t the drone. it’s that the bottleneck moved from writing code to describing exactly what you want built while everyone debates benchmarks, someone with a $31 gadget and one afternoon is already shipping hardware demos

THIS GUY BOUGHT A $31 TOY DRONE AND TURNED CLAUDE OPUS 4.8 INTO ITS ENGINEER he plugged it into a laptop, explained the control logic in plain english and let Claude build the flight interface by the end of the session it had calibration, live controls and a browser cockpit moving the drone in real time most people will use Opus 4.8 to save 12 minutes on emails. he used it to turn cheap plastic into a working demo the crazy part isn’t the drone. it’s that the bottleneck moved from writing code to describing exactly what you want built while everyone debates benchmarks, someone with a $31 gadget and one afternoon is already shipping hardware demos

735,627 次观看

This guy built a mini AI farm out of 4 Nvidia boxes It does not look like a data center. It looks like a stack of small machines sitting next to a laptop. But each box is a DGX Spark with Grace Blackwell inside, 128GB unified memory, and enough room to run models normal gaming GPUs cannot even open. Using the launch price from the article, 4 of them is almost $12,000 of local AI compute on one desk. That sounds expensive until you compare it to cloud GPUs. A serious AI builder can burn $1,500 to $3,000 a month renting A100s and H100s for client work, fine-tunes, agents and 70B models. He basically moved that bill from the cloud into hardware he owns. 4 Nvidia boxes. 512GB unified memory. No hourly meter running in the background. No rented GPUs eating the margin every time an agent runs too long. The funny part is most people still think local AI means a slow laptop running a toy model. Meanwhile guys like this are stacking compute at home. Save this, local AI is turning into the new mining farm.

This guy built a mini AI farm out of 4 Nvidia boxes It does not look like a data center. It looks like a stack of small machines sitting next to a laptop. But each box is a DGX Spark with Grace Blackwell inside, 128GB unified memory, and enough room to run models normal gaming GPUs cannot even open. Using the launch price from the article, 4 of them is almost $12,000 of local AI compute on one desk. That sounds expensive until you compare it to cloud GPUs. A serious AI builder can burn $1,500 to $3,000 a month renting A100s and H100s for client work, fine-tunes, agents and 70B models. He basically moved that bill from the cloud into hardware he owns. 4 Nvidia boxes. 512GB unified memory. No hourly meter running in the background. No rented GPUs eating the margin every time an agent runs too long. The funny part is most people still think local AI means a slow laptop running a toy model. Meanwhile guys like this are stacking compute at home. Save this, local AI is turning into the new mining farm.

591,405 次观看

19-year-old girl spent $42 and 30 minutes, then made $9,600 from children’s videos she never appeared in. 4,100,000 views on YouTube, no camera, no face, no editor. The entire channel was built around kids content. One video uploaded in 2023 still brings in money every month with zero extra work. Dozens of videos like this, each one turning simple stories, bright visuals and voiceovers into small digital assets. $6,000+ a month from a faceless kids channel running in the background. $42 spent on tools, $9,600+ made from content she didn’t even film herself. The best children’s channel is the one that works without needing you on camera.

19-year-old girl spent $42 and 30 minutes, then made $9,600 from children’s videos she never appeared in. 4,100,000 views on YouTube, no camera, no face, no editor. The entire channel was built around kids content. One video uploaded in 2023 still brings in money every month with zero extra work. Dozens of videos like this, each one turning simple stories, bright visuals and voiceovers into small digital assets. $6,000+ a month from a faceless kids channel running in the background. $42 spent on tools, $9,600+ made from content she didn’t even film herself. The best children’s channel is the one that works without needing you on camera.

518,408 次观看

19-YEAR-OLD GUY MADE $12K IN 1 MINUTE FROM HIS FIRST SHOPIFY DROP Not a big brand. Not a perfect product. Just one clean page, one offer, short-form traffic, and Claude for $20/month helping him tighten everything before launch. He used it to study competitors, rewrite the page, pull pain points from reviews, and turn them into hooks people would actually click. Then the store went live. 53 Shopify alerts later, the phone showed a $12K minute. The same store did $100K in one day. Most people keep looking for the right product. He made the offer, page, and ads sharp enough before the traffic arrived.

457,383 次观看

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

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

296,481 次观看

A 40-YEAR-OLD CHINESE MAN TURNED HIMSELF INTO AN AI GIRL AND BUILT A $4.7K/MONTH FANVUE FUNNEL he started with one face-swap clip. same room, same body, same camera, but the output looked like a completely different creator. not a filter, not cosplay, an ai identity built on top of his own footage the workflow is stupidly simple: claude picks the character, niche and visual style. comfyui generates the face, flux makes the content bank, kling turns still images into reels and capcut pushes out dozens of short clips the article breaks the system down: first month barely cleared $420, second month jumped to $4,700 after one reel crossed 600,000 views. the account reached 800 followers and 50 fanvue subscribers before the real automation even started the fanvue mcp is the part most people miss. claude can analyze messages, pricing, content performance and draft replies in the same style. instead of guessing what to post or say, the system turns the audience into data he only needed around 40 minutes a day. schedule reels, check what worked, generate new prompts, reply with claude, repeat. the business is not the ai girl, the business is the machine around her this is no longer content creation. it is identity arbitrage

A 40-YEAR-OLD CHINESE MAN TURNED HIMSELF INTO AN AI GIRL AND BUILT A $4.7K/MONTH FANVUE FUNNEL he started with one face-swap clip. same room, same body, same camera, but the output looked like a completely different creator. not a filter, not cosplay, an ai identity built on top of his own footage the workflow is stupidly simple: claude picks the character, niche and visual style. comfyui generates the face, flux makes the content bank, kling turns still images into reels and capcut pushes out dozens of short clips the article breaks the system down: first month barely cleared $420, second month jumped to $4,700 after one reel crossed 600,000 views. the account reached 800 followers and 50 fanvue subscribers before the real automation even started the fanvue mcp is the part most people miss. claude can analyze messages, pricing, content performance and draft replies in the same style. instead of guessing what to post or say, the system turns the audience into data he only needed around 40 minutes a day. schedule reels, check what worked, generate new prompts, reply with claude, repeat. the business is not the ai girl, the business is the machine around her this is no longer content creation. it is identity arbitrage

