Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

The gap between a PM getting AI slop from Claude Code and one getting 10x output is about one hour of file structure. Three folders. > A knowledge folder with static context: who you work with, what each stakeholder cares about, reference material that rarely changes. > A projects... folder where every task accumulates research, drafts, and artifacts that load instantly into your next session. > And a people folder that auto-updates from meeting transcripts through Granola's MCP. The people folder is the part that compounds. Build a skill that pulls what each person said in your last meeting, what they pushed back on, what they committed to. Now when you draft a message to your VP of Engineering, Claude Code already knows their communication preferences from 30 real conversations. That's context no prompt can replicate. Carl walked through this system on the episode and the compounding math stuck with me. Day 1, Claude Code knows nothing about your work. Day 30, it knows your stakeholders, your project history, your patterns. Day 90, it's surfacing connections across your work you haven't consciously noticed. Then layer on skills. A standup command that pulls from GitHub, Linear, your calendar, and your task folder in one shot. Website traffic compared against your LinkedIn posts this week. Analyses that would be impossible clicking between individual UIs, running before your first meeting. One hour of setup. Compounding returns every day after. The PMs typing prompts into a blank terminal and the PMs who built the operating system around it are already producing completely different categories of work. Build the operating system.show more

Aakash Gupta

281,729 subscribers

82,837 просмотров • 3 месяцев назад •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Most people use Claude Code like a chatbot, then wonder why it forgets everything by Tuesday. The ones quietly building $10K AI workflows give it a second brain instead, and it’s free. It’s called Obsidian. You download it, point it at one folder on your computer, and that folder becomes a vault. Every note inside it is now something Claude Code can read end to end. Open Claude in that folder and it’s connected, that simple. The trick isn’t the tool, it’s the map. 3 folders, that’s the whole system. Raw, you dump everything here. Notes, transcripts, screenshots, half thoughts, zero structure. Wiki, Claude reads the raw pile and writes clean Wikipedia style articles about it, structured, searchable, permanent. Output, when you want a deliverable, a PDF, a slide deck, a script, it pulls from the wiki and ships it. Most people skip the wiki layer and feed Claude a junk drawer of 400 files, then blame the model when the answers are garbage. The model isn’t the problem, your folder is. Give it a path it can follow and it finds anything in 1 second, give it chaos and it guesses. You don’t even have to design the structure yourself. Open the vault, tell Claude to build a file system that fits your work, and watch it organize your entire brain in one prompt. Free tool, 3 folders, a second brain that compounds while you sleep. The people falling behind are still copy pasting into a chat window.

Most people use Claude Code like a chatbot, then wonder why it forgets everything by Tuesday. The ones quietly building $10K AI workflows give it a second brain instead, and it’s free. It’s called Obsidian. You download it, point it at one folder on your computer, and that folder becomes a vault. Every note inside it is now something Claude Code can read end to end. Open Claude in that folder and it’s connected, that simple. The trick isn’t the tool, it’s the map. 3 folders, that’s the whole system. Raw, you dump everything here. Notes, transcripts, screenshots, half thoughts, zero structure. Wiki, Claude reads the raw pile and writes clean Wikipedia style articles about it, structured, searchable, permanent. Output, when you want a deliverable, a PDF, a slide deck, a script, it pulls from the wiki and ships it. Most people skip the wiki layer and feed Claude a junk drawer of 400 files, then blame the model when the answers are garbage. The model isn’t the problem, your folder is. Give it a path it can follow and it finds anything in 1 second, give it chaos and it guesses. You don’t even have to design the structure yourself. Open the vault, tell Claude to build a file system that fits your work, and watch it organize your entire brain in one prompt. Free tool, 3 folders, a second brain that compounds while you sleep. The people falling behind are still copy pasting into a chat window.

West Lord

32,401 просмотров • 15 дней назад

Most PMs tried Claude Code for a day, didn't get instant magic, and quietly decided it wasn't for them. The PMs pulling ahead are 1500 hours in and still rebuilding their setup every single day. That's the entire gap. Not talent. Not technical background. Just whether you stayed past the awkward week where nothing works yet. Hannah runs product at Anthropic and has the highest documented Claude Code mileage of any PM I've talked to. Her advice for someone with two hours this weekend isn't "build a workflow." It's "find one task to automate so you free up six hours next week to learn." That reframe is the whole game. Most people treat AI learning as something they'll get to after the real work is done. Hannah treats freeing up time to learn AS the real work. Two hours in, six hours out. Next week you reinvest those six into deeper automations that free up fifteen. The compounding only starts if you survive the first week. And almost nobody does, because day-one Claude Code feels mediocre. Your context isn't loaded. Your skills aren't written. Your CLAUDE.md is empty. The tool is guessing about your role, your product, your standards, everything. The PMs at 1500 hours aren't smarter than the ones who quit on day two. They just didn't quit on day two. Every PM interview at a frontier AI company in 2026 is some version of "show me your setup." The honest answer for most people right now is "I tried it once." Build the hour. Then build the loop.

