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i genuinely can't understand why this isn't the first thing every claude user builds... andrej karpathy, co-founder of openai, quietly solved the exact problem making your ai useless and almost nobody noticed here's the problem he solved... every session claude starts from zero, rereads the same files, forgets every...

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kai

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377,612 görüntüleme • 1 ay önce •via X (Twitter)

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i simply can't get over how few people are actually doing this... Andrej Karpathy, co-founder of openai, basically described the whole setup and almost nobody built it let me break down what it actually does... every scattered note, every source you dumped somewhere and forgot, every pattern buried across hundreds of files... compiled once into something claude can scan in seconds instead of rereading cold every session 1. three folders, that's the whole vault: raw holds the originals untouched, wiki holds what claude compiles from them, instructions holds the rules for how it compiles 2. claude reads raw/ once, turns each source into linked wiki pages with sources cited, never opens the raw files again after that 3. every contradiction gets flagged right inside the wiki with both sides and dates, every future session reads the flag first, so you catch it once instead of forever the raw files are disposable... the wiki is what actually holds the value full breakdown is in the article below
0:26

i simply can't get over how few people are actually doing this... Andrej Karpathy, co-founder of openai, basically described the whole setup and almost nobody built it let me break down what it actually does... every scattered note, every source you dumped somewhere and forgot, every pattern buried across hundreds of files... compiled once into something claude can scan in seconds instead of rereading cold every session 1. three folders, that's the whole vault: raw holds the originals untouched, wiki holds what claude compiles from them, instructions holds the rules for how it compiles 2. claude reads raw/ once, turns each source into linked wiki pages with sources cited, never opens the raw files again after that 3. every contradiction gets flagged right inside the wiki with both sides and dates, every future session reads the flag first, so you catch it once instead of forever the raw files are disposable... the wiki is what actually holds the value full breakdown is in the article below

kai

34,399 görüntüleme • 1 ay önce

i keep telling people to build this and they nod politely and never do it... andrej karpathy posted how to fix this a while ago, and everyone just keeps working the old way the dumb thing is this... you pay to teach claude the same lessons over and over, every chat is a fresh amnesia patient, every contradiction it catches evaporates the second you close the tab, and you accept this like it's just how ai works 1. one folder is a graveyard for originals that nobody edits, another folder is claude's active memory that only claude writes to, a third folder is a two-page rulebook that keeps claude from confusing them 2. a raw file gets read the day it arrives and then it's done, claude never touches it again, everything it needed is already extracted into wiki pages with the source cited right there 3. every time claude notices your new answer clashes with your old one, it doesn't pick a side, it writes both with dates, and from then on it treats you like someone who might be wrong the raw folder is a museum... the wiki is the actual working brain full breakdown is in the article below
0:20

i keep telling people to build this and they nod politely and never do it... andrej karpathy posted how to fix this a while ago, and everyone just keeps working the old way the dumb thing is this... you pay to teach claude the same lessons over and over, every chat is a fresh amnesia patient, every contradiction it catches evaporates the second you close the tab, and you accept this like it's just how ai works 1. one folder is a graveyard for originals that nobody edits, another folder is claude's active memory that only claude writes to, a third folder is a two-page rulebook that keeps claude from confusing them 2. a raw file gets read the day it arrives and then it's done, claude never touches it again, everything it needed is already extracted into wiki pages with the source cited right there 3. every time claude notices your new answer clashes with your old one, it doesn't pick a side, it writes both with dates, and from then on it treats you like someone who might be wrong the raw folder is a museum... the wiki is the actual working brain full breakdown is in the article below

kai

32,120 görüntüleme • 1 ay önce

I genuinely don't understand why everyone isn't using this yet. Andrej Karpathy, OpenAI co-founder, posted a simple idea that went massively viral: 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. Claude reads it, links it, 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: 1) Install Obsidian 2) Create a vault 3) Open it in Claude Code 4) Paste Karpathy's wiki idea and tell Claude to build it 5) Claude makes three folders: - raw (for sources) - wiki (for its pages) - CLAUDE. md (that runs it) 6) Drop any source into raw and say: "ingest this" 7) Ask questions across everything, forever Five minutes to set up and you never start from a blank chat again. Full step by step guide below.
1:48

I genuinely don't understand why everyone isn't using this yet. Andrej Karpathy, OpenAI co-founder, posted a simple idea that went massively viral: 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. Claude reads it, links it, 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: 1) Install Obsidian 2) Create a vault 3) Open it in Claude Code 4) Paste Karpathy's wiki idea and tell Claude to build it 5) Claude makes three folders: - raw (for sources) - wiki (for its pages) - CLAUDE. md (that runs it) 6) Drop any source into raw and say: "ingest this" 7) Ask questions across everything, forever Five minutes to set up and you never start from a blank chat again. Full step by step guide below.