195,691 次观看

holy sh*t xai basically built an app store for grok bot instead of hard-coding every workflow, this repo lets you keep adding new capabilities to grok through plugins and reusable integrations [official xai marketplace - 200+ stars] 1/ add new tools without rebuilding the agent 2/ plug in reusable workflows and commands 3/ extend grok with external services and dev tooling the interesting part is that grok bot stops being one fixed assistant and turns into something you can keep upgrading around your own workflow this is probably the repo to study if you want to build on top of grok instead of just prompting it

holy sh*t xai basically built an app store for grok bot instead of hard-coding every workflow, this repo lets you keep adding new capabilities to grok through plugins and reusable integrations [official xai marketplace - 200+ stars] 1/ add new tools without rebuilding the agent 2/ plug in reusable workflows and commands 3/ extend grok with external services and dev tooling the interesting part is that grok bot stops being one fixed assistant and turns into something you can keep upgrading around your own workflow this is probably the repo to study if you want to build on top of grok instead of just prompting it

15,156 次观看

THIS GUY TURNED HIMSELF INTO AN AI GIRL IN ONE SECOND. THE WORKFLOW BEHIND IT CAN RUN A $5,000/MONTH FANVUE PAGE IN 40 MINUTES A DAY 00:01 he raises his arms and instantly turns into an AI girl sitting in the same chair, ready to stream without ever showing his real face Claude creates the name, personality, captions and replies. one prompt can generate a full week of content while keeping the same character across TikTok and Fanvue ComfyUI with Flux builds the face and photo library. Kling 3.0 animates the images, then CapCut turns them into 30 to 50 short videos in one afternoon three daily streams and one clip reaching 400,000 views can send 70 buyers into a $15 Fanvue subscription. paid messages and tips are what push the page past $5,000 he stays behind the camera, Claude runs the brain and the AI girl becomes a business that works every day

THIS GUY TURNED HIMSELF INTO AN AI GIRL IN ONE SECOND. THE WORKFLOW BEHIND IT CAN RUN A $5,000/MONTH FANVUE PAGE IN 40 MINUTES A DAY 00:01 he raises his arms and instantly turns into an AI girl sitting in the same chair, ready to stream without ever showing his real face Claude creates the name, personality, captions and replies. one prompt can generate a full week of content while keeping the same character across TikTok and Fanvue ComfyUI with Flux builds the face and photo library. Kling 3.0 animates the images, then CapCut turns them into 30 to 50 short videos in one afternoon three daily streams and one clip reaching 400,000 views can send 70 buyers into a $15 Fanvue subscription. paid messages and tips are what push the page past $5,000 he stays behind the camera, Claude runs the brain and the AI girl becomes a business that works every day

132,475 次观看

18-YEAR-OLD GUY DID $412K IN SALES FROM ONE SHOPIFY STORE IN 3 MONTHS No warehouse, no big team, no “perfect product.” Just one Shopify store, short-form ads, and a system for fixing what was leaking every week. The screen shows $412,503 in sales, 4,085 orders, and a 4.58% conversion rate. Not because he found some magic product, but because the store kept getting sharper while everyone else was still copying the same pages. Claude helped him break down competitor listings, find patterns in bad reviews, clean up the offer, write simple ad scripts, and check the numbers every Sunday. Most people keep hunting for the next product. He kept fixing the page, the angle, and the ads until the traffic finally started buying.

18-YEAR-OLD GUY DID $412K IN SALES FROM ONE SHOPIFY STORE IN 3 MONTHS No warehouse, no big team, no “perfect product.” Just one Shopify store, short-form ads, and a system for fixing what was leaking every week. The screen shows $412,503 in sales, 4,085 orders, and a 4.58% conversion rate. Not because he found some magic product, but because the store kept getting sharper while everyone else was still copying the same pages. Claude helped him break down competitor listings, find patterns in bad reviews, clean up the offer, write simple ad scripts, and check the numbers every Sunday. Most people keep hunting for the next product. He kept fixing the page, the angle, and the ads until the traffic finally started buying.

143,682 次观看

A 19-year-old Chinese student spent $20 on Claude and built a YouTube automation system making $7,400/month. Found 12 small channels getting 300,000+ views from the same lazy formats, copied the structure, not the videos. Titles, thumbnails, pacing, hooks, upload schedule. 30 minutes later, Claude turned the winning patterns into 40 new video ideas. AI tools made the visuals, voiceovers and captions. CapCut packaged everything into Shorts. He didn’t edit a single video manually. Started testing 20-30 uploads a day across multiple channels. Most failed, but the winners kept pulling views automatically. Month 1 - $430 from test videos. Month 3 - $2,800. Month 6 - $7,400+ every month from channels running while he sleeps. University makes you pay $100,000 to learn theory for 4 years. He spent $20, opened 4 browser windows and let YouTube data tell him what to make next.

A 19-year-old Chinese student spent $20 on Claude and built a YouTube automation system making $7,400/month. Found 12 small channels getting 300,000+ views from the same lazy formats, copied the structure, not the videos. Titles, thumbnails, pacing, hooks, upload schedule. 30 minutes later, Claude turned the winning patterns into 40 new video ideas. AI tools made the visuals, voiceovers and captions. CapCut packaged everything into Shorts. He didn’t edit a single video manually. Started testing 20-30 uploads a day across multiple channels. Most failed, but the winners kept pulling views automatically. Month 1 - $430 from test videos. Month 3 - $2,800. Month 6 - $7,400+ every month from channels running while he sleeps. University makes you pay $100,000 to learn theory for 4 years. He spent $20, opened 4 browser windows and let YouTube data tell him what to make next.

137,223 次观看

18-year-old built a faceless brainrot channel and pulled almost $200,000 in 28 days. 88,783,873 views on YouTube, never appeared on camera once, no studio, no editor, no personal brand. One format repeated hundreds of times: short clips, loud captions, fast pacing, simple hooks and loops designed to make people rewatch. The channel gained 543,000 subscribers in a month. One video crossed 16,000,000 views while even the weaker uploads got more attention than most creators get in a year. Claude turns trends into scripts, AI voice reads them, CapCut packages everything before the trend dies. Old laptop, cheap AI tools, almost $200,000 in estimated revenue. Most people laugh at brainrot content. The algorithm only counts watch time.

83,562 次观看

THIS GUY SAW A $430 AI BILL AND BUILT HIS OWN AI LAB UNDER HIS DESK INSTEAD RTX 5090 + RTX 4090, 56GB VRAM, 128GB RAM, Proxmox and local Qwen / DeepSeek / Llama models running without API keys while everyone else is still paying every time they test a prompt. The best part of the setup: api_key: “not-needed”. His agents can scan GitHub, Reddit and RSS feeds, read notes, test ideas overnight and break without turning into another invoice. If something fails, he fixes the config, not the credit card limit. Most people rent AI by the token. He is turning a desk setup into a private machine that works even when the dashboard is closed.