Most PMs tried Claude Code for a day, didn't get instant magic, and quietly decided it wasn't for them. The PMs pulling ahead are 1500 hours in and still rebuilding their setup every single day. That's the entire gap. Not talent. Not technical background. Just whether you stayed past the awkward week where nothing works yet. Hannah runs product at Anthropic and has the highest documented Claude Code mileage of any PM I've talked to. Her advice for someone with two hours this weekend isn't "build a workflow." It's "find one task to automate so you free up six hours next week to learn." That reframe is the whole game. Most people treat AI learning as something they'll get to after the real work is done. Hannah treats freeing up time to learn AS the real work. Two hours in, six hours out. Next week you reinvest those six into deeper automations that free up fifteen. The compounding only starts if you survive the first week. And almost nobody does, because day-one Claude Code feels mediocre. Your context isn't loaded. Your skills aren't written. Your CLAUDE.md is empty. The tool is guessing about your role, your product, your standards, everything. The PMs at 1500 hours aren't smarter than the ones who quit on day two. They just didn't quit on day two. Every PM interview at a frontier AI company in 2026 is some version of "show me your setup." The honest answer for most people right now is "I tried it once." Build the hour. Then build the loop.

Aakash Gupta

49,411 просмотров • 3 месяцев назад

THIS GUY VIBE CODED A MAC APP THAT AUTOMATICALLY SETS FOLDER ICONS BASED ON THEIR NAMES every folder on your mac looks the same (all blue folders) you have to read every name to find what you're looking for this app reads the folder name and automatically assigns a matching icon your "Photos" folder gets a camera icon. your "Music" folder gets a music icon. your "Projects" folder gets a code icon, all automatic it uses an LLM to understand the folder name and match it to the right icon so it works even with creative or unusual folder names the small details that make your workspace feel organized are the ones nobody builds because they seem too simple to charge for but anyone who has stared at 30 identical blue folders trying to find the right one knows THIS is a real problem mac used to have custom folder icons built in on older versions of macOS. apple removed it. this guy brought it back

THIS GUY VIBE CODED A MAC APP THAT AUTOMATICALLY SETS FOLDER ICONS BASED ON THEIR NAMES every folder on your mac looks the same (all blue folders) you have to read every name to find what you're looking for this app reads the folder name and automatically assigns a matching icon your "Photos" folder gets a camera icon. your "Music" folder gets a music icon. your "Projects" folder gets a code icon, all automatic it uses an LLM to understand the folder name and match it to the right icon so it works even with creative or unusual folder names the small details that make your workspace feel organized are the ones nobody builds because they seem too simple to charge for but anyone who has stared at 30 identical blue folders trying to find the right one knows THIS is a real problem mac used to have custom folder icons built in on older versions of macOS. apple removed it. this guy brought it back

Om Patel

79,744 просмотров • 1 месяц назад

🚨do you understand what two Anthropic engineers just explained in 16 minutes. Barry and Mahesh built Claude Skills from scratch. here's the part nobody is talking about: > Skills are just folders. > folders that teach Claude your job. > your workflow. your expertise. your domain. Claude on day 30 is a completely different tool than day one. watch this before you write another prompt. before you build another agent. before you touch another tool. 16 minutes. bookmark it. watch it today. and if you want to learn everything about Claude from scratch the full 4 hour guide is waiting below.

🚨do you understand what two Anthropic engineers just explained in 16 minutes. Barry and Mahesh built Claude Skills from scratch. here's the part nobody is talking about: > Skills are just folders. > folders that teach Claude your job. > your workflow. your expertise. your domain. Claude on day 30 is a completely different tool than day one. watch this before you write another prompt. before you build another agent. before you touch another tool. 16 minutes. bookmark it. watch it today. and if you want to learn everything about Claude from scratch the full 4 hour guide is waiting below.

Kirill

5,332,145 просмотров • 3 месяцев назад

$THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this$

THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this

Yarchi

55,345 просмотров • 1 месяц назад

Cat Wu, head of product for Claude Code at Anthropic: "you can build almost anything with Claude from a single prompt now" one prompt gets you a working screen, not YOUR product Claude Code has never seen your design system, so it guesses the look fresh every time. how to hand Claude Code that system is in the article. better than the $300 design course in your tabs, and this one's free.

Cat Wu, head of product for Claude Code at Anthropic: "you can build almost anything with Claude from a single prompt now" one prompt gets you a working screen, not YOUR product Claude Code has never seen your design system, so it guesses the look fresh every time. how to hand Claude Code that system is in the article. better than the $300 design course in your tabs, and this one's free.