CyrilXBT

323,486 görüntüleme • 2 ay önce

Karpathy gave 100,000 people the LLM Wiki idea. 1 guy actually built it into a Claude + Obsidian brain that never forgets you. Every AI tool forgets you the second you close the tab. ChatGPT, Claude, Codex. All gone. He killed that. A shared memory layer your AI builds and maintains on its own. 3 layers. Raw, Wiki, Schema. You drop a source, Claude reads it, pulls the concepts, links them, cites the original, never touches your raw notes. Scales to 1,000s of notes without breaking. Then it goes deeper. An agentic firewall locks agents out of your other vaults. A local model running free and private, zero cloud. 2 videos walk through it all. 1 on why. 1 on the build, start to finish. Most people will keep pasting the same context into 6 tabs for the next 3 years. Build it once. Never explain yourself to a model again.
34:07

Karpathy gave 100,000 people the LLM Wiki idea. 1 guy actually built it into a Claude + Obsidian brain that never forgets you. Every AI tool forgets you the second you close the tab. ChatGPT, Claude, Codex. All gone. He killed that. A shared memory layer your AI builds and maintains on its own. 3 layers. Raw, Wiki, Schema. You drop a source, Claude reads it, pulls the concepts, links them, cites the original, never touches your raw notes. Scales to 1,000s of notes without breaking. Then it goes deeper. An agentic firewall locks agents out of your other vaults. A local model running free and private, zero cloud. 2 videos walk through it all. 1 on why. 1 on the build, start to finish. Most people will keep pasting the same context into 6 tabs for the next 3 years. Build it once. Never explain yourself to a model again.

West Lord

75,208 görüntüleme • 2 ay önce

This beginner guide to Karpathy's LLM Wiki is one of the most useful AI videos i've shared this year Karpathy's idea: instead of asking AI questions every time, make it build you a permanent knowledge base that grows smarter over time > drop your documents into a folder > Claude reads them and builds a structured wiki in Obsidian > every time you add a new source, Claude Sonnet updates existing pages and links new ideas > ask complex questions - Claude Opus answers from the organized wiki, not raw files it's like having a researcher who never forgets and connects dots across everything you've ever given it full setup guide is in the video above
14:21

This beginner guide to Karpathy's LLM Wiki is one of the most useful AI videos i've shared this year Karpathy's idea: instead of asking AI questions every time, make it build you a permanent knowledge base that grows smarter over time > drop your documents into a folder > Claude reads them and builds a structured wiki in Obsidian > every time you add a new source, Claude Sonnet updates existing pages and links new ideas > ask complex questions - Claude Opus answers from the organized wiki, not raw files it's like having a researcher who never forgets and connects dots across everything you've ever given it full setup guide is in the video above

Mr. Buzzoni

58,787 görüntüleme • 4 ay önce

Andrej Karpathy quietly shipped the best second brain idea in years not an app. a pattern. let an llm maintain a wiki of your notes. you dump sources, it reads them, links them, files them. knowledge compounds like interest. someone built it into a free claude code plugin. setup is two commands: claude plugin marketplace add AgriciDaniel/claude-obsidian claude plugin install claude-obsidian@agricidaniel-claude-obsidian then open obsidian, open claude code in the same folder, type /wiki. that's it. your notes are now queryable by claude and they get richer every time you read something. bookmark this. best thing you'll build this weekend.
0:42

Andrej Karpathy quietly shipped the best second brain idea in years not an app. a pattern. let an llm maintain a wiki of your notes. you dump sources, it reads them, links them, files them. knowledge compounds like interest. someone built it into a free claude code plugin. setup is two commands: claude plugin marketplace add AgriciDaniel/claude-obsidian claude plugin install claude-obsidian@agricidaniel-claude-obsidian then open obsidian, open claude code in the same folder, type /wiki. that's it. your notes are now queryable by claude and they get richer every time you read something. bookmark this. best thing you'll build this weekend.

