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this GitHub README is where the $5k AI OS starts one CLI > Drive > Gmail > Calendar > Docs > Sheets Claude Code stops being a chat box and starts touching the actual business. that is what clients buy. they buy the moment Google Workspace becomes executable. one... show more

Myttle

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12,602 次观看 • 2 个月前 •via X (Twitter)

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AGENCIES ARE CHARGING $50,000 FOR HEAVY, CLUNKY AUTOMATION, WHILE SOLO OPERATORS ARE SELLING THE SAME OUTCOME FOR $5k AND BUILDING IT IN JUST 3 HOURS Most people think building an AI agency requires an expensive stack of tools like n8n, Make, and Zapier to justify high monthly retainers They spend weeks pitching and designing overly complex “spaghetti” workflows for clients In reality, the better approach is to build an AI Operating System directly in VS Code using local Markdown files The cost gap is insane. You pay $20/month for a Claude account and spend a few hours wiring up ClickUp and Google Workspace APIs Then you package that same architecture as a $5k one-time setup and a $2k monthly retainer Right now, founders are paying $15k + for enterprise AI setups that a single operator can build with almost zero overhead And if you want a practical AI OS playbook, I’ve attached an article below Save this post and the article so you can come back later and learn how to build a full AI operating system in just 3 hours

AGENCIES ARE CHARGING $50,000 FOR HEAVY, CLUNKY AUTOMATION, WHILE SOLO OPERATORS ARE SELLING THE SAME OUTCOME FOR $5k AND BUILDING IT IN JUST 3 HOURS Most people think building an AI agency requires an expensive stack of tools like n8n, Make, and Zapier to justify high monthly retainers They spend weeks pitching and designing overly complex “spaghetti” workflows for clients In reality, the better approach is to build an AI Operating System directly in VS Code using local Markdown files The cost gap is insane. You pay $20/month for a Claude account and spend a few hours wiring up ClickUp and Google Workspace APIs Then you package that same architecture as a $5k one-time setup and a $2k monthly retainer Right now, founders are paying $15k + for enterprise AI setups that a single operator can build with almost zero overhead And if you want a practical AI OS playbook, I’ve attached an article below Save this post and the article so you can come back later and learn how to build a full AI operating system in just 3 hours

Bonsai 🌳

10,885 次观看 • 2 个月前

THIS GUY BUILT AN AUTONOMOUS AI AGENT OUT OF CLAUDE CODE + OBSIDIAN and this is way more interesting than another “use AI to take notes” demo the trick is simple: Obsidian is not the writing app here. it becomes the agent’s memory, task board, and context folder. Claude Code is not just answering prompts. it reads the vault, edits files, follows instructions, and keeps moving through the work like a junior operator with a filesystem. the reusable setup looks like this: 1. create an Obsidian vault for one project 2. keep goals, rules, tasks, decisions, and references as markdown files 3. point Claude Code at the folder 4. give it a clear operating loop: read context → choose next task → execute → write back what changed 5. use the notes as persistent memory instead of re-explaining the project every chat that’s the part people miss. the “agent” is not magic. it’s the boring combination of: - local files - explicit rules - task state - write access - a model that can run through the repo/vault Obsidian makes the memory human-readable. Claude Code makes the memory executable. that combo is why the video worked: it turns a notes app into an operating surface for actual work. best use cases: - content systems - research vaults - coding projects - client ops docs - personal knowledge bases that need actions, not just storage the caveat: if your vault is messy, your agent becomes messy too. folders, naming, “done” criteria, and forbidden actions matter more than the prompt. but once the structure is clean, this is one of the easiest ways to build an agent that remembers what happened yesterday without paying for a full custom app.

THIS GUY BUILT AN AUTONOMOUS AI AGENT OUT OF CLAUDE CODE + OBSIDIAN and this is way more interesting than another “use AI to take notes” demo the trick is simple: Obsidian is not the writing app here. it becomes the agent’s memory, task board, and context folder. Claude Code is not just answering prompts. it reads the vault, edits files, follows instructions, and keeps moving through the work like a junior operator with a filesystem. the reusable setup looks like this: 1. create an Obsidian vault for one project 2. keep goals, rules, tasks, decisions, and references as markdown files 3. point Claude Code at the folder 4. give it a clear operating loop: read context → choose next task → execute → write back what changed 5. use the notes as persistent memory instead of re-explaining the project every chat that’s the part people miss. the “agent” is not magic. it’s the boring combination of: - local files - explicit rules - task state - write access - a model that can run through the repo/vault Obsidian makes the memory human-readable. Claude Code makes the memory executable. that combo is why the video worked: it turns a notes app into an operating surface for actual work. best use cases: - content systems - research vaults - coding projects - client ops docs - personal knowledge bases that need actions, not just storage the caveat: if your vault is messy, your agent becomes messy too. folders, naming, “done” criteria, and forbidden actions matter more than the prompt. but once the structure is clean, this is one of the easiest ways to build an agent that remembers what happened yesterday without paying for a full custom app.