THIS GUY SAW A $430 AI BILL AND BUILT HIS OWN AI LAB UNDER HIS DESK INSTEAD RTX 5090 + RTX 4090, 56GB VRAM, 128GB RAM, Proxmox and local Qwen / DeepSeek / Llama models running without API keys while everyone else is still paying every time they test a prompt. The best part of the setup: api_key: “not-needed”. His agents can scan GitHub, Reddit and RSS feeds, read notes, test ideas overnight and break without turning into another invoice. If something fails, he fixes the config, not the credit card limit. Most people rent AI by the token. He is turning a desk setup into a private machine that works even when the dashboard is closed.

69,445 次观看

19-YEAR-OLD GUY BOUGHT A $90K BMW M3 AFTER HIS SHOPIFY STORE HIT $287K IN 30 DAYS The Shopify app shows $287K in sales, 50+ orders waiting, and a +4,533% jump in the last 30 days. A few clips later, he is filming a white BMW M3 at the gas station. His setup was simple: one Shopify store, short-form videos, a few products to test, and a $20/month Claude subscription helping him fix the page before sending more traffic. Claude helped rewrite the offer, find better angles from reviews, study competitors, and turn weak product benefits into ads people actually click. Most people keep searching for the perfect product. He kept improving the page, the hook, and the offer until the store started doing numbers. That’s the part people miss: the money didn’t come from one lucky product. It came from testing faster than everyone else.

19-YEAR-OLD GUY BOUGHT A $90K BMW M3 AFTER HIS SHOPIFY STORE HIT $287K IN 30 DAYS The Shopify app shows $287K in sales, 50+ orders waiting, and a +4,533% jump in the last 30 days. A few clips later, he is filming a white BMW M3 at the gas station. His setup was simple: one Shopify store, short-form videos, a few products to test, and a $20/month Claude subscription helping him fix the page before sending more traffic. Claude helped rewrite the offer, find better angles from reviews, study competitors, and turn weak product benefits into ads people actually click. Most people keep searching for the perfect product. He kept improving the page, the hook, and the offer until the store started doing numbers. That’s the part people miss: the money didn’t come from one lucky product. It came from testing faster than everyone else.

46,135 次观看

A 17-year-old guy skipped school and made around $9,300 in one month on YouTube. He used Claude to find trending formats for kids’ and ASMR videos, generate scripts instantly, and automate production. Editing, subtitles, and clips were done in minutes without filming a single frame. Four channels were launched simultaneously, each optimized for maximum reach. He spent just $35 on software and tools to make it all work. In one month, the channels totaled over 11.3 million views, generating roughly $9,300 from ads and small sponsorships. Revenue flows automatically while he tests new video ideas. Claude also helped him track performance, optimize content, and double output efficiency within the month.

A 17-year-old guy skipped school and made around $9,300 in one month on YouTube. He used Claude to find trending formats for kids’ and ASMR videos, generate scripts instantly, and automate production. Editing, subtitles, and clips were done in minutes without filming a single frame. Four channels were launched simultaneously, each optimized for maximum reach. He spent just $35 on software and tools to make it all work. In one month, the channels totaled over 11.3 million views, generating roughly $9,300 from ads and small sponsorships. Revenue flows automatically while he tests new video ideas. Claude also helped him track performance, optimize content, and double output efficiency within the month.

41,429 次观看

THIS DEVELOPER USED A 10,000+ STAR OBSIDIAN REPO TO TURN HIS GROWING VAULT INTO A SEARCHABLE AI MEMORY SYSTEM most people keep adding notes until the graph looks impressive but nobody can find the exact context when a real task starts new note → ai summary → entity links → backlinks → graph update → claude retrieves the right 3–5 files instead of scanning the entire vault the system connects projects, decisions, research, and unfinished ideas, so old context resurfaces automatically instead of disappearing inside hundreds of folders he built the workflow around Claudian, an open-source repo with 10,000+ GitHub stars that brings Claude Code directly into Obsidian → bookmark this before your next 1,000 notes become another beautiful graph that your AI still cannot use

THIS DEVELOPER USED A 10,000+ STAR OBSIDIAN REPO TO TURN HIS GROWING VAULT INTO A SEARCHABLE AI MEMORY SYSTEM most people keep adding notes until the graph looks impressive but nobody can find the exact context when a real task starts new note → ai summary → entity links → backlinks → graph update → claude retrieves the right 3–5 files instead of scanning the entire vault the system connects projects, decisions, research, and unfinished ideas, so old context resurfaces automatically instead of disappearing inside hundreds of folders he built the workflow around Claudian, an open-source repo with 10,000+ GitHub stars that brings Claude Code directly into Obsidian → bookmark this before your next 1,000 notes become another beautiful graph that your AI still cannot use

16,393 次观看

A 20-YEAR-OLD GIRL TURNED WORLD CUP 2026 + AI INTO $3,400 IN THE FIRST 4 DAYS she is not filming matches, stealing goals or running a football media page. she is turning basic world cup questions into youtube shorts for americans watching soccer for the first time the tournament has 48 teams, 104 matches and 3 host countries. every match creates a fresh search wave: what is offside, how do penalties work, who is this player, why is everyone talking about brazil her setup is simple. claude writes the script, an ai voice reads it, capcut cuts the video and canva makes the graphics. one short takes 15 to 20 minutes, so she can post 4 to 6 videos a day the niche is the whole edge. not random edits, not stolen highlights, not generic world cup news. just rules, player stories and country explainers for people who opened youtube after the match confused after just 4 days, one offside explainer crossed 820k views. two player stories passed 400k. with shorts revenue, affiliate links and one small sponsor slot, the channel cleared around $3,400 the crazy part is that the world cup has barely started. most creators are fighting over the same clips while she is selling explanations to a new audience with zero football context this is why timing beats talent. when millions of people search the same questions at the same time, the boring content machine wins

A 20-YEAR-OLD GIRL TURNED WORLD CUP 2026 + AI INTO $3,400 IN THE FIRST 4 DAYS she is not filming matches, stealing goals or running a football media page. she is turning basic world cup questions into youtube shorts for americans watching soccer for the first time the tournament has 48 teams, 104 matches and 3 host countries. every match creates a fresh search wave: what is offside, how do penalties work, who is this player, why is everyone talking about brazil her setup is simple. claude writes the script, an ai voice reads it, capcut cuts the video and canva makes the graphics. one short takes 15 to 20 minutes, so she can post 4 to 6 videos a day the niche is the whole edge. not random edits, not stolen highlights, not generic world cup news. just rules, player stories and country explainers for people who opened youtube after the match confused after just 4 days, one offside explainer crossed 820k views. two player stories passed 400k. with shorts revenue, affiliate links and one small sponsor slot, the channel cleared around $3,400 the crazy part is that the world cup has barely started. most creators are fighting over the same clips while she is selling explanations to a new audience with zero football context this is why timing beats talent. when millions of people search the same questions at the same time, the boring content machine wins