Mnimiy

113,042 просмотров • 27 дней назад

How to set up Claude Cowork so it actually works like an AI chief of staff (not just another chatbot): 1. Most people open Cowork, type a message, and get generic output. It's not a Claude problem. It's a setup problem. Cowork needs context before it can help you. Who you are. How you work. What you're building. Your team. Your priorities. Give it that, and every session feels like picking up a conversation with an executive assistant. 2. The setup has three layers: a) Global instructions (who you are, how you work, what Claude should never do). b) Connectors (Slack, Gmail, Google Calendar, Notion) c) And a folder structure on your computer that acts as Claude's long-term memory. That combination is what takes it from generic to personalized. 3. Skills are the real leverage. A skill is a markdown file that tells Claude exactly how to do one thing well. Write my newsletter. Coach me on a decision. Review a case study. Each skill lives in its own folder with context, examples, and a definition of what success looks like. 4. We built a CEO coach skill in the video below. Gave it business context, leadership style, company goals. Then tested it with a real decision: should we increase our newsletter from once to twice a week? It came back with trade-offs, second-order consequences, and risk assessment. 5. Then we built a multi-agent advisory board. Five subagents, each with a defined persona: a) the operator b) the skeptic c) the customer advocate d) the finance partner e) the legal/risk advisor. You feed it a decision. Each agent evaluates independently. The main agent synthesizes the feedback. It's like having a board meeting on demand. 6. Third skill: a thought leadership content pipeline. Topic scoring, idea capture, distribution cadence, tone calibration. All built from your actual expertise and audience. Designed so an executive can go from idea to published post without starting from scratch every time. 7. The workspace map is what ties it all together. It's a top-level file that shows Claude how to navigate your entire setup. Which folders exist, what skills live where, how to invoke them. Without it, Claude has to search for everything. With it, Claude goes straight to what it needs. 8. Everything you build is portable. The folder structure works in Cowork, Claude Code, and Codex. Push it to a private GitHub repo and you can access it from your phone through Claude Code, or use Claude Dispatch. 9. The pattern is repeatable. Pick a task you do often. Create a folder. Build a skill. Add examples of what success looks like, and what a bad output looks like. Test it. Workshop it. Move on to the next one. Each skill is like onboarding a new employee who never forgets and never needs to be re-trained. The people who invest in this setup now are the ones who will have a 10x advantage when these tools get even better. And they're getting better fast. I sat down with Alex Lieberman on Human In The Loop and we built all three of these live from scratch. Full breakdown in the video below.. I tried to explain this as clear as possible for my non-developer crowd. Send it to someone who should be using Cowork but isn't yet. Or bookmark it to level up when you're ready. Watch 👇🏼

How to set up Claude Cowork so it actually works like an AI chief of staff (not just another chatbot): 1. Most people open Cowork, type a message, and get generic output. It's not a Claude problem. It's a setup problem. Cowork needs context before it can help you. Who you are. How you work. What you're building. Your team. Your priorities. Give it that, and every session feels like picking up a conversation with an executive assistant. 2. The setup has three layers: a) Global instructions (who you are, how you work, what Claude should never do). b) Connectors (Slack, Gmail, Google Calendar, Notion) c) And a folder structure on your computer that acts as Claude's long-term memory. That combination is what takes it from generic to personalized. 3. Skills are the real leverage. A skill is a markdown file that tells Claude exactly how to do one thing well. Write my newsletter. Coach me on a decision. Review a case study. Each skill lives in its own folder with context, examples, and a definition of what success looks like. 4. We built a CEO coach skill in the video below. Gave it business context, leadership style, company goals. Then tested it with a real decision: should we increase our newsletter from once to twice a week? It came back with trade-offs, second-order consequences, and risk assessment. 5. Then we built a multi-agent advisory board. Five subagents, each with a defined persona: a) the operator b) the skeptic c) the customer advocate d) the finance partner e) the legal/risk advisor. You feed it a decision. Each agent evaluates independently. The main agent synthesizes the feedback. It's like having a board meeting on demand. 6. Third skill: a thought leadership content pipeline. Topic scoring, idea capture, distribution cadence, tone calibration. All built from your actual expertise and audience. Designed so an executive can go from idea to published post without starting from scratch every time. 7. The workspace map is what ties it all together. It's a top-level file that shows Claude how to navigate your entire setup. Which folders exist, what skills live where, how to invoke them. Without it, Claude has to search for everything. With it, Claude goes straight to what it needs. 8. Everything you build is portable. The folder structure works in Cowork, Claude Code, and Codex. Push it to a private GitHub repo and you can access it from your phone through Claude Code, or use Claude Dispatch. 9. The pattern is repeatable. Pick a task you do often. Create a folder. Build a skill. Add examples of what success looks like, and what a bad output looks like. Test it. Workshop it. Move on to the next one. Each skill is like onboarding a new employee who never forgets and never needs to be re-trained. The people who invest in this setup now are the ones who will have a 10x advantage when these tools get even better. And they're getting better fast. I sat down with Alex Lieberman on Human In The Loop and we built all three of these live from scratch. Full breakdown in the video below.. I tried to explain this as clear as possible for my non-developer crowd. Send it to someone who should be using Cowork but isn't yet. Or bookmark it to level up when you're ready. Watch 👇🏼