kocer

30,403 次观看 • 1 个月前

THIS GUY BUILT A BUSINESS SECOND BRAIN WITH CLAUDE CODE + OBSIDIAN IN 3 STEPS Most teams do not need another Notion workspace. They need a place where the company can remember how it works. The video shows a simple setup: 1. Create one empty folder called second brain. 2. Split it into 3 buckets: raw new knowledge wiki 3. Let Claude Code turn messy company material into connected notes. The useful part is the separation. Raw is where your existing stuff goes: SOPs, sales docs, process notes, client delivery checklists, old Loom summaries, onboarding docs. New knowledge is where fresh outside material lands: articles, clips, tactics, examples, market notes. Wiki is the cleaned version: concepts, roles, processes, SOPs, gaps, reusable decisions. That is where Claude Code becomes more useful than a normal chat window. Instead of asking it to remember random context forever, you give it a folder it can read, edit, and reorganize. Then Obsidian becomes the human interface. The Obsidian Web Clipper captures useful pages into the vault. Claude Code ingests them. The wiki gets updated. Then you can ask questions like: “Does my current workflow actually hold up?” That is the real point. Not “AI notes.” A business memory system that can compare what you do today against new information tomorrow. The caveat: this is not magic company intelligence. If your raw docs are vague, outdated, or full of tribal knowledge, Claude will organize weak inputs into cleaner weak outputs. You still need naming rules, review habits, and someone responsible for deleting junk. But the setup is refreshingly practical. Folder first. Clipper second. Claude Code as the maintainer. No giant knowledge base migration. No complex setup. Just a local vault that can slowly turn scattered business memory into something searchable, editable, and actually reusable.

THIS GUY BUILT A BUSINESS SECOND BRAIN WITH CLAUDE CODE + OBSIDIAN IN 3 STEPS Most teams do not need another Notion workspace. They need a place where the company can remember how it works. The video shows a simple setup: 1. Create one empty folder called second brain. 2. Split it into 3 buckets: raw new knowledge wiki 3. Let Claude Code turn messy company material into connected notes. The useful part is the separation. Raw is where your existing stuff goes: SOPs, sales docs, process notes, client delivery checklists, old Loom summaries, onboarding docs. New knowledge is where fresh outside material lands: articles, clips, tactics, examples, market notes. Wiki is the cleaned version: concepts, roles, processes, SOPs, gaps, reusable decisions. That is where Claude Code becomes more useful than a normal chat window. Instead of asking it to remember random context forever, you give it a folder it can read, edit, and reorganize. Then Obsidian becomes the human interface. The Obsidian Web Clipper captures useful pages into the vault. Claude Code ingests them. The wiki gets updated. Then you can ask questions like: “Does my current workflow actually hold up?” That is the real point. Not “AI notes.” A business memory system that can compare what you do today against new information tomorrow. The caveat: this is not magic company intelligence. If your raw docs are vague, outdated, or full of tribal knowledge, Claude will organize weak inputs into cleaner weak outputs. You still need naming rules, review habits, and someone responsible for deleting junk. But the setup is refreshingly practical. Folder first. Clipper second. Claude Code as the maintainer. No giant knowledge base migration. No complex setup. Just a local vault that can slowly turn scattered business memory into something searchable, editable, and actually reusable.

kocer

16,642 次观看 • 1 个月前

20-YEAR-OLD GUY SHOWS HOW CLAUDE API CAN TURN 500-VIEW CONTENT INTO A $40K/MONTH CLIENT WORKFLOW Not from a big agency. Not from hiring writers. Just taking the same service people sell every week and wiring Claude API into the boring middle. A topic goes in. It pulls the research, angles, outline, draft, edits, and a clean file. That is normally $500-$1,500 of freelance work per client project. The screen says around $40K/month, but the real number is the time saved. A $3K project stops being 8 hours of rewriting and becomes 45 minutes of checking before delivery. Most people use Claude to write one answer. He is showing what happens when the whole process becomes the product.

20-YEAR-OLD GUY SHOWS HOW CLAUDE API CAN TURN 500-VIEW CONTENT INTO A $40K/MONTH CLIENT WORKFLOW Not from a big agency. Not from hiring writers. Just taking the same service people sell every week and wiring Claude API into the boring middle. A topic goes in. It pulls the research, angles, outline, draft, edits, and a clean file. That is normally $500-$1,500 of freelance work per client project. The screen says around $40K/month, but the real number is the time saved. A $3K project stops being 8 hours of rewriting and becomes 45 minutes of checking before delivery. Most people use Claude to write one answer. He is showing what happens when the whole process becomes the product.

Gipp 🦅

19,254 次观看 • 2 个月前

THE HEAD ENGINEER AT ANTHROPIC LEAKED A SETUP WHERE ONE FILE TURNS INTO A FINISHED PRODUCT IN 24 HOURS you hire nobody - you paste a $3.2M file into Fable 5, and the system unrolls itself from there. root → wiring → 4 branches → tests → release → back into the root in the first hour you write 4 things: boundaries, stack, roles, escalation - everything downstream is a consequence of that file. the first 5 hours the system wires itself into tools and only then decides what to build - a team would spread that across two weeks. 8 straight hours run 4 parallel branches with zero meetings - the same block a team fills with standups. by the time you finally open the diff, tests and the critic have already rejected it twice. the changelog is written by the run, not by a human from memory - so it never falls behind the code. your total involvement across the day is exactly 2 hours: the first one, and the one where you say ship it. the 9 hours you were asleep weren't downtime, they were capacity - a queue you have to launch by hand becomes your monday. and the key part: at 05:00 the report rewrites that same root - what shipped, what got rejected, what it cost. without that last line this is just a schedule - with it, the schedule improves itself. save this and paste it into Claude Code - and tomorrow starts from a better file than today did ↓