Avid

339,134 görüntüleme • 3 ay önce

THE ANATOMY OF A SECOND BRAIN THAT WRITES ITSELF one Obsidian vault, three layers, and a loop that files every good answer back into a wiki you never touch the structure: > CLAUDE.md + AGENTS.md - the constitution. same rules whether Claude or Codex runs the loop > raw/ - inbox, articles, assets. frozen and read-only, you feed it and walk away > wiki/ - index.md, entities/, concepts/, synthesis.md. the agent grows this on its own > log.md - append-only, every move timestamped 47 sources in -> 210 pages out the agent typed 96% of it. you typed zero the cost trick: point Opus 5 only at synthesis.md, the one file that needs frontier reasoning. everything else runs fine on cheaper models under the hood it's loop engineering: you ask -> a good answer gets filed back -> the wiki grows start linking entities to each other and you're one step from a full graph your research compounds while you sleep. the full blueprint is below 👇
0:24

THE ANATOMY OF A SECOND BRAIN THAT WRITES ITSELF one Obsidian vault, three layers, and a loop that files every good answer back into a wiki you never touch the structure: > CLAUDE.md + AGENTS.md - the constitution. same rules whether Claude or Codex runs the loop > raw/ - inbox, articles, assets. frozen and read-only, you feed it and walk away > wiki/ - index.md, entities/, concepts/, synthesis.md. the agent grows this on its own > log.md - append-only, every move timestamped 47 sources in -> 210 pages out the agent typed 96% of it. you typed zero the cost trick: point Opus 5 only at synthesis.md, the one file that needs frontier reasoning. everything else runs fine on cheaper models under the hood it's loop engineering: you ask -> a good answer gets filed back -> the wiki grows start linking entities to each other and you're one step from a full graph your research compounds while you sleep. the full blueprint is below 👇

Annatar.md

22,801 görüntüleme • 4 gün önce

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.
1:57

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

32,845 görüntüleme • 2 ay önce

I just built a Claude skill that acts as a second brain for DTC brands 🤯 Drop your ad exports, customer reviews, competitor screenshots, and brand docs into a folder → Claude compiles it all into an organized wiki you can ask questions against. All inside Claude Cowork. Perfect for DTC brands and agencies whose knowledge is scattered across Google Drive, Notion, Meta Ads Manager, Figma, and 47 spreadsheets nobody has opened in 3 months. If every strategic question takes 2 hours to answer because the data lives in 8 different places ... This skill eliminates the entire loop: → Claude scaffolds a DTC folder structure: ads, customers, competitors, brand, performance, notes → You drop every file you have into those folders — messy, unorganized, exactly how you have them now → Claude reads everything and compiles a wiki: hooks-that-work, customer-pains, competitor-angles, brand-voice, performance-patterns, creative-brief-library → Every article is cross-linked and traceable back to the source file → You ask questions against the wiki — "what hooks are actually working?" "what objections come up most?" "where are my competitors weak?" → Claude answers, grounded entirely in your own data → Save the answers back in and the system gets smarter every time you use it No more hunting through 12 tools. No more "where did I save that brief?" No more answering the same question twice. What you get: → A complete DTC brand brain scaffold in 60 seconds → Six core wiki articles Claude populates automatically from your raw files → A schema file that tells Claude exactly how to maintain the wiki for DTC use cases → Monthly health checks that catch contradictions and flag gaps before errors compound → A knowledge base that compounds — every question you ask makes the next answer better Built on a methodology Andrej Karpathy shared for personal knowledge bases, I rebuilt the entire thing for DTC operators: folder structure, schema rules, wiki articles, and question frameworks all tuned for brands and agencies. I put together the full skill file plus a playbook walking through the exact setup and 5 real questions to ask your brand brain. Want it for free? > Like this post > Comment "BRAIN" And I'll send it over (must be following so I can DM)
0:35