JJ Englert

566,973 просмотров • 3 месяцев назад

Your AI is average. Mathematically If you're using the same ChatGPT as 100M other people with zero context about your actual work, you're getting average intelligence. Generic answers to specific problems. I watched my team copy-paste the same project context between Claude, ChatGPT, and Gemini all day. Re-uploading the same docs every session. Re-explaining the same projects on repeat. That's not an AI problem. That's a context problem. ClickUp just shipped Brain² and it flips the whole thing: one AI that already knows every task, doc, chat, and decision in your company — and how they all connect. No briefing. No re-explaining. It just knows. Pick any model (GPT, Claude Opus, Gemini), it routes to the best one for the job, runs with full context of your work, and actually does the work alongside your team. Multiplayer AI that gets smarter every time anyone on your team uses it. The wild part: the more your team uses it, the more it becomes your company's collective brain. 150 years of team expertise on tap instead of one person's memory. Average is a choice now.

Your AI is average. Mathematically If you're using the same ChatGPT as 100M other people with zero context about your actual work, you're getting average intelligence. Generic answers to specific problems. I watched my team copy-paste the same project context between Claude, ChatGPT, and Gemini all day. Re-uploading the same docs every session. Re-explaining the same projects on repeat. That's not an AI problem. That's a context problem. ClickUp just shipped Brain² and it flips the whole thing: one AI that already knows every task, doc, chat, and decision in your company — and how they all connect. No briefing. No re-explaining. It just knows. Pick any model (GPT, Claude Opus, Gemini), it routes to the best one for the job, runs with full context of your work, and actually does the work alongside your team. Multiplayer AI that gets smarter every time anyone on your team uses it. The wild part: the more your team uses it, the more it becomes your company's collective brain. 150 years of team expertise on tap instead of one person's memory. Average is a choice now.

Suryansh Tiwari

244,203 просмотров • 16 дней назад

Obsidian + Claude = 24/7 personal operating system Greg Isenberg just showed how to bridge a local Markdown vault and Claude Code via Obsidian CLI the setup that solves the context bottleneck: > /context - loads the complete model of your projects, schedule, and interests so you never have to re-explain details > /today - compiles calendar slots, tasks, and notes from the last week into a prioritized daily plan > /challenge - scans past entries to find contradictions, testing your current beliefs against your own history > /graduate - a custom command that Claude Code wrote for itself to extract structured essays from daily logs the people who build this tonight will never work the same way again bookmark this before your next setup session 👇

Obsidian + Claude = 24/7 personal operating system Greg Isenberg just showed how to bridge a local Markdown vault and Claude Code via Obsidian CLI the setup that solves the context bottleneck: > /context - loads the complete model of your projects, schedule, and interests so you never have to re-explain details > /today - compiles calendar slots, tasks, and notes from the last week into a prioritized daily plan > /challenge - scans past entries to find contradictions, testing your current beliefs against your own history > /graduate - a custom command that Claude Code wrote for itself to extract structured essays from daily logs the people who build this tonight will never work the same way again bookmark this before your next setup session 👇

