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BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE FABLE 5 + OBSIDIAN Andrej Karpathy (openai co-founder) shared an architecture that turns Claude into a persistent second brain instead of a basic chat window how it works: > you point Claude Code at an Obsidian vault folder > you drop articles, PDFs,...

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Mr. Buzzoni

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89,170 просмотров • 3 месяцев назад •via X (Twitter)

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I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this
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I genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets. Here's the whole thing: > Install Obsidian, create a vault, open it in Claude Code > Paste Karpathy's wiki idea file and tell Claude to build it > Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it > Drop any source into raw and say "ingest this" > Ask questions across everything, forever Five minutes to set up, and you never start from a blank chat again. Full step-by-step guide with Claude and Obsidian, link below. Bookmark this

Ridark

7,021,825 просмотров • 3 месяцев назад

It blows my mind how few people have implemented this setup. A year ago, this exact system allowed me to automate 90% of my tasks and expand my business Andrey Karpathy, co-founder of OpenAI, dropped a simple idea that generated 22 million views and 108,000 saves "stop relying on AI strictly for generating code, and start leveraging it to build a personal second brain" The logic is straightforward: You link Claude Code to a specific directory and throw in any reference materials (articles, meeting transcripts, or PDFs) The system analyzes the text, maps out connections, and constructs a living repository of everything you know. It compounds continuously: as you feed it more data, the entire ecosystem becomes significantly smarter How it breaks down in practice: Launch Obsidian, set up a new repository, and connect it to Claude Code Feed in the template based on Karpathy's wiki approach and instruct Claude to deploy the architecture The model automatically constructs three core areas: raw for your incoming documents, wiki for organized pages, and a master CLAUDE file that coordinates all processes Move any new resource into the raw folder and issue a quick command to process it Query your entire personal knowledge base whenever you need answers A quick five-minute deployment means you will never have to initiate a prompt from a blank canvas again I published the complete guide in the article. Make sure to bookmark it for later
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It blows my mind how few people have implemented this setup. A year ago, this exact system allowed me to automate 90% of my tasks and expand my business Andrey Karpathy, co-founder of OpenAI, dropped a simple idea that generated 22 million views and 108,000 saves "stop relying on AI strictly for generating code, and start leveraging it to build a personal second brain" The logic is straightforward: You link Claude Code to a specific directory and throw in any reference materials (articles, meeting transcripts, or PDFs) The system analyzes the text, maps out connections, and constructs a living repository of everything you know. It compounds continuously: as you feed it more data, the entire ecosystem becomes significantly smarter How it breaks down in practice: Launch Obsidian, set up a new repository, and connect it to Claude Code Feed in the template based on Karpathy's wiki approach and instruct Claude to deploy the architecture The model automatically constructs three core areas: raw for your incoming documents, wiki for organized pages, and a master CLAUDE file that coordinates all processes Move any new resource into the raw folder and issue a quick command to process it Query your entire personal knowledge base whenever you need answers A quick five-minute deployment means you will never have to initiate a prompt from a blank canvas again I published the complete guide in the article. Make sure to bookmark it for later

Bober_smart

108,807 просмотров • 7 дней назад

THIS GUY TURNS NOTES, DOCUMENTS, AND IDEAS INTO AN AI SECOND BRAIN the system stores all the context of your work and helps claude not forget anything how to build one yourself: install obsidian connect claude code keep your projects, notes, and sessions in one vault link similar ideas together use the graph to discover new connections as a result, claude gets memory of your projects and understands the context without you constantly having to explain everything the more you work, the smarter the system gets don’t collect notes build connections between them instead
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THIS GUY TURNS NOTES, DOCUMENTS, AND IDEAS INTO AN AI SECOND BRAIN the system stores all the context of your work and helps claude not forget anything how to build one yourself: install obsidian connect claude code keep your projects, notes, and sessions in one vault link similar ideas together use the graph to discover new connections as a result, claude gets memory of your projects and understands the context without you constantly having to explain everything the more you work, the smarter the system gets don’t collect notes build connections between them instead