I just built a Claude skill that acts as a second brain for DTC brands 🤯 Drop your ad exports, customer reviews, competitor screenshots, and brand docs into a folder → Claude compiles it all into an organized wiki you can ask questions against. All inside Claude Cowork. Perfect for DTC brands and agencies whose knowledge is scattered across Google Drive, Notion, Meta Ads Manager, Figma, and 47 spreadsheets nobody has opened in 3 months. If every strategic question takes 2 hours to answer because the data lives in 8 different places ... This skill eliminates the entire loop: → Claude scaffolds a DTC folder structure: ads, customers, competitors, brand, performance, notes → You drop every file you have into those folders — messy, unorganized, exactly how you have them now → Claude reads everything and compiles a wiki: hooks-that-work, customer-pains, competitor-angles, brand-voice, performance-patterns, creative-brief-library → Every article is cross-linked and traceable back to the source file → You ask questions against the wiki — "what hooks are actually working?" "what objections come up most?" "where are my competitors weak?" → Claude answers, grounded entirely in your own data → Save the answers back in and the system gets smarter every time you use it No more hunting through 12 tools. No more "where did I save that brief?" No more answering the same question twice. What you get: → A complete DTC brand brain scaffold in 60 seconds → Six core wiki articles Claude populates automatically from your raw files → A schema file that tells Claude exactly how to maintain the wiki for DTC use cases → Monthly health checks that catch contradictions and flag gaps before errors compound → A knowledge base that compounds — every question you ask makes the next answer better Built on a methodology Andrej Karpathy shared for personal knowledge bases, I rebuilt the entire thing for DTC operators: folder structure, schema rules, wiki articles, and question frameworks all tuned for brands and agencies. I put together the full skill file plus a playbook walking through the exact setup and 5 real questions to ask your brand brain. Want it for free? > Like this post > Comment "BRAIN" And I'll send it over (must be following so I can DM)

Mike Futia

15,243 görüntüleme • 5 ay önce

Andrej Karpathy (co-founder of OpenAI, LLM Wiki pattern creator): "Obsidian is the IDE. The LLM is the programmer. The wiki is the codebase. knowledge compounds like interest when the AI owns the maintenance." Someone built the open-source implementation of that principle. 6,800 stars. MIT licensed. Two minutes to install. Here is what it actually does: → ingest: drop a source, Claude reads it, pulls out people and ideas, creates 8-15 linked pages automatically → batch ingest: parallel agents read an entire pile at once, then cross-reference everything → query: ask your brain anything, it reads the cache, scans the index, cites the exact pages → /autoresearch: three rounds of search, fetch, synthesize, file — autonomous web research → lint: finds orphans, dead links, stale claims, missing cross-references → the real unlock: point every claude code project at the same vault — one brain, every project hot cache refreshed at the end of every session. next session opens with full recent context. no recap, no re-explaining. plain markdown, no subscription, no lock-in. Bookmark so you do not lose it! Follow NeilXbt for more Obsidian and Claude builds that show you what a self-maintaining second brain actually requires.
4:19

Andrej Karpathy (co-founder of OpenAI, LLM Wiki pattern creator): "Obsidian is the IDE. The LLM is the programmer. The wiki is the codebase. knowledge compounds like interest when the AI owns the maintenance." Someone built the open-source implementation of that principle. 6,800 stars. MIT licensed. Two minutes to install. Here is what it actually does: → ingest: drop a source, Claude reads it, pulls out people and ideas, creates 8-15 linked pages automatically → batch ingest: parallel agents read an entire pile at once, then cross-reference everything → query: ask your brain anything, it reads the cache, scans the index, cites the exact pages → /autoresearch: three rounds of search, fetch, synthesize, file — autonomous web research → lint: finds orphans, dead links, stale claims, missing cross-references → the real unlock: point every claude code project at the same vault — one brain, every project hot cache refreshed at the end of every session. next session opens with full recent context. no recap, no re-explaining. plain markdown, no subscription, no lock-in. Bookmark so you do not lose it! Follow NeilXbt for more Obsidian and Claude builds that show you what a self-maintaining second brain actually requires.

NeilXbt

33,993 görüntüleme • 2 ay önce

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
13:23

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

56,177 görüntüleme • 3 ay önce

Still baffled as to why people are sleeping on this. Implementing this strategy is what allowed me to bump my monthly earnings to $13,000 a year ago A simple concept shared by OpenAI co-founder Andrej Karpathy recently exploded to 21 million views. Stop treating AI as just a coding tool and start using it to construct your personal second brain The workflow is seamless. Direct Claude Code to a designated directory, drop in any raw material like a PDF, transcript, or article, and let Claude parse, connect, and integrate it into a dynamic personal wiki. It compounds over time, meaning the system grows sharper the more information you feed it The quick setup guide: Download Obsidian, spin up a new vault, and open it up in Claude Code Feed Claude the document outlining Karpathy's wiki framework and tell it to initialize the system The AI will automatically structure three core folders: raw for source uploads, wiki for your interconnected pages, and CLAUDE to manage the engine Drop new materials into raw and give the command: "ingest this" Search and query your entire accumulated database whenever you want Total setup time is about five minutes, and you will never stare at an empty prompt window again The full walkthrough is linked below. Hit bookmark so you don't lose it
0:24