Mr. Buzzoni

51,346 просмотров • 21 дней назад

Skills are the quickest way to 10x the quality and consistency of what you get from Claude Code. And you don't need to be a developer to use them. Anthropic just published how they use hundreds of skills internally every day. Most skill tutorials are made for developers — if you're in marketing, sales, content ops, or GTM, you probably watched those and moved on. But skills are just as important for non-developers. A skill is just a reusable prompt with clear instructions for a specific task. Instead of prompting Claude the same way over and over, you build it once and invoke it every time. I have a skill for writing on LinkedIn. A different one for YouTube outlines. Another for X. Each platform has different rules, different voice, different structure — so each one gets its own skill. If you're doing something repeatedly, it's time to make a skill. The biggest mistake most people make: building skills as a single .md file. A single file dumps everything into context whether Claude needs it or not. Wastes tokens. Gets worse results. Skills should be folders. Here's the structure that works: skill.md — the orchestrator. Tells Claude which files to read and when. It doesn't contain rules itself — it's the playbook. instructions/ — separate files for voice, structure, scope. Claude only loads the one it needs for the current step. examples/ — good AND bad. Good examples show what success looks like. Bad examples show patterns to avoid — AI writing tells, weak hooks, generic CTAs. Most people skip bad examples. Don't. eval/ — a checklist that scores every output before you see it. "Does it have a clear hook?" "Is it free of AI buzzwords?" Pass or fail on each item. templates/ — output formatting so you get consistent structure every time. The three types of skills that matter most for non-developers: 1. Business automation. Writing a newsletter. Checking reports and drafting follow-ups. Running programmatic ad campaigns. Any workflow you repeat — build a skill for it. 2. Content templates. Landing page copy, meta ads, email sequences, SEO briefs. Each one has specific requirements. Each one gets its own skill. 3. Thinking partners. This is the one people miss. Skills don't have to produce output. They can help you think — an advisory board that reviews your work from your ICP's perspective, a coach that pressure-tests your strategy, an ideation partner that researches competitors before suggesting your next move. If you already have skills as .md files, here's the exact prompt to restructure them in the Anthropic approved format: "I want to restructure my Claude Code skill file. Right now my skill is a single .md file and I want to break it into a folder system following Anthropic's best practices. Read my current skill file, then restructure it into a folder with: a skill.md orchestrator, an instructions/ folder with separate files for each concern (voice, structure, scope), an examples/ folder with good and bad examples, an eval/ folder with a quality checklist, and a templates/ folder for output formatting. Keep all my existing rules and intent — just reorganize them into the modular structure." Paste that into Claude Code pointed at the folder where your skill lives. It handles the rest. A few caveats: 1. Don't add too many skills. Every skill adds context Claude has to process. 50 skills loaded means everything slows down. Start with 3-5 covering your most repeated workflows. 2. Vet skills before downloading. If you grab a skill from the internet, read what's inside first. Skills can include shell commands and scripts. Check what you're running. 3. Share what works. Build a skill that performs well, put it in a shared GitHub repo. Your marketing org gets shared skills for copywriting, SEO, ad copy — new hires invoke the skill instead of learning every playbook from scratch. Onboarding time drops dramatically. 4. Keep your skills updated. When you see output you love, add it as a good example. When you see a pattern you hate, add it as a bad example. The skill gets sharper every time. I made a full video walking through all of this — including a live build of two skills from scratch (no terminal, no code), the exact prompt I use to restructure old skills, and 5 pro tips from Anthropic's internal playbook. Share this with your non-developer friends that want to do more with AI; or bookmark it to come back to at a later time.

Skills are the quickest way to 10x the quality and consistency of what you get from Claude Code. And you don't need to be a developer to use them. Anthropic just published how they use hundreds of skills internally every day. Most skill tutorials are made for developers — if you're in marketing, sales, content ops, or GTM, you probably watched those and moved on. But skills are just as important for non-developers. A skill is just a reusable prompt with clear instructions for a specific task. Instead of prompting Claude the same way over and over, you build it once and invoke it every time. I have a skill for writing on LinkedIn. A different one for YouTube outlines. Another for X. Each platform has different rules, different voice, different structure — so each one gets its own skill. If you're doing something repeatedly, it's time to make a skill. The biggest mistake most people make: building skills as a single .md file. A single file dumps everything into context whether Claude needs it or not. Wastes tokens. Gets worse results. Skills should be folders. Here's the structure that works: skill.md — the orchestrator. Tells Claude which files to read and when. It doesn't contain rules itself — it's the playbook. instructions/ — separate files for voice, structure, scope. Claude only loads the one it needs for the current step. examples/ — good AND bad. Good examples show what success looks like. Bad examples show patterns to avoid — AI writing tells, weak hooks, generic CTAs. Most people skip bad examples. Don't. eval/ — a checklist that scores every output before you see it. "Does it have a clear hook?" "Is it free of AI buzzwords?" Pass or fail on each item. templates/ — output formatting so you get consistent structure every time. The three types of skills that matter most for non-developers: 1. Business automation. Writing a newsletter. Checking reports and drafting follow-ups. Running programmatic ad campaigns. Any workflow you repeat — build a skill for it. 2. Content templates. Landing page copy, meta ads, email sequences, SEO briefs. Each one has specific requirements. Each one gets its own skill. 3. Thinking partners. This is the one people miss. Skills don't have to produce output. They can help you think — an advisory board that reviews your work from your ICP's perspective, a coach that pressure-tests your strategy, an ideation partner that researches competitors before suggesting your next move. If you already have skills as .md files, here's the exact prompt to restructure them in the Anthropic approved format: "I want to restructure my Claude Code skill file. Right now my skill is a single .md file and I want to break it into a folder system following Anthropic's best practices. Read my current skill file, then restructure it into a folder with: a skill.md orchestrator, an instructions/ folder with separate files for each concern (voice, structure, scope), an examples/ folder with good and bad examples, an eval/ folder with a quality checklist, and a templates/ folder for output formatting. Keep all my existing rules and intent — just reorganize them into the modular structure." Paste that into Claude Code pointed at the folder where your skill lives. It handles the rest. A few caveats: 1. Don't add too many skills. Every skill adds context Claude has to process. 50 skills loaded means everything slows down. Start with 3-5 covering your most repeated workflows. 2. Vet skills before downloading. If you grab a skill from the internet, read what's inside first. Skills can include shell commands and scripts. Check what you're running. 3. Share what works. Build a skill that performs well, put it in a shared GitHub repo. Your marketing org gets shared skills for copywriting, SEO, ad copy — new hires invoke the skill instead of learning every playbook from scratch. Onboarding time drops dramatically. 4. Keep your skills updated. When you see output you love, add it as a good example. When you see a pattern you hate, add it as a bad example. The skill gets sharper every time. I made a full video walking through all of this — including a live build of two skills from scratch (no terminal, no code), the exact prompt I use to restructure old skills, and 5 pro tips from Anthropic's internal playbook. Share this with your non-developer friends that want to do more with AI; or bookmark it to come back to at a later time.