Marvin

24,954 просмотров • 4 месяцев назад

HERMES AGENT HAS A SECOND BRAIN. 1,100+ KNOWLEDGE FILES. AUTO-LINKED. SELF-IMPROVING. GROWING EVERY NIGHT. THIS IS THE OBSIDIAN GRAPH BEHIND IT. every dot = one knowledge file (markdown) every line = one wiki-link between files every color = one category (skills, notes, decisions, sources, entities) HOW IT BUILDS ITSELF: Hermes ships with a bundled LLM Wiki skill. based on Andrej Karpathy's pattern. unlike RAG (rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. when you feed the agent a source: → it reads the content → writes a structured markdown page → auto-links to every related existing page → flags contradictions with previous entries → updates all affected pages one source in. multiple connections created. the graph grows denser with every entry. WHAT FEEDS THE WIKI: → articles and URLs you find interesting → meeting transcripts → PDF documents and research papers → conversation history from Hermes sessions → Claude Code and Codex session history → Slack logs, email threads, saved notes → YouTube transcripts → raw text dropped into a _raw/ folder the obsidian-wiki package supports multi-agent ingest from Hermes, Claude Code, Codex, OpenClaw, Pi, Windsurf, and ChatGPT exports. install: pip install obsidian-wiki obsidian-wiki setup --vault ~/wiki AUTOMATE THE GROWTH: set cron jobs to feed the wiki overnight: "every day at 9am, check for new meetings. ingest transcripts into the wiki." "every week, check arXiv for new papers in [niche]. summarize and file into the wiki." "every day, ingest today's Hermes sessions into the wiki under session-history." month 1: 50 entries. scattered. month 3: 300+ entries. cross-referenced. month 6: 1,000+ entries. the agent surfaces patterns you never searched for. WHY OBSIDIAN: the wiki is plain markdown files. no database. no lock-in. open it in Obsidian for graph view: → nodes show knowledge density → links show how ideas connect → clusters reveal your strongest domains → orphan nodes reveal gaps Hermes writes from a VPS. Obsidian reads on your laptop. obsidian-headless syncs without a GUI. agent writes from the server, you browse on your device. FOUR MEMORY LAYERS: Layer 1: memory.md + user.md (~2,200 + 1,375 chars. short-term.) Layer 2: SQLite with FTS5 (full session transcripts. searchable.) Layer 3: external providers (Mem0, SuperMemory, Honcho. optional.) Layer 4: Obsidian wiki via LLM Wiki skill (unlimited. compounding. the long-term brain.) layers 1-3 handle memory. layer 4 handles knowledge. the graph in this post is layer 4. SETUP: set in Desktop app, Dashboard, or config.yaml: WIKI_PATH=~/wiki OBSIDIAN_VAULT_PATH=~/wiki first run: Hermes asks for your domain. answer with your niche. the skill builds SCHEMA.md with tag taxonomy. after that: "index this into my wiki: [URL or text]" the wiki grows. the graph densifies. the agent gets smarter because the knowledge base got smarter. full 15 levels breakdown in the article 👇
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HERMES AGENT HAS A SECOND BRAIN. 1,100+ KNOWLEDGE FILES. AUTO-LINKED. SELF-IMPROVING. GROWING EVERY NIGHT. THIS IS THE OBSIDIAN GRAPH BEHIND IT. every dot = one knowledge file (markdown) every line = one wiki-link between files every color = one category (skills, notes, decisions, sources, entities) HOW IT BUILDS ITSELF: Hermes ships with a bundled LLM Wiki skill. based on Andrej Karpathy's pattern. unlike RAG (rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. when you feed the agent a source: → it reads the content → writes a structured markdown page → auto-links to every related existing page → flags contradictions with previous entries → updates all affected pages one source in. multiple connections created. the graph grows denser with every entry. WHAT FEEDS THE WIKI: → articles and URLs you find interesting → meeting transcripts → PDF documents and research papers → conversation history from Hermes sessions → Claude Code and Codex session history → Slack logs, email threads, saved notes → YouTube transcripts → raw text dropped into a _raw/ folder the obsidian-wiki package supports multi-agent ingest from Hermes, Claude Code, Codex, OpenClaw, Pi, Windsurf, and ChatGPT exports. install: pip install obsidian-wiki obsidian-wiki setup --vault ~/wiki AUTOMATE THE GROWTH: set cron jobs to feed the wiki overnight: "every day at 9am, check for new meetings. ingest transcripts into the wiki." "every week, check arXiv for new papers in [niche]. summarize and file into the wiki." "every day, ingest today's Hermes sessions into the wiki under session-history." month 1: 50 entries. scattered. month 3: 300+ entries. cross-referenced. month 6: 1,000+ entries. the agent surfaces patterns you never searched for. WHY OBSIDIAN: the wiki is plain markdown files. no database. no lock-in. open it in Obsidian for graph view: → nodes show knowledge density → links show how ideas connect → clusters reveal your strongest domains → orphan nodes reveal gaps Hermes writes from a VPS. Obsidian reads on your laptop. obsidian-headless syncs without a GUI. agent writes from the server, you browse on your device. FOUR MEMORY LAYERS: Layer 1: memory.md + user.md (~2,200 + 1,375 chars. short-term.) Layer 2: SQLite with FTS5 (full session transcripts. searchable.) Layer 3: external providers (Mem0, SuperMemory, Honcho. optional.) Layer 4: Obsidian wiki via LLM Wiki skill (unlimited. compounding. the long-term brain.) layers 1-3 handle memory. layer 4 handles knowledge. the graph in this post is layer 4. SETUP: set in Desktop app, Dashboard, or config.yaml: WIKI_PATH=~/wiki OBSIDIAN_VAULT_PATH=~/wiki first run: Hermes asks for your domain. answer with your niche. the skill builds SCHEMA.md with tag taxonomy. after that: "index this into my wiki: [URL or text]" the wiki grows. the graph densifies. the agent gets smarter because the knowledge base got smarter. full 15 levels breakdown in the article 👇