THE HEAD ENGINEER AT ANTHROPIC LEAKED A SETUP WHERE ONE FILE TURNS INTO A FINISHED PRODUCT IN 24 HOURS you hire nobody - you paste a $3.2M file into Fable 5, and the system unrolls itself from there. root → wiring → 4 branches → tests → release → back into the root in the first hour you write 4 things: boundaries, stack, roles, escalation - everything downstream is a consequence of that file. the first 5 hours the system wires itself into tools and only then decides what to build - a team would spread that across two weeks. 8 straight hours run 4 parallel branches with zero meetings - the same block a team fills with standups. by the time you finally open the diff, tests and the critic have already rejected it twice. the changelog is written by the run, not by a human from memory - so it never falls behind the code. your total involvement across the day is exactly 2 hours: the first one, and the one where you say ship it. the 9 hours you were asleep weren't downtime, they were capacity - a queue you have to launch by hand becomes your monday. and the key part: at 05:00 the report rewrites that same root - what shipped, what got rejected, what it cost. without that last line this is just a schedule - with it, the schedule improves itself. save this and paste it into Claude Code - and tomorrow starts from a better file than today did ↓

Sprytix

20,510 次观看 • 8 天前

THIS GUY SPENT 5 MINUTES SETTING UP A $20 CLAUDE WORKSPACE AND TURNED 30 MINUTES OF DAILY PROMPT CHAOS INTO A SYSTEM Most people open Claude, type 1 messy prompt, rewrite it 10 times, get the same generic answer and call the model “bad.” He opens Claude Cowork, adds the project rules, past context, working files, examples, decisions and a clean place for the model to remember what it is doing. Same Claude. Same $20 tool. Completely different output. The funny part is there is no magic prompt here. No secret template. No “10x Claude” trick. Just the boring layer Karpathy keeps pointing at: context, memory and structure before output. A setup like this can save 30 minutes a day, which is 15 hours a month. If you use Claude for client work at $50 to $100/hour, that is $750 to $1,500/month in time you stop burning on repeated prompts. The model is real. The output is real. The edge is in not making Claude start from zero every single time.

THIS GUY SPENT 5 MINUTES SETTING UP A $20 CLAUDE WORKSPACE AND TURNED 30 MINUTES OF DAILY PROMPT CHAOS INTO A SYSTEM Most people open Claude, type 1 messy prompt, rewrite it 10 times, get the same generic answer and call the model “bad.” He opens Claude Cowork, adds the project rules, past context, working files, examples, decisions and a clean place for the model to remember what it is doing. Same Claude. Same $20 tool. Completely different output. The funny part is there is no magic prompt here. No secret template. No “10x Claude” trick. Just the boring layer Karpathy keeps pointing at: context, memory and structure before output. A setup like this can save 30 minutes a day, which is 15 hours a month. If you use Claude for client work at $50 to $100/hour, that is $750 to $1,500/month in time you stop burning on repeated prompts. The model is real. The output is real. The edge is in not making Claude start from zero every single time.

Gipp 🦅

14,871 次观看 • 2 个月前

A DEVELOPER CONNECTED CLAUDE CODE TO OBSIDIAN SO HIS AI AGENT WOULD STOP FORGETTING THE PROJECT EVERY MORNING. Every coding session used to start the same way. Claude would understand the repo, fix the bug, explain the architecture, and then the moment the session ended, all of that context disappeared. Same codebase. Same decisions. Same architecture. Same mistakes repeated again. So he added a memory layer. Instead of treating Claude Code like a smart terminal, he connected it to a local Obsidian vault through MCP. Now Claude can read the repo, open the vault, create notes, link concepts, and write important decisions back into the system. When it studies the codebase, it does not just answer once and forget. It creates notes for the major services, maps how the architecture works, links auth to the database, connects APIs to storage, and records why certain migrations or design choices exist. Obsidian becomes the project graph. Now when he asks why something was built a certain way, Claude does not guess from the current prompt. It reads the decision notes. When he starts a new branch, Claude checks the active context file. When the work is done, it updates what changed, what is blocked, and what the next agent needs to know before touching the repo. That is the real loop: read context, write code, capture decisions, update memory. Most people are still using AI coding tools like disposable chat windows. Ask, patch, close, forget. This setup turns Claude Code into infrastructure. The repo gets a memory layer that survives every session, and multiple AI agents can work from the same project map without stepping on each other. The unlock is not better prompting. The unlock is giving the agent somewhere to remember what it already learned.