JJ Englert

29,322 просмотров • 3 месяцев назад

Claude Code is terrible at UI design and everyone knows it so this guy fixed it by building an MCP that gives Claude its own AI design tool instead of going back and forth between a design platform and your code editor, Claude now creates the designs itself and drops them straight into your codebase the MCP has full context of your existing design system and project so everything it generates actually matches what you already have. one command to set up and it installs the MCP and skill files so Claude instantly knows how to use it if you're tired of the same Inter font, purple gradient, card grid layout on every project, this is definitely worth trying

Claude Code is terrible at UI design and everyone knows it so this guy fixed it by building an MCP that gives Claude its own AI design tool instead of going back and forth between a design platform and your code editor, Claude now creates the designs itself and drops them straight into your codebase the MCP has full context of your existing design system and project so everything it generates actually matches what you already have. one command to set up and it installs the MCP and skill files so Claude instantly knows how to use it if you're tired of the same Inter font, purple gradient, card grid layout on every project, this is definitely worth trying

Om Patel

398,097 просмотров • 3 месяцев назад

Claude Code + Obsidian + 1 free GitHub skill = unlimited memory. Almost nobody is running this yet. Here’s the problem nobody tells you. Claude forgets you. Every new chat starts at 0. You re explain your business, your projects, your style every single time. That tax is why most people never compound anything with AI. The fix is 1 skill. It’s called Obsidian Mind. It turns your Obsidian vault into Claude’s long term brain. 2,000 notes, 14 projects, every idea you’ve ever dumped Claude reads it live and writes back to it live. It stops being a chatbot. It becomes a second brain that builds. What it does: → Bridges Claude Code straight into your vault. → Pulls any note in real time no copy paste, no context limit. → Updates your vault as you work Claude writes its own memory. → Links everything into 1 graph Claude can navigate. Day 1: Claude knows your last 6 months. Week 2: it drafts off your own past notes. Week 4: it’s running plays you forgot you wrote down. The people making real money with AI right now aren’t smarter. They just stopped starting from 0 every morning. Setup takes 11 minutes. The skill is free. You’ll have a brain that never forgets.

Claude Code + Obsidian + 1 free GitHub skill = unlimited memory. Almost nobody is running this yet. Here’s the problem nobody tells you. Claude forgets you. Every new chat starts at 0. You re explain your business, your projects, your style every single time. That tax is why most people never compound anything with AI. The fix is 1 skill. It’s called Obsidian Mind. It turns your Obsidian vault into Claude’s long term brain. 2,000 notes, 14 projects, every idea you’ve ever dumped Claude reads it live and writes back to it live. It stops being a chatbot. It becomes a second brain that builds. What it does: → Bridges Claude Code straight into your vault. → Pulls any note in real time no copy paste, no context limit. → Updates your vault as you work Claude writes its own memory. → Links everything into 1 graph Claude can navigate. Day 1: Claude knows your last 6 months. Week 2: it drafts off your own past notes. Week 4: it’s running plays you forgot you wrote down. The people making real money with AI right now aren’t smarter. They just stopped starting from 0 every morning. Setup takes 11 minutes. The skill is free. You’ll have a brain that never forgets.

West Lord

102,324 просмотров • 13 дней назад

One of my favorite upgrades to Claude Cowork right now: Projects Here's the problem it solves: By default, every new thread starts blank Claude has no memory of what you were working on, what other threads figured out, or what your instructions were So you'd re-explain yourself at the start of every session Or your agents would overlap, contradict each other, or miss context that another thread already had If you've been following my Cowork setup guides, you've already solved part of this — local files and a CLAUDE.md get you most of the way there Projects takes it the rest of the way Shared memory across every thread in the project Permanent instructions that apply everywhere — set once, always on Scheduled tasks that prep your work before you open the app One project HQ to launch every agent from The day-one prompt I paste into every new project: "I just created this project. Read every file in the folder. Then summarize what you know about this workspace — what's here, what I probably use it for, and what instructions you'll follow. If anything is unclear, ask me some questions." Run that once and Claude builds its own understanding of your project workspace from scratch Full video with my live build, including my 4 tips for getting Projects right, and where projects still lack. Send to someone whose ready to Do More with AI, or bookmark to implement this weekend!