YanXbt

35,900 просмотров • 3 месяцев назад

CLAUDE CODE AND OBSIDIAN TURN 4000 NOTES INTO AN AUTONOMOUS AI TEAMMATE By pointing Claude Code directly at a local Obsidian Markdown vault, a creator turned six years of static notes into an active AI partner. Guided by a single CLAUDE.md file, the terminal agent runs overnight to link orphaned ideas, detect belief contradictions, and draft essay outlines automatically.
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CLAUDE CODE AND OBSIDIAN TURN 4000 NOTES INTO AN AUTONOMOUS AI TEAMMATE By pointing Claude Code directly at a local Obsidian Markdown vault, a creator turned six years of static notes into an active AI partner. Guided by a single CLAUDE.md file, the terminal agent runs overnight to link orphaned ideas, detect belief contradictions, and draft essay outlines automatically.

0xMarioNawfal

48,209 просмотров • 2 месяцев назад

YOUR OBSIDIAN VAULT READS ALL 2,000 NOTES TO ANSWER ONE QUESTION. THAT'S NOT A SECOND BRAIN. That's a hoarder with markdown files. Hundreds of thousands of tokens burned per answer, and it still grabs the wrong note half the time. A real second brain runs on a graph: a router, an index, nodes, edges. Fable 5 reads 2-3 files instead of the whole vault. Answer back in under a second. The graph view everyone screenshots in Obsidian is a poster. The index is the actual engine. Full 11-step build below, from raw vault to working graph 👇
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YOUR OBSIDIAN VAULT READS ALL 2,000 NOTES TO ANSWER ONE QUESTION. THAT'S NOT A SECOND BRAIN. That's a hoarder with markdown files. Hundreds of thousands of tokens burned per answer, and it still grabs the wrong note half the time. A real second brain runs on a graph: a router, an index, nodes, edges. Fable 5 reads 2-3 files instead of the whole vault. Answer back in under a second. The graph view everyone screenshots in Obsidian is a poster. The index is the actual engine. Full 11-step build below, from raw vault to working graph 👇