A DEVELOPER CONNECTED CLAUDE CODE TO OBSIDIAN SO HIS AI AGENT WOULD STOP FORGETTING THE PROJECT EVERY MORNING. Every coding session used to start the same way. Claude would understand the repo, fix the bug, explain the architecture, and then the moment the session ended, all of that context disappeared. Same codebase. Same decisions. Same architecture. Same mistakes repeated again. So he added a memory layer. Instead of treating Claude Code like a smart terminal, he connected it to a local Obsidian vault through MCP. Now Claude can read the repo, open the vault, create notes, link concepts, and write important decisions back into the system. When it studies the codebase, it does not just answer once and forget. It creates notes for the major services, maps how the architecture works, links auth to the database, connects APIs to storage, and records why certain migrations or design choices exist. Obsidian becomes the project graph. Now when he asks why something was built a certain way, Claude does not guess from the current prompt. It reads the decision notes. When he starts a new branch, Claude checks the active context file. When the work is done, it updates what changed, what is blocked, and what the next agent needs to know before touching the repo. That is the real loop: read context, write code, capture decisions, update memory. Most people are still using AI coding tools like disposable chat windows. Ask, patch, close, forget. This setup turns Claude Code into infrastructure. The repo gets a memory layer that survives every session, and multiple AI agents can work from the same project map without stepping on each other. The unlock is not better prompting. The unlock is giving the agent somewhere to remember what it already learned.

DegenCalls

20,124 次观看 • 1 个月前

how to use openclaw to spin up 24/7 digital employees and build cash-flowing assets: 1. spin up openclaw (mac mini, vm, orgo, whatever) in a workspace so you can run 5–10 machines at once (main agent + sub-agents) 2. pick one boring workflow inside one industry (distributors, real estate, insurance, law firms) 3. map the workflow tip-to-tail (email/trigger → legacy software clicks → downloads → parsing → upload to crm) 4. use claude code to build the “under the hood” python pipeline (openclaw becomes the operator + trigger, code does the heavy lifting) 5. productize it as a repeatable bundle: “setup + 30 days management + new workflows each week” 6. use upwork as the lead source and the sandbox (it tells you what people pay for right now) 7. turn the best-paying workflow into a vertical workspace: 20 skills, 8 sub-agents, one invite link 8. sell it to bigger companies as “ai employees for this department” (with clear outcomes + SLA) "BuT yoU cAn'T bUiLD a BiG coMpaNY dOInG uPwoRk deAls" think about it like this “how does a $1k automation gig turn into a big company deal?” like this: 1. upwork gives you paid reps + proof someone pays for the workflow 2. those reps become case studies (“saved 12 hrs/week”, “uploaded 5k records/day”, “reduced ops errors by 80%”) 3. you stack 5–10 workflows in the same vertical 4. now you’re selling a package and not a one off deal which is tough 5. bigco buys packages because procurement 6. understands scopes + outcomes openclaw is the wrapper. claude code is the factory. sub agents/skills are the workforce. the vertical bundle is the product. episode is live on The Startup Ideas Podcast (SIP) 🧃 i will never gatekeep i want to see you win in this openclawed world i am rooting for you watch.

how to use openclaw to spin up 24/7 digital employees and build cash-flowing assets: 1. spin up openclaw (mac mini, vm, orgo, whatever) in a workspace so you can run 5–10 machines at once (main agent + sub-agents) 2. pick one boring workflow inside one industry (distributors, real estate, insurance, law firms) 3. map the workflow tip-to-tail (email/trigger → legacy software clicks → downloads → parsing → upload to crm) 4. use claude code to build the “under the hood” python pipeline (openclaw becomes the operator + trigger, code does the heavy lifting) 5. productize it as a repeatable bundle: “setup + 30 days management + new workflows each week” 6. use upwork as the lead source and the sandbox (it tells you what people pay for right now) 7. turn the best-paying workflow into a vertical workspace: 20 skills, 8 sub-agents, one invite link 8. sell it to bigger companies as “ai employees for this department” (with clear outcomes + SLA) "BuT yoU cAn'T bUiLD a BiG coMpaNY dOInG uPwoRk deAls" think about it like this “how does a $1k automation gig turn into a big company deal?” like this: 1. upwork gives you paid reps + proof someone pays for the workflow 2. those reps become case studies (“saved 12 hrs/week”, “uploaded 5k records/day”, “reduced ops errors by 80%”) 3. you stack 5–10 workflows in the same vertical 4. now you’re selling a package and not a one off deal which is tough 5. bigco buys packages because procurement 6. understands scopes + outcomes openclaw is the wrapper. claude code is the factory. sub agents/skills are the workforce. the vertical bundle is the product. episode is live on The Startup Ideas Podcast (SIP) 🧃 i will never gatekeep i want to see you win in this openclawed world i am rooting for you watch.

GREG ISENBERG

243,833 次观看 • 6 个月前

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

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

Gipp 🦅

10,776 次观看 • 1 个月前

Your Claude has a tell, and almost nobody uses it. Make it start every reply with your name. One line in custom instructions, no code. The moment it stops saying your name, its context window is full. That is the exact point the output starts drifting, and you do not notice. Name stops? Start a fresh chat. It has killed about 90% of my “why has Claude gone weird” moments. Miners sent a canary down the pit to catch the gas they could not see. Same trick, for your context. Comment GUIDE and I’ll send you the exact canary setup.

Your Claude has a tell, and almost nobody uses it. Make it start every reply with your name. One line in custom instructions, no code. The moment it stops saying your name, its context window is full. That is the exact point the output starts drifting, and you do not notice. Name stops? Start a fresh chat. It has killed about 90% of my “why has Claude gone weird” moments. Miners sent a canary down the pit to catch the gas they could not see. Same trick, for your context. Comment GUIDE and I’ll send you the exact canary setup.