Still baffled as to why people are sleeping on this. Implementing this strategy is what allowed me to bump my monthly earnings to $13,000 a year ago A simple concept shared by OpenAI co-founder Andrej Karpathy recently exploded to 21 million views. Stop treating AI as just a coding tool and start using it to construct your personal second brain The workflow is seamless. Direct Claude Code to a designated directory, drop in any raw material like a PDF, transcript, or article, and let Claude parse, connect, and integrate it into a dynamic personal wiki. It compounds over time, meaning the system grows sharper the more information you feed it The quick setup guide: Download Obsidian, spin up a new vault, and open it up in Claude Code Feed Claude the document outlining Karpathy's wiki framework and tell it to initialize the system The AI will automatically structure three core folders: raw for source uploads, wiki for your interconnected pages, and CLAUDE to manage the engine Drop new materials into raw and give the command: "ingest this" Search and query your entire accumulated database whenever you want Total setup time is about five minutes, and you will never stare at an empty prompt window again The full walkthrough is linked below. Hit bookmark so you don't lose it

Bober_smart

23,803 görüntüleme • 21 gün önce

HERMES AGENT SHIPS WITH A BUNDLED SKILL FOR ANDREJ KARPATHY'S LLM WIKI PATTERN. A SELF-IMPROVING KNOWLEDGE BASE THAT GROWS EVERY TIME YOU FEED IT. mentioned this briefly in the overnight workflow article. here is the full breakdown. what it is: a self-improving knowledge base built as interlinked markdown files. unlike RAG (which rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. cross-references stay linked. contradictions get flagged automatically. synthesis reflects everything ingested so far. why this matters for Hermes memory: Hermes built-in memory knows YOU. it remembers your conversations, your preferences, your business context across sessions. but it doesn't know your inbox. or your meeting transcripts. or that article you saved last week. or the expert framework you want it to learn. the LLM Wiki solves that. THE DIVISION OF LABOR human curates sources and directs analysis. agent summarizes, cross-references, files, and maintains consistency. you drop in articles, transcripts, notes. Hermes indexes them, links related concepts, flags contradictions, updates affected pages. your knowledge base grows itself. SETUP IS ONE COMMAND the skill ships with Hermes. enable it. set WIKI_PATH in ~/.hermes/.env: WIKI_PATH=/Users/you/wiki defaults to ~/wiki if unset. then drop anything into it: "index this article into my wiki: [paste URL or text]" Hermes reads it, builds a source page, updates related entries, flags contradictions. THE OBSIDIAN ANGLE set OBSIDIAN_VAULT_PATH to the same directory. now your wiki is visible in Obsidian's graph view. nodes, links, backlinks. all built by Hermes. for headless servers: install obsidian-headless. syncs vaults without a GUI. agent writes from the server, you read on your laptop. THE COMPOUND EFFECT Hermes knows you. the wiki knows your world. combine them and the agent answers questions using BOTH contexts at once. month 1: you explain things twice. month 3: the agent references the wiki on its own. answers get sharper because the knowledge base got sharper. AUTOMATIONS THAT FEED THE WIKI set cron jobs to ingest automatically: "every day at 9am, check Granola for new meetings. add any new transcripts to my wiki under meeting notes." "every morning, scan my Gmail starred items. add anything worth keeping to the wiki." "every week, check arXiv for new papers in [your niche]. summarize and file." your wiki grows while you sleep. Hermes never forgets what gets indexed. THE LIMITATION TO KNOW unlike Hermes memory (which is conversational and lives across sessions), the wiki is a separate knowledge layer. Hermes won't pull from the wiki automatically unless you reference it or save it as a skill. best setup: build an LLM Wiki personality that tells Hermes to consult the wiki when answering strategy questions or domain-specific queries. full HERMES AGENT OVERNIGHT WORKFLOW👇
14:28