unicode

53,046 просмотров • 1 месяц назад

LLM Knowledge Base → Slides When Andrej Karpathy shared his LLM Knowledge Base setup, many were wondering how to generate more visual forms of the wiki. There are many options, but I think Gamma is one of the best at producing high-quality, rich presentations. To showcase this, I just built a pipeline that turns my AI papers wiki (1K+ papers across 20 AI agent topics) into polished slide presentations using Gamma. The flow: Obsidian vault → Gamma MCP → embedded preview in my dashboard. I give one command to my agent, which pulls the top papers from each topic (via the wiki), feeds them to Gamma, and renders the presentation inline. The Gamma connector for Claude is a great choice for generating beautiful and professional slides. Easy to use. Go to your Claude instance and add the official Gamma connector. That's it! Claude Code will now have access to all the necessary MCP tools for generating slides. I use the Claude Agent SDK for my agent orchestrator, so I use the official Gamma MCP tools and embed the generated slides in an iframe via my artifact preview. See the clip below for an example.
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LLM Knowledge Base → Slides When Andrej Karpathy shared his LLM Knowledge Base setup, many were wondering how to generate more visual forms of the wiki. There are many options, but I think Gamma is one of the best at producing high-quality, rich presentations. To showcase this, I just built a pipeline that turns my AI papers wiki (1K+ papers across 20 AI agent topics) into polished slide presentations using Gamma. The flow: Obsidian vault → Gamma MCP → embedded preview in my dashboard. I give one command to my agent, which pulls the top papers from each topic (via the wiki), feeds them to Gamma, and renders the presentation inline. The Gamma connector for Claude is a great choice for generating beautiful and professional slides. Easy to use. Go to your Claude instance and add the official Gamma connector. That's it! Claude Code will now have access to all the necessary MCP tools for generating slides. I use the Claude Agent SDK for my agent orchestrator, so I use the official Gamma MCP tools and embed the generated slides in an iframe via my artifact preview. See the clip below for an example.

elvis

47,989 просмотров • 5 месяцев назад

CANCEL your weekend plans. Today is July 11. Half of 2026 is already gone. You still haven't built this. Karpathy — OpenAI co-founder, now Anthropic researcher — posted one idea that hit 21 million views: stop using AI to write code, use it to build a second brain. Not a chatbot. A knowledge base that compounds. Every source you add makes everything already inside it smarter. Three folders. One schema file. One command: "ingest this." Five minutes to set up, and you never start from a blank chat again. I turned his method into a full A–Z guide for Claude and Obsidian. find it below.
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CANCEL your weekend plans. Today is July 11. Half of 2026 is already gone. You still haven't built this. Karpathy — OpenAI co-founder, now Anthropic researcher — posted one idea that hit 21 million views: stop using AI to write code, use it to build a second brain. Not a chatbot. A knowledge base that compounds. Every source you add makes everything already inside it smarter. Three folders. One schema file. One command: "ingest this." Five minutes to set up, and you never start from a blank chat again. I turned his method into a full A–Z guide for Claude and Obsidian. find it below.

Kirill

123,993 просмотров • 2 месяцев назад

An Asian guy discovered a method to learn any knowledge fast using AI. The key is Claude + Obsidian. Most people learn slowly: read, forget, read again, forget again. His method: use Claude to break any content into small, interconnected notes. Use Obsidian to link them, so every piece of knowledge is never isolated. Slow method: highlight books, keep going, forget after a week. Fast method: Claude breaks it into atomic notes, Obsidian links them into a network. Six months later, a new idea instantly connects to twenty things you already know. I compiled the full A–Z guide to building this second brain with Claude and Obsidian that most people have never discovered. Article below
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An Asian guy discovered a method to learn any knowledge fast using AI. The key is Claude + Obsidian. Most people learn slowly: read, forget, read again, forget again. His method: use Claude to break any content into small, interconnected notes. Use Obsidian to link them, so every piece of knowledge is never isolated. Slow method: highlight books, keep going, forget after a week. Fast method: Claude breaks it into atomic notes, Obsidian links them into a network. Six months later, a new idea instantly connects to twenty things you already know. I compiled the full A–Z guide to building this second brain with Claude and Obsidian that most people have never discovered. Article below