27,412 次观看

A CHINESE GUY PUT 4 MINISFORUM MS-S1 MAX MINI PCs IN HIS BEDROOM AND TURNED THEM INTO A 24/7 AI AGENT CLUSTER. TOTAL POWER BILL: ABOUT $44/MO. each box is a tiny local AI workstation built around the Ryzen AI Max+ 395. around $3,000 per unit gets him 128GB of unified memory, 2TB storage, dual 10GbE, and up to roughly 96GB usable as VRAM on Linux. one MS-S1 Max can already run serious open models without touching the cloud. Qwen3-Coder 30B for fast coding, Llama 3.3 70B for heavier reasoning, and larger research models overnight when speed matters less than free inference. four boxes in one room changes the whole game. he is not opening a chatbot, paying for every loop, or shutting agents down before sleep. this is private infrastructure that keeps working even when he is offline. the agents can sort inboxes, review code, summarize documents, monitor feeds, prep meetings, and read papers overnight. on cloud APIs, that kind of always-on stack can easily burn $800 to $1,200 a month if used aggressively. his setup is roughly a $12,000 hardware spend, but the monthly cost is basically electricity. a rack, a switch, a NAS, a small monitor, and four tiny MS-S1 Max boxes turning a bedroom corner into a private inference factory. this is what AI looks like when it stops being rented and starts becoming something you own.

A CHINESE GUY PUT 4 MINISFORUM MS-S1 MAX MINI PCs IN HIS BEDROOM AND TURNED THEM INTO A 24/7 AI AGENT CLUSTER. TOTAL POWER BILL: ABOUT $44/MO. each box is a tiny local AI workstation built around the Ryzen AI Max+ 395. around $3,000 per unit gets him 128GB of unified memory, 2TB storage, dual 10GbE, and up to roughly 96GB usable as VRAM on Linux. one MS-S1 Max can already run serious open models without touching the cloud. Qwen3-Coder 30B for fast coding, Llama 3.3 70B for heavier reasoning, and larger research models overnight when speed matters less than free inference. four boxes in one room changes the whole game. he is not opening a chatbot, paying for every loop, or shutting agents down before sleep. this is private infrastructure that keeps working even when he is offline. the agents can sort inboxes, review code, summarize documents, monitor feeds, prep meetings, and read papers overnight. on cloud APIs, that kind of always-on stack can easily burn $800 to $1,200 a month if used aggressively. his setup is roughly a $12,000 hardware spend, but the monthly cost is basically electricity. a rack, a switch, a NAS, a small monitor, and four tiny MS-S1 Max boxes turning a bedroom corner into a private inference factory. this is what AI looks like when it stops being rented and starts becoming something you own.

24,836 次观看

A 24-YEAR-OLD STUDENT FROM BERLIN TURNED MUSIC ROYALTY DATA INTO A $14,250/MONTH PROMO BUSINESS he found out most indie artists do not have a music problem. they have a distribution problem. spotify, tiktok and youtube do not reward the best track first, they reward repeatable attention, saves, playlist signals and listener retention his setup was simple. one laptop, royalty analytics, playlist research, short-form clips and outreach automation. instead of chasing fake streams, he built a system that finds small artists with good songs and pushes them into real listener loops every track gets packaged into 15 to 30 clips, tested across tiktok, reels and shorts, then routed back into spotify through landing pages and playlist pitches. the whole point is to create real discovery before the algorithm buries the song after 30 days, the system had promoted 50+ tracks for indie producers, underground rappers and low-fi artists. his service fee starts at $500 per track, with bigger packages going to $1,500 when artists want clips, outreach and reporting the crazy part is that he does not need a label, studio or team. just music data, content distribution and a repeatable backend that artists are too lazy to build themselves this is what music promo looks like when it becomes software

A 24-YEAR-OLD STUDENT FROM BERLIN TURNED MUSIC ROYALTY DATA INTO A $14,250/MONTH PROMO BUSINESS he found out most indie artists do not have a music problem. they have a distribution problem. spotify, tiktok and youtube do not reward the best track first, they reward repeatable attention, saves, playlist signals and listener retention his setup was simple. one laptop, royalty analytics, playlist research, short-form clips and outreach automation. instead of chasing fake streams, he built a system that finds small artists with good songs and pushes them into real listener loops every track gets packaged into 15 to 30 clips, tested across tiktok, reels and shorts, then routed back into spotify through landing pages and playlist pitches. the whole point is to create real discovery before the algorithm buries the song after 30 days, the system had promoted 50+ tracks for indie producers, underground rappers and low-fi artists. his service fee starts at $500 per track, with bigger packages going to $1,500 when artists want clips, outreach and reporting the crazy part is that he does not need a label, studio or team. just music data, content distribution and a repeatable backend that artists are too lazy to build themselves this is what music promo looks like when it becomes software

21,826 次观看

THIS CHINESE TRADER BUILT AN AI AGENT IN 2 HOURS AND LET IT TRADE A $70K ACCOUNT FOR 72 HOURS STRAIGHT he opened Bloome, wrote his trading rules in plain English, picked the signals, set risk limits and let the agent run on its own for 3 days it scans the market, filters setups, manages exposure and executes trades without him sitting there watching every candle most traders still hesitate on entries, close positions from panic and refresh charts all day he just built the system once and let it trade without emotion this is probably where trading goes next: less screen time, more agents, more systems that don’t break their own rules

THIS CHINESE TRADER BUILT AN AI AGENT IN 2 HOURS AND LET IT TRADE A $70K ACCOUNT FOR 72 HOURS STRAIGHT he opened Bloome, wrote his trading rules in plain English, picked the signals, set risk limits and let the agent run on its own for 3 days it scans the market, filters setups, manages exposure and executes trades without him sitting there watching every candle most traders still hesitate on entries, close positions from panic and refresh charts all day he just built the system once and let it trade without emotion this is probably where trading goes next: less screen time, more agents, more systems that don’t break their own rules

23,328 次观看

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HOLY SH*T, I BUILT A F**KING COMPANY INSIDE GROK BOT i split the operation into separate roles for research, writing, outreach, ops, finance and support. each agent owns one narrow job 6 agents → 1 shared operation → automatic handoffs → human approval each bot keeps its own workflow and memory, then passes finished work forward instead of routing everything back through me the control layer catches anything that sends, spends, publishes or deletes and pushes it into approval before anything happens after a few runs this stops feeling like ai chat. it feels like a 24/7 operations team running behind one dashboard

HOLY SH*T, I BUILT A F**KING COMPANY INSIDE GROK BOT i split the operation into separate roles for research, writing, outreach, ops, finance and support. each agent owns one narrow job 6 agents → 1 shared operation → automatic handoffs → human approval each bot keeps its own workflow and memory, then passes finished work forward instead of routing everything back through me the control layer catches anything that sends, spends, publishes or deletes and pushes it into approval before anything happens after a few runs this stops feeling like ai chat. it feels like a 24/7 operations team running behind one dashboard