HERMES AGENT SHIPS WITH A BUNDLED SKILL FOR ANDREJ KARPATHY'S LLM WIKI PATTERN. A SELF-IMPROVING KNOWLEDGE BASE THAT GROWS EVERY TIME YOU FEED IT. mentioned this briefly in the overnight workflow article. here is the full breakdown. what it is: a self-improving knowledge base built as interlinked markdown files. unlike RAG (which rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. cross-references stay linked. contradictions get flagged automatically. synthesis reflects everything ingested so far. why this matters for Hermes memory: Hermes built-in memory knows YOU. it remembers your conversations, your preferences, your business context across sessions. but it doesn't know your inbox. or your meeting transcripts. or that article you saved last week. or the expert framework you want it to learn. the LLM Wiki solves that. THE DIVISION OF LABOR human curates sources and directs analysis. agent summarizes, cross-references, files, and maintains consistency. you drop in articles, transcripts, notes. Hermes indexes them, links related concepts, flags contradictions, updates affected pages. your knowledge base grows itself. SETUP IS ONE COMMAND the skill ships with Hermes. enable it. set WIKI_PATH in ~/.hermes/.env: WIKI_PATH=/Users/you/wiki defaults to ~/wiki if unset. then drop anything into it: "index this article into my wiki: [paste URL or text]" Hermes reads it, builds a source page, updates related entries, flags contradictions. THE OBSIDIAN ANGLE set OBSIDIAN_VAULT_PATH to the same directory. now your wiki is visible in Obsidian's graph view. nodes, links, backlinks. all built by Hermes. for headless servers: install obsidian-headless. syncs vaults without a GUI. agent writes from the server, you read on your laptop. THE COMPOUND EFFECT Hermes knows you. the wiki knows your world. combine them and the agent answers questions using BOTH contexts at once. month 1: you explain things twice. month 3: the agent references the wiki on its own. answers get sharper because the knowledge base got sharper. AUTOMATIONS THAT FEED THE WIKI set cron jobs to ingest automatically: "every day at 9am, check Granola for new meetings. add any new transcripts to my wiki under meeting notes." "every morning, scan my Gmail starred items. add anything worth keeping to the wiki." "every week, check arXiv for new papers in [your niche]. summarize and file." your wiki grows while you sleep. Hermes never forgets what gets indexed. THE LIMITATION TO KNOW unlike Hermes memory (which is conversational and lives across sessions), the wiki is a separate knowledge layer. Hermes won't pull from the wiki automatically unless you reference it or save it as a skill. best setup: build an LLM Wiki personality that tells Hermes to consult the wiki when answering strategy questions or domain-specific queries. full HERMES AGENT OVERNIGHT WORKFLOW👇

YanXbt

30,804 görüntüleme • 3 ay önce

Prompt engineering is where people go when they refuse to write files Karpathy's LLM Wiki gist is painfully simple: > raw sources stay untouched > the agent writes the wiki > `CLAUDE.md` or `AGENTS.md` tells it the rules > `index.md` maps the pages > `log.md` records what changed That is why a good answer should not die in chat history If the model gives you a useful comparison, summary, decision, bug explanation, or research thread, file it back into the project Use: > `wiki/topics/[topic].md` > `wiki/entities/[person-or-company].md` > `wiki/sources/[source-name].md` > `wiki/analysis/[question].md` Make the agent keep the wiki from rotting: > backlinks > summaries > contradictions > stale claims > orphan pages > missing source links For coding projects, same idea: > `CLAUDE.md`: who you are, project rules, files not to touch > `index.md`: current files and features > `log.md`: date, change, reason > saved pages: decisions you do not want to re-explain Start by saving one good answer today
11:03

Prompt engineering is where people go when they refuse to write files Karpathy's LLM Wiki gist is painfully simple: > raw sources stay untouched > the agent writes the wiki > `CLAUDE.md` or `AGENTS.md` tells it the rules > `index.md` maps the pages > `log.md` records what changed That is why a good answer should not die in chat history If the model gives you a useful comparison, summary, decision, bug explanation, or research thread, file it back into the project Use: > `wiki/topics/[topic].md` > `wiki/entities/[person-or-company].md` > `wiki/sources/[source-name].md` > `wiki/analysis/[question].md` Make the agent keep the wiki from rotting: > backlinks > summaries > contradictions > stale claims > orphan pages > missing source links For coding projects, same idea: > `CLAUDE.md`: who you are, project rules, files not to touch > `index.md`: current files and features > `log.md`: date, change, reason > saved pages: decisions you do not want to re-explain Start by saving one good answer today