Kirill

23,264 просмотров • 2 месяцев назад

I HAVEN’T OPENED A SINGLE BOOK THIS MONTH. CLAUDE READ 34 OF THEM FOR ME I built a vault in Obsidian, connected Claude and added Notebooklm went to sleep woke up with flashcards, mind maps, and an AI that answers from my own notes only my friends are still highlighting pdfs manually the only thing separating us is one setup: claude + obsidian + notebooklm every idea captured. every book processed. zero knowledge lost if this is the setup you’ve been looking for - like & bookmark so you don’t lose it
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I HAVEN’T OPENED A SINGLE BOOK THIS MONTH. CLAUDE READ 34 OF THEM FOR ME I built a vault in Obsidian, connected Claude and added Notebooklm went to sleep woke up with flashcards, mind maps, and an AI that answers from my own notes only my friends are still highlighting pdfs manually the only thing separating us is one setup: claude + obsidian + notebooklm every idea captured. every book processed. zero knowledge lost if this is the setup you’ve been looking for - like & bookmark so you don’t lose it

leopardracer

253,363 просмотров • 4 месяцев назад

1 Neural Network + Obsidian + Karpathy’s 1-file method = the most unhinged second brain build of 2026. It remembers everything you’ve ever done, and it costs $0 on top of what you already pay. The base is Karpathy’s append and review: 1 giant note, new thoughts stack on top, old ones sink, every few days you reread and pull the survivors back up. No folders, no tags, no plugins the rereading IS the system, because review is what turns storage into thinking. The flaw: past 10,000 lines, no human rereads anything. That’s where the neural network takes over. You keep the note in Obsidian 1 vault, everything dumps to the top: ideas, links, meeting fragments, half-thoughts. You never organize, you only dump. It all lives as plain markdown on your own disk, and that detail is the whole trick. Because now you point Claude Code at the vault folder, and it reads every line you’ve ever written. “What did I think about pricing in March.” “Find the 3 ideas I keep circling.” “What did I drop that deserves a second look.” It answers from YOUR notes, with quotes, in 15 seconds. Then once a week, 1 prompt closes the loop: read the last 7 days, surface the 5 entries worth pulling back up, flag anything that contradicts what I wrote a month ago. The model does the sinking and surfacing Karpathy did by hand, and the note stays alive instead of turning into a graveyard. Week 1 feels like nothing. Week 4 you hit the first “I already solved this in January.” Month 3 you consult your past self more than Google. Most second brains die in 11 days under 40 plugins and 200 folders. This one is 1 file and a loop, and it compounds because dumping takes 0 discipline. Notion stores what you thought. This thing argues back.
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1 Neural Network + Obsidian + Karpathy’s 1-file method = the most unhinged second brain build of 2026. It remembers everything you’ve ever done, and it costs $0 on top of what you already pay. The base is Karpathy’s append and review: 1 giant note, new thoughts stack on top, old ones sink, every few days you reread and pull the survivors back up. No folders, no tags, no plugins the rereading IS the system, because review is what turns storage into thinking. The flaw: past 10,000 lines, no human rereads anything. That’s where the neural network takes over. You keep the note in Obsidian 1 vault, everything dumps to the top: ideas, links, meeting fragments, half-thoughts. You never organize, you only dump. It all lives as plain markdown on your own disk, and that detail is the whole trick. Because now you point Claude Code at the vault folder, and it reads every line you’ve ever written. “What did I think about pricing in March.” “Find the 3 ideas I keep circling.” “What did I drop that deserves a second look.” It answers from YOUR notes, with quotes, in 15 seconds. Then once a week, 1 prompt closes the loop: read the last 7 days, surface the 5 entries worth pulling back up, flag anything that contradicts what I wrote a month ago. The model does the sinking and surfacing Karpathy did by hand, and the note stays alive instead of turning into a graveyard. Week 1 feels like nothing. Week 4 you hit the first “I already solved this in January.” Month 3 you consult your past self more than Google. Most second brains die in 11 days under 40 plugins and 200 folders. This one is 1 file and a loop, and it compounds because dumping takes 0 discipline. Notion stores what you thought. This thing argues back.