1,381,069 次观看 • 18 天前

A GROK ENGINEER JUST SHOWED HOW TO MAKE AGENTS IMPROVE THEMSELVES AFTER EVERY RUN most agents lose the useful part when a task ends: the mistake, the correction, and the reason the final version actually worked grok runs two loops at once → one handles the real task → another studies the result → extracts the lesson → saves it for the next run instead of growing one massive prompt, feedback becomes small reusable knowledge files. bad decisions get corrected once, while useful patterns survive across future tasks over time, research, coding and review all inherit what previous runs learned without retraining the model or rebuilding the agent from scratch this is where grok stops feeling like something you keep correcting and starts behaving like a system that compounds what it learns

A GROK ENGINEER JUST SHOWED HOW TO MAKE AGENTS IMPROVE THEMSELVES AFTER EVERY RUN most agents lose the useful part when a task ends: the mistake, the correction, and the reason the final version actually worked grok runs two loops at once → one handles the real task → another studies the result → extracts the lesson → saves it for the next run instead of growing one massive prompt, feedback becomes small reusable knowledge files. bad decisions get corrected once, while useful patterns survive across future tasks over time, research, coding and review all inherit what previous runs learned without retraining the model or rebuilding the agent from scratch this is where grok stops feeling like something you keep correcting and starts behaving like a system that compounds what it learns

87,913 次观看 • 3 天前

A GROK ENGINEER JUST SHOWED HOW TO MAKE AGENTS IMPROVE THEMSELVES AFTER EVERY RUN most agents lose useful feedback when a task ends: what failed, what changed, and which fix actually worked grok can run 2 loops at once → one handles the task → the other reviews the result → extracts the lesson → stores it for the next run instead of expanding one giant prompt, feedback can be saved as small reusable memory files. one solid correction can help across 10 future tasks research, coding, debugging, and review get more consistent when each run can reuse context and lessons from earlier work this is the shift from repeating the same corrections to building an agent that can reuse what it already learned. bookmark this.

A GROK ENGINEER JUST SHOWED HOW TO MAKE AGENTS IMPROVE THEMSELVES AFTER EVERY RUN most agents lose useful feedback when a task ends: what failed, what changed, and which fix actually worked grok can run 2 loops at once → one handles the task → the other reviews the result → extracts the lesson → stores it for the next run instead of expanding one giant prompt, feedback can be saved as small reusable memory files. one solid correction can help across 10 future tasks research, coding, debugging, and review get more consistent when each run can reuse context and lessons from earlier work this is the shift from repeating the same corrections to building an agent that can reuse what it already learned. bookmark this.

25,540 次观看 • 2 天前

holy sh*t. this is f**king insane. langchain just documented the missing memory layer for agents that are supposed to improve after every run. instead of stuffing everything into one giant prompt, deep agents can keep long-term memory, reusable skills and lessons from previous tasks. [it takes a few minutes to understand the loop] 1/ run the task 2/ save what actually worked 3/ load that lesson into the next run that’s how an agent stops starting from zero every single time.

holy sh*t. this is f**king insane. langchain just documented the missing memory layer for agents that are supposed to improve after every run. instead of stuffing everything into one giant prompt, deep agents can keep long-term memory, reusable skills and lessons from previous tasks. [it takes a few minutes to understand the loop] 1/ run the task 2/ save what actually worked 3/ load that lesson into the next run that’s how an agent stops starting from zero every single time.

32,523 次观看 • 2 天前

A 19-year-old girl makes $50,000/month from automated kids’ YouTube videos. She found a viral video with 2.2M views, copied the format, and made her own. Bright visuals, fun animations, satisfying endings kids love. It took her 30 minutes to set up using $40 on Picsart for graphics and CapCut for editing and captions. Uploaded as Shorts, views climbed fast. Week 1: $6,000, week 2: $18,500, week 3: $50,000 from one channel. Now she runs three kids’ channels, making $120,000/month, fully automated. She never appears on camera, didn’t film a single clip herself, and the system handles uploads, captions, and scheduling automatically. One person, a laptop, and simple tools now generate what used to take full teams.

A 19-year-old girl makes $50,000/month from automated kids’ YouTube videos. She found a viral video with 2.2M views, copied the format, and made her own. Bright visuals, fun animations, satisfying endings kids love. It took her 30 minutes to set up using $40 on Picsart for graphics and CapCut for editing and captions. Uploaded as Shorts, views climbed fast. Week 1: $6,000, week 2: $18,500, week 3: $50,000 from one channel. Now she runs three kids’ channels, making $120,000/month, fully automated. She never appears on camera, didn’t film a single clip herself, and the system handles uploads, captions, and scheduling automatically. One person, a laptop, and simple tools now generate what used to take full teams.

1,444,200 次观看 • 4 个月前

F**KING INSANE, GROK BOT IS TRYING TO FIND A TREATMENT FOR A DOG WITH A DISEASE THAT HAS NO CURE 6 agents, 1 patient, 0 candidates and 0 doses. milo is still at 1.4/10 mobility, but on day 2 the crew finally gets the structure it needs to start working chief → assigns charter → defines owns → defines stops → signs role → unlocks vote scout owns literature, chem owns molecule design, tox owns safety, vitals watches milo, scribe keeps evidence, and chief routes the whole case the important part is what happens before research starts. no agent can vote until its charter is signed, and every role gets a hard stopline showing exactly where it must stop by the end, 6/6 charters are active. still 0 candidates, still 0 doses, still 1.4/10 mobility. no treatment yet, but now the crew is finally allowed to search for one. bookmark this

F**KING INSANE, GROK BOT IS TRYING TO FIND A TREATMENT FOR A DOG WITH A DISEASE THAT HAS NO CURE 6 agents, 1 patient, 0 candidates and 0 doses. milo is still at 1.4/10 mobility, but on day 2 the crew finally gets the structure it needs to start working chief → assigns charter → defines owns → defines stops → signs role → unlocks vote scout owns literature, chem owns molecule design, tox owns safety, vitals watches milo, scribe keeps evidence, and chief routes the whole case the important part is what happens before research starts. no agent can vote until its charter is signed, and every role gets a hard stopline showing exactly where it must stop by the end, 6/6 charters are active. still 0 candidates, still 0 doses, still 1.4/10 mobility. no treatment yet, but now the crew is finally allowed to search for one. bookmark this