One of my favorite upgrades to Claude Cowork right now: Projects Here's the problem it solves: By default, every new thread starts blank Claude has no memory of what you were working on, what other threads figured out, or what your instructions were So you'd re-explain yourself at the start of every session Or your agents would overlap, contradict each other, or miss context that another thread already had If you've been following my Cowork setup guides, you've already solved part of this — local files and a CLAUDE.md get you most of the way there Projects takes it the rest of the way Shared memory across every thread in the project Permanent instructions that apply everywhere — set once, always on Scheduled tasks that prep your work before you open the app One project HQ to launch every agent from The day-one prompt I paste into every new project: "I just created this project. Read every file in the folder. Then summarize what you know about this workspace — what's here, what I probably use it for, and what instructions you'll follow. If anything is unclear, ask me some questions." Run that once and Claude builds its own understanding of your project workspace from scratch Full video with my live build, including my 4 tips for getting Projects right, and where projects still lack. Send to someone whose ready to Do More with AI, or bookmark to implement this weekend!

JJ Englert

29,809 просмотров • 3 месяцев назад

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

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

Yarchi

57,975 просмотров • 1 месяц назад

ANTHROPIC JUST OPEN-SOURCED 11 PLUGINS THAT TURN CLAUDE INTO YOUR WHOLE BACK OFFICE These plugins turn Claude into an actual coworker for your job, whatever your job is. Repo: /anthropics/knowledge-work-plugins Anthropic built and shipped 11 plugins, the same ones inspired by how their own teams work. One for each role: Sales, Marketing, Engineering, Data, Design, Product, HR, Support, Productivity, and more. Each one comes loaded with the real workflows that role needs. The sales one researches prospects, preps your calls, reviews your pipeline, drafts outreach, builds competitive battlecards. The data one writes your SQL, explores datasets, builds dashboards. The productivity one learns your people, your projects, your shorthand, so you say "ask Todd to do the PSR for Oracle" and Claude knows exactly who and what you mean. They work standalone right away, and get supercharged when you connect your tools (Slack, Notion, HubSpot, Linear, Figma, Snowflake, whatever you use). This is straight from the people who build Claude. Not a third-party copy. Bookmark this

ANTHROPIC JUST OPEN-SOURCED 11 PLUGINS THAT TURN CLAUDE INTO YOUR WHOLE BACK OFFICE These plugins turn Claude into an actual coworker for your job, whatever your job is. Repo: /anthropics/knowledge-work-plugins Anthropic built and shipped 11 plugins, the same ones inspired by how their own teams work. One for each role: Sales, Marketing, Engineering, Data, Design, Product, HR, Support, Productivity, and more. Each one comes loaded with the real workflows that role needs. The sales one researches prospects, preps your calls, reviews your pipeline, drafts outreach, builds competitive battlecards. The data one writes your SQL, explores datasets, builds dashboards. The productivity one learns your people, your projects, your shorthand, so you say "ask Todd to do the PSR for Oracle" and Claude knows exactly who and what you mean. They work standalone right away, and get supercharged when you connect your tools (Slack, Notion, HubSpot, Linear, Figma, Snowflake, whatever you use). This is straight from the people who build Claude. Not a third-party copy. Bookmark this

Yarchi

120,351 просмотров • 13 дней назад

I just built an AI-powered creative search engine with Gemini Embedding 2 + Claude Code 🤯 Drop in your UGC clips, product shots, and ad variations — then search through everything in plain English. "Show me all the unboxing clips." "Find product shots with natural lighting." "Which creator talked about sensitive skin?" All inside Claude Code. Perfect for DTC brands and agencies sitting on hundreds of creative files they can never find when they actually need them. If you're digging through a folder of random file names, scrubbing through raw footage to find that one clip, and relying on memory to track down what's already been shot... This system eliminates the entire loop: → Drop your videos, images, and docs into a project folder → One prompt to Claude Code — it builds the entire search app for you → Google's new Gemini Embedding 2 model actually watches your videos and looks at your images → It understands what's inside each file — not just the file name → Search in plain English and get back the actual assets with confidence scores No scrolling through folders. No relying on file names to find anything. No re-shooting footage you already have. What you get: → A searchable library of every creative asset your brand has ever produced → Natural language search across video, images, and documents at the same time → Results that show the actual files inline — play videos, view images, read docs → A system that gets smarter every time you add richer descriptions to your assets One free API key. No monthly subscriptions. Runs on your machine. I put together a full playbook with the exact build prompt, the setup process, and DTC/agency use cases to get this running in under 30 minutes. Want the full playbook? > Like this post > Comment "SEARCH" And I'll send it over (must be following so I can DM)