West Lord

24,679 просмотров • 2 месяцев назад

Claude, Obsidian and n8n form a second brain that clears $5,200 months from brand UGC deals. Most creators still open a blank CapCut file and hope the brand brief sticks. That loop dies at $1,800. The stack replaces hope with a closed system. Obsidian holds every brand voice, every past script that hit 400k views, every rejection note. Claude reads the vault through a local project and rewrites the next five UGC packages in 3 minutes. n8n watches the inbox, creates the note, triggers Claude, formats the brief, and drops the finished package into the brand portal while the creator sleeps. No more research tabs. No more “what angle worked last time.” Month 1: build the vault and wire the three tools. Month 2: first automated batch ships. Two brands pay $1,100 total. Month 3: the same loop runs on four brands. Average deal $480. Twelve packages leave. Bank shows $5,200. The second brain does not store notes. It compounds every win into the next model. Script that scored 18% engagement gets tagged. Claude pulls only those tags next run. The model improves without extra prompt engineering. UGC brands pay for consistency, not inspiration. This system delivers the same quality every week at the same speed. Set the vault once. Let the three tools run the rest. If this was useful - follow.
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Claude, Obsidian and n8n form a second brain that clears $5,200 months from brand UGC deals. Most creators still open a blank CapCut file and hope the brand brief sticks. That loop dies at $1,800. The stack replaces hope with a closed system. Obsidian holds every brand voice, every past script that hit 400k views, every rejection note. Claude reads the vault through a local project and rewrites the next five UGC packages in 3 minutes. n8n watches the inbox, creates the note, triggers Claude, formats the brief, and drops the finished package into the brand portal while the creator sleeps. No more research tabs. No more “what angle worked last time.” Month 1: build the vault and wire the three tools. Month 2: first automated batch ships. Two brands pay $1,100 total. Month 3: the same loop runs on four brands. Average deal $480. Twelve packages leave. Bank shows $5,200. The second brain does not store notes. It compounds every win into the next model. Script that scored 18% engagement gets tagged. Claude pulls only those tags next run. The model improves without extra prompt engineering. UGC brands pay for consistency, not inspiration. This system delivers the same quality every week at the same speed. Set the vault once. Let the three tools run the rest. If this was useful - follow.

Rugikk

10,318 просмотров • 2 месяцев назад

Claude Design + Shopify is f*cking ridiculous 🤯 You can now publish pages from Claude Design → Claude Code → Shopify. Built 100% with Claude Design, Claude Code, and the Shopify CLI. Perfect for DTC brands and agencies who want to skip the design → dev handoff entirely. Here's how it works: → Design any landing page in Claude Design → Export as a zip and drop it into Claude Code → Install the Shopify + Shopify AI Toolkit plugins → Prompt Claude to convert the HTML into a Shopify page template + push to live theme → Claude uploads the images, deploys the files, and creates a published page No more handing designs off to a dev and waiting 2 weeks for a Shopify page. What you get: - A workflow that turns any Claude Design page into a real Shopify page template - Editable sections so your marketing team can swap copy, images, and CTAs without code - Images uploaded straight to Shopify Files automatically - A files-only deploy that only touches what's new in your live theme - A repeatable pipeline you can use every time you design a new landing page This is essentially the design-to-deploy pipeline brands have been waiting for. I put together a step-by-step playbook for going from Claude Design → published Shopify page. Every install, every plugin, every command, and the exact prompt that runs the whole thing. Want the playbook for free? > Like this post > Comment "SHOP" And I'll send it over (must be following so I can DM)
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Claude Design + Shopify is f*cking ridiculous 🤯 You can now publish pages from Claude Design → Claude Code → Shopify. Built 100% with Claude Design, Claude Code, and the Shopify CLI. Perfect for DTC brands and agencies who want to skip the design → dev handoff entirely. Here's how it works: → Design any landing page in Claude Design → Export as a zip and drop it into Claude Code → Install the Shopify + Shopify AI Toolkit plugins → Prompt Claude to convert the HTML into a Shopify page template + push to live theme → Claude uploads the images, deploys the files, and creates a published page No more handing designs off to a dev and waiting 2 weeks for a Shopify page. What you get: - A workflow that turns any Claude Design page into a real Shopify page template - Editable sections so your marketing team can swap copy, images, and CTAs without code - Images uploaded straight to Shopify Files automatically - A files-only deploy that only touches what's new in your live theme - A repeatable pipeline you can use every time you design a new landing page This is essentially the design-to-deploy pipeline brands have been waiting for. I put together a step-by-step playbook for going from Claude Design → published Shopify page. Every install, every plugin, every command, and the exact prompt that runs the whole thing. Want the playbook for free? > Like this post > Comment "SHOP" And I'll send it over (must be following so I can DM)