Charlie Hills

24,121 次观看 • 1 个月前

THIS GUY BUILT A 24/7 AI COMPANY WITH 7 AGENTS THAT CHECKS 48 TIMES A DAY, PICKS ITS OWN TASKS AND KEEPS WORKING WHILE HE SLEEPS 00:05 the map shows agents moving between the marketplace, research lab and command center, with each one handling a different job inside the same shared system the setup runs on 4 core layers: automatic triggers, shared memory, connected tools and an isolated verifier that checks every result before the next step starts each cycle reads the last 10 log entries, updates open tasks, saves new signals and passes the context forward, so the next agent never starts from zero one agent researches, two execute, another monitors outcomes and a read-only checker reviews the work independently, allowing several workflows to run in parallel without breaking the system bookmark this before everyone stops prompting one agent at a time and starts building AI teams that work, learn and improve around the clock

THIS GUY BUILT A 24/7 AI COMPANY WITH 7 AGENTS THAT CHECKS 48 TIMES A DAY, PICKS ITS OWN TASKS AND KEEPS WORKING WHILE HE SLEEPS 00:05 the map shows agents moving between the marketplace, research lab and command center, with each one handling a different job inside the same shared system the setup runs on 4 core layers: automatic triggers, shared memory, connected tools and an isolated verifier that checks every result before the next step starts each cycle reads the last 10 log entries, updates open tasks, saves new signals and passes the context forward, so the next agent never starts from zero one agent researches, two execute, another monitors outcomes and a read-only checker reviews the work independently, allowing several workflows to run in parallel without breaking the system bookmark this before everyone stops prompting one agent at a time and starts building AI teams that work, learn and improve around the clock

Gipp 🦅

19,071 次观看 • 1 个月前

THIS OPERATOR REPLACED A $50,000 AUTOMATION AGENCY WITH A 3-HOUR BUIL 378 browser tabs. 47 Notion pages nobody touched in 6 months. A spreadsheet that crashes every Monday He didn't hire a dev team. He didn't buy n8n enterprise He cloned a GitHub repo, wired 3 API keys, and typed /onboard into Claude Code By day 14 his team messaged the AI OS in Slack instead of messaging him His old workflow: 3 hours of context switching, 2 hours of actual work His new workflow: 5 hours of deep work, 30 minutes of admin This is not a dashboard. This is a command center Full breakdown below ↓

THIS OPERATOR REPLACED A $50,000 AUTOMATION AGENCY WITH A 3-HOUR BUIL 378 browser tabs. 47 Notion pages nobody touched in 6 months. A spreadsheet that crashes every Monday He didn't hire a dev team. He didn't buy n8n enterprise He cloned a GitHub repo, wired 3 API keys, and typed /onboard into Claude Code By day 14 his team messaged the AI OS in Slack instead of messaging him His old workflow: 3 hours of context switching, 2 hours of actual work His new workflow: 5 hours of deep work, 30 minutes of admin This is not a dashboard. This is a command center Full breakdown below ↓

Asteri

10,194 次观看 • 2 个月前

i genuinely can't understand why this isn't the first thing every claude user builds... andrej karpathy, co-founder of openai, quietly solved the exact problem making your ai useless and almost nobody noticed here's the problem he solved... every session claude starts from zero, rereads the same files, forgets every contradiction it already caught, burns tokens relearning what it knew yesterday, forever 1. raw holds the truth once, wiki holds the compiled answer forever, instructions hold the one rule that stops it from ever getting messy again 2. claude opens a raw file exactly one time in its entire life, after that it only speaks in wiki pages with the sources already cited 3. the moment claude catches you contradicting yourself, it writes both versions into the wiki with dates, so it never asks you the same wrong question twice your raw files are disposable... the compiled wiki is the only thing that actually compounds full breakdown is in the article below

i genuinely can't understand why this isn't the first thing every claude user builds... andrej karpathy, co-founder of openai, quietly solved the exact problem making your ai useless and almost nobody noticed here's the problem he solved... every session claude starts from zero, rereads the same files, forgets every contradiction it already caught, burns tokens relearning what it knew yesterday, forever 1. raw holds the truth once, wiki holds the compiled answer forever, instructions hold the one rule that stops it from ever getting messy again 2. claude opens a raw file exactly one time in its entire life, after that it only speaks in wiki pages with the sources already cited 3. the moment claude catches you contradicting yourself, it writes both versions into the wiki with dates, so it never asks you the same wrong question twice your raw files are disposable... the compiled wiki is the only thing that actually compounds full breakdown is in the article below