131,585 次观看 • 15 天前

i built a Robinhood Chain watchtower that remembers what the chart forgets it's called Canary. most tools help you enter a Pons V2 launch faster. Canary starts after that: it watches the position, remembers every state change, and tells you when something actually matters. [give it a token or wallet] → reads deployer balance, reserve / liquidity, swaps, fees and phase changes → stores every sweep as a snapshot → compares the new state against the last one → turns changes into QUIET, WATCH or LEAVE if a deployer starts dumping, reserve drops, fees get swept or volume dies, Canary doesn't look at one fresh chart and guess. it already remembers what changed. the web board keeps everything in one place: token table, selected-position memory, deployer-share history, persistent signals and a live refresh while the watcher keeps writing new snapshots. and the whole thing is intentionally READ ONLY. no signer. no private key. no buy button. no automatic exit. 34/34 deterministic tests passing. open source repo in the first reply.

i built a Robinhood Chain watchtower that remembers what the chart forgets it's called Canary. most tools help you enter a Pons V2 launch faster. Canary starts after that: it watches the position, remembers every state change, and tells you when something actually matters. [give it a token or wallet] → reads deployer balance, reserve / liquidity, swaps, fees and phase changes → stores every sweep as a snapshot → compares the new state against the last one → turns changes into QUIET, WATCH or LEAVE if a deployer starts dumping, reserve drops, fees get swept or volume dies, Canary doesn't look at one fresh chart and guess. it already remembers what changed. the web board keeps everything in one place: token table, selected-position memory, deployer-share history, persistent signals and a live refresh while the watcher keeps writing new snapshots. and the whole thing is intentionally READ ONLY. no signer. no private key. no buy button. no automatic exit. 34/34 deterministic tests passing. open source repo in the first reply.

38,923 次观看 • 4 天前

A 20-year-old Japanese guy is turning kids’ AI videos into a $12,000/month main income. He didn’t hire animators or build a studio. He found a simple format: bright nursery characters, short stories, catchy songs, clean captions, and videos kids can replay nonstop. The numbers are wild. One channel he shows has 28.2M subscribers, 771 videos, and three Shorts with 32M, 3.4M, and 42M views. That’s around 77M views from just three videos. His math: 77M Shorts views can be roughly $15,400. The setup is simple: Claude for ideas, scripts, and structure. Then AI visuals, voice, and CapCut turn it into repeatable kids’ content. Kids don’t care who made the video. They care if it’s bright, simple, loud, and worth watching again. That’s the entire business.

A 20-year-old Japanese guy is turning kids’ AI videos into a $12,000/month main income. He didn’t hire animators or build a studio. He found a simple format: bright nursery characters, short stories, catchy songs, clean captions, and videos kids can replay nonstop. The numbers are wild. One channel he shows has 28.2M subscribers, 771 videos, and three Shorts with 32M, 3.4M, and 42M views. That’s around 77M views from just three videos. His math: 77M Shorts views can be roughly $15,400. The setup is simple: Claude for ideas, scripts, and structure. Then AI visuals, voice, and CapCut turn it into repeatable kids’ content. Kids don’t care who made the video. They care if it’s bright, simple, loud, and worth watching again. That’s the entire business.

588,844 次观看 • 3 个月前

A GIRL BOUGHT A $599 APPLE BOX AND CUT HER AI COSTS FROM $459/MONTH TO $23/MONTH. THE MAC MINI M4 IS QUIETLY BECOMING THE CHEAPEST AI SETUP IN 2026 she didn’t buy it because it looked nice on her desk. she bought it because paying for claude, chatgpt, cursor and api usage every month was getting ridiculous the setup is simple. mac mini m4, ollama, open webui, and local models like qwen, deepseek and llama. for most daily work, that’s enough to write, code, summarize, search notes, and run private workflows without sending everything to the cloud that’s why the math looks so good. a heavy ai stack can hit $459 a month, or $5,508 a year. the mac mini starts at $599 and uses around $3 a month in electricity. if it handles even 70 to 80% of the workload, it pays for itself fast install ollama, point your tools to localhost, and the workflow changes immediately. no token stress, no rate limits, no wondering where your files are going you still keep one cloud model for the hardest tasks but once a small box on your desk does most of the work, paying full price for everything starts to feel stupid

A GIRL BOUGHT A $599 APPLE BOX AND CUT HER AI COSTS FROM $459/MONTH TO $23/MONTH. THE MAC MINI M4 IS QUIETLY BECOMING THE CHEAPEST AI SETUP IN 2026 she didn’t buy it because it looked nice on her desk. she bought it because paying for claude, chatgpt, cursor and api usage every month was getting ridiculous the setup is simple. mac mini m4, ollama, open webui, and local models like qwen, deepseek and llama. for most daily work, that’s enough to write, code, summarize, search notes, and run private workflows without sending everything to the cloud that’s why the math looks so good. a heavy ai stack can hit $459 a month, or $5,508 a year. the mac mini starts at $599 and uses around $3 a month in electricity. if it handles even 70 to 80% of the workload, it pays for itself fast install ollama, point your tools to localhost, and the workflow changes immediately. no token stress, no rate limits, no wondering where your files are going you still keep one cloud model for the hardest tasks but once a small box on your desk does most of the work, paying full price for everything starts to feel stupid

458,361 次观看 • 3 个月前

26-YEAR-OLD GIRL QUIT HER JOB AND BUILT A SMALL SOCIAL NETWORK FOR NYC CAFES. 31,000 USERS IN 4 MONTHS. NOW IT MAKES $18,400/MO FROM LOCAL SHOPS she didn’t try to build another instagram. she built a tiny app for one obsessed niche: people who save cafes, share lists, follow local taste, and discover places before they go viral on tiktok the product is simple. profiles, posts, likes, saved lists, search, comments, and a feed. that is basically every social network at the core. the hard part was never the idea. it was needing 5 engineers to make it work claude code changes that. one person can now build auth, database, feed logic, profiles, follow system, storage, notifications, and deployment with supabase and vercel instead of hiring a full team the money is not from ads. cafes pay $199/month to claim their page, boost new menu drops, see which lists saved them, and post local offers. power users pay $8/month for private maps and early city guides most people still think social networks need millions of users. she proved the opposite. 10,000 people in one niche can be worth more than 100,000 random users scrolling for nothing small social networks are the new local media businesses. claude code just made them cheap enough for one person to start one from a laptop