Mike Futia

59,314 просмотров • 4 месяцев назад

you've read 200 articles this year. you remember maybe 5. the other 195 didn't vanish because you're forgetful — they vanished because they had nowhere to live. no system caught them, so they slipped straight through. here's the fix — Karpathy's second-brain method: > drop anything into one folder: an article, a PDF, a transcript > Claude breaks it into atomic notes and links each one to what's already there > nothing sits alone — every new source makes the whole vault sharper > then you stop searching and just ask, pulling from all of it at once three folders. one config file. set up before your coffee's done. no more cold starts — every session builds on everything you know. full A–Z guide below.
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you've read 200 articles this year. you remember maybe 5. the other 195 didn't vanish because you're forgetful — they vanished because they had nowhere to live. no system caught them, so they slipped straight through. here's the fix — Karpathy's second-brain method: > drop anything into one folder: an article, a PDF, a transcript > Claude breaks it into atomic notes and links each one to what's already there > nothing sits alone — every new source makes the whole vault sharper > then you stop searching and just ask, pulling from all of it at once three folders. one config file. set up before your coffee's done. no more cold starts — every session builds on everything you know. full A–Z guide below.

Kirill

33,091 просмотров • 2 месяцев назад

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

Gipp 🦅

16,393 просмотров • 2 месяцев назад

This is the best AI agent-first notes app I've found. It's called . It has the potential to be a productized version of Karpathy's "LLM Wiki" knowledge bases. Here's what I did: 1. Imported "Learning, Fast and Slow" a Continual Learning paper 2. Asked OpenKnowledge to create a visual explainer 3. Read the explainer and had Claude explain to me 4. Created a new section of my own understanding 5. Saved the durable version in my Obsidian vault because it's markdown Free and open-source. Absolutely incredible learning tool.
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This is the best AI agent-first notes app I've found. It's called . It has the potential to be a productized version of Karpathy's "LLM Wiki" knowledge bases. Here's what I did: 1. Imported "Learning, Fast and Slow" a Continual Learning paper 2. Asked OpenKnowledge to create a visual explainer 3. Read the explainer and had Claude explain to me 4. Created a new section of my own understanding 5. Saved the durable version in my Obsidian vault because it's markdown Free and open-source. Absolutely incredible learning tool.

Dan McAteer

17,326 просмотров • 3 месяцев назад

🚨 Anthropic just made Claude Code remote-controlled. Meet Channels. You can now: → Connect a persistent local Claude session directly to a Discord or Telegram Bot → Message tasks to your bot on the go → Come back to finished code 🔥 Here’s how to set it up: 1️⃣ Create a bot (via Telegram’s BotFather or the Discord Dev Portal) and copy the token 2️⃣ Inside Claude, run /plugin install telegram@claude-plugins-official (or discord) 3️⃣ Configure the token and relaunch your session with the --channels flag 4️⃣ DM your new bot, grab the 6-character code, and pair it to your session! Message the bot to fetch files, read history, and execute code locally while you are on the go. The flexibility is unmatched. Time to spin up your bot 👀
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🚨 Anthropic just made Claude Code remote-controlled. Meet Channels. You can now: → Connect a persistent local Claude session directly to a Discord or Telegram Bot → Message tasks to your bot on the go → Come back to finished code 🔥 Here’s how to set it up: 1️⃣ Create a bot (via Telegram’s BotFather or the Discord Dev Portal) and copy the token 2️⃣ Inside Claude, run /plugin install telegram@claude-plugins-official (or discord) 3️⃣ Configure the token and relaunch your session with the --channels flag 4️⃣ DM your new bot, grab the 6-character code, and pair it to your session! Message the bot to fetch files, read history, and execute code locally while you are on the go. The flexibility is unmatched. Time to spin up your bot 👀