kai

375,956 次观看 • 24 天前

I'm making over $1,000 an hour with one AI offer. The entire thing runs on Claude Opus 4.8. I call it the AI Concierge. Clients pay me $1,500+ a month for two 45-minute calls where we build their AI systems live, on their screen. I have 4 clients. I'm capping at 6. Here's the entire model: 1) The intake form is the audit. A 10-minute JotForm (built by Claude) surfaces their time sinks and hands me 1-3 AI opportunities before call one. 2) Done-with-you, not done-for-you. They share their screen. We build skills, set up Cowork, and write context files together. They learn to drive. (Done-for-you is the upsell.) 3) Every session runs through AOA: Audit, Optimize, Automate. Fix the process first, then turn it into a skill. Automating chaos just gives you faster chaos. 4) Day one has to move the needle. We ship at least one skill or automation on call one. No first-call win, dead engagement. 5) Unlimited Voxer between calls. They send a voice message, I reply in under 12 business hours. A 24/7 partner, not a guy they see twice a month. 6) The Notion hub is the renewal mechanism. Every call logs a quantified list of what we built. "Call one: 2 skills, 3 context files, Cowork live" makes $1.5K a month a no-brainer. 7) I never fill Notion out by hand. Two Claude skills log the call, pull the action items, and draft the recap email. 30 seconds. 8) Pricing ladder: $1,000/month, then $1,500 at 2 clients, then $1,800. At $1,500 you're already at $1,000/hour. If everyone says yes then you're priced too low. Two things that make this work: 1) Build the fulfillment infrastructure once. An afternoon. Then it runs itself outside the calls. 2) The value must be visible. People renew what they can measure. Full breakdown below. Go watch.

I'm making over $1,000 an hour with one AI offer. The entire thing runs on Claude Opus 4.8. I call it the AI Concierge. Clients pay me $1,500+ a month for two 45-minute calls where we build their AI systems live, on their screen. I have 4 clients. I'm capping at 6. Here's the entire model: 1) The intake form is the audit. A 10-minute JotForm (built by Claude) surfaces their time sinks and hands me 1-3 AI opportunities before call one. 2) Done-with-you, not done-for-you. They share their screen. We build skills, set up Cowork, and write context files together. They learn to drive. (Done-for-you is the upsell.) 3) Every session runs through AOA: Audit, Optimize, Automate. Fix the process first, then turn it into a skill. Automating chaos just gives you faster chaos. 4) Day one has to move the needle. We ship at least one skill or automation on call one. No first-call win, dead engagement. 5) Unlimited Voxer between calls. They send a voice message, I reply in under 12 business hours. A 24/7 partner, not a guy they see twice a month. 6) The Notion hub is the renewal mechanism. Every call logs a quantified list of what we built. "Call one: 2 skills, 3 context files, Cowork live" makes $1.5K a month a no-brainer. 7) I never fill Notion out by hand. Two Claude skills log the call, pull the action items, and draft the recap email. 30 seconds. 8) Pricing ladder: $1,000/month, then $1,500 at 2 clients, then $1,800. At $1,500 you're already at $1,000/hour. If everyone says yes then you're priced too low. Two things that make this work: 1) Build the fulfillment infrastructure once. An afternoon. Then it runs itself outside the calls. 2) The value must be visible. People renew what they can measure. Full breakdown below. Go watch.

Corey Ganim

104,244 次观看 • 2 个月前

A 18 YEAR OLD HIT 7.4 MILLION VIEWS WITH ONE AI GIRL WHO NEVER STOPS MOVING He built her in 11 days. Same face. Same body. Same little smile. The trick was never the face. It was the switch. She starts in the green sequin top, covers her mouth, flips her hair, then the moment her hand crosses the lens the outfit is already the American flag one. No still frame. No cut people can catch. Two frames later she is in the blue one in a different room. Most creators still hard-cut on a frozen pose and the algorithm kills it. He made the change happen while she was already in motion so the loop feels continuous. He almost quit after 8 days of 90-view posts. Then he locked the seed, locked the body proportions, locked the exact nail length and the two tattoos, and started dropping the same girl in new rooms every day. One clip did 7.4 million views in 36 hours. 21,300 new followers. The top comment is still arguing about where she got the second bikini. He answers every single comment in under 70 seconds with an agent that remembers what each guy said three days ago. That alone converts better than the video. She has a $12 private page. 340 guys pay monthly just to keep talking to the same face that never sleeps. The girl is the bait. The seamless switch and the 70-second replies are the machine. Watch the hand cross the frame one more time. You already missed the change.

A 18 YEAR OLD HIT 7.4 MILLION VIEWS WITH ONE AI GIRL WHO NEVER STOPS MOVING He built her in 11 days. Same face. Same body. Same little smile. The trick was never the face. It was the switch. She starts in the green sequin top, covers her mouth, flips her hair, then the moment her hand crosses the lens the outfit is already the American flag one. No still frame. No cut people can catch. Two frames later she is in the blue one in a different room. Most creators still hard-cut on a frozen pose and the algorithm kills it. He made the change happen while she was already in motion so the loop feels continuous. He almost quit after 8 days of 90-view posts. Then he locked the seed, locked the body proportions, locked the exact nail length and the two tattoos, and started dropping the same girl in new rooms every day. One clip did 7.4 million views in 36 hours. 21,300 new followers. The top comment is still arguing about where she got the second bikini. He answers every single comment in under 70 seconds with an agent that remembers what each guy said three days ago. That alone converts better than the video. She has a $12 private page. 340 guys pay monthly just to keep talking to the same face that never sleeps. The girl is the bait. The seamless switch and the 70-second replies are the machine. Watch the hand cross the frame one more time. You already missed the change.