Alpha Batcher

14,041 görüntüleme • 3 ay önce

I still don’t understand why everyone isn’t running one of these yet. mine has been compiling for six months and it already knows things I’ve forgotten I knew Andrej Karpathy published a folder structure in April 2026. 5,000 stars. 16 million views. engineers couldn’t stop sharing it. not a model, not a tool, a folder structure. the sentence that explains why: “RAG re-derives knowledge on every query. a compiled wiki derives it once and keeps it current” most people who try building one hit a wall around month three anyway. the notes pile up, the links exist, and then it just sits there. you’re still the one doing all the remembering here’s the sentence that explains that wall too: keeping fifty interlinked notes current, consistent, and cross-referenced is work no human sustains. so people stop maintaining it, and it turns into a graveyard of good intentions the fix isn’t discipline. it’s making the system do the maintenance instead of you here’s the gist drop any source into a folder called raw, untouched, ground truth Claude reads it once, writes a structured page into wiki, links it to everything already there, flags anything that contradicts what you already know one file called CLAUDE.md sits at the center holding who you are, so you stop re-explaining yourself every session ask it anything across everything you’ve ever fed it, and it answers from months of compiled understanding instead of starting from zero that loop is the whole system. Karpathy’s repo got 16 million views because engineers finally saw the difference written down: retrieval answers questions, compilation builds understanding five minutes to set up. you’ll never open an empty chat and re-explain your life again full build, every step, in the article. save it now
0:25

I still don’t understand why everyone isn’t running one of these yet. mine has been compiling for six months and it already knows things I’ve forgotten I knew Andrej Karpathy published a folder structure in April 2026. 5,000 stars. 16 million views. engineers couldn’t stop sharing it. not a model, not a tool, a folder structure. the sentence that explains why: “RAG re-derives knowledge on every query. a compiled wiki derives it once and keeps it current” most people who try building one hit a wall around month three anyway. the notes pile up, the links exist, and then it just sits there. you’re still the one doing all the remembering here’s the sentence that explains that wall too: keeping fifty interlinked notes current, consistent, and cross-referenced is work no human sustains. so people stop maintaining it, and it turns into a graveyard of good intentions the fix isn’t discipline. it’s making the system do the maintenance instead of you here’s the gist drop any source into a folder called raw, untouched, ground truth Claude reads it once, writes a structured page into wiki, links it to everything already there, flags anything that contradicts what you already know one file called CLAUDE.md sits at the center holding who you are, so you stop re-explaining yourself every session ask it anything across everything you’ve ever fed it, and it answers from months of compiled understanding instead of starting from zero that loop is the whole system. Karpathy’s repo got 16 million views because engineers finally saw the difference written down: retrieval answers questions, compilation builds understanding five minutes to set up. you’ll never open an empty chat and re-explain your life again full build, every step, in the article. save it now

rvaniaaa

54,967 görüntüleme • 12 gün önce

everyone's talking about building a second brain with claude code + obsidian right now. so i made a full video walkthrough showing exactly how to set it up from scratch. drop an article into a folder. claude code reads it, creates wiki pages, builds relationships between concepts, and links everything automatically. by 20 sources your wiki knows more about your domain than you can hold in your head. here's the full setup:
13:22

everyone's talking about building a second brain with claude code + obsidian right now. so i made a full video walkthrough showing exactly how to set it up from scratch. drop an article into a folder. claude code reads it, creates wiki pages, builds relationships between concepts, and links everything automatically. by 20 sources your wiki knows more about your domain than you can hold in your head. here's the full setup:

J.B.

55,133 görüntüleme • 5 ay önce

Andrej Karpathy, founding member of OpenAI and ex-Director of AI at Tesla: "creators are paying $5,000 a month to agencies to build the exact AI 'content factory' this free talk hands you in 39 minutes." this free 2025 talk holds the entire "$1M YouTube on autopilot" the 2026 threads sell you for $500. karpathy explains the whole thing on stage: the model is the new computer, your only job is to feed it memory and verify what it gives back. that's the "second brain." that's it. the gurus wrap it in obsidian folders, a /wiki command and a "secret stack." karpathy handed you the actual idea for zero dollars -> dump raw sources in one place, let the model synthesize and maintain an interlinked wiki it can actually use. raw → synthesis → reuse. the architecture's been public the whole time. and here's the part the thread skips. he calls these models "people spirits" -> fallible, confidently wrong, output you check, not trust. the moat was never the obsidian setup. the moat is what you feed it and the judgment to catch where it's lying. the folder structure is free. the taste isn't. bookmark & watch today ↓
39:12