Charly Wargnier

14,611 просмотров • 6 месяцев назад

Stop manually making flowcharts. Try this GitHub skill with Claude Code. I found an open-source tool that turns a plain description of a software system into a clean, interactive diagram. It's called Archify, and it has more than 66,000 stars on GitHub. You add it as a skill to an AI coding agent like Claude Code, Codex, Cursor, or OpenCode. Then you describe the system in the chat in one line. Archify turns that line into a single HTML file you can open, click through, and send to anyone. If you point your agent at an existing codebase, it reads the code and Archify maps how the pieces connect. I liked five things about it. 1. It makes five kinds of diagrams, including system maps and step-by-step workflows. 2. You can click any piece and trace what connects to it. 3. It checks the layout before it hands the diagram over, so arrows don't pile up and labels don't overlap. 4. It has dark and light themes and exports to PNG, SVG, or a short video. 5. You keep editing in plain chat, with requests like "add Redis" or "highlight the rollback path." You don't need a codebase to use it. A description in the chat is enough.
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Stop manually making flowcharts. Try this GitHub skill with Claude Code. I found an open-source tool that turns a plain description of a software system into a clean, interactive diagram. It's called Archify, and it has more than 66,000 stars on GitHub. You add it as a skill to an AI coding agent like Claude Code, Codex, Cursor, or OpenCode. Then you describe the system in the chat in one line. Archify turns that line into a single HTML file you can open, click through, and send to anyone. If you point your agent at an existing codebase, it reads the code and Archify maps how the pieces connect. I liked five things about it. 1. It makes five kinds of diagrams, including system maps and step-by-step workflows. 2. You can click any piece and trace what connects to it. 3. It checks the layout before it hands the diagram over, so arrows don't pile up and labels don't overlap. 4. It has dark and light themes and exports to PNG, SVG, or a short video. 5. You keep editing in plain chat, with requests like "add Redis" or "highlight the rollback path." You don't need a codebase to use it. A description in the chat is enough.

Alex Veremeyenko

61,928 просмотров • 18 дней назад

HE BUILT A 100% PRIVATE SECOND BRAIN IN OBSIDIAN TO AUTOMATE HIS RESEARCH USING HERMES AGENT AND NOTEBOOKLM He visualizes his entire knowledge graph on-premise without paying for cloud subscriptions By connecting Hermes Agent and NotebookLM, developers can index hundreds of documents and generate content locally Four components of this local knowledge architecture: 1. Memory layer - set up an Obsidian PARA vault to store markdown notes and profiles 2. Agent layer - connect Hermes Agent to write files and run background scripts 3. Synthesis layer - use NotebookLM to create structured overviews from raw transcripts 4. Automation layer - trigger cron tasks to synchronize files and calendar standups The setup saves over $4,000 annually while keeping all private files offline Get the full step-by-step configuration guide and setup commands in the article below ↓
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HE BUILT A 100% PRIVATE SECOND BRAIN IN OBSIDIAN TO AUTOMATE HIS RESEARCH USING HERMES AGENT AND NOTEBOOKLM He visualizes his entire knowledge graph on-premise without paying for cloud subscriptions By connecting Hermes Agent and NotebookLM, developers can index hundreds of documents and generate content locally Four components of this local knowledge architecture: 1. Memory layer - set up an Obsidian PARA vault to store markdown notes and profiles 2. Agent layer - connect Hermes Agent to write files and run background scripts 3. Synthesis layer - use NotebookLM to create structured overviews from raw transcripts 4. Automation layer - trigger cron tasks to synchronize files and calendar standups The setup saves over $4,000 annually while keeping all private files offline Get the full step-by-step configuration guide and setup commands in the article below ↓

marfin

20,684 просмотров • 3 месяцев назад

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.
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ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.

BuBBliK

200,690 просмотров • 4 месяцев назад