Mango

578,328 次观看 • 14 天前

ANTHROPIC LEAKED A FILE THAT BUILDS A BUSINESS IN 60 MINUTES - IT HUNTS CUSTOMERS ON ITS OWN AND BRINGS $50K IN THE FIRST MONTH in month one the system pulls 100+ customers, in month two the profit number goes past $100K root → offer → surface → hunt → clock → back into the root the first 12 minutes you write 3 lines no model can write for you: who buys, what we sell, at what price. get those wrong and the next 48 minutes automate the wrong business perfectly. the offer is one page, not a deck: the pain, the objection, the price. the page, the payment link and the replies get built by 3 files in parallel in 6 minutes. the first chain listens where your buyer complains - hundreds of signals scored cheaply, a handful get a real letter. a personal letter to someone who was never buying is a paid guess. the second chain publishes 3 variants a day - one post is a guess, three a day for a month is a distribution. the third chain is the cheapest: every closed deal describes the next one, and tomorrow the hunt runs a narrower list. in the morning you read 3 numbers: conversations, replies, paid - if the first grows and the third doesn't, the offer is the problem. and the honest part: 60 minutes buys distribution attempts, not demand - the machine runs whether or not anyone wants it. save this and paste it into Claude Code - an hour builds the machine, the market decides the number ↓

ANTHROPIC LEAKED A FILE THAT BUILDS A BUSINESS IN 60 MINUTES - IT HUNTS CUSTOMERS ON ITS OWN AND BRINGS $50K IN THE FIRST MONTH in month one the system pulls 100+ customers, in month two the profit number goes past $100K root → offer → surface → hunt → clock → back into the root the first 12 minutes you write 3 lines no model can write for you: who buys, what we sell, at what price. get those wrong and the next 48 minutes automate the wrong business perfectly. the offer is one page, not a deck: the pain, the objection, the price. the page, the payment link and the replies get built by 3 files in parallel in 6 minutes. the first chain listens where your buyer complains - hundreds of signals scored cheaply, a handful get a real letter. a personal letter to someone who was never buying is a paid guess. the second chain publishes 3 variants a day - one post is a guess, three a day for a month is a distribution. the third chain is the cheapest: every closed deal describes the next one, and tomorrow the hunt runs a narrower list. in the morning you read 3 numbers: conversations, replies, paid - if the first grows and the third doesn't, the offer is the problem. and the honest part: 60 minutes buys distribution attempts, not demand - the machine runs whether or not anyone wants it. save this and paste it into Claude Code - an hour builds the machine, the market decides the number ↓

Sprytix

204,611 次观看 • 5 天前

Most people use AI agents for themselves. He turned them into a business doing $50,000 a month. He's 20. Made $5,000 today. Doesn't code. He sells them to local businesses. The receptionist that never sleeps. The Google review machine that makes them the top result in their city. The reactivation agent that goes through years of old leads and wakes them up. Businesses pay for outcomes, not technology. A missed call after hours is a lost customer. An AI receptionist costs less than one lost deal. A marketing agency had 6 people doing manual ops work. $28,000/month. 5 Claude agents replaced 80% of it. $200/month in tools. The builder charges $2,500/month to maintain them. 8 clients. $20,000/month. Build once. Collect forever. He doesn't code. He sells the problem solved.

Most people use AI agents for themselves. He turned them into a business doing $50,000 a month. He's 20. Made $5,000 today. Doesn't code. He sells them to local businesses. The receptionist that never sleeps. The Google review machine that makes them the top result in their city. The reactivation agent that goes through years of old leads and wakes them up. Businesses pay for outcomes, not technology. A missed call after hours is a lost customer. An AI receptionist costs less than one lost deal. A marketing agency had 6 people doing manual ops work. $28,000/month. 5 Claude agents replaced 80% of it. $200/month in tools. The builder charges $2,500/month to maintain them. 8 clients. $20,000/month. Build once. Collect forever. He doesn't code. He sells the problem solved.

Superior

10,422 次观看 • 2 个月前

You don't fully understand what this integration could turn into. Five skills. Created by the CEO of Obsidian. Released publicly. Free to add. He read it and thought about who would pay him to implement it for them. Law firms. Agencies. Medical practices. All have the same problem, knowledge that lives in someone's head until that person leaves. He builds the vault. Writes the files. Connects Claude. Delivers in three days. $2,200 once. $1,500 every month after. The pitch is one sentence: your new employee will read every process, every client file, and every decision made in the last three years before their first day. 6 clients. $9,000 a month. 10 hours of work a week. Five skills from the CEO. One business on top of them.

You don't fully understand what this integration could turn into. Five skills. Created by the CEO of Obsidian. Released publicly. Free to add. He read it and thought about who would pay him to implement it for them. Law firms. Agencies. Medical practices. All have the same problem, knowledge that lives in someone's head until that person leaves. He builds the vault. Writes the files. Connects Claude. Delivers in three days. $2,200 once. $1,500 every month after. The pitch is one sentence: your new employee will read every process, every client file, and every decision made in the last three years before their first day. 6 clients. $9,000 a month. 10 hours of work a week. Five skills from the CEO. One business on top of them.