Mike Futia

12,239 просмотров • 4 месяцев назад

I just built a Brand Operating System inside Claude Cowork 🤯 A connected system of files that every skill automatically reads from, so your hook writer, brief generator, and script writer all speak in your exact brand voice. All inside Claude Cowork. Perfect for DTC brands and agencies tired of generic AI output that sounds like every other brand in their category. If you're opening a new Claude chat and re-explaining your brand, re-pasting your voice guidelines, and re-describing your customers every single time, a Brand OS fixes the entire loop: → Build 3 foundation files once per brand → Every skill you create reads from the Brand OS automatically → Hook writer pulls your voice + customer pain points → Brief generator pulls your positioning + angles → Script writer pulls the brief + brand DNA → Every output is calibrated to your brand on the first pass No re-briefing Claude on every chat. No editing for an hour to fix generic AI phrasing. No creative that sounds like it could belong to any brand. What you get in the playbook: → The exact Brand OS file structure I use → Templates for all 3 files you can fill in for any brand → The architecture that makes every Claude skill 10x sharper → The exact setup for agencies running a Brand OS per client For agencies: this is how you build a perfect, reusable knowledge base for every client on your roster. Set up the Brand OS once per client, and every campaign after that is already calibrated. I put together a full playbook with the file templates, the architecture, and the exact setup process so you can build your own Brand OS for your brand or your clients. Want it for free? > Like this post > Comment "OS" And I'll send it over (must be following so I can DM)

Mike Futia

30,159 просмотров • 3 месяцев назад

If you're hitting Claude Code's context limit, check your terminal output before blaming your project size. Every command Claude runs dumps raw output into your context window. git status : 76% of it is noise. A failed cargo test : 155 lines becomes 3. A grep across your codebase : same story You're not running out of context because your code is too big. You're running out because the commands are bleeding you dry before you get anywhere. RTK intercepts that output, compresses it, and hands Claude a clean version instead. 60–90% fewer tokens. Same information. Runs in the background after a one-command setup. Real numbers from 2,900+ commands: average 89% compression across the board. MIT license. Free. 39k GitHub stars. rtk init -g That's it. Restart Claude Code and every command is compressed automatically.

If you're hitting Claude Code's context limit, check your terminal output before blaming your project size. Every command Claude runs dumps raw output into your context window. git status : 76% of it is noise. A failed cargo test : 155 lines becomes 3. A grep across your codebase : same story You're not running out of context because your code is too big. You're running out because the commands are bleeding you dry before you get anywhere. RTK intercepts that output, compresses it, and hands Claude a clean version instead. 60–90% fewer tokens. Same information. Runs in the background after a one-command setup. Real numbers from 2,900+ commands: average 89% compression across the board. MIT license. Free. 39k GitHub stars. rtk init -g That's it. Restart Claude Code and every command is compressed automatically.

Charlie Hills

16,666 просмотров • 2 месяцев назад

THIS GUY BUILT A GOD-MODE SECOND BRAIN IN 3 STEPS THAT GETS SMARTER EVERY SINGLE DAY AND 10X HIS RESEARCH! Everyone hoards notes they never reopen, but he turned the dead pile into a brain that actually reads itself back, in three steps: > download Obsidian, make a vault, and point Claude Code at the folder > create two folders inside, raw-sources for everything you dump in and wiki where Claude writes the organized version, then drop in Andrej Karpathy's prompt > throw in every article, book note, meeting transcript and piece of research you ever saved and forgot Then you stop searching and start asking the wiki, "what are the gaps in my knowledge", "write me a briefing on this topic", and Claude pulls from your whole vault and answers with citations. Everyone copies the folders, but the part that actually matters is what happens next, every answer gets written back into the wiki and a weekly health check hunts for contradictions and outdated info, so it is not storage you query, it is a brain that compounds every day you use it. The full step by step guide with the Karpathy prompt and the .md files is in the article below.👇 P.S. you can send this article straight to your Claude to get the full context

THIS GUY BUILT A GOD-MODE SECOND BRAIN IN 3 STEPS THAT GETS SMARTER EVERY SINGLE DAY AND 10X HIS RESEARCH! Everyone hoards notes they never reopen, but he turned the dead pile into a brain that actually reads itself back, in three steps: > download Obsidian, make a vault, and point Claude Code at the folder > create two folders inside, raw-sources for everything you dump in and wiki where Claude writes the organized version, then drop in Andrej Karpathy's prompt > throw in every article, book note, meeting transcript and piece of research you ever saved and forgot Then you stop searching and start asking the wiki, "what are the gaps in my knowledge", "write me a briefing on this topic", and Claude pulls from your whole vault and answers with citations. Everyone copies the folders, but the part that actually matters is what happens next, every answer gets written back into the wiki and a weekly health check hunts for contradictions and outdated info, so it is not storage you query, it is a brain that compounds every day you use it. The full step by step guide with the Karpathy prompt and the .md files is in the article below.👇 P.S. you can send this article straight to your Claude to get the full context

Miraqle

15,128 просмотров • 12 дней назад

More people need to understand that Claude Code is a general intelligence that can do stuff on your computer. To help non-coders understand its power, I'm building Folio, an app where you share a folder with Claude and it can work on your files directly. Here's a quick demo:

More people need to understand that Claude Code is a general intelligence that can do stuff on your computer. To help non-coders understand its power, I'm building Folio, an app where you share a folder with Claude and it can work on your files directly. Here's a quick demo:

🎭

218,956 просмотров • 6 месяцев назад