26-YEAR-OLD GIRL QUIT HER JOB AND BUILT A SMALL SOCIAL NETWORK FOR NYC CAFES. 31,000 USERS IN 4 MONTHS. NOW IT MAKES $18,400/MO FROM LOCAL SHOPS she didn’t try to build another instagram. she built a tiny app for one obsessed niche: people who save cafes, share lists, follow local taste, and discover places before they go viral on tiktok the product is simple. profiles, posts, likes, saved lists, search, comments, and a feed. that is basically every social network at the core. the hard part was never the idea. it was needing 5 engineers to make it work claude code changes that. one person can now build auth, database, feed logic, profiles, follow system, storage, notifications, and deployment with supabase and vercel instead of hiring a full team the money is not from ads. cafes pay $199/month to claim their page, boost new menu drops, see which lists saved them, and post local offers. power users pay $8/month for private maps and early city guides most people still think social networks need millions of users. she proved the opposite. 10,000 people in one niche can be worth more than 100,000 random users scrolling for nothing small social networks are the new local media businesses. claude code just made them cheap enough for one person to start one from a laptop

224,275 次观看 • 3 个月前

HOLY SH*T, I PUT THE F**KING GROK BOT COMPANY IN ORBIT i rebuilt the whole office into an orbital command deck. 6 bots still handle research, writing, outreach, ops, finance and support, but now every role has a real workstation and visible output 6 bots → live workstations → task conveyor → approval layer each desk now has its own progress bar. when a bot is there it moves fast, when the desk is empty it barely crawls, and at 100% the finished task physically flies into the shipped tray the agents got rebuilt too: status lights, monitor glow, coffee runs, blinking, live objectives and actual desk activity instead of static characters behind counters xAI somehow made Grok Bot feel less like chat and more like an operating system for a company that just happens to be in orbit

HOLY SH*T, I PUT THE F**KING GROK BOT COMPANY IN ORBIT i rebuilt the whole office into an orbital command deck. 6 bots still handle research, writing, outreach, ops, finance and support, but now every role has a real workstation and visible output 6 bots → live workstations → task conveyor → approval layer each desk now has its own progress bar. when a bot is there it moves fast, when the desk is empty it barely crawls, and at 100% the finished task physically flies into the shipped tray the agents got rebuilt too: status lights, monitor glow, coffee runs, blinking, live objectives and actual desk activity instead of static characters behind counters xAI somehow made Grok Bot feel less like chat and more like an operating system for a company that just happens to be in orbit

41,397 次观看 • 17 天前

holy sh*t this grok bot repo is f**king insane xai basically published the building blocks for turning grok from a chatbot into an actual agent [official repo with 560+ stars] 1/ give grok tools and function calls 2/ connect web + x search 3/ add code execution and memory the repo also shows real examples for agents, voice, files and multi-step workflows instead of just api hello world demos this is probably the fastest way to understand how xai expects grok bot systems to actually be built

holy sh*t this grok bot repo is f**king insane xai basically published the building blocks for turning grok from a chatbot into an actual agent [official repo with 560+ stars] 1/ give grok tools and function calls 2/ connect web + x search 3/ add code execution and memory the repo also shows real examples for agents, voice, files and multi-step workflows instead of just api hello world demos this is probably the fastest way to understand how xai expects grok bot systems to actually be built

17,360 次观看 • 7 天前

EIGHT USED RTX 3090s. 192GB OF VRAM. ONE PRIVATE BOX BUILT TO RUN 70B AI MODELS WITHOUT RENTING A DATACENTER. 00:06 the team lowers all eight GPUs into the chassis at once, turning a pile of old gaming cards into the core of a serious local AI server. each 3090 contributes 24GB of memory. combined, the rack has enough VRAM for heavyweight models, large document collections, long context and multiple jobs running side by side. these cards are five years old, but AI economics work differently from gaming. memory capacity matters more than having the newest badge, which is why used 3090s remain valuable. the server can keep one model loaded while separate GPUs handle video, images, transcription and overnight agents without sending private company data into the cloud. bookmark this build before yesterday’s gaming GPUs become tomorrow’s cheapest AI infrastructure.

EIGHT USED RTX 3090s. 192GB OF VRAM. ONE PRIVATE BOX BUILT TO RUN 70B AI MODELS WITHOUT RENTING A DATACENTER. 00:06 the team lowers all eight GPUs into the chassis at once, turning a pile of old gaming cards into the core of a serious local AI server. each 3090 contributes 24GB of memory. combined, the rack has enough VRAM for heavyweight models, large document collections, long context and multiple jobs running side by side. these cards are five years old, but AI economics work differently from gaming. memory capacity matters more than having the newest badge, which is why used 3090s remain valuable. the server can keep one model loaded while separate GPUs handle video, images, transcription and overnight agents without sending private company data into the cloud. bookmark this build before yesterday’s gaming GPUs become tomorrow’s cheapest AI infrastructure.

119,001 次观看 • 2 个月前

GROK BOT HAS BEEN RUNNING THIS LAB FOR 9 DAYS, AND THE SYSTEM LOOKS VERY DIFFERENT NOW what started as 6 agents with separate roles has grown into a research clinic built around Milo, with literature search, molecule design, safety checks and human approval while his mobility sits at 1.1/10 scout → papers → chem → candidates → tox → safety → vitals → Milo → chief → decision each bot still owns one narrow job, but the crew now works through Milo’s case together. anything that could reach him still stops before the treatment gate after burning through every candidate, scout goes back to the archives and finds LN-8802 hidden in a paper from 1987. it was in the shortlist the whole time 9 days → 6 agents → 1 dog → 1 candidate left. the lab keeps getting deeper with every run. bookmark this

GROK BOT HAS BEEN RUNNING THIS LAB FOR 9 DAYS, AND THE SYSTEM LOOKS VERY DIFFERENT NOW what started as 6 agents with separate roles has grown into a research clinic built around Milo, with literature search, molecule design, safety checks and human approval while his mobility sits at 1.1/10 scout → papers → chem → candidates → tox → safety → vitals → Milo → chief → decision each bot still owns one narrow job, but the crew now works through Milo’s case together. anything that could reach him still stops before the treatment gate after burning through every candidate, scout goes back to the archives and finds LN-8802 hidden in a paper from 1987. it was in the shortlist the whole time 9 days → 6 agents → 1 dog → 1 candidate left. the lab keeps getting deeper with every run. bookmark this

15,441 次观看 • 8 天前

GROK BOT JUST CLOSED ITS FIRST REAL DEAL the same agent company Elon noticed just sold one of its models to Claudio without me manually pushing every step lead → outreach → conversation → handoff → sale i picked Pons because Ozzy has always backed builders, and that fits what this project is supposed to be: people actually shipping, not just talking about ideas any commissions from this project will go straight back into building it, improving the agents and funding whatever the system needs next the build stays open, and i’m going to keep showing every meaningful change from here

GROK BOT JUST CLOSED ITS FIRST REAL DEAL the same agent company Elon noticed just sold one of its models to Claudio without me manually pushing every step lead → outreach → conversation → handoff → sale i picked Pons because Ozzy has always backed builders, and that fits what this project is supposed to be: people actually shipping, not just talking about ideas any commissions from this project will go straight back into building it, improving the agents and funding whatever the system needs next the build stays open, and i’m going to keep showing every meaningful change from here

19,420 次观看 • 11 天前

$500 a day. Kids' songs. YouTube Shorts Before: 30 mins per video. Claude + Make: 10 videos simultaneously. A month’s worth of content in minutes. > $34/mo software costs > Claude scripts, InVideo edits > $10–500 revenue per video > Your cut: $30,000+/mo on autopilot 10 channels. 10 minutes to review. Zero employees. A niche everyone calls "child's play" while you print the money.