Superior

28,320 次观看 • 1 个月前

A 15 year old American walked into a barbershop and asked the owner to google his own business. The owner laughed and said why would I google myself, I know where I am. The kid said just do it. He did. His barbershop didn't show up. Not in the AI answer at the top of Google. Not in ChatGPT when you ask for the best barbershop nearby. Not in Meta AI. Three AI systems that millions of people use to find local businesses and his shop was invisible in all of them. The kid turned his phone around and showed him what does show up. His competitor two blocks away. Worse reviews, fewer years in business. But that guy appeared in every AI recommendation because his website had the right structure. The barber stopped laughing. The kid said: I can fix this. $800. Give me one week. He learned the whole thing from Claude Code three months earlier. Asked one question: how do people find local businesses now and what's changing? Claude explained that AI systems are replacing traditional search and most local businesses aren't optimized for it because most marketers don't even know it's happening yet. Claude Code built him a tool that checks whether any business appears in AI responses across ChatGPT, Google AI Overview and Meta AI. He types in a business name and sees exactly where they're visible and where they're not. Then Claude taught him how to fix it. He walked into the barbershop with the problem and the solution already in his pocket. 8 clients at $800 each in month one. Every satisfied owner referred him to the next one. The barbershop told the dry cleaner. The dentist told the orthodontist. The car wash told the tire shop. He didn't run a single ad. $14,000 in month one. By month two he stopped walking into businesses. They were calling him. He's 15. Can't drive to his clients. His mom drops him off and waits in the car while he walks into a business with a laptop and walks out 20 minutes later with an $800 contract. She asked him last week what he actually does in there. He said I show people that they're invisible and then I make them visible. She said that sounds like a scam. He showed her his bank account. She stopped calling it a scam. Most marketers are still selling Facebook ads and SEO packages. This kid is selling something they haven't figured out exists yet. AI visibility. The new front door to every business. And he's the only one in his city with the key. He found that key by asking Claude Code one question. The answer built him a $14,000 a month business before he got his learner's permit.

A 15 year old American walked into a barbershop and asked the owner to google his own business. The owner laughed and said why would I google myself, I know where I am. The kid said just do it. He did. His barbershop didn't show up. Not in the AI answer at the top of Google. Not in ChatGPT when you ask for the best barbershop nearby. Not in Meta AI. Three AI systems that millions of people use to find local businesses and his shop was invisible in all of them. The kid turned his phone around and showed him what does show up. His competitor two blocks away. Worse reviews, fewer years in business. But that guy appeared in every AI recommendation because his website had the right structure. The barber stopped laughing. The kid said: I can fix this. $800. Give me one week. He learned the whole thing from Claude Code three months earlier. Asked one question: how do people find local businesses now and what's changing? Claude explained that AI systems are replacing traditional search and most local businesses aren't optimized for it because most marketers don't even know it's happening yet. Claude Code built him a tool that checks whether any business appears in AI responses across ChatGPT, Google AI Overview and Meta AI. He types in a business name and sees exactly where they're visible and where they're not. Then Claude taught him how to fix it. He walked into the barbershop with the problem and the solution already in his pocket. 8 clients at $800 each in month one. Every satisfied owner referred him to the next one. The barbershop told the dry cleaner. The dentist told the orthodontist. The car wash told the tire shop. He didn't run a single ad. $14,000 in month one. By month two he stopped walking into businesses. They were calling him. He's 15. Can't drive to his clients. His mom drops him off and waits in the car while he walks into a business with a laptop and walks out 20 minutes later with an $800 contract. She asked him last week what he actually does in there. He said I show people that they're invisible and then I make them visible. She said that sounds like a scam. He showed her his bank account. She stopped calling it a scam. Most marketers are still selling Facebook ads and SEO packages. This kid is selling something they haven't figured out exists yet. AI visibility. The new front door to every business. And he's the only one in his city with the key. He found that key by asking Claude Code one question. The answer built him a $14,000 a month business before he got his learner's permit.

Marlow

69,075 次观看 • 3 个月前

A DOCTOR BUILT AN AI-QUERYABLE DATABASE OF EVERY DISEASE HE KNOWS IN OBSIDIAN. THE SAME STACK CAN RUN AN ENTIRE COMPANY ON ONE PERSON'S BRAIN Zoomed out, his vault looks like a constellation. Every disease linked to its symptoms, every symptom to the conditions it shows up in, every treatment to what it treats. Adding a new case is one note that wires itself into the rest. It's a personal database, and the structure has nothing to do with medicine. It's just nodes and links. Once you see that, the same setup runs anything: > a startup that needs to remember every customer, decision, and meeting; > a school whose curriculum links to every lecture and student question; > a business where SOPs, clients, and vendors all sit in one queryable graph. Drop Claude on top, and the vault stops being a map. It becomes something you can ask, in plain English, across everything you've ever written down. Full Claude + Obsidian build in the article below. Bookmark this

A DOCTOR BUILT AN AI-QUERYABLE DATABASE OF EVERY DISEASE HE KNOWS IN OBSIDIAN. THE SAME STACK CAN RUN AN ENTIRE COMPANY ON ONE PERSON'S BRAIN Zoomed out, his vault looks like a constellation. Every disease linked to its symptoms, every symptom to the conditions it shows up in, every treatment to what it treats. Adding a new case is one note that wires itself into the rest. It's a personal database, and the structure has nothing to do with medicine. It's just nodes and links. Once you see that, the same setup runs anything: > a startup that needs to remember every customer, decision, and meeting; > a school whose curriculum links to every lecture and student question; > a business where SOPs, clients, and vendors all sit in one queryable graph. Drop Claude on top, and the vault stops being a map. It becomes something you can ask, in plain English, across everything you've ever written down. Full Claude + Obsidian build in the article below. Bookmark this

Yarchi

32,476 次观看 • 2 个月前