Andrej Karpathy, founding member of OpenAI and ex-Director of AI at Tesla: "creators are paying $5,000 a month to agencies to build the exact AI 'content factory' this free talk hands you in 39 minutes." this free 2025 talk holds the entire "$1M YouTube on autopilot" the 2026 threads sell you for $500. karpathy explains the whole thing on stage: the model is the new computer, your only job is to feed it memory and verify what it gives back. that's the "second brain." that's it. the gurus wrap it in obsidian folders, a /wiki command and a "secret stack." karpathy handed you the actual idea for zero dollars -> dump raw sources in one place, let the model synthesize and maintain an interlinked wiki it can actually use. raw → synthesis → reuse. the architecture's been public the whole time. and here's the part the thread skips. he calls these models "people spirits" -> fallible, confidently wrong, output you check, not trust. the moat was never the obsidian setup. the moat is what you feed it and the judgment to catch where it's lying. the folder structure is free. the taste isn't. bookmark & watch today ↓

Ridark

48,183 görüntüleme • 2 ay önce

MOST "SECOND BRAINS" ARE JUST FOLDERS YOU FEEL GUILTY ABOUT. HERE'S HOW CLAUDE TURNS ONE INTO A BRAIN THAT ANSWERS YOU. that clip is the build: obsidian plus claude, structured like a filing cabinet. three drawers, one job each: raw: everything you dump in, docs, sheets, pdfs, transcripts, untouched new knowledge: what claude distills, links and rewrites into clean notes and the connections between them, drawn automatically the part most note apps miss: you are not the librarian. you drop the raw in. claude reads it once, files it, links it to what you already had, and updates the index. then you never dig through the raw pile again. you ask the brain, and it answers from the clean layer with sources. that graph on screen isn't decoration. every line is a connection you didn't have to make by hand. no re-reading the same pdf, no notes you wrote once and never opened, no app that guilts you for not organizing. the uncomfortable part isn't that note apps are messy. it's that a second brain was never about saving more, it was about something rereading you after you stopped. follow RetroChainer for systems that keep thinking after you close the tab, and bookmark this before your notes turn into another graveyard.
1:25

MOST "SECOND BRAINS" ARE JUST FOLDERS YOU FEEL GUILTY ABOUT. HERE'S HOW CLAUDE TURNS ONE INTO A BRAIN THAT ANSWERS YOU. that clip is the build: obsidian plus claude, structured like a filing cabinet. three drawers, one job each: raw: everything you dump in, docs, sheets, pdfs, transcripts, untouched new knowledge: what claude distills, links and rewrites into clean notes and the connections between them, drawn automatically the part most note apps miss: you are not the librarian. you drop the raw in. claude reads it once, files it, links it to what you already had, and updates the index. then you never dig through the raw pile again. you ask the brain, and it answers from the clean layer with sources. that graph on screen isn't decoration. every line is a connection you didn't have to make by hand. no re-reading the same pdf, no notes you wrote once and never opened, no app that guilts you for not organizing. the uncomfortable part isn't that note apps are messy. it's that a second brain was never about saving more, it was about something rereading you after you stopped. follow RetroChainer for systems that keep thinking after you close the tab, and bookmark this before your notes turn into another graveyard.

RetroChainer

13,775 görüntüleme • 1 ay önce

Your Claude has a tell, and almost nobody uses it. Make it start every reply with your name. One line in custom instructions, no code. The moment it stops saying your name, its context window is full. That is the exact point the output starts drifting, and you do not notice. Name stops? Start a fresh chat. It has killed about 90% of my “why has Claude gone weird” moments. Miners sent a canary down the pit to catch the gas they could not see. Same trick, for your context. Comment GUIDE and I’ll send you the exact canary setup.
0:48

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

Charlie Hills

24,155 görüntüleme • 2 ay önce

75% of what you pay Claude for is your agent re-discovering things it already knew yesterday. Graft fixes it with an absurdly simple idea: the agent learns the codebase once, , instead of relearning it every time. it scans the repo, writes it out as linked markdown inside your git, and the agent reads that before touching anything. Here's how:↓
0:47

75% of what you pay Claude for is your agent re-discovering things it already knew yesterday. Graft fixes it with an absurdly simple idea: the agent learns the codebase once, , instead of relearning it every time. it scans the repo, writes it out as linked markdown inside your git, and the agent reads that before touching anything. Here's how:↓

Hasan Toor

20,765 görüntüleme • 1 ay önce