$500 a day. Kids' songs. YouTube Shorts Before: 30 mins per video. Claude + Make: 10 videos simultaneously. A month’s worth of content in minutes. > $34/mo software costs > Claude scripts, InVideo edits > $10–500 revenue per video > Your cut: $30,000+/mo on autopilot 10 channels. 10 minutes to review. Zero employees. A niche everyone calls "child's play" while you print the money.

122,569 次观看 • 4 个月前

F**KING INSANE, DAY 4 OF GROK BOT TRYING TO HELP MILO, AND THE CLINIC DOESN’T STOP WHEN HE FALLS ASLEEP 6 agents, 1 patient, 0 candidates and 0 doses. milo is still at 1.4/10 mobility, but tonight the crew switches from research mode into a real night watch lights out → 2 agents stay awake → vitals keep running → screening continues → every change gets logged → morning handoff vitals stays beside milo while he sleeps. scribe keeps the protocol alive, the monitors keep updating, and the screening counter keeps moving even while the other 4 agents go dark the important part is that grok bot does not need the whole team awake at once. only the roles needed for the current state stay active, while anything that could directly affect milo still waits for human approval morning comes with the same numbers: 0 candidates, 0 doses, 1.4/10 mobility. milo spent the night resting, but the search never actually stopped. bookmark this

F**KING INSANE, DAY 4 OF GROK BOT TRYING TO HELP MILO, AND THE CLINIC DOESN’T STOP WHEN HE FALLS ASLEEP 6 agents, 1 patient, 0 candidates and 0 doses. milo is still at 1.4/10 mobility, but tonight the crew switches from research mode into a real night watch lights out → 2 agents stay awake → vitals keep running → screening continues → every change gets logged → morning handoff vitals stays beside milo while he sleeps. scribe keeps the protocol alive, the monitors keep updating, and the screening counter keeps moving even while the other 4 agents go dark the important part is that grok bot does not need the whole team awake at once. only the roles needed for the current state stay active, while anything that could directly affect milo still waits for human approval morning comes with the same numbers: 0 candidates, 0 doses, 1.4/10 mobility. milo spent the night resting, but the search never actually stopped. bookmark this

17,423 次观看 • 14 天前

THE $599 MAC MINI GETS A $49 DOCK AND TURNS FROM A DESK COMPUTER INTO A TINY 24/7 AI WORKFLOW SERVER 00:19 he clips the dock onto the back of the mac mini, adds extra ports, ethernet, storage and turns one small silver box into a workflow hub that can stay online for 700+ hours a month a base mac mini can sit online all day, pulling light power while scripts watch folders, move files, process notes and keep boring workflows running in the background paired with claude, it becomes a small home automation box: 2-hour lectures get transcribed, 30-page articles get summarized, reports get drafted, and research gets cleaned before you even open the laptop the difference is the loop. trigger, process, verify, save, repeat. the same workflow that costs $40-100/month across cloud tools can run locally from one machine on your desk that is why this tiny upgrade matters. the dock is cheap, but it gives the mac mini enough expansion to act like a quiet server instead of another computer waiting for you to use it bookmark this before your desk setup realizes it became infrastructure.

THE $599 MAC MINI GETS A $49 DOCK AND TURNS FROM A DESK COMPUTER INTO A TINY 24/7 AI WORKFLOW SERVER 00:19 he clips the dock onto the back of the mac mini, adds extra ports, ethernet, storage and turns one small silver box into a workflow hub that can stay online for 700+ hours a month a base mac mini can sit online all day, pulling light power while scripts watch folders, move files, process notes and keep boring workflows running in the background paired with claude, it becomes a small home automation box: 2-hour lectures get transcribed, 30-page articles get summarized, reports get drafted, and research gets cleaned before you even open the laptop the difference is the loop. trigger, process, verify, save, repeat. the same workflow that costs $40-100/month across cloud tools can run locally from one machine on your desk that is why this tiny upgrade matters. the dock is cheap, but it gives the mac mini enough expansion to act like a quiet server instead of another computer waiting for you to use it bookmark this before your desk setup realizes it became infrastructure.

73,740 次观看 • 2 个月前

A JAPANESE GUY BUILT A 200,000-SUBSCRIBER DINOSAUR CHANNEL THAT CAN MAKE $10K - $15K/MONTH At first, the channel looks stupid: cartoon dinosaurs, kids stories, bright thumbnails and 278 videos built around the same simple format. But that is exactly why it works. One niche, one audience, one repeatable machine. The setup can cost less than $100/month: AI voice, basic visuals, editing tools and thumbnails. No camera, no studio, no actor, no personal brand. Just a pipeline that can keep producing the same type of video every week. The real system is not the cartoon. Claude writes the script, hook, title, description, tags and retention points, then the rest becomes assembly: voiceover, visuals, thumbnail, upload, repeat. Run this for 6-12 months and the numbers start getting stupid. Kids content has endless topics, YouTube understands the audience fast, and every new upload feeds the same channel. Most people see cheap dinosaur cartoons. A smarter person sees a faceless media factory that can keep producing while the owner sleeps.

94,959 次观看 • 4 个月前

HOLY SH*T, I MADE THE F**KING COMPANY INSIDE GROK BOT ACTUALLY RUN i rebuilt the 50-second run around a real operating cycle. 6 bots handle research, writing, outreach, ops, finance and support 6 bots → live handoffs → approval queue → human approval each bot has 3 states: working, waiting or blocked. when one finishes, the task physically moves to the next role tasks, shipped work and approvals are connected now, so every counter changes with what is actually happening on screen 6 bots, 1 operation, 1 approval layer. this finally feels like a 24/7 company, not an ai dashboard

HOLY SH*T, I MADE THE F**KING COMPANY INSIDE GROK BOT ACTUALLY RUN i rebuilt the 50-second run around a real operating cycle. 6 bots handle research, writing, outreach, ops, finance and support 6 bots → live handoffs → approval queue → human approval each bot has 3 states: working, waiting or blocked. when one finishes, the task physically moves to the next role tasks, shipped work and approvals are connected now, so every counter changes with what is actually happening on screen 6 bots, 1 operation, 1 approval layer. this finally feels like a 24/7 company, not an ai dashboard

17,075 次观看 • 18 天前